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Pathogenic Salmonella strains that cause gastroenteritis are able to colonize and replicate within the intestines of multiple host species . In general , these strains have retained an ability to form the rdar morphotype , a resistant biofilm physiology hypothesized to be important for Salmonella transmission . In contrast , Salmonella strains that are host-adapted or even host-restricted like Salmonella enterica serovar Typhi , tend to cause systemic infections and have lost the ability to form the rdar morphotype . Here , we investigated the rdar morphotype and CsgD-regulated biofilm formation in two non-typhoidal Salmonella ( NTS ) strains that caused invasive disease in Malawian children , S . Typhimurium D23580 and S . Enteritidis D7795 , and compared them to a panel of NTS strains associated with gastroenteritis , as well as S . Typhi strains . Sequence comparisons combined with luciferase reporter technology identified key SNPs in the promoter region of csgD that either shut off biofilm formation completely ( D7795 ) or reduced transcription of this key biofilm regulator ( D23580 ) . Phylogenetic analysis showed that these SNPs are conserved throughout the African clades of invasive isolates , dating as far back as 80 years ago . S . Typhi isolates were negative for the rdar morphotype due to truncation of eight amino acids from the C-terminus of CsgD . We present new evidence in support of parallel evolution between lineages of nontyphoidal Salmonella associated with invasive disease in Africa and the archetypal host-restricted invasive serovar; S . Typhi . We hypothesize that the African invasive isolates are becoming human-adapted and ‘niche specialized’ with less reliance on environmental survival , as compared to gastroenteritis-causing isolates .
The 2 , 600 serovars of the genus Salmonella have considerable genetic diversity , which permits them to occupy a wide variety of environmental and animal niches and to cause clinical presentation in humans ranging from asymptomatic carriage through enterocolitis and invasive disease . Most cases of human disease are caused by a few serovars of Salmonella enterica , which are loosely categorized as being invasive/typhoidal ( serovars Typhi and Paratyphi A ) or nontyphoidal . The nontyphoidal salmonellae ( NTS ) typically cause self-limiting enterocolitis and include common serovars such as Salmonella Typhimurium and Salmonella Enteritidis [1 , 2] . This simple clinical distinction breaks down in settings where there is high prevalence of immunosuppressive illness , such as sub-Saharan Africa ( sSA ) . Here , NTS have emerged as a leading cause of bacterial bloodstream infection [3] , or invasive nontyphoidal Salmonella ( iNTS ) disease . In common with typhoid fever , iNTS disease frequently presents without diarrheal symptoms , with non-focal febrile illness being the dominant clinical presentation [4] . This disease is responsible for an estimated 681 , 000 deaths per year , with nonspecific symptomology , multidrug resistance , and poor clinical outcomes despite correct diagnosis contributing to this significant mortality rate [5] . There is great urgency to better understand iNTS disease and reduce its impact in Africa and other areas of the world [6] . Most NTS infect a wide range of host species and are considered host-generalist pathogens [7] . In contrast , typhoidal serovars are exemplars of host-restricted pathogens , with marked genomic degradation in comparison to NTS serovars [8] . There is evidence that the same process is underway in strains of S . Typhimurium and S . Enteritidis associated with invasive disease in sub-Saharan Africa [9 , 10] . Many of these gene mutations affect metabolic processes involved in anaerobic respiration on unique carbon sources , a mechanism that is pivotal for the replication and outgrowth of Salmonella in the inflamed intestinal tract [11 , 12] . Whether this represents a random process related to the different geographical location of these strains , convergent evolution with the typhoidal serovars towards an invasive rather than an enteric “lifestyle” , or adaptation to distinct environmental niches remains an outstanding question . Irrespective of invasive versus enteric lifestyle , all salmonellae are transmitted via the fecal-oral route , but key questions remain over how invasive strains interact with the environment between host colonization events [13 , 14] . Biofilm formation is proposed to aid in the survival and persistence of Salmonella cells during this environmental phase of the transmission cycle [15] . The most well-characterized format of Salmonella biofilm physiology has been termed the rdar ( red , dry , and rough ) morphotype , where a self-produced extracellular matrix interconnects cells and facilitates their adherence to abiotic and biotic surfaces [16–18] . Multiple cues , including ambient temperature , osmolarity , and nutrient availability , act via a complex regulatory network to activate CsgD , a member of the RpoS regulon and the primary transcriptional activator of the rdar morphotype [15 , 16] . CsgD in turn induces the expression of proteinaceous ( curli fimbriae [19] ) , BapA [20] ) and polysaccharide ( cellulose [17 , 21] , O-antigen capsule [18 , 22] ) polymers that act as major contributors to the recalcitrant matrix structure associated with this phenotype . The genes for curli fimbriae and cellulose are highly conserved in Salmonella [23–25]; however , almost all Typhi and Paratyphi isolates are phenotypically negative for the rdar morphotype [23 , 26] . Therefore , loss of the rdar morphotype may represent an additional signature of host adaptation . Landmark studies revealed genomic degradation within representative iNTS strains S . Typhimurium D23580 [27] and S . Enteritidis D7795 [10]–these observations were consistent with genetic signatures of host adaptation found in typhoidal and paratyphoidal Salmonella species [28 , 29] . As such , significant attention has focused on evaluating the virulence of these strains in laboratory models of Salmonella infection [9 , 30–32] . Comparatively less is known about the state of biofilm physiology of iNTS strains [33] , and in particular the CsgD-regulated rdar morphotype , which we and other labs have postulated may be important for the persistence of nontyphoidal Salmonella species in non-host environments [15 , 23 , 25 , 26 , 34] . We wanted to determine if S . Typhimurium D23580 and S . Enteritidis D7795 can form biofilms , and if not , to determine if the corresponding mutations are conserved in other African strains associated with invasive disease . We selected typical Typhimurium and Enteritidis strains that cause enterocolitis to act as controls in our phenotypic screens and to rule out any serovar-specific genetic variations that do not affect biofilm formation . We included the archetypal Typhi strain ( CT18 ) and modern versions of the H58 haplotype [35] to determine if patterns of gene loss or mutation are shared between invasive isolates .
The rdar morphotype was first described by Römling and colleagues during their research into the expression of curli fimbriae in S . Typhimurium 14028 [16] . For the wildtype strain , the morphotype was reported as a temperature-restricted phenotype , with transcription of curli biosynthesis ( csg ) genes and characteristic patterns on the colony surface constrained to cells grown at 28˚C in nutrient-rich medium of low osmolarity . These conditions have since been used as a standard for screening Salmonella isolates for the rdar morphotype [26] . After three to five days of growth at 28˚C , nontyphoidal and typhoidal Salmonella strains were easily distinguishable based on the different appearances of their macrocolonies ( Fig 1 ) . We added Congo red dye to the agar to visualize the presence of curli fimbriae and cellulose and identify strains that possess the red , dry , and rough ( rdar ) morphotype [19] . Control strains of NTS were rdar-positive and red in colour , while S . Typhi strains were smooth and white ( saw ) , or rdar-negative . S . Typhimurium D23580 formed pale red colonies with an incomplete wrinkling pattern on the colony’s surface , whereas S . Enteritidis D7795 was rdar-negative . Temperature-based restriction of curli expression can be overcome in some instances; examples of this include when strains carry certain mutations in the csgD promoter [16 , 36] , or when nontyphoidal Salmonella are grown in iron-limiting conditions [16] or in the presence of human bile [37] . However , all NTS strains displayed a temperature-based restriction of curli expression [16] , as they did not form rdar colonies at 37°C and curli ( csgBAC ) transcription was at basal levels ( S1 Fig ) . Rdar morphotype-positive Salmonella strains grown in an in vitro flask model of biofilm development will produce two unique subpopulations—multicellular , biofilm aggregates and planktonic cells [38 , 39]—due to the bistable production of CsgD [40] . We reasoned that multicellular aggregation in liquid cultures would provide a clearer diagnostic for the presence of a functioning biofilm phenotype in both strong and moderate biofilm-producing strains . Cultures of S . Typhimurium D23580 contained visible multicellular aggregates and planktonic cell subpopulations ( Fig 1 ) . However , the aggregates made up a lower proportion of the population biomass compared to aggregates from other NTS and had observable differences in their physical structure ( S2 Fig ) , suggesting a moderate but impaired biofilm phenotype . In contrast , cultures of S . Enteritidis D7795 and all typhoidal Salmonella strains consisted solely of planktonic cells . Cellulose production can be specifically assessed by supplementing T agar with calcofluor white dye and illuminating colonies with ultraviolet light [25] . Similar fluorescence intensity was observed for S . Typhimurium D23580 compared to other NTS , indicating the presence of cellulose production despite the partial rdar morphotype ( Fig 1 ) . In contrast , cellulose production was comparably minimal or absent from macrocolonies of S . Enteritidis D7795 and all S . Typhi isolates . The divergent csg operons are central to curli biosynthesis and include genes for curli fimbrial protein subunits ( csgBA ) , transcriptional regulation ( csgD ) , and curli assembly machinery ( csgC and csgEFG ) [41–43] . CsgD is involved in activating the transcription of both operons [16 , 19] , making detection of curli fimbrial subunits a strong indicator of CsgD activity . We probed the lysates of cell subpopulations emerging from flask cultures for synthesis of CsgD and CsgA , the major subunit of curli fimbriae ( Fig 2 ) . We detected both proteins in lysates from multicellular aggregates , including S . Typhimurium D23580 . In contrast , neither protein was detected for samples derived from S . Enteritidis D7795 or any of the S . Typhi strains . We also probed the lysates for RpoS , the sigma factor that controls csgD expression [19] ( S3A Fig ) . RpoS protein was detected in all nontyphoidal Salmonella strains , including both biofilm and planktonic cell subpopulations derived from biofilm-producing strains . S . Enteritidis D7795 appeared to have lower levels of RpoS compared to the other NTS strains . For the S . Typhi strains , there was significant variation in protein levels at the 24-hour time point used for sampling , with low levels of RpoS observed for S . Ty E03-9804 and S . Ty 8 ( 04 ) N . Bacterial luciferase reporter technology allows for the systematic comparison of transcriptional activity across a wide variety of strains [24 , 44] . To evaluate RpoS activity , we tracked the expression of a synthetic , RpoS-dependent promoter-luciferase reporter construct in each strain during growth in microbroth cultures [15] ( S3B–S3D Fig ) . All strains in our panel exceeded the standard RpoS activity threshold identified in our previous work with other Salmonella strains ( i . e . 10 , 000 CPS ) [24] , except for S . Enteritidis D7795 . We hypothesized that variation in csgD expression levels could account for differences in the biofilm phenotypes we observed . The sequence of the 755-bp intergenic region between the csgBAC and csgDEFG operons was compared between each strain in our panel ( Fig 3A ) . For S . Enteritidis D7795 and S . Typhimurium D23580 , unique single nucleotide polymorphisms ( SNPs ) were identified within the intergenic region ( Fig 3B ) . For S . Enteritidis D7795 , a C-to-T SNP was observed in the regulatory region 47 bp upstream of the csgD transcriptional start site . For S . Typhimurium D23580 , independent C-to-A and G-to-A transversion mutations were identified 80 bp and 189 bp upstream of the csgD transcriptional start site . To assess the effects of sequence or ‘cis’ differences in the csg intergenic region , we generated transcriptional reporters for the csgD and csgB promoters of all twelve strains . The reporters were transformed into S . Typhimurium 14028 to ensure that promoter activity was measured in a consistent cellular environment . Maximum expression levels were similar for all csgD or all csgB promoter-reporter constructs generated from NTS control strains and S . Typhi strains , suggesting that serovar-specific polymorphisms did not have a significant impact on promoter functionality ( Fig 3C ) . We noted slightly lower activity from the csgB promoter from S . Typhimurium SL1344 , but considered the promoter functional based on its overall expression profile ( S4 Fig ) . In contrast , the activity of csgD promoters from S . Typhimurium D23580 and S . Enteritidis D7795 were significantly lower than native S . Typhimurium 14028 promoters ( Fig 3C ) . S . Typhimurium D23580 had peak expression that was approximately three-fold lower than S . Typhimurium 14028 , whereas S . Enteritidis D7795 had near background levels of expression ( ~1 , 000 counts per second ) and appeared to be non-functional . In contrast , there was minimal difference between the activities of csgB promoters from the African NTS strains and the panel of control strains . To determine if strains harboured mutations in trans-acting regulatory elements , each strain was transformed with a set of biofilm-associated transcriptional reporters derived from S . Typhimurium 14028 . The csgD promoter was expressed in all Salmonella strains , though its activity was six-fold lower in S . Enteritidis D7795 , S . Ty E02-2759 , and S . Ty E03-9804 ( Fig 3D ) . This result suggested that mutations in the regulatory network upstream of csgD could be partially responsible for loss of the rdar morphotype in these three strains . However , sequence analysis of the promoters and genes of six common regulators of csgD transcription did not reveal any unique sequence changes in these strains ( i . e . , positive regulators OmpR , MlrA , IHF , RstA; negative regulators CpxR , H-NS [45 , 46] ) . Expression of the csgB promoter showed a clearer distinction , as all control NTS strains and S . Typhimurium D23580 had significantly greater csgB promoter expression than rdar-negative S . Enteritidis D7795 and the S . Typhi strains ( Fig 3D ) . A similar pattern was observed for the promoters of adrA , a gene which regulates cellulose production , and cpxRA , which is part of a two-component system that responds to envelope stress ( S5 Fig ) . These trans patterns of gene expression correlated with a lack of CsgD in S . Enteritidis D7795 and S . Typhi strains . S . Typhimurium D23580 possessed two unique SNPs in the csgD promoter region and the promoter had reduced activity when compared to S . Typhimurium 14028 . We used genome engineering to replace the SNP at the -80 bp position ( D23580 -80A>C ) , which boosted csgD promoter activity approximately two-fold as compared to the D23580 parent strain ( Fig 5A ) . Replacement of the SNP at -189 bp position ( D23580 -80A>C , -189A>G ) resulted in an additional boost in promoter activity to reach similar levels as the csgD promoter from wildtype S . Typhimurium 14028 ( Fig 5A ) . Despite the increase in promoter activity , replacement of both csgD promoter SNPs ( S . Typhimurium D23580-PcsgD -80A>C , -189A>G ) was unable to restore the rdar morphotype , and although the strain appeared to bind more Congo red than the parent S . Typhimurium D23580 strain , the difference was hard to quantitate ( Fig 5B ) . S . Typhimurium D23580 was first characterized as being rdar-negative or -intermediate due to the presence of a premature stop codon in bcsG , and the rdar morphotype was restored by over-expressing bcsG [47] . To evaluate the impact of the bcsG mutation , we introduced this SNP into the rdar-positive S . Typhimurium 14028 strain , which caused a loss of pattern formation on the colony surface and a drop in calcofluor binding intensity ( Fig 6B ) . We concluded from this data that S . Typhimurium D23580 possessed multiple mutations that influence curli and cellulose production , leading to a reduced biofilm phenotype . We performed in silico screening of additional serovar Enteritidis and Typhimurium strains isolated from Africa and other areas of the world [10 , 48] to determine how widespread the biofilm-altering SNPs were . For S . Enteritidis , all 167 strains in the central/east African clade ( i . e . , HierBAPs-predicted clade from [10] ) , which includes D7795 , possessed the inactivating csgD promoter SNP ( Fig 6A ) . In contrast , 100% of the 250 isolates from the HierBAPs-predicted global clade associated with human enterocolitis and/or poultry farming did not have this SNP ( Fig 6A; S3 Table ) . For S . Typhimurium , the csgD promoter mutation at position -189 was conserved in all 50 lineage I and 71 lineage II strains analyzed ( Fig 6B; S4 Table ) , that were isolated from people in sSA within the past 30 years [48] . Lineage II , which includes strain D23580 , is thought to have arisen from lineage I due to increased selection pressure from heavy antibiotic use [48] . Therefore , we predicted that lineage II isolates would carry some unique mutations . Consistent with this , all lineage II isolates possessed the csgD promoter SNP at position -80 as well as the premature stop codon in bcsG . Importantly , none of the 63 S . Typhimurium strains of other sequence types ( i . e . , ST-19 , -34 , -98 , -128 or -568 ) possessed the biofilm-altering mutations ( Fig 6B; S4 Table ) . Salmonella Typhi represents the best characterized group of strains that cause a more invasive disease than enterocolitis . All six S . Typhi strains that we analyzed had functional csgD promoters , and at least four strains appeared to have upstream regulatory components intact ( Fig 3 ) . In the S . Typhi CT18 genome sequence , Parkhill et al . identified a premature stop codon at the 3’ end of csgD , which would result in truncation of eight amino acids from the C-terminal end of CsgD [49] . To analyze the functionality of this truncated csgD allele ( i . e . , csgD^CT18 ) compared to full-length csgD ( i . e . , csgD^14028 ) , we performed complementation experiments in a S . Typhimurium 14028 ΔcsgD strain background . The presence of csgD^14028 in a multi-copy plasmid resulted in a strain with characteristic rdar morphotype colonies , whereas the p3xFLAG control strain was smooth and white ( Fig 7A ) . The presence of csgD^CT18 resulted in a strain that formed red colonies with rdar-intermediate morphology , indicating that the truncated CsgD protein was partially functional . When grown in liquid culture , the csgD^CT18 and p3xFLAG cultures were devoid of multicellular aggregates , whereas the csgD^14028 complemented culture produced both cell types ( Fig 7A ) . We detected robust CsgD-3xFLAG synthesis in the csgD^14028 culture , whereas only a faint CsgD band could be detected in the csgD^CT18 culture ( Fig 7B ) . When expression of csgD^CT18 was induced by addition of IPTG , it caused a boost in curli ( csgBAC ) gene promoter expression ( Fig 7B ) and aggregates were formed in liquid culture ( Fig 7C ) . Expression of the csgB promoter in the induced csgD^CT18 cultures reached levels similar to , but still below the levels in the csgD^14028 uninduced cultures ( Fig 6C ) . We were unable to measure csgB promoter activity in induced csgD^14028 cultures because growth ceased upon addition of IPTG . Together , these experiments demonstrated that truncated CsgD from S . Typhi CT18 had reduced functionality compared to full-length CsgD , but was able to restore both rdar and other CsgD-regulated biofilm phenotypes if expressed at higher levels . As a final test of functionality , we used genome engineering to introduce the premature stop codon in csgD into S . Typhimurium 14028 , resulting in a strain that was rdar-negative with minimal Congo red binding and reduced cellulose production ( Fig 7D ) . This experiment showed that the SNP at the 3’ end of csgD was sufficient to disrupt CsgD-regulated biofilm phenotypes in S . Ty CT18 . We wanted to determine if there were other mutations that could potentially affect curli or cellulose production within our panel of twelve Salmonella strains . For curli , we performed sequence alignment of the entire 4 , 450 bp region containing the divergent csgBAC and csgDEFG operons ( S7 Fig ) . Seventeen unique SNPs were identified in each of the six S . Typhi strains , however the only clear nonsynonymous mutation was the premature stop codon in csgD that was previously described [49] . Several serovar Typhimurium- and Enteritidis-specific SNPs were identified in the intergenic region and in the csg coding regions , however since the majority of these SNPs were found in biofilm-positive strains , we concluded that they likely do not pose a significant effect on csg function . For cellulose , we performed sequence alignment of the 14 , 273 bp region containing the divergent bcsRQABZC and bcsEFG operons ( S8 Fig ) . Overall , this DNA region was less conserved than the csg region . All six S . Typhi strains shared numerous SNPs , including 21 non-synonymous changes in the bcs coding regions , and four premature stop codons in bcsC . S . Enteritidis D7795 had one unique SNP in bcsC , which resulted in a non-synonymous change that was shared with S . Typhi strains , and S . Typhimurium D23580 had one unique SNP leading to a premature stop codon in bcsG , as previously described [47] . We wanted to determine if the SNPs identified in S . Enteritidis D7795 , S . Typhimurium D23580 and S . Typhi were unique to these lineages or could be detected in isolates from other S . enterica subspecies enterica serovars . We analyzed the genomes of 248 isolates from 55 serovars , including representatives of the most common serovars associated with human disease [50] and host-adapted serovars such as Dublin , Choleraesuis and Gallinarum ( S5 Table ) . The -47 C>T mutation of S . Enteritidis D7795 was found in one strain of serovar Weltevreden , one strain of serovar Anatum had a 110-bp deletion in the csgD promoter region comprising both the -47 C>T and -80 G>T mutations , and the -189 C>T mutation of S . Typhimurium D23580 was found in one strain of serovar Hillingdon and two strains of serovar Typhimurium ( S5 Table ) . The SNP leading to a premature stop codon in csgD was unique to Typhi strains , and the G>A mutation causing a premature stop codon in bcsG was not detected in any strains ( S5 Table ) . We also screened 82 West African serovar Enteritidis strains associated with invasive human disease [10] but none of the mutations were detected ( S6 Table ) . With just a few exceptions , the SNPs identified in our biofilm screening appeared to be unique to the invasive lineages of Salmonella where they were originally detected .
In this study , we identified critical changes that disrupt or reduce the rdar morphotype and other CsgD-regulated biofilm phenotypes in three invasive Salmonella lineages . For S . Enteritidis D7795 , a single promoter mutation was responsible for inactivating the csgD promoter and shutting off the rdar morphotype . The polymorphism was in one of the two most conserved bases in the OmpR recognition site ( ACNTTTNGNTA’C’ANNTAT; [51] ) . This is predicted to knock out OmpR binding to a region which has been shown to be a major activating factor for csgD transcription [52] . Restoring biofilm formation was as simple as replacing this SNP , which re-activated the csgD promoter , overcoming low RpoS activity in S . Enteritidis D7795 . We have observed mutations in this OmpR binding site before , in two strains of Salmonella serovar Arizonae that had lost biofilm formation , strains that we speculated were adapted for living within the snake intestine [24] . Conservation of the csgD promoter SNP in all 167 strains of the Central/East African clade of S . Enteritidis from sub-Saharan Africa , and lack of the SNP in 250 ‘global’ S . Enteritidis isolates , is strong evidence that loss of this CsgD-regulated biofilm phenotype has being selectively maintained in the invasive population since the most recent common ancestor , circa 1945 [10] . S . Typhimurium D23580 had multiple mutations that influenced the rdar morphotype . Two SNPs were identified in the csgD promoter region , each causing a reduction in transcriptional activity . We hypothesized that reduced csgD promoter activity in S . Typhimurium D23580 could explain the reduced levels of curli production measured in the biofilm flask model . The third mutation was a premature stop codon in bcsG that was first identified by Singletary et al . in 2016 [47] . Recent work has shown that deletion of bcsG shuts off cellulose production [53]; however , in our hands , S . Typhimurium D23580 still produced measurable amounts of cellulose . BcsG has at least two functions , to add phosphatidylethanolamine ( PE ) to monomers of the growing cellulose chain [54] , and to stabilize integration of BcsA into the inner membrane , a role that has been ascribed to the N-terminal half of the protein [53] . In S . Typhimurium D23580 , the premature stop codon occurs at amino acid 247 in BcsG . If the N-terminal region of BcsG is synthesized , it would allow BcsA , the cellulose synthase enzyme , to reach native levels within the cytoplasmic membrane [53] . This could explain why S . Typhimurium D23580 can still produce moderate levels of cellulose . The effects of the csgD promoter mutations and bcsG truncation could have a great impact in the natural lifecycle of Salmonella , since they would reduce both the amount of biofilm produced and alter the physical structure of any multicellular aggregates . This could result in isolates that do not survive as well in the environment , as recently demonstrated for invasive S . Typhimurium isolates in Mali [33] . Conservation of all three polymorphisms in 100% of African S . Typhimurium lineage II isolates , collected from human patients in sSA within the past 30 years [48] , is evidence of sustained selection against the rdar morphotype in this lineage . For Salmonella serovar Typhi , we showed that a premature stop codon , resulting in loss of eight amino acids from the C-terminus of CsgD , was sufficient to shut off the rdar morphotype . The truncated CsgD protein had reduced activity , but was able to activate rdar-like morphologies and multicellular aggregation when expressed at higher levels . Therefore , any increases in csgD transcription , which can be caused by known promoter mutations [16 , 24] or potentially host-related environmental signals such as iron limitation [16] or the presence of human bile [37] , may be enough to restore CsgD-regulated biofilm phenotypes in S . Typhi . To explain why CsgD was not detectable in S . Typhi , we hypothesize that the reduced activity of truncated CsgD was not able to activate the genetic feed-forward loop that normally amplifies CsgD production [39 , 55] . Key dimerization domains exist in the N-terminal half of CsgD [56] , but it is not yet clear why the C-terminal truncation would reduce its activity . Despite the lack of a rdar morphotype , it should be noted that S . Typhi can form biofilms on human gallstones [57 , 58] , a process which has been simulated with S . Typhimurium in a mouse model of chronic carriage; however , the nature of the extracellular matrix in such biofilms is still under investigation [37 , 59 , 60] . Our analysis highlighted the presence 4 premature stop codons in the bcsC of the S . Typhi strains included in our panel [23] . BcsC is an essential enzyme in cellulose biosynthesis [61] , with a C-terminal ‘pore’ domain that guides the growing cellulose chain out of the cell [62] . This suggests that S . Typhi strains could be negative for cellulose production irrespective of reduced CsgD function . The impacts on the curli and cellulose systems in all three lineages of invasive S . enterica isolates provides strong evidence that parallel evolution has occurred [63] . With the association of phenotypic changes to mutations in promoter regions [64–66] or in transcriptional regulatory proteins that can act as bistable switches [40 , 67 , 68] , we present further evidence that changes in gene expression can drive specialization or ecological divergence without significant changes in gene content [69 , 70] . We recently reported the increased expression of over 780 genes during the development of multicellular aggregates in flask cultures of S . Typhimurium 14028 [39] . The shift in the transcriptome of Salmonella cells contrasts sharply with both the small regulon of genes directly controlled by CsgD as well as the complex but limited number of regulatory factors that influence expression and synthesis of CsgD itself [34 , 45] . Variation in cis regulatory regions is hypothesized to have a reduced fitness cost compared to changes in coding sequence , since genetic plasticity is retained [71] . Within the three lineages of invasive Salmonella isolates , both regulatory and structural mutations have played a prominent role in loss or impairment of the rdar morphotype . It is possible that the accumulation of genetic changes has been aided by replication and circulation of African strains within immunocompromised hosts [72] . We do not fully understand what the selective pressures are that have led to loss or impairment of biofilm formation in invasive Salmonella isolates . The changes we identified were generally specific to the invasive lineages that were investigated and were not conserved across a wider variety of serovars and isolates . We know that enterocolitis-causing isolates replicate to high numbers in the intestine before passing out of the host and into the environment [7] . Replication is aided by Salmonella-induced inflammation , which destabilizes the normal microbiota and provides Salmonella with a selective advantage due to specific metabolic adaptations [30 , 73] . In contrast , Salmonella strains that cause systemic disease tend to have a stealth and persistence strategy and remain associated with the host for a longer duration of time [8] . The transition from the intestinal to systemic niche is thought to represent an evolutionary bottleneck for Salmonella [28] , with significant losses in the functional gene repertoire consistently observed for invasive variants [29] . Bistable genetic networks in bacteria , such as the one described for CsgD , are often associated with the formation of two distinguishable phenotypes within a clonal population [74] , which is thought to allow genotypes to persist in fluctuating environments [75] . It would make sense for enterocolitis-causing isolates to retain the CsgD network , because the presence of persistent ( CsgD-ON ) biofilm cells and virulent ( CsgD-OFF ) planktonic cells would likely improve the odds for future transmission events [15 , 23 , 26 , 39] . Systemic isolates might not require the CsgD network because they are increasingly reliant on human carriers for transmission , as noted for S . Typhi [28 , 57 , 58] . In general , the biofilm-altering SNPs identified in the invasive isolates were not found in lineages of S . Enteritidis or S . Typhimurium that typically cause enterocolitis in association with zoonotic transmission . An alternative explanation for selection against the rdar morphotype is that the biofilm surface structures themselves are targets of the host immune system . Several independent studies have shown that S . Typhimurium strains that have lost curli and cellulose production are able to invade tissue culture cells more efficiently [76 , 77] and spread systemically in vivo [78 , 79] . Curli have been established as potent stimulators of the innate immune system that are recognized by Toll-like receptor 1 and 2 complexes [80 , 81] , as well as intracellular NOD-like receptors [82] . Curli also have the ability to stimulate T-helper cell 17 ( Th17 ) differentiation and increase expression of pro-inflammatory interleukin ( IL ) cytokines IL-17A , IL-22 and IL-1ß [82 , 83] . Some questions still remain , however . Although there is evidence that cellulose can be produced in vivo [78 , 84] , it has yet to be conclusively established if this constitutes a biofilm phenotype . It is also difficult to extrapolate how much of an immune response could be generated against Salmonella biofilms in immunocompromised , often HIV-positive patients in sSA . Both csgD expression and the rdar morphotype are highly conserved across Salmonella enterica and E . coli [19 , 23 , 24 , 85] , with notable exceptions including Salmonella serovars associated with host restriction and systemic disease ( S . Typhi , S . Paratyphi A , and S . Gallinarum ) and enteroinvasive E . coli and Shigella [23 , 26] . Loss of the rdar morphotype in Salmonella has been correlated with invasion of the intestinal epithelial lining [23] . There are numerous examples of Salmonella biofilm formation providing a survival or persistence advantage under conditions of stress , such as desiccation , nutrient deprivation and disinfection [24 , 25 , 86–88] . The impairment or inactivation of the rdar morphotype in the African invasive lineages suggests that their lifestyle could be distinct from lineages of S . Typhimurium and S . Enteritidis associated with industrialized food supply chains in resource rich settings . Although it is generally accepted that the transmission route for these invasive organisms is fecal-oral , we know very little about their behaviour in the environment between hosts . Based on the data presented , we hypothesize that the African invasive NTS isolates are becoming human-adapted , as has been speculated by other researchers [89 , 90] . Increased knowledge about the ecological niches that harbor these specialized strains as well as their transmission patterns will be critical for developing public health measures to reduce the morbidity and mortality associated with invasive salmonellosis .
The bacterial strains used in this study are listed in S1 Table . For standard growth , strains were inoculated from frozen stocks onto LB agar ( lysogeny broth , 1% NaCl , 1 . 5% agar ) and grown overnight at 37˚C . One isolated colony was used to inoculate 5 mL LB broth and the culture was incubated for 18 hours at 37˚C with agitation at 200 RPM . For colony morphology assays , overnight cultures of each strain were normalized to an optical density of 1 . 0 at 600 nm and 2 μL were spotted onto 1% tryptone medium containing 1 . 5% Difco agar ( T agar ) [36] . To visualize the rdar morphotype , T agar was supplemented with 40–60 μg mL-1 Congo red . To visualize cellulose production , T agar was supplemented with calcofluor white ( fluorescent brightener 28; Sigma-Aldrich Canada ) at a final concentration of 200 μg mL-1 [25] . To analyze liquid culture growth under biofilm-inducing conditions , 1 x 109 CFU were inoculated into 100 mL of 1% tryptone , pH 7 . 4 , and incubated at 28˚C for 24 or 48 hours with agitation at 200 rpm . The pCS26 and pU220 reporter plasmids containing csgDEFG , csgBAC , and adrA promoter sequences from S . Typhimurium 14028 fused to the luxCDABE operon from Photorhabdus luminescens have been described previously [15 , 24] . The RpoS-dependent reporter plasmid sig38H4 contains the luxCDABE operon preceded by a synthetic promoter designed based on the alignment of multiple RpoS-controlled promoters [15] . To generate the pCS26-cpxR promoter-luxCDABE construct , the cpx intergenic region was PCR amplified from S . Typhimurium 14028 genomic DNA using primers cpxR1 and cpxR2 ( S2 Table ) and Phusion high-fidelity DNA polymerase ( New England BioLabs ) , with reaction conditions outlined by the manufacturer . The desired PCR product was purified ( Geneaid PCR cleanup kit ) , sequentially digested with XhoI and BamHI ( New England BioLabs ) , and ligated using T4 DNA ligase ( New England BioLabs ) into the pCS26 vector cut with XhoI and BamHI . To generate csgDEFG and csgBAC luciferase reporters from each Salmonella strain , the csg intergenic region was PCR amplified from genomic DNA using primers agfD1 and agfD2 ( S2 Table ) . The PCR products were then ligated into either pCS26 ( XhoI-BamHI ) or pU220 ( BamHI-XhoI ) to generate the csgB and csgD promoter-reporter constructs , respectively . LB overnight cultures of Salmonella strains were diluted 1 in 600 in a final volume of 150 μL of 1% tryptone broth supplemented with 50 μg mL-1 Kn in 96-well clear-bottom black plates ( Costar #9520; Corning Life Sciences ) . To minimize evaporation of the medium during the assay , cultures were overlaid with 50 μL of mineral oil . Cultures were assayed for absorbance ( 590 nm , 0 . 1 s ) and luminescence ( 1s; in counts per second [CPS] ) every 30 min during growth at 28˚C with agitation in a Victor X3 multilabel plate reader ( Perkin-Elmer ) . For planktonic cell samples , approximately 5 x 1010 cells were sedimented by centrifugation ( 11 , 000 x g; 10 min; 4˚C ) . For biofilm aggregate samples , approximately 30 mg samples were resuspended in 1 mL of water and homogenized with a glass tissue grinder ( Product #7727–2 , Corning Life Sciences ) for 25 dounces , prior to centrifugation ( 10 , 000 x g; 1 min ) to sediment the cell material . Sedimented samples were resuspended in 1 mL of SDS-PAGE sample buffer without 2-mercaptoethanol and bromophenol blue and boiled for 5 min . Using the DC protein assay ( Bio-Rad Laboratories ) , cell lysates were normalized to a final protein concentration of 3 mg/mL . Bromophenol blue ( 0 . 0002% final concentration ) and 2-mercaptoethanol ( 0 . 2% final concentration ) were added to each lysate before loading 15 μg of total protein per lane . SDS-PAGE was performed with a 5% stacking gel and a 12 or 15% resolving gel . Proteins were transferred to nitrocellulose for 40 min at 25 V using a Trans-Blot SD semi-dry transfer cell ( Bio-Rad Laboratories ) in tris-glycine buffer supplemented with methanol . To detect curli fimbriae , cell debris was sedimented following boiling in SDS-PAGE sample buffer , washed twice with 500 μL of distilled water , suspended in 250 μL of 90% formic acid , frozen and lyophilized [36] . The dried samples were resuspended in SDS-PAGE sample buffer and loaded directly without boiling into each SDS-PAGE gel lane . CsgD was detected using a CsgD-specific monoclonal antibody at a 1-in-6 dilution of tissue culture supernatant ( ImmunoPrecise Antibodies Ltd . , Victoria , BC ) . To detect RpoS protein , a commercially available mouse polyclonal immune serum recognizing epitope 33 to 256 of E . coli RpoS was used at a 1-in-2000 dilution ( BioLegend; 1RS1 ) . CsgA , the major subunit of curli fimbriae , was detected by using a rabbit polyclonal serum raised against whole purified curli [36] . GroEL was used as a protein-loading control and was detected with a 1-in-60 , 000 dilution of rabbit polyclonal immune serum ( Sigma-Aldrich; G6532 ) . Secondary antibodies IRDye 800CW Goat anti-Mouse immunoglobulin G ( IgG ) or 680RD Goat anti-rabbit IgG ( Mandel Scientific ) were used at a 1-in-10 , 000 dilution and detected using the the Odyssey CLx imaging system and Image Studio 4 . 0 software package ( Li-Cor Biosciences ) . Whole genome sequences were obtained from the National Centre for Biotechnology Information ( NCBI ) via the following accession numbers: NC_016810 ( S . Typhimurium SL1344 ) ; NC_016854 ( S . Typhimurium D23580 ) ; NC_003198 ( S . Typhi CT18 ) . Mapped assemblies for S . Typhi H58 haplotype strains E02-2759 , E03-9804 , ISP03-07467 , ISP04-06979 were available from http://www . sanger . ac . uk/Projects/S_typhi [28] . The S . Typhi 8 ( 04 ) N genome was available from the European Nucleotide Archive under the name SGB112 and associated with the assembly number GCA_001362315 . 1 . The sequence for S . Enteritidis D7795 was available from the Public Health England Pathogens BioProject on NCBI ( accession number PRJNA248792 ) . Overnight liquid cultures of Salmonella serovar Enteritidis strains 301 and ATCC 4931 were sub-cultured 1 in 100 in 200 mL LB broth and grown at 37˚C for 2 . 5 hours . Approximately 7 x 108 cells were centrifuged ( 6000 x g , 10 minutes , 4˚C ) , resuspended in 25 mM Tris , 1 mM EDTA solution ( pH 8 . 0 ) to a total volume of 3 . 5 mL , and then treated with 10 mg lysozyme ( Sigma-Aldrich; L6876 ) and 200 units of mutanolysin ( Sigma-Aldrich; M9901 ) for 1 hour at 37˚C . For cell lysis , each sample was treated with 50 μL of 25% SDS , 1 mg proteinase K ( Applied Biosystems; AM23548 ) , and 125 μL of a 5M sodium chloride solution and incubated at 65˚C for 30 minutes . Nucleic acid was isolated from cell lysates using a series of phenol:chloroform:isoamyl and phenol:chloroform extractions , precipitated by the addition of ammonium acetate ( at a final concentration of 2M ) , washed with ethanol , and resuspended in Tris-EDTA solution ( 10 mM Tris , 1 mM EDTA , pH 8 . 0 ) . To remove RNA , RNase A was added to each sample at a final concentration of 0 . 2 mg/mL and incubated for 1 hour at 37˚C . Samples were purified once more by phenol:chloroform:isoamyl extraction , precipitated with ammonium acetate , washed with ethanol , and resuspended in a final volume of 200 μL of Tris-EDTA solution . Purified chromosomal DNA samples were fragmented by cup horn sonication with a high-intensity ultrasonic processor ( Vibra-Cell , Danbury , CT ) for 10 cycles of a 30-second pulses and 2 minute rest . DNA libraries were prepared from 1 μg of fragmented DNA using the NEBNext Ultra DNA Library Prep Kit for Illumina ( New England BioLabs; E7645S ) and NEBNext Multiplex Oligos for Illumina ( Index Primer Set 2 ) ( New England BioLabs; E7500S ) according to the manufacturer’s protocols . Adaptor-ligated DNA was size-selected between 400 and 500 bp total library size ( length of insert sequence + adaptor sequence ) following kit instructions . DNA samples were assessed for quality , purity , and integrity using a NanoDrop ND-1000 spectrophotometer ( Fisher Scientific ) and an Agilent 2100 Bioanalyzer with a High Sensitivity DNA chip ( Agilent Technologies; 5067–4626 ) . To ensure efficient adaptor ligation , samples were analyzed by quantitative PCR using the KAPA Library Quantification Kit for the Illumina platform ( KAPA Biosystems; KK4824 ) . Samples were sequenced using the MiSeq Reagent Kit version 3 , 600 cycles ( 2 x 300 bp read length ) ( Illumina; MS-102-3003 ) . Genome sequencing assembly and DNA sequence alignments were performed using the Geneious Pro v8 . 1 . 5 software package ( Biomatters ) . Paired-end sequence reads from Entertidis strains 4931 and 301 were assembled into contigs based on mapping to the S . Enteritidis reference genome P125109 ( NC_011294 ) . Sequence alignments were performed using ClustalW and an IUB cost matrix ( gap open cost of 15 , gap extend cost of 6 . 66 ) . A phylogenetic tree for strains included in this study was constructed based on the csg operon region by using the Geneious Tree Builder program [91] , with the Tamura-Nei model of genetic substitution and the neighbour-joining algorithm with bootstrapping ( 1000 replicates and support threshold of 70% ) . The I-SceI suicide plasmid system developed by Victor de Lorenzo and colleagues [92] was used for genome engineering . The following fragments were PCR amplified: 1 ) csg intergenic region from S . Typhimurium 14028 or S . Enteritidis D7795 using primers agfD3-FWD and agfD4-REV ( S2 Table ) ; 2 ) csg intergenic region from S . Typhimurium 14028 using primers agfD5-FWD and agfD6-REV ( S2 Table ) ; 3 ) bcsG-containing region from S . Typhimurium 14028 or S . Typhimurium D23580 using primers bcsG-checkF and bcsG-checkR ( S2 Table ) ; and 4 ) csgD-containing region from S . Typhi CT18 using primers csgDORFstartPstI and csgDreplaceREV ( S2 Table ) . Phusion high-fidelity DNA polymerase was used for amplification , following reaction conditions outlined by the manufacturer ( New England BioLabs ) . PCR products were purified , digested with BamHI and PstI ( New England Biolabs ) and ligated into BamHI/PstI-digested pSEVA212 [94] . Clones corresponding to each product were selected in E . coli S17-1 ( λpir ) and mating was performed to move the plasmid constructs into S . Enteritidis D7795 , S . Typhimurium D23580 or S . Typhimurium 14028 . Merodiploid strains with pSEVA212 plasmid constructs inserted into the genome were selected by growth on M9 minimal agar supplemented with 1mM MgSO4 , 0 . 2% glucose and 100 μg mL-1 kanamycin ( M9-Glc-Kn100 ) and confirmed by re-streaking onto M9-Glc-Kn100 agar . Purified pSEVA628S ( 200–300 ng ) [93] was transformed into merodiploid strains by electroporation with selection on Luria agar supplemented with 1 mM m-toluate and 20 μg mL-1 gentamicin . Resulting colonies were re-streaked onto Luria agar supplemented with 20 μg mL-1 gentamicin , streaked on Luria agar supplemented with 50 μg mL-1 kanamycin to confirm loss of the pSEVA212 plasmid , and streaked on TCR plates ( 1% tryptone , 1 . 5% agar , 40 μg mL-1 Congo red ) to check the biofilm phenotype . Colonies were selected from TCR plates and grown at 37°C for two overnight growth steps without gentamicin to generate cells that lack pSEVA628S . Final colonies were streaked onto ( 1 ) Luria agar , ( 2 ) Luria agar + 50 μg mL-1 Kn , ( 3 ) Luria agar + 20 μg mL-1 gentamicin , and ( 4 ) TCR plates to select the desired phenotypes . To confirm the genotypes , csgD promoter- , bcsG- or csgD-containing regions were PCR-amplified from resulting strains and Sanger sequencing was performed ( Eurofins MWG Operon; Louisville , Kentucky , USA ) . The pFLAG-CTC expression vector ( Sigma Aldrich #E8408 ) was maintained in E . coli DH10B . Purified pFLAG-CTC was digested with SalI and XhoI restriction enzymes . A synthetic polylinker generated from phosphorylated oligonucleotides 3xFLAG-linkerA and 3xFLAG-linkerB ( S2 Table ) was ligated into the digested vector to generate p3xFLAG . The csgD open reading frame was PCR amplified from S . Typhimurium 14028 or S . Typhi CT18 genomic DNA using primers csgD-ORF-start and csgD-ORF-end ( S2 Table ) , followed by digestion with XhoI and BamHI . The csgD fragments were ligated into XhoI- and BglII-digested plasmid to generate p3xFLAG/csgD^14028 and p3xFLAG/csgD^CT18 . Insertion of the 3xFLAG polylinker and csgD ORF was confirmed by DNA sequencing . The csgD^CT18 allele does not have the 3xFLAG linker attached because of the premature stop codon in the 3’ end of csgD . The resulting p3xFLAG vectors were transformed into S . Typhimurium ΔcsgD prior to analysis of biofilm formation . S . Enteritidis D77 is one of 167 isolates recently sequenced and described as being part of a distinct clade of S . Enteritidis featuring genomic degradation and geographical restriction to central and eastern Africa [10] . Similarly , S . Typhimurium D23580 is part of a unique lineage of S . Typhimurium , consisting of isolates from sSA [48] . Genome assemblies of the S . Enteritidis and S . Typhimurium isolates were investigated for the presence or absence of csgD promoter or bcsG SNPs through in silico PCR . Primers of the csgD sequence with a SNP in the promoter region were searched for in the genome assemblies using in_silico_pcr . py script ( https://github . com/simonrharris/in_silico_pcr ) , allowing zero changes for a match . Names and accession numbers for each strain included in the SNP screening are listed in S3 and S4 Tables . A similar approach was followed to screen the genome sequences of 248 diverse S . enterica isolates [94] , as well as 82 strains of serovar Enteritidis that are part of the West Africa lineage of strains originally described by Feasey et al . [10] . Statistical analysis was performed using GraphPad Prism versions 7 . 0c and 8 . 0 . 2 . Data collected from promoter-reporter luciferase assays was reported as the maximum luciferase expression measured during the course of the experiment , and was expressed as the mean ± the standard deviation . This data was logarithmically transformed and evaluated for normal distribution using the Shapiro-Wilk normality test . If the data was normally distributed , comparisons of the mean maximum luciferase expression levels obtained from multiple experiments were performed using an ordinary one-way ANOVA with post-hoc analysis via Holm-Sidak’s multiple comparisons test with statistical significance set at p < 0 . 05 . If the data was not normally distributed , comparisons were performed using the Kruskal-Wallis test with post-hoc analysis via Dunn’s multiple comparison test with statistical significance set at a p value of 0 . 05 . All numerical data and statistical analysis has been deposited in figshare ( https://figshare . com/ ) and is publicly available at doi: https://doi . org/10 . 6084/m9 . figshare . 8220866 . v1 . The Illumina paired end sequence reads comprising the genome sequences of S . enterica suspecies enterica serovar Enteritidis strains have been deposited in the Sequence Read Archives ( strain 301—SAMN11956692; strain ATCC 4931—SAMN11956691 ) . | African clades of nontyphoidal Salmonella cause invasive disease on a daily basis and thousands of deaths each year . Although it is generally accepted that the transmission route for these organisms is fecal-oral , we know very little about their behaviour in the environment between hosts . In this paper , we have identified both a genotype and a phenotype that suggest environmental niche specialization that is distinct from lineages of Salmonella Typhimurium and Salmonella Enteritidis associated with industrialized food supply chains in resource-rich settings . We also compared with strains of Salmonella Typhi , which cause systemic typhoid fever infections exclusively in humans . In each invasive lineage , regulatory or structural gene mutations leading to loss or impairment of biofilm were identified , all associated with curli and cellulose production , the two main structures that comprise the biofilm matrix . This suggests that similar evolutionary pressures are acting on invasive Salmonella isolates . Public health strategies aimed at reducing the burden of invasive Salmonella disease must prevent transmission to vulnerable adults and children via water sanitation and hygiene practices–a process that starts with identification of environmental reservoirs . The results of our study will raise the profile of this neglected aspect of invasive salmonellosis and will challenge researchers and clinicians to search in new places for potential environmental reservoirs of these pathogens . | [
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"... | 2019 | Parallel evolution leading to impaired biofilm formation in invasive Salmonella strains |
Control of HIV replication is a rare immunological event , providing clues to understand the viral control mechanism . CD8+ T-cell responses are crucial for virus control , but it is unclear whether lasting HIV containment can be achieved after establishment of infection . Here , we describe lasting SIV containment in a macaque AIDS model . Analysis of ten rhesus macaques that controlled viremia for 2 years post-infection found accumulation of proviral gag and nef CD8+ T-cell escape mutations in four of them . These four controllers mounted CD8+ T cells targeting Gag , Nef , and other viral proteins at 4 months , suggesting that broadening of CD8+ T-cell targets can be an indicator of the beginning of viral control failure . The remaining six aviremic SIV controllers , however , harbored proviruses without mutations and showed no or little broadening of their CD8+ T-cell responses in the chronic phase . Indeed , three of the latter six exhibiting no change in CD8+ T-cell targets showed gradual decreases in SIV-specific CD8+ T-cell frequencies , implying a concomitant reduction in viral replication . Thus , stability of the breadth of virus-specific CD8+ T-cell responses may represent a status of lasting HIV containment by CD8+ T cells .
Human immunodeficiency virus ( HIV ) and simian immunodeficiency virus ( SIV ) infection induces chronic , persistent viral replication leading to AIDS onset in humans and rhesus macaques , respectively . While antiretroviral therapy ( ART ) has reduced the morbidity and mortality due to HIV , it does not cure infection . Much effort has been made aiming at inducing a functional cure , defined as HIV containment with cessation of ART [1–4] . A current trial of administration with a monoclonal broadly reactive neutralizing antibody under ART showed a longer aviremic period but eventual rebound viremia after ART interruption in rhesus macaques [5 , 6] . Virus-specific CD8+ T cells exert strong suppressive pressure on HIV/SIV replication [7–11] , but fail to control viremia in most infections . Studies of HIV-infected individuals have revealed the association of certain HLA or major histocompatibility complex ( MHC ) class I genotypes with lower viral loads [12–15] . In the Indian rhesus macaque AIDS model , animals possessing protective MHC alleles such as Mamu-B*08 and Mamu-B*17 tend to show slower disease progression after SIVmac251/SIVmac239 infection [16–18] . CD8+ T-cell responses restricted by these HLA/MHC molecules have been shown to be responsible for HIV/SIV control in most studies [15 , 19–21] . However , aviremic HIV/SIV control is rare , and even in those with undetectable viremia , residual viral replication can occur and allow accumulation of viral genome mutations resulting in viral escape from CD8+ T-cell recognition , possibly leading to eventual viremia rebound [22–25] . Several prophylactic T cell-based vaccine trials have currently shown primary viremia control in macaque AIDS models [26–29] . However , it is difficult to obtain sterile protection from virus infection by T cell-based vaccines , and whether vaccine-based , primary non-sterile viral control can be stably maintained is debatable . Analysis of those rare cases exhibiting aviremic HIV/SIV control may provide clues to the development of a novel intervention resulting in lasting HIV control . We previously developed a prophylactic AIDS vaccine using a DNA prime and a boost with a Sendai virus ( SeV ) vector expressing SIVmac239 Gag ( SeV-Gag ) [26 , 30] . Our trial showed vaccine-based control of an SIVmac239 challenge in a group of Burmese rhesus macaques sharing the MHC class I haplotype 90-120-Ia ( referred to as A+ animals ) [31] . The Mamu-A1*043:01 , Mamu-A1*065:01 , Mamu-B*061:03 , Mamu-B*068:04 , and Mamu-B*089:01 alleles have been confirmed in this haplotype [32 , 33] . Two-thirds of unvaccinated A+ animals showed persistent viremia after SIVmac239 infection , whereas all the A+ animals vaccinated with a DNA prime and an SeV-Gag boost controlled SIV replication without detectable viremia at 2 months post-challenge [31 , 33] . CD8+ T-cell responses specific for dominant Mamu-A1*043:01 ( GenBank accession number AB444869 ) -restricted Gag206–216 ( IINEEAADWDL ) and Mamu-A1*065:01 ( AB444921 ) -restricted Gag241–249 ( SSVDEQIQW ) epitopes are responsible for this vaccine-based SIV control [31] . However , two of these SIV controllers accumulated multiple gag CD8+ T-cell escape mutations and plasma viremia reappeared after 1 year of SIV control [25] . In the present study , we analyzed ten A+ animals that controlled viremia for 2 years after SIVmac239 challenge to determine whether such non-sterile aviremic SIV control can be stably maintained . Four of these ten SIV controllers exhibited an accumulation of proviral CD8+ T-cell escape mutations , indicating the latent viral control failure with preceding broadening of SIV-specific CD8+ T-cell targets . In contrast , the remaining six controllers showed no proviral mutations with little change in CD8+ T-cell targets in the chronic phase . Three of the latter six showed a gradual reduction in SIV-specific CD8+ T-cell frequencies , implying stable non-sterile SIV control with waning viral replication . These results suggest a possible achievement of lasting SIV containment by CD8+ T cells without transition of their targets .
Ten Burmese rhesus macaques possessing the MHC class I haplotype 90-120-Ia that controlled viremia for 2 years after SIVmac239 challenge were studied . In our previous study [34] , most A+ animals mounted Gag-specific and Nef-specific CD8+ T-cell responses in primary SIVmac239 infection . Seven 90-120-Ia-associated CD8+ T-cell epitopes , Gag206–216 , Gag241–249 , Gag367–381 , Nef9–19 , Nef89–97 , Nef193–203 , and Vif114–124 , in SIVmac239 antigens have been identified , and unvaccinated A+ animals that failed to control viral replication have been shown to select viral escape mutations from all of these epitope-specific CD8+ T cells within a year after SIVmac239 challenge [25 , 33 , 34] . Ten SIV controllers used in the present study consisted of two unvaccinated , one sham-vaccinated , and seven vaccinated A+ animals as shown in Table 1 . Three macaques ( R07-002 , R07-003 , and R07-008 ) were immunized with a single Gag241–249-epitope vaccine expressing the Gag241–249 epitope fused with enhanced green fluorescent protein ( EGFP ) [35] , three macaques ( R03-018 , R09-009 , and R09-010 ) with a single Gag206–216-epitope vaccine expressing the Gag206–216 epitope fused with EGFP [36] , and macaque R05-005 with a mixture of both . In these vaccinated animals , plasma viremia became undetectable at 2 months post-infection , whereas unvaccinated controllers showed undetectable viremia after 6 months ( Fig 1A ) . All the animals controlled SIV replication until 2 years , but two of them ( R05-005 and R03-018 ) clearly exhibited reappearance of plasma viremia after that ( Fig 1A ) . Viremia was undetectable at 1 year post-infection in all the ten SIV controllers even by quantitation of viral loads using fivefold-concentrated plasma ( Table 2 ) . However , this higher-sensitive assay detected marginal levels of viremia at 2 years post-infection in macaques R05-005 and R03-018 ( Table 2 ) . Peripheral CD4+ T lymphocytes were maintained in all of these SIV controllers ( Fig 1B ) . We examined whether viral gag CD8+ T-cell escape mutations accumulated during SIV control . Plasma viral loads were too low for us to recover viral gag cDNA fragments by reverse transcription ( RT ) and nested PCR amplification from concentrated plasma-derived RNA of these SIV controllers during the chronic phase of infection . We , therefore , analyzed sequences of proviral gag cDNA fragments amplified by nested PCR . Template DNAs were extracted from CD4+ T cells isolated from macaque peripheral blood mononuclear cells ( PBMCs ) obtained at approximately 2 years post-infection ( Fig 2 ) . Four animals ( referred to as Group M [Table 1] ) had multiple proviral gag mutations , exhibiting the accumulation of CD8+ T-cell escape mutations in the chronic phase . All Group M animals showed selection of mutations in Gag206–216 , Gag241–249 , and Gag367–381 epitope-coding regions with additional gag mutations . We have previously reported that the L216S ( leading to a L-to-S substitution at the 216th amino acid [aa] in Gag ) and D205E ( D-to-E at the 205th ) mutations result in escape from Gag206–216-specific CD8+ T-cell recognition [25 , 37] . We have also confirmed that D244E ( D-to-E at the 244th ) results in escape from Gag241–249-specific CD8+ T cells and that A373T ( A-to-T at the 373rd ) and V375M ( V-to-M at the 375th ) from Gag367–381-specific CD8+ T cells [25] . In contrast , the remaining six SIV controllers ( referred to as Group N [Table 1] ) showed no proviral mutations in Gag206–216 , Gag241–249 , and Gag367–381 epitope-coding regions . No mutation in other gag region was found in Group N animals except for macaque R09-010 having a single M424T mutation . Viral gag cDNA fragments were amplified from culture supernatants of CD4+ T cells derived from three of four Group M animals but not from Group N animals except for macaque R07-006 ( Table 1 ) , implying inefficient transcription or replication capacity of the proviruses with no gag mutations in Group N animals . We also analyzed proviral gag sequences in PBMCs obtained at 2 months and 1 year after SIVmac239 challenge ( Fig 2 ) . In contrast to the results obtained at 2 years post-infection , no proviral gag mutations were observed in Group M or Group N animals , except macaque R03-018 ( Group M ) having a single L216S mutation at 1 year . Thus , Group M macaques accumulated proviruses with multiple CD8+ T-cell escape mutations later than 1 year post-infection and had replication-competent viruses that could be recovered from PBMC culture at 2 years . We then examined proviral vif and nef sequences at 2 years in these SIV controllers ( Fig 3 ) . Proviral vif cDNA fragments were amplified from three of four Group M and five of six Group N animals . Proviral vif mutations were found in two of the three Group M but only one of the five Group N . Neither Group M nor N had mutations in the Vif114–124 CD8+ T-cell epitope-coding region . Group M animals had multiple proviral nef mutations , exhibiting accumulation of CD8+ T-cell escape mutations during the chronic phase of infection . Mutations in the Nef9–19- and Nef89–97-coding regions were selected in three and two of four Group M animals , respectively . We have previously reported that the P12T ( P-to-T at the 12th aa in Nef ) and S13P ( S-to-P at the 13th ) were Nef9–19-specific CD8+ T-cell escape mutations [34] . In the Nef193–203-coding region , however , no mutation was observed even in Group M animals . In contrast , Group N controllers showed no mutation in proviral Nef9–19- Nef89–97- and Nef193–203-coding regions , while macaques R07-001 and R07-003 had multiple G-to-A mutations ( S1 Fig ) , possibly due to the effect of the APOBEC3 family [38–41] . Thus , we found two groups of A+ SIV controllers , Group M accumulating CD8+ T-cell escape mutations and Group N having no dominant CD8+ T-cell escape mutations in proviruses . Next , we examined individual SIV antigen-specific CD8+ T-cell responses in our SIV controllers by using panels of overlapping peptides spanning the entire SIVmac239 Gag , Pol , Vif , Vpx , Vpr , Tat , Rev , Env , and Nef amino acid sequences ( Fig 4A ) . No significant difference in SIV whole antigen-specific CD8+ T-cell frequencies ( sum of individual antigen specific CD8+ T-cell frequencies ) was observed between Groups M and N at 4 months post-infection . However , the frequencies in Group M were significantly higher than in Group N at 1 year post-infection ( p = 0 . 0381 by Mann-Whitney U-test ) . All the Group M animals had higher frequencies at 1 year than at 4 months , but Group N showed no or minimal increase in the whole antigen-specific CD8+ T-cell frequencies . In particular , three Group N controllers , R07-008 , R09-009 , and R09-010 , exhibited gradual decreases in the whole antigen-specific CD8+ T-cell frequencies from 4 months to 2 years following challenge ( Fig 4A ) . All the A+ SIV controllers induced predominant Gag- and/or Nef-specific CD8+ T-cell responses at 4 months after SIVmac239 infection ( Fig 4A ) . Group M animals elicited additional CD8+ T-cell responses directed against SIV antigens other than Gag and Nef . These SIV non-Gag/Nef antigen-specific CD8+ T-cell frequencies were significantly higher in Group M than those in Group N at 4 months ( p = 0 . 0095 by Mann-Whitney U-test ) and 1 year ( p = 0 . 0095 ) ( Fig 4B ) . Indeed , the numbers of SIV non-Gag/Nef antigens targeted by CD8+ T cells were significantly higher in Group M than those in Group N at 4 months ( p = 0 . 0095 by Mann-Whitney U-test ) and 1 year ( p = 0 . 0095 ) ( Fig 4C ) . All the Group M animals showed increase in the numbers of SIV antigens targeted by CD8+ T cells at 1 year compared to those at 4 months . In particular , SIV non-Gag antigen-specific CD8+ T-cell frequencies were significantly higher in Group M at 1 year ( p = 0 . 0087 ) . These results indicate the broadening of the CD8+ T-cell response in Group M . All four animals in Group M mounted CD8+ T-cell responses specific for SIV non-Gag/Nef antigens , which were undetectable in all Group N animals at 4 months post-infection . Also at 1 year , all of the animals in Group M showed CD8+ T-cell responses specific for several targets besides the Gag and Nef antigens . In contrast , only Gag-specific and Nef-specific CD8+ T-cell responses were observed in Group N animals except for macaque R07-003 which had detectable Vif-specific CD8+ T-cell responses . At 2 years post-infection , Vif-specific CD8+ T-cell responses were detected in three macaques in Group N , while the remaining three showed Gag-specific and Nef-specific CD8+ T-cell responses only . Importantly , the latter three macaques ( R07-008 , R09-009 , and R09-010 ) exhibited gradual decreases in these Gag/Nef-specific CD8+ T-cell responses in the chronic phase , possibly reflecting the absence of measurable viral replication . We further examined CD8+ T-cell responses specific for 90-120-Ia-associated Gag epitopes; Gag206–216 , Gag241–249 , and Gag367–381 , in the ten SIV controllers ( Fig 5A ) . The sum of these Gag epitope-specific CD8+ T-cell frequencies was similar between Groups M and N ( Fig 5B ) . Induction of CD8+ T-cell responses directed against both dominant Gag206–216 and Gag241–249 epitopes were confirmed in all the animals in previous analyses at weeks 2 and 12 post-infection [35 , 36] . At 4 months , all had detectable Gag241–249-specific CD8+ T cells , although Gag206–216-specific CD8+ T-cell responses were undetectable in three animals . However , at 2 years post-infection , the Gag241–249-specific CD8+ T-cell responses became undetectable in three of four Group M animals but were maintained in Group N animals except for macaque R09-010 which exhibited Gag206–216-specific CD8+ T-cell responses . We also examined CD8+ T-cell responses specific for 90-120-Ia-associated Nef9–19 , Nef89–97 , Nef193–203 , and Vif114–124 epitopes in the SIV controllers ( Fig 6A ) . In most of the animals immunized with Gag241–249-epitope and/or Gag206–216-epitope vaccines ( except for macaque R09-009 ) , these Gag epitope-specific CD8+ T-cell responses were predominant but Nef/Vif epitope-specific CD8+ T-cell responses were undetectable at 4 months post-challenge . At 1 and 2 years post-infection , differences in these Nef/Vif epitope-specific CD8+ T-cell responses between Groups M and N became evident . All the Group M animals mounted Nef9–19- Nef89–97- , or Nef193–203-specific CD8+ T-cell responses at 1 year and Vif114–124-specific CD8+ T-cell responses at 2 years post-infection . In contrast , none of the Group N animals elicited Vif114–124-specific CD8+ T-cell responses . In two of them , macaques R07-008 and R09-010 , even Nef9–19- Nef89–97- , and Nef193–203-specific CD8+ T cells were undetectable . Indeed , the sum of Nef9–19- Nef89–97- , Nef193–203- , and Vif114–124-specific CD8+ T-cell frequencies in Group M was significantly higher than in Group N at 2 years ( p = 0 . 0190 by Mann-Whitney U-test ) ( Fig 6B ) . Thus , Group M animals mounted Nef and Vif epitope-specific CD8+ T-cell responses in the chronic phase of infection , whereas such broadening of CD8+ T-cell responses was unclear and Gag epitope-specific CD8+ T cells were maintained in Group N . In particular , in three of six Group N macaques , R07-008 , R09-009 , and R09-010 , comparison between 4 months and 2 years post-challenge showed no change in CD8+ T-cell target epitopes . Three of six Group N controllers , R07-008 , R09-009 , and R09-010 , showed gradual decreases and stable breadth in the SIV antigen-specific CD8+ T-cell responses from 4 months to 2 years post-infection . To confirm involvement of the CD8+ T-cell responses in this stable SIV control , we administered an anti-CD8 antibody to deplete the CD8+ cells in macaque R09-009 2 years following challenge . Peripheral CD8+ T cells were undetectable for approximately 2 weeks from day 3 after the initial anti-CD8 antibody administration at week 108 post-infection and became detectable at week 111 ( Fig 7A ) . Plasma viremia was detectable for approximately 3 weeks from day 3 after the initial anti-CD8 antibody administration and became undetectable at week 112 ( Fig 7B ) . This transient reappearance of plasma viremia concomitant with CD8+ cell depletion supports the notion that CD8+ T-cell responses are crucial for the stable SIV containment . Macaque R09-009 showed Gag- and Nef-specific but not non-Gag/Nef antigen-specific CD8+ T-cell responses before the anti-CD8 antibody administration at week 108 post-infection ( Fig 4A ) . Interestingly , however , this animal mounted high magnitude Vif-specific CD8+ T-cell responses in the CD8+ T-cell recovery phase from week 111 post-infection ( Fig 7C ) . Analysis at week 115 detected no or poor Gag/Nef epitope-specific CD8+ T cells but dominant Vif114–124 epitope-specific CD8+ T-cell responses ( Fig 7D ) . The plasma-derived viral genome cDNAs at week 110 post-infection had mutations L216S in the Gag206–216 epitope-coding region , D244E in Gag241–249 , V375M in Gag367–381 , S13P in Nef9–19 , I90R in Nef89–97 , and S201F in Nef193–203 ( Fig 7E ) . However , no mutation was detected in the Vif114–124 epitope-coding region . Plasma viremia re-appeared at week 118 , and the viruses at week 118 showed the similar pattern of sequences ( Fig 7E ) . Thus , even in lasting aviremic SIV controllers , replication-competent viruses with multiple CD8+ T-cell escape mutations may exist .
In the present study , we examined ten rhesus macaques that controlled SIV replication without detectable viremia for more than 2 years after infection . Four of these aviremic SIV controllers , Group M , exhibited proviruses with multiple proviral CD8+ T-cell escape mutations in the chronic phase , whereas the remaining six , Group N , had no proviral CD8+ T-cell escape mutations . Three of six Group N animals showed a decline in SIV-specific CD8+ T-cell frequencies , implying lasting non-sterile SIV control with a concomitant reduction in viral replication . Although the size and character of virus reservoirs may be different from those under ART [42 , 43] , a rhesus cytomegalovirus ( rhCMV ) vector vaccine trial indicated lasting , non-sterile SIV control by persistent rhCMV-induced CD8+ T-cell responses , possibly resulting in virus clearance [44] . Our results suggest possible achievement of lasting SIV control by CD8+ T cells without persistent exogenous stimulation . We were unable to find the genetic determinants for the difference in the Groups M and N by analyses of their second MHC class I haplotypes ( Table 3 ) , but this study presents a model of SIV containment , contributing to elucidation of the requisites for lasting , non-sterile HIV control . This study analyzed SIV controllers possessing the MHC-I haplotype 90-120-Ia . In our previous study [31] , all the A+ animals vaccinated with a DNA prime and an SeV-Gag boost controlled replication of the wild-type SIVmac239 , whereas those that received the same vaccine regimen failed to control a challenge with SIV carrying Gag206–216- and Gag241–249-specific CD8+ T-cell escape mutations . Thus , these A+ animals are useful to examine the mechanism of SIV control by CD8+ T cells , and the present study using these SIV controllers may provide a clue to understand the mechanism for lasting SIV control . Analysis of CD8+ T cell-mediated SIV control needs animals sharing MHC-I genotypes like A+ macaques . If we could accumulate long-lasting aviremic SIV controllers sharing other MHC-I alleles , although not easy , it would contribute to our further understanding of viral control mechanism . Gag206–216- and Gag241–249-specific CD8+ T-cell responses played a central role in primary viral control in these A+ SIV controllers as shown previously [31 , 35 , 36] . In most vaccine-based controllers , a viral CD8+ T-cell escape GagL216S mutation was rapidly selected and plasma viremia became undetectable after 5 weeks of infection . However , the wild-type sequence but not this CD8+ T-cell escape mutation was predominant in PBMC-derived proviruses at 2 months post-infection , reflecting containment of the rapidly-selected mutant viruses . The data infer that the detected proviruses with wild-type gag were maintained without eradication because of inefficient replication . Indeed , no virus was recovered from PBMC cultures in most Group N animals ( Table 1 ) . How these proviruses became non-functional remains unclear [45 , 46] , but two Group N animals showed multiple G-to-A mutations in proviral nef ( S1 Fig ) , possibly reflecting an effect of the APOBEC3 family [38–41] . Two years after infection , animals in Group M showed multiple CD8+ T-cell escape mutations in proviral gag and nef , suggesting replication of viruses carrying multiple mutations . In our previous study [33] , all the four MHC-I haplotype 90-120-Ia-positive macaques that failed to control SIVmac239 replication showed CD8+ T-cell responses targeting SIV non-Gag/Nef as well as Gag/Nef antigens at 3 months and/or 1 year post-infection . In all of these animals , analysis of plasma RNA-derived viral genome sequences at 1 year post-infection found predominant nonsynonymous mutations in all the seven regions encoding SIV Gag206–216 , Gag241–249 , Gag367–381 , Vif114–124 , Nef9–19 , Nef89–97 , and Nef193–203 epitopes , respectively . In the present study , analysis of these MHC-I haplotype 90-120-Ia-associated epitopes at 2 years showed Gag206–216 , Gag241–249 , and Gag367–381 epitope-specific CD8+ T-cell escape mutations in all Group M animals . Nef9–19-specific CD8+ T-cell escape mutations were also selected in most of them . However , mutations were not observed in Nef193–203 or Vif114–124 epitope-coding region . At 2 years after infection , only one of four Group M animals maintained Gag206–216/Gag241–249-specific CD8+ T cells , whereas all elicited Nef193–203 and Vif114–124 epitope-specific CD8+ T-cell responses , implying that these CD8+ T cells targeting Nef193–203 and Vif114–124 epitopes may contribute to sustained control of viremia in Group M animals . These results suggest undetectable level of viral replication in Group M animals , resulting in accumulation of CD8+ T-cell escape mutations during viremia control . Higher SIV-specific CD8+ T-cell frequencies and broadening of the CD8+ T-cell targets in this group are considered to reflect this undetectable level of viral replication . Proviral CD8+ T-cell escape mutations were undetectable at 1 year but accumulated at 2 years in Group M , while differences in SIV non-Gag/Nef antigen-specific CD8+ T-cell responses between Groups M and N were evident as early as 4 months post-infection . This implies that broadening of the CD8+ T-cell responses in aviremic SIV controllers could serve as an indicator of the beginning of viral control failure . All the Group M animals showed reduced numbers of non-Gag/Nef antigens targeted by CD8+ T cells at 2 years compared to those at 1 year ( Fig 4 ) . It is speculated that this might be because viruses accumulate CD8+ T-cell escape mutations in those viral genome regions encoding CD8+ T cell-targeted non-Gag/Nef antigens after 1 year post-infection . In contrast , proviral mutations did not appear in Group N macaques even at 2 years post-infection , indicating sustained viral control . These animals maintained Gag241–249-specific CD8+ T cells which are considered important for viral control . The breadth and magnitude of SIV-specific CD8+ T-cell responses remained constant in the chronic phase consistent with stable viral control in the presence of immunodominant Gag- and Nef-specific CD8+ T-cell responses . In three Group N animals ( R07-001 , R07-006 , and R07-003 ) , Vif-specific CD8+ T-cell responses became detectable at 2 years after infection , implying partial control failure by the Gag- and Nef-specific CD8+ T-cell responses . However , the remaining three vaccinated controllers ( R07-008 , R09-009 , and R09-010 ) in Group N showed no increased breadth of their CD8+ T-cell targets , possibly reflecting the absence of escape mutants stimulating additional CD8+ T-cell responses in the chronic phase . Effective and broad CD8+ T-cell responses have been indicated to be important for the control of HIV/SIV replication [15 , 47–50] . Even if aviremic HIV/SIV control is achieved by virus-specific potent CD8+ T-cell responses , residual viral replication may occur and allow accumulation of CD8+ T-cell escape mutations in viral genome , possibly leading to eventual viremia rebound . The present study addressed this issue after achievement of primary SIV control . The rhCMV vector vaccine trial indicated lasting SIV control by persistent rhCMV-induced non-classical CD8+ T-cell responses in rhesus macaques [44 , 51] . However , SIV controllers in the present study are thought to have no CD8+ T-cell stimulators other than virus-derived antigens post-infection . Thus , broadening of CD8+ T-cell responses is considered to be due to residual viral replication as observed in Group M animals . Broader CD8+ T-cell responses would be important for SIV control , but after achievement of a virus control condition , further broadening may indicate residual viral replication . In contrast , Group N animals , in particular three of them ( R07-008 , R09-009 , and R09-010 ) , showed no broadening of their CD8+ T-cell targets , which may represent a status of lasting SIV containment by CD8+ T cells . The anti-CD8 antibody administration to the Group N macaque resulted in transient reappearance of plasma viremia concomitant with CD8+ cell depletion , supporting the notion that CD8+ T-cell responses are crucial for the stable SIV control observed . Sequence analysis of the emergent virus indicated the existence of replication-competent viruses with multiple CD8+ T-cell escape mutations , which can be controlled . In summary , this study showed that increased breadth of virus-specific CD8+ T-cell responses is detected before the accumulation of proviral CD8+ T-cell escape mutations and viral control failure in aviremic SIV controllers . Broadly-reactive CD8+ T-cell responses may be crucial for HIV control , but our results suggest that if the host could achieve the conditions in which CD8+ T cells overwhelm HIV replication , non-broadening of CD8+ T-cell responses represents a status of lasting HIV containment by CD8+ T cells .
Animal experiments were carried out in Tsukuba Primate Research Center , National Institute of Biomedical Innovation ( NIBP; currently renamed National Institutes of Biomedical Innovation , Health and Nutrition [NIBIOHN] ) with the help of the Corporation for Production and Research of Laboratory Primates after approval by the Committee on the Ethics of Animal Experiments of NIBP ( permission number: DS21-27 , DS23-19 , and DS25-31 ) under the guideline for animal experiments at NIBP and National Institute of Infectious Diseases in accordance with the Guidelines for Proper Conduct of Animal Experiments established by Science Council of Japan ( http://www . scj . go . jp/ja/info/kohyo/pdf/kohyo-20-k16-2e . pdf ) . The experiments were in accordance with the "Weatherall report for the use of non-human primates in research" recommendations ( https://royalsociety . org/topics-policy/publications/2006/weatherall-report/ ) ) . Animals were housed in adjoining individual primate cages allowing them to make sight and sound contact with one another for social interactions , where the temperature was kept at 25°C with light for 12 hours per day . Animals were fed with apples and commercial monkey diet ( Type CMK-2 , Clea Japan , Inc . ) . Blood collection , vaccination , virus challenge , and anti-CD8 antibody treatment were performed under ketamine anesthesia . We analyzed the chronic phase of SIVmac239 infection in ten Burmese rhesus macaques ( Macaca mulatta ) possessing the MHC class I haplotype 90-120-Ia [32 , 33] ( Table 1 ) . These animals were previously used for vaccination and challenge experiments [35 , 36] . One-third of unvaccinated A+ animals controlled viremia after SIVmac239 infection in our previous study [35] , and unvaccinated macaques R06-037 and R07-001 and sham-vaccinated R07-006 were used in the present study . Macaque R07-006 received a control prime-boost vaccine using a DNA and a replication-incompetent F-deleted SeV ( F[–]SeV ) vector both expressing EGFP . Three macaques R07-002 , R07-003 , and R07-008 received a DNA-prime/F ( - ) SeV-boost vaccine eliciting Gag241–249-specific CD8+ T-cell responses . A pGag236-250-EGFP-N1 DNA and an F ( - ) SeV-Gag236-250-EGFP vector both expressing an SIVmac239 Gag236-250 ( IAGTTSSVDEQIQWM ) -EGFP fusion protein were used for the single Gag241–249-epitope vaccine [35] . Three macaques R03-018 , R09-009 , and R09-010 received a DNA-prime/F ( - ) SeV-boost vaccine eliciting Gag206–216-specific CD8+ T-cell responses . A pGag202–216-EGFP-N1 DNA and an F ( - ) SeV-Gag202–216-EGFP vector both expressing an SIVmac239 Gag202–216 ( IIRDIINEEAADWDL ) -EGFP fusion protein were used for the single Gag206–216-epitope vaccine [36] . Macaque R05-005 received both the Gag241–249-epitope and Gag206–216-epitope vaccines simultaneously . Animals received 5 mg of DNA intramuscularly and 6 weeks later received a single intranasal boost with 6 x 109 cell infectious units of F ( - ) SeV vector . Approximately 3 months after the F ( - ) SeV boost , animals were challenged intravenously with 1 , 000 50% tissue culture infective doses of SIVmac239 [52] . For CD8+ cell depletion , macaque R09-009 received a single subcutaneous inoculation of 10 mg/kg of body weight of monoclonal anti-CD8 antibody ( cM-T807 ) ( NIH Nonhuman Primate Reagent Resource [R24 RR016001 , N01 AI040101] ) followed by three intravenous inoculations of 5 mg/kg cM-T807 on days 3 , 7 , and 10 after the first inoculation at week 108 . Primary CD4+ T cells were prepared by negative selection from macaque PBMCs using a non-human primate CD4+ T cell isolation kit ( Miltenyi ) . Total cellular DNA was extracted from CD4+ T cells using DNeasy extraction kit ( QIAGEN ) . The DNA corresponding to the number of CD4+ T cells indicated in S1 Table was subjected to nested PCR amplification of proviral gag , vif , and nef cDNA fragments ( nucleotide numbers [nt] 1231–2958 for gag , nt 4829–7000 for vif , and nt 8677–10196 for nef in SIVmac239 [accession number M33263] ) for direct sequencing using dye terminator chemistry and an automated DNA sequencer ( Applied Biosystems ) as previously described [25] . For macaques R06-037 , R05-005 , R07-001 , and R07-006 at 2 years , total cellular DNAs were extracted not directly from CD4+ T cells but after 8 days of culture described below . Dominant non-synonymous mutations were determined . For virus recovery , 0 . 5–2 x 106 CD4+ T cells were cultured in the presence of 10 ng/ml human interleukin-7 ( IL-7 ) ( Miltenyi ) and 10 ng/ml human IL-15 ( Miltenyi ) for 8 days . Then , viral RNA was extracted from supernatants of CD4+ T-cell culture using the High Pure Viral RNA kit ( Roche Diagnostics ) and subjected to reverse transcription and nested PCR ( RT-PCR ) amplification of viral gag cDNA fragments . We measured virus-specific CD8+ T-cell frequencies by flow cytometric analysis of gamma interferon ( IFN-γ ) induction after specific stimulation as described previously [53] . Autologous herpesvirus papio-immortalized B-lymphoblastoid cell lines ( B-LCLs ) were pulsed with individual SIVmac239 epitope-coding peptides ( at a final concentration of 1–5 μM ) or peptide pools ( at a final concentration of 1–2 μM for each peptide ) using panels of overlapping peptides spanning the entire SIVmac239 Gag , Pol , Vif , Vpx , Vpr , Tat , Rev , Env , and Nef amino acid sequences ( Sigma-Aldrich Japan ) for 1 hour . PBMCs were cocultured with these pulsed B-LCLs in the presence of GolgiStop ( monensin , BD ) for 6 hours . Intracellular IFN-γ staining was performed with a CytofixCytoperm kit ( BD ) and fluorescein isothiocyanate ( FITC ) -conjugated anti-human CD4 ( BD ) , peridinin chlorophyll protein ( PerCP ) -conjugated anti-human CD8 ( BD ) , allophycocyanin-Cy7 ( APC-Cy7 ) -conjugated anti-human CD3 ( BD ) , and phycoerythrin ( PE ) -conjugated anti-human IFN-γ monoclonal antibodies ( Biolegend ) . In the flow cytometric analysis , PBMCs were gated in Forward Scatter-Side Scatter dot plots and B-LCLs were excluded . A representative gating schema for flow cytometric analysis is shown in S2 Fig . Specific T-cell frequencies were calculated by subtracting nonspecific IFN-γ+ T-cell frequencies from those after peptide-specific stimulation . Specific T-cell frequencies lower than 100 per million PBMCs were considered negative . Statistical analyses were performed with Prism software version 4 . 03 with significance levels set at a P value of <0 . 0500 ( GraphPad Software , Inc . ) . Comparisons between groups were made using non-parametric tests . SIVmac239 proviral DNA: M33263 . | CD8+ T-cell responses are crucial for HIV control , but it is unclear whether lasting HIV containment can be achieved after establishment of infection . Several T cell-based vaccine trials have currently shown primary viremia control in macaque AIDS models of simian immunodeficiency virus ( SIV ) infection , but residual viral replication may occur , followed by accumulation of viral CD8+ T-cell escape mutations , possibly leading to eventual viremia rebound . In the present study , we analyzed ten rhesus macaques that controlled SIV replication without detectable viremia for more than 2 years . Animals were divided into two groups on the basis of proviral genome sequences at 2 years post-infection . Analysis of the first group exhibiting multiple CD8+ T-cell escape mutations indicated that broadening of CD8+ T-cell responses can be an indicator of the beginning of viral control failure . Conversely , analysis of the second group having no mutation suggested that stability of the breadth of virus-specific CD8+ T-cell responses represents a status of lasting HIV containment by CD8+ T cells . Thus , this study presents a model of stable SIV containment , contributing to elucidation of the requisites for lasting HIV control . | [
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] | [] | 2015 | Broadening of Virus-Specific CD8+ T-Cell Responses Is Indicative of Residual Viral Replication in Aviremic SIV Controllers |
Long-term , repeated measurements of individual synaptic properties have revealed that synapses can undergo significant directed and spontaneous changes over time scales of minutes to weeks . These changes are presumably driven by a large number of activity-dependent and independent molecular processes , yet how these processes integrate to determine the totality of synaptic size remains unknown . Here we propose , as an alternative to detailed , mechanistic descriptions , a statistical approach to synaptic size dynamics . The basic premise of this approach is that the integrated outcome of the myriad of processes that drive synaptic size dynamics are effectively described as a combination of multiplicative and additive processes , both of which are stochastic and taken from distributions parametrically affected by physiological signals . We show that this seemingly simple model , known in probability theory as the Kesten process , can generate rich dynamics which are qualitatively similar to the dynamics of individual glutamatergic synapses recorded in long-term time-lapse experiments in ex-vivo cortical networks . Moreover , we show that this stochastic model , which is insensitive to many of its underlying details , quantitatively captures the distributions of synaptic sizes measured in these experiments , the long-term stability of such distributions and their scaling in response to pharmacological manipulations . Finally , we show that the average kinetics of new postsynaptic density formation measured in such experiments is also faithfully captured by the same model . The model thus provides a useful framework for characterizing synapse size dynamics at steady state , during initial formation of such steady states , and during their convergence to new steady states following perturbations . These findings show the strength of a simple low dimensional statistical model to quantitatively describe synapse size dynamics as the integrated result of many underlying complex processes .
Chemical synapses are sites of cell-cell contact specialized for the transmission of signals between neurons and their respective targets . Historically , synapses have been viewed as biological structures that can change when driven to do so by various physiological signals , but are otherwise relatively stable ( but see [1] ) . This view was radically altered , however , by the advent of techniques which allowed for repeated measurements of individual identified synapses in living neurons over long time durations . Such studies have revealed that synapses , in addition to activity-dependent changes in their morphological and functional properties , also change spontaneously in the absence of particular activity patterns , or , for that matter , any activity at all ( e . g . [2]–[11]; see also [12] ) . These spontaneous changes in synaptic properties are not surprising in view of the intense dynamics of synaptic molecules [13]–[18] Nearly two decades of intensive studies have uncovered a bewildering number of molecules and molecular processes involved in synaptic formation , plasticity and tenacity . While their involvement in aspects of synaptic biology is undeniable , principles of synaptic function often become obscured by the myriad of molecular details ( a conundrum raised long ago; see [19] ) . On the other hand , by accepting the premise that synaptic properties are the integrated result of numerous microscopic processes , which can be heterogeneous , non-stationary , stochastic , and to some extent intractable , repeated measurements of the properties of individual synapses provide an opportunity for quantitative , phenomenological study of long-term population dynamics of synapses . This is essentially a statistical approach in which the dynamics of the individual synapse are described probabilistically , while causal or deterministic relations emerge at the population level . Such studies can uncover overarching principles that govern synaptic population properties as well as their relationships with physiological signals such as network activity [3]–[5] and neuromodulation [20] . Indeed , recent work based on such measurements has resulted in several key findings , described in more detail below: ( 1 ) distributions of synaptic sizes are broad , skewed and remarkably stable over time; ( 2 ) individual synapse sizes exhibit significant spontaneous fluctuations over time scales of many hours; and ( 3 ) these synaptic dynamics are size-dependent and constrained by network activity and other physiological signals . In the current study we use a simple and well known statistical model , the Kesten process , to describe effectively synaptic remodeling dynamics based on the three aforementioned findings . We use empirical data from continuous , long-term ( days ) imaging experiments to show that the model captures the dynamics of individual synapses and the statistical properties of synaptic populations , the effects of network activity levels and cholinergic tone and the dynamics of synapse formation .
We base our model on empirical findings that were obtained in a previously described system [4] , [20] in which ex-vivo networks of rat cortical neurons , automated microscopy , multielectrode array ( MEA ) recordings of network activity , fluorescent reporters and provisions for maintaining optimized environmental conditions were combined to allow for imaging and tracking of individual synapses at 10–30 min intervals for many days ( as shown in Figs . 1A–C ) . Sizes of individual glutamatergic synapses were estimated by quantifying the fluorescence of enhanced green fluorescent protein tagged PSD-95 ( PSD-95:EGFP ) . PSD-95 is a core postsynaptic scaffolding protein in glutamatergic synapses that is thought to control the number of glutamate receptors at the postsynaptic membrane through direct and indirect interactions [21] , [22] . Therefore PSD-95:EGFP fluorescence can serve as a proxy of synaptic strength [23] . More conservatively , changes in PSD-95:EGFP fluorescence reflect synaptic remodeling , changes in spine head size and PSD area [24] , [25] ( and will be referred to hereafter as synaptic size ) . Previous work with this system as well as studies from other groups using different systems , gave rise to three key findings that form the basis of our model . We now summarize these in some detail: Synaptic size is affected by multiple molecular mechanisms of a variety of natures: direct and indirect , size-dependent and -independent , activity dependent and -independent , which collectively span a broad range of timescales [18] , [29] . The integrated effect of these various mechanisms support the long-term stability of synaptic structure but also result in rich dynamics over multiple timescales . From a practical point of view , changes in synaptic size can be broadly divided into two types: additive , namely independent of current synaptic size , and size-dependent , of which the simplest dependence is linear – namely multiplicative changes . The question of whether various forms of synaptic plasticity are additive or multiplicative has received considerable attention in the literature [28] , [30]–[32] . From general biological considerations , however , it is plausible to expect that over long enough times synapses will undergo both types of changes . Indeed , on the basis of plots such as that shown in Fig . 2 it has been suggested that individual synaptic dynamics are the sum of three components [20]: two deterministic components - a multiplicative downscaling and an additive positive term - with an added stochastic component ( see Fig . 5G in [20] ) . Here , we propose a model of synaptic dynamics which is inherently stochastic , includes both additive and multiplicative random components , and relates to electrical activity through a parametric dependence of the stochastic processes . We model the synaptic size trajectories by the following dynamics: ( 1 ) Where xt is the synaptic size at time t and εt and ηt are random variables drawn from some distribution . This is a minimalistic model that includes both additive and multiplicative random events; it is an effective description in which each variable does not necessarily relate directly to a microscopic event but rather captures the integrated effect of many processes as discussed in the Introduction ( see Supporting Information , Text S1 , for a more detailed justification ) . It is formulated here in discrete time , so that the random variables represent all processes that occurred in the time between two measurements; therefore , if measurements are made at a different time resolution , the effective variables εt and ηt will generally be altered . Accordingly , we focus here on general properties of the model and not on fitting precise , absolute values to the variables . In the simplest form of the model the variables εt , ηt are drawn independently at each time step and independently from one another , each from a given ( fixed ) distribution . Note that εt is drawn from a distribution that generally includes values smaller or larger than 1 , so that this factor can either decrease or increase synaptic strength . In probability theory the model ( 1 ) is known as the Kesten process [33] and has been used to describe complex systems in economics and other fields [34] , [35] . In spite of its seemingly simple formulation , it can give rise to rich and complex dynamics . The Kesten process is known to exhibit two qualitatively different behaviors depending on the regime of the crucial parameter 〈ln ε〉 , the average logarithm of ε over its distribution: For 〈ln ε〉>0 the process diverges and no limiting distribution is reached . For 〈ln ε〉<0 it is statistically stable and approaches a limiting distribution f ( x ) at long times . Some intuition for this property can be gained by considering the case ηt = 0 in ( 1 ) : the process then reduces to a purely multiplicative one . In this case , ln x performs a random walk with steps of size ln ε . If the mean step-size is positive , 〈ln ε〉>0 , the mean of the random walk drifts to infinity; adding ηt cannot prevent this runaway . If , on the other hand , the mean step-size is negative , 〈ln ε〉<0 , the logarithmic random walk tends to -∞ and accordingly the original variable xt decreases to zero . In this case the “injection” of a positive ( on average ) ηt in each step can provide the balancing drive away from zero required to induce a finite average and a stable limiting distribution [35] . This is indeed the case , and within this region , a stable limiting distribution exists regardless of the distribution of ε and η . This limiting distribution is generally non-Gaussian , skewed and decays asymptotically as a power-law [33] . It follows that in the stable regime 〈ln ε〉<0 the Kesten process exhibits the qualitative features of our data: fluctuating individual trajectories accompanied by skewed , non-Gaussian stable distributions . As 〈ln ε〉 increases and the process approaches the instability transition from below , although it remains stable , it changes quantitatively: trajectories exhibit larger and larger excursions to rare values ( “intermittent”-like behavior ) , and correspondingly the stable limiting distribution broadens ( as illustrated in Fig . 3 ) . We first characterized the regime of parameters of the model which is in quantitative agreement with our data . Naively , one might expect that a simple linear regression of the empirical mapping xt+1 = εtxt+ηt would give an estimate of the first moments of the ε- and η- distributions . Such estimations , however , prove to be highly noisy and unreliable , as the small changes in synapse sizes ( or more specifically , PSD-95:EGFP fluorescence levels ) measured over these short time intervals are dominated by measurement noise , as shown by measuring ‘changes’ in chemically fixed synapses ( Fig . S1; 1067 synapses from 4 neurons ) . Much of this measurement noise is removed by filtering the data with a 5 time-point low pass filter ( Fig . S1B–D ) , but this procedure precludes estimates based on single time steps . We therefore estimated the average values of ε and η from iterated mappings over multiple time steps ( i . e . longer time intervals ) and multiple synapses under the assumption that these values are stationary and similar for all synapses . This estimation is based on the following observation: When the Kesten mapping is applied twice consecutively one finds the relation ( 2 ) Repeated application of this relation and averaging over the distributions of the random variables given xt results in an explicit formula for the average k-iterated map ( 3 ) Estimates of could therefore be obtained by applying linear regressions to such mappings over an increasing number of time steps k , and fitting the slopes to a power k of . This procedure is illustrated in Fig . 4: Fig . 4A depicts a linear fit for a one-step empirical mapping ( k = 1; 1087 synapses tagged with PSD-95:EGFP; same low pass filtered data as in Fig . 2A ) , whereas Figs . 4B–D show mappings for 8 , 24 and 48-steps , respectively . As expected , these mappings become more noisy as the number of steps increases; at the same time , the slopes of the linear fits decrease , corresponding to an increasing value of k and the reduced value of 〈ε〉k ( reminder: in the stable regime approximately . As shown in Figs . 4E , F for 1087 synapses followed for 24 hours ( 48 time steps of 30 min ) this procedure allowed for a reasonable estimation of , which in this case was found to be 0 . 9923 . We validated this procedure by using only half of the data to estimate and then using this estimate ( 0 . 9925 ) to predict linear fit slope values for increasing k values in the second half of the data . As shown in Fig . S2A , the prediction was quite good . These estimates are very close to 1 , indicating that the process may be near the transition point ( formally 〈ln ε〉 = 0 ) , consistent with the distributions being broad and long-tailed . We used the same procedure on the data of Fig . 2B–D and found similar estimates ( 0 . 9899 , 0 . 9829 , 0 . 9934 for time steps of 25 , 25 and 60 min , respectively ) . The second parameter in Eq . ( 3 ) , , sets the scale of the population average . In the analysis presented in Fig . 4 the data was normalized to unit mean at t = 0; As the mean synapse size remains constant ( Fig . 1E ) the value of in these units is constrained to be . Consequently , equation 3 is reduced to ( 4 ) Indeed the values of the constant term in the aforementioned linear fits come out very close to not only for the four time points shown in Fig . 4A–D but also for the linear fits performed at all 48 time points ( Video S1 ) . We next tested the ability of the Kesten process in the estimated parameter regime to faithfully reproduce the experimentally measured dynamics of individual synapses , the distribution of synaptic sizes and the relationships between changes in synaptic size and initial size . The results are shown in Fig . 5 . Using the initial distribution of synapses from Fig . 2A and the estimate of derived in Fig . 4 , trajectories were simulated for all 1087 synapses for 320 half-hour time steps ( 160 hours ) . As shown in Fig . 5A , the ‘sizes’ of individual simulated synapses fluctuated in a manner qualitatively similar to that observed for real synapses ( compare with Fig . 1D ) . Interestingly , in common with experimental observations the simulation was associated with the ‘elimination’ of a small number of synapses , i . e . synapses whose ‘size’ dropped to zero . Such synapses ( 12 out of 1087 in this example ) were not included in subsequent analysis . The distribution of simulated synaptic sizes remained stable and similar to the original , experimentally measured , skewed distribution for the entire simulation period ( Fig . 5B ) . When the slopes of linear regressions were used to estimate as explained for Fig . 4 , the resulting estimate ( 0 . 9929; Fig . 5C–E ) was very close to the one used for the simulation ( 0 . 9923; Fig . 4 ) validating this approach to estimate . Finally , when changes in synaptic ‘sizes’ after the first 24 hours were plotted as a function of their original ‘sizes’ the resulting dependence was remarkably similar to that observed experimentally ( compare Fig . 5F with Fig . 2A ) . While the methods described above can give good estimates of the first moments ( means ) of ε and η , they do not provide information on their second moments ( variances ) . In the simulation described above , values for the latter were chosen such that the decay rate of goodness of fit ( R2 values in plots such as those of Fig . 5C , D ) was similar to that observed for the experimental data . In principal , the standard deviations of ε and η could be directly estimated from the squares of residuals in a linear regression of the mapping xt+1 = εtxt+ηt ( see legend of Fig . S2 ) . However , as noted above , apparent changes in synapse sizes measured over single time steps were dominated by measurement noise , effectively ruling out direct estimations of standard deviations in this manner . Nevertheless , when such estimations were obtained and compared for low-pass filtered experimental and simulated data sets , they were quite similar ( Fig . S2B , C ) indicating that the standard deviation values used in the simulation above were reasonable . These results thus show the Kesten process can quantitatively capture and faithfully reproduce the dynamics of individual synapses and the distributions of synaptic sizes in large populations of dynamic synapses . Being a phenomenological model , the question naturally arises how sensitive is the fit of experimental data to the parameters of the model . The answer to this question is largely determined by the sensitivity of the Kesten process itself to the underlying distributions from which ε , η are drawn . In his original work , Kesten showed that the tail of the limiting distribution , when it exists in the stable region , always decreases asymptotically as a power-law [33]: ( 5 ) where μ is a property of the ε-distribution . It is the positive number that obeys the relation 〈εμ〉 = 1; thus μ depends on all moments of the distribution and is not unique , as many different distributions can have the same value of μ satisfying this relation . This suggests that different ε-distributions belonging to the same μ-class , when used in Kesten processes , may give rise to similar limiting distributions . Indeed , simulations of the Kesten process displayed in Fig . 6 support the possibility that these limiting distributions are in fact of identical shape . Fig . 6A shows that three members of such a μ-class , with very different ε-distribution types ( Uniform , Gaussian and Gamma distributions ) , result in limiting distributions of the Kesten process with identical shapes when scaled linearly ( right panel ) , not only in their asymptotic tail but over their entire range . This implies that the distribution shape is robust with respect to the details of ε within a given μ-class . Not only is the Kesten process quite insensitive to the particular choice of the ε -distribution , we found that its limiting distribution is insensitive also to the additive random variable η , except in determining the absolute scale . In other words , limiting distributions of Kesten processes can be effectively scaled merely by changing the distribution of the random variable η . As explained above , intuitively the role of this variable is to provide an effective boundary condition for the multiplicative process , keeping synaptic sizes from collapsing to zero; accordingly , it does not affect the distribution shape but only the absolute set-point at which the “forces” balance each other . This property is illustrated in Fig . 6B , where the ε-distribution was held fixed and different distributions were assigned to η . This figure shows the resulting limiting Kesten distributions ( left ) , as well as the same distributions on a normalized scale ( right ) , showing that they all have the same shape . The conclusion from these results is that the same population distribution can be obtained from the Kesten process with many underlying sets of microscopic random variables ( ε and η ) . On one hand , this insensitivity to microscopic details strongly justifies its usefulness as an effective description of the phenomenon studied here; on the other , this robustness implies that by measuring the distribution alone one cannot infer much about the details of these underlying processes [36] . The analysis described so far indicates that synaptic size dynamics governed by a stochastic Kesten process result in synaptic populations with limiting size distributions which are qualitatively and quantitatively similar to empirically measured distributions of synaptic sizes . Can this statistical framework also explain changes in synaptic size distributions caused by various experimental manipulations ? Previous studies have shown that statistical properties of synaptic populations are affected by changes in network activity as well as by additional experimental perturbations . In the most well-known example , pharmacological suppression of network activity by TTX leads to a broadening of synaptic size distributions [4] , [37]; a similar effect was observed following experimental elevation of cholinergic tone using carbachol ( CCh ) , which did not strongly alter mean firing rates but changed the temporal structure of spontaneous activity [20] . Following TTX application , synaptic distributions were previously shown to retain their shape in scaled units , and so this phenomenon was referred to as “synaptic scaling” ( reviewed in [38] ) . This property is found also in our measurements of synaptic sizes: Fig . 7A shows the distribution of synaptic sizes measured for one neuron , before and 24 hours after the application of TTX . Suppression of spontaneous activity was associated with a broadening of synaptic size distribution . Fig . 7B shows the same distributions on a scaled axis: ( this variable , which measures the number of standard deviations away from the mean , is sometimes referred to as the z-score ) . It is seen that the distribution shape remained intact . The same scaling behavior is seen also following exposure to CCh ( Fig . 8A , B ) . Thus the scaling of synaptic size distributions – a change in the distribution scale but not in its shape – is found also in response to a more general perturbation that does not significantly change average firing rates . Scaling , or “data collapse” , of distributions is a well-known phenomenon in the physics of complex systems [39]–[41] , and has recently been observed also in biological fluctuations [36] . In order to understand the origin of scaling in synaptic size distributions following a perturbation , it is helpful to observe individual synapse dynamics before , during and after the perturbation , as our time-lapse measurements allow for . We have seen in the previous sections that individual synapses exhibit what appear to be stochastic trajectories over time , and our aim is now to reconcile these dynamics with the rescaling property at the population level . First , we consider the relation between the initial sizes of individual synapses and their size change 24 hours after performing a perturbation Δx = xt = 24 h−xt = 0 h . Figs . 7C and 8C depict this change averaged over synapses as a function of the initial value xt = 0 h , showing that there is no correlation between initial synaptic size and the change in its size induced by the perturbation . Second , one may use the rank order of individual synapses before and after the perturbation to investigate the transformation they have undergone: any deterministic , monotonically increasing transformation acting on individual synapses would preserve their rank order in the population . Figs . 7D and 8D show the rank orders prior to the perturbations as a function of value ( blue dots ) , tracing a curve with the same shape as that of the cumulative probability distribution . In the same figure , the final values after perturbation are depicted as a function of their original rank order ( red dots ) ; this analysis clearly shows that rank order is not preserved even though the distribution exhibits scaling . This result corroborates previous work which quantified the change in rank order over time within steady experimental conditions , and showed that the rank order gradually deteriorates even under conditions where the distribution remains exactly the same [4] . In principle , one could induce a scaling of the distribution by simply multiplying all synapses by a constant such that for each synapse ; this was the interpretation originally given to the population-level data [37] . At the individual synapse level , this would imply a synaptic change ( Δx ) which increases linearly with the initial value such that ( with a>1 for a broadening of the distribution , as in these experiments ) , and the preservation of rank order . Both these predictions are inconsistent with our single synapse measurements ( the result of such a transformation on the original data is illustrated in Figs . 7C , D and 8C , D ) . What , then , might be a plausible population-level explanation for the observed scaling of synaptic distributions ? Within the Kesten model , scaling emerges naturally from a change in the parameters of the underlying stochastic processes . Specifically , changes in ε-distributions and/or η-distributions can lead to a rescaling of the limiting distribution of synaptic sizes as shown in Fig . 6 . Previous work has shown that , in plots such as that shown in Fig . 2 , application of TTX affects strongly the slope whereas application of CCh noticeably alters the intercepts [4] , [20] , reflecting changes in the average values of the random variables ε and η respectively during these periods . Fig . 9 shows the same analysis as performed in Figs . 7 and 8 starting with the synapses of Fig . 7 . These synapses were first evolved for 24 hours according to a Kesten process , using fixed statistical parameters . At the time of a simulated perturbation , one parameter of this process was altered; in this particular example , only was changed , but similar results could be obtained by altering the η-distribution as well . A population-level rescaling results ( Fig . 9A–B ) , but individual synapse size does not scale multiplicatively ( Fig . 9C ) and consequently , rank order is not preserved ( Fig . 9D ) . We thus conclude that changes in population synaptic distributions induced by two very different pharmacological manipulations , both of which induce scaling at the distribution level but not at the individual synapse level , are well captured by assuming that these manipulations modify the stochastic parameters underlying the Kesten process . Up to this point , the analysis focused on synapses that existed throughout the entire experiment ( or analysis period ) . Cortical networks however , both in vivo and in vitro , also exhibit some degree of synaptic turnover , that is , the formation of new synapses and the elimination of others . The formation of a new excitatory synapse involves the formation of a new PSD , which can be detected as the accumulation of PSD-95:EGFP at a location at which no such accumulation was present before . An example of such an event is shown in Fig . 10A , B . Prior studies have suggested that this accumulation occurs in a gradual manner , but not necessarily monotonically , with periods of growth interspersed with pauses and even temporary periods of shrinkage [42] , [43] . Fig . 10C shows how fluorescence accumulates with time at a site that was identified as a newly forming synapse . Can the dynamics of new PSD formation also be captured by a Kesten process ? To examine this possibility , we scrutinized time-lapse image series such as those shown in Fig . 1A–C for synapse formation events , and measured the evolution of PSD-95:EGFP fluorescence at these new synapses . Data were collected from spontaneously active networks ( no pharmacological manipulations ) after 3–4 days of baseline imaging . As seen in Fig . 10C , the increase of PSD-95:EGFP fluorescence was gradual , not entirely monotonic and quite protracted . To pool data from multiple occurrences of synapse formation , data was first temporally aligned to the first time point at which a new synapse was detectable . Note that as new synapses appeared at different times during time-lapse sessions of finite duration , this alignment resulted in synaptic trajectories of varying lengths . When data for all new synapses ( n = 25 , 4 neurons from 3 experiments ) was normalized and pooled ( see legend of Fig . 10 ) , the average time course of PSD formation was obtained ( Fig . 10D ) . We then generated simulated trajectories for 200 synapses based on a Kesten process , using an ε-distribution ( and an η distribution constrained by such that as explained above ) that best fit the experimental data . Two exemplary trajectories shown in Fig . 10E appear qualitatively similar to typical trajectories measured in experiments , such as the one shown in Fig . 10C . Plotting the average time course for the simulated data revealed that the experimental data could be described very well by a Kesten process ( Fig . 10F ) . Interestingly , the values of which provided the best fits were slightly smaller ( 0 . 962 ) than estimates obtained for established synapses in the same neurons . The observed difference indicates that the molecular dynamics associated with new synapse formation are somewhat faster than those occurring at established synapses , in line with a recent comparison of PSD-95:EGFP fluorescence fluctuations at stable and transient dendritic spines in vivo [24] . Because the initial size of a new synapse is close to zero , the average trajectory of a growing synapse can be approximated as a sum of a geometric series: ( 6 ) Under our normalization this is simply , thus giving an exponential function with a typical timescale ≅13 h . As shown in Fig . 10F , calculating equation ( 6 ) for the same values of ( and ) used in the simulations resulted in an excellent fit with the experimental and simulated data . The average growth trajectory shows that the time course of PSD-95:EGFP accumulation at new sites occurred over many hours . This is much slower than the time course ( 1–2 hours ) previously reported for PSD-95:EGFP accumulation in cultured hippocampal neurons at 8–12 days in vitro [42] but in good agreement with the time course of synaptic maturation measured in the barrel cortex of adult ( >1 month old ) mice [44] , [45] . This difference may relate to the different developmental stage of the networks used in these studies . To examine this possibility , we measured PSD-95:EGFP accumulation at new sites in cortical networks grown and imaged in an identical fashion to those described throughout this study , except that here , week-long imaging sessions were initiated at days 9–10 in vitro instead of days 18–21 ( this dataset is mentioned briefly in [4] , and is exemplified in Video S1 in that study ) . We found that PSD-95:EGFP accumulation at new sites at days 10–13 in vitro ( 79 synapses , 3 neurons ) was dramatically faster ( Fig . 10G ) , concurring with rapid spine maturation in cultured slices of similar age [46] . Here too , the data could be very well fit to simulated trajectories based on a Kesten process as well as to the analytical approximation of equation ( 6 ) ( Fig . 10H ) , except that in this case , the values of required for such fits were radically smaller ( ∼0 . 405 ) than those used so far ( Figs . 4 , 5 , 9 ) . This indicates that synaptic molecular dynamics during early developmental stages are faster than those occurring later on , in agreement with the extraordinary axonal and dendritic dynamism and high synapse formation and elimination rates observed in such networks ( compare Video S1 in [4] , to Video S1 in [20]; for review , see [23] , [47] ) .
In the approach taken here the dynamics of the single synapse were assumed to reflect the integrated result of many microscopic processes , with their unknown dynamics represented by effectively random variables . As we have no prior knowledge of the statistical properties of these effective variables , an important consideration is the model's sensitivity to these statistics . We have found that the Kesten process shows a high degree of robustness with respect to these statistics: the shape of the distribution is completely insensitive to the properties of the additive variable ( Fig . 6 ) ; the insensitivity of the distribution tail is ensured by the Kesten theorem , and our results extend this to show insensitivity of the distribution shape in the entire range . The dependence on the multiplicative variable is weak , and here too , the known dependence of the tail on its properties seems to apply to the entire distribution shape . These properties render the Kesten model an attractive candidate for effective modeling of synapse size dynamics . Why is the Kesten process so generic and robust in its properties ? Let us consider some global properties of the neural network in which the synapses are embedded . We know that the system is homeostatic , adaptive , and maintains itself around a stable state for some length of time while still fluctuating around it . Therefore the effective single-synapse dynamics must contain a “restoring” component in addition to an additive random component . If the value of the restoring component is allowed to be random as well , then to first ( linear ) approximation the Kesten process is obtained ( see Text S1 for details ) . This proximity to a stable self-organized state may be at the core of the robustness of this model . An interesting result supporting the emergence of Kesten-like dynamics as a result of network self-organization can be found in recent simulations which included the realization of multiple plasticity mechanisms [48] . In these simulations the effective dynamics of individual synapse were computed directly , and it was found that a multiplicative element in these dynamics emerged although it was not explicitly incorporated into the ingredients of the simulation . Thus , notwithstanding the debate concerning the additive or multiplicative nature of synaptic changes , their embedding in a network with both positive and negative feedback resulted in effectively stochastic changes that were both additive and multiplicative . It is worth noting in this regard that the Kesten process is , arguably , the simplest stochastic model that includes a state-dependent component ( εtxt ) and a state-independent component ( ηt ) ; other models , in which the dependence on xt is nonlinear , may be equally plausible . Why should synapse dynamics be described by a statistical model , when so much is known about synaptic plasticity ? A useful analogue in this respect is the description of neurotransmitter release as a stochastic process , modeled according to well-known statistical models , namely binomial or Poisson processes [49] , [50] . Here synaptic vesicle release is characterized by a small number of parameters such as the number of release sites and the probability of release , both of which can vary as a function of history and stimuli in the network . Thus statistical models provide a compact , useful description which allows their parameters to change in response to physiological signals and perturbations . In contrast to this accepted statistical view of neurotransmitter release , changes in synaptic strength are usually described by deterministic rules that depend on detailed firing patterns of the connected neurons . The existence of a simple statistical model that reliably captures many aspects of the dynamics exhibited by individual synapses and synaptic populations is thus an interesting finding as it extends the stochastic view of the synapse to the realm of synaptic plasticity and tenacity . The formulation of synaptic dynamics as a compact , low dimensional statistical model , essentially a combination of multiplicative and additive components , would seem to invite attempts to map each component to a specific biophysical process . For example , εt might be considered to represent a rate constant in a first order reaction in which synaptic molecule loss ( and accumulation ) rates are proportional to synapse size [51] . Similarly , ηt might be viewed as an additive process related to diffusion ( or synthesis ) of scarce synaptic molecules . Such specific mappings imply that synaptic remodeling is ultimately dictated by a very small number of dominant processes , with the rest of the molecules and processes playing only secondary or modulatory roles . Indeed , it has recently been suggested that in spite of the hundreds of molecules and processes implicated in Long Term Potentiation , this form of synaptic plasticity mainly depends on a very small number of factors , such as an adequate pool of surface glutamate receptors [52] . Alternatively , the insensitivity of the model to many underlying details may suggest that it is better viewed as an effective description of a large collection of processes , generally correlated with one another , combining in such a manner that their overall outcome is effectively a sum of multiplicative and additive variables . If this is the case , the relative insensitivity to underlying details ( as exemplified in Fig . 6 ) , indicates that it may not be possible , even in principle , to “reverse engineer” the population dynamics in order to infer their underlying microscopic processes . Interestingly , a similar biological buffering effect was suggested to underlie protein distributions measured in cells and to induce universal distributions across microorganisms and conditions [36] . We propose that the general question of the relation between multiple correlated microscopic stochastic processes and emergent behavior at the population level of organization poses fundamental questions in Neuroscience as well as in cell biology that merit further investigation , both experimental and theoretical . Several groups have recently addressed the modeling of synaptic size dynamics by stochastic processes; we mention here two notably different approaches and compare them to ours . In the work of Yasumatsu and coworkers ( 2008 ) spontaneous synaptic size fluctuations were modeled by a generalized Fokker-Planck equation . Under this framework , different assumptions on the dependence of the moments on the synaptic volume lead to different distributions; thus to fit the data in various conditions ( for example inhibitors ) , separate realizations of the model are needed . This reflects the fact that in the Fokker-Planck equation essentially any distribution can be obtained by assuming the appropriate potential and a Gaussian noise term . However there is no justification to choose a particular potential; moreover the steady-state distribution is highly sensitive to this choice . A second approach was proposed by Loewenstein and coworkers ( 2011 ) in which spine remodeling is viewed as a purely multiplicative process , such that the log of the spine size is a sum of two Ornstein–Uhlenbeck processes and a white noise component . This model provides a good fit to the spine-size distribution and the timescales of the two processes can be fit from the correlation function , but is hard to justify biophysically beyond its successful fitting results . It should be noted that with finite data sets , broad distributions can often be fit equally well to several different functions . The reason is that the tails , which distinguish between different skewed distributions , are poorly sampled . Indeed our data can also be described by a log-normal distribution , as illustrated in Figure S3 . Interestingly , the low end of the distribution seems to be better described by the Kesten model than by the log-normal distribution ( Fig . S3 C , D ) . The non-uniqueness of steady-state distributions in determining underlying stochastic models has been raised also in other areas of biophysics [36] , [53] . It highlights the need for experiments that introduce perturbations and measure the system's transient dynamics , in addition to steady state measurements . The merit of different models should then be assessed based on properties other than fits to distributions . In this regard the Kesten model framework has two advantages: First , the inherent rescaling symmetry of the Kesten distribution under a change of underlying microscopic random variables , reflects nicely the measured property of synaptic distribution rescaling in response to perturbations; second , a compound process with two types of accumulation – sum and product – can be justified as a generic , effective stochastic description for a large number of correlated processes . Operationally , if one accepts the premise that synaptic remodeling is governed by a vast number of complex , interconnected and to some extent , intractable molecular processes , then the model proposed here may provide a useful framework for characterizing synaptic dynamics and predicting their outcome irrespective of underlying details . However , it is also worth considering the functional implications of this perspective . In the context of learning theories , synapse remodeling has been traditionally viewed as a process dictated by physiological signals , and interpreted in the context of synapse-specific “learning rules” or global homeostatic processes . Such learning rules are expected to ultimately provide a link between individual synapse behavior and the systems property , namely learning and memory . The approach proposed here , to view synaptic dynamics as stochastic , seems to represent a major departure from this deterministic view . Several caveats regarding these two views should be considered , however . Starting with the data used here , it is important to note that these were obtained in networks devoid of external input , and thus , perhaps , in the absence of strong instructive forces . Moreover , the forms of spontaneous activity observed in these networks are strongly reminiscent of cortical activity forms observed during deep sleep and anesthesia ( e . g . [20] , [54] ) . Thus , it may be argued that the remodeling dynamics observed and analyzed here might be more representative of “baseline” synaptic dynamics in the absence of meaningful input . However , it is noteworthy that fluctuations in PSD size [24] , [55] , spine volume [3] , [56] and presynaptic bouton size [10] of comparable magnitude are also observed in vivo . For example , recent measurements of synaptic size fluctuations in cortical neurons of 8 week old mice based on PSD-95:EGFP fluorescence ( as done here ) reveal that the magnitude of such fluctuations is very considerable ( ∼48% change on average over periods of 0 . 25 to 4 days [24]; for comparison , changes induced in organotypic rat hippocampal slice cultures by protocols that drive long-term potentiation are ∼33% on average [25] ) . While these spontaneous fluctuations might be driven by the animal's behavioral experiences , it should be noted that in cell culture [2] , [4] and in organotypic cultures [5] , fluctuations persist even when all activity is blocked . It would thus seem that our empirical observations are not limited to the setting of cell culture; furthermore , if spontaneous size fluctuations are as large as the aforementioned studies suggest , a framework which brings into account baseline size dynamics is needed . Second , suggestions for the governance of synaptic remodeling by selective , rather than instructive processes have been previously put forward ( for example [4] , [23] , [56]–[60] ) . The underlying notion is that remodeling occurs stochastically , and that favorable changes are selected by physiological signals . According to this view , even though synaptic remodeling is driven by stochastic processes , on the whole it is also governed by instructive processes in the form of feedback and reinforcement . Third , it is assumed that physiologically-relevant manipulations might lead to parametric changes in ε- and η- distributions; such changes could occur at select sets of synapses ( for example , synapses that undergo directed potentiation or depression ) or at larger sets of synapses ( in response to global changes in input or activity level , for example ) . Thus , while individual synapse remodeling may appear to be effectively stochastic , statistical properties of select or large synaptic populations may still change in a manner determined by signals in the environment [32] . It remains to be seen how sizes of such populations relate to the relatively small number of connections formed between any two neurons [61] and at what organizational level , if any , invariance and determinacy emerge [62] .
The data presented here is mainly taken from two prior studies ( [4] , [20] ) and [63] . Detailed descriptions of the methodologies used during those studies , which can be found in the aforementioned references , are summarized briefly below . Primary cultures of rat cortical neurons were prepared from cortices of 1–2 days-old rats ( either sex ) which were dissected , dissociated and plated on thin glass Multielectrode array ( MEA ) dishes ( MultiChannelSystems MCS , Reutlingen , Germany ) . Cells were plated in media containing minimal essential medium ( MEM , Sigma ) , 25 mg/l Insulin ( Sigma ) , 20 mM Glucose ( Sigma ) , 2 mM L-Glutamine ( Sigma ) , 5 µg/mL Gentamycin sulfate ( Sigma ) and 10% NuSerum ( Becton Dickinson Labware , Bedford , Massachusetts , United States ) . Preparations were then transferred to a humidified tissue culture incubator and maintained at 37°C in a gas mixture of 5% CO2 , 95% air . Half the volume of the culture medium was replaced 3 times a week with feeding media , essentially identical to seeding media , except for the omission of NuSerum , lower L-Glutamine concentrations ( 0 . 5 mM ) and the addition of 2% B-27 supplement ( Invitrogen , San Diego , CA ) . Expression of enhanced green fluorescent protein ( EGFP ) -tagged PSD-95 was carried out by transduction on day 5 in-vitro with third generation lentiviral particles prepared and used as described elsewhere [20] . Imaging was performed on a custom designed confocal laser scanning microscope using a 40× , 1 . 3 N . A . Fluar objective ( Zeiss ) . The system was controlled by software written by one of us ( NEZ ) and includes provisions for automated , multisite time-lapse microscopy . The MEA dishes were mounted on a commercial 60-channel headstage/amplifier ( MultiChannelSystems ) attached to the microscope's motorized stage , and covered with a custom designed cap containing inlet and outlet ports for perfusion media and air mixtures , a reference ground electrode and a removable transparent glass window . The MEA dish was continuously perfused with feeding media ( described above ) at a rate of 2 . 5–5 ml/day by means of a custom built perfusion system based on an ultra-slow peristaltic pump ( Instech Laboratories Inc . , Plymouth Meeting , PA , USA ) using an imbalanced set of silicone tubes . The tubes were connected to the dish through appropriate ports in the cap . A 95% air/5% CO2 mixture was continuously streamed into the dish at very low rates through a third port with flow rates regulated by a high precision flow meter ( Gilmont Instruments , IL , USA ) . The base of the headstage/amplifier and the objective were heated to 37°C and 36°C respectively using resistive elements , separate temperature sensors and controllers , resulting in temperatures of 36–37°C in the culture media . EGFP was excited using the 488 nm line of an argon laser . Fluorescence emissions were read through a 500–545 nm bandpass filter ( Chroma Technology , Brattleboro , VT ) . Time-lapse recordings were usually performed by averaging six frames collected at each of 7 to 26 focal planes spaced 0 . 8–1 µm apart . All data were collected at a resolution of 640×480 pixels , at 12 bits/pixel , with the confocal aperture fully open . Data was collected sequentially from up to 12 predefined sites , using the confocal microscope robotic XYZ stage to cycle automatically through these sites at intervals of 10 minutes ( Fig . 10G , H ) , 60 minutes ( Fig . 2D ) 25 minutes ( Fig . 2B , C ) or 30 minutes ( all other data ) . Focal drift during the experiment was corrected automatically by using the microscopes' “autofocus” feature . Experiments performed in chemically fixed neurons [4] , were performed as described above except that here preparations were first fixed with 4% paraformaldehyde in phosphate buffered solution ( PBS ) , washed several times with PBS , placed in growth medium , mounted on the microscope , heated , connected to the sterile air and perfusion systems and imaged at 30 minute intervals as described above for live neurons . Tetrodotoxin ( TTX , Alomone labs , Israel ) and CCh ( Carbachol , Carbamoylcholine ) were applied by diluting them into 100 µL of medium drawn from the culture dish while on the microscope . The mixture was subsequently returned to the dish and mixed gently . Applications to the dish were complemented by simultaneous addition to the perfusion media . Final concentrations in the dish and media were 1 µM ( TTX ) and 20–50 µM ( CCh ) . Data analysis of image time series was performed using custom written software ( “OpenView” ) written by one of us ( NEZ ) . Special features of this software allow for automated/manual tracking of objects in 3D time series of confocal images as described elsewhere [20] . 8×8 or 9×9 pixel ( ∼1 . 3×1 . 3 µm ) areas were then centered on the centers of such objects and mean pixel intensities within these areas were obtained from maximal intensity projections of Z section stacks . For tracking identified puncta , areas were placed initially over all puncta and then a smaller subset ( typically 100–150 per site ) was thereafter tracked . For tracking newly forming puncta , new puncta were manually identified in time-lapse movies and then tracked from the movement of their appearance for as long as they were present , as long as tracking was unambiguous , or the end of the time series was reached . As the reliability of automatic tracking was not absolutely perfect , all tracking was verified and , whenever necessary , corrected manually . Puncta for which tracking was ambiguous were excluded . Microscopy images for Figs . 1 and 10 were processed by contrast enhancement and low-pass filtering using Adobe Photoshop . All data were exported to Matlab or Microsoft Excel and analyzed using custom written scripts . Final graphs were prepared using Excel . All final figures were prepared using Microsoft PowerPoint . | Synapses are specialized sites of cell–cell contact that serve to transmit signals between neurons and their targets , most commonly other neurons . It is widely believed that changes in synaptic properties , driven by prior activity or by other physiological signals , represent a major cellular mechanism by which neuronal networks are modified . Recent experiments show that in addition to directed changes , synaptic sizes also change spontaneously , with dynamics that seem to have strong stochastic components . In spite of these dynamics , however , population distributions of synaptic sizes are remarkably stable , and scale smoothly in response to various perturbations . In this study we show that fundamental aspects of synapse size dynamics are captured remarkably well by a simple statistical model known as the Kesten process: the random-like nature of synaptic size changes; the stability and shape of synaptic size distributions; their scaling following various perturbations; and the kinetics of new synapse formation . These findings indicate that the multiple microscopic processes involved in determining synaptic size combine in such a way that their collective behavior buffers many of the underlying details . The simplicity of the model and its robustness provide a new route for understanding the emergence of invariants at the level of the synaptic population . | [
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] | 2014 | Synaptic Size Dynamics as an Effectively Stochastic Process |
Macroscopic oscillations of different brain regions show multiple phase relationships that are persistent across time and have been implicated in routing information . While multiple cellular mechanisms influence the network oscillatory dynamics and structure the macroscopic firing motifs , one of the key questions is to identify the biophysical neuronal and synaptic properties that permit such motifs to arise . A second important issue is how the different neural activity coherence states determine the communication between the neural circuits . Here we analyse the emergence of phase-locking within bidirectionally delayed-coupled spiking circuits in which global gamma band oscillations arise from synaptic coupling among largely excitable neurons . We consider both the interneuronal ( ING ) and the pyramidal-interneuronal ( PING ) population gamma rhythms and the inter coupling targeting the pyramidal or the inhibitory neurons . Using a mean-field approach together with an exact reduction method , we reduce each spiking network to a low dimensional nonlinear system and derive the macroscopic phase resetting-curves ( mPRCs ) that determine how the phase of the global oscillation responds to incoming perturbations . This is made possible by the use of the quadratic integrate-and-fire model together with a Lorentzian distribution of the bias current . Depending on the type of gamma ( PING vs . ING ) , we show that incoming excitatory inputs can either speed up the macroscopic oscillation ( phase advance; type I PRC ) or induce both a phase advance and a delay ( type II PRC ) . From there we determine the structure of macroscopic coherence states ( phase-locking ) of two weakly synaptically-coupled networks . To do so we derive a phase equation for the coupled system which links the synaptic mechanisms to the coherence states of the system . We show that a synaptic transmission delay is a necessary condition for symmetry breaking , i . e . a non-symmetric phase lag between the macroscopic oscillations . This potentially provides an explanation to the experimentally observed variety of gamma phase-locking modes . Our analysis further shows that symmetry-broken coherence states can lead to a preferred direction of signal transfer between the oscillatory networks where this directionality also depends on the timing of the signal . Hence we suggest a causal theory for oscillatory modulation of functional connectivity between cortical circuits .
Ranging from infraslow to ultrafast , brain rhythms are a nearly omni-present phenomenon covering more than four orders of magnitude in frequency . Of this variety of rhythms , gamma oscillations , falling in the frequency band of 30–150 Hz , is arguably the most studied rhythmic brain activity pattern [1 , 2] . Coherent gamma oscillations have been reported in many brain regions , across many species , and is associated with a variety of cognitive tasks [3 , 4] . There is nowadays growing evidence that the gamma cycle results from emergent dynamics of cortical networks , as a natural consequence of the interplay between interconnected pyramidal cells and subnetworks of interneurons [5 , 6] . Although brain rhythms such as gamma oscillations emerge locally [6] , they are known to interact in a coherent fashion across the cortical scale [7 , 8] . As such , macroscopic oscillations within different brain regions show multiple phase relationships that are persistent across time [9] . Such cross-coupling is crucial for a recently developed theory of how oscillations shape the information transfer within and across the cortex , the communication through coherence ( CTC ) hypothesis , it is further believed to be implicated in a number of higher cognitive functions . For example , enhanced inter-areal gamma-band coherence is considered as the neural correlate of selective attention , in which a network receiving several informational stimulus can preferentially react to one or another depending on task relevance [7] . The CTC hypothesis proposes a mechanism by which gamma rhythms may regulate the information flow [2] . The rationale behind it is that gamma oscillations are the consequence of rhythmic inhibitory feedback inducing an hyperpolarization of the principle cell membrane potential [5 , 6] . Synaptic inputs targeting excitatory cells are then expected to cause a stronger reaction when the inhibition drops off . This gives rise to a temporal window of excitability within the oscillatory cycle during which pyramidal neurons are more likely to respond to stimulation [10] . Ongoing oscillatory firing patterns rhythmically modulate the excitability of networks , and therefore , two oscillating neural groups communicate more efficiently when they maintain a coherent relationship: they can consecutively send their information at the most excitable phase of the target network [4 , 7] . According to the CTC hypothesis , neuronal interactions and transfer of information are dynamically shaped by the phase relationship between neuronal oscillations [11] . In fact it has been proposed that macroscopic rhythms offer a way of adjusting the effectivity of functional connectivity while leaving untouched the anatomical connections [9] and resulting in a functional connectivity [12 , 13] . This functional connectivity , often defined in correlational or information transmission terms , is determined by the relative phase relationship between the communicating networks . Note that an optimal locking mode is not always at the zero phase lag or perfect spike synchrony ( or macroscopic synchrony , as we will see in this manuscript ) . The reason is that , spike transmission from one network to another is not instantaneous and , depending on the distance , projection across the brain can take up to hundreds of milliseconds [14] . Therefore oscillations should be lagged in order to see their spikes arriving at the most excitable phase . This most excitable phase also depends on the biophysical properties of the constituent neurons and of the emergent rhythms ( e . g . as characterized by the network-wide phase response curves [15] ) . An optimal phase difference will thus depend on the properties of the neural groups at work and the distance between the two [16 , 17] . Recent experimental studies have reported a multiplicity of phase differences and it has been argued that such a diversity might facilitate information selectivity [17] . In other words , the emergent collective dynamics of the coupled networks defines how information is chaneled between them , hence by controlling these dynamics one can control dynamically the flow of information without having to change the structural connectivity . Over the past few years , computational studies have devoted a great deal of attention to uncovering the precise functional roles of gamma patterns and gamma interaction . Doing so , they have been able to reproduce experimental findings in support of several predictions of the CTC hypothesis . For instance , modeling approaches have shown that the gamma cycle generates a temporal window of excitability [18] , which is suitable to suppress irrelevant stimuli [19 , 20] . Others studies have demonstrated that the mutual information between two neural groups engaged in rhythmic patterns is tuned with respect to their phase lag [21 , 22] , and a directionality in the flow of information emerges through a symmetry breaking in the phase relationship [12 , 13] . A diversity of phase lags can then be observed which benefits information coding and stimulus reconstruction [23] . Finally , in a rather different line of thinking from the main current view of CTC , computational studies have exposed how cortical oscillations could implement a multiplexing [24–26] . However , the underlying mechanisms responsible for the emergence of the multiple phase-locking modes and of the ensuing functional connectivity as proposed by the CTC are not trivial . So far , no mechanistic view to explain the observed variety of phase lags has been proposed . The question is then to identify through what synaptic mechanisms can these rhythms coordinate their temporal relationships in such a diversity of locking modes . Answering this question is crucial and knowing the chain of causation that allows for coherent oscillations is key to understanding their functional role [27 , 28] . Hence , a subsequent question is how one can characterize the functional connectivity associated with the various phase-locking modes and how directed signal transmission can ensue . Here we approach the questions above by studying analytically the dynamical emergence of phase-locking within two bidirectionally delayed-coupled gamma-oscillatory spiking networks . Importantly , the neurons within the circuits have a relatively wide distribution of intrinsic excitability , meaning that most of them are not intrinsically oscillating . Hence the gamma rhythm in our network is an emergent property of the global dynamics , as opposed to phase synchrony of coupled oscillators ( see [29] for instance ) . Furthermore , the design of the interconnections between our networks is inspired from previous research [13 , 21 , 22] to essentially capture multiple communicating brain regions where transfer of information takes place . Each network is assumed to be made up of pyramidal cells and interneurons , and each cell is characterized by a conductance-based neural model [30 , 31] . A synaptic delay is included to account for possible long range distances separating the circuits [14] . We then take advantage of a thermodynamic approach combined with a reduction theory to simplify each network description—see [32–34]—and to express the macroscopic phase resetting curve ( mPRC ) of their oscillatory cycle [15 , 35 , 36] . The network mPRC is an important causal measure which allows us to use the weakly coupled oscillator theory [37 , 38] to characterize the inter-network dynamics . The fundamental assumption at the core of this theoretical setting is that synaptic projections from one circuit to another must be sufficiently weak . Please note that the weak coupling condition is not on the synaptic connections within each of the circuits , but only across them . The weak coupling condition allows one to take advantage of a variety of mathematical techniques and to abbreviate the bidirectionally delayed-coupled spiking circuits description to a single phase equation [39 , 40] . Note that the study of delayed coupled oscillators has already received some attention in computational neuroscience [41–44] . This simplification significantly reduces the complexity of the interacting macroscopic oscillations , making them mathematically tractable , while at the same time capturing crucial principles of phase-locking . As we show below , an analysis of the phase equation sheds light on the synaptic mechanism enabling circuits with emergent global oscillations to bind together . We give particular attention to the central role played by the synaptic conduction delays in producing symmetry-broken states of activity ( with purely symmetric connectivity ) , i . e to permit the emergence of a variety of non-symmetric phase lags . In other word , we look for conditions under which the role played by the two networks is not symmetric anymore: one network leads the dynamics and the other one follows . Such a collection of phase lags has been suggested to facilitate the control and selection of the information flow through anatomical pathways [17] , and conduction delays have been at the core of recent discussions regarding the CTC hypothesis [45] . Our final goal is then to show that non-symmetric phase lags lead to a directed functional coupling between the networks . We indeed show that symmetry-broken states induce a preferred direction of signal transfer between the networks , and therefore provide theoretical support for the role of oscillations in modulating functional connectivity between cortical circuits [12 , 13] . The paper is structured as follows . First , we present the network and neural model which will be used throughout . We explain the low dimensional system for which we can perform a bifurcation analysis and extract the infinitesimal PRC . From there , we compute the so-called interaction function and reduce the bidirectionally delayed-coupled spiking networks to a unique phase equation . The analysis of the phase equation enables us to make several predictions on the locking states between the emerging oscillations . We support our theoretical findings with extensive numerical illustrations and discuss our results in light of the CTC hypothesis and functional connectivity . Finally , the mathematical techniques are explained in a detailed Methods section at the end of the paper .
Our generic cortical circuit is assumed to be made up of Ne excitatory cells ( E-cells ) and Ni inhibitory cells ( I-cells ) coupled in an all-to-all fashion . Each cell is described by a well-established model—the quadratic integrate-and-fire ( QIF ) , see [46]—which is known to capture the essential dynamical features of the neural voltage [30] . The action potential is taken into account by a discontinuous reset mechanism ( note that for the QIF this reset is not at the firing threshold as for the regular integrate and fire model , but either at the top of during the active phase of the action potential ) . Whenever a cut off value vth is reached , the voltage is instantaneously set to vr , a reset parameter . To permit analytical computations , we use the canonical form of the QIF that corresponds to the normal form for the saddle-node on an invariant cycle bifurcation , where the threshold vth and reset vr are respectively taken at plus and minus infinity [30] . The QIF reads τ d d t v j = η j + v j 2 + I , ( 1 ) where v ( t ) is the neural voltage , j the neuron number , τ the membrane time constant , η the bias current that defines the intrinsic resting potential and firing threshold of the cell and finally I ( t ) the total synaptic current injected at the soma . To account for the network heterogeneity , the intrinsic parameter η is distributed randomly according to a Lorentzian distribution ( Note that we choose this distribution form in order to facilitate our analysis ) : L ( η ) = 1 π Δ ( η - η ¯ ) 2 + Δ 2 . Here η ¯ stands for the mean value ( in the Cauchy sense ) taken by the parameter η across the population and Δ is the half-width of the distribution . Note that the heavy-tailed Lorentzian distribution implies a wide range of intrinsic excitability , i . e . many neurons are not intrinsically oscillating and if they do , they have different firing frequency , as opposed to the classical framework of phasing of coupled oscillators ( see [29] for instance ) . Indeed , when the external current Iext is taken to be zero , the proportion of neurons not being intrinsic oscillator is given by ∫ - ∞ 0 L ( η ) d η = 1 π ( π 2 - arctan ( η ¯ Δ ) ) , which can not be zero as soon as there is heterogeneity within the network . Note nonetheless that the proportion will be affected by the synaptic current . The total synaptic current , I ( t ) is assumed to be the sum of an external input Iext ( t ) that takes into account inputs coming to the cell from sub-cortical structures or nearby cortical networks through lateral connections , and the synaptic inputs se and si which models the effect of recurrent connexions within the circuit , for the E-cells we have: I e = I e e x t + τ e s e e - τ e s e i , and for the I-cells: I i = I i e x t + τ i s i e - τ i s i i . The synaptic current , s ( t ) , depends on the synapse type , for the excitatory synapse , for the E-cells , we have τ s d d t s e e = - s e e + J e e r e , respectively for the inhibitory synapse , τ s d d t s e i = - s e i + J e i r i , and of course for the I-cells τ s d d t s i e = - s i e + J i e r e , respectively for the inhibitory synapse , τ s d d t s i i = - s i i + J i i r i . Here , τs the synaptic time constant , J the synaptic strength—see Fig 1—and r ( t ) the population firing rate . For the E-cells , we have: r e ( t ) = 1 N e ∑ k = 1 N e ∑ f δ ( t - t f k ) , and for the I-cells , we have: r i ( t ) = 1 N i ∑ k = 1 N i ∑ f δ ( t - t f k ) , where δ is the Dirac mass measure and t f k are the firing time of the neuron numbered k . To get a clear picture of how the synaptic structure shapes the firing patterns , we take advantage of a thermodynamic approach combined with a reduction method . The thermodynamic framework produces an average system written in terms of partial differential equations that is valid in the limit of an infinitely large number of neurons [47] . The reduction method allows further simplification and breaks down the mean-field system into a small set of differential equations [33 , 34] . In our case , the low dimensional dynamical system reads ( see Methods for more details of the derivation ) : { τ e d d t r e = Δ e π τ e + 2 r e V e τ e d d t V e = V e 2 + η ¯ e + I e - τ e 2 π 2 r e 2 , τ s d d t s e e = - s e e + J e e r e , τ s d d t s e i = - s e i + J e i r i , ( 2 ) and for the I-cells: { τ i d d t r i = Δ i π τ i + 2 r i V i τ i d d t V i = V i 2 + η ¯ i + I i - τ i 2 π 2 r i 2 . τ s d d t s i e = - s i e + J i e r e , τ s d d t s i i = - s i i + J i i r i , ( 3 ) Here , V ( t ) represents the mean voltage ( in the Cauchy sense ) of the population , while r ( t ) still stands for the firing activity . Note that the two systems are coupled via the expression of the total current arriving on each sub-population: I e = I e e x t + τ e s e e - τ e s e i , and I i = I i e x t + τ i s i e - τ i s i i . The numerical simulations presented in Fig 1 compare the dynamics of the full network with the low dimensional system ( 2 ) and ( 3 ) in response to a continuous external stimulus . The time evolution of the external stimulus is seen in the first panel ( Fig 1A ) , whereas the second panel gives the spiking activity obtained from a simulation of the full network ( Fig 1B ) . In the subsequent panels ( Fig 1C and 1D ) , the firing rate given by the reduced description is compared with the firing rate obtained from network simulations . We can see that both models are able to follow the stimulus amplitude in time ( the time-interval averaged firing rate of spikes for the full system and the rate variable for the reduced version ) . The perfect agreement between the population activities convinced us that the reduced dynamical system captures the fundamental aspects of the population firing rate . In addition , such a reduced description provides an efficient way to carry out a study of the circuit since it can be simulated very quickly and it is amenable to mathematical analysis . To understand how the emergent network gamma oscillations can phase lock , it is essential to first consider their basic underlying mechanisms . To gain insights , we carried out a nonlinear analysis of the reduced system . This enabled us to reveal how the inhibitory feedback loop renders possible the emergence of macroscopic gamma rhythms . Two processes can be described: the PING and the ING [6] . In the PING ( Pyramidal Interneuron Network Gamma ) interaction , see Fig 2 , the underlying synaptic machinery involves an interplay between the pyramidal cells and the inhibitory-spiking cells . For a chosen set of connectivity parameters , the dynamical system exhibits a Hopf bifurcation ( Fig 2A ) , such that , enhancing the external stimulus upon the pyramidal cells induces a graded progression toward a coherent oscillatory regime . Note that this rhythmic regime disappears as the network heterogeneity is expanded ( see Fig 2B and 2C ) . The rhythmic transition is illustrated with a simulation displayed in Fig 2D . A self-sustained oscillatory regime emerges as soon as the E-drive is strong enough . Of course , the presence of a Hopf bifurcation in the system should be put in relation with the seminal work of Wilson and Cowan [48] , where a similar path to oscillations was found . Note that , in contrast to the Wilson-Cowan equation , the spiking network presented in here does not require excitatory-to-excitatory connection to oscillate . In the ING ( Interneuron Network Gamma ) interaction , see Fig 3 , the mechanism requires an inhibitory feedback from inhibitory-spiking cells onto themselves and the rhythm arises from this interconnected inhibitory network which in turn defines the excitatory spike times . The nonlinear analysis reveals a Hopf bifurcation as the external drive is raised ( see Fig 3A ) . Again , this rhythmic regime disappears with too much heterogeneity ( see Fig 3B and 3C ) . The network activity undergoes a transition from an asynchronous regime toward an oscillatory which is displayed in Fig 3D . Interestingly , the ING behavior can not emerge within the traditional rate equation proposed by Wilson and Cowan [48] , see [49] for a more complete discussion . Although the shape of the synaptic filters does not alter the dynamics of the network , it is a necessary ingredient for the model to generate ING oscillations [49] . Note finally the frequency difference between the PING and the ING rhythm . The two interaction models are then seen as canonical descriptions of the low and fast gamma oscillations , PING for low gamma range and ING for fast gamma spectrum . In both cases , pyramidal cells do not fire in every oscillatory cyle . Over the past decades , the Phase Resetting Curve ( PRC ) has become one of the fundamental concepts in theoretical neuroscience . Its usefulness has been reviewed in multiple papers [37–39 , 50] and its outcomes are expected to impact our understanding of brain rhythms [27] . PRC measures the effects caused by transient stimuli on oscillatory systems and can be obtained experimentally [51–54] . In our case , the application of a short depolarizing current to the network affects the spiking activity , and the macroscopic oscillation shifts in time , see S1 , S2 , S3 and S4 Figs . The induced phase shift depends on the perturbation strength but also on the phase at which the perturbation is presented . It can either be delayed or advanced depending on the onset phase of the perturbation . Note that the input can be delivered either to the pyramidal or to the inhibitory neurons in the network . The PRC results in plotting the advance or delay with respect to the phase onset at which the perturbation is made . Doing so , it quantifies the effect of the perturbation on the macroscopic oscillation . For the cortical network under consideration , several PRCs can reasonably be defined at the same time depending on where the depolarizing input is applied ( to the pydamids or the interneurons ) . In the limit of short , weak perturbations , the shift in timing can be described by the so-called infinitesimally PRC ( iPRC ) . The iPRC is mathematically expressed by a linear differential system , known as the the adjoint system [55] . This method can be applied to the low dimensional system ( 2 ) and ( 3 ) and a semi-analytical expression of the macroscopic iPRC be obtained . Assuming that the reduced E-I system ( 2 ) and ( 3 ) has a stable limit cycle , we find that ( see Methods for more detail ) the iPRC Z ( t ) is a periodic vector that is a solution of the adjoint equation - d d t Z ( t ) = M ( t ) T · Z ( t ) , ( 4 ) where the matrix M ( t ) is given by a linearization of the E-I system ( 2 ) and ( 3 ) around the limit cycle , see Methods for its precise expression . When the perturbations made to the network are sufficiently small , the PRC becomes proportional to the iPRC [36 , 56 , 57] . We present in Figs 2E and 3E the iPRC obtained via a simulation of the adjoint system ( 4 ) as compared with direct perturbations made on the spiking network . The blue line , ( respectively the red line ) , corresponds to the iPRC of the excitatory input to the I-cells ( respectively the E-cells ) . Note that the noisy aspect of the PRC obtained from the direct method is the consequence of a finite-size effect . The network simulation being made with a finite number of neurons , the firing rate remains somewhat noisy ( see Fig 1C and 1D ) and the measure of the phase shift is not perfectly accurate . Computing the PRC via the direct method on the reduced system leads to a smoother curve , see S5 Fig . From the simulations and semi-analytical expression of the PRC we can classify the PING and ING rhythms as having different macroscopic PRC types , i . e . as having different rhythmic properties . For the PING dynamics , see Fig 2E , a biphasic shape of the PRC is observable when perturbations are made on the I-cells . In contrast , when perturbations are on the E-cells , the PRC is monophasic . This is a classification that has already been observed in our previous work where the synaptic dynamics were neglected and considered to be instantaneous [15] . Intuitively this result can be understood as follows: Giving an excitatory pulse to the E-cells , the rhythm can only go faster . On the other hand , a pulse to the I-cells might lead to different effect . If the perturbation is just past the time when the E-cells spike , the rhythm must accelerate , because it helps the I-cells to fire sooner , letting the inhibition wear off sooner and the pyramids can fire sooner on the following cycle . If the perturbation arrives in the middle of the ongoing cycle , it triggers extra I-cell activity which will slow down the rhythm . Regarding the ING pattern , see Fig 3E , the PRC is monophasic for perturbation targeting the I-cells . The PRC is null when perturbations are made onto the pyramidal cells , which means that any perturbations will die out after a few cycles . This comes without a surprise since in the ING interaction , pyramidal cells do not play a part in the emergence of the oscillations . PRCs are thus quite different between the ING and the PING oscillations . The difference in shape and type is very robust , and changing the parameters does not affect this observation , see Figs 2F and 3F . This is because the contribution of the cell type to the rhythmic behavior is largely different in the ING and PING mechanisms . The PRC difference between the ING and the PING oscillations has also been noted in a very recent work by Akao and colleagues [35] . From there , we can explore the consequences of differences of locking regimes to periodic pulsatile stimuli , and their result supports that the origin of the cell-type-specific response , already experimentally observed [10] , comes from the different entrainment properties [35] . Indeed , biphasic PRCs are known to facilitate entrainment to periodic inputs . This provides some theoretical supports for the implication of inhibitory spiking cells on the locking ability of neural networks . The amplitudes of the macroscopic PRCs we can also inform us about how sensitive is the network to perturbations onto the excitatory cells versus onto the inhibitory cells . As we see in Figs 2F and 3F , the overall PRC amplitude scaling strongly depends on parameters such as the external current and which cells are targeted by the perturbation . Since a PRC with small amplitude implies that a perturbation will have almost no effect on the oscillatory cycle , the low PRC amplitude can intuitively be interpreted as a stability marker of the oscillations . For instance , the PING oscillation is more sensitive to perturbation to the excitatory cells . We now turn to study the dynamical emergence of phase synchrony across multiple networks ( as a minimal paradigmatic model reflecting internactions between multiple brain regions ) . In other words , with the model being minimal , we cannot pretend to aim to study in detail specific brain interactions , however , the structure that is shown in Fig 4 reflects the architecture of many communicating cortical and sub-cortical areas where information transmission is at play [21 , 22] . In our set up we consider two coupled spiking circuits . Each circuit is assumed to be made up of interacting pyramidal cells and interneurons as presented in the previous sections ( see Fig 1 ) . Since the interneurons are known to make overwhelmingly local connections , the synaptic projection from one circuit to another is made via the pyramidal cells only . A delay , that we treat as a free parameter , is added to account for finite transmission speeds and synaptic time-courses across circuits . Importantly we note that the considered structural motif is symmetric: both circuits are identical and are symmetrically coupled . While in principle , we could have studied phase locking of circuits showing oscillations at different frequencies , in vivo experimental data suggest that locking across gamma oscillations is most prevalent within the same frequency range [4] . We will thus consider coupled networks with the same frequency and focus our study on two interacting schemes: the PING-PING interaction and the ING-ING interaction . The two mechanistic models of gamma generation having different oscillatory regimes , the interaction PING-ING would lead to a cross-frequency coupling . First , it is far beyond the scope of this paper to investigate the coherence between slow and fast oscillations . Second , we note that , under our knowledge , cross-coupling among slow and fast gamma has not been observed so far . As one more important point , we note that our whole analysis of phase locked states is based on the assumption that synaptic interactions across the circuits are sufficiently weak . Such an assumption , which guarantees that the perturbed macroscopic oscillations remain close to the unperturbed case , allows us to place our study within the framework of weakly coupled oscillators [39 , 40] . We emphasize that within each circuit , neurons are not weakly coupled . The assumption of weak coupling is only made upon the projection from one circuits to another . Within the weakly coupled framework , see Methods , the bidirectionally delayed-coupled neural circuits reduce to a single phase equation: d d t θ ( t ) = G ( θ ( t ) ) , where θ ( t ) is the phase difference ( or phase lag ) between the circuits and the G-function is the odd part of the shifted interaction function , the so-called H-function: G ( θ ) = H ( θ - d ) - H ( - θ - d ) , with d , the time delay between the two circuits , and the H-function: H ( θ ) = G e e T ∫ 0 T Z s e e ( s ) r e ( s - θ ) d s + G i e T ∫ 0 T Z s i e ( s ) r e ( s - θ ) d s , where T is the oscillation period and Gαβ denotes the connectivity strength from the population β of one circuit onto the population α of the other circuit , see Fig 4 . Note the involvement of the synaptic component of the PRC Zs ( t ) and the firing rate of the E-cells re ( t ) all along the oscillatory cycle . Let us emphasize that the theory used to obtain the functions H and G is the same than the standard theory used for individual neurons , as it is generic to weakly coupled oscillators . The only difference lies in the coupling , which in our case , is defined via the population firing activity of the excitatory cells . Therefore , the interaction function H can be intuitively interpreted as an average effect of the pre-synaptic excitatory firing rate on the phase the second network . The average being computed over one oscillation cycle . The G-function is essential for our study since it conveys knowledge about the possible phase-locking modes between the coupled circuits as well as their stability . Indeed , the zeros of the G-function correspond to the steady state phase lags . The stability of a locking mode is conditioned on a negative slope at the zero crossing ( s ) of this function ( G′ ( θ ) < 0 ) , while a positive slope ( G′ ( θ ) > 0 ) implies instability , Note that the necessity of a synaptic delay for symmetry breaking and the possibility of switching between symmetry broken leader/follower states have previously been shown in coupled oscillator models [41–44 , 58]; however , these results have not previously been shown for spiking neural networks with synaptic delays . To disentangle the synaptic mechanisms responsible for the dynamical emergence of cross-network phase-locking , we first fix the delay d to zero and focus our study on the effect of the coupling strengths . To put it in mathematical terms , we investigate the location of the zeros of the G-function with respect to the coupling strengths when the parameter d is set to zero . As we see from Fig 5 , which show results interacting PING circuits , modifying in the network coupling strength parameters changes the shape of the G-function quantitatively , while preserving the phase and the stability of the locked states . The zeros of the G-function are located at the in-phase ( synchrony ) and anti-phase locking ( anti-synchrony ) mode . The anti-phase state is unstable . We therefore expect the in-phase synchrony mode to emerge from the dynamics of the bidirectionally coupled circuits . This is the case for a cross-coupling targeting exclusively the E-cells ( Gie = 0 , Fig 5A ) or the I-cells only ( Gee = 0 , Fig 5B ) . Since in the general case , the interaction function will result in a linear superposition of the two previously mentioned possibilities , in the non-delayed coupling scenario , only a perfect zero lag synchrony can be expected , see Fig 5C . We illustrate this prediction by showing the network rasters in Fig 5D . The black dots correspond to the first network , whereas the colored dots to the second circuit . The spiking activity of the two circuits oscillate in phase , i . e . the two raster plots are synchronized at zero lag and thus overlap . Simulation and theoretical prediction are in perfect agreement . As we can see , despite its vast simplifications , the phase equation yields quantitativley accurate predictions . The fact that two oscillatory networks ( two oscillators ) synchronize at zero lag when delay is neglected was to be expected . However , in real settings , neuronal signals travel at finite speeds across the brain and a wide range of delays between neuronal populations has been reported [14] . How the presence of transmission delay reshapes the phase relationship between macroscopic oscillations has remained elusive so far . This is a central issue since recent studies have proposed an updated formulation of the CTC hypothesis where delay between communicating sites plays a critical role [45] . To put it into a mathematical perspective , we expect that distinct delays lead to different fixed-points in the G-function , and to illustrate this expectation , we plot the G-function obtained for two different example delays ( Fig 5E and 5F ) . As we can see , the stability of the locking modes are reversed , and the anti-phase mode , which was unstable , becomes stable . In contrast , the in-phase mode turns into an unstable state . Two phase-locking modes are then possible: the in phase mode for a short delay and the anti-phase mode for a large delay ( Fig 5E and 5F ) . We illustrate this analytical prediction by showing the network rasters in Fig 5H . As we can see , for large delay value , the spiking activity of the two circuits oscillate in an out of phase mode . Note that for very large values of the delay , the two networks will re-synchronize , see S6 Fig . We push our analysis further by investigating the transitions between the two in-phase and anti-phase locking modes we observed above . In Fig 6A we plot the G-function obtained for a range of delays . Black lines correspond to small delays while grey lines to bigger ones . A continuous deformation of the coupling function is seen , leading the zeros of the G-function to slip over the phase-axis . To get a better visualization , we plot a bifurcation diagram ( Fig 6B ) which shows us the phase modes positions and stability with respect to parameter change . In the figure , each dot is obtained from the phase at which the G-function intersects the x-axis . It thus displays the phase locations of the zeros of the G-function with respect to the delay . The color black or white indicates the stability of the fixed-point determined from the G-function slope at the zeros Such a diagram helps us to anticipate the locking ( or coherent ) states in the bidirectionally delayed-coupled networks . We note that the stability of the in-phase mode is kept for small delays . On the other hand , for larger transmission times , a switch of stability between the in-phase and anti-phase locking modes is observed . Importantly , a wide region of delays for which the phase lag goes over all the possibilities appears in the diagram . This result confirms the role of delay in the emergence of a complete variety of phase shifts across gamma interaction in the cortex [17 , 59] . In Fig 6D we validate this theoretical prediction by showing rasters of the spiking circuits that reflects the modulation of the emerging phase lag by the delay . As we see from Fig 6D , the spiking activity of the two networks oscillate with a small phase lag . Increasing slightly the delay leads the spiking activity of the two networks to oscillate with a bigger phase lag . Simulation and theoretical prediction are again in perfect agreement . This result shows that it is normal to observe persistent phase relationship across time that are so diverse across brain regions . In general , it is not possible to draw connection between the phase locking diagram ( Fig 6B ) to the oscillation period . This is only possible when an interaction function is a sine function [40] . As already noticed in [60] , this case corresponds to a spontaneous symmetry breaking . We talk about symmetry breaking because those variety of phase lag states do not share the symmetric feature with the full system . Note that when the delay is kept fixed , and sufficiently large , a variation of the synaptic strength onto the E-cells in Fig 6F leads to a transition from the in-phase state to the out-of-phase locking . As a part of this transition , a variety of stable phase lags appear . A reverse situation is depicted in Fig 6G: when the coupling onto the I-cells is varied the in-phase mode transitions to an anti-phase mode . As we can see from these diagrams , we can tune the phase shifts across brain oscillations at least for the PING rhythm . Of course these result are valid only for weak coupling . When the coupling across the circuits is taken to be too large , the theory will fail in capturing the transition . We also note that the transition between the in phase and the anti-phase modes is still takes place for larger connectivity regime , however it does not happen for values of the delay predicted by the theory , see S7 Fig . A similar situation emerges for the ING interaction . In Fig 7 , we show the interaction function and corresponding locking modes . While short delays induces only an in-phase locking mode Fig 7C–7F , larger delays will reverse the interaction function and induce an out of phase locking scheme Fig 7E and 7F . Once again , notice the spontaneous symmetry breaking implying the existence of a variety of phase lags for moderate values of the delay Fig 7G , 7H and 7I . Not that for the ING-ING interaction , modification of the synaptic coupling Gαβ will not affect the locking modes since the coupling is through the pyramidal neurons and these do not affect the macroscopic oscillatory phase . In the above simulations we saw that the two-circuit system can break into a non-symetric dynamic where one network spikes earlier and is followed shortly after within the global firing period . Hence we can call the earlier network the “leader” and the later , the “follower” . We note of course that which networks is the leader and which is the follower , is entirely determined by the network initial condition . In addition , a sufficiently strong transient perturbation to one of the networks , can switch their role , and make the leader a follower and vice versa . This effect can be explained mathematically from the PRC and it has been at the core of recent research on control of the directionality of signal flow [12] . However , making a theory in the case of weakly coupled circuits , we face the difficulty of convergence toward the stable mode . The two networks need to oscillate several cycles in order to reach the fixed point . To speed up the convergence , one would need to increase the coupling which breaks our assumption , see S8 Fig . We now turn to the functional role that could be supported by the dynamic symmetry breaking . Recent studies have associated spontaneous symmetry breaking with an effective transfer of information that is directed [12 , 13] . In other words , these works suggested that while the synaptic coupling between networks is fully symmetric , measuring information transfer shows that signals flow prevalently from one network to the other , while it is relatively attenuated in the opposite direction . The conclusion is that despite a symmetric structural connectivity , there is a directed functional connectivity resulting from the on-going network dynamics . However , since most if not all information transfer measures are correlational , functional connectivity has so far been characterized in a statistical manner with a limited implication for causality . We reasoned that our PRC methodology can give us a glimpse at a causal interpretation . To prove that there is indeed a causal directionality of signaling under symmetry-broken dynamics , we compute the PRC of the full delay system . For that purpose we define a global phase for the whole bi-directionally delayed spiking networks . This is possible because , in a phase-locked state , the spiking activity of the two networks is still periodic . Our intention is to measure how an impact of the input on one of the two networks affects the other circuit and the system as a whole . The logic goes as following; we stimulate one or the other network and measure the global phase shift that results on the two networks . Doing so , we compute what we call a global PRC . The global PRC quantifies how the effect of an external perturbation on one network is transferred to the other . In Fig 8 we illustrate this set up . When a short depolarizing current is applied to one network ( Fig 8B ) , the spiking activity and resulting macroscopic oscillation of the two networks will shift in time . A cartoon representing a raster plot illustrates the global phase shift on the spiking activity of the first and second network ( Fig 8A–8C ) . Here the black dots represent the first network , and the colored dots , the second circuit . After the stimulus presentation , spikes are shifted . The global PRC results in plotting this phase shift as a function of the perturbation phase onset . Note that Fig 8 is a cartoon and not a simulation . With the presence of delay across circuits , the phase shift on the second network does not appear as rapidly . We need to wait a few cycles before the effect of a perturbation on one network can be perceived on the other , as the two-circuit system settles to a perturbed firing cycle . As we pointed out before , in the symmetry broken state , we can heuristically define a leader circuit ( one that fires earlier in the global cycle ) and a follower circuit ( one that fires later ) . Indeed , the phase difference between the two networks is significantly less than their global period of oscillation . Hence the system fires in a galloping rhythm with one network firing after the other and then a longer delay is apparent before the next volley . We can define that the network firing after the longer period of silence as the leader and the network firing after the subsequent short delay as the follower . We then track how the incoming perturbations ( see Fig 8B ) to either the leader or the follower shift the spiking activity of both networks ( see Fig 8A–8C ) . We can then see how the global PRC differs when it is obtained from perturbation on the leader or on the follower . We use this difference as a footprint of causal directionality . While in this manuscript we have sought a fully analytical approach , we find that computing the global PRC is problematic due to the presence of delay . The analytical method’s convergence is not guaranteed . We therefore follow a semi-analytical approach . We use the direct perturbation method to compute the global PRC for the reduced model , which makes the computations efficient ( see Method Eqs ( 9 ) – ( 12 ) ) . We thus perturb the leader or the follower and observe the resulting asymptotical phase shift of the second network . Of course in the symmetrical dynamical state we expect that the global PRCs of the leader and the follower are identical . We thus posit that should we find that the global PRCs are identical for perturbations to either the leader or the follower , transmission of the incoming perturbation is symmetric . Should the two PRCs differ , we would claim that signal transfer has a directionality . Fig 9 illustrates the global PRCs . As expected , when the two networks are in phase , perturbing one or the other has similar outcomes . When the two networks are out of phase , the resulting global PRCs are only shifted with respect to one another . This is a natural consequence of the symmetry in the oscillatory modes of the macroscopic oscillations . The most interesting scenario is when the resulting phase-locking mode is not symmetric . In this situation , perturbing the leader or the follower does not give the same phase shift . As we can see , the leader-evoked and the follower-evoked PRCs are almost reverse , i . e . while a perturbation of the leader induces a phase advance , a perturbation on the follower implies a phase delay . Therefore , our intuition laid out above appears to be supported mathematically by our model . In addition to the intuition above , the amplitudes of the PRCs have also different order of magnitude . Perturbations of the leader have stronger impact than on the follower . Furthermore , we see that for each of the perturbations , phase shifts depend on the phase at which the external “signal” arrives: e . g . there are timings of the input where an excitatory perturbation on either networks advances the oscillations , and timings where perturbing the leader advances the phase , while exciting the follower delays the oscillation . In summary , we can interpret our results giving a causal directionality in the communication between the two circuits: shifting the phase of the leader has an effect on the follower that is qualitatively different than effect of a follower-phase-shift on the leader . As a note , it has been previously shown that the post-stimulus spike-time histogram ( PSTH ) can be directly related to the PRC [61 , 62] . Hence , the asymmetric PRCs for the leader and the follower predict that the PSTHs tied to perturbing the leader or the follower differ signficantly , once again giving a direct and causal measure of how broken-symmetry states can induce a directional functional connectivity despite complete structural symmetry . In Fig 10 we illustrate a summary of the observation . In the panel Fig 10A , we show the raster plot activity where we can clearly distinguish the leader and the follower , in panels Fig 10B and 10C the corresponding global PRCs , and finally the resulting connectivity of the network in the very last panel . The thick red arrow symbolizes the preference direction of signal flow . This has been recently showed using correlative statistical measures such as transfer entropy [12 , 13] .
The omnipresence of oscillations in the brain gives significant support to the hypothesis that rhythmic firing patterns are well suited to specific cognitive functions [1 , 2] . In particular , recent physiological experiments proposed that coherent gamma rhythms play a determinant part in the transfer of information across cortical areas [7 , 9 , 45] . As this communication depends on stable phase-relationships between the oscillatory cortical networks , a key question has been to determine the conditions under which two oscillatory brain circuits phase lock , what is the resulting phase lag between them and how the phase lag relates with delay and synaptic couplings [28] . Here , we have outlined and developed a new analytical approach to deal with the dynamical rise of phase synchrony between multiple spiking neural circuits . Making use of a mixture of mathematical techniques—mean-field theory , reduction methods , PRC measures and the framework of weakly coupled oscillators—we have been able to reduce the complexity of the problem to a single phase equation . However , this sequence of mathematical arguments can only be applied to the quadratic integrate-and-fire model when threshold and reset are set at infinity , and assuming a Lorentzian distribution of the bias current [32–34] . Although it does not alter the conclusion , it represents a limitation of our work . Indeed , while similar phase synchronies were observed with conductance-based models such as the Wang-Buzsáki-type conductance-based neurons [12] , the line of reasoning to provide a theoretical explanation cannot be reproduced for this type of models . Let us mention that recently , the macroscopic PRC of an oscillatory network was computed by Akao and colleagues [35] . The main difference with our work is the treatment of noise . In their case , the noise is treated by the use of standard Wiener process mimicking fluctuations of the membrane voltage . In our case , the noise has to be taken into account via a quenched variability expressed only in the form of a Lorentzian probability distribution . However , the continuous nature of the quadratic integrate-and-fire model is required in both approaches to provide an adjoint method [35] . The dynamical phase equation that we obtain using our method fully restitutes the contribution of cortical structure to the coordination of macroscopic firing patterns . More precisely , a nonlinear analysis of the phase equation reveals the role played by the delay and the synaptic coupling across circuits in shaping the locking mode of macroscopic oscillations . We have shown that this level of abstraction suffices to qualitatively reproduce and explain experimentally observed oscillatory patterns . For instance , our synaptic theory allows us to clarify the observed diversity of phase lags between multiple cortical gamma rhythms that have been proposed to play a crucial role in controlling and selecting information through anatomical pathways [17] . Furthermore , our technique allows us to determine the directionality of causal signal transfer between multiple interacting neural circuits with emergent gamma oscillations . Using the PRC technique , we first confirmed that the signal transfer is undirected in dynamical states with full symmetry: the global PRCs were identical or just phase shifted for in-phase and anti-phase synchrony . For dynamical symmetry-broken states , where the circuits separate into a leader and a follower ( also sometime called stuttering states ) , the global PRCs depend qualitatively on where the signal originates ( e . g . in the leader ) and where it propagates ( e . g . to the follower ) . Our results show that depending on this and on the timing of the external signal perturbations , the neural activity can be either advanced or delayed . Once again , this causal functional directionality in the communication between neural circuits appears as a consequence of the system dynamics and despite a completely mirror symmetric structural connectivity and the individual network properties . We believe that these results give a causal basis for the recent statistical directed functional connectivity measures . We posit that should we find that the global PRCs are identical for perturbations to either the leader or the follower , transmission of the incoming perturbation is symmetric . Should the two PRCs differ , we would claim that signal transfer has a directionality . For example , should the leader-evoked global PRC be primarily type I and follower-evoked global PRC be type II , one could claim that an excitation to the leader would give an immediate spiking response in the network while exciting the follower would produce a decrease of spiking immediately following the stimulus and hence de facto inhibition ( also see [61 , 62] for a link between the PRC and the PSTH that supports this intuition ) . In other words , spikes impinging on the leader would be likely to be transferred by spikes in the network , while spikes impinging on the follower would not . In the end , the series of mathematical arguments leads to a simple visualization technique—a bifurcation diagram—which compiles all the relevant information about circuit phase relationships when parameters are changed . Such graphical representation demonstrate that , in multiple delayed-coupled spiking networks , phase-locking of the emergent macroscopic oscillatory rhythms are natural features that can be controlled . Our synaptic theory sheds new light on the long range cortical circuit interactions , and importantly , it offers a way to make strong predictions that can be tested against experimental data . For instance , one can compare the phase-locking modes generated by different brain areas with distinct synaptic organization of the model . The formalism employed within the paper requires pyramidal neurons to work in a regime where projections across circuits are weak . Within this parameter regime , the presented sequence of theoretical arguments are fully valid . How our results extend to the strongly coupled regime remains a challenging topic for future studies . Although we have restricted our study to considering networks with homogenous synaptic weights and current-based synaptic interaction , the mathematical strategy that served throughout this paper is adjustable and easily accepts the inclusion of conductance-based synaptic description with a certain level of synaptic heterogeneity [34 , 63] . Similarly the accommodation of delay within the circuits themselves would not bring difficulty , neither for the reduction method [64] , nor for the PRC computation [56] . This could be an interesting subject of research for future works as well as the study of locking to an external periodic modulation for which the PRC offers several path of investigation [35 , 65] . All along the paper , we studied locking of oscillations having identical properties , however , several studies have reported coupling across different frequency bands of neural oscillations [59] . Termed as cross-frequency coupling , the locking of brain regions with different frequencies is an open subject of research . A promising extension would then be to generalize our phase-locking analysis to layered network with subsequent layers that include diversified interneuron types along with pyramidal neurons and hence oscillating at different frequencies [66–68] . We project that such analysis would clarify the specific roles of each layer and cell types in the generation of locking and elucidate the underlying synaptic mechanism and functional roles of cross-frequency coupling observed in slow-fast oscillations [59] . Following our PRC framework , we speculate that we would be able to determine the directionality of signalling between such layers . Hence an analytical study of interacting circuits with different intrinsic frequencies remains for us a key open issue to be investigated .
We consider an all-to-all coupled network made up of N spiking cells characterized by the quadratic integrate-and-fire ( QIF ) model: τ d d t v j ( t ) = η j + v j 2 ( t ) + I ( t ) , where v ( t ) represents the time evolution of the membrane potential , τ is the membrane time constant , I ( t ) is the total current , and we assume the intrinsic parameter η being randomly distributed across the network according to a Lorentzian distribution: L ( η ) = 1 π Δ ( η - η ¯ ) 2 + Δ 2 . with η ¯ the mean value and Δ the half-width of the distribution . The onset of an action potential is taken into account by a discontinuous mechanism with a threshold vth and a reset parameter vr respectively set at plus and minus infinity [30] . The population firing rate is then given by the sum of all the spikes: r ( t ) = 1 N ∑ k = 1 N ∑ f δ ( t - t f k ) where δ is the Dirac mass measure and t f k are the firing times of the neuron numbered k . In the mean-field limit , that is , when the number of cells is taken infinitely large , see [47] for instance , the system is well represented by the probability of finding the membrane potential of any randomly chosen cell at potential v at time t knowing the value η of its intrinsic parameter . The dynamic of this density , which we denote p ( t , v|η ) , is given by a continuous transport equation written in the form of a conservation law: τ ∂ ∂ t p ( t , v | η ) + ∂ ∂ v J ( t , v | η ) = 0 , ( 5 ) where the total probability flux is defined as J ( t , v | η ) = ( η + v 2 + I ( t ) ) p ( t , v | η ) . A boundary condition , consistent with the reset mechanism of the QIF model , is imposed: lim v → - ∞ J ( t , v | η ) = lim v → + ∞ J ( t , v | η ) . One can check easily the conservation property of the equation: ∫ - ∞ + ∞ p ( t , v | η ) d v = L ( η ) . Importantly , the firing rate of the population r ( t ) can be extracted from the mean-field equation , defining: r ( t , η ) = lim v → + ∞ J ( t , v | η ) , the firing rate is then given by the total probability flux crossing the threshold: r ( t ) = lim v → + ∞ ∫ - ∞ + ∞ L ( η ) r ( t , η ) d η . The reduction method , see [34] , consists in assuming that the solution of the mean-field Eq ( 5 ) has the form of a Lorentzian distribution: p ( t , v | η ) = 1 π x ( t , η ) ( v - y ( t , η ) ) 2 + x ( t , η ) 2 . ( 6 ) The mean potential and the firing rate are related to the Lorentzian coefficients: r ( t , η ) = 1 π x ( t , η ) , and y ( t , η ) = ∫ - ∞ + ∞ v p ( t , v | η ) d v . Thus the mean membrane potential of the network is V ( t ) = ∫ - ∞ + ∞ L ( η ) y ( t , η ) d η . Note that integrals are defined via the Cauchy principal value , the reason being that the Lorentz distribution only has a mean in the principal value sense . After algebraic manipulation , see [34] , the transport Eq ( 5 ) reduces to the dynamical system: { τ d d t r = Δ e π τ + 2 r V τ d d t V = V 2 + η ¯ + I - τ 2 π 2 r 2 , Such a reduced description has the tremendous advantage to be low dimensional . Considering now a network of two interacting neural populations of excitatory cells and inhibitory cells , the system is then represented by two probability density functions , one for the excitatory population , which we denote pe ( t , v|η ) , and one for the inhibitory neurons , which we denote pi ( t , v|η ) . Each density function follows a continuous transport equation similar to ( 5 ) . In our case , the dynamic of the two coupled PDEs that describe the time evolution of pe ( t , v|η ) and pi ( t , v|η ) reduces to a set of differential equations . For the E-cells , we have: { τ e d d t r e = Δ e π τ e + 2 r e V e τ e d d t V e = V e 2 + η ¯ e + I e - τ e 2 π 2 r e 2 , and for the I-cells: { τ i d d t r i = Δ i π τ i + 2 r i V i τ i d d t V i = V i 2 + η ¯ i + I i ( t ) - τ i 2 π 2 r i 2 . Note that the two systems are in interaction via the expression of the currents Ie and Ii which include self-recurrent connections and synaptic projections , see Fig 1 for a schematic view . For the E-cells , the total current has the following form: I e ( t ) = I e e x t ( t ) + τ e s e e ( t ) - τ e s e i ( t ) , and for the I-cells: I i ( t ) = I i e x t ( t ) + τ i s i e ( t ) - τ i s i i ( t ) , here , sαβ ( t ) represents the time evolution of the synaptic current of the population β projected on the population α and is given by an exponential filter of the firing activity . In the end , we get that the dynamic of the cortical network is well described by the following set of eight differential equations: { τ e d d t r e = Δ e π τ e + 2 r e V e τ e d d t V e = V e 2 + η ¯ e + I e e x t + τ e s e e - τ e s e i - τ e 2 π 2 r e 2 τ s d d t s e e = - s e e + J e e r e τ s d d t s e i = - s e i + J e i r i , ( 7 ) and { τ i d d t r i = Δ i π τ i + 2 r i V i τ i d d t V i = V i 2 + η ¯ i + I i e x t + τ i s i e - τ i s i i - τ i 2 π 2 r i 2 τ s d d t s i e = - s i e + J i e r e τ s d d t s i i = - s i i + J i i r i , ( 8 ) where τs is the synaptic time constant , and Jαβ is the synaptic strength of the population β projecting on the population α . The infinitesimal phase resetting curve ( iPRC ) is defined mathematically for infinitesimally small perturbation , and it is computed in a perfectly rigorous way via the adjoint method [55] . Let us consider a general dynamical system: d d t x ( t ) = F ( x ( t ) ) , where x ∈ R n . Assuming that the system admits a stable limit cycle x0 ( t ) , then if the system is perturbed by a small perturbation , the solution can be written as x ( t ) = x 0 ( t ) + ϵ p ( t ) , where p ( t ) is the small deviation from the limit cycle . Up to a linearization , we get that d d t p ( t ) = D F ( x 0 ( t ) ) · p ( t ) , where DF ( x0 ( t ) ) is the time dependent Jacobian matrix . The iPRC is then defined as d d t ( Z ( t ) · p ( t ) ) = 0 , which is equivalent to d d t ( Z ( t ) · p ( t ) ) = d d t Z ( t ) · p ( t ) + Z ( t ) · d d t p ( t ) = d d t Z ( t ) · p ( t ) + Z ( t ) · D F ( x 0 ( t ) ) · p ( t ) = d d t Z ( t ) · p ( t ) + D F ( x 0 ( t ) ) T · Z ( t ) · p ( t ) = ( d d t Z ( t ) + D F ( x 0 ( t ) ) T · Z ( t ) ) · p ( t ) = 0 . Since the last equation is valid for every perturbation p ( t ) , we get that the iPRC is solution of the adjoint equation: d d t Z ( t ) = - D F ( x 0 ( t ) ) T · Z ( t ) . This method can be applied on the low dimensional system ( 7 ) and ( 8 ) and a semi analytical expression of the iPRC can be extracted . Assuming that O ( t ) = ( r e o ( t ) , V e o ( t ) , s e e ( t ) , s e i ( t ) , r i o ( t ) , V i o ( t ) , s i e ( t ) , s i i ( t ) ) , is a stable limit cycle of the E-I system ( 7 ) and ( 8 ) of period T , that is , O ( t ) = O ( t + T ) we find that the iPRC Z ( t ) is a periodic vector of eight components Z ( t ) = ( Z r e ( t ) , Z v e ( t ) , Z s e e ( t ) , Z s e i ( t ) , Z r i ( t ) , Z v i ( t ) , Z s i e ( t ) , Z s i i ( t ) ) , that is a solution of the adjoint equation - d d t Z ( t ) = M ( t ) T · Z ( t ) , where the matrix M ( t ) is given by a linearization of the E-I system ( 7 ) and ( 8 ) around the limit cycle: M ( t ) = [ 2 V e o ( t ) τ e 2 r e o ( t ) τ e 0 0 0 0 0 0 - 2 τ e π 2 r e o ( t ) 2 V e o ( t ) τ e 1 - 1 0 0 0 0 J e e τ s 0 - 1 τ s 0 0 0 0 0 0 0 0 - 1 τ s J e i τ s 0 0 0 0 0 0 0 2 V i o ( t ) τ i 2 r i o ( t ) τ i 0 0 0 0 0 0 - 2 τ i π 2 r i o ( t ) 2 V i o ( t ) τ i 1 - 1 J i e τ s 0 0 0 0 0 - 1 τ s 0 0 0 0 0 J i i τ s 0 0 - 1 τ s ] . The iPRC Z ( t ) is given by the unique periodic solution that satisfies the normalization condition Z ( t ) · O ˙ ( t ) = 2 π / T . The iPRC can be compared with a direct method which consist in presenting perturbation to the network . Depending on the phase onset of the perturbation , the network activity is going to shift . Raster plots from numerical simulations of the full network ( Fig 11 ) illustrate the shift . Here the black dots correspond to the unperturbed network , whereas the colored dots to the perturbed circuit . Before the stimulus onset , the two rasters overlap perfectly . After the stimulus presentation , spikes of the perturbed network are shifted: either delayed ( Fig 11A ) or advanced ( Fig 11B ) depending on the onset phase of the perturbation . In the Result section , the two approches—direct perturbation and the adjoint method—are compared for the PING interaction in Fig 2 and the ING interaction in Fig 3 . Considering now two bidirectionally delayed coupled networks where the coupling is made via long projections of the pyramidal cells from one network to another , the whole system reduces to a set of sixteen differential equations . For the first network , we have { τ e d d t r e 1 = Δ e π τ e + 2 r e 1 V e 1 τ e d d t V e 1 = V e 1 2 + η ¯ e + + I e e x t + τ e s e e 1 - τ e s e i 1 - τ e 2 π 2 r e 1 2 τ s d d t s e e 1 = - s e e 1 + J e e r e 1 + G e e r e 2 ( t - d ) τ s d d t s e i 1 = - s e i 1 + J e i r i 1 , ( 9 ) and { τ i d d t r i 1 = Δ i π τ i + 2 r i 1 V i 1 τ i d d t V i 1 = V i 1 2 + η ¯ i + I i e x t + τ i s i e 1 - τ i s i i 1 - τ i 2 π 2 r i 1 2 τ s d d t s i e 1 = - s i e 1 + J i e r e 1 + G i e r e 2 ( t - d ) τ s d d t s i i 1 = - s i i 1 + J i i r i 1 , ( 10 ) and for the second network: { τ e d d t r e 2 = Δ e π τ e + 2 r e 2 V e 2 τ e d d t V e 2 = V e 2 2 + η ¯ e + + I e e x t + τ e s e e 2 - τ e s e i 2 - τ i 2 π 2 r e 2 2 τ s d d t s e e 2 = - s e e 2 + J e e r e 2 + G e e r e 1 ( t - d ) τ s d d t s e i 2 = - s e i 2 + J e i r i 2 , ( 11 ) and { τ i d d t r i 2 = Δ i π τ i + 2 r i 2 V i 2 τ i d d t V i 2 = V i 2 2 + η ¯ i + I i e x t + τ i s i e 2 - τ i s i i 2 - τ i 2 π 2 r i 2 2 τ s d d t s i e 2 = - s i e 2 + J i e r e 2 + G i e r e 1 ( t - d ) τ s d d t s i i 2 = - s i i 2 + J i i r i 2 , ( 12 ) Note the presence of long range projections between circuits , see Fig 3 for a schematic view . Here Gαβ denotes the connectivity strength of the population β of one network onto the population α of the other circuit , and the parameter d is the conduction delay between the two networks . Assuming that the two networks are oscillating and placing our study within the framework of weakly coupled oscillators , that is , if we assume that G α β ≪1 , we can reduce the bidirectionally delayed-coupled neural circuits description ( 9 ) , ( 10 ) , ( 11 ) and ( 12 ) to a single phase equation: d d t θ ( t ) = G ( θ ( t ) ) . Here θ ( t ) is the phase difference ( or phase lag ) between the circuits and the G-function is the odd part of the shifted interaction function ( the H-function ) , see [40] for instance: G ( θ ) = H ( θ - d ) - H ( - θ - d ) , with d , the time delay between the two circuits . In our case , the interaction function is mathematically described as H ( θ ) = G e e T ∫ 0 T Z s e e ( s ) r e ( s - θ ) d s + G i e T ∫ 0 T Z s i e ( s ) r e ( s - θ ) d s , where T is the oscillation period . Note the involvement of the synaptic component of the PRC Zs ( t ) and the firing rate of the E-cells re ( t ) all along the oscillatory cycle in the expression of the G-function . | Large scale brain oscillations emerge from synaptic interactions within neuronal circuits . Over the past years , such macroscopic rhythms have been suggested to play a crucial role in routing the flow of information across cortical regions , resulting in a functional connectome . The underlying mechanism is cortical oscillations that bind together following a well-known motif called phase-locking . While there is significant experimental support for multiple phase-locking modes in the brain , it is still unclear what is the underlying mechanism that permits macroscopic rhythms to phase lock . In the present paper we take up with this issue , and to show that , one can study the emergent macroscopic phase-locking within the mathematical framework of weakly coupled oscillators . We find that under synaptic delays , fully symmetrically coupled networks can display symmetry-broken states of activity , where one network starts to lead in phase the second ( also sometimes known as stuttering states ) . When we analyse how incoming transient signals affect the coupled system , we find that in the symmetry-broken state , the effect depends strongly on which network is targeted ( the leader or the follower ) as well as the timing of the input . Hence we show how the dynamics of the emergent phase-locked activity imposes a functional directionality on how signals are processed . We thus offer clarification on the synaptic and circuit properties responsible for the emergence of multiple phase-locking patterns and provide support for its functional implication in information transfer . | [
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... | 2019 | Macroscopic phase resetting-curves determine oscillatory coherence and signal transfer in inter-coupled neural circuits |
When Caenorhabditis elegans encounters an unfavourable stimulus at its anterior , it responds by initiating an avoidance response , namely reversal of locomotion . The amphid neurons , ASHL and ASHR , are polymodal in function , with roles in the avoidance responses to high osmolarity , nose touch , and both volatile and non-volatile repellents . The mechanisms that underlie the ability of the ASH neurons to respond to such a wide range of stimuli are still unclear . We demonstrate that the inositol 1 , 4 , 5-trisphosphate receptor ( IP3R ) , encoded by itr-1 , functions in the reversal responses to nose touch and benzaldehyde , but not in other known ASH-mediated responses . We show that phospholipase Cβ ( EGL-8 ) and phospholipase Cγ ( PLC-3 ) , which catalyse the production of IP3 , both function upstream of ITR-1 in the response to nose touch . We use neuron-specific gene rescue and neuron-specific disruption of protein function to show that the site of ITR-1 function is the ASH neurons . By rescuing plc-3 and egl-8 in a neuron-specific manner , we show that both are acting in ASH . Imaging of nose touch–induced Ca2+ transients in ASH confirms these conclusions . In contrast , the response to benzaldehyde is independent of PLC function . Thus , we have identified distinct roles for the IP3R in two specific responses mediated by ASH .
Like other animals , C . elegans negotiates its environment by responding to a range of noxious stimuli , by changing its direction of movement to avoid the source of the stimulus and thus avoid imminent injury . Mechanical stimulation is one type of stimulation that exerts such an effect . Depending on the position and strength of the mechanical stimulus , the neuronal circuitry responsible for this response differs . The response to nose touch relies primarily on the ASH pair of sensory neurons [1] , which output to the command interneurons , AVA , AVB , AVD , AVE and PVC , which control forwards and backwards movement [2] , [3] . These command neurons interact synaptically with one another and ultimately output to the motor neurons that control the body wall contractions necessary for sinusoidal movement . In contrast , the response to light anterior body touch relies on the ALM and AVM sensory neurons , which act upon these same command neurons . The ASH neurons are particularly interesting in that they are polymodal nociceptive neurons , implicated in avoidance responses to a diverse range of sensory cues , namely , high osmotic strength , nose touch , high ambient oxygen , volatile compounds and non-volatile repellents such as heavy metals , protons and detergents [4]–[8] . ASH is thus analogous to human nociceptors , capable of responding to heat , mechanical stimulation and chemicals such as capsaicin . So understanding the signalling pathways that underlie the polymodal function of ASH is proving important to our understanding of human pain sensation . The molecular mechanisms that enable ASH to sense such a wide range of inputs are still poorly described . Work thus far has identified “general” components that are required for responses to all stimuli , and has also identified “specific” molecules that are required for single , or a small subset of , responses . The transient receptor potential vanilloid ( TRPV ) -related channel proteins OCR-2 and OSM-9 [9] , [10] , for example , appear to be required for all ASH-mediated responses , while GPA-3 , a G-protein α subunit , is required for only a small subset [11] . Thus ASH utilises specific signalling pathways for individual stimuli , but these may converge on a common pathway . In the present study , we identify signalling through the inositol 1 , 4 , 5-trisphosphate receptor ( IP3R ) ( Figure 1A ) as a specific component , required for a small subset of ASH-mediated responses . IP3Rs in Caenorhabditis elegans are encoded by a single gene , itr-1 , and are widely expressed throughout the animal , including in the nervous system [12]–[14] . A wide range of functions for itr-1 have been identified . Genetic approaches have identified roles for itr-1 in ovulation and meiotic maturation ( [13] , [15] , [16] , defecation [13] , [16] , [17] , male mating [18] and in ventral enclosure [19] . We used a dominant-negative construct ( IP3 sponge ) , as well as loss-of-function mutants and RNA interference , to demonstrate that IP3 signalling and IP3Rs function in the regulation of pharyngeal pumping rate and in multiple stages of embryogenesis [20] . For some of these functions , we have some insights into the nature of events upstream of itr-1 and in particular into the member ( s ) of the phospholipase C ( PLC ) family responsible for IP3 production ( Figure 1A ) . For example , PLC-3 ( PLCγ ) appears to act upstream of ITR-1 in the regulation of gonadal sheath contraction ( with the receptor tyrosine kinases LET-23 and VAB-1 presumably acting further upstream , [16] ) , and also during the defecation motor program [17] . We also know that PLC-1 ( PLCε ) acts upstream of ITR-1 to regulate ventral enclosure [21] . Finally , there is evidence that EGL-8 ( PLCβ ) functions upstream of ITR-1 in the control of sperm transfer [18] . In the present study we have used transgenic approaches to disrupt either IP3 signalling or itr-1 function in the nervous system , and demonstrated a role in the avoidance responses to nose touch and benzaldehyde . Our evidence indicates that , for nose touch , two PLCs , PLC-3 and EGL-8 , act as the source of IP3 upstream . We use cell-specific expression of an IP3 sponge and cell-specific rescue to show that itr-1 and both PLCs are acting in the ASH neurons; and demonstrate that all three genes function in the production of nose touch-induced Ca2+ transients in ASH . Thus we have identified signalling components that are specific to two of the group of stimuli sensed by ASH .
The C . elegans strains used in this study are listed in Table S1 . Strains containing the plc-3 ( tm1340 ) allele were maintained as balanced heterozygous strains , and assayed as homozygotes . itr-1 , egl-8 and plc-3 strains carrying the sra-6p::YC2 . 12 construct were made by crossing the appropriate strain with AQ1444 [22] . Strains carrying itr-1 ( sy290gf ) also carry a closely linked allele of unc-24 , unc-24 ( e138 ) , which results in a locomotion ( weak kinker ) phenotype , which may interfere with the avoidance response . When using this allele we therefore rescued the unc-24 deficiency by transgenic expression of a genomic fragment containing the wild type unc-24 gene under the control of its own promoter . As a control , we rescued unc-24 ( e138 ) animals in the same way [18] . To construct sra-6 , glr-1 and unc-119 promoter plasmids , we used 3 . 8 Kb [23] , 5 . 2 Kb [24] and 1 . 3 Kb [25] , respectively , of upstream DNA . IP3 sponge derivatives were constructed as described previously [20] . RNAi inverted repeat constructs were constructed using pHAB200 [12] by inserting forward and reverse copies of the same region of E . coli lacZ or itr-1 cDNA either side of a “linker” made from gfp or a unique part of lacZ , respectively . plc-3 rescue plasmids were constructed using a full length genomic fragment . itr-1 and egl-8 rescue plasmids were constructed using the Gateway system ( Invitrogen ) , using the full-length cDNA ( itr-1 ) or a “minigene ( egl-8 , as in [26] ) . These were introduced , along with the relevant promoter , into the destination vector pHP2 ( see Table S1 ) . Constructs were introduced into C . elegans by injection [27] with a mec-7p::gfp marker plasmid , pPD117 . 01 ( a gift from A . Fire ) . RNA-mediated interference ( RNAi ) of itr-1 was carried out using E . coli HT115 carrying derivatives of the vector pPD129 . 36 [28] , which contains two flanking T7 RNA polymerase promoters . For RNAi of PLC genes we used derivatives of pPD129 . 36 , pHAB301 ( egl-8 ) and pHAB303 ( plc-3 ) [18] . As a control we used a derivative of pPD129 . 36 with an E . coli chloramphenicol acetyltransferase ( CAT ) DNA insert . Plasmids were transformed into E . coli HT115 ( DE3 ) and these strains used to perform RNAi feeding experiments [28] . The response to nose touch was assayed on food at 20°C using an eyelash , as described by Kaplan and Horvitz [1] . The response to anterior body touch was assayed similarly . Reversal responses ( initiated within 3 seconds of the stimulus ) were quantified as distance reversed , expressed in worm lengths . Three categories of response were used , >1 worm length , which corresponds to a “good” reversal response , >0 . 1 worm length and 0 worm lengths , considered “poor” avoidance responses . A minimum of 40 animals were assayed for each genotype or condition shown . The response to repellents was assayed using the “dry drop” test [6] , except for octanol , which was assayed using a “smell-on-a-stick” assay [23] , as described by Chao et al . [29] . Results were analysed using Chi-squared tests . Optical recordings were performed essentially as described [30] , [31] on a Zeiss Axioskop 2 upright compound microscope equipped with a Dual View beam splitter and a Uniblitz Shutter . The following filters and dichroics were used: excitation: 400–440 nm bandpass; excitation dichroic: 455 nm; CFP emission: 465–495 nm bandpass; emission dichroic: 505 nm; YFP emission: 520–550 nm bandpass . Individual adult worms ( ∼24 h past L4 ) were glued with Nexaband S/C cyanoacrylate glue to pads composed of 2% agarose in extracellular saline ( 145 mM NaCl , 5 mM KCl , 1 mM CaCl2 , 5 mM MgCl2 , 20 mM D-glucose , 10 mM HEPES buffer , pH 7 . 2 , 2 mM serotonin ) . Fluorescence images were acquired using MetaVue 6 . 2 . Acquisitions were taken at 28 Hz ( 35 ms exposure time ) with 4×4 or 2×2 binning , using a 63× Zeiss Achroplan water immersion objective . Nose touch stimulation was performed as described [32] . A rounded glass needle was placed perpendicular to the worm's body at a distance of 150 µm from the side of the nose , displaced 8 µm into the side of the worm's nose , held in position for 1 second , and then pulled back to its original position . For each strain , we recorded 2 responses for 10 animals , with 5 minutes between stimuli . Results were compared using a Mann-Whitney rank sum test .
In order to investigate the role of IP3 signalling in the nervous system , we expressed the cDNA encoding the IP3 binding domain of itr-1 ( an “IP3 sponge” , [20] ) under the control of the promoter of unc-119 , which is widely , and exclusively , expressed in the nervous system [25] . Two derivatives of the IP3 sponge were used , as described previously [33] . The “control sponge” ( K579Q , R582Q ) , is deficient in IP3 binding and therefore should not disrupt IP3 signalling , while the “super sponge” ( R511C ) has increased affinity for IP3 . In a second approach , to disrupt IP3R function rather than IP3 signalling , we used the unc-119 promoter to control expression of an itr-1 dsRNAi “snapback” construct [34] . Figure 1 illustrates these approaches . We determined the role of IP3 signalling and itr-1 in the avoidance response to nose touch . Mechanical stimuli were delivered to the nose of moving animals using an eyelash , essentially as described by Kaplan and Horvitz [1] . In order to detect differences in the type of movement response exhibited , we used a scoring system in which the length of reversal was expressed in worm lengths ( see Methods ) . Three categories of response were used , >1 worm length , >0 . 1 worm length and 0 worm lengths . The first is considered a “good” response , while the latter two correspond to “poor” responses . This scoring method is similar to that used by Kindt et al . [32] , with the >0 . 1 worm length category usually corresponding to a “head withdrawal” response [32] , [35] . As Figure 2A shows , when cDNA encoding the IP3 super sponge is expressed under the control of the unc-119 promoter , the reversal response to nose touch is severely disrupted , while expression of the control sponge in the same way has no effect . However , the response to light anterior body touch , which uses a different neuronal circuitry but relies on the same command neurons and muscle groups , remains unaffected , indicating that the defect is specific to nose touch , rather than a general movement defect . The avoidance responses to harsh anterior body touch and both harsh and light posterior body touch are similarly unaffected ( DSW and HAB , unpublished ) . Thus , IP3 signalling functions in the avoidance response to nose touch . As Figure 2B shows , when an itr-1 dsRNAi “snapback” construct is expressed in the nervous system , the response to nose touch is significantly disrupted . A dsRNAi construct for the E . coli lacZ gene , expressed in the same way , has no effect . As Figure 2C shows , itr-1 ( sa73 ) ( temperature sensitive , loss-of-function ) animals also demonstrate a defective response to nose touch at 20°C , a partially restrictive temperature . In both cases , the response to light anterior body touch is unaffected , as were the responses to other types of mechanical stimuli ( DSW and HAB , unpublished ) . Since the vast majority of animals still exhibit a slight movement response ( >0 . 1 worm length ) , head withdrawal appears to be unaffected . Thus , itr-1 functions specifically in the reversal response to nose touch . The response to nose touch is largely mediated through the ASHL and ASHR pair of amphid sensory neurons , although minor roles appear to be played by FLP and OLQ neurons [1] . The ASH neurons are polymodal in function , with roles identified not only in the avoidance of nose touch , but also in the avoidance of high osmolarity and both volatile and non-volatile repellents [4] , [6] , [8] . To determine whether itr-1 has a global role in ASH responses or is specifically required for nose touch , we tested whether it has a similarly important role in other responses known to be mediated by ASH . As Figure 3A–3F shows , expression of the itr-1 dsRNAi construct under the control of the unc-119 promoter does not significantly disrupt the avoidance responses to high osmolarity ( fructose ) , SDS , copper , quinine or glycerol ( although our experiments do not exclude more subtle roles ) . However , the response to the volatile repellent benzaldehyde is disrupted ( Figure 3G ) . Similarly , itr-1 ( sa73 ) animals display a defective response to benzaldehyde ( Figure 3H ) . Interestingly , however , the use of an IP3 sponge failed to disrupt the aversive response to benzaldehyde ( Figure 3I ) , suggesting that this response could be independent of IP3 . We tested another volatile repellent , octanol , and found that , in the presence of food , the responses to 30% and 100% octanol are unaffected ( Figure 3J ) whilst wild type , and tph-1 and mod-5 mutants , behave as expected [29] . Thus itr-1 appears to function in a very limited subset of ASH-mediated avoidance responses , to nose touch and benzaldehyde . PLCs catalyse the hydrolysis of PIP2 , to produce IP3 ( Figure 1 ) and are therefore good candidates for the source of signal that activates the IP3R . We therefore investigated the role of C . elegans PLCs in the avoidance response to nose touch . In C . elegans five PLC genes and one further PLC-like gene have been identified in the genome [18] . They correspond to vertebrate PLC-β ( egl-8 [26] , [36] , [37] ) , PLC-δ , PLC-γ ( plc-4 and plc-3 , respectively [16] ) , PLC-ε ( plc-1 [37] ) , and an unusual , β-like protein ( plc-2 [18] ) . As Figure 4A shows , both egl-8 and plc-3 loss-of-function mutants exhibit a significant defect in the aversive response to nose touch , while loss-of-function mutants for the other PLC genes remain unaffected . The response to light anterior body touch is unaffected , as were the responses to other types of stimuli ( data not shown ) . Thus , egl-8 and plc-3 function specifically in the aversive response to nose touch . Since PLC-β and PLC-γ catalyse the production of two second messengers , IP3 and diacylglycerol ( DAG ) , we wished to demonstrate that it is via the generation of an IP3 signal that they function in the nose touch response . To this end , we investigated whether itr-1 ( sy290 ) , a gain-of-function allele [38] , could rescue the defects in nose touch response that resulted from egl-8 or plc-3 RNAi . itr-1 ( sy290 ) has a mutation , R582Q , in the IP3 binding site [38] , which results in a two-fold increase in IP3 binding affinity [20] . As Figure 4B shows , RNAi of plc-3 and of egl-8 ( in a wild type itr-1 background ) is able to reproduce the defect in nose touch response that was observed for loss-of-function mutants . However , RNAi of egl-8 and plc-3 on itr-1 ( sy290 ) animals failed , significantly , to disrupt the nose touch response to such an extent . Thus , an itr-1 mutation that increases the receptor's affinity for IP3 partially rescues the defects in nose touch response that result from knockdown of either plc-3 or egl-8 , suggesting that IP3 is an important component of the downstream signal from these PLCs . We investigated the role of PLCs in the response to benzaldehyde . As Figure 4C shows , the response to benzaldehyde remained intact in all of the PLC loss-of-function mutants . As both egl-8 and plc-3 are implicated in the response to nose touch we also attempted to test a plc-3 , egl-8 , double mutant for responses to benzaldehyde , however the double mutant animals had severe locomotive defects and we were not able to perform the relevant assays . Thus it appears that the response to benzaldehyde , although IP3R-dependent , may be independent of PLC function . Although we cannot rule out that the action of PLCs is redundant in this response , this data is compatible with the suggestion that this response does not depend on IP3 ( Figure 3I ) . The most likely candidates for the site of action of itr-1 in the nose touch response are the ASH neurons themselves or the downstream command neurons . In order to distinguish between these possibilities ( and the alternative , which is that it functions elsewhere to influence the function of these neurons in some way ) , we exploited the availability of neuron-specific promoters . The promoter of sra-6 directs expression in ASH , and ( weakly ) in ASI and PVQ [23] , while that of glr-1 directs expression in the command neurons AVA , AVB , AVD , AVE and PVC and several others , but not in ASH [35] . We therefore used these promoters to carry out cell-specific rescue and disruption of itr-1 function . As Figure 5A shows , when the IP3 super sponge is expressed under control of the sra-6 promoter , the response to nose touch is disrupted . In contrast , when it is expressed under control of the glr-1 promoter the response is unaffected . Likewise , expression of the control sponge , using either promoter , does not disrupt the response . Thus , disruption of IP3 signalling in ASH , but not the command neurons , interferes with the response to nose touch . We also used the opposite approach , expressing itr-1 cDNA under control of specific promoters and assessing whether this could rescue the defect in nose touch response that is observed in JT73 animals , which carry the itr-1 ( sa73 ) loss-of-function mutation . As Figure 5B shows , expression of itr-1 under the control of the sra-6 promoter rescues the defect seen in itr-1 ( sa73 ) animals , as does the expression of itr-1 under control of the pan-neuronal unc-119 promoter . In contrast , expression of itr-1 using the glr-1 promoter failed to rescue this defect . Thus , the defect in the reversal response to nose touch observed in itr-1 ( sa73 ) animals can be rescued by expression of itr-1 cDNA in ASH , but not in the command neurons . Since plc-3 and egl-8 appear to act upstream of itr-1 , we hypothesised that they also effect their role in the nose touch response in the ASH neurons . To test this , we used sra-6 and glr-1 promoters to rescue plc-3 and egl-8 in a neuron-specific manner in loss-of-function mutants . As Figure 6A shows , when plc-3 is expressed under the control of the sra-6 promoter in plc-3 ( tm1340 ) homozygotes , the defect in nose touch response is significantly rescued , while expression of plc-3 under the control of the glr-1 promoter fails to rescue . Thus , as predicted , the site of plc-3 function in the response to nose touch also appears to be the ASH neurons . As Figure 6B shows , when egl-8 is expressed under the control of the sra-6 promoter in egl-8 ( n488 ) animals , the defect in nose touch response is significantly rescued , while expression of egl-8 under the control of the glr-1 promoter fails to rescue . Thus the site of egl-8 function in the response to nose touch is also the ASH neurons . In order to more directly observe how itr-1 , egl-8 and plc-3 affect sensory responses in ASH , we used the genetically encoded Ca2+ sensor , cameleon , to examine in vivo calcium transients evoked by nose touch in ASH . As previously observed [22] , [32] , mechanical stimulation of the nose evoked calcium influx in the ASH neurons of wild-type animals expressing cameleon under control of the sra-6 promoter ( Figure 7 ) . However , nose touch-evoked calcium transients were significantly disrupted in itr-1 mutant animals , indicating that the IP3 receptor is required for ASH mechanosensory responses . Likewise , mutants defective in egl-8 or plc-3 showed significantly reduced calcium transients in ASH in response to nose touch . Together , these results indicate that the IP3 pathway is required for nose touch mechanosensation in ASH .
We have shown that signalling through IP3Rs is required for aversive responses to nose touch and benzaldehyde in C . elegans . The response to nose touch requires itr-1 function and the action of plc-3 and egl-8 in the polymodal ASH neurons , where they function in the generation of Ca2+ transients . The ability of the IP3 sponge to disrupt nose touch and the rescue of nose touch defects in plc-3 and egl-8 RNAi animals by an itr-1 gain-of-function allele , both support the conclusion that IP3 is the signalling molecule downstream of PLC and upstream of itr-1 activation . Thus nose touch requires a canonical IP3 signalling pathway in ASH . ASH neurons display striking polymodality and clearly distinguish functionally between different stimuli . For example , habituation to repeated nose touch has no effect on the response to octanol or high osmotic strength [39] . Likewise , prolonged exposure to copper affected behavioural and neural responses to copper but not to other repellents detected by ASH such as glycerol [22] . The ability of ASH neurons to discriminate between different aversive stimuli and undergo stimulus-specific adaptation indicates that at some level ASH uses different sensory transduction mechanisms for different modalities . At the molecular level , genes which are required for subsets of responses have been identified ( see review in [40] ) . For example , OSM-10 is required to sense osmolarity but not for other sensory responses [39] , while GPA-3 specifically affects acute responses to quinine [22] . Our new results identify the IP3 pathway as playing a specific role in the mechanosensory modality of ASH . Interestingly , itr-1 also affects a second ASH-dependent behaviour - avoidance of high concentrations of benzaldehyde . Thus it would be interesting to determine to what extent these responses show segregation or interact , for example whether habituation to nose touch alters responses to benzaldehyde or vice versa . The molecular overlap between the responses to these two very different stimuli is intriguing . Although both require itr-1 they do show some differences . The response to benzaldehyde is not disrupted by the use of IP3 sponges , and appears not to be dependant on PLC ( although we cannot eliminate the possibility that egl-8 and plc-3 act redundantly ) . This would suggest that , although both responses use the IP3R , the upstream components may be different . One explanation for these results is that the benzaldehyde response is mediated by an IP3-independent mechanism . IP3 independent activation of IP3Rs by proteins ligands such as CaBP ( Ca2+ binding protein ) , CIB1 ( Ca2+ and integrin binding 1 , also known as calmyrin ) and G-protein βγ subunits has been shown in other systems [41] , Homologues of CIB1 and Gβγ are both present in worms so such mechanisms could act within ASH . It would be interesting to know whether the site of itr-1 function in the benzaldehyde response is also ASH . However , due to technical limitations , we have been unable to test this . The profound movement defects of egl-30 mutants have also prevented us from testing whether this response is also Gαq-independent . The TRPV channels OSM-9 and OCR-2 are required for all ASH mediated responses , suggesting that response-specific signalling pathways converge on a common mechanism of activation . However , how the detection of such a wide range of stimuli is coupled to gating of these channels is unclear . The identification of signalling components that are required for detection of single stimuli , or small subsets , is vital to resolving this issue . OSM-10 , for example , is only required for detection of osmotic stimuli [39] . Similarly we have shown that itr-1 is only required for two responses , nose touch and benzaldehyde . It remains to be established how itr-1 mediated signals are coupled to the activation of OSM-9 and OCR-2 . It is probable that signals downstream of itr-1 are transduced by Ca2+ released from the ER . Many TRP channels are regulated by calmodulin , a key target of intracellular Ca2+ release . Calmodulin can act as both a positive and negative regulator of TRP channels [42] . Interestingly , TRPV4 and 6 are both positively regulated by CaM . The TRPV4 C-terminal CaM binding site which is required for positive regulation [43] shows some conservation with OSM-9 ( HAB , unpublished ) . A range of other signals are known to be involved in regulating TRP channel function . For example polyunsaturated fatty acids ( PUFAs ) are known to play an important role in regulating the activity of some TRP channels [44] and it has been suggested that PUFAs play a key role in regulating OSM-9/OCR-2 function [45] . Thus itr-1 might also regulate OSM-9/OCR-2 indirectly through other pathways . Our results place egl-8 ( PLC-β ) and plc-3 ( PLC-γ ) as being upstream of itr-1 . In each case we observed partial rescue when the genes were expressed in ASH in loss-of-function backgrounds . This partial rescue may be due to inadequate expression from the sra-6 promoter or could reflect a requirement for these genes in other cells , although we do not observe any rescue on expression in command neurons . The identification of a role for two PLC subtypes is at first glance surprising , however there are many examples of multiple PLC subtypes being utilised in physiological processes ( see for example [17] ) . In ASH our results suggest that both act , at least in part , through IP3 . The signals upstream of PLC are unknown . PLC-β is usually regulated by members of the Gqα subunits of heterotrimeric G-proteins . We were unable to test the role of EGL-30 ( Gqα ) in this process as egl-30 mutants have widespread defects in locomotion . In addition , ASH expresses at least 9 G-alpha subunits . Some of these have identified and specific functions whilst some are more general; e . g . odr-3 appears to be required for all known ASH-mediated responses , while gpa-3 is only required for the response to water soluble repellents [11] , [46] . Whether any of the other Gα subunits are specifically required in nose touch remains unclear . We tested the effect of mutations in the Gα subunits expressed in ASH , however , we found that most impaired nose touch , to varying degrees ( DSW and HAB , unpublished data ) . It seems likely that their role is complex , involving multiple cells types and perhaps redundancy between subunit types . How does PLC and IP3 signalling facilitate the response to nose touch ? The mechanism by which ASH neurons detect nose touch is unclear . Kindt et al . [32] have shown that the response of two other neurons QLQ and Il1 to nose touch involves the mechanosensitive TRPA channel TRPA-1 . However TRPA1 does not appear to be required in ASH [32] . Thus mechanosensation in ASH may use a different mechanism . One possibility is that IP3 signalling in ASH lies downstream of ligand independent activation of GPCRs . Analysis of the “Bayliss Response” in which small resistance arterial blood vessels constrict in response to rises in blood pressure has identified a pathway which is initiated by the activation of GPCRs by membrane stretch [47] . In these vascular smooth muscle cells ligand independent activation of the Angiotensisn II AT1 receptor by membrane stretch regulates a TRP channel , TRPC6 , through a mechanism that requires both Gαq and PLC . Other Gαq linked GPCRs also demonstrate mechanosensitive properties [47] . The signal between PLC and TRPC6 has not been identified . As discussed above we have shown that in ASH , nose touch is mediated by PLC-β ( egl-8 ) which is normally downstream of Gαq coupled GPCRs so our data are compatible with such a mechanism operating in these cells . Alternatively , IP3 signalling might not be directly activated by nose touch . Many mechanosensory processes involve ion channels that are directly activated by force; thus , IP3 signalling might regulate the activity of a mechanosensitive channel responsible for sensing nose touch in ASH . In this model , IP3 signalling does not mediate sensory transduction per se , but rather acts downstream of G-protein-mediated neuromodulatory pathways to modify touch sensitivity . Pathways of this sort would be critical for modality-specific adaptation in a polymodal neuron such as ASH . In summary , we have shown that the IP3 signalling cassette is part of the specific signalling machinery for nose touch in ASH neurons . This adds to our molecular understanding of the molecular mechanisms that enable the segregation of signals in these polymodal sensory neurons and contributes to our understanding of how polymodal neurons , such as human nociceptors , function in general . | In order to avoid potential hazards , animals detect and discriminate between a wide range of aversive stimuli . To detect some of these stimuli , animals use polymodal sensory neurons , that is neurons of a single type that can detect a range of different stimuli and transmit an appropriate signal to the downstream nervous system . Pain-sensing nociceptors in humans and the ASH neurons in C . elegans are both polymodal . The ASH neurons mediate responses to high osmotic strength , nose touch , high ambient oxygen , and volatile and non-volatile compounds . It remains unclear how these cells detect and discriminate between these different stimuli . We show that signalling through the second messenger inositol 1 , 4 , 5-trisphosphate ( IP3 ) and its receptor ( IP3R ) is required in ASH for animals to respond to nose touch . We also show that IP3Rs are required for the response to the volatile compound benzaldehyde . However , these signalling components are not required for a range of other ASH-mediated responses . Thus , we have identified a signalling mechanism that is specific to a small subset of ASH-mediated responses . These results add to our understanding of how ASH discriminates between a variety of stimuli and thus to our understanding of polymodal neurons in general . | [
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] | 2009 | Inositol 1,4,5-Trisphosphate Signalling Regulates the Avoidance Response to Nose Touch in Caenorhabditis elegans |
Trends in HIV virulence have been monitored since the start of the AIDS pandemic , as studying HIV virulence informs our understanding of HIV epidemiology and pathogenesis . Here , we model changes in HIV virulence as a strictly evolutionary process , using set point viral load ( SPVL ) as a proxy , to make inferences about empirical SPVL trends from longitudinal HIV cohorts . We develop an agent-based epidemic model based on HIV viral load dynamics . The model contains functions for viral load and transmission , SPVL and disease progression , viral load trajectories in multiple stages of infection , and the heritability of SPVL across transmissions . We find that HIV virulence evolves to an intermediate level that balances infectiousness with longer infected lifespans , resulting in an optimal SPVL∼4 . 75 log10 viral RNA copies/mL . Adaptive viral evolution may explain observed HIV virulence trends: our model produces SPVL trends with magnitudes that are broadly similar to empirical trends . With regard to variation among studies in empirical SPVL trends , results from our model suggest that variation may be explained by the specific epidemic context , e . g . the mean SPVL of the founding lineage or the age of the epidemic; or improvements in HIV screening and diagnosis that results in sampling biases . We also use our model to examine trends in community viral load , a population-level measure of HIV viral load that is thought to reflect a population's overall transmission potential . We find that community viral load evolves in association with SPVL , in the absence of prevention programs such as antiretroviral therapy , and that the mean community viral load is not necessarily a strong predictor of HIV incidence .
Virulence can be defined as the severity of disease caused by a pathogen; the virulence of a pathogen may evolve within a host population as the rates of transmission and host mortality are balanced by natural selection . For HIV , virulence can be defined as the rate of disease progression in the absence of antiretroviral treatment . Understanding if HIV virulence has evolved will inform our understanding of HIV epidemiology and pathogenesis , as increases in HIV virulence would result in more rapid disease progression [1]–[4] , the earlier initiation of antiretroviral therapy [5] , and an increased per-contact transmission risk [6]–[10] . The estimation of epidemic trends in HIV virulence includes the measurement and analysis of proxy markers for HIV disease progression , with set point viral load ( SPVL ) the most prognostic single marker of the time to AIDS after HIV infection [1]–[4] . While exact definitions of SPVL vary , it is generally the HIV plasma RNA viral load after the resolution of acute infection , but within 6 months to two years after seroconversion ( and prior to initiation of antiretroviral therapy ) . We previously completed a meta-analysis of 8 published studies of population-level trends in SPVL; our meta-analysis found a positive summary trend ( 0 . 013 log10 copies/mL/year , P = 0 . 07 ) [11] , consistent with increased virulence of HIV . However , the studies also showed large variation in SPVL trends ( range: −0 . 013 to 0 . 035 log10 copies/mL/year ) [11] . The causes of this variability remain unexplained , but may include estimation methods ( clinical or statistical ) or differences among the HIV cohorts ( and associated local epidemics ) in which trends were studied . These cohorts contain primarily men of European descent with HIV subtype B infections . Our previous analysis of study parameters in these 8 cohorts ( including transmission risk group frequency , sample size , length , calendar year time period , seroconversion lag , and sampling lag ) showed that only seroconversion lag was associated with SPVL trend; i . e . , shorter periods between the last negative and first positive HIV-1 antibody tests were correlated with increased SPVL trends . It followed that for the 6 of 8 studies in the meta-analysis that were prospective seroconverter cohorts , the summary SPVL trend was 0 . 018 log10 copies/mL/year , 38% greater than the summary trend of 0 . 013 copies/mL/year for all eight cohorts ( including both seroconverter and seroprevalent cohorts ) . However , this explanation for variation in SPVL trends is insufficient , as trends from seroconverter cohorts are still highly variable ( range: −0 . 002 to 0 . 035 log10 copies/mL/year ) [11] . Positive trends in mean population SPVL ( HIV virulence ) may reflect the process of viral adaptive evolution in the human population; recent modeling studies [12] , [13] have proposed the existence of an evolutionarily optimal SPVL of 4 . 52 log10 copies/mL , defined as the viral load that balances transmission probability with infected lifespan . For example , low SPVL will result in lower infectivity but more total transmissions ( due to greater life expectancy ) , whereas high SPVL will result in high infectivity but fewer total transmissions ( due to decreased life expectancy ) . The proposed optimal SPVL of 4 . 52 log10 was qualitatively consistent with mean SPVL levels found in the Amsterdam Cohort Study ( 4 . 36 log10 copies/mL ) [12] and the Zambian Transmission Study ( 4 . 74 log10 copies/mL ) [9] . Mean SPVLs in the studies included in our meta-analysis were also qualitatively similar to 4 . 52 , albeit with a wider range ( from 4 . 25 to 5 . 2 log10 copies/mL ) . An even greater range in population viral loads was seen in a review of 57 studies , where medians ranged from 3 . 7 and 5 . 6 log10 copies/mL and the overall median was 4 . 45 log10 copies/mL [14] . These 57 studies were not studies of SPVL distributions , specifically; however , viral loads in the asymptomatic period are generally stable and likely to be close to SPVL [15] , [16] . We have developed a stochastic , agent-based HIV evolutionary and epidemic model based on the dynamics of HIV viral load . This model is unique for HIV epidemic models in that it allows for the viral virulence phenotype ( set point viral load ) to change over the course of an epidemic . The model contains known functions related to viral load trajectories in acute , chronic and disease stages , viral load and transmission probability , SPVL and disease progression rate , and the heritability of SPVL across transmission pairs . These components provide an evolutionary framework in which a balance is achieved between efficient transmission and slow disease progression . This type of evolutionary structure for HIV transmission potential was proposed by Fraser [12] . Our primary aims are to understand both the underlying causes of empirical SPVL trends and also the variation among populations/cohorts in the estimation of these trends ( rather than variation in SPVL among individuals e . g . , [15] , [17] , or the relative contributions of viral genetic and environmental factors to SPVL variation [13] ) . To do this , we estimate the temporal changes in SPVL that can result from adaptive viral evolution in human populations , and we assess deviations from these trends related to virologic parameters such as initial mean SPVL , maximum per-contact transmission rate , or epidemic stage . We also examine the effects of potential sampling biases due to improvements in the rates of HIV diagnosis , changes in cohort recruitment procedures , or earlier initiation of ART after diagnosis—biases that were not explicitly considered by the studies of empirical SPVL trends described in the meta-analysis . A secondary aim is to understand trends in HIV community viral load ( CVL ) . CVL is typically defined as the arithmetic or geometric mean ( or median ) of all reported individual viral loads ( individuals diagnosed and sampled , with detectable viral load ) in a specific community . CVL is considered to be a heuristic proxy for overall transmission potential ( and level of HIV-associated health care ) in a given community [18]–[21] . Thus , the ability to accurately assess trends in CVL is critical for prevention programs that promote reduced population viral load and transmission potential as a measure of effectiveness: CVL needs to be a robust and informative metric for comparisons through time , meaningfully related to HIV epidemiological parameters that are important to the public health community . However , recent work has described potential pitfalls in the relationship between CVL and transmission potential ( e . g . , issues of sampling bias , population context , and ecological fallacy ) [22] . In our analysis , we focused on the potential evolutionary context of trends in CVL: there are similarities between the estimation of SPVL and CVL trends , and we hypothesize that understanding biases related to SPVL trends will inform our understanding of CVL trends . Overall , we expect our model will improve our understanding of HIV epidemics and the virologic metrics that are used to study them .
This component includes HIV-uninfected people , HIV-infected people , and people who have died of AIDS . Each simulation starts with N total HIV-uninfected and infected individuals at time zero , with each infected individual ( of n total HIV-infected individuals ) provided a SPVL value following from a Gaussian distribution with user-defined mean and variance , with the variance parameter following published estimates [12] , [14] . Entry of new ( uninfected ) individuals into the population is at a constant input rate such that the population , in absence of HIV infection , will stay at its initial value . Infected individuals may die of their HIV infections according to formulas given below . Further model details are given in Text S1 . We ran epidemic simulations for 100 years , in discrete time-steps of one day . For each model run we tracked individual viral load trajectories , infected lifespan , sexual partnerships and transmission histories , and epidemic growth or decline , and we estimated population measures of AIDS mortality , SPVL trends and heritability . The mean , median , and variance of SPVL in the population could be calculated directly at any day in a simulated epidemic . Likewise , the mean , median , and variance of community viral load ( CVL ) could be calculated at any day using the viral load from each currently alive and infected individual . We conducted sensitivity analyses on each parameter from Table 1 , but focused on: the rate of viral load increase in the asymptomatic period ( s from Equation 1 in Text S1 ) ; the rate of disease progression ( maximum time to AIDS after infection , Dmax from Equation 2 in Text S1 ) ; and the maximum daily rate of transmission in the asymptomatic period ( Bmax in Equation 3 in Text S1 ) . To examine the potential for adaptive evolution of HIV virulence , we examined 10 replicate epidemic simulations for three different values of initial population mean SPVL ( 3 . 5 , 4 . 5 , and 5 . 5 log10 copies/mL ) . Trends in SPVL were calculated by regressing against the times of infection recorded for each individual ( each individual had individual-specific SPVL and time of infection ) . We sought to place published SPVL trends in the context of results from our epidemic model . To do this , we created hypothetical null distributions of SPVL trends for epidemics with initial mean SPVL values equal to 3 . 5 , 4 . 5 , or 5 . 5 log10 copies/mL . For each of the 10 replicate runs for each initial mean SPVL , we randomly chose 100 separate 20-year time periods with replacement; we chose 20-year periods as most empirical estimates of SPVL trends cover 20-year periods . From each of these 20-year time periods we estimated a univariate linear regression of SPVL by calendar year of infection . This created a distribution of 1×103 possible observed SPVL trends ( 100 20-year periods from 10 replicate model runs ) for any given set of model parameters , where only the starting random number seed and the randomly chosen 20-year period were different between trend estimates . The HIV epidemics of European and North American countries are younger than 100 years; the first introduction of HIV to the US is estimated to have occurred in 1969 [28] with introductions to Europe following . Empirical SPVL trends have been estimated most often using data from approximately 1985 to 2010 [29] . This may affect our choice of an appropriate null distribution for SPVL trends produced by our model . To accommodate this uncertainty we created separate null distributions , each spanning a different subset of the complete 100-year simulated epidemics: a ) all 100 years of the model output; b ) years 10–100 of the model output , under the assumption that European and North American subtype B epidemics began ∼1970 , which , as studies of empirical SPVL trends began sampling at the earliest in 1984 , leaves a ∼10-year window of the HIV epidemic that was not sampled by cohorts; c ) years 0–40 of the model output , under the assumption that because empirical studies of SPVL trends include years up to ∼2010 , this represents the first 40 years of the subtype B epidemic ( ∼1970 to 2010 ) ; and d ) years 10–40 , the most restrictive null , meant to reflect the empirical sampling years ∼1980 to 2010 . Two distinct types of sampling biases may potentially result from the fact that HIV viral loads in primary infection are higher in symptomatic individuals [30] , [31]: a trend in mean SPVL may result from improvements over time in referral or cohort recruitment practices [32] , or improvements over time in diagnostic techniques and identification of new HIV infections [33] . For example , if rapid progressors are more readily identified and diagnosed as the epidemic progresses , and these individuals initiate ART before set point is measured , then fewer individuals with ( relatively ) high SPVL will be sampled as the epidemic ages . This is a bias caused by earlier diagnosis and ART initiation , and may lead to inferred trends of decreasing virulence . Alternatively , if increased diagnosis and recruitment of newly infected individuals is associated with improvements in referral or cohort recruitment , but does not lead to earlier ART initiation , biased sampling in the opposite direction may result . In this case , relatively more symptomatic individuals would be sampled , and trends of increasing virulence may be inferred . ( We recognize that increased and earlier diagnosis not leading to earlier ART initiation is not consistent with current clinical practice; however , most published studies of HIV virulence trends included sampling years from the 1980s and 1990s . ) We recreated the above types of biased sampling in simulated epidemics as follows: 1 ) we divided randomly chosen 20-year epidemic periods ( used to estimate SPVL trends ) into individuals infected in years 1–10 versus years 11–20; 2 ) from the latter subpopulation ( years 11–20 ) , we created subsamples that included individuals with SPVLs either greater or less than SPVL = 5 . 0 log10 copies/mL ( http://aidsinfo . nih . gov/guidelines/archive/adult-and-adolescent-guidelines ) ; 3 ) depending on the type of sampling bias to be recreated , we randomly selected a portion of individuals to be removed from either the “SPVL>5 . 0” or “SPVL<5 . 0” subsamples ( Figure S1 ) . For each day in a simulated epidemic , we calculated community viral load ( CVL ) as the mean and median viral load of all HIV-infected individuals who were currently in day 45 or greater of their infection ( one half of the time to reach set point; with the length of acute infection set to 90 days in our standard parameter settings ) . This threshold is meant to mimic empirical estimates of CVL , where the majority of individuals in early acute infection are unsampled and do not contribute to CVL estimates .
For model runs of 100 years with standard parameter values ( Table 1 ) , we found the following: epidemic growth , starting from 500 HIV-infected individuals in an initial population size of 75 , 000 ( infected and uninfected ) , varies across initial mean SPVL values . Runs with intermediate ( 4 . 5 ) and high ( 5 . 5 ) initial mean SPVLs resulted in faster rates of epidemic growth; these resulted in >35 , 000 HIV-infected individuals before year 20 ( Figure 1A ) . Kaplan-Meier survival curves stratified by quartiles of SPVL were consistent with published survival analyses from two separate cohorts [3] , [12] ( Figure S2 ) . The estimated heritability of SPVL across transmission pairs were consistent with empirical estimates of SPVL heritability [24]–[27] , and decreased over the course of simulated epidemics as variance in SPVL decreased ( Figure S3 ) . Population variation in SPVL and VL were consistent with empirical estimates: a recent meta-analysis reported interquartile ranges ( IQR ) for 51 studies of population viral loads [14] with an average IQR of ∼1 . 0 log10 copies/mL; IQRs of SPVL for our model were 0 . 9 , 0 . 86 , and 0 . 84 log10 copies/mL for new infections taking place in years 25 , 50 and 75 of simulated epidemics , respectively ( Figure S4 ) . For a standard epidemic run ( Table 1 ) , ∼5% of all infections ( over 100 year epidemic simulations ) took place while the source partner was in “early HIV infection” ( defined as 3 months , up to Fiebig stage V [34] ) , although this frequency was higher ( ∼10% ) in the early stages of simulated epidemics ( Figure S5 ) . Changing the definition of “early HIV infection” to include the entire first year of infection increased the frequency of early infection transmissions to ∼20% of all transmissions ( and this frequency is higher , ∼25% , if only simulated epidemic years 10 to 40 ( ∼1980 to 2010 ) were considered ) ( Figure S5 ) . We found that SPVL evolves toward a equilibrium value of approximately 4 . 75 log10 copies/mL , regardless of the mean SPVL of the founding population of infected individuals ( at time zero ) ( Figure 1B ) . Variability across 10 replicate model runs ( with only the random number seed changed ) in SPVL trends was minimal ( Figure 1B ) . This SPVL is slightly higher than the 4 . 52 optimal SPVL predicted by Fraser [12] and Shirreff [13] , as well as the 4 . 45 overall median of 57 studies reported by Korenromp [14] . We next compared empirical SPVL trends to results from our model by producing null distributions of 20-year linear SPVL trends . Figure 2A shows the different null distributions for model runs with founder mean SPVLs of 3 . 5 , 4 . 5 , and 5 . 5 log10 copies/mL , using all 100 years of simulated epidemics . Broadly , trends estimated from epidemics with initial mean SPVL = 3 . 5 were positive and trends from epidemics with initial mean SPVL = 4 . 5 or 5 . 5 were negative ( Figure 2A ) . Interestingly , the distribution for epidemics with starting mean SPVL = 4 . 5 included mostly negative trends despite the optimal SPVL equal to ∼4 . 75 copies/mL , due to transient increases in virulence early in epidemics , before the number of susceptible individuals begins to decrease ( Figure 1B ) [13] , [35] . We compared the empirical SPVL trends to these null distributions , and the magnitudes of the empirical trends were similar to ( and therefore consistent with ) the model-based trends . The majority of these trends were located to the far right ( positive ) side of the distributions ( SPVL trends>0 . 01 log10 copies/mL/year ) ( Figure 2A ) . ( 95% confidence intervals for the empirical trends are overlaid on null distributions created from model years 0 to 100 in Figure S6A . ) When we compared empirical SPVL trends to potentially more appropriate null distributions ( produced by sampling only years 0 to 40 , or years 10 to 40 , of simulated epidemics ) , the empirical trends were even more similar to model-based trends . Specifically , the larger empirical trends ( >0 . 01 log10 copies/mL/year ) were consistent with the median trends from null distributions for simulated epidemics with initial mean SPVL = 3 . 5 ( Figure 2B ) . Thus , the larger empirical trends may be unbiased measures of adaptive viral evolution in populations where the initial founding viral lineages contained low virulence . The median SPVL trend for the null distribution produced from sampling from years 10 to 40 of epidemics with initial mean SPVL = 3 . 5 was 0 . 0073 log10 copies/mL/year ( Figure 2B ) , compared to a median SPVL trend of 0 . 0011 log10 copies/mL/year when sampling from years 0 to 100 . ( 95% confidence intervals for the empirical trends are shown overlaid on null distributions created from model years 10–40 in Figure S6B . ) We simulated two types of sampling biases to begin in the latter half of 20-year time periods: 1 ) earlier ART initiation; and 2 ) increased rates of diagnosis ( without associated earlier ART initiation ) . Hypothetically , these sampling biases may result in linear SPVL trends that are decreased and increased relative to true trends , respectively . Indeed , simulating these biases on model output resulted in incorrect estimates of the true evolutionary trends in SPVL ( Figures 3A and 3B ) . Figure 3A shows incremental positive shifts in SPVL trend distributions that result from increased sampling biases ( by increasing the proportion of the HIV-infected population that is be affected by , in this example , increased rates of diagnosis without associated earlier ART ) . For this specific example ( which included only simulated epidemics with initial mean SPVL = 3 . 5 ) , the medians of biased SPVL trends were significantly different from the median of the true trend distribution ( unbiased median = 0 . 0011; 10% removed median = 0 . 0028; 50% removed median = 0 . 0129 log10 copies/mL/year ) . Similar shifted distributions , though in the opposite direction , were found for biases due to earlier ART initiation . Figure 3A shows the effect of sampling biases on null distributions produced from years 0 to 100 of simulated epidemics . As noted above , a more appropriate null distribution may be a time period from simulated epidemics that reflects the expected sampling times of HIV subtype B epidemics; this can be years 10 to 40 of simulated epidemics , reflecting approximately years 1980 to 2010 . When this narrowed time period is used to recreate potential sampling biases , the effects on SPVL trend distributions are distinct than those seen when using the full 100 years of simulated epidemics: the median trend values increase significantly with more increased sampling biases ( unbiased median = 0 . 0073; 10% removed median = 0 . 0094; 50% removed median = 0 . 0208 log10 copies/mL/year ) , but all distributions overlapped extensively ( Figure 3B ) . In effect , with this narrow null distribution it is more difficult to distinguish between adaptive viral evolution and sampling biases as possible explanations for the empirical SPVL trends . An assumption inherent to many studies of HIV virulence is that SPVL trends will be linear . This assumption is likely false , as epidemic growth or decline is affected by the availability of susceptible individuals ( among other factors ) ; epidemics may not experience constant linear growth , and thus evolutionary pressures on the virus may shift over the course of an epidemic . Furthermore , processes of HIV evolution , including natural selection and genetic drift , can be affected in complex ways by changes in the viral effective population size ( measured in this context most simply as prevalence ) . We examined the distribution of SPVL slopes in progressing stages of simulated epidemics ( Figure 4A ) . For simulated epidemics with varying initial mean SPVLs ( 3 . 5 , 4 . 5 , and 5 . 5 log10 copies/mL ) , the distribution of slopes changed over time , as more extreme slopes ( further away from zero ) occurred in the first 20 years of epidemics , and all distributions converged to near zero as the epidemic entered years 40 and greater . This suggests that if the empirical SPVL trends are due to adaptive viral evolution , then we can hypothesize that local/regional epidemics ( represented by national HIV cohort populations ) with increasing SPVL were founded by viruses of low virulence ( SPVL∼3 . 5 ) . We tested whether model output was sensitive to the parameters of the viral load functions . We initially focused on: 1 ) the viral load progression rate in chronic infection; 2 ) the maximum rate of progression to AIDS; and , 3 ) the maximum daily rate of transmission in the asymptomatic period . Variation in the rate of viral load increase and in the rate of disease progression had only minor effects on epidemic growth and the evolution of virulence ( Figures S7 and S8 ) . Variation in the maximum transmission rate ( Bmax ) had large effects on epidemic growth and the early pattern of evolution toward optimal SPVL ( Figure S9 ) . With higher maximum transmission rates , the epidemic size increases more rapidly and virulence ( SPVL ) increases; these increases in SPVL were transient , however , as the supply of susceptible individuals soon declines and limits further epidemic growth . The evolutionarily optimal SPVL remains equivalent across different values of Bmax . This pattern of increasing virulence in the early stage of the epidemic followed by decreasing virulence as susceptible supply declines might be expected [35] and was also observed in the simulations of Shirreff [13] . Model simulations with Bmax following directly from Fraser [12] ( Bmax = 0 . 001044 per day ) resulted in epidemic growth that was slow relative to expectations from empirical HIV epidemic data . As Bmax in Fraser [12] and Shirreff [13] was the maximum transmission rate estimated for serodiscordant couples within HIV cohorts [9] , and likely an underestimate of the transmission rate in the general population [12] , we increased Bmax for our standard runs ( e . g . , Figures 1 to S7 ) to Bmax = 0 . 0025 per day . Increasing Bmax allowed more accurate recreation of HIV epidemic growth rates; this did not affect the optimal HIV SPVL , but variation in Bmax did affect the rate at which SPVL changes in the early epidemic , with higher Bmax associated with early increases to higher SPVL ( Figure S9 ) . In addition to the viral load progression rate , the maximum rate of disease progression , and the maximum transmission rate , we examined the effects of variation in other model parameters on SPVL trends . However , the time to peak viremia , the peak viral load in acute infection , the length of acute infection , the viral load at AIDS , the heritability of SPVL at time zero , and the mutational variance of SPVL all had minimal impacts on optimal SPVL . In our simulated epidemics the mean CVL , measured as the mean or median of log10-transformed VL of all infected ( and sampled ) individuals in a population at a given time , changed over time ( Figure 4B ) . ( Mean and median CVL are nearly identical in our simulations . ) Community viral load evolved in association with SPVL: CVL trends were influenced by the initial mean SPVL of the founding population , and annual trends in mean/median CVL were qualitatively similar to annual SPVL trends . Mean CVL was consistently lower than mean SPVL due to frailty bias ( individuals with low SPVLs were included in CVL estimates more often than individuals with high SPVLs ) ( Figure 4B ) . The variance around the mean CVL decreased over the first half of the model runs before stabilizing around 0 . 3 log10 copies/mL . The distribution of all viral loads in our simulations was qualitatively similar to the expected distribution proposed by Miller [22] for a population sample of “detectable viral loads from individuals not on treatment . ” We assessed the hypothesis that CVL is a heuristic measure of a population's overall transmission potential , i . e . , that mean CVL is positively associated with incidence [18]–[20] . First , for complete 100-year epidemic simulations , with initial mean SPVL values of 3 . 5 , 4 . 5 and 5 . 5 log10 copies/mL , we compared yearly values of mean CVL to annual incidence ( infected/susceptible ) for each year ( Figure 5A ) . Over this extended timescale , mean CVL and annual new infections were significantly correlated only for initial SPVL = 3 . 5 ( Spearman's rho = 0 . 56 , P-value = 1 . 86−09; for initial SPVL = 4 . 5 , rho = 0 . 11 , P-value = 0 . 293; for initial SPVL = 5 . 5 , rho = 0 . 12; P-value = 0 . 254 ) . Next , we modified this model-based comparison of CVL and incidence in order to make comparisons more equivalent to the 10-year timescales of empirical observations of CVL [18]–[20] . We created a data set containing all 10-year time periods from the 100-year simulated epidemics , each created with a sliding window of length 10 years with increment of one year . For each of these 10-year periods , we estimated Spearman's rho and P-value between yearly CVL and new infections ( Figure 5B ) . A minority of 10-year time periods from each epidemic ( each initial mean SPVL ) contained significant ( P<0 . 05 ) associations between yearly mean CVL and number of infections , and the direction of association ( Spearman's rho ) alternated between positive and negative over the course of the epidemic ( Figure 5B ) . These simulations were run in the absence of prevention programs such as antiretroviral therapy , yet suggest that mean CVL is not necessarily a strong predictor of HIV transmission potential .
Our model shows that HIV virulence , using set point viral load as a proxy , can adaptively evolve in a host population . This result is consistent with previous work [12] , [13] , in both evolutionary processes ( adaptation of HIV virulence to optimize transmission potential ) and patterns ( optimal SPVL ∼4 . 75 log10 copies/mL ) . It is also consistent with studies showing HIV adaptation to the human population in response to both cellular [36] , [37] and humoral [38] , [39] responses over the course of the epidemic . To assess the published empirical trends in SPVL , we created hypothetical null distributions of 20-year linear trends in SPVL and placed the empirical trends within these distributions . Because local epidemics with published SPVL trends may have unique epidemic and evolutionary contexts , particularly the SPVL ( virulence ) of the founding viral strain , we created null distributions of SPVL trends for simulated epidemics with initial SPVL means of 3 . 5 , 4 . 5 and 5 . 5 log10 copies/mL . Notably , the simulated and empirical trends are within the same magnitude ( between −0 . 02 to 0 . 03 log10 copies/mL/year ) , which suggests that adaptive HIV evolution may explain observed trends in HIV virulence . What explains the variation among empirical trends ? The placement of the empirical SPVL trends spans the three null distributions; yet , five ( out of eight ) lie within the upper distribution ( >0 . 01 log10 copies/mL/year ) of the simulated trends ( Figures 2A ) . If we narrow our null distribution to years 10 to 40 of simulated epidemics to better reflect the years 1980 to 2010 of European and North American subtype B epidemics , the empirical trends of greater magnitude appear more consistent with model-based trends; these empirical trends are consistent with these epidemics being founded by viral populations of low virulence ( virulence less than the optimal level ) ( Figure 2B ) . We know from the respective publications that 4 of these 5 empirical trends belong to HIV cohorts with initial mean or median SPVLs less than our model-predicted optimal SPVL ( <∼4 . 75 ) : 3 . 6 [40] , 4 . 19 [41] , 4 . 3 [42] , and 4 . 4 [43] log10 copies/mL ( the first sampling period for these studies was most often a 2 to 5-year period starting in 1985; this would correspond to a time approximately between years 15 to 20 in our simulated epidemics ) . It is essential for future work to compare simulated adaptive evolution of SPVL to real epidemic data , using phylodynamic analysis to reconstruct epidemic histories overlaid with empirical and simulated SPVL trends . While our model results suggest that adaptive evolution may explain empirical trends , and that epidemic context may explain variation in empirical trends , we also assessed whether trends and variation among trends could be the result of cohort-specific sampling biases . To do so , we recreated two types of simple biases: improvements in diagnosis that result in increased sampling of high virulence individuals; or earlier ART initiations that result in decreased sampling of high virulence individuals . We found that the empirical SPVL trends are consistent with biased trends resulting from improved diagnosis of symptomatic cases . Whether this particular type of sampling bias may explain the empirical trends—as opposed to being explained by adaptive evolution—requires study of specific cohort clinical and community practices . Diagnosis of symptomatic individuals without earlier ART initiation is not consistent with clinical practice; it is unclear what the strength of this bias could be over time in HIV cohorts , and it is likely that both of the potential biases recreated here do exist ( to some relative degree ) in every HIV cohort . We can try to infer , using data from the meta-analysis of observed SPVL trends [11] and our model output , which potential type of sampling bias is stronger in the empirical data . The meta-analysis contained 8 studies of SPVL trends , 6 of which were prospective cohorts that estimated virulence trends using only SPVL data from individuals with an estimated date of HIV infection . These seroconverter cohorts are less vulnerable to sampling biases , because individuals enter the cohort uninfected . In the meta-analysis , the summary SPVL trend for all eight cohorts ( including both seroconverter and seroprevalent cohorts ) was 0 . 013 log10 copies/mL/year , 38% lower than the summary trend of 0 . 018 seen for the six seroconverter cohorts . A discrepancy between trend estimates in this direction ( decreasing SPVL trend ) is consistent with a sampling bias caused by earlier ART initiation in the seroprevalent cohorts . ( i . e . the lower SPVL trends in the seroprevalent cohorts could be explained by a sampling bias caused by earlier ART initiation in those populations ) . This hypothesis is consistent with decreasing clinical thresholds for ART initiation ( http://aidsinfo . nih . gov/guidelines/archive/adult-and-adolescent-guidelines ) . The use of community viral load as a population-level metric of HIV transmission potential has been proposed [18]–[21] . To date few studies , empirical or modeling , have assessed this proposition thoroughly [22]; for CVL to be a useful tool for public health inferences , it must accurately and precisely reflect HIV epidemiological parameters of interest . There are similarities between the estimation of SPVL and CVL trends—we hypothesize that understanding the underlying causes or sampling biases related to SPVL trends can inform our understanding of CVL trends . With our model , we attempted to evaluate the possible affects of HIV epidemic and evolutionary context on trends in mean CVL . Our findings suggest the relationship between CVL and incidence is not straightforward , yet is strongly modulated by epidemic context , including: 1 ) the initial mean SPVL of an epidemic; and 2 ) the epidemic stage in which the CVL and incidence relationship is evaluated . As shown in Figure 5B , significant associations between CVL and incidence can be identified in simulated epidemics , but there are both positive and negative associations . In this scenario CVL is not a robust population-level metric of HIV transmission potential . However , our estimate of CVL does not include individuals on ART with depressed viral loads and thus does not perfectly coincide with real world applications . Nevertheless , our model shows that attempts to infer transmission potential from CVL can give highly misleading results , as CVL is influenced by both historical and evolutionary factors . The global HIV pandemic is one of multiple separate epidemics that can be stratified by viral genotype ( subtypes or circulating recombinant forms ) [44] , [45] , and by human population ( e . g . , transmission risk group , geography ) [46] , [47] . Our model is not designed to recapitulate the entire global pandemic , but rather local epidemics containing a single subtype . The disease progression function of our model is based on subtype B data; it is possible that the relationship between SPVL and disease progression is different across subtypes [48]–[52] , but the disease progression function likely holds for different risk groups within local subtype B epidemics ( e . g . , heterosexual sex , men who have sex with men , or injecting drug use within subtype B epidemics ) . The transmission function of our model is based on serodiscordant heterosexual couples with counseling [9]; as discussed above , using Bmax from Fraser [12] that saturates at viral loads results in slower epidemic growth rates . Elevating this rate to perhaps better reflect transmission rates in the general population results in more realistic growth rates but a similar level of optimal virulence . Additionally , SPVL is known to vary among hosts due to host genetics ( HLA type ) [53]; our model does not distinguish among individuals in their susceptibility to infection or host effect on SPVL ( which can influence transmission and disease progression ) . Nor does our model allow for variation within individuals in viral reproductive rate; i . e . , in our model all viral lineages within a single person are assumed to contain the same viral genetic factors for viral reproduction and SPVL/virulence . When this is not the case , and virions within a host are allowed to vary in reproductive rate , it is theoretically possible that different evolutionary trends in relation to optimal SPVL may be seen [54] . Our model includes simple demographic and sexual mixing terms , which we believe are sufficient to address the issues explored in this paper . A notable result from our model epidemics was the relatively low frequency of transmissions from “early HIV infection” relative to other published estimates [55] . For our standard epidemic runs , ∼10% to 25% of infections took place while the source partner was in “early HIV infection” ( with “early HIV infection defined as either the duration of acute infection or the first year of infection , respectively ) . Further work will clarify whether our low estimates suggest that behavioral or network parameters ( rather than strictly viral dynamics , as included in our model ) are the likely source of the high contribution of early HIV infection to onward transmission that is reported elsewhere . An additional possible cause of the high reported frequencies of transmission in early HIV infection are viral genetic factors associated with increased transmissibility in early infection [56]–[59]; our model does not provide viruses with stage-specific transmission probabilities . We plan to extend our model and analysis by comparing virulence trends among populations with more complex sexual mixing patterns , and among populations with varying sample fractions at different stages of an ART treatment cascade . We hope this epidemic modeling approach based on viral dynamics will be a useful tool in the prediction or evaluation of potential outcomes of prevention programs . | Virulence can be defined as disease severity; virulence of a pathogen may evolve as the rates of host mortality and transmission are balanced . HIV virulence trends are estimated using set point viral load , a proxy for the rate of HIV disease progression . To assess the capacity for HIV virulence to evolve and to place published virulence trends in an evolutionary context , we developed an evolutionary model based on HIV viral load dynamics . Our model reveals that HIV virulence evolves to an optimal set point ( ∼4 . 75 log10 copies/mL ) similar to levels seen in natural populations . In comparing published trends to model-based trends , we infer: a ) published trends are consistent with HIV adaptation to the human population; and b ) variation among published trends may be explained by epidemic context or by sampling biases resulting from improvements in HIV screening and diagnosis . We also assess trends in HIV community viral load , defined as the mean viral load of all reported viral loads in a community , and thought to reflect a population's transmission potential . We find that community viral load evolves in association with set point , in the absence of prevention programs like antiretroviral therapy , and does not necessarily predict HIV incidence . | [
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... | 2014 | An HIV Epidemic Model Based on Viral Load Dynamics: Value in Assessing Empirical Trends in HIV Virulence and Community Viral Load |
Chickens , pigs , and cattle are key reservoirs of Salmonella enterica , a foodborne pathogen of worldwide importance . Though a decade has elapsed since publication of the first Salmonella genome , thousands of genes remain of hypothetical or unknown function , and the basis of colonization of reservoir hosts is ill-defined . Moreover , previous surveys of the role of Salmonella genes in vivo have focused on systemic virulence in murine typhoid models , and the genetic basis of intestinal persistence and thus zoonotic transmission have received little study . We therefore screened pools of random insertion mutants of S . enterica serovar Typhimurium in chickens , pigs , and cattle by transposon-directed insertion-site sequencing ( TraDIS ) . The identity and relative fitness in each host of 7 , 702 mutants was simultaneously assigned by massively parallel sequencing of transposon-flanking regions . Phenotypes were assigned to 2 , 715 different genes , providing a phenotype–genotype map of unprecedented resolution . The data are self-consistent in that multiple independent mutations in a given gene or pathway were observed to exert a similar fitness cost . Phenotypes were further validated by screening defined null mutants in chickens . Our data indicate that a core set of genes is required for infection of all three host species , and smaller sets of genes may mediate persistence in specific hosts . By assigning roles to thousands of Salmonella genes in key reservoir hosts , our data facilitate systems approaches to understand pathogenesis and the rational design of novel cross-protective vaccines and inhibitors . Moreover , by simultaneously assigning the genotype and phenotype of over 90% of mutants screened in complex pools , our data establish TraDIS as a powerful tool to apply rich functional annotation to microbial genomes with minimal animal use .
Salmonella enterica is a facultative intracellular pathogen of worldwide importance , associated with c . 21 . 7 million cases of systemic typhoid fever and 93 . 8 million cases of non-typhoidal gastroenteritis in humans each year [1] , [2] . Around 86% of human cases of non-typhoidal salmonellosis are the result of food-borne infections [2] , and chickens , pigs and cattle are key reservoirs of infection [3] . The major S . enterica subspecies enterica encompasses a wide variety of serovars . Some of these , such as S . Typhimurium and S . Enteritidis , exhibit a wide host range , whereas others such as S . Typhi are largely restricted to a single host species . The molecular basis of the host- and tissue-tropism of S . enterica has long eluded researchers and there has been a disproportionate emphasis on the basis of Salmonella persistence and pathogenesis in murine models of colitis and typhoid fever . Comparative analyses of whole genome sequences have associated host-restriction of S . enterica serovars with gene decay . Interpretation of the impact of variation in the repertoire , sequence or expression of S . enterica genes requires an understanding of the roles of those genes in relevant hosts . Random transposon insertion mutants have been screened individually in chickens [4] , but high-throughput simultaneous analysis of mutant phenotypes was made possible by the advent of signature-tagged mutagenesis ( STM ) [5] . STM allows the survival of individual mutants within a pool to be assessed qualitatively through hybridization of a probe to a unique tag sequence within the transposon . Comparison of hybridization signals obtained from “input pools” of mutants grown in vitro with the those obtained from the same set of mutants screened for survival in a model of infection ( “output pool” ) allows attenuated mutants to be identified . The insertion sites can then be identified by subcloning and sequencing . Analysis of pools of signature-tagged S . Typhimurium mutants in mice [5] led to the discovery of Salmonella Pathogenicity Island ( SPI ) -2 [6] , a gene cluster that encodes a type III secretion system ( T3SS-2 ) that acts as a molecular syringe for the secretion of effector molecules and influences systemic virulence and intracellular survival [7] . A distinct T3SS , encoded by SPI-1 , was already known to be essential for infection of mice via the oral route [8] . Subsequently , STM libraries constructed in a range of Salmonella serovars were examined for their ability to colonize multiple hosts [9]–[14] . Comparative analysis of a library of 1045 mutants in chickens , pigs and calves suggested that S . Typhimurium deploys both conserved- and host-specific virulence factors [10] , [12] . Notably , SPI-1 and -2 were vital in intestinal colonization of calves and pigs and to a lesser extent chickens [10] , [12] , yet a Type I protein secretion system encoded by SPI-4 appeared to influence infection of calves , but not chickens [12] or pigs [10] . Although STM has provided valuable insights into Salmonella pathogenesis , the technique is limited by the number of unique tags available , and the time and effort required to construct the library and identify attenuating mutations . Moreover , only negatively-selected mutants tend to be investigated and subjective judgments are used to compare signal intensities relative to the input and to other screened mutants . Transposon-directed insertion-site sequencing ( TraDIS ) [15] , one of a new generation of STM-like techniques , addresses some of these limitations . TraDIS exploits Illumina sequencing [16] to obtain the sequence of the genomic region flanking each transposon . The massively parallel nature of the sequencing permits comparison of the number of specific reads derived from the input pools and the output pools after animal infection , providing a numerical measure of the extent to which mutants were negatively- or positively-selected during colonization ( see Figure 1 ) . TraDIS-like sequencing methods have been used to identify the essential gene complement of S . Typhi [15] and Streptococcus pneumoniae [17] , genes involved in virulence of Haemophilus influenzae [18] and S . pneumoniae [19] in mice , and genes required for survival of the symbiont Bacteroides thetaiotaomicron in the murine gut [20] . Here we apply TraDIS to simultaneously assign the genotype and relative fitness of 7702 distinct S . Typhimurium mutants during intestinal colonization of chickens , pigs and cattle , providing highly relevant data for the control of zoonotic and animal salmonellosis .
To validate the quantitative nature of TraDIS , we applied it to investigate pools of Mu and mini-Tn5 mutants of S . Typhimurium strain SL1344 before and after intravenous infection of BALB/c mice ( see Text S1 ) . These mutant pools had been characterized previously using transposon-mediated differential hybridization ( TMDH ) [21] , a microarray-based method that relies on hybridization of run-off transcripts arising from transposon-encoded T7 and SP6 promoters to high-density oligonucleotide arrays . In total , using TraDIS , 9792 distinct transposon insertions ( 4992 Mu and 4800 Tn5 ) were unambiguously mapped at the level of the single nucleotide to the SL1344 genome , providing relative fitness scores for 94 . 4% of the 10368 mutants screened , This is likely to be an underestimate of the performance of TraDIS , since it is likely that there were siblings of mutants with mapped insertions within the pool of 10368 mutants . The fitness scores assigned by TraDIS are defined as the log2-fold change in the number of sequence reads obtained across the boundaries of each transposon insertion between the input and output pools ( see Materials and Methods ) , and were significantly correlated with the existing TMDH data ( Figure S1; P<2 . 2×10−16 ) , verifying the quantitative nature of TraDIS . TraDIS allowed identification of a number of mutants missed by TMDH ( see Text S1 ) , and provided finer mapping of insertion sites than can be achieved by hybridization of transposon-flanking sequences to tiling arrays , extending the conclusions of the earlier study and demonstrating the superiority of the TraDIS approach . Though useful , previous attempts to assign comprehensively the role of S . Typhimurium genes relied on parenteral infection of atypically susceptible mice [21]–[23] , and do not reflect the roles of Salmonella genes during intestinal colonization of food-producing animals infected via the natural oral route . To identify genes relevant to colonization of animal reservoirs and therefore zoonosis , we generated a library of 8550 mini-Tn5 mutants of S . Typhimurium strain ST4/74 and applied TraDIS to assess the survival of these mutants during oral infection of chickens , pigs and calves . Pools of 475 mutants were screened in individual pigs and calves and pools of 95 mutants were screened in duplicate chickens . Pilot studies in which selected pools had been repeatedly screened in each species indicated the reliable negative selection of the same mutants at these pool complexities in the absence of stochastic loss that may be due to population bottlenecks ( data not shown ) . TraDIS mapped 7702 distinct insertions to the nucleotide level , representing at least 90 . 1% of the mutants screened , and demonstrated the random distribution of the transposon insertions around the genome ( see Figure 2 ) , which disrupt 2715 different genes . TraDIS analysis revealed evidence of random drop-out of mutants from the pools in one chicken , two pig and two calf experiments , likely owing to recovery of output pools of an inadequate size , and data from these animals were omitted from subsequent analysis ( see Text S1 ) . TraDIS assignments of the insertion sites and fitness scores of mutants are listed in Table S1 ( BALB/c mice dosed intravenously ) and Table S2 ( chickens , pigs and calves dosed orally ) . The raw TraDIS sequence data are available from the NCBI Short Read Archive ( accession numbers ERA000172 and ERP000286 ) . To facilitate exploration of the TraDIS data , a user-friendly online genome browser was constructed with which the insertion site and fitness score can be viewed in the context of the linear genome , GC content , transcription start sites and existing annotation ( http://www-tradis . vet . cam . ac . uk ) . Figure 3 shows the fitness scores obtained by TraDIS analysis of S . Typhimurium mutants screened in mice , chickens , pigs and calves , plotted against read coverage ( equivalent to the “M/A” plots commonly used to display microarray data ) . The proportion of significantly attenuated mutants identified during intestinal colonization of food-producing animals was greater than in the murine typhoid model . In each host , a large proportion of mutations did not exert a strong negative or positive effect , indicating that a high number of accessory or redundant functions exist . P values were estimated using the available biological replicates ( all pools were screened in duplicate in chickens , 2 pools were screened in duplicate calves and 3 pools were screened in triplicate pigs ) , and attenuated mutants were defined as those with a negative fitness score and P≤0 . 05 . To summarize the dataset further , genes were scored as potentially important in colonization if they were disrupted in at least one significantly attenuated mutant in any of the four host species . This enables comparisons between datasets derived from different transposon libraries ( such as the mouse and chicken/pig/cattle datasets ) , and visualization of the data in comparison with other genome-wide datasets . For some genes , insertions at different subgenic locations can have divergent effects on the encoded protein resulting in contrasting fitness scores , so it is important to consider the genetic context of each individual transposon when interpreting the TraDIS data in detail . This is true for all transposon-based mutant screens , although earlier technologies such as STM and TMDH lacked sufficient resolution to permit such considerations . We recommend the use of the TraDIS browser ( http://www-tradis . vet . cam . ac . uk ) to assist interpretation of our data in the context of the genome annotation . Fitness scores were obtained for 3194 distinct genes disrupted by transposon insertions in the mouse screen , and 2715 genes in the chicken , pig and calf screens , of which fitness score existed for 2435 genes in all three food-producing animals . Fitness scores were available from all four hosts for 1935 genes , of which 1069 had a significantly attenuated mutant in at least one host . Venn diagrams showing the numbers of significantly attenuated mutants , and the numbers of genes potentially important for colonization in chickens , pigs and cattle are shown in Figure 4 . A further Venn diagram , combining the chicken/pig/cattle and mouse datasets , is available in Figure S2 , and Figure S3 shows a comparison between the chicken , pig and cattle TraDIS data , and the data obtained from equivalent mutants in the earlier STM screens [10] , [12] . A table of all genes disrupted by a transposon insertion , indicating if any of the mutants in each gene was significantly attenuated , is available in Table S3 . To facilitate exploration of the TraDIS data , custom files have been prepared that allow proteins in KEGG metabolic pathway diagrams [24] to be coloured blue if an attenuated mutant was found in the encoding gene , or red if the gene was mutated but no significant attenuation was observed . The KEGG colour files are available from http://www-tradis . vet . cam . ac . uk . As an example , Figure S4 shows the effect of mutations affecting multiple steps in chorismate biosynthesis , which is known to influence persistence of S . Typhimurium in vivo . It is evident that mutations affecting sequential steps in the pathway are attenuating , with just two exceptions: the initial condensation of D-erythrose-4-phosphate and phosphoenolpyruvate into 3-deoxy-D-arabino-heptulosonate-7-phosphate , and the conversion of shikimate to shikimate-3-phosphate , both of which can be catalyzed by the products of multiple genes ( aroFGH and aroKL , respectively ) . Thus , TraDIS identifies pathways in which defects exert a common effect , but also reveals steps at which functional redundancy exists . During the analysis of the TraDIS data it became clear that many regions of the genome with low GC content are important for intestinal colonization of chickens , pigs and cattle ( see Text S1 and Figure S5 ) . Twelve genes were selected for further investigation based on the TraDIS data: carB , clpB , ilvC , mig-14 , pagN , SL1344_0084 ( STM0084 ) , SL1344_4248 ( STM4312 ) , SL1344_3128 ( STM3154 ) , trxA , virK , ytfL and zirT ( SL1344_1599 ) . These targets were chosen based on their fitness scores ( at least one mutant in each gene shows significant attenuation ) , and to include some genes with established roles in colonization in chickens ( clpB [4] ) or mice ( trxA [25] , mig-14 [26] , virK [27] ) , genes with a postulated role in colonization ( pagN [28] , SL1344_0084 [12] ) , the mouse anti-virulence factor zirT [29] , genes demonstrating variable fitness scores ( SL1344_0084 , SL1344_3128 and ytfL ) and genes that demonstrate putative host-specific effects on colonization in the TraDIS data ( clpB , ilvC and ytfL ) . Each gene was inactivated separately by λRed recombinase-mediated integration of linear PCR amplicons by homologous recombination [30] . Mutant phenotypes were evaluated in groups of 3 chickens per mutant per time interval . For each mutant , competitive indices ( CIs ) were derived 4 , 6 and 10 days post-inoculation of age-matched chickens with the kanR-tagged mutant and ST4/74 nalR wild-type strain in a 1∶1 ratio ( see Table 1 ) . With a single exception ( SL1344_3128 ) all mutants were negatively-selected relative to the parent strain at day 4 post-inoculation , which corresponds to the time at which mutants were recovered for the TraDIS analysis . The difference in the mutant∶wild-type ratio was significantly different from the ratio in the inocula for 8 of the mutants at day 4 . For a further 2 mutants , significant differences were detected at later time points . Taken together with comparisons to existing datasets for signature-tagged mutants of the same strain in the same animal models [10] , [12] ( see Text S1 ) , the data strongly support evidence of attenuation detected by TraDIS . Variance from TraDIS fitness scores is likely to reflect differences in competition dynamics for a given mutant relative to co-screened wild-type or mutant bacteria . For one gene ( SL1344_3128 ) , no evidence was found of any attenuation of the defined mutant , which performed comparably to the wild-type at all time intervals . This gene was chosen for further investigation because its mutants exhibited a wide range of TraDIS fitness scores ( −1 . 02 to −9 . 20 ) . Interestingly , mutants in the gene cluster SL1344_3128-30 are predicted to be deficient in swarming motility [31] , suggesting the possibility that such motility may be an occasional but not universal requirement for colonization .
The TraDIS dataset is a powerful resource for understanding intestinal colonization of a range of highly relevant hosts by Salmonella , and thus zoonotic transmission and animal disease . The data suggest that the definition of what constitutes a colonization gene is not straightforward , encompassing genes involved in metabolism , stress responses and transcriptional regulation , together with genes with well-established roles in virulence . The T3SSs encoded by SPI-1 and SPI-2 are both essential for infection in chickens , pigs and cattle , although there are some mutants within both regions that are not attenuated or exhibit a less pronounced phenotype in chickens . T3SSs allow the secretion of effector molecules into the host cytoplasm , these effectors being encoded both within SPI-1 and 2 and distally . Most of the known effector genes , including sopA , sopB , sopE2 , sipA , avrA , sipC , sseG , sseI , sifA , sseK1 , pipB2 and sopD2 , were identified by TraDIS as being important for infection of all three food-producing animals , although as with the T3SS structural genes , the phenotype was often less pronounced in chickens . Other T3SS effectors , including sptP , slrP , gogB and sspH2 , could be disrupted without affecting colonization . Of these , slrP has been implicated as a host-specificity factor , essential for oral infection of mice but not required for calf infection [14] . Null mutants of sptP are not impaired in their interactions with cultured macrophages or epithelial cells [32]–[34] , and sspH2 mutants do not show any defect in vacuole-associated actin polymerization [35] . For both sptP and sspH2 , the lack of phenotype was suggested to be due to functional redundancy amongst T3SS effectors . There are also attenuated mutants that harbour insertions within the other recognized Salmonella pathogenicity islands [36] . In SPI-3 , mutants in some genes ( mgtC , marT , SL1344_3717 and SL1344_3721 ) were attenuated , with others ( misL , sugR , slsA and mgtB ) showing no attenuation . Interestingly , marT , which encodes a transcriptional regulator , is a pseudogene in S . Typhi , and restoring it reduces survival during infection of a human cell culture [37] . A role for marT in infection of chickens , pigs and cattle suggests a selection pressure for its retention in the S . Typhimurium genome . SPI-4 was previously thought to play a role in infection of cattle but not chickens or pigs , based on STM screens [10] , [12] . TraDIS suggests a role for SPI-4 in all three species , although the phenotypes in chickens and pigs are more subtle than in calves , highlighting the increased sensitivity of TraDIS relative to STM . Some transposon insertions within the central highly repetitive region of siiE are tolerated in chickens and pigs , but are attenuated in cattle . Interestingly , siiE is split into two ORFs in both S . Typhi genome sequences , and part of the repetitive central region is absent from the genome of S . Paratyphi A . SiiE is secreted [38] , indicating that in trans complementation by co-screened mutants does not obscure the identification of secreted colonization factors by TraDIS . All of the genes of the enteritis-associated SPI-5 that were disrupted by a transposon ( pipACD , sopB and orfX ) were required in all three species , although often with a milder phenotype in chickens . Several clusters of attenuated mutants were also found in the Salmonella chromosomal island ( SCI , also known as SPI-6 in S . Typhi ) , including mutants in the hypothetical genes sciJ , sciQ , SL1344_0286A and sciX , the fimbrial subunit safA and its chaperone safB , the regulator sinR , SL1344_0301 ( STM0305 ) which encodes a putative cytoplasmic protein , the pagN adhesin ( STM0306 ) and sciZ ( STM0307 ) , a homologue of Shigella virG . Deletion of SCI affects invasion and virulence in a mouse intraperitoneal infection model [39] , and the phenotype of a defined safA mutant has been confirmed in pigs [10] . Fimbriae play a well-established role in Salmonella attachment and intestinal colonization [40] . All twelve fimbrial operons were disrupted by multiple transposons in the TraDIS screen . No obvious host-specific phenotypes were seen , with a common pattern that mutants of fimbrial subunit genes were attenuated , whereas assembly genes were often dispensable , suggesting cross-talk in the assembly pathways . Stress responses are also important in the infection process , as Salmonella is subjected to a range of stresses including low pH , oxidative stress and heat shock [41] . The genetic components of these stress responses overlap [42] , and many of these genes harboured transposons that resulted in attenuation . These included the sigma factor gene rpoE and its anti-sigma factor resA , the heat shock chaperone genes dnaK and dnaJ and the heat shock protease gene degP ( htrA ) . Interestingly , several stress response genes are variably attenuated in the different hosts , suggesting species-specific stresses . These include the two-component regulatory system genes envZ and ompR , and the oxidative stress response genes dps , katE and proV which are all attenuated in pigs and cattle but show little or no attenuation in chickens . Conversely , transposon mutants in clpB , clpP and clpX , which encode proteases and are involved in the regulation of rpoS , are attenuated in chickens but not pigs or cattle . Many S . Typhimurium genes beyond the classical virulence factors and stress response genes were revealed to be important for oral infection of livestock species . These include genes involved in nucleotide metabolism ( pyrCD , purADGH , dgt , dcd , guaA , pyrCD and carAB ) , aromatic amino acid biosynthesis ( aroABCDE ) , inorganic ion transport ( trkAH , znuABC , fepCDG ) , protein synthesis ( tufAB , fusA , efp , rplI , rpsK ) , protein export ( tatABC , yajC ) and many genes involved in carbohydrate metabolism . Additionally , numerous low GC clusters of genes with putative metabolic functions and multiple attenuating mutations were identified . Several global regulators , including crp , smpB and dam , result in attenuation in all three hosts , whereas another , fnr , appeared only to be important for infection in chickens . On occasion , TraDIS revealed functional data at a sub-genic level . For example , most of the insertions that disrupt the SPI-1 gene sptP result in attenuation , but insertions close to the 3′ end of the gene are tolerated . The gene rpoC , which encodes the β′ subunit of RNA polymerase , is essential in S . Typhimurium [43] . However , one transposon insertion in the chicken , pig and cattle dataset , and two in the mouse dataset , were identified close to the 3′ end of rpoC . These insertions would disrupt the extreme C-terminal end of the encoded protein , and were found to reduce the fitness of the mutants in the animal screens . Similarly , an insertion was found at the 3′ end of the essential polA gene which encodes DNA polymerase I , and this mutant was significantly attenuated in chickens , pigs and cattle . The recent RNAseq-based analysis of the S . Typhimurium SL1344 transcriptome [44] identified a number of small-regulatory RNAs . As indicated in Table S4 several of these were implicated in colonization by TraDIS . For many it is difficult to demonstrate conclusively a colonization-associated phenotype from the TraDIS data alone , since we cannot preclude the potential for polar effects on adjacent genes . This is the case for InvR , which is encoded within SPI-1 . Table S4 details only the sRNA genes annotated in the SL1344 genome ( which differs from ST4/74 by just 8 SNPs [45] ) , but in the TraDIS data there are a number of attenuating transposons within large intergenic regions that could reveal the presence of novel sRNA genes . The chicken , pig and cattle TraDIS data presented in Figure 4 indicate that a shared core set of 611 genes is required for efficient colonization of all three species , with a smaller set of species-specific colonization factors . The core set comprises approximately two thirds of the genetic requirements for infection of each individual species , and 48% of the total set of colonization-associated genes . There are 259 genes which are required for systemic infection of mice for which comparable data are available from the food-producing animals ( Figure 4 ) ; of these , 140 also contribute to oral infection of chickens , pigs and cattle , and only 43 are putative mouse-specific factors . Many of the differences between the mouse and chicken/pig/cattle datasets may arise from the additional genetic requirements for infection via the oral route . Although most colonization factors were necessary for infection of chickens , pigs and cattle , there were some patterns amongst the colonization factors that appeared to function in a host-specific manner that may reflect underlying differences in host biology . There are many genes associated with flagellar motility that are essential for infection of pigs but not required for chicken or calf infection , including fliY , flgK , fliN , flgN , fliB and fliZ . Several other flagellum-associated genes ( flgB , flgL , fliL ) are required for infection of cattle but not chickens or pigs . In chickens , many genes that are involved in anaerobic growth are required; these include genes involved in the production of group I hydrogenase ( hypOBF , hybABCDF ) , fumarate reductase ( frdAD ) , pflB , pfkA , rNTP reductase ( nrdDG ) and the global regulator Fnr . Differences in oxygen tension proximal to villus tips have been detected that modulate the regulation of Shigella virulence genes [46] , therefore the requirement for distinct respiratory pathways by S . Typhimurium in food animals may reflect differences in the niches occupied . Also required in chickens , but apparently not calves or pigs , are the virK homologue ybjX , ilvGE , clpB and the his operon . The observation that many of the host-specific phenotypes were observed independently in multiple genes affecting the same pathways strongly suggests that these effects are due to differences in the within-host environment . For example , in relation to fumarate reductase there were nine independent frdA mutants that were all significantly attenuated in chickens; of these only one showed significant attenuation in pigs , and none in calves . Similarly , in relation to group I hydrogenase , from a total of 15 mutations affecting the hybABCDF genes , 12 showed significant attenuation in chickens , but none in pigs or calves ( Table S2 ) . The serovar Typhimurium strain ST4/74 investigated here is a natural bovine isolate that elicits pathology typical of clinical salmonellosis in all the host species used in this study . However , some atypical S . Typhimurium strains exist that have lost the capability to colonize a broad range of hosts . For example , the laboratory-adapted strain LT2 and its derivatives tend to be avirulent or less virulent in mice relative to natural isolates of serovar Typhimurium [47] and ST4/74-based strains . It is noteworthy that the rpoS gene encoding the sigma factor σS , which is defective in LT2 and associated with the relative avirulence of this strain [48] , was found to be required in all four species tested by screening of the S . Typhimurium libraries we describe ( Table S3 ) . TraDIS identified additional regions of the ST4/74 genome that are required for infection , but which are absent from the LT2 genome . These include several genes that are encoded within the same phage element: SL1344_1965 , which is required for infection of mice , and SL1344_1929/30 and SL1344_1976 , which are required for infection of chickens , pigs and cattle . Moreover , some Typhimurium strains have become adapted to a particular host , and the genome sequence of a human-adapted variant [49] reveals the decay of a number of genes important in colonization of food animals ( e . g . allP , sseI , pipD , ydeE ) , but also other pseudogenes for which no role in food animals for the intact gene could be detected ( e . g . ratB , ygbE , yhjU ) . Integration of genome sequences with high-resolution functional data of the kind we describe will provide further clues to explain the differential virulence of host-adapted or laboratory strains relative to natural isolates . Our study represents the first comprehensive genome-wide survey of the role of thousands of Salmonella genes during colonization of the primary reservoirs of human non-typhoidal salmonellosis . TraDIS simultaneously assigned the genotype and relative fitness of 7702 distinct S . Typhimurium insertion mutants in chickens , pigs and cattle , representing over 90% of the mutants screened in pools of up to 475 mutants per animal . TraDIS therefore represents a significant advance in the reduction , refinement and replacement of animal models relative to STM , where only negatively-selected mutants tend to be interrogated and the vast majority of insertion sites and phenotypes are unreported [50] . Multiple lines of evidence suggest that the TraDIS data are robust and reliably reflect the fitness of the screened mutants in each host animal . Many of the attenuated mutants were found to harbour transposons in genes known to be involved in colonization . The TraDIS fitness scores correlated well with established datasets obtained using STM [10] , [12] and TMDH [21] . Multiple mutations within the same gene or pathway usually gave comparable phenotypes , and most of the attenuated mutants demonstrated the same phenotype independently in the three different food-producing animal hosts . The examples of putatively host-specific attenuation tended to be restricted to particular pathways with multiple independent mutations . Finally , analysis of defined knockout mutants of targets chosen based on the TraDIS data reproduced attenuated phenotypes in all but one case . Many novel colonization-associated genes were identified within the S . Typhimurium genome and the data provide an invaluable resource for the community to mine and extend . Moreover , TraDIS indicated that thousands of mutations exerted little or no effect in vivo , implying functional redundancy that may limit and refine the selection of targets for novel inhibitors , as previously suggested [51] . Unlike library screens conducted in murine typhoid models to date , we provide highly relevant data for control of intestinal S . enterica infections in food-producing animals , and thus zoonosis . Attenuating mutations may be suitable for selection and refinement of live vaccines for food-animals , and these in turn may express heterologous antigens . Further , the data will guide the interpretation of existing and fast emerging datasets on the repertoire , sequence and expression of Salmonella genes and aid the modelling of virulence in a wider evolutionary and ecological context . Our data reflect mutant phenotypes at a specific time and site , and further studies on the temporal and spatial role of Salmonella genes are likely to be informative . This study also establishes TraDIS as a quantitative technology in functional genomics , which has potential for widespread application beyond the realm of microbial pathogenicity .
Animal experiments were conducted according to the requirements of the Animals ( Scientific Procedures ) Act 1986 ( project license number 30/2485 ) with the approval of the local Ethical Review Committee . For full details of experimental animals , bacterial strains , materials , molecular biological techniques and statistical methods see Text S1 . Briefly , a library of 8550 mini-Tn5 mutants was generated in a spontaneous nalidixic acid resistant variant of S . Typhimurium ST4/74 . The mutants were combined into pools of 95 for chickens , and 475 for pigs and calves . Animals were inoculated orally and killed humanely 4 days ( chickens and calves ) or 3 days ( pigs ) after infection , or earlier if the clinical endpoint was reached . A section of an appropriate tissue ( whole caeca for chickens , spiral colonic mucosa for pigs and distal ileal mucosa for calves ) was homogenized and grown overnight on MacConkey agar plates to isolate the output bacteria . Genomic DNA was prepared from the inocula and output samples , and fragmented to ∼300 bp . An Illumina adapter was ligated to the fragments , and PCRs were performed using an adapter-specific primer in conjunction with primers homologous to each end of the transposon . The sequences of all oligonucleotide primers used in this study are detailed in Table S5 . The resultant products were sequenced on single end Illumina flowcells using a sequencing primer designed to read a 10 bp tag of transposon-derived sequence , plus 27 bp of flanking genomic DNA . Sequences containing the tag were mapped to the S . Typhimurium SL1344 genome sequence . A transposon was inferred to be present if there were corresponding reads derived from each end of the transposon in the input pool . The number of reads corresponding to each transposon in the input pool , and the number of reads mapping to the equivalent position in the output pool data , were compared using DESeq [52] . The ratio of input∶output read counts was determined , after normalisation to account for variations in the total number of reads obtained for each sample , and expressed as log2 ( fold change ) , referred to as the fitness score . A negative fitness score indicates an attenuated mutant , a positive score indicates a mutant which was more abundant in the output pool than in the input . For strongly attenuated mutants , no reads were obtained in the output pool , so it was not possible to calculate a finite log2 ( fold change ) ; such mutants were assigned an arbitrary fitness score of −15 . For each individual mutant , the hypothesis that the fitness score was equal to zero ( i . e . that the mutant was present at equivalent levels in the input and output pools ) was tested using the negative binomial distribution as implemented in DESeq . DESeq models variance under the assumption that mutants with comparable levels of sequence coverage exhibit similar levels of dispersion . We exploited this model to estimate P values for all mutants whilst minimising the number of biological replicates by fitting using only those mutants for which replicate data points were available , and applying the resultant model to the data derived from all mutants . Defined null mutants were obtained for twelve genes identified as attenuated in the TraDIS screen , and assessed in competition with wild-type ST4/74 during oral infection of chickens . The ratios of mutant∶wild-type bacteria from caecal isolates at day 4 , 6 and 10 were compared with those in the inoculum , and the significance of any differences was tested using Student's t-test . | Salmonella Typhimurium is a major cause of human diarrhoeal infections , usually acquired from chickens , pigs , cattle , or their products . To understand the basis of persistence and pathogenesis in these reservoir hosts , and to inform the design of novel vaccines and treatments , we generated a library of 7 , 702 S . Typhimurium mutants , each bearing an insertion at a random position in the genome . Using DNA sequencing , we identified the disrupted gene in each mutant and determined its relative abundance in a laboratory culture and after experimental infection of mice , chickens , pigs , and cattle . The method allowed large numbers of mutants to be investigated simultaneously , drastically reducing the number of animals required to perform a comprehensive screen . We identified mutants that grow in culture but do not survive in one or more of the animals . The genes disrupted in these mutants are inferred to be important for the infection process . Most of these genes were required in all three food-producing animals , but smaller subsets of genes may mediate persistence in a specific host species . The data provide the most comprehensive map of virulence-associated genes for any bacterial pathogen in natural hosts and are highly relevant for the design of control strategies . | [
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"agriculture",
"... | 2013 | Comprehensive Assignment of Roles for Salmonella Typhimurium Genes in Intestinal Colonization of Food-Producing Animals |
Humans infected with yellow fever virus ( YFV ) , a mosquito-borne flavivirus , can develop illness ranging from a mild febrile disease to hemorrhagic fever and death . The 17D vaccine strain of YFV was developed in the 1930s , has been used continuously since development and has proven very effective . Genetic differences between vaccine and wild-type viruses are few , yet viral or host mechanisms associated with protection or disease are not fully understood . Over the past 20 years , a number of cases of vaccine-associated disease have been identified following vaccination with 17D; these cases have been correlated with reduced immune status at the time of vaccination . Recently , several studies have evaluated T cell responses to vaccination in both humans and non-human primates , but none have evaluated the response to wild-type virus infection . In the studies described here , monocyte-derived macrophages ( MDM ) and dendritic cells ( MoDC ) from both humans and rhesus macaques were evaluated for their ability to support infection with either wild-type Asibi virus or the 17D vaccine strain and the host cytokine and chemokine response characterized . Human MoDC and MDM were also evaluated for their ability to stimulate CD4+ T cells . It was found that MoDC and MDM supported viral replication and that there were differential cytokine responses to infection with either wild-type or vaccine viruses . Additionally , MoDCs infected with live 17D virus were able to stimulate IFN-γ and IL-2 production in CD4+ T cells , while cells infected with Asibi virus were not . These data demonstrate that wild-type and vaccine YFV stimulate different responses in target antigen presenting cells and that wild-type YFV can inhibit MoDC activation of CD4+ T cells , a critical component in development of protective immunity . These data provide initial , but critical insight into regulatory capabilities of wild-type YFV in development of disease .
Yellow fever virus ( YFV ) , the causative agent of yellow fever ( YF ) , is a mosquito-borne flavivirus . YFV infection in humans can range from a sub-clinical infection to severe hemorrhagic fever and death . The currently available live-attenuated YFV vaccine , 17D , was developed in 1937 and over 500 million doses have been delivered . Vaccination with the 17D vaccine provides long-term protective immunity ( at least 10 years ) with a single immunization . Despite the existence of the 17D vaccine , YFV remains a significant human health concern . In fact , outbreaks of YF continue to occur in Africa and South America with an estimate of 130 , 000 cases per year in Africa alone with a case fatality rate of 60% in 2013[1] . While 17D is considered a safe and efficacious vaccine , over the past 20 years it has become increasingly apparent that occasional cases of vaccine-associated YF occur [2] . In cases of vaccine-associated disease from which virus was recovered , sequencing of the viral genome revealed it to be the vaccine strain 17D with no evidence of reversion to wild-type virus [3] . In some cases of vaccine-associated YF , there was evidence of underlying health issues potentially causing impaired immune status , particularly thymic disorders [3–5] . However , demonstration that co-morbidities contribute directly to development of disease is lacking . Given the apparent association of thymic disorders and impaired T cell immunity with vaccine-associated YF , the past several years have seen extensive efforts toward understanding the role of the T cell response following vaccination against YFV . These studies have largely focused on changes in T cell populations in vaccinated individuals and honing in on the criticality of the CD8+ T cell response following vaccination or infection of animals with the 17D vaccine strain [6–13] . Furthermore , evidence suggests limited B cell and CD8+ T cell responses may decrease vaccine efficiency in certain African populations [14] . Although fewer studies have focused on the CD4+ T cell response , CD4+ T cells play a critical role in development of a protective anti-YFV response and long-term immunological memory [15] . The few studies that are published have focused almost exclusively on the immune response to vaccination and not on the response to wild-type virus infection . Identification of differences between wild-type and vaccine virus infections is critical toward understanding mechanisms that viruses use to modulate the host immune response . In previous studies we found that wild-type YFV and live-attenuated 17D YFV elicited different responses in human hepatocytes and Kupffer cells . These studies demonstrated that infection with 17D YFV led to limited virus propagation and an immune response that would be indicative of rapid viral clearance and immune protection . On the other hand , the response to wild-type YFV infection was pronounced suggesting a “cytokine storm” that may be a critical component of the disease process [16 , 17] . In the work presented here , we continued our investigation into the ability of YFV to regulate the host response to infection . Here , we asked whether carefully defined and highly purified subtypes of either human or rhesus macaque mature monocyte-derived dendritic cells ( MoDC ) or macrophages ( MDM ) were susceptible to infection with either the wild-type ( Asibi ) or vaccine ( 17D ) strains of YFV . To determine if there were specific responses that differed between Asibi and 17D YFV infected cells , we measured cytokine secretion following in vitro viral infection . In addition , we evaluated the ability of infected human antigen presenting cells ( APC ) to stimulate CD4+ T cells in an effort to determine if YFV infection limited activation of cell-mediated immunity . We found that MoDC and MDM were susceptible to infection with either Asibi YFV or 17D YFV and that the kinetics of infection were consistent between human and non-human primate ( NHP ) derived cells . Interestingly , propagation of Asibi YFV was delayed in both MoDC and MDM relative to 17D YFV with kinetics suggesting decreased attachment efficiency . We also found that the cytokine response in human and NHP MoDCs was very limited , yet human DCs infected with 17D virus were effective at activating CD4+ T cells . Conversely , infection of human and NHP MDM stimulated a moderate cytokine response , but infected human MDM did not stimulate CD4+ T cells . These data demonstrate a central but differential role for DCs and macrophages as APC during Asibi virus infection and suggest that YFV inhibits intracellular response mechanisms that lead to activation of CD4+ T cells .
Many studies evaluating the response and role of APCs in virus infection rely upon poorly defined or mixed populations of cells . A primary objective of our studies was to generate pure phenotypically homogeneous APCs . Confirmation of purity and viability was assessed by flow cytometric phenotyping . Our isolation and maturation protocols worked consistently for both human and NHP-derived cells with minimal inter-experimental variability . Characterization of human and NHP MDM showed that they were CD11b+ , CD11c+ , CD14+ , CD86+ , CD163+ , CD206+ , HLA-DR+ , and CD83- ( Fig 1 ) . Human and NHP MoDCs were CD11c+ , CD80+ , CD83+ , CD86+ , HLA-DR+ and CD14- ( Fig 1 ) . Preliminary studies were completed to determine the susceptibility of immature NHP DC ( imDC ) and human bulk PBMC to infection with YFV 17D . Immature DCs supported replication in a manner similar to that seen in mature MoDCs while bulk PBMCs did not support YFV 17D infection and replication ( S1 Fig ) . Due to challenges ensuring consistent generation of homogeneous populations of imDCs , continuing studies focused on mature cells . In order to determine if YFV could replicate in MDM or MoDCs , cells were infected at a multiplicity of infection ( MOI ) of 0 . 1 and cell culture supernatants were collected immediately after virus adherence ( i . e . 1 hour post-infection [hpi] ) and daily until 7 days post infection ( dpi ) . In MDM derived from both humans and NHP it was found that both wild-type Asibi virus and the vaccine strain 17D virus were able to infect and replicate within MDM based on evidence that viral titers in cells from each donor increased by at least 1 log10 subsequent to infection ( Fig 2 ) . The virus titers determined from supernatants collected at 1 hpi from 17D-infected MDM demonstrated titers in the 2–4 log10 range from all donors except from one NHP where the titer was less than 1 log10 . In each set of donor MDM infected with 17D virus , peak titers ranged between 4–7 log10 1–2 dpi . The kinetic profiles of 17D virus-infected MDM were virtually the same for all NHP donors and while the profiles were similar for human cells , titers in MDM from one human donor were about 2 log10 lower than MDM from other donors . Viral titers from NHP MDM infected with Asibi virus peaked at 3–5 log10 late in the infection cycle with significant donor-to-donor variation in the kinetics . The viral kinetics from human MDM following Asibi virus infection were virtually the same from all donors with a peak titer of around 5 log10 at 3–4 dpi . Interestingly , evidence of residual titer at 1 hpi seen in 17D virus infected MDM was not apparent in Asibi virus infected cells , possibly suggesting enhanced surface adherence of the 17D virus to MDM . In MDM tested from nearly all donors , both human and NHP , increases in viral titer following Asibi virus infection were not evident until at least 2 dpi , and in one instance as late as 5 dpi . These data suggest a restriction on wild-type Asibi virus replication in MDM , particularly those from rhesus macaques . Kinetics studies with YFV-infected MoDCs produced results similar to those seen for YFV-infected MDM ( Fig 2B ) . Both the 17D and Asibi viruses replicated in MoDCs with peak titers in 17D virus-infected NHP MoDCs in the range of 5–7 log10 and 4–8 log10 in human MoDCs . The kinetics in Asibi virus-infected MoDCs were delayed much like what was seen in Asibi virus-infected MDM , with increases in viral titer not typically seen until 2 dpi and as late as 5–6 dpi . Peak titers in both human and NHP MoDCs infected with Asibi virus ranged from 4–6 log10 , regardless of the day of apparent replication onset . As was seen in the MDM studies , there was a relatively high residual virus titer at 1 hpi in 17D virus-infected MoDC from both humans and NHP suggesting that the 17D virus may adhere more tightly to MDM and MoDCs than the Asibi virus . The delayed replication or poor adherence of the Asibi virus in MoDC , as was seen in MDM , also suggests a restriction in wild-type YFV internalization or replication that is not seen in 17D virus-infected cells . To demonstrate that the residual virus was not an artifact , a small-scale study analyzing virus titers before and after a single wash step was performed on human MoDC and MDM from three donors . This study found that a single PBS wash could remove residual YFV Asibi from both MoDC and MDM while residual YFV 17D was around 3 log10 pfu/ml ( S2 Fig ) . The efficiency of viral infection by YFV 17D and YFV Asibi could have a direct impact on subsequent biological processes , including cytokine responses and T cell interactions , as could residual or lightly adhered virus particles not removed by washing of cells . In order to determine if structural differences between YFV 17D and Asibi could impact virus attachment and be responsible for the high residual titers in YFV 17D infected APC , we aligned amino acid sequence data from Beck et al [18] ( Genbank Accession #s KF769016 , KF769015 ) and submitted to the Swiss-Model modeling server ( http://swissmodel . expasy . org/ ) . We then compared the returned structures to previously published YFV NMR data from Volk et al [19] These models demonstrated five amino acid residue differences at the surface of the viral receptor-binding domain ( Envelope protein , domain III ) . These changes are significant as they change the residue size , charge or polarity ( e . g . Phe305Ser or Ser325Pro ) and could directly impact the interaction between the virus and its receptor on the surface of APC ( S3 Fig ) . In order to evaluate the reactivity of APCs to YFV infection and to determine if specific differences existed between the response to Asibi and 17D virus infections , we measured the release of a panel of cytokines and chemokines from virus- or mock-infected cells . In addition , we made specific comparisons between APCs derived from humans and those derived from NHP to identify similarities or differences between the human condition and the best animal model for YFV infection . Many of the cytokines or chemokines that were evaluated demonstrated a negligible change relative to mock-infected cells . Re-stimulation studies were carried out only with human samples due to a limited availability of NHP material . To evaluate the ability of infected MoDC to stimulate CD4+ T cells we infected MoDC with YFV and co-cultured them with autologous CD4+ T cells at a 1:60 ratio of MoDC:T cells . After two weeks of expansion , CD4+ T cells were re-stimulated with freshly YFV-infected MoDC . As a measurement of CD4+ T cell activation following stimulation , intracellular production of IFN-γ and IL-2 was measured by flow cytometry . In order to determine if active MoDC infection was required for CD4+ T cell stimulation , T cells were stimulated once or twice with either live ( L ) or inactivated ( gamma irradiated ) ( dead ) ( D ) YFV ( Fig 7 ) . CD4+ T cells initially co-cultured with MoDC + live YFV 17D demonstrated a significant increase in the percentage of IFN-γ+ T cells compared to unstimulated controls regardless of the re-stimulation conditions used ( Fig 8 ) . However , no significant increase was observed in percentages of either IFN-γ+ IL-2+ double positive or IL-2+ T cells . In contrast , CD4+ T cells initially co-cultured with MoDC + no virus followed by re-stimulation with MoDC + live Asibi ( 7 hours ) resulted in a significant increase in the percentage of IL-2-producing T cells compared to unstimulated controls ( Fig 8 ) . T cells stimulated with MoDC + inactivated YFV ( 17D or Asibi ) did not show significant increases in the percentages of cytokine-producing T cells compared to unstimulated controls . Half of the donors tested in these studies were previously vaccinated with the 17D vaccine . In order to determine if vaccination impacted IFN-γ or IL-2 production by CD4+ T cells , data were analyzed based on vaccination status ( Fig 9 ) . As with the analyses based on virus strain , stimulation with MoDC + inactivated virus had no significant impact on IFN-γ or IL-2 production , while infection with MoDC + live virus resulted in increased percentages of cytokine-producing T cells . Although significant differences relative to unstimulated controls were observed , there were no significant differences in either IFN-γ or IL-2 production between vaccinated and unvaccinated donors . Control , unstimulated , CD4+ T cells retained >95% viability over the course of the study ( Table 1 ) . T cells stimulated with Asibi virus also maintained >95% viability while viability of CD4+ T cells stimulated with the 17D virus was considerably lower with average viabilities of 72–74% . However , T cells initially stimulated with MoDC + inactivated 17D virus had viability >93% which is similar to cells stimulated only once with either live or inactivated virus ( i . e . N+L or N+D ) ( Table 1 ) . These data suggest that stimulation with MoDC infected with replicating YFV 17D has a negative impact on the viability of CD4+ T cells in this co-culture system while stimulation with MoDC infected with wild-type Asibi virus had negligible impact on CD4+ T cell viability . Interestingly , while viability was somewhat lower , CD4+ T cells co-cultured with MoDC + live 17D demonstrated the most pronounced increase in the percentage of cytokine-producing cells compared to unstimulated controls . There were no consistent differences in viability among donors naïve for YFV and those who had previously been vaccinated . Similar studies were carried out using MDM stimulation of CD4+ T cells . In these studies there was no evidence of CD4+ T cell stimulation by APCs treated with either 17D or Asibi viruses ( S4 and S5 Figs ) .
The importance of adaptive immunity following vaccination is well recognized , but in the case of flavivirus infections , the focus on adaptive immunity has largely been toward the development of an antibody response . Historical definitions of protective immunity against flaviviruses have identified a 1:10 neutralizing antibody titer as protective . Over the past few years a greater appreciation of the importance of the cell-mediated response in flavivirus infections has become evident . However , for YFV infection , comparatively little is known about the role of APC and T cells in protection against , or development of , disease . Recently , a number of groups have been evaluating a range of host response parameters in human YFV vaccine trials and found that the human T cell response is significant and appears critical toward development of protective immunity following vaccination . As might be expected , vaccination with the 17D vaccine induced effector CD4+ T cell responses with a peak around 2 weeks post-vaccination then transitioning to a central memory response [15] . Further studies have shown that CD8+ T cells also play a role in the response to vaccination , whether by clearing the vaccine virus or in development of a sustained memory response detectable up to 25 years post-vaccination [10 , 12 , 20] . Clearly the role of T cells in development of a protective response following vaccination is critical , but none of these studies address the potential role of T cells , or inhibition of a T cell response , in an acute wild-type virus infection . The role of APCs in the stimulation of an effective T cell response is critical for the development of protective immunity . Previous work has shown that YFV 17D can replicate in human DCs , does not induce maturation of immature DCs and can stimulate CD4+ and CD8+ T cells [21 , 22] . In the studies described here , we strove to expand upon previous efforts with direct comparisons between infection of APCs with the 17D virus or wild-type YFV . Our objective was to identify specific differences in the response to infection indicative of direct viral regulation of the development of protective immunity . Initial studies were also performed to identify parallels between the response of NHP-derived APC and those derived from humans in an effort to enhance our understanding of the rhesus macaque as a model for YFV infection in humans . Replication kinetics in MDM and MoDC from both human and NHP found that these cells were susceptible to infection with both wild-type Asibi YFV and the vaccine strain 17D . In human MDM and MoDC there was little variability between donors when infected with the 17D virus , but there was considerable variability when infected with the wild-type Asibi virus . Interestingly , in either MoDC or MDM from both humans and NHP , the kinetics profiles were consistent in cells infected with the 17D virus with increased titers at 1 dpi and peak titers 2–3 dpi . In cells infected with Asibi virus , there was frequently a considerable delay in virus replication , on some occasions up to 4–5 dpi before virus titers could be measured . In these studies , the data presented are compilations of several individual experiments performed independently . A single study with three donors also clearly demonstrated that YFV Asibi could easily be washed from the MoDC and MDM . These data suggest a restriction on wild-type YFV replication or efficiency of infection that is not present in 17D virus infected cells . This restriction may be critical to limiting an innate response to virus infection and to provide for efficient virus dissemination . In addition , the restriction identified in these experiments could have a direct impact on the results of these studies as the specific number of virus particles entering the target cells during the 1 hour infection cannot be quantified , but is likely different between YFV 17D and YFV Asibi . Previous studies have shown that potential attachment proteins , such as DC-SIGN and some integrins , do not facilitate virus entry into DCs [21] . The data provided here suggests that differences in virus attachment and entry may be associated with structural or chemical differences between the wild-type and 17D viruses . Glycosylation of the viral envelope protein should be consistent between virus stocks as both were generated in Vero cells . The 17D vaccine strain differs from its parental wild-type strain Asibi by only 32 amino acids in a 3411 amino acid open reading frame with seven occurring in the viral envelope protein , several of which are in the putative receptor-binding domain [18 , 23] . Structural analysis of the YFV E protein domain III demonstrated significant amino acid differences between YFV 17D and Asibi changes that could impact virus attachment and entry . These differences in the amino acid sequence of the receptor-binding domain could potentially impact interactions with receptors on MDM or MoDCs . Recently , Fernandez-Garcia et al have shown that the differential attachment and internalization between YFV 17D and Asibi is due to differences in the endocytic pathway used by the viruses to infect host cells [24] . These studies , which focused on immortalized cell lines and immature MoDC , found that YFV Asibi utilizes a clathrin-mediated endocytic pathway while YFV 17D utilizes a clathrin-independent pathway . Fernandez-Garcia et al suggested that differences in the virus structural proteins could impact the choice entry pathway . Our modeling data suggests that receptor attachment may be the critical factor for determining the virus entry mechanism . Evaluation of the host cytokine and chemokine response suggested activation of MDM by both wild-type Asibi virus and the 17D vaccine strain . Unlike what we previously observed in human Kupffer cells ( resident liver macrophages ) [16] , wild-type YFV did not induce a significant and extended pro-inflammatory response , but rather both viruses induced a response that was broadly antiviral , with increases in IFNα and TNFα . Infection of human MDM with YFV also stimulated a chemotactic response evidenced through release of the chemokines MIP1α , MIP1β and RANTES . There were differences in the kinetics of release of the above cytokines and chemokines that largely reflected the virus propagation kinetics profiles for the respective viruses and may be associated with the infection efficiency of the two viruses or residual virus following washing of the cells . These data suggest that the cytokine and chemokine response is likely driven by increases in intracellular viral RNA potentially through recognition by pattern recognition receptors ( PRR ) such as RIG-I , MDA5 and TLR8 . The processes by which these PRR function is well established and leads to activation of transcriptional regulators , such as NF-κB and IRF-7 , that are critical for development of an innate immune response [25] . The limited pro-inflammatory response in MDM suggests that YFV infection may regulate or limit components of host innate immunity . The increase in chemokine release also suggests that YFV is able to stimulate recruitment of macrophages and T cells . However , our studies found that YFV infected MDM did not activate CD4+ T cells suggesting that YFV infection may limit the role of macrophages as APCs . In NHP MDM the response to 17D virus infection was similar to what was seen in human MDM with evident increases in IFNα2 and TNFα , but little evidence of a pro-inflammatory response . The release of IFNα2 and TNFα did not mimic virus propagation kinetics as was seen in human MDM , but was a staged response with TNFα appearing early in the infection and IFNα2 increasing at 3–5 dpi . In Asibi virus-infected NHP MDM , there was little evidence of any cytokine response . Infection of NHP MDM with either Asibi or 17D viruses induced the release of MIP1α and MIP1β . In 17D virus-infected cells the MIP1α and MIP1β response was early in the infection ( peaking with virus titers ) and rapidly waned while in Asibi virus-infected cells the response was prolonged and didn’t diminish as the infection progressed . Interestingly , there was no evidence of RANTES secretion , which , in our experience , is unusual for virus infections . As was the case with human MDM , these data suggest activation of typical intracellular antiviral pathways , particularly those associated with a chemotactic response . The limited response of IFNα2 and TNFα in Asibi virus-infected cells suggests that this virus may inhibit some components of intracellular signaling , but given the limited response difference between Asibi and 17D virus-infected cells , it is not clear that any inhibitory response is significant . The cytokine response to YFV infection in both human and NHP MoDCs was largely muted , with very few differences between virus- and mock-infected cells . In NHP MoDCs , the only significant difference was an apparent inhibition of the constitutive expression of IL-12p40 in Asibi virus-infected cells . While this result could be indicative of an impact on T cell differentiation , in the absence of other biological data , it is difficult to interpret . In human MoDC , IL-1β was elevated in cells infected with either the 17D vaccine virus or the wild-type Asibi virus . The chemokines RANTES and IP-10 were elevated late following Asibi virus infection , but were not elevated in 17D virus-infected cells . The increase in IL-1β suggests activation of TLR signaling through endosomal TLR8 binding to viral ssRNA and subsequent activation of NF-κB which would drive expression of RANTES and IP-10 [26] . The IL-1 precursor is induced following activation of TLR/RIG-I like receptors and NF-κB , but cleavage of the precursor into its active form requires cleavage by caspase1 [27] that is a part of the inflammasome activated by PRR activation . Caspase-1 is also associated with activation of apoptosis; however , there was no significant evidence of cell death in any of the YFV-infected MoDC . Fernandez-Garcia et al also examined the cytokine response in their studies with immortalized cells and immature MoDC [24] . Given that the cells tested in the Fernandez-Garcia study have biologically different roles during an infection than those used in this study , and none of the cytokine analytes were the same , it is difficult to make direct comparisons of the induced immune response between the two studies . Through the use of re-stimulation assays , we were able to test the ability of YFV-infected APC to interact with and stimulate CD4+ T cells . We found that YFV-infected MDM did not stimulate CD4+ T cells , a result that is not surprising given that macrophages in general are considered less efficient as APCs than are dendritic cells . YFV-infected MoDCs , however , were able to stimulate CD4+ T cells and there were critical differences in the measured IFN-γ and IL-2 responses in these cells . In our studies , primary infection of MoDC with live 17D virus resulted in significantly higher percentages of IFN-γ producing CD4+ T cells than stimulation with MoDC infected with live Asibi virus , but this response may be associated with virus infection efficiency or residual virus in the assay system . The elevated IFN-γ response in the context of YFV 17D infected MoDC was consistent regardless of the secondary stimulation . In these studies , it is also evident that viral replication , or persistent stimulation , is required for CD4+ T cell activation as there was no significant elevation in IFN-γ or IL-2 responses in cells stimulated with inactivated YFV . These results conflict with studies by Moser et al and Gaucher et al who found that UV inactivated 17D YFV induced IL-2 expression in re-stimulated CD4+ T cells [22 , 28] . The principal difference between the studies is the method of virus inactivation . The different mechanisms of inactivation could have a significant impact on interaction between viral RNA and PRR , or other molecules , within the cell . UV inactivation cross-links RNA to itself or closely associated proteins while the use of ionizing radiation induces nicks or breaks in the viral RNA . Both methods will block virus replication , but processing of the endocytosed particle and activation of intracellular signaling pathways could be very different . Three of the human donors evaluated during these studies had previously been vaccinated with the 17D vaccine , although all of the vaccinations occurred more than 3 years prior to study onset . In order to determine if there was an evident T cell memory response in these donors , we compared intracellular IFN-γ and IL-2 responses following re-stimulation between donors who had and had not been vaccinated for YFV . These data indicate that there was not a significant response difference between vaccinated and unvaccinated donors , despite there being significant differences between YFV-infected MoDC and mock treated cells . There was also no difference in response between cells re-stimulated with 17D virus or Asibi virus . While an evident memory response could be anticipated , the number of peripheral memory CD4+ T cells is small and their response could have been insufficient to be measured in the context of these studies without additional enrichment processes . The ability of virus infection to inhibit antigen presentation or activation of T cells is not unprecedented as a number of viruses have devised means to inhibit antigen presentation or MHC expression [29–33] . The studies completed here suggest that wild-type Asibi YFV may have a means of inhibiting the interaction between MoDC and CD4+ T cells . There are a number of amino acid differences between the 17D and the Asibi viruses [23] , but the functional differences induced by these mutations are unknown . Structural analysis of the virus receptor-binding domain identified several amino acid differences between YFV 17D and Asibi that could directly affect receptor interaction , efficiency of infection and , subsequently , the ability of infected MoDC to stimulate T cells . In addition , if wild-type YFV is capable of inhibiting antigen presentation in the context of MHC class II and a mutation within the genome of the vaccine virus negates this capability , this could explain , in part , why the 17D virus is such an effective vaccine and why co-morbidities affecting T cells may be related to development of vaccine related disease . There are also some differences in the cytokine response in infected MoDCs , but none of these markers are obvious potential regulators of T cell responsiveness . It is possible that in the context of the co-culture environment , there are additional interactions among MoDC and CD4+ T cells that are not apparent in monoculture systems . In the studies presented here , research efforts focused on potential differences in the interaction of APCs with wild-type or vaccine YFV . In these studies we developed a process to assure nearly homogeneous populations of APCs and demonstrated that wild-type and vaccine YFV could infect and replicate within these cells . We also found that YFV replication kinetics in human- or NHP-derived cells were remarkably similar and that 17D vaccine virus appeared to infect APCs more efficiently than did the wild-type Asibi virus . Cytokine response differences in infected APCs were marginal , but there were clear differences in the ability of infected MoDC to stimulate CD4+ T cells . These differences could be critical toward our understanding of YFV pathogenesis , the effectiveness of the 17D vaccine and potential high-risk co-morbidities that would preclude an individual from being vaccinated with the 17D virus . Clearly , there is significant work to be done toward determining if , in fact , antigen presentation is inhibited by wild-type YFV and , if so , the mechanisms associated with this discovery .
Wild-type YFV strain Asibi and the 17D-204 vaccine strain were obtained from Dr . Robert Tesh at the World Reference Collection for Emerging Viruses and Arboviruses ( WRCEVA ) at the University of Texas Medical Branch . Viruses were cultivated on Vero E6 cells ( ATCC CRL-1586 ) in DMEM ( Invitrogen ) containing 10% heat-inactivated FBS ( Sigma ) . Stocks were generated by infecting VeroE6 cells at a multiplicity of infection ( MOI ) of 0 . 1 ( YFV 17D ) or 0 . 01 ( YFV Asibi ) and allowing the cells to incubate at 37°C/5% CO2 until onset of cytopathic effects ( 4–7 days ) . The cell culture supernatants were collected and clarified by centrifugation at 500xg prior to aliquoting and storage at -80°C . Virus stocks used for these studies were passage two from receipt from the WRCEVA . HuH-7 cells were provided by Hideki Ebihara at the NIAID Rocky Mountain Laboratories ) and were cultivated in RPMI-1640 supplemented with 10% FBS . Conditioned medium for macrophage differentiation was generated from cultures of KPB-M15 cells ( Dr . Atsunoba Hiraoka , International Patent Organism Depositary , National Institute of Technology and Evaluation , Japan ) grown in RPMI-1640 supplemented with 10% FBS . Yellow fever virus was inactivated by gamma irradiation ( 5 Mrad ) in a JL Shepherd 484R-2 60Co source . Complete inactivation was verified by titration of inactivated virus stocks . Inactivated YFV was used in T cell co-culture studies ( see below ) . Cells were plated at a density of 2x105 cells per well in 48-well plates and infected at a MOI of 0 . 1 for 1h at 37°C . The inoculum was removed , cells were washed once with PBS and the media was replaced with RPMI ( Lonza ) containing 10% FBS . Cell culture supernatants were collected at the indicated time-points and frozen at -80°C until use . Viruses were titrated on HuH-7 cells by 10-fold serial dilution of virus stocks in RPMI-1640 with 2% FBS . One-hundred μl of diluted virus was added to cells in a six-well plate and allowed to incubate for 1h at 37°C/5% CO2 with routine rocking . A semi-solid overlay , 0 . 8% gum tragacanth ( f/c ) in 1x EMEM containing 2% FBS , was added to the cells and the plates incubated undisturbed for 5 days at 37°C/5% CO2 . The overlay was then removed and the cells fixed with neutral buffered formalin containing 0 . 25% crystal violet for 1h at room temperature . The fixed cell monolayers were washed with water and the plaques enumerated . Human whole blood from healthy donors was obtained as a commercial resource through an agreement with the National Cancer Institute ( NCI ) in Frederick , MD and allowed repeated acquisition of blood from consistent donors . This attribute of NCI’s donor program allowed testing on material from the same donors throughout the study . Whole blood from NHPs was obtained from animals held within NIAID and also allowed for repeated acquisition of blood from the same individuals . PBMCs were isolated from both human and NHP whole blood using Histopaque density gradient purification . Briefly , blood was diluted in PBS ( pH 7 . 2 ) and layered over Histopaque ( density 1 . 077 g/ml ) ( Sigma Chemical ) and centrifuged at room temperature ( RT ) at 1000 xg for 10 minutes with the brake off . The interface was collected , diluted to 50 ml with PBS and then centrifuged at RT for 10 minutes at 300 xg with the brake on . The pellet was re-suspended in 50 ml PBS containing 2% FBS ( v/v ) prior to pelleting at RT for 10 min at 300 xg . The PBS/FBS wash was repeated twice more . Following the final wash , cells were counted and plated as required . In some instances , particularly with NHP PBMCs due to limited availability , cells were frozen using Recovery Cell Culture Freezing medium ( Life Technologies ) and stored in liquid nitrogen before use . CD14+ cells were isolated from bulk PBMCs using species-specific magnetic microbead enrichment kits ( Miltenyi Biotec ) following the manufacturer’s instructions . To differentiate CD14+ monocytes into dendritic cells , monocytes were re-suspended in RPMI-10 containing 20 ng/ml GM-CSF and 10 ng/ml IL-4 and incubated for 6 days at 37°C/5% CO2 with a change of media every second day . On day 6 post-plating , the media was changed to DC maturation cocktail ( RPMI-10 containing 10 ng/ml TNF-α , 10 ng/ml IL-1β , 15 ng/ml IL-6 , 1 ug/ml prostaglandin E2 , 20 ng/ml GM-CSF and 10 ng/ml IL-4 ) and incubated overnight at 37°C/5% CO2 . Non-adherent cells were washed with cold PBS and collected . Adherent cells were collected using enzyme-free Dissociation Buffer ( Gibco ) and incubated for 5–15 min at 37°C/5% CO2 . Cells were pelleted by centrifugation at 300 xg for 10 min at RT , re-suspended and combined prior to counting , plating and characterization by flow cytometry . To differentiate CD14+ monocytes into macrophages , monocytes were re-suspended in macrophage culture medium ( 50% RPMI-10 , 50% KPB-M15 conditioned medium and 10 ng/ml M-CSF ) . Cells were cultured at 37°C/5% CO2 for 7 days with feeding on days 2 , 4 and 6 by removal and replacement of the medium . Cells were harvested in cold PBS containing 2 mM EDTA . MDM and MoDC were characterized by flow cytometry . Briefly , the harvested cells were washed once with PBS containing 2% FBS . The cells were then incubated at room temperature with fluorochrome-conjugated monoclonal antibodies diluted in PBS/ 2% FBS for 20 minutes while protected from light . The cells were washed again , and the resulting cell pellet re-suspended in PBS/ 2% FBS . The sample data were acquired using BD LSR II Fortessa flow cytometer equipped with BD FACSDiva software . The antibody panel for MDM included: anti-CD11b ( ICRF44 ) -Pacific Blue , anti-CD11c ( N418 ) -AF700 , anti-CD14 ( M5E2 ) -FITC , anti-CD86 ( 2331 ( FUN-1 ) ) -PE-Cy7 , anti-CD163 ( GHI61 ) -APC , anti-CD206 ( 15–2 ) -PE-Cy5 , anti-HLA-DR ( G46-4 ) -V500 and yellow VID live-dead stain . The MoDC panel included: anti-CD14 ( M5E2 ) -PE , anti-CD40 ( 5C3 ) -FITC , anti-CD80 ( L307 . 4 ) -Qdot605 , anti-CD83 ( HB15e ) -PerCP-Cy5 . 5 , anti-HLA-DR ( G46-4 ) -V500 and yellow VID live-dead stain . Antibodies were purchased from either BD Biosciences or BioLegend . Yellow viability dye was purchased from Invitrogen . Data was analyzed using Community Cytobank data analysis software ( Cytobank ) . Cell culture supernatants collected during kinetics assays were tested for secretion of a panel of cytokines using custom designed 16-plex magnetic bead multi-analyte panels ( Millipore ) . Milliplex custom cytokine kits included a 16-plex human panel ( GM-CSF , TNF-α , IL-1RA , IL-1β , IL-5 , IL-6 , IL-10 , IL-12/23 ( P40 ) , IL-13 , IL-15 , IL-17A , MIP-1α , MIP-1β , IFNα2 , IP-10 , and RANTES ) and a 14-plex NHP panel ( GM-CSF , TNF- α , IL-1RA , IL-1β , IL-5 , IL-6 , IL-10 , IL-12/23 ( P40 ) , IL-13 , IL-15 , IL-17A , IL-18 , MIP-1 α , MIP-1β ) supplemented with a 3-plex human panel ( IFNα2 , IP-10 , and RANTES ) that is cross-reactive with rhesus macaque antigens . TGF-β assays were not available in multi-plex format; single bead kits were purchased from Millipore . All reagents were prepared according to the manufacturers' instructions and assays completed in 96-well mylar plates ( Millipore ) . Fluorescent-coded magnetic beads microspheres coated with a capture antibody were incubated with cell culture supernatant test material . The volume of concentrated beads required for each assay was determined using the protocol chart provided by the manufacturer and diluted to the correct volume using bead diluent . The plates were assayed on a Luminex FLEXMAP 3D system equipped with xPonent 4 . 2 software ( Luminex Corp ) . The data collection software was set to acquire data by collecting an average of 50 beads per analyte per well in a volume of 100 μl . The raw data was measured as mean fluorescence intensity ( MFI ) and the concentration of each analyte was calculated using a 4- or 5-parameter logistic fit curve generated for each analyte from the 6 standards . The lower limit of quantification ( LLOQ ) was determined using the lowest standard that was at least 3 times above background . The calculation of the LLOQ was performed by subtracting the MFI of the background ( diluent ) from the MFI of the lowest standard concentration and back-calculating the concentration from the standard curve . Data were further analyzed using Prism 6 . 0 software ( GraphPad ) . Human MoDCs or MDM were isolated as described above and treated with each of the following stimulants: live Asibi virus , inactivated Asibi virus , live 17D virus , inactivated 17D virus , or mock stimulated with media diluent . Following addition of the stimulant , cells were incubated for 1h at 37°C . Cells were then washed with PBS to remove residual virus . Autologous CD4+ T cells were isolated using CD4 specific microbeads ( Miltenyi Biotec ) to positively select CD4+ populations . The CD4+ T cells were then added to the APC in a ratio of 60:1 ( T cell:APC ) and allowed to incubate for 14d at 37°C/5% CO2 . At the end of the primary stimulation , the T cells were purified from the co-culture and mixed with fresh autologous APCs that had been stimulated as indicated above . The secondary stimulation was continued with incubation of the co-culture at 37°C/5% CO2 for 7h , with 1ug/ ml Brefeldin A ( Sigma ) added for the final 5h of the incubation . Cells were then collected and stained with live/ dead cell stain kit ( Invitrogen ) along with surface staining for CD3 , CD4 for 20 min at room temperature in the dark . The cells were washed , fixed and permeabilized using cytofix/cytoperm ( BD Biosciences ) , with intracellular staining performed by incubating permeabilized cells with anti-IFN-γ and anti-IL-2 specific fluorophore-conjugated antibodies at RT for 1 hour [22 , 28] . The cells were then washed twice prior to acquisition . The antibody panel used for re-stimulated T cells included: anti-CD3 ( SP34-2 ) -v500 , anti-CD4 ( S3 . 5 ) -APC-AF750 , anti-IL-2 ( MQ1-17H12 ) -APC , anti-IFNγ ( B27 ) -PE-Cy7 and yellow VID live-dead stain . Antibodies were purchased from either BD Biosciences , Invitrogen , eBiosciences or BioLegend . Yellow viability dye was purchased from Invitrogen . Data was analyzed using Community Cytobank data analysis software ( Cytobank ) . The gating strategy used for analyzing re-stimulated T cells is included in S6 Fig . GraphPad Prism 6 . 0 was used for determination of statistical significance and graphical representations . The non-parametric multi-T test built into GraphPad Prism 6 . 0 was applied to determine the significance of T cell responses in APC co-culture studies . Repeated measures ANOVA run in SAS was used to determine statistical significance in multiplex cytokine analyses in human/NHP MDM and MoDC infected with YFV . In all analyses , p values < 0 . 05 were considered significant . Acquisition and use of human material utilized in these studies was exempt from NIAID IRB approval , but met all requisite approvals at the NCI , Frederick , a commercial resource . The acquisition of whole blood from non-human primates was conducted in accordance with an Animal Study Protocol approved by the NIAID Division of Clinical Research Animal Care and Use Committee ( Protocol #IRF-001 ) following recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . This institution also accepts as mandatory the PHS policy on Humane Care of Vertebrate Animals used in testing , research and training . All animal work at NIAID is performed in a facilities accredited by the American Association for the Accreditation of laboratory Animal Care . Non-human primates were housed either singly or in pairs in an ABSL-2 facility with appropriate enrichment including , but not limited to , polished steel mirrors and durable toys . Animals were anesthetized prior to collection of blood to minimize stress to the animals . Animals were observed following blood collection to ensure recovery from the anesthesia . All work with non-human primates was done in accordance with the recommendations of the Weatherall Report . | Yellow fever virus ( YFV ) is a mosquito-borne flavivirus that can cause lethal hemorrhagic fever in infected humans . An effective live-attenuated vaccine , 17D , was developed in 1937 and continues to be used today . Over the past several years , a number of cases of vaccine-associated disease have been identified and linked to a compromised immune status . In the studies presented here we evaluated the susceptibility of macrophages and dendritic cells ( DCs ) to YFV infection , their cytokine response to infection and their ability to interact with and stimulate CD4+ T cells . These studies found that macrophages and DCs derived from both humans and non-human primates were susceptible to infection with either a wild-type Asibi YFV or the 17D vaccine virus , that the two viruses stimulated different cytokine responses in these cells and that human DCs infected with the 17D virus were able to stimulate CD4+ T cells while those infected with Asibi virus did not . These data demonstrate clear differences between the wild-type and vaccine viruses that may be related to the success of the 17D vaccine . These data also suggest that wild-type YFV may be able to inhibit critical components of the immune response to allow virus propagation and dissemination . | [
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"preventive... | 2016 | Characterization of Yellow Fever Virus Infection of Human and Non-human Primate Antigen Presenting Cells and Their Interaction with CD4+ T Cells |
Pathogens are known to manipulate the reproduction and development of their hosts for their own benefit . Wolbachia is an endosymbiotic bacterium that infects a wide range of insect species . Wolbachia is known as an example of a parasite that manipulates the sex of its host's progeny . Infection of Ostrinia moths by Wolbachia causes the production of all-female progeny , however , the mechanism of how Wolbachia accomplishes this male-specific killing is unknown . Here we show for the first time that Wolbachia targets the host masculinizing gene of Ostrinia to accomplish male-killing . We found that Wolbachia-infected O . furnacalis embryos do not express the male-specific splice variant of doublesex , a gene which acts at the downstream end of the sex differentiation cascade , throughout embryonic development . Transcriptome analysis revealed that Wolbachia infection markedly reduces the mRNA level of Masc , a gene that encodes a protein required for both masculinization and dosage compensation in the silkworm Bombyx mori . Detailed bioinformatic analysis also elucidated that dosage compensation of Z-linked genes fails in Wolbachia-infected O . furnacalis embryos , a phenomenon that is extremely similar to that observed in Masc mRNA-depleted male embryos of B . mori . Finally , injection of in vitro transcribed Masc cRNA into Wolbachia-infected embryos rescued male progeny . Our results show that Wolbachia-induced male-killing is caused by a failure of dosage compensation via repression of the host masculinizing gene . Our study also shows a novel strategy by which a pathogen hijacks the host sex determination cascade .
Wolbachia is a genus in Rickettsiales , a diverse order of intracellular bacteria . Recent meta-sequencing analysis shows that over 65% of insect species possess Wolbachia [1] , indicating that Wolbachia is the most widespread and common intracellular bacterium that infects insects . Wolbachia is a well-known example of a parasite that alters host reproduction to facilitate its own propagation . Wolbachia-induced phenotypes include parthenogenesis , feminization , cytoplasmic incompatibility , and male-killing , each of which is supposed to be adaptive for Wolbachia by enhancing the production of infected females [2] . Wolbachia-induced male-killing has been reported in three insect orders , Coleoptera [3] , Diptera [4] , and Lepidoptera [5] , in which male-killing occurs mainly during embryogenesis . Recent advances in Wolbachia-induced male-killing have been made mainly from studies using Ostrinia moths [5–7] . Ostrinia species ( corn borer ) have a WZ/ZZ sex chromosome system and all of the progeny of Wolbachia-infected mother moths have a W chromosome , indicating the existence of male-killing [7] . The male-type splice variant of doublesex ( dsx ) , a gene that acts at the downstream end of the sex differentiation cascade [8–9] , is not detected in Ostrinia late embryos that originate from Wolbachia-infected mothers [7] , suggesting that Wolbachia’s sexual manipulation is presumably established at an early embryonic stage . However , the molecular mechanism ( s ) by which Wolbachia manipulates sex and male lethality in Ostrinia moths has remained elusive . The sex determination cascade in lepidopteran insects has been studied mainly using silkworm Bombyx mori as a model insect [10–11] . In B . mori , females have ZW sex chromosomes and males have two Z chromosomes . B . mori femaleness is strongly determined by the presence of the W chromosome irrespective of the Z chromosome number , suggesting that there is a dominant feminizing gene ( Fem ) on the W chromosome [12–13] . In 2014 , we discovered that Fem is a precursor of a single W chromosome-derived PIWI-interacting RNA ( piRNA ) [14] . We also identified the target gene of Fem-derived piRNA ( Fem piRNA ) , which is located on the Z chromosome . Depletion of this Z-linked gene , Masculinizer ( Masc ) , in male embryos leads to the production of the female-type splicing of B . mori dsx , indicating that the product of Masc is a masculinizing factor . These results revealed that sex of B . mori is determined by the Fem piRNA-Masc cascade [14] . Further experiments showed that silencing of Masc in B . mori embryos results in male-specific lethality [14] . Deep sequencing ( RNA-seq ) of Masc mRNA-depleted embryos revealed that the Masc protein is required for the repression of global transcription from the Z chromosome in male embryos , and that a failure of this dosage compensation causes male-specific embryonic death [14] . Bioinformatic analysis also revealed that most of the Z-linked genes are dosage compensated by 72 hours post-oviposition ( hpo ) [15] . These results indicate that Masc-mediated control of dosage compensation at an early embryonic stage is essential for male development of B . mori . In this study , we attempted to explore the mechanism by which Wolbachia accomplishes sexual manipulation using Wolbachia-infected Ostrinia moths as a model . We previously showed that artificial depletion of Masc mRNA in B . mori early embryos results in male-specific embryonic lethality [14] . This phenomenon likely mimics the way that Wolbachia induces male-killing in Ostrinia [7] . In the light of these facts , we first focused on the expression of Ostrinia homologue of Masc in Wolbachia-infected embryos . Transcriptome analysis by RNA-seq revealed that Wolbachia-induced male-killing is established by a failure of dosage compensation through Masc mRNA depletion . Furthermore , injection of Masc cRNA into Wolbachia-infected Ostrinia embryos prevented males from being killed at embryonic stages . This is the first study to identify the Wolbachia’s target that is utilized for sexual manipulation .
We collected over 80 Ostrinia moths in the field and found 3 female moths that were infected with Wolbachia ( Fig 1A ) . One of these moths produced only female progeny . By sex pheromone analysis , this female was found to be O . furnacalis . Subsequently , when the females were mated with other Wolbachia-free O . furnacalis males only female progeny were produced . There was no deviation in this pattern of female only progeny through 5 generations ( in total 302 females and no males judged by external morphology at the adult stage ) ( Fig 1B ) . We established the quantitative PCR ( qPCR ) -based molecular sexing method for O . furnacalis ( S1A Fig ) , and verified that Wolbachia-infected moths were all female ( S1B Fig ) . Using this method , we found that Wolbachia-infected embryos ( just prior to hatching ) contained both female and male individuals ( S1C Fig ) . However , the hatched larvae were all female ( S1C Fig ) , indicating that this Wolbachia induces male-specific embryonic lethality . In addition , when Wolbachia was eliminated from infected individuals by tetracycline treatment and Wolbachia-eliminated female moths were mated with other Wolbachia-free males , only male progeny were produced ( S1D Fig ) . Taken together with these results , we concluded that this Wolbachia strain induces male-killing in O . furnacalis , which is similar to the phenotype observed in Wolbachia-infected O . scapulalis [7] . Sugimoto and Ishikawa [7] reported that the male-type splice variants of Ostrinia dsx [6] is not expressed in all 5-day-old O . scapulalis embryos ( just prior to hatching ) that are infected with a male-killing Wolbachia . In order to determine the precise developmental stage at which Wolbachia starts sexual manipulation in Ostrinia , we examined the splicing patterns of dsx in Wolbachia-infected Ostrinia embryos starting immediately after oviposition . Both male- and female-type variants of dsx were observed in uninfected embryos ( Fig 1C ) . The male-type variant in uninfected embryos was detected from 12 hpo , indicating that the sex determination signal is transmitted prior to 12 hpo in Ostrinia . In contrast , the male-type dsx variant was not detected in Wolbachia-infected embryos throughout embryogenesis ( Fig 1C ) . These results indicate that Wolbachia manipulates the sex of Ostrinia from the beginning of the sex determination period . In order to investigate what occurs during Wolbachia-induced sexual manipulation , we performed RNA-seq experiments using RNAs prepared from Wolbachia-infected and-uninfected embryos ( of both sexes ) at 0 , 12 , 24 , 36 , and 48 hpo . We recently showed that Masc protein encodes a lepidopteran-specific CCCH-tandem zinc finger protein , which is required for both masculinization and dosage compensation in B . mori [14] . RNA interference-mediated knockdown experiments also show that depletion of Masc mRNA in B . mori early embryos results in male-specific death via a failure of dosage compensation [14] . In order to test whether this male-specific death in B . mori is related to the Wolbachia-induced male killing in Ostrinia , we first identified and characterized the Masc homolog of Ostrinia . Using RNA-seq data , we identified contigs that potentially encode a protein with significant homology to Masc proteins ( Fig 2A and S2 Fig ) . Ostrinia Masc was composed of 583 amino acid residues and showed 28 . 1% identity to B . mori Masc ( S2 Fig ) . Phylogenetic analysis based on the amino acid sequences of zinc finger domains revealed that Ostrinia Masc was closely related to that of Chilo suppressalis ( Fig 2A ) . The silkworm ovarian cell line BmN4 expresses the female-type Bmdsx variant only , whereas transfection of B . mori Masc cDNA results in the production of the male-type splice variant [14] . Using this system , we examined whether Ostrinia Masc protein also has a masculinizing activity . As shown in Fig 2B , we observed the expression of the male-type variant of Bmdsx in BmN4 cells when transfected with Ostrinia Masc cDNA as well as B . mori Masc cDNA . In addition , we examined the expression of B . mori insulin-like growth factor II mRNA-binding protein ( BmIMP ) , a factor that is involved in the male-specific splicing of Bmdsx [16] , in Ostrinia Masc cDNA-transfected cells . We found that either B . mori or Ostrinia Masc cDNA markedly enhanced BmIMP expression ( Fig 2C ) . These results strongly suggest that Ostrinia Masc encodes a masculinizing protein and may be required for masculinization in Ostrinia sex determination pathway . We next compared the level of Masc mRNA in Wolbachia-infected and-uninfected embryos by mapping RNA-seq tags onto the Ostrinia Masc coding sequence . We found a significant decrease in Masc mRNA in Wolbachia-infected embryos prior to 12 hpo ( Fig 3A ) . To elucidate this reduction in greater detail , we performed reverse transcription-qPCR ( RT-qPCR ) using total RNA isolated from Wolbachia-infected and uninfected embryos at 0 , 6 , 12 , and 18 hpo . In uninfected embryos , Masc expression peaked at 6 hpo and decreased rapidly . In contrast , Masc expression in Wolbachia-infected embryos declined by 6 hpo , and remained at a low level compared with that observed in uninfected embryos ( Fig 3B ) . These results clearly showed that Wolbachia infection markedly reduces Masc mRNA level during embryogenesis of Ostrinia . Together with transfection results ( Fig 2B and 2C ) and our previous results showing that knock down of Masc mRNA results in the production of the female-type dsx in male embryos of B . mori [14] , we conclude that the lack of the male-type dsx in Wolbachia-infected Ostrinia embryos ( Fig 1C ) was caused by down-regulation of Masc mRNA ( Fig 3A and 3B ) . Considering our recent finding that depletion of Masc mRNA in early embryos of B . mori results in male-specific embryonic lethality due to a failure of dosage compensation [14] , we hypothesized that a decrease in Masc mRNA in Wolbachia-infected Ostrinia embryos also affects dosage compensation , presumably resulting in a male-specific embryonic death . To test this hypothesis , we examined dosage compensation effects in Wolbachia-infected Ostrinia embryos using RNA-seq data . As reported previously [14] , Z-linked transcripts are expressed at higher levels in Masc mRNA depleted B . mori embryos than in control embryos ( Fig 4A , left panel ) . A similar transcriptional bias in putative Z-linked genes in Wolbachia-infected Ostrinia embryos at 48 hpo was also found ( Fig 4A , right panel ) . A failure of dosage compensation of Z-linked genes was detected from 24 hpo and continued to 48 hpo ( Fig 4B and S3 Fig ) . These results strongly support our hypothesis that Wolbachia infection leads to abnormally enhanced expression of Z-linked genes in male embryos via Masc mRNA down-regulation , resulting in a male-killing phenotype . To obtain direct evidence that down-regulation of Masc mRNA in Wolbachia-infected Ostrinia embryos results in the male-killing phenotype , we performed rescue experiments by injecting in vitro synthesized capped , poly ( A ) -tailed Masc cRNA into Wolbachia-infected embryos . As shown in Fig 5 , the hatched larvae injected with control ( GFP ) cRNA were all female , whereas both male and female larvae were observed when injected with Masc cRNA . This clearly indicates that introduction of Masc cRNA into Wolbachia-infected embryos can rescue male embryos . Together with the results of transcriptome data , we conclude that a decrease in Masc mRNA in Wolbachia-infected embryos causes a male-killing phenotype via a failure of dosage compensation . In conclusion , our study answered the question of how Wolbachia manipulates sex ratios in moths: in Ostrinia , Wolbachia targets Masc , a masculinizing gene that was originally characterized in B . mori , to establish male-killing ( Fig 6 ) . In Drosophila , the Sex lethal protein functions as a master switch for sex determination , and also controls dosage compensation by inhibiting translation of male-specific lethal 2 ( msl-2 ) [17] . Veneti et al . reported that a male-killing Spiroplasma targets the dosage compensation complex , including msl-2 , to kill male D . melanogaster [18] . Our current results demonstrate that a similar event occurs in Wolbachia-infected lepidopteran insects; Wolbachia infection leads to male-killing by down-regulating Masc ( Fig 3A and 3B ) , which is an essential factor controlling both sex determination and dosage compensation pathways in lepidopteran insects [14] . This analogy comes from the fact that the sex determination cascade is often tightly associated with the control of dosage compensation in insects . In B . mori , femaleness is determined by Fem piRNA-mediated , highly tuned post-transcriptional regulation of Masc mRNA [14 , 19] . Our findings suggest that Wolbachia has captured an unknown factor through evolution and succeeded in mimicking this sex determination system to execute the male-specific death . Our future goal is to identify a Wolbachia factor that decreases Masc mRNA post-transcriptionally or that directly inhibits Masc transcription ( Fig 6 ) .
Moths were collected at Matsudo ( 35 . 8° N , 139 . 9° E ) and Nishi-Tokyo ( 35 . 4° N , 139 . 3° E ) , Japan , in early summer , 2014 . GC-MS analysis of the pheromone gland extracts of the moths used in this study showed the presence of ( E ) -12- and ( Z ) -12-tetradecenyl acetates ( E12-14:OAc and Z12-14:OAc ) . The relative abundance of the two components was 1:1 . 6 ( E12-14:OAc and Z12-14:OAc ) in Wolbachia-infected and 1:2 . 7 in Wolbachia-uninfected moths , indicating that they were O . furnacalis ( Lepidoptera: Crambidae ) . Wolbachia-infected strain was maintained by crossing with Wolbachia-free O . furnacalis male moths . Ostrinia larvae were reared on an artificial diet ( Insecta LF , Nosan Corp . ) at 23°C under a photoperiod of 16 L and 8 D . Tetracycline treatment was performed as described previously [7] . Molecular sexing of Ostrinia moths and embryos was performed by qPCR using two Z-linked genes triose phosphate isomerase ( Tpi ) and kettin as described by Kern et al . [20] . The autosomal gene EF-1α was used for normalization . Primers used for qPCR are listed below: Tpi_F: 5'-ACGGAGGATCGGTTACTGGAGC-3' Tpi_R: 5'-CGATGTCAACGAACTCTGGCTTGA-3' kettin_F: 5'-AGGACTCTGGACGCATGGCT-3' kettin_R: 5'-TGCAAGGCTATCAACAGGGCA-3' EF1a_F: 5'-TTGCCACACAGCCCACATTG-3' EF1a_R: 5'-TTGACAATGGCGGCATCACC-3' Total RNA and genomic DNA were prepared simultaneously from Ostrinia embryos ( 25–50 embryos at each time point ) using TRIzol reagent ( Invitrogen ) according to the manufacturer’s protocol . Libraries for RNA-seq were generated from 0 , 12 , 24 , 36 , 48 hpo embryos using the TruSeq RNA Sample Preparation kit ( Illumina ) . The cDNAs were analyzed using the Illumina HiSeq 2500 platform with 100-bp paired-end reads according to the manufacturer's protocol [21] . De novo assembly of RNA-seq data from 10 data sets was performed as described previously [14] . Ostrinia Masc was identified from assembled contigs by BLAST using the B . mori Masc amino acid sequence as a query . Because extensive synteny conservation is observed among several lepidopteran insects including Ostrinia [22–24] , we identified putative corresponding chromosomes for Ostrinia RNA-seq derived contigs by BLAST using 13 , 789 B . mori gene models ( putative protein-coding genes whose chromosomal locations are identified ) . Transcript abundance in each contig was quantified as described previously [14–15] . RNA-seq data of B . mori Masc RNAi experiments ( GFP and Masc RNAi embryos of each sex , 72 h post-injection , 4 data sets ) [14] were used as a control data set . Total RNA and genomic DNA were prepared from Ostrinia embryos ( 25–50 embryos at each time point ) using TRIzol reagent ( Invitrogen ) according to the manufacturer’s protocol . Total RNA was subjected to reverse transcription using avian myeloblastosis virus ( AMV ) reverse transcriptase with an oligo-dT primer ( TaKaRa ) . PCR was carried out with KOD FX-neo DNA polymerase ( TOYOBO ) . Sex-specific splicing of Ostrinia dsx by RT-PCR and Wolbachia detection by wsp PCR were performed with primers reported previously [6] . RT-qPCR analyses were performed using a KAPATM SYBR FAST qPCR kit ( Kapa Biosystems ) and specific primers . The expression levels of rps3 were used to normalize transcript levels . Primers used for RT-qPCR are listed below: OstriniaMasc_F: 5'-TTTGCCGCATTCATTCGCAG-3' OstriniaMasc_R: 5'-TGGTTTTGGTGCAAGCAATTCG-3' OstriniaRPS3_F: 5'-TGGCCACCAGAACTCAAAGC-3' OstriniaRPS3_R: 5'-GAAACGCTTCTGGACTACGGA-3' Ostrinia Masc cDNA was cloned into the pIZ/V5-His vector ( Invitrogen ) . Transfection experiments were performed as described previously [14] . In brief , BmN4 cells were transfected with plasmid DNAs using X-tremeGENE HP ( Roche ) . Cells were collected at 72 h after transfection , and RT-PCR for Bmdsx and RT-qPCR for BmIMP were performed . B . mori Masc was used as a positive control for this experiment . BmIMP mRNA level was normalized to that of rp49 . Primers used for RT-qPCR are listed below: Bmdsx_F: 5'-AACCATGCCACCACTGATACCAAC-3' Bmdsx_R: 5'-GCACAACGAATACTGCTGCAATCG-3' rp49_F: 5'-CCCAACATTGGTTACGGTTC-3' rp49_R: 5'-GCTCTTTCCACGATCAGCTT-3' BmIMP_F: 5'-ATGCGGGAAGAAGGTTTTATG-3' BmIMP_R: 5'-TCATCCCGCCTCAGACGATTG-3' The DNA template for cRNA synthesis was amplified by PCR using the pIZ/V5-His vector containing Ostrinia Masc ( described above ) or GFP ( control ) cDNA . Primers used for PCR are listed below: pIZ-F-T7: 5'-TAATACGACTCACTATAGGGAGACAGTTGAACAGCATCTGTTC-3' pIZ-R: 5'-GACAATACAAACTAAGATTTAGTCAG-3' Capped , poly ( A ) -tailed cRNA was synthesized using mMESSAGE mMACHINE T7 Ultra Kit ( Ambion ) . cRNA injection was performed as described previously [14] with some modifications . We injected 1–2 nl of Masc or GFP cRNA solution ( 1 μg/μl in 100 mM potassium acetate , 2 mM magnesium acetate , 30 mM HEPES-KOH; pH7 . 4 ) into Wolbachia-infected Ostrinia embryos within 4 h after oviposition . The hatched larvae were collected and molecularly sexed by qPCR . Phylogenetic analysis of Ostrinia Masc protein was performed as described previously [14] . The amino acid sequences of proteins in the NCBI database and those deduced form the RNA-seq data obtained in this study with significant homology ( E-value of < 1 × 10−9 ) to residues 51–122 of Masc were identified using the BLAST program . A neighbor-joining tree was constructed using 43 sequences [including 3 Ostrinia sequences ( Ostrinia Masc , c66984_g1_i4 , and c66984_g1_i3 ) ] and the reliability of the tree was tested by bootstrap analysis with 1000 replications . The nucleotide sequence of Ostrinia Masc has been submitted to the DDBJ/EMBL/GenBank data bank under the accession number LC028928 . Deep sequencing data obtained in this study are available under the accession number DRA003038 ( DDBJ ) . | Pathogens are known to manipulate the physiology , behavior , and reproduction of their hosts for their own benefit . The endosymbiotic bacterium Wolbachia is known to manipulate the sex of its host's progeny . Male-killing is one of the phenotypes that Wolbachia induces , but the mechanism of how Wolbachia induces sex-specific death is unknown . Here we found a marked down-regulation of Masc , a lepidopteran-specific zinc finger protein gene , in embryos that are produced by Wolbachia-infected Ostrinia moths . We also observed that dosage compensation fails in Wolbachia-infected Ostrinia embryos . The findings of this study and our previous study using a lepidopteran model insect Bombyx mori indicate that Wolbachia has evolved to hijack the Masc-dependent , lepidopteran insect-specific sex determination system by capturing an unknown factor during Wolbachia-host coevolution . | [
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"Methods"
] | [] | 2015 | The Endosymbiotic Bacterium Wolbachia Selectively Kills Male Hosts by Targeting the Masculinizing Gene |
Toxoplasma gondii causes substantial morbidity , mortality , and costs for healthcare in the developed and developing world . Current medicines are not well tolerated and cause hypersensitivity reactions . The dihydrotriazine JPC-2067-B ( 4 , 6-diamino-1 , 2-dihydro-2 , 2-dimethyl-1- ( 3′ ( 2-chloro- , 4-trifluoromethoxyphenoxy ) propyloxy ) -1 , 3 , 5-triazine ) , which inhibits dihydrofolate reductase ( DHFR ) , is highly effective against Plasmodium falciparum , Plasmodium vivax , and apicomplexans related to T . gondii . JPC-2067-B is the primary metabolite of the orally active biguanide JPC-2056 1- ( 3′- ( 2-chloro-4-trifluoromethoxyphenyloxy ) propyl oxy ) - 5-isopropylbiguanide , which is being advanced to clinical trials for malaria . Efficacy of the prodrug JPC-2056 and the active metabolite JPC-2067-B against T . gondii and T . gondii DHFR as well as toxicity toward mammalian cells were tested . Herein , we found that JPC-2067-B is highly effective against T . gondii . We demonstrate that JPC-2067-B inhibits T . gondii growth in culture ( IC50 20 nM ) , inhibits the purified enzyme ( IC50 6 . 5 nM ) , is more efficacious than pyrimethamine , and is cidal in vitro . JPC-2067-B administered parenterally and the orally administered pro-drug ( JPC-2056 ) are also effective against T . gondii tachyzoites in vivo . A molecular model of T . gondii DHFR-TS complexed with JPC-2067-B was developed . We found that the three main parasite clonal types and isolates from South and Central America , the United States , Canada , China , and Sri Lanka have the same amino acid sequences preserving key binding sites for the triazine . JPC-2056/JPC-2067-B have potential to be more effective and possibly less toxic treatments for toxoplasmosis than currently available medicines .
Toxoplasmosis is a neglected tropical disease as well as a significant illness affecting persons throughout the world and new and improved medicines are greatly needed for this and other apicomplexan infections [1]–[40] . In developing tropical countries , the problems for persons with AIDS can be exacerbated due to lack of both anti-retroviral treatment and anti-Toxoplasma gondii treatment . In this setting , this opportunistic pathogen causes substantial neurologic disease and treatment of this illness can be especially difficult because current gold standard medicines are unobtainable and/or unaffordable and , due to their toxicity , require monitoring which exceeds the capacity of many of the available health care systems . Toxoplasmic eye disease ( chorioretinitis ) is frequent in certain areas of Brazil and Colombia , areas where the gold standard drugs are particularly problematic , and is caused by atypical parasites that present major recrudescent and recurrent clinical problems . T . gondii is highly pathogenic and lethal in an emerging problem in French Guiana and Suriname [22] , [34] . Throughout the world , new T . gondii infection during pregnancy can lead to devastating disease for the fetus and newborn infant , later impacting on the child's health and development and potentially on his/her later productivity [1]–[3] . In all areas of the world , this infection is life threatening and causes substantial neurologic damage for those with immune compromise . For some immunologically normal individuals this infection causes recurrent ophthalmologic and other organ damage [1]–[3] . Thus , toxoplasmosis is an important neglected disease in developing tropical countries , as well as an important cause of illness in developed countries in tropical and temperate climates [16]–[37] . All forms of toxoplasmosis ( acute acquired , with or without symptoms; congenital; ocular; and in immune-compromised persons ) occur throughout the world [1]–[3] , [16]–[40] . In Europe and in the U . S . reports are that there are three predominant clonal types of T . gondii [22]–[24] . Clonal genetic type II T . gondii have been reported to predominate in France , Poland , and the U . S [24] . Atypical genetic types of T . gondii have been reported to occur in association with unusually severe eye disease in the U . S . in a small case series [25] and clonal type I parasites in some patients with AIDS and toxoplasmic encephalitis [26] , but clonal type II parasites have been predominant among U . S . and European human isolates reported to date [24] . The presence of atypical T . gondii parasites in South and Central America have recently been discovered and found to be associated with significant human disease [27]–[32] . T . gondii strains in certain areas of Brazil , Colombia , and Guatemala [33] are atypical ( rather than the European and U . S . predominant three clonal types ) and are often genetically polymorphic [34] . In the Minas Girais area of Brazil ( 36 ) , infection with T . gondii is common . In Erechim , Rio Grande do Sul 17 . 7% of the population had ocular toxoplasmosis . In Colombia , where atypical , non clonal type I , II , or III , parasites are endemic , frequency of retinal lesions of ocular toxoplasmosis in medical residents was 6% [31] . Severe congenital disease occurs in 0 . 5% of live births in Colombia [32] . In addition , in sharp contrast to clonal type II parasites predominating in Europe , in certain tropical countries with wild felids and a wide variety of wild mammals , the parasites are genetically more diverse and the many potential mammalian hosts apparently appear to be associated with the presence of greater genetic diversity in these atypical strains [34] . For example , in French Guiana [34] , parasites have many felid hosts and these parasites have been considered to be representative of those found in the tropical Amazon reservoir [35] . In Northern Coastal South America they have caused lethal and severe diseases in humans including French soldiers; these diseases have included persistent neurologic findings , Guillain Barre syndrome , severe pneumonia , and death [37] . Substantial waterborne epidemics have occurred in Brazil [38] , in Canada [39] , and in U . S . soldiers in Panama [40] , considered to be secondary to feral or wild cats in proximity to drinking water [38]–[40] . A cat excretes up to 20 million unsporulated oocysts during just a few days , these become infections following sporulation , and even 1 oocyst is infectious [1] . Oocysts excreted by cats can persist in warm moist soil for up to a year and in seawater for up to 6 months . Thus infection is readily spread in nature and is a very common infection throughout the world . Congenital toxoplasmosis is a significant problem in the developed and developing world , but it is particularly difficult in parts of the developing world to obtain the gold standard medicines , pyrimethamine and sulfadiazine . For example , in Colombia , it is not possible to obtain pyrimethamine and sulfadiazine to treat congenitally infected infants . The cost of compounding , administering and monitoring the safe use of these medicines also would likely be prohibitive for most residents of rural Africa or Central and South America . These issues also are especially problematic for those with AIDS and toxoplasmosis in the developing world , because the medicines and the monitoring required for their proper and safe use are often also both unavailable and unaffordable [17] . In patients with AIDS , toxoplasmosis is a major , presenting , opportunistic , central nervous system infection and this is also the case throughout the entire course of the AIDS infection when HAART is not obtainable or affordable [17] . Early in the AIDS epidemic in the U . S . and Europe , approximately half of seropositive , i . e . , individuals with chronic T . gondii infection , and AIDS infected individuals developed toxoplasmic encephalitis [16] . An example of the likely magnitude of this problem can be seen when one considers sub-Saharan Africa [17] . In sub-Saharan Africa approximately 25 million people have HIV infection/AIDS [18] , and co-infection with T . gondii frequently remains undetected and thus untreated [17] . T . gondii seroprevalence ranges from 35% to 84% in different African countries south of Sahara ( reviewed in [19] ) . Because approximately 30–50% of persons who have been co-infected with HIV and T . gondii in the U . S . or Europe in the pre-HAART era ultimately developed toxoplasmosis , the high seroprevalence in sub-Saharan Africa combined with the HIV-pandemic indicate that 2 . 5–10 million people in this region are likely to be at risk of dying from toxoplasmosis . A recent study of types of parasites using a SAG2 marker indicated that all three SAG2-types have been found in chickens in Africa [20] . HIV infection is not the only immunodepressive health condition that is frequent in the developing world and that worsens manifestations of toxoplasmosis . In India , adults who were malnourished but otherwise immunologically normal and who were without HIV infection had severe , symptomatic toxoplasmic encephalitis [21] . Ideal medicines to treat toxoplasmosis in developing tropical countries would be effective , easily obtained and affordable , without toxicity , including hypersensitivity and neutropenia which requires co-adminstration of leukovorin and careful monitoring of neutrophil count . They also would be non teratogenic so the fetus and pregnant woman could be treated . In addition they would be rapidly effective , safe , without any toxicity , when available in pediatric suspensions . Further , they would be available parenterally for those who are acutely ill and unable to take oral medicines . They would be effective against all isolates of T . gondii ( all three clonal types and atypical parasites ) . Ideally a medicine would also be cidal against bradyzoites . An ideal medicine for toxoplasmosis would have superb penetration into the eye and brain . These would be major advantages for this neglected disease throughout the world , and especially important in developing countries . JPC-2056/JPC-2067-B have the potential to address some of these issues ( e . g . cidal for tachyzoites , less toxicity , available for oral and parenteral use , and potentially available in pediatric suspensions that are stable without refrigeration ) . Further testing and development will reveal whether JPC-2056/JPC-2067-B can address the other characteristics of an ideal anti-toxoplasmosis medicine . Current treatment of toxoplasmosis includes the combination of a folic acid antagonist and an inhibitor of dihydropteroic acid synthesis: The gold standard treatment has been the classic anti-malarial combination of pyrimethamine and sulfadiazine . In vitro and in vivo experimental models of toxoplasmosis parallel this clinical approach [1] , [3] . Herein , results using those same in vitro and in vivo toxoplasmosis models with a new anti-malarial candidate , JPC-2067B ( 4 , 6-diamino-1 , 2-dihydro-2 , 2-dimethyl-1- ( 3′- ( 2-chloro-4-trifluoromethoxyphenoxy ) propyloxy ) -1 , 3 , 5-triazine ) and its pro-drug JPC-2056 are presented [4]–[10] . This new anti-malarial class [4]–[10] , without a sulfonamide , has dramatic potency against multi-drug resistant Plasmodium falciparum strains [4]–[10] . We have waited a long time for a representative of this series of compounds to advance to the clinic for the treatment of T . gondii infection . This is especially important for those with this infection who are immune compromised and potentially also for those infected in pregnancy and in utero . New medications are needed because the classic gold standard medications have substantial toxicity [1] , [2] . Moreover , pyrimethamine cannot be used in the first trimester of pregnancy , as folate depletion is detrimental to fetal development [1] . Neutropenia is a common toxicity with pyrimethamine treatment even when leukovorin is administered in conjunction with this medicine [3] . Furthermore , pyrimethamine is generally administered in a synergistic combination with sulfadiazine which has substantial associated hypersensitivity [2] and toxicity ( e . g . kidney stones or hepatic or renal complications ) . New medicines are greatly needed for individuals suffering from toxoplasmosis The extremely promising candidate , JPC-2067-B , comes from a pre-clinical anti-malarial series well known in malariology by the name of the related metabolite WR99210 ( 4 , 6-diamino-1 , 2-dihydro-2 , 2-dimethyl-1-[3′ ( 2 , 4 , 5-trichlorophenoxy ) propyloxy]-1 , 3 , 5-triazine ) [4]–[10] . In vitro anti-malarial testing of WR99210 against drug-sensitive and drug-resistant strains has shown high potency and full activity against P . falciparum strains not responsive to pyrimethamine , proguanil or chloroquine with an ED50 of 0 . 05 ng/mL in vitro . As yet there is no strain resistant to this class of compounds . WR99210 is discussed here in order to provide a common point of cross reference . Like proguanil , the new clinical candidate JPC-2056 ( Figure 1 ) is a biguanide pro-drug which is metabolized in vivo to the active dihydrotriazine JPC-2067-B ( Figure 1 ) . For in vitro testing the metabolite must be used; for oral usage the biguanide must be given . The ongoing work in development and progression to use in the care of patients of this very promising anti-malarial clinical candidate ( Jacobus et al , unpublished ) also is useful in development of the same medicine for treatment of toxoplasmosis . The previously described triazine WR99210 and its pro-drug , PS-15 , were developed in response to resistance of P . falciparum to pyrimethamine and cycloguanil [4]–[11] . WR99210 was found to be a very tight binding and potent inhibitor of P . falciparum DHFR-TS [4]–[11] . WR99210 and PS-15 also were highly active in vivo against P . falciparum , with activity 2 logs greater than that of pyrimethamine . These compounds were also highly active against P . vivax , without cross-resistance to other antifolates ( S . Hunt , personal communication ) . The therapeutic/toxic ratio is increased because the high avidity of these compounds for the P . falciparum DHFR differs from its lower avidity to mammalian DHFR [11] . Unfortunately , toxicity of WR99210 limited its development and use and it will not be a clinically useful compound . We previously evaluated the active triazine metabolite of proguanil ( cycloguanil ) against T . gondii tachyzoites [12] , and more recently found that WR99210 was also highly active against T . gondii in vitro and in vivo when administered parenterally [13] . PS15 also was found to be effective in vivo [13] . A major drug discovery effort over the past 6 years has identified an analog of WR99210 , JPC-2067-B , which has superior pharmacological characteristics . Importantly , pro-drug JPC-2056 , is easily absorbed , bioavailable , and relatively nontoxic . In studies with P . falciparum , oral administration of JPC-2056 resulted in conversion to the JPC-2067-B which was cidal for the malaria parasite . The high potency and selectivity of JPC-2067-B for inhibition of apicomplexan parasite DHFR relative to mammalian DHFR reduces the likelihood of neutropenia , thus enhancing the margin of safety and convenience in monitoring white blood counts with its use . JPC-2056 was also as active as monotherapy in vitro as the synergistic combination of pyrimethamine and sulfadiazine and is currently being advanced to clinical trials , leading to a new and markedly improved class of anti-folate medicines for the treatment of malaria . The effect of JPC-2067-B on T . gondii is of considerable interest and importance . The lack of toxicity of JPC-2067-B and the favorable absorption and distribution profile of its prodrug JPC-2056 offers the possibility of overcoming the limitations of pyrimethamine . The benefit of greater specificity for the parasite rather than host DHFR could have the dual advantage of reducing host toxicity while eliminating the need for simultaneous administration of a sulfonamide . Whether an IC 50 of 6 . 5 nM is sufficient to be used as a single agent for either malaria or toxoplasmosis or would be better used in conjunction with another anti-microbial in vivo under clinical conditions remains to be determined . Structures of JPC-2067-B and its corresponding pro-drug JPC-2056 ( Jacobus Pharmaceutical Company , Princeton , NJ ) are shown in Figure 1 . The biguanide pro-drug is converted in vivo to the biologically active dihydrotriazine through P450 metabolism in the liver , and so in vitro experiments are always conducted with the dihydrotriazine ( JPC-2067-B ) . The overall aim of the experiments was to determine effect of the dihydrotriazine on T . gondii in vitro and in vivo and inhibitory effect of the dihydrotriazine on T . gondii that was observed is described herein .
Tachyzoites of the RH strain of T . gondii were passaged in human foreskin fibroblasts ( HFF ) . They were used to infect fibroblasts to determine antimicrobial effects of candidate compounds . Outcome was assessed with microscopy and uracil uptake after four days in culture as described [8] , [12] , [13] . Briefly , for testing of inhibitors in vitro against T . gondii tachyzoites , four-day old confluent cultures of human foreskin fibroblasts ( HFF ) were infected with 103 tachyzoites and cultured for 1 hour to allow parasite invasion . Inhibitor was added and cells cultured for 3 days . They were supplemented with 3H uracil and incubation extended for a further day , whereupon uracil incorporation into cells and thus parasite growth were assessed by liquid scintillation counting [8] , [12] , [13] . Studies were performed with inhibitors as described in [8] , [12] , [13] . Lack of toxicity for mammalian host cells was demonstrated first by visual inspection of the monolayer and by parallel concomittant evaluation of separate 3H thymidine incorporation assays by non-confluent HFF cell monolayers . For in vitro studies , a stock solution of JPC-2067-B was initially dissolved in 100% dimethyl sulfoxide ( DMSO ) and then diluted in complete tissue culture medium ( IMDM-C ) [IMDM with NaHCO3 and 25 mM Hepes ( Cambrex Bio Science , Walkersville , MD ) , 10% fetal bovine serum ( Gibco , Grand Island , N . Y . ) , 1× antibiotic-antimycotic solution ( Cellgro , Mediatech ) , and 2 mM L-glutamine ( Gibco ) . Working concentrations of JPC-2067-B were made using IMDM-C . Concentrations measured ranged from 10 to 100 nM . For certain in vivo studies , JPC-2067-B was initially dissolved in 100% DMSO and then diluted 100 fold in 1× PBS without calcium or magnesium ( Cellgro ) and administered intra-peritoneally ( i . p . ) 15 minutes following i . p . inoculation of the parasite . In other in vivo studies , the orally bioavailable pro-drug JPC-2056 ( 40 mg/kg/dose , bid ) was administered per orally by gavage beginning one day following i . p . inoculation of the parasite . DHFR from Pneumocystis carinii was produced as the recombinant enzyme expressed in Escherichia coli [41] . The sequence of the protein was identical to that predicted for the previously reported gene sequence [4] . DHFR from T . gondii was isolated directly from RH strain T . gondii grown in culture on Chinese hamster ovary cells lacking DHFR ( CHO/dhfr- , American Type Culture Collection 3952 CL ) [42] . Organisms were introduced into a confluent monolayer and harvested when the mammalian cells were lysed . The 100 , 000× g supernate was stored in liquid nitrogen . Mycobacterium avium-intracellulare used in these studies was a clinical isolate ( serovar 4 ) from Indiana University School of Medicine , Department of Pathology . The strain was maintained on Lowenstein-Jensen slants ( Baxter Scientific ) grown at room temperature . To produce enzyme , the organism was grown in Middlebrook 7H-9 liquid medium at 37°C to an OD660 of 0 . 5 to 0 . 7 , which took several weeks . At harvest , the bacteria were centrifuged , sonicated , and the 100 , 000 Xg supernate was stored under liquid nitrogen until assay . These supernates contained both DHFR and dihydroopteroate synthetase activity . Rat liver DHFR was prepared from livers of female Sprague-Dawley rats . The 100 , 000× g supernate was partially purified by ammonium sulfate precipitation; the 50–90% precipitate was re-dissolved and stored in liquid nitrogen . The spectrophotometric assay for DHFR was optimized for temperature and concentration of substrate and cofactor for each enzyme . The standard assay contained Na phosphate buffer pH 7 . 4 ( 40 . 7 mM ) , 2-mercaptoethanol ( 8 . 9 mM ) , NADPH ( 0 . 117 mM ) , dihydrofolic acid ( 0 . 09 mM ) , KCL ( 150 mM ) , and sufficient enzyme to produce a change in OD340 of 0 . 035/minute at 37°C . The reaction was continuously recorded for 3 minutes . Activity under these conditions was linear with enzyme concentration over a 4-fold range . The low background activity in the absence of dihydrofolic acid was subtracted from all rates . DHFR was assayed with several concentrations of inhibitor to produce rates ranging from 1 to 90% of the uninhibited rate . At least three concentrations were required for calculation; most curves contained five concentrations . Semi-logarithmic plots of the data gave sigmoidal curves that were fit by non-linear methods to determine the concentration yielding 50% inhibition ( IC50 ) [Prism 4 . 0 ( GraphPad ) ] . DHFR from T . gondii [43] prepared as above was also directly compared to purified recombinant P . falciparum DHFR ( pfDHFR ) and purified recombinant human DHFR ( hDHFR ) . The hDHFR was from pDFR plasmid [10] . The enzyme was purified following ammonium sulfate precipitation , methotrexate:agarose affinity chromatography , and finally a Superdex 200 size exclusion column . The pfDHFR isolation methods were those reported previously [11] , [44] . Pyrimethamine and JPC-2067-B were tested for activity against recombinant pfDHFR , recombinant hDHFR and the T . gondii lysate DHFR . The same buffer as used in the other assays comparing T . gondii DHFR with DHFRs from rat liver P . carinii and M . avium intracellulare was used but the maximal activity , temperature , and length of observation were adjusted for assays on the specific plate reader . The series of pfDHFR and hDHFR assays were run twice for hDFHR and three times for pfDHFR and the representative data are shown ( see Results ) . The tgDHFR sample was exhausted after one set of assays at a lower activity than the others ( uninhibited change in OD340 of 0 . 004/min versus 0 . 02/min for the recombinant enzymes ) . The reaction was setup at 23°C , the plate loaded , and the OD340 recorded at 20 second intervals for 10 minutes . The first 8 minutes were used to generate linear fit slopes in Excel . Each concentration has been reported as the mean of 5 replicate reactions with the standard deviation reported as the error . Results are expressed as the percent of control activity versus log concentration of inhibitor . Prism 5 . 0 was used to generate curves from 12 different concentrations of inhibitor using a non-linear fit method . JPC-2067-B levels were quantitated using an HPLC system comprised of a Spectra System P4000 pump , AS300 autosampler , UV2000 detector and a ChromJet integrator . The column is a Phenomenex Synergi 4μ MAX-RP 80A 150×4 . 6 mm , s/n 219259 . Elution was effected with a gradient of Mobile Phase A ( 0 . 05% aqueous TFA ) and Mobile Phase B ( 0 . 025% TFA in acetonitrile ) . The flow rate was 0 . 5 ml/min , the injection volume was 20 µl and the detector was set to 290 nm . Observed retention times for WR99210 , PS-15 and JPC-2067-B were 9 . 5 , 15 . 7 and 9 . 1 minutes , respectively . Tachyzoites also were used to infect mice . Outbred Swiss Webster mice were bred in our specific pathogen free colony . When they were approximately 30 g , they received 10 , 000 RH strain tachyzoites intra-peritoneally ( i . p . ) ; numbers of parasites present in peritoneal fluid were counted four days later as described [8] , [13] . Mice were maintained and utilized in accordance with IACUC and NIH guidelines and approvals . JPC-2067-B was administered parenterally . In initial studies , this was given 15 minutes after i . p . infection and then each day for four days ( 1 . 25 mg/kg/day ) . Peritoneal parasite burden was quantitated on the fourth day after injection . Control mice received 1% DMSO in PBS . Beginning one day following infection of outbred SW mice with tachyzoites of the RH strain of T . gondii mice received JPC-2056 by gavage at a concentration of 40 mg/kg in 0 . 5 ml twice daily . Peritoneal T . gondii burden was determined on day 4 following infection . Sequences of DHFR in each of the conventional parasite clonal types ( RH , type I; Me49 type II; and VEG , type III ) from the data base and by PCR using strains ( isolates ) from Brazil , Guyana , Guatemala , Canada , China , and Sri Lanka [45]–[50] were determined with PCR using cDNA or g DNA as template . The primers used were: Forward , 5′-AGGGACGGTGAAGTTTCGCTTTA-3′; Reverse , 5′-TTTCCGGTCTTCTTCGTCCATCCA-3′ . Modeling of the T . gondii DHFR was based upon the crystal structure of the closely related P . falciparum DHFR in complex with WR99210 , NADPH and dUMP ( pdb id 1j3i ) , using the structure based sequence alignment as a guide . Those residues which displayed sequence variation between P . falciparum and T . gondii DHFR and were located within 4Å of the ligand binding pocket were analysed to look for significant differences . A 42-day toxicology study in CD-1 mice at doses up to 98 mg/kg evaluating well-being , weight gain , and histopathology was performed . A comparable 42-day toxicology study in Macaca fascicularis also was performed . 7 . 5 mg/kg was established as the NOAEL ( No Observed Adverse Effect Level ) . JPC-2056 and JPC-2067 were assayed in the Ames Test with and without microsomal activation with tester strains TA97 , TA98 , TA100 , TA102 and TA1535 . Significance of differences was determined using a Mann Whitney U test or Student's T-test . All experiments were performed at least twice and representative experiments are shown .
JPC-2067-B was highly effective against T . gondii tachyzoites in tissue culture . A representative experiment of two trials is shown in Figures 2A and B . The IC50 and IC90 for JPC-2067-B were ≈20 nM and 50 nM , respectively . Differences between control and treated groups at these and higher concentrations were statistically significant ( p<0 . 05 ) . We observed some precipitation of the compounds in the stock solutions , and so the supernatant was analyzed by HPLC . We found that the actual concentrations measured in the supernatants were approximately four-fold less than the initial amounts . The actual amounts measured are shown in Figure 2 . Data are shown both as uptake of 3H uracil into nucleic acid of the parasites ( Figure 2B ) and with micrographs of Giemsa stained microscopic preparations ( Figure 2C ) , with efficacy confirmed by both methods . Direct comparison of WR99210 and JPC-2067-B and similar IC 50 and 90s for WR99210 . Human foreskin fibroblasts were tested concomitantly with T . gondii tachyzoites with increasing concentrations of JPC-2067-B . Data from a representative experiment are also shown in Figure 2A and demonstrate no toxicity measured as uptaked of tritiated thymidine by nonconfluent fibroblasts . The increased uptake of thymidine in these cultures remains unexplained but also has been noted with certain other compounds such as triclosan . In separate experiments , to determine whether JPC-2067-B would be cidal for T . gondii , cultures were maintained for 52 days after removing JPC-2067-B on the 4th day of culture . No plaques or growth of parasites were detected ( Figure 2D ) . The absence of growth following removal of JPC-2067-B from HFF exposed to T . gondii indicates that this compound is “cidal” and not merely “static” for T . gondii . JPC-2067-B was also highly effective against T . gondii tachyzoites in a mouse model . A representative experiment with JPC-2067-B is shown in Figure 3A . In the experiment in Figure 3A , mice were infected i . p . with 10 , 000 tachyzoites of the RH strain of T . gondii for 15 minutes prior to initial treatment with JPC-2067-B . For these parenterally treated mice , female mice received a dose of 1 . 25 mg/kg/day of JPC-2067-B , administered i . p . for the next 3 days . Control mice received an equivalent amount of DMSO ( 1% ) in 1× PBS . In a separate experiment , DMSO at this concentration was shown not to modify subsequent parasite numbers when compared with i . p . inoculation of PBS . Mice treated with JPC-2067-B appeared sleek and active 4 days after infection . In contrast , infected control mice appeared ill , with ruffled fur and hunched posture . Intraperitoneal parasite numbers were reduced by two logs with treatment with JPC-2067-B on the fifth day after injection of parasites ( Figure 3A ) . These differences between control and treated mice were statistically significant ( p<0 . 05 ) . In addition , a similar experiment was performed with oral administration of the orally bioavailable pro-drug JPC-2056 ( 40 mg/kg/dose , bid ) beginning one day following i . p . inoculation of the parasite . Parasite number in peritoneal fluid was quantitated three days after that , i . e . the fourth day following infection . For the mice orally treated with JPC-2056 there were similar significant differences in parasite peritoneal burden on the third day of treatment ( Figure 3B , p<0 . 03 ) . The IC50 values determined for reference compound pyrimethamine ( JPC-1090 ) were in agreement with prior assays of the compound ( S . Queener , unpublished data ) . Both JPC-1090 and JPC-2013 ( cycloguanil ) had IC50 values in the micromolar range and were not significantly selective for pathogen DHFR ( Table 1 ) . JPC-208 ( WR92210 ) was more potent , with IC50 values in the nanomolar range , but was not selective . JPC-2067-B had nanomolar IC50 values for the DHFRs from all three pathogens and higher IC50 value for the mammalian DHFR , yielding about 3 . 4 to 5 . 9 fold selectivity . The potency for this compound greatly exceeds the concentration of pyrimethamine used clinically ( Figure 4 ) . Semilogarithmic plots of the data yielded normal sigmoidal curves for pyrimethamine and cycloguanil ( Hill slope of the normalized log-concentration-response curve was about −1 ) but both WR-99210 and JPC-2067-B yielded very steep curves for the DHFRs from rat liver , P . carinii , and T . gondii; these compounds produced normal dose response curves with M . avium DHFR . The steep Hill slopes for JPC-208 and JPC-2067-B suggests that the interaction of these compounds with these enzymes is not following a simple 1∶1 interaction expected with a competitive inhibitor . In Figure 5 and Table 2 , the IC50 for P . falciparum DHFR was 3 . 9 nM , T . gondii DHFR was 32 nM , and human DHFR was 150 nM . For pyrimethamine , the IC50 for P . falciparum was 42 nM , for T . gondii DHFR was 280 nM , and for human DHFR was 1 , 900 nM . The differences in values between Figures 4 and 5 may be due to variations in assays . Assays towards the comparison to inhibition of opportunistic pathogens are run on partially purified lysates at 37°C for a shorter duration while this set of assays is run in a high-throughput manner with several recombinant enzymes and a more drawn out observation time at 23°C . The amount of enzyme used has been reduced to extend the length of observation and minimize the effect of data points lost during plate setup . These differences in methodology likely explain the slight shift in IC50 . The ratio of IC50 values measured via high throughput method ( hDHFR/tgDHFR ) to the ratio measured from lysates ( rat liver DHFR/TgDHFR ) under different conditions are 4 . 6 versus 3 . 4 , which are comparable . Overall , JPC-2067-B has considerable potency and some selectivity relative to mammalian reference enzymes , in two independent laboratories under slightly different assay conditions demonstrating the effect of this compound on T . gondii DHFR . In order to further investigate the efficacy of the dihydrotriazines on P . falciparum versus T . gondii with regard to drug design and molecular mode of action , we have analyzed structural models of the DHFR enzyme in the apicomplexan parasites . Of the 9 residues which form interactions with the dihydrotriazine inhibitor , WR99210 in the structure of P . falciparum DHFR Ile14 , Cys15 , Asp54 , Met55 , Phe58 , Ile111 , Leu119 , Ile164 and Tyr170 all are either identical or very similar in T . gondii DHFR ( Figure 6A ) . In particular Asp54 and Tyr170 which make important H-bonds to the inhibitor are conserved in T . gondii DHFR . Furthermore , modeling studies suggest that the substitution of Ile in P . falciparum DHFR for Met and Val at positions 111 and 164 , respectively , in T . gondii DHFR results in little change in the Van der Waals packing interactions made to the inhibitor ( Figure 6B ) . Modeling of the potent inhibitor JPC-2067-B into T . gondii DHFR reveals that the additional trifluoromethoxy group is positioned such that it is exposed to the solvent and as such can probably be tolerated by the enzyme with respect to inhibitor binding . In addition , Cys50 , which when mutated has been shown to play a role in pyrimethamine resistance [52] in P . falciparum DHFR , is replaced by His27 in T . gondii DHFR . Given its position close to the trifluoromethoxy group of JPC-2067-B it may well be that further modification to this part of the inhibitor could lead to favorable interactions with the imidazole ring of His27 ( Figure 6B ) . However , these small changes in the T . gondii JPC-2067-B binding site , when compared to its homologue in P . falciparum may contribute to the somewhat lower sensitivity of this enzyme to JPC-2067-B . The deduced amino acid sequences of DHFRs [43] in the data base for RH ( U . S . , type I ) , Me49 ( U . S . , type II ) , VEG ( U . S . , type III ) , and Coug ( atypical ) , and identified by PCR of DHFRs from strains isolated from Brazil , Canada , Guyana , Guatemala , China and Sri Lanka ( Table 3 , [45]–[50] ) were identical ( data not shown ) . A 42-day toxicology study in CD-1 mice ( Table 4 ) produced no histopathology findings at doses up to 98 mg/kg and no gross pathology with the exception of a reduction in the rate of weight gain . A comparable 42-day toxicology study in Macaca fascicularis ( Table 4 ) produced histopathology findings at 15 mg/kg with sproradic episodes of loose stools/diarrhea that resolved upon drug withdrawal . No histopathology or gastrointestinal effects were observed over the 42-day period . 7 . 5 mg/kg was established as the NOAEL ( No Observed Adverse Effect Level ) . When JPC-2056 and JPC-2067 were assayed in the Ames Test , with and without microsomal activation , no activity was exhibited with tester strains TA97 , TA98 , TA100 , TA102 and TA1535 ( Table 4 ) .
Our studies demonstrate that JPC-2067-B is effective against T . gondii in vitro with an IC50 of 20 nM and in vivo when administered by i . p . injection and the pro-drug JPC-2056 is effective in vivo when administered orally . Each of our results described herein with this novel new class of anti-folate compound , dihydrotriazine , parallels earlier findings with progenitors of this class which were not as suitable for use for humans , e . g . proguanil [12] and WR99210 [13] . The major and compelling advantages of JPC-2056 , which is moving into clinical trials , is in the reduction of toxicity and development of a much more readily bioavailable compound than WR99210 . WR99210 will never be a medicine for humans because of difficulties in those areas , also reflected in the effect on the mammalian enzyme , Table 1 . The advantages of bioavailability , high potency , specificity , selectivity and potential for elimination of toxicities that occur with pyrimethamine either used alone or in conjunction with sulfadiazine and other medicines and because JPC-2056 will be entering clinical trials for the treatment of malaria , testing of this new class of anti-folates against the related apicomplexan T . gondii , was very important . Our results suggest that the activity against T . gondii is significant and that JPC-2056 has the potential to replace the combination of pyrimethamine plus sulfadiazine or second line drugs in the treatment of toxoplasmosis . The modeling of T . gondii DHFR in complex with this family of inhibitors gives us understanding at the molecular level of why compounds of this class are highly active against T . gondii tachyzoites . JPC-2056 already has been optimized for pharmacokinetics and lack of toxicity and is being progressed to the clinic as a potentially effective treatment for both P . falciparum and P . vivax malaria . This ongoing work with malaria treatment provides a major benefit for the development of JPC-2056 for the treatment of toxoplasmosis . It was of importance to determine whether in DHFR the amino acids that bind this novel , highly active triazine vary in any of the atypical parasites . Analysis of available DHFR sequences in the data base for T . gondii isolates called RH , Me 49 , VEG and Coug parasites , i . e . , from a clonal types I , II and III and atypical strains , and analyses of isolates from Brazil , Guyana , Guatemala , Canada , China , and Sri Lanka [45]–[50] demonstrates that the key amino acids for binding the triazine are conserved ( data not shown ) . There are parasites that are genetically different in different countries , e . g . in Brazil there are a variety of genetically different parasites of clonal type I/III background with an association with a very high prevalence of retinal disease; in Northern Coastal South America highly virulent parasites that have recently been lethal or caused severe illness and death in French soldiers in French Guiana and in a recent epidemic in a village in Suriname [53]; and atypical parasites in Central America and Mexico . In Asia there are unique genotypes which differ from the typical I , II , III genotypes , and in Africa there are all the genetic clonal types of parasites . In Europe and Poland the predominant type is clonal type II , and in the U . S . there are other types but a recent abstract described predomininance of type II parasites . In an epidemic in Sea Otters in Moro Bay California and on Vancouver Island , the parasites are also atypical . Each of these parasites might have different growth rates ( new isolates often grow more slowly than laboratory adapted strains , JP Dubey , personal observations ) and DHFRs with slightly different sequences or significant mutations are a possibility . To begin to address this issue as it is relevant to toxoplasmosis in the developing world , we have compared the sequences of DHFRs in each of the conventional parasite clonal types ( I , II , and III ) from the data base , and by PCR of DHFR from isolates including a Brazilian strain , a strain from Guyana , a strain from Guatemala , a strain from Canada , a strain from China and a strain from Sri Lanka ( Table 3; [45]–[50] ) . There are no differences in amino acid sequence of the DHFRs . As shown in the enzyme inhibition and parasite inhibition assays herein , upon conversion of JPC-2056 to JPC-2067-B by cytochrome p 450 , the product , JPC-2067-B , becomes a highly effective treatment for apicomplexan infections . Toxicological data ( Table 4 ) supports the advancement of JPC-2056 to clinical development . A 42-day toxicology study in CD-1 mice produced no histopathology finings at does up to 98 mg/kg and no gross pathology with the exception of a reduction in the rate of weight gain . A comparable 42-day toxicology study in Macaca fascicularis produced histopathology findings at 15 mg/kg with sproratic episodes of loose stools/diarrhea that resolved upon drug withdrawal . Antimicrobial activities of JPC-2067 suggest that the gastrointestinal events may be related to disruptions in intestinal flora . No histopathology or gastrointestinal effects were observed over the 42-day period . 7 . 5 mg/kg was established as the NOAEL ( No Observed Adverse Effect Level ) . JPC-2056 and JPC-2067 were assayed in the Ames Test with and without microsomal activation . No activity was exhibited with tester strains TA97 , TA98 , TA100 , TA102 and TA1535 . In summary , JPC-2056 has two advantages over WR99210 . Biguanides are better absorbed and less toxic than their dihydrotriazine metabolites as has been well established in the case of Proguanil . Cycloguanil , the active dihydrotriazine metabolite of biguanide prodrug Proguanil is poorly absorbed and is locally toxic . In addition , WR99210 and its biguanide PS-15 possess a 2 , 4 , 5-trichlorophenoxy structural feature , which is synthesized from 2 , 4 , 5-trichloro-phenol . This phenol has the potential to generate the highly regulated toxin , 2 , 3 , 7 , 8-tetrachlorodibenzo-p-dioxin ( TCDD ) . This issue precluded the development of both WR99210 as well as its prodrug PS-15 . Significantly , JPC-2056 and its active metabolite JPC-2067-B are devoid of this liability and as such offer a significant advance in this therapeutic class ( Table 4 ) . Finally , the LD50 value for JPC-2056 at high doses in the Thompson Antimalarial Assay provides sufficient therapeutic index to justify continued clinical development . Improved , simpler to use , less toxic drugs that are easily affordable , which can be prepared in stable solution , are needed to treat toxoplasmosis . This new biguanide , moving into clinical trials , promises to be a major advance for the treatment of those with all forms of toxoplasmosis throughout the world . The development of JPC-2056 addresses factors limiting use of current medicines in the developing world for this neglected tropical disease including ease of administration , lack of toxicity , ease of monitoring , the potential for low cost , pediatric and parenteral formulations of a new and improved medicine . This therapeutic is likely to be of special benefit for those with this neglected tropical disease in developing countries . JPC-2067-B and JPC-2056 have considerable promise as a new class of anti-folate medicines to provide improved and less toxic means to treat toxoplasmosis as well as malaria caused by P . falciparum and P . vivax and thus to become a new standard of care for treating these diseases . The potential of these compounds to act in the absence of sulfadiazine or in conjunction with other anti-microbials such as atovaquone presents the possibility of increasing tolerance and decreasing detrimental side effects including hypersensitivity . | Toxoplasmosis is a neglected tropical disease , an emerging disease as well as a significant problem in developed countries causing a substantial health burden . Better medicines with less toxicity are greatly needed . Herein , we found that a novel triazine currently being advanced to clinical trials for malaria , JPC-2067-B , is highly effective against T . gondii . We demonstrate that JPC-2067-B inhibits T . gondii growth in culture ( IC50 20 nM ) , inhibits the purified enzyme ( IC50 6 . 5 nM ) , is more efficacious than pyrimethamine , and is cidal in vitro . JPC-2067-B administered parenterally and the orally administered pro-drug ( JPC-2056 ) are also effective against T . gondii tachyzoites in vivo . A molecular model of T . gondii DHFR-TS complexed with JPC-2067-B was developed . We found that the three main parasite clonal types and isolates from South and Central America , the United States , Canada , China , and Sri Lanka have the same amino acid sequences preserving key binding sites for the triazine . Toxicology data are presented . JPC-2056/JPC-2067-B have potential to be more effective and less toxic treatments for toxoplasmosis than currently available medicines . | [
"Abstract",
"Methods",
"Results",
"Discussion"
] | [
"infectious",
"diseases/protozoal",
"infections"
] | 2008 | Novel Triazine JPC-2067-B Inhibits Toxoplasma gondii In Vitro and In Vivo |
In this paper we describe how to efficiently record the entire genetic history of a population in forwards-time , individual-based population genetics simulations with arbitrary breeding models , population structure and demography . This approach dramatically reduces the computational burden of tracking individual genomes by allowing us to simulate only those loci that may affect reproduction ( those having non-neutral variants ) . The genetic history of the population is recorded as a succinct tree sequence as introduced in the software package msprime , on which neutral mutations can be quickly placed afterwards . Recording the results of each breeding event requires storage that grows linearly with time , but there is a great deal of redundancy in this information . We solve this storage problem by providing an algorithm to quickly ‘simplify’ a tree sequence by removing this irrelevant history for a given set of genomes . By periodically simplifying the history with respect to the extant population , we show that the total storage space required is modest and overall large efficiency gains can be made over classical forward-time simulations . We implement a general-purpose framework for recording and simplifying genealogical data , which can be used to make simulations of any population model more efficient . We modify two popular forwards-time simulation frameworks to use this new approach and observe efficiency gains in large , whole-genome simulations of one to two orders of magnitude . In addition to speed , our method for recording pedigrees has several advantages: ( 1 ) All marginal genealogies of the simulated individuals are recorded , rather than just genotypes . ( 2 ) A population of N individuals with M polymorphic sites can be stored in O ( N log N + M ) space , making it feasible to store a simulation’s entire final generation as well as its history . ( 3 ) A simulation can easily be initialized with a more efficient coalescent simulation of deep history . The software for recording and processing tree sequences is named tskit .
Since the 1980’s , coalescent theory has enabled computer simulation of the results of population genetics models identical to that which would be produced by large , randomly mating populations over long periods of time without actually requiring simulation of so many generations or meioses . Coalescent theory thus had three transformative effects on population genetics: first , giving researchers better conceptual tools to describe gene trees and thus bringing within-population trees into better focus; second , producing analytical methods to estimate parameters of interest from genetic data; and finally , providing a computationally feasible method to produce computer simulations of population genetics processes . However , these powerful advances came with substantial caveats: the backwards-in-time processes that are described by coalescent theory are only Markovian , and thus feasible to work with , under the following important assumptions: ( a ) random mating , ( b ) neutrality , ( c ) large population size , and ( d ) small sample size relative to the population size . The first two assumptions can be side-stepped to a limited extent [1 , 2] , but it remains a challenge to map results of coalescent models onto species that are distributed across continuous geographical space [3 , 4] and/or have large numbers of loci under various sorts of selection . Usually , the relationship between the life history of a species—fecundity and mortality schedules , density-dependent effects on fitness , and demographic fluctuations—are all absorbed into a single compound parameter , the coalescence rate . More mechanistic models are possible using “forwards–backwards” simulations , that first simulate population size changes forwards in time and then thread a coalescent backwards [5] , but these still require the assumptions above to be met for each subpopulation . The last assumption is no longer safe , either—for example , a recent study [6] simulated 600 , 000 samples of human chromosome 20 to examine biases in GWAS . Several studies have now shown that in samples approaching the size of the population , genealogical properties may be distorted relative to the coalescent expectation [7–9] . These considerations , and increasing computational power , have led to a resurgence of interest in large forwards-time , individual-based simulations . For instance , Harris and Nielsen [10] used SLiM [11] to simulate ten thousand human exomes to assess the impact of genetic load and Neanderthal introgression on human genetic diversity . Sanjak et al . [12] used fwdpp [13] to simulate a series of models of quantitative traits under mutation-selection balance with population sizes of 2 × 104 diploids in stable populations and populations growing up to around 5 × 105 individuals , using the output to explore the relationship between the genotype/phenotype model and GWAS outcomes . Modern computing power easily allows simulations of birth , death and reproduction in a population having even hundreds of millions of individuals . However , if our interest lies in the resulting genetic patterns of variation—and often , the point of such simulations is to compare to real data—then such simulations must record each individual’s genome . As samples of most species’ genomes harbor tens or hundreds of millions of variant sites , carrying full genotypes for even modest numbers of individuals through a simulation can quickly become prohibitive . To make matters worse , a population of size N must be simulated across many multiples of N generations to produce stable genetic patterns [14 , 15] . Because of this computational burden , even the fastest simulation frameworks such as SLiM 2 [16] and fwdpp [13] can “only” simulate tens of megabases of sequence in tens of thousands of individuals for tens of thousands of generations . In practice , current state-of-the-art simulation software may take on the order of weeks to simulate models of large genomic regions without selection [13 , 17] , and existing simulation engines differ in how efficiently they calculate fitnesses in models with selection [13] . These population and region sizes are still substantially short of whole genomes ( hundreds to thousands of megabases ) for many biological population sizes of interest . However , it is thought that most genetic variation is selectively neutral ( or nearly so ) . By definition , neutral alleles carried by individuals in a population do not affect the population process . For this reason , if one records the entire genealogical history of a population over the course of a simulation , simply laying down neutral mutations on top of that history afterwards is equivalent to having generated them during the simulation: it does not matter if we generate each generation’s mutations during the simulation , or afterwards . To add mutations after the fact , we need to know the genealogical trees relating all sampled individuals at each position along the genome . Combined with ancestral genotypes and the origins of new mutations , these trees completely specify the genomic sequence of any individual in the population at any time . To obtain this information , we record from forward simulation the population pedigree—the complete history of parent-offspring relationships of an entire population going back to a remote time—and the genetic outcomes of each ancestral meiosis , periodically discarding all information irrelevant to the genetic history of the extant population . The information in this embellished pedigree is stored as a succinct tree sequence ( or , for brevity , “tree sequence” ) , which contains all the information necessary to construct the genealogical tree that relates each individual to every other at each position on the genome . The idea of storing genealogical information to speed up simulations is not new . It was implemented in AnA-FiTS [18] , but without the critical step of discarding irrelevant genealogical information . Padhukasahasram et al . [19] obtained impressive speedups for a Wright–Fisher simulation by keeping track of genealogies over the preceding 8 generations and only tracking neutral genotypes for those segments having descendants across this window . Our approach is similar , but uses genealogies across the entire duration of the simulation . The embellished pedigree is equivalent to the ancestral recombination graph , or ARG [20 , 21] , which has been the subject of substantial study [22–25] . However , it is unclear if an ARG-based approach would share the computational advantages of the data structures we use here [26] . In this paper , we describe a storage method for succinct tree sequences ( and hence , genome sequence ) as well as an algorithm for simplifying these . The data structure is succinct in the sense that its space usage is close to optimal , while still allowing efficient retrieval of information ( see , e . g . , [27] ) . We also describe how these tools can efficiently record , and later process , the embellished population pedigree from a forwards-time simulation . While providing substantial savings in computational time and space , our methods provide in principle much more information than simply simulating the genomes—the tree sequence encodes all marginal genealogies of individuals living at the end of the simulation . These marginal genealogies enable fast data storage and processing , but also provide additional information that can be used to better understand the notoriously complex dynamics of population genetics . Although we were motivated by a need for more efficient genomic simulations , these tools may prove more widely useful . This work originated as improvements to the algorithmic tools and data structures in the coalescent simulator msprime . The software tools described here for working with tree sequences are referred to as tskit; they are currently bundled with the Python package msprime , but will soon be separately available as a Python API and an embeddable C library .
To measure the performance gains from recording the pedigree we ran simulations both with and without recording . ( Although we record more than just the parent–offspring relationships of the pedigree , for brevity we refer to the method as “pedigree recording” ) . All simulations used fwdpp to implement a discrete-time Wright-Fisher population of N diploid individuals , simulated for 10N generations ( details below ) . Simulations without pedigree recording introduced neutral mutations at a rate equal to the recombination rate , so μ = r , where μ and r are the expected per-generation number of mutations per gamete and recombination breakpoints per diploid , respectively . Simulations with pedigree recording introduced neutral mutations at the same rate retrospectively , as described below , resulting in statistically identical simulation results . We ran simulations with different values of N and varied the size of the genomic region according to the scaled recombination parameter ρ = 4Nr . Deleterious mutations were introduced at rate ρ/100 per generation , drawing scaled selection coefficients ( 2Ns ) from a Gamma distribution with a mean of -5 and a shape parameter of 1 . This distribution of fitness effects results in thousands of weakly-deleterious mutations segregating in the population , many of which drift to intermediate frequencies . The case of many mutations with selection is a non-trivial violation of exchangeability assumptions of the coalescent [2] . Therefore , these selected mutations must be explicitly tracked in our forward simulation and the time savings due to pedigree recording come from not having to record neutral mutations . Pedigree tracking dramatically reduced runtimes , as shown in Fig 1 , producing a relative speedup of up to around 50 fold relative to standard simulations that track neutral mutations ( Fig 2 ) . Pedigree tracking results in greater relative speedups for larger N and we observe increasing relative speedups as 4Nr increases for a given N ( Fig 2 ) . Importantly , runtimes are approximately linear in region size ρ when pedigree tracking ( partially obscured by the log scale of the horizontal axis in Fig 1 ) . In a more limited set of neutral simulations we found the same qualitative behavior , and a numerically larger speedup by using pedigree tracking ( see S1 Text ) . In our implementation , simulations with pedigree recording used substantially more RAM than simple forward simulations ( see S1 Text ) . This is unsurprising: unsimplified tree sequences grow quickly , and so storing history can use arbitrarily much memory . However , this is not a requirement of the method , only a straightforwards consequence of a speed–memory tradeoff: the amount of required memory is mostly determined by the interval between simplification steps , but less frequent simplification reduces overall computation time ( see S1 Text ) . In fact , our method could in some situations reduce the amount of memory required , if memory usage in the forwards simulation was dominated by the cost of maintaining neutral genetic variants . We now explain what we actually did to achieve this 50× speedup . The “pedigree recording” simulations above recorded information about each new individual in a collection of tables that together define a succinct tree sequence ( or , simply “tree sequence” ) . A tree sequence is an encoding for a sequence of correlated trees , such as those describing the history of a sexual population . Tree sequences are efficient because branches that are shared by adjacent trees are stored once , rather than repeatedly for each tree . The topology of a tree sequence is defined via its nodes and edges , while information about variants is recorded as sites and mutations; we give an example in Fig 3 . This formulation is derived from the “coalescence records” encoding of tree sequences [26] , normalised to remove redundancy and generalised to include a more general class of tree topologies . The nodes of a tree sequence correspond to the vertices in the individual genealogies along the sequence . Each node refers to a specific , distinct ancestor , and so has a unique “time” , thought of as the node’s birth time , which determines the height of any vertices the node is associated with . ( Note that since each node time is equal to the amount of time since the birth of the corresponding parent , time is measured in clock time , not in meioses ) . The example of Fig 3 has five nodes: nodes 0 , 1 and 2 occur at time 0 and are the samples , while nodes 3 and 4 represent those ancestors necessary to record their genealogy , who were born one and two units of time in the past , respectively . The edges define how nodes relate to each other over specific genomic intervals . Each edge records the endpoints [ℓ , r ) of the half-open genomic interval defining the spatial extent of the edge; and the identities p and c of the parent and child nodes of a single branch that occurs in all trees in this interval . The spatial extent of the edges defining the topology of Fig 3 are shown in the bottom left panel . For example , the branch joining nodes 1 to 3 appears in both trees , and so is recorded as a single edge extending over the whole chromosome . It is this method of capturing the shared structure between adjacent trees that makes the tree sequence encoding compact and algorithmically efficient . Recovering the sequence of trees from this information is straightforward: each point along the genome at which the tree topology changes is accompanied by the end of some edges and the beginning of others . Since each edge records the genomic interval over which a given node inherits from a particular ancestor , to construct the tree at a certain point in the genome we need only retrieve all edges overlapping that point and construct the corresponding tree . To modify the tree to reflect the genealogy at a nearby location , we simply remove those edges whose intervals do not overlap that location , and add those new edges whose intervals do . Incidentally , this property that edges naturally encode differences between nearby trees ( e . g . , as “subtree prune and regraft” moves ) allows for efficient algorithms to compute statistics of the genome sequence that take advantage of the highly correlated nature of nearby trees [26] . Given the topology defined by the nodes and edges , sites and mutations encode the sequence information for each sample in an efficient way . Each site records two things: its position on the genome and an ancestral state . For example , in Fig 3 we have two sites , one at position 2 . 5 with ancestral state ‘A’ and the other at position 7 . 5 with ancestral state ‘G’ . If no mutations occur at a given site , all nodes inherit the ancestral state . Each mutation records three things: the site at which it occurs , the first node to inherit the mutation , and the derived state . Thus , all nodes below the mutation’s node in the tree will inherit this state , unless further mutations are encountered . Three mutations are shown in Fig 3 , illustrated by red stars . The first site , in the left-hand tree , has a single mutation , which results in node 2 inheriting the state ‘T’ . The second site , in the right hand tree , has two mutations: one occurring over node 3 changing the state to ‘C’ , and a back mutation over node 1 changing the state to ‘G’ . This encoding of a sequence of trees and accompanying mutational information is very concise . To illustrate this , we used msprime to simulate 500 , 000 samples of a 200 megabase chromosome with human-like parameters: Ne = 104 and per-base mutation and recombination rates of 10−8 per generation . This resulted in about 1 million distinct marginal trees and 1 . 1 million infinite-sites mutations . The HDF5 file encoding the node , edge , site and mutation tables ( as described above ) for this simulation consumed 157MiB of storage space . Using the tskit Python API , the time required to load this file into memory was around 1 . 5 seconds , and the time required to iterate over all 1 million trees was 2 . 7 seconds . In contrast , recording the topological information in Newick format would require around 20 TiB and storing the genotype information in VCF would require about 1 TiB ( giving a compression factor of 144 , 000 in this instance ) . Working with either the Newick or VCF encoding of this dataset would likely require several days of CPU time just to read the information into memory . The facilities for working with succinct tree sequences are implemented as part of the tskit Python API , which provides a powerful platform for processing tree topology and mutation data . The portions of tskit that we discuss here are dedicated to tree sequence input and output using simple tables of data , as described above , so we refer to this as the “Tables API” . The Tables API is primarily designed to facilitate efficient interchange of data between programs or between different modules of the same program . We adopted a ‘columnar’ design , where all the values for a particular column are stored in adjacent memory locations . There are many advantages to columnar storage—for example , since adjacent values in memory are from the same column , they tend to compress well , and suitable encodings can be chosen on a per-column basis [28] . A particular advantage of this approach is that it enables very efficient copying of data , and in principle zero-copy data access ( where a data consumer reads directly from the memory of a producer ) . Our implementation efficiently copies data from Python as a NumPy array [29] into the low-level C library used to manipulate tree sequences . This architecture allows for data transfer rates of gigabytes per second ( impossible under any text-based approach ) , while retaining excellent portability . NumPy’s array interface provides a great deal of flexibility and efficiency , and makes it straightforward to transfer data from sources such as HDF5 [30] or Dask [31] . For small scale data and debugging purposes , a simple text based format is also supported . The tskit Python Tables API provides a general purpose toolkit for importing and processing succinct tree sequences , and a collection of tutorials are being developed at https://github . com/tskit-dev/tutorials . Interoperation with Python simulators is then straightforward . The implementation we benchmark here uses pybind11 ( https://github . com/pybind/pybind11/ ) to interface with the fwdpp C++ API [13] . No modifications were required to the fwdpp code base; rather , we simply need to bookkeep parent/offspring labels , and perform simple processing of the recombination breakpoints from each mating event to generate node and edge data . This information is then periodically copied to the tskit Tables API , where it is sorted and simplified . To record the genealogical history of a forwards time simulation , we need to record two things for each new chromosome: the birth time; and the endpoints and parental IDs of each distinctly inherited segment . These are naturally stored as the nodes and edges of a tree sequence . To demonstrate the idea , we write out in pseudocode how to run a neutral Wright–Fisher simulation that records genealogical history in this way . The simulation will run for T generations , and has N haploid individuals , each carrying a single chromosome of length L . For simplicity , we sample exactly one crossover per generation . Note that the table recording portion of the algorithm does not depend on the Wright–Fisher nature of the population simulation; next we will describe how to record tables from any simulation . We use R U ( A ) to denote an element of the set A chosen uniformly at random ( and all such instances are independent ) . Given a node table N , the function N . addrow ( t ) adds a new node to the table N with time t and returns the ID of this new node . Similarly , the function E . addrow ( ℓ , r , p , c ) adds a new edge ( ℓeft , right , parent , child ) to the edge table E . The function simplify ( P , N , E ) ( described below ) simplifies the history stored in the tables N and E to the minimal information required to represent the genealogies of the list of node IDs P; after simplification the nodes appearing in P are relabeled ( 0 , 1 , … , |P| − 1 ) . A step-by-step explanation follows the pseudocode . It is desirable for many reasons to remove redundant information from a tree sequence . To formalize this: suppose that we are only interested in a subset of the nodes of a tree sequence ( which we refer to as our ‘samples’ ) , and wish to reduce this input tree sequence to the smallest one that still completely describes the history of the specified samples , having the following properties: Simplification is essential not only for keeping the information recorded by forwards simulation manageable , but also is useful for extracting subsets of a tree sequence representing a very large dataset . We implement simplification by starting at the end of the simulation , and moving back up through history , recording in the new tree sequence only that information necessary to construct the tree sequence of the specified individuals . This process of tracing ancestry back through time in a pedigree was the motivation for Hudson’s coalescent simulation algorithm [33] , so it is unsurprising that simplification uses many of the same tools as the implementation of Hudson’s algorithm in msprime [26] . The main difference is that events in a coalescent simulation are random , while in our simplification algorithm they are predetermined by history . An implementation in pseudocode is provided in S1 Text , and a python implementation as supplementary information . Conceptually , this works by ( a ) beginning by painting the chromosome in each sample a distinct color; ( b ) moving back through history , copying the colors of each chromosome to the portions of its parental chromosomes from which it was inherited; ( c ) each time we would paint two colors in the same spot ( a coalescence ) , record that information as an edge and instead paint a brand-new color; and ( d ) once all colors have coalesced on a given segment , stop propagating it . This “paint pot” description misses some details—for instance , we must ensure that all coalescing segments in a given individual are assigned the same new color—but is reasonably close . Fig 5 shows an example tree sequence , before and after simplification , and Fig 6 depicts the “paint pot” state of the algorithm during the process of simplifying this tree sequence . Since the method begins with the samples and moves back through time , in the output tree sequence , the n samples will be numbered 0 , 1 , … , n − 1 and subsequent nodes will be ordered by time since birth . This is seen in the red labels of Fig 5 . More concretely , the algorithm works by moving back through time , processing each parent in the input tree sequence in chronological order . The main state of the algorithm at each point in time is a set of ancestral lineages , and each lineage is a linked list of ancestral segments . An ancestral segment ( ℓ , r , u ) is found in a lineage if the output node u inherits the genomic interval [ℓ , r ) from that lineage ( and so u corresponds to a “color” in the description above ) . We also maintain a map from input nodes to lineages . Crucially , the time required to run the algorithm is linear in the number of edges of the input tree sequence .
The methods described here for efficiently storing tree sequences may prove useful in other fields . We have focused on the interpretation of tree sequences as the outcome of the process of recombination , but in principle , we can efficiently encode any sequence of trees which differ by subtree-prune-and-regraft operations . Since each such operation requires a constant amount of space to encode , the total space required is O ( n + t ) for t trees with n leaves [26] . For instance , the large numbers of large , correlated trees produced by MCMC samplers used in Bayesian phylogenetics ( e . g . , [38] ) might be compactly stored as a tree sequence , which would then allow highly efficient computation of properties of the posterior distribution . In this article , we applied our methods for storing trees to the problem of pedigree recording in a forward-time simulation . However , the method applies to any simulation scheme generating nodes and edges . For example , one could use the methods described here to generate succinct tree sequences under coalescent processes not currently implemented in msprime , such as the coalescent with gene conversion [39] , using the structured coalescent to model various forms of natural selection [40–42] , or the coalescent within a known pedigree . For such models , one could in principle generate tables of nodes and edges to be simplified in tskit . The resulting succinct tree sequence object would be in the same format as those generated by msprime’s simulate function , and therefore compatible with existing methods for downstream analyses . Another application of our methods would be the case of simulating coalescent histories conditional on known pedigrees . The standard description of the Wright-Fisher coalescent averages over pedigrees . However , conditional on a realized pedigree , the distribution of coalescent times in the recent past differs from that of the unconditional coalescent [43] . For populations with known pedigrees ( e . g . , [44] ) , it may be of use to simulate transmission along such pedigrees for the purpose of inference . In preparing this manuscript , we debated a number of possible terms for the embellished pedigree , i . e . , the “pedigree with ancestral recombination information” , the object through which each tree of a tree sequence is threaded . Etymological consensus [45] has “pedigree” derived from the french “pied de grue” for the foot of a crane ( whose branching pattern resembles the bifurcation of a single parent-offspring relationship ) . An analogous term for the embellished pedigree might then be nedigree , from “nid de grue” , as the nest of a crane is a large jumble of ( forking ) branches . We thought it would be confusing to use this term throughout the manuscript , but perhaps it will prove useful elsewhere .
We implemented simulations and the connection to tskit in C++ , using fwdpp library functions and interface code using a continuum-sites model for both mutation and recombination . Simulations were run using fwdpy11 ( version 0 . 13 . a0 ) , a Python package based on fwdpp ( version 0 . 5 . 7 ) . The majority of results are presented based on a single-threaded implementation . However , we also implemented a parallelized version using Python’s queue . Queue to run the simplification step in a separate Python thread . Our implementation allows a maximum of four simplification intervals to be in the queue at once . This parallelized version also performed fitness calculation in parallel using two threads of execution in C++ . Code for all simulations and figures is available at https://github . com/petrelharp/ftprime_ms . These made use of the GNU Scientific Library ( version 1 . 16 , [46] ) , pybind11 ( version 2 . 2 . 1 , [47] ) , and GCC ( version 4 . 8 . 5 ) . We ran all benchmarks on an Ubuntu Linux ( version 16 . 04 ) system with two 2 . 6 GHz Intel E5-2650 CPU with hyperthreading enabled . We ran one simulation at a time and the machine was under minimal load otherwise . We used GNU parallel [48] to kill any simulation that did not finish within 72 hours , and the Linux time command to record run time and peak memory usage of each replicate . | Sexually reproducing organisms are related to the others in their species by the complex web of parent-offspring relationships that constitute the pedigree . In this paper , we describe a way to record all of these relationships , as well as how genetic material is passed down through the pedigree , during a forwards-time population genetic simulation . To make effective use of this information , we describe both efficient storage methods for this embellished pedigree as well as a way to remove all information that is irrelevant to the genetic history of a given set of individuals , which dramatically reduces the required amount of storage space . Storing this information allows us to produce whole-genome sequence from simulations of large populations in which we have not explicitly recorded new genomic mutations; we find that this results in computational run times of up to 50 times faster than simulations forced to explicitly carry along that information . | [
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"... | 2018 | Efficient pedigree recording for fast population genetics simulation |
For the yeast Saccharomyces cerevisiae , nutrient limitation is a key developmental signal causing diploid cells to switch from yeast-form budding to either foraging pseudohyphal ( PH ) growth or meiosis and sporulation . Prolonged starvation leads to lineage restriction , such that cells exiting meiotic prophase are committed to complete sporulation even if nutrients are restored . Here , we have identified an earlier commitment point in the starvation program . After this point , cells , returned to nutrient-rich medium , entered a form of synchronous PH development that was morphologically and genetically indistinguishable from starvation-induced PH growth . We show that lineage restriction during this time was , in part , dependent on the mRNA methyltransferase activity of Ime4 , which played separable roles in meiotic induction and suppression of the PH program . Normal levels of meiotic mRNA methylation required the catalytic domain of Ime4 , as well as two meiotic proteins , Mum2 and Slz1 , which interacted and co-immunoprecipitated with Ime4 . This MIS complex ( Mum2 , Ime4 , and Slz1 ) functioned in both starvation pathways . Together , our results support the notion that the yeast starvation response is an extended process that progressively restricts cell fate and reveal a broad role of post-transcriptional RNA methylation in these decisions .
Upon nutrient limitation , diploid cells of the yeast Saccharomyces cerevisiae can undergo two distinct developmental responses . In the presence of a fermentable carbon source ( e . g . , dextrose or galactose ) , starvation induces a modified mitotic division that produces elongated daughter progeny termed pseudohyphae ( PH ) [1] . Reiterated cell division under this PH program forms chains of elongated cells on solid agar , allowing yeast to forage for nutrients [2] , [3] . In contrast , cells engage in meiotic development and sporulation if starved for nitrogen in the presence of a non-fermentable carbon source ( e . g . , acetate or glycerol ) . Under this program , the diploid genome is duplicated ( 2C to 4C ) and then segregated into four haploid ( 1C ) meiotic products encased in a spore wall . This spore structure protects haploid progeny until favorable nutrient conditions are available . Recent findings suggest that the two developmental responses to nitrogen deprivation , PH development and meiotic sporulation , are not entirely separate pathways . First , cells that are returned to mitotic growth from meiotic prophase produce elongated buds , reminiscent of PH cells [4] . Second , PH development and sporulation share a set of regulatory factors . Genes that are necessary for meiotic induction , IME1 and IME2 ( Inducer of Meiosis 1 and 2 , respectively ) [5] , [6] , [7] , [8] , are also necessary for PH development and the subsequent formation of filaments on solid agar [9] . Furthermore , strains lacking the function of the early meiotic gene IME4 display both meiotic defects and an increased ability to adhere to agar , a phenotype associated with PH development [10] , [11] . In yeast , IME4 encodes the sole functional member of a class of RNA-modifying enzymes conserved throughout eukaryotes [12] . These enzymes , identified by homology to the N6-adenosyl methyltransferase in humans , MT-A70 , catalyze the post-transcriptional methylation of adenosine ( to form N6-methyladenosine—m6A ) in RNA . The function of this modification on mRNA is as yet unclear . In vitro work suggests that m6A enhances the translational activity of modified messages [13] , whereas in vivo experiments suggest that this modification may play an additional role in message stability and processing [14] , [15] , [16] . Although this form of RNA methylation is barely detectable in yeast undergoing mitotic growth , m6A accumulates on mRNA molecules during meiosis [17] , [18] . Strains encoding catalytically inactive alleles of IME4 do not accumulate m6A and display defects in meiotic entry [18] . Ime4 modifies the transcripts of IME1 and IME2 under these conditions , which may explain these defects upon nutrient starvation [17] . Here , we investigated the role of mRNA methylation in the programmed response to nutrient starvation . Because earlier work had shown that cells remain capable of resuming mitotic growth until the exit from meiotic G2 ( reviewed in [19] ) , we examined the early starvation response in temporal detail . We found that cells were already committed to a starvation response after meiotic cell cycle entry , because they formed PH buds when returned to nutrient-rich conditions . Lineage restriction during this period was partially dependent on the RNA methylation activity of Ime4 , which had separable roles in promoting meiosis and inhibiting PH growth . Both functions also required Mum2 and Slz1 , two poorly understood meiotic proteins that interacted with Ime4 and , like Ime4 , were necessary for maintaining normal levels of meiotic mRNA methylation . These results point to a central role of mRNA methylation in coordinating starvation-induced developmental decisions in yeast .
We investigated the relationship between meiotic induction and PH growth in SK1 , a strain that efficiently undergoes both the PH and meiotic developmental programs [9] , [20] . To analyze the early starvation response in a controlled and synchronous manner , we employed a Return-To-Growth ( RTG ) assay [19] , [21] , in which diploid cells were incubated for a given amount of time in extremely nutrient-poor liquid medium ( SPO ) before being returned to rich medium ( YPD ) . Previous studies used this approach to show that cells exiting from meiotic G2/prophase are committed to meiosis and will complete sporulation even in rich medium [22] , [23] , suggesting that analysis of cell morphology after RTG provides a measure for the developmental potential of nutrient-starved cells . By analyzing morphological changes at hourly intervals in an RTG time course , we confirmed that cells become committed to meiosis as they exit from meiotic G2/prophase and enter the meiotic divisions . This commitment occurred 5 to 7 hours after inoculation in SPO in our strains ( Figure 1A , 1B ) . Analysis of cell morphology from the RTG experiment also revealed an earlier decision point , when cells became committed to a starvation response . Cells returned to growth after short starvation ( 0–1 hours ) formed the ovoid buds characteristic of vegetative growth . However , cells that had largely completed pre-meiotic S phase or were in meiotic G2/prophase ( 3–4 hours after shift to SPO ) were unable to do so . Instead , these cells formed elongated daughter cells that resembled PH cells ( Figure 1A , 1B ) . Similar elongated buds are also apparent in images of RTG cells published recently by Dayani and colleagues [4] . Further analysis revealed that formation of these elongated buds paralleled PH development on solid nitrogen starvation medium ( SLAD ) in all aspects tested . Specifically , RTG3 bud elongation occurred only in diploid cells and was dependent on FLO11 , which encodes a cell surface protein necessary for PH development , and its transcriptional regulator , FLO8 ( Figure 1C–1F ) [24] , [25] , [26] . Furthermore , buds formed after DNA replication and mother and daughter pairs re-budded synchronously after cytokinesis ( Figure S1 ) [3] . We termed this process RTG-PH development and conclude that , after meiotic entry , yeast cells are restricted to either meiosis or PH development . This finding suggests that nutrient-deprived yeast pass a decision point that commits them to starvation-induced differentiation . Because this developmental restriction coincided with pre-meiotic S phase ( Figure 1B ) , we investigated whether pre-meiotic DNA replication was required for RTG-PH development . Pre-meiotic DNA synthesis in meiosis was prevented either chemically , using hydoxyurea , or genetically , by deleting the S phase cyclins CLB5 and CLB6 [27] . Neither condition inhibited PH development during RTG or on solid medium ( Figure S2 ) . In fact , when pre-meiotic DNA synthesis was prevented , cells instead replicated the genome upon RTG ( Figure S2 ) . These observations indicate that pre-meiotic S phase is not itself necessary for RTG-PH development . Notably , RTG-PH developmental potential followed the “readiness-for-sporulation" period as defined by Simchen as colleagues , which occurred earlier in meiosis ( 1 hour after induction into SPO ) under our sporulation conditions ( Figure S2 ) . To probe the genetic underpinnings of RTG-PH development , we investigated the roles of factors known to regulate both meiosis and PH growth . The transcription factor Ime1 is essential for entry into the meiotic program [5] . Similarly , loss of the meiosis-specific CDK-like kinase Ime2 leads to an extreme delay in meiotic entry [28] . Both factors are also required for PH development on SLAD medium [5] , [6] , [7] . We found that in the absence of either IME1 or IME2 , cells failed to enter RTG-PH development and instead formed ovoid buds upon RTG3 ( Figure 2A , 2B ) , although it should be noted that ime2Δ/Δ cells were able to form elongated RTG-PH buds after extended periods in SPO ( Figure S3 ) . These data suggest that , upon severe starvation , Ime1 and Ime2 promote both RTG-PH development and meiosis . Because IME1 and IME2 are both regulated by the RNA methyltransferase Ime4 , we also analyzed meiosis and RTG-PH development in ime4Δ/Δ mutants . Previous work demonstrated that IME4 promotes efficient entry into meiosis , although the severity of the meiotic entry defect of ime4Δ/Δ mutants varies considerably between strain backgrounds [17] , [18] . In SK1 , ime4Δ/Δ mutants exhibited only a minor delay in the initiation of meiotic DNA replication ( Figure 3A ) , but were severely delayed in exit from meiotic G2/prophase as determined by monitoring the induction of the middle-meiotic transcription factor NDT80 and the kinetics of meiotic DNA segregation ( Figure 3B , 3C ) . Additionally , spore formation was substantially reduced in ime4Δ/Δ cells ( Figure 3D ) . However , the viability of those spores that formed was comparable to that of wild-type cells , indicating that , although the meiotic divisions were delayed , chromosome segregation was not affected in these strains ( Figure 3E ) . A strain carrying point mutations in the evolutionarily-conserved catalytic motif IV of Ime4 ( ime4-D349A , W351A—referred as ime4-cat ) [12] , [18] recapitulated these phenotypes , albeit with reduced severity ( Figure 3A–3E ) , indicating that the RNA methyltransferase activity of Ime4 contributes to the efficient progression through meiosis . Unlike IME1 or IME2 , loss of IME4 leads to increased agar adhesion [10] , a phenotype associated with increased PH development . Moreover , deletion of IME4 or mutation of its RNA methyltransferase domain resulted in bud hyper-elongation upon RTG3 and the formation of hyper-filamentous colonies on SLAD medium ( Figure 3F , 3G ) . These phenotypes represented genuine forms of PH development because they were dependent on FLO11 and FLO8 ( Figure S4 ) . ime4Δ/Δ cells lacking FLO11 or FLO8 failed to form elongated daughter cells upon RTG and were deficient for PH colony development on nitrogen starvation SLAD medium . Thus , IME4 acts as an inhibitor of PH development . To test whether inhibition of PH development occurred independently of the role Ime4 plays in regulating IME1 and IME2 , we analyzed double mutants . As shown in Figure 3H and 3I , ime4Δ/Δ ime2Δ/Δ double mutants were hyper-elongated in both the RTG and SLAD contexts , even when compared to a time point at which ime2Δ/Δ cells are capable of forming RTG-PH cells ( Figure S2 ) . The hyper-elongation of ime4Δ/Δ cells even in the absence of IME2 suggests that IME4 regulates PH growth in part independently or downstream of IME2-dependent meiotic initiation and thus indicates separable functions for IME4 in promoting meiosis and inhibiting PH development . To determine the period during starvation when Ime4 is most abundant , we analyzed Ime4 protein levels by Western blotting in a synchronous time course after inoculation in SPO . As shown in Figure 4A , Ime4 levels increased soon after the shift to starvation conditions and peaked during pre-meiotic S and G2/prophase . Once cells entered into the meiotic divisions , full-length Ime4 disappeared rapidly . We also observed the accumulation of a faster-migrating band that may represent a carboxy-terminal cleavage product of Ime4 ( Figure 4A ) . To investigate whether Ime4 protein levels correlated with activity we followed the kinetics of m6A accumulation on polyadenylated RNA by two-dimensional thin-layer chromatography . This analysis revealed that m6A accumulation tightly matched the levels of full-length Ime4 during the starvation time course . m6A accumulated soon after the shift to SPO , peaked during pre-meiotic S and G2/prophase , and decreased as cells entered into the meiotic divisions ( Figure 4B ) . Entry into the meiotic divisions resulted in a decrease in the IME4 sense transcript and the concomitant accumulation of the IME4 regulatory antisense transcript [10] , [29] ( Figure 4C ) , suggesting that IME4 expression may be regulated both at the protein and transcriptional levels to ensure tight repression of IME4 . To determine more precisely the point at which m6A was lost we employed cells encoding an estradiol-inducible allele of NDT80 , the transcription factor necessary for exit from meiotic G2/prophase [8] , [30] , [31] . In the absence of estradiol , these cells arrest at the end of G2/prophase [8] , [32] . Under these conditions , cells continued to produce methylated transcripts even after 9 hours of starvation ( Figure 4D ) . By contrast , cells that were induced to express NDT80 displayed reduced levels of m6A at this time point . Thus , NDT80 activation and exit from meiotic G2/prophase is necessary for the down-regulation of RNA methylation activity . To identify regulators of Ime4 , we conducted a two-hybrid screen using full-length Ime4 as bait [33] . The two most abundant hits isolated from this screen were MUM2 ( MUddled Meiosis 2 ) and SLZ1 ( Sporulation-specific Leucine Zipper 1 ) both of which have previously been implicated in meiotic progression [34] , [35] , [36] . Our screen identified 28 independent clones of MUM2 and 8 independent clones of SLZ1 . All 28 clones spanned the 3′ region of MUM2 and all 8 clones spanned the 3′ region of SLZ1 , suggesting that the respective carboxy-terminal regions of these proteins are sufficient for conferring interaction with Ime4 ( Figure S5 ) . In support of the physical interactions revealed by two-hybrid analysis , Ime4 efficiently co-immunoprecipitated with Mum2 and , to a lesser extent , Slz1 ( Figure 5A ) . Like Ime4 , Mum2 and Slz1 were induced during starvation in SPO as determined by Western blotting ( Figure 5B ) . To test whether Mum2 and Slz1 acted together with Ime4 in controlling mRNA methylation during starvation , we quantified m6A levels in meiotic G2/prophase in cells lacking IME4 , MUM2 or SLZ1 . As previously reported , ime4Δ/Δ cells did not accumulate m6A in meiosis [18] . Importantly , mum2Δ/Δ mutants also failed to accumulate m6A mRNA in pre-meiotic G2 and m6A in slz1Δ/Δ cells accumulated to substantially lower levels than in wild type cells ( Figure 5C ) . Taken together , these findings indicate that Ime4 , Mum2 , and Slz1 bind to each other and function together to mediate m6A RNA methylation during starvation . We term this protein complex the MIS ( Mum2 , Ime4 , Slz1 ) complex . Consistent with their shared functions in mRNA methylation , mum2Δ/Δ and slz1Δ/Δ cells recapitulated the defects of ime4Δ/Δ mutants with respect to meiotic progression and PH development . Like ime4Δ/Δ , deletion of either MUM2 or SLZ1 resulted in hyper-filamentation upon RTG3 and on SLAD plates . The hyper-filamentation phenotype appeared less pronounced for slz1Δ/Δ cells ( Figure 5D , 5E ) . Similarly , like ime4Δ/Δ cells , both mum2Δ/Δ and slz1Δ/Δ mutants replicated DNA under starvation conditions with essentially wild-type kinetics , but were delayed in progressing into the meiotic divisions ( Figure 5F , 5G ) . Again , the delay was less severe for slz1Δ/Δ mutants than for ime4Δ/Δ or mum2Δ/Δ mutants , mirroring the less dramatic effect of SLZ1 deletion on m6A levels . The loss of function mutations in MUM2 and SLZ1 had meiotic defects consistent with the other phenotypes: deletion of MUM2 resulted in a spore formation defect similar to loss of IME4 , whereas deletion of SLZ1 did not appreciably affect spore formation ( Figure 5H ) . We conclude that the MIS complex controls m6A RNA methylation and the yeast starvation response . The necessity of IME4 , MUM2 , and SLZ1 for the methylation of mRNA during meiosis raised the question of whether expression of these genes was sufficient to induce the methylation of mRNA . To test this , one copy of each gene was placed under control of the inducible CUP1 promoter in diploid cells while the other copy remained unaltered . Expression of these genes was induced by the addition of cupric sulfate in rich medium , a condition in which m6A does not normally accumulate on mRNA ( Figure 6A ) . Under these growth conditions , neither Mum2 nor Ime4 were expressed at levels close to those found in meiosis ( Figure 6B ) ; Slz1 did not accumulate in cells until induction of meiotic development ( Figure 5B ) . We found that inducing expression of IME4 , MUM2 , or SLZ1 singly in these conditions was not sufficient to induce m6A accumulation on mRNA ( Figure 6A ) . By contrast , induction of both IME4 and MUM2 resulted in a strong accumulation of m6A . Induction of all three MIS components ( MUM2 , IME4 , and SLZ1 ) further elevated m6A , albeit only by a small fraction , consistent with the role of SLZ1 as a non-essential component of the MIS complex ( Figure 6A ) . Notably , none of the strains that express m6A in rich conditions exhibited any obvious morphological or growth differences as compared to un-induced control cells ( data not shown ) . These data suggest that the restriction of mRNA methylation to times of starvation is largely a result of the starvation-specific expression of the MIS complex . Taken together , these phenotypes suggest a model in which Mum2 and Ime4 are essential components of an RNA methyltransferase complex , with Slz1 providing an accessory role necessary for optimal function . The MIS complex acts as an inhibitor of PH development , which raises the question of how cells are able to enter RTG-PH development during meiotic G2/prophase when the levels of MIS complex components and m6A are high . To answer this question , we monitored m6A levels upon RTG3 . This analysis revealed that m6A levels dropped rapidly after RTG3 , approaching the level of vegetative cells by 75 minutes after RTG3 , shortly before bud formation was initiated in RTG cultures ( Figure 7A ) . These observations suggest that MIS-dependent inhibition of PH development is alleviated in time to allow elongated bud growth in RTG3 cultures . The drop in m6A levels upon RTG3 was accompanied by modification of MIS complex components . Western analysis revealed that Ime4 protein levels gradually decreased and were undetectable by 75 minutes after RTG3 ( Figure 7B ) . Concomitantly , a fraction of Mum2 accumulated in a higher molecular-weight form , a modification that was also apparent when cells entered the meiotic divisions ( Figure 5B ) . Similar to Ime4 , Slz1 was quickly degraded and was no longer detectable by 30 minutes after RTG ( Figure 7B ) . These data indicate that before initiating the PH developmental program , cells remove existing methylated RNA and , in parallel , deactivate the mRNA methyltransferase program by modifying or degrading components of the MIS complex before initiating the PH developmental program . To test whether this down-regulation of the mRNA methyltransferase program is necessary for PH development upon RTG , we ectopically expressed the MIS complex components in RTG3 cells . As shown in Figure 7C and 7D , RTG3 cells expressing the MIS complex failed to form PH cells and instead developed ovoid buds . These data support the conclusion that mRNA methylation is inhibitory to PH development and suggest that the decrease in m6A expression upon RTG is necessary for PH cell development .
Our results are consistent with a progressive restriction of diploid cell fate in response to severe nutrient deprivation . During the initial lineage restriction , which coincides with pre-meiotic DNA replication , cells commit to starvation-induced differentiation . In this state , cells remain bipotential , as they can either form spores or engage in PH development , depending on nutrient availability . Only after starvation conditions have persisted long enough to initiate the middle-meiotic program do cells become committed to meiosis and sporulation [22] , [23] . The timing of the bipotential stage occurred after readiness-to-sporulate and before meiotic commitment , as defined by Simchen and colleagues [22] . We propose that the bipotential state is geared toward balancing the need to proliferate with survival under nutrient deprivation . Although the formation of protective spores provides better odds of survival for individual cells ( or their meiotic offspring ) in a harsh environment , sporulation is very time-intensive , which represents a competitive disadvantage if neighboring cells continue to proliferate . By maintaining the option to enter PH development while completing the early stages of sporulation , cells are primed to forage the environment and proliferate , should nutrient deprivation turn out to be transient . The RTG regimen has proven a powerful tool for probing the yeast starvation response and has provided important insights into a variety of meiotic processes including meiotic commitment and DNA repair [4] , [21] , [22] , [23] , [37] , [38] . Importantly , the RTG-PH procedure also offers a new avenue for dissecting the kinetics and biochemistry of PH development . Previous assays analyzed PH development in S . cerevisiae on solid medium or liquid suspension [3] , [39] , [40] . Under these conditions , PH cells form colonies comprised of a mixture of yeast form and PH cells that divide asynchronously with respect to each other and invade into agar . The asynchronous population of multiple cell types prohibited a biochemical analysis of gene expression in PH cells . Other studies have utilized butanol in liquid culture to study PH development [41] , [42] . Although growth in butanol results in elongated cells , formation of those cells does not require FLO11 or its regulators . By contrast , the genetic and morphological features of RTG-PH are indistinguishable from PH development on solid agar . The RTG-PH method thus provides an opportunity to study PH development in homogeneous and synchronous cultures . The RTG procedure enabled the discovery that a tightly controlled m6A mRNA methylation program governs cell fate restriction during starvation . m6A is an enigmatic mRNA modification that is highly increased during starvation in diploid yeast [11] , [18] and may function to enhance translational activity [13] , [16] or to regulate message processing and stability [14] , [15] . Previous work had identified the meiotic inducer Ime4 as the enzyme necessary for m6A formation [18] . Our experiments show that Ime4 binds two additional proteins , Mum2 and Slz1 , to form a protein complex , which we termed the MIS complex . All three proteins are required for efficient RNA methylation , indicating that Mum2 and Slz1 promote the methyltransferase activity of Ime4 . There are no obvious protein domains that would indicate a specific function of either Mum2 or Slz1 other than the Slz1 leucine-zipper motif , a domain type that often functions in protein dimerization . However , based on the severity of the phenotypes associated with loss of these two proteins , we predict that Mum2 forms an integral activator of the MIS complex , possibly by activating Ime4 catalytic activity or by targeting Ime4 to mRNA substrates , whereas Slz1 likely only has accessory functions . Our results suggest that accumulation of m6A mRNA is largely governed by regulating the abundance of MIS complex components . All three proteins are specifically expressed during pre-meiotic S and G2/prophase and are sufficient to induce m6A methylation in rich medium . Moreover , concomitant with the loss of m6A mRNA during the meiotic divisions or during return to growth , expression of MIS complex components drops and the proteins are rapidly modified or degraded . However , given the rapid drop in m6A mRNA observed after return to growth in particular , m6A mRNA may also become actively demethylated . In human cells , the protein FTO was recently shown to act as an mRNA demethylase [43] , but homologues of FTO have thus far not been identified in yeast . MIS-complex-dependent RNA methyltransferase activity governs multiple developmental processes during nutrient starvation . All three MIS complex components are required for efficient sporulation and may act at multiple steps during this process [18] , [34] , [36] . Ime4 and Mum2 had been shown to promote entry into the meiotic program and premeiotic DNA replication , respectively [18] , [35] , [36] , although our results as well as previous observation suggest that the importance of these early roles varies with strain background [18] . Our findings indicate that RNA methylation also functions later in the meiotic program to promote the expression of the middle-meiosis transcription factor NDT80 and thus meiotic commitment . Ime4 may activate NDT80 expression either directly , by methylating the NDT80 transcript , or indirectly , through the previously characterized modification of IME2 transcript [17] , as Ime2 activity is necessary for expression of Ndt80 protein [8] . Interestingly , NDT80 is , in turn , required to down-regulate of mRNA methylation during the meiotic divisions revealing a negative feedback loop in switching off mRNA methylation . MIS-complex activity suppresses PH development in a manner that is at least partially separable from its function in promoting meiosis and that involves down-regulation of the key PH factor , FLO11 . Inhibition of FLO11 expression may occur through methylation ( and hence , activation ) of SFL1 , a well-characterized inhibitor of FLO11 and the PH program [44] . Identification of specific substrates for mRNA methylation will be necessary to determine how Ime4 regulates these developmental decisions . Sequence and functional comparisons suggest that Ime4 and Mum2 are conserved throughout eukaryotic evolution . Previous biochemical studies in human cells isolated two independent components , with a possible third additional factor , as necessary for catalyzing mRNA methylation [45] , [46] . Of these three components , only MT-A70 , the human homolog of IME4 , has been cloned [46] . This subunit is conserved throughout virtually all eukaryotes , including Arabidopsis thaliana and Drosophila melanogaster [12] , [14] , [46] , [47] . Mum2 is similarly conserved; the Arabidopsis MUM2 homolog , AtFIP37 , was previously found to interact with the Arabidopsis IME4 homolog , MTA , although its role in RNA methylation was not determined [14] . MUM2 also bears homology to Drosophila melanogaster Fl ( 2 ) d and human WTAP-1 , the latter of which therefore is a strong candidate to be the cognate human mRNA methyltransferase component . Alignment of MUM2 , Fl ( 2 ) d , AtFIP37 and WTAP-1 protein sequences revealed that MUM2 is the most diverged from the other homologues , although all four genes have conserved residues near the C-terminus , a region we suggest is necessary for interaction with Ime4 ( Figure S6 ) . Intriguingly , MUM2 and AtFIP37 homologues in metazoans have been shown to play a role in mRNA splicing [48] , [49] , [50] , [51] . Although the yeast genome is generally intron-poor , introns are strongly over-represented in early meiotic transcripts [52] , [53] , raising the possibility that mRNA methylation may influence the splicing of these transcripts to regulate the starvation-induced development in yeast . The homologues of IME4 and MUM2 are highly expressed in the reproductive organs as well as other developing tissues in higher eukaryotes [14] , [47] , [50] , [54] . Thus , the control of developmental decisions by mRNA methylation may be widely conserved .
Strain genotypes are shown in Table S1 . To induce synchronous meiotic entry , cells were pre-selected on 1% yeast extract , 2% peptone , 3% glycerol , 2% agar for 24 hours at 30°C , grown for 24 hr in 1% yeast extract , 2% peptone , 4% dextrose at 30°C , diluted in BYTA ( 1% yeast extract , 2% tryptone , 1% potassium acetate , 50 mM potassium phthalate ) to OD600 = 0 . 2 and grown for another 16 hr at 30°C , 300 rpm . Cells were then washed once with water and re-suspended in SPO ( 0 . 3% potassium acetate ) at OD600 = 2 . 0 and incubated at 30°C at 190 rpm . For RTG experiments , cells were removed from SPO at the indicated times , collected by centrifugation , re-suspended in pre-warmed 1% yeast extract , 2% peptone , 2% dextrose and incubated at 30°C at 190 rpm . Pseudohyphal growth was assayed after 6 days of growth on synthetic low-ammonium dextrose ( SLAD ) medium described in [2] containing 0 . 5% glucose . The CUP1 promoter was induced with 100 µM CuSO4 in rich media . RTG cells were photographed and measured after one complete cell cycle , when the daughter cell initiated budding , in order to gauge maximal length of daughter buds . Two hybrid analysis was performed as in [33] . Full-length IME4 was expressed as a fusion to the Gal4 DNA-binding domain and was transformed into a bait strain that was mated with the two-hybrid library . Plasmids from colonies that showed growth on auxotrophic media and expressed LacZ were further purified and sequenced . Cells were photographed under 40× magnification and primary bud morphology was quantified using ImageJ ( Rasband W . , National Institutes of Health , http://rsb . info . nih . gov/ij/index . html ) . Total RNA was obtained by standard phenol∶chloroform∶isoamyl alcohol extraction . cDNA was generated using random hexamers or strand-specific primers and the Qiagen QuantiTect Reverse Transcription Kit . Transcript abundance was quantified using reagents from Applied Biosystems and the ABI 7500 real-time PCR system . Primer sequences are provided in Table S2 . 50 ml of meiotic culture was harvested 3 hours after meiotic induction in the presence of protease inhibitors ( Complete protease inhibitors , Roche ) . Cells were washed once with 1M Tris-HCl , pH 7 . 5 and snap-frozen . Frozen pellets were resuspended in lysis buffer ( 150 mM NaCl , 50 mM Tris pH 7 . 5 , 1% NP40 , 10 mM PMSF , Complete mini protease inhibitors ( Roche ) at 2× concentration ) and glass-bead homogenized three times for 5 minutes at 4°C . Debris was pelleted by centrifugation for 10 minutes , and supernatant was incubated with HA-conjugated agarose beads ( Pierce ) with head-over-tail rotation for three hours . Beads were washed 5times in lysis buffer and boiled in reducing loading buffer , followed by the standard protocol for Western analysis as described below . Flow cytometric analysis of DNA content , 4′ , 6-diamidino-2-phenylindole ( DAPI ) staining for DNA segregation analysis and cell staging by spindle morphology using tubulin indirect immunofluorescence were performed as described in [55] . Western analyses were performed as described in [56] , with anti-c-myc ( 9E10 , Covance ) or anti-HA ( HA . 11 , Covance ) at a concentration of 1∶1000 . TLC analysis was carried out as in [14] . RNA was extracted from cells using a standard hot acid phenol protocol; poly ( A ) RNA was purified from total RNA with the Dynabeads mRNA purification system ( Invitrogen ) and analyzed on cellulose plates ( 20 cm×20 cm ) from EMD . | Cellular differentiation involves the limitation of cellular potential in response to developmental cues . Budding yeast cells differentiate in response to nutrient availability . In the presence of nutrients , cells divide mitotically by producing round , yeast-form buds . Under nutrient limitation , cells can either divide under a pseudo-hyphal ( PH ) foraging program or undergo meiosis to form protective spores . We show here that developmental commitment occurs in two distinct phases . When nutrients were removed , cells first became committed to a starvation response , during which they entered the meiotic program . If nutrient limitation persisted , cells became committed to meiosis and sporulation . By contrast , if nutrients were returned at this point , cells synchronously initiated PH foraging growth . We found that both sporulation and PH growth were governed by RNA methylation , and we identified an mRNA–methyltransferase complex comprising Mum2 , Ime4 , and Slz1 as a central regulator of these developmental trajectories . Our results indicate that the yeast starvation response is an extended developmental process and reveal a fundamental role for post-transcriptional RNA modification in controlling cell fate . | [
"Abstract",
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] | [
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] | 2012 | RNA Methylation by the MIS Complex Regulates a Cell Fate Decision in Yeast |
Chikungunya virus ( CHIKV ) is transmitted by Aedes species mosquitoes and is the cause of an acute febrile illness characterized by potentially debilitating arthralgia . After emerging in the Caribbean in late 2013 , the first locally-acquired case reported to public health authorities in Puerto Rico occurred in May 2014 . During June–August 2014 , household-based cluster investigations were conducted to identify factors associated with infection , development of disease , and case reporting . Residents of households within a 50-meter radius of the residence of laboratory-positive chikungunya cases that had been reported to Puerto Rico Department of Health ( PRDH ) were offered participation in the investigation . Participants provided a serum specimen and answered a questionnaire that collected information on demographic factors , household characteristics , recent illnesses , healthcare seeking behaviors , and clinical diagnoses . Current CHIKV infection was identified by rRT-PCR , and recent CHIKV infection was defined by detection of either anti-CHIKV IgM or IgG antibody . Among 250 participants , 74 ( 30% ) had evidence of CHIKV infection , including 12 ( 5% ) with current and 62 ( 25% ) with recent CHIKV infection . All specimens from patients with CHIKV infection that were collected within four days , two weeks , and three weeks of illness onset were positive by RT-PCR , IgM ELISA , and IgG ELISA , respectively . Reporting an acute illness in the prior three months was strongly associated with CHIKV infection ( adjusted odds ratio [aOR] = 21 . 6 , 95% confidence interval [CI]: 9 . 24–50 . 3 ) . Use of air conditioning ( aOR = 0 . 50 , 95% CI = 0 . 3–0 . 9 ) and citronella candles ( aOR = 0 . 4 , 95% CI = 0 . 1–0 . 9 ) were associated with protection from CHIKV infection . Multivariable analysis indicated that arthralgia ( aOR = 51 . 8 , 95% CI = 3 . 8–700 . 8 ) and skin rash ( aOR = 14 . 2 , 95% CI = 2 . 4–84 . 7 ) were strongly associated with CHIKV infection . Hierarchical cluster analysis of signs and symptoms reported by CHIKV-infected participants demonstrated that fever , arthralgia , myalgia , headache , and chills tended to occur simultaneously . Rate of symptomatic CHIKV infection ( defined by arthralgia with fever or skin rash ) was 62 . 5% . Excluding index case-patients , 22 ( 63% ) participants with symptomatic CHIKV infection sought medical care , of which 5 ( 23% ) were diagnosed with chikungunya and 2 ( 9% ) were reported to PRDH . This investigation revealed high rates of CHIKV infection among household members and neighbors of chikungunya patients , and that behavioral interventions such as use of air conditioning were associated with prevention of CHIKV infection . Nearly two-thirds of patients with symptomatic CHIKV infection sought medical care , of which less than one-quarter were reportedly diagnosed with chikungunya and one-in-ten were reported to public health authorities . These findings emphasize the need for point-of-care rapid diagnostic tests to optimize identification and reporting of chikungunya patients .
Chikungunya virus ( CHIKV ) is a mosquito-transmitted alphavirus that can cause an acute febrile illness characterized by potentially debilitating arthralgia [1] . Aedes aegypti and Ae . albopictus mosquitoes are the most common vectors of CHIKV and also transmit the four viruses that cause dengue ( DENV-1–4 ) [1] . CHIKV previously caused outbreaks in Southeast Asian and African countries where large portions of the population ( e . g . , 38–75% ) were affected [2–5] , which may be attributable to high viremia in the host , high viral load in mosquitos , immunologically naive populations , and the absence of sustainable and effective vector control methods [6] . Although infection with CHIKV results in long-term protection from reinfection [7] , it has been associated with persistent arthritis and/or arthralgia that may last several months [8 , 9] . In areas where both CHIKV and DENVs circulate , misdiagnosis of chikungunya may be common , as patients with either disease may present with fever , myalgia , and arthralgia [10] . The first documented locally-acquired chikungunya case in the Western Hemisphere was reported in December 2013 on the Caribbean island of St . Martin [11] . Soon after , CHIKV spread to at least 45 countries and territories throughout the Americas where over 2 million suspected cases have been reported to date [12] . In the United States territory of Puerto Rico , the first laboratory-confirmed chikungunya case occurred in a patient from the San Juan metropolitan area who had illness onset in May 2014 and no history of recent travel [13] . The peak of cases reported through passive surveillance occurred in August 2014 [14] , and to date >30 , 000 suspected chikungunya cases have been reported [15] . However , detection of anti-CHIKV antibodies in nearly 25% of blood donated during 2014 suggests a higher incidence of infection than was reported to public health authorities [16] . Because they are transmitted by the same mosquito vectors , CHIKV is thought to have similar transmission patterns as DENV , which often results in clusters of infected individuals in and around the households where infected individuals reside [17–20] . This is largely due to the anthropophilic nature of Ae . aegypti , which tend to disperse relatively short distances ( <100 meters ) and congregate around households [18] . Consequently , human movement has been identified as the primary mode of DENV dissemination beyond 100 meters [21] . Human population density , particularly in relation to urban centers , has also been associated with clustering of chikungunya cases [22] . Following the introduction of CHIKV into Puerto Rico , we conducted household-based cluster investigations to describe the spectrum of disease and factors associated with CHIKV infection , identify host factors associated with symptomatic infection , describe care-seeking behavior in individuals with chikungunya , and identify patient characteristics associated with accurate clinical diagnosis and case reporting of chikungunya patients .
The investigation protocol underwent institutional review at CDC and was determined to be public health practice and not research . As such , institutional review board approval was not required . Puerto Rico , an unincorporated territory of the United States located in the Caribbean Sea , has an area of 3 , 424 square miles and in 2014 had an estimated population of 3 , 548 , 397 ( 1 , 036 residents per square mile ) [23] . A cross-sectional investigation was conducted in which neighbors of chikungunya patients were offered enrollment in household-based cluster investigations . A convenience sample of laboratory-positive chikungunya cases was identified from suspected chikungunya cases that were reported to Puerto Rico Department of Health ( PRDH ) and tested laboratory-positive for CHIKV infection ( “index cases” ) . Index case-patients or their parent or guardian were contacted by telephone within 30 days of the index case-patients’ illness onset and a home visit was scheduled . All household investigations were conducted between June 20 and August 19 , 2014 ( S1 Fig ) . During each household visit , the head-of-household of the index case-patient’s household ( the “index household” ) and all households within a 50-meter radius of the index household were eligible for enrollment in the investigation . If the head-of-household agreed to participate in the investigation , all available members of the household were offered participation . Households were not revisited if the head-of-household was not home or declined participation . A questionnaire ( S1 Appendix ) addressing household characteristics was administered to the head-of-household , and an individual questionnaire ( S1 Appendix ) addressing demographics , travel history , and recent illnesses was administered to all participants . Parents or guardians answered individual questionnaires by proxy for participants aged <8 years . Serum specimens were collected from all household investigation participants and transported to CDC Dengue Branch in San Juan , Puerto Rico for diagnostic testing . To detect evidence of CHIKV infection , all specimens were tested by rRT-PCR [24] , IgM antibody capture ( MAC ) ELISA [25] , and IgG ELISA [26] . Specimens were also tested for evidence of DENV infection , the results of which have been previously reported [13] . In summary , 5% of participants were positive for recent DENV infection , and none were positive for current DENV infection . Inclusion of DENV diagnostic test results in epidemiologic analyses did not appreciably affect the statistical significance of any findings , as there was minimal overlap of participants with evidence of infection with both CHIKV and DENV ( i . e . , 1 of 74 [1 . 4%] ) . Hence , DENV diagnostic test results are not included in the analyses presented herein . Names and dates of birth of all CHIKV-infected participants were queried in surveillance databases at CDC and PRDH to determine if they had been reported as a suspected chikungunya case-patient . Participants were individuals that provided a serum specimen and answered an individual questionnaire . Current CHIKV infection was defined by detection of CHIKV nucleic acid by rRT-PCR . Because CHIKV was first detected to be circulating in Puerto Rico in May 2014 and all household investigations were completed by mid-August 2014 , recent CHIKV infection was defined by detection of either anti-CHIKV IgM antibody by MAC ELISA or anti-CHIKV IgG antibody by IgG ELISA . Participants were defined as being laboratory-positive for CHIKV infection if they had evidence of either current or recent infection . Participants were defined as laboratory-negative for CHIKV infection if they had no evidence of either current or recent CHIKV infection . For participants with current CHIKV infection that did not report any symptom of illness ( n = 2 ) , development of illness after interview was ruled out by follow-up phone call within 30 days of the household visit . Findings from multivariable and hierarchical clustering analysis of signs and symptoms associated with current or recent CHIKV infection were used to define symptomatic CHIKV infection . General estimating equations ( GEE ) were used to model associations between individual health and household characteristics and binary outcomes of CHIKV infection status , correct chikungunya diagnosis , or asymptomatic infection . All GEE models were fit with a logit link and assuming an exchangeable correlation matrix . This method estimates the population-averaged effect , accounting for correlations in data of members from the same household and investigation cluster that might otherwise bias estimates [27] . Multivariate GEE analysis was performed to obtain a final model for the association between laboratory-positivity and symptoms reported among participants with illness in the past three months . Backward elimination was used in best-fitting model selection , removing variables from the full model that lowered the Quasilikelihood Information Criteria ( QIC ) relative to the full model [28] . Hierarchical cluster analysis , which uses a distance measure to identify similar clusters of variables and an agglomeration method to link clusters , was performed to analyze patterns of symptoms among participants with recent illness . Manhattan distance , a measure of similarity that sums the absolute differences among observations , was used due to the binary nature of outcomes . Ward’s method , which groups variables by minimizing the internal sum of squares , was used as the agglomeration method [29] . GEE analyses were performed using SAS 9 . 3 ( SAS Institute Inc . , Cary , NC ) , and hierarchical cluster analysis was performed using R version 3 . 2 . 3 . ArcGIS version 10 . 2 ( ESRI , Redlands , CA ) was used for mapping household clusters .
A total of 21 household-based cluster investigations were conducted in the health regions of San Juan , Bayamón , Ponce , Arecibo and Caguas ( S1 Table ) . Of 499 households eligible for participation , heads-of-household from 200 ( 46 . 2% ) occupied households were available to be offered enrollment , and 137 ( 68 . 5% ) accepted ( Fig 1 ) . Median rate of enrollment by cluster and health region was 66 . 7% ( range: 37 . 5–100% ) and 66 . 7% ( range: 62 . 5–78 . 9% ) , respectively . Of the 410 residents of all enrolled households , 250 ( 61 . 0% ) participated in the investigation . Participants tended to be older than all residents living in participating households ( median age = 45 vs . 25 years , respectively ) . Of the 250 household cluster investigation participants , 74 ( 29 . 6% ) had evidence of CHIKV infection . Although infection rates varied by cluster both between and within health regions , all clusters had at least one infected individual apart from the index case-patient ( Fig 2 ) . This included 12 participants with current CHIKV infection and 62 participants recent CHIKV infection . Among those with current CHIKV infection , 9 ( 75 . 0% ) were positive only by rRT-PCR , 1 ( 8 . 3% ) was positive by rRT-PCR and IgM ELISA , and 2 ( 16 . 7% ) were positive by rRT-PCR as well as both IgM and IgG ELISA . Of those with recent CHIKV infection , 53 ( 85 . 4% ) were positive by both IgM and IgG ELISA , 5 ( 8 . 1% ) were positive by IgM ELISA only , and 4 ( 6 . 5% ) were positive by IgG ELISA only . Duration of detection of diagnostic markers of CHIKV infection was plotted for all participants who had evidence of CHIKV infection by any method and reported recent symptoms of illness and a date of illness onset ( n = 54 ) ( Fig 3 ) . All specimens collected before day four post-illness-onset ( PIO ) were positive by rRT-PCR . Detection of CHIKV nucleic acid by rRT-PCR decreased over time by day of specimen collection PIO , and by day 13 PIO no rRT-PCR-positive specimens were identified . Percent positivity by anti-IgM and IgG ELISA both increased according to day of specimen collection PIO . All specimens collected after week two PIO were IgM-positive , while all specimens collected after week three PIO were IgG-positive . Following bivariate analysis , age and gender were not significantly associated with CHIKV infection ( Table 1 ) . Participants that reported having chronic joint disease or arthritis had nearly two-fold increased odds of having evidence of CHIKV infection . Reporting having had an acute illness in the past three months or having a household member that had an acute illness in the past three months were both associated with 14-fold increased odds of being laboratory-positive for CHIKV infection . No significant associations were found between CHIKV infection and housing type , having screened windows and doors , and reporting leaving doors or windows open regularly . Participants that reported using household air conditioning or citronella candles had two- or three-fold decreased odds of being laboratory-positive for CHIKV infection , respectively . Following multivariable analysis that controlled for age and gender , female gender was associated with protection from CHIKV infection . Neither reporting having a chronic medical condition nor use of daily medications was associated with protection from CHIKV infection . Reporting having an acute illness or having a household member with an acute illness in the past three months both remained strongly associated with increased odds of CHIKV infection . Use of mosquito repellent and citronella candles remained associated with protection from CHIKV infection . Of 99 participants that reported having an acute illness within the previous three months , 61 ( 61 . 6% ) were laboratory-positive for CHIKV infection ( Table 2 ) . Median duration of illness in laboratory-positive participants was six days ( range: 2–21 days ) . Following bivariate analysis , signs and symptoms associated with CHIKV infection in ill participants were fever , skin rash , arthralgia , and arthritis . Cough , rhinorrhea , and sore throat were associated with being laboratory-negative for CHIKV infection . No laboratory-positive symptomatic participants reported cough , rhinorrhea , or sore throat in the absence of fever or arthralgia . Following multivariable analysis , arthralgia and skin rash remained significantly associated with laboratory-positive symptomatic participants , and only retro-orbital eye pain remained significantly associated with laboratory-negative symptomatic participants . Headache , fever , arthralgia , myalgia , and chills tended to occur simultaneously more often among laboratory-positive participants , whereas cough , rhinorrhea , and sore throat occurred together more often among laboratory-negative participants ( Fig 4 ) . Because of the prevalence of respiratory illness concurrent with chikungunya virus transmission , combinations of symptoms that grouped together following hierarchical cluster analysis and were most frequently reported among laboratory-positive participants following multivariate analysis were utilized to refine the definition of “symptomatic CHIKV infection” in order to minimize incorrect classification of symptomatically-infected participants ( S2 Table ) . The maximal association of symptom combinations among laboratory-positive participants with concomitant minimization of association with laboratory-negative participants was arthralgia with skin rash or fever . This combination of symptoms yielded a symptomatic CHIKV infection rate of 62 . 5% , and was present among 6 . 8% of participants without evidence of CHIKV infection . This combination of symptoms was utilized in subsequent analyses to define “symptomatic CHIKV infection” . Twenty-one ( 37 . 5% ) participants , including two that had CHIKV nucleic acid detected by RT-PCR , were defined as having asymptomatic infection . Age was not significantly associated with asymptomatic infection ( Table 3 ) , nor was being a child ( 1 of 5 [20%] children with asymptomatic infection vs . 20 of 51 [39%] adults; OR = 0 . 30 , 95% CI = 0 . 03–3 . 67 ) . Neither sex nor reported chronic medical conditions was significantly associated with asymptomatic infection . Participants who reported having a household member with an acute illness within the previous three months more often had symptomatic infection ( 100% vs . 81% ) . After again excluding the index case-patients , 22 ( 62 . 9% ) of 35 symptomatic , laboratory-positive participants sought medical care . Seeking medical care for acute illness was associated with 3-fold increased odds of being laboratory-positive ( Table 2 ) . Neither hospitalization nor duration of illness was significantly associated with being laboratory-positive for CHIKV infection . No demographic or clinical characteristics were significantly associated with seeking medical care . Of 22 laboratory-positive , symptomatic participants that sought medical care , five ( 22 . 7% ) reported having been diagnosed with chikungunya ( S3 Table ) . Neither age nor sex were significantly associated with correct reported diagnosis of chikungunya . All laboratory-positive , symptomatic patients diagnosed with chikungunya reporting having arthralgia in the hands , wrist , knee , ankle , and feet . Two ( 9 . 1% ) laboratory-positive , symptomatic participants that sought medical care were reported to public health authorities .
By conducting household-based cluster investigations during the early months of the 2014 chikungunya epidemic in Puerto Rico that included 250 participants residing within 50 meters of a known chikungunya case-patient , we found that 30% of participants had evidence of CHIKV infection . Reporting having had an acute illness in the past three months and having a household member with an acute illness were associated with increased odds of infection , while use of either air conditioning or citronella candles were associated with decreased odds of infection . Symptoms significantly associated with CHIKV infection included arthralgia and skin rash . Nearly two-thirds of symptomatically-infected individuals sought medical care; however , less than one-quarter of these individuals were diagnosed with chikungunya , and one-tenth were reported to public health authorities as a chikungunya case . These findings demonstrate the utility of household-based cluster investigation to describe the epidemiologic and clinical characteristics associated with an emerging infectious disease and reasons for underreporting of clinically-apparent disease cases . Serosurveys following chikungunya epidemics in Malaysia , Kenya , La Reunion , and Mayotte Island reported infection rates ranging from 37–75% [2–5] . Overall , 30% of participants in this investigation had evidence of CHIKV infection , which varied by cluster from 6 . 3% to 100% . These estimates likely do not reflect the final infection rates in these communities , as investigations were conducted during the first weeks of the epidemic in Puerto Rico where further CHIKV transmission likely occurred . A critical facet regarding interpretation of these results is that the objective of this investigation was not to determine the number of individuals infected with CHIKV during the indicated time frame , but rather to identify and compare the behaviors and characteristics of infected and uninfected participants . As such , the estimates of seroprevalence from previous studies and our findings are not directly comparable , as previous studies retrospectively measured rate of infection whereas this investigation collected a cross-sectional “snapshot” of infection rates during the initial stages of the epidemic . Nonetheless , demographic and behavioral characteristics were able to be associated with susceptibility to or protection from CHIKV infection . Having a household member with acute illness in the last three months was strongly associated with increased the odds of infection , which supports the notion that , like DENV , CHIKV infections tend to cluster within households and neighborhoods [30] . Air conditioning use was associated with decreased odds of CHIKV infection , as has been reported in previous studies of DENV infection [31] . This finding may not be attributable to cooler temperatures in air conditioned homes but rather to buildings with air conditioning tending to have closed windows and doors and drier environments that result in lower rates of survival of Ae . aegypti mosquitos [32] . Use of citronella candles was also associated with reduced odds of CHIKV infection; however , the proportion of all participants using citronella candles was relatively small ( 17% ) , and thus likely did not contribute substantially to protection from infection on a population level . Past studies have shown varying and inconsistent levels of reduction of mosquito abundance associated with citronella candles [33 , 34] as the quantity , concentration , and positioning of candles may play a role in their effectiveness [35] . By using findings from multivariable and hierarchical cluster analyses to identify arthralgia with fever or rash as being associated with CHIKV infection , we were able to more confidently define the rate of symptomatic CHIKV infection in this population as being 62 . 5% . Conversely , one-third of CHIKV-infected participants appear to have experienced asymptomatic infection , which is consistent with findings from past outbreaks that reported asymptomatic infection rates of 3–39% [36–38]; however , recent reports have suggested substantially higher rates of asymptomatic infection ( e . g . , 81% ) [39] . , Hence , further investigation including careful and potentially region-specific definitions of symptomatic infection is needed to determine factors influencing the rate of and progression to symptomatic CHIKV infection among diverse populations . Most CHIKV-infected participants identified in this investigation that reported an acute illness in the past three months complained of characteristic symptoms of chikungunya: fever , arthralgia , myalgia , and skin rash [6] . Laboratory-negative CHIKV participants with recent illness were more likely to report symptoms of cough , rhinorrhea , or sore throat , suggestive of an upper respiratory infection . Symptomatic laboratory-positive CHIKV participants had three-fold increased odds of having sought medical care compared to participants that were laboratory-negative with reported recent illness . These observations together suggest greater disease severity of chikungunya as compared to common respiratory illnesses . Future studies should quantitate the burden of the chikungunya epidemic on health care resources in Puerto Rico . Nearly two-thirds of symptomatically-infected patients sought medical care , demonstrating a relatively high rate of care-seeking behavior that may reflect the increased severity of arthralgia and myalgia as compared to patients with other etiologies of acute febrile illness . However , only one-quarter of chikungunya patients that sought care reported having been diagnosed with chikungunya , suggesting gaps in clinical suspicion of chikungunya . Other common diagnoses included more common etiologies of acute febrile illness including dengue and non-specific diagnoses such as viral syndrome . Because just one-tenth of clinically apparent chikungunya cases were reported as such to public health authorities , it is unclear how accurately the number of chikungunya cases reported to PRDH in 2014 reflects the true incidence of disease due to CHIKV infection . As with other reportable conditions for which passive case reporting is sub-optimal [40] , including dengue [41 , 42] , the identified gaps in case detection via passive surveillance should be taken into consideration when making estimates of the burden of symptomatic and clinically-apparent chikungunya . Strengths of this investigation included the ability to detect asymptomatic , sub-clinical , and clinically-apparent CHIKV infections , as well as the use of three different laboratory tests to identify current or recent CHIKV infection . It is therefore unlikely that any participants with CHIKV infection were not identified . Similarly , recall bias was likely to have been minimal since questionnaires captured events that had occurred within the prior three months . Conversely , a convenience sample of reported chikungunya cases was utilized to initiate cluster investigations , most of which were conducted in the San Juan metropolitan area . Moreover , factors that can influence both mosquito density ( e . g . , rainfall , temperature , humidity ) [43] as well as the efficiency of CHIKV transmission ( e . g . , population density ) [44] vary throughout Puerto Rico . For both of these reasons , our findings may not be representative of the entire population of Puerto Rico . Last , four laboratory-positive participants were defined as such by detection of anti-CHIKV IgG antibody only . Because lifetime travel history was not captured , it is possible that these individuals had been infected with CHIKV outside of Puerto Rico . Nonetheless , exclusion of these four individuals would not have significantly altered the observed associations . Factors identified with protection from CHIKV infection identified in this investigation were household rather than individual behaviors , suggesting the importance of prevention practices in and around the household . Such behaviors should be encouraged in areas where Aedes mosquitoes are found . The clinical findings of this investigation highlight the need for increased capacity to identify chikungunya patients in out-patient settings . Due to the difficulty in utilizing signs and symptoms alone to differentiate patients with chikungunya from other febrile illnesses , clinical diagnosis and decision-making as well as case reporting would be aided by improved availability of rapid diagnostic tests . | Chikungunya is a mosquito-borne virus that causes an acute febrile illness that often occurs with severe joint pain . The virus first arrived in the Western Hemisphere in late 2013 and has since caused epidemics in much of the Caribbean and the Americas . During the first months of the 2014 epidemic in Puerto Rico , we conducted household-based cluster investigations to identify factors associated with chikungunya virus infection and progression to disease . We found that using air conditioning and citronella candles in and around the home were associated with decreased rates of infection . Symptoms significantly associated with chikungunya virus infection included fever , joint pain , skin rash , and arthritis . Less than one-quarter of participants infected with chikungunya virus that sought medical care were diagnosed with chikungunya and one-in-ten were reported to public health authorities . This investigation demonstrates the importance of household-level behavioral interventions to avoid chikungunya virus infection , as well as the need for rapid diagnostic tests to improve identification of chikungunya patients . | [
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"p... | 2016 | Use of Household Cluster Investigations to Identify Factors Associated with Chikungunya Virus Infection and Frequency of Case Reporting in Puerto Rico |
Balanced chromosomal rearrangements represent one of the most common forms of genetic abnormality affecting approximately 1 in every 500 ( 0 . 2% ) individuals . Difficulties processing the abnormal chromosomes during meiosis lead to an elevated risk of chromosomally abnormal gametes , resulting in high rates of miscarriage and/or children with congenital abnormalities . It has also been suggested that the presence of chromosome rearrangements may also cause an increase in aneuploidy affecting structurally normal chromosomes , due to disruption of chromosome alignment on the spindle or disturbance of other factors related to meiotic chromosome segregation . The existence of such a phenomenon ( an inter-chromosomal effect—ICE ) remains controversial , with different studies presenting contradictory data . The current investigation aimed to demonstrate conclusively whether an ICE truly exists . For this purpose a comprehensive chromosome screening technique , optimized for analysis of minute amounts of tissue , was applied to a unique collection of samples consisting of 283 oocytes and early embryos derived from 44 patients carrying chromosome rearrangements . A further 5 , 078 oocytes and embryos , derived from chromosomally normal individuals of identical age , provided a robust control group for comparative analysis . A highly significant ( P = 0 . 0002 ) increase in the rate of malsegregation affecting structurally normal chromosomes was observed in association with Robertsonian translocations . Surprisingly , the ICE was clearly detected in early embryos from female carriers , but not in oocytes , indicating the possibility of mitotic rather than the previously suggested meiotic origin . These findings have implications for our understanding of genetic stability during preimplantation development and are of clinical relevance for patients carrying a Robertsonian translocation . The results are also pertinent to other situations when cellular mechanisms for maintaining genetic fidelity are relaxed and chromosome rearrangements are present ( e . g . in tumors displaying chromosomal instability ) .
The incidence of balanced chromosomal rearrangements in the general population is appreciable , detected in 0 . 19% of newborns [1] . Most carriers of a balanced chromosome rearrangement do not display an obvious phenotype and remain undetected until they attempt to reproduce . The presence of a rearrangement leads to unusual pairing configurations between the derivative chromosomes and their structurally normal homologues during meiosis . This increases the risk of abnormal chromosome segregation and the production of gametes with losses and/or gains of chromosomal material , associated with problems such as miscarriage , birth of children with congenital abnormalities and , in some cases , reduced fertility [2] . Not surprisingly , translocation carriers are found at increased frequency in certain patient populations , such as couples with recurrent miscarriage , where the incidence is 25-fold higher than the general population [3] , [4] . The rate is also elevated amongst infertile couples who have had several unsuccessful cycles of in vitro fertilisation ( IVF ) treatment , affecting 1 . 4% [5] . It has been suggested that , besides the direct effect on the chromosomes involved in the rearrangement , there may also be an impact on the segregation of other , structurally normal , chromosomes during meiosis . This might be a consequence of disrupted chromosome alignment on the spindle , or due to interference with other key aspects of the chromosome segregation process , leading to a generalised increase in the risk of producing aneuploid gametes . This phenomenon is known as an inter-chromosomal effect ( ICE ) [6] . Many researchers have sort to establish whether or not an ICE truly exists , but the limitations of the available cytogenetic technologies has meant that conclusive data has remained elusive and the existence of an ICE remains the subject of debate [7]–[17] . Particularly valuable data concerning the possibility of an ICE has come from cases of preimplantation genetic diagnosis ( PGD ) carried out for carriers of chromosome rearrangements . This process involves the generation of embryos using assisted reproductive technologies followed by genetic analysis . In most instances the embryos develop in vitro until approximately the 8-cell stage , at which time a single cell is removed and analysed using fluorescence in situ hybridisation ( FISH ) in order to determine the copy number of chromosomal regions involved in the translocation . Only embryos found to be normal/balanced for these regions are transferred to the mother's uterus and consequently the risk of any resulting pregnancy miscarrying or producing a child affected by a congenital abnormality is greatly reduced . The first clinical application of PGD techniques for translocation carriers took place in the late 1990s [18] , [19] and since then thousands of PGD cycles have been performed [20] . A focus on gametes and preimplantation embryos is especially valuable when attempting to determine the presence or absence of an ICE since , at early stages of development , elimination of embryos harbouring lethal chromosomal anomalies ( via developmental arrest , implantation failure or miscarriage ) has not yet taken place . Consequently , the primary incidence of chromosome malsegregation can be assessed . Some previous studies , investigating embryos produced by carriers of chromosome rearrangements undergoing PGD , have produced data supporting the existence of an ICE [8] , [12] . However , once again there is controversy with other research suggesting that an ICE is either entirely absent or negligible in these patients [15] . Studies conducted on sperm provide the strongest data in favour of an ICE ( see [11] for detailed summary ) , although the results are variable , with the effect detected in some samples but not others [9] , [11] . We are not aware of any studies assessing the possibility of an ICE in female meiosis . Very recently , comprehensive chromosomal screening strategies , such as microarray comparative genomic hybridization ( aCGH ) , have begun to replace FISH for the PGD of translocations and other chromosomal rearrangements ( Figure 1 ) . Not only do methods of this kind reveal abnormalities affecting the specific chromosomes involved in the rearrangement , but they also detect aneuploidies affecting any other chromosomes [21]–[24] . In contrast , FISH methods only permit a very limited chromosomal screening and consequently most attempts to identify an ICE in human gametes or embryos have been restricted to the analysis of small numbers of chromosomes ( additional to those involved in the translocation ) . While this limitation does not invalidate the results of such studies , it means that very few chromosome segregations can be examined in each sperm or embryo tested . The aim of this study was to determine whether an ICE truly exists . The strategy was to exploit unique access to a large number of human oocyte and embryo samples derived from carriers of chromosomal rearrangements , coupled with the latest molecular cytogenetic methods . This allowed us to look at more than 10 , 000 individual chromosomes in samples from chromosome rearrangement carriers and more than 200 , 000 chromosomes in well-matched controls . The large number of chromosomes evaluated greatly increased the sensitivity and statistical power of this investigation compared with preceding studies . The study revealed that an ICE does exist , but suggests that it may be confined to a narrow developmental window and may be associated with specific types of chromosomal rearrangement . These results were unexpected and yet may explain some of the apparently contradictory findings in previous studies . Additionally , the findings raise important questions concerning fundamental aspects of cell biology and have implications for the clinical management of patients with chromosome rearrangements .
Overall , a total of 283 samples derived from chromosome rearrangement carriers were analyzed ( Table 1 and Table 2 ) . Oocytes were assessed by comprehensive chromosome analysis of the first and second polar bodies , cleavage stage embryos were evaluated following removal of a single cell , while analysis of blastocysts involved the biopsy and testing of an average of five cells per embryo . A robust control group was created for each patient by careful matching with data from oocytes , cleavage stage embryos or blastocysts from multiple individuals of normal karyotype and identical female age , having treatment at the same clinic during the same time interval and using the same diagnostic test ( i . e . microarray-CGH ) . The chromosomally normal control patients had requested oocyte or embryo testing as part of a routine IVF cycle , with the aim of reducing the risk of miscarriage and Down syndrome caused by spontaneously arising aneuploidy . The control group consisted of 5 , 078 samples . Of the samples tested from rearrangement carriers , most were abnormal ( 81 . 3% ) with aneuploidies affecting chromosomes involved in the rearrangement and/or with spontaneously occurring errors affecting unrelated chromosomes . Not surprisingly , the karyotypically normal control group displayed fewer abnormalities ( P<0 . 0001 ) , although the rate of aneuploidy was still appreciable; 65 . 3% of the control samples had an abnormal chromosome number . In order to assess the presence of an ICE , the chromosomes involved in the rearrangement in each patient were excluded from analysis in both patient and corresponding control groups , thereby focusing the evaluation on chromosomes that were structurally normal in both populations ( Table 2 and Table 3 ) . In the samples from the rearrangement carriers , a total of 10 , 837 chromosomes were examined and 553 aneuploidies were identified . Thus , on average there was a 0 . 051 probability of a given chromosome having undergone malsegregation . In the control group , 204 , 406 chromosomes were assessed , leading to the detection of 9 , 598 distinct abnormalities ( 0 . 047 probability of aneuploidy per chromosome per sample ) . Although small , the increase in the risk of aneuploidy affecting structurally normal chromosomes ( 0 . 4% increase per chromosome per sample ) was statistically significant ( P<0 . 0001 ) , suggesting the existence of an ICE . A detailed breakdown of aneuploidies detected at each biopsy stage in patient and control samples is given in Table 4 . As expected , samples from rearrangement carriers and samples from the control group both displayed a dramatic increase in aneuploidy with advancing female age . This is presumably due to the well-known increase in meiotic error rate seen as women age . The extent of the ICE was not affected by maternal age , remaining at a similar level for all ages . Although an ICE was apparent when all of the data was summed together , a more detailed assessment , considering each of the different classes of rearrangement separately , showed that not all were consistently associated with elevated chromosome malsegregation . The analysis of results from reciprocal translocation carriers revealed no overall difference in aneuploidy rate compared to the appropriate control group ( P = 0 . 87 ) . Some previous findings obtained using FISH analysis of small numbers of chromosomes , mostly carried out in sperm , have suggested that reciprocal translocations can be associated with an ICE [9] , [12] , while other investigations have reported opposite findings [8] , [16] , [17] . The current study suggests that most reciprocal translocations are probably not associated with an ICE , but does not rule out the possibility that translocations involving specific breakpoints/chromosomal regions might exhibit this phenomenon . No ICE was apparent in samples from inversion carriers ( P = 0 . 18 ) , however , the number of samples with this class of rearrangement was considered insufficient to conclusively determine whether or not an ICE exists ( only 528 chromosomes assessed ) . The possibility that inversions are associated with an ICE remains unproven and requires further exploration . Interestingly , in the current study , one patient who produced an unusual number of highly abnormal embryos ( each embryo affected by multiple aneuploidies ) had an inversion in combination with a reciprocal translocation ( patient 10 in Table 2 ) . Whether or not the presence of two rearrangements can , together , produce a more potent ICE cannot be determined from a single patient , but remains an intriguing possibility . Robertsonian translocations were the only class of rearrangement for which an ICE was clearly identified . Comparison of samples from Robertsonian translocation carriers with corresponding control groups revealed a highly significant increase in aneuploidy rate ( P = 0 . 0002 ) . However , subdivision of the data revealed that this pronounced ICE was only obvious at the cleavage stage ( P<0 . 0001 ) . No ICE was observed in polar bodies ( i . e . oocytes ) or samples from blastocysts ( P = 0 . 72 and P = 0 . 25 respectively ) . The fact that the ICE was absent from oocytes , but clearly detected in the cleavage stage embryos of both male and female carriers ( P = 0 . 0022 and P = 0 . 012 respectively ) provides strong evidence for an impact of the rearrangement during mitosis , occurring in the cell divisions immediately following fertilisation . The possibility that some types of translocation might affect the segregation of structurally normal chromosomes during the first few mitotic divisions has not previously been considered , but could explain some of the discordant findings reported in the literature concerning inter-chromosomal effects . Previous studies have tended to be focused on either gametes or embryos , rarely both , and have assumed that any ICE would always have a meiotic origin . The possibility that early embryogenesis might be particularly sensitive to disruption of chromosome segregation is not without precedent . It is well documented that human embryos display an elevated frequency of chromosomal malsegregation during the first few mitotic divisions following fertilisation . This is true regardless of whether or not the parents have normal karyotypes . The high mitotic error rate frequently results in chromosomal mosaicism and aneuploidy in cleavage stage embryos [25]–[27] . Genetic instability in human preimplantation embryos extends beyond loss/gain of whole chromosomes and also includes chromosome breakage leading to segmental abnormalities in some cases [28]–[30] . The embryonic genome is , for the most part , inactive from fertilization until the 4–8 cell stage and it is thought that a deficiency , or perhaps rigidity , of cell-regulatory mechanisms , including the cell cycle checkpoints that usually act to maintain chromosome segregation and genomic integrity , may be the underlying cause of the observed instability . Although a developmental phase characterized by genetic instability may provide the necessary environment for errors caused by an ICE to be propagated , it does not explain how the structurally abnormal chromosome disrupts the normal mitotic process . Several studies looking at sperm , have considered the mechanisms that might give rise to an ICE during meiotic divisions [9] , [11] . This work has provided an insight into why certain segregation modes are favoured in patients with different types of rearrangement , but the reason why some male translocation carriers display an ICE in their sperm and others do not remains obscure . Similarly , the mechanism by which a rearrangement could disrupt mitosis is not clear . One possibility is that mitotic recombination involving rearranged chromosomes may disturb the ordered arrangement of chromosomes on the spindle , holding together chromosomes that would usually be in separate locations . This is analogous to the principle hypothesis concerning a meiotic ICE , in which the paring of rearranged chromosomes with their structurally normal homologues disrupts the positioning , pairing and segregation of other chromosomes during meiosis [6] , [31] . Although mitotic recombination is generally considered to be a rare phenomenon there is good reason to believe it occurs at an appreciable frequency in the cells of human embryos . Mitotic recombination is a mechanism of DNA repair and is usually initiated by a double strand break ( DSB ) . It is becoming increasingly clear that DSBs are very common in the cells of cleavage stage embryos , leading to a high frequency of chromosome breakage [28]–[30] . An elevated incidence of DSBs is further evidenced by the detection of micronuclei , which are often seen in the cells of preimplantation embryos and are suggestive of the presence of fragmented chromosomes . A second possibility is that the rearranged chromosomes alter normal patterns of chromosome positioning in interphase nuclei , with consequences for attachment to the mitotic spindle during metaphase . The fact that the ICE detected during the current study was only obvious for Robertsonian translocations may be of particular relevance to hypotheses involving positioning in the nucleus or on the spindle . This class of translocations involve acrocentric ( D and G group ) chromosomes , the short arms of which are composed of tandem copies of ribosomal RNA ( rRNA ) genes . These regions co-localise during interphase , acting as a focus for formation of the nucleolus . A Robertsonian translocation involves fusion of chromosomes at the centromere , accompanied by loss of the short arms . This is highly likely to lead to the affected chromosomes failing to associate with the nucleolus . Since most chromosomes have specific sequences that interact with nucleoli [32] , disturbance of the chromosome territories in this area could have wide ranging effects . For Robertsonian translocation carriers the risk of any given chromosome being abnormal at the cleavage stage was 0 . 065 . This corresponds to a relative risk of aneuploidy of 1 . 41 per chromosome compared with matched controls . However , since many embryos contain multiple aneuploidies , the probability of abnormality at the level of the embryo , rather than at the level of the chromosome , is not increased as dramatically . It is inevitable that additional aneuploidies caused by the ICE will often fall within embryos that were already abnormal due to aneuploidy unrelated to the ICE . Of 1 , 861 embryos in eligible control groups 1 , 185 ( 63 . 68% ) were abnormal for one or more chromosomes ( excluding embryos in which aneuploidy only affected chromosomes involved in the Robertsonian translocation in the corresponding patient ) . This compares to a 69 . 81% aneuploidy rate in the embryos of Robertsonian translocation carriers ( again excluding those with abnormality affecting the translocated chromosomes only ) . Thus , the relative risk of a Robertsonian translocation carrier producing an abnormal cleavage stage embryo , due to an error unrelated to their constitutional rearrangement , is 1 . 096 . In other words , out of every 11 euploid zygotes produced by a Robertsonian translocation carrier one is expected to become abnormal by the cleavage stage due to an ICE . Most aneuploidies detected in cleavage stage embryos from Robertsonian translocation carriers , which presumably include those arising as a result of the ICE , are of types incompatible with development beyond the first few days of life , producing embryos that would fail to implant or result in an early miscarriage . Indeed , the fact that a significant increase in aneuploidy rate was not seen in blastocyst stage embryos ( five days after fertilization of the oocyte ) suggests that many of the abnormal embryos , or at least the aneuploid cells potentially produced as a consequence of a mitotic ICE , are rapidly eliminated . The embryonic genome is active during development from the cleavage to the blastocyst stages , which may allow cell-cycle regulatory mechanisms to clear highly abnormal cells via apoptosis or other processes . Nonetheless , it is conceivable that some abnormalities resulting from the ICE could occasionally produce miscarriages or , more rarely , the birth of children with severe congenital abnormalities ( e . g . Down , Edwards , Patau , Klinefelter or Turner syndromes ) . While the incidence of aneuploidy at birth is only likely to be slightly elevated , there may be a more pronounced effect on fertility , due to the increased mortality of early embryos . This may be particularly relevant for patients using assisted reproductive techniques such IVF or PGD . An important clinical consideration is that for Robertsonian translocation carriers undergoing IVF , preimplantation genetic diagnosis using a comprehensive chromosome screening technique , capable of detecting aneuploidy affecting any chromosome is highly advisable [21]–[24] , [33]–[36] . Older PGD methods utilizing FISH , which focus on analysis of the rearranged chromosomes only , should be discouraged , since they will fail to detect abnormalities affecting other chromosomes , arising as a consequence of an ICE . In conclusion , an ICE affects carriers of Robertsonian translocations and may contribute to higher rates of abnormal embryos , resulting in a small increase in the risk of miscarriage and birth of children with congenital abnormalities and a potential reduction in fertility . These possibilities should be considered when counselling patients about the risk of abnormal pregnancy following natural conception or the likelihood of producing embryos suitable for uterine transfer during cycles of PGD . Further research to determine the mechanism by which rearranged chromosomes can disrupt the process of mitotic chromosome segregation should be encouraged . In the case of cleavage stage embryos , the combination of chromosome rearrangement and compromised cellular mechanisms for the maintenance of genetic fidelity may be important . Chromosome rearrangements and reduced genetic stability are also a hallmark of many tumor cells , suggesting that the mitotic ICE described here may have important implications in cancer research and the understanding of tumor evolution as well as in developmental biology and clinical genetics .
All patients had their chromosomal rearrangements accurately defined by clinical cytogeneticists using standard chromosome banding techniques . The samples were obtained during 54 PGD cycles undertaken for 44 couples ( Table 1 ) . The average maternal age was 35 . 6 years ( maternal age range 26–43 ) and the chromosome rearrangements included 20 Robertsonian translocations , 23 reciprocal translocations and 3 inversions ( for one couple , the male partner was a carrier of a reciprocal translocation and the female partner was a carrier of an inversion ) . The PGD cases were undertaken over a three year period , with patients undergoing assisted reproductive treatment at seven different IVF clinics and genetic diagnosis performed at two different PGD laboratories ( Reprogenetics UK [Oxford , UK] and Reprogenetics LLC [New Jersey , USA] ) . All IVF centres involved in this study had the necessary ethical and clinical approvals and licenses required for the tests offered to patients . All patients were provided with counselling regarding PGD using aCGH , and signed consent was obtained in all cases . Diagnosis was performed at one of three different preimplantation stages ( Table 1 ) . All biopsies involved breach of the zona pellucida encapsulating the oocyte/embryo with a laser , regardless of the embryonic stage being tested . Standard methods of ovarian stimulation , biopsy and embryo culture were utilized . Oocyte analysis involved aCGH of the first and second polar bodies; cleavage stage analysis was undertaken with the biopsy of a single blastomere three days after fertilization of the oocyte ( 8-cell stage ) ; blastocyst evaluation employed removal of approximately five cells from the trophectoderm layer five days after fertilization . Microarray-CGH analysis was undertaken according to our previously validated protocol [21] . Briefly , whole genome amplification was carried out in order to generate sufficient DNA from the minute samples under analysis ( SurePlex , Rubicon , USA ) . Amplified sample and reference DNAs were labelled with Cy3 and Cy5 respectively and then hybridized to the probes of a bacterial artificial chromosome ( BAC ) microarray ( 24Sure+ , BlueGnome , Cambridge , USA ) . Chromosome losses and gains were revealed by differences in the fluorescence intensity corresponding to sample and reference DNAs for BAC probes derived from the affected chromosome or chromosomal region . Labelling of the amplified samples , hybridization to microarray slides , post-hybridization washes and analyses were performed as described previously [21] . Published values for the accuracy rate for aCGH are 94% , 98% and 95% for polar bodies , blastomeres and trophectoderm cells , respectively [36]–[38] . In order to assess whether the incidence of abnormalities was the same in the presence of a chromosome rearrangement , the data from patient and control samples were compared statistically ( Chi squared test with Yates' correction ) . However , pooling data from multiple patient-specific controls was not straightforward , as some control groups were composed of larger numbers of samples than others . Given the importance of female age in aneuploidy predisposition the control data could have been inadvertently skewed by including disproportionately large numbers of samples from individuals of specific ages . To overcome this problem , we ensured that the samples from each patient-specific control were given equal weight to the samples from the matched patient ( i . e . control data was transformed to match the sample number of the corresponding patient ) . In order to accomplish this we first deduced the frequency of aneuploid chromosomes per sample in each control group ( i . e . total number of errors divided by total number of chromosomes analysed ) . We then multiplied this figure by the number of chromosomes assessed for the corresponding matched patient ( after excluding the chromosomes involved in the rearrangement ) . The result represents the number of chromosome errors that would have been expected in the control group had it consisted of the same number of samples as produced by the matched patient . The expected numbers of aneuploidies for the control groups are detailed in Table 5 . | Translocations involve exchange of material between two or more chromosomes and are a common form of genetic abnormality . The rearrangements are difficult to process during meiosis , frequently producing gametes with missing/extra pieces of the affected chromosomes . It has been suggested that translocations might also disrupt the segregation of structurally normal chromosomes , a so-called interchromosomal effect ( ICE ) , but the published data is contradictory . Here we report results from a unique collection of samples , consisting of oocytes and embryos from translocation carriers . Examination of more than 210 , 000 chromosomes revealed no evidence of an ICE in oocytes , but a significant effect in embryos tested three days after fertilization ( 6–10 cell stage ) in a subset of patients . Clinically , this means that some translocation carriers are at even higher risk of chromosomally abnormal pregnancies than previously suspected , a factor that should be considered during genetic counselling . Scientifically , the results illuminate a poorly understood stage of human development , characterized by chromosomal instability , reminiscent of that observed in some tumors . The restriction of the ICE to a narrow developmental window was unexpected , yet may explain why some earlier studies could not agree on the existence of an ICE . | [
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... | 2012 | Embryos of Robertsonian Translocation Carriers Exhibit a Mitotic Interchromosomal Effect That Enhances Genetic Instability during Early Development |
The metabolic events associated with maintaining redox homeostasis in Mycobacterium tuberculosis ( Mtb ) during infection are poorly understood . Here , we discovered a novel redox switching mechanism by which Mtb WhiB3 under defined oxidizing and reducing conditions differentially modulates the assimilation of propionate into the complex virulence polyketides polyacyltrehaloses ( PAT ) , sulfolipids ( SL-1 ) , phthiocerol dimycocerosates ( PDIM ) , and the storage lipid triacylglycerol ( TAG ) that is under control of the DosR/S/T dormancy system . We developed an in vivo radio-labeling technique and demonstrated for the first time the lipid profile changes of Mtb residing in macrophages , and identified WhiB3 as a physiological regulator of virulence lipid anabolism . Importantly , MtbΔwhiB3 shows enhanced growth on medium containing toxic levels of propionate , thereby implicating WhiB3 in detoxifying excess propionate . Strikingly , the accumulation of reducing equivalents in MtbΔwhiB3 isolated from macrophages suggests that WhiB3 maintains intracellular redox homeostasis upon infection , and that intrabacterial lipid anabolism functions as a reductant sink . MtbΔwhiB3 infected macrophages produce higher levels of pro- and anti-inflammatory cytokines , indicating that WhiB3-mediated regulation of lipids is required for controlling the innate immune response . Lastly , WhiB3 binds to pks2 and pks3 promoter DNA independent of the presence or redox state of its [4Fe-4S] cluster . Interestingly , reduction of the apo-WhiB3 Cys thiols abolished DNA binding , whereas oxidation stimulated DNA binding . These results confirmed that WhiB3 DNA binding is reversibly regulated by a thiol-disulfide redox switch . These results introduce a new paradigmatic mechanism that describes how WhiB3 facilitates metabolic switching to fatty acids by regulating Mtb lipid anabolism in response to oxido-reductive stress associated with infection , for maintaining redox balance . The link between the WhiB3 virulence pathway and DosR/S/T signaling pathway conceptually advances our understanding of the metabolic adaptation and redox-based signaling events exploited by Mtb to maintain long-term persistence .
The success of Mtb as a remarkably effective pathogen is due to the ability of the bacilli to latently infect ∼2 billion people world wide [1] . The metabolic events necessary for Mtb to enter , maintain and emerge from a latent infection are poorly understood , but are crucial towards the development of new drugs and vaccines , primarily because latent Mtb is in a state of drug unresponsiveness . Persistent infection is a complex interplay between the host immune system and bacterial virulence mechanisms , and little is known about the environmental signals and regulatory cascades involved in the regulation of specific bacterial component involved in this process . The role of Mtb cell wall polyketide lipids has received wide attention because it has been demonstrated that surface exposed polyketides such as PDIM and PGL-tb interact with the host to regulate Mtb virulence [2] , [3] . An earlier study hypothesized that the failure of Mtb to induce a complex protective response against oxidative stress is because its complex cell wall lipids act as a constitutive defense mechanism to withstand oxidative insult [4] . Indeed , cell wall components such as phenolic glycolipid ( PGL-1 ) [2] , mycolic acids and PDIM were shown to play a role in protecting Mtb against redox stress and antibiotics [5]–[7] whereas other lipids ( e . g . , SL-1 ) exert immunomodulatory effects [8] . Complex lipids are also thought to regulate the degree of virulence , for example hypervirulence of the W-Beijing strains was linked to the production PGLs [3] . Recent studies have demonstrated that TAG accumulates in Mtb cells during hypoxia , nitric oxide ( NO ) exposure [9] , in the sputum of TB patients [10] , and in Mtb Beijing strains [11] . Subsequently , it was proposed that Mtb TAG functions as a preferred carbon source during long-term persistence and reactivation [9] . However , it has also been suggested that bacterial TAG may function as a sink for reducing equivalents [12] . Collectively , these studies point toward a complex mechanism involving Mtb lipids to effectively adapt and respond to host generated redox stress . Identity of an Mtb regulator that integrates environmental redox stress signals with the production of bioactive lipids to modulate pathogenesis is not known , and will be an important contribution to the TB field . Previously , we have shown that Mtb WhiB3 controls virulence in two animal models of TB [13] . WhiB orthologues have been implicated in a variety of pathways including sporulation , pathogenesis , cell division [14] , oxidative stress [15] , and antibiotic resistance [16] . Mtb whiB3 expression was shown to be induced in phagosomes [17] and during infection of mouse lungs [18] . The pathology defect exhibited by MtbΔwhiB3 in the mouse model [13] as well as the altered colony rugosity and growth properties of MtbΔwhiB3 on acetate [19] suggest that WhiB3 is involved in maintaining redox homeostasis by regulating fatty acid metabolism in Mtb . A fundamentally important question remains yet unanswered: What is the mechanism by which WhiB3 contributes to Mtb persistence and virulence ? In this study we exploited transmission ( TEM ) and scanning electron microscopy ( SEM ) and studied the ultrastructure of wild type ( wt ) Mtb and MtbΔwhiB3 . We comprehensively analyzed the lipid content of wt Mtb and MtbΔwhiB3 under oxido-reductive stress conditions , and upon infection of macrophages . Importantly , we examined the intracellular redox state of wt Mtb and MtbΔwhiB3 cells derived from infected macrophages and analyzed the outcome of whiB3 loss on the host immune response . Finally , we examined the ability of WhiB3 to bind the promoter regions of polyketide biosynthetic genes in a redox-dependent manner . Our results provide mechanistic insight into the metabolic events required for maintaining redox homeostasis in Mtb during infection .
MtbΔwhiB3 cells cultured in liquid media containing tween-80 displayed significant clumping and aggregation specifically in the late stationary growth phase i . e OD600 nm = 3 . 0 ( Fig . 1A , tube 2 ) . To investigate the possibility that the observed aggregation was not due to the efficient utilization of Tween-80 by the MtbΔwhiB3 mutant , we examined the aggregation phenotype in liquid media containing tyloxapol ( a non-hydrolyzable dispersing agent ) . Similar aggregation of MtbΔwhiB3 was observed when cultured in the liquid media containing tyloxapol ( data not shown ) . On solid media , MtbΔwhiB3 generated a disordered colony organization , suggesting the loss of cording ( Fig . 1B ) . On the SEM grid , MtbΔwhiB3 cells were organized in discrete clusters such that it was difficult to identify individual cells for morphological analysis ( Fig . 1C inset and 1D ) . Wt Mtb appeared as long rods ( average length , ∼2 . 8±0 . 8 µm ) whereas MtbΔwhiB3 cells were significantly reduced in length ( average length , ∼0 . 9±0 . 05 µm ) ( Fig . 1C and 1D ) , and appeared irregular and shrunken . In our TEM analysis , we consistently observed poor contrast and hyper-staining of MtbΔwhiB3 cells compared to wt Mtb cells ( Fig . 1E ) , reflecting clear perturbations of the cell wall composition . These results confirmed the essential role of WhiB3 in maintaining the appropriate cell size , shape , and surface architecture of Mtb . In order to confirm that the altered in vitro growth morphology phenotype of MtbΔwhiB3 was due to defective cell envelope lipid composition , we biochemically analyzed the lipid content of wt Mtb and MtbΔwhiB3 cells . We performed our lipid analysis using well dispersed cultures of MtbΔwhiB3 grown to OD600 nm = 1 . 5 . Lipids containing methyl-branched fatty acids of wt Mtb and MtbΔwhiB3 cells were metabolically labeled using 14C propionate as a radiotracer . Interestingly , wt Mtb incorporates 20–25% of the administered 14C into total lipid whereas MtbΔwhiB3 incorporates only 10–15% in 24 h . Since wt Mtb and MtbΔwhiB3 showed similar growth characteristics as judged by the increase in cell mass and CFU analysis [data not shown] , we normalized for the difference in lipid biosynthetic ability of MtbΔwhiB3 by loading equal radioactive counts per minute ( cpm ) of 14C incorporated total lipids and analyzed the samples via thin layer chromatography ( TLC ) . A detailed analysis of the 14C distribution pattern showed significant alterations among PAT , DAT , SL-1 , PDIM and TAG in MtbΔwhiB3 ( Table 1 ) . As shown in Fig . 2A , we observed that the polar lipid fraction was absent in MtbΔwhiB3 . Consistent with this observation , MtbΔwhiB3 showed a defect in the production of methyl-branched polar lipids PAT , DAT and SL-1 ( Fig . 2B , D ) . Intriguingly , we observed a 5-fold increase in the labeling of PDIM , and minor accumulation of TAG in MtbΔwhiB3 compared to wt Mtb ( Fig . 2C ) . Similar changes were observed for PAT and PDIM isolated from early logarithmic phase cultures ( OD600 nm = 0 . 6 ) ( Fig . S1 ) . The defective production of surface exposed polar lipids such as SL-1 , PAT and DAT along with the accumulation of non-polar lipids such as PDIM , suggests that the aggregation phenotype exhibited by MtbΔwhiB3 cells is due to increased hydrophobicity of the cell surface . Next , we examined the mycolic acid profiles of wt Mtb and MtbΔwhiB3 using [1] , [2] 14C acetate as tracer . Both wt Mtb and MtbΔwhiB3 incorporated 25–30% of 14C into total lipids in 24 h . No quantitative or qualitative differences between wt Mtb and MtbΔwhiB3 were observed in the case of arabinogalactan linked mycolates ( data not shown ) . However , we observed a 2-fold decrease in the labeling of α , α′-trehalose di-mycolate ( TDM ) and 5-fold decrease of α , α′-trehalose mono-mycolate ( TMM ) in MtbΔwhiB3 cells ( Fig . 2E ) . Importantly , complementation using wt Mtb whiB3 restored the cell wall lipid defect of MtbΔwhiB3 . We also detected an altered lipid profile from the culture filtrate similar to the cell pellet of MtbΔwhiB3 , ruling out the contribution of a defect in the secretion of lipids in the observed phenotype ( data not shown ) . In sum , our lipid analysis demonstrated that MtbΔwhiB3 is defective in the production of surface associated virulence lipids . An important discovery is that MtbΔwhiB3 accumulates PDIM ( and TAG ) , a finding that has not been reported for any Mtb mutant to date . These data strongly suggest that the prior pathology defect exhibited by the MtbΔwhiB3 strain in mice [13] was in part due to an altered repertoire of bioactive polyketides . To date , the identity of environmental stimuli regulating the production of complex Mtb virulence polyketides or lipids remains unknown . We have previously proposed that Mtb WhiB3 acts as an intracellular redox sensor involved in maintaining redox balance by regulating central metabolism [19] . To confirm that WhiB3 couples the intracellular redox environment of Mtb with lipid synthesis , wt Mtb and MtbΔwhiB3 lipid profiles were analyzed under defined redox stress conditions . We chose to compare the effect of an altered Mtb intracellular redox environment on the assimilation of propionate into PAT and PDIM production . Wt Mtb and MtbΔwhiB3 cells from the logarithmic growth phase were exposed to 5 mM diamide or DTT , followed by radiolabeling with 14C propionate . Interestingly , in the DTT containing medium , wt Mtb incorporated 3-fold less 14C into total lipid as compared to cells grown in control ( 7H9 ) or diamide containing medium . However , in the case of MtbΔwhiB3 , we observed a 1 . 5 and 3-fold reduction in the incorporation of 14C during growth in DTT or diamide containing medium , respectively , as compared to the control . Since , 5 mM DTT or diamide has no influence on the growth of wt Mtb or MtbΔwhiB3 ( as judged by spot colony phenotype; data not shown ) , we normalized the difference in rate of 14C incorporation by loading equal cpm on the TLC plates . First , we analyzed wt Mtb . Fig . 3 demonstrates that diamide exposed wt Mtb cells produces 5-fold more PAT as compared to DTT exposed Mtb cells . In contrast , DTT exposed Mtb cells incorporate 10-fold more propionate into PDIM as compared to diamide treated cells ( Fig . 3 ) . Next , we analyzed how reduced or oxidized MtbΔwhiB3 cells affect propionate assimilation into PAT and PDIM . We demonstrated that in MtbΔwhiB3 , the production of PAT and PDIM in response to diamide and DTT was exactly the opposite of wt Mtb ( Fig . 3 ) . Since production of TAG is slightly enhanced in MtbΔwhiB3 , we analyzed the assimilation of 14C propionate into TAG under oxidizing and reducing conditions . Strikingly , Fig . 3 shows a 3-fold induction of TAG production in DTT-exposed MtbΔwhiB3 as compared to wt Mtb . Consistent with these results , we observed similar accumulation of TAG in DTT-exposed MtbΔwhiB3 when labeled using [1] , [2] 14C acetate as a tracer ( Fig . S2 ) . Importantly , the altered lipid profile of MtbΔwhiB3 upon modulation of the intracellular redox environment was restored to wt Mtb lipid levels by complementing MtbΔwhiB3 cells with wt whiB3 . The implications of these findings are significant and suggest that intracellular oxidative or reductive stress in Mtb modulates anabolism of diverse polyketides required for virulence , as well as TAG , which might be essential for long-term persistence and reactivation . Much of the existing Mtb literature is derived from the transcriptional response of lipid biosynthetic genes in vivo , and does not reflect the exact physiological level and composition of virulence lipids produced during infection . To gain insight into Mtb metabolic and redox-mediated events during infection , we performed the first assessment of lipid profile changes of Mtb residing in Raw 264 . 7 macrophages . We infected macrophages using well dispersed , logarithmically grown cultures of MtbΔwhiB3 . Radiolabeling of lipids was performed using 14C propionate as a tracer . Wt Mtb and MtbΔwhiB3 showed 4-fold reduction in the incorporation of 14C into total lipids within macrophages as compared to cells cultured in vitro ( 7H9 or DMEM ) . With the newly developed [14C]-propionate labeling and extraction method , we demonstrated that wt Mtb within macrophages assimilates 2 , 3 and 10- fold more propionate into SL-1 , PAT and TAG , respectively , as compared to cells cultured in vitro ( 7H9 ) ( Fig . 4 and Fig . S3 ) . Strikingly , MtbΔwhiB3 cells cultured in vivo incorporated 2-fold less 14C propionate into PAT and SL-1 ( Fig . 4 and Fig . S3 ) and a 3 and 15-fold increased incorporation into PDIM and TAG , as compared to cells cultured in vitro ( Fig . 4 ) . Lipids derived from macrophages were successfully removed by washing infected cells twice in methanol ( see Materials and Methods ) . As a control , uninfected macrophages were metabolically labeled with [14C]-propionate and treated in a similar manner as infected macrophages to ensure that lipids were derived from intracellular bacteria and not macrophages ( see Materials and Methods ) . Further , using Fourier Transform Ion Cyclotron Resonance Mass Spectrometry ( FT-ICR MS ) we analyzed the total lipid profile of Mtb as previously described [20] . As anticipated , FT-ICR MS analysis of total lipid extracts derived from Mtb and MtbΔwhiB3 after infection of macrophages resulted in the identification of complex lipid species including phosphatidylinositol mannosides ( PIMs ) , PDIM and SL-1 ( Fig . S4 ) . Differences in phosphatidyl inositol ( PI ) and phosphatidyl inositol mannoside ( PIM ) production by wt Mtb and MtbΔwhiB3 within macrophage cells were not observed ( Fig . S4A ) . However , the SL-1 profile was noticeably altered in lipid samples from MtbΔwhiB3 infected macrophages ( Fig . S4B ) . In fact , the SL-1 spectrum , which is comprised of various lipoforms differing by 14 mass units between m/z 2400–2600 [20] , was completely absent in the MtbΔwhiB3 sample ( Fig . S4B ) . Furthermore , consistent with our metabolic labeling data , we did observe PDIM in crude lipid extracts derived from in vivo grown wt Mtb and MtbΔwhiB3 ( Fig . S4C ) . FT-ICR MS analysis of lipids isolated from wt Mtb and MtbΔwhiB3 cultured in vitro also demonstrated a similar profile to the in vivo data ( not shown ) . Importantly , as shown by metabolic labeling ( Fig . 4 ) and FT-ICR MS analysis ( Fig . S4 ) , complementation of MtbΔwhiB3 with whiB3 restored the wt lipid profile inside macrophages . In sum , data generated using two independent techniques provide novel insight into the metabolic adaptation of Mtb during growth in vitro and in vivo . Lastly , WhiB3 was identified as an important physiological regulator of PAT , DAT , SL-1 , PDIM and TAG anabolism in Mtb . Since it was proposed that methyl-branched polyketide production functions as a mechanism to remove toxic levels of propionate in vivo [21] , we analyzed the growth of MtbΔwhiB3 on propionate containing medium . Wt Mtb and MtbΔwhiB3 grew virtually identically in media containing 10 mM of propionate as a sole carbon source ( Fig . 5A ) . However , in 20 mM propionate , wt Mtb was severely impaired for growth , whereas MtbΔwhiB3 growth appeared unaffected ( Fig . 5B and inset ) . This striking phenotype was reversed by complementation of MtbΔwhiB3 with an intact copy of whiB3 ( Fig . 5 ) . These observations suggest that increased resistance of MtbΔwhiB3 to toxic levels of propionate could be due to channeling of propionate into PDIM via the methyl-malonyl CoA ( MMCoA ) pathway , and TAG . Having established that the synthesis of virulence lipids is directly mediated by WhiB3 in a redox-dependant manner , we now sought to examine the defined role of WhiB3 in maintaining the Mtb intracellular redox environment . Since the pyridine nucleotides ( NAD+ and NADH ) and their phosphorylated forms ( NADP+ and NADPH ) are central to catabolic and anabolic metabolism , respectively , we utilized a recently developed [14C] nicotinamide incorporation assay [22] and measured the redox poise of NADH or NADPH from Mtb cells cultured in vitro , or derived from macrophages ( see Protocol S1 ) . Since the Mtb NAD salvage pathway is not efficient in vitro [22] , we observed minor incorporation of nicotinamide into NAD+ of wt Mtb and MtbΔwhiB3 cultured in vitro ( results not shown ) . However , a significant increase in the incorporation of exogenously added nicotinamide into NAD+ in wt Mtb cells from infected macrophages was observed ( Fig . 6A lane 1 , B ) . Furthermore , a dramatic increase in the labeling of the band that corresponds to NADH and/or NADPH from MtbΔwhiB3 cells within macrophages was observed ( Fig . 6A lane 2 , 6B ) . Consistent with previous reports [23] , using different solvents , separation of NADH and NADPH by TLC was ineffective . Regardless , these results demonstrate that MtbΔwhiB3 accumulates significant quantities of NADH and/or NADPH within macrophages , and therefore experiences considerable reductive stress . In order to determine the exact contribution of NADH and NADPH in the above radiolabeling experiments , we exploited an enzymatic cycling assay to distinguish between NADH and NADPH . We cultured Mtb derived from macrophages in 7H9 basal medium containing acetate as a sole carbon source [19] . We observed a small , but reproducible increase in NAD+/NADH from MtbΔwhiB3 cells grown in vitro as compared to wt Mtb ( Fig . 6C ) , suggesting efficient recycling of NADH because of increased acetate metabolism . This is consistent with our previous findings [19] that MtbΔwhiB3 grow better on acetate containing media than wt Mtb . Surprisingly , the increased NAD+/NADH ratio in MtbΔwhiB3 was restored to wt Mtb levels during growth in macrophages ( Fig . 6C ) . Since NADPH is an essential reductant used in lipid anabolism [24] , we sought to examine the influence of defective lipid anabolism in MtbΔwhiB3 on the redox poise of NADP+/NADPH . During growth in vitro , the NADP+/NADPH ratio remained the same ( Fig . 6D ) . However , we observed a ∼2-fold reduction in the NADP+/NADPH ratio from MtbΔwhiB3 cells growing within macrophages as compared to wt Mtb ( Fig . 6D ) , demonstrating that MtbΔwhiB3 accumulates substantial levels of NADPH . The radiolabel and enzymatic cycling assays are in reasonable agreement . However , although widely used , the acidic/alkaline extraction method used in the enzymatic assay is associated with a loss or oxidation of reduced pyridine nucleotides . Therefore , the radiolabeling method is a much more accurate indicator of the intrabacterial redox poise . In sum , these results suggest that MtbΔwhiB3 experiences reductive stress during infection , and that the WhiB3-dependant redox regulation of virulence lipids is essential for maintaining intrabacterial redox homeostasis during macrophage infection . Mtb cell wall lipids are direct modulators of the host immune response . Our current and previous [13] results strongly suggest that the WhiB3-mediated redox regulation of virulence lipids may influence macrophage response . Here we sought to examine and compare the release of pro and anti-inflammatory cytokines from macrophages infected with wt Mtb and MtbΔwhiB3 . We infected macrophages with well-dispersed MtbΔwhiB3 cells to completely rule out the influence of aggregation on infection . We analyzed the levels of IL-2 , IL-4 , IL-5 , IL-10 , IL-12 ( p70 ) , GM-CSF , IFN-γ and TNF-α in the culture supernatant of macrophages 24 h post infection . Both strains grew at a similar rate within macrophages ( data not shown ) and induce the release of various cytokines in the culture supernatant 24 h post infection . However , MtbΔwhiB3 elicited significantly higher levels of pro- and anti-inflammatory cytokines as compared to wt Mtb ( Fig . 7 ) . Thus , in spite of an identical number of intracellular bacteria , macrophages infected with MtbΔwhiB3 produced higher amounts of cytokines , and this provides further proof that the immune suppressing capacity of Mtb is impaired in MtbΔwhiB3 . The data suggest that the WhiB3-mediated regulation of complex lipids , and perhaps other Mtb factors , [25] modulates the kinetics and balance between pro- and anti-inflammatory cytokines to favor long term persistence of the bacilli , which may explain the in vivo phenotype exhibited by MtbΔwhiB3 [13] . Having fully confirmed the role of WhiB3 in regulating cell wall lipid biosynthesis in vitro and in macrophages , we now sought to examine the underlying molecular and biochemical mechanisms . For more than 15 years WhiB homologues in actinomycetes have been speculated to be putative redox- responsive DNA-binding transcription factors [26] . However , formal proof demonstrating their DNA binding activity in a redox-dependent manner is lacking . In the sections below , we first describe how the expression of polyketide genes was altered in the MtbΔwhiB3 . We then demonstrate the influence of the redox state of the 4Fe-4S cluster on DNA binding of reconstituted WhiB3 ( otherwise referred to as holo-WhiB3 ) . Furthermore , we then examine how changes in the Cys thiol oxidation state affect DNA binding of apo-WhiB3 ( without 4Fe-4S cluster ) . Lastly , we analyzed apo- and holo-WhiB3 DNA binding properties . Here we examine whether WhiB3 regulates the production of complex lipids by controlling the expression of genes encoding modular polyketide synthases . Since the identity of genes required for SL-1 , PAT , DAT , TDM and PDIM are well established , we used quantitative PCR ( Q-PCR ) and analyzed the expression of pks2 ( necessary for SL-1 production ) , pks3 ( necessary for PAT/DAT production ) , fbpA ( necessary for TDM production ) , mas , ppsA , fadD26 or fadD28 ( necessary for PDIM production ) in wt Mtb and MtbΔwhiB3 cells . Consistent with our lipid data ( Fig . 2A–E ) , we found that pks2 , pks3 and fbpA expression were down-regulated 62 . 5 , 32 . 8 and 111-fold , respectively , in MtbΔwhiB3 ( Fig . 8 ) . In sum , our data suggest that WhiB3 is a positive transcriptional regulator of genes responsible for the production of PAT , DAT , SL-1 and TMM/TDM . However , we did not detect any significant changes in the transcript levels of genes involved in the biosynthesis of PDIM . This suggest a post-transcriptional mode of regulation for PDIM , perhaps by escalating PDIM production to compensate for increasing propionyl CoA and/or methyl malonyl CoA ( MMCoA ) levels caused by inefficient utilization via PAT/DAT and SL-1 ( Fig . 8 inset ) . These results are consistent with a recent study linking the regulation of SL-1 and PDIM biosynthesis with a common precursor , MMCoA [20] . Having established that WhiB3 regulates the production of major complex polyketides and lipids of Mtb , we next sought to determine if WhiB3 could directly bind to the promoter regions of Mtb pks2 and pks3 . Interestingly , WhiB3 overexpressed and purified from E . coli was always associated with contaminating genomic DNA . Subsequently , we took thorough measures to ensure complete removal of DNA prior to performing DNA binding studies ( See Protocol S1 ) . The WhiB3 [4Fe-4S]2+ cluster was effectively reconstituted in vitro using NifS and confirmed by UV-Vis spectroscopy ( Fig . S5 ) as described previously [19] . Holo-WhiB3 was then analyzed for DNA binding activity under anaerobic conditions . The data demonstrate that WhiB3 binds to the promoter regions ( ∼300 bp upstream from ATG ) of both pks2 and pks3 ( Fig . 9A and 9B ) in a concentration dependent manner . When incubated with 400 nM and 800 nM holo-WhiB3 , a diffused smear was observed , suggesting weak DNA binding activity . The weak DNA binding acitivty of holo-WhiB3 was confirmed by performing EMSA analyses in the presence of a NaCl gradient ( see below ) . In sum , this data demonstrate that Mtb holo-WhiB3 possesses DNA binding activity . Previously , we have shown that the WhiB3 [4Fe-4S]2+ cluster can easily be reduced to [4Fe-4S]1+ by the one electron reducing agent dithionite [19] . Since it is well known that the redox status of Fe-S clusters of regulatory proteins can affect DNA binding ( e . g . , SufR; [27] ) or transcriptional activation ( e . g . , SoxR; [28] ) , we sought to examine the effect of the redox status of the WhiB3 Fe-S cluster on DNA binding . Reduction of the WhiB3 [4Fe-4S]2+ cluster to a [4Fe-4S]1+ cluster by DTH was confirmed by UV-vis spectroscopy as described [19] . Reduced ( [4Fe-4S]1+ ) and oxidized ( [4Fe-4S]2+ ) holo-WhiB3 fractions were purified via size exclusion chromatography and analyzed for pks3 promoter DNA binding under anaerobic conditions . As shown in Fig . 9C , reduced and oxidized holo-WhiB3 binds to the pks3 promoter at similar concentrations . Also , we did not observed any noticeable difference in the mobility of WhiB3 [4Fe-4S]2+:DNA and WhiB3 [4Fe-4S]1+:DNA complexes , strongly suggesting that the redox state of the WhiB3 4Fe-4S cluster does not modulate DNA binding . It is known that despite containing redox active 4Fe-4S cluster , aconitase binds specific mRNAs in the apo-form [29] . Furthermore , the RNA binding activity of aconitase is regulated by the redox state of its Cys residues . Since O2 destroys WhiB3 Fe-S cluster to generate apo-protein containing exposed Cys residues [19] , we sought to examine apo-WhiB3 and the influence of the redox state of its Cys residues on DNA binding . Apo-WhiB3 was generated as described [30] . Complete loss of Fe-S cluster from WhiB3 was confirmed by UV-Vis spectroscopy and mass spectrometry ( data not shown ) . We thoroughly deoxygenated apo-WhiB3 and pre-incubated with diamide ( a thiol-specific oxidant ) or DTT ( a thiol-specific reductant ) and examined the protein∶DNA complexes by electromobility shift assays ( EMSA ) under fully anaerobic conditions . Fig . 10A shows that apo-WhiB3 treated with diamide ( WhiB3-SS ) rapidly induces the formation of a WhiB3-SS:DNA complex of retarded mobility ( Fig . 10A ) . However , in the case of DTT-treated WhiB3 ( apo-reduced; WhiB3-SH ) , we observed complete inhibition of DNA-binding ( Fig . 10A ) . Furthermore , DNA binding was rapidly restored when WhiB3-SH was exposed to diamide . Similarly , DNA binding was lost when WhiB3-SS was treated with DTT ( Fig . 10A ) . Lastly , we showed that under these experimental conditions , >100 µM diamide is sufficient to induce apo-WhiB3 DNA binding ( Fig . 10B ) . The above results suggest that oxidation of WhiB3 Cys thiols stimulates apo-WhiB3 DNA binding , but that reduction of the WhiB3 thiols abolish DNA binding . Consistent with the above findings , our in vitro thiol trapping experiment confirmed that diamide induces oxidation of the four WhiB3 Cys residues to generate two intramolecular disulphide bonds ( Fig . S6 ) . In sum , our results demonstrate that the WhiB3 Cys center functions as a thiol-based nano-switch that modulates DNA binding . In order to study the specificity of WhiB3 binding to the radiolabeled pks3 promoter , several DNA fragments were utilized in the competition assays , ( i ) specific Mtb DNA comprised of the pks3 and pks2 promoter region , ( ii ) non-specific Mtb open reading frame ( ORF ) DNA ( Rv3874 , cfp-10 ) and ( iii ) non-specific eukaryotic ORF DNA encoding FK506 binding protein ( FKBP ) . First , we performed competition assays to examine the sequence specificity of WhiB3-SS DNA binding . Fig . 11A demonstrated that competition with an 800-fold molar excess of specific unlabeled pks3 DNA resulted in complete loss of WhiB3-SS DNA-binding whereas the same concentration of non-specific eukaryotic DNA , fkbp , caused no loss of DNA binding . Interestingly , we observed that an 800-fold molar excess of mycobacterial ORF DNA , cfp-10 , resulted in significant , but not complete loss of WhiB3 DNA binding ( Fig . 11A ) . Furthermore , our results showed that competition with cfp-10 generates a sharp band of progressively changing mobility , suggesting discrete structural complexes of different mobilities . Similar findings were obtained using the specific Mtb pks2 promoter region and non-specific Mtb ORF DNA ( Rv2151c , ftsQ ) ( results not shown ) . Next , an identical set of experiments were performed as described in Fig . 11A , except that holo-WhiB3 was used . As anticipated , Fig . 11B shows that holo-WhiB3 retarded DNA marginally as compared to WhiB3-SS . Furthermore , a 200-fold molar excess of specific unlabeled pks3 or pks2 DNA resulted in complete loss of DNA binding , whereas , a 400-fold ( cfp-10 ) to 800-fold ( fkbp ) excess of non-specific competitor DNA caused a complete loss of holo-WhiB3:DNA binding . Since , holo and apo-WhiB3 generate distinct complexes , our results suggest that differences in oligomerization influence their mobilities . . Lastly , to analyze strength of apo- and holo-WhiB3 DNA , we performed EMSA in the presence of a NaCl gradient . As expected , 400–600 mM of NaCl completely abolished holo-WhiB3 DNA binding whereas 1 M of NaCl was insufficient to prevent apo-WhiB3 DNA binding ( Fig . 11C ) . These results confirmed that WhiB3-SS binds DNA significantly stronger than holo-WhiB3 . In sum , the data generated by several independent experiments demonstrate that WhiB3 is a redox-responsive DNA binding protein , and that WhiB3-SS and holo-WhiB3 bind specific and non-specific DNA with a low degree of discrimination
Members of the WhiB-like protein family play an important role in actinomycete biology and pathogenesis . However , a detailed biochemical and genetic mechanism of WhiB function has not yet been established . In this study we provide unique insight into the mechanism of action of Mtb WhiB3 and show that WhiB3 regulates the production of the inflammatory polyketides PAT , DAT , SL-1 and PDIM , and lipid inclusion bodies ( TAG ) via a novel , redox-dependent switching mechanism . We developed a methodology to characterize lipid profiles of Mtb residing in macrophages and demonstrated that intrabacterial redox homeostasis is maintained by WhiB3 in part via channeling reducing equivalents into Mtb lipid synthesis , which modulate inflammatory cytokine production . These findings , as well as the discovery of a link between the intracellular WhiB3 virulence pathway and extracellular DosR/S/T dormancy signaling pathway , significantly impact our understanding of the role of WhiB3 in Mtb pathogenesis and persistence . Our findings introduce a new mechanism , which suggests that WhiB3 modulates Mtb lipid anabolism in response to oxido-reductive stress associated with infection to maintain redox balance and persistence . Previously , we proposed that WhiB3 senses fluctuations in the intracellular redox state of Mtb in response to O2 depletion and fatty acid metabolism , and maintains redox balance by regulating polyketide anabolism [19] . Surprisingly , the role of oxidative and/or reductive stress in regulating Mtb lipid anabolism has not yet been described and represents an understudied area of TB research . The absence of PAT , DAT and SL-1 , and accumulation of PDIM and TAG in MtbΔwhiB3 strongly suggests a role for WhiB3 in regulating lipid anabolism in response to the redox imbalance associated with normal cellular metabolism . Importantly , the fact that the expression of genes responsible for PDIM production is not differentially regulated in MtbΔwhiB3 suggests a post-transcriptional mode of regulation for PDIM biosynthesis , which is in agreement with a recent study suggesting the regulation of SL-1 and PDIM biosynthesis by a common precursor , MMCoA [20] . According to this model , inhibition of the PDIM pathway leads to accumulation of MMCoA , which is then diverted towards the synthesis of SL-1 [20] . However , disruption of the SL-1 pathway did not result in the accumulation of PDIM [20] , suggesting that other factors are involved . Our WhiB3 data provides new insight into this important central metabolic branch point , suggesting that joint inhibition of all three methyl branched lipids ( PAT , DAT and SL-1 ) , as opposed to SL-1 alone , is required to accumulate suitable levels of MMCoA to enhance PDIM levels ( Fig . 8 inset ) . Furthermore , since MtbΔwhiB3 also accumulates TAG ( which utilizes malonyl CoA rather than MMCoA ) , this suggests a central role for propionyl CoA rather than MMCoA in the synthesis of PAT , DAT , SL-1 , PDIM and TAG ( Fig . 8 , inset ) . The Mtb response regulator PhoP , which responds to a yet-to-be identified environmental signal , has been shown to positively regulate the production of PAT , DAT and SL-1 [31] . However , the expression of phoP is not altered in MtbΔwhiB3 ( unpublished observation ) and MtbΔphoP did not accumulate PDIM or TAG , suggesting that the WhiB3-dependent control of cellular redox homeostasis is an additional factor that is required to regulate the flux of propionyl CoA to methyl-branched polyketides and TAG synthesis . Thus , we discovered a new redox switching mechanism by which Mtb differentially assimilates fatty acid ( propionate ) into PDIM , TAG , SL-1 and PAT under defined oxidizing and/or reducing conditions in vitro . The physiological relevance of these redox-related metabolic events was supported by directly examining the lipid profiles of Mtb in resting macrophages ( Fig . 4 ) . Using a combination of sensitive metabolic labeling techniques and high resolution mass spectrometry , we demonstrated that WhiB3 is a major redox regulator of pathogenic lipid anabolism in vitro and within macrophages . During macrophage infection , wt Mtb predominantly assimilate propionate into methyl-branched polyketides ( PAT and SL-1 ) and surprisingly , also into the TAG biosynthetic pathway . Minor induction of PDIM biosynthesis was also observed . In contrast , MtbΔwhiB3 mainly accumulates PDIM and TAG inside the macrophages . These results are in agreement with a recent intraphagosomal microarray data demonstrating synchronized induction of WhiB3 with the genes responsible for the production of PAT , DAT , SL-1 and TAG [17] , supporting the role of WhiB3 as a physiological regulator of Mtb lipids in vivo . Since Mtb subsists on fatty acids as a primary carbon source in vivo [32] , it is believed that persistent Mtb not only requires efficient metabolism of fatty acid oxidation intermediates ( e . g . , propionate ) as a energy source , but also their detoxification [21] . The regulatory mechanism controlling Mtb growth and survival in response to accumulation of toxic levels of propionate is not known . The increased resistance of MtbΔwhiB3 towards toxic concentrations of propionate , and the induction of PDIM and TAG production in MtbΔwhiB3 in macrophages , strongly suggests that the WhiB3-mediated regulation of polyketide/lipid anabolism represents a mechanism for the detoxification of accumulated propionate metabolites in vivo . These findings provide new insight into the mechanisms of virulence and long-term persistence in vivo . For example , two recent reports suggested that in vivo persistence of Mtb hinges on methyl-branched polyketide anabolism , which alleviates the potential toxic effect of propionate accumulation during growth on odd chain fatty acids as carbon source [20] , [33] . Our findings suggest that Mtb has evolved an efficient genetic and metabolic circuit operated by WhiB3 to effectively coordinate propionate flux into methyl-branched fatty acids and TAG , which is necessary for growth on fatty acids . The link between lipid anabolism and intrabacterial redox balance was further substantiated by directly measuring the accumulation of significant quantities of NADPH and/or NADH in MtbΔwhiB3 isolated from macrophages ( Fig . 5A–D ) . NADPH is an essential cofactor for lipid anabolism and varying levels of lipid synthesis will influence the NADP+/NADPH poise . Consistent with this , our results suggest that the upregulation of methyl-branched lipids and TAG in wt Mtb results in efficient consumption of NADPH , and is therefore associated with an increased NADP+/NADPH ratio within macrophages . However , since the PAT and SL-1 pathways are absent in MtbΔwhiB3 , attempts to restore physiological levels of NADPH via increased production of PDIM and TAG appears to be partially successful and resulted in amplified levels of NADPH and NADH . Since TAG expression and production [9] is also induced upon exposure to NO , CO ( which inhibits respiration ) and hypoxia via the DosR/S/T dormancy system , our results establish a novel association between TB dormancy signals , NADPH accumulation ( reductive stress ) and TAG production . Nonetheless , we do not exclude other mechanisms that may also modulate reductive stress . For example , NADPH accumulation could be due to alterations in mycothiol disulfide ( MSSM ) reduction by NADPH-dependent mycothiol-reductase , or changes in the expression/activity of pyridine nucleotide transhydrogenase ( SthA ) , which is responsible for generating NADPH . This is currently under investigation . Since it has been suggested that host fatty acid catabolism provides precursors ( e . g . , propionate etc ) for Mtb lipid anabolism [20] , our data also provides new insight into this mechanism by suggesting that essential reductants ( NADH ) are generated by β-oxidation of host lipids , which are required for Mtb lipid anabolism . Consistent with this view , Boshoff et al . , [22] , have demonstrated dramatic accumulation of Mtb NADH and/or NADPH during infection in vivo , thereby providing unambiguous evidence of a role for reductive stress in Mtb pathogenesis . Our findings point to a general , albeit important role for Mtb lipid anabolism as a mechanism for relieving propionate toxicity as proposed earlier [33] as well as dissipating excess reducing equivalents . This mechanism has obvious in vivo relevance since it is widely accepted that Mtb switches from carbohydrates to host fatty acids in the phagosome [32] . An overlooked , albeit well-known physicochemical feature is that long chain host fatty acids ( e . g . , palmitate [C16H32O2] ) have highly reduced oxidation states ( carbon oxidation state = −28 , 106 ATP ) compared to glucose ( carbon oxidation state = 0 , 38 ATP ) and upon β-oxidation cause a substantial cellular redox imbalance favoring the production of NADH , which generates reductive stress . Ironically , the production of ROI is increased through the auto-oxidation of NADH [34] , which amplifies oxidative stress . This apparent counterintuitive concept has significant implications for understanding oxidative stress , which can be prevented by efficient disposal of excess reductants . Bacterial disposal mechanisms of excess reductants include using nitrate as terminal electron acceptor under anaerobic conditions , the reductive fixation of CO2 ( via the reductive TCA cycle ) , and the use of NADH to reduce metabolic intermediates ( fermentation ) . However , none have yet been demonstrated in Mtb . Reductive stress has a clear bearing on bacterial pathogenesis e . g . , under nitrosative stress , S . aureus starts fermenting to dispose of excess NADH [35] , whereas Pseudomonas spp . maintain cellular redox balance by secreting redox active polyketides ( phenazines ) to oxidize accumulating NADH [36] . Since most human pathogens have to subsist on an in vivo nutrient ( e . g . , carbon ) source , and are exposed to NO and/or CO , our findings may serve as a model foundation for understanding how pathogens respond to environments in vivo that generates intrabacterial reductive stress . Although the detailed mechanism remains to be established ( currently in progress ) , we anticipate that the newly discovered link between oxido-reductive stress , lipid anabolism and Mtb persistence described in this study invites new and unexplored avenues of future research . In Fig . 12 we propose a “reductive stress dissipation model” for WhiB3 redox regulation . The Th1 and Th2 cytokine data ( Fig . 6 ) demonstrate that MtbΔwhiB3 enhances both the pro- and anti-inflammatory immune response . Since careful dosing of a Th1 and Th2 response is essential for controlling Mtb infection without causing detrimental immunopathology [37] , the disturbed kinetics and balance between Th1 and Th2 cytokines caused by the loss of whiB3 could in part explain the unique in vivo phenotype exhibited by MtbΔwhiB3 [13] . This is not unprecedented , since live cells or lipids derived from Mtb CDC1551 induced higher levels of Th1 and Th2 cytokines and exhibits an altered immuno-pathology [38] , a phenotype also exhibited by MtbΔwhiB3 [13] . The fact that WhiB3 modulates polyketide production under oxidative and reductive stress and is required for the expression of pks2 , pks3 and fbpA suggest a role for WhiB3 as a redox-dependent transcription factor . To explore the molecular mechanism underlying WhiB3 function , we extensively characterized its DNA binding properties under various redox conditions and resolved a long-standing issue whether the WhiB-like proteins can bind DNA . We provide conclusive evidence that at least one WhiB member binds DNA , and that WhiB3 is the first redox-dependent DNA binding protein identified in Mtb . In the case of metal-based sensors , either the presence ( e . g FNR ) or redox state ( e . g SufR ) of an Fe-S cluster regulates DNA binding [27] , [29] . However , thiol-based sensors exploit a thiol-disulfide redox switch ( e . g . OxyR , CrtJ ) to modulate DNA binding [29] . Interestingly , despite possessing a Fe-S cluster , the RNA binding activity of aconitase is regulated by the redox state of its thiols [39] . On the other hand , to the best of our knowledge , methodical studies examining the effect of the redox state of apo-FNR or apo-SoxR Cys thiols on DNA binding are fragmentary . Our findings demonstrating that the redox state of the 4Fe-4S cluster has virtually no effect on the ability of holo-WhiB3 to bind DNA , whereas post-translational modification of the Cys thiols significantly stimulates WhiB3 DNA binding , are unique . This is reminiscent of OxyR where similar thiol-based post-translational modifications influence DNA binding and transcription activation properties to generate graded transcriptional responses [40] . Although DNA binding does not reflect transcriptional activation , it is tempting to speculate that the WhiB3 thiol modifications also differentially affect transcription . A characteristic that may shed light on the biological function of WhiB3 is the poor discrimination between specific and non-specific DNA binding . A clear DNA binding ( e . g . HTH ) domain is absent in WhiB3 . However , WhiB7 [16] and WhiB3 contain characteristic AT-hook motifs RPRGRPRKDAVA and TMGRTRGIRRTA , respectively , at their C-termini . These motifs are found in several non-specific DNA binding proteins with weak specificity such as the high-mobility group ( HMG ) non-histone nuclear proteins . Similar to histones in chromatin , architectural bacterial proteins such as Lrp , and H-NS bind DNA specifically and non-specifically [41] . However , the non-specific and specific DNA binding of the various redox forms of WhiB3 requires further investigation and is the focus of an independent study . In sum , our data establishes a paradigm for WhiB-like proteins in maintaining redox homeostasis . In particular , our data implicate WhiB3 in sensing reductive stress generated by host lipid catabolism . Importantly , Mtb WhiB3 functions as an intracellular redox sensor by controlling the flux of lipid precursors and reducing equivalents through the biosynthesis of virulence polyketides and storage lipids necessary for achieving redox balance and to modulate host innate immunity .
M . tuberculosis H37Rv , MtbΔwhiB3 , and MtbΔwhiB3 tetRO:whiB3 [19] were grown at 37°C in 7H9 ( broth ) or 7H11 ( agar ) media with 1xADS enrichment ( albumin-dextrose-NaCl ) , 0 . 05% glycerol and 0 . 1% Tween 80 ( broth ) . E . coli cultures were grown in LB medium . Antibiotics were added as described earlier [19] . For propionate toxicity assays , bacteria were grown in 7H9 broth containing 0 . 5% albumin , 0 . 085% NaCl , 0 . 02% tyloxypol and 10 mM or 20 mM sodium propionate as the carbon source . Mtb strains were grown to stationary phase ( 10 days growth ) and cells were analyzed by SEM and TEM as previously described [42] . Metabolic radiolabeling of complex cell wall lipids of Mtb were performed as previously described [31] . In short , Mtb were cultured to OD600 nm = 1 . 5 in 20 ml of 7H9 medium followed by addition of 20 µCi of [1 , 2-14C] sodium acetate ( for labeling mycolic acids ) or [1-14C] sodium propionate ( for labeling methyl branched lipids ) and incubating for 24 h . When necessary , 5 mM diamide or DTT were added to the culture along with the corresponding radiolabeled lipid precursor . Cultures were centrifuged , and washed once in distilled water . Cell wall surface lipids were extracted first with CHCl3/CH3OH ( 1∶2 , v/v ) for 24 h , and then with CHCl3/CH3OH ( 2∶1 , v/v ) , for 48 h . The organic phases were pooled , washed twice with distilled water and dried . Mycolic acid methyl esters ( MAME ) were prepared from [1 , 2-14C] acetic acid labeled Mtb cells by extraction with 20% tetrabutylammonium hydroxide ( Sigma-Aldrich ) at 100°C in an oil bath . This was followed by methylation using methyl iodide , extraction with dichloromethane , and finally drying under nitrogen . The crude lipid extracts were analyzed by TLC on precoated silica plates ( F254; Sigma-Aldrich ) in different solvent systems . Radiolabeled lipids were visualized by autoradiography of the TLC plates using phosphoimaging . The utilization of solvent systems to identify various lipids based on the retention factor ( Rf ) by TLC was performed as described [5] , [43] , [44] . Raw264 . 7 cell lines ( 5×108 ) were infected in quadruplicate using DMEM medium containing 10% FCS at a multiplicity of infection ( MOI ) of 10∶1 with various strains and incubated for 4 h for internalization . Infected macrophages were washed thrice with warm DMEM medium followed by the addition of fresh medium and 50 µCi of sodium propionate and incubation was continued for 2 days . Two days post-infection macrophages were washed and harvested in PBS . Macrophage-derived lipids were removed by suspending infected macrophages in 10 ml methanol , followed by vortexing ( thrice for 10 s each ) , and centrifugation ( 4 , 000 rpm for 10 min ) . This step was repeated twice . This was followed by extraction of mycobacterial lipids with 10 ml of chloroform∶methanol ( 2∶1 ) for 48 h . Lipids were isolated from Mtb inside macrophages as described above and analyzed by FT-ICR MS as described [20] . Lipids were suspended in choloroform∶methanol ( 2∶1 ) , in 0 . 1% formic acid . A monolithic microchip-based electrospray interface , the TriVersa NanoMate ( Advion , Ithaca , NY ) served as the ESI source as previously reported [45] , [46] . The NanoMate was set to load 5 µl of sample which was electrosprayed in negative ion mode by applying −1 . 8 kV spray voltage and 0 . 2 psi nitrogen head pressure to the sample tip to obtain a constant spray for 15–20 min . The capillary temperature , spray voltage , and tube lens voltage were set to 200 C , −36 V , and −100 V , respectively . Mass spectra were acquired by use of a hybrid two dimensional linear quadrupole ion trap Fourier transform ion cyclotron resonance mass spectrometer ( LTQ FT MS , Thermo Fisher Scientific , San Jose , CA ) . The mass spectrometer was operated in the high mass range to obtain negative ion FT-ICR mass spectra ( 1550<m/z<3500 ) at a mass resolving power of 100 , 000 at m/z 400 and a automatic gain control ( AGC ) target value of 2×106 , maximum fill 200 ms . Each displayed spectrum represents a sum of 30–50 scans . For the in vivo estimation of pyridine nucleotides , we infected Raw264 . 7 macrophages with wt Mtb and MtbΔwhiB3 for 2 days . Preparation of Mtb cells and pyridine nucleotide analysis were performed as described [47] except that 5 mM acetate was used in the growth incubation step . A similar approach was recently utilized to study salvage pathway involved in NAD+ and NADH synthesis in Mtb growing in vivo [22] . As an in vitro control , Mtb strains were cultured directly in 7H9 medium containing 5 mM acetate and pyridine nucleotides were estimated . Assaying for NADPH was performed in a similar manner , except that glucose-6-phosphate dehydrogenase and glucose-6-phosphate was utilized as enzyme and substrate , respectively . Raw264 . 7 macrophages were infected with various strains for 2 days as described in the previous section . Bacteria derived from macrophages were grown in 7H9 basal medium containing 5 mM acetate as the sole carbon source for 24 h and 20 µCi of [14C] nicotinamide was added for labeling of NAD+ and NADH ( American Radiolabeled chemicals , Inc ) . Labeled nucleotides were extracted and analyzed by TLC analysis as described [22] . Raw264 . 7 cell lines were infected in triplicate as described in the previous section . Supernatants from the infected macrophages was harvested 24 h post-infection and subjected to cytokine analysis using the Bio-Plex multiplex Human Cytokine Th1/Th2 Assay kit ( Bio-Rad ) and the Cytokine Reagent kit ( Bio-Rad ) in accordance with the manufacturer's protocols . Mtb cells were harvested and RNA was isolated as described [48] . First-strand synthesis was performed by using 500 ng total RNA with iScript Select cDNA Synthesis Kit ( Bio-Rad ) using random oligonucleotides . PCR was performed using gene specific primers . Expression of genes was analyzed with real-time PCR using iQ SYBR Green Supermix ( Bio-Rad ) and a BioRad iCycler 5 with an iQ Multicolor Real-Time PCR Detection System ( Bio-Rad ) . Data analysis was performed with the iQ Multicolor Real-Time PCR Detection System Optical Software System ( Bio-Rad ) , version iQ5 . PCR efficiencies were normalized to obtain accurate expression levels . For comparisons between wt Mtb and MtbΔwhiB3 , the induction ratio for each gene was normalized to Mtb 16s rRNA expression . Mtb WhiB3 was overexpressed in E . coli and purified as described in Protocol S1 . WhiB3 Fe-S cluster assembly was performed under anoxic conditions and monitored by UV-visible spectroscopy as described previously [19] ( see also Protocol S1 ) . Apo-WhiB3 was generated as previously described [30] . Reduced apo-WhiB3 ( WhiB3-SH ) was generated by addition of 5 to 20 mM of DTT for 30 min , followed by size exclusion chromatography inside an anaerobic glove box . Oxidized WhiB3 ( WhiB3-SS ) was generated by removal of DTT from apo-WhiB3 by size exclusion chromatography followed by treating samples with 5 to 20 mM diamide for 30 min . For EMSA assays , promoter fragments ( ∼300 bp upstream of translational start codon ) of pks2 , and pks3 were PCR amplified from the Mtb H37Rv genome and the 5′-end labeled with [γ-32P] ATP ( GE Healthcare ) using T4 polynucleotide kinase ( MBI Fermentas ) according to the manufacturer's instructions . Binding of WhiB3 to pks3 or pks2 promoters were performed inside a PlasLabs anaerobic glovebox . Reactions were performed in buffer containing 89 mM Tris , 89 mM boric acid and 1 mM EDTA , pH 8 . 4 in the presence of 50 µg of salmon sperm DNA . WhiB3 , DNA and buffers were completely degassed using argon gas . Aliquots were incubated for 30 min at room temperature . The reactions were separated inside an anaerobic glovebox using 4–20% gradient TBE PAGE gels ( Bio-Rad ) . Gels were exposed to autoradiographic film and visualized via phosphorimaging ( GE ) . | Currently , approximately one-third of the world's population is latently infected with Mycobacterium tuberculosis ( Mtb ) , the bacterium that causes tuberculosis ( TB ) . A central question in TB research is to identify the mechanisms that allow the organism to persist for long periods of time in humans . The mycobacterial cell wall has a high lipid content and contains several important lipid groups , including poly- and di-acyltrehaloses ( PAT/DAT ) , sulfolipids ( SL-1 ) , and phthiocerol dimycocerosates ( PDIM ) . These lipids are produced and actively secreted during infection to subvert the host immune system , eventually leading to Mtb persistence . We have discovered that the regulatory protein WhiB3 controls the differential production of PAT , DAT , SL-1 , and PDIM and the storage lipid triacylglycerol ( TAG ) in response to fluctuations in the intracellular redox environment . We demonstrated that WhiB3 directly regulates lipid production by binding to the promoter regions of lipid biosynthetic genes in a redox-dependent manner . We also discovered that through this regulatory process , WhiB3 controls fatty acid metabolism and maintains intracellular redox homeostasis by channeling toxic reducing equivalents into lipid anabolism . Thus , our results suggest that Mtb lipid anabolism functions as a reductant sink to neutralize the reductive stress associated with the catabolism of host lipids during infection . These findings may serve as a model foundation for how pathogens adjust their metabolism to cope with stresses encountered during infection . | [
"Abstract",
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"Results",
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"Methods"
] | [
"infectious",
"diseases/bacterial",
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] | 2009 | Mycobacterium tuberculosis WhiB3 Maintains Redox Homeostasis by Regulating Virulence Lipid Anabolism to Modulate Macrophage Response |
Enduring interest in the Apolipoprotein E ( ApoE ) polymorphism is ensured by its evolutionary-driven uniqueness in humans and its prominent role in geriatrics and gerontology . We use large samples of longitudinally followed populations from the Framingham Heart Study ( FHS ) original and offspring cohorts and the Long Life Family Study ( LLFS ) to investigate gender-specific effects of the ApoE4 allele on human survival in a wide range of ages from midlife to extreme old ages , and the sensitivity of these effects to cardiovascular disease ( CVD ) , cancer , and neurodegenerative disorders ( ND ) . The analyses show that women's lifespan is more sensitive to the e4 allele than men's in all these populations . A highly significant adverse effect of the e4 allele is limited to women with moderate lifespan of about 70 to 95 years in two FHS cohorts and the LLFS with relative risk of death RR = 1 . 48 ( p = 3 . 6×10−6 ) in the FHS cohorts . Major human diseases including CVD , ND , and cancer , whose risks can be sensitive to the e4 allele , do not mediate the association of this allele with lifespan in large FHS samples . Non-skin cancer non-additively increases mortality of the FHS women with moderate lifespans increasing the risks of death of the e4 carriers with cancer two-fold compared to the non-e4 carriers , i . e . , RR = 2 . 07 ( p = 5 . 0×10−7 ) . The results suggest a pivotal role of non-sex-specific cancer as a nonlinear modulator of survival in this sample that increases the risk of death of the ApoE4 carriers by 150% ( p = 5 . 3×10−8 ) compared to the non-carriers . This risk explains the 4 . 2 year shorter life expectancy of the e4 carriers compared to the non-carriers in this sample . The analyses suggest the existence of age- and gender-sensitive systemic mechanisms linking the e4 allele to lifespan which can non-additively interfere with cancer-related mechanisms .
The Apolipoprotein E ( ApoE ) common polymorphism ( e2 , e3 , and e4 ) is one of the most studied genetic variants in humans . The interest in this polymorphism is two-fold . First , the functional diversity of the ApoE polymorphism appears to be a unique signature of humans with no coding variation in this gene even in human's closest ancestries in which the monomorphic ApoE sequence resembled human's e4 allele [1] , [2] . Understanding the functional diversity of the ApoE gene , thus , can help in gaining insights on human evolution . Second , the ApoE polymorphism is of fundamental interest for geriatrics and gerontology because of its profound role in human diseases in late ( post-reproductive ) life and lifespan . Most consistent associations were reported for the detrimental effect of the e4 allele on Alzheimer disease [3]–[5] . Studies also mostly documented a detrimental role of the e4 allele in cardiovascular health [6] , [7] although a protective role of this allele was also reported [6] , [8] . The e4 allele was associated with human lifespan and longevity in a number of studies [9]–[19]; some studies reported , however , no significant effect [20]–[22] ( see also http://genomics . senescence . info/longevity ) . Studies of the role of the e4 allele in human longevity were mostly limited to comparing frequencies of genotypes in long-living individuals and younger controls [23] , a strategy which has limitations [24] . Studies examining survival of older individuals carrying the e4 allele are rare ( notably , [17] , [18] ) . Sexual dimorphism of the ApoE gene in human survival has not been widely studied so far ( see [17] and references therein ) . Since the e4 allele may be involved in regulation of such common diseases in the elderly as dementia and cardiovascular diseases ( CVD ) , it is often assumed that the detrimental effect of the e4 allele on human longevity is mediated by these diseases ( e . g . , [11] , [14] , [25] ) . Studies of the systemic effect of the e4 allele and major human diseases on lifespan in the same samples are rare [16] , [17] primarily because they require large samples of genotyped individuals followed for a long period of time to have sufficient number of events . Despite the detrimental role of the e4 allele in human health and longevity , this allele continues to be widespread in human population [26] . The persistence of this allele has been proposed to be a result of balancing selection implying that the e4 allele should be also evolutionarily advantageous with a beneficial role in early life [27]–[30] . In this work we examine three inter-related problems which , taken together , address the systemic role of the e4 allele in human lifespan . First , we investigate gender-specific effects of the ApoE4 allele on survival in a wide range of ages starting from midlife to extreme old ages . Second , we examine whether major human diseases such as CVD , cancer , and neurodegenerative disorders ( ND ) can explain ( i . e . , mediate ) the effect of the e4 allele on survival . Third , we investigate whether these diseases can modulate the e4-specific survival non-additively . This wide range of systemic analyses is possible given the large sample with directly genotyped ApoE polymorphism available for the analyses and selected from the Framingham Heart Study ( N = 5182 ) and the Long Life Family Study ( N = 4659 ) followed longitudinally for up to 60 years with a total of 2557 deaths .
Our empirical analysis showed no consistent detrimental effect of the e4 allele across ages on the survival of men either in the FHS or FHSO cohorts ( Figures 1A and 1C ) . Contrary to men , the e4 female carriers have shorter lives than the non-carriers ( Figures 1B and 1D ) . An important result is that the role of the e4 allele in survival can change with age . Specifically , there is no e4-specific difference in survival of either the FHS men or women at ages 95 years and older ( Figures 1A and 1B ) . The e4 allele does not affect survival at ages 70 years and younger ( Figure 1D ) either . Analysis of survival age patterns of the LLFS male and female offspring/spouses directly supports these observations . Specifically , the LLFS female offspring and spouses carrying the e4 allele show worse survival than those who do not carry this allele ( Figure 2D ) . Survival of the LLFS male offspring and spouses is not sensitive to this allele ( Figure 2C ) . To better understand survival age patterns of the LLFS participants from the parental generation ( Figures 2A–B ) , one should keep in mind that this is a population selected for its exceptional chances to live a long life based on family history and their own survival to old ages ( see Methods ) . Accordingly , this population resembles the subpopulation of individuals who survive to the very old ages in the FHS original cohort rather than the entire sample of a normal population in this cohort . Then , an important result is that the LLFS women selected for their chances of exceptional longevity ( Figure 2B ) and the long-living women in the FHS original cohort ( represented in Figure 1B by a tail of the survival age pattern ) have the same lifespan regardless of whether they carry the e4 allele . When analyzing survival age patterns one should also consider the possibility of survival selection in aging cohorts; if this selection is sensitive to a specific genetic variant then we may have biased empirical age patterns for carriers of genotypes from this variant particularly at advanced ages . Then , although the lifespans of the long-living LLFS men may be sensitive to the e4 allele ( Figure 2A ) , further analyses are necessary ( see next subsection ) to determine whether this effect is real . Thus , Figures 1B and 2B document an important result that survival of long-living women participating in the FHS ( see upper tail in Figure 1B ) and LLFS is insensitive to the e4 allele . Figures 1D and 2D show another remarkable result that the effect of the e4 allele on survival in the FHSO and LLFS offspring/spouses is pronounced: ( i ) starting at the same age , 70 years and ( ii ) in women only . We evaluated the sensitivity of the survival of the long-living LLFS men to the e4 allele seen in Figure 2A . Evaluation of the relative risk ( RR ) of death for the e4 allele carriers using a model without adjustment for birth cohorts supported the presence of the effect ( RR = 1 . 52 , p = 6 . 9×10−3 ) in this sample ( Table 2 ) . However , adjustment for birth cohorts entirely explained this association ( RR = 1 . 17 , p = 0 . 319; Table 2 ) , suggesting that this sensitivity was likely due to differential survival of the e4 carriers and non-carriers in different birth cohorts in the LLFS . The relative risks obtained from the data in Figures 1 and 2 revealed the presence of a significant detrimental effect of the e4 allele on survival in women in the FHS ( RR = 1 . 25 , p = 0 . 027 ) , FHSO ( RR = 1 . 59 , p = 2 . 4×10−4 ) , and LLFS offspring/spouse ( LLFS_O+S; RR = 2 . 23 , p = 5 . 2×10−3 ) samples ( Table 2 , all ) . No significant effect was seen in men in either sample or in long-living women in the LLFS ( Table 2 , all ) . Pooled data from the FHS and FHSO slightly improved the significance of the estimates for women , RR = 1 . 36 , p = 1 . 3×10−4 ( Table 2 , FHS+FHSO , all ) . However , given the empirical evidence on the substantial role of age-related heterogeneity ( Figures 1 and 2 ) , analyses of the relative risks using the Cox proportional hazards regression model , which disregards such heterogeneity , likely underestimate the effects . A more appropriate way to address the impact of age-related heterogeneity is to consider more homogeneous groups of individuals for whom the variation of the hazards is proportional over age . Empirical evidence from independent FHS and LLFS cohorts ( Figures 1 and 2 ) suggests selecting more homogeneous groups of individuals who died or were censored at ages: ( i ) younger than 95 years in the FHS ( note that there were virtually no genotyped individuals with lifespans less than 70 years in this sample ) , ( ii ) 70 years and older in the FHSO and LLFS_O+S ( note , virtually all genotyped participants in these samples had lifespans less than 95 years ) , and ( iii ) 70 to 95 years in the pooled sample of the FHS and FHSO . Table 2 shows that individuals from these more homogeneous groups in each sample are at substantially larger risk of death compared to the entire sample . For example , we observe 9% increment ( from RR = 1 . 36 to RR = 1 . 48 ) in the risk of death in the more homogeneous 70–95 year group of the FHS and FHSO women . Correspondingly , the significance of the estimate also sharply increases from p = 1 . 3×10−4 to 3 . 6×10−6 . Importantly , the analyses also confirm the lack of a significant effect of the e4 allele on survival in the groups of individuals who did not belong to the selected more homogeneous groups ( Table 2 ) . Specifically , no significant effects were observed in: ( a ) the groups of individuals with lifespans less than 70 years in the FHSO and LLFS_O+S , ( b ) individuals with exceptional survival including the entire sample of the LLFS long-living men and women ( LLFS_P ) , and ( c ) individuals who were aged 95 years and older in the FHS . The lack of significant effects cannot be explained by the sample size differences ( Table 2 ) . To address this question , we focused on the more homogeneous groups of participants of the FHS original and FHSO cohorts defined in the previous subsection ( the LLFS sample is underpowered for such analyses ) in order to diminish bias attributable to disproportionality of hazards when using the Cox regression model . Given slightly smaller samples of the FHS participants with known ND status ( Table 1 ) , these analyses were limited to individuals with missing information on ND excluded ( sample sizes are provided in the respective tables along with the effect estimates ) . Additive adjustments of the Cox regression models estimating the risk of death for carriers and non-carriers of the e4 allele by ( i ) CVD , ( ii ) CVD and cancer , and ( iii ) CVD , cancer , and ND , reveal that CVD and cancer do not explain the observed associations . Contrarily , CVD and cancer tend to improve the estimates in each sample with a more pronounced role for cancer ( Figure 3 ) . ND plays at most minor mediating role in the associations of the e4 allele with survival of either men ( Figure 3A ) or women ( Figure 3B ) . Thus , none of these diseases explain the association of the e4 allele with risks of death ( see Supplementary Information , Table S1 ) . Given no qualitative difference in the additive role of CVD , cancer , and ND in the e4-specific risks of death across the FHS samples , we evaluated the risks in the largest more homogeneous pooled sample of the FHS and FHSO participants in disease-stratified analyses ( see Methods ) . Figure 4 and Table 3 show that the risks of death for women are the same regardless of CVD or ND status , i . e . , neither CVD nor ND increase mortality of the e4 female carriers nonlinearly even after adjustment for alternative diseases . These diseases do not non-additively modulate men's survival either . A striking result was that non-skin cancer significantly ( p = 0 . 029 for multiplicative interaction of cancer with ApoE ) differentiated the e4-specific risks of death for women from the more homogeneous group ( with moderate lifespans of 70 to 95 years ) increasing them by 52% from RR = 1 . 36 ( p = 3 . 8×10−3 ) for women who did not have cancer to RR = 2 . 07 ( p = 5 . 0×10−7 ) for women who had cancer ( Figure 4B and Table 3 ) . The high risk of death for women with moderate lifespan who had cancer explained the 3 . 2-year shorter life expectancy for the e4-allele carriers compared to the non-carriers ( Table 4 ) . The same trend on the e4-specific excess in the risks of death was seen for male cancer patients compared to non-patients ( Figure 4A ) . Cancer increases risks for the e4 allele carriers compared to the non-carriers making them marginally significant , RR = 1 . 31 ( p = 0 . 080 ) ( Table 3 ) . The available sample size allowed us to gain some insights on potential differences between cancer sites ( other than skin ) in these associations . In these analyses we excluded major sex-specific sites , i . e . , prostate in men and breast in women . Figure 5 and Table 3 show that relative risks of death for men without non-sex-specific cancers ( RR = 1 . 11 ) increases compared to men without cancers ( RR = 1 . 03 ) but it declines for men having non-sex-specific cancers ( RR = 1 . 17 ) compared to men having cancers ( RR = 1 . 31 ) . This pattern suggests that the potential modulating effect of cancer in men is likely not sensitive to cancer site . Contrary to men , Figure 5 and Table 3 show that modulating role of cancer in women is entirely attributed to non-sex-specific cancers . The relative risk of death for women with moderate lifespan who had non-sex-specific cancers became much more pronounced ( RR = 2 . 51 , p = 5 . 3×10−8 ) . This high risk explained the 4 . 2-year difference in life expectancy for the e4-allele carriers and non-carriers in this group ( Table 4 ) .
Analysis of genotyped offspring in the FHS revealed that the e4 allele is irrelevant to survival in mid to early-old life , up to about 70 years ( Table 2 ) . This result appeared to be corroborated in an independent population of the LLFS offspring and spouses ( Table 2 ) . The e4 allele changed its role from neutral in mid to early-old life to detrimental at older ages . This change was found in independent samples of the FHS Offspring cohort ( Figure 1D ) and the LLFS offspring and spouses ( Figure 2D ) . Moreover , this change occurred concordantly in the FHSO and LLFS: ( i ) at about the same age of 70 years and ( ii ) in women only . The detrimental effect of the e4 allele at old ages ( until 95 years of age ) was also found in a sample of the FHS women ( Figure 1B; note that virtually no individuals with lifespan less than 70 years were genotyped in this cohort ) . At extreme ages ( 95 years and older ) we concordantly observed a neutral role of the e4 allele in each gender in the FHS ( Figures 1A and 1B ) . Analysis of the long-living individuals in the LLFS corroborated these findings ( see the “Empirical Age Patterns of Survival of the FHS and LLFS Men and Women” and “Risks of Death of the FHS and LLFS Men and Women” subsections ) . Overall , these analyses demonstrated a strong detrimental effect of the e4 allele on survival which was mostly attributed to women with moderate lifespans of 70 to 95 years in the FHS , FHSO , and LLFS . For example , the e4 allele increased the risks of death of the FHS and FHSO women by about 48% ( RR = 1 . 48 ) with very high confidence , p = 3 . 6×10−6 ( Table 2 ) . Although our study provided robust evidence of a women-specific detrimental effect of the e4 allele on lifespan in three different samples of mostly North-American population ( i . e . , FHS , FHSO , and LLFS , see Methods ) , there is also robust evidence of a detrimental effect of this allele in Swedish men but not women [17] . Further , although our results on the neutral role of the e4 allele at extreme ages ( 95 years and older ) are in agreement with some meta-analyses [e . g . , 32] , there is also evidence of a significant detrimental effect of the e4 allele at those ages in the Danish population [18] . The results by Rosvall et al . [17] , Jacobsen et al . [18] , and ours explicitly show that the effect of the e4 allele on lifespan may not be the same in different populations . These robust evidences from different populations illustrate that the concept of replication of the same effect of the same allele on the same complex phenotype characteristic for post-reproductive period has inherent limitations [33]–[36] . The e4 allele is a major susceptibility allele for Alzheimer disease ( which is a subtype of the ND in this study ) particularly in Caucasians [4] ( but may be not in Hispanics [37] ) . Despite that , our well-powered analyses show that ND explains at most a tiny part in the association of the e4 allele with survival ( Figure 3 ) . The results of our analyses do not support the hypothesis that the lack of a mediating effect of ND can be due to potential ND misclassification . This is evidenced in Figure 3 by: ( i ) the tiny reduction of the effect size attributed to ND ( Figure 3 ) despite the large prevalence of ND ( particularly in the FHS as the older cohort , Table 1 ) , and ( ii ) the role of cancer as a nonlinear modulator of the effect of the e4 allele on survival ( Figure 4 ) . Additive contributions of the e4 allele and dementia to survival was also observed in other studies [16] although the attenuation of the effect size by dementia varied [17] . Despite the associations of the e4 allele with CVD [6] , [7] and with CVD-free life [19] , [38] , our analyses show that CVD does not explain the effect of the e4 allele on women's survival ( Figure 3 ) . Recent analyses support these results by showing independent associations of the e4 allele and various characteristics of cardiovascular health and CVD with survival [16] , [17] , [39] . Several studies reported on a role of the ApoE gene in cancer [40]–[43] . It has been also shown that the e4 allele can increase cancer-free lifespan in the FHS and FHSO men [19] , [38] . The analyses in this study show no mediating role of cancer in the association of the e4 allele with women's survival; the additive contribution of cancer , however , can modulate the effect of the e4 allele , increasing the strength of this association ( Figure 3 ) . CVD and cancer are the most common causes of death in humans and ND is fast growing cause of death in the elderly . CVD and ND are the diseases which have been most consistently associated with ApoE4 . Despite that , these diseases do not explain the detrimental role of the e4 allele in lifespan . This finding implies the existence of a mechanism linking the e4 allele with lifespan which is largely independent of the mechanisms affecting susceptibility to CVD , cancer , and ND . Given also that the e4 allele may not be associated with frailty [14] , [44] , it is likely that this allele can be directly involved in regulation of human aging through intrinsic biological mechanisms . One potential mechanism could be associated with inflammation which may be involved in aging through two main pathways associated with “immunosenescence and synergies with chronic diseases that have inflammatory components” [29] . Given no mediating role of CVD , cancer , and ND observed in our study and that these diseases ( particularly CVD and ND ) can have e4-specific inflammatory etiology [8] , [45] , it might well be the case that the e4 allele affects survival through immunosenescence whereas it affects the risks of diseases through disease-specific inflammatory component . Neither CVD nor ND non-additively ( i . e . , nonlinearly ) modulates the detrimental effect of the e4 allele on women's survival , i . e . , the relative risks of death for the e4 allele carriers are the same regardless of women's CVD and ND statuses ( Figure 4B ) . This result is in line with findings by Little et al . [16] . However , the e4 allele was shown to be mostly associated with dementia-caused deaths by Newman et al . [39] . We found that cancer showed a significant nonlinear modulating effect in the association of the e4 allele with women's survival ( Figure 4B ) . The e4-positive female cancer patients have about a two-fold increased risk of death at ages between 70 and 95 years compared to the non-e4 allele carriers ( RR = 2 . 07 ) which is highly significant , p = 5 . 0×10−7 ( Table 3 ) . Such a strong effect results in a 3 . 2-year shorter life expectancy of the e4 carriers compared to the non-carriers in this sample ( Table 4 ) . Further analyses show that this effect is attributed to non-sex-specific cancer sites , it substantially increases , i . e . , RR = 2 . 51 , p = 5 . 3×10−8 ( Table 3 ) , and it explains the large 4 . 2 year differential in the life expectancy ( Table 4 ) . Women without cancer carrying the e4 allele are still at significant risk of death . The same non-additive role of cancer was found in the effect of the e4 allele on men's survival , i . e . , this allele negatively affected cancer survivorship ( Figure 4A ) . The diminished role of cancer as a nonlinear modulator of the effect of the e4 allele on survival in men compared to women can be attributed to a protective role of this allele in susceptibility to risk of cancer in men but not in women [19] , [38] , i . e . , protection against risks of cancer may well explain modest risks of cancer survivorship of male e4 carriers . The cancer-sensitive non-additive effect of the e4 allele on human lifespan suggests that mechanisms associated with cancer survivorship ( i . e . , with its progression and/or treatment ) can interfere with a mechanism linking the e4 allele to lifespan . Our findings are particularly in line with inflammatory pathways [29] , [43] which may overlap for aging and cancer survivorship as a result of the compromising of the immune system with age [46] ( see also next subsection ) . Thus , the non-additive role of cancer in the effect of the e4 allele on lifespan and the lack of this role for CVD and ND likely underscores the synergism between cancer and aging . Given the persistence of the e4 allele in humans , it may be beneficial in early life and , thus , be subject to balancing selection [27]–[30] . Indeed , several studies provided support for a beneficial role of the e4 allele in early life . For example , it was shown that the proportion of the e4 allele was significantly smaller in spontaneously aborted embryos than in adults [47] . The proportion of the e4 allele was also found to be significantly larger in healthy liveborn infants compared with stillborn infants and with adults [48] . These findings suggest that the e4 allele can benefit early survival . Then , given the detrimental role of this allele for survival in old ages , we should expect a neutral role at some point in between . Our finding of a neutral role of the e4 allele in survival in mid to early-old life of the genotyped FHS and LLFS participants supports this logic . Studies also show that ApoE4 may protect against early life infectious diseases such as , e . g . , diarrhea [49] and liver damage caused by the hepatitis C virus infection [50] , [51] . A putative protective mechanism may be associated with an enhanced function of the immune system in early life [25] with a role of ApoE as an immunomodulator [52] . At old ages immunosenescence may be a factor favoring neoplasia [53] . Then , if ApoE4 boosts the immune system in early life , this may naturally lead to prematurely exhausting this system later in life which may affect cancer survivorship for carriers of this allele ( and , thus , implying antagonistic pleiotropy ) . This hypothesis is supported by our findings of a strong non-additive modulating role of cancer in survival of female e4 allele carriers ( Figure 5 ) , by the very high proportion of deaths ( 80% ) among female e4 carriers with non-sex-specific cancer by age 95 years ( 44 deaths among 55 carriers; Table 4 ) , and by the 150% excess risk of death for such women compared to the non-e4 carriers ( RR = 2 . 51 , p = 5 . 3×10−8; Table 3 ) . These high death rates can , in part , explain the diminishing detrimental effect of ApoE4 at very advanced ages ( 95+ years ) in the FHS . The lack of an association of ApoE4 with survival at extreme ages ( 95+ ) in the FHS and in an exceptional population of the LLFS long-living participants suggests that the detrimental effect of ApoE4 can be counterbalanced in some individuals . Potential factors can include buffering mechanisms ( by other genes [54] ) and/or environmental modulations of genetic effects [36] . Given large samples of long-living individuals in the LLFS , this study could be highly promising for revealing such mechanisms . Analyses of the association of the ApoE4 allele with lifespan in three populations of the FHS , FHSO , and LLFS participants showed that women's lifespan was more sensitive to the e4 allele than men's . The adverse role of the e4 allele was limited to women with moderate lifespans of about 70 to 95 years; no survival disadvantage is seen for women with lifespans less than 70 or more than 95 years . The highly significant association of the e4 allele with lifespan was not explained by major diseases including CVD , ND , and cancer , whose risks can be sensitive to this allele , in large FHS samples . Non-skin cancer non-additively increased mortality of the FHS women with moderate lifespans increasing the risks of death of the e4 carriers two-fold compared to the non-carriers . High and highly significant risks of death of the e4-allele carriers in this sample explained their 3 . 2 year shorter life expectancy . The results suggest a pivotal role of non-sex-specific cancer as a nonlinear modulator of survival in this sample of women that increased the risk of death of the ApoE4 carriers by 150% ( p = 5 . 3×10−8 ) compared to the non-carriers and explained the 4 . 2 year differential in life expectancy in this group . Our results suggest the existence of age- and gender-sensitive systemic mechanisms linking the e4 allele to lifespan which can non-additively interfere with cancer-related mechanisms .
We use data on longitudinally followed FHS/FHSO and LLFS participants to characterize the role of the ApoE4 allele ( e2/4 , e3/4 , and e4/4 ) and non-e4 genotypes ( e2/2 , e2/3 , and e3/3 ) in the lifespans of men and women separately . Associations of the e4 allele with risks of death were characterized by the Kaplan-Meier estimator and the Cox proportional hazards regression model . The time variable in the analyses was age at death or age at the end of follow up . The model adjustments were explicitly stated when applicable . To examine whether or not major human diseases can shape the association of the e4 allele with survival , we considered additive and nonlinear roles of CVD ( diseases of hearth and stroke combined ) , cancer , and ND ( dementia and Alzheimer disease combined ) in this association . We considered all non-skin cancers unless explicitly stated . CVD and ND were chosen because they were most consistently associated with the ApoE polymorphism [3] , [6] , [7] , [64] . Recent studies also showed that the ApoE polymorphism can be associated with cancer [e . g . , 41] . These analyses were conducted using rigorously ascertained information on diseases in the FHS/FHSO only because the LLFS data are currently underpowered for such analyses . To address nonlinear effect of diseases on the association of the e4 allele with survival , we conducted disease-stratified analyses . Each disease group included individuals who were diagnosed with the disease ( or died from it ) prior to death or the end of follow up in 2008 . Otherwise , individuals were included in the complementary non-disease group [65] . We used the robust sandwich estimator of variances in the Cox model to account for potential clustering ( e . g . , familial ) . Statistical analyses were conducted using SAS ( release 9 . 3 , Cary , NC , USA ) . This study used de-identified data from the FHS and LLFS . The FHS data are available from the NHLBI through dbGaP . No new data were collected in this work . As such , this study does not require either ethics committee approval or written consent . | Discovering genetic origins of healthspan and lifespan could lead to breakthroughs in increasing the years of healthy and long life . In this paper we characterize the association of the e4 allele of the well-studied ApoE gene with lifespan in two generations of participants of large longitudinal studies , the Framingham Heart Study and the Long Life Family Study , and investigate the role of major human diseases such as cardiovascular disease , cancer , and neurodegenerative disorders in this association . This wide range of systemic analyses is possible given the large sample with directly genotyped ApoE polymorphism available from these studies ( N = 9841 , with 2557 deaths ) . The analyses show that women's lifespan is more sensitive to the e4 allele than men's in these populations . However , the strongly adverse effect of the e4 allele is not observed for all women , but only for those 70 to 95 years old . Cardiovascular disease , cancer , and neurodegenerative disorders do not mediate the association of the e4 allele with lifespan . However , cancer , but not cardiovascular and neurodegenerative diseases , non-additively enhances this effect resulting in 4 . 2 years of difference in mean lifespan for the e4 allele carriers compared to the non-carriers . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [
"genetics",
"of",
"disease",
"genetics",
"biology"
] | 2014 | Age, Gender, and Cancer but Not Neurodegenerative and Cardiovascular Diseases Strongly Modulate Systemic Effect of the Apolipoprotein E4 Allele on Lifespan |
The yeast Saccharomyces cerevisiae is able to accumulate ≥17% ethanol ( v/v ) by fermentation in the absence of cell proliferation . The genetic basis of this unique capacity is unknown . Up to now , all research has focused on tolerance of yeast cell proliferation to high ethanol levels . Comparison of maximal ethanol accumulation capacity and ethanol tolerance of cell proliferation in 68 yeast strains showed a poor correlation , but higher ethanol tolerance of cell proliferation clearly increased the likelihood of superior maximal ethanol accumulation capacity . We have applied pooled-segregant whole-genome sequence analysis to identify the polygenic basis of these two complex traits using segregants from a cross of a haploid derivative of the sake strain CBS1585 and the lab strain BY . From a total of 301 segregants , 22 superior segregants accumulating ≥17% ethanol in small-scale fermentations and 32 superior segregants growing in the presence of 18% ethanol , were separately pooled and sequenced . Plotting SNP variant frequency against chromosomal position revealed eleven and eight Quantitative Trait Loci ( QTLs ) for the two traits , respectively , and showed that the genetic basis of the two traits is partially different . Fine-mapping and Reciprocal Hemizygosity Analysis identified ADE1 , URA3 , and KIN3 , encoding a protein kinase involved in DNA damage repair , as specific causative genes for maximal ethanol accumulation capacity . These genes , as well as the previously identified MKT1 gene , were not linked in this genetic background to tolerance of cell proliferation to high ethanol levels . The superior KIN3 allele contained two SNPs , which are absent in all yeast strains sequenced up to now . This work provides the first insight in the genetic basis of maximal ethanol accumulation capacity in yeast and reveals for the first time the importance of DNA damage repair in yeast ethanol tolerance .
The capacity to produce high levels of ethanol is a very rare characteristic in nature . It is most prominent in the yeast Saccharomyces cerevisiae , which is able to accumulate in the absence of cell proliferation , ethanol concentrations in the medium of more than 17% , a level that kills virtually all competing microorganisms . As a result this property allows this yeast to outcompete all other microorganisms in environments rich enough in sugar to sustain the production of such high ethanol levels [1] , [2] . Very few other microorganisms , e . g . the yeast Dekkera bruxellensis , have independently evolved a similar but less pronounced ethanol tolerance compared to S . cerevisiae [3] . The capacity to accumulate high ethanol levels lies at the basis of the production of nearly all alcoholic beverages as well as bioethanol in industrial fermentations by the yeast S . cerevisiae . Originally , all alcoholic beverages were produced with spontaneous fermentations in which S . cerevisiae gradually increases in abundance , in parallel with the increase in the ethanol level , to finally dominate the fermentation at the end . The genetic basis of yeast ethanol tolerance has attracted much attention but until recently nearly all research was performed with laboratory yeast strains , which display much lower ethanol tolerance than the natural and industrial yeast strains . This research has pointed to properties like membrane lipid composition , chaperone protein expression and trehalose content , as major requirements for ethanol tolerance of laboratory strains [2] , 4 but the role played by these factors in other genetic backgrounds and in establishing tolerance to very high ethanol levels has remained unknown . We have recently performed polygenic analysis of the high ethanol tolerance of a Brazilian bioethanol production strain VR1 . This revealed the involvement of several genes previously never connected to ethanol tolerance and did not identify genes affecting properties classically considered to be required for ethanol tolerance in lab strains [5] . A second shortcoming of most previous studies is the assessment of ethanol tolerance solely by measuring growth on nutrient plates in the presence of increasing ethanol levels [2] , [4] . This is a convenient assay , which allows hundreds of strains or segregants to be phenotyped simultaneously with little work and manpower . However , the real physiological and ecological relevance of ethanol tolerance in S . cerevisiae is its capacity to accumulate by fermentation high ethanol levels in the absence of cell proliferation . This generally happens in an environment with a large excess of sugar compared to other essential nutrients . As a result , a large part of the ethanol in a typical , natural or industrial , yeast fermentation is produced with stationary phase cells in the absence of any cell proliferation . The ethanol tolerance of the yeast under such conditions determines its maximal ethanol accumulation capacity , a specific property of high ecological and industrial importance . In industrial fermentations , a higher maximal ethanol accumulation capacity allows a better attenuation of the residual sugar and therefore results in a higher yield . A higher final ethanol titer reduces the distillation costs and also lowers the liquid volumes in the factory , which has multiple beneficial effects on costs of heating , cooling , pumping and transport of liquid residue . It also lowers microbial contamination and the higher ethanol tolerance of the yeast generally also enhances the rate of fermentation especially in the later stages of the fermentation process . Maximal ethanol accumulation capacity can only be determined in individual yeast fermentations , which are much more laborious to perform than growth tests on plates . In static industrial fermentations , maintenance of the yeast in suspension is due to the strong CO2 bubbling and this can only be mimicked in lab scale with a sufficient amount of cells in a sufficiently large volume . The advent of high-throughput methods for genome sequencing has created a breakthrough also in the field of quantitative or complex trait analysis in yeast [6] , [7] . The new methodology has allowed efficient QTL mapping of several complex traits [5] , [8] , [9] and reciprocal hemizygosity analysis [10] has facilitated identification of the causative genes . The efficiency of the new methodologies calls for new challenges to be addressed , such as comparison of the genetic basis of related complex properties . In addition , complex trait analysis in yeast has been applied up to now mainly to phenotypic properties that are easy to score in hundreds or even thousands of segregants [5] , [8]–[16] . However , many phenotypic traits with high ecological or industrial relevance require more elaborate experimental protocols for assessment and it is not fully clear yet whether the low numbers of segregants that can be scored in these cases are adequate for genetic mapping with pooled-segregant whole-genome sequence analysis . The aim of this work was to compare the genetic basis of the complex traits of maximal ethanol accumulation capacity and tolerance of cell proliferation to high ethanol levels . We show that both traits have a partially different genetic basis and we have identified for the first time specific genes involved in maximal ethanol accumulation capacity .
We have evaluated 68 different yeast strains in small-scale fermentations for maximal ethanol accumulation capacity under very high gravity ( VHG ) conditions [17] , using 33% ( w/v ) glucose . The robust wine strain V1116 was used as reference in each series of fermentation experiments . Figure 1A shows the number of strains able to accumulate a certain maximal ethanol level expressed as percentage of the ethanol level accumulated by V1116 in the same experiment , which was 18 . 4±0 . 4% ( v/v ) . There was no correlation between the final glycerol and ethanol levels produced but there was an inverse correlation between the final glycerol level and the ethanol yield . Table 1 shows the fermentation results for a number of representative strains ranked according to the maximal ethanol level produced in comparison with the reference V1116 . The fermentation of the reference strain , V1116 , took 9 . 4±1 . 1 days to complete . The ethanol productivity was 0 . 65 g . L−1 . h−1 ( or 0 . 83 g . L−1 . h−1 when we omit the last two days where the fermentation had slowed down very much ) . The productivity was highest during the first three days ( 1 . 17 g . L−1 . h−1 ) . The yield was 0 . 446 g ethanol/g glucose ( 87 . 4% ) . There was 2 . 20±0 . 57% ( w/v ) glucose leftover . Glycerol production was 10 . 34±0 . 47 g/L . The final pH was 4 . 5±0 . 2 for all strains evaluated . The best ethanol producer was the sake strain , CBS1585 , that accumulated 103 . 4% of the amount of ethanol accumulated by V1116 . The relative ethanol production ( % compared to V1116 ) , the final ethanol % ( v/v ) , the glycerol yield ( g/L ) and ethanol yield ( % of maximum theoretical yield ) for all 68 strains are listed in Table S1 . The laboratory strains BY4741 ( Mata his3Δ1 leu2Δ0 ura3Δ0 met15Δ0 ) and S288c ( prototrophic ) produced only 64% and 80% , respectively , of the ethanol level accumulated by V1116 . This is in accordance with previous studies that showed the prototrophic laboratory strain ( S288c ) to be generally more stress tolerant than its auxotrophic counterpart ( BY4741 ) [18] , although this has not yet been documented for ethanol tolerance . The eight beer strains tested all produced less than 80% of the ethanol produced by V1116 , in agreement with the relatively low ethanol levels generally present in beers . On the other hand , strains used for the production of bioethanol and sake were among the best for maximal ethanol accumulation , which fits with the high level of ethanol produced in these industrial fermentations [19] , [20] . Cell viability at the end of the fermentation was lower than 10% , and usually only 1–5% , for all strains tested , except for Ethanol Red and CBS1585 . The bioethanol production strain Ethanol Red retained 22 . 1%±4 . 1% viable cells and the sake strain , CBS1585 , even 31 . 5%±5 . 1% . The latter strain also showed the highest ethanol accumulation among all strains evaluated . High ethanol production is a well-known trait of sake strains [21] . The high residual viability is remarkable in view of the 18–19% of ethanol accumulated . The ethanol level could be enhanced further by applying continuous stirring ( 200 rpm ) and raising the glucose concentration to 35% . In this case , ethanol levels between 20 and 20 . 5% ( v/v ) were routinely obtained , with an absolute maximum of 20 . 9% ( v/v ) . In six consecutive fermentations with the same cells under these conditions , 20 . 5% ethanol was accumulated in the first fermentation and 16 . 5–19 . 5% ethanol ( v/v ) in the subsequent fermentations , demonstrating the persistent viability of strain CBS1585 under high ethanol conditions . We have compared the maximal ethanol accumulation capacity with the ethanol tolerance of cell proliferation in the 68 strains . The results are summarized in Figure 1B and all original data are provided in Table S1 . The results show that most strains with a low ethanol tolerance of cell proliferation also displayed poor maximal ethanol accumulation and that none of these strains reached a final ethanol titer of more than 18% ( v/v ) . Strains with a higher ethanol tolerance of cell proliferation tended to produce higher maximal ethanol levels . This was most pronounced in the strains able to grow in the presence of 20% ethanol on plates . All of these strains showed high maximal ethanol accumulation and 50% produced a final ethanol level higher than 18% ( v/v ) . On the other hand , the general correlation between the two traits showed only weak significance ( Spearman one-tailed test: 90% confidence interval , P-value = 0 . 0984 ) . This suggested that the genetic basis of the two traits was at least partially different . The diploid sake strain CBS1585 was sporulated and stable mating type a and α segregants were obtained indicating heterothallism of the parent strain . Ten segregants were phenotyped in small-scale VHG semi-static fermentations . A segregant , Seg5 ( MATa ) , was identified , which showed the same fermentation profile ( Figure 2A ) and maximal ethanol accumulation capacity as its parent strain , CBS1585 ( Figure 2B ) . The laboratory strain BY710 ( derived from BY4742; same genotype: Matα his3Δ1 leu2Δ0 ura3Δ0 lys2Δ0 ) showed a lower fermentation rate and also a much lower maximal ethanol accumulation capacity , which was only around 12% ( v/v ) ( Figure 2A and 2B ) . The a mating type of the Seg5 strain was stable and FACS analysis confirmed that its DNA content was half that of its diploid parent CBS1585 ( data not shown ) . We have crossed Seg5 with BY710 to obtain the diploid Seg5/BY710 , which showed a similar high fermentation rate ( Figure 2A ) and high ethanol accumulation capacity ( Figure 2B ) as the original CBS1585 diploid strain . Growth assays on solid media , with or without glucose , and containing different levels of ethanol , showed that CBS1585 , Seg5 and Seg5/BY710 had a similar ethanol tolerance of cell proliferation whereas the laboratory strain ( BY710 ) was much more sensitive ( Figure 2C ) . These results indicate that the two ethanol tolerance traits are dominant characteristics in the strain backgrounds used . We have investigated whether ethanol tolerance as determined by the classical assays of cell proliferation on solid nutrient plates containing different levels of ethanol , correlates with maximal ethanol accumulation capacity in fermenting cells in the absence of cell proliferation . For that purpose , Seg5 was crossed with BY710 , the Seg5/BY710 diploid sporulated and the segregants were first plated on solid media containing glucose and/or ethanol ( 18% to 20% v/v ) . Figure 3A shows a representative result . The haploid parent Seg5 showed high tolerance of cell proliferation to ethanol whereas the laboratory strain BY710 was much more ethanol sensitive . Among the segregants we could observe some with very high ethanol tolerance ( e . g . Seg 11C ) , some with intermediate tolerance ( e . g . Seg 10A ) and others that were as ethanol sensitive as the laboratory strain ( e . g . Seg11D ) . Out of 301 segregants evaluated in this way , 101 segregants showed moderate to high ethanol tolerance , whereas about half of the segregants ( 48 . 8% ) could not grow at all on plates containing 18 or 20% ethanol ( v/v ) . In the first category , 32 segregants showed an ethanol tolerance level as high as Seg5 . Hence , about 1 in 9 segregants showed the same high ethanol tolerance as the superior parent . If we suppose random segregation of the loci and no epistasis , this ratio predicts three independent loci as being involved in determining the high ethanol tolerance of Seg5 compared to the laboratory strain BY710 . Subsequently , we tested 15 ethanol sensitive segregants ( similar to Seg11D of Figure 3A ) by fermentation in 250 mL of YP+33% ( w/v ) glucose . All 15 segregants clearly showed poor fermentation performance , with a low ethanol accumulation capacity ( <14% v/v ) ( not shown ) . This suggests that there is a correlation between ethanol tolerance as measured by the cell proliferation assays on solid nutrient plates and maximal ethanol accumulation capacity in VHG fermentation , at least for the ethanol sensitive strains . Hence , to reduce the high workload required for phenotyping all segregants in fermentations , we tested in the small-scale fermentations only the 101 segregants that showed moderate to high ethanol tolerance in the growth assays on solid nutrient plates . We are aware that the strains with poor ethanol tolerance of cell proliferation may contain mutant genes that compromise maximal ethanol accumulation capacity or that when these strains show relatively high maximal ethanol accumulation capacity , they may contain ( in part ) different mutant alleles than the strains with high ethanol tolerance of cell proliferation . The main purpose of this work , however , was to identify the first set of major causative genes determining maximal ethanol accumulation capacity and this is the main reason why we continued first with the strains preselected for medium to high ethanol tolerance of growth . The distribution of maximal ethanol accumulation capacity among the 101 segregants , as tested in semi-static small-scale fermentations in 250 mL of YP+33% ( w/v ) glucose , is shown in Figure 3B . We have also compared ethanol tolerance of cell proliferation and maximal ethanol accumulation capacity for the 101 segregants . The results are shown in Figure 3C . They are similar to the results obtained for the 68 natural and industrial yeast strains ( Figure 1B ) in two aspects . First , irrespective of the ethanol tolerance of cell proliferation , the segregants show a wide range of ethanol accumulation capacities . This confirms that the correlation between the two properties is weak . Second , the segregants with a higher ethanol tolerance of cell proliferation show a tendency towards higher ethanol accumulation capacity . The latter effect is less pronounced than with the selection of strains in Figure 1B , but this can be due to the fact that the poorest segregants for ethanol tolerance of cell proliferation have already been eliminated for the high-gravity fermentation experiments . Only 22 segregants produced ethanol titres higher than 17% ( v/v ) , similar to the ethanol production of Seg5 and Seg5/BY710 . If we assume that all ethanol sensitive segregants , as determined by growth assays on solid nutrient plates , also display poor maximal ethanol accumulation , we have a ratio of one superior strain in ±14 segregants ( 301/22 = 13 . 7 ) . Assuming random segregation of the QTLs and no epistasis , this ratio is consistent with four independent loci being responsible for the superior ethanol accumulation capacity of Seg5 compared to the BY710 control strain . We constructed several diploids by crossing the four best performing segregants but none of those showed higher ethanol accumulation capacity than the original CBS1585 diploid strain ( data not shown ) . We have performed genetic mapping of the two polygenic traits: on the one hand , high ethanol accumulation capacity in fermenting cells in the absence of cell proliferation , using the 22 best-performing segregants ( pool 1 ) as determined in semi-static VHG fermentations , and on the other hand , tolerance of cell proliferation to high ethanol levels , using the 32 segregants ( pool 2 ) that showed the best growth on solid nutrient media containing 18 to 20% ( v/v ) ethanol . The two pools had 12 segregants in common . Identification of the QTLs was performed by pooled-segregant whole genome sequence analysis [5] , [6] , [8] , [9] . Genomic DNA was sent to two independent companies ( GATC Biotech , Konstanz , and BGI , Hong Kong ) for custom whole-genome sequence analysis with an average depth of ∼38 by the Illumina platform . Other sequencing parameters are summarized in the Methods section . Sequence analysis of the genome of the superior parent Seg5 and comparison to S288c , allowed us to select 48 , 512 high-quality SNPs after filtering for sufficient coverage ( ≥20 times ) and ratio ( ≥80% ) [5] , [22] . The coverage of at least 20 times was based on previous findings that a 20-fold sequencing coverage is sufficient to compensate for errors by the number of correct reads [23] . The ratio of at least 80% was chosen based on the plots of the SNPs between the two parent strains [5] . We also mapped the reads to the assembled sequence for the Kyokai n°7 strain available in the Saccharomyces genome database [24] . We were able to map about 20 , 000 additional reads to this sequence and 93% of the total read pairs aligned with proper distance and orientation to the Kyokai n°7 assembly , while only 87% of the read pairs mapped in the same way to S288c . We also identified the sake strain specific genes AWA1 and BIO6 [24] , which further confirmed that CBS1585 belongs to the sake cluster of S . cerevisiae strains . Genomic DNA was extracted from the two selected pools , containing 22 and 32 segregants , respectively , and also from an unselected pool , composed of 237 segregants ( pool 3 ) in order to assess proper segregation of all chromosomes and possible links to inadvertently selected traits , such as sporulation capacity or spore viability . After sequence analysis , the SNP variant frequency was plotted against the chromosomal position ( Figure 4 ) . Upward deviations from the mean of 0 . 5 identify QTLs linked to the superior parent Seg5 , while downward deviations identify QTLs linked to the inferior parent BY710 . In most areas of the genome , and especially in the QTL areas , the independent sequence analysis by the two companies matched well , which confirms the robustness of the pooled-segregant whole-genome sequencing technology . Only in some selected areas the matching was poorer , which may be due to the low pool sizes . The SNP variant frequencies were smoothed using a Linear Mixed Model ( LMM ) framework [5] and the putative QTLs were identified by applying a Hidden Markov Model ( HMM ) similar to the one implemented in the FastPHASE package [25] . For each polymorphism , the HMM had three possible states: ( i ) a link with the superior parent ( Seg5 ) , ( ii ) a link with the inferior parent ( BY710 ) and ( iii ) no link ( background level ) . The SNP frequencies for each pool of segregants , analysed with the HMM , were assigned probability scores , that indicated to which state ( Seg5 , BY710 or background ) they belonged and hence identified the QTLs , linked to either the superior parent ( Seg5 ) or to the inferior parent ( BY710 ) . The smoothed data of the SNP variant frequency and the Probability of linkage values obtained by HMM analysis with the selected pools 1 and 2 and the unselected pool 3 , are shown in Figure 4 . The QTLs identified with the HMM approach are listed in Tables 2 and 3 for pools 1 and 2 , respectively . SNPs were considered significantly linked to the superior or inferior parent strain when the Probability of linkage was higher than 0 . 95 or lower than −0 . 95 , respectively . The QTLs were numbered according to their position in the genome starting from chromosome I , independently of the trait ( Tables 2 and 3 ) . The unselected pool 3 ( 237 segregants ) showed ±50% SNP variant frequency in most of the genome and thus no evidence of any QTLs ( Figure 4 ) . The only exception was the right arm of chromosome V which was preferentially inherited from the BY parent strain . Comparison with the data of the selected pools , suggested some weak linkage with the genome of the BY parent strain in this part of chromosome V . Because of the weak linkage this was not retained for further analysis . Crosses of Seg5 with other BY strains did not show aberrant segregation of the right arm of chromosome V ( results not shown ) . The results obtained with the unselected pool show that the QTLs identified for the two ethanol tolerance traits were not due to linkage with inadvertently selected traits , such as sporulation capacity or spore viability . The QTLs identified with the selected pools 1 and 2 showed two common QTLs ( on chr XIII and chr XV ) . They were called 12 . 1 and 17 . 1 for pool 1 and 12 . 2 and 17 . 2 for pool 2 . It has to be emphasized that the ‘common’ character of these QTLs is only based on their common location in the genome . In principle , they could be located in the same place on a chromosome but caused by a different causative gene . Moreover , the QTLs 15 and 16 ( pool 2 ) were also present in pool 1 as minor putative QTL of which the significance could not be demonstrated with the current number of segregants ( Probability of linkage <0 . 95 ) . Other minor putative QTLs of which the significance could not be demonstrated with the current number of segregants ( Probability of linkage <0 . 95 ) were present in pool 1 and pool 2 . They were also seen with the smoothed data and the HMM analysis ( Figure 4 ) ( e . g . on chromosome VII ) . There was no indication for linkage of the areas with the sake strain specific genes AWA1 and BIO6 to one or both of the ethanol tolerance traits . We have analysed in detail two QTLs ( 2 and 3 ) involved in high ethanol accumulation capacity ( pool 1 ) because this trait is more relevant in industrial fermentations and because these two QTLs were among those with the strongest linkage . QTL2 is located on chromosome I and was fine-mapped by scoring selected markers in the 22 individual segregants . This reduced the length of the QTL to the area between chromosomal positions 151 kb and 178 kb ( P-value<0 . 05 ) ( Figure 5A ) . The association percentage of the markers , their genomic positions , the respective P-values and the genes located in the putative QTL 1 are shown in Figure 5A . Nearly all genes present in the centre of the QTL had at least on polymorphism either in the ORF , promotor or terminator . Hence , it was not possible to exclude on this basis a significant number of genes as candidate causative genes . Because of the large number of candidate genes and the high workload of the phenotyping for maximal ethanol accumulation capacity , we have introduced a modification of the Reciprocal Hemizygosity Analysis ( RHA ) methodology , which has been used previously for identification of causative genes [10] . Instead of testing one candidate gene at a time , we first evaluated a series of adjacent genes by ‘bulk RHA’ . For that purpose a set of adjacent genes was deleted directly in the heterozygous diploid background ( Seg5/BY710 ) so as to obtain the two reciprocally deleted hemizygous diploids of which the phenotype was subsequently compared . The first block of genes ( bRHA 1 . 1 ) deleted , consisted of NUP60 , ERP1 , SWD1 , RFA1 and SEN34 . The two reciprocally deleted diploid strains were tested by fermentation in YP+33% ( w/v ) glucose , to address the effect of the Seg5 and BY710 alleles on ethanol accumulation capacity . The results showed no difference in the fermentation profile and maximal ethanol accumulation ( Figure 5B ) , suggesting that none of these five genes were causative genes . There was also no difference in fermentation profile and maximal ethanol accumulation with the hybrid parent strain Seg5/BY710 , further supporting that these genes did not influence these phenotypes . The second block of genes tested consisted of YARCdelta3/4/5 , YARCTy1-1 , YAR009c , YAR010c , tA ( UGC ) A , BUD14 , ADE1 , KIN3 and CDC15 ( bRHA 1 . 2 ) ( Figure 5A ) . In this case there was a clear reduction of the fermentation rate and maximal ethanol accumulation when the alleles of the Seg5 strain were absent compared to absence of the BY710 alleles ( Figure 5C ) . Glucose leftover correlated inversely with final ethanol titer . This suggested the presence of one or more causative genes in this region . Moreover , the fermentation rate was higher in the hemizygous strain where the BY710 alleles were absent compared to the hybrid parent strain Seg5/BY710 , indicating that one or more of the BY710 alleles had a negative effect on this phenotype . YARCdelta3/4/5 , YARCTy1-1 , YAR009c and YAR010c are transposable elements , while tA ( UGC ) A encodes one of the sixteen tRNAs for the amino acid alanine . BUD14 is involved in bud-site selection [26] , ADE1 is involved in de novo purine biosynthesis [27] , KIN3 encodes a non-essential serine/threonine protein kinase involved in a . o . DNA damage repair [28] and CDC15 encodes a protein kinase involved in control of the cell division cycle [29] . In order to identify the genes ( s ) involved in ethanol accumulation capacity , we investigated the most likely candidate genes individually with the classical one-gene RHA [10] . Involvement of the transposable elements appeared unlikely and was not evaluated by RHA . The other genes , BUD14 , ADE1 , KIN3 and CDC15 , have polymorphisms ( SNPs and/or indels ) within their ORFs and/or promoter regions . RHA with the genes ADE1 and KIN3 showed that deletion of the Seg5 alleles resulted in strains with clearly lower ethanol accumulation capacity and higher glucose leftover compared to the strain with deletion of the respective BY allele , indicating that ADE1 and KIN3 are causative genes for high ethanol accumulation capacity in Seg5 ( Figure 6A ) . For both genes , the hybrid parent strain Seg5/BY710 behaved in a similar way as the strain with the deleted BY710 allele . For CDC15 and BUD14 there was no difference in the performance of the two reciprocally deleted diploid strains ( not shown ) . Deletion of ADE1 and KIN3 in the Seg5 and BY backgrounds caused a more pronounced effect in the Seg5 sake genetic background ( Figure 6B ) . The causative genes ADE1 and KIN3 were located in QTL2 , which was not linked with ethanol tolerance of cell proliferation . When we tested the hybrid diploid strains previously used in RHA for maximal ethanol accumulation for determination of ethanol tolerance of cell proliferation , we could indeed not observe any significant difference between the two strains ( Figure 6C ) . This confirms that these causative genes are specific for maximal ethanol accumulation capacity and that the genetic basis of the two ethanol tolerance traits is indeed partially different . We also analysed in more detail QTL3 , located on chromosome V . In the same chromosomal region , Swinnen et al . [5] previously identified URA3 as a causative gene in tolerance of cell proliferation to high ethanol levels of VR1 , a Brazilian bioethanol production strain , in comparison with BY4741 as inferior parent strain . Since we crossed Seg5 with an ura3 auxotrophic laboratory strain ( BY710 ) , we first tested whether deletion of URA3 in Seg5 affected maximal ethanol accumulation in this genetic background . The fermentation profile and maximal ethanol accumulation of the strain Seg5-ura3Δ/BY710-ura3Δ ( which is thus homozygous for ura3Δ ) compared with the Seg5/BY710-ura3Δ diploid ( which is heterozygous for ura3Δ ) are shown in Figure 7A . Double deletion of URA3 resulted in a strain with a reduced ethanol fermentation rate , lower maximal ethanol accumulation and higher glucose leftover . We have also tested the effect of introducing URA3 in the ura3 auxotrophic strain BY4741 , which accumulates only low amounts of ethanol under VHG conditions ( ±12% v/v ) . Introduction of URA3 enhanced the fermentation rate in the later stages of the fermentation and resulted in a clearly higher maximal ethanol titer and lower glucose leftover ( Figure 7B ) . These results show that URA3 positively affects maximal ethanol accumulation capacity . The URA3 gene was located in QTL3 , which was not significantly linked with ethanol tolerance of cell proliferation . When we tested the hybrid diploid strains previously used in RHA for maximal ethanol accumulation for determination of ethanol tolerance of cell proliferation , we observed slightly better growth for the strain with the URA3 allele from Seg5 ( Figure 7C ) . This confirms that URA3 has only a minor contribution to this phenotype in this genetic background and suggests that the very weak upward deviation in the SNP variant frequency plot observed in this position for ethanol tolerance of cell proliferation might have been due to the URA3 gene . Comparison of the sequence of ADE1 and KIN3 in Seg5 and BY710 ( S288c background ) revealed a C to T transition in the promoter of ADE1 and a C to T transition in the promoter of KIN3 as well as three synonymous transition mutations in the ORF of KIN3 . We have checked the presence of these SNPs in the ADE1 and KIN3 genes of 36 yeast strains of which the whole genome sequence has been published . The results are shown in Table 4 . ( Among the 36 strains there were additional SNPs compared to S288c , which were not present in Seg5 . These SNPs are not shown ) . The C to T change at position 169227 in ADE1 is present only in two other strains , Kyokai nr . 7 and UC5 . Both strains are sake strains and these strains are known to have superior maximal ethanol accumulation capacity . Sake fermentation produces the highest ethanol level of all yeast fermentations for production of alcoholic beverages [21] . The SNPs in KIN3 of Seg5 at positions 170564 and 170945 are present in many other strains . Interestingly , however , the two other SNPs in KIN3 of Seg5 , at positions 170852 ( in the ORF ) and 171947 ( in the promoter ) are not present in KIN3 of any one of the 36 sequenced strains and therefore may be rather unique .
Tolerance to high ethanol levels is an exquisite characteristic of the yeast Saccharomyces cerevisiae and no other microorganism has ever been reported to show higher ethanol tolerance . This unique property of yeast lies at the basis of the production of most alcoholic beverages and of ethanol as biofuel . In most studies , ethanol tolerance has been assayed by measuring cell proliferation in the presence of increasing ethanol levels . Although this assay is convenient for routine measurement and large-scale screenings , its true relevance for ethanol tolerance in yeast fermentation is unclear . Industrial yeast fermentations always start with an excess of fermentable sugar compared to other essential nutrients . As a result , the ethanol production rate in the second phase of the fermentation , the extent of attenuation of the residual sugar and the final ethanol titer reached are always achieved by stationary phase cells . In this work we have compared for the first time the genetic basis of maximal ethanol accumulation capacity in fermenting cells in the absence of cell proliferation with that of ethanol tolerance of cell proliferation . To avoid interference by the genetic background of the strain , we have used the same pool of segregants derived from one hybrid parent . The results of the QTL mapping by pooled-segregant whole-genome sequence analysis reveal a partial overlap between the genetic basis of the two traits . Although only two significant QTLs , 12 . 1/12 . 2 on Chr . XIII and 17 . 1/17 . 2 on Chr . XV appear identical , there were minor QTLs in pool 1 of which the significance could not be demonstrated with the current number of segregants ( e . g . on Chr . VII and XV ) , which are likely overlapping with significant QTLs in the same position in pool 2 . However , because of the lower number of segregants in pool 1 , the P-value of these QTLs is not low enough for significance . It is also important in this respect to recall that the two pools had 12 segregants in common . A stronger argument for partial overlap between the genetic basis of the two traits could be made if two pools would be assembled not only with different segregants but containing in each pool only segregants that would not fit phenotypically in the other pool . This would have required , however , a large amount of additional experimental work . Our work has shown that successful QTL mapping using pooled-segregant whole-genome sequence analysis can be performed with relatively low numbers of segregants . This is particularly important for elucidation of the genetic basis of complex traits of industrial importance , like maximal ethanol accumulation capacity , which require laborious experimental protocols for scoring . It has also shown that resorting to seemingly similar traits , like ethanol tolerance of cell proliferation , which can be scored easily with simple growth tests on plates , is not a valid alternative . On the other hand , there were several minor QTLs detected for the trait of maximal ethanol accumulation capacity , for which the significance could not be demonstrated with the number of segregants used . The ability to detect QTLs depends on the importance of the causative allele for establishing the trait and on the number of QTLs/causative alleles involved . Higher numbers of segregants will therefore always be useful to map minor QTLs and identify their causative alleles . Detailed analysis of QTL 2 on Chr . I and QTL 3 on Chr . V identified three genes specifically linked to maximal ethanol accumulation capacity , which indicates that ethanol tolerance as relevant for maximal ethanol accumulation in fermentations cannot be fully assessed in a reliable way by simple growth tests on solid nutrient plates in the presence of ethanol . The identification of KIN3 as a causative gene is striking because it reveals for the first time a role for DNA damage repair in ethanol tolerance as required for maximal ethanol accumulation . Moreover , the superior KIN3 allele of Seg5 contained two SNPs , which were absent in the KIN3 gene of all yeast strains of which the genome has been fully sequenced up to now , suggesting that they may be important for the exceptional ethanol accumulation capacity of the Seg5 strain and its diploid parent CBS1585 . KIN3 encodes a serine-threonine protein kinase , required for arrest at the G2/M-phase checkpoint in response to the DNA damage inducing agents MMS , cisplatin , doxorubicin and nitrogen mustard [28] . Involvement of Kin3 in the DNA damage response may be consistent with its requirement for tolerance to high ethanol levels . Ethanol was reported to be mutagenic and to induce single-strand DNA breaks in repair-deficient but not in repair-proficient yeast cells [30] . It was also reported to trigger chromatin condensation , fragmentation , and DNA cleavage in yeast , features suggestive of induction of apoptosis [31] . Mitochondrial DNA loss in yeast is induced by ethanol and mitochondrial DNA from more ethanol tolerant flor yeasts enhanced ethanol tolerance when transferred into a laboratory strain [32] . Also in mammalian cells , ethanol was shown to induce DNA damage and is a known carcinogen [33] . A role for DNA repair in protecting mammalian cells from ethanol-induced damage has been proposed [34] . It will be interesting to investigate to what extent maximal ethanol accumulation in yeast can be enhanced by further strengthening DNA damage repair capacity . The case of URA3 is remarkable . It encodes one of the most active enzymes , oritidine 5-phosphate decarboxylase ( OCDase ) , that catalyzes the decarboxylation of oritidine 5-phosphate ( OMP ) to uridylic acid ( UMP ) [35] , [36] . This is the sixth enzymatic step in the de novo biosynthesis of pyrimidines . Yeast strains lacking URA3 need supplementation with uracil in the medium . Our previous work identified ura3 [5] and several other auxotrophic mutations ( unpublished results ) as causative mutations for ethanol tolerance of cell proliferation in a cross of a Brazilian bioethanol production strain VR1 and the BY laboratory strain . We have now identified ura3 as causative gene for maximal ethanol accumulation capacity in the cross of the sake strain CBS1585 and BY . However , in this genetic background ura3 was not significantly linked to ethanol tolerance of cell proliferation . This indicates that the genetic basis of the latter property is dependent on the genetic background of the strain . A stronger capacity to generate the electrochemical potential required for symport , may for instance offset the ethanol sensitivity of the uptake of auxotrophic supplements . Lower expression of auxotrophic genes , like URA3 , or lower activity of the gene product , forces the yeast cells to take up most uracil using the uracil permease , Fur4 , which is an active proton symporter [37] . Stress conditions , including nutrient starvation , can trigger degradation of Fur4 [38] . Hence , the requirement of URA3 for maximal ethanol production capacity might be linked to nutrient starvation towards the end of the semi-anaerobic , high-gravity fermentation process , which can take up to 21 days . Uracil is likely depleted and/or its transporter Fur4 may be degraded because of the nutrient starvation conditions at the end of the fermentation . In addition , ethanol toxicity may also compromise the proton gradient , which is required for uptake by symport of uracil and protons from the medium . This type of inhibition was reported for amino acid uptake by the proton symporter Gap1 [39] . The reduction of maximal ethanol accumulation in ura3 auxotrophic strains suggests that in general the active uptake of nutrients may be compromised by the increasing ethanol level at the end of the fermentation . Yeast cells have only one permease to transport uracil , Fur4 , which may make this system more sensitive to ethanol inhibition compared to for instance amino acid transport , for which many transporters exist . Another relevant factor may be the general fitness problem of URA3 deleted strains . URA3 auxotrophic strains ( BY710-ura3Δ , BY4741-ura3Δ and Seg5-ura3Δ/BY710-ura3Δ ) showed much less biomass production in the pre-cultures performed in YPD , YP+5% glucose , YP+10% glucose and during the fermentations in YP+33–35% glucose ( OD600 around 12 . 4±2 . 68 ) whereas Seg5/BY710-ura3Δ ( prototrophic ) for example , had much higher cell densities ( 32 . 6±3 . 42 in stirred fermentations ) . Low cell densities contribute to a slow fermentation phenotype that is also associated with lower final ethanol levels . The importance of uracil supplementation and fitness problems related to uracil auxotrophic strains have been reported recently by Basso et al . [19] . We identified the ADE1 allele in Seg5 by RHA as a superior allele for maximal ethanol accumulation capacity in high-gravity fermentation . As in the case of URA3 , there was no link between ADE1 and tolerance of cell proliferation to high ethanol levels . ADE1 encodes a N-succinyl-5-aminoimidazole-4-carboxamide ribotide ( SAICAR ) synthetase , that is required for de novo purine biosynthesis [27] . ADE genes have not been connected previously to ethanol tolerance , but they have been linked to high sugar tolerance . In a genome-wide screen with the deletion strain collection , Ando et al . [40] identified three adenine biosynthetic genes ( ADE5 , 7 , ADE6 and ADE8 ) as being required for tolerance to 30% ( w/v ) sucrose . These genes were not required for tolerance to high sorbitol and NaCl , indicating a specific role in high sugar tolerance . The ADE genes are involved in biosynthesis of purine and derived metabolites , such as ATP . Measurements of the ATP level revealed a reduction with two-fold in the ade mutants , indicating that inability to synthesize sufficient ATP could be related to the high sucrose stress sensitivity . Alternatively , in the ade mutants the STRE-controlled stress response gene , HSP12 , which encodes a plasma membrane chaperone protein , was not induced under high-sucrose stress , as opposed to sorbitol and salt stress [40] . This suggests a possible defect in induction of stress protection factors as cause for the high-sucrose sensitivity and once more a specific role of ADE genes in high sugar stress . Osmotic stress is known to trigger the HOG-pathway [41] . Phosphorylation of Hog1 , the central component of the HOG pathway , however , was normal under all three osmotic stress conditions in all ade mutant strains , suggesting that deficiency of the HOG pathway , or at least the osmosensing systems , was not involved in the sensitivity of the ade mutants [40] . Because we measured maximal ethanol accumulation in fermentations with a very high sugar level ( 33% , w/v , glucose ) , the link with the superior allele of ADE1 in QTL2 ( chr I ) may be due to its importance for tolerance to high sugar stress . If this would be the reason why the superior ADE1 allele of Seg5 supports higher ethanol accumulation under VHG conditions , it would explain why the ADE1 gene was not linked to ethanol tolerance of cell proliferation as measured with pool 2 , since the solid nutrient plates contain a low sugar level and a high ethanol level . The ADE1 gene from the superior parent Seg5 did not have any mutation in the ORF compared to the sequence in the laboratory strain BY . However , one SNP was located in the promoter region of the Seg5 allele ( Chr I: 169 . 228 bp - C/T ) . The promoter of ADE1 is known to bear a hexanucleotide ( 5′ TGACTC 3′ ) element that is under amino acid control [27] . Although the mutation is not within that regulatory element , it is possible that it is affecting ADE1 expression and thereby also high sugar tolerance . In conclusion , our work has shown that successful QTL mapping with pooled-segregant whole-genome sequence analysis can be performed for traits of industrial importance , which require elaborate experiments to score the phenotype , using a relatively low number of segregants . We have identified for the first time genes required for maximal ethanol accumulation capacity in the absence of cell proliferation in fermenting yeast cells and have shown that the genetic basis of this trait is partially different from that of tolerance of cell proliferation to high ethanol levels . The superior alleles identified can be used for improvement of maximal ethanol accumulation capacity in industrial yeast strains for bioethanol production and for the production of alcoholic beverages . This improves attenuation of the sugar at the end of the fermentation , which enhances yield in industrial bioethanol production and reduces residual sugar levels in alcoholic beverages . A higher final ethanol level in bioethanol production reduces distillation costs and lowers the liquid volumes in the plant , which in turn reduces costs associated with cooling , heating , pumping and transport of liquid residue .
The S . cerevisiae strains utilized in this study are listed in Table S2 . Yeast cells were grown with orbital agitation ( 200 rpm ) at 30°C in YPD medium containing 1% ( w/v ) yeast extract , 2% ( w/v ) Bacto peptone and 2% ( w/v ) glucose . VHG fermentations were performed in which the glucose concentration was raised to such an extent ( 33% w/v ) that a maximal final ethanol level ( 17–18% ) was obtained with only minimal residual sugar left [17] . A further increase in glucose concentration above this level reduced the maximal ethanol level again . Cells were first pre-grown in 3 mL of YPD medium for 24 h ( 200 rpm , 30°C ) , after which 0 . 5 mL was transferred to 5 mL of YP+5% ( w/v ) glucose and the culture incubated for 24 h ( 200 rpm , 30°C ) . Cells of the last pre-culture were inoculated in 100 mL of YP+10% ( w/v ) glucose with initial OD600 of 1 . 0 . The cells were grown for 2 days ( 200 rpm , 30°C ) until stationary phase . 12 . 5×109 cells , based on cell counting , were harvested . The cells were centrifuged ( 3000 rpm , 5 min , 4°C ) , the pellet was resuspended in 3 mL of YP and inoculated into 250 mL of YP+33% ( semi-static ) or 35% ( continuous stirring ) ( w/v ) glucose . The fermentations were performed at 25°C . Agitation was performed with a magnetic rod ( 30×6 mm ) at 120 rpm ( semi-static , 4 h ) or 200 rpm ( continuous stirring ) . The fermentation was followed by weighing the tubes and from the weight loss the glucose leftover was calculated . Samples were taken at the end of the fermentation for HPLC analysis and cell viability determination . The metabolites quantified by HPLC were glucose , glycerol and acetic acid . The HPLC system utilized ( Waters Breeze ) consisted of an ion-exclusion column ( WAT010290 ) at 75°C and detection was performed by refractive index ( model 2414 ) . The eluent used was H2SO4 ( 5 mM ) at a flow rate of 1 . 0 mL/min . Samples of 10 µL were automatically injected and processed for 20 min . Ethanol was quantified by near infrared spectroscopy ( Alcolyzer , Anton Paar ) . Cell viability was assessed by oxonol staining followed by flow cytometry analysis [42] . The ethanol yield ( g of ethanol produced per g of glucose consumed ) was calculated by dividing the ethanol produced with the glucose consumed ( initial glucose concentration minus glucose leftover ) . The cells were pre-grown in YPD for 2 days ( 200 rpm , 30°C ) . The OD600 was measured in triplicate and the cells were diluted to an initial OD600 of 0 . 5 . Four serial dilutions were made ( 10−1 , 10−2 , 10−3 and 10−4 ) . A volume of 4 µL was spotted on plates: YPD ( control ) , YPD+16% ( v/v ) ethanol , YP+16% ( v/v ) ethanol , YPD+18% ( v/v ) ethanol , YP+18% ( v/v ) ethanol and YPD+20% ( v/v ) ethanol . The plates were incubated at 30°C for up to 11 days and growth was scored from the second day on . The ethanol levels indicated are initial ethanol levels . During the preparation and incubation of the plates some ethanol may evaporate . Therefore , sample and control strains were always put together on the same plates . General procedures for sporulation and tetrad dissection were used [43] . A small amount of cells ( 1 . 5 mg ) was incubated with 10 µL of NaOH ( 0 . 02N ) for 1 h ( RT ) . The determination of the mating type was done by PCR with the primers for the MAT locus and MATa and MATα ( alpha ) DNA [44] . The 3 primers were used together . Preparation of the DNA pools from the segregants was done either by ( 1 ) individual genomic DNA extraction and pooling of the DNA in equimolar concentrations; ( 2 ) mixing of the cells , based on dry weight , prior to DNA extraction , or ( 3 ) mixing of the cells based on OD600 , prior to DNA extraction . For all preparations , the genomic DNA was extracted according to Johnston [45] . At least 3 µg of DNA per pool was provided for whole-genome sequencing to both GATC Biotech GA ( Konstanz , Germany ) and Beijing Genomics Institute ( BGI , Hong Kong , China ) . In both cases the sequencing was performed with the Illumina platform and gave for most of the genome , and especially in the QTL areas , very similar results . For both pools and at both companies the sequencing depth was ∼38 and the read length was 75 at GATC Biotech and 90 at BGI . Assembly and mapping were done with DNAstar Lasergene software . Smoothing of the sequencing data was performed with a Linearized Mixed Model ( LMM ) framework [5] , [22] . We implemented a Hidden Markov Model ( HMM ) to identify regions related with the phenotypes similar to the one implemented in the FastPHASE package [25] . For each variant , the HMM has three possible states: ( i ) relation with the superior parent , ( ii ) relation with the control parent and ( iii ) no relation ( background ) . To capture the effect of recombination , the transition between two states of the same type is the probability of no recombination and the probability of the transition between two states of different type is the probability of recombination divided by two . We estimated the probability of recombination for each pair of neighbor variants using a negative exponential relation with the physical distance as in [25] . The emission of each state is the number of calls of the alternative allele which is an integer between zero and ni , where ni is the total number of allele calls for the variant i . We used beta-binomial distributions for all states to take into account the fact that given the finite number of segregants , the contribution of each parent to the pool is not exactly half . For the superior parent states we setup α = 10 and β = 1 . For the control parent states we set α = 1 and β = 10 . For the background states we estimated α and β using the alternative allele frequencies in all sites . We checked that for the background distribution α≈β>1 , which makes the background distribution to be close to a binomial with probability 0 . 5 ( as expected ) . We used the forward-backward algorithm to calculate the posterior probability of each state given the allele counts for each dataset . A manuscript with a complete explanation of the algorithm and comparisons with currently available methods is in preparation . The QTLs detected were further analyzed by scoring SNPs in the segregants individually using allele-specific primer sets , which were rigorously tested for reliability with the two variants of each SNP in the parent strains and all segregants . Statistically significant QTLs were confirmed by multiple testing using a false discovery rate ( FDR ) control [46] . Yeast cells were transformed with the LiAc/SS-DNA/PEG method [47] . Genomic DNA was extracted with PCI [phenol/chlroform/isoamyl-alcohol ( 25∶24∶1 ) ] [48] . Polymerase chain reaction ( PCR ) was performed with Accuprime polymerase ( Invitrogen ) for sequencing purposes and ExTaq ( Takara ) for diagnostic purposes . Sanger sequencing was performed by the Genetic Service Facility of the VIB . The detection of SNPs by PCR was performed as previously described [5] . RHA was performed as described previously [5] , [10] in the diploid Seg5/BY710 genetic background . In addition to single gene deletions we also performed large deletions ( bulk RHA ) of regions up to 27 kb long . The selection marker utilized was the amidase gene ( AMD1 ) , which was amplified from the vector pF6a-AMD1-MX6 . The gene AMD1 was cloned from Z . rouxii [49] . The primers utilized in the AMD1 amplification had at least 80 extra bases that corresponded to the flanking regions of the area to be deleted . The transformants were selected on solid YCB + acetamide 10 mM ( yeast carbon base 11 . 7 g/L; sodium phosphate buffer 0 . 03 M; agar 20 g/L ) . The correct integration of the constructs was checked by PCR , using one primer that annealed within AMD1 and two other primers that annealed either downstream or upstream of the deleted region . The PCR products were sequenced and the polymorphisms ( SNPs and indels ) present in the regions flanking the selection marker were identified when the Seg5 allele was replaced by AMD1 . On the other hand , when the laboratory allele was deleted , no polymorphism was detected by Sanger sequencing . Double allele deletion was not observed during the bulk RHA because the deleted regions contained at least one essential gene . The fermentations with different yeast strains were done with the reference strain V1116 as a control in duplicate . The most interesting strains were repeated at least once . The fermentations with different meiotic segregants were done with the reference strains Seg5 , BY710 and Seg5/BY710 . The segregants showing more than 16 . 5% ( v/v ) ethanol production were evaluated by fermentation at least once more . The fermentations for RHA were done in triplicate . The results were analyzed with a paired t-test ( p<0 . 01 , except for the comparison of V1116 and CBS1585 for which p<0 . 05 was used ) . All sequence data have been deposited in the Sequence Read Archive ( SRA ) at the National Center for Biotechnology Information ( NCBI ) and can be accessed with account number SRA056812 . | The yeast Saccharomyces cerevisiae is unique in being the most ethanol tolerant organism known . This property lies at the basis of its ecological competitiveness in sugar-rich ecological niches and its use for the production of alcoholic beverages and bioethanol , both of which involve accumulation of high levels of ethanol . Up to now , all research on yeast ethanol tolerance has focused on tolerance of cell proliferation to high ethanol levels . However , the most ecologically and industrially relevant aspect is the capacity of fermenting yeast cells to accumulate high ethanol levels in the absence of cell proliferation . Using QTL mapping by pooled-segregant whole-genome sequence analysis , we show that maximal ethanol accumulation capacity and tolerance of cell proliferation to high ethanol levels have a partially different genetic basis . We identified three specific genes responsible for high ethanol accumulation capacity , of which one gene encodes a protein kinase involved in DNA damage repair . Our work provides the first insight in the genetic basis of maximal ethanol accumulation capacity , shows that it involves different genetic elements compared to tolerance of cell proliferation to high ethanol levels , and reveals for the first time the importance of DNA damage repair in ethanol tolerance . | [
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] | 2013 | Comparative Polygenic Analysis of Maximal Ethanol Accumulation Capacity and Tolerance to High Ethanol Levels of Cell Proliferation in Yeast |
Recent systems-based analyses have demonstrated that sleep and stress traits emerge from shared genetic and transcriptional networks , and clinical work has elucidated the emergence of sleep dysfunction and stress susceptibility as early symptoms of Huntington's disease . Understanding the biological bases of these early non-motor symptoms may reveal therapeutic targets that prevent disease onset or slow disease progression , but the molecular mechanisms underlying this complex clinical presentation remain largely unknown . In the present work , we specifically examine the relationship between these psychiatric traits and Huntington's disease ( HD ) by identifying striatal transcriptional networks shared by HD , stress , and sleep phenotypes . First , we utilize a systems-based approach to examine a large publicly available human transcriptomic dataset for HD ( GSE3790 from GEO ) in a novel way . We use weighted gene coexpression network analysis and differential connectivity analyses to identify transcriptional networks dysregulated in HD , and we use an unbiased ranking scheme that leverages both gene- and network-level information to identify a novel astrocyte-specific network as most relevant to HD caudate . We validate this result in an independent HD cohort . Next , we computationally predict FOXO3 as a regulator of this network , and use multiple publicly available in vitro and in vivo experimental datasets to validate that this astrocyte HD network is downstream of a signaling pathway important in adult neurogenesis ( TGFβ-FOXO3 ) . We also map this HD-relevant caudate subnetwork to striatal transcriptional networks in a large ( n = 100 ) chronically stressed ( B6xA/J ) F2 mouse population that has been extensively phenotyped ( 328 stress- and sleep-related measurements ) , and we show that this striatal astrocyte network is correlated to sleep and stress traits , many of which are known to be altered in HD cohorts . We identify causal regulators of this network through Bayesian network analysis , and we highlight their relevance to motor , mood , and sleep traits through multiple in silico approaches , including an examination of their protein binding partners . Finally , we show that these causal regulators may be therapeutically viable for HD because their downstream network was partially modulated by deep brain stimulation of the subthalamic nucleus , a medical intervention thought to confer some therapeutic benefit to HD patients . In conclusion , we show that an astrocyte transcriptional network is primarily associated to HD in the caudate and provide evidence for its relationship to molecular mechanisms of neural stem cell homeostasis . Furthermore , we present a unified systems-based framework for identifying gene networks that are associated with complex non-motor traits that manifest in the earliest phases of HD . By analyzing and integrating multiple independent datasets , we identify a point of molecular convergence between sleep , stress , and HD that reflects their phenotypic comorbidity and reveals a molecular pathway involved in HD progression .
Huntington’s disease ( HD ) is a progressive and fatal neurodegenerative disorder caused by abnormal expansion of the CAG repeat in the huntingtin gene ( HTT ) . Mutant huntingtin protein causes variable morphological pathology and differential gene expression throughout the brain , with the striatum exhibiting the earliest and most severe effects[1] . Consequently , patients suffering from HD most notably develop motor abnormalities , including chorea and dystonia . However , HD patients also develop significant non-motor symptoms , including depression , anxiety , and sleep disturbance , that are often associated with stress and typically precede significant neuronal loss and the onset of motor dysfunction by many years[2–9] . Understanding the biological bases of these early non-motor symptoms may reveal therapeutic targets that prevent disease onset or slow disease progression[4 , 10] , but the molecular mechanisms underlying this complex clinical presentation remain largely unknown . There is rapidly accumulating evidence that many genetic and molecular factors contribute to complex phenotypes[11 , 12] , and recent systems-based analyses suggest that sleep and stress traits , in particular , emerge from shared genetic and transcriptional networks[10] . These results have led to the hypothesis that common networks shared between sleep , stress , and neurodegenerative diseases may elucidate novel pathological mechanisms and reveal therapeutic targets[10] . In particular , since stress-related psychiatric and sleep disturbances precede motor symptoms and severe neuronal loss in HD , a systems-level analysis that integrates HD-relevant gene networks with non-pathological stress and sleep gene networks may reveal convergent network domains where HTT proteotoxicity impinges on normal functions of stress response and sleep . In the present work , we tested this hypothesis explicitly by investigating common striatal transcriptional networks underlying HD , stress , and sleep phenotypes ( Fig 1 ) . To perform this analysis , we primarily integrated two different datasets: 1 ) a public microarray dataset ( GSE3790 from GEO ) from a human HD cohort and age- and sex-matched controls; and 2 ) genetic , phenotypic , and RNA-sequencing data from a large ( N = 100 ) chronically stressed ( B6xA/J ) F2 mouse population that has been extensively phenotyped ( 328 stress- and sleep-related measurements ) . Previous work has described systems-based pathologies involved in the onset and progression of HD[13–16] , and some groups have explored a variety of approaches for combining different types of HD-relevant data[17 , 18] . In this work , we integrate gene and network-level analyses to identify transcriptional networks whose expression and connectivity are dysregulated in HD and evaluate which HD-associated networks are associated with stress susceptibility and sleep disruption . We revealed significant alterations to molecular networks in the caudate , cortex , and cerebellum of a human HD cohort that were not previously appreciated by differential expression alone . We found that an astrocyte network is most relevant to HD pathology in the caudate and showed that this astrocyte HD network is downstream of a signaling pathway important in adult neurogenesis ( TGFβ-FOXO3 ) . We found that this HD-relevant astrocyte network is conserved in the striatum of a ( B6xA/J ) F2 mouse population and is correlated to several sleep and stress measures implicated in HD . Lastly , we identified the candidate causal regulators of this astrocyte network through Bayesian network analysis and showed that their downstream nodes are significantly modulated by deep brain stimulation , a medical intervention thought to confer some therapeutic benefit to HD patients[19 , 20] . By analyzing and integrating multiple independent datasets , we identified a point of molecular convergence between sleep , stress , and HD that reflects their phenotypic comorbidity and supports a fundamental mechanism of neuropathogenesis .
To identify HD-relevant molecular networks , we examined publicly available human microarray gene expression data ( GSE3790 ) from 203 brain samples . The HD-gene-positive cases include 39 caudate nucleus ( CN ) samples , 38 cerebellar ( CB ) samples , and 37 frontal cortex ( CTX ) samples , and the age- and sex-matched controls include 28 CN , 32 CB , and 29 CTX samples . Using weighted gene coexpression network analysis[21] , we constructed transcriptional networks of the CN , CB , and CTX from the HD cohort , and we identified 85 , 36 , and 96 modules in the three brain regions , respectively ( Fig 2A , 2C and 2E ) . Each module represents a group of coexpressed genes , named using an arbitrarily assigned color and determined to be robust through resampling methods ( S1 Fig ) . As a resource , we report network-based statistics and module membership assignments for each module in S1–S3 Tables . To identify modules most relevant to HD , we compared modules between the pathological cohort and a cohort of age- and sex-matched controls . For each brain region , we calculated modular differential connectivity ( MDC ) , which measures changes in connectivity in HD-associated modules with respect to their module counterpart in the control cohort[11] . We identified differentially connected molecular networks in all three brain regions ( Fig 2B , 2D and 2F ) and confirmed these results using an independent methodology that measures module preservation[22] ( S2 Fig ) . We note that differential connectivity signatures capture more transcriptional information between cases and controls than was previously appreciated by differential expression alone[1] ( Fig 3A and 3B ) . This is best exemplified in the cerebellum , a region thought to be largely spared in HD . While very few cerebellar genes are differentially expressed between cases and controls , differential connectivity analyses reveal that HD strongly alters gene networks in the cerebellum , affecting 6-fold more genes than was estimated by differential expression experiments . These significant changes to cerebellar gene networks are consistent with more recent evidence for macro- and microstructural damage to the cerebellum in HD and its association to both motor and non-motor symptoms[23] . Since differential connectivity reveals novel pathological information , we investigated if network-level analysis supported the common notion that HD primarily affects the caudate . Hodges et al . ( 2006 ) argues that the number of differentially expressed genes in HD parallels morphological pathology ( caudate>cortex>cerebellum ) [1] , and we note that this pattern is also reflected in the number of genes in differentially connected networks , as expected . However , we note that pathological changes to molecular networks are far more equally dispersed across brain regions than differential expression analyses have revealed , supporting the notion that HD is a multi-focal and systemic brain disease[13 , 24] ( Fig 3A ) . For example , previous work with the same human cohort reported that the number of differentially expressed genes in the cerebellum are approximately 5% of the number of differentially expressed genes in the caudate[1] , but this difference is far less pronounced when comparing differentially connected genes ( 40% ) . Taken together , these results further support the prominence of caudate pathology in HD . However , they also reveal that the HTT mutation causes more significant and widespread effects across multiple brain regions than previously appreciated by differential expression analysis alone . Since the caudate network is most significantly affected in HD , we focused our downstream analysis on this brain region . We reasoned that modules most relevant to HD would exhibit both gene- and network-level dysregulation , so we ranked modules by their MDC score and their enrichment for differentially expressed genes in HD ( S4 Table ) . We calculated module enrichment for two published HD differential expression signatures—calculated in this cohort ( GSE3790 ) and a replication cohort ( GSE26927 from GEO ) –in order to ensure robustness . Several modules were either differentially connected or enriched with differential expressed genes . A neuron-specific module ( Skyblue ) , which includes D1 and D2 dopamine receptors , and a module involved in apoptotic regulation ( Lightcyan ) both showed significant gene-level dysregulation , but only small changes in network connectivity . On the other hand , a cytoskeletal module ( Blue ) and an antigen processing and presentation module ( White ) were differentially connected in HD , but not enriched robustly for differentially expressed genes . Our unbiased ranking revealed that Thistle2 was the module most relevant to HD , since it was the only module that was both strongly differentially connected ( MDC = 2 . 47 , FDR < 0 . 001 ) and overrepresented with HD differential expression signatures from both datasets ( GSE26927: P = 5 . 7 x 10−23; GSE3790: P = 7 . 1 x 10−19; Bonferroni corrected , Fisher’s exact test ) , particularly genes upregulated in HD ( GSE26927: P = 3 . 2 x 10−31; GSE3790: P = 1 . 5 x 10−52 ) . Next , we investigated whether Thistle2 was overrepresented with cell-type specific gene signatures derived by fluorescence-activated cell sorting ( FACS ) [25] . We noted enrichment for an astrocyte gene expression signature ( P = 1 . 1 x 10−82 ) , which was specific to in vivo astrocytes ( P = 3 . 0 x 10−40 ) and not cultured astrocytes ( P > 0 . 05 ) . Thistle2 was not overrepresented with either neuronal ( P > 0 . 05 ) or oligodendrocyte ( P > 0 . 05 ) gene signatures . We also noted Thistle2 was enriched with an independent astrocyte gene signature derived from in situ hybridization[26] ( P = 4 . 7 x 10−10 ) . Lastly , we found that this module was overrepresented with an astrocyte-specific proteome signature as well [27] ( P = 2 . 6 x 10−84 ) . These analyses support the conclusion that Thistle2 is astrocyte specific using multiple independently derived cell-type specific signatures across two orthogonal data types . Additional analyses confirmed that this module enrichment was not correlated with pathological grade , suggesting it is unlikely that this network simply reflects astrocytosis ( S3 Fig ) . Furthermore , to show that this HD-relevant astrocyte network was reproducible , we examined microarray data from an independent human cohort ( GSE26927 ) . These analyses revealed that this astrocyte module captures highly robust gene coexpression patterns that show both significant gene and network dysregulation in HD ( S4 Fig ) . Taken together , this evidence suggests that the transcriptional module most relevant to HD pathology is astrocyte specific ( Fig 3C ) . Since genes in the Thistle2 module are coexpressed , we reasoned that their common regulatory control could be driven a by shared transcription factor ( TF ) . We identified 36 TFs predicted to regulate the astrocyte module and calculated a composite rank statistic that prioritizes TFs by their binding site enrichment score and differential expression profile in HD ( S5 Table ) . FOXO3 , an important regulator of adult neural stem cell homeostasis , was the highest-ranking transcription factor ( Fig 3D ) . To validate that FOXO3 modulates the astrocyte module , we examined three independent datasets ( GSE60137 , GSE13347 , and GSE18326 from GEO ) , in which FOXO3 was manipulated with different experimental approaches ( shRNA in C2C12 cells , siRNA in C1E-ER-GATA1 cells , and FoxO3-/- murine brain , respectively ) . The astrocyte module was overrepresented with each of the three FOXO3-dependent differential expression profiles , confirming that FOXO3 robustly regulates the astrocyte module ( GSE60137: P = 9 . 0 x 10−7; GSE13347: P = 4 . 3 x 10−39; GSE18326: P = 3 . 5 x 10−12 ) . Lastly , we investigated if FOXO3 modulation of Thistle2 is downstream of any common signaling pathways . We found that the TGFβ pathway was the most significant upstream regulator for both the Thistle2 module and its 36 predicted TFs ( S5A Fig ) . Further , we found that FOXO3 is itself regulated by the TGFβ pathway and note that the subset of Thistle2 genes with FOXO3 binding sites also are strongly modulated by TGFβ signaling ( P = 7 . 33 x 10−8 ) ( S5B Fig ) . Together , these results implicate TGFβ-FOXO3 signaling as an important regulator of HD-associated transcriptional coexpression in the caudate . To determine if HD-relevant networks are associated with sleep and stress traits , we investigated if any HD transcriptional networks in the caudate also were coexpressed in the striatum of a chronically stressed ( B6xA/J ) F2 mouse population ( GSE60312 from GEO ) that has been extensively phenotyped ( 328 stress- and sleep-related measurements ) [10] . We unbiasedly mapped modules from the H . sapiens Huntington’s disease cohort ( hsHD ) to the modules previously calculated from RNA-seq data ( N = 100 ) in the M . musculus sleep/stress cohort ( mmSS ) . This analysis revealed that 18% of hsHD modules were also coexpressed in the mmSS cohort and that the Thistle2-hsHD module mapped specifically to the Blue-mmSS module ( Fig 4A ) . Further analyses confirm that genes in Thistle2-hsHD are highly expressed and robustly measured across the human and mouse experiments[28] ( S6 Fig ) . To determine if the Blue-mmSS module was relevant to sleep and stress traits , we investigated if its module eigengene ( 1st principal component of the module ) was significantly correlated with any of the 328 sleep and stress traits measured in the ( B6xA/J ) F2 population[10] . Blue-mmSS is strongly associated with fear conditioning , sleep fragmentation after restraint stress , and baseline power band measures ( Fig 4B ) . Notably , the human corollaries of many of these mouse traits are dysregulated in HD cohorts[2 , 3 , 29] . Overall , these analyses reveal that the HD-relevant astrocyte network is associated to non-motor ( sleep and stress ) traits and provide a strategy for identifying molecular pathways likely associated with non-motor symptoms . These data suggest that Thistle2-hsHD may be relevant to early HD pathogenesis because of its associations with non-motor phenotypes . In order to corroborate this evidence , we investigated if Thistle2-hsHD gene expression is dependent upon CAG length . CAG repeat length is inversely correlated with HD onset age[30] , but weakly associated with disease progression[31] . Therefore , CAG length-dependent gene expression can point to the early phases of HD molecular pathogenesis[32] . A recent comprehensive study has identified robust CAG length-dependent networks in mouse striatum[16] , so we compared these networks to our HD-relevant networks . This analysis revealed that Thistle2 was most strongly overrepresented with a network whose expression was shown to be inversely correlated with CAG length ( “M11” , P = 2 . 9 x 10−8 ) . Previous work also demonstrated that this CAG length-dependent network ( “M11” ) is conserved in BACHD-ΔN17 , R6/2 , and HdhQ150 mice , suggesting this module is robust across mouse models of HD . Our analysis shows that a bottom-up ( CAG length-dependence ) and top-down ( phenotype ) approach to studying early phases of HD pathogenesis converge onto the Thistle2-hsHD astrocyte network . To identify the candidate causal regulators ( CCRs ) of the Blue-mmSS module , we used an integrative genomics approach that leveraged both genetic and gene expression data from 100 ( B6xA/J ) F2 mouse samples to calculate causal probabilistic relationships between genes [11 , 33–36] . In previous work , we identified genes whose expression was dependent on genetic variability ( cis-eQTLs ) in order to construct a Bayesian network ( with cis-eQTLs priors ) of all gene-gene relationships[10] . In this analysis , we specifically investigated the Blue-mmSS module and calculated its CCRs ( nodes with a significant number of downstream partners ) . These CCRs drive the expression of the Blue-mmSS module , and therefore represent its most important members . We identified 26 Blue-mmSS CCRs , which include some genes that have been implicated previously in HD-associated pathology ( Fig 5A ) . For example , Nucb1 encodes a protein that inhibits amyloid fibril formation often observed in HD[37] , and Gpx8 encodes a glutathione peroxidase , an enzyme recently shown to be neuroprotective in HD animal models[1 , 38] . Next , we investigated if the CCRs of Blue-mmSS are themselves dysregulated in HD . Four CCRs ( Tcn2 , Ace , Spint2 , and Ltbp3 ) are differentially expressed in the human HD cohort ( GSE3790 ) . Ltbp3 is especially interesting since the LTBP family regulates the localization , activation , and bioavailability TGFβ[2–6 , 39–41] , the signaling pathway that we identified as most relevant to Thistle2-hsHD in the human HD caudate . However , we note that the 26 CCRs are not enriched for differentially expressed HD genes ( P = 0 . 8 ) , while their downstream nodes are ( P = 1 . 6 x 10−3 ) . This relationship is further supported when examining the members of Blue-mmSS that are also coexpressed in Thistle2-hsHD . Only one Blue-mmSS CCR , Tspan33 , is a member of the human HD Thistle2 module , while the downstream network is overrepresented for the Thistle2-hsHD module ( P = 2 . 9 x 10−6 ) , and more specifically for Thistle2-hsHD genes with FOXO3 binding sites ( P = 2 . 7 x 10−7 ) ( Fig 5B ) . As a whole , this evidence suggests that CCRs relevant to sleep and stress control the expression of the HD-relevant transcriptional network . To further support the claim that CCRs of the sleep and stress mouse network are relevant to HD , we investigated their protein interaction network ( PIN ) . We constructed their PIN by querying first-degree protein-protein interactions previously identified through experimental and computational methods and considered only interactions between proteins that are expressed in the caudate ( S6 Table ) . We found that the PIN was overrepresented with proteins known to cause abnormal voluntary movement ( P = 5 . 7 x 10−8 ) and abnormal emotional and affective behavior ( P = 5 . 3 x 10−4 ) , suggesting that the CCRs strongly interact with proteins that are necessary for motor and non-motor traits relevant to HD ( Fig 5C ) . We then investigated whether these CCRs may be directly affected by HTT-toxicity . Notably , their PIN is overrepresented with HTT-interacting proteins , identified by a yeast two-hybrid screen[42] ( P = 2 . 7 x 10−15 ) . We confirmed this finding with a second independent dataset that identified in vivo HTT-complexed proteins from a mouse model of HD by affinity purification-mass spectrometry[14] ( P = 6 . 4 x 10−7 ) . Overall , these results provide strong orthogonal evidence that the Blue-mmSS CCRs are relevant for both motor and non-motor phenotypes associated with HD and associated with HTT proteotoxicity . To examine if modulating CCRs is associated with motor and non-motor phenotypes , we determined which bioactive small molecules coherently affect our CCRs using transcriptional profiles in Connectivity Map . We reasoned that molecules affecting psychiatric or neurological traits may work in part by modulating candidate causal nodes in the Blue-mmSS subnetwork . This analysis revealed a number of molecules that concordantly up- or down-regulate these CCRs ( P < 0 . 05 , Benjamini-Hochberg corrected , Kolmogorov-Smirnov ) . Molecules that significantly downregulate these CCRs include drugs which ameliorate motor symptoms , depression , and anxiety . On the other hand , molecules that upregulate these candidate causal nodes include drugs which can induce dystonia , motor restlessness , extrapyramidal symptoms , jitteriness , and insomnia ( Fig 5D ) . For example , CCRs are downregulated by citalopram ( P = 0 . 0097 ) and trihexyphenidyl ( P = 0 . 0027 ) , treatments for depression/anxiety and Parkinson’s disease , respectively . On the other hand , these CCRs are upregulated by cyclizine ( P = 0 . 0166 ) , which has been reported to induce chorea[43–45] , mefloquine ( P = 0 . 0203 ) , which can induce or exacerbate a variety of neuropychiatric and sleep phenotypes[46 , 47] , and protriptyline ( P = 0 . 0216 ) , whose side effects include anxiety , insomnia , and decreased motor coordination . These results provide further orthogonal evidence associating these CCRs with the emergence of sleep , stress , and motor symptoms . All scores and statistics reflecting compound-causal regulator associations are provided in S8 Table . Deep brain stimulation ( DBS ) is used as a therapeutic tool in several neuropsychiatric disorders , and recent reports suggest that DBS targeting the globus pallidus internus and the subthalamic nucleus ( STN ) may ameliorate motor and non-motor symptoms in HD patients[19 , 20] . Therefore , we tested the therapeutic viability of the astrocyte network by investigating whether it is affected by striatal transcriptional changes induced by DBS to the STN . Previous work has characterized the striatal molecular signature induced by STN-DBS in the rat[48] , and we find that this striatal DBS signature is overrepresented in both Thistle2-hsHD ( P = 1 . 5x 10−2 ) and Blue-mmSS ( P = 6 . 5 x 10−5 ) . We note that the DBS signature exclusively affects downstream nodes of the Blue-mmSS subnetwork , suggesting the potential therapeutic benefits of upstream modulation . Slc4a2 is directly modulated by DBS and is immediately downstream of Ltbp3 , discussed above as a CCR of our network and an important modulator of TGFβ signaling . While Slc4a2 knockout causes motor deficits[49] , its upregulation is associated motor symptom resolution after STN-DBS[48] . Though the relationship between Slc4a2 and TGFβ pathway has been proposed in other systems[50] , our network analysis reveals that this mechanism may contribute to the therapeutic benefits of DBS . In sum , STN-DBS modulates a striatal astrocyte network relevant to both motor and non-motor symptoms of HD , suggesting that regulating this network may confer therapeutic benefit .
Our work provides a systems-based approach for identifying and prioritizing networks and pathways relevant to HD , and our analysis has revealed many novel insights into the molecular mechanisms underlying HD pathogenesis . Previous systems analyses have identified gene networks in post-mortem HD brain correlated with pathological grade[15] , while other work has investigated neural stem cells differentiated from HD-patient derived iPSCs and revealed gene networks whose module eigengene expression distinguishes neural stem cells with the CAG expansion from neural stem cells genetically corrected with homologous recombination-based gene targeting methods[51] . More recent work has used allelic series knock-in mice to identify CAG length-dependent gene networks in order to study early HD pathogenesis[16] . In our work , we leverage a multi-species population approach to study early HD pathogenesis that integrates genetic , transcriptomic , proteomic , and behavioral data across human and mouse cohorts to identify HD-relevant networks associated with non-motor traits prevalent in early HD . We provide evidence that an astrocyte module is the caudate network whose connectivity and expression is most altered in HD . We confirmed its coexpression in an independent cohort , associated it with FOXO3-TGFβ signaling , showed it was CAG length-dependent , and correlated it with many sleep and stress phenotypes in a ( B6xA/J ) F2 mouse population , including several traits that have been previously identified in human HD populations . Lastly , we show that CCRs of this sleep and stress network control the HD-associated nodes and are strong therapeutic candidates . Most functional and molecular work on HD has focused on medium spiny neurons , but our analyses instead suggest a primary role for astrocytes in HD striatal pathology . Our results also suggest that the HD-relevant astrocyte network is insufficiently explained by astrocytosis , since module enrichment for astrocyte-specific genes was not correlated with pathological grade . Given this evidence , we argue that this astrocyte network is critical to HD pathogenesis , a conclusion also supported by data from the prefrontal cortex in multiple HD cohorts[24 , 52] . Other evidence suggests that astrocyte-specific expression of the mutant huntingtin protein is sufficient to cause the striatal neuron degeneration[53] and age-dependent neurological symptoms[54] observed in HD , and both the altered neuronal excitability[55] and chronic inflammation[56] in HD may be the result of primary astrocyte dysfunction . Our integrative network analyses , accompanied by these functional data , support the hypothesis that astrocytes are a primary contributor to HD pathogenesis . However , alternative interpretations may be considered when interpreting these data . For instance , the nature of post-mortem brain samples make it difficult completely rule out astrocytosis as a partial contributor to this HD-relevant network . Also , it is possible that astrocyte network dysregulation in early HD may be secondary to increased oligodendrocyte density[57] . Further work is required to understand how astrocytes affect neuropathological and phenotypic features of early HD . We integrated our network analysis with experimental knockdown data and highlighted that this astrocyte network is downstream of TGFβ-FOXO3 signaling . Previous work has studied the role of the FOXO homologue ( daf-16 ) in a Caenorhabditis elegans model of early mutant htt toxicity in which expanded polyQs cause a defective touch response but minimal cell death[58–60] . These studies demonstrate an important role for FOXO in improving touch response in 128Q nematodes . Other evidence in immortalized striatal cell lines demonstrates that Sirt1 requires Foxo3a to make cells with mutant HTT resilient to serum withdrawal , complementing C . elegans evidence for the protective effects of FOXO3a[61] . While these data suggest that FOXO3 is neuroprotective and repressed in HD , other evidence from R6/2 mice and human post-mortem caudate argues that FOXO3 overexpression is associated with HD partly due to an overactive autofeedback loop[62] . These seemingly conflicting data suggest that HD-relevant mechanisms are dynamic , multifactorial , and perhaps not always well-conserved between animal models and human disease . Our analytical strategy was agnostic to these neuroprotection hypotheses and did not intend to resolve these problems . Instead , our data-driven analyses suggest that FOXO3 regulates a human striatal astrocyte gene network that is CAG length-dependent and associated with non-motor phenotypes relevant to early HD . These data implicate a novel pathway through which FOXO3 can influence HD pathogenesis . We note that previous experiments focused on FOXO3-dependent effects on neurons and often did not directly assay astrocytes , and this gap may also partially explain conflicting conclusions drawn by previous literature . It is intriguing that FOXO3 may exert its protective or degenerative effects through specific cell-types , or through different cell-types at different stages of HD pathogenesis , but further work needs to be done to disentangle these complex cellular phenomena . Dysregulation of neurotrophic and growth factors in HD are also well documented . Previous work has identified a HD-associated gene network in iPSC-derived neural stem cells that is associated with TGFβ signaling[51] . It is especially notable that two different approaches to studying early HD pathogenesis implicate the TGFβ pathway since previous molecular work on non-motor HD symptoms tend to focus on the TrkB pathway[2 , 63] . The importance of TGFβ signaling in early HD pathogenesis is further supported by work demonstrating that valproic acid and lithium , both of which have been shown to improve mood in HD patient[63–65] , can affect TGFβ signaling[66 , 67] . Furthermore , TGFβ has been noted as an important regulator of FOXO transcription factors in a number of conditions and tissues[68 , 69] , and our analysis ties this mechanism to an astrocyte gene network in HD caudate . It is also important to note that several signaling pathways converge onto FOXO transcription factors[70–72] and function through FOXO3 in HD pathogenesis[60] . These findings emphasize the importance of studying system-level gene interactions in order to understand and disentangle the complex and multifactorial mechanisms associated with HD . Lastly , adult generated neurons are depleted in the striatum of HD patients[73] , and both FOXO3 and TGFβ play fundamental roles in regulating and maintaining adult neural stem cell populations[74–77] . Furthermore , dysregulation of neural differentiation networks has been associated with glial pathogenesis in the human prefrontal cortex of both Alzheimer’s disease and Huntington’s disease cohorts[52] . Our results link these molecular mechanisms of adult neural stem cell maintenance to astrocyte pathology in the caudate , which is consistent with previous work showing that FoxO3 dysregulation disrupts neural stem cell homeostasis by specifically skewing the population toward astrocyte lineages[76 , 78] . Overall , our analyses suggest astrocyte pathophysiology and neural stem cell depletion in HD may emerge from a single pathological mechanism . We mapped this astrocyte network to independently derived striatal networks from chronically stressed ( B6xA/J ) F2 mice and showed that its expression correlated with stress and sleep phenotypes . Previous studies have demonstrated that astrocytes can modulate cortical slow oscillation , sleep amount , and sleep drive[79–81] and can contribute to sleep-loss induced deficits[82] . Our work presents strong evidence that alterations in mood and sleep traits are associated with the HD astrocyte network in the striatum . Each of these phenotypes has been previously identified in human HD patients , but our systems-based analyses associate these seemingly disparate phenotypes to a HD-relevant transcriptional network in the caudate . We also showed that the expression of this astrocyte network is dependent upon CAG length , further suggesting its role in early HD pathogenesis . However , it is important to note that previous work found insufficient evidence to corroborate the genotype-expression correlation of these genes in the human cohort ( GSE3790 ) . This difference may be explained partly by limitations in power across a diverse range of CAG length in the human cohort . Differences in cell population changes between the mouse and human cohorts also may have confounded this approach for these specific astrocyte genes . Nevertheless , we emphasize that our multi-species population approach and the allelic series knock-in mouse models both implicate this astrocyte network in early HD pathogenesis . The convergence of these approaches was further supported by showing that the primary module described by Langfelder et al ( “M2” ) was overrepresented with previously identified F2 networks , Turquoise-mmSS and Mediumpurpl2-mmSS[10] . These F2 networks partly motivated the present study since they were strongly associated with sleep , stress susceptibility , and neuropsychiatric disease and suggested that HD-relevant pathways are direct modulators of sleep and stress phenotypes . One of these networks was driven by Htt ( Mediumpurple2-mmSS ) and a second network ( Turquoise-mmSS ) includes Rrm2b and Ncald among its most connected genes ( hubs ) , two genes near a locus associated with earlier clinical onset of HD[83] . In sum , these analyses strongly suggest that two independent strategies for studying early HD pathogenesis implicate similar pathways and integrating these data revealed specific sleep and stress traits correlated with CAG length-dependent striatal networks that are altered in human HD . Further network analyses revealed that sleep and stress CCRs control the expression of the HD-relevant nodes and are affected by HTT-toxicity . The organization within this shared network reflects the emergence of stress- and sleep-related phenotypes in the early phases of HD and the eventual manifestation of significant motor symptoms later in the disease . It also suggests upstream modulation of this sleep and stress subnetwork may be therapeutically efficacious by delaying the progression of HD . These results support the notion that psychiatric symptoms are a primary clinical presentation of HD and suggest that targeting the molecular mechanisms of non-motor symptoms may significantly improve both psychiatric and motor function in HD patients , as has been done with antipsychotics like risperidone[84] . Notably , we show that this network shared between sleep , stress , and HD is affected by deep brain stimulation of the subthalamic nucleus , a medical intervention that ameliorates both the motor and non-motor symptoms in some HD patients[20] . Functional data support our network analysis , implicating astrocytes in the therapeutic mechanism of action of DBS[85 , 86] . However , we note that DBS does not modulate any CCRs of this astrocyte network , which may explain the limited and short-term benefits of this therapy in HD . Robust modulation of this network may lead to more efficacious treatment , and our network analysis can serve as a resource for evaluating therapeutic options in silico and prioritizing future in vivo experiments . In these analyses , we have shown that sleep , stress , and HD share an astrocyte network affected by signaling pathways of adult neurogenesis , and our systems-based approach provides a framework for considering psychiatric symptoms as the primary manifestation of neurodegenerative disease . It is important to note that not all HD patients experience the same non-motor symptoms , but this astrocyte network is a striatal pathway through which HD can impinge upon sleep and stress traits in genetically or environmentally susceptible individuals . By integrating molecular networks from comorbid psychiatric and neurological conditions , we can identify novel points for therapeutic intervention , prioritize mechanisms of neurodegenerative pathogenesis , and perhaps even capture molecular dynamics of disease progression , which are difficult to measure directly in human brain . Though this work makes significant steps towards systematically studying the common molecular basis of motor and non-motor features of HD , we acknowledge that our analysis focuses on only one of many points of intersection worthy of further exploration . We also acknowledge that further in vivo investigation of Thistle2-Blue network is essential for completely understanding the functional and morphological consequences of each CCR and the best points of therapeutic intervention . This may include an expanded investigation of transcription factor binding and upstream pathway regulation . We validated FOXO3 , but 35 other transcription factors also are predicted to control the Thistle2 module , including several that are differentially expressed in the HD caudate . Some predicted transcription factors , like HOXA5 and FOXF2 , have also been implicated in HD pathogenesis in the prefrontal cortex[24] . Lastly , our results indicate that HD causes significant changes to transcriptional networks across the caudate , frontal cortex , and cerebellum . While this work emphasizes caudate-specific pathophysiology , it also provides evidence that HD-relevant transcriptional networks in other brains regions are significantly associated with pathogenesis and require proper investigation , a molecular feature not previously captured by differential expression . Specifically , three cerebellar networks ( Blue , Royalblue , Midnightblue ) exhibit both gene- and network-level changes in HD and would be strong candidates for HD-relevant functional studies in the cerebellum ( S9 Table ) . These modules are associated with protein folding and oxidative phosphorylation functional pathways , and one cerebellar module ( Royalblue ) is even overrepresented with the Huntington’s disease Kyoto Encyclopedia of Genes and Genomes ( KEGG ) pathway , suggesting that HD does not spare the cerebellum . This conclusion is well supported by more recent pathological studies that indicate profound changes in brain regions outside the striatum ( like brainstem nuclei and cerebellum ) , which may play significant roles in motor and non-motor symptom manifestation , especially in the early phases of the disease[23 , 87–89] . Therefore , we believe a comprehensive understanding of HD requires further investigation of both the mechanisms underlying its comorbid psychiatric and neurological features and the effects of pathology on networks across multiple brain regions .
Hodges et al . ( 2006 ) studied differential gene expression across three brain regions in a cohort of 44 HD-gene-positive cases and 36 age- and sex-matched controls using Affymetrix microarray HG-U133A and U133B[1] . HD cases had between 42–46 CAG repeats while unaffected controls ranged from 17–21 . The pathological range is considered greater than 35 repeats . Neuropathological staging of the HD cohort ranges from 0–4 , and the majority of HD cases were graded as Grade 1 or 2 . Three cases ( graded as either 0 or 1 ) were considered presymptomatic . We downloaded the author-normalized ( MAS5 ) expression data and associated covariate table from GEO ( GSE3790 ) . The dataset consists of 203 samples , with 67 cerebellar samples , 70 caudate samples , and 66 frontal cortex samples . For each brain region , we further adjusted the expression data for age and sex by fitting a robust linear regression model and taking the residuals as the corrected expression levels . Lastly , we used surrogate variable analysis to account for unknown and unmeasured covariates[90] . The same protocol was used to prepare the expression data from the validation cohort ( GSE26927 ) . We generated coexpression modules from the corrected expression data in the HD cohort ( GSE3790 ) , using weighted gene coexpression analysis[21] . We identified linear relationships between gene expression using pairwise Pearson correlation and defined the “scale-free” adjacency matrix of the gene expression graph by raising the Pearson correlation matrix to a positive power , β[21] . Nearest-neighbor links were accounted for by quadratically transforming the adjacency matrix into topological overlap matrix ( TOM ) , which depicts biological interactions with high fidelity[91] . Coexpression modules were then defined using a hierarchical clustering method that implements the Dynamic Tree Cut algorithm[92] . Modules were arbitrarily assigned colors , with the grey module identifying genes failing to segregate into a particular module . We assessed the robustness of each module by repeatedly splitting the data into training and test sets and calculating a module preservation score between the resulting networks[22] . Module association to pathological grade was quantified by relating each module’s 1st principal component to pathological grade with a Kruskal-Wallis test , and module-grade associations were expressed as its –log10 ( P ) . Fisher’s exact test was used to assess module enrichment for cell-type specific and HD differential expression signatures , and Bonferroni corrected p-values are reported for all Fisher’s exact tests . We used cell-type specific signatures derived from FACS and in situ hybridization experiments , and we tested module enrichment for HD differential expression profiles derived from this cohort ( GSE3790 ) and a second cohort ( GSE26927 ) in order to ensure robustness and reproducibility . Module conservation was tested for all HD modules with greater than 50 module members . Fischer’s exact test was used to determine module conservation between the HD cohort and the ( B6xA/J ) F2 cohort , for which a module was considered conserved with Bonferroni corrected p-value < 0 . 05 ( accounting for all module-module comparisons ) and Odds Ratio > 2 . Module conservation was similarly assessed between the HD cohort and the allelic series knock-in cohort . When necessary , homology information provided by Ensembl was used for human-mouse conversion . In the case of many-to-many homology , all possible pairs of human and mouse genes were kept . Recent work has demonstrated that the RNA-seq and microarray estimates of gene expression are most divergent for lowly expressed genes , while genes with higher expression are robustly estimated across assays[28] . To ensure that our coexpression graph overlap for the astrocyte module ( Thistle2 ) was not biased by lowly expressed genes that were poorly estimated across assays , we examined median gene expression in all modules calculated in the human HD cohort . We note that genes with low expression were difficult to distinguish from noise ( background hybridization ) , so unsupervised clustering tended to assign them to “grey” ( no module ) . Consequently , the median expression of genes in grey was systematically lower than genes in modules with a color assignment , as expected ( Kolmogorov Smirnov P < 2 . 2 x 10−16 ) ( S6A and S6B Fig ) . In general , this suggests that genes assigned to coexpression modules are not significantly affected by any systematic bias attributable to the microarray . Further , we directly compared Thistle2 to all other modules ( including grey ) . Genes in Thistle2 are among the most highly expressed ( S6C Fig ) , suggesting that they are robustly measured within and between assays . In a previous study characterizing mouse striatal gene networks underlying multiple stress and sleep phenotypes , we described in detail a set of phenotypic , genetic and RNA-Seq gene expression data collected in a chronically stressed population of 338 male ( B6×A/J ) F2 mice[10] . Briefly , starting from 4–5 weeks of age , all F2 mice were subjected to a battery of stressors , including social isolation , novel exposed environments ( elevated plus maze , open field , elevated zero maze ) , restraint , forced swimming , fear conditioning , social defeat , cold exposure , a metabolic stressor ( 6-hr fast and glucose tolerance test ) , and the sleep behavior response to sleep deprivation and restraint . Extensive behavioral and physiological measurements were taken during the chronic stress treatment . Sleep/wake behavior was recorded from each mouse using electroencephalography and electromyography . Following all stress and sleep tests , animals were euthanized by decapitation , and blood and tissue samples were collected for additional analyses . Genotypes of all animals were determined from DNA extracted from tail-tip biopsies by using the Illumina medium density single nucleotide polymorphism ( SNP ) panel . Gene expression profiling in the striatum of a randomly selected subset of 100 animals was performed using RNA sequencing . 100 base pair single-end sequencing reads were aligned against the Ensembl NCBIM37 mouse reference genome for gene-level expression profiling ( expression data available at GSE60312 ) . Weighted gene coexpression analysis was used to characterize the transcriptional landscape of the striatum , and 1st principal components of each module were correlated with phenotypes measured in the cohort to determine module-trait associations . The relevance of a module to a phenotype was determined by ranking the number of significant module-trait associations for each module ( P < 0 . 05 , FDR < 0 . 05 ) . As previously described[11] , we calculated a MDC statistic for each module by quantifying the ratio of the average connectivity of its genes in the disease network to that of the same genes in the control network . Consequently , MDC > 1 indicates that a module gained connectivity in disease , while MDC < 1 suggests lost connectivity . In this work , we used stricter thresholds to ensure the robustness of our results ( MDC >2 and MDC < 0 . 5 ) . We estimated two separate false discovery rates ( FDR ) by randomly shuffling samples and genes of disease and control networks . Shuffling samples creates networks with random edges and shuffling genes creates networks with random nodes . We quantified the final FDR by selecting the larger estimate and used a conservative FDR threshold to assess significance ( FDR < 0 . 001 ) . We also confirmed that the MDC statistic revealed similar module preservation features as the medianRank statistic calculated with a separate analytical method [22] . This procedure calculates a rank-based measure that accounts for a variety of network metrics of density , connectivity , and separability , which MDC does not directly assess . MDC and medianRank statistics are highly concordant in their assessment of module preservation , as demonstrated in S2 Fig . After confirming the robustness of the MDC statistic , we integrated MDC scores and differential expression enrichment to identify modules most affected by HD on the gene and network levels . To confirm this strategy with an orthogonal method , we calculated coexpression networks from all caudate gene expression data ( cases and controls in a single expression matrix ) and identified modules associated with case-control status . This analysis revealed an astrocyte module strongly associated with HD , which was highly overlapping with the Thistle2 module from the original analysis , providing support for our analytical approach ( S10 Table ) . As described in our previous work[10] , we reconstructed directed acyclic graphs called Bayesian networks to identify relationships between the gene expression profiles of each gene in our network . Edges between nodes reflect the conditional probability distributions of each node given the expression of its parent node[33 , 93] . Using a Monte Carlo Markov Chain ( MCMC ) simulation , we reconstructed one thousand gene networks that fit our data , as assessed by Bayesian Information Criterion ( BIC ) [94]–a method conservative to overfitting . A consensus network was calculated using thresholds identified to be ideal in balancing recall rate and precision[34] . Bayesian networks do not necessarily contain causal information , since many graphical models are Markov equivalent and causally indistinguishable . By integrating genetic data in the form of expression quantitative trait loci ( eQTLs ) , we can improve network reconstruction , as has been validated by simulation[34] and in vivo experimentation[33 , 35] , and infer causality between nodes by breaking symmetrical Markov equivalent structures and improve network reconstruction . We identified causal regulators in our directed acyclic graph by calculating the size of the h-layer neighborhood ( HLN ) downstream of each gene in our network[95] . Nodes whose HLN is one standard deviation greater than the mean were considered causal regulators , since they have significantly more downstream partners than the average node in the module . To predict transcript factor binding , we used the oPOSSUM database[96] . Using this tool , we collected genomic DNA sequences of the Thistle2 module from the Ensembl database and identified phylogenetically conserved non-coding DNA sequences using ORCA[97] . We then used vertebrate-specific position specific scoring matrices ( PSSMs ) catalogued by JASPAR[98] to identify relationships between transcription factor binding sites ( TFBS ) and their target DNA binding motifs , restricting the search space for TFBS to phylogenetically conserved , non-coding DNA to improve specificity[99 , 100] . Two statistics , Z score and Fisher’s exact probability , were used to quantify TFBS enrichment , in order to account for the rate of occurrence of TFBSs and the overall proportion TFBSs in our coexpressed genes , respectively[101] . We used empirical thresholds of Z > 10 and Fisher’s < 0 . 01 to identify significant TFBS enrichment , which have a false positive rate of ~15% . However , we note that our effective false positive rate is significantly lower , since all of our significant targets have Z > 10 and Fisher’s p < 1 x 10−10 . We ranked all transcription factors by their Z score and Fisher score , as well as by their differential expression profile in the HD cohort , to identify a prioritized list of significant transcription factors . To identify relevant signaling pathways upstream of the Thistle2 module and its predicted TFs , we utilized 215 heterogeneous microarray experiments curated by the Signaling Pathway Enrichment using Experimental Data Sets ( SPEED ) database . This methodology identifies elements of the transcriptome consistently regulated by pathway perturbations across many experiments[102] . Enrichment of our gene signatures in experimentally validated downstream pathways was assessed by Fisher’s exact test . We used default criteria ( z = 1% , overlap = 20% , expression = 50% ) for identifying gene signatures of each pathway and accounted for multiple hypotheses testing by quantifying the false discovery rate ( FDR ) using the hypergeometric distribution[103] . The sensitivity and specificity of this method are 83% and 98% , respectively . We constructed a PIN by integrating 13 different sources that describe known and predicted protein-protein interactions , which was compiled by HDNetDB ( hdnetdb . sysbiolab . eu ) . These databases include data from yeast two-hybrid screens ( MDC , CCSB ) , literature curation ( HTT-HTP , Human Protein Reference Databse , BioGRID , Reactome , Database of Interating Proteins , BIND , IntAct , HomoMINT ) , computational text mining ( COCIT ) , and orthology-based predictions ( OrthoDB , OPHID , HomoMINT ) . The overwhelming majority ( ~90% ) of edges in our constructed PIN are derived from databases curating experimentally validated protein-protein interactions , and more than half of all edges were derived from either REACTOME[104] or Human Protein Reference Database[105] ( S6 Table ) . We assessed PIN enrichment for HTT-interacting proteins[14 , 42] and proteins known to cause motor and mood abnormalities with Fisher's exact test . Proteins relevant for motor and mood abnormalities ( S7 Table ) were curated by the Mouse Genome Informatics database and are retrievable through the mouse phenotype identifiers MP0003491 and MP0002572 , respectively[106] . CCRs of the Blue-mmSS module were used to query Connectivity Map , a large library of drug induced transcriptional profiles[107] . We merged the 6 , 100 individual experiments into a single representative signature for the 1 , 309 unique small molecule compounds , according to the prototype-ranked list method[108] . For each unique compound , a modified Kolmogorov-Smirnov ( KS ) score was calculated[107] , summarizing each drug’s transcriptional relationship to our Blue-mmSS CCRs and quantifying the tendency for those genes to be concordantly up- or downregulated in the presence of a given compound . Significance of individual scores was estimated by generating an empirical KS score distribution from the query network to 1 , 000 permuted drug signatures , and compounds with P < 0 . 05 ( Benjamini-Hochberg corrected ) were considered significant . | Huntington’s disease is a complex neurodegenerative disorder caused by CAG expansion in the huntingtin gene . Huntington’s disease leads to abnormal involuntary movements in patients , but recent studies have shown that many non-motor psychiatric and sleep changes also manifest in the earliest phases of the disease , often before gross changes in movement . This study identifies gene networks that are affected by Huntington’s disease and associated with these non-motor traits , revealing biological pathways and the cell-types likely involved in the earliest stages of Huntington’s disease . | [
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"anal... | 2016 | Systems Genetic Analyses Highlight a TGFβ-FOXO3 Dependent Striatal Astrocyte Network Conserved across Species and Associated with Stress, Sleep, and Huntington’s Disease |
Dengue virus ( DENV ) is a mosquito-borne flavivirus that causes serious human disease and mortality worldwide . There is no specific antiviral therapy or vaccine for DENV infection . Alterations in gene expression during DENV infection of the mosquito and the impact of these changes on virus infection are important events to investigate in hopes of creating new treatments and vaccines . We previously identified 203 genes that were ≥5-fold differentially upregulated during flavivirus infection of the mosquito . Here , we examined the impact of silencing 100 of the most highly upregulated gene targets on DENV infection in its mosquito vector . We identified 20 genes that reduced DENV infection by at least 60% when silenced . We focused on one gene , a putative cysteine rich venom protein ( SeqID AAEL000379; CRVP379 ) , whose silencing significantly reduced DENV infection in Aedes aegypti cells . Here , we examine the requirement for CRVP379 during DENV infection of the mosquito and investigate the mechanisms surrounding this phenomenon . We also show that blocking CRVP379 protein with either RNAi or specific antisera inhibits DENV infection in Aedes aegypti . This work identifies a novel mosquito gene target for controlling DENV infection in mosquitoes that may also be used to develop broad preventative and therapeutic measures for multiple flaviviruses .
Dengue virus ( DENV ) is the most important arbovirus in tropical areas leading to substantial pediatric morbidity and mortality worldwide [1–6] . DENV is transmitted to humans via the bite of an infected mosquito of the Aedes spp . Infection with DENV in humans can result in dengue fever ( DF ) , dengue shock symptom ( DSS ) and dengue hemorrhagic fever ( DHF ) , the latter two that can lead to severe disease and death . There are no specific antivirals or approved vaccines for use in DENV treatment or prevention [4 , 7–9] . Current dengue control methods rely mostly on activities to reduce vector population [10 , 11] . The increase in number of cases despite vector control indicates that these strategies are not as effective as expected , and that new tools need be developed to alleviate disease burden in endemic areas [12–14] . During the last five decades , much effort has been invested in the development of vaccines against DENV [15–23] . One of the obstacles in dengue vaccine development is the potential risk of severe disease mediated by the presence of sub-neutralizing antibodies against virus particles . These antibodies can predispose an individual to severe disease through a phenomenon called antibody-dependent enhancement ( ADE ) , where the virus can infect cells via FcR in mononuclear cells [8 , 9 , 24–28] . Traditional vaccine approaches have included live attenuated viruses , recombinant subunits , virus-like particles and plasmid or viral vectors . There are live attenuated and chimeric DENV vaccines that have gone into clinical trials but none have proven to provide complete and lasting protection against all four DENV serotypes [21 , 29] . An attractive complement to traditional vaccines is to induce an immune response in the vertebrate host ( infected or non-infected ) that will block virus infection of the mosquito vectors . This would successfully interrupt transmission by inducing antibody responses against non-viral antigens [30] . These type of vaccines are called transmission-blocking vaccines ( TBV ) , since they aim to interfere with pathogen development within the vector , thereby blocking transmission to human hosts [31] . The majority of TBVs designed to inhibit malaria infection are based on the mammalian immune response to pathogen proteins [31] . Another category of TBVs in development are based on arthropod molecules able to reduce pathogen infection in vector tissues [32] . For arboviruses , vector molecules able to interact directly with the pathogen ( i . e . ligands/receptors ) are highly suitable candidates for blocking transmission [33 , 34] . The main global transmission vector for DENV is Ae . aegypti . Extensive research has shown that DENV infection of Ae . aegypti induces many varied changes in gene expression [35–44] . Our hypothesis is that genes upregulated during DENV infection are required for virus survival or are related with defense against infection [37] . Consequently , a better understanding of the role of mosquito proteins regulated by DENV infection will reveal important insights into DENV biology and transmission as well as be helpful to the design of an effective TBV against DENV . For example , antibodies directed against mosquito molecules involved in steps of the pathogen life cycle are promising candidates for TBV . In addition , a recent study demonstrated that antibodies against a mosquito C-type lectin , mosGCTL1 , effectively interrupts the infection of Ae . aegypti mosquitoes with DENV [34] . Other proteins which genes are unregulated upon infection also show promising capacity of interrupting infection since they are considered important for the microorganism survival . One of these proteins is the tick histamine release factor ( tHRF ) from Ixodes scapularis upregulated during Borrelia burgdorferi infection . Previous work showed that expression of tHRF is associated with the tick blood feeding and that the silencing its gene by RNA interference or antibodies not only effectively impairs tick feeding but subsecuently decreases B . burgdorferi burden [45] . Using comprehensive microarray analysis to identify key alterations in the Ae . aegypti transcriptome during flavivirus infection , we previously identified 203 mosquito genes that were up- and 202 genes that were down-regulated during infection [35] . Comparative analysis revealed that at least 15 of these genes had differential expression during infection with DENV , Yellow fever ( YFV ) and West Nile virus ( WNV ) [35] . One of these conserved , up-regulated genes was a putative cysteine-rich venom protein ( AAEL000379 ) , which we named CRVP379 . Cysteine-rich venom proteins ( CRVPs ) are expressed in multiple mosquito tissues including the salivary glands [37 , 46 , 47] . Examples of mosquito CRVPs include an An . stephensi peptide annotated as salivary-secreted serine protease inhibitor [48] and a putative cysteine-rich protease inhibitor found in the sialotranscriptome of adult female Culex quinquefasciatus [49] . The specific role of these proteins in mosquitoes remains unknown [46 , 47] . Here , we describe a requirement for CRVP379 during DENV infection in mosquito cells and live mosquitoes , including a direct correlation between the amount of CRVP379 expressed and the level of DENV infection . We demonstrate the importance of an interaction between CRVP379 and prohibitin , a putative DENV receptor protein in mosquitoes . We also assess the tissue-specific expression of CRVP379 during DENV infection . Finally , we use both RNAi and specific antibody to demonstrate that blocking CRVP379 results in inhibition of DENV infection in Ae . aegypti . These results further our understanding of DENV pathogenesis in the mosquito vector and highlight a potential target protein for the creation of a DENV TBV to break the host-vector transmission cycle .
We previously used microarray analysis to identify a number of Ae . aegypti genes that were significantly up-regulated during infection with DENV and other selected flaviviruses [35] . These genes are likely required for flaviviral infection of Ae . aegypti or are part of the mosquito immune response to viral infection . To elucidate the role of these genes and their corresponding proteins , we reduced gene expression through RNAi knockdown and analyzed the effect on viral infection . We designed siRNA against 100 genes that were significantly up-regulated during DENV infection of Ae . aegypti ( S1 Fig ) . The siRNA was used to silence these genes in an Ae . aegypti cell line , Aag2 , and the resulting effects on DENV infection were examined . Cells were infected with DENV 72h after siRNA transfection and analyzed for infection using qRT-PCR 24h post-infection . We found that gene silencing both increased and decreased DENV infection , as expected ( S2 Fig ) . The silencing of 9 genes caused cytotoxicity beyond our ability to accurately measure infection levels . Silencing approximately 55 individual genes decreased DENV infection of the cells to below 60% of control infection ( Fig 1A ) , which is greater than 40% inhibition of infection . A number of these genes encode hypothetical proteins for which the function is not known . Several of our target genes do have putative known functions , including a cytochrome P450 ( AAEL009762 ) , histone H3 ( AAEL003685 ) and a cysteine-rich venom protein ( AAEL000379 ) . The cysteine-rich venom protein ( CRVP ) , which we will call CRVP379 , was a particularly interesting target . CRVP proteins are known to contain a trypsin inhibitor-like ( TIL ) domain , which indicates that the CRVP379 protein could be a serine protease inhibitor . Both serine proteases and their inhibitors are known to be involved in DENV infection and pathogenesis in the mosquito vector as well as in mammals [50–55] . The expression levels of 19 mosquito CRVP genes were examined during flavivirus infection with the previous microarray analysis . CRVP379 was the only CRVP significantly up-regulated in Ae . aegypti during infection with any of the 3 prototypic flavivirus infections , including DENV , West Nile virus ( WNV ) and Yellow Fever virus ( YFV ) , at all timepoints tested ( Table 1 ) [35] . In addition , the 19 CRVP genes that we looked at in our microarray actually have very low sequence identify at the amino acid level ( S3 Fig ) . This indicates that they may not have identical or even similar functions , though they are grouped in a protein family due to the presence of multiple cysteines and a TIL domain . Therefore , we decided to assess the role of CRVP379 in DENV infection of the mosquito vector in greater detail . Looking at gene expression over time in DENV-infected Aag2 cells , we found that CRVP379 expression increased more than 800-fold when compared to mock-infected cells ( Fig 1B , P<0 . 01 ) . Since the gene was upregulated in mosquito cells during DENV infection , we wanted to examine the phenotype during DENV infection with loss of function experiments . We used RNA interference ( RNAi ) with siRNA to reduce CRVP379 gene expression . To confirm gene knockdown , levels of CRVP379 were measured after siRNA transfection over time ( Fig 1C ) , and the expression levels remained below 10% at 72h post-transfection . To determine how the reduction of CRVP379 altered DENV infection , we examined infection levels in Aag2 cells at various timepoints from 1 to 24h post-infection during siRNA knockdown . Silencing CRVP379 reduced DENV infection at all timepoints measured , as compared to infection in control cells transfected with siRNA against GFP ( Fig 1D ) . Interestingly , we noticed that levels of CRVP379 were slightly elevated during DENV infection even during siRNA knockdown , when compared to uninfected cells . This can be seen by looking at the fold change in CRVP379 expression in GFP siRNA-transfected cells as compared to CRVP379 siRNA-transfected cells during DENV infection over time ( Fig 1E ) . Together , these results indicated that the silencing effects of RNAi on CRVP379 are slightly overcome by the gene upregulation during DENV infection , but that infection levels still remained quite low when compared to cells with no CRVP379 silencing . Since we found that the presence of CRVP379 is required for DENV infection , we wanted to test whether increasing CRVP379 levels would enhance infection levels . To do this , we cloned the CRVP379 coding region into the insect expression vector pAc5 . 1/V5-His ( Life Technologies , CA ) , resulting in pAcCRVP379 vector . This expression vector was transfected into an Ae . aegypti mosquito cell line , Aag2 , and the cells were subsequently infected with DENV . A vector expressing GFP was transfected as a control into a separate group of DENV-infected cells . Transfection levels as measured by GFP transfection are over 50% , which will give meaningful results when looking at gene expression and effects on DENV infection ( S4 Fig ) . At 48h post-infection , levels of CRVP379 expression were measured by qRT-PCR . The expression levels of CRVP379 were over 1000 times higher in the cells that were transfected with the CRVP379 plasmid ( Fig 2A ) . We next infected the transfected cells with DENV at 48h post-transfection . At 24 hpi , RNA was isolated and qRT-PCR done to measure DENV infection in the cells . We found that the overexpression of CRVP379 did not increase DENV infection levels in the cells ( Fig 2B ) . This indicated that the endogenous levels of CRVP379 protein are sufficient and that the virus has likely evolved to require only those amounts for optimum infection . Since we found that CRVP379 was required for DENV infection of mosquito cells , we decided to next look at the requirements for infection in live Ae . aegypti . To do this , we designed dsRNA against the CRVP379 coding region and inoculated mosquitoes via intra-thoracic injection . At days 2 , 4 and 8 post-injection , we dissected out midgut tissues and measured levels of CRVP379 expression by qRT-PCR analysis . Although knockdown was not achieved in all tissues tested , a near-complete reduction of CRVP379 expression ( over 95% ) in midguts was seen 70% of the time by day 8 ( Fig 3-all panels ) . We next examined the effects of silencing CRVP379 on DENV acquisition in the mosquito midgut . Mosquitoes were again injected with dsRNA against CRVP379 or a control dsRNA against GFP protein . At day 4 post-injection , mosquitoes were infected with DENV by blood feeding using a hemotek apparatus . At day 4 post-infection , midgut tissues were dissected out and analyzed for both CRVP379 expression and DENV infection by qRT-PCR . Since not all midgut tissues had reduction in CRVP379 expression , we analyzed each midgut individually in order to examine the effects on DENV infection in midguts that did have reduced CRVP379 . The levels of CRVP379 in the selected midguts are shown in Fig 3A . In the midguts that had reduced CRVP379 expression , DENV infection was almost completely inhibited , as compared to infection in control mosquito midguts ( Fig 3B , P<0 . 01 ) . We also analyzed the data after adding back in the midguts that did not have sufficient gene knock down and looked at levels of DENV infection . Fig 3C shows the levels of CRVP379 in these midguts . Interestingly , in midgut tissues where CRVP379 was not knocked down , DENV infection was comparable to levels in the GFP dsRNA-injected mosquitoes ( Fig 3D-squares ) . Plotting the data points as level of DENV versus level of CRVP379 , there is a correlation between expression of CRVP379 in the mosquito midgut and level of DENV infection in that same midgut ( Fig 3E , r = 0 . 6442 , P<0 . 0001 ) . This indicates that CRVP379 levels are directly related to levels of DENV infection in the mosquito midgut . Finally , we repeated the RNAi experiment and allowed the DENV infection to disseminate for 7 days . At day 7 post-infection , whole mosquitoes were homogenized and analyzed for both CRVP379 expression and DENV infection by qRT-PCR ( Fig 3F ) . The mosquitoes that received the dsRNA against CRVP379 had a significant reduction in DENV infection levels as compared to the control mosquitoes . This indicates that the reduction of CRVP379 blocks DENV infection in the whole mosquito . After establishing that DENV requires CRVP379 in both mosquito cells and live Ae . aegypti , we next wanted to investigate the mechanistic role that CRVP379 plays during infection . To do this , we used the tandem affinity purification ( TAP ) assay to identify putative mosquito proteins that bind CRVP379 during DENV infection . We cloned the coding region of CRVP379 into the NTAP vector ( Stratagene , CA ) , which fuses the gene to purification tags , and transfected this plasmid into Aag2 mosquito cells . Cells were infected with DENV 24h post-transfection and lysed 24h post-infection . The cell lysate was processed and CRVP379 was purified using the expressed tags , along with interacting mosquito proteins . The resulting solution was sent for LC/MS-MS analysis to determine which proteins were pulled out of the mosquito cell lysate by CRVP379 during DENV infection . A separate set of cells was transfected with the NTAP vector expressing GFP as control . Table 2 lists the mosquito proteins that putatively bound CRVP379 and were not identified during control experiments . One of the proteins identified , prohibitin , was previously characterized as binding to DENV in Aedes A7 cells [56] and has also been suggested as a putative DENV receptor in mosquito cells [57] . Since we found that prohibitin binds CRVP379 during DENV infection using the TAP assay , this may indicate that the proteins act together to facilitate DENV entry into mosquito cells . In establishing prohibitin as a putative receptor in mosquito cells , Kuadkitkan et al used siRNA against the mosquito prohibitin gene to inhibit protein production and saw a significant decrease in DENV infection in mosquito cells [57] . To confirm that prohibitin is required for DENV infection in mosquitoes , we designed dsRNA against the mosquito prohibitin gene and examined the impact of silencing prohibitin on DENV infection . Ae . aegypti were intra-thoracically inoculated with the dsRNA and at 4 days post micro-injection ( dpmi ) , mosquitoes were infected with DENV via blood feeding . At 4 days post-infection ( dpi ) , mosquito midguts ( MG ) were dissected and analyzed for infection by qRT-PCR analysis . Our results show that DENV infections levels were greatly inhibited by prohibitin silencing as compared to the control mosquitoes ( Fig 4A ) , confirming a requirement for prohibitin in DENV mosquito infection . We next performed co-immunoprecipitation to confirm the protein interaction between CRVP379 and prohibitin . Aag2 cells were transfected with an expression vector coding for His-tagged CRVP379 protein and/or infected with DENV . Cells were then lysed and antibody against the His tag was used to pull down His-CRVP379 from the cell lysate . Western blot analysis identified prohibitin protein in the immunoprecipitate ( Fig 4B ) , demonstrating that His-tagged CRVP379 bound prohibitin during DENV infection in the mosquito cells . We then used immunoflourescent imaging to visualize the putative prohibitin-CRVP379 protein interaction . Aag2 cells were transfected with the His-tagged CRVP379 expression construct and infected with DENV 48 hours post-transfection . At 24 hours post-infection , cells were fixed and stained with antibodies against the His tag and prohibitin protein . Fig 4C shows that the two proteins were highly colocalized during DENV infection . We next wondered whether prohibitin overexpression could rescue the mosquito cells that were resistant to DENV infection due to reduced CRVP379 expression . To investigate this , we transfected CRVP379 siRNA into Aag2 cells and then overexpressed mosquito prohitibin before infecting the cells with DENV . We found that the overexpression of prohibitin did not significantly increase DENV infection in cells with reduced CRVP379 , though there was a slight enhancement ( S5 Fig ) . This indicates that , though the proteins may act together to facilitate DENV infection in mosquito cells , prohibitin cannot replace the function of CRVP379 protein . Interestingly , the overexpression of prohibition in control Aag2 cells ( with siRNA against GFP ) did increase DENV infection ( S5 Fig ) . Since we found that inhibiting CRVP379 gene expression using RNA interference reduced DENV in Ae . aegypti , we next wanted to try and inhibit protein function with antibody and examine the effects on DENV infection . To do this , recombinant protein consisting of residues 21–128 of CRVP379 was expressed in E . coli along with a GST tag for purification . To generate polyclonal antiserum , rabbits were immunized with the recombinant CRVP379 ( rCRVP379 ) . We used the antisera in Western blot analysis to confirm that antibodies would bind the recombinant protein ( Fig 5A ) . We next ensured that the polyclonal antisera contained antibodies that recognized endogenous CRVP379 protein in the mosquito . To test this , we used the antisera to stain Aag2 cells and found that there was a strong reaction between the CRVP379 antisera and protein in the cells ( Fig 5B ) . We then used the antisera to probe mosquito midgut tissue for endogenous protein . Fig 5C demonstrates that the CRVP379 antisera , but not the pre-immune control sera , recognized protein in the dissected mosquito MG tissue . We also used the antisera to probe MG tissue with reduced CRVP379 expression due to RNAi ( S6 Fig ) . To confirm that the antisera did recognize the CRVP379 protein in the mosquito , we ectopically expressed a His-tagged CRVP379 protein in Aag2 cells and used antibody against the His tag along with the CRVP379 antisera . Staining with the CRVP379 antisera colocalized with the anti-His staining , indicating that the antisera recognized the CRVP379 protein ( Fig 5D ) . We then looked at tissue-specific expression of CRVP379 and found that levels are increased in both the salivary glands ( SG ) and midguts ( MG ) of DENV-infected mosquitoes , as compared to uninfected mosquito tissues , at all timepoints examined ( Fig 5E ) . We also used ELISA analysis with the CRVP379 antisera using both Aag2 cell lysate , Ae . aegypti salivary gland tissue and Ae . aegypti saliva to confirm that the antisera bound endogenous CRVP379 protein ( Fig 5F ) . Next , we tested the effects of the antisera on DENV infection in Aag2 cells . We used two experimental protocols; in one , the antisera was incubated with the cells for 2h at RT and then infected with DENV ( pretreatment group ) , in the second , antisera and DENV were incubated for 1h at RT and then added to cells ( simultaneous group ) . We used pre-immune sera for a control and also did the same experiment in the Huh-7 human liver cell line as an additional control , as antisera against a mosquito protein should not have an effect on DENV infection in mammalian cells . Infection was analyzed by qRT-PCR analysis at 24 hpi . We found that the antisera against CRVP379 inhibited DENV infection in Aag2 cells at dilutions up to 1/100 ( Fig 6A ) . We also found that incubating the antisera with the cells before DENV infection resulted in a slightly larger reduction in infection levels ( Fig 6A ) . We did not see any reduction in DENV infection in either experimental group using Huh-7 cells ( Fig 6B ) . We then tested the effects of the antisera against CRVP379 on DENV infection in Ae . aegypti . Mosquitoes were fed a mixture of human blood , DENV and either CRVP379 antisera or preimmune sera at 1/10 and 1/100 dilutions . We also used control antisera against two unrelated , GST-tagged mosquito proteins MMP ( AAEL003012 ) and PC ( AAEL011045 ) . On 3 dpi , mosquito MG were dissected and qRT-PCR was done to analyze DENV infection . The antisera against CRVP379 significantly reduced the DENV infection in the mosquitoes at both 1/10 and 1/100 dilution as compared to mosquitoes which fed on the preimmune sera ( Fig 6C ) . The antisera against the control GST-tagged proteins did not reduce DENV acquisition in the mosquito MG tested ( Fig 6D ) .
Flaviviruses are known to modify gene expression in their mosquito transmission vectors during infection . Our previous results showed that infection of Ae . aegypti with either DENV , WNV or YFV , modifies expression levels of at least 405 genes [35] . The study of mosquito genes modified during flavivirus infection may lead to the identification of key vector antiviral mechanisms as well as key factors for interruption of the viral life cycle . One of the genes that we identified as being significantly upregulated during DENV infection was the CRVP379 gene . Cysteine-rich venom protein ( CRVPs ) are members of a large family of cysteine-rich secretory proteins ( CRISPs ) , predominantly found in mammalian males and reptile venom [58] . CRISPs contain characteristic cysteine rich C-terminal domains thought to act as ion channel regulators [58] and are also characterized by their role in proteolytic and defense mechanisms [59] . CRISPs and CRVPs have been described in a broad spectrum of insects and higher vertebrates [59–62] . Recently , Bonizzoni et al found several CRVP genes to have differentially regulated expression during DENV infection of Ae . aegypti , including CRVP379 , which was shown to be upregulated on day 1 and day 14 in the mosquito MG during infection [42] . Here , we found that CRVP379 was the only CRVP significantly upregulated in mosquitoes after infection with DENV . Furthermore , knockdown of CRVP379 protein both in vivo and in vitro was able to reduce viral infection , and we found a significant positive association between the level of CRVP and DENV infection . This indicates that CRVP379 is specifically required for DENV infection of Ae . aegypti , at least in our current studies . The genetic variations between both DENV and mosquito strains likely contributes to differences among various studies , and consistent reporting of these discrepancies warrants further research into these variations along with additional transcriptomic analysis of the impact of DENV infection on mosquitoes . Recent work has shown that another mosquito venom protein , a member of the antigen-5 family ( Ag5 ) , is upregulated in the salivary glands of Ae . aegypti during Chikungunya virus infection [63] . This protein is present in the saliva of several insects and is associated with platelet aggregation inhibition in blood sucking arthropods [46 , 64] . More investigation is needed to determine whether mosquito CRVP proteins and the Ag5 proteins are related or have similar functions during virus infection . Another group of CRVP proteins , the Cysteine-rich secretory proteins , Antigen 5 , and Pathogenesis-related 1 proteins ( CAP ) superfamily , has been descried in the sialotranscriptome of Ae . Aegypti as well as in Culex [49 , 65 , 66] . Previous reports indicate that these genes could be preferentially expressed in the salivary glands of female mosquitos , perhaps suggesting an important role during blood feeding . Our study showed that up-regulation of CRVP379 occurs in both midgut and salivary glands of mosquitoes , and expression in salivary glands increased from day 1 to day 7 during DENV infection . This suggests that CRVP379 may be found in the saliva of DENV-infected mosquitoes . We have previously found that Ae . aegypti and certain Anopheles saliva have the ability to induce an antibody response in humans that can be correlated with the level of exposure to mosquito bites and disease status [67 , 68] . Several insect proteins from the CAP superfamily have also been reported to stimulate mammalian immune responses [69] . Given that CRVP379 has no homologous proteins in humans , we suspect that it will be a potent immunogen if used as a TBV . Many CRVP proteins contain trypsin inhibitor-like ( TIL ) domains found in members of the serine protease inhibitor family [70] and functional sequence analysis confirmed that CRVP379 does contain a TIL domain from amino acids 23–79 . Serine proteases and their inhibitors are known to have very specific interactions , and they play central roles in many cellular processes [71–73] . In addition , both serine proteases and their inhibitors have been shown to have an impact on DENV infectivity in both mammals and mosquitoes [50 , 55 , 74] . As such , we sought to identify the serine protease that CRVP379 potentially bound by using the TAP assay to investigate which mosquito proteins CRVP379 bound during DENV infection . We discovered that CRVP379 interacted with a number of mosquito genes during infection , including histones , ubiquitin and prohibitin . Previous research has suggested that prohibitin may be a receptor for DENV in mosquitoes , as expression levels of this protein correlate with the susceptibility of DENV infection in both Ae . aegypti and Ae . albopictus cell lines [57] . Prohibitin is a protein pervasive expressed and highly conserved in eukaryotic cells [75] and has been previously described as an inhibitor of cell proliferation [76] . Prohibitin is found in several cellular compartments including nucleus , mitochondria and cytoplasm [57] . Furthermore , a recent report shows that Cry4B , one of the major insecticidal toxins produced by Bacillus thuringiensis israelensis , co-precipitates and co-localizes with prohibitin in Ae . aegypti larva midgut , and this interaction is able to reduce DENV infection under physiological conditions [77] . These findings suggest that the inhibition of proteins that interact with viral receptors may potentially block mosquito infection . Additionally , several proteins have been reported to bind prohibitin conferring resistance to bacteria phagocytosis [78] as well as cell surface expressed binding protein [79] . In DENV infection , it has been suggested that prohibitin interacts directly at the cell surface with the viral envelope protein . Our current work shows that CRVP379 is able to interact with several other mosquito proteins including prohibitin , suggesting that CRVP379 may be involved in virus cell entry along with other putative roles . In spite of decades of effort , there are currently no approved DENV vaccines available . A recent study with a live-attentuated tetravalent DENV vaccine developed by Sanofi Pasteur has demonstrated partial protection against DENV [22] and shows promising results , though efforts continue to develop vaccines that will confer full protection . A vector-based vaccine would nicely complement these efforts at traditional vaccine development and could contribute as an additional strategy to combat the increasing global spread of DENV . The development of vaccines targeting either a pathogen or vector protein to prevent transmission to human hosts is considered essential to the eradication of many emerging tropical diseases , including malaria . Transmission-blocking vaccines ( TBVs ) are currently being developed and have been shown to be successful at preventing malaria infection of Anopheles mosquitoes ( 12–15 ) . One of these , a TBV developed against the Plasmodium protein Pfs25 , was able to prevent the transmission of malaria from infected mice to naïve mosquitoes ( 12 , 13 ) . Another group found that vaccinating mice with the mosquito protein serpin-2 prevented the transmission of Plasmodium berghei to a naïve group of mosquitoes ( 16 ) . In addition , an arthropod-specific TBV based on the outer surface protein A ( OspA ) of Borrelia burgdorferi , the causative agent of Lyme disease , has been shown to protect mice from spirochete infection ( 17 ) . Proteins of the sand fly have also been used successfully as TBVs to prevent the transmission of Leishmania ( 18 ) . Dengue virus is transmitted to humans in saliva during mosquito probing and blood feeding . During this process , mosquitoes take in host factors contained in the blood including host antibodies , complement proteins and immune cells that remain active for several hours post-feeding [80 , 81] . Previous studies have shown that the presence of antibodies against mosquito proteins are able to disrupt mosquito infection and transmission of pathogens [82 , 83] . This type of TBV has several advantages over a TBV targeting pathogen antigens , including the ability to target a conserved molecule among vector genera and that the targeted genes may also affect mosquito survival in nature . Recently , Cheng et al demonstrated that antibodies against mosquito C-type lectin proteins were able to block DENV infection in Aedes mosquitoes [34] . Their data strongly suggested that a TBV targeting DENV acquisition in mosquitoes is possible and may be close at hand . Our results inhibiting DENV in Aedes using antisera targeting CRVP379 protein showed a similar reduction in viral infection and suggests that CRVP379 may also be a viable target for the development of a TBV . Importantly , CRVP379 has no homolog in humans and extremely low sequence identity to any protein in the human proteome . This means there should not be any off-target immune reaction targeting self if CRVP379 were to be used to stimulate antibody production in humans . In the present study , we identified a mosquito protein that was required for DENV infection in mosquito cells , CRVP379 . We showed a correlation between this protein and DENV infection levels in vitro and in vivo . The interaction between CRVP379 and prohitibin , a putative viral receptor in mosquitoes , may be the mechanism behind the requirement for infection . In addition , antiserum against CRVP379 protein was able to significantly inhibit DENV acquisition in Ae . aegypti . Given that the CRVP379 protein was also upregulated in the mosquito during infection with WNV and YFV , it stands to reason that a TBV developed against this protein may act to block acquisition and transmission of multiple , globally important flaviviruses . We have also been able to detect an antibody response against CRVP379 in human serum samples , indicating that the protein is immunogenic . We are currently designing studies to correlate levels of these antibodies with putative protection against dengue virus infection and disease severity upon infection .
The Aag2 Ae . aegypti cell line ( ATCC , VA ) was used for transfection and infection studies . The cells were grown at 30°C and 5% CO2 in DMEM supplemented with 10% heat-inactivated fetal bovine serum ( Gemini , CA ) , 1% penicillin-streptomycin and 1% tryptose phosphate broth ( Sigma , MO ) . Dengue virus stock was grown in C6/36 Ae . albopictus cell line using the same media . The dengue strain used was DENV-2 New Guinea C . Cells were infected at an m . o . i . of 1 . 0 , virus was allowed to propagate for 6–8 days , supernatant was removed , spun down and virus stock was stored at -80°C until use . S1 Fig provides a complete list of the siRNA molecules used in our in vitro knock-down studies . Dharmafect4 reagent ( Dharmacon , ) was used to transfect the siRNA into the Aag2 cells according to manufacturer’s instrucitons . For gene knockdown in live mosquitoes , dsRNA was produced from 500bp coding regions of either Ae . aegypti CRVP379 , Ae . aegypti prohibitin or GFP . Briefly , PCR was used to produce a DNA template with T7 overhangs that was then used with the Ambion Megascript kit to produce the dsRNA molecules . The dsRNA was transfected into mosquitoes as described . The Rockefeller strain of Ae . aegypti were infected by blood-feeding , using 400 μL of DENV-infected C6/36 cell supernatant added to 1 mL serum-inactivated human donor blood ( The Blood Center , New Orleans , LA ) . Mosquitoes were fed for 20 minutes at room temperature using a hemotek feeder and maintained in groups of 10 at 30°C , 80% humidity . Mosquitoes were supplied sucrose water as a source of dietary sugar . At the conclusion of experiments , mosquitoes were briefly washed in 70% ethanol and then rinsed in sterile PBS . Organs were dissected in sterile PBS and transferred to Eppendorf tubes separately . Mosquito organs were stored in PBS with protease inhibitors for protein assays and homogenized in RLT buffer ( Qiagen , CA ) for gene expression assays . RNA was isolated from infected Ae . aegypti mosquitoes on Days 1 , 2 , 7 and purified using RNeasy kit ( Qiagen , CA ) according to manufacturer’s instructions . The quantitative RT-PCR ( qRT-PCR ) analysis was done using the QuantiFast kit according to manufacturer’s instructions ( Qiagen , CA ) . Oligos for the qRT-PCR reactions were: DENV envelope: F: 5’-CATTCCAAGTGAGAATCTCTTTGTCA-3’ R: 5’-CAGATCTCTGATGAATAACCAACG-3’; Ae . aegypti Actin: F: 5’-GAACACCCAGTCCTGCTGACA-3’ , R: 5’-TGCGTCATCTTCTCACGGTTAG-3’ DNA plasmids were injected according to our published whole-body transfection method [84] . Briefly , Cellfectin II ( Invitrogen , CA ) was mixed with S2 Schneider’s medium at a 1:1 ratio and then keep at RT for 10 min . Plasmid DNA was combined with this mixture and incubated at RT for 30 minutes before thoracic microinjection into Aedes aegypti . Mosquitoes were injected with 500ng plasmid/300 nL solution . The dsRNA was injected as previously described and as indicated in the figure legends . Aag2 Ae . aegypti cells were infected with DENV at an MOI of 0 . 1 . At 24 hours post-infection , infected cells and control cells were fixed in 4% paraformaldehyde for 20 min at RT , washed with PBS ( - ) and then stained for infection using antibodies against CRVP379 ( L2 Diagnostics , CT ) , DENV envelope gene ( Millipore , MA ) and/or prohibitin ( Abcam , MA ) . The antibodies were diluted in 1% BSA at 1/250 and cells were incubated for 20 minutes at RT . Any secondary antibodies used were standard ( anti-mouse or anti-rabbit TRITC and FITC , DAPI and phalloidin ) , and were diluted according to manufacturer’s instructions . Infection was visualized using fluorescent microscopy , equipment and specifics can be found in figure legends . All plasmids were prepared using Qiagen miniprep kits ( Valencia , CA ) after standard transformation into DH5α competent bacterial cells . The tagged virus protein nTAP expression plasmids were made by cloning the coding regions for each viral protein into the N-terminal TAP plasmid ( Stratagene , CA ) . Solutions were run on a 4–12% SDS-PAGE gel for 1 . 5 h at 15 milliamps per gel ( unless figure legend indicates otherwise ) . The proteins were then transferred to PVDF membrane . The membrane was blocked with 5% milk in 1% TBST for 1h at RT and then incubated with the appropriate primary antibody overnight at 4°C . The membrane was washed and then incubated with the appropriate horseradish peroxidase secondary antibody for 1h at RT . The protein blots were incubated with ECL substrates ( Amersham , NJ ) for 5 min at RT and then detected on Kodak film . Antisera production is described below and prohibitin antibody was purchased from Santa Cruz . The expression plasmids were made from pAc5 . 1/V5-His A vector ( Invitrogen , CA ) and cloning was done using PCR along with gene-specific primers as previously described [85] . We used the Qiagen mini-prep kit to isolate DNA from bacterial cultures after transforming DH5-alpha cells . Plasmids were transfected into cells using Effectene ( Qiagen , CA ) according to manufacturer’s instructions . Briefly , for a 10 cm2 plate , 10 μg of DNA was mixed with 500 μL buffer EC and 32 μL enhancer was added . This was allowed to incubate for 5 min on the benchtop . Then , 30 μL Effectene reagent was added and the solution vortexed briefly . After 10 min incubation , the solution was added to the cells . The TAP assay was used to identify mosquito cell proteins that interacted with CRVP379 protein . All steps were done at 4°C to maintain the protein interactions . The cell or tissue lysates were applied to streptavidin resin , incubated at 4°C for 2 h , washed , and bound proteins eluted off . A second purification step was done with calmodulin resin and the proteins were boiled off into PBS ( - ) . The eluted proteins were analyzed at the Yale University W . M . Keck Foundation core facility . The eluate was subjected to trypsin digestion followed by LC/MS-MS ( liquid chromatography and mass spectometry ) for peptide sequencing and identification using the recently completed Aedes aegypti mosquito genome [47] . Putative mosquito proteins were identified via amino acid sequence identity to both known mosquito proteins and their mammalian counterparts using the BLAST software on the NCBI website . Mosquito proteins found to bind the tags alone as well as proteins found to bind tagged green fluorescent protein were eliminated as putative interacting partners . A recombinant protein consisting of residues 21–128 of CRVP379 was synthetically cloned into the pGEX-6p-1 expression vector ( GE Life Sciences ) into the BamH1 and Xho1 sites . The recombinant plasmid was transformed into Rosetta DE3 pLys2 E . coli cells . GST-CRVP379 protein was purifed from the bacteria cells as inclusion bodies by passing the E coli cells through a cell disruptor at 20 psi of pressure . Inclusion bodies were used to immunize rabbits to generate polycolonal antisera ( CoCalico Biologicals , Reamstown , PA ) . Prior to immunization , rabbits were bled to obtain pre-immune control sera . Serum samples were coated onto a 96-well ELISA plate ( Thermo Fisher Sci , MA ) and incubated overnight at 4°C . The plate was blocked with 1% BSA in PBS ( - ) and incubated with recombinant CRVP for an hour at RT . The proteins were washed off , antibodies were added for 30 min at RT , washed off and secondary-HRP was added for 30 min at RT , washed off and TMB substrate was added for 20 min at RT . Stop solution was added and the O . D . of the wells was read at 450 nm . | Dengue virus ( DENV ) is responsible for serious human disease worldwide and the World Health Organization estimates that over 2 billion people are at risk for disease . There are no vaccines or specific antiviral medications currently available for DENV infection . DENV is transmitted to humans by infected mosquitoes during feeding and probing . By examining the effects of virus infection on gene expression , and interactions between virus and vector , we may be able to find new targets for prevention and treatment . Here we look at a mosquito protein , CRVP379 , whose gene expression was highly increased during DENV infection in mosquitoes . We show a requirement for CRVP379 during DENV infection in the mosquito and a correlation between the levels of CRVP379 and levels of infection . Our results indicate that the protein may be acting with a putative DENV receptor in the mosquito , prohibitin protein . These data also suggest that blocking CRVP379 function may be used to block DENV infection in the mosquito . | [
"Abstract",
"Introduction",
"Results",
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"Methods"
] | [] | 2015 | Dengue Virus Infection of Aedes aegypti Requires a Putative Cysteine Rich Venom Protein |
DNA methylation and demethylation are opposing processes that when in balance create stable patterns of epigenetic memory . The control of DNA methylation pattern formation by replication dependent and independent demethylation processes has been suggested to be influenced by Tet mediated oxidation of 5mC . Several alternative mechanisms have been proposed suggesting that 5hmC influences either replication dependent maintenance of DNA methylation or replication independent processes of active demethylation . Using high resolution hairpin oxidative bisulfite sequencing data , we precisely determine the amount of 5mC and 5hmC and model the contribution of 5hmC to processes of demethylation in mouse ESCs . We develop an extended hidden Markov model capable of accurately describing the regional contribution of 5hmC to demethylation dynamics . Our analysis shows that 5hmC has a strong impact on replication dependent demethylation , mainly by impairing methylation maintenance .
DNA methylation is an epigenetic modification essential for the regulation of genome stability and genome function [1 , 2] . During development the distribution of DNA methylation is under strict control to maintain a temporal and cell type specific persistence of epigenetic information [3] . The methylation of DNA in mammals is restricted to the C-5 position of cytosine and is predominantly found in a CpG sequence context [4 , 5] . Our current knowledge suggests that DNA methylation patterns ( 5mC ) are mainly established by DNA methyltransferases Dnmt3a and Dnmt3b [3 , 6] . The palindromic nature of a CpG sequence in which 5mC occurs allows a recognition of the 5mC hemimethylated state after semi-conservative replication and a copying of the parental methylation pattern to the newly synthesized DNA strand ( see Fig 1 ) . A series of experiments revealed that Dnmt1 in conjunction with Uhrf1 are responsible for this copying also referred to as maintenance methylation . Dnmt1 and Uhrf1 have a high preference for binding to hemimethylated CpG substrates [7–9] . Together they assure the maintenance symmetric CpG methylation patterns after each round of replication . In contrast to Dnmt1 , Dnmt3a and Dnmt3b act on hemi- as well as unmethylated CpGs and their activity is not coupled to DNA replication . Both enzymes are highly regulated and regarded as the main enzymes to establish new methylation patterns and are therefore classified as de novo DNA methyltransferases . However , recent data shows that Dnmt1 may also de novo methylate unmethylated dyads and that Dnmt3a and Dnmt3b are also involved in reestablishing ( thus “maintaining” ) complete methylation patterns at certain loci [10] . In summary , the persistence of methylation patterns is controlled by a coordinated action of de novo and maintenance functions of all three enzymes . Besides the establishment and the persistence of methylation its removal is also of great biological importance . Demethylation events can occur on a local scale in case of individual gene activation but also on a global genome wide level like in the early zygote and the germ line , where genomes are reprogrammed for new developmental functions [11 , 12] . In both cases demethylation can be achieved either by an active mechanism ( direct removal ) , a passive replication-dependent loss or a combination of both . Recent findings suggest that the oxidation of 5mC modulates active and passive demethylation processes . 5-hydroxymethyl cytosine ( 5hmC ) is generated by oxidation of 5mC in an enzymatic reaction catalyzed by the oxoglutarate- and Fe ( ii ) -dependent ten-eleven trans-location dioxygenases ( Tet1 , Tet2 , and Tet3 ) [13] . Tet enzymes also catalyze further oxidations to 5-formylcytosine ( 5fC ) and to 5-carboxycytosine ( 5caC ) , which have been shown to promote processes of active demethylation [14–16] . Still 5hmC is the most prevalent oxidation type and widely discussed to having an influence on DNA methylation pattern stability in dividing cells . 5hmC not only alters the chemical properties but also the biological recognition of the base . Dnmt1 binds to 5hmC with a much lower efficiency than to 5mC . This may impair the replication dependent copying of 5mC [17] . In mouse ES cells ( mESCs ) , in the early mouse embryo and in the early germ cells DNA demethylation stability is influenced by the conversion of 5mC into 5hmC . Disturbances or depletion of Tet enzymes in these phases result in massive changes of 5hmC and lead to developmental consequences [18–20] . These findings indicate that the controlled alteration of DNA methylation patterns across DNA replications is dependent on 5hmC . However , the underlying mechanisms are still under debate . Mouse ESCs are a well established system to study these effects as they rapidly lose DNA methylation on a genome wide scale when the cells are transferred from conventional serum medium containing LIF ( primed state ) to a synthetic 2i medium [21 , 22] . This loss of 5mC is coupled to a temporary gain of 5hmC . In our study we follow the dynamic of DNA demethylation in mESCs over time and DNA replications using a novel combination of hairpin sequencing with bisulfite sequencing ( BS ) and oxidative bisulfite sequencing ( oxBS ) . This method allows us to determine the methylation status of both complementary DNA strands at individual chromosomes and the status of 5hmC levels at given time points [10 , 23 , 24] . We propose a stochastic model that describes the evolution of both methylation and hydroxylation patterns over time . Our model allows that methylation can be lost due to cell replication and methyl groups can be added due to either maintenance or de novo enzyme activity [10 , 25] . In addition , we assume that all methylated sites can be hydroxylated . Based on these assumptions we define a hidden Markov model ( HMM ) for each data set and construct likelihood functions on the basis of the two sequencing methods . The combination of the two likelihoods allows us to derive estimations for the levels of ( hydroxy- ) methylation based on observations at four different time points . Finally , we determine unknown parameters of the model , i . e . , methylation and hydroxylation efficiencies as well as the initial distribution of the hidden states . Despite its simplicity , the model accurately predicts the evolution of the ( hydroxy- ) methylation patterns and allows us to test different assumptions about the activities of the involved enzymes .
Currently no comprehensive data are available allowing to model the fate of 5hmC at a single base resolution level . Therefore , extending the method described in Fitz et al . 2014 and Arand et al . [10 , 21] we established a workflow enabling us to produce such data . To obtain base resolution information of the modification status we apply hairpin bisulfite sequencing on DNA samples split into oxidative ( oxBS-Seq ) and non oxidative standard bisulfite reaction ( BS-Seq ) data sets . The use of the hairpin linker strategy allows us then to determine the levels of 5hmC and 5mC on both DNA strands [23] and to determine the methylation status ( hemimethylated , unmethylated or fully methylated ) at each individual CpG dyad within the sequenced loci at single molecule resolution . To obtain a sufficient coverage ( >1000x ) per CpG we use very deep NGS based sequencing of selected loci . The deep sequencing enables us to determine accurate rates and error rates for each modification . To cover larger parts in the genome we included the analysis of mobile elements which occur in multiple identical copies across the genome and to which we refer as “repetitive elements” . In fact our analysis covers about 91% of all annotated IAP ( IAPLTR1a_mM ) ( N = 1635 ) , 20% of L1md_A ( N = 3287 ) , 12% for L1md_T ( N = 2784 ) and 30% of MuERVL ( N = 725 ) . In this case the >1000x coverage has to be seen as the aggregate of about a 5x coverage of each individual copy of a given repetitive element . Fig 2 outlines the main experimental steps of the procedure . In the first step genomic DNA is digested using restriction enzymes which generate cuts close to the gene/locus selected for methylation analysis . In a following reaction both DNA strands are ligated to a back-folding “hairpin”-oligonucleotide . Next the DNA is unfolded and subjected to a bisulfite or oxidative bisulfite treatment followed by a locus specific PCR amplification . PCR primers contain Mi-Seq ( Illumina ) compatible extensions to perform deep ( paired end 2x300bp ) sequencing ( up to 10K/product ) . Sequencing data are processed using our in house software BiQ-HT and a python script . In the bisulfite only reaction 5mC and 5hmC remain as cytosines , while in the oxidative bisulfite reaction 5hmC is converted to uracil/thymine . Each individual sequence covers the hairpin linker which contains modified and unmodified cytosines at known positions . This allows us to monitor the efficacy of bisulfite and oxidative bisulfite reactions per molecule ( note that all unmodified cytosines are converted to thymines ) and calculate exact error rates by dividing the number of unconverted bases by the total number of analyzed cytosines . Additional information about the protocol is given in S1 Text together with reference- , primer- and linker-sequences . Our model considers a CpG site ( alternatively dyad ) over time and describes its state as a ( discrete time ) Markov chain { X ( t ) , t ∈ N } taking values in S = { u , m , h } 2 . Each state ( s1 , s2 ) ( for s1 , s2 ∈ {u , m , h} ) encodes whether the upper strand ( lower strand ) is unmethylated ( u ) , methylated ( m ) or hydroxylated ( h ) . For instance , in state ( s1 , s2 ) = ( u , h ) the upper strand is unmethylated and the lower strand is hydroxylated . We will often simply write ( s1 s2 ) instead of ( s1 , s2 ) . The time parameter t corresponds to the number of cell divisions and the state transitions are triggered by three consecutive events: cell division , methylation and hydroxylation . The corresponding transition probability matrices are D ( t ) , M ( t ) , and H ( t ) , respectively . Thus , the combined transition probability matrix of X is defined as P ( t ) = D ( t ) · M ( t ) · H ( t ) , with entries Pij ( t ) that equal the probabilities that given X ( t ) = i = ( s 1 s 2 ) , the next state is X ( t + 1 ) = j = ( s 1 ′ s 2 ′ ) for all i , j ∈ S . Note here we assume that hydroxylation occurs after methylation to ensure that between two cell divisions a transition from u to m and then to h is possible . Moreover , note that we allow P ( t ) to change over time , so that we capture the case that the ( hydroxy- ) methylation efficiencies do not remain constant over time . In the sequel we give a detailed description of D ( t ) , M ( t ) , and H ( t ) . For a formal definition of the matrices , we refer to S1 Text .
Previous genome wide analyses showed a high or moderate decrease of DNA methylation in ESCs transferred from serum into 2i medium [21 , 22] . Furthermore , it was shown that the oxidation of 5mC to 5hmC is likely to contribute to this DNA demethylation [21] . The goal of our work was to develop a model which describes the 5hmC dependent molecular mechanisms that cause this loss of DNA methylation upon consecutive rounds of replication . For the modeling we generated an ultra deep DNA methylation data set of selected loci in mouse ES cells ( ESCs ) collected at defined time points after cultivation in 2i . For our analysis we chose five multicopy , repetitive elements , IAPs ( intracisternal A particle ) , L1mdA and L1mdT ( both Long interspersed nuclear elements ) , MuERVL ( Murine endogenous retrovirus ) and mSat ( major satellite ) , as well as four single copy loci in the genes Afp , Snrpn , Ttc25 and Zim3 . It was already known that some of these repetitive elements are subject to demethylation . Ttc25 and Zim3 where previously shown to exhibit a less pronounced loss of methylation in the absence of Tet1/Tet2 in 2i medium . [21] . Imprinted genes such as Snrpn were shown to be “resistant” to demethylation in 2i . Deep locus specific DNA methylation profiles were generated from mESCs grown in conventional serum/LIF medium ( day0 ) and after their transfer and cultivation into 2i medium for 24h ( day1 ) , 72h ( day3 ) and 144h ( day6 ) , respectively . During this period the ESCs undergo a maximum of six cell divisions ( as inferred from cell densities ) . For each time point and locus we performed consecutive bisulfite and oxidative hairpin bisulfite reactions using high coverage Mi-Seq sequencing ( see Methods section ) . Following sequence processing ( alignment , trimming , QC filtering ) we obtained two data sets for each locus: one describing the combined 5mC+5hmC status ( BS-Seq ) and one describing the 5mC status alone ( oxBs-Seq ) . The hairpin refolding of sequences then let us determine the accurate double stranded CpG methylation status at a given locus ( hemi- , fully- or unmethylated ) . With this data we used our HMMs ( described in the Methods section ) to estimate the amount of 5mC and 5hmC in these loci and to predict the efficiencies of maintenance methylation , de novo methylation and hydroxylation over time . In our modeling we analyzed both aggregated and single CpG behavior for each locus . Both average and single CpG modeling gave similar results . The single CpG data , summarized in the supplementary information ( see S3 and S4 Figs ) , gave slightly increased confidence intervals compared to averaged data . In our further analysis we use averaged data for model interpretation . Using the estimated values of the model’s unknown parameters we could predict the probabilities of the observable states and compare them to the measured data at various time points . The model accurately describes the dynamics for all loci except for some underestimations of two states CC and TT for oxBs in Ttc25 and Zim3 , respectively . ( Fig 5 and S1 Fig ) . Fig 6 shows the probabilities of the hidden states in L1mdT , mSat , Afp , and Zim3 , where the parameters are chosen according to the results of the maximum likelihood estimation . The left bar diagram shows the probabilities of all fully methylated ( mm ) , hemimethylated ( um and mu ) and unmethylated ( uu ) sites , as well as the total amount of the hydroxylated CpG dyads , i . e . , those containing at least one 5hmC . The detailed level of all hydroxylated sites is depicted in the right diagram . From previous experiments it was known that 5hmC levels initially increase during cultivation in 2i [21 , 22] . However , precise levels had not been determined per locus . Our analysis provides the first accurate locus specific determination of 5hmC changes . Our estimation of 5hmC confirms an initial increase of hydroxylated cytosines over time for most loci besides L1mdA and Snrpn . L1mdA shows a low level of 5mC and 5hmC , which only slightly decreases in 2i . Snrpn also shows a relatively low level of 5mC and a non significant amount of 5hmC , which do not change in 2i over time ( S2 Fig ) . The highest hydroxylation levels are found in the single copy genes Zim3 and Afp with a maximum level of 0 . 30 and 0 . 20 . For Afp , mSat , IAP and MuERVL ( see Fig 6 and S2 Fig ) , the maximum hydroxylation level is seen at day6 , while for L1mdT , Ttc25 and Zim3 at day3 . The latter can be explained by the particularly low 5mC levels between day3 and day6 in these loci which naturally reduces the potential substrates for the Tet enzymes . However , the level of 5hmC ( orange bar in Fig 6 and S2 Fig , left ) relative to the total modification level ( 5hmC + 5mC ) ( red , orange and green bars ) , becomes maximal on the sixth day for all loci that show a loss of 5mC . This points towards an increasingly important role of 5hmC in the loss of methylation over time . Indeed , the probability p ( see HMM subsection ) that a 5hmC site is not recognized by Dnmt1 ( or the Dnmt1/Uhrf1 complex ) , which corresponds to states ( hu ) and ( uh ) in the model , is estimated to be 1 with very small standard deviations for all the loci that show significant 5hmC levels . We estimated smaller values for p only for those loci where hydroxylation is nearly absent ( mSat , MuERVL , Snrpn ) . In Fig 7 we plot the functions μm ( t ) , μd ( t ) , η ( t ) and λ ( t ) over time together with their estimated standard deviations . Note that the estimated standard deviations of all the efficiencies are very small ( maximum half width of all confidence intervals is 0 . 031 ) . For the exact estimates and their standard deviations see S3 and S4 Tables . From the above efficiencies we can deduce the impact of de novo methylation activity on the hemimethylated dyads as the difference between the total methylation efficiency and maintenance methylation , i . e . , λ ( t ) - μ m ( t ) = μ ¯ m ( t ) · μ d ( t ) ( see Fig 7 ) . Our data indicates that persistence of DNA methylation at Afp , mSat , IAP and MuERVL elements clearly depends also on de novo enzymes acting on hemimethylated CpGs . For each efficiency , we performed a statistical test with a confidence level of 1% for the null hypothesis that the slope of the corresponding linear function is zero , i . e . , that the efficiencies are constant over time ( see in addition S1 Text ) . Furthermore , to eliminate the possibility of overfitting due to the linear assumption , we performed leave-one-out cross-validation ( LOOCV ) to estimate the test error of our model with constant efficiencies against a linear model . Results in S5 Table show that the linear assumption improves the prediction up to 38 . 3% . Further tests concerning the sensitivity of the model w . r . t . the parameters showed that the model is also sufficiently robust ( see S1 Text ) . Overall , the estimation of the efficiency functions reveals some common and some locus specific features that accompany the DNA demethylation dynamics over time in 2i . As a common feature we observe that the total methylation on hemimethylated sites , λ ( t ) , decreases over time in all examined loci but at different rates . Along with this decrease we observe also a drop of de novo methylation activity at all loci besides Ttc25 and Zim3 . In contrast , hydroxylation activity increases for most loci over time ( except for Snrpn ) . Interestingly , the largest increase of η ( t ) occurs in L1mdT and the two DMRs in the genes Ttc25 and Zim3 , where we also observe low or even total absence of de novo activity . On the other hand , a weaker hydroxylation activity in mSat , as well as IAP and MuERVL ( S2 Fig ) , is accompanied by a strong decrease of μd ( t ) in the same loci , while in Afp both de novo methylation and hydroxylation show a moderate decrease and increase , respectively . At last , maintenance methylation seems to differ among loci . For all repetitive multicopy loci and Afp maintenance activity remains nearly constant while for Ttc25 and Zim3 it shows a significant decrease . For the imprinted Snrpn locus , where the methylation level remains constant , our model accurately predicts the apparently constantly high maintenance efficiency of 1 . 0 . Altogether , these findings point towards a major impairment of maintenance methylation by 5hmC . Additionally , for each locus this impairment is modulated by a distinct combination of decreasing ( e . g . Dnmt3a , b ) or increasing ( e . g . Tet ) activities in a locus specific manner . Some of the locus specific differences may also have their origin in the particular methylation and ( hydroxy- ) methylation status present in serum/LIF before the shift into 2i .
The goal of our study was to investigate the role of 5hmC in the process of progressive DNA demethylation at single copy and mulitcopy loci across the genome . As a model system we used the DNA of ES cells grown under conditions where the cells experience a genome wide reduction of DNA methylation [21 , 22] . Using time dependent comparative bisulfite and oxidative bisulfite hairpin sequencing data we generated two HMMs: one that represents the dynamics of total modifications ( 5mC and 5hmC in BS ) and the other only representing the 5mC levels ( in oxBS ) . The comparison allowed us to accurately determine the amount and changes of 5hmC at certain genomic loci , to estimate the transient distribution of both 5mC and 5hmC in the DNA and to compute statistically reliable estimates for the efficiencies of maintenance and de novo methylation , as well as for hydroxylation over time . Our first finding is that 5hmC changes over time and can be modeled along with the overall changes in symmetric DNA methylation at CpGs . Our estimates give us an exact knowledge of 5hmC dynamics , which is congruent with the finding that several Tet enzymes are up-regulated in 2i medium [21 , 22] . The calculation of the hidden state probabilities and the efficiencies of the different enzyme-driven processes show that the 5hmC dependent demethylation rates differ considerably from locus to locus . However , the dynamics of the ( hydroxy- ) methylation levels for the CpGs of the same locus show a certain homogeneity ( see S3 and S4 Figs ) . The second major finding is that loci with an enrichment of 5hmC such as Afp , L1mdT and IAP show higher demethylation rates compared to mSat or Snrpn . Hence , 5hmC containing DNA strands are indeed more likely to lose DNA methylation over time . Our modeling strongly supports the hypothesis that 5hmC is less well recognized by the maintenance methylation machinery ( Dnmt1/Uhrf1 complex ) as indicated by the estimation of the corresponding non-recognition probability p . The accumulation of 5hmC then causes a passive dilution mechanism of CpG methylation with each DNA replication/cell cycle , despite of the fact that the model predicts a constant behavior of maintenance activity in most of the analyzed loci . In ES cells maintained in 2i medium this mechanism appears to be the main driving force for a rapid and linear DNA demethylation . Interestingly , in contrast to the previously shown unchanged mRNA expression of Dnmt1 and Uhrf1 in 2i [21 , 22] we observe a strong decrease of maintenance function for the single copy genes Ttc25 and Zim3 ( see Fig 7 and S2 Fig , red line ) . Since the influence of 5hmC on the maintenance mechanism is reflected by the recognition probability p , the observed decrease is independent of the high 5hmC levels at these loci . This indicates an additional impairment or absence of the maintenance machinery at these loci . However , we cannot exclude the possibility that with the strong decrease in maintenance efficiency our model , at least to some extent , compensates for active demethylation which we cannot capture with our current experimental/model design . Being able to estimate the de novo methylation impact of Dnmt3a/b on hemimethylated sites , the third observation of our model is that all analyzed elements show a compromised de novo methylation activity as an additional factor contributing to an enhanced local DNA demethylation . The predicted behavior for the involved enzymes’ activities appears to follow their relative expression in 2i medium , in which both Dnmt3a and Dnmt3b are clearly down regulated [21 , 22] . Our observations , thus , suggest that the down regulation of Dnmt3a and Dnmt3b activities appears to enhance the 5hmC dependent CpG demethylation . This may be either directly due to a decreased methylation efficiency on hemimethylated sites or due to a lower abundance of the enzymes . In summary , we present a novel HMM method that allows to precisely measure and describe effects related to the influence of 5hmC on the persistence of DNA methylation in the mammalian genome . The modeling allows us to decipher complex DNA methylation patterns and enables us to accurately infer enzymatic activities . In its current form the model already captures a fraction of possible demethylation dynamics and scenarios most likely reflecting many loci in the genome . A genome wide application of our modeling is possible . It comes , though , at the expense of locus specific accuracy since with the existing whole genome hairpin sequencing methods data is difficult to generate and will not reach a sufficient sequencing depth . However , our approach can also be used to accurately model 5hmC dependent methylation dynamics in diseases , e . g . certain cancers and in aging processes of long lived cells . By integrating novel precise sequencing methods , which detect other oxidized modifications the model can be enhanced to additionally capture active demethylation and describe the involved processes . | Oxidation of 5mC by Ten-eleven translocation ( Tet ) enzymes leads to the formation of 5hmC and other higher oxidized forms in the DNA . Several findings indicate that oxidation induces demethylation processes , but the mechanistic contribution of 5hmC to this process remains unclear . Using an innovative combination of 5hmC detection chemistry and high resolution sequencing , we generate data that can be used for a novel hidden Markov modeling approach . This new model for the first time incorporates 5hmC dynamics and allows to test certain scenarios of demethylation mechanisms . Our findings support the conclusion that 5mC oxidation compromises the copying of DNA methylation patterns across generations in ES-cells . | [
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"chromat... | 2016 | The Influence of Hydroxylation on Maintaining CpG Methylation Patterns: A Hidden Markov Model Approach |
In plants , RNA silencing plays a key role in antiviral defense . To counteract host defense , plant viruses encode viral suppressors of RNA silencing ( VSRs ) that target different effector molecules in the RNA silencing pathway . Evidence has shown that plants also encode endogenous suppressors of RNA silencing ( ESRs ) that function in proper regulation of RNA silencing . The possibility that these cellular proteins can be subverted by viruses to thwart host defense is intriguing but has not been fully explored . Here we report that the Nicotiana benthamiana calmodulin-like protein Nbrgs-CaM is required for the functions of the VSR βC1 , the sole protein encoded by the DNA satellite associated with the geminivirus Tomato yellow leaf curl China virus ( TYLCCNV ) . Nbrgs-CaM expression is up-regulated by the βC1 . Transgenic plants over-expressing Nbrgs-CaM displayed developmental abnormities reminiscent of βC1-associated morphological alterations . Nbrgs-CaM suppressed RNA silencing in an Agrobacterium infiltration assay and , when over-expressed , blocked TYLCCNV-induced gene silencing . Genetic evidence showed that Nbrgs-CaM mediated the βC1 functions in silencing suppression and symptom modulation , and was required for efficient virus infection . Moreover , the tobacco and tomato orthologs of Nbrgs-CaM also possessed ESR activity , and were induced by betasatellite to promote virus infection in these Solanaceae hosts . We further demonstrated that βC1-induced Nbrgs-CaM suppressed the production of secondary siRNAs , likely through repressing RNA-DEPENDENT RNA POLYMERASE 6 ( RDR6 ) expression . RDR6-deficient N . benthamiana plants were defective in antiviral response and were hypersensitive to TYLCCNV infection . More significantly , TYLCCNV could overcome host range restrictions to infect Arabidopsis thaliana when the plants carried a RDR6 mutation . These findings demonstrate a distinct mechanism of VSR for suppressing PTGS through usurpation of a host ESR , and highlight an essential role for RDR6 in RNA silencing defense response against geminivirus infection .
Viruses are obligate molecular parasites that have limited coding capacity and depend on host resources to survive . To successfully infect their hosts , viruses have evolved strategies to exploit cellular functions for multiplication , as well as mechanisms to evade or subvert elaborate host defense mechanisms . In plants , RNA silencing , also called post-transcriptional gene silencing ( PTGS ) , represents an important antiviral immunity mechanism that operates in a sequence-specific manner . Double-stranded RNAs ( dsRNAs ) derived from virus replication products serve as pathogen-associated molecular patterns for defense recognition and are processed into primary small interfering RNAs ( siRNAs ) of 21 to 25 nucleotides ( nt ) by ribonuclease III-like enzymes , termed DICER-like proteins ( DCLs ) in plants . The siRNAs then interact with members of the ARGONAUTE ( AGO ) family of proteins to form RNA-induced silencing complexes ( RISCs ) , which use the siRNAs as guides to target cognate viral RNAs for cleavage . In plants , fungi and nematodes , viral RNAs or their cleavage products can serve as templates for host RNA-dependent RNA-polymerases ( RDRs ) to produce dsRNAs that subsequently generate secondary siRNA by DCLs cleavage [1] , [2] . Two RDRs have been implicated in plant virus defense [2]–[4]: Tobacco RDR1 is induced by salicylic acid or virus infection and functions to restrict systemic spread of Tobacco mosaic virus ( TMV ) and Potato virus X ( PVX ) [5]; in Arabidopsis thaliana , efficient RNA silencing also requires RDR6 and its dsRNA-binding partner , Suppressor of Gene Silencing 3 ( SGS3 ) , to amplify viral siRNAs that allow plants to mount effective defense response against virus infection [6]–[10] . Likewise , Nicotiana benthamiana plants with reduced RDR6 levels develop hypersusceptibility to some RNA viruses [8] , [11]–[14] , emphasizing the important role of RDR6 in antiviral defense . Despite the potency of RNA silencing in antiviral defenses , plant viruses still systemically infect diverse plant species and cause diseases . Most , if not all , plant viruses have evolved mechanisms to counterattack RNA silencing by encoding proteins termed viral suppressors of RNA silencing ( VSRs ) [1] , [15] , [16] . Various VSRs often share little sequence similarity and target different steps in the RNA silencing pathway . A common strategy employed by some VSRs is to bind to dsRNA or siRNA duplexes , thereby preventing the sensing and dicing of dsRNA trigger , or interfering with the incorporation of siRNA into RISC [17]–[20] . Other suppressors directly target component of dicing machinery . One such example is P6 of Cauliflower mosaic virus ( CaMV ) , which interferes with viral siRNAs processing by interacting with dsRNA-binding protein 4 , an essential partner of the antiviral DCL4 [21] . Alternatively , some VSRs , such as 2b of Cucumber mosaic virus ( CMV ) , p38 of Turnip crinkle virus ( TCV ) and P0 of poleroviruses , either inhibit AGO functions [22] , [23] , or target AGO proteins for degradation [24] , [25] . Several studies have shown that some VSRs suppress PTGS indirectly by affecting cellular regulators of the small RNA pathway . For instance , p19 of Cymbidium ring spot virus represses the AGO1-directed antiviral response by specific induction of miR168 , which in turn , negatively regulates AGO1 mRNA levels [26] . Suppression of PTGS by HC-Pro of Tobacco etch virus ( TEV ) is mediated by the tobacco calmodulin-like protein rgs-CaM , the first identified endogenous suppressor of RNA silencing ( ESR ) [27] . In addition , an ethylene-induced transcription factor RAV2 in Arabidopsis is needed for suppression of primary RNA silencing by two unrelated VSRs , namely HC-Pro of Turnip mosaic virus ( TuMV ) and p38 of TCV . Although RAV2 itself has not been shown to directly suppress RNA silencing , it is necessary for TuMV HC-Pro to induce the expression of several putative ESRs including AtCML38 ( Calmodulin-like protein 38 ) , a closely related homolog of rgs-CaM in Arabidopsis [28] . Calmodulins or calmodulin-like proteins are small acidic proteins that contain varied numbers of the ‘EF-hand’ motif . These proteins sense and decode cellular calcium ( Ca2+ ) cation signals through high-affinity binding of their EF-hand domains to Ca2+ , which induces a conformation change in the proteins and exposes their hydrophobic surfaces . The activated calmodulins then interact with many downstream target proteins to modulate their activities in diverse cellular functions . Alternatively , some of the calmodulin/Ca2+ complexes may function directly as transcription regulators to control the expression of downstream effectors [29] , [30] . Plants have evolved a diversity of calmodulins and calmodulin-like proteins that play a vital role in response to development cues and environmental stimuli [29] . The identification of the tobacco rgs-CaM as an ESR indicates that calmodulin-like proteins are involved in fine-tuning the functions of the RNA silencing pathway , which has also been implicated in developmental regulation and stress responses [31] . The Geminiviridae is a large family of plant viruses that cause economically important crop diseases worldwide . Geminiviruses contain circular , single-stranded DNA ( ssDNA ) genomes encapsidated in twinned icosahedral particles . [32] . Although ssDNA viruses have no dsRNA phase in their replication cycle , transcripts produced by geminiviruses can both induce and be targeted by cytoplasmic PTGS ( reviewed in [33] , [34] ) . Geminivirus-derived small RNAs of 21 , 22 , and 24 nt have been detected in infected hosts and all four DCLs in Arabidopsis have been implicated in the production of geminiviral siRNAs [35] . Studies of virus induced gene silencing ( VIGS ) triggered by Cabbage leaf curl virus ( CaLCuV ) , a member of the Begomovirus genus belonging to the Geminiviridae family , have revealed requirements for RDR6 and SGS3 in CaLCuV-induced RNA silencing of an endogenous gene [36] . RDR6 and SGS3 are thought to convert geminivirus-derived transcripts into dsRNAs that induce RNA silencing [36] . Consequently , several proteins encoded by geminiviruses are able to suppress PTGS ( reviewed in [33] ) , although the mechanisms in many cases are not fully understood . Betasatellites represent novel DNA molecules that are associated with some monopartite begomoviruses in the Geminiviridae family including Tomato yellow leaf curl China virus ( TYLCCNV ) [37] , [38] . While able to infect their hosts alone , these monopartite begomoviruses are often incapable of inducing typical symptoms , and require betasatellites for accumulation to high titers and elicitation of disease symptoms [39] , [40] . The betasatellite contains a single open reading frame ( βC1 ) that encodes a symptom determinant [41]–[44] . Earlier studies have shown that βC1 proteins are potent PTGS suppressors [43]–[49] , but their modes of action have not been elucidated . In the present study , we have demonstrated that the N . benthamiana calmodulin-like protein , designated “regulator of RNA silencing” ( Nbrgs-CaM ) is up-regulated by βC1 of Tomato yellow leaf curl China betasatellite ( TYLCCNB ) and that Nbrgs-CaM is required for both PTGS suppression and symptom induction by TYLCCNB βC1 . We also have determined that Nbrgs-CaM suppressed PTGS likely acting through repressing the expression of NbRDR6 , an important component in the anti-geminiviral RNA silencing pathway . These data , together with previous findings with TEV HC-Pro [27] , suggest that cellular regulators of RNA silencing can be subverted by evolutionarily divergent plant viruses to counteract antiviral defenses .
To gain more insights into the mode of action of TYLCCNB βC1 in PTGS suppression , whole genome tiling microarrays were used to probe the changes of transcriptome profile in response to TYLCCNB . The global gene expression patterns of N . benthamiana infected with TYLCCNV isolate Y10 ( hereafter referred to 10A ) were compared to infections with TYLCCNV and the associated TYLCCNB betasatellite ( hereafter referred to 10Aβ ) . The most pronounced of the differentially expressed genes , was an N . benthamiana ortholog of tobacco calmodulin-like protein , which has been previously identified as an endogenous regulator of gene silencing ( rgs-CaM ) that is induced by the potyvirus-encoded VSR HC-Pro [27] . Relative transcript quantification by reverse transcription quantitative real-time PCR ( RT-qPCR ) verified that N . benthamiana rgs-CaM ( Nbrgs-CaM ) is substantially up-regulated in 10Aβ-infected plants as compared to plants infected by 10A alone or mock-treated plants ( Fig . 1A ) . Northern blots analyses indicated that the levels of Nbrgs-CaM mRNA are low in mature leaves of mock-treated plants and of 10A-infected plants , but are enhanced greatly by 10Aβ infections ( Fig . 1B ) . To determine whether βC1 , the only protein known to be encoded by TYLCCNB , is responsible for the enhanced expression of Nbrgs-CaM , we measured the mRNA levels of Nbrgs-CaM in transgenic N . benthamiana plants expressing βC1 under the control of the constitutive CaMV 35S promoter [39] . Levels of Nbrgs-CaM mRNA in the βC1 transgenic plants were over 20-fold higher than those of wild-type ( wt ) plants ( Fig . 1A–B ) . In addition , in other Solanaceae hosts , TYLCCNV infections containing the betasatellite also exhibited up-regulated expression of the rgs-CaM orthologs in tobacco ( Ntrgs-CaM ) and tomato ( Slrgs-CaM ) ( Fig . S1 ) . EST sequences of Nbrgs-CaM were aligned to Ntrgs-CaM and Slrgs-CaM sequences obtained from the Genbank database , and primers were designed to amplify the full-length genes encoding the proteins . Sequencing revealed that the Nbrgs-CaM open reading frame ( ORF ) is 573-nt ( GenBank accession number JX402081 ) , and Blast searches against the N . benthamiana transcriptome database ( http://benth-web-pro-1 . ucc . usyd . edu . au/blast/blast . php ) demonstrated that the ORF had a 100% identity to the Nbv3K725607008 unigene transcript . Sequence analysis also revealed that Nbrgs-CaM encodes a 188-amino acid ( aa ) calcium-binding protein , which has the highest similarity ( 94% and 80% aa identities ) to Ntrgs-CaM and Slrgs-CaM ORF , respectively . These rgs-CaM orthologs contain a ∼50-aa N-terminal domain , in addition to a calmodulin ( CaM ) domain in the C-terminal region that has three characteristic EF-hand calcium binding motifs ( EF I , II and IV ) ( Fig . 1C ) . A phylogenetic tree was constructed to compare the evolutionary relationships between the rgs-CaMs and representative calmodulins ( CaM ) , calmodulin-like ( CML ) proteins and calcineurin B-like ( CBL ) proteins from Arabidopsis and Nicotiana spp . The Rgs-CaMs are clustered with Arabidopsis CMLs , with the closest relationships to CML38 and CML39 . The three Rgs-CaMs are only distantly related to two CaMs from tobacco ( NtCaM1 and NtCaM2 ) , which formed a separate branch with CaMs from Arabidopsis ( Fig . 1D ) . To investigate functional links between Nbrgs-CaM and βC1 , we generated transgenic N . benthamiana lines over-expressing Nbrgs-CaM under the control of the CaMV 35S promoter ( 35S:CaM ) . Many of the Nbrgs-CaM primary transgenic plants displayed developmental abnormities that could be grouped into three types based on phenotypic severity . Type I plants developed mild morphological alterations with slightly upward curled leaves . Type II plants showed moderate upward leaf curling and small interveinal outgrowths from abaxial leaf surfaces ( Fig . 2A ) . The upper leaves of the type I and II plants usually appeared normal ( Fig . 2A ) , and these plants produced fertile inflorescence . Type III plants had severely distorted , upward curling leaves and more extensive tissues outgrowth ( Fig . 2A ) . The upper leaves of Type III plants maintained the severe curling syndrome and most of these plants failed to produce inflorescences or produced only sterile flowers . Overall the phenotypes of 35S:CaM plants were strikingly similar to those of N . benthamiana transgenic plants expressing βC1 ( 35S:βC1 ) [39] . Both the 35S:CaM and 35S:βC1 transgenic plants developed similar abnormities including upward leaf curling , vein swelling and outgrowth of tissues ( compare left panels with right panels in Fig . 2A ) , albeit several 35S:CaM plants lines showed a chlorotic mottling on leaves that was not routinely observed in 35S:βC1 plants ( Fig . 2A , middle panel ) . Three independent transgenic lines #1 . 1 , #2 . 3 and #3 . 1 , which represented type I , II and III phenotype plants , respectively , were analyzed for transgene expression by Northern and Western blotting . High levels of Nbrgs-CaM accumulated in these transgenic lines compared to undetectable levels in nontransgenic ( wt ) plants ( Fig . 2B ) . Although plants with severer phenotypes appeared to have slightly higher levels of Nbrgs-CaM mRNA and protein ( Fig . 2B ) , a direct correlation between transgene expression and symptom severity was not evident . Nevertheless , the phenotypic resemblance between 35S:CaM and 35S:βC1 plants suggests that both genes may have functional similarities . For subsequent studies , line #1 . 1 was used unless otherwise stated due to its high levels of transgene expression and lack of severe phenotype in the plants . Transgenic plants with reduced expression of endogenous Nbrgs-CaM were also generated by transforming N . benthamiana plants with a hairpin RNA interference ( RNAi ) construct under the control of CaMV 35S promoter ( 35S:dsCaM ) . These 35S:dsCaM plants appeared to be normal without discernible developmental defects ( Fig . 2C ) . Moreover , Nbrgs-CaM transcripts in wt and 35S:dsCaM plants were low in abundance and difficult to detect by Northern blotting ( data not shown ) , although RT-qPCR showed that RNAi had reduced the Nbrgs-CaM mRNAs to approximately 20% of wt levels ( Fig . 2D ) . An earlier study has shown that Ntrgs-CaM suppresses PTGS , representing the first identified ESR in plants [27] . To investigate whether Nbrgs-CaM and its orthologs can suppress PTGS , we employed a transient silencing suppression assay based on the GFP transgenic N . benthamiana line 16c [50] , [51] in the study . In this assay , Agrobacterium tumefaciens cultures harboring a binary vector designed to transiently express sense GFP mRNA ( 35S:GFP ) and Agrobacterium derivative harboring a candidate suppressor gene were co-infiltrated into leaves of 16c plants . Agroinfiltration of 16c leaves with 35S:GFP and an empty vector ( negative control ) triggered GFP RNA silencing and resulted in weak GFP fluorescence under long-wavelength UV light at 4-days post infiltration ( dpi ) ( Fig . 3A ) . As expected , co-infiltration of 35S:GFP with βC1 of TYLCCNB or p19 of Tomato bushy stunt virus ( TBSV ) elicited strong green fluorescence as a consequence of suppression of GFP RNA silencing ( Fig . 3A ) . Expression of Nbrgs-CaM , Ntrgs-CaM and Slrgs-CaM also suppressed GFP silencing as indicated by appearance of green fluorescence in co-infiltrated regions ( Fig . 3A ) . The GFP fluorescence imaging shown in Fig . 3A was also correlated with the accumulation of GFP protein and mRNA as assessed by immunoblot and RNA blot analyses ( Fig . 3B ) . High levels of expression of Nbrgs-CaM , Ntrgs-CaM and Slrgs-CaM in agroinfiltrated leaves were also verified by RNA blotting with rgs-CaM-specific probes ( Fig . 3B ) . Notably , transient expression of βC1 also led to increased accumulation of Nbrgs-CaM mRNA compared to undetectable basal levels in vector-infiltrated leaves . By contrast , an unrelated VSR p19 failed to induce Nbrgs-CaM expression ( Fig . 3B ) , suggesting that induction of Nbrgs-CaM is unlikely a common feature associated with VSRs . Small RNA gel blot analysis revealed that high levels of 21 , 22 and 24 nt GFP-specific siRNAs accumulated in the vector control-treated leaves as a result of GFP RNA silencing . In contrast , expressions of the three rgs-CaMs and βC1 markedly decreased the amount of GFP siRNAs ( Fig . 3B ) . Similarly , p19 also inhibited the accumulation of the siRNAs ( Fig . 3B ) as previously reported [26] . Rgs-CaMs infiltrated leaves had comparable suppression activity to those of βC1 infiltrations , but were weaker than that elicited by p19 ( Fig . 3A–B ) . Overall , these data demonstrate that , as with βC1 , all three rgs-CaMs exhibit PTGS suppression activity and inhibit siRNA biogenesis . To further examine the function of Nbrgs-CaM in RNA silencing suppression in the context of a virus infection , we tested whether Nbrgs-CaM could suppress VIGS by using a previously established VIGS vector based on 10A helper virus in association with a geminivirus alphasatellite derivative ( 2mDNA1 ) [52] , [53] . The alphasatellite vector ( 2mDNA1-NbSu ) was designed to express a fragment of the N . benthamiana sulfur ( Su ) reporter gene that encodes a component required for chlorophyll II biosynthesis . The recombinant viral vector ( 10A+2mDNA1-NbSu ) triggered Su silencing in leaves of infected plants as evidenced by yellow-white leaf spots [52] , [53] . In wt N . benthamiana infected by the VIGS vector , the typical Su silencing phenotype first appeared along the main veins of the newly expanded leaves at 10 dpi , and later expand to the lateral veins to produce a white lattice-like phenotype at 30 dpi ( Fig . 3C ) . However , infected 35S:CaM transgenic line #1 . 1 failed to develop an Su silencing by 30 dpi ( Fig . 2C ) . Even at late stages of infection ( 40 dpi ) , only sporadic white spots were observed in some of the newly emerged leaves in 35S:CaM plants ( data not shown ) . On the other hand , Su silencing appeared 4 to 5 days earlier in infected Nbrgs-CaM RNAi line plants ( 35S:dsCaM ) than in wt plants , and more extensive Su silencing was noted at 30 dpi ( Fig . 3C ) . When additional Nbrgs-CaM transgenic lines were analyzed , similar lack of or delayed Su silencing phenotypes were observed in 35S:CaM lines , in contrast to more extensive silencing in 35S:dsCaM lines ( Fig . S2 ) . Analysis of Su mRNA levels in these plants by RT-qPCR also supported the observed silencing phenotypes ( Fig . 3D ) . When compared to endogenous Su mRNA level in mock-silenced plants ( infection with an empty VIGS vector 10A+2mDNA1 ) , VIGS reduced the Su mRNA levels by ∼4-fold in wt plants , and ∼5-fold in 35S:dsCaM plants but less than 2-flod in 35S:CaM plants ( Fig . 3D , Fig . S2 ) . Notably , both the 10A helper virus and alphasatellite accumulated to higher levels in 35S:CaM plants and to lower levels in 35S:dsCaM plants , relative to wt plants ( Fig . 3E ) . Therefore , the altered VIGS efficiencies in Nbrgs-CaM transgenic lines are not a consequence of differential virus accumulations . These data indicate that the cellular levels of Nbrgs-CaM are negatively correlated with the effectiveness of VIGS in N . benthamiana , and support a model that Nbrgs-CaM functions as an endogenous negative regulator of RNA silencing . In plants , PTGS can be triggered by sense RNA ( S-PTGS ) or inverted repeat RNA ( IR-PTGS ) . Gene silencing triggered by sense RNA trigger requires the host RNA copy machinery to convert target RNA into dsRNA in the initiation step , whereas inverted repeat RNA or hairpin RNA could directly trigger PTGS [3] , [4] . To pinpoint the specific steps targeted by βC1 and Nbrgs-CaM in RNA silencing pathway , we investigated their abilities to suppress S-PTGS and IR-PTGS . For S-PTGS , N . benthamiana leaves were co-infiltrated with Agrobacterium cultures expressing the suppressors , GFP reporter ( 35S:GFP ) and a C-terminal 400 bp-fragment of sense GFP RNA ( 35S:FP ) . The procedure of IR-PTGS suppression assay is similar to that of S-PTGS , except that a fragment of GFP dsRNA was expressed from binary vector ( 35S:dsFP ) to serve as a silencing inducer . As shown in Fig . 4A–B , in the absence of a suppressor ( vector control ) , GFP expression was efficiently silenced by simultaneous expression of either the sense RNA trigger ( 35:FP ) or the dsRNA trigger ( 35S:dsFP ) as indicated by red fluorescence in the infiltrated leaves ( top row ) . Similar to the experiments in Fig . 3A , both βC1 and Nbrgs-CaM suppressed GFP silencing triggered by 35S:FP , resulting in bright green fluorescence in co-infiltrated areas of leaves ( Fig . 4A , second and third row , respectively ) . However , neither βC1 nor Nbrgs-CaM suppressed GFP silencing in IR-PTGS , as the infiltrated areas showed red autofluorescence similar to the vector-infiltrated leaves ( Fig . 4B , compare second and third rows with top row ) . As a positive control , p19 suppressed both S-PTGS and IR-PTGS of GFP ( Fig . 4A–B , bottom row; Fig . 4C–D ) , which is consistent with the model that p19 suppresses RNA silencing by sequestering 21-nt siRNA [20] . The GFP imaging data were further confirmed by immunoblot and RNA blot analyses of the accumulation levels of GFP protein and mRNA in infiltrated leaf patches ( Fig . 4C–D ) . The siRNA blots also confirmed that βC1 , Nbrgs-CaM and p19 drastically reduced the GFP siRNA during S-PTGS ( Fig . 4C ) . For detection of GFP siRNAs in IR-PTGS assays , we designed two different probes corresponding to the FP portion and G portion of GFP mRNA . The “FP siRNAs” were presumably produced from DCLs-processing of dsRNA precursors transcribed from the 35:dsFP binary vector , and thus represents primary siRNAs . The “G siRNAs” were likely generated from GFP mRNA templates by activities of plant RDRs followed by DCLs-cleavages , and hence should be regarded as secondary siRNAs . Small RNA hybridization showed that both βC1 and Nbrgs-CaM strongly inhibited G siRNA levels without obvious effect on FP siRNAs ( Fig . 4D ) , suggesting that the two proteins suppressed secondary siRNA production . Likewise , Ntrgs-CaM and Slrgs-CaM were also found to suppress S-PTGS but not IR-PTGS of GFP ( Fig . S3 ) . Therefore , our data suggest that both βC1 and rgs-CaMs interfere with a step upstream of dsRNA generation in the PTGS pathway . The up-regulation of Nbrgs-CaM by βC1 ( Fig . 1 ) , together with their overlapping functions in PTGS suppression and symptom modulation ( Fig . 2 , 3 and 4 ) , led us to develop a model in which βC1 functions are mediated by Nbrgs-CaM . To test this hypothesis , we first analyzed the ability of βC1 to suppress S-PTGS in wt and 35S:dsCaM plants using a transient agroinfiltration assay . In wt plants , suppression of S-PTGS of GFP by βC1 was confirmed by the presence of strong GFP fluorescence in infiltrated leaf patches under UV light ( Fig . 5A ) , the accumulation of GFP protein and mRNA and the absence of GFP siRNA ( Fig . 5B ) . However , in 35S:dsCaM plants , βC1 failed to suppress GFP silencing ( Fig . 5A–B ) , even though comparable amounts of βC1 were expressed in wt and 35S:dsCaM plants ( Fig . 5B ) . As a positive control , p19 suppressed GFP silencing in both wt and 35S:dsCaM plants ( Fig . 5A–B ) . To exclude any unspecific defect of the 35S:dsCaM transgenic plants in the βC1 VSR function , we used N . benthamiana 16c plants in which the expression of Nbrgs-CaM was silenced by the well-characterized Tobacco rattle virus ( TRV ) -based VIGS vector [54] , which decreased Nbrgs-CaM mRNA levels to 20% of mock-treated plants at 7 dpi ( Fig . S4B ) . Systemically silenced leaves of these plants were then used for Agrobacterium co-infiltration in the transient PTGS suppression assay . Again , the abilities of βC1 to suppress GFP silencing and decreased GFP siRNA levels were compromised in Nbrgs-CaM-silenced plants , but not in mock-silenced plants ( Fig . S4A and S4C ) . These data collectively suggest that Nbrgs-CaM is required for the ability of βC1 to suppress PTGS and to inhibit siRNA generation . To further investigate whether βC1-induced developmental abnormities are mediated by Nbrgs-CaM , we infected wt and 35S:dsCaM N . benthamiana plants at 6–7 leaf stage with a recombinant PVX vector carrying the βC1 gene ( PVX-βC1 ) . As shown in Fig . 5C , PVX-βC1-infected wt plants developed typical βC1-associated phenotypes such as upward leaf curling and enation , in addition to the PVX mosaic symptoms . However , in PVX-βC1-infected 35S:dsCaM plants , symptoms characteristic of βC1 failed to appear , and only slightly downward leaf curling and mosaic symptoms indicative of PVX infection were observed . Comparable levels of the recombinant PVX genomic and subgenomic RNAs were verified by RNA blot analyses with probes specific to PVX coat protein ( CP ) and βC1 ( Fig . 5D ) . Furthermore , immunoblotting also confirmed similar expression levels of βC1 and PVX CP in wt and 35S:dsCaM plants ( Fig . 5E ) . Taken together , we conclude that βC1 functions as a VSR and symptom determinant are mediated by Nbrgs-CaM . Given the important roles of βC1 in TYLCCNV pathogenesis [38] , [39] , and the involvement of Nbrgs-CaM in these processes ( Fig . 5 ) , we anticipated that Nbrgs-CaM has a major function in TYLCCNV infection . To this end , we compared the susceptibilities of Nbrgs-CaM transgenic plants and wt plants to 10Aβ infection . After infection , the 35S:CaM plants showed more extensive leaf curling and greater numbers of curled leaves than wt plants . In contrast , the symptoms in infected 35S:dsCaM plants were much milder than those in wt plants ( Fig . 6A ) . The onset of disease symptoms was also advanced by 2 days in 35S:CaM plants ( 5 dpi compared to 7 dpi in wt plants ) , but was delayed to 9 to 10 days in 35S:dsCaM plants . Because the #1 . 1 line of the 35S:CaM plants had only minor abnormality in upper leaves prior to infection ( Fig . 2A ) , the exacerbated symptoms observed in 35S:CaM plants were most likely due to enhanced virulence of 10Aβ in the plants . Accordingly , Southern blot analysis indicated an increased viral DNA accumulations of both helper ( 10A ) and the betasatellite ( 10β ) in 35S:CaM plants . This finding , plus decreased viral DNA accumulations in 35S:dsCaM plants ( Fig . 6B ) , further supports a role of Nbrgs-CaM in TYLCCNV infection . We also tested the sensitivities of these Nbrgs-CaM transgenic plants to infection with CMV , an unrelated RNA virus . As with the case with 10A and 10Aβ , 35S:CaM plants were more prone to CMV infection whereas 35S:dsCaM plants were more recalcitrant , as judged from symptom severities and viral CP accumulations ( Fig . S5 ) . Thus , it appears that Nbrgs-CaM-mediated negative regulation of RNA silencing in plants may confer general susceptibilities to virus infections . Given that expressions of Ntrgs-CaM and Slrgs-CaM were also induced by TYLCCNB in tobacco and tomato plants , respectively ( Fig . S1 ) , and the three rgs-CaMs possessed comparable activity in suppressing PTGS ( Fig . 3A–B ) , we next explored whether Ntrgs-CaM and Slrgs-CaM have similar roles in 10Aβ infection . To this end , N . benthamiana , tobacco and tomato seedlings were agro-infiltrated with recombinant TRV vectors which carry partial fragments of Nbrgs-CaM , Ntrgs-CaM and Slrgs-CaM , respectively . Knowdowns of the three rgs-CaMs were verified by RT-qPCR , which showed an approximately 80% reduction in their mRNA levels as compared to TRV-GFP-treated plants or mock plants ( no TRV infection ) at 7 dpi ( Fig . S6 ) . Rgs-CaM-silenced N . benthamiana , tobacco and tomato plants had indistinguishable symptoms from TRV-GFP-infected plants , indicating reductions in the abundance of rgs-CaM do not cause discernible phenotype in these host plants ( data not shown ) . The rgs-CaM-silenced plants were infected with 10Aβ and monitored for symptom appearance . As shown in Fig . 6C–D , at 20 days after 10Aβ infection , rgs-CaM-silenced plants developed much milder symptoms and accumulated lower amounts viral DNAs than TRV-GFP-treated or mock-silenced plants , suggesting similar roles of these rgs-CaMs in TYLCCNV infection in Solanaceae hosts . Overall , our data are consistent with a model that Nbrgs-CaM and its orthologs in Solanaceae hosts function as negative cellular regulators of RNA silencing that are induced by βC1 to potentiate TYLCCNV infections . In plants , calmodulins or calmodulin-like proteins regulate a variety of cellular processes by controlling the expression of genes encoding downstream effectors [29] , [30] . To investigate whether βC1-induced Nbrgs-CaM altered the expression of components in the RNA silencing pathway , specific primers for RT-qPCR detection were designed to analyze the transcription levels of N . benthamiana homologs of DICER 1 ( NbDCL1 ) , DICER 2 ( NbDCL2 ) , DICER 3 ( NbDCL3 ) , DICER 4 ( NbDCL4 ) , ARGONAUTE 1-1 ( NbAGO1-1 ) , ARGONAUTE 4-1 ( NbAGO4-1 ) , SGS3 ( NbSGS3 ) , RDR1 ( NbRDR1 ) , RDR2 ( NbRDR2 ) and RDR6 ( NbRDR6 ) . For this purpose , individual Agrobacterium cultures expressing GFP ( 35S:GFP ) , Nbrgs-CaM ( 35S:CaM ) or βC1 ( 35S:βC1 ) were infiltrated into N . benthamiana leaves and the transcription levels of RNAi components were measured by RT-qPCR . As compared with the GFP control , expression of βC1 or Nbrgs-CaM at 48 hours post infiltration ( hpi ) resulted in only moderate changes ( 60∼150% ) in mRNA levels of the RNAi components in repeated experiments ( Fig . 7A ) , although up-regulation of NbDCL3 , NbDCL4 and NbRDR1 , and down-regulation of NbDCL1 , NbAGO4 or NbSGS3 expression by either βC1 or Nbrgs-CaM appeared to be significant ( p≤0 . 05 or p≤0 . 01 ) . However , the NbRDR6 mRNA level was consistently reduced by 2-fold by both Nbrgs-CaM and βC1 ( Fig . 7A ) . The inhibitory effect was more evident when βC1 and Nbrgs-CaM were expressed from a PVX vector or from a stable transgene , and in these cases , NbRDR6 mRNA was reduced to 10∼20% of that of control plants ( Fig . 7B ) . Infections with 10Aβ also decreased the NbRDR6 mRNA levels to ∼40% of that in 10A-infected or mock-infected plant at 7 dpi ( Fig . 7D ) . The parallel functions of Nbrgs-CaM and βC1 in PTGS suppression and NbRDR6 down-regulation led us to postulate that Nbrgs-CaM is required for βC1 to repress NbRDR6 expression . To test this possibility , Agrobacterium cultures harboring expression cassettes of the GFP ( control ) or βC1 were infiltrated into leaves of wt and 35S:dsCaM plants , and the effects on NbRDR6 transcription were measured by RT-qPCR . As compared to expression of GFP , expression of βC1 reduced the NbRDR6 mRNA levels by more than 2-fold in wt plants . However , upon transient expression of GFP and βC1 in 35S:dsCaM plants , the NbRDR6 mRNA levels were comparable ( Fig . 7C ) . Likewise , 10Aβ infection also led to reduced NbRDR6 expression in wt plants but not in in 35S:dsCaM plants , when compared to that of 10A-infected or mock plants ( Fig . 7D ) . These results indicate that the requirement of Nbrgs-CaM for repression of NbRDR6 transcription is likely to be biologically relevant . It is worth noting that higher basal levels of NbRDR6 mRNA ( ∼1 . 5-fold ) were observed in 35S:dsCaM plants than in wt plants ( Fig . 7D , compare mock-treatment in dsCaM and wt plants ) , suggesting that endogenous Nbrgs-CaM suppresses NbRDR6 expression . Taken together , our data suggest that Nbrgs-CaM acts downstream of βC1 to suppress NbRDR6 expression . To verify the role of NbRDR6 in host antiviral defense against TYLCCNV infection , we used a N . benthamiana NbRDR6 RNAi line ( dsRDR6 ) described earlier [13] . We first compared the efficiency of Su silencing induced by the 10A-derived VIGS vector in wt and dsRDR6 N . benthamiana plants . At 30 dpi , typical Su silencing phenotypes were developed on wt plants , but not on dsRDR6 plants ( Fig . 8A ) . RT-qPCR analysis revealed a 5-fold reduction of Su mRNA in wt plants compared to mock-silenced plants ( infected by 10A+2mDNA1 ) , whereas in dsRDR6 plants Su mRNA was reduced less than 2-fold ( Fig . 8B ) , confirming the defective Su silencing in dsRDR6 plants ( Fig . 8A ) . Interestingly , in dsRDR6 plants , both DNA components of the viral vector accumulated to higher levels than in wt plants ( Fig . 8C ) , suggesting that the compromised Su silencing in dsRDR6 plants is due to an inability to mount RNA silencing response upon TYLCCNV infection , rather than a failure to support robust virus replication . The functions of NbRDR6 in RNA silencing-based defense were further tested by infection of 10A and 10Aβ . As described in earlier studies [38] , infection of wt plants with 10A elicited very mild symptoms , which were greatly exacerbated when the pathogenesis-enhancing satellite was present ( 10Aβ ) ( Fig . 8D ) . Interestingly , in dsRDR6 plants , infection with the 10A helper alone resulted in severe downward leaf curling . However , the phenotypes characteristic of the betasatellite infection , including shoot bending , leaf distortion , vein thickening and enations , were not observed ( Fig . 8D ) . Infection of dsRDR6 plants with 10Aβ produced slightly severer symptoms than those in wt plants ( Fig . 8D ) , and the disease onset was also advanced in dsRDR6 plants ( 3∼4 dpi ) as compared to those in wt plants ( 6∼7 dpi ) . Southern blot hybridization analysis of 10A-infections also revealed that total viral DNA accumulated at higher levels in dsRDR6 plants than in wt plants ( Fig . 8E ) . Similarly , betasatellite co-infections also resulted in increased helper viral DNA accumulation . In particularly , the single-stranded viral DNA forms ( ssDNA ) were barely visible in 10A-infected wt plants , but were greatly enhanced in dsRDR6 plants and in betasatellite co-infected plants ( Fig . 8E ) . Previously , it was thought that disease phenotypes induced by 10Aβ could be solely attributed to the expression of the pathogenesis factor βC1 , because infections with 10A alone elicited negligible symptoms ( Fig . 8D ) . However , our data here suggest that betasatellite-mediated amplification of 10A , likely as a result of repression of NbRDR6 , also contributes to disease manifestation . Small RNA blot analyses also showed that betasatellite suppressed viral siRNA ( vsiRNA ) production ( Fig . 8F , compare 10Aβ-infectd plants with 10A-infected plants ) . Interestingly , vsiRNAs accumulated at higher levels in dsRDR6 plants when compared with wt plants , regardless of the presence or absence of the betasatellite , so is also the case with the NbSu-derived siRNAs ( Fig . 8F ) . Nevertheless , the abundant siRNAs observed in dsRDR6 plants apparently failed to efficiently silence their targets ( Fig . 8A–C ) or to confer effective antiviral defense ( Fig . 8D–E ) . A . thaliana is known as a susceptible host for only a few geminiviruses including CaLCuV and Beet curly top virus . TYLCCNV , either alone ( 10A ) or in association with betasatellite ( 10Aβ ) , has consistently failed to systemically infect Arabidopsis ecotype Columbia ( Col-0 ) ( Fig . 9 A–B ) . Remarkably , Arabidopsis rdr6 mutant plants were susceptible to infection of 10Aβ , showing typical downward leaf curling on new leaves starting at 7 dpi ( Fig . 9A ) . The narrow curled leaves and cotyledons of infected plants were reminiscent of the phenotypes induced by transgenic expression of βC1 in Arabidopsis [55] . After 30 dpi , the infected plants began to develop necrosis on newly expanded leaves and shoots , and some of the shoots eventually died . However , in contrast to 10Aβ , 10A alone failed to systemically infect rdr6 plants ( Fig . 9A ) . Consistent with the observed symptoms , Southern blot analysis showed high levels of helper and satellite DNA accumulations in leaves of rdr6 plants systemically infected with 10Aβ , whereas viral DNAs were absent in inoculated wt plants or 10A-inoculated rdr6 plants ( Fig . 9B ) . These data strongly suggest a major role of RDR6 in host antiviral defense against TYLCCNV infection and underscore the function of RDR6-mediated RNA silencing in restricting the host range of a geminivirus .
In plants , RNA silencing represents a major defense mechanism against virus infection . Consequently , plant viruses have evolved to encode VSRs as potent molecular arms to counteract antiviral RNA silencing [1] , [2] . These structurally distinct VSRs often interact with various components in the RNA silencing pathway , including long or short dsRNA duplex , AGOs , DCLs and RDRs as well as their functional partners , thereby to disable the RNA silencing-based host defense systems [15] , [16] . Besides an antiviral role , RNA silencing also regulates essential developmental processes such as endogenous gene expression and genome stability [31] . Given the important role of RNA silencing in normal cell physiology and its “spreading” nature by means of signal amplification , it is not surprising that this process requires appropriate controls by cellular regulatory factors or pathways . Indeed , genetic screenings have identified several endogenous silencing suppressors or anti-silencing factors involved in the negative regulation of RNA silencing [56]–[60] . These factors may function to reactivate the expression of certain silenced genes or to prevent undesirable action of RNA silencing . It is conceivable that those endogenous pathways may be explored by gene-poor viruses to counterattack host antiviral responses . Such a scenario has been suggested by the identification of the calmodulin-like protein Ntrgs-CaM in tobacco , which interacts with and is induced by the TEV-encoded VSR HC-Pro [27] . However , it is not known whether Ntrgs-CaM is required for HC-Pro VSR functions . Here we report that a DNA geminivirus-encoded βC1 protein up-regulates the endogenous Nbrgs-CaM gene and its orthologs in Solanaceae hosts . Furthermore , PTGS suppression and symptom induction by βC1 are mediated by induction of Nbrgs-CaM and likely by subsequent repression of RDR6-mediated antiviral RNA silencing defense responses . The identification of rgs-CaM as a common factor for two unrelated VSRs suggests that subversion of ESR may be a common and effective strategy whereby viruses to suppress RNA silencing . It has previously been shown that the Ntrgs-CaM suppresses VIGS and reverses established PTGS , thus representing the first identified ESR [27] . Recently , however , an opposite effect of tobacco rgs-CaM on VSRs has been reported by Nakahara and co-workers , leading to the proposal that tobacco rgs-CaM acts as a host defense measure by interacting with and quenching VSRs that contain dsRNA binding domain [61] . Nakahara et al . have also showed that transgenic tobacco plants over-expressing rgs-CaM promote the degradation of VSRs , including HC-Pro of potyviruses and 2b of cucumoviruses , and thus are less susceptible to infections of these viruses [61] . However , here our data are not in agreement with the proposed function of rgs-CaM as a counter-VSR factor , but instead reinforce the notion that rgs-CaMs are bona fide ESRs based on the following observations: ( i ) rgs-CaMs suppress S-PTGS and secondary siRNA biogenesis in several transient assays based on conventional agroinfiltration ( Fig . 3A–B , Fig . S3 and Fig . 4 ) ; ( ii ) transgenic over-expression of Nbrgs-CaM suppresses VIGS of an endogenous gene whereas down-regulation of Nbrgs-CaM enhances silencing phenotypes ( Fig . 3C , Fig . S2 ) ; ( iii ) over-expressed Nbrgs-CaM induces phenotypes resembling those of VSR-expressing plants ( Fig . 2A ) ; ( iv ) Nbrgs-CaM suppresses NbRDR6 expression ( Fig . 7 ) and consequently , down-regulation of NbRDR6 suppresses geminivirus-VIGS ( Fig . 8A ) ; ( v ) leaves of both 35S:CaM and dsRDR6 N . benthamiana plants inhibit S-PTGS but not IR-PTGS in an agroinfiltration assay ( Fig . S7 ) ; ( vi ) finally , 35S:CaM plants have enhanced susceptibility to TYLCCNV and CMV infections whereas 35S:dsCaM plants are more resistant ( Fig . 6 , Fig . S5 ) . We also did not observe changes in the stability of βC1 or CMV 2b in plants with altered Nbrgs-CaM mRNA levels ( Fig . 5 , Fig . S5 ) , suggesting that Nbrgs-CaM do not direct these VSRs for degradation . In addition , we provide genetic evidence that Nbrgs-CaM mediated the βC1 functions in PTGS suppression and symptom induction ( Fig . 5 ) . Our findings have thus revealed a positive role for Nbrgs-CaM in VSR function and virus infection . These seemingly contradictory findings could be due to different experimental conditions employed , since Nakahara et al . also determined that Ntrgs-CaM suppresses RNAi when expressed in Drosophila S2 cells [61] . Alternatively , it is possible that rgs-CaM homeostasis contributes to the proper regulation of RNA silencing . In support of the latter hypothesis , Roth et al . observed that only moderate levels of Ntrgs-CaM suppress sense-transgene silencing when ectopically expressed in Arabidopsis , whereas highly expressed Ntrgs-CaM does not [62] . This suggests that the suppression activity of Ntrgs-CaM may be subjected to negative feedback regulation . Although several Nbrgs-CaM transgenic lines generated in our study displayed uniform activity in VIGS suppression ( Fig . S2 ) , we cannot exclude the possibility that a certain range of Nbrgs-CaM expression levels might have different effect . Unlike HC-Pro , which is a cytoplasmic protein and binds to siRNA duplex [63] , βC1 of TYLCCNB primarily localizes in nuclei and binds to single- but not double-stranded RNA [41] , [64] . It is unclear how structurally unrelated HC-Pro and βC1 have evolved independently to induce rgs-CaM . Induction of rgs-CaM was not observed for p19 of TBSV ( Fig . 3B ) , another well-characterized VSR with a siRNA-binding domain [20] , suggesting that exploitation of rgs-CaM is not a common feature associated with VSRs . A recent study has shown that an ethylene inducible RAV/EDF transcription factor is required for the HC-Pro functions as a VSR and symptom modulator [28] . Subsequent microarray analyses have revealed differential expression of many biotic and abiotic stress response genes in Arabidopsis in response to HC-Pro in a RAV2-dependent manner . Among these are Arabidopsis FIERY1 ( AtFRY1 ) , which negatively regulates transitive silencing [57] , and AtCML38 ( Calmodulin-like protein 38 ) , a closely related homolog of rgs-CaM in Arabidopsis ( Fig . 1D ) , both of which were up-regulated [28] . Interestingly , our global gene expression analysis also revealed that many ethylene responsive transcription factors and stress-related genes are differentially up-regulated in βC1 transgenic plants . Notably , the list includes the N . benthamiana homolog of RAV2 ( NbRAV2 ) ( unpublished data ) . It has been shown that biotic and abiotic stresses , or treatment with Ethephon , a synthetic compound which decomposes into ethylene , could divert plants from antiviral silencing to cope with other stress responses [65] . Thus , it is tempting to speculate that HC-Pro and βC1 may have convergently evolved a mechanism for PTGS suppression through induction of the ethylene-mediated stress response . Further studies are needed to determine whether an N . benthamiana ortholog of RAV2 mediates the induction of Nbrgs-CaM by βC1 , and whether AtFRY1 and AtCML38 are downstream mediators of HC-Pro . Alternatively , βC1 has also been shown to be a TGS suppressor and when ectopically expressed , βC1 causes global reductions in host genome cytosine methylation [66] . It is possible that the transcription of Nbrgs-CaM is silenced by a DNA methylation-related mechanism under normal conditions , which is derepressed by the TGS suppressor function of βC1 . Our data reveal that up-regulation of Nbrgs-CaM expression by βC1 represses NbRDR6 expression ( Fig . 7 ) . Consistence with this finding , both βC1 and rgs-CaMs suppress S-PTGS but not IR-PTGS , and inhibits the production of secondary siRNAs ( Fig . 4 , Fig . 8F and Fig . S3 ) , suggesting that βC1 and rgs-CaMs act to inhibit dsRNA formation catalyzed by the activity of cellular RDRs . This notion is further reinforced by the observation that both 35S:CaM and dsRDR6 plants are defective in S-PTGS but not IR-PTGS in a conventional agroinfiltration assay ( Fig . S7 ) . Perhaps the most convincing genetic evidence to demonstrate a specific role for VSRs is rescue of the infections of VSR-deficient mutant viruses with host cells defective in RNA silencing [67] . Such an approach has been used to establish the antiviral role of RDRs-mediated secondary vsiRNAs biogenesis against the infections of several plant RNA viruses [6] , [9] , [10] , and to reveal the natural antiviral functions of RNAi in mammals [68] , [69] . It has been shown that 10A and some other monopartite begomoviruses are incapable of blocking host RNA silencing and inducing typical symptoms , and that their betasatellites are required for the full virulence of the helper viruses [43] , [44] . Here our data showed that the 10A DNA accumulation and pathogenicity can be partially rescued in N . benthamiana plants deficient in NbRDR6 ( Fig . 8D–E ) , underscoring the specific roles of βC1 in suppressing RDR6 functions . The essential role of RDR6 in antiviral defense has been reinforced by our observations that Arabidopsis rdr6 mutant plants were susceptible to 10Aβ , which otherwise can not establish robust infection in wt plants ( Fig . 9 ) . Previously , it has been reported that AGO2-mediated RNA silencing defense confers nonhost resistance to PVX infection of Arabidopsis [70] . To our knowledge , our data represent the first evidence that RNA silencing functions to constrain the host range of a DNA virus . RDR6 was originally identified in Arabidopsis as required for PTGS triggered by sense-transgenes ( S-PTGS ) but not by inverted repeat RNA ( IR-PTGS ) or by RNA viruses such as PVX ( RNA-VIGS ) [3] . Unlike RNA viruses , geminiviruses lack a dsRNA phase in their life cycle and thus do not obligatorily trigger RNA silencing . It has been suggested that abundant geminiviral transcripts could be perceived as aberrant RNAs and subsequently be recruited by host RDRs as templates to produce dsRNA [30] . In this sense , geminivirus-induced gene silencing is similar to S-PTGS in the initial stage because both processes require the actions of host RDRs ( Fig . 10 ) . In support of this notion , VIGS of an endogenous gene in Arabidopsis by CaLCuV-derived geminiviral vector requires RDR6 as well as SGS3 [33] . Our data also shows that VIGS of the Su gene by the 10A-derived vector was compromised in NbRDR6-deficient N . benthamiana plants ( Fig . 8A–B ) . Another hypothetic origin for geminiviral dsRNA precursor are the 3′ end overlapping transcripts generated by convergent transcription on the viral circular genome , which could be DCLs substrates for generation of vsiRNA ( Fig . 10 ) . Notably , SGS3 , the dsRNA binding partner of RDR6 , specifically recognizes dsRNAs with 5′ overhangs , a structure analog to 3′ end partially overlapped geminiviral transcripts [71] . This raises the intriguing possibility that such viral transcripts or their derivatives could be recruited by SGS3 and RDR6 to produce dsRNA precursors for vsiRNAs . Interestingly , TYLCV V2 suppresses PTGS likely through interacting with SGS3 and/or competing for binding to dsRNA substrates [71] , [72] . As with TYLCCNV βC1 , TYLCV V2 also suppresses S-PTGS but not IR-PTGS [73] , indicating that interference with SGS3/RDR6-mediated dsRNA formation is a common theme for geminiviruses-encoded VSRs . Interestingly , Aregger et al . have recently found that CaLCuV-derived siRNA populations are largely unaffected by Arabidopsis rdr1/2/6 triple mutation using deep sequencing and blot hybridization [74] , suggesting that the bulk of vsiRNAs are RDR1 , 2 and 6-independent ( i . e . primary vsiRNAs ) . It is worth mentioning that in addition to RDR1 , 2 and 6 , the Arabidopsis genome also encodes three poorly characterized RDRs of the γ class namely RDR3 , RDR4 and RDR5 . The prevailing assumption is that these three RDRs play no major role in antiviral defense . However , a recently study report that the tomato yellow leaf curl geminivirus Ty-1 and Ty-3 resistance genes code for a γ Class RDR that represents tomato homologs of Arabidopsis RDR3/4/5 [75] , suggesting that this group of RDRs in Arabidopsis may also be involved in vsiRNA biogenesis . Here we have shown that after 10A infection ( either alone , with betasatellite or with DNA1 component ) , even higher levels of vsiRNAs accumulated in N . benthamiana dsRDR6 plants than in wt plants ( Fig . 8F ) , and vsiRNA levels are proportional to the viral DNA accumulations in these plants . Therefore , these abundant RDR6-independent vsiRNAs ( assuming that the residual RDR6 activity is negligible in dsRDR6 plants ) seem to be unable to silence their targets efficiently , as manifested by the compromised NuSu VIGS ( Fig . 8A–C ) and by the hypersensitivity to 10A infections in the dsRDR6 plants ( Fig . 8D–E ) . It appears that plants defective in RDR6 are unable to mount an effective RNA silencing response upon TYLCCNV infections . As a result , TYLCCNV multiplies to higher levels , which , in turn , may produce more aberrant mRNA transcripts to generate abundant primary vsiRNAs or secondary vsiRNAs via the activities of other RDRs . It has been suggested that Arabidopsis RDR6 functions as a genome surveillance factor to monitor aberrant mRNAs derived from transgenes and targets those mRNAs for PTGS [76] . Given the resemblance of transgene-derived mRNAs and abundant geminiviral transcripts , such an RDR6-mediated protection mechanism may also operate to detect geminivirus infections . Alternatively , RDR6 may act at systemic levels to potentiate distal tissues to initiate an immediate early response against virus infection . Previously , Schwach and associates have shown that RDR6 is not required for production of PVX-derived siRNAs , but prevents systemic PVX infection likely through amplification of systemically movable silencing signals [13] . It remains to be determined whether RDR6 function at cellular level or systemic tissue , or both , to defend against geminivirus infections . It is important to note that the betasatellite greatly suppresses vsiRNA biogenesis in infected wt and dsRDR6 plants ( Fig . 8F ) , which is consistent with its activities on GFP siRNA production observed in agroinfiltration assays ( Fig . 3B , Fig . 4C–D , Fig . 5B and Fig . S3C–D ) . However , the dominant effect of TYLCCNB βC1 on vsiRNA biogenesis can not be solely attributed to its function in RDR6 suppression , because knockdowns of NbRDR6 do not reduced vsiRNA production ( Fig . 8F ) . Therefore , expression of βC1 likely has pleiotropic effects on the host RNA silencing pathway . Indeed , transient expression of βC1 also reduced the mRNA levels of NbSGS3 and NbAGO4 ( P≤0 . 05 ) , and in this regard , NbAGO4 is also suppressed by Nbrgs-CaM ( P≤0 . 01 ) ( Fig . 7A ) . Nuclear-replicating geminiviruses encounter host RNA silencing defense at both transcriptional ( TGS ) and post-transcriptional ( PTGS ) levels [33] , [34] . Raja and associates have shown that the Arabidopsis homolog of NbAGO4 plays an important role in methylation-based epigenetic defense against geminivirus [77] . In addition , we have recently reported that TYLCCNB βC1 suppresses TGS through interactions that inhibited the activity of S-adenosyl homocysteine hydrolase ( SAHH ) , a key enzyme in the host DNA methylation pathway [66] . Notably , the fact that 10A alone is not able to infect Arabidopsis rdr6 mutant suggests that suppression of other layers of host defense by betasatellite are required for 10A to establish robust infection in this host species . Another interesting aspect of our finding is the similar phenotypes of 35S:CaM and 35S:βC1 plants , and the genetic requirement of Nbrgs-CaM for βC1-disease manifestation ( Fig . 5A–B ) . Down-regulation of NbRDR6 alone by Nbrgs-CaM cannot account for the observed phenotypic defects observed in βC1 and 35S:CaM plants , since dsRDR6 plants have largely normal phenotypes ( data not shown; also in [12]–[13] ) . Therefore , other unknown targets downstream of Nbrgs-CaM may be involved in the development of βC1-induced symptoms . The upward-curled leaf phenotypes in βC1 and 35S:CaM plants suggest that these proteins may disrupt the leaf adaxial–abaxial identity . In Arabidopsis , ASYMMETRIC LEAVES1 ( AS1 ) and AS2 are important factors for promoting the establishment of leaf adaxial-abaxial identity . AS1 and AS2 form a repressor complex that binds directly to the regulatory motifs present in promoters of the KNOX genes that specify leaf polarity [78] . It has been shown that Arabidopsis RDR6 , as well as SGS3 and AGO7 in the trans-acting siRNA pathway , genetically interact with AS1/AS2 to synergistically regulate leaf development . The rdr6 and as1 or as2 double mutants display an abnormal leaf adaxial identity with a ruffled surface [79]–[80] that is reminiscent of the phenotypes shown in βC1 and 35S:CaM transgenic plants . Interestingly , Han et al . have recently showed that Arabidopsis calmodulin physically interacts with AS1 and relieves the AS1/AS2-suppression of KNOX transcription [81] . It remains to be determined whether Nbrgs-CaM has a similar effect in N . benthamiana . Yang et al . have also suggested that TYLCCNB-encoded βC1 uses molecular mimicking of AS2 to form a complex with AS1 to regulate leaf development [55] . Therefore , multiple pathways involved in leaf development may be affected by the βC1 , which could lead to disease manifestations ( Fig . 10 ) . Future studies are needed to address the effects of βC1 on the transcription levels of specific downstream targets of the AS1-AS2 pathway and the RDR6-SGS3-AGO7 pathway .
N . benthamiana seedlings were potted in soil and placed in an insect-free growth chamber at 25°C and 60% relative humidity under a 16 h light/8 h dark photoperiod . 35:βC1 transgenic N . benthamiana lines were generated in a previous study [36] , and the transgenic GFP 16c and dsRDR6 lines were generous gifts of David C . Baulcombe . The A . thaliana ecotype Columbia ( Col-0 ) and rdr6-11 mutant were used for this study . Seeds were surface sterilized with 75% ethanol and 50% bleach , and then washed three times with sterile water . Sterile seeds were suspended in 0 . 05% agarose and plated on Murashige and Skoog ( Duchefa Biochemie , Haarlem , Netherlands ) medium plus 2 . 0% sucrose . Plates were stratified in darkness for 3 d at 4°C and then transferred to a tissue culture room at 22°C under an 8-h-light/16-h-dark photoperiod . After 2 weeks , seedlings were potted in soil and placed in a growth chamber at 22°C and with 70% relative humidity under an 8-h-light/16-h-dark photoperiod . The tobacco rgs-CaM sequence was used to identify orthologous sequences from available N . benthamiana ESTs . BLAST searches revealed high homology between rgs-CaM from tobacco and N . benthamiana . Primers designed to anneal to conserved sequences in the 5′ and 3′ untranslated regions of tobacco rgs-CaM were used to amplify the coding region of N . benthamiana rgs-CaM by reverse transcription PCR ( RT-PCR ) . Amplification with primer pairs CaM-cds-F/CaM-cds-R yielded a specific product of approximately 600-bp , which was cloned into pMD18-T ( TaKaRa , Dalian , China ) and sequenced . Detailed primer information is listed in Table S1 . The full-length coding sequence of Nbrgs-CaM was deposited in GenBank under the accession number JX402081 . To construct the plant Nbrgs-CaM expression vector for transgenic over-expression or transient agroinfiltration assays , a primer pair CaM-F/CaM-R was designed to amplify the full-length coding region of Nbrgs-CaM . The Nbrgs-CaM coding sequence was subcloned into the binary vector pCHF3 downstream of a CaMV 35S promoter to produce pCHF3-35S-CaM , or into the PVX-based vector ( a kind gift of David Baulcombe ) between the ClaI and SalI sites to produce PVX-Nbrgs-CaM . An RNAi construct containing an Nbrgs-CaM inverted repeat sequence of spaced by a soybean intron was produced by overlapping PCR . The fragment of Nbrgs-CaM sense sequence was amplified with A-CaM-F/A-CaM-intron-R primer pair and overlapped with intron sequence amplified by B-CaM-intron-F/B-Intron-R primers . The overlapping products were cloned into pCHF3 between the SacI and BamHI sites to produce pCHF3-35S-CaM-intron . The corresponding antisense Nbrgs-CaM fragment was amplified with the primer pair C-CaM-F/C-CaM-R and subsequently cloned into pCHF3-35S-sCaM-intron between BamHI and PstI sites to produce the RNAi construct pCHF3-35S-dsCaM . To construct a TRV-based recombinant VIGS vector of Nbrgs-CaM , a partial fragment of Nbrgs-CaM was generated by PCR amplification with the primer pair TRV-CaM-F/TRV-CaM-R and then cloned into the pTRV2 vector ( a kind gift of Yule Liu ) between the BamHI and XhoI sites [54] . The coding sequences of Ntrgs-CaM and Slrgs-CaM were PCR-amplified from N . tabacum and S . lycopersicum and then subcloned to the pCHF3 binary vector or the TRV vectors using different primers and restriction enzyme sites listed in Table S1 . The pCHF3-based vectors were used for the transient expression of rgs-CaMs in N . benthamiana leaves , and the TRV-based VIGS vectors were used to silence the expression of rgs-CaMs in N . tabacum and S . lycopersicum , respectively . Binary vectors for the PTGS suppression assay , such as pCHF3-35S-GFP and pCHF3-35S-dsFP , were constructed previously [82] . The pCHF3-35S-FP vector for transcription of a partial sense sequence of C-terminal fragment of 400 bps of GFP was constructed by amplification with the primer pair S-FP-F/S-FP-R and cloned into pCHF3 . Transgenic lines over-expressing or down-regulating Nbrgs-CaM were generated by transforming N . benthamiana with the pCHF3-CaM and pCHF3-dsCaM constructs , respectively . The binary vectors were mobilized into A . tumefaciens EHA105 strain , and then used to transformed N . benthamiana leaf discs . Selection of transformants was performed in media containing 200 µg/ml kanamycin . Kanamycin-resistant shootlets were collected , placed on rooting media , grown to a height of 5–6 cm , and then transferred to soil . Transgenic plants were first screened by PCR with specific primers targeted to promoter or intron sequences and then confirmed by Southern blot hybridization . Alterations in Nbrgs-CaM mRNA levels in transgenic plants were confirmed by RT-qPCR and Northern blot analyses . For virus agroinoculation , equal volumes of individual A . tumefaciens cultures at an OD600 of 1 were mixed prior to inoculations . Viral infectious clones , including TYLCCNV ( pBinPLUS-Y10-1 . 7A ) , and TYLCCNV/TYLCCNB ( pBinPLUS-Y10-1 . 7A+Y10β ) , were described previously [38] . The TYLCCNV-derived VIGS vectors 2mDNA1 ( pBinPLUS-2mDNA1 ) and 2mDNA1-NbSu ( pBinPLUS-2mDNA1-NbSu ) were constructed previously [52] , [53] . The recombinant PVX vector expressing βC1 gene ( PVX-βC1 ) was described previously [66] . Agrobacterium cultures carrying viral infectious clone ( s ) were infiltrated into N . benthamiana leaves and inoculated plants were photographed with a Canon 400D digital camera at different periods . For CMV rub-inoculation , 1 g of CMV-infected N . glutinosa leaves were ground in 1 mL of 5 mM phosphate buffer , pH 7 . 2 . N . benthamiana plants at the 6–7 leaf stages were inoculated by rubbing leaves with freshly prepared sap . Inoculated plants were grown in an insect-free growth chamber at 25°C and monitored for symptom appearance . For PTGS experiments , transient silencing suppression assays were performed as described previously [50] , [51] . Classic two-component transient PTGS assays were performed by agroinfiltration of 35S:GFP with control or suppressor vectors into leaves of N . benthamiana 16c plants at the 6–7 leaf stages . For S-PTGS experiments , Agrobacterium cultures harboring the pCHF3-35S-GFP , pCHF3-35S-FP and VSRs-expressing vectors were mixed in equal proportions and infiltrated into N . benthamiana leaves . For IR-PTGS experiments , the pCHF3-35S-dsFP was used as an RNA silencing trigger instead of the pCHF3-35S-GF as a RNA silencing trigger . After 3 dpi , GFP fluorescence was monitored with a 100-W handheld long-wavelength UV lamp ( Black Ray Model B 100A; UV products ) and the infiltrated leaves were photographed with a Canon 400D digital camera with a 58-mm yellow filter . Exposures were 3 to 6 seconds long , depending on the fluorescence intensity and distance from the leaf . Total DNA was extracted from infected plant leaves using the CTAB method ( 35 ) . DNA agarose gels were stained with ethidium bromide to provide a loading control . After denaturation and neutralization , total DNA was transferred to Hybond N+ nylon membranes ( GE Healthcare , Pittsburgh , PA ) by capillary transfer . Membranes were hybridized at 55°C to specific probes labeled with [α-32P] dCTP . Total RNAs were extracted from plants with Trizol reagent ( Invitrogen , Carlsbad , CA ) as recommended by the manufacturer . Total RNA was stained with ethidium bromide as a loading control , and then transferred to Hybond N+ nylon membranes by upward capillary transfer in 20×SSC buffer . Membranes were hybridized to specific probes for rgs-CaM , βC1 , GFP or PVX CP labeled with [α-32P] dCTP using random primed labeling System ( Promega , Madison , WI ) . The hybridization signals were detected by phosphorimaging with a Typhoon 9200 imager ( GE Healthcare ) . To analyze the production siRNAs , low-molecular-mass RNAs were enriched from total RNA as described previously [3] . The enriched small RNAs ( 15 µg ) were fractionated on a 15% denaturing polyacrylamide–7 M urea gel in 0 . 5× Tris–borate–EDTA ( TBE ) buffer . The RNA was transferred to Hybond N+ membranes ( GE Healthcare ) by electroblotting in 0 . 5× TBE at 400 mA for 1 h . The transferred RNAs was UV crosslinked to the membrane 4 times at 1200 µJ in a UV Stratalinker 1800 ( Stratagene , La Jolla , CA ) . Membranes were stored at 4°C until probing . One DNA oligonucleotides complementary to N . benthamiana U6 RNA and a mixture of oligonucleotides corresponding to G , F and P regions of GFP mRNA sequences were synthesized and used as probes for siRNA hybridization ( Table S1 ) . The oligos were end-labelled with [γ-32P] ATP in 50 µL reactions containing 1 µM DNA oligo and 7 U T4 polynucleotide kinase . Hybridizations were performed overnight at 42°C and the membranes were subsequently washed three times ( 10 min each ) at 40°C with 1× SSC ( 0 . 15 M NaCl and 0 . 015 M sodium citrate ) supplemented with 0 . 1% SDS . Hybridization signals were detected as described above for Northern blot analysis . For RT-qPCR analysis , 10 µg of total RNA was treated with DNase I ( Takara ) and reverse transcribed according to manufacturer's instructions . Specific primer pairs , which annealed to GFP , βC1 , Nbrgs-CaM , Su or genes encoding known components in RNA silencing pathway ( Table S1 ) , were designed by Primer Premier 5 software . The GenBank accession numbers of genes analyzed in this study are as follows: Ntrgs-CaM ( AF329729 ) , Slrgs-CaM ( AY642285 ) , NbDCL1 ( FM986780 ) , NbDCL2 ( FM986781 ) , NbDCL3 ( FM986782 ) , NbDCL4 ( FM986783 ) , NbAGO1-1 ( DQ321488 ) , NbAGO4-1 ( DQ321490 ) , NtSGS3a ( AB690269 ) , NbRDR1m ( AY574374 ) , NbRDR2 ( AY722009 ) , NbRDR6 ( AY722008 ) . The lengths of amplification products were between 180–250 bp , and the Tm for each primer pair was between 55–65°C . RT-qPCR was performed using a LightCycler 480 ( Roche Diagnostics , Rotkreuz , Switzerland ) for 45 cycles , and NbGAPDH was used an internal control unless otherwise stated . Each experiment was performed in triplicate and repeated three times , and the results were analyzed by software supplied by the manufacturer . Total proteins were extracted from N . benthamiana leaves as described previously [66] . Immunoblotting was performed with primary mouse monoclonal or rabbit polyclonal antibodies , followed by goat anti-mouse or anti-rabbit secondary antibody conjugated to horseradish peroxidase ( Bio-Rad , Hercules , CA ) . The GFP monoclonal antibody was obtained from Hua An Company , China , and the monoclonal antibodies against PVX CP , CMV CP and βC1 were generated in house . The rabbit polyclonal antibody against CMV 2b was a generous gift from Dr . Huishan Guo . Blotted membranes were washed thoroughly and visualized using chemiluminescence according to the manufacturer's manual ( GE Healthcare ) . Nbrgs-CaM antibody was produced in rabbit with recombinant protein expressed in E . coli . In brief , we expressed Nbrgs-CaM in E . coli cells as a 6× Histidine and Maltose binding protein ( MBP ) fusion . The Nbrgs-CaM-MBP-His fusion protein was purified over a nickle column ( Merck , Darmstadt , Germany ) and eluted with a buffer containing 200 mM imidazole according to the manufacturer's manual . The purified protein was used to immunize rabbits for polyclonal antiserum . The Nbrgs-CaM-specific immunoglubin was given an additional purification step on an affinity column filled with Cyanogen bromide-activated agarose beads conjugated with the Nbrgs-CaM-MBP-His fusion proteins . | In plants , RNA silencing plays a key role in developmental regulation and antiviral defense . To successfully infect their hosts , plant viruses encode silencing suppressors ( VSRs ) as counter-defense measures . These VSRs function to disable host antiviral RNA silencing defenses through various mechanisms that are not well understood . Here we report that a host calmodulin-like protein called Nbrgs-CaM , which appears to be an endogenous suppressor of RNA silencing , plays essential roles in suppression of RNA silencing and induction of symptoms by the VSR βC1 , the sole protein encoded by a geminivirus-associated DNA satellite . The Nbrgs-CaM was up-regulated by Tomato yellow leaf curl China geminivirus ( TYLCCNV ) -encoded VSR βC1 upon virus infection or stable expression via a transgene . Further analyses revealed that up-regulation of Nbrgs-CaM by βC1 suppressed RNA silencing likely through repressing the expression of RNA-DEPENDENT RNA POLYMERASE 6 ( RDR6 ) . We have demonstrated that RDR6-mediated RNA silencing plays an important role in antiviral defense in Nicotiana benthamiana and confers host range restriction against TYLCCNV infection on Arabidopsis thaliana . Our study suggests that exploiting a cellular suppressor can be an efficient mechanism for viruses to counteract host RNA silencing defense response . | [
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] | 2014 | Suppression of RNA Silencing by a Plant DNA Virus Satellite Requires a Host Calmodulin-Like Protein to Repress RDR6 Expression |
The association between cholera in pregnancy and negative fetal outcome has been described since the 19th century . However , there is limited published literature on the subject . We describe pregnancy outcomes from a specialized multidisciplinary hospital unit at the onset of a large cholera outbreak in Haiti in 2010 and 2011 . Pregnant women with cholera were hospitalized in a specialized unit within the MSF hospital compound in Léogâne and treated using standard cholera treatment guidelines but with earlier , more intense fluid replacement . All women had intravenous access established at admission regardless of their hydration status , and all received antibiotic treatment . Data were collected on patient demographics , pregnancy and cholera status , and pregnancy outcome . In this analysis we calculated risk ratios for fetal death and performed logistic regression analysis to control for confounding factors . 263 pregnant women with cholera were hospitalized between December 2010 and July 2011 . None died during hospitalization , 226 ( 86% ) were discharged with a preserved pregnancy and 16 ( 6% ) had live fullterm singleton births , of whom 2 died within the first 5 days postpartum . The remaining 21 pregnancies ( 8% ) resulted in intrauterine fetal death . The risk of fetal death was associated with factors reflecting severity of the cholera episode: after adjusting for confounding factors , the strongest risk factor for fetal death was severe maternal dehydration ( adjusted risk ratio for severe vs . mild dehydration was 9 . 4 , 95% CI 2 . 5–35 . 3 , p = 0 . 005 ) , followed by severe vomiting ( adjusted risk ratio 5 . 1 , 95% 1 . 1–23 . 8 , p = 0 . 041 ) . This is the largest cohort of pregnant women with cholera described to date . The main risk factor identified for fetal death was severity of dehydration . Our experience suggests that establishing specialized multidisciplinary units which facilitate close follow-up of both pregnancy and dehydration status due to cholera could be beneficial for patients , especially in large epidemics .
The association between cholera in pregnancy and negative fetal outcome has been described since the 19th century [1] . Modern published literature reports fetal loss rates during cholera episodes as varying between 2% and 36% [2]–[7] . However , comparison of outcomes among different reports is difficult , due to differences in inclusion criteria ( trimester of pregnancy , severity of dehydration , hospitalization , and biological confirmation ) , treatment provided , and the development level of countries where these reports originated . Although the exact cause of fetal death during a cholera episode has not been identified , several studies suggest an association between fetal loss and the degree of dehydration and hypovolemia [3] , [5]–[7] . Correction of hypovolemia is further complicated in pregnancy , since it can be difficult to accurately estimate the degree of dehydration , especially during the second half due to maternal physiological hypervolemia [8] . In Haiti , over 500 , 000 cholera cases and 7 , 000 deaths were registered between the beginning of the epidemic in October 2010 and early 2012 [9] . Since the outbreak began , anecdotal accounts from treatment units suggested high fetal loss among women delivering in cholera treatment units; for example , during the first weeks of the outbreak , Médecins Sans Frontières ( MSF ) reported 14 stillbirths among the 17 deliveries at one of its cholera isolation units in an obstetric hospital in Port-au-Prince [10] . The objective of this retrospective study was to describe pregnancy outcomes and identify risk factors for negative outcome from routinely collected data in a specialized cholera treatment unit within an MSF hospital in Léogâne .
Léogâne , a town of about 80 , 000 inhabitants situated 50 km west of Port-au-Prince , was almost completely destroyed during the 2010 earthquake . In November 2010 , MSF set up a cholera treatment center in the outskirts of the town , as well as a specialized isolation unit for pregnant cholera patients inside the hospital compound . The hospital , a second level district facility , serves the population of the town and the commune of Léogâne ( 300 , 000 people ) and includes an obstetric and gynecology department with a neonatal intensive care unit . The obstetric department is particularly busy , averaging 300 deliveries per month in 2010 . The cholera isolation unit for pregnant women , with a capacity of 20 beds , was established within the hospital compound . Following standard isolation procedures , the unit was separated by a fence from the rest of the hospital and had independent water and sanitation facilities . The unit comprised a delivery room and , in a separate container building , an operating theatre for emergency surgical obstetric interventions . The isolation unit was open to all pregnant women with suspected cholera . Pregnancy status was by self report . A suspected cholera case was defined as any patient presenting with three or more liquid stools and/or vomiting episodes in the previous 24 hours . Association of pregnancy with cholera was classified as a complication , and therefore hospitalization was offered to all pregnant women with cholera , regardless of their level of dehydration . Other cholera treatment centers in the region were advised to refer pregnant women with suspected cholera to this unit . Patients' dehydration status was classified according to World Health Organisation ( WHO ) categories: no dehydration ( plan A ) , moderate dehydration ( plan B ) or severe dehydration ( plan C ) [11] . WHO and MSF guidelines for cholera treatment were followed [11] , [12] . In summary: patients with severe dehydration ( plan C ) received 100 ml of Ringer's lactate IV per kg of body weight in the first 3–4 hours ( 30 ml/kg in the first hour , and 70 ml/kg in next 3 hours ) , patients with moderate dehydration ( plan B ) received 75 ml/kg of Ringer's lactate IV in the first 4 hours , and patients without signs of dehydration ( plan A ) received maintenance fluids only ( 2 l of IV Ringer lactate per day ) . To correct on-going losses , all patients received 250 ml of ORS orally ( or Ringer lactate intravenously in case of vomiting ) after each stool . Once the dehydration was corrected , patients continued to receive IV maintenance fluids , with continuous correction of ongoing losses . As for any cholera patient , the objective was to rehydrate the patient rapidly , but we also wanted to avoid any dehydration episodes that might not be dangerous for the mother but could cause hypoperfusion of the placenta leading to fetal death . We privileged intravenous fluid replacement because pregnant women are more likely to experience nausea and vomiting and therefore have difficulty drinking enough fluids to replace the losses immediately . Throughout their hospitalization the dehydration status of each patient was closely monitored clinically , including the measurement of blood pressure and pulse rate . No laboratory tests were done systematically , but blood glucose level was measured in cases where hypoglycemia was suspected . During the early phases of Haiti's cholera epidemic , we observed several cases of severe hypoglycemia in adults . As a preventive measure , all pregnant women in our cholera unit therefore received a 50 ml bolus of 50% glucose upon admission . Patients who were vomiting or unable to drink ORS received an additional 50 ml of 50% glucose in each liter of Ringer's lactate . The level of plasma glucose was monitored and replacement adjusted accordingly . All patients received oral antibiotics ( erythromycin ) , in order to reduce the purging rate , shorten its duration and reduce the excretion of Vibrio cholerae in the stool [13] . Patients in their second or third trimester were encouraged to lie in the left decubitus position , to prevent compression of the inferior vena cava . Fetal status was closely monitored by a midwife through the presence of fetal movement and heartbeat ( confirmed by fetal Doppler ) . In the absence of fetal heartbeat , fetal status was checked by ultrasonography . Tocolysis was available in case of premature labor . Standard delivery procedures were followed , and the perineal region and newborn baby were disinfected with 0 . 05% chlorine solution . In cases of neonatal complications , immediate resuscitation took place in the delivery room and referral to the intensive care neonatal unit was done as needed . Newborns without severe complications remained hospitalized with their mothers until discharge . Exclusive breastfeeding was encouraged and maternal breasts were disinfected with 0 . 05% chlorine solution before each feeding . Cases of incomplete abortion were treated according to MSF protocol [14] . Cases of intrauterine fetal death were confirmed by ultrasonography and managed with misoprostol , after stabilization of cholera symptoms . Patients remained hospitalized until they fully recovered from cholera and completed treatment for any obstetrical complications . Before discharge , all patients received a cholera health education session . The unit adapted the standard cholera patient file and , upon admission , recorded demographic data ( age ) and information related to pregnancy ( gestational age by week , parity and gravidity ) , cholera episode ( estimation of dehydration status , blood pressure , pulse rate , temperature at admission , time of onset ) , and fetal status ( presence of fetal heartbeat , movement ) . Dehydration level was classified as described above [11] . Patients were closely monitored during hospitalization and relevant surveillance data was recorded , including dehydration status , number of stool and vomiting episodes , amount of fluid and any medication received , and fetal status monitoring . Relevant events during hospitalization , such as miscarriage , delivery and procedures undertaken , were also reported . At discharge , the outcome of the patient and the pregnancy was recorded . Data was entered in Excel and analyzed using Stata 9 . 0 statistical package ( College Station , Texas , USA ) . Intrauterine fetal death was defined as fetal death at any time during pregnancy . Risk ratios for fetal death were calculated; to control for confounding factors , variables from univariate analysis ( significant at p<0 . 4 level ) were included into the logistic regression model , using backward selection ( likelihood ratio test , p<0 . 05 ) . Missing data were not imputed . The analysis was based on routinely collected clinical data from an MSF program , conducted in agreement with the Ministry of Health in Haiti; therefore ethical review and individual patient consent were not sought . Data used for analysis were anonymized .
The median age was 26 years ( range 16–43 years ) . Half of all patients were in their second trimester of pregnancy , 34% were in the third , and the remaining 14% in the first trimester . For 22% of patients it was their first pregnancy , for 44% , their second or third one , and for the remaining 33% , their fourth or more ( up to 14 pregnancies ) . Among 263 women in this analysis , 14 had obstetric complications at admission: these included preeclampsia ( 3 ) , urinary tract infection ( 3 ) , vaginal bleeding ( 3 ) , hypertension with kidney failure ( 1 ) , vaginal infection ( 1 ) , pre-existing severe vomiting ( 1 ) , jaundice ( 1 ) , and ruptured membranes ( 1 ) . Two patients were febrile ( axillary temperature >38°C ) at admission . Five women arrived with threatened pre-term labor and were given tocolysis . The median delay in seeking treatment was 1 day ( range 0–8 days ) . On admission 51% of patients were not dehydrated , 42% were moderately dehydrated , and 6% were severely dehydrated; almost all patients passed watery stools . The median number of stools per cholera episode was 34 ( range 0–311 ) . Almost 60% of patients were vomiting during hospitalization . Patients received on average 12 litres of Ringer's lactate . The median length of stay was 3 days ( range 0–10 days ) . No pregnant women died during hospitalization . No signs of fluid overload were reported . Of the 263 hospitalized pregnant women in this analysis , 226 ( 86% ) were discharged with a preserved pregnancy; 16 ( 6% ) women delivered a live baby of 35–40 weeks of gestation . 21 pregnancies ( 8% ) resulted in intrauterine fetal death ( Table 1 ) . Among these 21 intrauterine fetal deaths , 10 occurred before the mother's arrival at the cholera treatment unit and 9 occurred after admission; timing of the remaining 2 fetal deaths could not be determined . Of the 9 fetal deaths that occurred during hospitalization , the median delay between admission and time that fetal death was noticed or confirmed was 48 hours ( mean 62 hours , range 7–144 hours ) . There was no difference in dehydration status of the women whose fetuses died before or after admission . For 7 patients the dehydration level was recorded at the time confirmation of fetal death: 1 was severely dehydrated , 5 were moderately dehydrated and 1 was not dehydrated . Nearly all fetal deaths occurred during the second ( 10/21 ) or third trimester ( 8/21 ) of pregnancy . Among the 16 singleton newborns there were 2 neonatal deaths . Both were low birth weight ( <2500 g ) , one born at 35 weeks of gestation and the other at 40 weeks . One death occurred on day 5 postpartum and was associated with congenital malformations and necrotic enteritis . The second death occurred after 24 hours postpartum in a newborn with an Apgar score of 2 and who showed no improvement . Both newborns were admitted to the hospital's intensive care . For the remaining 14 newborns , we were able to contact 9 mothers at 1 to 5 weeks after their discharge from the treatment unit . All children were alive and healthy at the time of our call , apart from one infant who was sick with flu-like syndrome . The risk factors associated with fetal death during cholera in pregnancy are shown in Table 2 and were linked to the severity of the cholera episode: dehydration status on admission , number of stools passed , presence and number of vomiting episodes , number of litres of Ringer's lactate received during the treatment , and length of hospitalization . Risk factors for complicated pregnancy and childbirth , such as young or older age and the number of previous pregnancies and deliveries were not associated with negative outcome during cholera in pregnancy . After adjusting for confounding factors , the severity of dehydration remains the strongest risk factor for fetal death during cholera in pregnancy ( adjusted risk ratio ( RR ) for severe vs . mild dehydration is 9 . 4 ( 95% CI 2 . 5–35 . 3 , p = 0 . 005 ) ) . Severe vomiting also remains a statistically significant risk factor , independent of the severity of dehydration ( RR 5 . 1 , 95% 1 . 1–23 . 8 , p = 0 . 041 ) . The severity of dehydration remains the most important risk factor once fetal deaths that occurred before the admission are excluded from the analysis .
We describe pregnancy outcomes of cholera patients during a cholera epidemic in Haiti . Our findings are in line with the hypotheses of previous authors , suggesting a link between the risk of fetal death and the severity of maternal dehydration due to cholera . Close supervision of the hydration status of pregnant women , as well as availability of high quality obstetric and neonatal services , can help prevent negative maternal , fetal and neonatal outcomes . In addition , this strategy reinforces a woman-centered approach to patient care and helps protect her dignity . Our experience in Haiti suggests that setting up specialized multidisciplinary units to treat pregnant women with cholera could be beneficial , especially in large epidemics . Further research is needed to better understand the mechanism of fetal death during cholera episode , to estimate the degree of dehydration in pregnancy , using laboratory tests or others , and to propose better adapted treatment protocols for this high risk group of cholera patients . While clinical trials for such relatively rare events might be difficult to conduct , we encourage other clinicians treating cholera patients to document the pregnancy outcomes and any adaptation of treatment protocols , which might contribute to the understanding and treatment of these neglected patients . | Cholera in pregnancy has been long associated with high rates of stillbirths and abortions , but there is very limited published literature describing this association or possible mechanisms . During the major cholera epidemic that hit Haiti in October 2010 , we set-up a specialized cholera treatment unit for pregnant women inside the Médecins sans Frontières hospital in Léogâne , allowing for intensive follow-up of cholera-associated dehydration and of pregnancy , and facilitating access to high-quality obstetric and neonatal services in case of complications . To describe the pregnancy outcomes and risk factors for fetal death , we analyzed routinely collected data from patient files . Of 263 women hospitalized , 21 ( 8% ) lost their pregnancy during hospitalization for cholera; an additional 16 ( 6% ) delivered a live baby at the hospital , and the remaining 226 women ( 86% ) were discharged with preserved pregnancy . The risk factor most strongly associated with fetal demise was severity of dehydration at admission . In large epidemics , multidisciplinary units can help prevent negative maternal , fetal and neonatal outcomes . | [
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"cholera",
"obstetrics",
"and",
"gynecology",
"pregnancy"
] | 2013 | Cholera in Pregnancy: Outcomes from a Specialized Cholera Treatment Unit for Pregnant Women in Léogâne, Haiti |
Intracellular pathogens must withstand nitric oxide ( NO· ) generated by host phagocytes . Salmonella enterica serovar Typhimurium interferes with intracellular trafficking of inducible nitric oxide synthase ( iNOS ) and possesses multiple systems to detoxify NO· . Consequently , the level of NO· stress encountered by S . Typhimurium during infection in vivo has been unknown . The Base Excision Repair ( BER ) system recognizes and repairs damaged DNA bases including cytosine and guanine residues modified by reactive nitrogen species . Apurinic/apyrimidinic ( AP ) sites generated by BER glycosylases require subsequent processing by AP endonucleases . S . Typhimurium xth nfo mutants lacking AP endonuclease activity exhibit increased NO· sensitivity resulting from chromosomal fragmentation at unprocessed AP sites . BER mutant strains were thus used to probe the nature and extent of nitrosative damage sustained by intracellular bacteria during infection . Here we show that an xth nfo S . Typhimurium mutant is attenuated for virulence in C3H/HeN mice , and virulence can be completely restored by the iNOS inhibitor L-NIL . Inactivation of the ung or fpg glycosylase genes partially restores virulence to xth nfo mutant S . Typhimurium , demonstrating that NO· fluxes in vivo are sufficient to modify cytosine and guanine bases , respectively . Mutants lacking ung or fpg exhibit NO·–dependent hypermutability during infection , underscoring the importance of BER in protecting Salmonella from the genotoxic effects of host NO· . These observations demonstrate that host-derived NO· damages Salmonella DNA in vivo , and the BER system is required to maintain bacterial genomic integrity .
Host innate immunity represents the first line of defense against invading pathogenic microorganisms . Nitric oxide ( NO· ) is an essential component of this innate immune system , which is required for the efficient clearance of pathogenic fungi , viruses , parasites and bacteria [1] , [2] . Inflammatory NO· is produced by the inducible Nitric Oxide Synthase ( iNOS ) of activated phagocytes [3] . NO· exposure can inhibit bacterial growth through the modification of multiple intracellular targets including protein thiols , heme containing proteins , thiol-coordinated metals , lipid bilayers , and DNA [4]–[8] . The Type III Secretory System ( TTSS ) of S . Typhimurium encoded on Salmonella Pathogenicity Island 2 ( SPI2 ) impedes trafficking of iNOS to the Salmonella Containing Vacuole ( SCV ) in host macrophages [9] . In addition , NO· is detoxified by the Hmp flavohemoglobin , which is required for virulence in hosts proficient for inflammatory NO· production [10] . Thus , Salmonella has evolved multiple mechanisms to limit bacterial NO· exposure during infection , and consequently the degree of nitrosative stress to which S . Typhimurium is subjected in vivo is unknown . Although NO· does not directly damage DNA , NO· congeners such as nitrous anhydride ( dinitrogen trioxide , N2O3 ) or peroxynitrite ( ONOO− ) are capable of directly modifying nucleic acids [8] , [11] . Nitrous anhydride generated from the spontaneous NO· autooxidation is a potent deaminating species of the DNA bases guanine , adenine , and cytosine , to produce xanthine ( dX ) , hypoxanthine ( dHX ) , and uracil ( dU ) , respectively [8] . Unless repaired , dU , dX and dHX in a DNA molecule are highly mutagenic resulting in transition mutations , i . e . , GC→AT or AT→GC . Peroxynitrite produced by the reaction of NO· and superoxide ( O2− ) is an oxidant that can preferentially target guanine residues in DNA to produce mutagenic 8-oxoguanine and unstable 8-nitroguanine residues [11] , [12] . Moreover , the increased reactivity of 8-oxoguanine towards peroxynitrite can produced secondary cytotoxic oxidation products [11] . Thus , cells exposed to high concentrations of host NO· must respond to both mutagenic and cytotoxic DNA lesions . However , whether host-derived NO· is capable of promoting mutagenesis of intracellular S . Typhimurium has not been determined . The base excision repair ( BER ) pathway has proven to play a critical role in the defense against the deleterious effects of NO· . BER involves the recognition of modified bases by specific DNA glycosylases , which cleave the N-glycosidic bonds of damaged bases to release them from the phosphodiester DNA backbone . In enteric bacteria , several DNA glycosylases are responsible for the removal of damaged DNA bases . Following base deamination , Uracil DNA Glycosylase ( Ung ) is required for the removal of dU , and 3-methyladenine DNA glycosylase ( AlkA ) can remove dX and dHX residues [13] , [14] . Oxidized guanines ( i . e . , 7 , 8-dihydro-8-oxodeoxyguanine ( 8-oxoG ) and formamidopyrimidine ( FapyG ) ) are processed by Formamidopyrimidine DNA glycosylase ( Fpg ) , which can also recognize hypoxanthine and xanthine , albeit with lower affinity [15] , [16] . A related enzyme , Endonuclease VIII ( Nei ) , removes oxidized pyrimidines , although Nei can also exhibit activity towards FapyG and 8-oxoG [17] . Finally , Endonuclease III ( Nth ) repairs oxidized and ring-saturated pyrimidine bases , although these lesions are not typically associated with nitrosative stress [18] . The AP sites resulting from glycosylase-mediated base removal cannot be acted upon directly by DNA polymerase and may consist of altered DNA ends such as a 3′-PO4 or a 3′-phospho-α , β-unsaturated aldehyde . Rather , glycosylase-generated AP sites must first be processed by one of two AP endonucleases in enteric bacteria , endonuclease IV ( Nfo ) and exonuclease III ( Xth ) , the latter of which comprises ∼90% of total cellular AP endonuclease activity [19] , [20] . AP endonuclease processing leaves 5′-PO4 and 3′-OH DNA ends that can be repaired by DNA polymerase I ( PolA ) and ligase . Cells devoid of AP endonuclease activity ( xth nfo ) have been shown to be hypersusceptible to ionizing radiation , oxidative stress and NO· exposure in Escherichia coli and Salmonella enterica serovar Typhimurium [21] , [22] . Without AP endonuclease activity , glycosylase-generated AP sites can persist and yield more serious single- and double-strand breaks , lesions known to be toxic to rapidly dividing cells [23] , [24] . It has been hypothesized that glycosylases recognize and remove NO·-modified bases , resulting in an accumulation of AP sites that reduces the viability of nitrosatively-stressed xth nfo mutant bacteria [23] . Indeed , inactivation of specific glycosylases in E . coli , particularly ung and fpg , partially reverses the NO· sensitivity of xth nfo mutants suggesting that elimination of the source of excess AP sites is beneficial to nitrosatively stressed cells devoid of AP endonuclease activity [23] . Moreover , NO· treatment of E . coli results in increased RecA-dependent recombination that can be ameliorated by further inactivation of ung or fpg [23] . Thus , NO·-stressed cells appear to suffer an abundance of double-strand breaks that presumably arise from unprocessed AP sites . Previous studies of wild type S . Typhimurium failed to provide evidence of direct DNA damage in the intramacrophage environment [25] . However , Suvaranapunya and Stein found that xth nfo mutant S . Typhimurium exhibits impaired survival in cultured macrophages and a competitive defect in mice , implying that base damage occurs during Salmonella-host cell interactions [22] . The macrophage survival defect was dependent on the production of reactive oxygen or nitrogen species , as it was not observed in macrophages deficient in both the NADPH phagocyte oxidase and inducible NO· synthase ( phox−/− iNOS−/− C57BL/6 peritoneal elicited macrophages ) [22] . Thus , host innate immunity appears to cause DNA base damage in S . Typhimurium in the intracellular environment . However , these investigators failed to establish a specific contribution of NO· , nor did they determine whether excess AP sites in xth nfo mutant S . Typhimurium arise spontaneously or result from glycosylase-mediated repair of damaged bases during infection . Given that many DNA glycosylases ( e . g . Fpg , Nei and Nth ) can be inactivated by NO·-exposure , the ability of these enzymes to contribute to the generation of AP sites in the presence of NO· has been questioned [26]–[28] . The present study extends earlier work in the context of the host-pathogen interaction by exploiting the NO·-sensitivity and attenuated virulence of xth nfo mutant S . Typhimurium to probe the mechanism of DNA base damage during infection . In addition , the effects of NO· on bacterial mutation rates within the host environment have been determined . Our observations demonstrate for the first time that host-derived reactive nitrogen species are able to cause DNA base damage in intracellular bacteria , leading to the glycosylase-mediated generation of AP sites . More importantly , while BER is dispensable for S . Typhimurium to cause acute lethal infection in mice , this pathway is sufficient to limit all mutagenic effects associated with host-generated NO· .
An S . Typhimurium xth nfo mutant lacking AP endonuclease activity is hypersensitive to NO· , as demonstrated by a ∼12 h growth lag following the addition of 1 mM Spermine NONOate ( SperNO ) ( Figure 1A ) . The extended lag period is attributable to increased cell death observed in NO·-exposed xth nfo mutants as compared to wild type cells ( Figure 1B ) . The xth nfo mutant was killed rapidly following administration of SperNO , and cell killing continued for three hours until the NO· had been detoxified ( Figure 1B ) . This directly contrasts with the bacteriostatic actions of NO· on wild type cells ( Figure 1B ) . Additional inactivation of the ung or fpg glycosylase genes in xth nfo S . Typhimurium reduced the extended lag interval by 5 h and 4 h , respectively , and significantly enhanced survival during nitrosative stress ( Figure 1A and 1C ) . Moreover , the ameliorative effects of ung or fpg inactivation on the NO·-sensitivity of the xth nfo mutant were additive , as demonstrated in an ung fpg xth nfo mutant strain ( Figure 1A and 1C ) . In contrast , inactivation of nei or nth had little effect on the NO·-sensitivity of xth nfo mutants , suggesting that pyrimidine oxidation does not occur readily in NO·-exposed DNA ( Figure 1A and 1C ) . Inactivation of alkA did not improve the survival of xth nfo cells during nitrosative stress , consistent with previous observations in E . coli [23] , even though xanthine and hypoxanthine residues are known to accumulate in DNA following NO·-exposure [29] . Collectively , these data indicate that growth arrest correlates with decreased cell survival following NO·-exposure ( Figure 1A and 1C ) . The enhanced NO·-susceptibility of xth nfo S . Typhimurium appears to be a consequence of the accumulation of lethal Ung- and Fpg-generated AP sites during the repair of NO·-exposed DNA . C3H/HeN mice infected i . p . with 103 cfu of S . Typhimurium 14028s or isogenic mutant derivatives demonstrated the attenuated virulence of an xth nfo mutant ( Figure 2A and 2B ) . Virulence was completely restored to the xth nfo strain by oral administration of the NOS2-specific inhibitor L-NIL [L-N6- ( 1-iminoethyl ) -lysine] [30] ( Figure 2A ) . Furthermore , the competitive defect of xth nfo mutant versus wild type cells was abrogated by the inhibition of NO· production ( Figure 2B ) . In concordance with the in vitro observations , the inactivation of ung or fpg increased the virulence of an xth nfo mutant , indicating that host-derived NO· leads to enzymatically-generated chromosomal AP sites ( Figure 2B and 2C ) . The additional inactivation of other DNA glycosylases such as nei and nth had no effect on the virulence of an xth nfo mutant ( data not shown ) . Although the inactivation of ung significantly increased the virulence of an xth nfo mutant strain , the ung mutation failed to restore full wild type virulence . This is best rationalized by the attenuating effects of an ung mutation in isolation; ung and xth nfo ung mutants display comparable virulence phenotypes ( data not shown ) . The explanation for the effects of an isolated ung mutation on Salmonella virulence is presently unknown . Nevertheless , it can be concluded that Fpg and Ung together are responsible for a significant fraction of NO·-induced chromosomal AP sites during S . Typhimurium infection of murine hosts , making AP endonucleases ( Xth and Nfo ) essential in this setting . Treatment of wild type S . Typhimurium with authentic NO· ( from the NO· donor SPER/NO ) resulted in a ∼14-fold increase in the rate of resistance to rifampin ( Table 1 ) . Exposure to peroxynitrite ( ONOO− ) or other oxidants generated by SIN-1 ( 3-morpholinosydnonimine ) increased rifampin resistance rates by two-fold . SIN-1 can promote metal-catalyzed oxidative damage in addition to peroxynitrite-mediated cytotoxicity [31] . However , no effect of iron chelation was observed when this experiment was repeated in the presence of SIN-1 and 2 , 2′-dipyridyl ( data not shown ) . S . Typhimurium ung mutants exhibited hypermutability even in the absence of NO· , reflecting basal levels of spontaneous cytosine deamination . However , following NO· exposure , ung mutants displayed mutation rates more than 50% higher than wild type cells ( Table 1 ) . In contrast , SIN-1 treatment did not significantly affect the mutability of ung cells , whereas SIN-1 doubled the mutation rates in wild type S . Typhimurium and quadrupled mutation rates in fpg mutant cells . These observations are consistent with differential targeting by various reactive nitrogen species . NO·-mediated deamination of cytosine in vitro results in C→T transitions that are counteracted by Ung . Similarly , peroxynitrite-dependent guanine oxidation results in G→T transversions that appear to be limited by Fpg . Rates of spontaneous resistance to conventional antibiotics like rifampin are too low ( ∼5×10−8 ) to be readily used as a measure of mutation frequency in vivo since total pre-terminal bacterial burdens in the murine Salmonella model only modestly exceed 106 cfu/organ . An assay based on resistance to the antifungal agent 5-fluorocytosine ( 5-FC ) was therefore used to measure bacterial mutation rates in vivo . 5-FC resistance results from loss-of-function mutations in the codBA genes that encode a cytosine permease and deaminase , respectively [32] , [33] . Mutations that inactivate codA or codB prevent transport of the base analog into the cell or conversion to the highly toxic metabolite 5-fluorouracil , respectively . Measurement of 5-FC resistance in wild type S . Typhimurium recovered from the livers of infected mice demonstrated that host NO· does not exert mutagenic effects on Salmonella during infection; i . e . , inhibition of host NO· production did not reduce observed 5-FC resistance rates ( Figure 3 ) . In contrast to wild type cells , NO·-mediated hypermutability was observed in S . Typhimurium strains lacking Ung or Fpg . In the case of ung mutant cells , the 12-fold excess in 5-FC mutation rate observed in vivo was entirely attributable to host NO· , as the administration of L-NIL completely eliminated hypermutability ( Figure 3 ) . In contrast , the 21-fold increase in 5-FC resistance exhibited by fpg mutant cells was only partially a consequence of DNA damage by host NO· ( Figure 3 ) . Treatment of fpg mutant-infected mice with L-NIL reduced bacterial mutability by 6-fold , although this mutant strain still exhibited 5-FC resistance rates significantly higher than those of wild type cells . This suggests that Fpg also plays a role in limiting mutations caused by NO·-independent mediators in the host environment , e . g . , reactive oxygen species produced by the NADPH phagocyte oxidase .
A hallmark of Salmonella pathogenesis is the organism's ability to survive and replicate within the vacuoles of professional phagocytic cells . In this environment , Salmonella is exposed to cytotoxic NO· ( or its congeners ) produced by inducible NO· synthase ( iNOS , NOS2 ) . Thus , S . Typhimurium harbors many factors that allow it resist the cytotoxic effects of NO· and its oxidized congeners ( e . g . , the Hmp flavohemoglobin ) [10] . This work demonstrates that Salmonella is additionally capable of avoiding the mutagenic effects of host NO· and maintaining genomic stability despite the highly genotoxic host environment . Mutant strains lacking specific elements of the Base Excision Repair ( BER ) pathway , in combination with the measurement of in vivo mutation rates , have allowed us to demonstrate NO·-dependent bacterial DNA damage in a murine infection model . S . Typhimurium xth nfo mutants lacking AP endonuclease activity exhibit hypersusceptibility to NO· as well as to a variety of DNA damaging treatments including reactive oxygen species , alkylating agents , and UV- or Γ-irradiation . Each of these conditions generates an excess of chromosomal AP sites resulting either from direct modification of nucleic acids or the actions of various BER glycosylases . The accumulation of AP sites in an xfo nth mutant ultimately results in double strand breaks and chromosomal fragmentation . The NOS-dependent attenuation of S . Typhimurium xth nfo mutants during infection indicates that exposure to host-derived NO· is sufficient to damage bacterial DNA and generate AP sites ( Figure 2 ) . Previous work suggested that Salmonella DNA damage during infection might be attributable to either NO· or O2−-production [22] , but our observations specifically implicate NO· in the creation of excess AP sites requiring Xth or Nfo for repair . AP endonuclease activity is dispensable for Salmonella during infection of L-NIL treated mice ( Figure 2 ) , although L-NIL inhibits only NO· but not O2− production . NO· is able to mediate the deamination of DNA bases that contain primary amines: cytosine , guanine and adenine [8] . However , inactivation of the alkA- and/or tag-encoded glycosylases does not affect the NO·-sensitivity of xth nfo mutants , implying that glycosylase-mediated removal of deaminated dG ( dX ) or dA ( dHX ) does not contribute significantly to NO· generation of AP sites ( Figure 1C ) . This may be because dX and dHX can also be removed from NO·-damaged DNA by Endonuclease V ( nfi ) , a redundant repair enzyme that does not require additional AP endonuclease processing [34] . In contrast , no backup pathway exists for the removal of chromosomal dU produced by cytosine deamination , so the repair of NO·-deaminated dC relies exclusively on the Ung glycosylase and subsequent processing by Xth or Nfo . This accounts for the particular importance of dU in the sensitivity of xth nfo mutant S . Typhimurium to NO· . The deamination of dC by NO· is not the only potential source of increased genomic dU requiring BER . The dut gene encodes a dUTPase enzyme responsible for minimizing the steady state concentration of dUTP in the free nucleotide pool . Mutations in dut result in increased DNA misincorporation of dUTP . The role of AP endonucleases in removing dU from misincorporation is demonstrated by the synthetic lethality of dut-1 and xth mutations [35] . In a dut-1 background , the Ung glycosylase eliminates misincorporated dU in DNA but generates AP sites that are repaired by Xth . Accordingly , the conditional lethality of dut-1 and xth mutations can be ameliorated by the inactivation of ung [36] . Interestingly , many other DNA repair genes are also synthetically lethal when combined with a dut-1 mutation ( including xth , polA , lig , recA , recBC , and ruvABC ) [36] . Mutations in many of these same genes increase sensitivity to NO· in vitro and attenuate bacterial virulence [21] , [37] . Thus , dUTP misincorporation in a dut-1 mutant simulates the increased dU resulting from NO·-mediated dC deamination . Both conditions result in an excess of AP sites following Ung-mediated removal of chromosomal dU , and thus both conditions require intact BER and recombinational repair for viability . NO·-dependent DNA damage is not limited to base deamination . The products of activated macrophages can oxidize chromosomal dG bases at the C8 position , primarily generating 8-oxoG ( 8-oxoguanine ) and Fapy ( formamidopyrimidines ) [38] . NO· , when combined with superoxide to form the potent oxidant peroxynitrite , can potentiate the formation of 8-oxo-G and Fapy [24] , [37] . 8-oxoG and Fapy are the predominant substrates for the Fpg glycosylase , as are some forms of oxidized pyrimidines ( e . g . , uracil glycol , 5-hydroxycytosine and 5-hydroxyuracil ) unassociated with NO·-exposure . The partial restoration of NO·-resistance and virulence in xth nfo mutant S . Typhimurium following the inactivation of fpg is consistent with the generation of AP sites by Fpg-mediated excision of NO·-damaged dG . This implies that some Fpg activity is present in NO·-exposed S . Typhimurium during infection , despite the NO·-labile zinc-finger domain of Fpg [28] . Furthermore , these data suggest that sufficient concentrations of peroxynitrite are generated to result in dG oxidation in vivo . 8-oxoG , together with deaminated DNA bases , accounts for a major portion of the glycosylase-mediated AP sites generated by host NO· exposure . While the NO·-sensitivity of xth nfo can be used as a probe to identify the types of base damage resulting from nitrosative stress , an intact BER pathway protects S . Typhimurium from the cytotoxic effects of host NO· . Nevertheless , high concentrations of nitrogen oxides are mutagenic for wild type S . Typhimurium . Exposure of S . Typhimurium in culture to NO· released from 1 mM SperNO increases the measurable mutation rate by nearly 14-fold ( Table 1 ) . A significant proportion of NO·-induced mutation is limited by Ung-mediated removal of dU . Of the two sources of chromosomal dU , dUTP incorporation is far more abundant ( 105-fold ) than spontaneous dC deamination [39] , but is not mutagenic because dUTP only pairs with dA . The tendency of dut-1 ung mutants to accumulate significant chromosomal dU levels ( nearly 1 dU residue per 125 nucleotides ) without severe physiological consequences demonstrates that chromosomal dU is not inherently detrimental to the cell [40] , [41] . However , the mutagenic potential of deaminated dC provides a strong selective pressure for the presence of Ung activity . Indeed , ung mutants possess inherent increased baseline mutability resulting from spontaneous dC deamination that is exacerbated by the addition of NO· ( Table 1 ) [42] . Furthermore , S . Typhimurium ung mutants exhibit a 12-fold increase in 5-FC resistance rates compared with wild type cells during infection ( Figure 3 ) . This in vivo hypermutability is the direct result of NO·-mediated dC deamination , as the inhibition of murine NO·-production eliminates excess mutability associated with the ung mutation ( Figure 3 ) . Nevertheless , it is also noteworthy that wild type Salmonella does not exhibit NO·-dependent hypermutability during infection , indicating that Ung and BER are sufficient to remove excess deaminated dC arising from host NO·-exposure . In addition to its cytotoxic effects , 8-oxoG can also be mutagenic resulting from its propensity to form 8-oxo-dG:dA pairs . However , the contribution of oxidized dG to overall NO·-induced hypermutability in broth cultures in vitro appears to be less than that of deaminated dC . Specifically , NO·-exposed ung cells in broth culture exhibit elevated mutability compared with wild type bacteria , but NO·-treated fpg mutants do not ( Table 1 ) . This can be rationalized by the existence of other DNA glycosylases that protect against 8-oxoG-associated mutations , e . g . , MutY and Nei [43] . MutY specifically removes dA paired to 8-oxoG , and Nei can also remove chromosomal 8-oxoG , albeit with lower efficiency . Furthermore , the low production of peroxynitrite in aerated NO·-treated broth cultures would be anticipated to reduce the frequency of 8-oxoG-derived mutations . Indeed , fpg mutants exhibit significantly greater mutability than wild type cells upon direct exposure to the peroxynitrite generated following the addition of SIN-1 to highly aerated cultures . Moreover , during infection when Salmonella is exposed to high levels of both NO· and reactive oxygen species , the role of Fpg in avoiding NO·-mediated hypermutation is readily apparent ( Figure 3 ) . S . Typhimurium fpg mutants exhibit a 21-fold increase in 5-FC resistance rates during infection compared with wild type cells . Whereas host-derived NO· is solely responsible for the in vivo hypermutability observed in ung mutant bacteria , iNOS inhibition with L-NIL in mice infected with fpg mutant S . Typhimurium fails to eliminate all excess bacterial mutability ( Figure 3 ) . Damaged DNA base substrates for Fpg can be created by reactive oxygen species independently from peroxynitrite , accounting for the residual hypermutability of fpg mutant bacteria in L-NIL treated mice . These observations suggest that Salmonella growing in an immunocompetent host encounter peroxynitrite , but the bacterium is capable of minimizing the mutagenic effects of this oxidant through the actions of Fpg and the BER pathway ( Figure 4 ) . Collectively , this work demonstrates that the Salmonella chromosome incurs high levels of base deamination and guanine oxidation during infection as a result of host NO· production , but BER limits the mutagenic effects associated with these DNA modifications ( Figure 4 ) . The function of BER is not to prevent bacterial killing by NO· , because cytosine deamination and guanine oxidation are not lethal per se , but rather to preserve genomic fidelity . While it continues to be debated whether enhanced mutation rates can be adaptive under stress conditions [44] , our observations indicate that BER allows S . Typhimurium to maintain a low mutation rate despite the stressful intracellular environment . It has been suggested that host DNA damage resulting from inflammation may lead to permanent tissue damage , chromosomal lesions and cancer [37] , [45] . Our studies suggest that an important human pathogen is able to use a highly conserved DNA repair pathway to limit the genotoxic effects of NO· generated by the host inflammatory response .
Bacteria used in this study are derivative of S . Typhimurium 14028s and are listed in Table 2 . Strains were routinely grown in Luria-Bertani ( LB ) broth and the following antibiotics were added when appropriate: penicillin G ( 250 μg·ml−1 ) kanamycin ( 50 μg·ml−1 ) , and chloramphenicol ( 40 μg·ml−1 ) . When indicated , culture medium was supplemented with 1 mM concentrations of the NO· donor Spermine/NONOate ( SperNO ) ( Cal Biochem ) or 4 mM concentrations of the peroxynitrite-generator SIN-1 ( A . G . Scientific , Inc . ) . Mutant S . Typhimurium strains were constructed using the λ−red method ( Table 2 ) [46] . Each mutation was confirmed by PCR analysis using gene-flanking primers ( Table 2 ) , then transduced via P22 phage back into wild type 14028s . Growth kinetics following NO·-exposure was determined by measuring optical density at 600 nm at 37°C using a Bioscreen C incubator/reader ( Growthcurves USA ) . Overnight culture were diluted to 1:100 in LB medium and grown to early log phase ( OD600 ∼0 . 2 ) before the addition of 1 mM SperNO . For cell viability determination , bacterial samples were taken hourly and serially diluted and plated onto LB agar following NO· exposure . Colony forming units ( cfu ) were scored after incubation at 37°C for 18 hrs . Six to eight week old CH3/HeN mice ( Charles River Laboratories ) were inoculated intraperitoneally with 1×103 cfu of wild type and isogenic mutants S . Typhimurium strains . Survival was monitored in twelve mice were used for each tested condition . The mice were checked twice daily for 28 days and moribund mice sacrificed per IACUC protocol . Competitive defects in mutant bacteria were also assessed in murine liver and spleen tissue from 5 mice each on days 3 , 5 , 7 and 9 post-infection . Tissue was homogenized and plated on appropriate antibiotics . Competitive indices were determined as the ratio ( mutant:WT ) OUT to ( mutant:WT ) IN . To selectively inhibit NO· production by NOS2 , L-NIL [L-N6- ( 1-iminoethyl ) -lysine] was administered via drinking water at 500 μg·ml−1 . L-NIL has been shown to have ∼30 fold selectivity for the inhibition of NOS2 over other NOS isoforms [30] . In vitro mutation frequency of wild type and mutant S . Typhimurium was measured as the rate of spontaneous rifampin-resistance ( resulting from mutations in rpoB ) . Overnight cultures of Salmonella were diluted 1:100 in 5 ml of fresh LB exposed either to 1 mM SperNO or 4 mM SIN-1 . SperNO treated strains were grown in 18 mm test tubes , while SIN-1 treated strains were grown in 250 ml Erlenmeyer flasks to maximize aeration . All bacterial cultures were grown overnight at 37°C and plated onto LB agar with or without 100 μg·ml−1 rifampin ( Fisher Scientific ) . In vivo mutability was determined by infecting C3H/HeN mice with 1×103 cfu of wild type or isogenic mutant S . Typhimurium . When appropriate , mice were treated with the NOS2 inhibitor L-NIL administered via drinking water at 500 μg·ml−1 . Mice were monitored for seven days and their livers were harvested , homogenized in 1 ml of PBS and viable cfu/g liver determined . Appropriate dilutions were also plated onto M9 agar containing 60 μg·ml−1 5-fluorocytosine ( 5FC ) ( Sigma-Aldrich ) . Homogenates were grown for 48 hrs at 37°C , then replica plated onto fresh 5FC plates for further incubation at 37°C overnight . Mutation frequency was calculated from number of cfu on 5FC plates divided by the total number of viable cfu per g liver . | The host innate immune system represents the first line of defense against invading microorganisms . An integral part of this response involves the production of nitric oxide ( NO· ) , a potent antimicrobial effector . Bacterial pathogens have evolved a variety of systems to counteract the inhibitory effects of host NO· . Here we describe the role of a complex DNA repair pathway in the bacterium Salmonella Typhimurium that minimizes the mutagenic nature of host NO· . We have determined the mutation rate of bacteria during a model infection . Our results reveal that the Salmonella Base Excision Repair system ( BER ) , comprised of DNA glycosylases and AP endonucleases , is able to eliminate excess mutations that accumulate in NO·–exposed cells during their interaction with the host . Thus , during Salmonella infections , the BER system protects the bacterium against potentially detrimental DNA damage arising from NO·–exposure . This provides genomic stability to a pathogenic microorganism that has evolved to survive within the genotoxic intracellular environment of host phagocytes . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"biochemistry/replication",
"and",
"repair",
"microbiology/microbial",
"evolution",
"and",
"genomics",
"microbiology/medical",
"microbiology",
"microbiology/innate",
"immunity"
] | 2009 | The Base Excision Repair System of Salmonella enterica serovar Typhimurium Counteracts DNA Damage by Host Nitric Oxide |
Accurately encoding time is one of the fundamental challenges faced by the nervous system in mediating behavior . We recently reported that some animals have a specialized population of rhythmically active neurons in their olfactory organs with the potential to peripherally encode temporal information about odor encounters . If these neurons do indeed encode the timing of odor arrivals , it should be possible to demonstrate that this capacity has some functional significance . Here we show how this sensory input can profoundly influence an animal’s ability to locate the source of odor cues in realistic turbulent environments—a common task faced by species that rely on olfactory cues for navigation . Using detailed data from a turbulent plume created in the laboratory , we reconstruct the spatiotemporal behavior of a real odor field . We use recurrence theory to show that information about position relative to the source of the odor plume is embedded in the timing between odor pulses . Then , using a parameterized computational model , we show how an animal can use populations of rhythmically active neurons to capture and encode this temporal information in real time , and use it to efficiently navigate to an odor source . Our results demonstrate that the capacity to accurately encode temporal information about sensory cues may be crucial for efficient olfactory navigation . More generally , our results suggest a mechanism for extracting and encoding temporal information from the sensory environment that could have broad utility for neural information processing .
There are four fundamental dimensions to all sensory modalities—quality , quantity , space and time . While the quality and quantity dimensions of olfaction are well appreciated and increasingly understood , it has long been assumed that olfaction yields little information about space and time . In contrast , in vision and audition , neural encoding of space and time information provides effective perception of the dynamic world [1 , 2] , commonly referred to as ‘scene analysis’ [3] . Since olfaction presumably is the oldest sensory system ( e . g . , [4] ) , it would be surprising if animals relying heavily on olfaction did not evolve some version of ‘olfactory scene analysis’ as an edge for survival [5] . Indeed , many animals , including humans ( e . g . [6] ) are capable of using odor cues to navigate . The best-studied example of this type of navigation is known as olfactory search , a behavior in which animals locate the source of an odor emitted by food or potential mates ( e . g . , [7–11] ) . For all but the smallest animals , searches take place in turbulent air or water . The considerable difficulties associated with finding an odor source in turbulence have been well documented ( see e . g . , [12–14] ) . The question is , how do organizational features inherent in the olfactory system allow animals to accomplish this task ? Past studies of olfactory search have generally either proposed navigational algorithms and demonstrated their efficiency in idealized environments ( e . g . , [12 , 13 , 15] ) , or studied behavioral responses to controlled scent stimuli ( e . g . , [10 , 16 , 17] ) . These studies have yielded general principles of search and greater knowledge of the behavioral responses of searchers to odor cues . Yet , it is still not clear what features of odor cues animals actually measure , neurally encode , and use for navigation . Here , we suggest that reverse-engineering search strategies from the neurophysiology of the olfactory system may provide a way forward . In vision , the relative motion of objects provides information about the spatial structure of the environment and animals use this information to navigate . The head related transfer function serves a similar purpose in audition . In the case of olfaction , the time intervals between odor encounters inherent in the structure of odor plumes ( i . e . , odor intermittency ) can vary dramatically with distance to odor sources and therefore appear to be candidate cues for olfactory navigation ( e . g . , [14 , 18] ) . If this is generally the case , one could hypothesize the existence of a specialized sensory subsystem that could capture and represent timing of past odor encounters . We recently demonstrated [19] that a subset of olfactory receptor neurons ( ORNs ) —known as ‘bursting’ ORNs ( bORNs ) because they spontaneously and rhythmically oscillate and are entrained by odorants—have the capacity to encode time intervals between odor encounters . bORNs have been identified in a diverse range of animals including arthropods [20] , amphibians [21] , and mammals [21–24] , suggesting that they may provide an important and basic function in the olfactory system . The finding that bORNs appear to be capable of capturing information about the timing of odor encounters supports the hypothesis that animals have evolved a functionally distinct sensory subsystem with the capacity to accurately measure and encode the times between odor arrivals . However , whether this capability is related to the navigational challenges that animals face in natural odor environments , and precisely how it could influence search behavior is an open question . We address this question in what follows . Bursting olfactory receptor neurons exhibit several functional properties that suggest they may serve to measure and encode the timing of odor cues . Unlike canonical , tonic ORNs whose activity follows the concentration of a stimulus or the rate of change in concentration [25] , bORNs burst spontaneously , even in the absence of odor stimulation , in addition to bursting in response to odors . Each bORN’s spontaneous activity is characterized by a distinct intrinsic bursting frequency ( Fig 1A ) , and whether a bORN responds to an odor stimulus depends on when the odorant arrives relative to its inherent bursting cycle ( Fig 1A ) . The probability that a bORN will burst in response to an odor increases strongly as a function of the time since its last burst τ ( Fig 1A and 1B ) . The bORN’s probability of responding to a stimulus can be characterized by two functions: the evoked response probability ( Fig 1B , blue curve and points ) and the probability of going τ seconds without bursting spontaneously ( Fig 1B , red curve ) . The composition of these two functions gives rise to a ‘time entrainment tuning curve’ for that bORN ( Fig 1B , green curve ) . The population of bORNs is heterogeneous , creating an ensemble sensitivity to a wide range of odor arrival periodicities that can extend from hundreds of milliseconds to tens of seconds ( Fig 1C ) . As a population , bORNs encode in their pattern of bursting the time since the last odor was encountered ( Fig 1D ) . This neurally encoded time interval can be decoded using a simple maximum likelihood procedure , implemented , for example , with a winner take all operation on the population of neurons that receives axonal projections from the bORNs ( Fig 1E ) . Unlike other proposed methods for neurally encoding time intervals , which require precise fine-tuning of ensembles of neurons ( e . g . , [26 , 27] ) , bORN-based encoding requires no such fine-tuning and yields low variance in the estimate of time , even for long time-intervals between odor encounters [19] . This means that the time since the last odor encounter can be measured , encoded , and decoded with high accuracy , even when odors arrive infrequently . bORNs represent a sensory-specific timing mechanism [28] that provide animals that have them [21–24 , 29] with the ability to peripherally encode the time intervals between odor encounters . The central hypothesis we test in this manuscript is whether bORNs provide a neural mechanism for extracting useful navigational information in natural turbulent odor environments . Here we combine a model based on neurophysiological measurements obtained from the spiny lobster Panulirus argus [19] with detailed data from a real turbulent plume to show that populations of bORNs can directly measure properties of odor intermittency that are useful for navigation . We use detailed data on the concentration of a fluorescein dye from planar laser-induced fluorescence ( PLIF ) recordings from a turbulent plume [18] to rigorously characterize the timing of odor arrivals . Our analysis shows that , at scales relevant to animals searching for odor sources , there is sufficient information in the timing of odor arrivals to distinguish different locations in the plume . Finally , we use a computational model parameterized with experimental measurements from P . argus bORNs and the turbulent plume data to show that a searching animal with paired olfactory organs can quickly locate an odor source using the real-time measurements of odor intermittency captured by bORNs .
Turbulent odor plumes in nature have a large range of odor frequencies; time periods between the arrival of bursts of high odor concentration can exist from milliseconds to many seconds [30 , 31] . An animal traveling in such an environment could potentially measure many different features of the odor landscape . To determine whether bORNs are capable of measuring particular features of the odor field that contain useful navigational information , we use PLIF ( planar laser-induced fluorescence ) videos recorded at 15 different sites in a large laboratory flume ( dimensions: 25 m long , 0 . 6 m wide , and 0 . 3 m deep ) into which fluorescein dye was released to mimic an odorant ( see [18] and Materials and Methods for details ) . The flow conditions and plume created by dye release were chosen to mimic plumes experienced by lobsters under natural foraging conditions [18] . From pixel intensities in the movies , we extracted a time series of fluorescence intensity at each of the 15 sites ( Fig 2 ) and used these time series to characterize the dynamic behavior of dye in the turbulent plume ( see Materials and Methods ) . We assume that the intensity of fluorescence is equivalent to odor concentration and we use these terms interchangeably . Unlike steady concentration gradients , turbulent odor plumes are characterized by large fluctuations in odor concentration at any point in space . A biological or artificial sensor suspended in the plume will register a time series of odor measurements characterized by bursts , in which the odor concentration well exceeds its mean value , and “blanks , ” in which concentration is very low relative to its mean ( Fig 3 lower panels , [14] ) . These large fluctuations in concentration mean that the organism must measure concentration for a long period of time in order to accurately estimate mean odor concentration far from the odor source ( see e . g . , [13] ) . An alternative to measuring odor concentration itself is to measure the time intervals during which odor concentration is below detectable threshold [13 , 15 , 32] . If the arrivals of detectable odor bursts were periodic , the periodicity of odor arrival ( e . g . , the inter-arrival period ) would be a natural metric for measuring the time intervals . In turbulent flows , however , the arrival of bursts is not perfectly periodic . Instead , we employ a concept from dynamical systems theory known as recurrence , which extends the concept of periodicity to events that reoccur in time but do not necessarily follow a regular periodic cycle . The recurrence time provides a generalization of the inter-event period ( the period between arrivals of whiffs of odor above a detectable threshold in this case ) , and , as we will show below , recurrence time turns out to be a statistical property of the odor field that can be estimated and encoded peripherally by bORNs . Measuring recurrence time of the odor plume data requires that we be able to characterize the time between “similar” events in the concentration time series . This , in turn , requires that we define what it means for two time periods in an odor time series to be similar . Dynamical systems theory provides a rigorous method for doing this . In particular , we define a criterion for determining whether two points in the odor time series are similar enough to be considered recurrences by characterizing a dynamical invariant of the turbulent flow known as the attractor ( see e . g . , [33 , 34] for a detailed discussion ) . Any point in the odor time series can be mapped to a corresponding point on the attractor , which is a high-dimensional object that characterizes the dynamical behavior of concentration over time . Two points that are close to one another on the attractor are considered to be similar if they fall within a specified threshold distance of one another . The time required for the time series to revisit such similar points is the recurrence time . To reconstruct the attractor from the time series of odor concentration measurements at each position in space we use Takens’ delay embedding theorem [35] , which creates a bijective mapping between the time series and a sufficiently high-dimensional attractor ( 10 dimensions in this case; details of attractor reconstruction are described in S1 Appendix , [33] ) . After reconstructing the attractor , we can define formally what it means for two points in time to be similar using recurrence theory ( [36 , 37] and extension by Eckmann et al . [38] ) . The recurrence plot is a matrix R that quantifies the dynamics of the turbulent flow and can be measured locally by R ( i , j ) = Θ ( r - | | x i - x j | | ) , i , j = 1 , 2 , . . . N , ( 1 ) where r is an allowable neighborhood distance , Θ is a Heaviside function , and ||xi − xj|| denotes a Euclidean distance between xi and its translated version across time xj . The Heaviside function provides a value of one ( R ( i , j ) = 1 ) when the difference between xi and xj is smaller than r , and zero for all other cases . To estimate recurrence of trajectories at a given concentration , we open a similarity sphere of radius r , around a reference value xi . When the concentration falls within this sphere at a later time , a recurrence occurs ( black points in Fig 3 , see also S1 Appendix ) . The recurrence plot provides a visual representation of the self-similarity of the odor arrival time series ( instantaneous odor concentrations at different spatial locations are shown in Fig 3; upper panels are recurrence plots , lower panels are the corresponding concentration time series ) . The essential observation is that the features of the odor plume shown in Fig 3 vary dramatically , both with distance to the source ( compare Fig 3A and 3B ) and distance from the plume centerline ( compare Fig 3B and 3C ) . This implies that the timing of odor arrivals contains structure that could , in principle , be used to determine position relative to the odor source . This empirical result , obtained using methods from dynamical systems theory , is consistent with theoretical results from statistical fluid dynamics [14] . Given the differences in recurrence behavior in different regions of the plume ( Fig 3 ) , an immediate question is whether the sensory capabilities of bORNs could allow an animal to measure features of this structure that are useful for navigation . A searcher moving through a plume must decide , in real time and with local measurements , whether it is traveling in the right direction and adjust its movements accordingly [12] . Rather than recording a stationary time series of odor encounters , a moving animal will experience a sequence of encounters that is time-varying ( i . e . , the rate of odor arrivals changes as the animal moves from one location in the plume to another ) . Recurrence theory suggests a solution to this problem: recurrence time—the time needed for a trajectory to revisit the same area in phase space [39 , 40]—is a sensitive metric for quantifying the degree to which the dynamics of a time series change over time . We consider two types of recurrence time statistic that are consistent with the known functional properties of bORNs: the mean recurrence times of first and second types , which we will denote T ¯ 1 and T ¯ 2 [39] . From a specific trajectory in the reconstructed state space produced through time-delay embedding , we select a reference point x0 . Points that fall within the region defined by {x: ||x − x0|| < r} are deemed similar to the reference point ( the points within a distance r of the reference point shown in Fig 4A ) . These points define a set of trajectories S1 = {xt1 , xt2 , … , xti , …} . The recurrence time of the first type is simply computed by subtracting successive times in the subset: {T1 ( i ) = ti+1 − ti , i = 1 , 2 , …} . T ¯ 1 is the average of these return time intervals . By removing from the count the successive points inside the neighborhood , called sojourn points , we obtain a new set S 2 = { x t 1 ′ , x t 2 ′ , . . . , x t i ′ , . . . } that is composed of only returning points ( black-filled circle in Fig 4A ) . The recurrence times of the second type T ¯ 2 can be computed by averaging intervals between return times of {T2 ( i ) = ti′+1 − ti′ , i = 1 , 2 , …} . Heuristically , T ¯ 1 is the average time taken for the odor concentration time series experienced by the searcher to revisit a similar point in phase space . To measure T ¯ 1 exactly , a population of bORNs would need to be able to resolve the time intervals between all similar points in the odor time series , even if these points occur in short succession . By contrast , T ¯ 2 excludes points that occur in short succession ( Fig 4A , sojourn points are excluded ) , as one might expect if bORNs burst in response to an odor detection , but remain refractory if the next odor whiff arrives shortly thereafter . Because the precise refractory characteristics of entire populations of bORNs are not fully characterized , we include both of these metrics . To investigate whether T ¯ 1 and T ¯ 2 contain navigational information using the flume data , we assumed the detection threshold corresponded to a dye concentration of 2 . 55% of source concentration and r = 0 . 33% ( S1 Appendix ) . It is not possible to relate this value directly to the bORN odor sensitivity threshold because dye concentration serves only as a surrogate for odor concentration ( see Materials and Methods ) . Fig 4B and 4C show the mean and standard deviation of T ¯ 1 and T ¯ 2 for downstream and cross-stream positions . The mean of T ¯ 1 and T ¯ 2 increases with increasing distance from the source or plume centerline , which indicates the recurrence time contains information about where the animal is located relative to the odor source . Fig 4 illustrates that there is navigational information inherent in T ¯ 1 and T ¯ 2 when these metrics are computed from an embedded version of the odor time series . We use embedding because it ensures that the full information contained within the odor time series is preserved; yet , it is unclear whether an organism such as P . argus could perform the neural computation required to generate such an embedding . However , many recurrence metrics used to identify changes in the dynamics of time series exhibit an interesting property: these metrics can generally be reliably estimated directly from the original time series without embedding [34] . This means that the time intervals encoded directly by bORNs may serve as effective estimators of the recurrence time . In particular , a subset of bORNs in the population will burst in response to an odor concentration that exceeds a threshold , which serves as the reference concentration x0 , selecting implicitly a trajectory of constant concentration in the turbulent flow where the animal is located . As described above , the next time that the bORNs burst in response to odor concentration x0 , the population encodes the time since the last odor encounter , which can be decoded by maximum likelihood . This time corresponds to a stochastic estimation of mean recurrence time ( T ¯ 1 or T ¯ 2 ) of a trajectory in the flow at the particular odor concentration that triggered the bORN and will be denoted T ^ 1 and T ^ 2 respectively . If bORNs were able to respond instantaneously to odor arrivals , regardless of the time at which the last odor arrived , the bORN population would estimate T ^ 1; however , because cells have a minimum neural refractory period , the population filters out up-crossings that occur in short succession , making the estimate closer to T ^ 2 . To determine whether an animal could use the recurrence times estimated by bORNs to navigate , we use a computational search model parameterized with data from P . argus neurophysiology and a simulated environment based on the turbulent plume data ( see Materials and Methods ) . At each time step , the searcher determines its movement direction by comparing bilateral measurements of the scent field ( Fig 5A; [17] ) . We study a strategy with two sensors because lobsters have been shown to exhibit longer search times and far more tortuous search paths when one of their olfactory organs is ablated , suggesting that bilateral comparisons of odor measurements ( i . e . , tropotaxis ) is an important component of their search behavior [41] . The searcher probes the odor plume using its two sensors and waits a maximum observation time for an odor encounter; otherwise it returns to its previous position to avoid leaving the plume ( see Materials and Methods; similar behavior , in which lobsters that exit a plume turn to re-enter it has been observed experimentally [41] ) . We consider two quantities that a searcher could measure: time since the last odor encounter , which can be measured by bORNs , and concentration , which can be measured by ordinary olfactory receptor neurons . Strategies based on scent concentration are discussed extensively in the literature ( e . g . [42] ) and we include such a strategy for reference . In the strategy based on the time since the last encounter , the searcher steers in the direction of the sensor that measures smaller recurrence time , which the searcher estimates locally by the time since the last encounter measured by each sensor . In the strategy using instantaneous concentration , the searcher moves to the direction of the sensor measuring the larger instantaneous concentration ( Table B in S1 Appendix ) . For comparison , we also study the performance of single sensor strategies ( S1 Appendix ) . Fig 5B shows an example trajectory of a searcher that uses time since last encounter . The casting pattern in the trajectory ( i . e . , zigzagging across the plume ) resembles trajectories of real olfactory searchers ( e . g . , [43 , 44] ) . For both strategies , the number of steps increases as the downstream distance from the source increases ( Fig 5C ) . However , the strategy based on time since last encounter requires far fewer steps to locate the source . Strategies based on a single olfactory sensor are still capable of finding the odor source , but take far longer ( S1 Appendix ) , which is consistent with experiments showing that lobsters with only one functional antenna take longer to reach a scent source [41] . Notably , the strategy that relies on time since last encounter depends only very weakly on the distance to the plume center-line ( Fig 5C ) , an important feature given that there is no guarantee that an odor source will be directly up current . Although olfactory searchers likely implement search strategies that are more complex than the simple strategy explored here ( e . g . , [45] ) , Fig 5 demonstrates that the statistic measured by bORNs is sufficient to lead a searcher quickly to a scent source , even in the absence of any other measurements of the search environment ( e . g . , flow direction ) .
Our results suggest that bursting olfactory receptor neurons serve a crucial but previously unappreciated role in olfactory navigation by accurately encoding the time intervals between odor encounters . In real turbulent odor plumes like the one studied here , there is structure in the sequence of odor arrivals at any given location ( e . g . , Fig 3; [14 , 18] ) and this structure is strongly correlated with position relative to the odor source . Navigational information contained in this structure can be captured by a simple metric: recurrence time ( the T 1 ¯ and T 2 ¯ metrics discussed above , Fig 4 ) . bORNs are capable of collectively encoding the time since the last odor encounter ( Fig 1 ) and this quantity is precisely a low-dimensional stochastic estimate of recurrence time . The implication is that the lobster has evolved a specialized sensory subsystem that is highly sensitive to changes in the local structure of turbulent odor plumes [39 , 40] . A searcher employing a simple heuristic that uses only the information captured by bORNs can quickly and reliably locate an odor source in a realistic turbulent plume ( Fig 5 ) . This demonstrates that the interval between odor encounters is useful for solving the online navigational problem animals actually face when searching a turbulent environment—to locate the source without wasting time waiting in places where the likelihood of encountering an odor is low [12 , 15] . Recurrence times are ideally suited to this task because , unlike other metrics that are typically applied to time series analysis , recurrence times are highly sensitive to changes in the rate of arrival of odor pulses ( i . e . , nonstationarity of the attractor , [39] ) , which occur when the searcher actively moves through the plume as it samples odors . Though a searcher could also use measurements of odor concentration , strategies based on concentration estimates alone perform poorly ( Fig 5 , Fig C in S1 Appendix ) suggesting , counterintuitively , that the most important navigational information captured by the olfactory system may come in the form of measurement of time rather than measurement of concentration . It is likely that our findings apply to other species of olfactory searchers in different types of turbulent odor environments ( e . g . , air versus water ) . Using a very different approach from that taken here , Celani et al . [14] applied methods from statistical fluid dynamics to characterize the features of odor transport in idealized turbulent plumes that are believed to be most relevant for olfactory navigation . While the mean odor concentration and the probability distribution of concentration varies systematically with position relative to an odor source , the manner in which these statistical features of the plume change with distance to the source are strongly influenced by properties of the plume such as the mean speed of advection ( i . e . flow rate ) and the amount of odorant released at the source . By contrast , the duration of time intervals during which the odor is below a detection threshold ( analogous to the T ^ 2 statistic defined above ) depends far less strongly on the details of the environment , which implies that there is information embedded in this statistic that can be extracted without knowledge of the properties of the flow and odor source . A second advantage of navigating using odor inter-arrival times is that these intervals decay rapidly with distance from the plume mid line ( e . g . Fig 3 ) , whereas other features of the odor field do not [14] . The statistical fluid dynamics approach is complementary to our method of empirically characterizing the dynamics of odor concentration using dynamical systems theory . Moreover , the results of [14] suggest that our general conclusion—that odor inter-arrival times are a sensitive metric for navigating odor plumes , and therefore , that bORNs can encode useful navigational information—is likely to extend to environments that differ substantially from the laboratory plume studied here ( e . g . different flow speeds , odor concentrations , air vs . water , differences in chemical diffusivity ) . Animals that engage in olfactory search also use information from other sensory modalities to guide search behavior . For example , male moths locate females using measurements of prevailing winds in addition to measurements of the pheromones females emit [14] and mosquitos combine visual and thermal cues with CO2 detection to localize hosts [46] . In the case of most species that navigate using olfactory cues , it remains to be shown precisely how information from multiple sensory modalities is integrated to govern movement decisions . Various strategies for olfactory navigation have been proposed ( e . g . , the “mapless” scheme of [45] , the “infotaxis” scheme of [13] , the signal-modulated random walks studied in [15 , 32] ) , but at present , the behavioral and neurophysiological data necessary to evaluate such navigational strategies and compare them to one another is lacking . However , the utility of odor inter-arrival times and the existence of a sensory subsystem capable of measuring them directly strongly suggest that temporal information inherent in the olfactory signal itself is fundamental to the search process . The presence of bORNs in animals as phylogenetically diverse as arthropods [20] , amphibians [21] , and mammals [21–24] suggests that the dynamic encoding of temporal information these neurons provide may even be fundamental to olfactory navigation . Taken together , our results reveal a neural mechanism for extracting and encoding navigational information from a noisy sequence of odor encounters . They add to an increasing understanding of how complex olfactory data are captured , encoded , and relayed through the brain [17 , 47 , 48] . Our results argue strongly that the ability of bORNs to encode time not only has behavioral significance , but that the dimension of time , and through time , the dimension of space , is inherent in olfaction . Thus , olfactory scene analysis is not limited to the sensory dimensions of quality and quantity ( e . g . , [49] ) but also appears to employ the spatial and temporal dimensions . This would make olfaction not unlike vision and audition , where visual and auditory scene analyses effectively combine space and time information to disambiguate the external world .
We define the flow direction in the laboratory flume as the x-axis and the lateral direction transverse to the flow as the y-axis . The dye ( flourescein ) source was located at x = 0 m , y = 0 m and dye was dispersed by turbulent water flow with the mean velocity of 4 . 6 cm s−1 . Laser light was emitted by an argon-ion laser at an output intensity of 100mW , which illuminated a vertical light sheet through the water column . When passed through the laser light , flourescein dye ( peak absorption at 490 nm ) emits light at mean wavelength of 515 nm . Videos of the flouresced dye were recorded within a vertical plane area of 18 × 16 cm centered and parallel to the flow using a 480 × 420 pixel resolution digital camera . An in situ calibration was performed to convert pixel intensity to concentration . The dye concentration was measured at downstream positions x = 0 . 5 , 1 . 0 , 1 . 5 , 2 . 0 and 2 . 5 m from the source and at cross-stream positions y = 0 , 0 . 05 , 0 . 1 m where y = 0 m is the odor plume centerline ( Fig 2 ) . Videos consist of 1025 frames where the frame rate is 60 frames s−1 . Video recordings were performed 10 times at each location . All images were normalized by the source concentration in each run; therefore dye amplitude in each pixel is represented by a percentage of source concentration . To more accurately reconstruct the dynamics a lobster would experience in the plume , we selected an area of 3 by 3 pixels in each image to reflect the dimension of the single annulus of the lobster antennule ( 1 mm x 1 mm ) , which is composed of hundreds of somata and cilia [50] . The time series of odor concentrations sampled by a single annulus are extracted by averaging the 9 pixels intensities to find the odor dynamics at this region . Data are included as supplementary material ( S1 and S2 Datasets ) . We simulated a searcher with two olfactory sensors in an odor plume parameterized by the PLIF data . The searcher begins each simulation heading up current ( heading angle = 180° ) . The angle of separation between sensors was 60° and the antennule length ( i . e . the distance from the body to each sensor ) was set to 5 cm to match the morphology of P . argus . Step length was also set to 5 cm . We set the maximum observation time at each position as 10 s and computed the number of steps required to find the source in each of 100 Monte Carlo simulations for each initial position . The searcher finds the odor source if its antennule position is within 5 cm of the source . Because dye amplitude was measured from cross section images of flow at 15 distinct locations in the plume we selected from each image 3 equally spaced locations in the downstream direction for a total of 45 measurements to build a statistical model that could be used to interpolate odor statistics to all locations visited by simulated searchers . Statistical fluid dynamics can be used to predict the theoretical behavior of various statistics of a turbulent odor plume ( e . g . , [14] ) . These methods yield functional forms for the relationship between odor statistics ( e . g . , mean concentration , the times between odor encounters , the time intervals for which a given threshold is exceeded , etc ) and position relative to the plume source . However , because we had access to data from a turbulent plume specifically designed to mimic those experienced by searching marine organisms , we chose to fit odor statistics to data using functional forms that best described observed relationships rather than fitting the forms predicted from theory . For the length scales concerned here , this choice has little bearing on our results and , in fact , the general conclusions we reach about the utility of the time intervals between odor arrivals are consistent with the results of theory . The time since the last odor threshold up-crossing was well-fitted by an exponential distribution . The parameter for the exponential distribution , i . e . , the mean time since the last up-crossing , increased roughly exponentially as the distance from the source increases along the plume centerline [51]: Δ ¯ ( x , 0 ) = Δ 0 e λ x , x > 0 , y = 0 . ( 2 ) In the direction of the cross stream , the mean was assumed to increase exponentially with increasing distance from the plume centerline at a fixed downstream distance as Δ ¯ ( x , y ) = a ( x ) e η ( x ) | y | , x > 0 , | y | = 0 . ( 3 ) where a ( x ) = g exp ( hx ) + n , η ( x ) = pxq + n , and again , the functional forms were chosen based on PLIF data . The parameters g , h , p , and q were obtained by fitting the mean values at 45 measured locations . The additive Gaussian noise n is zero mean with a standard deviation set equal to the fitting error . Dye intensity in each of the 15 frame locations was well-fitted by a Gamma distribution and we used this distribution to model instantaneous odor concentration . The mean concentration along the plume centerline was modeled as C ¯ ( x , 0 ) = C 0 e - β x , x > 0 , y = 0 , ( 4 ) whereas the mean in the cross-stream direction was modeled with a Gaussian function [51 , 52] , C ¯ ( x , y ) = c ( x ) e - y 2 σ ( x ) 2 , x > 0 , | y | > 0 , ( 5 ) where c ( x ) = k exp ( bx ) + n and σ ( x ) = mxd + n . The parameters k , b , m , and d and the noise n was again obtained by fitting mean concentration at 45 measurement locations . The mean of the Gamma distribution is the product of its two parameters , i . e . , the shape and scale parameters , so we modeled the scale parameter in the same manner as the mean concentration , and compute the shape parameter by dividing mean concentration by the scale parameter . | Many animals navigate turbulent environments using odor cues , a behavior known as olfactory search . We propose a neural mechanism for olfactory search based on evidence that a functional subset of olfactory receptor neurons ( ORNs ) called bursting ORNs or bORNs can encode the time intervals between successive encounters with odor . We show that these time intervals are estimators of the recurrence time , an information-rich statistic of the turbulent flow . Using a computational model parameterized with data from an actual turbulent plume , we demonstrate that a searcher can locate an odor source efficiently using only input from bORNs . These findings provide scientific evidence that the most important navigational information captured by the olfactory system may come in the form of measurements of time . | [
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] | [] | 2016 | Neurally Encoding Time for Olfactory Navigation |
In vitro studies and mathematical models are now being widely used to study the underlying mechanisms driving the expansion of cell colonies . This can improve our understanding of cancer formation and progression . Although much progress has been made in terms of developing and analysing mathematical models , far less progress has been made in terms of understanding how to estimate model parameters using experimental in vitro image-based data . To address this issue , a new approximate Bayesian computation ( ABC ) algorithm is proposed to estimate key parameters governing the expansion of melanoma cell ( MM127 ) colonies , including cell diffusivity , D , cell proliferation rate , λ , and cell-to-cell adhesion , q , in two experimental scenarios , namely with and without a chemical treatment to suppress cell proliferation . Even when little prior biological knowledge about the parameters is assumed , all parameters are precisely inferred with a small posterior coefficient of variation , approximately 2–12% . The ABC analyses reveal that the posterior distributions of D and q depend on the experimental elapsed time , whereas the posterior distribution of λ does not . The posterior mean values of D and q are in the ranges 226–268 µm2h−1 , 311–351 µm2h−1 and 0 . 23–0 . 39 , 0 . 32–0 . 61 for the experimental periods of 0–24 h and 24–48 h , respectively . Furthermore , we found that the posterior distribution of q also depends on the initial cell density , whereas the posterior distributions of D and λ do not . The ABC approach also enables information from the two experiments to be combined , resulting in greater precision for all estimates of D and λ .
Skin cancer consists of two groups: melanoma and non-melanoma . Melanoma is the least common , approximately 5% of all skin cancer occurrences , but it is responsible for most skin cancer deaths [1] . It is estimated that 132 , 000 new cases of melanoma are reported worldwide each year , with more than 12 , 500 of these cases reported in Australia [2] . During the early stage of the disease , melanoma colonies grow and spread laterally within the epidermis . Thus , quantifying the underlying mechanisms that drive the expansion of melanoma cell colonies such as motility , proliferation , and cell-to-cell adhesion can improve our understanding of melanoma biology and its response to treatment . Although much progress has been made in terms of developing and analysing mathematical models of expanding cell colonies , far less progress has been made in terms of understanding how to estimate model parameters including the cell diffusivity , D , the cell proliferation rate , λ , and the cell-to-cell adhesion , q , from experimental in vitro image-based data . Obtaining precise estimates of D , q and λ is important for developing a systematic approach to assessing the effectiveness of a potential treatment [3] . Several studies have investigated the in vitro expansion of cell colonies using partial differential equations [4–7] . These approaches are limited in that they provide point estimates , and the uncertainty in the estimate is not quantified . An alternative modelling approach uses discrete , individual-based models [8–10] , which can incorporate several important biological factors such as cell heterogeneity [11] . Discrete models can also produce discrete image-based and video-based information which is ideally suited to collaborative investigations involving applied mathematicians and experimental cell biologists . However , the likelihood functions for these discrete models are generally intractable , so standard statistical inferential methods for these models are not applicable . To overcome these issues , an approximate Bayesian computation ( ABC ) approach is developed to jointly infer the values of D , q and λ from a discrete stochastic model describing the expansion of cell colonies . ABC is a well established method that has been successfully applied in a wide range of areas such as population genetics [12] , infectious diseases [13 , 14] , astronomical model analysis [15] and cell biology [16] . Generally , ABC approximates the likelihood function by model simulations , the outcomes of which are compared with the observed data [16 , 17] . In this paper , we propose a new ABC algorithm that is shown to be more efficient than state-of-the-art algorithms available in the literature [17–20] by developing a new sequential Monte Carlo approach . ABC requires the specification of a set of summary statistics to compare the observed and simulated data . Each of our experimental datasets is initially summarised using a high dimensional vector of summary statistics ( hereafter referred to as the pilot summary statistics ) . Unfortunately , ABC is not able to handle high dimensional summary statistics in an efficient manner [21] , so we adopt a semi-automatic approach [22] to reduce the dimension of the pilot summary statistics . Using a synthetically generated dataset , we demonstrate that combining our new ABC algorithm and the derived set of summary statistics can precisely recover all parameters . We apply this procedure to the experimental data of human malignant melanoma cells ( MM127 ) in a barrier assay [23] in two different experimental scenarios: ( 1 ) Mitomycin-C is applied as a treatment to suppress cell proliferation , and ( 2 ) no treatment is applied . We aim to obtain a joint approximate posterior distribution for D , q and λ for different combinations of initial cell densities , C ( 0 ) , and experimental times , T , in each scenario . Through the ABC analyses , the associated uncertainty in the parameter values is quantified and interpreted in terms of the coefficient of variation ( CV ) and probability intervals of the posterior distribution . Thus , our work adds significant extra information about model parameters relative to the previous analysis [23] , which obtained point estimates of D , q and λ separately . In the previous analysis [23] , D and q were estimated only from the experiments with cell proliferation suppressed . Previous approaches often assume that these parameter values are the same over different experimental conditions [3 , 23 , 24] . The findings from this study show that the posterior estimate of D appears to depend on experimental time and weakly depend on the initial cell density , which is consistent with the results reported in Vo et al . [16] for 3T3 fibroblast cells . A similar trend of dependency is also found for q; but in contrast the posterior estimates of λ remain similar over time . These results suggest that a more complicated model might be warranted . However , this finding could not have been achieved without first exploring the suitability of the standard model under consideration here . The experimental data analysed in Vo et al . [16] also consists of two separate scenarios , with and without Mitomycin-C pre-treatment . Vo et al . [16] demonstrate that λ cannot be identified by leading edge data solely , unless prior information about D ( obtained from the experiment with the treatment applied ) is incorporated via a sequential Bayesian learning approach . In this paper , we show that all parameters ( including λ ) can be estimated precisely through the inclusion of additional summary statistics ( cell densities and percentages of isolated cells ) even when only vague prior information is specified for parameter values . Nonetheless , we show that the Bayesian sequential learning approach [16] is still useful here as we are able to obtain greater precision of the parameter values .
The details of the experimental method were described previously [23] . Briefly , monolayers of human malignant melanoma cells ( MM127 , [25 , 26] ) were cultured in 24-well tissue culture plates , where each well had a diameter of 15 . 6 mm . Experiments were conducted in two different experimental scenarios: ( 1 ) with Mitomycin-C pre-treatment to suppress cell proliferation , and ( 2 ) without Mitomycin-C pre-treatment . Mitomycin-C , an alkylating antibiotic , is used to block DNA and RNA replication and protein synthesis . Thus , given an appropriate concentration , Mitomycin-C inhibits mitosis and proliferation of several cell types [27] . For the melanoma experiments here , 10 µg ml−1 Mitomycin-C was added to the cells one hour prior to transfer to the wells [23] . To initiate each experiment , either 20 , 000 or 30 , 000 cells were approximately evenly distributed within a circular barrier , of diameter 6 . 0 mm , located at the centre of the well . After allowing the cells to attach for 1 h , the barriers were lifted and population-scale images were recorded at either 24 h or 48 h , independently . To extract detailed information about the location of individual cells in the population , high magnification images of a transect across the centre of the cell population were also acquired , where the nuclei were stained with Propidium Iodide ( PI ) . Furthermore , each experimental scenario , for each initial cell density and each termination time , was repeated three times . Thus , a 2 × 2 × 2 balanced experimental design was conducted with three replicates , producing a total of 24 independent experimental images of expanding cell colonies and the corresponding transect images . From preliminary analysis , we note that cell colonies maintain an approximately circular shape during the experiments . Thus , for each population-scale image , which shows the spatial expansion of the entire melanoma cell colony , we detect the position of the leading edge , then estimate the radius of the colony by converting the area enclosed by the leading edge to the equivalent circular radius , R , using a segmentation algorithm written with the Matlab Image Processing Toolbox [16 , 28] ( Table S1 in S1 Text ) . We use the exact same edge detection algorithm for both our experimental data and the images produced by the discrete simulation model described in the next section . Images in Fig 1A–1C show the entire expanding cell colonies for the 30 , 000 initial cell experiments at time 0 h and 48 h where cells were pre-treated with Mitomycin-C , and 48 h without the treatment , respectively , together with the estimated leading edge superimposed . To extract cell densities and measure cell clustering , we mapped the position of the cells to a square lattice with spacing Δ = 18 µm ( Fig 1H and 1I ) , which corresponds to an average diameter of the cell nucleus [23] . For each experiment , we analyse six sub-regions along a transect image ( Fig 1G ) . Each sub-region has size 700 × 500 µm or 39 × 28 lattice sites . We then count the number of cells in each sub-region , { c i } i = 1 6 , together with the proportion of isolated cells , { p i } i = 1 6 . A cell is identified as isolated if all of its nearest neighbours ( north , south , east and west ) are unoccupied . For each experiment at each initial cell density and termination time , at each sub-region , we average ci and pi over three replicates ( Tables S2 and S3 in S1 Text ) . Summaries of { c i } i = 1 6 and { p i } i = 1 6 ( average over the three replicates ) for experiments initialised with 20 , 000 cells are given in Fig 2 . We observe that , for experiments where cells were not pre-treated with Mitomycin-C ( Fig 2B ) , { c i } i = 1 6 increases significantly over time , whereas the differences in { c i } i = 1 6 for the corresponding experiments ( Fig 2A ) , where cell proliferation was suppressed , are minimal . Furthermore , { p i } i = 1 6 ( Fig 2C and 2D ) appear to decrease over time which suggests that melanoma cells possibly form more clusters as the experiments proceed . These trends are consistent with previous research [23] , which shows that cell-to-cell adhesion plays an important role in the melanoma expanding colonies . To describe the expansion of a single layer of melanoma cell colonies , we employ a discrete lattice based model that incorporates cell migration ( unbiased random walk ) , cell proliferation and cell-to-cell adhesion . The discrete model here is similar to the model used in [9 , 16 , 23] . We incorporate a volume exclusion process and realistic crowding effects [8 , 9 , 29] , so each lattice site can be occupied by at most one agent . To simulate the experiments , we use a two-dimensional square lattice of size 867 × 867 , with lattice spacing Δ = 18 µm , so that the width of the lattice corresponds to the diameter of the well , 15 . 6 mm ( 15600 µm/18 µm = 867 ) . Let C ( t ) be the number of agents in the discrete model at time t , Pm ∈ [0 , 1] be the probability that an isolated agent will attempt to step a distance Δ within a time step of duration τ , and Pp ∈ [0 , 1] represent the probability that an agent will attempt to proliferate and deposit a daughter within a time step of duration τ . The strength of cell-to-cell adhesion is represented by q ∈ [0 , 1] . Initially , C ( 0 ) agents ( 20 , 000 or 30 , 000 agents ) are placed randomly inside a circle which has a radius of 177 lattice sites , corresponding to the mean radius of the experimental observations at time t = 0 h . We use an approximate random sequential update ( RSU ) algorithm [30 , 31] to perform the simulations . To step from time t to time t + τ , C ( t ) agents are sampled , with replacement , and given the opportunity to move with probability Pm × ( 1 − q ) n , where 0 ≤ n ≤ 4 is the number of occupied nearest neighbour sites . If an agent is at position ( x , y ) and has an opportunity to move , it will attempt to step to either ( x ± Δ , y ) or ( x , y ± Δ ) , with each target site chosen with equal probability . The higher the value of q , the more difficult it is for an agent to move away from its neighbours . A similar mechanism is employed for proliferation events . A proliferative agent at position ( x , y ) will attempt to deposit a daughter agent at ( x ± Δ , y ) or ( x , y ± Δ ) , with each target site chosen with equal probability . Since the model is an exclusion process , any attempted motility or proliferation event that would place an agent on an occupied site is aborted ( S1 Text , Algorithm S1 ) . We do not consider any death mechanism in this model since there was no evidence of any cell death in the experiment [23] . Given the termination time , T ( 24 h or 48 h ) , the model requires T/τ time steps . The cell expanding colonies are governed by three parameters ( Pm , q , Pp ) . These parameters are related to the cell diffusivity , D , and the proliferation rate , λ , by D = Pm Δ2/4τ and λ = Pp/τ , respectively [29] , with Δ and τ set fixed . In this work , we apply our new ABC algorithm to obtain joint posterior distributions for ( Pm , q , Pp ) , then use these relationships and the values of Δ and τ , to rescale posterior distributions of Pm and Pp into posterior distributions of D and λ , respectively . We note that the RSU algorithm is an approximation of the exact , continuous time Gillespie algorithm [32] . The value of the time duration τ is a trade-off between the accuracy of the approximation and the computational time to simulate the experiments . To choose a suitable value for τ , we perform 100 model simulations using the same diffusion coefficient D = 220 µm2h−1 , obtained with different pairs of parameters ( τ = 0 . 1 h , Pm = 0 . 2716 ) , ( τ = 0 . 08 h , Pm = 0 . 2173 ) , ( τ = 0 . 06 h , Pm = 0 . 1630 ) , ( τ = 0 . 04h , Pm = 0 . 1086 ) and ( τ = 0 . 02 h , Pm = 0 . 0543 ) . We then compare the plots of the probability density of the resulting radii , percentages of isolated cells and total number of cells in six sub-regions . We found that there is a negligible difference between results from simulations with τ = 0 . 04 h and τ = 0 . 02 h . This means that τ = 0 . 04 h is small enough to produce reasonably accurate simulations . Therefore , for all model simulations hereafter , we use τ = 0 . 04 h . Snapshots of the discrete stochastic models initialised with 30 , 000 agents and termination time at 0 h , 48 h in Scenario 1 , and 48 h in Scenario 2 are shown in Fig 1D–1F , respectively . In this paper , we do not have any measurement for the uncertainty in C ( 0 ) . Thus , all of the simulations from the discrete models use the same initial values of C ( 0 ) , i . e . 20 , 000 cells or 30 , 000 cells . However , if we have this measurement , we can easily incorporate it in the ABC algorithms by drawing the value of C ( 0 ) from its distribution before proceeding to simulate a realisation of the model . The discrete models described above can incorporate realistic cell behaviour . However , their likelihood functions are not available in an analytical form and are not computationally tractable , so standard statistical inferential methods for these models are not applicable . Combining ABC and the discrete stochastic model is a promising approach since ABC bypasses the evaluation of the likelihood by a simulation-based procedure [12 , 17] . The aim of the ABC approach is to find the joint approximate posterior distributions , which are the distributions of the unknown parameters given the observed summarisation of the data and the prior information . All inferences about the parameters including point estimates and probability intervals are made from the posterior distributions . Let yobs and ysim represent the observed and the simulated data , θ = ( Pm , q , Pp ) represent the vector of unknown parameters and π ( θ ) be the prior distribution for θ . We define a distance metric ρ which is a function of yobs and ysim , ρ = ρ ( yobs , ysim ) . ABC approaches consist of four major steps: sampling a proposed parameter θ⋆ , simulating data as per the observed data structure from the model with θ⋆ , comparing ysim with yobs by computing ρ = ρ ( yobs , ysim ) and accepting the proposed θ⋆ if ρ ( yobs , ysim ) ≤ ϵ , where ϵ ≥ 0 is a tolerance value . The accepted sample of parameter values forms the approximation of the posterior distribution of the model parameters . The choice of ϵ is a trade-off between accuracy and computational effort . In practice , different ABC algorithms have different approaches to sample the values of θ⋆ . ABC rejection is the simplest ABC algorithm , which generally samples θ⋆ from the prior distribution . This algorithm is easy to implement and is embarrassingly parallel . However , for complex models where the prior distribution is substantially different from the posterior , this approach results in low acceptance rates and is computationally inefficient . Vo et al . [16] employed the ABC rejection algorithm to estimate D and λ , using the leading edge data of 3T3 fibroblast cell populations . This study samples a large number of proposed parameters from the prior , each with a corresponding artificial dataset and a value of discrepancy ρ . These parameters are then sorted by their discrepancies and only a small proportion of parameters with the lowest discrepancy are retained . In the study of Vo et al . [16] , a uniform prior was used , suggesting that for a reasonably low ϵ , the proportion of parameters being kept is very small , approximately 0 . 1% . Thus , this study suggests that it is necessary to generate 106 model simulations to obtain an ABC posterior sample of size 1 , 000 . Several studies [33–35] proposed a Markov chain Monte Carlo approach to ABC ( MCMC-ABC ) . MCMC-ABC algorithms make local proposals in high ( ABC ) posterior support regions , thus they can improve the acceptance rates . However , the posterior samples are highly correlated and the algorithms can easily be trapped in regions of low posterior density [35] . Another class of ABC is SMC-ABC which was pioneered by [36] to overcome the problems associated with ABC rejection and MCMC-ABC . SMC-ABC algorithms involve sampling from a sequence of ABC posterior distributions with a non-increasing sequence of tolerances , { ϵ k } k = 1 M . Thus , this last class of ABC only draws proposed parameters in sequentially higher posterior support regions , rather than the entire parameter space . A review of ABC algorithms can be found in [37] . In this paper , we only focus on SMC-ABC algorithms . Instead of drawing a proposed value θ⋆ one at a time , the SMC algorithms work with a large set of parameter values simultaneously and treat each parameter vector as a particle . The particles are moved and filtered at each stage of the algorithm . Initially , a set of N particles , { θ i } i = 1 N , is often sampled from the prior distribution π ( θ ) and each sampled particle has an equal weight of 1/N . To propagate a particle from iteration k − 1 to iteration k , SMC-ABC algorithms involve three steps: ( i ) re-sampling: a sampled particle candidate θ⋆ is chosen randomly from the set of particles at k − 1 with probability proportional to their weights , θ ⋆ ∼ { θ i k - 1 , W i k - 1 } i = 1 N; ( ii ) perturbing: the particle candidate θ⋆ is perturbed by a transition kernel to propose a new particle θ⋆⋆ , θ⋆⋆ ∼ Kk ( ⋅|θ⋆ ) , and ( iii ) simulating ysim from the model , ysim ∼ f ( ⋅|θ⋆⋆ ) . To maintain N particles throughout the algorithm , the steps ( i-iii ) are repeated until a parameter value is found such that the condition ρ ( yobs , ysim ) ≤ ϵk is satisfied . Different SMC algorithms can be distinguished by the transition kernel , the schedule of the tolerances and how sampling weights are assigned to the particles . In the literature , there are several versions of SMC-ABC algorithms . For example , SMC-ABC algorithms of [18 , 19 , 38] use a Gaussian Markov kernel with a covariance matrix as twice the empirical covariance matrix of the current set of particles . These algorithms also assign to each particle θk a weight given by: W k ∝ π ( θ k ) ∑ j = 1 N W j k - 1 K k ( θ k | θ j k - 1 ) . ( 1 ) These algorithms have the advantage that they require fewer model simulations , although the sequence of tolerances in these algorithms is determined manually . Drovandi et al . [17] and Del Moral et al . [39] proposed an adaptive SMC algorithm that can determine a decreasing set of tolerances dynamically . This can be achieved by sorting the particles by their discrepancies and then dropping a proportion of the particles with the highest discrepancy . However , these algorithms use an MCMC kernel which has a drawback of replications of particles . To reduce this problem , Drovandi et al . [17] suggest to repeat the MCMC step ( steps ( ii ) and ( iii ) above ) a number of times , which also can lead to a large number of unused model simulations . We take the advantage of fewer model simulations from SMC-ABC algorithms [18 , 19 , 36] and the advantage of automatically determining tolerance values from [17] ( also named the SMC replenishment ( RSMC ) algorithm ) and incorporate these in one algorithm , hereafter referred to as ASMC ( S1 Text , Algorithm S2 ) . Our ASMC algorithm is similar to that proposed in [20] ( also named adaptive population Monte Carlo ( APMC ) algorithm ) who also determine the sequence of tolerances adaptively and use the re-weighting scheme above . However , in each iteration , the APMC algorithm [20] only performs steps ( i-iii ) above once and keeps all the N particles , so the particle’s discrepancy value is not enforced to be below a particular tolerance . In the APMC algorithm , the sequence of tolerances fluctuate , whereas the sequence of tolerances in the RSMC and ASMC algorithms is always non-increasing . Therefore , we cannot use a single indicator to compare the performance of the three algorithms . We suggest comparing the RSMC and ASMC using the final tolerance , and comparing the ASMC and APMC using the same computational effort . Using synthetically generated data , we show that our algorithm requires fewer model simulations than the RSMC algorithm [17] , given the same target tolerance ϵfinal . In addition , given the same number of simulations , our algorithm is shown to produce a lower tolerance value ( thus higher accuracy ) relative to the APMC algorithm [20] .
To examine the utility of our new ABC algorithm and to investigate whether the derived set of summary statistics is informative for parameter inferences , we simulated a dataset with biologically relevant parameter values ( Pm = 0 . 1 , q = 0 . 2 , Pp = 0 . 0012 ) , which corresponds to ( D = 202 . 5 µm2h−1 , q = 0 . 2 , λ = 0 . 03h−1 ) . The synthetic dataset has C ( 0 ) = 20 , 000 cells , T = 24 h and is replicated three times . This dataset represents experiments in Scenario 2 . We first summarise the synthetic dataset in terms of the pilot summary statistics , including three radii of the expanding cell colonies for three replicates ( order statistics ) , the numbers of cells and the percentages of isolated cells in six sub-regions along a transect after averaging over three replicates . The ABC posterior distributions resulting from the pilot run with the pilot summary statistics have significant spread . So , a multiple linear regression procedure is performed to generate one summary statistic for each parameter . We then apply the new ABC algorithm with the derived set of summary statistics and uniform priors for all parameters , Pm ∼ U ( 0 , 1 ) , q ∼ U ( 0 , 1 ) and Pp ∼ U ( 0 , 1 ) . The resulting posterior distributions for ( Pm , q , Pp ) are presented in Fig 3 . These results show well-defined posterior distributions with narrow spread and posterior means close to the true values . The posterior correlation coefficients of ( Pm , q ) , ( q , Pp ) and ( Pm , Pp ) are between −0 . 2 to 0 . 3 . Thus , it is evident that our new ABC algorithm combined with our method for determining summary statistics allows us to recover all parameters rather precisely . Using the synthetically generated data , we also compare the performance of the three algorithms: RSMC , APMC and ASMC . For all algorithms , we set N = 1000 particles and run each algorithm 10 times to compare the resulting posterior distributions , the total number of model simulations and the generalized variance ( GV , or the determinant of the posterior variance-covariance matrix ) . A comparison of ABC posterior distributions from the three algorithms is shown in Fig 4 . For RSMC and ASMC , we set ϵfinal = 0 . 1 . For all cases , the posterior distributions from RSMC ( the dashed black curves ) and ASMC ( the solid red curves ) are almost indistinguishable , however , the RSMC requires approximately 2 . 5 times more model simulations than the ASMC algorithm ( Fig 5A ) . For the APMC algorithm , we use 62 iterations ( giving the total number of model simulations similar to the number of model simulations for ASMC , 62 , 000 ) . Results in Fig 4 suggest that the posterior distributions from the ASMC algorithm has smaller variance than the results from the APMC algorithm ( the blue curves with markers ) due to the ability of ASMC in getting to a smaller value of ϵ with a similar computational effort . We then compute the GV of the resulting ABC joint posterior distributions from the ASMC and APMC algorithms from the 10 runs ( Fig 5B ) . We observed that the GVs for the resulting posterior distributions from APMC are approximately three times larger than the corresponding GV from the ASMC algorithm . Thus , for this application , our algorithm performs better than the RSMC and the APMC algorithms . We now apply the ASMC algorithm to the experimental data in the two scenarios and interpret the results in terms of the biologically relevant parameters D , q and λ . This section presents the results for D and q for all experimental conditions in Scenario 1 , where cells were pre-treated with Mitomycin-C to suppress cell proliferation . Uniform priors are placed on all parameters , Pm ∼ U ( 0 , 1 ) and q ∼ U ( 0 , 1 ) . From the regression procedure to generate one summary statistic S for each parameter , for all cases , we observe that all pilot summary statistics ( R ( 1 ) , R ( 2 ) , R ( 3 ) , { c i } i = 1 6 and { p i } i = 1 6 ) are informative about D . However , to obtain estimates for q , only R ( 1 ) , { c i } i = 1 6 and { p i } i = 1 6 were significant in the regression . The ABC estimate of the posterior expected value of D and q , E[D] and E[q] , 90% credible intervals , CI , the coefficient of variation , CV , and the correlation coefficient , r , from all experimental conditions , are given in Table 1 . To assess the accuracy of our resulting estimates from the true ABC posteriors , we computed the Monte Carlo standard error , MCSE , for E[D] and E[q] in all experimental conditions , MCSE = σ / ESS [41] . Here , σ is the posterior standard deviation and ESS is the effective sample size . We use Kish’s approximation method [42] to compute the ESS , ESS = 1 / ∑ i = 1 N W i 2 , where Wi is the normalised weight for the ith parameter value . For all cases , the ABC posterior consists of 1 , 000 parameter values , which leads to an ESS usually in the range 700–850 . Our posterior sample size leads to a small MCSE for both E[D] and E[q] , less than 0 . 2% and 0 . 4% of the estimate of their expected values , respectively . From Table 1 , we observe that the CV for D and q are also quite small , approximately 6% and 10% , respectively , which means that we can obtain reasonably precise estimates for D and q using the derived summary statistics . The correlation coefficient between D and q for all combinations is between 0 . 2 to 0 . 6 . This suggests that multiple combinations of values of D and q can generate similar expanding cell colonies in terms of our pilot summary statistics . For both initial cell densities ( 20 , 000 and 30 , 000 cells ) , we observe that the values of E[D] for the experiments terminated after 48 h are higher than those values for experiments terminated after 24 h . This finding suggests that estimates of D appear to depend on the experimental time , T , which is consistent with the results reported in [16] for 3T3 fibroblast cells . It is conjectured that some amount of time could be required for the cells to adjust to their new or modified environments encountered as part of the experimental protocol . The cell motility , therefore , could be reduced during this transition phase . A similar trend of dependency is also found for q . This motivates us to investigate the values of D and q for the period 24–48 h . Let {D ( 0–24 ) , q ( 0–24 ) } , {D ( 24–48 ) , q ( 24–48 ) } and {D ( 0–48 ) , q ( 0–48 ) } represent the cell motility coefficient and strength of cell-to-cell adhesion for the period 0–24 h , 24–48 h and 0–48 h , respectively . Estimates of posterior distributions for {D ( 0–24 ) , q ( 0–24 ) } and {D ( 0–48 ) , q ( 0–48 ) } have already been obtained from experimental data at 24 h and 48 h , respectively . To obtain estimates for {D ( 24–48 ) , q ( 24–48 ) } , two stages of simulations are required , from 0–24 h and from 24–48 h . In the first stage , model simulations use parameter sets that are drawn from the distributions of {D ( 0–24 ) , q ( 0–24 ) }; whereas , in the second stage , the model simulations update the cell colonies with parameter sets that are drawn from the distributions of {D ( 24–48 ) , q ( 24–48 ) } . We consider two approaches to infer the values of {D ( 24–48 ) , q ( 24–48 ) } . Approach 1: We jointly infer the values of {D ( 0–24 ) , q ( 0–24 ) } and {D ( 24–48 ) , q ( 24−48 ) } by simultaneously comparing experimental data that are terminated at 24 h and 48 h with the simulated data at the corresponding terminated times . In this approach , we place a uniform prior on both parameter sets {D ( 0–24 ) , q ( 0–24 ) } and {D ( 24–48 ) , q ( 24–48 ) } . We observe that the ABC posterior distributions of {D ( 0–24 ) , q ( 0–24 ) } in this approach are indistinguishable with the estimates previously obtained by using the experiments terminated at 24 h . Approach 2: We make use of the ABC posterior of {D ( 0–24 ) , q ( 0–24 ) } previously obtained from the experiments terminated at 24 h , and only infer the values of {D ( 24–48 ) , q ( 24–48 ) } by matching on the summary statistics at 48 h . To achieve this , for each initial cell density , we fit a bivariate normal distribution to the ABC joint posterior distributions of {D ( 0–24 ) , q ( 0–24 ) } . To perform a model simulation , we draw a parameter set from the bivariate normal distribution for the first stage , and another parameter set from the uniform prior for {D ( 24–48 ) , q ( 24–48 ) } for the second stage . We use the same uniform prior for {D ( 24–48 ) , q ( 24–48 ) } in the two approaches . The second approach has the advantage that the SMC-ABC algorithm only needs to search over the parameter space of 24–48 h , {D ( 24–48 ) , q ( 24–48 ) } . Thus , we expect the second approach to be faster and more efficient . For each joint posterior distribution of {D ( 0–24 ) , q ( 0–24 ) } , we assess the bivariate normality assumption using a Q-Q plot of chi-square quantiles against the squared Mahalanobis distance [43] . The Q-Q plots suggest that the bivariate normality assumption is reasonable for both initial cell densities . We found that the ABC posterior distributions of {D ( 24–48 ) , q ( 24–48 ) } in the two approaches are indistinguishable . However , the second approach is more efficient in terms of computational time . Therefore , for all experimental conditions in the two scenarios , we first obtain estimates for periods 0–24 h and 0–48 h then use the second approach to obtain estimates for 24–48 h . A comparison of D and q for different time periods is shown in Fig 6 . Results in Fig 6A–6D correspond to experiments initiated with 20 , 000 and 30 , 000 cells , respectively . We observe that the estimated posterior distributions of D ( 0–24 ) and D ( 24–48 ) are non-overlapping , which implies that estimates of cell diffusivity are significantly different for the two periods of the experiment . Comparing the posterior estimates of D for different C ( 0 ) suggests that values of D for the 30 , 000 initial cell density experiment is higher than for those in the 20 , 000 initial cell density experiment during the period 0–24 h . However , the difference is insignificant for the period 24–48 h and for the entire period 0–48 h . These findings indicate that estimates of cell diffusivity depend less on the initial cell density for longer experiments . In contrast , the posterior estimates of cell-to-cell adhesion strength , q , for different C ( 0 ) are substantially different for all three periods . In particular , the estimates of q for the experiments initiated with 30 , 000 cells are higher than the corresponding values from the experiments initiated with 20 , 000 cells . This implies that estimates of cell-to-cell adhesiveness depend on initial cell densities . The higher the initial density , the stronger the cell-to-cell adhesion strength . In the literature , several studies have investigated the role of cell-to-cell adhesion in collective cell spreading [44–46] by matching the cell density profiles between the experimental data and the model simulation with several values of q . The previous approach is limited in that it can only give a point estimate of q and provide no insight into the uncertainty in the estimate or the correlation between D and q . Therefore , this study is the first attempt to provide a systematic approach to jointly infer the values of D and q , and compare the distributions of D and q for different experimental conditions . To analyse the second set of experiments , we consider two approaches: ( i ) assuming that the values of D and q in the two experimental scenarios are completely unrelated , and thus , inferences of D , q and λ are based solely on the experimental data in Scenario 2 , and ( ii ) assuming that the values of D and q from Scenario 1 are equal to those of D and q in Scenario 2 . For the latter approach , we adopt a Bayesian sequential learning approach and use the posterior distribution of D and q from Scenario 1 as the prior for D and q for the corresponding experiments in Scenario 2 .
Quantifying the underlying mechanisms that drive the expansion of melanoma cell colonies such as migration , proliferation , and cell-to-cell adhesion is important for developing a systematic approach to assessing the effectiveness of a potential treatment . Typical approaches to parameter estimation often use a deterministic framework [4–7 , 23] and only produce point estimates . There is , therefore , a risk that future model projections based on such point estimates could be made with undue confidence . In this paper , we present a new ABC algorithm to estimate D , q and λ which represent the cell motility , the cell-to-cell adhesion strength and the cell proliferation rate , respectively . To the best of our knowledge , this is the first time that joint inferences have been obtained for all three parameters in a discrete stochastic model describing expanding melanoma cell colonies , using data from a single assay . The new ABC algorithm shows favourable performance relative to state-of-the-art algorithms and together with our derived summary statistics , we can estimate all model parameters precisely across different scenarios , even when a vague prior is used ( Tables 1 and 2 ) . This emulates a situation in which virtually no biological knowledge about D , q and λ is assumed . Furthermore , the methodology developed here overcomes the limitation in the previous work [16] , which demonstrated that without prior information about D , λ cannot be identified using solely leading edge data . The methodology proposed here allows us to obtain inferences for D , q and λ in a fully Bayesian framework . The resulting posterior distributions enable us to quantify the associated uncertainty with the parameter estimates which can not be achieved using a deterministic approach . Furthermore , comparing the distributions of D , q and λ ( Figs 6 , 7 and 9 ) provides insight into the dependency of the parameter posterior estimates on the experimental elapsed time and on the initial number of cells . Thus , our work adds significant extra information about the parameters relative to the previous analyses [23] . Another advantage of using an ABC approach is the possibility of combining information from the two experiments in a principled way . This approach is shown to be useful in our previous work [16] . Here , it also enables us to gain additional information for D and λ . We acknowledge that our discrete individual-based model , which is straightforward to implement and computationally cheap , makes an assumption that cell diffusivity is constant . Although the density dependence is less pronounced for experiments terminated at 48 h , it suggests that the underlying assumption of a constant diffusion coefficient D is violated . Thus , it is suggested that the use of a non-linear diffusion coefficient , where D is a function of cell density , D ( C ) , may be more appropriate . In particular , using non-linear diffusion coefficients is shown to provide a better description of the collective behaviour of a cell population in a lattice-free model [47] and a model with complex contact interactions [48] . We expect that implementation of the ABC approach for these models will lead to further research . It should also be noted that [23] obtained point estimates of D , q and λ separately; D and q from the experiments with cell proliferation suppressed , and λ from experiments with cell proliferation . Thus , this approach may not be applicable if one does not have access to this kind of detailed experimental data sets . Furthermore , results from our analyses also indicate that cell-to-cell adhesion may differ between the two scenarios . In particular , the values of cell-to-cell adhesion is slightly higher for the experiments with cell proliferation occurring , due to the increasing cell population . Thus , we suggest that future studies should consider estimating all parameters simultaneously . One particular finding from our analysis is that the posterior distributions of D and q consistently depend on the experimental time period , whereas the posterior distribution of λ is approximately time constant . This finding is in agreement with the results of [16] for 3T3 fibroblast cells , however , this feature has not been investigated elsewhere . As demonstrated earlier , this effect is significant and should be included when modelling mechanisms governing the expansion of cell colonies in future research . To achieve this , we suggest that experimental data should be collected at several time points and to optimally do this we leave for future research . In addition , our ABC algorithm together with the derived summary statistics could also be implemented in a model selection algorithm to distinguish between discrete lattice-based and lattice-free models describing the expansion of cell colonies . In lattice-free models , agents are allowed to migrate and proliferate in a continuous domain , and the direction of movement is a continuous variable [10] . Thus this model is considered to be more realistic than the lattice-based model . | Quantifying the underlying parameters that drive the expansion of melanoma cell colonies such as the cell diffusivity , cell proliferation rate and cell-to-cell adhesion strength can improve our understanding of melanoma biology and its response to treatment . We combine a simulation-based model of collective cell spreading with a novel Bayesian computational algorithm to estimate these parameters from carefully chosen summaries of collective cell image data and to quantify their associated uncertainty across different experimental conditions . Our summarisation of the image data leads to precise estimates for all parameters . Our analysis reveals that the cell diffusivity and the cell-to-cell adhesion strength estimates depend on experimental elapsed time . Furthermore , the cell-to-cell adhesion strength estimate appears to depend on the initial cell density , whereas the cell proliferation rate estimate is approximately the same over different experimental conditions . | [
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] | [] | 2015 | Melanoma Cell Colony Expansion Parameters Revealed by Approximate Bayesian Computation |
Trachoma prevalence surveys provide the evidence base for district and community-wide implementation of the SAFE strategy , and are used to evaluate the impact of trachoma control interventions . An economic analysis was performed to estimate the cost of trachoma prevalence surveys conducted between 2006 and 2010 from 8 national trachoma control programs in Africa . Data were collected retrospectively from reports for 165 districts surveyed for trachoma prevalence using a cluster random sampling methodology in Ethiopia , Ghana , Mali , Niger , Nigeria , Sudan , Southern Sudan and The Gambia . The median cost per district survey was $4 , 784 ( inter-quartile range [IQR] = $3 , 508–$6 , 650 ) while the median cost per cluster was $311 ( IQR = $119–$393 ) . Analysis by cost categories ( personnel , transportation , supplies and other ) and cost activity ( training , field work , supervision and data entry ) revealed that the main cost drivers were personnel and transportation during field work . Population-based cluster random surveys are used to provide the evidence base to set objectives and determine when elimination targets have been reached for several neglected tropical diseases , including trachoma . The cost of conducting epidemiologically rigorous prevalence surveys should not be a barrier to program implementation or evaluation .
Trachoma is an eye disease , caused by infection with ocular Chlamydia trachomatis , which causes blindness . However , trachoma can be treated and prevented through the SAFE strategy , endorsed by the World Health Organization ( WHO ) : Surgery for trichiasis; Antibiotic therapy through mass distribution; Facial cleanliness promotion through health education; and Environmental improvement with sanitation . Trachoma is endemic in 57 countries worldwide , with the burden of disease concentrated in sub-Saharan Africa and the Middle East[1] . The WHO estimates that over 80 million people currently have active trachoma and another 8 million suffer from trichiasis , with a potential productivity loss of $2 . 9 billion annually at the global scale[2] . The World Health Assembly has set 2020 as the target date for the elimination of blinding trachoma worldwide[3] . Where trachoma is suspected to be a public health problem , the WHO recommends that the prevalence of the clinical signs of the disease are estimated using a cluster random survey methodology at the district level[4] . There are two other less common methods used to assess the burden of trachoma disease: trachoma rapid assessments ( TRA ) ; and acceptance sampling trachoma rapid assessment ( ASTRA ) [5] , [6] . As demonstrated in the literature[7] , the population-based probability sampling ( PBPS ) method is the most epidemiologically robust method available to generalize the prevalence of clinical signs to the domain of interest . In brief , the PBPS method employs a multi-stage cluster random survey design to randomly select clusters , and households within the clusters . Once households are selected , all members of the household are examined for clinical signs of trachoma disease using the WHO Simplified Grading System[8] . Survey team members are trained to conduct trachoma grading and household selection before participating in survey field work . Most survey teams consist of pairs of trachoma examiners and recorders , with one or two pairs needed to survey a cluster . Upon completion , double entry of survey data and analysis are performed by temporary staff or non-governmental organizations and Ministry of Health personnel . Trachoma prevalence surveys provide an estimate of the burden of disease at the level of interest , usually the district . These data serve as the evidence base for determining how the SAFE strategy should be employed . For example , where the prevalence of the clinical grade TF ( trachomatous inflammation , follicular ) exceeds 10% in children aged 1–9 years , the WHO recommends district-wide mass treatment with antibiotics and facial cleanliness and environmental improvements—the “AFE” of SAFE . Prevalence survey data are also used to calculate annual intervention targets and ultimate intervention goals ( UIGs ) , such as the number of people who require trichiasis surgery . These targets are used to plan annual activity budgets , forecast the need for donated pharmaceuticals and other supplies , and monitor progress towards the elimination of blinding trachoma . Although survey implementation may vary by location , there are currently no data on the cost of trachoma prevalence surveys in the peer-reviewed literature . There are examples in the literature where different survey methods were compared to determine the most cost-effective method to estimate immunization coverage[9] , [10] . While comparisons such as these can be used to evaluate the cost-effectiveness of different survey methods , they do not provide sufficient data to generalize the cost of conducting these surveys at the regional or global level . In this paper , we present an analysis of costs incurred in the implementation of trachoma prevalence surveys across eight national trachoma control programs . The findings from this analysis will enable national trachoma program managers and international partners to budget for trachoma prevalence mapping appropriately .
The analysis of prevalence survey cost data did not involve any research on human subjects . The prevalence surveys reviewed in this paper were conducted in accordance with the Declaration of Helsinki and reviewed by the Emory University Institutional Review Board or the London School of Hygiene and Tropical Medicine ( LSHTM ) Ethical Committee and each country's respective Ministry of Health . External funding for the prevalence surveys was as follows: LSHTM , The Gambia survey; Helen Keller International , Sikasso Region of Mali; The International Trachoma Initiative and The Carter Center , 18 districts in Ghana; The Carter Center , all other surveys . A systematic review of trachoma prevalence surveys conducted in Ethiopia , Ghana , The Gambia , Mali , Niger , Nigeria , Sudan , and Southern Sudan was performed February through May 2010 . This review of prevalence survey costs included surveys that employed a PBPS methodology to estimate trachoma prevalence at the district level , or the administrative unit equivalent to a district ( administrative unit with population of approximately 100–250 thousand people: woreda in Ethiopia , region in The Gambia , local government area in Nigeria , locality in Sudan , and county in Southern Sudan ) . Included surveys were implemented from 2006–2010 , and funded or co-funded by The Carter Center , LSHTM ( The Gambia ) , The International Trachoma Initiative ( Ghana ) , or Helen Keller International ( Sikasso Region , Mali ) . All surveys were ‘cluster random surveys’ that used a two stage sampling process to select clusters ( communities , villages , or enumeration areas ) representative of the domain in the first stage and households within the cluster in the second . The numbers of clusters and households in the surveys was not constant between districts . A data collection tool was used to collect the actual costs incurred in local currency during survey activities from accounting records in the programs . The tool collected data for four cost activities: training , field work , supervision and data entry . Training included costs such as per diem of trainees and trainers , meeting facility and supplies , transportation to the practical exercise and any required overnight accommodation . Field work costs included per diems for survey personnel ( trachoma grader and recorder ) , transportation of survey field team , accommodation and supplies such as tetracycline eye ointment and magnifying loupes . Supervision included any per diem , transport and accommodation paid to Ministry of Health or NGO personnel retained for supervision of field work activities . Data entry costs included per diem of data entry clerks , cost of computer rental and information technology support ( if required ) and supplies . For each cost activity , data were collected on the number of people paid , the daily rate and the number of days paid . Transportation costs included any vehicle rental , fuel expense and driver per diem . The data collected in this study captured the incremental cost of conducting prevalence surveys in the context of an existing national trachoma control program . Ministry of Health and NGO salaries and other associated costs were not included in the analysis . Integrated prevalence surveys ( more than one disease measured ) were excluded from this analysis . “Headquarters” expenses were not included in the primary analysis of prevalence survey costs . Although beneficial , consultant or other outside technical assistance is not required for a national program to conduct trachoma prevalence surveys . Furthermore , the cost of outside technical assistance is dependent on travel expense policies which are unique to each partner . The cost of Carter Center headquarter support for specific survey activities are reported in this review , but were not included in the district-level cost data , as these costs are organization-specific and cannot be generalized . Once completed , the cost data forms were verified against the financial reports from the Carter Center , Helen Keller International , LSHTM or the Ministries of Health . In Ghana , Ethiopia and Northern Sudan , exact data on distance traveled were not available; the data reported for these programs' distance traveled are estimates from the national programs . Data were converted to US dollars using the mean of the weighted average exchange rate from the World Bank ( http://data/worldbank . org/indicator/PA . NUS . FCRF ) for the years 2007–2009 . Since most district-level prevalence surveys were conducted in groups ( i . e . all districts in a region surveyed at the same time ) , costs were not reported for each individual district . Rather , each “grouping” of surveys that were financed at the same time was analyzed as the same observation . For example , in the Kayes Region of Mali , all 7 districts were surveyed using the same survey personnel within the same period of time . Funds were provided to the Ministry of Health to conduct the survey work for the entire region , which resulted in efficiencies gained by conducting one initial training and reducing the amount of transport required . Where data were reported in this fashion , the districts are treated as the same observation in the analysis . Based on these observations , the analysis generates the overall costs , the average survey costs per district and average costs per cluster for each observation . Data were first entered into Excel and then analyzed using STATA to generate descriptive statistics for each cost activity . Subsequently , a cost composition analysis was performed . The data were classified into activities as defined in the data collection tool to calculate the proportion of the total cost for each cost activity . Within each of the four activities ( training , field work , supervision and data entry ) , four main cost categories were identified: personnel , transportation , supplies and other . The costs for each category were compared against the total cost for each activity to identify the main cost drivers of survey expenses . Normally distributed data are presented as the mean and standard deviation ( SD ) . Not-normally distributed data is presented by the median and inter-quartile range ( IQR ) .
A total of 29 observations were collected from eight national trachoma control programs . The cost per district by observation is presented in Table 1 . Overall , a total of 165 district-level surveys were included ( Figure 1 ) , representing a total of 3 , 203 clusters surveyed . The average costs per district were skewed to the right by an outlier ( Ayod in Southern Sudan , $25 , 409 ) so are described by the median , $4 , 784 and IQR , $3 , 508–$6 , 650 . The median cost per cluster was $311 ( IQR = $119–$393 ) whilst the median cost per person screened was $3 . 50 ( IQR = 1 . 94–4 . 16 ) . ( The mean cost per district , cluster and person was $5 , 849 ( SD = $4 , 635 ) , $324 ( SD = $236 ) , and $3 . 39 ( SD = $2 . 02 ) respectively ) . The least expensive survey per district was in Ethiopia , approximately $1 , 511 per district . The number of districts , clusters and persons sampled per observation is presented in Table 1 . When the costs for each survey activity were compared against the total cost ( Table 2 ) , the data showed that field work comprised on average 69 . 9% of the total cost of a survey . Among the observations , the proportion of total costs spent on field work ranged from 44 . 9% to 90 . 5% . Training costs ranged from 1 . 0% to 29 . 6% of total costs , supervision expenses were between 0 . 0% and 20 . 9% of the total , and data entry costs ranged from 0 . 0% to 25 . 0% across all observations . Within each survey activity , personnel costs were the most expensive , with personnel costs in field work accounting for 40 . 4% of the total survey costs reported by the national programs , followed by transportation during field work at 22 . 4% . Training and data entry activity costs were reported by observation as the cost for each activity . These costs were not always directly related to the number of districts surveyed as some programs did not incur cash costs for these activities . The mean cost of training was $1 , 342 ( SD $659 ) while the median was $1 , 791 . 50 ( IQR = $588–$1 , 816 ) . The mean cost of data entry was $2 , 548 ( SD $3 , 493 ) and the median was $1 , 028 ( IQR = $415–$4 , 431 ) . Although the cost of outside technical assistance was not factored into the district or cluster level cost analysis , there were 9 observations that were surveyed with at least one representative from The Carter Center Headquarters ( Atlanta , Georgia , USA ) present , covering a total of 58 districts . The average cost for airfare , hotel , meals and incidentals per person-trip was $1 , 779 ( n = 13 , SD = $2 , 027 ) from 2006–2010 .
It is possible that trachoma control programs do not implement prevalence surveys due to a perception that the costs will be beyond the capacity of the program . However , the results of this analysis show that such surveys are not cost-prohibitive . The range of costs per district varied from $1 , 151–$25 , 409 , in large part due to differences in accessibility and the number of clusters sampled in each survey . Of the 29 observations , only three surveys reported a cost per cluster exceeding $500: Ayod in Southern Sudan , Kidal in Mali and the Northern Region in Sudan . These surveys were characterized by both high transport and personnel costs . In Ayod County of Southern Sudan , where the average cost per cluster was $1 , 270 and average cost per person screened was $10 . 88 , vast distances of water-logged and unforgiving terrain made vehicle transport impossible , requiring a chartered airplane to transport staff to airstrips from where they traveled to the clusters on foot over a period of days . These exceptional circumstances therefore required additional staff , working for a longer period of time , and transport by chartered aircraft . In Kidal Region ( a desert region of Mali ) , the second most expensive survey per cluster ( $739 per cluster , $6 . 83 per person screened ) , the sparse population ( 80 , 000 ) and low population density ( less than one person per square kilometer ) resulted in the national program treating the region as the domain , with the consequence that the distances between clusters was hundreds of kilometers . To conduct this survey , the program rented vehicles instead of using Ministry of Health and NGO transport due to security concerns in the area . The Northern Region of Sudan ( $552 per cluster , $3 . 29 per person screened ) is also on the edge of the Sahara with similar demands on transport and time . Least expensive , at under $100 per cluster , were the surveys conducted in the Amhara region of Ethiopia ( $84 per cluster , $1 . 31 per person screened ) and Plateau and Nasarawa States of Nigeria ( $92 per cluster , $1 . 11 per person screened ) where per diem rates were low and the population is relatively dense , reducing both the travel costs and time spent travelling between clusters . In total , 7 observations cost less than $125 per cluster and these also had the lowest cost per person screened ( $0 . 91–$1 . 31 ) . In these surveys , the relative proximity of clusters and low per diem rates contributed to lower costs in comparison to the more expensive surveys . Among the cost categories reported , the per diem of field staff and supervisors and the cost of transportation accounted for 73% of the total survey costs . In settings where distances between communities are great , trachoma control programs may consider reducing the number of clusters surveyed and increase the number of people screened per cluster to reduce costs but maintain an adequate sample size . However , the risks to accuracy and precision around the prevalence estimate should be considered . Cost savings on transport and accommodation costs can be achieved by planning the route of vehicles between clusters carefully . A route for two teams can often be planned in which the teams share one vehicle , work in the first and second clusters simultaneously ( with the vehicle shuttling between as necessary ) and then travel together to the next cluster where they camp for the night and sensitize the village population of the survey to be conducted the following day . Such transport sharing and camping has been both effective and enjoyable in most of the countries in this analysis . Per diem and allowance costs vary by national program , level of trained personnel recruited to serve as survey team members and local supervision requirements . Per diem costs in the surveys studied ranged from $6 . 21 per day for graders ( junior health staff ) to $250 a day for senior supervisors ( an ophthalmology professor and National Coordinator ) . When designing surveys , due consideration should be given to assign roles and responsibilities consistent with the qualification and per diem given . Junior health staff who are comfortable with the climate , social circumstances and geography of the area to be surveyed make ideal field staff , and serve to lower per diem costs . It is appropriate for a National Coordinator or ophthalmology professor to spend a day or two testing the ability of the trained examiners before the survey starts , but costs can be reduced if that person does not spend many days in the field . The review of data entry costs also presents new findings for Ministries of Health . Although data entry was not an expense for all surveys reported , data entry accounted for an average of 11% of total survey expenses . In this sample , the incremental cost of data entry ranges from 0% in surveys where existing program staff conducted data entry on existing computers incurring no additional cash cost to 25% of the total cost of the survey where external contractors were hired to complete the work . Survey planners should consider the cost of data entry in their own country context to ensure that costs for double entry , analysis and preparation of printed reports are included in budgets . By design , we did not capture the cost of each Ministry of Health and NGO employee who contributed time to conduct survey work , the incremental cost effectiveness ratio is likely to be underestimated since these costs were not taken into account . This could be included in the analysis as an opportunity cost . However , since the implementation of prevalence surveys is recommended as the standard monitoring and evaluation framework for trachoma control programs by the WHO , these surveys were within the mandate of the Ministry of Health personnel who were engaged in field work and supervision . Salary costs were excluded as they were considered part of the functional trachoma control program and we sought to establish the incremental cost of conducting surveys in the presence of a program . We also did not include the cost of technical assistance ( including travel ) for ‘headquarters’ staff . Although the average cost of a person-trip from The Carter Center for technical assistance was $1 , 779 ( SD = $2 , 027 ) , we considered this to be a non-essential cost for a program , subject to considerable variation between supporting NGOs who have different travel policies , and likely to come from a different operating budget which would not have an incremental effect on the cost of a national program . The selection of a sample representative of the underlying population presents an opportunity to collect data on multiple conditions and this has been done for trachoma and malaria[11] and trachoma and urinary schistosomiasis[12] . Such integrated surveys were not included in this analysis since they were considered special cases and not what is typically done . However , the costs of adding indicators for additional diseases or conditions are the additional personnel , equipment and consumables required for that survey , with the other cost items such as transport and per diem of the drivers and assistants covered by the ‘parent’ survey . Although the data presented show costs from a variety of settings , there are a few limitations . The data in this analysis were reported retrospectively and therefore , it is possible that some costs may not have been captured . For some surveys ( Ghana , Ethiopia and Northern Sudan ) log book entries for distance travelled were not available and we relied on the local knowledge of the national program to calculate distance travelled . Each of these surveys was conducted in the presence of a functioning trachoma control program; there was no need to purchase new vehicles or make other large capital expenses . Survey work performed in the absence of this infrastructure would be more expensive . New country programs may find it necessary to rent vehicles and seek technical assistance for training survey staff , the costs of which would need to be considered in addition to the incremental costs of conducting a survey presented here . There are variations in the number of clusters surveyed among the different observations , based on the population of each survey domain , which may affect the comparability of the survey costs among different countries . However , the authors expected variation among national programs due to differences such as per diem rates , the level of qualified health professional involved in field work , and the capacity to complete data entry . The variation seen in these data illustrate the context-specific nature of planning survey activities . However , these limitations should not discourage program managers from using the data presented in this paper as benchmarks for determining funding needs . Twenty-six out of the 29 observations were conducted with external funding exclusively from The Carter Center , which may imply the cost estimates are limited to those surveys supported by this NGO . However , there are similarities between the cost per cluster from The Gambia , which was fully funded by LSHTM , districts in Mali supported by Helen Keller International , and districts in Ghana co-sponsored by the International Trachoma Initiative and The Carter Center . This suggests that our findings are not unique to the operating principles of one NGO . Since transport and per diem were identified as major cost drivers , it is possible to predict total survey costs for areas requiring surveys . It is also possible to use these data to project the cost of other survey methodologies by applying the average cost per cluster to the number of clusters required . Despite the potential limitations of this study , these data present the only summary of actual costs incurred during trachoma prevalence surveys in the peer-reviewed literature . For the goal of elimination of blinding trachoma worldwide by 2020 to be met , national programs will need to budget for impact evaluation at the district level . The cost of epidemiologically rigorous surveys should not been seen as a barrier to their implementation . With adequate baseline and impact evaluation data , national programs can maximize their limited programmatic resources . These data should inspire national trachoma program managers and ministry of health staff involved in other public health supervisory roles to consider implementation approaches that ensure surveys are designed in a cost-effective and efficient manner . These cost data will enable the international trachoma control community to create global estimates on the cost to complete trachoma prevalence mapping and estimate the financial needs to support impact assessments to measure progress towards the elimination of blinding trachoma . | The costs of conducting population-based prevalence surveys for neglected tropical diseases such as trachoma are often cited as a reason that program managers do not conduct baseline or impact assessments when guidelines suggest they are warranted . The authors conducted a review of actual costs incurred during the implementation of 165 district level surveys in 8 national trachoma control programs to identify the median and mean costs per district and per cluster . In addition , the costs of the principal activities that are the most expensive were measured . The data show that field work is the most expensive activity for a prevalence survey , with personnel ( per diems , allowances and accommodation ) and transport costs driving the total cost of the survey . These findings can be used by program managers to budget for population-based prevalence surveys that are recommended for baseline and evaluation surveys , and periodic uptake surveys for neglected tropical diseases such as trachoma . | [
"Abstract",
"Introduction",
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] | [
"infectious",
"diseases/neglected",
"tropical",
"diseases",
"ophthalmology"
] | 2011 | Incremental Cost of Conducting Population-Based Prevalence Surveys for a Neglected Tropical Disease: The Example of Trachoma in 8 National Programs |
Scrub typhus is an important endemic disease in tropical Asia caused by Orientia tsutsugamushi for which no effective broadly protective vaccine is available . The successful evaluation of vaccine candidates requires well-characterized animal models and a better understanding of the immune response against O . tsutsugamushi . While many animal species have been used to study host immunity and vaccine responses in scrub typhus , only limited data exists in non-human primate ( NHP ) models . In this study we evaluated a NHP scrub typhus disease model based on intradermal inoculation of O . tsutsugamushi Karp strain in rhesus macaques ( n = 7 ) . After an intradermal inoculation with 106 murine LD50 of O . tsutsugamushi at the anterior thigh ( n = 4 ) or mock inoculum ( n = 3 ) , a series of time course investigations involving hematological , biochemical , molecular and immunological assays were performed , until day 28 , when tissues were collected for pathology and immunohistochemistry . In all NHPs with O . tsutsugamushi inoculation , but not with mock inoculation , the development of a classic eschar with central necrosis , regional lymphadenopathy , and elevation of body temperature was observed on days 7–21 post inoculation ( pi ) ; bacteremia was detected by qPCR on days 6–18 pi; and alteration of liver enzyme function and increase of white blood cells on day 14 pi . Immune assays demonstrated raised serum levels of soluble cell adhesion molecules , anti-O . tsutsugamushi-specific antibody responses ( IgM and IgG ) and pathogen-specific cell-mediated immune responses in inoculated macaques . The qPCR assays detected O . tsutsugamushi in eschar , spleen , draining and non-draining lymph nodes , and immuno-double staining demonstrated intracellular O . tsutsugamushi in antigen presenting cells of eschars and lymph nodes . These data show the potential of using rhesus macaques as a scrub typhus model , for evaluation of correlates of protection in both natural and vaccine induced immunity , and support the evaluation of future vaccine candidates against scrub typhus .
Scrub typhus is a common but under recognized acute febrile illness caused by Orientia tsutsugamushi , a Gram-negative obligate intracellular bacterium . Mites ( Acari: Trombiculidae ) , serve as both the vector transmitting the bacteria during their larval stage ( chigger ) to vertebrate hosts and the reservoir maintaining the bacteria during their life cycle [1] . The clinical signs and symptoms of scrub typhus are similar to other infectious diseases , which complicates clinical diagnosis . Despite available drugs ( tetracyclines , chloramphenicol , azithromycin , rifampicin ) , scrub typhus remains an underappreciated health care problem due to difficulties in clinical and laboratory diagnosis , delayed treatment responses in northern Thailand and southern India , and the lack of an effective vaccine [2] . Studies of scrub typhus pathogenesis and immunity , critical to vaccine development , require suitable animal models to understand the interaction and temporal dynamics between O . tsutsugamushi and host responses . Various animal models have been developed for scrub typhus , including mice , guinea pigs , and non-human primates ( NHP ) [3–7] . In mouse models , both inbred and outbred mice developed clinical manifestations in various degrees; however , the mouse models did not develop reproducible pathology resembling human scrub [8] . In immunological studies , a CD8 T-cell mediated cytotoxic immune response was shown necessary for clearance of O . tsutsugamushi and protection from lethal infection [9 , 10] . Although cell-mediated immunity ( CMI ) plays a central role in heterologous protection amongst the different strains of O . tsutsugamushi in inbred mice it was short-lived and waned after few months [11 , 12] . Recently , apoptosis was proposed as a potential contributor to this phenomenon in humans , but this alone does not explain all findings associated with the transience of broad immune protection [11 , 12] . A NHP model mimicking human disease will enable investigations into these mechanisms [4 , 13] . Previous studies in NHPs; Chattopadhyay et al . evaluated a truncated recombinant 56-kDa outer membrane protein of the Karp strain ( Kp r56 ) as a vaccine candidate in cynomolgus monkeys ( Macaca fascicularis ) , which induced both cellular and humoral immune responses that decreased local inflammation at the inoculation site , but did not confer protection to re-infection [3] . Then , Walsh et al . characterized the eschar and regional lymph node using histological and immunohistochemistry staining and demonstrated the localization of O . tsutsugamushi within the eschar and a regional lymph node . However , only two out of six monkeys developed necrotic eschars with unequivocal black crusted ulcers at the injection site [14] . A recent vaccine study using 47-kDa htrA candidate vaccines in cynomolgus monkeys demonstrated induction of sterile immunity against high-dose homologous challenge of O . tsutsugamushi . In addition , Paris et al . provided the first phenotypic correlates of immune protection in scrub typhus and presented the time course dynamics of bacteremia and host immune responses [4 , 5 , 13 , 14] . Clearly further detailed studies of natural and vaccine-induced immune mechanisms in response to O . tsutsugamushi are required , with evaluation of other vaccine targets . Colony-reared cynomolgus monkeys are scanty compared to rhesus macaques ( Macaca mulatta ) which are more widely used as infectious disease models , and are likely to have more immunological data available . Even though cynomolgus macaques are considered suitable NHP models for scrub typhus , the disease manifestations are mild and correlates of immune protection appear delayed compared to humans . The aim of this study was to evaluate the role of rhesus macaques for a standardized NHP disease model for scrub typhus , in view of dissecting the dynamics of disease dissemination and early host-pathogen interactions in both natural infection and the vaccination/challenge setting with further characterization of early innate and adaptive immune responses . We anticipated that this study would provide improved data on the factors/parameters associated with immune protection and provide an animal model with sufficient parallels to humans for evaluating the safety , immunogenicity and efficacy for future scrub typhus vaccine candidates .
All animal research was performed strictly under approved Institutional Animal Care and Use Committee ( IACUC ) protocol by the IACUC and Biosafety Review Committee at the Armed Forces Research Institute of Medical Sciences ( AFRIMS ) Bangkok , Thailand , an AAALAC International-accredited facility . The IACUC protocol number was PN12-01 ( approved 31st Jan 2012 ) . The animal research was conducted in compliance with Thai laws , the Animal Welfare Act , and all applicable U . S . Department of Agriculture , Office of Laboratory Animal Welfare and U . S . Department of Defense guidelines . All animal research adhered to the Guide for the Care and Use of Laboratory Animals , NRC Publication ( 8th Edition ) [15] . Animals were housed individually in standard squeeze-type stainless steel cages with a minimum floor space of 4 . 4 square feet equipped with standard enrichments and exposed to ambient environmental conditions inside an Animal Biosafety Level 3 ( ABSL-3 ) containment laboratory . All NHPs were fed daily with commercially prepared old-world primate extruded feed and supplemented with fresh fruit or vegetable four times per week . Fresh chlorinated water ( 5–10 ppm ) was provided ad libitum via automatic water valves . Cages were cleaned daily and sanitized biweekly . Animals were trained for 2–3 weeks for pole-collar-chair restraint prior to the commencement of the study in which no anesthesia was required . All other procedures were performed under anesthesia using ketamine hydrochloride , and all efforts were made to minimize stress , improve housing conditions , and to provide enrichment opportunities . Animals were euthanized by ketamine hydrochloride injection ( 5–20 mg/kg intramuscularly ) followed by barbiturate ( 86 . 7 mg sodium pentobarbital/kg ) in accordance with the Guidelines for the Euthanasia of Animals ( 2013 Edition of the American Veterinary Medical Association ) . Laboratory-reared Indian-origin rhesus macaques ( Macaca mulatta ) from AFRIMS colony were used in this study . The AFRIMS rhesus macaque colony was established in 1981 . The Indian-origin rhesus macaques were originally imported from primate centers in the USA and have been reared at the AAALAC International-accredited AFRIMS facilities since 1999 . All monkeys utilized in this study were born and reared at AFRIMS . Six of 7 macaques had participated in a prior malaria study ( Plasmodium cynomolgi ) and one was naïve . The seven macaques ( 3 males and 4 females ) were three years of age and weighed between 4 . 7–5 . 4 kg at the start of the study . The animals had no prior exposure to O . tsutsugamushi with negative antibody titers to O . tsutsugamushi and negative serology for Simian Immunodeficiency Virus ( SIV ) , Simian Retrovirus ( SRV ) , Simian T-lymphotropic Virus ( STLV-1 ) and Macacine Herpesvirus 1 ( B virus ) . The macaques were randomly allocated to either a ‘control or mock infection’ ( n = 3 ) or ‘O . tsutsugamushi infection’ ( n = 4 ) group . One week prior to Inoculation Day 0 , macaques underwent a complete physical examination that included a blood draw ( total of 5 . 0 ml of whole blood ) for complete blood count , blood chemistry analysis , O . tsutsugamushi-specific quantitative real-time polymerase chain reaction ( qPCR ) assay , and immunological and serological tests to establish baseline values . All animals had good general health as determined by the attending veterinary staff through complete physical examination and laboratory examinations ( completed blood count ( CBC ) and blood chemistry ) . The human isolated strain ( Karp , Papua New Guinea , 1943 ) of O . tsutsugamushi was propagated in CD-1 Swiss mice at the Naval Medical Research Center , Silver Spring , Maryland , USA [16] . Pre-aliquots of liver-spleen homogenates of O . tsutsugamushi ( Karp strain ) at 1x106 murine LD50 ( MuLD50 ) were prepared and applied to the O . tsutsugamushi infected macaques as previously described [4 , 6] . The control animals received aliquots of liver-spleen homogenates from healthy uninfected mice . A trained veterinarian performed all inoculations on anesthetized macaques via intradermal injection ( 26G needle ) on Inoculation Day 0 . All macaques were inoculated at the left anterior medial thigh , and were observed daily for clinical signs including the development of skin lesion , regional and generalized lymphadenopathy , loss of appetite , and elevated body temperature . Rectal temperature was measured daily without anesthesia between 15:00 to 15:20 using pole and collar restraint . Local inoculation sites were observed and scored following the Draize and Rise scoring protocols ( S1 Table ) . Blood was drawn every other day for bacterial quantitation ( qPCR ) and at day 0 , 14 , and 28 post inoculation ( pi ) for hematological , biochemical , and immunological bioassays . Control monkeys were euthanized at day 28 pi while O . tsutsugamushi-infected monkeys were euthanized at day 30 pi , and a panel of tissue specimens for histopathological examination and cerebro-spinal fluid ( CSF ) were collected for O . tsutsugamushi qPCR quantification , and immunohistochemical staining . To determine and quantitate the bacterial load of O . tsutsugamushi post-inoculation , an O . tsutsugamushi-specific 47kDa gene qPCR assay was performed on blood , CSF , tissues , and eschar swab DNA preparations [6] . The rhesus-specific qPCR assay targeting the single copy macaque oncostatin M ( osm ) gene was used to quantitate host cells in tissue samples as previously described [6 , 17] . Results are reported as the ratio of O . tsutsugamushi to host cell counts . PCR reactions were performed on a CFX96 Real-Time System ( BioRad , Foster City , CA , USA ) , “no template” negative controls were run with each reaction and plasmid DNA served for standard curves in serial dilutions from 106 to 3 copies/μl of 47 kDa protein and macaque osm genes . The copy number was calculated from the cycle threshold using Bio-Rad software , and quantitation of 47 kDa protein gene was expressed per 104 macaque cells . The area under the curve was calculated using GraphPad Prism 7 software . Complete blood counts were performed to determine erythrocyte count , hemoglobin , hematocrit , platelet count , leukocyte count , leukocyte differential , mean red blood cell volume , mean red blood cell hemoglobin , mean red blood cell hemoglobin concentration , and mean platelet volume . Plasma collected from heparinized blood was assessed for the concentration of albumin , creatinine , aspartate aminotransferase , alanine aminotransferase , alkaline phosphatase , cholesterol , total bilirubin , urea nitrogen , and creatinine kinase levels . Soluble E-selectin , L-selectin , ICAM-1 , and VCAM-1 in macaque sera were assessed using E-selectin ( Abcam , Cambridge , UK ) , VCAM-1 ( Uscn , Wuhan , China ) , and ICAM-1 ( Abnova , Taoyuan , Taiwan ) ELISA kits following the manufacturer instructions . Serum samples were diluted 1:10 . All samples and standard dilutions were assayed in duplicate , the optical densities measured using a microplate spectrophotometer ( Multiskan Go; Thermo scientific , Waltham , MA ) , and the concentrations of cell adhesion molecules were determined from a standard curve . Serum samples were assessed for O . tsutsugamushi-specific IgM and IgG antibody titers by indirect immunofluorescence ( IFA ) and ELISA assays at D0 , D14 and D28 . Antigen slides coated with O . tsutsugamushi Gilliam ( Burma ) and Litchfield ( Australia ) stains were purchased from the Australian Rickettsial Reference Laboratory ( Geelong , Australia ) . Serum samples were serially diluted two-fold from 1:100 to 1: 25 , 600 in 2% skimmed milk PBS buffer and incubated onto the antigen slides for 30 min . After washing three times with PBS buffer , slides were incubated with FITC-conjugated goat anti-monkey IgM or IgG ( Brookwood Biomedical , Birmingham , AL ) for 30 min , and mounted with fluorescence mounting medium ( Dako , Glostrup , Denmark ) for fluorescence-based microscope endpoint titer determination . O . tsutsugamushi strain Karp ( Papua New Guinea ) whole cell antigen was kindly provided by the Naval Medical Research Center . One-half of a 96-well microtiter plate was coated with O . tsutsugamushi antigen ( 100 μl/well ) , and the other half without antigen ( 100 μl PBS/well ) , and stored at 4°C ( min . 48 hours ) . Following steps were performed at room temperature; plates were washed with 0 . 1% Tween 20 ( Sigma , St . Louis , MO , USA ) in PBS , and blocked with blocking buffer ( 5% Skim milk , 0 . 1% Tween 20 in PBS ) for 1 hour . Diluted serum samples ( 1:100 in blocking buffer ) , were added to all wells ( 100 μL/well ) and incubated for 1 h . After three wash cycles , incubation with horseradish peroxidase conjugated goat anti-monkey IgG or IgM ( Kirkegaard & Perry Laboratories , Gaithersburg , MD ) with 100 μl/well at 1:2000 dilution followed for 1 hour . After three wash cycles , ABTS ( 2 , 2′-azino-di- ( 3-ethylbenzthiazoline sulfonic acid ) ) peroxidase substrate ( Kirkegaard & Perry Laboratories , Gaithersburg , MD ) was added and incubated for 15 min . Optical densities were measured at 405 nm by Microplate Spectrophotometer ( Multiskan Go; Thermo scientific , Waltham , MA ) , and the net optical density ( OD ) of each sample was obtained by subtracting the background OD ( no antigen reading value ) from the O . tsutsugamushi-antigen OD . Positive serum samples ( net OD >0 . 5 ) were serially diluted ( 1:100 , 1:400 , 1:1600 , 1:6400 ) to determine the endpoint titer . The titers were expressed as the inverse of the highest dilution in which a net OD of ≥ 0 . 200 was obtained . The mean net OD of three negative control sera was consistently less than an optical density of 0 . 200 . Peripheral blood mononuclear cells ( PBMC ) were isolated from 4 ml heparinized blood samples as previous described [18] . ELISpot assays for gamma interferon ( IFN-γ ) were performed as per the manufacturer’s instruction ( Mabtech , 3421M-2A , Stockholm , Sweden ) [18] . PBMC were stimulated with 0 . 2 μg of 47kDa O . tsutsugamushi antigen ( recombinant full-length 47kDa Karp strain was produced and purified by Biomatik , USA ) . Leucoagglutinin ( PHA-L ) ( Sigma , St . Louis , MO , USA ) was used as a positive control at 0 . 5 μg per well , and there was no antigen in negative control wells . After 28 days pi , all infected macaques were euthanized and tissue specimens ( normal skin , inoculation site ( eschar ) , draining lymph node , non-draining lymph node , lung , heart , spleen , kidney , liver , bone marrow , mesenteric lymph node , ileum , meninges , brain , brain stem ) were collected . All tissues were fixed in 10% neutral buffered formalin solution ( Sigma , St . Louis , MO , USA ) for at least 2 weeks and processed using an automated tissue processor ( SLEE medical , Mainz , Germany ) . The tissues were then embedded into paraffin blocks and sectioned at 5 μm using a semi-automated rotary microtome ( RM2245 , Leica , Buffalo Grove , IL , USA ) . The tissue sections were mounted onto poly L-lysine coated microscope slides , baked at 60 °C for 14–18 h , and stained with hematoxylin-eosin ( H&E ) or used for immunohistochemistry ( IHC ) . All histopathological sections were evaluated by a board certified veterinary pathologist . The formalin-fixed paraffin embedded tissues were processed as previously described as previously described [6 , 19] . The anti-O . tsutsugamushi monoclonal antibody ( clone 1C4B11 ) of the 56 kDa surface protein of O . tsutsugamushi was applied at dilution 1:2 . Cell marker antibodies used in this study contains CD1a clone NA1/34 at 1:100 ( Dako , Glostrup , Denmark ) , polyclonal CD3 antibody at 1:100 ( Dako , Glostrup , Denmark ) , CD14 clone NCL-L-CD14-223 at 1:75 ( Leica , Newcastle , UK ) , CD31 clone JC70A at 1:2 ( OxFab , Oxford , UK ) , CD68 clone KP-1 at 1:3 ( OxFab , Oxford , UK ) , DCSIGN clone DC28 at 1:200 , and HLADR clone CR3/43 at 1:2 ( OxFab , Oxford , UK ) . Images were acquired and examined using standard fluorescence microscopy ( Nikon Eclipse 80i using the NIS element software from Nikon Tokyo , Japan ) and a confocal laser scanning microscope ( Zeiss LSM 700 , using the AxioVision 40 v4 . 7 . 1 . 0 software from Carl Zeiss Imaging Solutions Gmbh , Germany ) . Images were merged and minimally optimized as a whole file following the requirements for scientific imagery [20] , using Photoshop CS3 extended , version 10 . 0 . Statistical analyses were performed using GraphPad Prism Software v . 7 or STATA version 14 SE ( StataCorp , Texas , USA ) . The results between the infected and non-infected groups were compared using the non-parametric Mann-Whitney U- test . The data of surrogate markers were expressed as median and inter-quartile range , unless otherwise stated . Significant differences between time points within a group were determined with the non-parametric Wilcoxon t-test . Two-tailed P values less than 0 . 05 were considered significant .
All O . tsutsugamushi inoculated macaques developed classical eschar lesions at the injection site within 7 days . The eschars presented as small indurated , erythematous , vesiculo-papules on day 5 , with moderate perifocal erythema and edema , which grew in diameter with increasing erythema , perifocal edema and demarked excoriation resulting in a dark central necrosis with black crust and a raised indurated border on day 7 . Eschars were completely painless , with a round shape , indurated border and a necrotic zone of 6–10 mm in diameter . They reached maximum size on day 10–12 , and then decreased slowly in size until day 21–23 to leave a hyperpigmented area , but no scar ( Fig 1 ) . Explicit regional lymphadenopathy ( inguinal draining lymph node ) was observed in all O . tsutsugamushi inoculated macaques starting on day 7 which developed into generalized lymphadenopathy and resolved before day 21 ( Fig 2 ) . During the bacteremia phase ( median qPCR-positivity from Day 6 to Day 16 ) the infected macaques demonstrated a significantly higher core temperature ( p = 0 . 0335 ) , when the distribution of the median rectal temperatures was compared . The duration of fever was 7 days ( Fig 3 ) , and interestingly , a brief paradoxical drop in rectal temperature was observed before the onset bacteremia ( as noted previously in cynomolgus macaques ) [4] . On day 14 pi , hematological analyses demonstrated significantly elevated leukocyte ( WBC ) counts in O . tsutsugamushi inoculated macaques compared to control macaques , and no differences in erythrocyte ( RBC ) counts , hematocrit ( Hct ) , hemoglobin ( Hb ) , platelet , mean red blood cell volume ( MCV ) , mean red blood cell hemoglobin ( MCH ) , and mean red blood cell hemoglobin concentration ( MCHC ) ( S2 Table ) . Biochemical analyses demonstrated significant changes of albumin and liver enzyme levels ( aspartate transaminase , alanine transaminase , and alkaline phosphatase ) , but not creatinine , cholesterol , total bilirubin , urea nitrogen , and creatinine kinase levels ( S3 Table ) . To detect bacteremia in macaques , whole blood samples were collected every two days for DNA extraction and 47 kDa O . tsutsugamushi qPCR assay . O . tsutsugamushi DNA was first detected on day 6 for all inoculated macaques . The duration of bacteremia ranged from 6 to 18 days , and the bacterial loads ranged from 1 to 85 organisms / 10 , 000 macaque cells per timepoint ( Table 1 ) . Additional eschar swab specimens on days 12 and 14 demonstrated the presence of O . tsutsugamushi DNA in all samples . To reduce eschar crust damage only 2 swab samples were performed . A large bacterial load was detected in animal BR1-02’s eschar , which correlated with bacteremia results ( Table 1 ) . Evidence for endothelial and leukocyte activation was found by increased serum levels of soluble cell adhesion molecules ( sE-selectin , sICAM-1 , and sVCAM-1 ) in O . tsutsugamushi-infected macaques , when compared to mock-infected macaques . Soluble E-selectin and sICAM-1 , but not VCAM-1 serum levels were significantly elevated on day 14 pi compared to controls ( Fig 4 ) . The IgM antibody titers increased rapidly to reach their highest dilution before D14 in both IFA and ELISAs , while IgG levels increased more slowly and were highest at the D28 timepoint . The results from ELISA shown higher antibody titers compared to IFA results ( Fig 5 ) . IgM and IgG antibody titers against O . tsutsugamushi increased in all infected macaques ( n = 4 ) and remained undetectable in the control group ( n = 3 ) . The isolated PBMCs were subjected to the O . tsutsugamushi antigen-specific IFN-γ production ELISpot assay . The median IFN-γ production increased in O . tsutsugamushi inoculated macaques over time , and although the range was wide all O . tsutsugamushi inoculated macaques showed induction of IFN-γ at D28 ( Fig 6 ) . The histopathological evaluation of the submitted tissues noted no significant pathological findings in 16 tissues of O . tsutsugamushi inoculated macaques when compared with control macaques at D29 , suggestive of complete recovery . O . tsutsugamushi DNA was detected by qPCR in eschar and spleen samples of macaque BR1-02 , the draining lymph node of BR1-03 , and in the non-draining lymph node in BR1-05 . The eschar sample contained the highest number of O . tsutsugamushi organisms compared to other tissues . Immunohistochemistry staining of these tissue specimens with anti-O . tsutsugamushi monoclonal antibody 1C4B11 demonstrated O . tsutsugamushi organisms in the dermis of the eschar and in the parenchyma of all three tissues , and a large number of O . tsutsugamushi organisms was observed in the eschar compared to spleen , draining lymph node , and non-draining lymph node . The highest number of intracellular O . tsutsugamushi organisms was observed in antigen-presenting cells ( APCs , HLADR+ , Fig 7 ) . In the eschar ( BR1-02 ) , O . tsutsugamushi was associated with dendritic cells ( HLADR+ , DCSIGN+ , CD1a+ ) and monocyte/macrophage ( CD68+ , CD14+ ) , but not T cells ( CD3+ ) and endothelial cells ( CD31+ ) ( Fig 8 ) , while in the spleen section of the same macaque the only association of O . tsutsugamushi with a leucocyte phenotype was within APCs ( HLADR+ ) ( Fig 7 ) . For the draining and non-draining lymph node samples , O . tsutsugamushi was found to associate with APCs ( HLADR+ ) ( Fig 7 ) .
This study characterized a rhesus macaque intradermal inoculation model of scrub typhus in view of future vaccine development studies . Human scrub typhus is characterized by a febrile illness , often with nonspecific symptoms , an early bacteremia period , during which an inoculation eschar can develop , possible skin rash , a strong association with raised liver transaminases and regional lymphadenopathy after ID inoculation of O . tsutsugamushi via mite bite , and subsequent establishment of humoral and cellular immune responses [12 , 21–24] . The clinico-pathophysiological responses observed in rhesus macaques after ID O . tsutsugamushi inoculation demonstrated striking similarity to human disease , with development of fever during bacteremia , marked eschar formation , regional followed by generalized lymphadenopathy , similar bacteremia onset and duration , altered liver function , increased WBC counts , and pathogen-specific antibody ( IgM and IgG ) and cell-mediated immune responses . Additionally , time course sCAM serum levels demonstrated endothelial and leucocyte activation in analogy to published observations in humans [25] . Although pathophysiological features of human scrub typhus have been described in a cynomolgus macaque ( Macaca fascicularis ) ID inoculation model , these data have not been challenged by or compared to any alternative models i . e . rhesus macaques [26] . The rhesus macaque response was characterized with an earlier onset of clinical disease , a more pronounced eschar formation , stronger liver function damage and a bacteremia phase that corresponded more closely with observations in humans ( D6-16 ) ( Table 2 ) . Importantly , the features and lesions serving as phenotypic correlates of immune protection described in our recent scrub typhus vaccine-challenge study in cynomolgus macaques [3 , 4 , 13] , were found to be more pronounced and resembled more closely to human disease dynamics in the rhesus macaque ( Macaca mulatta ) model: the distribution of fever was significantly raised during the entire bacteremia phase; the eschar lesions were larger in size , more clearly delineated and invariably demonstrated induration , erythema and central necrosis–features required for the RISE score ( S1 Table ) ; bacteremia curves were consistent in onset ( time-to-bacteremia ) ; and biochemistry/hematological markers ( albumin reduction , increased liver transaminases and leukocytosis ) were more pronounced than previously in the cynomolgus macaque model . The rhesus macaque is among the best-known species of Old World monkeys , and due to its wide distribution , and large population , it is listed as “least concern” in the IUCN Red List of Threatened Species . Although rhesus macaques have been well studied for a number of important infectious diseases like tuberculosis , malaria , HIV/SIV-AIDS and recently for Zika , it is important to remain cautious when interpreting data generated in rhesus macaque models in the absence of known human disease mechanisms , as these may differ and prove imperfect for research in certain conditions [27–29] . The extent of research involving rhesus macaques and the broad availability of validated laboratory reagents , especially leucocyte immune-phenotyping reagents ( i . e . mAbs , ELISAs , histopathology reagents , cytokines etc . ) as well as published procedures and protocols ( i . e . antigen retrieval , antibody dilution optimizations and conditions etc . ) currently allow for more in-depth investigations in rhesus than cynomolgus laboratory NHP models . The available data on human scrub typhus was summarized for comparative purposes in this study ( Table 2 ) , and is a non-exhaustive collation from non-standardized investigations and serves for approximate guidance; these data were retrieved from old publications , where scrub typhus pre-exposed and naïve volunteers were ID inoculated using O . tsutsugamushi suspensions . Data on biochemistry , hematology and bacteremia included recent reports from clinical patient series from Laos and Thailand . Our previous study with cynomolgus macaques used the same inoculum preparation ( mouse liver/spleen homogenate , dosed at 106 muLD50 ) as this study , but the bacteremia period in rhesus macaques was shorter ranging from D6-D16 post-inoculation , than in the cynomolgus macaques ( ranged from D9-D21 ) . The shorter duration and earlier onset of bacteremia is much closer to human findings , where O . tsutsugamushi qPCR positivity is found as early as D2 up to D12 of fever manifestation ( not post-inoculation ) [33] . Early studies involving human volunteers have demonstrated that a latency of approximately 3–4 days following the mite inoculation before the onset of fever [23] . Hence , the human “rickettsemia phase” can be estimated at approximately D5-6 to D15 post-inoculation , which is similar to our findings in rhesus model . A delay between onset of symptoms after pathogen exposure could be associated with pre-existing partially protective immunity ( disease endemic regions ) , variation of inoculum dosage , strain virulence and the inoculum route applied [3 , 4 , 12 , 23] . Further characterization of the effects of these factors on disease onset and manifestation is crucial , as they relate to the major phenotypic correlates of immune protection in scrub typhus ( fever , bacteremia , inoculation lesion characteristics ) and should be an object of future investigations [4] . The rhesus macaques developed significantly raised core temperatures during the bacteremia phase–a clinically highly relevant feature used to estimate the bacteremia phase in humans . An animal model that does not develop fever will always be limited due to its dependence on bacterial dissemination dynamics–a feature not regularly assessed in humans . The transformation of fever time course data into area under the curve for comparisons between interventional/vaccine groups are important , as these data correlated previously with the density of bacteremia [4 , 33] . The sCAM time course profiles with significant rise in sE-selectin and sICAM plasma levels ( unfortunately no rhesus sL-selectin assays were available at this time ) provide additional support to corroborate the usefulness of this model for scrub typhus; a previous study in humans demonstrated that elevated sE-selectin levels correlated significantly with the duration of fever/illness before admission , the presence of eschar formation and lymphadenopathy , as well as elevated WBCs and neutrophils [25] . The sample size of this study did not allow for correlations to be made , but we anticipate these markers to be useful in future evaluations . Immunophenotyping of infected host leucocytes revealed intracellular O . tsutsugamushi infection only within host monocytes and dendritic cells in the skin ( inoculation site ) , spleen , draining and non-draining lymph node specimens , representing identical findings of the cellular tropism for O . tsutsugamushi in humans [19] . O . tsutsugamushi infected exclusively APCs—also in agreement with previous findings in human eschar biopsies—and no evidence of endothelial infection was seen , although the co-localization imaging was done on D28 post-mortem samples . The availability of validated antibodies for rhesus enabled characterization of infected leucocyte subsets , including "inflammatory" monocytes expressing CD14/CD68 , dendritic cell phenotypes with CD1a/DCSIGN positivity , but no intracellular infection of T-cells , or endothelial cells was found . The new finding of numerous intact O . tsutsugamushi within Langerhans cells , monocytes and dermal dendritic cells at the inoculation site following resolution of infection , is suggestive of ongoing replication in the skin throughout the disease course , even after healing of the eschar lesion ( in untreated cases ) . The absence of endothelial infection and scarring/sequelae dynamics again compare well with findings in human eschar biopsies [19] . At termination of the study ( D28 ) , the tissue specimens containing O . tsutsugamushi DNA , as determined by qPCR-assay , included skin ( inoculation site ) , spleen , draining and non-draining lymph node specimens , suggesting that either these tissues had particularly high bacterial loads , or that they might be associated with bacterial persistence and potential relapse in case of inadequate treatment [34] . All infected host cells in lymph nodes and spleen at D28 were APCs–these cellular subsets may represent a niche for this obligate intracellular bacterium , and pathogen-host immunomodulation is likely to occur within them . No viability testing was performed in this study , and no evidence for O . tsutsugamushi was found in lung and/or liver as recently described in persistent infections in a C57BL/6 mouse model [35 , 36] . Additional investigations into the phenotypes of infected cells in lymph node and other organs throughout the disease course need to precisely address where orientiae invade , survive and replicate , as this will contribute to our understanding of the immunopathophysiology and facilitate discovery of immune correlates of protection in scrub typhus . In humans , natural protective immunity against O . tsutsugamushi requires both humoral and cell-mediated responses [21 , 22 , 37] . The antibody response dynamics in rhesus macaques were identical to those observed previously in cynomolgus macaques , with increasing titers at D14 and all animals reaching maximum titers at D28 for both IgG and IgM . Cell-mediated immune responses ( CMI ) were seen in all infected macaques at D28 of the study , however only 2 macaques demonstrated strong responses ( >500SFC/mio PBMC ) . In subsequent studies we have further optimized antigen and ELISpot assay conditions and observed consistent CMI responses [18] . These results are comparable to responses seen in the control macaque group in the previous cynomolgus study , where unvaccinated controls did not exhibit an increase in the number of antigen-specific IFN-γ secreting cells until D21 after ID challenge with O . tsutsugamushi [4] . The 47kDa htrA antigen ELISpot assay used in this study ( based on peptide pools ) was chosen due to promising findings with a 47kDa htrA based vaccine candidate in a previous study [4] . The cell-mediated immune response induced by the 47kDa htrA gene co-presented with the pRhGM-CSF plasmid adjuvant was more rapid than the 47kDa antigen-specific cellular response of the natural immune response . This may also be associated with the inoculum route ( intradermal ) or inoculum dose , where a smaller dose would result in a delayed bacteremia and followed by a delayed cell-mediated response . The establishment of the strong cell-mediated immune response in rhesus macaques ( measured by a 47kDa htrA peptide-pool ) , is further evidence for the suitability in vaccine evaluations , as IFN-γ and type-1 immune responses have been associated with protection from O . tsutsugamushi infections in animal models , and strong IFN-γ responses to O . tsutsugamushi infection have been associated with acute scrub typhus in humans [3 , 4 , 12 , 13 , 21 , 22 , 38] . In summary , when comparing findings between both macaque models using the same inoculation preparation , strength and route , the rhesus macaques unequivocally produced more reliable classic eschar formation with central necrotic crusts at the inoculation site than the cynomolgus model . This study characterized scrub typhus disease features in rhesus macaques , and provided data on cell adhesion molecule dynamics and the cellular tropism of O . tsutsugamushi in rhesus macaques , which were similar to findings described in humans and of high relevance in evaluating new animal models for vaccine development . Importantly , the time course dynamics of eschar formation , temperature and bacteremia–which all represent phenotypic correlates of immune protection in scrub typhus—occurred earlier and more pronounced in the rhesus model . The aim was not to develop a lethal model , but compare previous findings in cynomolgus macaques to those in rhesus macaques . Taking into account all findings , the rhesus macaques disease characteristics following ID inoculation resembled that of human patients with scrub typhus more closely and importantly more consistently than cynomolgus macaques . In addition , the access to a broader panel of validated immunologic assays/reagents for the rhesus macaques compared to cynomolgus and other NHPs makes this laboratory animal a more useful model for scrub typhus to investigate immunopathology , correlates of immune protection and vaccine candidate evaluations . Further characterization and development of the rhesus macaque model for scrub typhus should include the effect of increasing inoculum dosages , the variation of immunopathophysiological responses and cross-protection to O . tsutsugamushi strains , treatment studies , and assessment of elicited immune response dynamics of immunogenic antigens . These data will enable more in-depth evaluation of correlates of protection for both natural and vaccine induced immunity , to subsequently support the evaluation of future vaccine candidates against scrub typhus . | Scrub typhus is a febrile illness caused by bacteria that invade and live within cells of the immune and blood vessel systems . Small earth-bound mites can bite humans and transmit these bacteria into the skin . Scrub typhus is treatable with antibiotics , but currently there is no scrub typhus vaccine available . Unfortunately if humans get scrub typhus , the immune response is usually weak and short-lived , especially against different strains , and affected individuals can get ill again within a year . This is a problem in areas where the infection is very common and a vaccine could be an effective approach to protect susceptible humans against scrub typhus . In this study , we characterized the immune response and disease features of scrub typhus in rhesus macaques by inoculating the bacteria directly into the skin–similar to the mite bite in nature–previously this had only been done in cynomolgus macaques ( Macaca fascicularis ) . We found that the scrub typhus symptoms and immune responses of rhesus macaques resemble more closely the human responses than those of cynomolgus macaques . Studying the immune response in rhesus macaques will help us to understand how humans react against different bacterial proteins , to identify new markers of protection and to find the strongest vaccine candidates . This will then help us develop new and better vaccines ( and also diagnostics ) against scrub typhus in the future . | [
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"ly... | 2018 | Characterization of the rhesus macaque (Macaca mulatta) scrub typhus model: Susceptibility to intradermal challenge with the human pathogen Orientia tsutsugamushi Karp |
The accumulation of the reactive oxygen species ( ROS ) in rice is important in its interaction with the rice blast fungus Magnaporthe oryzae during which the pathogen scavenges ROS through the production of extracellular enzymes that promote blast . We previously characterized the MoYvh1 protein phosphatase from M . oryzae that plays a role in scavenging of ROS . To understand the underlying mechanism , we found that MoYvh1 is translocated into the nucleus following oxidative stress and that this translocation is dependent on MoSsb1 and MoSsz1 that are homologous to heat-shock protein 70 ( Hsp70 ) proteins . In addition , we established a link between MoYvh1 and MoMrt4 , a ribosome maturation factor homolog whose function also involves shuttling between the cytoplasm and the nucleus . Moreover , we found that MoYvh1 regulates the production of extracellular proteins that modulate rice-immunity . Taking together , our evidence suggests that functions of MoYvh1 in regulating ROS scavenging require its nucleocytoplasmic shuttling and the partner proteins MoSsb1 and MoSsz1 , as well as MoMrt4 . Our findings provide novel insights into the mechanism by which M . oryzae responds to and subverts host immunity through the regulation of ribosome biogenesis and protein biosynthesis .
Magnaporthe oryzae is the causal agent of rice blast and also an established model organism to study plant-pathogen interactions [1 , 2] . In a previous study , we have characterized MoYvh1 as a homolog of the budding yeast Saccharomyces cerevisiae protein phosphatase Yvh1 that regulates growth , sporulation , and glycogen accumulation [3] . We found that MoYvh1 not only plays a similar important role in vegetative growth and conidia formation but also regulates virulence [4] . In addition , we found that deletion of MoYVH1 results in an increased accumulation of the host-derived reactive oxygen species ( ROS ) [4] . ROS levels are known to govern the pathogen and host interaction , how MoYvh1 regulated growth and virulence is linked to its role in affecting ROS levels remains an interesting but unresolved research subject . S . cerevisiae Yvh1 is known to also have a role in ribosome maturation and function [5] . In eukaryotic cells , mature ribosomes are composed of five different proteins that include Rpp0 and two copies of each of proteins P1 and P2 [6–8] . Rpp0 interacts directly with the 60S ribosome subunit to form the base of the stalk for binding to P1 and P2 proteins [9 , 10] . Also in S . cerevisiae , the ribosome assembly factor and the nucleolar protein Mrt4 are closely related to Rpp0 , based on the conserved N-terminal ribosome binding domain they shared with [11 , 12] . Eukaryotic cells respond to environmental stresses , including elevated temperatures , via a family of well-characterized heat-shock proteins ( Hsp ) [13] . As ubiquitous molecular chaperones that function in a wide variety of cellular processes , Hsp70s act by reversibly binding and releasing the short hydrophobic stretches of amino acids in a nucleotide-dependent fashion [14 , 15] . Hsp70 heat shock proteins are known to affect ribosomal function and protein biosynthesis [16] . For example , the ribosomal L31 protein binds to chaperone Zuo1 that in turn anchors Hsp70 Ssz1 and Hsc70 proteins to regulate polypeptide translocation [17–21] . Given the multifaceted role of MoYvh1 previously established [4] , further addressing of MoYvh1 functional mechanisms would promote our understanding of the rice blast mechanisms . We here showed that MoYvh1 is translocated to the nucleus under the oxidative stress condition and that MoYvh1 functions through interactions with Hsp70 protein homologs MoSsb1 and MoSsz1 . In addition , we showed that MoYvh1 is required for proper translocation of the ribosomal maturation factor homolog MoMrt4 , since the loss of MoYvh1 caused MoMrt4 mislocalization to the cytoplasm resulting in virulence defects .
We have identified MoYvh1 as a homolog sharing amino acid sequence conservation with S . cerevisiae Yvh1 that in turn shares homology with the dual-specificity phosphatase from vaccinia virus [22] . We found that MoYvh1 has a multiple role in the growth and virulence of M . oryzae and that deletion of MoYVH1 results in an accumulation of ROS surrounding the infection sites [4] . To address whether MoYvh1 exhibits a cytoplasmic-nuclear shuttling ability , similar to S . cerevisiae Yvh1 , we constructed the strains expressing MoYvh1-GFP , in which the expression of the C-terminal GFP fusion protein is under the control of the native MoYVH1 promoter . Notably , MoYvh1 was present in both the cytoplasm and the nucleus in conidia , which is the expected default steady-state distribution pattern . Treated with 5 mM H2O2 for 2 hours ( h ) , an enhanced nuclear localization was observed in conidia ( 68 . 42 ± 7 . 31% ) ( Fig 1A ) . In the aerial hyphae , however , no changes were seen under the same stress condition ( Fig 1B ) . Plants generate a vast array of oxidative agent in response to pathogen invasion including superoxide radical and hydroxyl radical . To further understand the changes observed in the localization pattern of MoYvh1 was specific to H2O2 or general to other oxidative stress , KO2 and hydroxyl radical were used to treat the ΔMoyvh1/MoYVH1-GFP strain . The results showed that both KO2 and hydroxyl radical induced an accumulation of MoYvh1 in the nucleus in conidia but not the aerial hyphae ( S1 Fig ) . These data suggested that oxidative stress could promote cytoplasmic MoYvh1 nuclear localization in conidia . To understand MoYvh1 functions associated with its nuclear translocation , we identified MoSsb1 and MoSsz1 that are heat-shock 70 ( Hsp70 ) protein homologs following screening a yeast two-hybrid cDNA library constructed with RNA pooled from various stages including conidia and infections ( 0 , 2 , 4 , 8 , 12 and 24 h ) ( Fig 2A ) . We then validated these interactions by co-introducing the MoYVH1-FLAG and MoHSP70s-GFP fusion constructs into the protoplasts of the wild type strain Guy11 . Total proteins were extracted from conidia of the putative transformants , and MoYvh1 , MoSsa1 , MoSsb1 , and MoSsz1 were detected using the anti-FLAG and anti-GFP antibodies . In proteins eluted from MoSsb1 and MoSsz1 anti-GFP beads , MoYvh1 was detected ( Fig 2B ) . The interactions were further confirmed by the bimolecular fluorescence complementation ( BiFC ) assay . The MoYVH1-CYFP and MoSSB1-NYFP , MoSSZ1-NYFP fusion constructs were introduced into the protoplasts of Guy11 , with the empty vectors used as negative controls . The recombined YFP fluorescence signal was detected in the cytoplasm containing corresponding protein pairs ( Fig 2C and S2 Fig ) . Interestingly , the interactions were also observed under the oxidative stress , with YFP fluorescence being transferred to the nucleus following treatment with 5 mM H2O2 ( Fig 2C ) . Previously , we demonstrated that the MoYvh1 C-terminal zinc-binding domain is required for growth and virulence of the fungus . Our evidence here showed that the same C-terminal is also responsible for binding with MoSsb1 and MoSsz1 ( S3 Fig ) . An interaction between MoYvh1 and MoSsa1 could not be established , suggesting that MoYvh1 interactions with MoSsb1 and MoSsz1 are specific ( Fig 2A , 2B and 2C ) . We also generated MoSSB1 and MoSSZ1 deletion mutants and assessed their effects on MoYvh1 distribution . The MoYVH1-GFP fusion construct was introduced into ΔMossb1 , ΔMossz1 , and ΔMoyvh1 mutants . In the resulting transformants , GFP signal was observed in both the cytosol and the nucleus . However , the GFP signal was predominantly observed in the cytoplasm of ΔMossb1 and ΔMossz1 upon oxidative stress , in contrast to complemented strains ( 72 . 16 ± 5 . 77% ) where GFP was predominantly seen in the nuclei ( Fig 2D ) . To further evaluate the nuclear translocation of MoYvh1 in these strains , we separated nuclear proteins from cytoplasmic ones and performed Western blotting analysis . MoYvh1-GFP was significantly enriched in the nucleus in the complement strain when treated with 5 mM H2O2 . However , MoYvh1-GFP was uniformly distributed in the conidia of the ΔMossb1 and ΔMossz1 mutants ( S4 Fig ) . These results suggested that MoSsb1 and MoSsz1 could facilitate nuclear translocation of MoYvh1 under oxidative stress through direct interactions . To further understand MoYvh1 nuclear translocation upon stress and associated functions , we searched for additional proteins that interact with MoYvh1 and identified MoMrt4 ( MGG_08908 ) that shares sequence homolog with S . cerevisiae nucleolar protein Mrt4 . The yeast Mrt4 contains a Gly residue at position 68 whose substitution with Asp or Glu could suppress the growth defect of the Δyvh1 strain [5 , 23 , 24] . To investigate whether MoYvh1 shares functional conservation with S . cerevisiae Mrt4 , we constructed strains expressing MoMRT4G69D-GFP and MoMRT4G69E-GFP , respectively . We found that MoMrt4G69D and MoMrt4G69E , but not MoMrt4 , were able to rescue the defect on growth and virulence of the ΔMoyvh1 strain ( Fig 3A , 3B and 3C and S5A Fig ) . Because MoYvh1 functions upstream of MoPdeH to regulate the cAMP levels and pathogenicity [4] , we also found that MoMrt4G69D and MoMrt4G69E suppress the defects in cAMP levels of the ΔMoyvh1 mutant ( S5B Fig ) . As MoYvh1 plays a role in scavenging host-derived ROS , we examined ROS levels by staining host cells with 3 , 3’-diaminobenzidine ( DAB ) at 36 h after inoculation . The primary infected rice cells with infectious hyphae of the ΔMoyvh1 and ΔMoyvh1/MoMRT4 strains were stained intensely by DAB , with reddish-brown precipitate around the infected cells , while the ΔMoyvh1/MoMRT4G69D and ΔMoyvh1/MoMRT4G69E strains exhibited weak staining , a phenotype similar to Guy11 ( Fig 3D ) . MoMrt4 is normally accumulated in the nucleus of the wild-type strain ( Fig 4A ) . To study how MoMrt4G69D and MoMrt4G69E suppress the defects of the ΔMoyvh1 mutant , we assessed the effect of MoYvh1 on the subcellular localization of MoMrt4 . As expected , MoMrt4G69D and MoMrt4G69E were predominantly nuclear localized , while MoMrt4 was mostly cytoplasmic , in the ΔMoyvh1 mutant ( Fig 4A ) . As MoMrt4G69D and MoMrt4G69E mutation showed similar roles in the ΔMoyvh1 mutant , we used the ΔMoyvh1/MoMrt4G69E strain to determine whether its affinity for the ribosome was compromised . We found that binding of MoMrt4G69E to the ribosome was more sensitive to 100 and 500 mM NaCl than MoMrt4 that was largely unaffected . 500 mM NaCl caused the majority of MoMrt4G69E to be dissociated from the ribosome ( Fig 4B ) . Therefore , MoMrt4G69E showed weaker affinity for ribosomes than MoMrt4 , implying easier separation from the ribosome . We further speculated that the affinity for ribosomes between MoYvh1 and MoMrt4 is important for the normal function of M . oryzae . To test this hypothesis , we assessed whether MoMrt4 competes with MoYvh1 in ribosome binding . Western blotting analysis showed that MoYvh1 bound to the ribosome in both the wild-type and the ΔMomrt4 mutant . However , the MoMrt4 recruitment to ribosomes in the presence of MoYvh1 was significantly reduced in the wild-type strain ( Fig 4C ) , suggesting that MoYvh1 and MoMrt4 indeed compete for binding to the ribosome . The Rpp0 protein is one of the five conserved components of mature ribosomes [7 , 10] . We have cloned the MoRpp0 homolog and generated the ΔMoyvh1/MoRpp0-FLAG-MoYvh1-GFP , ΔMomrt4/MoRpp0-FLAG-MoYvh1-GFP , and Guy11/MoRpp0-FLAG-MoYvh1-GFP strains to investigate whether deletion of MoYvh1 or MoMrt4 causes any defects in ribosome maturity . Ribosome proteins were extracted . In the ΔMomrt4 mutant , MoRpp0 was bound to the ribosome similar to that in the wild-type strain . However , MoRpp0 remained in the suspension in the ΔMoyvh1 mutant ( Fig 4D ) , suggesting that MoYvh1 has a role in ribosome maturity . Since MoMrt4 is important for MoYvh1 function , we characterized its function in growth and pathogenesis . The ΔMomrt4 mutant displayed significantly attenuated growth on CM , minimal medium ( MM ) , straw decoction and corn agar ( SDC ) , and oatmeal medium ( OM ) plates ( Fig 5A and S5C Fig ) . Conidia formation was drastically reduced in the ΔMomrt4 mutants by ~70% when compared with the wild-type strain ( Fig 5D and 5E ) . To determine whether MoMrt4 plays a role in pathogenicity , susceptible CO-39 rice seedlings were respectively sprayed with the conidia of the wild-type , ΔMomrt4 mutant , and complemented strains . The production of fewer , small lesions by the ΔMomrt4 mutant at 7-day post-inoculation ( dpi ) ( Fig 5B and 5C ) indicated that MoMrt4 is required for full virulence . Our previous study showed that deletion of MoYVH1 results in an increase in the accumulation of ROS but reduced virulence [4] . To test that the reduced virulence was due to a lack of ROS scavenging , we examined host-derived ROS levels by DAB staining . At 30 h after inoculation , no staining was observed in the primary rice cells infected by the ΔMomrt4 mutant ( S6 Fig ) . We also evaluated binding of MoMrt4 to ribosomes in these strains and found that MoRpp0 remained in the suspension of the ΔMoyvh1 mutant . However , MoRpp0 bound to the ribosome in the ΔMomrt4 mutant which was similar to that in Guy11 , indicating that deletion of MoMRT4 was not involved in the ribosome maturity , in contrast to MoYvh1 ( Fig 5F ) . These results revealed that MoMrt4 is required for vegetative growth , conidiation , and full virulence , but these functions are independent of ribosome maturity . As the nuclear localization of MoYvh1 is enhanced in conidia upon oxidative stress , we hypothesized that MoYvh1 is also translocated to the nucleus during host-imposed stress during infection . To test this , we screened rice cultivars resistant to Guy11 and the ΔMoyvh1/MoYVH1 strains . We found that the wild type strains caused only the restricted lesions on the rice cultivar K23 that contains the resistant gene Pi12 [25] ( Fig 6A ) . As the ΔMoyvh1/MoYVH1 strains showed restricted lesions on the K23 , DAB was further used to evaluated the host-derived ROS accumulated around the infection sites in K23 . Cells with ΔMoyvh1/MoYVH1-GFP infectious hyphae on rice cultivar K23 were stained by DAB , with the reddish-brown precipitate around the infected cells , indicating that the ΔMoyvh1/MoYVH1-GFP strain fails to scavenge H2O2 on K23 ( Fig 6B ) . To assess nuclear translocations of MoYvh1 , we extracted nuclear proteins and performed Western blotting analysis . In K23 , MoYvh1-GFP was significantly enriched in the nucleus in comparison with LTH ( Fig 6C ) . As it is difficult to stain the nucleus by DAPI during infection , we used the histone H1 fused to red fluorescent protein ( RFP ) to mark the nucleus of infectious hyphae . We found an enrichment of MoYvh1 in the nucleus when co-localization with H1-RFP in the infection hyphae of K23 , in comparison with LTH cultivar ( Fig 6D ) . However , MoYvh1 was not translocated into the nucleus in the ΔMossb1 and ΔMossz1 mutants ( S7 Fig ) . These results indicated that MoYvh1 is indeed nuclear enhanced during infection . At the early stages of infection , M . oryzae secretes numerous effector proteins to suppress plant defense responses and modulate host cellular processes that promote infections [26] . Since MoYvh1 has a role in ribosome maturity ( Fig 5D ) and the ribosome is important for the synthesis of proteins , we tested whether the production of extracellular proteins was compromised in the ΔMoyvh1 mutant . The extracellular fluid ( EF ) was prepared as described by Patkar and colleagues [27] . Conidia from Guy11 and the ΔMoyvh1 strains were inoculated on a hydrophobic glass sheet and EF was harvested following 24 h incubation . We first detected the localization of MoYvh1 under this condition and the results showed that MoYvh1 was present in both nucleus and cytoplasm , indicating MoYvh1 functions in the nucleus during the appressorium formation ( S8 Fig ) . EF extracts from wild type were subsequently added to the rice leaf sheaths following infection by the ΔMoyvh1 mutant . We found that native EF , but not that denatured by boiling , rescued the defects in host cell invasion and ROS scavenging at the infected sites ( Fig 7A and 7B ) . Our previous study showed that deletion of MoYVH1 resulted in reduced peroxidase and laccase activities [4] , so we further assayed the peroxidase and laccase activities in both EF harvested from the wild type and ΔMoyvh1 mutant strains . The enzyme activity assay was performed as described by Chi and associates [28] by using the EF from both Guy11 and ΔMoyvh1 mutant . We observed very low levels of laccase and peroxidase activities in the ΔMoyvh1 mutant when compared with Guy11 ( Fig 7C ) . We further performed the spray and drop assays on rice leaves . Conidia of the ΔMoyvh1 mutant were collected with 5 ml of the EF or boiled EF of Guy11 . The conidial suspensions of each treatment were sprayed onto rice leaves . After inoculation for 7 days , the results showed that the EF of Guy11 could suppress the defects of the ΔMoyvh1 mutant in pathogenicity ( Fig 7D and 7E ) . The conidial suspensions of each treatment were also drop inoculated onto detached rice leaves and the results revealed that the EF of the wild type strain partially rescues the defect in pathogenicity on the detached rice leaves ( S9 Fig ) . These results indicated that the EF of Guy11 contains candidate proteins that are important for infection . To identify candidate proteins in EF regulated by MoYvh1 , we compared the EF production through SDS-PAGE analysis and found that the amount of EF proteins in ΔMoyvh1 EF was significantly less than that of wild type Guy11 ( Fig 7F ) . In addition , mass spectrometry ( MS ) analysis revealed the presence of over 70 proteins with signal peptides in EF of the wild type strain but not of the ΔMoyvh1 mutant . To address whether the absence of these proteins is caused by the defect in ribosomal biogenesis , we randomly chosen 30 of them to evaluate the transcriptional difference between Guy11 and the ΔMoyvh1 mutant in the conidia after 24 h incubation on a hydrophobic glass sheet . Among these genes , only three were significantly reduced in transcription ( p < 0 . 01 ) ( S10 Fig ) . In 70 identified proteins , 13 were associated with oxidoreducation ( Fig 7G and S2 Table ) . Thus , the defect in scavenging host-derived ROS of the ΔMoyvh1 mutant was associated with the defect in the production of extracellular proteins .
Virulence in the rice blast fungus M . oryzae is a multifaceted trait contributed by not only the complex circuitry in the pathogen side but also that of the host . In dissecting molecular events leading to virulence , we have previously characterized the dual specificity phosphatase MoYvh1 that shares sequence conservation and functional mechanisms to certain degree with S . cerevisiae Yvh1 . Importantly , we found that MoYvh1 plays a role in not only growth , conidia formation , but also virulence in M . oryzae [4] . Here , we provided mechanistic evidence to show that MoYvh1 undergoes cytoplasmic to nuclear translocation in response to oxidative stress and that MoYvh1 affects ribosome maturation . Our findings reveal a novel link between ribosome biogenesis and fungal virulence that is mediated by MoYvh1 . In S . cerevisiae , Yvh1 is a shuttling protein that could remain in the nucleus if fused with a nuclear localization sequence [23 , 29] . Previous studies also found that Yvh1 binds with the pre-60S ribosome subunit to export it to the cytoplasm . Once arrives there , Yvh1 is released from the pre-ribosome following mature ribosomal protein P0 binding to the ribosomal stalk [23 , 24 , 30 , 31] . How Yvh1 is translocated into the nucleus remains unclear . Through studies of MoYvh1 here , we provided evidence that MoYvh1 exhibits similar nucleo-cytoplasmic shuttling ability and that it functions through interactions with MoSsb1 and MoSsz1 . An unexpected finding is that the interaction between MoYvh1 and MoSsb1 and MoSsz1 differs from aerial hyphae to conidia and the infection stage ( Fig 2 , S2 and S11 Figs ) . Similar differentiated interactions were seen before . A BiFC assay showed that Pth11 and Rgs1 interacted in vivo during early pathogenesis but not during vegetative growth [32] . The interaction between MoCap1 and MoMac1 was weak during vegetative growth but was enhanced during appressorium formation [33] . In addition , Liu and colleagues showed that MoAtg4 interacts with MoAtg8 only under the nitrogen starvation condition [34] . In view of these findings , we hypothesized that 1 ) the interaction occurs only under oxidative stress , and 2 ) MoYvh1 and Hsp70s interactions are developmental stage specific . In agreement with these hypotheses , the YFP fluorescence signal was transferred to the nucleus only following treatment with 5 mM H2O2 ( Fig 2C ) . Therefore , we concluded that MoSsb1 and MoSsz1 recruitments to MoYvh1 to facilitate its nuclear translocation upon oxidative stress during specific growth stages in M . oryzae . Further evidence showed that MoYvh1 is not accumulated in the nucleus when MoSsb1 and MoSsz1 are not interacted with MoYvh1 during the aerial hyphae ( Fig 1B and S11 Fig ) . And also , deletion of MoSSB1 or MoSSZ1 which interdicted the interaction caused cytoplasmic-MoYvh1 not translocated into the nucleus even in the conidia and infection stages ( Fig 2D , S4 and S7 Figs ) . These results further confirmed that the accumulation of MoYvh1 in the nucleus under oxidative stress is dependent on the interaction between MoSsb1 and MoSsz1 . Upon the exposure to oxidative stress , MoYvh1 nuclear translocation is accelerated by its interaction with MoSsb1 or MoSsz1 during the conidial and infection stages . Since MoYvh1 still could be detected in the nucleus in the ΔMossb1 and ΔMossz1 mutants ( S4 Fig ) , we postulated that additional translocation facilitators of MoYvh1 that are independent of oxidation stress may also exist . We found that MoYvh1 and MoMrt4 bind with ribosomes in a competitive manner . To further examine the relationship between MoYvh1 and MoMrt4 , we characterized the function of MoMrt4 by generating a ΔMomrt4 mutant , which is significantly attenuated in growth , conidia production , and pathogenicity . However , the lesions produced by the ΔMomrt4 mutant on rice leaves were fewer and smaller than those of the ΔMoyvh1 mutant . A DAB assay suggested that deletion of MoMRT4 did not affect the scavenging of ROS accumulated around the infection sites . Our analysis further suggested that MoYvh1 binds to pre-ribosomes and thereby helps to release MoMrt4 . Thus , ribosome immaturity resulted in pathogenicity defects in the ΔMoyvh1 mutant but not the ΔMomrt4 mutant . The ribosome extract assay confirmed that cells continue to synthesize ribosomes in the absence of MoMrt4 . This finding is consistent with studies in S . cerevisiae in which the deletion of MRT4 causes defects in growth but no blocking in ribosome synthesis [5 , 11 , 23 , 35] . M . oryzae secretes a wide array of factors into the host to facilitate invasion [26 , 36 , 37] . However , host plants have evolved to recognize these effectors and counteract by activating defense responses to limit pathogen spreading [38–41] . Small-molecule phytohormones , such as jasmonates , salicylic acid and brassinosteroids , play key roles in regulating this defense response [42–44] . Our recent findings showed that the scavenging of host-derived ROS at the infection site is important for virulence of the ΔMoyvh1 mutant , as deletion of MoYVH1 causes virulence defect [4] . Consistent with the findings , the EF of the wild-type scavenges ROS accumulated around the sites of infection , in contrast to the ΔMoyvh1 mutant , where the restricted invasion is the result of ROS accumulation due to lack of extracellular proteins in EF . When treated with ROS , MoYvh1 in the cytoplasm is translocated into the nucleus causing an enhanced nuclear localization in both the conidia and invasion hyphae ( Figs 2 , 7C and 7D ) . In the mycelium , however , the cytoplasmic location pattern of MoYvh1 remained unchanged . These results suggested that the differential localization patterns of MoYvh1 might be developmentally regulated and it may be relevant to virulence . Since H2O2 stress blocks the formation of appressorium , the glass surface was not subjected to H2O2 stress allowing conidia to germinate , and under this condition MoYvh1 was present in both nucleus and cytoplasm ( S8 Fig ) . Here , we found that the EF of non-induced Guy11 rescued the defects in invasion and ROS scavenging around the infected sites ( Fig 7A and 7B ) , suggesting that original MoYvh1 in the nucleus ( S8 Fig ) without treatment regulated the ribosome maturation that provides abundant extracellular proteins to inhibit host-derived ROS . Under ROS stress , MoYvh1 in the cytoplasm translocates into the nucleus and accelerates ribosome synthesis to produce more extracellular proteins , which inhibits host-derived defense and promote infection . Why does the wild-type EF suppress the defects of the ΔMoyvh1 mutant and does the EF contain necessary ribosome or other proteins ? In S . cerevisiae , Rpp0 is loaded onto the 60S ribosome subunit to assemble the mature stalk [23 , 24] . In this study , deletion of MoYVH1 led to the separation of MoRpp0 from the ribosome , suggesting a ribosomal maturation defect in the ΔMoyvh1 mutant which would impair the production of proteins ( Fig 5D ) . During the early stages of infection , M . oryzae secretes various extracellular proteins to suppress plant immunity for promoting colonization . Blockage of secreted protein synthesis due to immature ribosome in the ΔMoyvh1 mutant likely results in the defect in virulence . Indeed , we showed that EF from the wild type strain restored pathogenicity of the ΔMoyvh1 mutant when added to the conidia suspension ( Fig 7A and 7C and S9 Fig ) . These findings indicated that MoYvh1 has a role in the production of EFs that inhibit rice immunity . We therefore present a model for how MoYvh1 functions in growth , virulence , and host immune avoidance in M . oryzae ( Fig 8 ) . Our findings demonstrate that during M . oryzae infection , rice produces an ROS burst to suppress pathogen invasion . Under this stress , MoSsb1 and MoSsz1 , together with MoYvh1 , are translocated to the nucleus , where MoYvh1 has a role in ribosome maturation through the release of MoMrt4 from the pre-ribosome . Mature ribosomes promote EF synthesis and secretion to scavenge ROS and modulate the rice defense response . Our model reveals an important pathway by which M . oryzae recruits a nucleocytoplasmic shuttling phosphatase , MoYvh1 , in response to host immune response . Further studies of MoYvh1-mediated response and the identification of EFs regulated by MoYvh1 would promote the understanding of M . oryzae pathogenesis mechanisms .
M . oryzae Guy11 strain was used as the wild type in this study . All strains were cultured on complete medium ( CM ) agar plates for 3–15 days at 28°C [45] . Mycelia were harvested from liquid CM and used for DNA and RNA extractions . Protoplasts were prepared and transformed as described previously [46] . Transformants were selected on TB3 medium ( 3 g of yeast extract , 3 g of casamino acids , 200 g of sucrose , and 7 . 5 g of agar in 1 l of distilled water ) with 300 μg/ml hygromycin B ( Roche ) or 200 μg/ml zeocin ( Invitrogen ) . Ribosomal proteins were extracted from mycelia as previously described [23] . Briefly , fungal strains were cultured on solid CM medium for 7 days at 28°C , and approximately 1 x 1 mm square of agar containing the culture was inoculated in liquid CM and grown for another 2 days . Mycelia were filtered through Miracloth , blotted dry , and ground into powder in liquid nitrogen with a mortar and a pestle . 5 g mycelium was mixed with 15 ml 1st extraction buffer I ( 0 . 1 M natrium aceticum , 10 mM Tris-HCl , 10 mM MgCl2 with 0 . 07% β-mercaptoethanol ) and incubated at 4°C for 2 h . Samples were centrifuged at 5000 g for 30 min at 4°C and repeated once before discarding the pellets . The upper phase was centrifuged at 96000 g at 4°C for 2 h and the pellet were dissolved in 2nd extraction buffer ( 20 mM Tris , pH 7 . 5 , 6 mM MgCl2 , 10% glycerol , 0 . 1% NP-40 , 1 mM PMSF , 1 μM leupeptin , and 1 μM pepstatin A ) . 2 . 5 ml of protein extracts were overlaid on 7 . 5 ml 1 M sucrose in 20 mM Tris , 8 mM MgCl2 , and 100 mM KCl in 10 ml ultracentrifuge tubes ( Beckman Coulter ) . Samples were centrifuged again at 96000 g at 4°C for 2 h . Finally , the pellets were dissolved in dissolution buffer ( 5 M Urea , 2 M Thiourea , 2% CHAPS , 2% SB3-10 , 40 mM Tris , 5mM Mercaptoethanol ) . To generate the MoMRT4 gene replacement vector pCX62 , approximately 1 kb upstream and downstream fragments were amplified with primer pairs ( S1 Table ) . The resulting PCR products were ligated to the hygromycin resistance cassette released from pCX62 , as previously described [25] . Putative mutants were screened by PCR and confirmed by Southern blotting analysis . To complement the ΔMomrt4 mutant , the DNA fragment containing the putative promoter and the coding sequence was amplified and inserted into pYF11 ( bleomycin resistance ) by homologous recombination in S . cerevisiae . Plasmids were extracted and introduced into Escherichia coli competent cells , and then the plasmids with correct inserts were introduced into protoplasts , as previously described [25] . cDNA of MoYVH1 , MoYVH1ΔC ( the N-terminus ) , MoYVH1ΔN ( the C-terminus ) , MoSSB1 , MoSSZ1 and MoSSA1 was respectively amplified with Super Fidelity DNA Polymerase ( Vazyme , Nanjing ) . Amplified products were cloned into pGBKT7 and pGADT7 vectors ( BD Biosciences , Oxford , UK ) , respectively . After sequence verification , they were introduced into yeast AH109 strain . Transformants grown on synthetic medium lacking leucine and tryptophan ( SD–Leu–Trp ) were transferred to synthetic medium lacking leucine , tryptophan and histidine ( SD–Leu–Trp–His ) . For BiFC assay , the MoYVH1-CYFP fusion construct was generated by cloning MoYVH1 into pHZ68 [47] . Similarly , MoSSB1-NYFP and MoSSZ1-NYFP fusion constructs were generated by cloning MoSSB1 and MoSSZ1 into pHZ65 , respectively . Construct pairs of MoYVH1-CYFP , MoSSB1-NYFP and MoSSZ1-NYFP were introduced into the protoplasts of Guy11 , respectively . Transformants resistant to both hygromycin and zeocin were isolated and confirmed by PCR . To generate MoYVH1G69D and MoYVH1G69E constructs , the 2 . 7 kb upstream fragment including the MoYVH1 native promoter , the 1 . 1 kb fragment from the start codon of the coding sequence ( containing the Gly 69 ) , and the 0 . 5 kb downstream fragment including the rest of the gene coding sequence ( containing both of the Gly 69 ) were co-introduced with XhoI digested pYF11 into yeast strain XK1-25 [47 , 48] . Plasmid pYF11::MoYVH1G69D and pYF11::MoYVH1G69E were rescued from the resulting Trp+ yeast transformants . Conidial germination and appressorium formation were measured on a hydrophobic surface as previously described [49] . Appressorium induction and formation rates were obtained also as described previously [50 , 51] . For infection , conidia were harvested from 10-day-old SDC agar cultures , filtered , and resuspended to a concentration of 5 × 104 spores /ml in a 0 . 2% ( w/v ) gelatin solution . For the leaf assay , leaves from two-week-old seedlings of rice ( Oryza sativa cv . CO39 ) and 7-day-old seedlings of barley were used for spray inoculation . For rice leaves , 5 ml of a conidial suspension of each treatment was sprayed . Inoculated plants were kept in a growth chamber at 25°C with 90% humidity and in the dark for the first 24 h , followed by a 12 h /12 h light /dark cycle . Lesion formation was observed daily and recorded by photography 7 days after inoculation [52 , 53] . Mycelia were harvested and ground into powder in liquid nitrogen . 1 mg mycelium was mixed with 20 μl 6% TCA solution , centrifuged ( 1700 g , 15 min ) , and top layers were collected . After washing twice with five volumes of anhydrous ether , pellets were collected and subjected to HPLC analysis using a programmable Agilent Technology zorbax 1200 series liquid chromatography . The solvent system consisted of methanol ( 90% ) : water ( 10% ) , at a flow rate of 1 ml /min . 0 . 1 mg/ml cAMP solution was eluted through the column ( SB-C18 , 5 μl , 4 . 6 × 250 mm ) and detected at 259 nm UV . Samples were loaded through the column in turns . Conidia of indicated strains were harvested from 10-day-old SDC agar cultures , filtered , and resuspended to a concentration of 1 × 105 spores /ml in a 0 . 2% ( w/v ) gelatin solution . 4 ml of the suspension was sprayed onto rice leaves and harvested 24 hpi . 5 g of Leaves were ground into powder in liquid nitrogen . The powder was transferred to a 50 ml tube and mixed with 20 ml M1 buffer ( 10 mM Tris-HCl ( pH = 8 . 0 ) , 10 mM MgCl2 , 0 . 1 mM PMSF , 1 M NaCl , 0 . 07% β-mercaptoethanol and 0 . 4 M Sucrose ) using a chilled spoon . After agitated the tube in ice box for 10 min . The suspensions were filtered through Miracloth ( Calbiochem ) into a 50 ml tube and the supernatants containing cytoplasmic proteins were collected following centrifugation at 1000 x g for 20 min at 4°C . Remove the supernatant for the cytoplasm protein . Five ml of M2 buffer ( 10 mM Tris-HCl ( pH = 8 . 0 ) , 10 mM MgCl2 , 0 . 1 mM PMSF , 1 M NaCl , 0 . 07% β-mercaptoethanol , 0 . 25 M Sucrose and 1% TritonX-100 ) was added to the pellet portion , re-suspended , and tubes re-centrifuged at 12000 x g for 10 min at 4°C . The supernatant was removed and the step was repeated 3 times . Finally , 300 μl Nuclei Lysis Buffer ( P0013B , Beyotime Biotech ) was added to the pellet and the suspension ( nuclear proteins ) was recovered . After 7 days cultivation , conidia were collected and suspended in 100 ml of distilled water in a concentration of 1 × 105 spores /ml . 50 ml of the conidia were centrifuged at 3600 g for 10 min to extract the protein for equalization of protein amounts . The rest of 50 ml of conidia were divided into 200 μl ( 1 x 105 spores/ml ) and placed onto the hydrophobic glass sheet at 28°C for 24 h . Suspensions harvested from the hydrophobic glass sheet were centrifuged at 3600 g for 10 min and the supernatants were recovered . For HLPC-MS/MS analysis , a 100 μg protein suspension was harvested . The suspension was mixed with 2 . 5 μg trypsin for digestion at 37°C for 4 h . 2 . 5 μg trypsin was added again and incubated for another 8 h . The peptides were then dechlorinated by Strata X and separated by a 65 min gradient elution at a flow rate 300 nl/min with the LC-20AD nano-HPLC system ( Shimadzu , Japan ) , which was directly interfaced with Q-Exactive mass spectrometer ( Thermo Fisher Scientific , USA ) . Mobile phase A consists of 0 . 1% formic acid and 2% acetonitrile , and mobile phase B consists of 0 . 1% formic acid and 98% acetonitrile . The mass spectrometer was operated in the DDA ( data-dependent acquisition ) mode and there was a single full-scan mass spectrum in the Orbitrap ( 350–1600 m/z , 70 , 000 resolution ) . Results were presented as the mean ± standard deviation ( SD ) of at least three repeats . The significant differences between samples were statistically evaluated by using SDs and one-way analysis of variance ( ANOVA ) in SPSS 2 . 0 . The data between two different treatments were then compared statistically by ANOVA , followed by the F-test , if the ANOVA result is significant at P< 0 . 01 . | ROS accumulation is important for the interaction between the blast fungus M . oryzae and its rice host . The protein phosphatase MoYvh1 affects the scavenging of host-derived ROS that promotes M . oryzae infection . We found that MoYvh1 is translocated to the nucleus under oxidative stress by a mechanism that is dependent on its interactions with MoSsb1 and MoSsz1 . MoYvh1 triggers the release of MoMrt4 from the ribosome in the nucleus that contributes to ribosome maturation . Importantly , we have provided evidence to demonstrate that MoYvh1 is important for the synthesis of extracellular proteins that are involved in ROS scavenging . Our findings provide insight into the mechanism by which M . oryzae responds to host immunity through MoYvh1 that regulates ribosome function to evade the host defense response . | [
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"a... | 2018 | MoYvh1 subverts rice defense through functions of ribosomal protein MoMrt4 in Magnaporthe oryzae |
In order to design strategies for eradication of HIV-1 from infected individuals , detailed insight into the HIV-1 reservoirs that persist in patients on suppressive antiretroviral therapy ( ART ) is required . In this regard , most studies have focused on integrated ( proviral ) HIV-1 DNA forms in cells circulating in blood . However , the majority of proviral DNA is replication-defective and archival , and as such , has limited ability to reveal the dynamics of the viral population that persists in patients on suppressive ART . In contrast , extrachromosomal ( episomal ) viral DNA is labile and as a consequence is a better surrogate for recent infection events and is able to inform on the extent to which residual replication contributes to viral reservoir maintenance . To gain insight into the diversity and compartmentalization of HIV-1 under suppressive ART , we extensively analyzed longitudinal peripheral blood mononuclear cells ( PBMC ) samples by deep sequencing of episomal and integrated HIV-1 DNA from patients undergoing raltegravir intensification . Reverse-transcriptase genes selectively amplified from episomal and proviral HIV-1 DNA were analyzed by deep sequencing 0 , 2 , 4 , 12 , 24 and 48 weeks after raltegravir intensification . We used maximum likelihood phylogenies and statistical tests ( AMOVA and Slatkin-Maddison ( SM ) ) in order to determine molecular compartmentalization . We observed low molecular variance ( mean variability ≤0 . 042 ) . Although phylogenies showed that both DNA forms were intermingled within the phylogenetic tree , we found a statistically significant compartmentalization between episomal and proviral DNA samples ( P<10−6 AMOVA test; P = 0 . 001 SM test ) , suggesting that they belong to different viral populations . In addition , longitudinal analysis of episomal and proviral DNA by phylogeny and AMOVA showed signs of non-chronological temporal compartmentalization ( all comparisons P<10−6 ) suggesting that episomal and proviral DNA forms originated from different anatomical compartments . Collectively , this suggests the presence of a chronic viral reservoir in which there is stochastic release of infectious virus and in which there are limited rounds of de novo infection . This could be explained by the existence of different reservoirs with unique pharmacological accessibility properties , which will require strategies that improve drug penetration/retention within these reservoirs in order to minimise maintenance of the viral reservoir by de novo infection .
In the majority of HIV-1 infected individuals antiretroviral therapy ( ART ) is able to sustain suppression of plasma viral load to undetectable levels ( <50 copies HIV RNA/ml plasma ) for sustained intervals . However , viremia resumes if treatment is interrupted . Therefore , HIV-1 is able to persist in the face of suppressive ART . In addition low-level residual viremia has been detected with ultrasensitive assays that are able to measure down to several copies of HIV RNA/ml plasma [1] , [2] . It has been suggested that low level viremia in ART-suppressed patients represents release of viral particles by long-lived latently infected CD4+ T-cells [3] , [4] , [5] or virions produced as a result of low-level , residual viral replication [6] , [7] , [8] , [9] , [10] , [11] . The nature of this residual viremia , remains poorly understood , mainly because the very low number of virions in plasma limits its molecular characterization [3] , [12] , [13] . Intensification protocols employing integrase inhibitors have been used to probe the viral reservoirs that persist in ART-suppressed patients . When viral integration is inhibited , the linear viral genome , which is the precursor to the integrated provirus , is converted to episomes [14] , [15] . Although sequences gleaned from episomal DNAs could be present in both productive and non-productive infections , integrase inhibition specifically results in increased episome formation and since linear cDNA is a product of reverse transcription , increases in episomal cDNA in blood cells after starting raltegravir indicates de novo infection and blocked integration . Because of the dynamic nature of episomes , they harbor a higher percentage of contemporary sequences as compared to proviral sequences that contain a higher percentage of archival sequences . Therefore , although episomes are dead-end products of viral replication , sequences contained within them will also be observed in functional viral genomes . As a consequence , characterization of the nature of episomal HIV-1 DNA during raltegravir intensification of a suppressive HAART regimen could provide new insights into the molecular diversity and compartmentalization of the viral reservoirs that persist in the face of suppressive therapy . We previously reported that raltegravir intensification of HAART-suppressed patients affected HIV-1 replication and immune dynamics in a large percentage of these patients [16] , [17] . In order to gain further insight into the molecular diversity , population structure , and compartmentalization of replicative viral forms under suppressive HAART , episomal and integrated HIV-1 DNA samples were longitudinally analyzed by deep sequencing after intensification with raltegravir . We found signs of molecular compartmentalization distinguishing episomal and integrated HIV-1 DNA populations in PBMC , suggesting that proviruses in a cellular/anatomical compartment other than those cells may give rise to stochastic release of replication-competent virus during HAART .
The study sample comprised two participants from our previously reported raltegravir-intensification study [16] , [17] who had plasma viremia below 50 HIV-1 RNA copies per ml for two years on stable HAART . Subjects were selected based on sample availability . Reverse-transcriptase genes from episomal and integrated HIV-1 DNA were specifically amplified and analyzed at weeks 0 , 2 , 4 , 12 , 24 and 48 following raltegravir intensification . Only viral sequences present in ≥1% of the virus population were considered for further analysis . The median number and interquartile range of episomal HIV-1 DNA clonal sequences for patients 1 and 2 was 3 , 063 ( 2 , 017–3 , 473 ) and 4 , 040 ( 2 , 106–6 , 131 ) , respectively . For integrated HIV-1 DNA in patients 1 and 2 , the median was 2 , 645 ( 1 , 570–3 , 592 ) and 2 , 889 ( 2 , 247–4 , 184 ) , respectively . We constructed a phylogenetic tree for each patient to assess if episomal and integrated HIV-1 DNA sequences belonged to different genetic populations or to one intermixed population . We used a neighbor-joining approach , as implemented in MEGA4 [18] , to construct a phylogenetic tree for each patient with the best evolutionary model found in jModeltest v0 . 1 . 1 . Phylogenetic trees did not show a clear cluster differentiation of both DNA forms ( Figs . 1 and 2 ) , suggesting a lack of population structure between both DNA samples , at least at the sequence composition level . Even when sequences do not clearly group into separate branches , statistical analysis can still reveal differences in sequence diversity between different HIV populations [12] , [19] , [20] . Therefore , to better assess possible compartmentalization , we performed a population structure test based on the analysis of molecular variance ( AMOVA ) on pairwise genetic distances and percentages of the presence of each clone in each population [21] . This test showed different ratios of population structure ( FST ) between episomal and integrated sequences ( Table 1 ) , which all were statistically significant ( P<10−6 ) in both patients . As different tests of population structure can yield contradictory results , we performed a recommended conservative analysis [22] using a complementary compartmentalization test . We applied the Slatkin-Maddison test [23] , which is based only on tree topology comparison . Consistent with the AMOVA test , the results of the Slatkin-Maddison analysis showed only a few migration events between episomal and integrated samples: 12 out of 55 possible migration events , and 9 out of 46 possible migration events in patients 1 and 2 respectively ( P = 0 . 001 ) ( Table 1 ) . In addition , we obtained similar results when a longitudinal point-by-point comparison was performed between both DNA viral forms , except for three samples where the migration events had a high probability of being random ( Table 1 ) . Interestingly , two of these three samples were taken at the study baseline , i . e . right before HAART intensification with raltegravir . Overall , these results point to statistically significant compartmentalization between episomal and integrated DNA samples and suggest that they belong to different viral populations . We next assessed whether longitudinal episomal and integrated DNA sequences had a temporal structure . Firstly , we constructed a separate neighbor-joining phylogenetic tree for each patient and each viral DNA form ( Fig . 3 and 4 ) . Phylogenies showed evidence of a temporal structure within episomal and integrated viral DNA forms across different time-points . Temporal structure was more evident in the episomal samples of patient 2 ( Fig . 4a ) and the integrated samples of patient 1 ( Fig . 3b ) . However , a clear sign of temporal structure was difficult to observe in the remaining phylogenetic trees ( Fig . 3a and 4b ) . Therefore , we used the AMOVA and Slatkin-Maddison tests to again assess the presence of temporal population structure within each viral DNA form . AMOVA showed that all longitudinal comparisons within episomal and integrated samples were significantly different ( P<10−6 ) indicating different temporal population structures ( Tables 2–5 ) . Statistically significant Slatkin-Maddison results were partly consistent with those detected by AMOVA ( Tables 2–5 ) . Discrepancies between both tests might be due to the large number of sequences with the same haplotype ( sometimes present in both compartments ) . In fact , the performance of the Slatkin-Maddison test might be limited when there is a combination of relatively short sequence , high depth and low within-patient diversity [23] , as in this case . Our results revealed that in both episomal and integrated HIV-1 DNA samples , distinct genetic populations appeared at different time-points , suggesting that the appearance of each viral DNA form in blood could be the result of stochastic mobilization of different HIV-infected cells . This effect has been observed for residual viremia [12] and for different populations of CD4+ T-cells [7] . Furthermore , we did not observe any signs of evolution across longitudinal samples within episomal DNA or within integrated viral forms ( Fig . 3 and 4 ) . We found temporal variation but no evidence of continued evolution . Of note , patient 1's viruses harbor the mutation M184I in the reverse transcriptase of the integrated HIV sequences from weeks 0 and 2 ( but not from weeks 4 or 24 ) , which is associated to resistance to lamivudine and emtricitabine . This patient was under a regimen containing tenofovir , lamivudine , lopinavir , ritonavir and raltegravir . In contrast episomal sequences from weeks 0 , 2 and 4 were wild type , which suggest that 2LTR circles were generated in a different cellular/anatomical compartment that is possibly less accessible to lamivudine . A population structure can occur at two levels: ( i ) different composition at the sequence level and ( ii ) different proportions of specific haplotypes . Therefore , the percentage of each clonal sequence of each DNA sample was represented ( Fig . 3c–d and Fig . 4c–d ) . The results show that some haplotypes were shared among and within HIV-1 viral DNA forms , but unique haplotypes were also found . Moreover , when sequences were shared , the percentage of each haplotype was different between samples . This observation , together with the low molecular variability found in each sample ( Table 1 ) , suggests that patients under suppressive HAART have a limited variability in viral DNA sequences and that the presence and relative proportion of each clonal sequence might determine whether a population structure exists .
Previous reports have shown evidence of compartmentalization between residual plasma viremia and proviruses in fractionated and unfractionated PBMC [12] . However , this is the first time that episomal cDNA and integrated HIV-1 DNA genomes have been extensively compared . We found a statistically significant compartmentalization between episomal and integrated DNA samples in PBMC suggesting that , as with residual plasma viral RNA , episomal HIV-1 DNA forms are genetically distinct from proviral genomes and that they encompass two different genetic populations . In addition we have shown that in both episomal and integrated HIV-1 DNA samples , distinct genetic populations appeared , in a non-chronologic manner , at different time points . Longitudinal , non-chronological population structure between and within samples was detected in both circular episomal and proviral HIV-1 DNA viral forms . One explanation for our findings is that episomal and proviral sequences were generated in distinct cell types or anatomical compartments , possibly with different pharmacological penetration profiles . The detection of both DNA forms could result from stochastic mobilization from tissues to blood of a few infected cells , as their low molecular variance suggests . However , the labile nature of episomal DNA and its specific dynamics after raltegravir intensification [16] implies that the infection events that generated them occur in a pharmacologically privileged site ( because the infections that generated them are occurring in the face of RT inhibitors ) yet that is still accessible to raltegravir . A recent report shows that ileum may support ongoing productive infection in some patients on HAART , even if the contribution to plasma RNA is not discernible . In fact , raltegravir intensification contributed to a decrease in the cell-associated HIV RNA in this anatomic site relative to other gut sites or PBMC , suggesting that gut sites differ with respect to penetration by antiretroviral drugs , immunologic environments or the composition of CD4+ T cell populations [24] . Alternatively , our results might also suggest that cells containing these transiently-increased episomes might result from new infections with replication-competent viruses originating from rare proviruses not detectable in peripheral blood mononuclear cells , and that these episomes have had their integration blocked by raltegravir . The lack of population structure or evolution in integrated HIV-1 genomes is best explained by the fact that proviruses are predominantly defective and archival . Although the provirus is the molecular precursor for all virions , only a very small percentage of proviruses are replication competent and only a small percentage of these would exist in a latent state- one capable of producing replication-competent virions . Therefore , temporal structure might simply be a result of continuous seeding of new cells over time . In this regard , multiple monotypic HIV-1 sequences have been observed across the uterine cervix and in blood , presumably as a result of the proliferation of cells harboring proviruses [25] . Although the origin of these cells with integrated HIV-1 DNA in our study remains unknown , forthcoming genotypic analysis across cell subpopulations in blood and tissues may cast light on this issue . Memory CD4+ T cells are thought to be a stable reservoir of HIV infection [26] , [27] , [28] , [29] , [30] , [31] . The transient increases in 2LTR circles in PBMC from patients during early HAART in the absence of raltegravir , has recently been associated with the redistribution of 2LTR-enriched memory CD4+ T-cells from lymphoid tissues due to short-term decreases in immune activation [32] . In our study , changes in immune activation occurred more slowly . As such , distinct mechanisms appear to account for the changes in 2LTR circles . Interestingly , it has also recently been shown that the majority of a highly specialized subset of antigen-specific memory CD4+ T cells in mice were found to reside in a resting state in the bone marrow , surviving in close proximity to IL-7-secreting stromal cells [33] . Coincidently , IL-7 also induces homeostatic proliferation of human central memory CD4+ T cells without causing viral reactivation [34] . Therefore , the different population structure within integrated DNA , which is not coincident with the episomal DNA population , could be explained by the re-activation and mobilization of memory CD4+ T-cells from different niches in bone marrow without subsequent viral production , and could be a consequence of cellular rather than viral dynamics . Previous studies have examined rebounding viremia following treatment interruption and suggested that emerging viral variants result from the stochastic reactivation of different HIV-1 infected cells [4] , [35] , [36] , [37] . Finally , infectious events during HAART can occur in multiple , temporary , small and locally scattered bursts [38] consistent with our observed genotypic compartmentalization . In addition , we observed that the cell-associated HIV proviral DNA remained relatively stable ( Fig . S1 ) despite the large shifts in sequence populations observed during the study . This would not only mean that newly infected cell populations had undergone expansion but that other populations contracted at the same time . It is tempting to speculate that these dynamics might be consistent with the continuous trafficking between blood and tissues ( preferentially lymphoid tissue ) of stochastically activated antigen-specific memory CD4+ T-cells . We believe that it is unlikely that the results obtained reflect limited sampling , because we detected different proportions of shared haplotypes at different longitudinal time points ( Fig . 1c , d and Fig . 2c , d ) . Sequence diversity restrictions due to sampling limitations would be reflected by either a completely different population structure or by invariable shared haplotypes in different samples . Moreover , at least in some time points , there is quite a large number of unique haplotypes ( >1% ) , suggesting good depth . Proviral HIV sequences are currently thought to be representative of archival HIV infection in an infected patient . Based on this hypothesis , sources of residual viremia other than CD4+ T-cells have been postulated as long-lived viral reservoirs [3] . Our observation that longitudinal detection of proviral genomes is dynamic in patients on HAART is important because it points to some limitations in the conclusions drawn from cross-sectional studies comparing HIV sequences in plasma and circulating T-cells . Our results collectively suggest the presence of a chronic viral reservoir in which there is stochastic release of infectious virus and in which there are limited rounds of de novo infection . This could be explained by the existence of a limited cellular/anatomic reservoir in which de novo infection continues during HAART because some antiretroviral drugs do not effectively inhibit replication in this compartment . However , evidence that episomes transiently increase after raltegravir intensification suggests that this cellular/anatomic reservoir may be accessible to raltegravir , in contrast to other drugs . If proven in future work , the concept that ongoing replication during successful HAART originates from proviruses that are not detectable in peripheral blood mononuclear cells has important implications for the design of strategies aimed at viral eradication or functional cure . It indicates the need to further define the limited and covert cellular/anatomic reservoir in which ongoing HIV replication may occur during suppressive HAART .
The study was approved by the Germans Trias i Pujol hospital review board and informed consent was obtained in writing from study participants . We extensively analyzed longitudinal samples from 2 HIV-infected patients whose plasma viral load had been suppressed to <50 HIV-1 RNA copies/ml for 2 years on a stable HAART regimen . Both patients had participated in a previously reported raltegravir-intensification study [16] , [17] were intensification of a three-drug suppressive HAART regimen resulted in a specific and transient increase in episomal DNA in a large percentage of patients . The original study was designed to compare populations of episomal and integrated HIV-1 DNA and plasma viral RNA in 5 patients with detectable episomal DNA before raltegravir intensification . Although plasma viral load assays employed 7 ml of plasma , we were unable to amplify viral RNA sequences for the majority of time points nor amplify episomal and integrated HIV-1 DNA from the majority of longitudinal samples in 3 patients . For this reason , structure comparisons between episomes and integrated HIV-1 DNA were only possible for the 2 subjects shown in this study . Episome and proviral DNA dynamics for both patients are shown in Fig . S1 . HAART regimens included lopinavir , ritonavir , lamivudine , tenofovir and raltegravir for patient 1 and efavirenz , emtricitabine , tenofovir and raltegravir for patient 2 . None of the included patients had previously been exposed to integrase inhibitors . Peripheral blood mononuclear cells ( PBMC ) and plasma samples included in this study encompassed weeks 0 , 2 , 4 , 12 , 24 and 48 after raltegravir intensification . A median of 6×107 PBMC were obtained at weeks 0 , 2 , 4 , 12 , 24 and 48 after intensification and purified by Ficoll centrifugation and resuspended in 350 µl of P1 buffer ( Qiaprep miniprep kit , Qiagen ) . 250 µl of cell suspensions were used for extrachromosomal HIV-1 DNA extraction ( Qiaprep miniprep kit , Qiagen ) using a modification for the isolation of low-copy-number plasmids . Total cellular DNA was purified from 100 µl of cell resuspension with a standard protocol ( QIAamp DNA Blood Kit , Qiagen ) as previously described [16] . Analysis of HIV genomes from a sample containing a low copy number of HIV , such as PBMC from patients with undetectable viral load , can result in a high probability of resampling . The probability of resampling is related to both the number of target molecules during the amplification step and the number of sequenced clones . Therefore the higher the input of target molecules in the PCR and the higher the number of sequenced clones , the less likely the probability of resampling [39] . In order to avoid resampling , we extracted episomal and integrated DNA from a median of 6×107 PBMC to increase the number of input molecules during the first PCR . In addition , only samples with individual clonal sequences higher than 1 , 500 after deep sequencing were considered for further analysis . We used a two-step PCR to amplify the RT region of episomal and integrated HIV-1 DNA . Primers Aluf and LA7 for integrated DNA and Jct f and LA7 for episomal DNA were used as previously described [10] . Nested PCR amplification of the RT region ( codons 150 to 250 ) was performed as part of the DS protocol ( see below ) . Nested PCR of background controls with primers DR pol f and DR pol r [10] , in parallel to 454 amplification , was carried out to ensure that nested PCR was specific for integrated and episomal DNA viral forms . Pooled , purified PCR products were used as template to generate a single amplicon covering codons 150 to 250 from the RT region . The amplicon library was generated in triplicate during 20 cycles of PCR amplification ( Platinum Taq DNA Polymerase High Fidelity , Invitrogen , Carlsbad , CA ) followed by pooling and purification of triplicate PCR products using magnetic beads ( Agencourt AMPure Kit ( Beckman Coulter , Benried , Germany ) to eliminate primer-dimers . The number of molecules was quantified by fluorometry ( Quant-iT PicoGreen dsDNA assay kit , Invitrogen , Carlsbad , CA ) . The quality of each amplicon was analyzed by spectrometry using a BioAnalyzer ( Agilent Technologies Inc . , Santa Clara , CA ) . Deep Sequencing ( DS ) was performed in-house on a 454 Life Science/Roche platform . The error rate of the in-house DS technique , as inspected with 992 pNL43 clonal sequences obtained with DS under the same conditions as those used for patient samples , was 0 . 07% ( 0 . 13% ) , which is close to previous reports [40] . This mismatch rate corresponds to a variability rate of 1 . 69×10-5 , within the range of expected PCR error . The 99th percentile of mismatches would establish the threshold for nucleotide errors in 0 . 61% . Therefore , we decided to include for further analysis only patient clonal sequences present at ≥1% of the viral population . 454 DNA amplicon sequences were aligned with an HXB2 reference sequence using Muscle v3 . 7 [41] and an independent alignment for each DNA , time-point and patient was built . In order to increase the number of sequences for further analysis and to avoid sequencing errors produced at the end of the sequencing run , we extracted from codon 50 to 209 from each of the sequences obtained with DS . Technical errors of the DS technique drive the introduction of indeterminations ( introducing N instead of A , T , G or C ) into the sequences . These indetermination were substitute by gaps . An in-house method was used to merge clonal sequences into unique sequences . Only clonal sequences present at ≥1% of the clonal population were used . Alignments are available upon request . jModeltest v0 . 1 . 1 [42] was used to infer the best phylogenetic model to explain the alignment sequence evolution . This program is able to implement a discrete gamma distribution ( Γ ) which models the heterogeneity rate among sites . A neighbour-joining approach , as implemented in MEGA4 [18] , was used to construct a phylogenetic tree with the best evolutionary model found in jModeltest v0 . 1 . 1 . In order to detect differences in sequence composition between episomal and integrated DNA at different time-points , we performed two analyses , ( i ) an analysis of molecular variance ( AMOVA ) as implemented in the Arlequin software package [21] , which is based on pairwise genetic distances and percentage of presence of each clone at each population , and ( ii ) a tree based topology method , the Slatkin-Maddison test [23] as implemented in HYPHY [43] . The Slatkin-Maddison tests involve estimating the number of migrations between populations , and determining whether the estimated number of migrations is less than expected if there were no compartmentalization . As the maximum possible number of migrations depends on the number of sequences analyzed from each compartment , a randomization test is performed to estimate a p value to assess the significance of compartmentalization . This approach has previously been used to study differences in sequence diversity between different HIV populations [12] , [19] , [20] . AMOVA is a genetic distance-based test where the frequency of a sequence variant ( haplotype ) i in the organ j , xij , can be expressed as xij = x + ai + bij , where ai and bij are episomal or integrated DNA and the haplotype within-DNA specific effects , respectively . These two factors have associated variances and that can be described as total variance among haplotypes as . The FST index measures the population differentiation . This value is defined as the ratio between , and it can be estimated from the usual partition of total variance into its components in a nested analysis of variance ( ANOVA ) [44] . We carried out AMOVA analysis by computing FST with a distance matrix obtained from Arlequin program using the best evolutionary model found by jModeltest . | In the majority of HIV-1 positive patients , antiretroviral therapy ( ART ) effects a sustained reduction in plasma viremia to below detectable levels . Despite this , replication competent viruses persist and fuel viremia if antiretroviral treatment is interrupted . This viral persistence stands in the way of viral eradication through ART . While this ability to persist in the face of therapy is generally considered to be attributable to a reservoir of latently infected cells , there is debate as to how this reservoir is maintained and in particular , whether there is replenishment of the reservoir by low level , residual replication . Novel antiviral agents targeting the viral integrase offer tools to explore the viral reservoirs that persist in the face of ART and we have shown that raltegravir perturbs these reservoirs as evidenced by an accumulation of episomal DNA upon rategravir intensification ( Buzon et al . , 2010 ) . Through “deep sequencing” technology , we have longitudinally analyzed the genotypes of HIV episomes and integrated HIV DNA to evaluate whether they represent interrelated sequences or whether they have distinct origins . Statistical methods showed molecular compartmentalization , among and within episomal and integrated HIV-1 DNA samples , and suggest that episomal DNA in PBMC originates from a cellular/anatomic reservoir that is not revealed by sequencing of proviral DNA in PBMC in this study . These , and other data , suggest that ongoing replication , which can be blocked by adding raltegravir , occurs from proviruses that are genetically distinguishable from those detected at >1% frequency in these circulating blood cells . | [
"Abstract",
"Introduction",
"Results",
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] | [
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] | 2011 | Deep Molecular Characterization of HIV-1 Dynamics under Suppressive HAART |
The innate immune response plays a key role in fighting infection by activating inflammation and stimulating the adaptive immune response . However , chronic activation of innate immunity can contribute to the pathogenesis of many diseases with an inflammatory component . Thus , various negatively acting factors turn off innate immunity subsequent to its activation to ensure that inflammation is self-limiting and to prevent inflammatory disease . These negatively acting pathways include the production of inhibitory acting alternate proteins encoded by alternative mRNA splice forms of genes in Toll-like receptor ( TLR ) signaling pathways . We previously found that the SF3a mRNA splicing complex was required for a robust innate immune response; SF3a acts to promote inflammation in part by inhibiting the production of a negatively acting splice form of the TLR signaling adaptor MyD88 . Here we inhibit SF3a1 using RNAi and subsequently perform an RNAseq study to identify the full complement of genes and splicing events regulated by SF3a in murine macrophages . Surprisingly , in macrophages , SF3a has significant preference for mRNA splicing events within innate immune signaling pathways compared with other biological pathways , thereby affecting the splicing of specific genes in the TLR signaling pathway to modulate the innate immune response .
While the innate immune response plays a critical role in fighting infection , overactive or chronically activated innate immunity can contribute to many diseases with an inflammatory component [1–4] . Thus to fight infection without inducing inflammatory disease , a complex regulatory system has evolved to activate innate immunity when humans are exposed to pathogens and then turn the system off after a period of time to ensure that it is self-limiting . One family of innate immune receptors that senses pathogenic components is the Toll-like receptor ( TLR ) family . Different TLRs respond to different pathogenic stimuli; for example , TLR4 is activated in the presence of lipopolysaccharide ( LPS ) from Gram negative bacteria [5 , 6] . Binding of LPS to TLR4 and its co-receptor MD-2 leads to recruitment and activation of the signaling adaptor MyD88 , which in turn recruits a family of related kinases: IRAK4 , IRAK1 , and IRAK2 [7] . This signaling cascade continues , culminating in the activation of the transcription factor NFκB and the activation of several MAP kinase pathways [7] . This in turn leads to the production of , among other things , inflammatory cytokines . One mechanism that has evolved to ensure that TLR4 activation is self-limiting is the feedback-induced production of a variety of negative regulators of TLR signaling [8–14] including the production of alternatively spliced forms of TLR signaling components [15–25] . For example , while the LPS receptor TLR4 is encoded by a three exon mRNA , an alternately spliced mRNA that includes an extra exon between exons two and three has been identified [18] . This extra exon introduces a premature stop codon , resulting in the production of a soluble fragment of TLR4 ( sTLR4 ) that can bind LPS but that cannot signal to the downstream components of the pathway . Thus , sTLR4 acts as a dominant inhibitor of TLR signaling [18] . Similarly , negatively acting splice forms of MD-2 , MyD88 , IRAK1 , IRAK2 , and many other TLR signaling components have been described [15–25] . The production of many of these negatively acting alternate splice forms is induced by LPS stimulation [16–19] , suggesting that the inflammatory stimulus mediates its own negative feedback loop to limit the innate immune response , thereby preventing inflammatory disease . While RNAseq and individual gene studies have determined that alternative splicing is an important regulatory mechanism to control TLR signaling , thus far there has been only limited investigation of how this alternative pre-mRNA splicing is regulated . We have identified the SF3a and SF3b mRNA splicing complexes as novel regulators of innate immunity [26 , 27] . These mRNA splicing complexes bind to the U2 small nuclear ribonucleoprotein ( snRNP ) , which in turn binds to the branch site near the 3’ end of introns to control mRNA splicing with the rest of the spliceosome [28–34] . Weakening of U2 snRNP activity is expected to perturb mRNA splicing , causing exon skipping or intron retention [35–38] . We found that inhibition of SF3a or SF3b by RNAi or a pharmacological agent in mouse or human macrophages weakened the innate immune response induced by several TLR agonists including LPS [26 , 27] . In particular , SF3a1 inhibition diminished the LPS-induced production of IL-6 , TNFα , RANTES , and IL-10 [27] . Importantly , this effect on innate immunity occurred at a level of gene inhibition ( roughly 80% ) that did not affect general cell functions such as viability or phagocytosis [26] . This suggests that inflammatory signaling pathways may be more sensitive to perturbation of the spliceosome than other pathways . Consistent with this theory , RNAi-mediated inhibition of Eftud2 , which functions with the U5 snRNP at a later stage of spliceosome assembly [30 , 39–45] , also weakened the innate immune response to LPS without affecting cell viability [46]; in contrast , overexpression of Eftud2 increased the response to LPS [46] . The effects of these splicing factors on innate immunity are mediated in part by control of alternative splicing of MyD88 [26 , 46] . MyD88 is encoded by a five-exon mRNA ( long form or MyD88L ) that encodes the positively acting TLR signaling adaptor . A shorter mRNA lacking exon 2 ( MyD88S ) encodes a dominantly acting negative regulator of TLR signaling that prevents IRAK activation [15 , 19 , 20] . Inhibition of SF3a , SF3b , or Eftud2 leads to an increase in the production of MyD88S , which in part explains the effect of these mRNA splicing genes on innate immunity [26 , 46] . However , our data indicated that other TLR signaling components also likely mediate the effects of mRNA splicing genes on innate immunity [26] . Based on these data , we have hypothesized that the splice site choices in MyD88 and perhaps other TLR signaling genes have evolved to be exquisitely sensitive to cellular conditions because of their functional significance , and may be key regulatory points of a mechanism to limit inflammation . To better understand the effects of the spliceosome on TLR signaling , we now use RNAseq to examine the full complement of genes and splicing events regulated by the SF3a complex in mouse macrophages . We find that key cis-acting regulatory sequences mediate the effects of SF3a on alternative splicing . In keeping with our hypothesis , pathway analyses of these data indicate that TLR signaling and other innate immune signaling pathways are among the most sensitive pathways to inhibition of SF3a1 in macrophages . We find several genes in TLR pathways whose expression or mRNA splicing are altered by SF3a1 inhibition . These include the production of the known negative regulatory splice form of TLR4 as well as a newly identified negatively acting splice form of IKKβ . Thus , SF3a1 regulates innate immunity by controlling multiple mRNA splicing events in TLR signaling pathways in macrophages .
A schematic outlining our experimental strategy is depicted in Fig . 1 . To test the effect of SF3a1 inhibition , the RAW264 . 7 mouse macrophage cell line was treated with either SF3a1 siRNA or control non-targeting siRNA . Following siRNA treatment , the cells were exposed for four hours to either 20 ng/ml LPS or no LPS as a control . All siRNA treatments and subsequent LPS exposures were performed in triplicate , resulting in 12 total samples analyzed by RNAseq ( Fig . 1A ) . Following the LPS exposures , supernatant was collected for ELISA analysis to verify that , as expected , LPS induced IL-6 production and that SF3a1 siRNA treatment inhibited LPS-induced IL-6 production . RNA was purified from the adherent cells for qPCR analysis to verify SF3a1 gene knockdown ( ∼80% ) and for RNAseq analysis . No effects on viability were observed at this level of knockdown [26] . Three different experimental comparisons were monitored ( Fig . 1A ) : ( 1 ) the effect of LPS was monitored by comparing the effects of control siRNA treatment in either the absence or presence of LPS; ( 2 ) the effect of SF3a1 inhibition in the absence of LPS; and ( 3 ) the effect of SF3a1 inhibition in the presence of LPS . Several computational approaches were taken for this analysis as outlined below . To investigate the global effects of SF3a on mRNA splicing , we used the MISO [47] software package ( Fig . 1B , S1–S5 Tables ) . MISO identifies changes in mRNA splicing by mapping RNAseq data onto pre-identified intron and exon isoform structures from a subset of genes . These data were in turn used for computational analyses of intron and exon sequences that regulate mRNA splicing ( Fig . 1C ) . To determine how SF3a affects innate immunity , three different software packages ( DESeq , DEXSeq , and Cufflinks ) were used to identify genes and gene isoforms whose expression was regulated by SF3a ( Fig . 1B ) . DESeq [48] maps RNAseq data onto pre-identified gene structures . Thus this gene-level analysis can be used to identify changes in total expression of each gene ( S6–S8 Tables ) , but cannot identify changes in isoform usage . In contrast , DEXSeq [49] , which performs an exon-by-exon level analysis of RNAseq data , was used to identify changes in exon expression and therefore isoform usage ( S9–S11 Tables ) . Finally , Cufflinks [50 , 51] , which unlike the other software packages that compare sequence data to known transcripts , analyzes the sequence data de novo to identify both known and novel transcripts , which can then be compared between experiments using Cuffdiff ( S12–S18 Tables ) . These gene and isoform lists were then used to inform pathway analysis with the GATHER [52] and DAVID [53 , 54] software tools ( Fig . 1D ) and also were used to identify genes responsible for mediating the effects of splicing factors on innate immunity ( Fig . 1E ) . As expected , treatment with LPS increased mRNA levels for numerous cytokines and chemokines ( S6 Table ) including but not limited to TNFα , IL-6 , IL-1β , and IL-12 . Among the top pathways altered by LPS at both the gene level ( S6 Table ) and exon level ( S9 Table ) were innate immune signaling pathways: TLR signaling , cytokine-cytokine receptor signaling , and MAP Kinase signaling ( Table 1 ) . Thus , LPS stimulation alters the expression of LPS-response genes at both the gene and isoform levels . SF3a1 is an essential mRNA splicing factor , and as such , its inhibition is expected to alter mRNA splicing . Using MISO , we determined that SF3a1 inhibition , in either the absence or presence of LPS , affected multiple classes of alternative splicing events ( Fig . 2 , S19 Table ) , including intron retention , exon skipping , alternate 3’ and 5’ splice site usage , and altered mutually exclusive exon usage . In particular , a large number of intron retention and exon skipping events were identified by this analysis . In contrast , LPS stimulation affected all classes of splicing changes but did so at much lower frequency . While SF3a1 inhibition affected numerous alternative pre-mRNA splicing events ( Fig . 2 ) , the vast majority of potential mRNA splicing events in macrophages were not significantly affected even though SF3a1 levels are at only 20% of their wild type levels in these studies . What renders some splice site choices so sensitive to SF3a inhibition ? To answer this question , we investigated intron sequences known to regulate mRNA splicing . Intron sequences that govern splicing include the GT at the 5’ splice site , the AG at the 3’ splice site , the polypyrimidine tract that is located just upstream of the 3’ splice site , and the branch site located still further upstream [55] . Assembly of splicing regulators at the 3’ splice site involves binding of the SF1 protein to the branch site [56–58] and the U2AF1/2 complex to the polypyrimidine tract and 3’ splice site [59–62] . This facilitates the recruitment of the U2 small nuclear ribonucleoprotein ( snRNP ) , which binds to the branch site . Activation of the U2 snRNP additionally requires two accessory protein complexes , SF3a and SF3b [31–33 , 63–65] . We used MISO to identify introns that were retained when SF3a1 was inhibited ( SF3a-“dependent” introns ) and introns that were spliced out normally when SF3a1 was inhibited ( SF3a-“independent” or at least “less dependent” introns ) and subsequently compared their sequences . Similarly , we compared introns upstream of exons that were skipped when SF3a1 was inhibited to downstream introns and to introns flanking exons that were not skipped , despite being annotated as potential candidates . We did not observe any significant differences in the nucleotides immediately surrounding the 5’ or the 3’ splice site when SF3a1 inhibition induced intron retention or exons skipping . However , we did observe differences in the polypyrimidine tracts of introns that were retained following SF3a inhibition ( Fig . 3A–D ) . These introns ( undergoing SF3a-dependent splicing ) had a less U-rich and more C-rich polypyrimidine tract compared to introns that were not retained ( SF3a-independent splicing ) ( Fig . 3A–D , raw data in S20 Table ) . In contrast , the polypyrimidine tracts in introns upstream of skipped exons were not significantly different from those in introns downstream of skipped exons . Moreover , these polypyrimidine tracts that flanked skipped exons were not significantly different from those that flanked non-skipped exons . We also examined the length of introns and exons at alternatively spliced sites when SF3a1 was inhibited and found that skipped exons were shorter than non-skipped exons ( Fig . 3E , mean length 114 skipped vs 150 non-skipped , p = 4×10−15 , Mann-Whitney U-test ) . Moreover , as noted previously [66–68] , we observed that exons were more likely than expected by chance ( >33% ) to be of a length that is a multiple of three base pairs , and skipped exons tended to be even more enriched for such “in-frame” exons ( no LPS: 44 . 5% not skipped vs 56 . 3% skipped , p = 0 . 0020; with LPS: 45 . 0% not skipped vs 55 . 3% skipped , p = . 0086 , both Pearson’s χ2-test ) . Thus , skipped exons in genes frequently do not alter the reading frame of their encoded proteins , making it more likely that they will not completely abolish protein function . As observed previously [26 , 27] , inhibition of SF3a1 in the presence of LPS diminished production of numerous cytokines and chemokines ( S8 Table ) , including but not limited to IL-6 , CCL5 and IP10 . We previously speculated that inflammatory processes in macrophages were more sensitive to perturbation of the spliceosome than are other pathways , because inhibition of splicing factors weakened innate immunity without significantly affecting macrophage viability or phagocytosis [26] . Consistent with this speculation , while many genes and pathways are affected by SF3a1 inhibition in macrophages , we find that innate immune signaling pathways are among the most significantly altered pathways at the level of mRNA splicing ( DEXSeq analysis ) when SF3a1 is inhibited , either in the absence or presence of LPS ( Table 2 ) . Examination of TLR signaling pathways identified several genes whose expression or splicing was altered by SF3a1 inhibition in the absence and/or presence of LPS ( Fig . 4 ) . We decided to investigate the effects of three of these genes in detail that function in the MyD88-NFκB arm of the LPS response pathway ( Fig . 4 ) . These three genes were the LPS receptor TLR4 and the downstream signaling kinases IRAK1 and IKKβ ( alias IKBKB ) . TLR4 , IRAK1 , and IKKβ were identified by the DEXSeq analyses as alternatively spliced in both the absence and presence of LPS ( S10–S11 Tables ) . IKKβ was additionally identified by one of the Cuffdiff analyses ( S15 Table ) . All three of these genes are positive effectors of the innate immune response . Additionally , we chose to investigate two other genes that affect upstream components of the TLR4 signaling pathway that were not identified by DEXSeq but were identified in the other analyses . RAB7b controls the trafficking and subsequent destruction of TLR4 [69] and thus is a negative regulator of TLR signaling . CD14 functions to bring LPS to the TLR4 receptor and is a positive effector of TLR signaling [70] . Expression of RAB7b ( alias 5430435G22Rik ) was flagged as significantly increased in several analyses including DESeq ( S7–S8 Tables ) and Cuffdiff ( S12 Table ) . CD14 was identified in Cuffdiff analyses that used mouse genome mm9 but was not identified as a significantly changed gene in these analyses using mouse genome mm10 , possibly due to differences in CD14 gene annotation in the two databases . The RNAseq analysis indicated that three of these five genes had intron retention events when SF3a was inhibited: IRAK1 intron 1 ( Fig . 5A ) , IKKβ intron 15 ( Fig . 5B ) , and CD14 intron 1 . While DEXSeq identifies alterations in exon expression in RNAseq data , in all these cases , DEXSeq also identified intron retention events due to reported non-canonical isoforms in Ensembl . To validate these RNAseq data , we monitored expression of the various gene isoforms using qPCR with isoform-specific primers . Moreover , we performed these qPCR studies on a second set of RNA samples from independent SF3a1 RNAi treatments and LPS exposures . In all three cases , we found that inhibition of SF3a1 in the presence of LPS led to increased retention of the expected intron and a concomitant decrease in the expression of the isoform that crossed that particular exon-exon junction ( Fig . 5C–H ) . We also confirmed that the canonical IKKβ isoform was decreased following SF3a inhibition by using a second set of qPCR primers that lie further downstream in the gene ( Fig . 5I ) . Thus , intron retention in these three genes diminishes production of the wild type , positively acting isoform . This is consistent with the effects of SF3a inhibition , which weakens innate immunity [26 , 27] . To confirm that these mRNA splicing changes were reflected at the protein level , we monitored the level of IRAK1 and IKKβ by western blot following SF3a1 siRNA treatment . Retention of intron 1 in IRAK1 is predicted to truncate the 750 amino acid protein after only 47 amino acids . Retention of intron 15 in IKKβ is predicted to truncate the 757 amino acid full length protein and generate a 555 amino acid protein containing the first 526 amino acids of IKKβ and 29 novel intron-encoded amino acids . Using antisera that recognize IRAK1 and IKKβ , we observed decreased levels of IRAK1 and IKKβ when SF3a1 was inhibited by RNAi ( S1 Fig . ) [note that IRAK1 levels were monitored in the absence of LPS as LPS exposure alters electrophoretic mobility and stability of IRAK1 [15 , 71–74]] . In contrast , SF3a1 inhibition did not affect production of βactin ( S1 Fig . ) . We were not able to detect the predicted 555 amino acid truncated IKKβ , even on much longer exposures of the western blot . This may be because the relative levels of the proteins differ ( which we cannot determine from the current qPCR data ) or because the truncated protein is unstable . To test how general these effects were , we also monitored these intron retention events when SF3a1 was inhibited in a second mouse macrophage cell line , J774A . 1 . Inhibition of SF3a1 in J774A . 1 cells also diminishes the innate immune response to LPS [27] . As observed previously [26] , qPCR analysis indicated that expression of the negatively acting MyD88S isoform was increased when SF3a1 was inhibited in RAW264 . 7 cells ( Fig . 6A , B ) , and we find that MyD88S is likewise increased following SF3a1 inhibition in J774A . 1 cells ( S2A–S2B Fig . ) . We found that some but not all of the effects of SF3a1 knockdown on intron retention events were recapitulated in J774A . 1 cells . CD14 intron 1 was retained in J774A . 1 cells following SF3a1 inhibition ( S2C–S2D Fig . ) . We also observed a decrease in IRAK1 levels in J774A . 1 cells following SF3a1 inhibition ( S2E Fig . ) but did not observe a concomitant increase in IRAK1 intron 1 retention ( S2F Fig . ) . We did not detect intron 15 retention in IKKβ in J774A . 1 cells when SF3a1 was inhibited with siRNA ( S2G–S2H Fig . ) . Thus , some but not all of the altered splicing events detected in RAW264 . 7 cells were recapitulated in a second macrophage cell line J774A . 1 . The differences could reflect a difference in SF3a1 knockdown in the two cell lines . Despite our ability to detect alterations in MyD88S by qPCR when SF3a1 is inhibited ( Fig . 6A , B ) , we did not identify differential expression of MyD88S in the current RNAseq study , likely because of the very small quantity of MyD88S mRNA present in cells . The vast majority of sequence reads in MyD88 lie entirely within exons . These reads cannot distinguish between the two splice forms because they will be common to both MyD88L and MyD88S; thus , only reads that cross the unique splice junctions in MyD88L and MyD88S will be informative as to the ratio of the two isoforms . Based on RT-PCR , we previously estimated that the ratio of MyD88L:MyD88S was approximately 20:1 in unstimulated cells [26] . The current RNAseq data suggest that this ratio could even be larger; in unstimulated cells , we identified 282 reads that crossed the exon 1-exon 2 junction and 217 reads that crossed the exon 2-exon 3 junction ( both of which are reads corresponding to MyD88L ) . In contrast , in unstimulated cells , we only obtained 7 reads that crossed the unique MyD88S exon 1-exon 3 junction . The RNAseq data also indicated that an alternative splice form of TLR4 was generated when SF3a1 was inhibited; this involved splicing of TLR4 to either of two alternative exons >70 kb downstream of TLR4 . However , neither of these alternative splice forms has been identified in the plethora of previous studies on TLR4 , and we were unable to obtain products corresponding to these computational predictions using RT-PCR . However , we did note that RNAseq reads were identified between exons 3 and 4 in TLR4 when SF3a1 is inhibited . An alternative splice form of TLR4 has been described previously in which an extra exon is incorporated between exons 3 and 4; this extra exon introduces a stop codon that produces a truncated soluble version of TLR4 ( sTLR4 ) that acts as a negative regulator of signaling [18] . Using qPCR , we were able to verify that TLR4 levels were moderately decreased and sTLR4 levels were substantially increased when SF3a1 was inhibited ( Fig . 6C , D ) . Our RNAseq analysis also indicated that expression of the negative regulator RAB7b was increased when SF3a1 was inhibited , and we were able to verify this by qPCR ( Fig . 6E ) . Thus , SF3a1 inhibition leads to increased expression of Rab7b and sTLR4 , both negative regulators of TLR signaling . As described above , inhibition of SF3a1 led to a decrease in production of the wild type IKKβ mRNA and an increase in an alternative mRNA form of IKKβ retaining intron 15 ( Fig . 5B , G–I ) . cDNAs with similar intron 15 retention events also have been reported in humans ( Ensembl transcript ENST00000520201 , UCSC transcript uc010lxh . 2 , mRNA AB209090 ) . While this alternate transcript also includes intron 14 ( 163 nt ) in human , we see no evidence of intron 14 retention in our experiments with mouse . Retention of intron 15 in mouse results in a premature stop codon that truncates IKKβ after amino acid R526 plus 29 intron-encoded amino acids; this deletes the last 231 amino acids of IKKβ . The resulting protein contains the NH2-terminal kinase domain but lacks the COOH-terminal NEMO binding domain . IKKβ , IKKα , and NEMO together form a complex that phosphorylates IκBα and is thus critical for LPS-induced NFκB activation [75 , 76] . Interestingly , an alternative splice form of the related protein IKKε that is truncated in a similar location encodes a dominant negative signaling molecule that inhibits viral infection-induced activation of IRF3 and NFκB [77] . We therefore investigated if this truncated IKKβ ( which we refer to as IKKβb ) could likewise act in dominant negative fashion . We inhibited production of this alternatively spliced IKKβb mRNA using either of two different siRNA duplexes that target intron 15 in IKKβ . Both siRNAs decreased production of both IKKβ and IKKβb isoforms , with stronger inhibition of the IKKβb isoform ( Fig . 7A , B ) , and increased LPS-induced IL-6 production ( Fig . 7C ) . Inhibition of wild-type IKKβ should diminish LPS-induced cytokine production , so this increased IL-6 production is consistent with IKKβb being a novel inhibitory isoform . Our RNAseq analysis demonstrated that many TLR signaling pathway genes exhibit altered expression or mRNA splicing when SF3a1 was inhibited . This included a decrease in the production of several positively acting factors because of intron retention ( CD14 , IRAK1 , and IKKβ ) and an increase in production of several negatively acting factors from a variety of mRNA splicing changes ( RAB7b , sTLR4 , and possibly IKKβb ) . Additionally , using qPCR and RT-PCR , we previously demonstrated that SF3a1 inhibition led to an increase in production of the inhibitory splice form MyD88S [26] . All of these changes in positively and negatively acting factors could contribute to the overall decrease in innate immune responsiveness caused by SF3a1 inhibition . To test the effect of several of these candidate negative regulators , we inhibited either of IKKβb , Rab7b , or MyD88S using siRNA and found that all three treatments led to increased LPS-induced IL-6 production ( Fig . 8A ) . To verify that the effect of SF3a on innate immunity was mediated by these various factors , we used siRNA to simultaneously inhibit SF3a1 and these negatively acting isoforms . As described previously [46] , inhibition of MyD88S is able to partially rescue the effect of SF3a1 inhibition on LPS induced IL-6 production ( Fig . 8B ) . Similarly , inhibition of Rab7b or IKKβb with siRNA each led to a small rescue of the effects of SF3a1 inhibition ( Fig . 8C ) , suggesting that the effects of SF3a1 on innate immunity are mediated by altered splicing of multiple TLR signaling pathway genes . We found that LPS stimulation ( Table 1 ) and SF3a1 inhibition ( Table 2 ) both affected alternative pre-mRNA splicing of genes in innate immune signaling pathways . This suggested that specific alterations in the spliceosome may also influence specific effects of LPS on mRNA splicing in macrophages . To test this idea , we compared the lists of genes that were alternatively spliced in the DEXSeq analysis following LPS stimulation or SF3a1 inhibition and found , as expected from the MISO analysis ( Fig . 2 ) , that SF3a1 inhibition induced more alternative splicing events than did LPS stimulation ( Fig . 9 ) . More than half of all SF3a1-dependent alternative pre-mRNA splicing events were in the same 474 genes , regardless of LPS stimulation status ( Fig . 9 ) . A smaller set of differentially spliced genes ( 307 ) , were observed with SF3a1 inhibition alone , and 324 differentially splice genes were unique to the combination of SF3a1 and LPS , consistent with a role for SF3a1 activity in modulating innate immunity regulation . Roughly half of the alternative gene splicing events specific to LPS stimulation alone ( 39/81 ) were also affected by SF3a1 inhibition ( Fig . 9 ) , suggesting that SF3a1 and the spliceosome exhibit some specificity in macrophages for regulating LPS-induced alternative splicing at this level of SF3a1 knockdown .
More than 95% of human genes are alternatively spliced [78–80] , contributing to the complexity of the proteome . Cis-acting mutations that affect splicing of specific genes account for as much as 35% of inherited genetic disease [81–84] . Heritable mutations in splicing genes cause several rare diseases including spinal muscular atrophy , retinitis pigmentosa , Nager syndrome , mandibulofacial dysostosis , and oesophageal atresia [81–83 , 85–94] . Somatic mutations in splicing regulators also have been identified in various malignancies [95–106] . Thus , proper regulation of alternative splicing is critical for normal cellular functions and disease prevention . While there have been reports of alternative pre-mRNA splicing in genes of the TLR signaling pathway , either globally [25] or on a gene by gene basis [15–20 , 23 , 24 , 26 , 107–112] , there has been little study of how this alternative splicing is regulated . Our discovery that the TLR signaling pathway is particularly sensitive to perturbation of the core SF3a and SF3b spliceosome components in mouse and human macrophages [26] has provided an entry point for such a mechanistic study , and the current investigation of SF3a function has confirmed this surprising role of the core splicing machinery in regulation of the TLR signaling pathway in macrophages . As expected , SF3a1 inhibition affected a large number of splicing events , particularly intron retention and exon skipping . We note that these results may be biased as MISO examines only a subset of pre-identified possible alternative pre-mRNA splicing events [47] . Nevertheless , it is clear that when SF3a1 levels are reduced to 20% of their wild-type levels , the vast majority of mRNA splicing events still occur normally . It has been reported that the mRNA splicing machinery is limiting within the cell [113 , 114] , so it is logical to assume that some genes will have splicing regulatory sequences that are more sensitive to spliceosomal perturbation than other genes . This partial specificity is not unexpected , as several studies demonstrate that inhibition or mutation of core splicing factors affects splicing of only a subset of genes [115–125] , although the partial specificity of splicing factors for innate immune signaling pathways has not been noted previously . Moreover , the cis-acting regulatory sequences identified in this analysis are similar to those reported in other studies of the regulation of alternative pre-mRNA splicing [126 , 127] . Presumably in a complete knockout situation , many more mRNA splicing events would be affected . Consistent with this , inhibition of SF3a in HeLa cells affects cell survival [128]; this could reflect the stronger RNAi possible in HeLa cells or could be due to a cell-type specific effect . The possibility of cell-type specific effects of mRNA splicing factors are also raised by the report that SF3a1 functions with human estrogen receptor α to regulate mRNA splicing in other cell types [129] . We found that both LPS stimulation and SF3a1 inhibition affected alternative splicing of a common set of genes in innate immune signaling pathways , suggesting that SF3a1 could play a role in mediating the effect of LPS on alternative pre-mRNA splicing . Inhibition of SF3a1 led to a decrease in production of several positive regulators of TLR signaling ( intron retention in IRAK1 , CD14 , and IKKβ ) ; SF3a1 inhibition also led to an increased production of negatively acting mRNA isoforms of TLR pathway genes ( sTLR4 , MyD88 , Rab7b , and possibly IKKβ ) . Moreover , these negatively acting alternative isoforms are produced by a variety of alternative splicing events ( sTLR4 , exon inclusion; MyD88 , exon skipping; IKKβ , intron retention; Rab7b , gene expression increase ) . Why are these particular splicing events so sensitive to perturbation of the core spliceosome component SF3a1 ? An intriguing possibility is that perhaps , because of their functional significance , the mRNA splice site choices in these genes evolved to be key points of regulation to limit inflammation in macrophages . There is precedent for LPS or other components of pathogens altering the splicing machinery . For example , MyD88 activation in the presence of viral infection can decrease Polypyrimidine Tract Binding Protein ( PTB ) mRNA levels [130] ( although PTB mRNA levels are not affected by LPS stimulation in our RNAseq data ) . LPS has been shown to stimulate phosphorylation of hnRNP A0 , which binds to and stabilizes some cytokine mRNAs [131] . It is possible that LPS treatment could affect the activity of these or other components of the splicing machinery . It is possible that SF3a ( or another component in the complex ) could itself be modified by LPS stimulation . We have performed some preliminary tests to assess this possibility . SF3a1 subcellular localization ( monitored using a SF3a1-GFP fusion ) was not grossly altered following LPS stimulation . SF3a1 mRNA and protein levels did decrease slightly ( to ∼70% of wild type levels ) following LPS stimulation ( monitored using qPCR and western blot ) , although it is unclear what the significance of this moderate decrease is . Conceivably , SF3a1 activity could also be modified by LPS treatment through some covalent modification . Future investigations of these specific splicing events will inform us how this alternate splicing is regulated and if these splicing events are regulated by a single common mechanism or if multiple independent mechanisms regulate alternative splicing in the TLR signaling pathway . Harnessing these regulatory mechanisms to alter mRNA splicing in the TLR signaling pathway could prove to be a useful novel approach to modulate inflammation , thereby treating numerous inflammatory diseases .
The RAW264 . 7 mouse macrophage cell line was transfected with either SF3a1 siRNA or control non-targeting siRNA ( Dharmacon ) using the 96-well shuttle transfection system ( Amaxa ) as described previously [26] . Twenty-four hours later , cells were exposed to either 20 ng/ml LPS ( List Biological labs ) , or not as a control . All RNAi treatments and exposures were performed in triplicate . Four hours after LPS stimulation , the supernatant was removed for ELISA analysis and the cell pellet was lysed in RLT buffer ( Qiagen ) . Total RNA was purified using the RNAeasy kit ( Qiagen ) . A portion of the RNA was set aside for qPCR analysis , and the remainder was purified further for RNAseq . PolyA-RNA was isolated from total RNA using the Dynabeads mRNA Direct Purification kit ( Life Technologies ) . The polyA RNA was then processed for next-generation sequencing ( NGS ) library construction following standard procedures for Ion Proton sequencing using the Ion Total RNA-seq kit for whole transcriptome libraries ( Life Technologies ) . Briefly , library construction proceeded from adaptor ligation , to reverse transcription , cDNA size selection and amplification , and finally bead templating . Once validated , the libraries were sequenced as barcoded-pooled samples on multiple Ion P1 chips using an Ion Proton NGS platform . The RNAseq data presented in this article have been deposited in the Gene Expression Omnibus database ( http://www . ncbi . nlm . nih . gov/geo/ ) under accession number GSE58432 . The gene model used throughout these analyses is based on the Ensembl annotation downloaded July 29 , 2013 , from the UCSC Genome Browser ( http://genome . ucsc . edu/ ) . Sequence reads 30 nucleotides long or greater were mapped to the UCSC release mm10 of the Mus musculus genome using GSNAP version 2013-11-27 ( http://research-pub . gene . com/gmap/ [132 , 133] ) with SNP data version 137 and splice sites compatible with the Ensembl annotation , as well as detection of novel splice sites . With the exception of the Cufflinks/Cuffdiff analysis , only uniquely mapping reads were used for further analysis; multiply-mapped reads without translocations were added for the Cufflinks/Cuffdiff analysis . A separate set of alignments was generated for analysis with MISO , which requires a fixed read length . For MISO , sequences were truncated to 70 nt ( replicate 1 ) or 60 nt ( replicates 2 and 3 ) and shorter reads discarded prior to mapping with GSNAP . Genes with splicing events that differ significantly between treatments were identified with MISO version 0 . 4 . 9 ( http://genes . mit . edu/burgelab/miso/ [47] ) , using version 2 of MISO’s annotation of alternative splicing events for UCSC release mm10 . Because MISO cannot take into account replicates , we treated an event as significantly different between treatments if the change was in the same direction for all three replicates and the Bayes factor of each was at least 1 . Events were considered unchanged between treatments if all three Bayes factors were less than 1 . To identify potential differences in the splice sites of genes with and without changes in splicing , we created sequence logos [134] of those sites with WebLogo version 3 . 3 ( http://weblogo . threeplusone . com/ [135] ) . Based on the logos of the 3′-splice site , we compared the base composition of the polypyrimidine tract region extending from positions −17 to −5 counting from the 3’ splice site . Fractions of each base in each intron of one set ( e . g . introns significantly more retained in SF3a1-depleted cells than in control cells ) were compared to a control set ( e . g . introns that showed no change , regardless of SF3a1 levels ) using the nonparametric Mann–Whitney U-test ( wilcox . test function in the stats package of R version 3 . 0 . 1 [136] ) . For intron-retention events , we compared introns that were significantly more retained when SF3a1 was inhibited to introns whose retention was not altered by SF3a1 inhibition ( as identified by MISO , see above ) . For exon skipping events , we compared 3′-splice site sequence logos for the introns both upstream and downstream of the potentially skipped exon . To determine if exon and intron lengths differed significantly between the various conditions , the nonparametric Mann–Whitney U-test ( wilcox . test function in the stats package of R version 3 . 0 . 1 ) was used . Reads mapping to each gene in the Ensembl annotation were quantified using the htseq-count program from the HTSeq package version 0 . 5 . 4p3 in the “intersection-nonempty” mode ( http://www-huber . embl . de/users/anders/HTSeq/ [137] ) . These counts were analyzed for differential expression with the DESeq package version 1 . 12 . 1 [48] under R version 3 . 0 . 1 , using a false discovery rate ( FDR ) of 0 . 1 . To examine changes in splicing based on differential exon expression , we used the DEXSeq package version 1 . 6 . 0 [49] under R version 3 . 0 . 1 with an FDR of 0 . 1 . Exon counts for this analysis were obtained with the included HTSeq-based script dexseq_count . py and an annotation based on the Ensembl gene model . Cufflinks version 2 . 1 . 1 [50 , 51 , 138 , 139] was used to assemble and quantify transcripts with parameters to mask rRNA and tRNA sequences and enable bias correction and multi-mapped read correction , and without a reference annotation . Other cufflinks parameters were as follows: -j 0 . 1 -A 0 . 05 —overhang-tolerance 5 —max-bundle-length 5 , 000 , 000 . Transcript models from the different samples and replicates were combined using cuffmerge with the Ensembl annotation and the mouse mm10 genome sequence as references . Testing for differences in gene expression and splicing was performed using cuffdiff with bias correction and multi-mapped read correction , as well as masking of rRNAs and tRNAs , using the default FDR of 0 . 05 . Since three replicates were available for each treatment , dispersion was estimated separately for each condition . To determine which pathways were altered by LPS treatment or SF3a1 inhibition , the genes identified in the DEXseq analysis were analyzed using the GATHER utility in network mode [52] or the DAVID utility [53 , 54] . qPCR was performed using the Quantitect SYBR-green RT-PCR assay kit ( Qiagen ) and an ABI 7900 thermocycler . Data was normalized relative to β-actin , whose splicing is not affected by this level of SF3a1 inhibition [26] . Primer sequences used for qPCR are listed in S21 Table . qPCR was performed in triplicate and analyzed with Graphpad Prism 5 using t-tests to determine statistical differences ( p<0 . 05 ) . RAW264 . 7 or J774A . 1 mouse macrophages were tranfected with siRNAs ( Dharmacon , either SMARTpools targeting particular genes or non-targeting control pools ) using the Amaxa nucleofector Shuttle ( Lonza ) as described previously [26 , 27 , 46] . Cells were then plated in 96-well format ( 100 , 000 cells per well ) . Twenty-four hours later , cells were stimulated with 20 ng/ml LPS for six hours , supernatant was collected for ELISA ( R&D Biosystems ) and cell pellets were used to monitor viability with fluorescein diacetate [140 , 141] and lysed in RLT ( Qiagen ) buffer to prepare RNA for qPCR ( which was performed as described above ) . In experiments using two siRNAs simultaneously , siRNA treatments containing only one siRNA were supplemented with a second negative control non-targeting siRNA to render the volumes equivalent . Sequences of the siRNAs targeting IKKβ intron 15 were 5′-AAGCAGAAGUCUCAGGAUA ( UU ) -3′ and 5′-GGGCAGAGUUGCUCCGGAU ( UU ) -3′ . ELISA experiments were performed in triplicate and analyzed using Graphpad Prism 5 using t-tests to determine statistical differences ( p<0 . 05 ) . RAW264 . 7 cells were transfected with either SF3a1-specific siRNA or control non-targeting siRNA as described above . Following the siRNA treatment , cells were lysed on ice in RIPA buffer supplemented with protease inhibitors . Lysates were centrifuged at 12 , 000 RPM for 15 minutes at 4°C , protein concentration of the supernatant was assessed by BCA Assay ( Pierce ) , and samples were boiled in SDS-loading buffer . Samples were separated on 10% SDS-polyacrylamide gels and transferred to nitrocellulose . The membranes were blocked for 2 hours at room temperature in TBS-T containing 5% non-fat milk , incubated overnight at 4°C with primary antibodies ( 1:1000 ) in TBS-T plus 5% BSA ( rabbit-anti-IRAK1 and rabbit-anti-IKKβ antisera were from Cell Signaling Technology; mouse-anti-β-actin antiserum was from Millipore ) , washed in TBS-T , then incubated with HRP-conjugated secondary antibodies ( 1:1000 ) for 1 hour at room temperature . The membrane was then washed , treated with ECL Substrate ( Pierce ) , and fluorescence was captured by autoradiography . Images of the films were captured with a Nikon D200 camera . Bands were quantified using Image J [142] and subsequently analyzed for significant differences in Graphpad Prism 5 using t tests ( p<0 . 05 ) . | Within minutes after we are exposed to pathogens , our bodies react with a rapid response known as the “innate immune response . ” This arm of the immune response regulates the process of inflammation , in which various immune cells are recruited to sites of infection and are activated to produce a host of antimicrobial compounds . This response is critical to fight infection . However , this response , if it is activated too strongly or if it becomes chronic , can do damage and can contribute to numerous very common diseases ranging from atherosclerosis to asthma to cancer . Thus it is essential that this response be tightly regulated , turned on when we have an infection , and turned off when not needed . We are investigating a mechanism that helps turn off this response , to ensure that inflammation is limited to prevent inflammatory disease . This mechanism involves the production of alternate forms of RNAs and proteins that control inflammation . We have discovered that a protein known as SF3a1 can regulate the expression of these alternate inhibitory RNA forms and are investigating how to use this knowledge to better control inflammation . | [
"Abstract",
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"Results",
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"Methods"
] | [] | 2015 | Regulation of Toll-like Receptor Signaling by the SF3a mRNA Splicing Complex |
Photon diffraction limits the resolution of conventional light microscopy at the lateral focal plane to 0 . 61λ/NA ( λ = wavelength of light , NA = numerical aperture of the objective ) and at the axial plane to 1 . 4nλ/NA2 ( n = refractive index of the imaging medium , 1 . 51 for oil immersion ) , which with visible wavelengths and a 1 . 4NA oil immersion objective is ∼220 nm and ∼600 nm in the lateral plane and axial plane respectively . This volumetric resolution is too large for the proper localization of protein clustering in subcellular structures . Here we combine the newly developed proteomic imaging technique , Array Tomography ( AT ) , with its native 50–100 nm axial resolution achieved by physical sectioning of resin embedded tissue , and a 2D maximum likelihood deconvolution method , based on Bayes' rule , which significantly improves the resolution of protein puncta in the lateral plane to allow accurate and fast computational segmentation and analysis of labeled proteins . The physical sectioning of AT allows tissue specimens to be imaged at the physical optimum of modern high NA plan-apochormatic objectives . This translates to images that have little out of focus light , minimal aberrations and wave-front distortions . Thus , AT is able to provide images with truly invariant point spread functions ( PSF ) , a property critical for accurate deconvolution . We show that AT with deconvolution increases the volumetric analytical fidelity of protein localization by significantly improving the modulation of high spatial frequencies up to and potentially beyond the spatial frequency cut-off of the objective . Moreover , we are able to achieve this improvement with no noticeable introduction of noise or artifacts and arrive at object segmentation and localization accuracies on par with image volumes captured using commercial implementations of super-resolution microscopes .
The spatial resolution and definition of the cellular protein matrix is fundamental to the characterization and analysis of cellular function . The accurate resolution of sub-organelle protein localization , in tissue , on a proteomic scale is immensely useful . It is with this in mind that we developed Array Tomography ( AT ) , a proteomic imaging technique . AT uses ribbon arrays of ultrathin ( 50–100 nm ) physical sections of resin-embedded , fixed tissue for multiple rounds of immunohistological detection , which produces a rich , high-dimensional matrix of protein information in an ex-vivo context [1] , [2] . AT allows the collection of 30+ channels of protein information in a cubic millimeter volume of brain tissue [1] , [2] . This information is only useful if we can , with spatial accuracy , localize spatially aggregated protein units within cellular structures and in relation to all other imaged protein channels . This places a premium on the computational segmentation of objects in the image volume , and is highly dependent on resolution and contrast . The axial resolution of AT image volumes is limited only by the physical sectioning , which is 50–100 nm and is far smaller than the diffraction limited axial resolution of most microsocopes ( ∼385 nm ) . However , the lateral resolution of AT image volumes is still limited by the Abbe diffraction limit ( ∼200 nm for visible wavelengths ) [3] , [4] . At that lateral resolution , the segmentation of densely packed proteins , such as Synapsin ( a highly abundant presynaptic protein in the brain ) , is unreliable and difficult . Recently , AT was combined with direct stochastical optical reconstruction microscopy ( dSTORM ) to achieve lateral resolution of ∼40 nm [5] . However , dSTORM imaging is time consuming and requires specialized microscopes . Thus , we investigated deconvolution as a simple and efficient method to improve our resolution in AT . The reason for considering deconvolution is that the physical sectioning of AT provides full removal of out of focus light , and the ideal correction of refractive index , astigmatism , coma , spherical aberration and curvature of field [1] . Moreover , the thinness of the tissue coupled with the direct placement of the sample onto glass also means that the heterogeneity of refractive indexes in normal biological samples is not present , which further eliminates sources of aberration and wave-front distortions . These properties , which are not present in most imaging techniques , allow AT to produces image volumes where the point spread function ( PSF ) is truly spatially invariant throughout , which makes these images an ideal substrate for deconvolution . Deconvolution is a method by which the diffracted light is computationally returned back into its actual source using either an idealized or empirically measured PSF [6] , [3] , [4] . The PSF describes the diffraction of light from a point source . Specimens in the image are blurred by the PSF at a point by point basis . This blurring can be considered a convolution operation on the image [7] , [8] , [3] , if it is linear ( each point source in the image sums their intensity linearly ) and shift invariant ( the PSF is the same for the entire field of view ) . Wide-field is such an imaging systems [8] , although in actual biological tissue the heterogeneity and depth of the tissue volume does introduce aberrations , wave-front distortions and out of focus light contributions that can cause significant deviations in the PSF across the image volume , which adversely affect the quality of deconvolution . This is not the case for AT thin sections where the PSFs are truly spatially invariant . Moreover , it might be easier to appreciate the advantages of thin physical sections by thinking about the analogy to conventional optical sectioning microscopes such as confocals . Confocals achieve optical sectioning by using a pinhole to reject out of focus light . This improves image quality by increasing the collection of high spatial frequency information in the image , but this comes at a cost of reduced signal to noise , due to the rejection of in focus light by the pinhole . AT physically removes all out of focus light sources , which means that AT does not need to use a pinhole for optical sectioning thus allowing it to provide both high signal to noise ( which , in normal confocal microscopy , would be maximized by a large-diameter pinhole ) and measurement of high-frequency spatial information ( which would be maximized by a small-diameter pinhole ) [9] , [3] . The content of high-frequency information in the image is reflected in the bandwidth of the Optical Transfer Function ( OTF ) , which is the Fourier Transform ( FT ) of the PSF . In confocal the OTF bandwidth varies inversely with pinhole diameter [9] , [3] . The OTF determines the actual spatial frequencies transferred to the recorded image . Thus , if the OTF were small at high spatial frequencies ( as is the case for an expanded confocal pinhole or a conventional wide-field setup ) , the high-frequency components of the specimen would be greatly attenuated , causing blurring and decreased resolution . Interestingly , the OTF of a theoretical infinitely-small pinhole would have twice the bandwidth of a standard wide-field OTF [10] , [9] . In AT , we approximate this ideal pinhole with physical sectioning , and combined with the spatially invariant PSF , allow us to perform deconvolution at its mathematical optimum , which should , with the correct algorithm , allow us to greatly increase the magnitude of recovery for high spatial frequency information in the OTF up to the physical bandwidth limit , which is defined by diffraction . Richardson-Lucy deconvolution ( RL ) is a Bayesian based expectation maximizing deconvolution method originally developed for the restoration of images in astronomy [11]–[14] . RL has several advantages for AT images . It assumes the non-negativity of the observations and that the statistic of the associated noise follows a Poisson distribution , which is appropriate for fluorescent images [15] , [13] , [16] . RL is globally and locally intensity-conserving at each iteration [11] , [12] , thus ensuring that intensity data remain quantifiable after deconvolution [13] , [15] . RL is computationally efficient , and the restored images are robust against small errors in the image and the point-spread function ( PSF ) [12] , [11] , [17] , [15] , which makes its real world implementation realistic . Finally , in our tests on AT images , RL significantly out performs other non-Bayesian based deconvolution methods , and has demonstrated a greater than 8 fold increase in the magnitude of spatial frequency recovery up to the diffraction limit , without any measurable introduction of artifact or noise into the images . Moreover , RL in our application demonstrated mathematically a potential for the recovery of spatial frequencies beyond the diffraction limit , which likely contributes to the analytical improvements seen in the analysis of the deconvolved tissue volumes . Thus , the confluence , in AT , of an essentially two-dimensional sample imaged at the optical optimum of the imaging system ( e . g . , minimal spherical aberration , optimal refractive index correction , ideal flatness of field , high signal to noise and a spatially invariant PSF ) [1] , [2] allows AT in combination with RL to achieve volumetric resolution significantly better than the diffraction limit . Using this technique , we demonstrate accurate and clean computational separation of objects in densely labeled tissue volumes .
Two-dimensional RL deconvolution is used to improve the resolution of protein structures . Initial deconvolution trials using ultra-thin sections seeded with 110 nm beads using RL with a high-quality , low-noise empirical PSF ( Figure 1 ) or blind deconvolution using a hypothetical Gaussian as an initial PSF ( Figure 2A ) demonstrated that RL performed significantly better , returning most of the diffracted light back into the central pixel ( 1 pixel = ∼100 nm , 1 . 4NA Oil objective ) . Further tests using RL on volumes of YFP labeled dendrites of Layer 5 pyramidal neurons , imaged in traditional wide-field AT ( ATW ) , demonstrated significant improvements in contrast and the visible recovery of high spatial frequency information in the image , which lead to a dramatic qualitative improvement in image quality ( Figure 2B ) . This qualitative increase in image quality accompanies a quantitative increase in object separation that can be further demonstrated through a simulation of improved point source discrimination by deconvolution of two adjoining points of light ( Figure 3A–D ) . Within a fluorescent image measured intensity from point sources of light sum linearly [3] , [8] . In figure 3 and Figure S1 , two point sources are progressively moved further apart , and it is clear in both the image and the cross-sectional plot that after deconvolution the two point sources start to become visibly separate with only a single pixel between them ( Figure 3B , S1B ) , while in the original image the two points only become noticeably separate with 3 pixels between them ( Figure 3D , S1D ) . This demonstrates a theoretical improvement in resolution that pushes the resolvability of point sources in the image to 1pixel separation or 100 nm in our setup . Although the simulations approximate real imaged objects in a noise free environment , a real world demonstration of improved resolvability is critical . Thus , we imaged in AT a volume of microtubules , and after deconvolution ( Figure 4A–C ) we demonstrated that indeed the resolvability of nearby microtubules , including those that are separated by a single pixel ( Figure 4C ) is improved . Furthermore , the most important aspect of this work is that , because array tomography generates large and information-rich datasets , we need methods of image processing and segmentation that are simple , fast and computationally efficient . Two-dimensional Bayesian based deconvolution significantly improves the performance and accuracy of finding the weighted centers of Synapsin puncta , an abundant presynaptic protein [2] , by a simple 26 neighborhood connected component analysis , in 3D volumes of cortical tissue . ( Figure 4D ) . The apparent improvement of object separation in ATD images requires us to verify this result with imaging of AT ribbons using previously described and commercially available forms of super resolution microscopy . We first compared ATD with Structured Illumination Microscopy ( SIM ) . SIM images the specimen using gratings of several orientations , which creates moiré fringes along the boundaries of the gratings . These moiré fringes provide extra spatial frequency information that can be extracted in Fourier space and used to reconstruct a new image with 100 nm resolution [18] , [19] . We imaged AT ribbon arrays stained and labeled for tubulin , first using a commercial SIM , then using our wide-field AT setup . The result is a direct comparison of SIM , ATW , and ATD images of the exact same tissue volume with the exact same labeling ( Figure 5 ) . Qualitatively , the ATD images and the SIM images are virtually identical , whereas the wide-field AT image appears to have significantly lower contrast and definition ( Figure 5A ) . Furthermore , looking at the intensity profiles of two microtubules running side by side it is clear that SIM and ATD provide similar quantitative separation of the two intensity profiles as well as matching intensity peaks and valleys , which suggest similar localization accuracy ( Figure 5B–C ) . Finally , it is informative to look at the FT of the image volumes in the three modalities , which show that in the ATD and SIM case there is a significant increase in high spatial frequency information as demonstrated by the expansion of the magnitudes in the frequency domain ( Figure S2 ) . Next we compared ATD to Continuous Wave Stimulated Emission Depletion microscopy ( CWSTED ) [20] , which uses an excitation beam that is perfectly aligned with an annular depletion beam that limits the fluorescent release of photons to only a small nanometer size spot in the imaged specimen [21] , [22] , [20] . For this experiment , we were able to achieve 90 nm resolution with CWSTED . We imaged ribbon arrays in CWSTED and AT in a setup similar to the SIM experiments with the exception that instead of tubulin we stained the brain tissue for Synapsin . Again , the CWSTED and ATD images are extremely similar by visual comparison ( Figure 6A , B ) . More importantly , the locations of the calculated centers of mass using CWSTED and ATD are similar , even with the expected jitter caused by the alignment and scaling of images due to the differences in the two imaging setups ( 100× objective with 50 nm pixels for CWSTED and 63× objective with 100 nm pixels for AT ) ( Figure 6C–E ) . A histogram of point to point distances between the modalities shows that the majority of points are within 1 . 5 pixels of each other ( Figure 6F ) . The most striking difference between ATW and ATD in comparison to CWSTED is the number of objects computationally segmented in the image volume using 3D connected component analysis , with ATW lagging CWSTED and ATD due to the poor 3D object separation in the image volume ( Figure 6G ) . Finally , it is of interest to look at the empirical OTFs of the above modalities . More specifically , we are interested in the modulus of the OTF or the Modulation Transfer Function ( MTF ) , which describes the amount of signal power present at each spatial frequency , or more practically , the amount of contrast that can be generated for each spatial frequency and relates directly to the resolvability of that spatial frequency in the actual image . The measured MTF was generated by applying FT to PSFs generated with 100 nm beads imaged at 488 nm wavelength for AT images and single sub-diffraction primary with secondary fluorescent antibodies at 488 nm in CWSTED . The MTF of ATW falls off dramatically as we approach the theoretical cut-off frequency of a 1 . 4NA objective ( Figure 7 ) . The cut-off frequency is described by the equation 2NA/λ ( λ = wavelength , NA = numerical aperture ) . This clearly demonstrates the bandwidth-limited nature of the MTF in AT imaging . Two dimensional blind deconvolution of the ATW images increases the amount of signal at the higher spatial frequencies , but it only serves to bring the MTF edge closer to the theoretical cut-off ( Figure 7 ) . CWSTED's major gain in the MTF is at the higher spatial frequencies and as expected for a super resolution technique it surpasses the cut off value ( Figure 7 ) . The most significant aspect of the ATD MTF is the dramatic increase in modulation at all frequencies within the frequency cut-off . This massive improvement in modulation is the most likely cause of the image improvement seen in ATD , however intriguingly the ATD MTF , like CWSTED was able to extend beyond the frequency cut-off of the objective . The MTF of the actual AT images are bandwidth limited by diffraction , but it appears that in ATD , our deconvolution algorithm has mathematically extended the high spatial frequency information , which does eventually hit a hard limit , that is set by the image pixel size ( 100 nm ) , whereas CWSTED does not ( pixel = 50 nm ) ( Figure 7 ) . Further testing of ATD with 50 nm pixels using a 1 . 6× optivar and the 63× objective revealed that the higher spatial frequency component can be further pushed out approaching CWSTED levels ( Figure 7 ) . While this is a curious result and has interesting implications to the interpretation of our result , this phenomenon has been demonstrated in astronomical imaging . RL , but not blind deconvolution , applied to images with high signal to noise and band-limited OTFs can recover , through analytic continuation in the Fourier domain , frequency information beyond that of the measured object , thus allowing the extension of the MTF beyond the diffraction limit [23]–[25] , [15] . Analytic continuation is a method in complex analysis that allows the extension of the domain over which a function is defined [26] , [23] , [25] , [27] . Analytic continuation requires an original function to be analytic within its domain of definition , and not every complex function is analytic . In essence analytic continuation states that knowing the value of a complex function in some finite complex domain uniquely determines the value of the function at every other point . In image restoration , if a 2D object is compact in the space domain , i . e . , confined within a finite region , its FT is analytic [28] , [29] . In wide-field fluorescence images with diffraction limited OTFs , the image is an analytic function restricted to the pass-band , which analytic continuation maybe be applied to extrapolate it beyond the pass-band [23] , [25] , [30] . In practice , analytic continuation is highly sensitive to noise [26] , [23] , [31] , [32] ( Figure 8 ) , and applied without constraints on real images results in little resolution improvement [33] . However , if we apply the reasonable constraint that all observations in our images are non-negative , which is an intrinsic assumption in RL , significant improvements in resolution can be obtained even with a moderate signal to noise ratio [23] , [16] , [25] . Finally we thought it might be of interest to test whether deconvolution of confocal images from our thin sections would improve our results further , because the confocal PSF is the multiplication of the excitation PSF and the emission PSF , which sharpens the lateral PSF and improves lateral resolution . Empirically we show , as we stated earlier , confocal have better native lateral resolution and spatial frequency capture , as can be seen in its MTFs as compared to ATW ( Figure 9 A , B , E , F ) . Moreover , as one expects , by decreasing the pinhole size the MTF does see an appreciable increase in all spatial frequencies ( Figure 9 A , B , E , F ) . RL deconvolution of confocal images , much like ATD , allowed the extension of spatial frequencies beyond the cut-off limit of the objective , especially when 50 nm pixels were used , and in some cases ( when the pinhole is 1 airy unit ( au ) or smaller ) , RL plus confocal actually out performs ATD ( Figure 9 D , H ) . This suggests that for array tomography , confocal imaging is a viable alternative to wide-field , although the gain in spatial frequency capture and recovery might not outweigh the increased image acqusition time , equipment cost and illumination intensity ( especially , for small pinhole sizes ( < = 1au ) where confocal deconvolution beats ATD ) .
It must be noted that although our comparison of ATD with commercial SIM and CWSTED appear to suggest that ATD images in certain instances can approach the resolution of those techniques , we must caution that ATD is purely a mathematical process based on reasonable , but not perfect assumptions . It does not record extra spatial frequencies as SIM and CWSTED does through the use of deterministic light patterns . Moreover , the proper implementation of RL requires that the algorithm to converge through the iterations [34] , and although in practice applying RL to AT images has always converged , one must be aware that this is a mathematical process that can fail , and the results of any deconvolution must be carefully interpreted . That said , the ideal optical characteristics of ultra-thin ( 50–100 nm ) sectioning ( minimal non-linear aberrations , optimal refractive index correction , ideal flatness of field , high signal to noise and a spatially invariant PSF ) creates optimal circumstances for two-dimensional Bayesian based deconvolution ( RL ) to dramatically improve the MTF of AT images and perhaps even mathematically extend it , thus improving the resolution and computational segmentation of imaged protein structures . Our application of deconvolution , in the AT framework , truly allows RL to shine , because of the ideal data characteristics , which in many ways mimic the astronomical images that RL was originally designed for . Interestingly this does suggest that optical methods , such as evanescent field microscopy , that have extremely fine optical sectioning , could also benefit greatly from RL deconvolution . The combination of deconvolution and AT creates volumetric images of intact tissue with a combination of speed , resolution , coverage and cost that cannot be matched by any other imaging modality . This coupled with the highly multiplexed imaging of proteins that is native to the AT procedure opens the door for the detection of biologically relevant protein localization in intact tissue samples at a scale and detail that will be crucial for understanding the function and dysfunction of biological systems . This spatial proteomic approach , where protein localization is maintained with sub-organelle precision from the in-vivo context can provide an essential piece of information that is missing in traditional proteomic approaches . It has become increasingly clear that the analysis of total expression level of proteins lacks the nuance that will be required to understand function at a complex cellular and systems level . The localization of a protein within a cell in relation to other proteins within its interaction repertoire is as important to the function of that protein as its modification state or its intrinsic structural and catalytic capabilities . The collection and analysis of this data is the information space that is uniquely occupied by ATD . It is this convergence of proteomic breadth with sub-organelle localization accuracy that will allow a much deeper analysis of biological function that can contribute significantly to our understanding of biological processes .
Tissue preparation , array creation and immunohistochemistry are described in detail in previous publications [1] , [2] . In short , a small piece of tissue ( ∼2 mm high by 1 mm wide by 1 mm deep ) , in our case cortical tissue from the somatosensory cortex of the mouse brain , is microwave fixed in 4% Paraformaldehyde . The fixed tissue is then dehydrated in graded steps of ethanol , and then embedded in LR White resin overnight at 50°C . The embedded tissue is section on an ultramicrotome at a thickness of 70 nm and placed as a ribbon array directly on gelatin or carbon coated glass coverslips . Immunohistochemistry is then carried out on the arrays using primary antibodies targeting antigens of choice ( alpha-Tubulin , Abcam ab18251 and Synapsin , Cell Signaling Technology 5297S ) . The primary antibodies are visualized via fluorescently labeled secondary antibodies ( Alexa 594 , Invitrogen A11037 , Alexa 488 , Invitrogen A11034 , and Alexa 647 , Invitrogen A21245 ) , and mounted in SlowFade Gold antifade with DAPI ( Invitrogen ) . Wide-field imaging of ribbons were accomplished on a Zeiss Axio Imager . Z1 Upright Fluorescence Microscope with motorized stage and Axiocam HR Digital Camera as previously described [1] , [2] . A position list was generated for each ribbon array of ultrathin sections using custom software modules written for Axiovision . Single fields of view were imaged for each position in the position list using a Zeiss 63×/1 . 4 NA Plan Apochromat objective . SIM imaging of ribbons were performed on a Zeiss ELYRA PS . 1 super resolution scope using an Andor iXon 885 EMCCD camera . Positions on the ribbons were manually acquired across each section of the ribbon , and each fluorescent channel was imaged with five pattern rotations with 5 translational shifts , using a Zeiss 63×/1 . 46 NA Plan Apochromat objective . The final SIM image was created using modules build into the Zen software suite that accompanies the imaging setup . CWSTED imaging was performed on a Leica TCS SP5 II using Lecia HyD hybrid PMT detectors . Positions on the ribbons were manually acquired across each section of the ribbon , and CWSTED images were acquired with a calibrated 90 nm resolution using a Lecia HCX PL APO 100× 1 . 40NA objective . Confocal imaging was performed on a Zeiss LSM-510 using a Zeiss 63×/1 . 46 NA Plan Apochromat objective . Images of 100 nm beads , seeded on AT thin sections , were acquired using manually set pin-hole sizes ranging from 0 . 5 airy unit to 8 airy unit using either 100 nm pixels or 50 nm pixels . Image stacks from ATW , SIM and STED were imported into FIJI and aligned using both rigid and affine transformations with the Register Virtual Stacks plugin . The aligned image stacks were further registered across image sessions using MultiStackReg . The aligned and registered image stacks were imported into Matlab ( Mathworks ) and deconvolved using the native implementation of Richardson-Lucy deconvolution with empirical or theoretical PSFs with 10 iterations [15] . Custom functions were written to automate and facility this work flow . Blind deconvolution is also natively implemented in Matlab . Matlab native function ( regionprops ) was used to calculate the centers of mass of punctas in the image volumes using 26 neighborhood 3D connected component analyses with an assumed background threshold that is 0 . 1 of the total dynamic range , which is 6553 . 5 for a 16bit image , and is in line with previous background thresholds used for AT analysis [2] . Custom functions were implemented to facility the handling and processing of the data . | Biological function at its fundamental level involves molecular interactions on a nanometer scale , and it is this reason that biological imaging has pushed for increasingly better resolution . Light microscopy is highly prevalent in biology due to its combination of large field of view , simple sample preparation , cost effective usage and relatively high tolerance by biological samples . The problem with light microscopy is that diffraction of light limits the resolution of achievable images to hundreds of nanometers in volumetric space , which is much too low for the accurate localization of proteins in subcellular organelle or structures , such as the synapse of a neuron . Super-resolution light microscopy is now available , but its implementation usually requires technically complex and expensive imaging systems . In this paper , we demonstrate a method that combines physical thin sectioning of tissue with Bayesian based deconvolution of conventional , fluorescent microscopy to achieve volumetric resolution well below the diffraction limit , and that using this method we are able to greatly improve the computational segmentation and localization of labeled proteins in a reconstructed volume of brain tissue . | [
"Abstract",
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] | [
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] | 2012 | Sub-diffraction Limit Localization of Proteins in Volumetric Space Using Bayesian Restoration of Fluorescence Images from Ultrathin Specimens |
Genome-wide association studies ( GWAS ) have identified more than 2 , 000 trait-SNP associations , and the number continues to increase . GWAS have focused on traits with potential consequences for human fitness , including many immunological , metabolic , cardiovascular , and behavioral phenotypes . Given the polygenic nature of complex traits , selection may exert its influence on them by altering allele frequencies at many associated loci , a possibility which has yet to be explored empirically . Here we use 38 different measures of allele frequency variation and 8 iHS scores to characterize over 1 , 300 GWAS SNPs in 53 globally distributed human populations . We apply these same techniques to evaluate SNPs grouped by trait association . We find that groups of SNPs associated with pigmentation , blood pressure , infectious disease , and autoimmune disease traits exhibit unusual allele frequency patterns and elevated iHS scores in certain geographical locations . We also find that GWAS SNPs have generally elevated scores for measures of allele frequency variation and for iHS in Eurasia and East Asia . Overall , we believe that our results provide evidence for selection on several complex traits that has caused changes in allele frequencies and/or elevated iHS scores at a number of associated loci . Since GWAS SNPs collectively exhibit elevated allele frequency measures and iHS scores , selection on complex traits may be quite widespread . Our findings are most consistent with this selection being either positive or negative , although the relative contributions of the two are difficult to discern . Our results also suggest that trait-SNP associations identified in Eurasian samples may not be present in Africa , Oceania , and the Americas , possibly due to differences in linkage disequilibrium patterns . This observation suggests that non-Eurasian and non-East Asian sample populations should be included in future GWAS .
Genome-wide association studies ( GWAS ) have become a popular method for identifying genomic loci that contribute to complex traits [1] . In GWAS , large sample sets of individuals ( now on the order of several thousand ) , whose phenotype for some trait has been assessed , are genotyped for common SNPs . Algorithms are then used to identify SNPs that demonstrate allele frequency differences between cases and controls or between persons representing opposite ends of the phenotypic range ( for continuous traits such as height ) [1] . It remains controversial how often the alleles at these SNPs themselves have direct effects on the phenotype under study; it is likely that in many cases these SNPs instead act as markers linked to the causal genomic variants [2] , [3] . Nonetheless , numerous individual SNPs have significant trait associations in more than one independent GWAS , confirming the association between these SNPs and particular human phenotypes [4] , [5] . As it is increasingly common for complex traits to have been the focus of multiple independent GWAS , it is now possible to discern which SNPs are most likely to have true trait associations and which are likely false positives [5] . Most GWAS are conducted on subjects of European ancestry [6] . As GWAS have reduced power to detect trait associations for SNPs with low minor allele frequency ( MAF ) , this means that most “GWAS SNPs” have a relatively high MAF in Europe [6] . Outside Europe , the allele frequencies of some GWAS SNPs vary considerably . Perhaps the most cited examples of this are the SNPs associated with pigmentation phenotypes , many of which exhibit extreme allele frequency differences between continental groups [7] . Other examples of individual GWAS SNPs with large allele frequency differences between particular pairs of continents have been found , including variants associated with Type 2 Diabetes and Crohn's disease [7] , [8] . However , most individual GWAS SNPs have allele frequency patterns that are indistinguishable from those of random SNPs with no known trait associations [8] , [9] . An understanding of the global allele frequency distributions of GWAS SNPs is important for two reasons . First , the frequency of a trait-associated allele determines to what degree it can contribute to variability in its phenotype in a given population . This is particularly true for SNPs that contribute directly to phenotypic variation rather than tagging causative variants [10] . Second , large allele frequency differences between populations for trait-associated SNPs may indicate that selection has acted upon the trait [8] . Past studies of the allele frequency patterns of GWAS SNPs have tended to be limited to particular human populations or pairs of populations [9] , [11] . Such studies have also tended to focus on SNPs associated with phenotypes thought to be likely targets of selection ( e . g . metabolic diseases like Type 2 Diabetes and resistance to infectious pathogens ) [7] , [8] . Additionally , these studies have examined the allele frequency patterns of individual GWAS SNPs rather than looking for commonalities in the behavior of groups of SNPs associated with a particular trait or identified in a single study [7] , [9] , [11] . Here we examine approximately 1 , 300 GWAS SNPs associated with a wide variety of phenotypes . We explore the allele frequency patterns of these SNPs in 53 globally distributed populations using 4 different statistics . These statistics are calculated for different population groupings in order to detect individual GWAS SNPs and groups of SNPs that exhibit unusual allele frequency patterns on a local and/or global level . While pigmentation SNPs do seem to exhibit the most extreme variations in allele frequency , we found that groups of SNPs associated with blood pressure , infectious disease , and autoimmune disease also differ from random groups of SNPs in their allele frequency distributions .
We analyzed trait-associated SNPs reported by published genome-wide association studies ( GWAS ) and cataloged online by the National Human Genome Research Institute ( NHGRI ) [5] . As of April 1 , 2010 , this database contained 2 , 284 SNPs ( both autosomal and X-linked ) that had reached genome-wide significance in at least one GWAS . These SNPs were associated with a total of 330 traits in 477 different studies ( some SNPs have been identified in multiple studies and some have been associated with multiple traits ) . We investigated these SNPs in the dataset reported by Li et al . [12] , which contains information on 640 , 698 autosomal SNPs genotyped in 938 individuals of the Centre D'Etude du Polymorphism Humaine-Human Genome Diversity Project ( CEPH-HGDP ) collection . These individuals are members of 53 globally distributed populations which can be divided into 8 continental groups [13] , [14] . Of the 2 , 259 autosomal SNPs that we compiled from the NHGRI website , 1 , 336 are found in this dataset . The remainder of this paper will focus mainly on these 1 , 336 SNPs , 592 of which were identified in more than one GWAS ( see Methods ) . The full set of 1 , 336 GWAS SNPs and this subset of 592 ( which we will refer to as “independently identified SNPs” ) are handled separately in the analyses below . Before beginning our primary analyses , we calculated the minor allele frequencies ( MAFs ) in Europe of all autosomal SNPs from the Li et al . [12] dataset ( see Methods ) . GWAS studies have more power to detect trait-SNP associations for SNPs with high MAF [1] , so GWAS SNPs are expected to have a higher average MAF in Europe than the remaining SNPs in our dataset ( see Text S1 , Figure S8 , and Figure S9 ) . This is indeed the case; we found that there were proportionally more GWAS SNPs in all high MAF bins ( Figure 1A ) . GWAS SNPs are also expected to differ from the other SNPs in our dataset in terms of their linkage disequilibrium ( LD ) relationships with neighboring SNPs ( see Text S1 , Figure S8 , and Figure S9 ) . SNPs that are in high LD with their neighbors “tag” larger regions of the genome than do SNPs that are not in LD with surrounding variants . Because of this , the former are more likely to tag a region of the genome containing a causative variant for a particular GWAS trait . To quantify LD in our dataset , we calculated an “LD score” ( see Methods ) for all 640 , 698 autosomal SNPs . Again we found that GWAS SNPs differ from the remaining SNPs in the dataset in that proportionally more GWAS SNPs were found to be in high LD with neighboring SNPs ( Figure 1B ) . We used 3 statistics to characterize SNP allele frequency distributions across the 53 CEPH-HGDP populations: ( i ) delta values , which represent the difference in allele frequency between two continental groups or populations , ( ii ) group Fst values , which reflect the variation in allele frequency among populations in a group of populations , and ( iii ) correlations with longitude and latitude ( we will refer to these as latitude/longitude correlation or “LLC” scores ) , which assess how closely changes in the allele frequency of a SNP follow geographical coordinates . We also used a fourth statistic , iHS [15] to characterize the lengths of the haplotypes surrounding each allele of a SNP . We chose to use iHS rather than other statistics that indicate genomic regions which may have been subject to past selection , because previous studies [8] , [9] have found few GWAS SNPs with large allele frequency differences between populations ( with the notable exception of pigmentation SNPs ) . This suggests that the selective sweeps affecting GWAS SNPs are likely to have been weak or incomplete ( see Text S2 ) . Such sweeps are more effectively detected by iHS than by other selection statistics [15] . We calculated each of these four statistics for the pairs and groups of populations listed in Table 1 . For clarity , we will refer to a delta , Fst , LLC , or iHS value calculated for a particular population or populations as a “measure” or “score” . We used these measures of allele frequency and haplotype length to compare GWAS SNPs to SNPs from the CEPH-HGDP dataset in three different ways . First , we assigned a p-value to each individual GWAS SNP by comparing its value for a particular allele frequency measure or iHS score to the values of other SNPs from our full set of 640 , 698 autosomal SNPs . These “other SNPs” were similar to each GWAS SNP in terms of MAF and LD score ( see Methods for full details ) . For each delta , Fst , LLC , and iHS measurement , SNPs with sufficiently extreme p-values were deemed significant ( see Table 2 for significance criteria and Table 3 and Table 4 for SNPs with significant p-values ) . We will refer to this first phase of the analysis as the “individual SNP analysis” . Next , we divided our 1 , 336 GWAS SNPs into groups based on the GWAS study that reported their trait association ( some SNPs were in multiple groups if they were identified in more than one study ) . These “study groups” were then “pruned” by removing one SNP of any pair that were less than 1MB apart; the remaining SNP was the one with the smaller association p-value in the relevant GWAS . Our objective in carrying out this pruning process was to have in each study group one SNP ( the one with the most significant trait association ) representing each trait-associated genomic region . Groups with only one SNP remaining after this process were removed from consideration in the following analysis . For each delta , Fst , LLC , and iHS measure , each group was assigned a score based on the measure values of all SNPs in the group . As our group size ranged from n = 2 to n = 51 SNPs , we created an empirical distribution for each measure and each group size n ( see Methods ) . We used these empirical distributions to assign to each group a p-value for each measure . Finally , we used the NHGRI website [5] to determine which allele was the risk allele for 1 , 041 of our GWAS SNPs ( the risk allele for GWAS SNPs is not always identified ) . We were then able to assign a signed value for all of our delta , LLC , and iHS measures to these 1 , 041 SNPs ( see Methods ) . SNPs were again grouped according to the study that identified them and we again created empirical distributions for each measure and each group size ( see Methods ) . To distinguish between the two types of group analyses , we will refer to the first as the “unsigned group analysis” and to the latter as the “signed group analysis” . In the individual SNP analysis , three SNPs were significant for one or more delta , Fst , LLC , or iHS measure . These three - rs28777 , rs1834640 , and rs12913832 – were all associated with pigmentation traits in GWAS ( see Table 3 for a complete list of SNPs with significant p-values ) . A total of 8 groups reached significance for at least one measure in the unsigned group analysis while 10 reached significance in the signed group analysis . Included among these 10 were 3 pigmentation study groups that were significant in both analyses . We observed three other study groups that were significant in both analyses: an obesity study group [16] containing SNPs whose allele frequencies were significantly correlated with latitude in Eurasia , a hypertension study group [17] whose SNPs were associated with latitude in Africa , and a study group containing SNPs that are associated with the rate of AIDS progression [18] that produced high iHS scores in Europe . Other study groups were significant only in the unsigned or signed group analysis . SNPs in a psoriasis study group [19] produced high Fst scores in the African Agriculturists in the unsigned analysis , while a study group of SNPs associated with lung adenocarcinoma [20] and another containing SNPs associated with response to treatment for acute lymphoblastic leukemia ( ALL ) [21] were significant only in the signed analysis . SNPs and study groups associated with pigmentation and immunological traits made up a majority of those that reached significance in our analysis . To test whether any of these general trait categories were enriched for SNPs producing large delta , Fst , LLC , or iHS scores , we divided the GWAS SNPs into 18 groups based on the trait with which they were associated . These 18 groups , which we will call “trait classes” , are listed in Table S1 . For each of the 128 lists of p-values ( there are a total of 45 delta , Fst , LLC , and iHS measures each in the individual SNP and unsigned group analyses and 38 total measures in the signed group analysis ) , we identified trait classes with a large number of SNPs or study groups with p-values less than or equal to 0 . 05 ( see Methods for details and Figure S1 for full results ) . For the individual SNP analysis , there were a large number of delta , Fst , LLC , and iHS measures ( 12 and 9 , respectively ) for which pigmentation and autoimmune disease SNPs were over-represented in the top 5% of the empirical distribution . Pigmentation SNPs tended to produce low p-values for delta , Fst , and LLC measurements involving Eurasian and East Asian populations while autoimmune disease SNPs produced high iHS scores and correlated well with latitude on several continents . Pigmentation study groups had low p-values for many of the same delta , Fst , LLC , and iHS measures in the unsigned and signed group analyses . The measures for which autoimmune disease SNPs/study groups had low p-values varied somewhat across the phases of analysis , but in all phases they tended to produce high iHS scores . Blood pressure SNPs and study groups were also over-represented in the top 5% of the empirical distribution for 10 measures in the individual SNP analysis and 8 measures in the unsigned group analysis . These measures included several Eurasian and East Asian delta , Fst , and iHS measures , but blood pressure SNPs also had high scores for measures assessing allele frequency correlation with latitude in Africa . Blood pressure study groups did not have particularly low p-values for any measures in the signed group analysis; this may have been due to the small number of blood pressure study groups considered in this particular phase of the analysis . Several other trait classes were notable in two of the three phases of analysis . In the individual analysis and the signed group analysis , the SNPs/study groups of the infectious diseases trait class had low p-values for iHS scores in the Middle East ( iME ) , East Asia ( iEA ) , and Oceania ( iOceania ) and for measures of allele frequency correlation with latitude in East Asia ( LEALat and LEurasiaEALat ) . Additionally , the metabolic trait class ( which includes weight and Type 2 Diabetes study groups ) produced low p-values for a number of measures in both the unsigned and signed group analysis , although the measures varied between analyses . We repeated all our above analyses focusing only on the 592 GWAS SNPs that were reported in more than one study ( see Methods for details ) . We will call these 592 SNPs “independently identified” or II SNPs . The results were quite similar to those for the full set of 1 , 336 GWAS SNPs with a few exceptions ( Table 4 ) . A number of study groups included in our initial analysis were not considered here because they contained fewer than two II SNPs . Included among these was the hypertension study group [17] whose SNPs significantly correlated with latitude in Africa ( LAfricaLatDE ) . However , we found that two other blood pressure study groups containing SNPs associated with diastolic blood pressure ( DBP ) [17] , [22] were significant for at least one measure in our II unsigned group analysis . Both of these DBP study groups were significant for allele frequency difference between Europe and Central Asia ( DEuropeCA ) and one was significant for allele frequency correlation with latitude in Eurasia ( LEurasiaLat ) . Again for each delta , Fst , LLC , and iHS measure , we looked for trait classes containing a large number of SNPs or study groups with p-values ≤0 . 05 . Although the number of study groups in some trait classes was quite small for the II analyses , the results were still similar to those from our analysis of all GWAS SNPs . The pigmentation and blood pressure trait classes again produced low p-values for more delta , Fst , LLC , and iHS measures than did the other trait classes in the individual SNP and unsigned group analyses . In one departure from previous observations , blood pressure study groups also produced low p-values for a number of measures in the signed group analysis . Additionally , we noted that in the II unsigned group analysis , study groups of the hematological trait class produced low p-values for a number of iHS and LLC measures in Eurasia and East Asia . Overall , our analyses indicate that SNPs associated with pigmentation , blood pressure , and autoimmune disease have unusual allele frequency distributions ( or elevated iHS scores ) relative to random SNPs; to a lesser degree , this is also true for SNPs associated with infectious disease , metabolic , and hematological traits . There was considerable variability across p-value distributions for different delta , Fst , LLC , and iHS measures . In particular , GWAS SNPs generally seem to produce smaller p-values for measures involving Eurasian and East Asian populations ( Figure 2 , Figure S2 , and Figure S3 ) . This holds across all 6 p-value sets ( one set for the individual SNP , unsigned group , and signed group analyses for both the full set of 1 , 336 GWAS SNPs and the subset of 592 II GWAS SNPs ) although there are some exceptions . Most notably , the proportion of GWAS SNPs/study groups with p-values ≤0 . 05 for Fst among American populations ( FAmerica ) and for the correlation of allele frequencies with latitude ( LAmericaLat ) , distance from the equator ( LAmericaLatDE ) , and longitude ( LAmericaLong ) in America is quite high for some sets of p-values . As pigmentation SNPs often have low p-values for Eurasian and East Asian delta , Fst , LLC , and iHS measures , we re-evaluated all p-value sets after removing pigmentation SNPs and study groups from consideration . The proportion of SNPs/study groups with p-values ≤0 . 05 was somewhat diminished for certain Eurasian measures , especially delta values comparing Eurasian and East Asian populations . However , non-pigmentation SNPs and study groups still tended to produce smaller p-values for Eurasian and East Asian delta , Fst , LLC , and iHS measures relative to other measures . Although GWAS once focused almost exclusively on individuals of European ancestry , studies are now being conducted on cases and controls from other human populations . We reviewed all 477 GWAS studies and found that 375 used only European subjects ( see Methods ) , 24 used only East Asian subjects , 2 used only Oceanic subjects , one used only African subjects , and one used only Native American subjects . The remaining studies used either subjects from multiple continents or used human populations that were the product of recent admixture ( for example , Hispanic-American individuals ) . We compiled a list of all GWAS SNPs and study groups from studies using only European subjects ( we will call these “European GWAS SNPs/study groups” ) and a list of all GWAS SNPs and study groups from studies using only East Asian subjects ( we will call these “East Asian GWAS SNPs/study groups” ) . We used these to determine whether there were any measures with a large number of East Asian GWAS SNPs/study groups with p-values in the top 5% of the empirical distribution ( see Methods and Figure S4 for complete results ) . We found that this was true for East Asian GWAS study groups for American LLC measures in the group analyses . We also compared the p-values of European and East Asian GWAS SNPs/study groups for each for delta , Fst , LLC , and iHS measure using an unpaired Wilcoxon test ( see Methods and Figure S5 ) . East Asian GWAS SNPs/study groups produced lower p-values ( significant at the 0 . 05 level ) for all three American LLC measures . East Asian GWAS SNPs and study groups also tended to produce lower p-values than European GWAS SNPs/study groups for FAmerica as well as for the delta measure comparing allele frequencies between the Biaka and Mbuti Pygmies ( DPygmy ) . European GWAS SNPs and study groups produced lower p-values than East Asian GWAS SNPs/study groups for the two measures of allele frequency correlation with latitude across all 53 CEPH-HGDP populations ( LWorldLat and LWorldLatDE ) . Finally , we examined individual studies that used European and East Asian samples to determine the relationship between the SNPs associated with a particular trait in studies using individuals from different continents . Are the SNPs associated with Trait X in a European study the same as those identified in an East Asian study ? Among the GWAS that used East Asian subjects , we identified four that focused on height [23]–[26] , four that focused on Type 2 Diabetes ( T2D ) [27]–[30] , and two that focused on Systemic Lupus Erythematosus ( SLE ) , commonly called Lupus [31] , [32] . We listed all SNPs associated with height in any study on the NHGRI website [5] ( regardless of the ethnicity of the study subjects ) . We then identified genomic regions containing a “hit” in more than one GWAS ( see Methods ) . There were 26 such regions , two of which were associated with height only in GWAS that used exclusively East Asian samples . We then calculated minor allele frequencies for the SNPs contained within these regions and found that although the MAFs of these SNPs were fairly high in East Asia ( 16%–27% ) , they all fell to less than 5% in Europe , except in one case . We made a similar observation for T2D and SLE . In both of these cases , we found only one region that was associated with T2D and SLE , respectively , in GWAS using only East Asian samples . For T2D , this region , on the short arm of chromosome 11 , contained SNPs with a MAF range of 3 . 8% to 5 . 1% in Europe . The SLE region , on the long arm of chromosome 11 , also contained SNPs whose MAFs were smaller in Europe than in East Asia , although in this case the European MAFs were all about 11% . Conversely , we find that genomic regions associated with height , T2D , and SLE by GWAS using only European subjects often contain SNPs with relatively high MAFs in East Asia ( see Figure S6 ) . Of the 2 , 284 SNPs reported by the NHGRI website to be trait associated , 26 were located on the X chromosome . 21 of these , associated with traits like height , prostate cancer , LDL cholesterol , and Type 1 Diabetes ( T1D ) , were also found in the CEPH-HGDP dataset . We calculated our delta , Fst , LLC , and iHS measures for these SNPs and used the 16 , 297 X-linked SNPs from Li et al . [12] to construct an empirical distribution for each measure ( see Methods and Figure S7 for details pertaining to MAFs and LD scores for X-linked SNPs ) . The Bonferroni-corrected p-value cut-off for significance at the 0 . 05 level was 2 . 38×10−3 ( since there were 21 X-linked SNPs ) . Table 5 lists all X-linked SNPs that were significant for at least one of our measures . Two out of the 21 X-linked GWAS SNPs were associated with HIV/AIDS Progression by Fellay et al . [33] . As these two SNPs are separated by 45MB on the long arm of the X chromosome they are unlikely to be in linkage disequilibrium with one another . However , both SNPs , rs17324272 and rs12012519 , were significant for the measure assessing allele frequency correlation with longitude in Eurasia and East Asia ( LEurasiaEALong ) . rs17324272 was also significant for LEALong and for iHS in East Asia ( iEA ) . Overall , these two SNPs have p-values less than 0 . 05 for many delta measures comparing allele frequencies between the continents of Eurasia and East Asia as well as many measures of allele frequency correlation with longitude in Eurasia and East Asia . An X-linked height SNP , rs1474563 [34] , was also significantly correlated with latitude in Europe ( LEuropeLat ) . Paralleling our autosomal results , this SNP was also the X-linked GWAS SNP with the largest allele frequency difference between the two Pygmy groups; previously , we noted that a height SNP produced the largest value for DPygmy out of all 1 , 336 autosomal GWAS SNPs in the CEPH-HGDP dataset . Of all the trait-associated X-linked SNPs , rs1474563 also had the largest allele frequency difference between the Eurasian continents and East Asia and the highest Fst scores among the African Hunter-Gatherers , African Agriculturists , Europeans , and Eurasians .
The NHGRI Catalog [5] includes studies on a total of 14 pigmentation traits; we identified 6 of these as having associated SNPs or study groups that were significant for at least one delta , Fst , LLC , or iHS measure . We listed all SNPs identified as being associated with at least one of the 14 pigmentation phenotypes and found that the majority of these SNPs fell into one of 7 genomic clusters , each of which is associated with a known pigmentation gene – SLC45A2 , IRF4 , TYR , SLC24A4 , HERC2 , MC1R , and ASIP . ( As the focus of our work is specifically on GWAS and the SNPs they have identified , only pigmentation genes associated with GWAS hits are included in our discussion here . ) Numerous previous studies have found evidence for selection at loci associated with pigmentation [15] , [40]–[50] . The majority of this evidence has been found in European populations , but there have also been reports of selection at pigmentation loci in East Asian and African populations [41] , [45] , [47]–[50] . In our work , we noted that pigmentation SNPs and study groups produced low p-values ( p-values ≤0 . 05 ) for three types of measures: delta values comparing different Eurasian populations , Eurasian Fst measures ( FEurope and FEurasia ) , and LLC measures assessing allele frequency correlation with latitude in Eurasia . There were almost no cases where a pigmentation SNP or study group had a p-value less than or equal to 0 . 05 for a measure not involving Eurasians . Variation in pigmentation phenotypes is certainly not limited to Eurasians nor is there any reason to believe that selection on loci associated with pigmentation would be limited to Eurasia . However , our results indicate that SNPs associated with pigmentation in GWAS display unusual allele frequency patterns almost exclusively in Europe , the Middle East , and Central Asia . This suggests to us that there may be SNPs , perhaps in or near genes other than SLC45A2 , IRF4 , TYR , SLC24A4 , HERC2 , MC1R , and ASIP , which are associated with pigmentation in non-Eurasian populations , but which have yet to be identified by GWAS . GWAS for pigmentation traits carried out using non-European subjects are needed to explore this possibility further . Allele frequencies for functional variants in 5 genes associated with blood pressure – AGT , GNB3 , ADRB2 , SCNN1α , and SCNN1γ – have previously been shown to be correlated with latitude; specifically , alleles conferring higher blood pressure seem to decrease in frequency with distance from the equator [51] , [52] . This pattern may be due to selection favoring lower blood pressures in cooler climates following the out of Africa migration [51] , [52] . Although none of the blood pressure SNPs included in our study are close enough to any of these five genes to be in linkage disequilibrium with them , we observed that two blood pressure study groups were significant for measures assessing allele frequency correlation with latitude – a hypertension study group [17] containing SNPs whose allele frequencies correlated with distance from the equator in Africa ( LAfricaLatDE ) in both the unsigned and signed analyses , and a diastolic blood pressure study group [17] that contained SNPs whose allele frequencies correlated with latitude in Eurasia ( LEurasiaLat ) in the unsigned analysis . We reviewed the results of the unsigned analysis and found that 4 out of 5 total blood pressure study groups had p-values less than 0 . 05 for LEurasiaLat and 3 out of 5 had p-values less than 0 . 05 for LWorldLat . We then reviewed all II blood pressure SNPs individually and found that 7 out of 8 of them had p-values less than 0 . 1 for LEurasiaLat . However , in Eurasia the frequency of the allele associated with higher blood pressure is not always negatively associated with latitude . One of the blood pressure SNPs whose risk allele for higher blood pressure is positively correlated with latitude in Eurasia is rs3184504 , a non-synonymous SNP in SH2B3 . The rs3184504 T allele , which is associated with increased blood pressure , was recently shown to cause increased cytokine production [53] and is believed to have experienced positive selection in Europe in response to an infectious disease [22] , [53] . Of the 8 risk alleles for II blood pressure SNPs , this is the only allele that is strongly positively correlated with latitude across all 53 HGDP populations . Most of the remaining risk alleles are negatively correlated with latitude when all 53 HGDP populations are considered , much like the risk alleles in AGT , GNB3 , ADRB2 , SCNN1α , and SCNN1γ [51] . rs3184504 was also the only II blood pressure SNP where there was strong selection in Eurasia in favor of the risk allele as measured by iHS . Overall , we observed that allele frequencies at blood pressure SNPs are often highly correlated with latitude , especially in Eurasia , although the risk allele for higher blood pressure is not always negatively associated with latitude . This may be due to the pleiotropic effects of blood pressure SNPs on other traits , as could be the case with rs3184504 . Polymorphisms with effects on the immune system are thought to be under selection in many organisms including primates [54] . In human-specific genome-wide scans for selection , more than 300 immunological genes have been “hits” and when only those genes involved in recent sweeps are considered , immunity genes are over-represented relative to genes with other functions [55] . Many focused studies of individual or groups of immunological genes have also found patterns of genetic variation consistent with the effects of selection [56]–[75] . Included among these studies are many investigations of loci associated malaria resistance [60]–[65] . Some of these studies focus on genes like G6PD [61] , HBB [64] , and DARC [62] , [63] , which are associated with protection from malaria but may not be typically thought of as immunological genes . In much the same way , genes generally associated with immune function and those associated with autoimmune and infectious diseases by GWAS are not necessarily the same thing . 384 immunity-related genes have either been hits of genome-wide selection scans or have been identified as under selection since the human-chimpanzee split [55] . Of the 258 autoimmune and infectious disease SNPs that we considered here , only 16 were in any of these genes and only a further 88 were within 1 MB of any of them . Despite this , we identified one infectious disease trait and one autoimmune disease trait whose associated variants consistently produced elevated measure scores . We also observed that infectious and autoimmune disease SNPs had generally elevated scores for many different measures ( Figure S1 ) . This suggests either that selection on autoimmune and infectious disease traits may commonly influence genomic loci not typically associated with immunity or that there may be selection acting on immunity-related loci that has not been detected by previously applied methods . Although HIV has caused significant mortality in humans for less than 50 years , alleles at some variants associated with resistance to HIV infection and delayed disease progression , most famously the CCR5-Δ32 deletion , are thought to have experienced selection in the past due to their protective role against other infectious diseases [66] , [67] , [76] . We found a study group containing SNPs associated with HIV/AIDS progression [18] that was significant for iHS in Europe in both unsigned and both signed analyses . This is not particularly surprising as both SNPs in this study group are located close to the HLA region on chromosome 6 , which is thought to be strongly affected by selection in many populations including Europeans [57]–[59] . More notable perhaps are our results for two X-linked SNPs associated with HIV/AIDS progression by Fellay et al . [33] . Although separated by more than 40MB on the long arm of the X chromosome , the allele frequencies of both variants were found to be significantly correlated with longitude in Eurasia and East Asia ( LEurasiaEALong ) , while rs17324272 was also found to be significant for LEALong and for iHS in East Asia ( Figure 3 ) . Another X-linked variant , rs5968255 , which is located nearly 4MB from rs17324272 , was not included in our original analyses , but was found to be associated with HIV viral load in another study by the same authors [77]; we calculated its p-value for LEurasiaEALong to be 6 . 136×10−5 , far below the significance cutoff for our X chromosome analysis . All three X-linked SNPs had low p-values for many of the measures assessing correlation of allele frequencies with longitude in Eurasia and East Asia , for iHS in East Asia , and for delta measures comparing Eurasian , American , and Oceanic populations with East Asian populations . The study group containing the autosomal SNPs identified by Fellay et al . [33] was found to have low p-values for many of the same measures in the unsigned group analysis . These measures include iHS in East Asia , for which the Fellay et al . [33] study group had the lowest p-value out of all 270 groups , 8 . 65×10−4 , even though only one out of the 19 SNPs in this study group is located in the HLA region ( Figure 3 ) . This evidence suggests that variants associated with HIV viral load and progression may be collectively under selection across the Eurasian continent , particularly in East Asian populations . As with the variants associated with characteristics of HIV infection , SNPs associated with autoimmune diseases may have experienced selection due to their interactions with infectious pathogens . The hygiene hypothesis postulates that the same alleles that bolster the immune system in the presence of infection may lead to autoimmune disease in its absence [78] . This hypothesis is supported by the findings that risk alleles at autoimmune disease variants are sometimes protective against infectious disease [79] and that the frequencies of some of these risk alleles are positively correlated with pathogen diversity [78] . We found evidence among our results to support the idea that some risk alleles for autoimmune disease have experienced positive selection in the past . In particular , many of the SNPs associated with psoriasis in four different GWAS studies produced high iHS scores for all continents except Oceania and America; the longer haplotypes centered at these loci were almost always associated with the psoriasis risk allele ( Figure 4 ) . As a result of this , at least one ( and often both ) of the two psoriasis study groups [80] , [81] included in the signed group analysis of all 1 , 336 GWAS SNPs had a p-value ≤0 . 05 for iBantu , iME , iEurope , iCA , and iEA . While psoriasis has been associated with loci in the HLA region , neither of these two study groups included an HLA SNP . iHS scores for a psoriasis-associated HLA SNP from a third study [19] indicated that selection on this locus also tends to favor the psoriasis risk allele in Africa , Eurasia , and East Asia ( Figure 4 ) . In addition , we observed that one psoriasis study group [19] was significant for Fst among African Agriculturists in both unsigned group analyses; this indicates that the force which led to the elevated iHS scores for psoriasis SNPs in the Bantu may have caused large differences in allele frequencies at the same SNPs between the Bantu , Mandenka , and Yoruba . Of the 16 autoimmune diseases that have been examined by GWAS , psoriasis produced the highest iHS values for the highest number of continental regions . At least one psoriasis study group had a p-value ≤0 . 05 for iBantu , iME , iEurope , iCA , and iEA in the signed group analysis of all 1 , 336 GWAS SNPs . In each case , the longer haplotypes around the SNPs in these study groups were associated with the risk allele . We reviewed the signed group analysis of all 1 , 336 GWAS SNPs for other autoimmune disease study groups and found ten other instances where such a study group had a p-value ≤0 . 05 for an iHS score . In all 10 cases , the group iHS value indicated that longer haplotypes were associated with the risk allele for the disease . We also reviewed the iHS scores produced by individual SNPs associated with autoimmune disease . For each continent , we found that a considerable proportion of these SNPs produce high iHS scores ( Figure 5A ) . In the majority of these cases , the risk allele is associated with a longer haplotype than the protective allele ( Figure 5B ) . Overall , our findings suggest there could be a general trend which extends across continents for selection at autoimmune disease GWAS SNPs in favor of risk alleles . In addition to identifying traits that were consistently associated with low p-values , we also noticed that GWAS SNPs/study groups tend to have higher empirical p-values for measures involving Africa , Oceania , and the Americas . This trend is particularly notable for iHS score ( Figure 2 and Figure S3 ) . For all analyses , with or without pigmentation SNPs , a smaller percent of GWAS SNPs and study groups have p-values ≤0 . 05 for iBantu than for any other iHS score . More GWAS SNPs and study groups have p-values ≤0 . 05 for iOceania and iAmerica than for iBantu , but these percentages are still consistently less than observed for iME , iEurope , iCA , and iEA . Assuming that direct or indirect association with a trait does indeed increase the probability that a SNP will be influenced by selection , we would expect that more than 5% of GWAS SNPs/study groups would fall into the top 5% of the empirical distribution for an iHS score . LD patterns vary between human populations , so that a SNP linked to a causative variant in Europe may not be linked to that causative variant elsewhere , especially in Africa where LD patterns vary widely within the continent as well as differing from those of non-African populations . The majority of GWAS SNPs were identified as being trait-associated in European subjects; in African and to a lesser extent in Oceanic and American populations , GWAS SNPs may be unlinked to causative variants , which might lower the probability that they would be affected by selection . If this is the true explanation for our observations , then SNPs identified by GWAS using Eurasian subjects and by those using non-Eurasian subjects may not be the same . Given the limited number of GWAS studies with non-European subjects , we were only able to test this hypothesis directly by comparing European and East Asian GWAS studies . We found that at least for height , T2D , and SLE , GWAS studies done in Europe and in East Asia tend to identify the same genomic regions . However , as roughly similar numbers of GWAS SNPs/study groups have p-values ≤0 . 05 for iEurope and iEA , this is not surprising . Further GWAS studies in non-European populations are needed to ascertain if trait-SNP associations are generally universal or if they instead vary considerably from one human population to the next . Despite our broad-based approach , we found only a few examples of what may be a polygenic response to a single selective pressure . We did use stringent significance criteria which might mean that additional examples can be found among the study groups that did not quite meet our threshold of significance . It may also be that there is something about “GWAS” traits and their underlying genetics that served to undermine our approach . First , it is likely that the common SNP variants that we have studied here do not themselves contribute to phenotypic variation . Rather , it is usually assumed that these genotyped variants are in high LD with common causative variants [3] . If this were generally the case , we would expect our approach to still be sound , although as the LD decreases between the two common variants the population structure of the causal variant might not be fully transmitted to the genotyped variant . However , there has been much speculation lately about the importance of rare variants in human phenotypic variation [2] , [3] , [82] . Goldstein and colleges [2] , [3] have demonstrated that causative rare variants tend to be associated with one allele of nearby common variants , creating the appearance that these common alleles themselves are associated with a trait . The authors call these “synthetic associations” . Specifically , they think that common variants may be linked to small clusters of rare causal variants [2] , [3] . If this is the case , it seems unlikely that the population structure of a cluster of rare variants could be fully characterized by a single linked common variant . That is , it is quite possible for any or all the rare variants in such a cluster to have a high Fst score or clinal pattern which is not reflected in the common variant . iHS might be an exception to this . Rare copy number variants may also play an important role in human phenotypic variation [83]; we would expect them to affect our analysis in much the same way that rare SNPs would . Second , even if common variants alone , whether they are the genotyped variants themselves or in LD with genotyped variants , are responsible for variation in GWAS traits , our approach may be undermined by other features of the genetic architecture of these traits . Specifically , epistasis may be widespread among polymorphic sites in the human genome and can be difficult to detect , particularly as the number of putatively interacting loci considered increases . Epistasis has been frequently found to exist between loci in model organisms like flies and mice [84] , [85] . Additionally , its effects can be larger than and in the opposite direction as the individual effects of the interacting loci [84] . It may also be quite possible that many , even most , GWAS SNPs are associated with more than one trait . Like epistasis , pleiotropy has been found to be common for variants influencing complex traits in model organisms [84] , [85] and we found multiple instances of it in the dataset that we studied here . The presence of epistasis and pleiotropy can mean that the response of a variant to selection is dependent on the genetic background and the existence and strength of selection on other traits , complexities we did not account for in our analysis . Lastly , the type of selection acting on GWAS traits may not be well detected by our methods . Some of these traits may simply be limited in their fitness effects , with little or no selection acting on them . Alternatively , GWAS traits may be influenced primarily by balancing or negative selection . If this selection is fairly uniform across environments , our measures would likely not detect it ( see Text S2 ) . Also , if negative or balancing selection is particularly widespread in the human genome , any variant experiencing this selection would likely not have reached our stringent significance cutoff given the large number of other variants that would have attained similar measure values . Recent work has proposed negative selection as one explanation for what appear to be common non-neutral patterns of variation in the human genome , such as the elevation of Fst values in genes and the reduction of diversity at sites linked to coding and regulatory regions [35] , [86]–[88] . Overall , our analyses may have been limited by two factors that are not yet well understood: the type and strength of the selection acting on GWAS SNPs and the underlying genetic architecture of GWAS traits . Theory predicts that these two factors are , in fact , interrelated as the nature of the selection on a trait can shape the allele frequency spectrum of causative variants [38] , [39] . Conversely , it has been proposed that an understanding of allele frequencies of causative variants may be the best way to empirically discern the nature of the selection acting on a trait [38] , [39] . Are there any clues in our results as to the nature of selection on GWAS SNPs or to the architecture of GWAS traits ? More than 5% of all GWAS SNPs commonly produced p-values of 0 . 05 or less for measures involving Eurasian populations . We feel that this indicates a general pattern of ( possibly weak ) selection at GWAS SNPs and/or linked variants in Eurasia . Included among the measures that were generally elevated for GWAS SNPs were delta and Fst scores . This suggests a role for positive selection in shaping patterns of variation surrounding GWAS SNPs , as it is probably the selective force most likely to cause notable allele frequency differences between populations . Our observation that iHS scores were generally elevated for GWAS SNPs is consistent with the effects of positive selection as well . However , SNPs under negative selection may also produce elevated iHS scores . Furthermore , a GWAS trait under negative selection would tend to have rare causative variants [38] , [39] . This would lead to the sequestration of some causative variants in a limited number of populations and would explain why p-values for GWAS SNPs are higher for measures involving African , American , and Oceanic population when most GWAS are conducted using European subjects . Thus , our results suggest that both negative and positive selection may influence variation at GWAS SNPs . Their relative contributions , however , remain unclear . How do the significant traits ( pigmentation , blood pressure , autoimmune disease , and infectious disease resistance ) differ from the other traits we studied ? Are they examples of positive selection driving polygenic adaptation ? If so , are they the only examples among the traits we studied ? Or are the genetic architectures of these traits somehow simpler than other traits , perhaps because they are less polygenic ( as has been proposed previously for pigmentation [35] ) ? The definitive answers to these questions ultimately lie in the identification of the causative variants underlying GWAS traits . In summary , we have examined 1 , 336 trait-associated SNPs in the 53 CEPH-HGDP populations looking for individual SNPs and groups of SNPs with unusual allele frequency patterns and elevated iHS scores . We identified 13 different traits with an associated SNP or study group that produced a significantly elevated score for at least one delta , Fst , LLC , or iHS measure , a small percentage of the total number of traits analyzed . We believe that the limited number of positive results could be due to our stringent significance criteria or to features of the genetic architecture of the traits themselves . Specifically , the roles of rare variants , epistasis , and pleiotropy in human complex traits are , although areas of active inquiry , still generally not well understood . Our measures may also not be optimal for detecting all types of selection acting on GWAS traits . It has been speculated that variants underlying complex traits will be influenced primarily by negative or balancing selection , which may not produce extreme values for our measures , particularly if these forces are relatively uniform across populations or are acting on many regions in the genome . The SNPs and study groups that were significant were almost all clustered within four trait classes – pigmentation , blood pressure , infectious disease , and autoimmune disease . Our results suggest that the traits encompassed by these trait classes are likely examples of phenotypes that have undergone evolution by polygenic adaptation . The pattern of elevated measures was unique for each of these four trait classes , which would seem to indicate that a different selective force is driving allele frequency changes at SNPs within each class . However , we cannot rule out the possibility that some of the SNPs in these trait classes are associated with multiple traits and thereby experience multiple selective pressures . It also remains unclear whether the type and the strength of the selection acting on a phenotype or the underlying genetic architecture of a trait was the important factor in distinguishing significant traits from those that were not significant in our analysis . We also found that both SNPs and study groups tend to have lower p-values for Eurasia and East Asian measures . We theorize that this may be due to global variation in linkage disequilibrium patterns , causing SNPs associated with a trait in one population to be unassociated with that trait in another population . If this is the correct interpretation of our results , it has important implications for the future of GWAS as it suggests that the SNPs identified by two GWAS using samples from two different continents may be quite different . As almost no GWAS studies have been done using samples from Africa , Oceania , or the Americas , the three continents where we observed a deficit of low p-values , it is impossible at present to test this hypothesis directly . We believe that extending GWAS analyses to include individuals from these regions is an important next step in this area of research . Such studies will elucidate whether SNP-trait associations are generally universal and if not , have the potential to associate new loci with traits previously studied in other human populations .
We listed all SNPs identified by NHGRI's online catalog of genome-wide association studies [5] in the order of their chromosomal positions ( this included GWAS SNPs not included in the CEPH-HGDP dataset ) . A SNP was designated as II if there was another SNP located within 1MB that was associated with the same trait ( or with a similar trait within the same trait class ) in at least one other GWAS . For instance , we counted a Crohn's disease SNP as II if there was an ulcerative colitis SNP within 1MB , and a hypertension SNP as II if there was a systolic blood pressure SNP within 1MB . SNPs that were associated with the same trait or with a similar trait by more than one study were also considered II . Through this process , we hoped to identify GWAS SNPs that were likely to have genuine trait associations by excluding SNPs in genomic regions identified by only one study . This method is , however , biased against SNPs associated with traits that have been investigated by a limited number of GWAS . For this reason , we conducted our analyses using both the full set of 1 , 336 GWAS SNPs and the subset of 592 II GWAS SNPs . The minor allele frequency ( MAF ) in Europe was calculated for each SNP in the Li et al . [12] dataset . We then divided these SNPs into 11 groups based on MAF , including one group which contained all SNPs with an MAF of 0 in Europe . For each of our 640 , 698 autosomal SNPs and 16 , 297 X-linked SNPs , we obtained the value of R2 between it and any hapmap SNP within 200KB in CEU individuals from the HapMap website [89] . We then calculated for each SNP the percentage of those R2 values exceeding 0 . 8 . We used the value of this percentage , which we will refer to as our “LD score” , to divide both our autosomal and X-linked SNPs into 9 different LD score bins of approximately the same size . One of these bins ( referred to as “NA” in Figure 1 ) contains all SNPs that are fixed in Europe . We divided the 640 , 698 SNPs from the Li et al . [12] dataset into 99 bins ( 9 groups based on LD score and 11 groups based on MAF ) . For each SNP and each measure , we calculated a standardized score equal to the difference between the SNP's value for that measure and the bin average for that measure ( as each GWAS SNP is assigned to a bin based on its MAF and LD score ) divided by the standard deviation of the measure values in that bin . The SNP was then assigned an empirical p-value for that measure by comparing its standardized score to the standardized score of all other 640 , 698 autosomal SNPs for that measure . This is the p-value used in the individual SNP analysis . We used this same procedure to carry out our analysis of the X chromosome using our 16 , 297 X-linked SNPs . For the unsigned group analysis , we created an empirical distribution for each group size n and each measure by randomly drawing n values from the list of standardized scores for that measure 1 , 000 , 000 times and then taking the average standardized score for the n values . The p-value for each study group and each measure was assigned by comparing the average standardized score for the study group to the corresponding list of 1 , 000 , 000 averages . For our signed group analyses , we determined the risk allele for as many of the CEPH-HGDP GWAS SNPs as possible . We then calculated values for these SNPs for the 38 delta , LLC , and iHS measures with respect to the risk allele as follows . Delta values were positive if the risk allele frequency was higher in the second population than in the first . Latitude/Longitude correlation values were positive if there was a positive correlation between latitude or longitude and the frequency of the risk allele . iHS values were positive if selection on the SNP favored the risk allele . Some GWAS traits are physiological rather than pathological , with alleles at associated SNPs favoring one side of the physiological spectrum . For such traits , we picked one end of this physiological spectrum to represent the “disease” end and denoted alleles favoring this end as risk alleles . We used this assignment for all studies of that trait . For instance , there are many GWAS studies that examine height . We deemed all alleles favoring taller stature to be risk alleles and used this system for all height GWAS . To calculate p-values for this part of the analysis , we recalculated the standardized score for each SNP and each measure . In the individual and unsigned group analysis , we used only the absolute values of the delta , Fst , LLC , and iHS measures in our calculation of standardized scores and in our construction of the empirical distributions . That is , each SNP had only one corresponding value and one standardized score for each measure . In this phase of the analysis , for each SNP and each measure , we included both the value of the measure and its additive inverse in our calculations of standardized scores . For each measure and each study group size n , we created the empirical distributions in the same way as for the unsigned group analysis , except that we drew from a list of 1 , 281 , 396 standardized scores ( since each of the 640 , 698 SNPs in our dataset “contributed” two standardized scores instead of one ) . For each phase of our analysis of autosomal CEPH-HGDP GWAS SNPs , we divided all GWAS SNPs or study groups into 18 trait classes ( see Table S1 ) . We then determined whether any of these 18 trait classes were over-represented in the top 5% of the empirical distribution , given the number of SNPs or study groups in the trait class . To explain how we did this , we will use a specific example . In the individual SNP analysis for all 1 , 336 GWAS SNPs , the autoimmune disease trait class contained 216 SNPs . For DPygmy , there are 1 , 336 total p-values , one corresponding to each CEPH-HGDP GWAS SNP . We randomly drew 216 p-values from our list of 1 , 336 p-values 10 , 000 times , each time counting the number of p-values that were ≤0 . 05 . From this list of 10 , 000 values , we determined that only 5% of the time did a random draw of 216 values contain 13 or more values that were ≤0 . 05 . If there had been more than 13 autoimmune disease SNPs that had a p-value ≤0 . 05 for DPygmy , we would have said that autoimmune disease SNPs were over-represented in the 5% tail of the empirical distribution of DPygmy p-values ( there were only 11 in this case ) . We repeated this procedure for all trait classes and all delta , Fst , LLC , and iHS measures for the individual SNP analysis with the full set of 1 , 336 GWAS SNPs . We then conducted the same procedure for the individual SNP analysis of just II SNPs and the four group analyses , with study groups substituted for individual SNPs . The full results of these calculations are shown in Figure S1 . In the “Sample Ethnicity” section , we used the same method to determine if East Asian GWAS SNPs or study groups were overrepresented in the top 5% of the empirical distribution for any of our measures . We used NHGRI's GWAS catalog to find the primary sources for the GWAS results listed on the website [5] . We reviewed these sources to determine the ethnicity of the samples used in each GWAS . We included samples that were used for replication analyses as well as those that were used for initial or discovery analyses . Individuals from the United States , Canada , or Australia that were described as “white” , “Caucasian” , or of European ancestry were considered European . African Americans from the United States were considered to be an admixed population . The one study that we reported as having been done on African samples used individuals native to the African continent . For each delta , Fst , LLC , and iHS measure in the individual SNP analysis of all GWAS SNPs , we made a list of all the p-values associated with East Asian GWAS SNPs and a list of all of the p-values associated with European GWAS SNPs . We used a one-tailed , unpaired Wilcoxon test to determine if the European p-values were less than the East Asian p-values or if the East Asian p-values were less than the European p-values . We then repeated this procedure for the II individual SNP analysis and all four group analyses . All of the comparisons we discuss in the results section had a p-value of 0 . 05 or less . The results of all tests are shown in Figure S5 . We listed all SNPs associated with height ( including those not in the Li et al . [12] dataset ) in order of their genomic positions . Any two SNPs that were less than 1MB apart were grouped together into one region . For this analysis , we considered only regions containing more than one SNP ( regions defined by one SNP that was identified in more than one GWAS qualify as containing more than one SNP ) . For height , there were 26 such regions . We repeated this procedure for T2D and SLE . | Natural selection exerts its influence by changing allele frequencies at genomic polymorphisms . Alleles associated with harmful traits decrease in frequency while those associated with beneficial traits become more common . In a simple case , selection acts on a trait controlled by a single polymorphism; a large change in allele frequency at this polymorphism can eliminate a deleterious phenotype from a population or fix a beneficial one . However , many phenotypes , including diseases like Type 2 Diabetes , Crohn's disease , and prostate cancer , and physiological traits like height , weight , and hair color , are controlled by multiple genomic loci . Selection may act on such traits by influencing allele frequencies at a single associated polymorphism or by altering allele frequencies at many associated polymorphisms . To search for cases of the latter , we assembled groups of genomic polymorphisms sharing a common trait association and examined their allele frequencies across 53 globally distributed populations looking for commonalities in allelic behavior across geographical space . We find that variants associated with blood pressure tend to correlate with latitude , while those associated with HIV/AIDS progression correlate well with longitude . We also find evidence that selection may be acting worldwide to increase the frequencies of alleles that elevate autoimmune disease risk . | [
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"genetics... | 2011 | Genome-Wide Association Study SNPs in the Human Genome Diversity Project Populations: Does Selection Affect Unlinked SNPs with Shared Trait Associations? |
The Mycobacterium tuberculosis Ser/Thr kinase PknB has been implicated in the regulation of cell growth and morphology in this organism . The extracytoplasmic domain of this membrane protein comprises four penicillin binding protein and Ser/Thr kinase associated ( PASTA ) domains , which are predicted to bind stem peptides of peptidoglycan . Using a comprehensive library of synthetic muropeptides , we demonstrate that the extracytoplasmic domain of PknB binds muropeptides in a manner dependent on the presence of specific amino acids at the second and third positions of the stem peptide , and on the presence of the sugar moiety N-acetylmuramic acid linked to the peptide . We further show that PknB localizes strongly to the mid-cell and also to the cell poles , and that the extracytoplasmic domain is required for PknB localization . In contrast to strong growth stimulation by conditioned medium , we observe no growth stimulation of M . tuberculosis by a synthetic muropeptide with high affinity for the PknB PASTAs . We do find a moderate effect of a high affinity peptide on resuscitation of dormant cells . While the PASTA domains of PknB may play a role in stimulating growth by binding exogenous peptidoglycan fragments , our data indicate that a major function of these domains is for proper PknB localization , likely through binding of peptidoglycan fragments produced locally at the mid-cell and the cell poles . These data suggest a model in which PknB is targeted to the sites of peptidoglycan turnover to regulate cell growth and cell division .
Bacterial cell growth and cell division are highly regulated processes , requiring the coordination of multiple activities within the cell . DNA replication and chromosome segregation for example , must occur at the correct time and in the correct location , and be coordinated with septum formation and cytokinesis . The molecules involved in septum formation and the sequence in which they are recruited to the division site have been the subject of intense investigation in the model organisms Bacillus subtilis and Escherichia coli , and the identities and functions of many bacterial cell division proteins have been elucidated [1] , [2] . In addition to divisome assembly and DNA segregation , bacterial growth and cell division require remodeling of the peptidoglycan ( PGN ) mesh that forms the cell wall [3] . The enzymes and the sequence of reactions involved in cell wall synthesis are relatively well understood as are the enzymatic activities of many of the PGN hydrolases that can degrade this polymer [4] , [5] . In the model organism B . subtilis , the mechanisms by which cell wall hydrolases are regulated to achieve morphogenesis are at least partially understood [6] . In other bacteria , including the slow growing actinomycete Mycobacterium tuberculosis , less is known about the regulation of PGN synthesis and hydrolysis , how these opposing processes are balanced , and how they are coordinated with other cell processes in growing and dividing vs . non-growing dormant cells . Because of the apparent ability of M . tuberculosis to become dormant in the human host , leading to asymptomatic latent infection , there has been great interest in understanding how cell growth and cell division are regulated in this organism [7] . A longstanding observation that “spent” or “conditioned” medium , i . e . filter-sterilized supernatant from bacterial cultures grown in liquid medium , is able to stimulate growth of dormant cells , led to the identification of a resuscitation promoting factor ( Rpf ) by purifying from spent medium a component that was able to stimulate growth of the actinomycete Micrococus luteus [8] . Rpf is small protein that has homologues in other actinobacteria , including M . tuberculosis , which has five rpf genes [9] . Functional studies of these genes in M . tuberculosis have shown that individually they are not required for resuscitation of dormant M . tuberculosis cells and single rpf mutant strains do not have other growth or morphologic phenotypes . When two or more rpf genes are inactivated , however , growth or resuscitation defects are observed [10] , [11] , [12] . The recent demonstration that the Rpf's are PGN hydrolases suggests that growth stimulation of dormant cells may result from the enzymatic activity of these secreted proteins , possibly through alterations in PGN structure or through the interaction of PGN degradation products with the bacterial cell surface [13] . A domain found to occur in the extracytoplasmic regions of penicillin binding proteins and serine/threonine kinases ( PASTA domain ) was identified by bioinformatic analysis and predicted to bind to the stem peptide of un-crosslinked PGN precursors , based on the structure of the PASTA-containing penicillin binding protein PBP2X of Streptococcus pneumoniae bound to a cephalosporin antibiotic [14] . Recently the PASTA domain of a Ser/Thr kinase of B . subtilis was shown to bind both intact and hydrolyzed PGN [15] . Incubation of B . subtilis spores with PGN stimulated spore germination and increased Ser/Thr phosphorylation . Some specificity with respect to the source of PGN and these functional effects was observed , suggesting a preference for meso-diaminopimelic acid ( m-DAP ) -containing PGN in stimulating spore germination in this organism . The M . tuberculosis genome encodes two proteins that contain PASTA domains , the Ser/Thr protein kinase PknB ( Rv0014c ) whose extracytoplasmic region comprises four PASTA domains , and the bifunctional penicillin binding protein PBP2 ( PonA2 , Rv3682 ) , which has a single PASTA domain at the extreme carboxy-terminus of the protein distal to the extracytoplasmic transpeptidase and transglycosylase-containing regions [16] . In this work we investigated the quantitative binding of a series of synthetic muropeptides to the extracytoplasmic region of PknB . We identified specific features of these molecules that are required for high affinity binding , and investigated the functional effects of these compounds in vivo on mycobacterial growth , morphology and the localization of PknB . We determined that PknB is strongly localized to septum and less strongly to the cell poles , the sites of active PGN synthesis in mycobacteria , and that the PASTA domains of PknB are required for its localization .
The region of pknB that encodes the extracytoplasmic domain of PknB ( ED-PknB ) was amplified by PCR , cloned and ED-PknB was expressed in Escherichia coli as an N-terminal Glutathione-S-transferase ( GST ) fusion protein . The ED-PknB comprises 4 PASTA motifs that share limited sequence similarity aside from the key residues that define the motif ( Figure S1 ) . Soluble recombinant GST-ED-PknB was affinity purified to >95% purity and after removal of the GST tag was used in subsequent binding experiments ( Figure S2 ) . A series of PGN fragments ( muropeptides ) were synthesized as tri- , tetra- and penta-peptides linked to N-acetylmuramic acid ( MurNAc ) or as unlinked peptides . Amino acids characteristic of PGN stem peptides from Gram-positive bacteria , Gram-negative bacteria or actinobacteria were incorporated into different compounds . Modifications of amino acid side chains that correspond to PGN modifications that are found in vivo were also included in the compound series ( Figure 1 ) . These compounds were then used in surface plasmon resonance ( Biacore ) experiments to measure binding affinities of the muropeptides to ED-PknB . To obtain kinetic and thermodynamic parameters , a range of compound concentrations was assayed and kinetic analysis was performed using Biacore Software . An example of a set of sensorgrams for a compound with a relatively low KD is shown in Figure 2 . Sensorgrams for the other compounds tested are shown in Figure S3 . Table S1 shows detailed kinetic parameters obtained from these experiments . As shown in Table 1 , these experiments demonstrated moderately strong binding of several PGN fragments that have DAP at the third position of the stem peptide . N-acetylation of the amino group of DAP as in compound 6e ( MTrP-DAP ( amide/acid ) NHAc ) , which is designed to mimic branching of the PGN subunits within the PGN polymeric structure , resulted in a six-fold decrease in binding compared to compound 6a . The MurNAc-pentapeptide , compound 7 , corresponding to newly synthesized PGN prior to remodeling , bound strongly though about two-fold less than the corresponding MurNAc-tetrapeptide ( 6a ) . In addition to preference for DAP at the third position of the stem peptide , another clear result of these experiments is the requirement for amidation of D-isoglutamate ( D-iGlu ) to D-isoglutamine ( D-iGln ) at the second position , in order to achieve high affinity binding . Compound 6a , which contains both D-iGln and DAP at the second and third positions , respectively , exhibited the highest affinity , while compound 6d , which is identical except for D-iGlu at the second position , bound four-fold less strongly . Similarly , compound 6c , which also bound with a relatively high affinity ( KD = 15 µM ) , contains D-iGln together with amidation of the carboxyl group of DAP . In contrast , a similar compound , ( 6b ) , that has D-iGlu at the second position instead of D-iGln did not show measurable binding . The importance of this residue is further underscored by the finding that among the Lys-containing compounds , the only one that showed detectable interaction was compound 2a , the muramyl tetrapeptide incorporating a D-iGln moiety . While the data indicate a preference for DAP at the third position , the ε-carboxylic acid group that is a major feature that distinguishes DAP from Lys is not an essential requirement for binding . To determine whether the MurNAc moiety was important for binding , compounds 4 and 8 , pentapeptides not linked to MurNAc and containing either Lys or DAP at the third position , respectively , were tested . Neither compound showed significant interaction , indicating an important contribution of MurNAc in binding to the PknB PASTA domains . The Rpf's have been shown to have PGN hydrolytic activity , and are thought to cleave the ß-1–4 glycosidic linkage between N-acetylmuramic acid and N-acetylglucosamine [13] . This muralytic activity has been shown to be essential for the resuscitation activity of these Rpf proteins , but the mechanism remains uncertain . To determine whether muropeptides that bind to the PASTA domains of ED-PknB can stimulate resuscitation of dormant M . tuberculosis cells , we utilized an established M . tuberculosis dormancy and resuscitation model [17] . In this assay , M . tuberculosis cells are incubated under hypoxic conditions for several months , at which point the number of cells capable of resuming growth in liquid culture is markedly decreased . In this assay , addition of sterile spent medium “resuscitates” dormant cells , leading to an increase in the number of cells that can grow on solid or in liquid medium . In two independent experiments , we took M . tuberculosis stationary phase cultures that had been incubated under hypoxic conditions for 6 or 9 months , and performed this resuscitation assay . In addition to cells incubated in Sauton's medium alone , cells were incubated with a synthetic muropeptide with a high affinity for ED-PknB ( 6c in Figure 1 ) , a muropeptide with low affinity for ED-PknB ( 3b in Figure 1 ) , or with sterile conditioned medium as a positive control . The muropeptides were used at a concentration of 10 times the KD of the high affinity compound as determined in the SPR experiments . Using most probable number analysis [18] , which has been used to analyze results from this assay , we observed three and nine-fold increases in the viability of cells that were incubated with the high affinity muropeptide in the two independent experiments . No increase in viability was observed for cells incubated with the low affinity peptide . The cells incubated with sterile spent medium showed a much stronger resuscitation phenotype , with 14 and 100-fold increased viability relative to the cells incubated in fresh medium alone ( Table 2 ) . The original identification of Rpf in M . luteus was based on the observation that stationary phase cells show decreased viability when plated or diluted to low density in liquid medium , but that addition of sterile conditioned medium stimulates growth [8] . A similar phenomenon is observed when mycobacteria are inoculated at low density . To determine whether synthetic muropeptides stimulate growth when stationary phase cells are inoculated at low density , cells from cultures of M . tuberculosis ( O . D600 of 2 . 4–3 . 6 ) were washed and diluted 10 , 000-fold in minimal medium with or without the addition of the high or low affinity muropeptide . As shown in Figure 3 , no growth stimulation by either muropeptide was observed in this assay . In contrast , strong growth stimulation by conditioned medium was observed . Based on its sequence , PknB is predicted to have a single transmembrane segment , with an intracellular kinase domain and an extracytoplasmic region that incorporates the four PASTA domains [16] . To determine whether PknB is a membrane protein and in which subcellular fraction ( s ) PknB is located , we performed immunoblotting with a PknB-specific monoclonal antibody . As a control , we probed these subcellular fractions with an antibody to the membrane protein PknA , which like PknB has a single transmembrane segment , but which has a small extracytoplasmic region that is not known to interact with cell wall components . We found that PknB does , as predicted , localize to the membrane fraction of the cell ( Figure 4 ) . An even stronger signal was seen in the cell wall fraction , further confirming the association of PknB with the cell envelope . The PknA antibody gave equally strong signals from the membrane and cell wall fractions . These results demonstrate that PknB is a membrane protein and that membrane is present in the cell wall fractions used in these experiments . A construct designed to express a PknB-RFP fusion protein , in which RFP is fused to the amino terminus of PknB , was introduced into wild type M . smegmatis . Additional constructs , in which RFP is fused a ) to the PknB kinase domain , intracellular juxtamembrane sequence and transmembrane segment , but which lacks the extracytoplasmic domain , and b ) to the membrane and ED-PknB regions but which lacks the intracellular linker and kinase domains , were also introduced into wild type M . smegmatis . Cells were grown to early log phase , expression of the fusion protein was induced , and the cells were examined using fluorescence microscopy ( Figure 5 ) . Cells expressing the full-length PknB-RFP fusion showed strong localization of this protein to the mid-cell and symmetrical , less intense localization to both cell poles . In contrast , in cells expressing the fusion that lacks the extracytoplasmic domain containing the PASTA domains , foci of fluorescence were visible at discrete sites along the length of the cell . While in some cells there appears to be increased signal at the poles , we did not observe clear mid-cell localization in cells expressing this construct . To confirm that these foci are not cytoplasmic aggregates , we prepared subcellular fractions of these cells and confirmed that the large majority of this protein is present in the cell membrane and cell wall fractions ( Figure S4 ) . Cells expressing the ED-PknB-RFP fusion lacking the intracellular linker and kinase domains showed clear localization to the mid-cell but minimal signal from the poles . This result indicates that the extracytoplasmic PASTA domains are required for proper localization of PknB to the mid-cell and likely to the cell poles and suggests that the intracellular linker-kinase region makes a contribution to localization at the cell poles . To verify these findings , we performed additional imaging of live cells ( Figure S5 and Protocol S1 ) , which demonstrates the same localization patterns observed with the fixed cell preparations . To determine whether diffusible , non-localized muropeptides might bind ED-PknB and disrupt PknB localization , we incubated M . smegmatis for 8 hours with the high affinity muropeptide used in the resuscitation experiments . No change in the morphology of wild type bacteria were observed , and in the strain expressing the PknB-RFP fusion protein the RFP signal remained localized to the septum and poles ( not shown ) .
In this work we report three major findings . First , we demonstrated that muropeptides bind to the extracytoplasmic region of PknB , which contains four PASTA domains , and defined molecular requirements for ligand binding . These requirements include both specific residues at the second and third positions in the stem peptide , and the presence of the sugar moiety ( MurNAc ) linked to the amino-terminal residue of the peptide . Using an extensive series of chemically synthesized compounds , we found moderately high affinity binding by muropeptides that contain DAP at the third position of the stem peptide , in which the D-iGlu at the second position is amidated to D-iGln . The preference for DAP is consistent with the predominant structure of the stem peptide of mycobacteria , where DAP is present at this position , in contrast to most Gram-positive organisms in which Lys occurs at this position . D-iGln at the second position has been reported to be predominant in M . tuberculosis PGN , however D-iGlu is present in a minority of stem peptides [19] , [20] . Whether synthesis of PGN incorporating D-iGlu vs . D-iGln is site- or growth-stage specific in M . tuberculosis is not known . The markedly stronger binding of compounds containing D-iGln suggests that variation in the structure of PGN stem peptides may affect binding by ED-PknB in vivo , with potentially important physiologic effects . A recent paper examining stimulation of B . subtilis spore germination using synthetic muropeptides confirmed prior results using purified native PGN in showing the importance of DAP at the third position of the stem peptide for this phenotype in this species [21] . In this assay the presence of N-acetylglucosamine linked to MurNAc was also required for potent activity . A second finding of this work is that PknB localizes strongly to the mid-cell and less strongly to the cell poles of mycobacteria , the sites of active PGN synthesis and hydrolysis in these organisms [22] . Our results with RFP fusions to full-length PknB and to separate domains of this protein in M . smegmatis demonstrate that the PASTA motif-containing extracytoplasmic domain of PknB is required for its localization to the mid-cell . We attempted to perform a similar experiment with full-length PknB-RFP in M . tuberculosis , however we were unable to obtain consistent expression of the fusion protein . We observed fluorescence in a minority of cells , which was highly variable from cell to cell , and we observed markedly abnormal morphology of many cells , suggesting severe toxicity of pknB overexpression , as previously described [23] . Despite these limitations , we were able to see similar localization of full-length PknB in a minority of rod-shaped cells expressing the pknB-rfp fusion ( data not shown ) . In the context of our in vitro binding results , these data suggest that binding of PGN fragments by its extracytoplasmic domain is critical for PknB localization to the mid-cell and possibly to the poles . This result , together with the finding that PknB is found in the cell wall and membrane fractions of M . tuberculosis lysates , suggests that the PASTA motifs of PknB bind endogenous cell wall or membrane-anchored PGN precursors and/or PGN hydrolysis fragments produced at the septum and poles of the cell . The finding that incubation of growing cells with a high affinity muropeptide had no effect on PknB localization is consistent with this model , and suggests that exogenous muropeptides may not be able to penetrate the complex , lipid-rich mycobacterial cell envelope to reach the PknB PASTA domains at the surface of the cytoplasmic membrane . Because both de novo synthesized PGN precursors and PGN hydrolysis products are likely to be localized at the septum and the poles , our data do not indicate which of these are the major PknB PASTA ligands in vivo . The third important finding of this work is that , in contrast to spent medium , which strongly stimulated both growth of non-dormant M . tuberculosis cells and resuscitation of dormant cells , a muropeptide with relatively high affinity for the PASTA domains of ED-PknB did not stimulate M . tuberculosis growth and had only a modest effect on resuscitation . This result suggests that while muropeptide binding may play a role in resuscitation of M . tuberculosis , other factors present in spent medium may be more important in stimulating M . tuberculosis growth . In this regard , D-amino acids present in conditioned medium have recently been shown to be a potent growth stimulus for Vibrio cholerae and to play a key role in biofilm disruption leading to resumption planktonic growth in B . subtilis [24] , [25] . Alternatively , PknB may require a different muropeptide ligand , e . g . a disaccharide muropeptide or a multivalent muropeptide , or higher concentrations of these ligands , which may be present in vivo , for greater stimulation of growth or resuscitation . The first structure of a PASTA domain was determined as part of the structure of PBP2x from S . pneumoniae bound to a cephalosporin antibiotic [26] . In this structure two PASTA domains interacted to form a compact globular domain . In recent work , the structure of the PASTA motifs of M . tuberculosis ED-PknB was determined using NMR and small angle X-ray scattering [27] . While the individual folds of each PASTA domain were similar to those of the PBP2x PASTA domains , the four PASTA domains of PknB are organized as a linear molecule , which is maintained with what the authors termed a ß′/ß′′ brace that prevents interactions between the individual PASTA domains of a single molecule of PknB . A previous structure of the PknB intracellular domain demonstrated the presence of a highly flexible intracellular juxtamembrane segment linking the transmembrane segment to the intracellular kinase domain , indicating that ligand binding resulting in transmembrane propagation of conformational changes leading to PknB activation is unlikely [28] . Based on the PknB PASTAs structure , a model was proposed in which binding of a single ligand to two molecules of PknB would result in dimerization of the extracytoplasmic domains , which would then cause dimerization of the intracellular kinase domains , resulting in kinase activation [27] . Our data showing relatively high affinity binding of muropeptide monomers , however , suggest an alternative model by which muropeptide binding to ED-PknB could lead to localization and activation of this kinase . In this model , at sites of active PGN hydrolysis and synthesis , i . e . the septum and the cell poles , local concentrations of PGN precursors and PGN hydrolysis products will be high , and binding of these ligands by ED-PknB would result in the septal and polar localization of PknB that we observed . The recruitment of PknB to these sites will consequently result in high concentrations of the intracellular kinase domain , leading to the dimerization that results in kinase activation [28] , [29] , [30] . PknB activation will then lead to phosphorylation of protein substrates , resulting in regulation of cell division and cell wall synthesis ( Figure 6 ) . In this model , there is no requirement for binding of a single muropeptide by PASTA domains from two PknB molecules , or for muropeptides that diffuse from a distance , to achieve PknB localization and activation . In summary , we have demonstrated sequence-specific binding of muropeptides to the PASTA domain-containing extracytoplasmic region of M . tuberculosis PknB , and that the presence of the PASTA domains is required for localization of PknB to sites of PGN turnover . In the context of our phenotypic data and the finding that peptides that bind with high affinity have peptide sequences characteristic of M . tuberculosis PGN , our results suggest that in M . tuberculosis , the PknB PASTAs bind to PGN precursors or fragments resulting from local PGN synthesis and/or hydrolysis at the mid-cell and poles . This PASTA domain-mediated localization provides a mechanism by which PknB and the co-regulated kinase PknA can regulate cell division and PGN turnover by reversible phosphorylation of proteins involved in these processes , several of which have been shown to be PknA or PknB substrates and to localize to these sites [22] , [23] , [31] , [32] , [33] .
Escherichia coli TOP10 ( Invitrogen ) was used for cloning and was grown in LB broth . E . coli BL21 ( DE3 ) ( Stratagene ) was used for expression of recombinant ED-PknB . M . tuberculosis H37Rv or M . smegmatis mc2-155 were grown at 37°C in Middlebrook 7H9 liquid medium ( Difco ) supplemented with albumin-dextrose complex ( ADC ) , 0 . 2% Glycerol and 0 . 05% Tween 80 , except for resuscitation experiments where M . tuberculosis was grown in Sauton's medium ( Difco ) . Kanamycin ( 50 µg ml−1 ) or ampicillin ( 100 µg ml−1 ) was added to culture media or agar when appropriate . For expression and purification of ED-PknB , the nucleotide sequence encoding PknB from Gly354 to Gln626 was PCR-amplified from genomic DNA of M . tuberculosis H37Rv and cloned in pGEX-4T-3 ( GE Healthcare ) for expression as a glutathione-S-transferase ( GS ) fusion protein . Recombinant GST-ED- PknB was affinity purified to >95% homogeneity using immobilized glutathione agarose ( Pierce ) ( Figure S2 ) . To cleave the GST from the fusion protein , the thrombin CleanCleave kit ( Sigma ) was used . In brief 900 µg of purified recombinant ED-PknB-GST was incubated with 100 µL of 50% ( v/v ) suspension of thrombin agarose for 1 hr at room temperature . After centrifugation the supernatant containing ED-PknB and free GST was incubated with 500 µL of 50% ( v/v ) suspension of Glutathione-agarose for 15 min . After centrifugation the supernatant containing ED-PknB was collected . For SPR analysis the supernatant was dialyzed against phosphate buffered saline ( PBS ) pH 7 . 4 prior to use . For localization of PknB or PknB lacking the extracytoplasmic domain ( PknBΔED ) in wild type M . smegmatis , the full length pknB gene or the nucleotide sequence encoding the region from Met1 to Gly354 of PknB ( pknBΔED ) respectively , were PCR-amplified from genomic DNA of M . tuberculosis H37Rv . Overlap PCR amplification of the above PCR products was performed with the PCR product of the red fluorescent protein ( rfp ) gene using a forward primer annealing to the 5′ region of rfp and a reverse primer annealing to the 3′ region of pknB or PknBΔED to obtain the PCR products rfp-pknB or rfp-pknBΔED . A PacI site was introduced between rfp and pknB . The fusion PCR products were cloned into the integrating vector pMV306-pacet downstream of the inducible acetamide promoter at NdeI and XbaI sites to obtain pMV306-pacet-rfp-pknB or pMV306-pacet-rfp- pknBΔED . To obtain recombinant clone pMV306-pacet-rfp-pknBΔKD expressing RFP linked to transmembrane and extracellular domains of PknB ( ED-PknB-RFP ) the pknB gene of the clone pMV306-pacet-rfp-pknB was replaced with the nucleotide sequence encoding Ile326 - Gln626 using PacI and XbaI sites . Cloned DNA was sequenced to verify the absence of mutations . A mycobacterial replicating vector that constitutively expresses RFP was a gift from Eric Rubin . Compounds were synthesized using classical fluorenylmethoxycarbonyl ( Fmoc ) chemistry and standard manual solid-phase peptide synthesis techniques as previously described [34] , [35] , [36] , [37] , [38] , [39] . In the preparation of the peptide portion of the compounds , Sieber Amide resin was swelled in dimethylformamide ( DMF ) for 45 min and then treated with piperidine in DMF . After a reaction time of 30 min , the solvents were removed by filtration and the resin washed with DMF , and then treated with Fmoc-linked amino acid building blocks . This generated PGN partial structures with N-termini . Compound 8 was newly synthesized for this work as follows . Rink amide AM LL resin ( 0 . 1 mmol ) was swelled in dichloromethane for 30 min and then rinsed with DMF ( 3×5 mL ) . The resin was treated with piperidine in DMF ( 20% , 3×5 mL ) . After a reaction time of 30 min , the solvents were removed by filtration and the resin was washed with DMF ( 3×5 mL ) , followed by treatment with Fmoc-D-Ala-OH ( 155 . 7 mg , 0 . 5 mmol ) in DMF in the presence of HATU ( mg , 0 . 5 mmol ) and DIPEA ( mL ) . The reaction progress was monitored by a Kaiser test . After completion of the coupling , the resin was washed with DMF ( 3×5 mL ) . The Fmoc protecting group was removed by treatment with piperidine in DMF ( 20% , 3×5 mL , 3×10 min ) . The reaction cycle was repeated using Fmoc-D-Ala-OH ( 155 . 7 mg , 0 . 5 mmol ) , Fmoc-DAP ( BOC , tBu ) -OH ( 113 . 7 mg , 0 . 2 mmol ) , Fmoc-D-iso-Gln-OH ( 73 . 7 mg , 0 . 2 mmol ) , Fmoc-L-Ala-OH ( 155 . 7 mg , 0 . 5 mmol ) . The final Fmoc protecting group was removed by treatment with piperidine in DMF ( 20% , 3×5 mL , 3×10 min ) . The resin was washed with DMF ( 3×5 mL ) and the resin bound peptide was capped by treatment with acetic anhydride and ( 10% ) and DIPEA ( 5% ) in DMF ( 3×5 mL , 3×10 min ) . The resin was washed with DMF ( 3×5 mL ) , dichloromethane ( 7×5 mL ) , and methanol ( 3×5 mL ) and dried in vacuo overnight . The peptide was released from the resin by treatment with TFA/TIPS/Water ( 95%/2 . 5%/2 . 5% ) in DMF for 2 h . The resin was filtered and washed with TFA ( 1×10 mL ) . The filtrate was concentrated under reduced pressure and co-evaporated with toluene . The crude peptide was dissolved in water/acetonitrile and purified by semi-preparative HPLC ( Eclipse XDB-C18 column , 5 mm , 9 . 4×250 mm , eluent: water/acetonitrile/0 . 1%TFA ) to afford , after lyophilization of the appropriate fraction , the target compound 8 . HRMS-MALDI-TOF calculated for C23H40N8O9Na [M + Na]: 595 . 29 , experimental: 595 . 41 . Binding interactions between ED-PknB and PGN analytes were examined using a Biacore T100 biosensor system ( Biacore Life Sciences - GE Healthcare ) . Soluble ED-PknB was immobilized by standard amine coupling using an amine coupling kit ( Biacore ) . The surface was activated using freshly mixed N-hydroxysuccimide ( NHS; 100 mM ) and 1- ( 3-dimethylaminopropyl ) -ethylcarbodiimide ( EDC; 391 mM ) ( 1/1 , v/v ) in water . Next , ED-PknB ( 50 µg/ml ) in aqueous NaOAc ( 10 mM , pH 4 . 5 ) was passed over the chip surface until a ligand density of approximately 5 , 000 RU was achieved . The remaining active esters were quenched by aqueous ethanolamine ( 1 . 0 M; pH 8 . 5 ) . The control flow cell was activated with NHS and EDC followed by immediate quenching with ethanolamine . HBS-EP ( 0 . 01 M HEPES , 150 mM NaCl , 3 mM EDTA , 0 . 005% polysorbate 20; pH 7 . 4 ) was used as the running buffer for the immobilization and kinetic studies . Analytes were dissolved in running buffer and a flow rate of 20 µL/min was employed for association and dissociation at a constant temperature of 25°C . A double sequential 60 s injection of aqueous NaOH ( 50 mM; pH 11 . 0 ) at a flow rate of 50 µl/min followed by 5 min stabilization with running buffer was used for regeneration and achieved prior baseline status . The same experimental surface was used for approximately 4 weeks and maintained under running buffer conditions . MTP-DAP ( amide/acid ) ( 5 ) was used as a positive control in each experiment to check the stability of the ED-PknB surface activity during the course of the experiments . To minimize bulk refractive index changes , nonspecific binding and instrument drift on the generated binding sensorgrams , a double referencing of the data was performed . First , bulk refractive index change effects were minimized by preparing all analytes in the HBS-EP buffer . Then , the binding responses over the reference surface were subtracted from the active surface to correct for nonspecific binding . A blank analyte run of running buffer alone was also subtracted from the specific binding sensorgrams to minimize instrument noise . Using Biacore T100 evaluation software , the response curves of various analyte concentrations were globally fitted to the two-state binding model [40] . Conditioned medium was prepared as previously described [41] . Briefly , supernatant was obtained from M . tuberculosis H37Rv culture grown in ADC-supplemented Sauton's medium containing 0 . 05% Tween 80 at 37°C with shaking to an optical density at 600 nm ( OD600 ) of 1 . 2 . After centrifugation ( 4000 rpm , 10 min ) , the supernatant was sterilized by passage through 0 . 22 µm filter , tested for sterility , and used for the resuscitation experiments . To obtain non-culturable dormant bacilli , Mycobacterium tuberculosis H37Rv was grown under long-term oxygen starvation in broth growth medium ( Sauton's medium containing 0 . 05% tween 80 and supplemented with ADC ) as previously described [10] . In brief , M . tuberculosis was initially grown to late stationary phase at 37°C with shaking . From this initial culture , 100 µL was subcultured into 20 ml of growth medium and grown to an optical density at 600 nm ( OD600 ) of 1 . 8 to 2 . Finally 100 µL was inoculated into 75 ml of growth medium containing 1 . 5 µg/ml methylene blue in a sealed 250-ml flask and grown with shaking at 37°C for 6 or 9 months . Methylene blue became colorless by 10 days of incubation , indicating oxygen depletion . For resuscitation experiments muropeptides were dissolved in sterile Sauton's medium to a concentration of 20 times the binding constant ( KD ) of the high affinity compound ( 6c ) The dormant culture was serially diluted ( 10−1 to 10−6 ) in growth medium . From each dilution 4 sets of triplicate 100 µL culture were aliquoted in wells of 96 well plates ( one set each for muropeptides ( 2 muropeptides tested ) , growth medium and spent medium ) . 100 µL of growth medium , muropeptide , or spent medium was added to each well of the corresponding set . The final concentration of muropeptide was 10 times the KD of the high affinity compound , and of the spent medium was 50% . Plates were incubated at 37°C . Drying was prevented by maintaining sterile water in outer wells of the plate . After 2 months the wells with visibly turbid growth were recorded and MPN values were calculated as previously described [42] . To investigate the effect of muropeptides on growth initiation of low inoculum cultures of M . tuberculosis , stationary phase ( O . D600 of 2 . 4–3 . 6 ) cultures grown in Sauton's medium supplemented with ADC and 0 . 05% Tween 80 were passed through five micron pore filter ( Millipore ) to remove clumps . To obtain a single cell suspension , the culture was passed five times through a 27½ gauge needle followed by washing three times with Sauton's medium . 100 µl of a 10−4 dilution was inoculated into wells of a 96 well plate for a final volume of 200 µl . 1x alamar Blue was included in each well . As above , the final concentration of the muropeptides was 10 times the KD of the high affinity compound , and of the spent medium was 50% . Each condition was tested in duplicate . Growth was monitored in each well by measuring fluorescence using excitation of 550 nm and emission of 595 nm and plotted as fluorescence intensity units versus time in days . For cellular localization of RFP fusions to intact PknB or its domains , the corresponding plasmid expressing the fusion under control of the acetamidase promoter was electroporated into M . smegmatis cells . The resulting strains were grown in Middlebrook 7H9 liquid medium supplemented with ADC , 0 . 2% Glycerol and 0 . 05% Tween 80 to mid-log phase , followed by induction with 0 . 2% acetamide for 6 hrs . Cells were fixed in 4% paraformaldehyde at 37°C for 30 min followed by incubation with 50 mM ammonium chloride for 5 min at room temperature . Cells were transferred onto a glass slide , air-dried and one drop of Prolong Gold antifade reagent ( Invitrogen ) was applied before covering with a coverslip . After 24 hrs of curing in the dark , cells were observed using a Zeiss Axiophot microscope with a 63x differential interference contrast ( DIC ) oil immersion objective and red fluorescence filter . Images were captured by a Spot cooled CCD camera ( Diagnostic Instruments ) , acquired with Spot software and processed by Adobe Photoshop CS2 . For cellular localization of native PknB in wild type M . tuberculosis cells , 60 µg total protein of cytosol , cell wall , cell membrane and culture filtrate fractions , prepared at Colorado Statue University and obtained from the Biodefense and Emerging Infections Research Resources Repository , was fractionated on 10% SDS-PAGE and transferred to a PVDF membrane . The blot was blocked in Tris-buffered saline containing 0 . 1% Tween 20 ( TBST ) and 5% milk for 1 hr at room temperature . The blot was incubated overnight at 4°C with 1∶10 , 000 dilutions of either a mouse monoclonal antibody raised against extracytoplasmic domain of PknB or with a rabbit polyclonal antibody against PknA . After thorough washing with TBST , the blot was incubated with a 1∶10 , 000 dilution of HRP-conjugated secondary antibodies ( Cell Signaling ) for 3 hrs at room temperature . Finally after 3 washes with TBST the blot was developed with Lumiglo ( Cell Signaling ) and the blot image was obtained on a Kodak Image Station 4000 . PknA: P65726 PknB: POA5S4 | Regulation of growth by Mycobacterium tuberculosis is important in the pathogenesis of tuberculosis ( TB ) , including asymptomatic latent TB infection and active TB disease . The M . tuberculosis kinase PknB regulates cell growth and cell division by phosphorylating proteins involved in these processes to modify their function . The activity of PknB is thought to respond to extracellular stimuli by binding specific molecules with its extracytoplasmic domain . In this work we show that cell wall fragments bind to this domain , and that strong binding requires that these interacting molecules have specific molecular features . We demonstrate that a peptidoglycan fragment that binds strongly can stimulate growth of dormant bacteria , but that it does not affect growth of non-dormant bacteria . We also show that PknB localizes to the site of cell division and to the growing tip of the bacterium , where cell wall synthesis and degradation occur , and that the extracytoplasmic domain is required for this localization . These findings indicate that a major function of the extracytoplasmic domain of PknB is to place it at the sites of cell wall turnover , and suggest a model by which PknB can regulate growth and cell division , and thereby contribute to the pathogenesis of TB . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"biology"
] | 2011 | The Extracytoplasmic Domain of the Mycobacterium tuberculosis Ser/Thr Kinase PknB Binds Specific Muropeptides and Is Required for PknB Localization |
TDP-43 is a multifunctional nucleic acid binding protein linked to several neurodegenerative diseases including Amyotrophic Lateral Sclerosis ( ALS ) and Frontotemporal Dementia . To learn more about the normal biological and abnormal pathological role of this protein , we turned to Caenorhabditis elegans and its orthologue TDP-1 . We report that TDP-1 functions in the Insulin/IGF pathway to regulate longevity and the oxidative stress response downstream from the forkhead transcription factor DAF-16/FOXO3a . However , although tdp-1 mutants are stress-sensitive , chronic upregulation of tdp-1 expression is toxic and decreases lifespan . ALS–associated mutations in TDP-43 or the related RNA binding protein FUS activate the unfolded protein response and generate oxidative stress leading to the daf-16–dependent upregulation of tdp-1 expression with negative effects on neuronal function and lifespan . Consistently , deletion of endogenous tdp-1 rescues mutant TDP-43 and FUS proteotoxicity in C . elegans . These results suggest that chronic induction of wild-type TDP-1/TDP-43 by cellular stress may propagate neurodegeneration and decrease lifespan .
TDP-1 is the Caenorhabditis elegans orthologue of the multifunctional DNA/RNA binding protein TDP-43 ( TAR DNA Binding Protein 43 ) . Mutations and accumulations of TDP-43 have been found in patients with Amyotrophic Lateral Sclerosis ( ALS ) , Frontotemporal Dementia , and in a growing number of neurodegenerative disorders [1] . As part of its numerous roles in RNA metabolism , TDP-43 is a component of the cytoplasmic ribonucleoprotein complexes known as stress granules that form in response to environmental stresses like heat shock , oxidative and osmotic stress among others [2] , [3] . ALS is an age-dependent neurodegenerative disorder and given that TDP-43 is a stress responsive protein we hypothesized that TDP-1 may regulate longevity and the cellular stress response . In worms a major axis of stress-response signaling and longevity is the Insulin/IGF-signaling ( IIS ) pathway . IIS follows an evolutionarily conserved and genetically regulated pathway that regulates numerous processes including development , metabolism , fecundity , cellular stress resistance and aging [4] . In C . elegans , IIS initiates a phosphorylation cascade through the DAF-2/Insulin-IGF receptor that phosphorylates the forkhead transcription factor DAF-16 and retains it in the cytoplasm [5]–[8] . Hypomorphic daf-2 mutants relieve DAF-16 phosphorylation causing DAF-16 to translocate to the nucleus where it activates a large number of genes resulting in increased lifespan and augmented stress resistance [9] . daf-2 mutants are also resistant to numerous stresses including oxidative , osmotic , thermal and proteotoxicity [10] . The IIS pathway likely employs multiple mechanisms to combat a variety of cellular insults but little is known about how these separate functions are regulated by DAF-16 . We attempted to address this issue by asking whether TDP-1 participated in the cellular stress response and longevity pathways in C . elegans . We asked if TDP-1 participated in the IIS pathway to specify developmental , stress response , and longevity outcomes . Given the importance of human TDP-43 to neurodegeneration we also asked if tdp-1 regulated age-dependent proteotoxicity . Our work points to TDP-1 as a key stress response protein at the crossroads of IIS , proteotoxicity and endoplasmic reticulum ( ER ) stress . Moreover , persistent induction of TDP-1 may actively promote neurodegeneration .
Downregulation of DAF-2 extends lifespan and promotes stress resistance via regulation of DAF-16 transcriptional activity [9] . To determine if tdp-1 participated in the IIS pathway we used a deletion mutant tdp-1 ( ok803 ) that removes the two RNA Recognition Motifs of TDP-1 ( Figure S1A ) . Looking directly at the IIS pathway and longevity , daf-2 ( e1370 ) animals were long-lived but this phenotype was significantly reduced in a daf-2 ( e1370 ) ;tdp-1 ( ok803 ) double mutant strain ( Figure 1A , Table S1 ) . Conversely , daf-16 ( mu86 ) mutants were short-lived compared to wild type worms and the inclusion of tdp-1 ( ok803 ) did not further reduce daf-16 mutants' lifespan ( Figure 1A , Table S1 ) . We confirmed that tdp-1 regulated daf-2 mediated longevity with RNA interference and observed that tdp-1 ( RNAi ) reduced the extended lifespan of daf-2 mutants ( Figure 1B , Table S1 ) . These data suggest that tdp-1 regulates the lifespan phenotypes of reduced IIS and the inability of tdp-1 to further reduce daf-16 lifespan suggests that this effect is dependent on daf-16 . Surprisingly , despite tdp-1 ( ok803 ) limiting the extreme lifespan of daf-2 mutants we observed that at 20°C tdp-1 ( ok803 ) mutants had a small but significant increase in lifespan versus N2 controls ( Figure 1C , Table S1 ) . However this effect was lost when the worms were grown at 25°C ( Figure 1D , Table S1 ) suggesting that tdp-1 may respond to stressful environmental conditions . Consistently , opposite to reducing tdp-1 function , overexpression of TDP-1 fused to GFP from the endogenous tdp-1 promoter ( tdp-1p::TDP-1::GFP ) greatly reduced lifespan compared to wild type N2 worms and tdp-1 deletion mutants at 20°C ( Figure 1E ) . The lifespan of a tdp-1 ( ok803 ) ;TDP-1::GFP strain was greater than TDP-1::GFP alone , but less than either N2 worms or the tdp-1 ( ok803 ) deletion mutant ( Figure 1E , Table S1 ) . Finally , TDP-1::GFP transgenics showed a further decrease in mean and maximum lifespan when grown at 25°C compared to N2 worms ( Figure 1F , Table S1 ) . These data show that tdp-1 has a dose-dependent effect on lifespan in worms and that lifespan is sensitive to tdp-1 expression levels , which is consistent with studies of TDP-43 in flies [11] and mice [12] where overexpression also reduces lifespan . Intimately linked to IIS regulation of lifespan in worms is dauer formation and stress resistance [4] . daf-2 ( e1370 ) mutant larvae show near complete dauer formation when grown at 25°C , but this phenotype was not altered in daf-2 ( e1370 ) ;tdp-1 ( ok803 ) mutants ( Figure S2A ) suggesting that tdp-1 does not function in the dauer formation axis of IIS in worms . To further define the role of tdp-1 in the in vivo stress response , we challenged worms against juglone induced oxidative stress . Juglone is a natural product derived from the black walnut tree that raises intracellular oxide levels [13] . Adult wild type N2 worms transferred to juglone plates showed complete mortality after 14 hours , while daf-2 ( e1370 ) worms were completely resistant ( Figure 2A ) . If tdp-1 were required for protection against stress we would expect the mutant tdp-1 worms to be hypersensitive to juglone-induced toxicity . Interestingly , tdp-1 ( ok803 ) mutants were more sensitive to juglone than N2 worms , and tdp-1 ( ok803 ) completely abolished daf-2's resistance to juglone in the daf-2 ( e1370 ) ;tdp-1 ( ok803 ) double mutant strain ( Figure 2A ) . To corroborate the role of tdp-1 in resistance to oxidative stress we used hydrogen peroxide , which is another oxidative stress enhancer . Tested on hydrogen peroxide plates we observed that tdp-1 ( ok803 ) animals were more sensitive than wild type N2 worms , and tdp-1 ( ok803 ) sensitized the normally resistant daf-2 animals to stress-induced mortality ( Figure 2B ) . These data show that tdp-1 is required for daf-2 mediated resistance to oxidative stress . Given the effect of tdp-1 ( ok803 ) on daf-2 mutants' stress resistance compared to the lack of effect on dauer phenotypes we wondered if tdp-1 might have a more specific role in the stress response axis of IIS . Not all forms of stress are equal at the cellular level so we investigated several additional forms of cellular stress including hypertonic stress with elevated sodium chloride ( NaCl ) or sorbitol , increased temperature , low oxygen and ultraviolet irradiation . Compared to N2 worms , tdp-1 mutants were sensitive to hypertonic stress from NaCl ( Figure 2C ) . Interestingly , both daf-2 ( e1370 ) and daf-2 ( e1370 ) ;tdp-1 ( ok803 ) mutants were resistant to this hypertonic stress suggesting that tdp-1 may not function , or may function in parallel to the IIS pathway to regulate the response to osmotic stress . To confirm this hypothesis we used sorbitol , another hypertonic stress producer , and similarly observed that tdp-1 ( ok803 ) mutants were sensitive to osmotic stress but daf-2 ( e1370 ) and daf-2 ( e1370 ) ;tdp-1 ( ok803 ) mutants were both resistant after either 14 hours ( Figure 2D ) or 48 hours of exposure ( Figure S2B ) . Finally , tdp-1 had no discernable role in the response to thermal stress , hypoxia , or radiation since there was no difference between N2 and tdp-1 ( ok803 ) worms , as well as daf-2 ( e1370 ) and daf-2 ( e1370 ) ;tdp-1 ( ok803 ) mutants in response to these stresses ( Figure S2C–S2E ) . Thus , tdp-1 functions in the IIS pathway to specify the response to oxidative stress and lifespan , but tdp-1 is dispensable for the regulation of hypertonic stress by the IIS pathway . A second tdp-1 deletion allele , ok781 , was available for investigation and although we observed that tdp-1 ( ok781 ) animals had a modest increase in lifespan , they were statistically indistinguishable from wild type N2 worms in stress assays ( Figure S3 ) . A component of DAF-2's response to cellular stress is induction of DAF-16 stress response genes [9] . Thus we examined if DAF-16 targets implicated in oxidative stress signaling were affected by tdp-1 . We used RT-PCR to examine expression levels of three DAF-16 genes including the catalases ctl-1 and ctl-2 , as well as the superoxide dismutase sod-3 in various genetic backgrounds . First of all , no expression of tdp-1 was observed in strains containing the deletion allele tdp-1 ( ok803 ) ( Figure 2E ) . Next we observed that ctl-1 and clt-2 expression levels were unaltered by the deletion of tdp-1 , either alone or in combination with daf-2 ( e1370 ) ( Figure 2E ) . However , we observed that sod-3 expression was greatly reduced in daf-2 ( e1370 ) ;tdp-1 ( ok803 ) animals ( Figure 2E ) . These data suggest that under low IIS conditions tdp-1 is required for the expression of certain DAF-16 targets implicated in oxidative stress and may partially explain the sensitivity of tdp-1 mutants to juglone and hydrogen peroxide . Given the remarkable sensitivity of tdp-1 ( ok803 ) mutants to oxidative and osmotic stresses we next wanted to see if there were in vivo changes in TDP-1 expression in response to these two stress conditions . In wild type unstressed animals TDP-1::GFP is lowly expressed ( Figure 3A ) , primarily nuclear and is expressed in most tissues ( Figure 3B–3D ) . We next tested if shifting TDP-1::GFP animals to either NaCl or juglone plates affected TDP-1::GFP expression . Young adult TDP-1::GFP worms were exposed to either NaCl or juglone for 90 minutes and live animals were examined for changes in TDP-1::GFP expression . Strikingly , exposure to hypertonic or oxidative stress greatly increased TDP-1::GFP expression compared to untreated control worms as detected by visual inspection and quantification of images ( Figure 3E and Figure S4A ) . Endogenous tdp-1 was not required for expression of the TDP-1::GFP transgene since expression was induced by stress in tdp-1 ( ok803 ) deletion mutants ( Figure 3F and Figure S4B ) . As a control for generic effects of stress on transgene expression we tested two other strains and observed no induction with a neuronal GFP reporter , while juglone and NaCl induced expression of the well-characterized sod-3p::GFP reporter ( Figure S5 ) . Having shown that our TDP-1::GFP transgenics are potent stress reporters , using daf-2 and daf-16 mutants we tested if IIS regulated this effect . We observed that TDP-1::GFP was highly induced in the daf-2 ( e1370 ) ;TDP-1::GFP strain ( Figure 3G ) compared to TDP-1::GFP controls ( Figure 3A ) and was further elevated in daf-2 ( e1370 ) mutants exposed to stress ( Figure 3G and Figure S4C ) . Given the pleiotropic phenotypic effects of daf-2 mutations we tested another allele and observed that opposite to e1370 , TDP-1::GFP expression remained low under normal and stress conditions in the presence of the daf-2 ( e1368 ) mutation ( Figure 3H and Figure S4C ) suggesting a complex role for IIS in TDP-1 expression . Looking deeper into the IIS pathway , previous research has shown that the increased stress resistance of daf-2 mutants is dependent on daf-16 mediated nuclear transcription [14] . TDP-1::GFP was not upregulated by mutation in daf-16 under normal conditions ( Figure 3I ) . Next , to directly test if daf-16 was essential for the stress dependent induction of tdp-1 we exposed daf-16 ( mu86 ) ;TDP-1::GFP transgenics to stress . Exposure to NaCl continued to induce TDP-1::GFP expression in daf-16 mutants ( Figure 3I ) while treatment with juglone failed to induce TDP-1::GFP expression in the daf-16 mutants ( Figure 3I and Figure S4D ) . These data suggest that the expression of TDP-1 in response to oxidative stress is dependent on daf-16 , while induction of TDP-1 by osmotic stress is independent , which is consistent with our data showing that tdp-1 is not required for daf-2's resistance to hypertonic stress ( Figure 2C and 2D ) . Additionally , the upregulation of TDP-1::GFP in daf-2 ( e1370 ) mutants was abolished by daf-16 ( RNAi ) directly linking the IIS pathway to tdp-1 expression ( Figure S6A and S6B , and Figure S4E ) . Finally , stress resistance and lifespan phenotypes from low IIS requires nuclear localization of DAF-16 and transcriptional activation of target genes [6] , [9] , [14] but we observed that tdp-1 ( ok803 ) had no effect on DAF-16::GFP stress-induced nuclear localization ( Figure S6C–S6F ) . Since TDP-43 is known to shuttle between the nucleus and cytoplasm we wondered if the subcellular distribution of TDP-1::GFP was altered under stress conditions . Examining TDP-1::GFP animals under high magnification we observed that when exposed low IIS from the daf-2 ( e1370 ) mutation TDP-1::GFP was no longer restricted to the nucleus and was observed in the cytoplasm ( Figure 3J and 3K ) . These data suggest stress and/or low IIS significantly influences the expression and cellular distribution of TDP-1 proteins . To make certain that the induction of TDP-1 by stress was not a phenomenon restricted to our transgenic reporter strain we examined endogenous TDP-1 protein levels under normal and stress conditions . Using a monoclonal antibody against C . elegans TDP-1 ( Figure S7 ) and western blotting we observed a significant increase in TDP-1 protein levels in N2 worms exposed to hyperosmotic or oxidative stress compared to untreated controls ( Figure 4A ) . To confirm the opposing effects of daf-2 mutations on TDP-1 expression we examined daf-2 ( e1370 ) and daf-2 ( e1368 ) mutants under normal and stressed conditions . As seen with our TDP-1::GFP reporter strain , we observed that TDP-1 protein levels were elevated in daf-2 ( e1370 ) animals , and we observed a further increase in TDP-1 levels in daf-2 ( e1370 ) animals exposed to oxidative stress ( Figure 4B ) . Consistent with what we observed in the daf-2 ( e1368 ) ;TDP-1::GFP animals , we observed that TDP-1 protein levels remained low in daf-2 ( e1368 ) animals under normal and stress conditions ( Figure 4C ) . Finally , endogenous TDP-1 protein was lowly expressed in daf-16 mutants , greatly increased upon exposure to osmotic stress , but again remained low in daf-16 animals treated with juglone ( Figure 4D ) in agreement with our findings with the daf-16 ( mu86 ) ;TDP-1::GFP reporter strain . In summary , TDP-1 is a stress responsive protein whose expression is greatly influenced by the IIS pathway especially in the context of oxidative stress . Our findings begin to outline a complex role for TDP-1 in lifespan and the cellular stress response in relation to the IIS pathway . As one of our main interests is understanding the role of aging and stress signaling in the context of age-dependent neurodegeneration we next investigated how proteotoxicity contributed to these processes . A feature of many late neurodegenerative disorders is proteotoxic stress caused by misfolded proteins and mutations in human TDP-43 are believed to cause proteotoxicity leading to neuronal dysfunction and cell death [15] . We examined this directly with transgenic worm strains expressing human wild type and mutant TDP-43 in worm motor neurons [16] . HSP-4 is a C . elegans Hsp70 protein orthologous to mammalian Grp78/BiP , and the transgenic C . elegans hsp-4p::GFP reporter is activated in response to misfolded proteins within the endoplasmic reticulum ( ER ) , including chemically by compounds like tunicamycin ( Figure 5A and 5B ) [17] . Using this reporter we observed that transgenic strains expressing wild type TDP-43 did not induce reporter expression whereas transgenics expressing mutant TDP-43 strongly induced hsp-4p::GFP expression ( Figure 5C and 5D ) . These data indicate that mutant TDP-43 toxicity may activate the ER unfolded protein response ( UPRER ) . We did not observe induction of GFP in reporter strains for the mitochondrial chaperones hsp-6/Hsp70 and hsp-60/Hsp10/60 or the cytoplasmic chaperone hsp-16 . 2/Hsp16 ( Figure S8 ) . Since we identified TDP-1 as a stress responsive protein we wondered if it also responded to ER and proteotoxic stress . We noticed increased expression of TDP-1::GFP in worms grown on plates with the ER stress inducing compound tunicamycin compared to untreated controls ( Figure 6A and 6B ) . Looking at proteotoxic stress with our TDP-43 transgenics we observed that wild type TDP-43 had no effect on TDP-1::GFP expression while mutant TDP-43 strongly induced TDP-1 expression ( Figure 6C and 6D , and Figure S4F ) . To confirm that induction of TDP-1::GFP was due to protein misfolding and proteotoxicity and not to an artifact of mutant TDP-43 transgenes we examined another proteotoxicity model based on the expression of wild type and mutant human FUS in motor neurons [16] . FUS is a nucleic acid binding protein related to TDP-43 that has also been implicated in ALS and dementia and the expression of an ALS-linked FUS allele in C . elegans motor neurons produces degenerative phenotypes similar to mutant TDP-43 [16] . Similar to the TDP-43 model , we observed no effect on TDP-1 expression from wild type FUS but mutant FUS greatly induced TDP-1 expression ( Figure 6E and 6F , and Figure S4F ) . These data suggest that misfolded mutant TDP-43 and FUS initiate the UPRER , which in turn activates expression of TDP-1 . Finally , activation of TDP-1 by ER stress converged on the IIS since induction of TDP-1::GFP expression by tunicamycin was blocked by a null mutation in daf-16 ( Figure 6G ) . A consequence of processing misfolded proteins within the ER is the production of reactive oxygen species as part of what is termed the integrated stress response [18] . Our data show that tdp-1 responds to oxidative stress in a daf-16 dependent matter so we hypothesized that the ER stress produced from mutant TDP-43 and FUS may generate oxidative stress thus linking proteotoxicity to the IIS pathway . To test this hypothesis we stained our transgenic TDP-43 and FUS strains with dihydrofluorescein diacetate ( DHF ) , a compound that fluoresces when exposed to intracellular peroxides associated with oxidative stress [18] . We observed no DHF signal from wild type TDP-43 and FUS transgenics but strong fluorescence from mutant TDP-43 and transgenics ( Figure 7A–7D ) . These data suggest that in addition to activating the UPRER mutant TDP-43 and FUS generate oxidative stress . To further establish the link between proteotoxicity and the IIS we examined the subcellular localization of DAF-16 . DAF-16::GFP is typically cytoplasmic under non-stressed and/or low insulin signaling conditions ( Figure 7E ) . Consistently we observed nuclear localization of DAF-16 in a TDP-43[A315T];DAF-16::GFP strain indicating that mutant TDP-43 causes cellular stress that is transmitted by the IIS pathway ( Figure 7F ) . Several studies have shown that reduced daf-2 function suppresses proteotoxicity [19]–[22] . However we found that daf-2 mutations have opposite effects on TDP-1 expression and if elevated TDP-1 expression were cytotoxic then we would expect to see opposing effects of daf-2 ( e1368 ) and daf-2 ( e1370 ) on TDP-43 toxicity in our models . To examine this directly we created daf-2 ( e1368 ) ;TDP-43[A315T] and daf-2 ( e1370 ) ;TDP-43[A315T] strains and scored paralysis phenotypes . Interestingly , we observed that daf-2 ( e1368 ) suppressed paralysis while daf-2 ( e1370 ) enhanced paralysis compared to TDP-43[A315T] alone ( Figure 8A ) . This intriguing finding suggests that daf-2 can have variable effects on proteotoxicity . Furthermore , daf-2 ( e1368 ) significantly reduced the motor neuron degeneration caused by mutant TDP-43 [16] while daf-2 ( e1370 ) enhanced degeneration ( Figure 8B ) . Since the IIS pathway is believed to regulate the expression of numerous protein quality control genes we examined if the two daf-2 alleles had an effect on misfolded mutant TDP-43 with a biochemical assay to detect protein aggregation . Here , homogenized protein extracts from transgenic worms are separated into two fractions , supernatant ( detergent-soluble ) and pellet ( detergent-insoluble ) and by western blotting with human TDP-43 antibodies we have previously shown that mutant TDP-43 is prone to aggregation and is highly insoluble [16] . Looking at protein extracts from TDP-43[A315T] , daf-2 ( e1368 ) ;TDP-43[A315T] , and daf-2 ( e1370 ) ;TDP-43[A315T] animals we observed that daf-2 ( 1368 ) greatly reduced the amount of insoluble TDP-43 compared to control transgenics while daf-2 ( e1370 ) had no effect ( Figure 8C ) . In summary these data suggest that different daf-2 alleles have widely variable effects on proteotoxicity but are consistent for each allele: e1368 reduces mutant TDP-43 insolubility , suppresses mutant TDP-43 induced paralysis , neurodegeneration , and keeps TDP-1 expression low while e1370 has no effect on protein insolubility , enhances paralysis , neurodegeneration and induces TDP-1 expression . Although loss of tdp-1 sensitizes worms to oxidative and osmotic stress , elevated and chronic expression of TDP-1 leads to decreased lifespan suggesting that the induction of TDP-1 by proteotoxicity , oxidative stress or the IIS pathway may exacerbate neuronal toxicity and decrease neuronal survival . We directly tested this hypothesis by crossing TDP-1::GFP worms with our mutant TDP-43[A315T] and FUS[S57Δ] transgenics and scored for survival and the onset of paralysis . We observed that TDP-43[A315T] and FUS[S57Δ] strains containing the TDP-1::GFP transgene had significantly decreased lifespans compared to control transgenics ( Figure 9A and 9B , Table S1 ) . The expression of either mutant TDP-43[A315T] or FUS[S57Δ] causes motility defects leading to progressive paralysis and strains also expressing TDP-1::GFP had accelerated rates of paralysis compared to single transgenic controls ( Figure 9C and 9D ) . These data suggest that induction of wild type TDP-1 expression by proteotoxicity has negative consequences on survival and neuronal function . To rule out the possibility that the negative effects observed were simply due to transgene effects from TDP-1 overexpression we predicted that removing endogenous TDP-1 would reduce proteotoxicity . To test this we constructed TDP-43[A315T];tdp-1 ( ok803 ) and FUS[S57Δ];tdp-1 ( ok803 ) double mutant strains and observed that these animals had a significantly lower rate of paralysis compared to single transgenic TDP-43[A315T] or FUS[S57Δ] worms ( Figure 9E ) . The expression of mutant TDP-43[A315T] or FUS[S57Δ] is accompanied by the age-dependent degeneration of motor neurons that was reduced in tdp-1 ( ok803 ) mutants ( Figure 9F ) . Finally , to examine if protein misfolding was reduced in tdp-1 ( ok803 ) strains co-expressing mutant TDP-43 or mutant FUS , we examined the solubility of mutant TDP-43 and FUS proteins with our biochemical assay [16] . We observed no change in protein solubility after deletion of the endogenous tdp-1 suggesting that the protective effects are not due to down-regulation or clearance of mutant proteins ( Figure 9G and 9H ) .
This work identified tdp-1 as a key stress responsive gene at the interface of longevity , stress resistance and neurodegeneration ( Figure 10 ) . The role of TDP-1 in lifespan is complex and suggests that worms like other species are sensitive to TDP-1/TDP-43 levels [23]–[26] . TDP-1 overexpression reduces lifespan while deletion of tdp-1 in unstressed worms promotes a modest increase in lifespan but leaves worms sensitive to specific environmental stresses . TDP-1 also has a complex role in the cellular stress response . We showed here that TDP-1 specifies the response to cellular stress with roles in oxidative , osmotic and protein-misfolding stress , but independent of high temperature , low-oxygen and damage from radiation . TDP-43 is a component of the ribonucleoprotein complexes known as stress granules that form under stressful conditions where they perform molecular mRNA triage where mRNAs are sorted for storage , degradation , or translation during stress and recovery [3] . The stress-inducible aspect of TDP-1/TDP-43 function likely reflects an ancient mechanism for enduring acute environmental stress until conditions improve . While the role of TDP-43 in response to acute stress is being actively studied [27]–[29] , its role in response to chronic stresses like protein misfolding during aging is unknown . Although the tdp-1 alleles ok803 and ok781 are predicted to be molecular null alleles they did not show identical phenotypes . Both alleles extended lifespan but ok781 did not affect several stress phenotypes . The difference between the two alleles is that ok781 still maintains the putative Nuclear Localization Signal ( Figure S1 ) and any potential protein product may behave differently than ok803 . Furthermore our predictions show that the ok781 allele may also produce an amino acid sequence with no known homology thus limiting its biological relevance . We believe the lifespan and stress phenotypes observed in the tdp-1 ( ok803 ) mutants are truly linked to this gene based on several lines of experimental evidence . Concerning the lifespan phenotypes , tdp-1 ( RNAi ) reduces the long-lived phenotype of daf-2 ( e1370 ) worms in agreement with the tdp-1 ( ok803 ) ;daf-2 ( e1370 ) strain mutant . We also tested if introducing wild type tdp-1 DNA sequence could rescue the long-lived phenotype of tdp-1 ( ok803 ) mutants . Using a strain expressing a full length TDP-1 open reading frame driven by the endogenous tdp-1 promoter we observed that it could partially rescue the extended lifespan phenotype of tdp-1 ( ok803 ) mutants . This is a direct proof that the lifespan phenotypes we observe in tdp-1 ( ok803 ) mutants is due to loss of the sequence and that we can correct this phenotype by introduction of wild type tdp-1 sequence . We corroborated the role of tdp-1 in the cellular stress response with several experimental approaches . First , tdp-1 ( ok803 ) mutants are sensitive to oxidative and osmotic stress and we observed that our TDP-1::GFP reporter is induced by these same stresses . Second , western blotting with a TDP-1 antibody showed that endogenous TDP-1 protein levels are also induced by oxidative and osmotic stress . Third , our genetic experiments with tdp-1 ( ok803 ) showed that these mutants are sensitive to oxidative stress via the IIS pathway , but sensitivity to osmotic stress is independent of the IIS pathway . Our experiments with the TDP-1::GFP reporter or immunoblotting with the TDP-1 antibody fully support the observations made with the tdp-1 ( ok803 ) mutant . Finally , tdp-1 ( ok803 ) suppresses proteotoxicity while TDP-1::GFP enhances toxicity . Again , this is akin to a classic genetic rescue experiment and provides direct evidence that the phenotype observed by deletion of tdp-1 can be modified by the introduction of wild type tdp-1 sequence . In total we believe our hypothesis that tdp-1 has roles in lifespan and stress is well supported by multiple approaches . It is not clear why we see very little effect for the ok781 allele in stress assays , but at the same time there is not yet general consensus for any of the phenotypes observed for the tdp-1 mutants . An early location for mutant TDP-43 and FUS toxicity may be within the ER . The ER has critical cellular functions including protein folding , and misfolded proteins within the ER cause stress leading to activation of the UPRER to restore homeostasis [30] . Cellular insults can lead to increased protein misfolding as can the expression of genetically encoded proteins like mutant TDP-43 or FUS [16] . Early phases of the UPRER are protective but ER stress also stimulates the clearance of misfolded proteins from the ER through ER-associated degradation ( ERAD ) by transporting misfolded proteins from the ER lumen to the cytoplasm for degradation by the ubiquitin-proteasome . ERAD is energetically costly , redox intense and leads to substantial production of oxidative stress and if the ER stress is not resolved it can lead to cell death [30] . We hypothesize that protein misfolding is an early step in neurodegeneration that may result in at least three overlapping mechanisms of toxicity: primary toxicity from misfolded proteins , secondary toxicity from increased oxidative stress and tertiary toxicity propagated by stress induced TDP-1 expression ( Figure 10 ) . This feed forward mechanism originating in the ER may drive cytotoxicity and neurodegeneration . If this mechanism is conserved , these data may help explain why the intracellular accumulation of wild type TDP-43 is observed in a growing number of neurodegenerative disorders . Furthermore , given TDP-43's propensity to aggregate and its inherent cytotoxicity , wild type TDP-43 may actively contribute to neurodegeneration . Indeed recent hypotheses suggest that mutant proteins may act as seeds for the accumulation of wild type TDP-43 into pathogenic conformations as described for prion toxicity [31] . Our model complements the “two-hits” hypothesis for sporadic diseases that highlights the role of environmental stresses in combination with cytoplasmic accumulations of TDP-43 as part of the trigger for pathogenesis [32] . Proteostasis is essential to survival and healthy aging but gradually becomes less efficient as organisms age and may contribute to the accumulation of TDP-43 [33]–[35] . Add to this the stress-induced expression of TDP-43 and the cell is faced with increased cytoplasmic aggregation leading to pathogenesis . Many TDP-43 models have been described and they all show toxicity from the over expression of wild type TDP-43 , which is sometimes less toxic than mutant but not always [11] , [12] , [21] , [24] , [36]–[41] . These findings again demonstrate that control of TDP-43 levels is important for cell survival and that wild type TDP-43 may contribute to neuronal toxicity . We genetically tested this premise in C . elegans by creating transgenic strains that either overexpressed stress-activated TDP-1 or were missing the worm's endogenous tdp-1 . Paralysis and lifespan phenotypes of TDP-43 and FUS transgenics were worsened by increased expression of TDP-1 . Consistently , deletion of endogenous tdp-1 from strains expressing mutant TDP-43 or FUS remarkably reduced paralysis and motor neuron degeneration phenotypes . Taken together we directly showed that wild type tdp-1 plays an important role in neurodegeneration caused by mutant TDP-43 and FUS proteins . However two studies in C . elegans have shown no effect on TDP-43 toxicity in animals mutant for endogenous tdp-1 [24] , [37] while another study has shown that deleting tdp-1 reduces TDP-43 and SOD1 toxicity [42] . The reason for the differences are not clear but may be due to differences between models , where in our model animals express mutant TDP-43 in only 26 GABAergic motor neurons [16] while the other models described rely on the expression of TDP-43 transgenes throughout the worms entire nervous system [24] , [37] , [42] . In our model we observe adult-onset , progressive motility defects and neurodegeneration [16] , while the other models describe uncoordinated motility problems from earlier stages . It may be that the pan neuronal expression of TDP-43 in some models causes phenotypes that are too severe for modulation by reducing endogenous tdp-1 . Additionally , the fact that we see a reduction of mutant FUS toxicity by deleting tdp-1 bolsters the notion that proteotoxic induction of TDP-1 propagates toxicity and this may not be a phenomenon restricted to mutant TDP-43 . A surprising finding is that the UPRER appears to be activated in a cell non-autonomous manner . The hsp-4p::GFP reporter is expressed primarily in the worms intestinal cells while mutant TDP-43 and FUS are expressed in motor neurons . Thus ER stress generated within neurons is capable of signaling to other cells and tissue types perhaps as part of a coordinated organism wide response . Cell non-autonomous signaling has been described in C . elegans for mitochondrial stress regulating longevity [43] and the heat shock response [44] . Whether mutant TDP-43 and FUS similarly induce a system wide ER stress response in mammals awaits investigation . Concerning the regulation of lifespan , our work describes a complex relationship between tdp-1 and daf-2 . tdp-1 ( ok803 ) mutants have extended lifespan but are stress sensitive , while daf-2 ( e1370 ) ;tdp-1 ( ok803 ) mutants are stress sensitive and have decreased lifespan compared to daf-2 ( e1370 ) alone . In all systems examined increased TDP-43 expression is toxic [45] and there is widespread speculation in the field that wild type TDP-43 may contribute to cytotoxicity and neurodegeneration over long term settings [31] . Thus deleting tdp-1 from worms leaves them sensitive to stress but frees them from potential long-term cytotoxic effects . We are not alone in the observation that removing tdp-1 increases lifespan [42] but we are the first to look at tdp-1's role in the cellular stress response . Looking at daf-2 , the difference here may be that tdp-1 is essential for the stress resistance aspects of daf-2 mutants and concomitant long-lived phenotype . Thus removing tdp-1 renders daf-2 animals sensitive to stress induced damage limiting their extended lifespan . A surprising finding was the opposing effects of daf-2 mutations on proteotoxicity and TDP-1 expression . Several publications have reported that reduced daf-2 function suppresses proteotoxicity [19]–[21] . Our experiments are not fully comparable to these studies since some studies rely solely on daf-2 ( RNAi ) or on a single daf-2 allele ( e1370 ) to investigate proteotoxicity while we looked at two different daf-2 alleles , e1368 and e1370 . Further complicating the matter is the fact that some models are based on muscle-cell expression vectors and/or have severe developmental effects like the recently described TDP-43 model [21] . daf-2 mutations are grouped into a complex allelic series comprising two classes . Class 1 alleles are less severe and mutations fall within the extracellular regions of the DAF-2 receptor protein [46] . Class 2 alleles tend to be more severe , display pleiotropic effects and the mutations are found within the ligand binding area of the receptor or the tyrosine kinase domain [46] . Using the class 1 allele daf-2 ( e1368 ) and the class 2 allele daf-2 ( e1370 ) we observed that the two alleles had opposing effects on mutant TDP-43 toxicity and TDP-1 expression . In our mutant TDP-43 worms we observed that daf-2 ( e1368 ) suppressed mutant TDP-43 induced paralysis , while the class 2 allele daf-2 ( e1370 ) enhanced paralysis . Furthermore , daf-2 ( e1368 ) reduced the insolubility of mutant TDP-43 protein , while daf-2 ( e1370 ) had no effect on mutant TDP-43 solubility . Using a TDP-1::GFP reporter or western blotting with a TDP-1 antibody we observed that daf-2 ( e1370 ) increased the expression of TDP-1 while daf-2 ( e1368 ) had no effect . Given that the IIS pathway regulates both the toxicity of mutant TDP-43 proteins and the expression of endogenous TDP-1/TDP-43 , altered IIS may directly contribute to ALS pathogenesis . The pleiotropic and sometimes opposite effects of daf-2 are known and they are consistent within each class [46] . Regarding stress , a notable example is that class 1 daf-2 ( e1368 ) mutants are sensitive to hypoxia while class 2 daf-2 ( e1370 ) mutants are highly resistant to hypoxia [47] . Here we observe opposing effects for daf-2 on proteotoxicity and the cytotoxic induction of TDP-1 expression both of which are consistent for each allele . Our data are in agreement with studies showing that reduced IIS diminishes proteotoxicity but the question remains as to why the more severe class 2 daf-2 ( e1370 ) allele enhances toxicity in our TDP-43 transgenics . Part of the reason may lie with intrinsic differences between models . Our transgenics are based on the expression of TDP-43 in 26 GABAergic neurons and the worms do not show motor impairment until well into adulthood [16] while the other models show early effects and the animals are severely impaired by the time they reach adulthood [19] , [21] . Thus it may be that stronger daf-2 mutations are required to suppress severe phenotypes but are too strong for the milder , late-onset toxicity in our TDP-43 transgenics . There may be an optimal rate of IIS unique to each situation that has been referred to the Insulin Signalling Paradox [10] . Our data begin to shed light on this phenomenon where changes in signaling can have dramatically different effects and suggests that the role of IIS in neurodegeneration is more complicated that currently appreciated and requires further investigation . It is still unclear if mutant TDP-43 results in a gain , a loss of function or both but work from zebrafish and fly TDP-43 models suggest that it may be both [11] , [41] . Our data introduce a novel gain of function mechanism where the increased expression of wild type TDP-1 is induced by proteotoxic stress . Several strategies come to mind to alleviate the neuronal toxicity caused by wild type and mutant TDP-43 including reducing levels of wild type TDP-43 , mutant TDP-43 , and/or reducing UPRER stress by promoting protein folding . In the future it will be important to determine if strategies to reduce TDP-43 neuronal toxicity may be applicable to additional neurodegenerative disease as a shared mechanism of cell death in the development of new therapeutics .
Nematode strains used were described previously [16] or received from the Caenorhabditis elegans Genetics Center CGC ( St Paul , MN ) . All strains were maintained following standard methods on OP50 bacteria plates . Strains used in this study include: tdp-1 ( ok803 ) and tdp-1 ( ok781 ) both outcrossed 5 times to N2 prior to use , daf-2 ( e1368 ) , daf- 2 ( e1370 ) , daf-16 ( mu86 ) , gpIs1[hsp-16 . 2::GFP] , oxIs12[unc-47p::GFP;lin-15 ( + ) ] , xqIs93[tdp-1p::TDP-1::GFP] , xqIs132[unc-47p::TDP-43-WT;unc-119 ( + ) ] , xqIs133[unc-47p::TDP-43[A315T];unc-119 ( + ) ] , xqIs173[unc-47p::FUS-WT;unc-119 ( + ) ] , xqIs98[unc-47p::FUS[S57Δ];unc-119 ( + ) ] , zIs356[daf-16p::daf-16-gfp; rol-6] , zcIs4[hsp-4p::GFP] , zcIs9[hsp-60p::GFP] , gpIs1[hsp-16 . 2p::GFP] and zcIs13[hsp-6p::GFP] . Sixty synchronized L4 were grown on OP50 bacteria plates ( 20 animals/plate ) and three independent assays were performed . Lifespan analyses were performed at 20°C and 25°C and worms were scored every 1–2 days from adult day 1 until death . Worms were scored dead if they didn't respond to tactile or heat stimulus . RNAi-treated strains were fed with E . coli ( HT115 ) containing an Empty Vector ( EV ) , daf-16 ( R13H8 . 1 ) , or tdp-1 ( F44G4 . 4 ) RNAi clones from the ORFeome RNAi library ( Open Biosystems ) . RNAi experiments were performed at 20°C . Worms were grown on NGM enriched with 1 mM Isopropyl-b-D-thiogalactopyranoside ( IPTG ) . For lifespan , worms were transferred to RNAi 5-fluorodexyuridine ( FUDR , 12 . 5 mg/L ) plates at adult day 1 until death . Worms were declared dead if they didn't respond to tactile or heat stimulus . Experiments were conducted with 20 animals/plate by triplicates . Young adult daf-2 ( e1370 ) were allowed to lay eggs overnight at 20°C . The eggs were then transferred to 25°C and scored for dauer formation 5 days later . Three different trials on different days were performed . Stress tests were performed at 20°C ( oxidative , osmotic and UV stress ) , 25°C ( hypoxia ) and 37°C ( thermal stress ) . Worms were grown on NGM and transferred to NGM plates + 240 µM juglone ( oxidative stress ) , or NGM plates + 10 mM Hydrogen peroxide ( oxidative stress ) , or NGM plates + 400 mM NaCl ( osmotic stress ) , or NGM plates + 611 mM Sorbitol ( osmotic stress ) , all at adult day 1 . For the oxidative , osmotic and thermal stress assays , worms were evaluated for survival every 30 minutes for the first 2 hours and every 2 hours after up to 14 hours; for sorbitol we also performed a test over 48 hours , starting the counts after 14 hours on the compound . For UV irradiation , adult day 1 worms were transferred to NGM plates without any food source and exposed to UV ( 1200 J/m2 ) . Worms were then transferred to NGM plates with OP50 bacteria and died animals were counted every 2 hours till 14 hours after irradiation . For hypoxia experiments young adult animals were transferred to a new plate and subjected to low oxygen conditions with the AnaeroPack system ( Mitsubishi Gas Chemical America ) for 24 hours and assayed for survival . For all experiments nematodes were scored as dead if they were unable to move in response to heat or tactile stimuli . For all tests worms , 20 animals/plate by triplicates were scored . Gateway system ( Invitrogen ) compatible tdp-1 promoter and open reading frame plasmid clones were obtained from Open Biosystems and recombined with plasmid pDES-MB14 ( kindly donated by M . Vidal , Harvard ) , and verified by sequencing to create a tdp-1p::TDP-1::GFP plasmid , which was injected at 5 ng/µl into unc-119 ( ed3 ) animals along with myo-3p::mCherry , myo-2p::mCherry comarkers at 5 ng/µl and wild type transformants expressing GFP were kept . The transgene was integrated using UV radiation and wild type , GFP positive animals were kept for further study . Multiple stable transgenics were isolated and outcrossed to N2 4 times before use . Strain XQ93 xqIs93[tdp-1p::TDP-1::GFP] was used in this study . For visualization of TDP-1::GFP animals , M9 buffer with 5 mM levamisole was used for immobilization . Animals were mounted on slides with 2% agarose pads . TDP-1::GFP expression was visualized with a Leica CTR 6000 and a Leica DFC 480 camera . L4 animals were grown on NGM plates and transferred to NGM plates + 240 µM juglone ( oxidative stress ) or NGM plates + 400 mM NaCl ( osmotic stress ) for 90 minutes , and examined for fluorescence with the Leica system described above . Some animals were also stained with DAPI ( 1∶1000 , diluted in 1× PBS ) . Image processing was done with Adobe Photoshop . For images of TDP-1::GFP alone , images were converted to black and white and the images reversed to allow for better contrast and visualization . Quantification of TDP-1::GFP levels was done with ImageJ ( NIH ) and the mean and SD was calculated from 5 images for each strain and experimental condition . For visualization of DAF-16::GFP , hsp-4p::GFP , hsp-6p::GFP , hsp-16 . 2p::GFP and hsp-60p::GFP animals , M9 buffer with 5 mM levamisole was used for immobilization . Animals were mounted on slides with 2% agarose pads and examined for fluorescence with the Leica system described above . For visualization of oxidative damage in the transgenic strains the worms were incubated on a slide for 30 minutes with 5 mM dihydrofluorescein diacetate dye ( Sigma-Aldrich ) and then washed with 1× PBS three times . After the slide was fixed fluorescence was observed with the Leica system described above . RNA was extracted with an RNAeasy kit ( Qiagen ) and reverse transcribed with QuantiTect ( Qiagen ) . Primers used include: ctl-1 forward , AGGTCACCCATGACATCACCAAGT; ctl-1 reverse , GAT TGCGCTTCAGGGCATGAATGA; ctl-2 forward , TTCGCTGAGTTGAACAATCCG; ctl-2 reverse , GTTGCTGATTGTCATAAGCCATTGC; tdp-1 forward , AAAGTGGGATCGAGTGACGAC; tdp-1 reverse , GACAGCGTAACGAATGCAAAGC; sod-3 forward , CGAGCTCGAACCTGTAATCAGCCATG; sod-3 reverse , GGGGTACCGCTGATATTCTTCCACTTG; act-3 forward , GTTGCCGCTCTTGTTGTAGAC; act-3 reverse , GGAGAGGACAGCTTGGATGG . Worms were collected in M9 buffer , washed 3 times with M9 and pellets were placed at −80°C overnight . Pellets were lysed in RIPA buffer ( 150 mM NaCl , 50 mM Tris pH 7 . 4 , 1% Triton X-100 , 0 . 1% SDS , 1% sodium deoxycholate ) + 0 . 1% protease inhibitors ( 10 mg/ml leupeptin , 10 mg/ml pepstatin A , 10 mg/ml chymostatin LPC;1/1000 ) . Pellets were passed through a 271/2 G syringe 10 times , sonicated and centrifuged at 16000 g . Supernatants were collected . For TDP-43 and FUS transgenics , soluble/insoluble fractions , worms were lysed in Extraction Buffer ( 1 M Tris-HCl pH 8 , 0 . 5 M EDTA , 1 M NaCl , 10% NP40 + protease inhibitors ( LPC;1/1000 ) . Pellets were passed through a 271/2 G syringe 10 times , sonicated and centrifuged at 100000 g for 5 minutes . The soluble supernatant was saved and the remaining pellet was resuspended in extraction buffer , sonicated and centrifuged at 100000 g for 5 minutes . The remaining pellet was resuspended into 100 µl of RIPA buffer , sonicated until the pellet was resuspended in solution and saved . All supernatants were quantified with the BCA Protein Assay Kit ( Thermo Scientific ) following the manufacturer instructions . Worm RIPA samples ( 175 µg/well for transgenic worms; 15 µg/well for non transgenics ) were resuspended directly in 1× Laemmli sample buffer , migrated in 10% polyacrylamide gels , transferred to nitrocellulose membranes ( BioRad ) and immunoblotted . Antibodies used: rabbit anti-TDP-43 ( 1∶200 , Proteintech ) , rabbit anti-FUS/TLS ( 1∶200 , Abcam ) , rabbit anti-TDP-1 ( 1∶500 , Petrucelli laboratory ) and mouse anti-Actin ( 1∶10000 , MP Biomedical ) . Blots were visualized with peroxidase-conjugated secondary antibodies and ECL Western Blotting Substrate ( Thermo Scientific ) . Densitometry was performed with Photoshop ( Adobe ) . For lifespan and stress-resistance tests , survival curves were generated and compared using the Log-rank ( Mantel-Cox ) test , and 20–30 animals were tested per genotype and repeated at least three times . For progeny counts , dauer-formation assays and hypoxia tests the mean and SEM were calculated for each trial and two-tailed t-tests were used for statistical analysis . | TAR DNA Binding Protein 43 ( TDP-43 ) is implicated in several human age-dependent neurodegenerative disorders , but until now little was known about TDP-43's role in the aging process . Here we used the nematode Caenorhabditis elegans to study the role of the TDP-43 orthologue tdp-1 in aging and neurodegeneration . In this study we discovered that tdp-1 is a stress-responsive gene acting within the Insulin/IGF signaling pathway to regulate lifespan and the response to oxidative stress . We found that , although worms missing tdp-1 were stress-sensitive , elevated expression of tdp-1 was toxic . We asked if tdp-1 also responded to the stress caused by toxic proteins found in Amyotrophic Lateral Sclerosis ( ALS ) . Using worm models for ALS , we discovered that mutant TDP-43 generated oxidative stress and induced tdp-1 expression with negative consequences on neuronal function and lifespan . Consistently , removing tdp-1 rescued toxicity in our worm ALS models . tdp-1's role in the cellular stress response likely reflects an ancient adaptation to deal with unfavorable environmental conditions that is inappropriately activated and maintained by genetic mutations leading to proteotoxic and oxidative stress . We predict that similar mechanisms may exist in humans , helping explain the involvement of TDP-43 in a growing number of neurodegenerative disorders . | [
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"gene... | 2012 | TDP-1/TDP-43 Regulates Stress Signaling and Age-Dependent Proteotoxicity in Caenorhabditis elegans |
Computer studies are often used to study mechanisms of cardiac arrhythmias , including atrial fibrillation ( AF ) . A crucial component in these studies is the electrophysiological model that describes the membrane potential of myocytes . The models vary from detailed , describing numerous ion channels , to simplified , grouping ionic channels into a minimal set of variables . The parameters of these models , however , are determined across different experiments in varied species . Furthermore , a single set of parameters may not describe variations across patients , and models have rarely been shown to recapitulate critical features of AF in a given patient . In this study we develop physiologically accurate computational human atrial models by fitting parameters of a detailed and of a simplified model to clinical data for five patients undergoing ablation therapy . Parameters were simultaneously fitted to action potential ( AP ) morphology , action potential duration ( APD ) restitution and conduction velocity ( CV ) restitution curves in these patients . For both models , our fitting procedure generated parameter sets that accurately reproduced clinical data , but differed markedly from published sets and between patients , emphasizing the need for patient-specific adjustment . Both models produced two-dimensional spiral wave dynamics for that were similar for each patient . These results show that simplified , computationally efficient models are an attractive choice for simulations of human atrial electrophysiology in spatially extended domains . This study motivates the development and validation of patient-specific model-based mechanistic studies to target therapy .
Atrial fibrillation ( AF ) is the most common sustained cardiac arrhythmia and is associated with increased morbidity and mortality from stroke and heart failure [1] . Unfortunately , therapy for this condition is suboptimal due to its mechanistic complexity [2 , 3] . Because of difficulties in studying AF mechanisms in humans , and since animal models of AF may differ from human AF , mechanistic studies of arrhythmias are increasingly turning to computational modeling to bridge the gap between clinical unmet needs and cellular studies . Essential in these computational studies is the choice of the electrophysiological model which simulates the membrane potential through a set of parameterized equations that describe the ion channels . This model can range in complexity from detailed [4–8] , which describe as many channels as possible , to simplified [9–11] , which capture only essential dynamical features of cardiac tissue . However , these computational models are rarely validated in humans , and their parameters are typically based on imprecise , incomplete , or animal data . We set out to address this problem by developing computational models that recapitulate cellular and tissue behavior in human AF . We used three sets of clinically obtained data from the left atria in 5 different patients with clinical AF at invasive electrophysiological studies . The data included action potential ( AP ) morphology , excluding the upstroke due to pacing artifacts , AP duration ( APD ) , and conduction velocity ( CV ) restitution curves obtained during controlled pacing using a monophasic action potential ( MAP ) catheter , and maps of AF propagation obtained from direct contact wide-area multipolar basket catheters [12] . We used a simulated annealing fitting procedure to adjust the model parameters such that the numerical results fit the AP morphology and the restitution curves simultaneously . This was done first for the detailed Koivumäki et al ( KKT ) atrial myocyte model [7] which extends earlier detailed models [5 , 6] to account for Ca2+ dynamics in the sarcoplasmic reticulum . We show that our fitting procedure was able to generate parameter sets that accurately reproduce clinical data . These sets differ significantly between patients and are markedly different than the published one . We then fitted the clinical restitution curves and the full AP morphology obtained from the KKT model ( i . e . , including the upstroke ) to the simpler Fenton-Karma ( FK ) model [9] . We show that we are able to obtain parameters that can reproduce the clinical data and the fitted AP morphology well . Of note , a modeling sequence in which the FK model is fitted to clinical data , followed by a KKT fit to the FK output is equally possible . Finally , we simulated spiral wave reentry in two-dimensional sheets using the fitted parameters sets for both models in all patients . We find that the dynamics of the spiral waves are similar for each patient . This suggests that simplified , computationally efficient models can be used to investigate spatio-temporal dynamics of cardiac activation . Our study shows how numerical models can be tailored to patient-specific clinical data , an important step towards guiding therapy based on individual AF mechanisms .
We acquired data from 5 patients with atrial fibrillation undergoing ablation for standard clinical indications , of age 64 . 2±10 . 6 years , left atrial diameter 42±3 mm and left ventricular ejection fraction 60±10% . All patients were studied after discontinuing all anti-arrhythmic medications for over 5 half-lives ( amiodarone in 1 patient was discontinued 1 year earlier ) . MAPs were recorded during incremental pacing from slow heart rates to AF onset[13] . In brief , a deflectable 7F MAP catheter ( EP Technologies , Sunnyvale , CA ) was advanced to record AP in the antra of the right and left superior pulmonary veins . The protocol was completed before ablation . Patients in AF were electrically cardioverted to yield sinus rhythm , and the protocol started 10 minutes later . APs were recorded from distal poles of the MAP catheter while pacing the proximal poles . The close proximity of the recording and pacing poles necessitated special treatment for the first 30 ms of each AP morphology , as detailed in the Supporting Information . The resulting AP morphology captures repolarization but does not include the upstroke . We paced for >84 beats at each cycle length ( CL ) of 500 ( baseline ) , 450 , 400 , 350 , and 300 ms , then in 10 ms steps to AF or capture failure , whichever came first . Further details regarding signal processing , APD , and how activation time data was used to determine CV can be found in the Supporting Information . Simulations were carried out using the monodomain equation: dudt=D∇2u−IionCm where u is the membrane voltage , Cm represents the membrane capacitance , D is the diffusion coefficient ( 1D ) or isotropic tensor ( 2D ) and Iion represents the membrane currents . Simulations in our fitting procedure were carried out in homogeneous 1D cables , consisting of 100 elements with a spatial discretization of 0 . 02 cm and a time step of 0 . 01 ms using no-flux boundary conditions . Decreasing the time step to 0 . 005 ms adjusted the CV restitution values by less than 4 . 5% for the FK model , and less than 1 . 5% for the KKT model while decreasing the spatial discretization to 0 . 01 cm changed these values by less than 7% . For the 2D simulations , we solved the monodomain equations in isotropic sheets of at least 9 . 6x9 . 6 cm using a square computational grid , again with a spatial discretization of 0 . 02 cm and a time step of 0 . 01 ms using an explicit Euler method . Spiral wave reentry was generated through cross-activation and spiral tip trajectories were computed using a previously published algorithm [9] . It is also important to note that while all simulations were carried out with isotropic tissue , actual tissue is heterogeneous . Including tissue anisotropy would require more detailed data on tissue conduction and fiber orientation . Computations were performed using the C++ language and MPI parallelization on a high-performance workstation consisting of dual quad-core Xeon E5-2637 CPUs . Typical fitting simulations starting with the published parameters as initial conditions consisted of 50 iterations and required approximately 6 CPU hours for the FK model and 32 hours for the KKT model . This time can be significantly reduced if the initial parameter values are close to the final results . For instance , if two patients have similar dynamics , then the fitted parameters for one can be used as the starting point for the other . 2D simulations were performed on a GPU parallel computing platform with a Nvidia Tesla K40 graphics card . Computing 1000 ms of spiral wave propagation on a 512x512 grid required approximately 8 min for the FK model and 37 min for the KKT model . In this study , we employed a version of the FK model which consists of four variables , three gating variables and the membrane potential , and 24 parameters [14] . Three of these parameters were fixed ( see Supporting Information ) , resulting in 21 adjustable parameters . The KKT model consists of 43 variables and more than 100 parameters [5 , 7] and , as described in the Supporting Information , fits were carried out by allowing 21 parameters to vary ( S1 Table ) . When shifted 50% away from their original published values , each of these parameters was found to increase the error by 1 to 65% . Here , error is quantified as specified in the Supporting Information . Many of these parameters were shifted by even larger amounts in the final fits . We used a simulated annealing fitting procedure in which parameter values are repeatedly adjusted in an attempt to minimize error functions which compare the numerical results to the clinical data set ( see S1 Text ) . Unlike other algorithms , simulated annealing samples a large region of parameter space and does not automatically reject parameter choices that do not improve the fit [15] . This is done by assigning an artificial “temperature” which determines the amount of variation of parameters for each iteration and is slowly reduced during the fitting procedure [15] . Note that this temperature is a variable of the fitting procedure , and is not related to any physiological value in the models or data . This algorithm has been successfully applied to biological data [16 , 17] . Simulations were started from a high temperature [18] and typically consisted of 50 iterations after each of which we reduced the temperature by 10% .
In Fig 1A we show the clinically obtained AP morphologies for different CLs in one of the five patients , with voltage rescaled to span 0 and 1 and APD rescaled to 1 ( raw APD90 ranged from 223–313 ms ) . Importantly , AP shapes are roughly independent of the CL , allowing us to define an average AP morphology for all CLs . This morphology , after the first 10 ms due the pacing artifacts has been removed , is shown in Fig 1B , together with its high-order polynomial fit ( solid line ) . The resulting smooth AP morphology can then be used in the fitting procedure and can be adjusted to the required APD by a simple time dilation or contraction . Fig 2 shows examples of APD and CV restitution curves used in our fitting study for one of our patients ( #3 ) . Fig 2A shows APD restitution as a function of diastolic interval ( DI ) from the MAP data ( symbols ) along with a logarithmic fit ( S1 Text ) . The clinical data relating CV and CL for the same patient , together with the polynomial fit , is shown in Fig 2B while in Fig 2C we have plotted the DI as a function of CL . The CV restitution curve based on the polynomial fit in Fig 2B and the dependence of DI on CL shown in Fig 2C is plotted in Fig 2D . The CV data for the remaining patients are shown in S1 Fig and S2 Fig . As discussed above , the clinical data does not incorporate information about the AP upstroke . This upstroke , however , is largely responsible for the wave front dynamics and a meaningful comparison of spatio-temporal dynamics between the results of the KKT and the FK model is only possible if the upstroke in both models is similar . To enable such a comparison , we chose to first fit the clinical data to the KKT model . The resulting AP morphology , now including the upstroke , and clinical restitution curves were then used as fitting input to the FK model . This fitting sequence ensures that , in the case of a successful fit , the AP upstroke in both models is similar . We have verified that switching the order of the fitting procedure did not change the computational times in a significant manner . For the KKT model , we fitted the parameters to the clinical data of the 5 patients . The resulting values of the five parameter sets are listed in S2 Table . The parameters for the FK model , fitted to the KKT output , can be found in S3 Table . For one of the patients , #1 , we determined a second , alternate , set of parameters , by using different initial conditions for the parameter values . We quantified the accuracy of our fits by determining the average error for each fitted point ( see Methods ) . A full summary of the results is shown in Fig 3 , and discussed in more detail below . For reference , the percent error for the original published parameters of each model was also quantified . The average percent error in AP shape ranged from 100% to 226% for the FK model , and from 10% to 24% for the KKT model . The APD restitution ranged from 26% to 37% for the FK model , and 4 . 5% to 39% for the KKT model . The CV restitution ranged from 28% to 57% for the FK model , and 40% to 63% for the KKT model . We note that the original parameter set for the FK model was not chosen to describe atrial myocytes . Fig 4 shows the AP morphology , corresponding to the largest DI value , obtained in all patients as dashed lines . Even though AP morphologies are similar , they differed in their precise shapes . The resulting morphologies from the KKT model , using parameters obtained from the fitting procedure , are shown in red . In this Figure , we show the shapes corresponding to the largest S2 stimulus ( which differs for all patients ) that was applied during the S1-S2 pacing protocol . Also shown in Fig 4 , in blue , are the morphologies obtained by the FK model , fitted to the AP shapes from the KKT model . A visual inspection reveals that both models can accurately reproduce the AP morphology for these patients . We quantified the accuracy of our fits by determining the average error for each fitted point ( see Methods ) , and found that both models have a total error less than 6 . 8% when averaged over all S2s ( Fig 3 ) . The largest average error for a single S2 in the FK model was 11% ( patient 4 ) while the largest error in the KKT model was 8% ( patient 1 ) . Furthermore , as shown in S3 Fig , the upstroke of the AP is similar between the KKT and FK models . Fig 5 displays the polynomial fits to the clinically obtained APD restitution curves as gray symbols . Note that while the polynomial is a continuous function , only data points used for the model fits are shown . As expected , the general shape of this data is identical , with decreasing APD for decreasing DI [19] . The most noticeable difference between patients is the change in maximum APD values . While patient 1 only reaches to approximately 220 ms , the maximum APD of patient 5 is close to 380 ms . Furthermore , the maximum slope of the restitution curve was also different from patient to patient , ranging from 0 . 57 for patient 3 to 1 . 15 for patient 2 . Both models ( blue and red lines ) are shown to reproduce the gray symbols well and overlap for most of the DI range , demonstrating that the model parameters can be adjusted to reproduce a range of restitution curves . One noticeable difference between the two models is that for our fitted parameter sets the KKT model tends to have a larger slope than the FK model for DI less than 50ms . As for the AP morphology , we can quantify the percent error of the model fits ( Fig 3 ) . We found that for the KKT model the average error over the entire APD restitution curve was less than 1 . 5% for all patients . For the FK model , the average error was below 1% for all patients . Thus , there was little difference in the error between the FK and KKT models . The polynomial fits to the clinical CV restitution data are shown in Fig 6 as gray symbols . For three patients ( 2 , 4 , and 5 ) we found that this restitution curve is approximately flat while for patients 1 and 3 it decreases as the DI decreases . This is consistent with earlier reports that found that CV restitution can be flat or can decrease for decreasing DI [20] . The fits from both models are shown as solid lines and can be seen to match the clinical data over the entire range of DIs . The average error for the KKT model was found to be less than 1 . 3% for all patients ( Fig 3 ) while the largest single point error is for small DI in the patients with flat CV restitution where the fitted CV differs from the clinical CV by 5 . 3% ( patient 5 ) . The cumulative error in the FK model was less than 1 . 5% for all patients and the largest deviation from clinical CV is for small DI in patient 3 ( 6 . 9% ) . Two-dimensional spiral waves were generated for each of the fitted parameter sets in both models . Snapshots of the resulting activation pattern for each patient , including the alternate parameter set for patient 1 , are shown in Fig 7 where the membrane voltage in the KKT model is shown in a color scale and in the FK model in a gray scale with white ( black ) corresponding to high ( low ) voltage . Both models produced stable spiral waves in 4 out of 5 patients , with patient 2 exhibiting spiral wave breakup . In the lower row of Fig 7 we have plotted the trajectory of the spiral tips of the stable spirals ( red for the KKT model and blue for the FK model ) . The trajectories in the two models show a similar pattern for all patients , including the alternative set . The scale of the meander pattern is very similar for patient 1 and 4 while slightly different for patients 3 and 5 . The rotation period in the KKT model ranged from 125 ms ( patient 4 ) to 457 ms ( patient 5 ) . Spiral wave periods in the FK model were roughly similar , differing from 2% ( patient 2; 196 ms for the KKT model and 200 ms for the FK model ) to approximately 20% ( patient 5; 457 ms vs . 370 ms ) .
The present study performed detailed analyses of the ability of 2 computational models for atrial tissue , the detailed KKT model and the simpler FK model , to recapitulate APD and CV dynamics and AP morphology in a series of carefully studied patients with clinical AF . We found that the parameters of both the simplified and detailed models can be adjusted to reproduce clinically observed tissue behavior . We also found that these parameters varied significantly from patient to patient and from published parameter sets , indicating the need for personalized model building . Furthermore , we simulated the spiral wave reentry using the model equations parameterized by our fits . The spiral wave dynamics are qualitatively similar for each patient between models . The fact that simplified models produce results that can accurately fit clinical data , can generate similar spatio-temporal dynamics that is similar to the dynamics from detailed models , and have a small computational cost suggests that they might be better suited to model cardiac arrhythmias in spatially extended domains than computationally expensive detailed models . The current study is in several ways distinct from previous studies which attempted to fit computational models to data [21–25] . First , we used clinical data instead of animal or numerical data to modify the parameters of two computational models . Detailed AP and CV restitution data were obtained from the left atrium of 5 patients with clinical AF at electrophysiological study . Second , our fitting procedure was designed to fit not only temporal dynamics using single cell characteristics but also conduction velocity data , a measure of spatio-temporal dynamics . This was achieved by fitting simultaneously the AP morphology as well as APD and CV restitution curves and adjusting model parameters so as to minimize the difference between clinically determined and numerically obtained tissue characteristics . These tissue characteristics are widely considered to be essential features of cardiac tissue and were obtained using recording electrodes , thus representing measurements at discrete locations within the atrium . Thus , and in contrast to fitting schemes that attempt to fit in a sequential fashion , our final parameter set produces a morphology and restitution curves that are optimal fits to the entire clinical data set . Our results indicate that we are able to fit the clinical data equally well with the FK model and the KKT model . Both models produce fits that vary less than 7% for the AP morphology and approximately 1% for the APD and CV restitution curves . In our fitting algorithm we allowed parameter values to be increased or decreased by an order of magnitude in the KKT model and allowed a variable range in the FK model . These ranges can clearly be easily adjusted , for example using experimentally obtained restrictions of permissible values . We find that at least several parameters vary significantly ( > 2-fold ) from patient to patient and that every parameter varies significantly in at least one patient ( S2 and S3 Tables ) . In addition , we found that there exist multiple parameter sets that fit the clinical data equally well . This was determined by re-computing the best fit using different initial parameter values for patient 1 ( S2 and S3 Tables ) . The errors from the two different parameter set are roughly equivalent ( Fig 3 ) indicating that both sets have an equal goodness of fit . In the FK model we allowed nearly all parameters ( 21 ) to vary while in the KKT model 21 parameters were fitted with many more held constant ( S1 Table ) . These constant parameters were chosen based on their minimal effect on the AP morphology or because they are well-established ( for example , the cell size and volume ) . Not restricting the available parameter space by fixing these values will render the fitting procedure computationally unfeasible . It should be noted , however , that modifying which parameters can be varied is straightforward . Furthermore , we have explicitly verified that the inclusion of 11 more parameters did not result in an improvement in the fit ( see S4 Table ) . Our results demonstrate that there can be multiple parameter sets with equal goodness of fit . This is perhaps not surprising given the large dimensionality of the parameter space which can lead to multiple local minima [24 , 25] . Even reducing this dimensionality , however , does not necessarily guarantee a unique set of parameters that fit a specific data set . For example , we have explicitly verified that reducing the number of fit parameters in the KKT model to 5 ( gKs , gK1 , gNab , gCab and PNa ) can still lead to multiple parameter sets that fit the AP morphology and APD restitution within less than 1% error . For this , we created four trial parameter sets by randomly varying the parameters within ±50% of their original values . On average , each of the new , and distinct , parameter sets found by our fitting algorithm varied by 17 . 0% , 10 . 0% , 8 . 7% , and 13 . 6% from the original values ( S5 Table ) . Thus , even a reduced number of parameters can have multiple local minima in the goodness of fitness space . Of course , these sets produced identical AP morphology and APD restitution , but other model properties , including 2D or 3D activation dynamics , might differ . It is perhaps also not surprising that the parameter sets determined for the detailed KKT model differ from the published ones . The model parameters appear in the explicit descriptions of ion channels which take the form of coupled differential equations . However the structure of these equations and their parameters are derived not only from human ion channel or whole cell data but also from animal cells [26] , that may limit their general applicability to human modeling . In addition , the parameters are not always precisely determined , not all channels might be incorporated into the model , and some data is obtained at unphysiological temperatures . Indeed , several recent detailed comparative studies of detailed models has shown that they can exhibit dynamical behavior that is not consistent with cardiac tissue [27–29] . The fact that our current study produced parameter sets that widely varied from patient to patient points to the need of algorithms that can adjust parameters based on clinical data . This is important , as human atrial tissue is not homogeneous and different atrial cell types display different AP morphologies [30] . In addition , pathophysiological remodeling of atrial tissue is likely to be a heterogeneous process [31] and requires reformulating the channel parameters [32] . Thus , it is unlikely that a single set of parameters or perhaps even a single model is able to capture the behavior of the entire atrium , and the parameters will need to be adjusted . We used the results from our fits to simulate spiral wave dynamics in both the FK and KKT model . This is highly relevant for AF since recent mapping studies have revealed that spiral wave reentry plays a central role in AF [12 , 33] and that the position of these spiral waves are a promising target for localized ablation [34] . To better understand and address the role of reentry in cardiac tissue and the best way to ablate , simulations of ionic models in spatially extended domains with the characteristics of a particular patient are thus desirable . To facilitate this comparison we ensured that the upstroke of the AP was similar in both models . With a similar AP morphology and restitution curves , the two models produced spiral wave with very similar dynamics , including stability of the spiral wave , tip trajectory and the spiral wave period . The slight differences between the two models are likely due to electrotonic effects and memory effects [35] that act at timescales that are longer than single stimuli [36] . The comparison between the two models suggests that simplified models might be more advantageous to use in simulations of spatially extended phenomena than detailed models . Clearly , simulating detailed models is computationally expensive , as it requires solving a large set of stiff differential equations and to date , only a limited number of computational studies have been carried out using detailed models in 2 [37] and 3D [38–40] . The FK model , and similar simple models , on the other hand , are computationally much more efficient than detailed models [29 , 41] , and have been extensively used to model cardiac dynamics of single cells and in 2D [42] and 3D geometries [14 , 43] . This comes , of course , at the expense of detailed knowledge about the precise role of the channels in normal and abnormal cardiac rhythms . Nevertheless , as we have shown here , the parameters of simplified models can be adjusted to represent clinical data with equal precision compared to detailed models . Thus , detailed models might not represent cardiac tissue dynamics more precisely than simplified models , making the latter attractive choices for simulations of phenomena that do not depend on specific ion channels or if computational speed is critical . Our fitting procedure is not limited to the data sets we used here and other clinically relevant data can be incorporated . For example , it is possible to include data about the onset of alternans , implicated in the initiation of AF [13 , 44] , without altering the fitting scheme . On the other hand , data that is inherently spatially extensive , for example spiral wave rotation periods , would require simulating activation fronts in 2D . If combined with AP morphology and restitution curve data , it should be possible to use that data to fit model parameters in a simultaneous fashion . Of note , that type of data requires high resolution mapping of activation fronts and is currently unavailable in humans . In addition , modifications in our fitting procedure in which , for example , the AP morphology counts more than the restitution curves are straightforward to implement . It should also be clear that our methodology can be applied to other cardiac tissue , including the right atrium and the ventricles . Furthermore , it can be used to fit data obtained in different parts of the atrium , thus generating model parameters that are adjusted in a regional fashion . The electrophysiological models that are then created can be combined with detailed information about the atrial geometry to create truly patient-specific atrial models [45–47] . This might be particularly interesting when applied to diseased tissue [31] and could be combined with detailed mapping of structural tissue remodeling to create patient-specific models . These computational models might become an important tool in the study of cardiac arrhythmias , possibly resulting in a deeper mechanistic understanding of AF and the development of novel therapies . Our study has several limitations . First , CV was estimated from the activation times of electrodes on the same spline . A more accurate determination would require constructing high-resolution isochrones in patient-specific geometries . Also , the AP shape was derived from MAP recordings , which are intrinsically noisy . Furthermore , these MAP recordings only represent local tissue characteristics and quantifying atrial heterogeneity would require multiple recording sites . In addition , since our MAP electrode was close to the stimulus location , we do not have accurate data for the upstroke part of the AP . Also , our spatially extended simulations are in homogeneous 2D sheets , thus ignoring tissue anisotropy and potential 3D effects . Finally , a quantitative comparison between our spatio-temporal simulations and clinical data is currently challenging and would require accurate patient-specific data on the dynamics of wave fronts . Such a comparison necessitates extending our simulations to include anisotropy and 3D properties and would require detailed data on tissue conduction and atrial geometry , along with highly-optimized fitting algorithms and is the subject of future research . | Simulations generated by computers are often an effective way to study the dynamics of cardiac cells . A crucial component in these studies is the mathematical model that describes the electrical signal across the cells . The models vary from detailed , with numerous components , to simplified , with a minimal set of variables . While the detailed models contain more information , they are slower computationally . In this study we develop physiologically accurate computational human atrial models by fitting parameters of a detailed and of a simplified model to clinical data for five human patients . For both models , our fitting procedure generated parameter sets that accurately reproduced clinical data , but differed markedly from published sets and between patients , emphasizing the need for patient-specific adjustment . Both models were also capable of producing two-dimensional spiral wave dynamics for each patient . While the spiral waves differed significantly between patients , the models produced similar results for each case . These results show that simplified , computationally efficient models are an attractive choice for simulations of human atrial electrophysiology . This study motivates the development and validation of patient-specific model-based studies to target therapy . | [
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"... | 2016 | Comparison of Detailed and Simplified Models of Human Atrial Myocytes to Recapitulate Patient Specific Properties |
Although leprosy is one of the oldest diseases known to humanity , it remains largely misunderstood . Misconceptions about leprosy lead to stigma towards people with the disease . This study aimed at exploring the knowledge , perceptions and attitudes regarding leprosy in rural Cameroon . We carried out a cross-sectional community survey of 233 respondents aged 15–75 years , free from leprosy , and living in two rural health districts of the South-west Region of Cameroon . A questionnaire designed to evaluate knowledge , perceptions and attitudes about leprosy was used . Binary logistic regression was used to determine independent predictors of negative attitudes . About 82% of respondents had heard about , and 64 . 4% knew someone with leprosy . Information on leprosy was mainly from community volunteers ( 40 . 6% ) , friends ( 38 . 0% ) , and the media ( 24% ) . Only 19 . 7% of respondents knew the cause of leprosy , and a considerable proportion linked it to a spell ( 25 . 3% ) , unclean blood ( 15 . 5% ) and heredity ( 14 . 6% ) . About 72% knew that leprosy is curable and 86 . 3% would advise medical treatment . Attitudes towards leprosy patients were generally negative . Only 42% would shake hands , 32 . 6% would share the same plate , and 28 . 3% and 27% respectively , would allow their child to play or marry a person with leprosy . Furthermore , only 33 . 9% approved of participation of leprosy patients , and 42 . 9% of their employment . Independent predictors of negative attitudes were: the belief that leprosy is a curse; is caused by a germ; and having seen a leprosy patient . The negative attitudes were dampened by: the beliefs that leprosy is a punishment , is hereditary and is due to poor personal hygiene . An awareness intervention using community volunteers and the media , with information on the cause of leprosy , its clinical manifestations and curability , and sensitization messages correcting the misconceptions and beliefs regarding leprosy , could improve the community knowledge and attitudes towards leprosy . This would ultimately contribute to the reduction of leprosy burden in the community .
Leprosy is one of the oldest diseases known to humanity , and can be traced as far back as 100 000 years [1] . It is an infectious disease caused by Mycobacterium leprae . It affects peripheral nerves , the skin and the mucosa of the upper respiratory pathways [2] . Although the exact mode of transmission is not clear , it is believed to occur through nasal droplets or prolonged skin contact with an untreated patient [3; 4] . For a long time , humans were believed to be the only reservoir of Mycobacterium leprae . However , since 2005 the 9-banded armadillos in southcentral [5] and south-eastern [6] United States of America were confirmed to harbour the bacilli and to transmit it amongst themselves [6] . Another rodent , the red squirrels in the British Isles has also been shown to harbour the bacilli [7] . These new findings have implications for zoonotic transmission of leprosy [5; 6] as well as for the eradication of this scourge [8] . Untreated leprosy patients or those with late diagnosis usually develop irreversible and progressive disabilities and disfiguring complications . Physical deformities in addition to socio-cultural misconceptions about leprosy have led to intense social stigma and discrimination of people with leprosy ( PWL ) throughout history [9; 10; 11] . Social stigma related to leprosy is typically anticipated , felt or experienced by the victim [9] and is generally characterised by social exclusion , rejection , blame , and participation restriction among others [12; 13; 11] . Social stigma has been blamed for delay in seeking treatment by leprosy patients , who because of anticipated stigma , would rather prefer to conceal their condition [14; 15] . This has been an obstacle to early detection , prompt treatment and cure of leprosy patients . Despite the advances in treatment [16; 17] and political commitment at the global level [18] with attendant reduction in leprosy burden worldwide [19] , further reduction of leprosy burden meets with enormous challenges . These challenges are three-prong , including further reduction in the number of new cases , the registered prevalence , and the social stigma and exclusion through prevention and management of disabilities [20] . The full involvement of endemic communities as well as persons affected by leprosy is primordial in these efforts of leprosy burden reduction [20] . In Cameroon , leprosy elimination was achieved at the national level since 2000 . The current prevalence and detection rates are below 0 . 20/10 000 and 1 . 46/100 000 population respectively [21] . By the end of 2014 , the proportion of MB leprosy among new cases was 87% , the proportion of child cases was 18% , and the female proportion was 43% . The grade-2-disability proportion was 7% and the rate was 0 . 10/100 000 population [21] . In addition , ten health districts ( HD ) remained highly endemic for leprosy by the end of 2014 [21] . In order to assist the national leprosy control programme ( NLCP ) to improve the strategies for further reduction of the leprosy burden , we carried out a community-based study to assess knowledge , perceptions and attitudes regarding leprosy in the Ekondotiti and Mbonge HDs in the South-west Region of Cameroon .
We carried out a community-based cross-sectional descriptive and analytical study of knowledge , perceptions and attitudes regarding leprosy in rural Cameroon . The study was done within the framework of a screening campaign for leprosy and other skin diseases in Ekondotiti and Mbonge HDs of the South-west Region of Cameroon , organized by the NLCP ( results presented elsewhere ) . This community-based survey was carried out in April and May 2015 in two neighbouring rural HDs of Ekondotiti and Mbonge of the South-west Region of Cameroon ( Fig 1 ) . These districts were among those with the highest leprosy-burden in the country between 2010 and 2014 [21] . Ekondotiti and Mbonge HDs comprise 78 and 65 villages respectively . Six villages from Ekondotiti and seven from Mbonge respectively , were selected for the survey , based on leprosy case-notification from 2010–2014 . The 2010–2014 trend in leprosy prevalence rate was constantly above 1 per 10000 populations in Ekondotiti . For Mbonge , it fluctuated from 3 . 23 in 2010 down to 0 . 36 in 2012 and back to 1 . 73 per 10000 population in 2014 ( Fig 2A ) . Over the same period , the leprosy detection rate was stable at about 21 per 100 , 000 population in Ekondotiti from 2010–2011 , then dropped to 6 in 2012 before rising again to 43 . 1 per 100 , 000 in 2014 . In Mbonge , the detection rate was higher than in Ekondotiti but witnessed fluctuations from about 50 per 100 , 000 populations between 2010 and 2011 , down to 1 . 2 in 2012 , then rose sharply to 145 . 5 in 2013 before dropping again to 80 in 2014 ( Fig 2B ) . Three-quarters of the inhabitants of Ekondotiti and Mbonge HDs were of the Oroko tribe , sub-divided into ten clans [23] , with each clan speaking their own dialect [24] . Despite the predominance of Oroko people , the two HDs are quite cosmopolitan , with inhabitants from diverse ethnic origins of Cameroon . With this mix , the use of Pidgin English language has been highly developed and is widespread in the area [25] . The two HDs fall within the cocoa production basin of the South-west Region and majority of the inhabitants are farmers , involved mainly in cocoa farming .
The questionnaire designed for the survey included fifteen questions: 7 to assess knowledge and perceptions and 8 to assess attitudes regarding leprosy ( Table 1 ) . Ethical approval was obtained from the National Ethics Committee for Research in Human Health , Yaounde , Cameroon ( N° 172/CNE/SE/2011 ) . Participation in the study was voluntary and each participant gave an informed consent . All data were anonymized and confidentiality was strictly respected in the data handling and analysis . Data management consisted of checking whether questionnaires were filled completely and correctly using appropriate codes . This was done daily until all the data was collected . The data was stored in a safe place until analysed . Data was entered on Microsoft Excel spread sheets and exported to SPSS for Windows version 20 statistical software for analysis . Proportions were calculated and the Chi-square test was used to examine associations between responses and variables . The level of significance was set at p <0 . 05 . After performing orienting univariate analyses , we carried out binary logistic regression analysis to determine predictors of negative attitudes .
Two hundred and sixty-one ( 261 ) individuals were contacted and 233 accepted to participate in the survey , giving a response rate of 89 . 3% . Their ages ranged from 15 to 75 years with a mean age of 33 ± 12 years . They were 118 ( 50 . 6% ) males . Seventy-two percent were protestant Christians . The majority ( 65 . 7% ) were from the Oroko tribe , while 34 . 3% of them originated from 21 other Cameroonian tribes . Most ( 59 . 7% ) of the participants had only the primary level of education , 56 . 7% were married and 59 . 2% of them were farmers . The details of familiarity with and knowledge of leprosy are shown in Table 2 . Generally , our respondents were very familiar with leprosy , as 82 . 4% had heard about it and 64 . 4% had seen someone with the condition . About 75% of them declared that leprosy was curable however; only 19 . 7% knew the cause of the disease . The knowledge of leprosy and its cause were not influenced by demographic variables . Regarding familiarity with leprosy , respondents below 20 years of age ( p<0 . 001 ) , females ( p = 0 . 006 ) , those with no level of formal education ( p = 0 . 041 ) , and singles ( p = 0 . 028 ) were least likely to have seen someone with leprosy . Those below 20 years of age ( p = 0 . 033 ) , females ( p = 0 . 014 ) , and singles ( p = 0 . 045 ) were least likely to know someone with the condition ( Table 2 ) . We found the highest proportion of respondents in the group aged 30–39 years ( p = 0 . 005 ) who reported having a relative with leprosy . The unemployed ( p = 0 . 043 ) and those with no level of formal education ( p = 0 . 047 ) were the least likely to know that leprosy is curable ( Table 2 ) . For the 192 ( 82 . 4% ) respondents who declared having heard about leprosy , their main sources of information on leprosy were from community volunteers ( 40 . 6% ) , friends ( 38 . 0% ) and the media ( 24 . 0% ) ( Fig 3 ) . The beliefs and perceptions held about leprosy in the Mbonge and Ekondotiti HDs are portrayed in the nature of causes cited by the respondents ( Table 3 ) . Although 29% , 27% and 10 . 3% of them respectively rightly linked leprosy to germs , poor personal hygiene , and living in close contact with an untreated leprosy patient , a considerable proportion cited erroneous causes . A considerable proportion of them believed that leprosy is a spell ( 25 . 3% ) , is caused by unclean blood ( 15 . 5% ) , is hereditary ( 14 . 6% ) , or results from marrying from a family that has/had leprosy ( 11 . 2% ) . A much lesser proportion of the respondents believed that leprosy is punishment for sins , is caused by natural forces , or results from eating some food types or from malnutrition . Between 43% and 71% of our respondents admitted that PWL and their families face a variety of problems , ranging from difficulties getting employment , admission in school , or getting married themselves; to bringing shame in the family and causing other problems to family members ( Fig 4 ) . Table 4 shows details of attitudes regarding leprosy among our respondents . A high proportion ( 86 . 3% ) of them would advise a relative or friend with leprosy to consult a health professional , and 58 . 8% would be willing to tell someone if they had leprosy . Most of our respondents portrayed very negative attitudes with respect to leprosy , as only 42% would shake hands , and 32 . 6% would eat from the same plate with a leprosy patient . Only 28 . 3% and 27% would allow their child play with another child who had leprosy , or marry from a family with a history of leprosy , respectively . Only 33 . 9% of our respondent approved of leprosy patients participating in activities like anyone else , and 42 . 9% agree that they should be employed normally . Attitudes generally were not influenced by demographic variables , except for pupils/students , who were the least likely to reveal their leprosy status to anyone ( p = 0 . 019 ) . The analysis of the effect of knowledge , beliefs and perceptions regarding leprosy of our respondents on their attitudes toward PWL is detailed in Table 5 . The acceptance to refer a relative or friend with leprosy to a health facility was greater in respondents who knew or who had seen someone with leprosy ( p = 0 . 026 ) , and who understood that leprosy is caused by a germ ( p = 0 . 014 ) and that it is curable ( p<0 . 001 ) . Only those who understood leprosy is curable declared they would shake hands with patients ( p = 0 . 002 ) . Those who had heard about leprosy ( p = 0 . 041 ) , and who understood that leprosy is curable ( p = 0 . 002 ) were more likely to eat from the same plate with a patient , but those who thought leprosy was due to poor personal hygiene were least likely to do so ( p = 0 . 042 ) . Respondents who knew leprosy is curable were more likely to feel ashamed ( p<0 . 001 ) . Those who had heard about leprosy ( p = 0 . 039 ) and who knew leprosy is curable were more likely to conceal their status ( p<0 . 001 ) if they had leprosy , but those who believed leprosy is a punishment for sins ( p = 0 . 005 ) or is caused by living in close contact with a patient ( p = 0 . 027 ) were least likely to conceal their status if they were affected . Those who had heard about leprosy ( 0 . 039 ) and who understood it is curable ( p = 0 . 014 ) , or believed it was a punishment for sins ( p = 0 . 011 ) , were least likely to allow their children play with one who had leprosy . Respondents who had heard about leprosy ( p = 0 . 026 ) were least likely to allow their children marry from a family with a history of leprosy , meanwhile those who knew leprosy is curable ( p = 0 . 016 ) were readier to let their children marry from such a family . Those who had heard about leprosy ( p = 0 . 034 ) , who believed it was caused by living in close contact with an untreated patient ( p = 0 . 018 ) or due to poor personal hygiene ( 0 . 022 ) were least likely to accept that leprosy patients participate in activities like anyone else . However , those who knew leprosy is curable ( p = 0 . 005 ) had no problem with patients participating normally in activities . Concerning employment of PWL , those who had heard about the condition ( p = 0 . 004 ) , or who knew it was curable ( p = 0 . 002 ) were more likely to offer them employment , but those who believed leprosy was hereditary ( p = 0 . 033 ) or due to poor personal hygiene ( p = 0 . 007 ) would not do so . In a binary logistic regression inputting community perceptions and knowledge that influenced attitudes with respect to leprosy , seven independent predictors were identified ( Table 6 ) . The positive attitude of advising a relative or friend to seek treatment from a health facility was enhanced by two predictors: the understanding that leprosy is caused by a germ , and that it is curable . The eight negative attitudes studied ( Table 6 ) were driven by three independent predictors , namely: having seen a leprosy patient , the belief that leprosy is a curse , and the knowledge that it is caused by a germ . However , the effect of these negative attitudes was dampened by three predictors namely: the knowledge that leprosy is due to poor personal hygiene or the beliefs that it is a punishment or that it is hereditary , which were found to be protective .
Although the WHO enhanced global strategy for further reducing the burden of leprosy for the period 2011–2015 [20] has been implemented in Cameroon , over 300 new cases of leprosy continue to be reported in the country each year [21] . A new WHO global leprosy strategy 2016–2020 has been launched and has as main focus: the reduction of leprosy transmission and of leprosy related disabilities , stigma and discrimination [29] . The implementation of this strategy could face the hurdle of lack of community knowledge , and erroneous perceptions about leprosy [15] . The success of any intervention to improve upon the outcomes of leprosy control would depend on a good understanding of these community knowledge and perceptions [15] . In the current study , 82 . 4% of respondents had heard about leprosy . Though relatively high , this figure is less than the 100% reported in an Ethiopian study [30] . The sources of community information on leprosy in our study were varied ( Fig 1 ) . The most important sources of information were from community volunteers , friends and the media and only to a lesser extent from health personnel and schools . In Cameroon , community relay agents ( volunteers ) are important stake-holders in community health programmes like vaccination , community distribution of ivermectine against onchocerciasis and distribution of treated bed nets in the fight against malaria , and Buruli ulcer control [31; 32] . From our findings , an intervention to address community awareness on leprosy through the community relay agents , and local community radios could be the most effective approach . Only 19 . 7% of our participants knew the cause of leprosy . This is comparable to the 19 . 26% reported in Ethiopia [30] , but better than the 0% reported in a community in Pakistan [33] . The majority of our participants wrongly cited as causes of leprosy: curse , bad blood , heredity , punishment for sins , and eating some types of food ( Table 3 ) . Similar misconceptions have been reported in the northwest of Cameroon [13] . In Ethiopia it is believed that leprosy is linked to curse/punishment by god , heredity , bad blood , and immoral conduct [30] , while in eastern Sudan it has been linked mainly to some food types [34] . These misconceptions are clearly grounded in the customs and beliefs of the communities concerned , and are common to cultures in Africa , Asia and South America [15] . Seventy-five percent of our participants knew that leprosy is curable . This is higher than the 67 . 9% reported in Mezam division in the northwest of Cameroon [35] , 60% in Mangalore-India [36] and 18 . 3% in Pakistan [33] , but less than the 92 . 5% reported in Ethiopia [30] . In our sample , business men ( P = 0 . 043 ) and those with a high school or university education ( P = 0 . 047 ) , were most likely to know that leprosy is curable . Furthermore , 86 . 3% would refer a relative or friend with leprosy to a health facility for treatment . A comparable finding was reported in India [36] . This practice was strongly influenced by the knowledge that leprosy is curable ( P<0 . 001 ) , the understanding that leprosy is caused by a germ ( P = 0 . 014 ) , or knowing someone with leprosy ( P = 0 . 026 ) . A considerable proportion ( 43% to 71% ) of our respondents acknowledged that PWL face various and varied challenges in the society . At the individual patient level , the challenges range from difficulties in getting employment , getting admission in schools , interacting with other people , to getting married . The challenges went beyond the individual patient to affect the patient’s family like bringing shame to the family , and problems in marriage . The challenges faced by PWL are certainly a reflection of the society’s attitudes towards them . Attitudes were generally negative in our sample ( Tables 4 and 5 ) . The negative attitudes were not influenced by demographic variables in our study , but were strongly influenced by lack of knowledge about leprosy and socio-cultural perceptions of the diseases ( Table 5 ) . Similarly , negative attitudes towards PWL have been reported in Ethiopia [30] , and Secunderabad , India [37] . One positive and eight negative attitudes were found in our study . The lone positive attitude of advising a relative or friend with leprosy to seek medical treatment was independently driven by the knowledge that leprosy is caused by a germ , and that it is curable . This finding has important public health implications . The ultimate goal of any leprosy control programme is to break the transmission chain in endemic communities . This can only happen if all detected leprosy patients are treated adequately with multi-drug-therapy against leprosy . Increasing community knowledge on these two aspects regarding leprosy is therefore paramount . The independent predictors of negative attitudes were: having seen a leprosy patient , the knowledge that leprosy is caused by a germ and the belief by some that it is a curse . In the Oroko language , the name for leprosy is “diangi” signifying a disease that cuts off fingers , toes and destroys the face . With this kind of perception about leprosy , community members develop fear of being infected and becoming a leper , if they associated with PWL . The common tendency is therefore to avoid PWL in all circumstances . The knowledge that leprosy is due to poor personal hygiene or the beliefs that it is a punishment for sins or is hereditary , were found to be independently protective against some negative attitudes in this study . Some community members tend to pity PWL and would not support some of the negative attitudes like refusing to shake hands with PWL; not allowing their child to play with PWL; or their relative to marry from a family with history of leprosy , on the basis that leprosy is due to poor personal hygiene . In rural communities of Cameroon , environmental and personal hygiene are generally poor , with very poor housing conditions and limited access to potable water [38] which is not limited only to PWL . In our study , some community members also did not see why PWL should not be employed , on the basis of the belief that leprosy is hereditary . We conclude that familiarity with leprosy was very high , with the major sources of information being from community volunteers and the media . However , knowledge on the cause of leprosy was very low , with a considerable proportion having erroneous perceptions about its cause . Quite a high proportion of our participants understood that leprosy is curable and would refer their relatives or friends with leprosy for medical treatment . Attitudes toward PWL were very negative in our sample . These negative attitudes were independently driven by the perception that leprosy is a curse , the knowledge that leprosy is caused by a germ , and having seen a leprosy patient . The negative attitudes were however dampened by the beliefs that leprosy is a punishment , is hereditary or is due to poor personal hygiene . We recommend that , a leprosy awareness intervention , through the channel of community volunteers and the media , with information on the correct cause of leprosy , its curable nature , and messages discouraging the erroneous perceptions regarding it , could improve upon the community knowledge of leprosy , as well as attitudes towards PWL . This could ultimately lead to the reduction of leprosy burden in this community . | Leprosy is one of the oldest diseases known to humanity but remains largely misunderstood . This misunderstanding leads to stigma towards people with leprosy ( PWL ) . We explored knowledge , perceptions and attitudes regarding leprosy among 233 community members in the South-west of Cameroon . Our respondents were very familiar with leprosy . Their information on leprosy was mainly from community volunteers , friends or from the media . Despite high familiarity , very few knew the cause of leprosy . A good proportion attributed it to curses , unclean blood , or heredity . However , most of them agreed that leprosy was curable and would advise medical treatment . Attitudes of community members towards PWL were generally negative . Very few of them would shake hands with , eat from the same plate , or allow their child to play with or marry a PWL . The main reasons for these negative attitudes were the beliefs that leprosy is a curse; is caused by a germ; and having seen a leprosy patient . An awareness campaign using community volunteers and the media , with information on the cause of leprosy , its clinical manifestations and curability could improve community knowledge and attitudes towards leprosy . This would ultimately contribute to the reduction of leprosy burden in the community . | [
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"... | 2018 | Community knowledge, perceptions and attitudes regarding leprosy in rural Cameroon: The case of Ekondotiti and Mbonge health districts in the South-west Region |
Nasopharyngeal carcinoma ( NPC ) is an epithelial malignancy facilitated by Epstein-Barr Virus infection . Here we resolve the major genetic influences for NPC incidence using a genome-wide association study ( GWAS ) , independent cohort replication , and high-resolution molecular HLA class I gene typing including 4 , 055 study participants from the Guangxi Zhuang Autonomous Region and Guangdong province of southern China . We detect and replicate strong association signals involving SNPs , HLA alleles , and amino acid ( aa ) variants across the major histocompatibility complex-HLA-A , HLA –B , and HLA -C class I genes ( PHLA-A-aa-site-62 = 7 . 4×10−29; P HLA-B-aa-site-116 = 6 . 5×10−19; P HLA-C-aa-site-156 = 6 . 8×10−8 respectively ) . Over 250 NPC-HLA associated variants within HLA were analyzed in concert to resolve separate and largely independent HLA-A , -B , and -C gene influences . Multivariate logistical regression analysis collapsed significant associations in adjacent genes spanning 500 kb ( OR2H1 , GABBR1 , HLA-F , and HCG9 ) as proxies for peptide binding motifs carried by HLA- A*11:01 . A similar analysis resolved an independent association signal driven by HLA-B*13:01 , B*38:02 , and B*55:02 alleles together . NPC resistance alleles carrying the strongly associated amino acid variants implicate specific class I peptide recognition motifs in HLA-A and -B peptide binding groove as conferring strong genetic influence on the development of NPC in China .
Nasopharyngeal carcinoma ( NPC ) is an epithelial malignancy with highly variable incidence rates around the world . An estimated 84 , 400 incident cases of NPC and 51 , 600 deaths occurred in 2008 with the highest incidence in South-Eastern Asia , relative to the Americas , Europe , Africa , and Central and Eastern Asia [1] . An early indicator of NPC development is the occurrence of immunoglobulin ( Ig ) A antibodies to Epstein-Barr virus ( EBV ) capsid antigens ( EBV-IgA/VCA ) . [2] , [3] NPC incidence for individuals expressing IgA/VCA antibodies were 31 . 7 times higher than the incidence in the age matched general population . [4] Linkage and family studies indicated that genetic predisposition also plays an important role in NPC onset and susceptibility . [5] , [6] Among host genetic markers implicated as associated with NPC , the highly variable class I human leukocyte antigen ( HLA ) genes on chromosome 6 ( 6p21 . 3 ) have shown a strong and consistent association with NPC risk . [7] , [8] , [9] , [10] , [11] , [12] , [13]_ENREF_7 HLA class I association studies across mainland China [11] , [13] , Taiwan [10] , [12] , and Singapore [8] have consistently demonstrated that HLA-A*11 and B*13 are associated with NPC resistance , while A*02 ( A*02:07 ) , A*33 , B*46 and B*58 are associated with increased NPC susceptibility ( Table S1 ) . Genome-wide association studies ( GWAS ) have been applied to numerous complex diseases to implicate common risk variants through well powered genetic studies [14] , [15] , [16] . Recent GWAS also affirmed a strong HLA influence on NPC incidence and implicated four additional non-HLA genes , however extensive linkage disequilibrium across the gene dense HLA region have confounded identification of the causal association gene ( s ) . [17] , [18] , [19] To refine and extend these reports , we explore here the operative factors of genetic association for this disease in a comprehensive four step study utilizing: 1 ) A GWAS utilizing 591 , 458 SNPs resolved by Affymetrix 6 . 0 genotyping platform to identify gene regions associated with NPC; 2 ) SNP genotyping to replicate the top signals in a second independent NPC cohort; 3 ) High resolution HLA molecular genotyping to identify specific alleles and haplotypes associated with NPC; and 4 ) Amino acid variant analysis to fine map the major genetic determinants associated with this disease . The analyses demonstrates that two independent association signals , specifying peptide binding grove motifs in HLA-A and in HLA –B drive the signals tracked by scores of SNP and amino acid variants that are association proxies for the HLA class I NPC association .
We performed a GWAS with 1104 southern Chinese individuals from NPC-phase II study cohorts [20] , [21] ( See Materials and Methods ) using the Affymetrix Genome-Wide SNP 6 . 0 genotyping platform . After SNP- and sample-base quality control ( Table S2 ) , 591 , 458 SNPs genotyped in 1043 study participants ( 567 cases and 476 controls; Table S3 , line I ) . Principal components analysis confirmed that all samples came from individuals of Southern Chinese ancestry ( Figures S1 , S2 , S3 , S4 , S5 ) . A quantile-quantile plot of the observed p-values showed a clear deviation from the null distribution which suggested that the most significant lower p-values are smaller than those expected by chance and likely reflect genetic association ( Figure S6 ) . The GWAS allele associations suggested a strong influence in the HLA-A region of chromosome 6 and weaker signals on chromosome 16 and 17 ( Figure 1A ) . Twenty-four SNPs ( Table S4 ) with p-values less than 5×10−5 in 16 association tests ( Table S5 ) and sixteen previous GWAS reported NPC associated SNPs ( Table S6 ) and were selected for replication . Replication SNP genotyping was conducted in an independent Chinese cohort that included 356 NPC cases and 629 controls ( Table S3 , line II ) . Six of 40 SNPs that showed genome-wide significant NPC association and replication were within 500 kb of each other in the MHC region of chromosome 6 ( Table 1 , Table S7 ) . The most significant SNP rs417162 ( Pcombined = 1 . 1×10−11 , OR = 0 . 61 ) is located within the HLA-A locus , while four additional replicated SNPs were within adjacent genes , GABBR1 and HCG9 . A fine-grain view of the pattern of GWAS SNPs around the HLA-A locus is illustrated in Figure 1B . An extensive cluster of associated HLA-A region SNPs that approach or exceed genome-wide association threshold p-values ( p<10−8 ) is apparent within 500 kb including associations in the adjacent HCG9 and GABBR1 genes ( Figure 1C ) . The strong linkage disequilibrium ( LD ) across the HLA region is well known , which raises the question whether these HLA region associations represent single , multiple independent , or LD-proxy driven associations . To characterize the HLA association with NPC in finer detail , high-resolution molecular HLA genotyping was performed on 4055 study participants; 1043 subjects in the discovery cohort , 985 subjects in the replication cohort , and 2027 subjects that comprise the remainder of cohort ( Table S3 ) . [20] , [21] NPC cases , controls with EBV-IgA/VCA positive , and controls with EBV-IgA/VCA negative were examined for association of HLA alleles and HLA haplotypes with NPC risk and EBV IgA/VCA antibody status . Three HLA alleles , A*11:01 , B*38:02 and B*55:02 showed the most significant association with NPC ( P = 1 . 7×10−19 , P = 7 . 0×10−11 , and P = 1 . 6×10−10 respectively; Table 2 ) . In addition to the strong HLA-A and -B associations , there was a moderate association of HLA-C*12:02 allele as well ( P = 4 . 3×10−5; Table 2 ) . NPC associated HLA-A-B-C haplotypes which included HLA allele combinations from Table 2 were also apparent ( Table S8 ) . Functional variation of different MHC molecules to bind peptides and activate effector cells in the immune system underlies their association with disease . [22] , [23]_ENREF_18 To identify the specific site driving the NPC HLA associations , HLA gene sequence was translated to identify amino acid variants using a web-based software of the Immunology Database and Analysis Portal ( ImmPort ) system [24] . Genetic association of 284 detected HLA amino acid variant within the three HLA class I genes implicated the most significant NPC association of glutamine ( Gln , Q ) at amino acid position 62 of HLA-A gene ( P = 1 . 2×10−24 , OR = 0 . 59; Figure 2A; Tables S9 and S10 ) which marks HLA-A*11 , however there are 25 additional amino acid sites I in HLA-A that also show exceed genome wide significance ( P<_ENREF_1810−8; Figure 2A ) . The HLA-B signal centered on amino acid Leucine ( Leu , L ) at amino acid position −16 and 116 ( P = 1 . 7×10−13 and 2 . 4×10−13 , OR = 0 . 65 and 0 . 63; Table S10 ) , which marks B*13:01 and B*55:02 . A far less significant association was observed for the amino acid residue Tryptophan ( Trp , W ) at amino acid position 156 for HLA-C ( P = 1 . 4×10−9 , OR = 0 . 47; ) . Amino acid residues that correspond to the antigenic peptide binding groove residues showed the strongest association ( See color code in Figure 2A–2C ) suggesting that the peptide binding groove and function are major genetic factors for NPC risk . Given the plethora and complexity of HLA genetic associations plus the extensive LD within HLA , we attempted to resolve which HLA region SNPs and aa-variants represent proxy variants for one or more functional sites ( i . e . they were tracking by LD ) and which represent independent ( non-LD ) association signals using a multivariate logistic regression analyses [25] . Strongly associated aa-variants ( Figure 2 and in Tables S9 and S10; e . g HLA-A-62Gln ) were analyzed in a multivariate logistical regression analysis adjusting statistically for non-random influence of each of the adjacent aa-variants ( Figure 3; also in Table S11 ) . A dramatic reduction of association p-value significance for the strongest HLA-A aa variant , HLA-A-62Gln , is observed when this model is adjusted for adjacent aa-variants within and about the HLA-A gene but are not diminished by adjusting for variants in HLA-B or HLA-C . Thus , we conclude that there is a single association signal in HLA-A tracked by several dozen proxy aa/SNP variants within the HLA-A region . When HLA-A*11:01 is the index allele , the extreme NPC association signal is diminished to 0 . 1–0 . 01 by HLA-A aa variants as well as each SNP in the genes adjacent to HLA-A locus ( See Figure 3B and HLA-A*11:01 column in Table S11 ) . This multivariate dependence plus the knowledge that HLA-A*11:01 carries the five strongly significant associated aa variants ( 62Gln , 276Leu , 114Arg , 70Gln , and 97Ile ) in the peptide binding groove and reaches the highest significance in allele level would support the conclusion that the causal association is driven by the HLA-A*11:01 allele ( Table 2 , Table S10 , Figure S7 ) . A multivariate logistical regression analysis for HLA-B variants indicates that HLA-B associations are independent from the HLA-A signals and driven by two amino acid sites in strong LD with each other ( HLA-B: -16Leu and 116Leu; P = 1 . 7×10−13 and 2 . 4×10−13 ) ( Figure 3C and Table S9 ) . The most significant HLA-B signal is located at amino acid position 116 ( Figure 2B ) . The amino acid variant HLA-B-116Leu is present in the two strongly associated protective HLA-B alleles B*13:01 and B*55:02 , but the encoded amino acid in the associated suscetible allele HLA-B*38:02 is Phenylalanine ( Table S9 ) . It is also relevant that the same location of HLA-B amino acid position 116 has also been definitively implicated as the single aa site that drives high susceptibility of the HLA-B*35 association with very rapid AIDS progression in HIV-1 infected European Americans . [26] , [27] It seems that this variant influences HLA peptide repertoire recognition and/or presentation for both HIV and EBV infections . The amino acid substitution in the heavy chain at position 116 could abolish the ability of P9 picket of HLA-B*35:01 to bind tyrosine but preferentially accommodate smaller hydrophobic residues such as methionine , valine , or leucine at the carboxy-terminal anchor had been shown by peptide-binding assays . [28] The HLA-C signal is ten logs weaker than HLA-A or HLA-B and is diminished slightly by adjusting for HLA-A or HLA-B variants ( Figure 3E , Table S11 ) . Further , the most significant HLA-C alleles ( HLA-C*03:02 and -C*12:02 ) track HLA-A and -B alleles in the haplotype analyses ( Table S8 ) , suggesting the HLA-C association are likely proxies of the stronger HLA-B and -A associations . We interpret these cumulative data as suggestive that there are two robust independent HLA association signals with NPC development: HLA-A including at least five amino acid position in 62Gln , 70Gln , 97Ile , 114Arg and 276Leu carried by HLA-A*11:01 and HLA-B including the -16Leu and 116Leu-bearing alleles . Our GWAS analysis also provided an opportunity to inspect regions of the genome outside HLA that had been implicated in previous NPC studies . The results ( Table S6 and Table 1 ) offer strong supportive confirmation of SNPs in the HLA-A gene region ( including the adjacent HCG9 , and GABBR1 genes ) as suggested by previous GWAS . [18] , [19] However , our SNP replication ( Table S6 ) and multivariate logistical regression analysis ( Figure 3; Table S11 ) indicate that all these associations are by and large proxies for the primary functional aa variants association in our cohort . We also replicated the TNFRSF19 , MDS1-EVI1 , CDNK2A/2B gene associations [19] in our cohort ( p = 1 . 5×10−5; 5 . 0×10−5 and 5 . 6×10−3 respectively ) although these genes did not achieved genome wide significance ( Table S6 ) . The ITGA9 association reported by Ng et al14 was not replicated in our cohort ( Table S6 ) .
We present and interpret a 1 M SNP GWAS , in subjects from Guangxi Zhuang Autonomous Region and Guangdong province of southern China , where perhaps the highest recorded NPC incidence has been found . [3] , [4] , [20] , [21] Multiple genome wide significant association signals were evident with the HLA gene region and in a few other chromosomal regions ( Figure 1A ) . Because the HLA region is complex and displays extensive LD , we sought to resolve the causal association signals with several different approaches . These included replication in an independent cohort from the same area , sequence based gene typing of the HLA-A , -B and -C genes , and analysis of sequence based nucleotide alleles as well as 284 amino acid site variants across the HLA genes ( Figure 2 ) . We compared association signals of SNPs , aa variants , HLA- alleles defined by molecular typing and associated HLA –A , -B and C haplotypes . To resolve the operative variants from proxies that track signals by LD , we enlisted a multivariate logistical regression of alleles and site variants with the strongest signals ( Figure 3 , Table S11 ) . Finally we revisited and attempted replication in our cohort reports from other NPC gene associations including GWAS recently published , [17] , [18] , [19] ( TNFRSF19 -CHR 13 , MDS1-EVI1-CHR 3 , and CDNK2A/2B- CHR 9; Table S6 ) affirming gene influence that are important in this disease . In the present study , two independent powerful association signals within the HLA region were resolved for NPC , amidst a background of scores of adjacent associated LD-proxy variants . The first influence involved the HLA-A*11:01 allele sequence and function , specifically in the peptide binding groove , which recognizes invading antigens . This conclusion derives from several lines of evidence: 1 . ) HLA-A*11:01 is a common allele in the populations ( F = 0 . 25 ) and is the only “protective” allele with genome wide significant HLA-A signal ( OR = 0 . 59; P = 1 . 7×10−19; Table 1 ) the strongest of all HLA alleles . 2 . ) HLA-A*11:01 is included in the significantly associated protective HLA haplotypes ( Table S8 ) ; 3 . ) 100% of associated SNPs and aa variants about HLA-A , including those in adjacent genes , namely the HCG9 , and GABBR1 loci , are proxies HLA-A*11:01 ( Figure 3; Table S11 ) ; 4 . ) HLA-A*11:01 carries five strongly significant associated aa variants ( 62Gln , 276Leu , 114Arg , 70Gln , and 97Ile ) in its peptide binding groove ( Table S10 ) . Taken together , the HLA-A association is centered on HLA-A*11:01 allele function and tracked by internal and closely linked proxy aa and SNP variants . It may also be relevant that the sequence of HLA-A*11:01 allele ( F = 0 . 25 in this population ) differs by only one amino acid residue ( Lys19Glu ) from that of the HLA-A*11:02 allele ( F = 0 . 04 ) , yet HLA-A *11:02 shows no apparent association with NPC onset . Both HLA-A*11:01 and HLA-A*11:02 alleles share a unique peptide binding motif signature of “ . [YT]……[K-]” ( Table 2 ) and an identical sequence within the defined residues of the antigen recognition site . [23] Since the only Lys19Glu residue difference between the two HLA-A*11 alleles is outside the peptide binding region , the possibility of an alternative mechanisms for NPC pathogenesis , e . g . HLA-A/KIR innate immunity involvement [29] or dendritic cell interaction , [30] should be considered and explored in future studies . We further demonstrate an independent HLA-B signal derived from three representive alleles , two protective alleles ( B*13:01 and B*55:02 ) and a suscetible allele B*38:02 . Both HLA-A and -B associations involve functional variants in the antigenic recognition site . The strongest HLA-B aa site implicated is identical to the single aa site that mediates HLA-B*35 rapid AIDS progression reported previously . [26] , [27] , [30] All the NPC associations were genome wide significant in one or more analyses , replicated internally in independent Guangxi cohorts and externally in other genetic association studies in Asia . Our study demonstrates a powerful genetic influence on NPC onset in Chinese people , implicates explicit HLA alleles , peptide recognition motifs , and aa variants that confer strong genetic influence on the development of NPC in China . HLA disease associations are likely to involve multiple mechanisms . A recent study in HIV disease showed that allelic diversity of HLA-C can cause variation in the level of surface expression of the HLA-C molecule , which in turn affects viral load control and disease progression [31] , perhaps through both HLA-restricted CTL responses and HLA/KIR-mediated NK cell activities . The functional basis for HLA associations with NPC should be explored fully , now that the genetic basis of this disease is well-characterized , in hopes of explaining the complex HLA association with NPC in the Chinese population .
This study were approved by institutional ethics review committees at the relevant organizations , and conducted with the IRB approval ( NIH IRB -02-C-N056 ) . Informed consent was obtained from all study participants . A total of 4055 study subjects ( 1405 NPC cases and 2650 controls , Table S3 ) were recruited in two independent collection phases: phase I -April 2000 to June 2001 and phase II-November 2004 to October 2005 , from the Guangxi autonomous region and Guangdong province of southern China . [20] All study subjects were of Han ethnic origin and reside in the catchment area of the Xijiang River . IgA antibodies to EBV capsid antigen ( EBV-IgA/VCA ) were confirmed by serologic testing for all the subjects at the time of study enrollment . In phase I , the case group included 356 unrelated patients with biopsy-confirmed NPC . The mean age was 50 . 1 years ( range 19–80 ) , 95 . 5% of them were EBV-IgA/VCA antibody positive . Controls included case spouses or geographically matched residents who were NPC free at the time of study enrollment . An additional 422 adult children of the study subjects were enrolled for haplotype inference and for quality control assessment , but they were excluded in association analyses . In phase II , the case group included 1049 unrelated patients with biopsy-confirmed NPC . The mean age was 46 . 3 years ( range 10–77 ) , 96 . 3% of them were EBV-IgA/VCA antibody positive . Two distinct NPC-free control groups were included; one group was positive ( N = 1001 ) and the other negative ( N = 1020 ) for the EBV-IgA/VCA antibody . The mean ages were 46 . 1 and 46 . 6 , for the antibody positive and negative controls groups . All study subjects were self-reported Guangxi or Guangdong provincial ancestry for either maternal or paternal ancestry for at least three generations . A total of 598 NPC cases and 506 controls were randomly selected from phase II enrollment cohort for GWAS analysis . DNA was extracted from whole blood by traditional phenol/chloroform method with phase Lock Gel tube ( Qiagen , MaXtract High Density , catalog # 129065 ) . The genome-wide genotyping experiments were conducted by using the Affymetrix Genome-Wide SNP Array 6 . 0 genotyping platform . 325 nanograms of DNA per sample were prepared for both Sty1 and Nsp1 restriction enzyme digestion for this assay , genotyping in according to the manufacturer's instructions . Validation and replication genotyping of significant SNPs from our GWAS and from other studies was performed using the ABI Taqman genotyping assays by design in accordance with the manufacturer's instructions . The sequence detection software ( SDS2 . 2 , Applied Biosystems , Foster City , CA , USA ) was used for allelic discrimination and confirmed the good quality of genotyping . High resolution HLA molecular typing was performed for all 1 , 405 unrelated NPC cases and 2 , 650 unrelated controls from both enrollment cohorts . HLA class I alleles were characterized using a PCR-SSOP ( sequence-specific oligonucleotide probe ) typing protocol developed by the 13th International Histocompatibility Workshop [32] for the first enrollment study cohort ( N = 985 ) , and using a DNA sequence-based typing ( SBT ) protocol in the second enrollment study cohort ( N = 3070 ) . The sequencing analysis was performed using the ABI Big Dye Terminator Cycle Sequencing Kit and the ABI3730xl DNA analyzer ( Applied Biosystems , Foster City , CA ) . HLA alleles were assigned on the basis of the sequence database of known alleles with the help of the ASSIGN software developed by Conexio Genomics ( Conexio Genomics , Western Australia , Australia ) . Ambiguous heterozygous genotypes were resolved by additional PCR and sequencing procedures using allele-specific PCR primers to selectively amplify only one of the two alleles . Haplotype of HLA-A , HLA-B and HLA-C allelic combinations were assessed using 422 children of the phase I study subjects in 179 patients and 379 controls . Based on expectation maximization algorithm to generate maximum likelihood estimation haplotype , we observed 90% accuracy on HLA-A-B-C haplotypes , 91% on HLA-A-B and HLA-A-C haplotypes , and 99% on HLA-B-C haplotypes . For the remaining NPC cases and controls , HLA haplotypes were assigned by population-based estimation methods of PROC HAPLOTYPE in SAS/Genetics package . Because the most significant NPC associated SNPs is located on the HLA class I region ( see Results ) , an amino acid analysis was carried out to evaluate the role of functional relative amino acid residues in HLA associations . From our high resolution HLA genotyping results , we were able to define corresponding amino acid sequences for all study subjects . The amino acid variants in HLA class I genes were defined by using web-based software of the Immunology Database and Analysis Portal ( ImmPort ) system [24] . We have used the method of testing each variant for reduced-p-values in multi-variants models resulting from co-linearity of variants to recognize LD and independence of signals in the association of NPC with HLA-A , -B and -C . Multicollinearity in logistic regression models is a result of strong correlations between variables . The existence of multicollinearity ( high r2 ) between variants inflates the variances of the parameter estimates . That will likely result in lowered p-values for a given SNP that was determined to be in significant association with NPC when tested signally . We used a reduction in significance as an indicator that two variants were in strong LD , and therefore not independent signals as has been done by recent authors [18] . This gives us a general idea about independence of the signals within HLA and adjacent genes within the context of the disease association . However , we recognize that although multicollinearity may lower magnitudes of regression coefficient estimates and resulting p-value significance in cases of LD , this method may be subject to error such as when a rare SNP on a haplotype does not have a large effect on the model . These methods are provided as an indicator of independence , but not as a definitive measure in our understanding of the disease . We performed logistic regression model analysis for all SNPs passing the quality control filters , using a Cochran-Armitage trend , co-dominant , dominant , recessive , and allelic model taking the number of copies of the rare allele 0 , 1 or 2 , as the explanatory variable . The comparisons were conducted between NPC cases and NPC free controls , NPC cases and NPC-free but EBV-IgA/VCA antibody positive controls ( EP controls ) , NPC cases and NPC-free but EBV-IgA/VCA-antibody negative controls ( EN controls ) , EP controls and EN controls respectively . Population structure/stratification was assessed using the Principal Components Analysis ( PCA ) module of Eigensoft software [33] . Study samples were first run together with HapMap individuals of European , African , and Asian descents to identify any potential admixed individuals . Later , PCA analyses of only the study samples were conducted . Initially all autosomal SNPs that passed the quality control filters were used to estimate the contribution of each SNP to the top ten eigenvectors . Previously reported correlated genome regions [19] ( such as on chromosomes 6 , 8 , and 11 ) were observed and excluded from the following PCA analyses . Moreover , to avoid any confounders due to LD among the SNPs , the genotype data was pruned to 90 K independent SNPs distributed throughout the genome by PLINK prior to the PCA analyses . The logistic regression analysis performed using PLINK [25] , controlling for gender , age and the first three eigenvectors; the significance was evaluated using the log likelihood test . SNPs were sorted according to the lowest P-value in a combined set of samples in one of these models . The chi-square tests were used for testing case-control association for allele effects . HLA allele frequencies were calculated based on observed genotypes; HLA-A , -B and -C haplotype were assigned based on maximum likelihood estimation using the SAS/Genetics HAPLOTYPE procedure . The effect of HLA alleles on the development of NPC and EBV-IgA/VCA antibody was evaluated by computing odds ratios ( OR ) and 95% confidence intervals ( CI ) using logistic regression . For HLA allele and haplotype test , P values were calculated by logistic regression and then corrected by the Bonferroni , which was multiplied by the number of all detected alleles or haplotypes . Significance was considered at P<0 . 05 after correction . | NPC is a deadly throat cancer in China that is dependent on EBV infection . Here , we performed a 1 M SNP genome-wide association study using a large cohort of Chinese study participants at risk for NPC . Although several putative gene regions show significant associations , the strongest statistical signals involved scores of variants within the HLA region on chromosome 6 . HLA poses a formidable association-genetics challenge because of extensive linkage disequilibrium , rather low allele frequencies , and multiple physically close interacting genes of diverse function . We examined over 250 NPC-HLA associated variants detected with sequence-based nucleotide alleles and amino acid variants . The multiple associations were collapsed to implicate causal signals by multivariate logistical regression to resolve allele association interaction . One operative variant was identified as the HLA-A*11:01 allele motif , specifically in the peptide binding groove , which recognizes invading antigens; a second involved two aa sites with HLA-B tracking B*13:01 and B*55:02 alleles . We synthesize these new and previous discoveries to help resolve the important gene influences on this disease . | [
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] | 2012 | The Principal Genetic Determinants for Nasopharyngeal Carcinoma in China Involve the HLA Class I Antigen Recognition Groove |
Leprosy is a major public health problem in many low and middle income countries , especially in India , and contributes considerably to the global burden of the disease . Leprosy and poverty are closely associated , and therefore the economic burden of leprosy is a concern . However , evidence on patient’s expenditure is scarce . In this study , we estimate the expenditure in primary care ( outpatient ) by leprosy households in two different public health settings . We performed a cross-sectional study , comparing the Union Territory of Dadra and Nagar Haveli with the Umbergaon block of Valsad , Gujrat , India . A household ( HH ) survey was conducted between May and October , 2016 . We calculated direct and indirect expenditure by zero inflated negative binomial and negative binomial regression . The sampled households were comparable on socioeconomic indicators . The mean direct expenditure was USD 6 . 5 ( 95% CI: 2 . 4–17 . 9 ) in Dadra and Nagar Haveli and USD 5 . 4 ( 95% CI: 3 . 8–7 . 9 ) per visit in Umbergaon . The mean indirect expenditure was USD 8 . 7 ( 95% CI: 7 . 2–10 . 6 ) in Dadra and Nagar Haveli and USD 12 . 4 ( 95% CI: 7 . 0–21 . 9 ) in Umbergaon . The age of the leprosy patients and type of health facilities were the major predictors of total expenditure on leprosy primary care . The higher the age , the higher the expenditure at both sites . The private facilities are more expensive than the government facilities at both sites . If the public health system is enhanced , government facilities are the first preference for patients . An enhanced public health system reduces the patient’s expenditure and improves the health seeking behaviour . We recommend investing in health system strengthening to reduce the economic burden of leprosy .
Leprosy is caused by Mycobacterium leprae , affecting the peripheral skin , nerve and nasal mucosa [1] . The adverse impact of leprosy on human lives is serious due to nerve function impairment and disabilities . Moreover , the early manifestation of disability in the form of sensory loss of hands or feet , often fails to seize attention of clinicians and patients , resulting into detection delay and further transmission of M . leprae [2 , 3] . Therefore , the annual new case detection rate ( NCDR ) of leprosy is stagnant since many years [4] . The expectation to permanently eradicate leprosy , also referred as zero transmission [5] is now reflected into new WHO targets i . e . zero grade 2 disabilities among children , and new cases with grade 2 disability <1 case/million population [6] . However , the targets are difficult to achieve in the near future [7 , 8] , which means that leprosy will keep on imposing burden in many endemic countries . Leprosy and poor socioeconomic status are in a vicious cycle , characterized by inequality [9–11] , poor education [12] , poverty [13 , 14] , stigma , etc . [15 , 16] . A broad spectrum of evidence confirms the strength of the relationship between leprosy and poverty [17–21] . Evidence from Bangladesh shows that leprosy affected households have a poor nutritional level due to lower food expenditure per capita and household food stocks . This in fact increases the risk of acquiring leprosy in healthy household members [22] . Another study revealed that “people affected by leprosy are less likely to be stigmatized because of leprosy impairments than for their incapacity to contribute to family/community finances” [23] . Furthermore , leprosy incidence is high in the productive age group , resulting in long term financial loss [17] . Therefore , we suspect that the economic burden of leprosy is higher than perceived so far . Household expenditure represents the patient’s perspective and is critical in estimating the economic burden . It is now routinely done across diseases [24] , revealing underlying expenditure like income loss , which can sometimes be significant . Unfortunately , the cost evidence in leprosy is limited [25] . A literature search on PubMed using a broad search builder with ‘leprosy’ as MeSH term and ‘economics’ as sub-MeSH heading ( year 2001 onwards ) , resulted in 51 records . Only 6 records presented some cost estimates: three studies focused on a particular event ( ENL reaction and ulceration ) in hospital settings [26–28]; two cost-effectiveness analysis ( CEA ) studies on provider’s perspective [29 , 30]; and one study on human resource cost of a project [31] . No study was found exclusively on primary care in a general public health setting , covering the patient’s perspective . Leprosy is a chronic infectious disease with long treatment duration , therefore needs long term care and support , mainly in an outpatient setting . Therefore , the primary objective of our study is to estimate the expenditure in primary ( outpatient ) care incurred by leprosy patients in two different health system settings in India . The secondary objective is to compare the effect of the health systems on consumer behaviour and practices . The results will help in understanding the economic burden of leprosy in primary care , and eventually contribute in building an investment case for leprosy elimination [25] .
The study was conducted under the Leprosy Post Exposure Prophylaxis ( LPEP ) program , approved in India by the Institutional Human Ethics Committees of the National Institute of Epidemiology ( NIE/IHEC201407-01 ) . Written informed consent was received from the respondents and necessary permission was taken from the concerned departments . India contributes almost 60% to the global leprosy burden [4] . The LPEP program was launched in March 2015 in the Union Territory of Dadra and Nagar Haveli ( DNH ) , located on the western coast of India . The program aims to assess impact and feasibility of contact tracing and administration of single dose of rifampicin ( SDR ) to asymptomatic contacts of leprosy cases . LPEP is implemented by the National Leprosy Elimination Program ( NLEP ) of India [32] . The study followed a cross-sectional design , where a cohort from the Union Territory of DNH was compared with a cohort from Umbergaon block of Valsad district , Gujarat , India . A union territory is an administrative division , ruled directly by the federal government , whereas a block is the smallest administrative unit under a district . The cohorts were leprosy cases detected between April 2015 and March , 2016 . A sample of 120 participants from each group was selected randomly from the annual leprosy case detection list . In the financial year of 2015–16 , DNH reported 425 and Umbergaon reported 287 cases . DNH and Umbergaon share boundaries and are comparable with regard to demographic , epidemiological , and socioeconomic indicators ( Table 1 ) , but not to public health facilities due to the different governmental arrangement ( see below ) . Both study sites are mainly tribal areas , but there is a remarkable difference in the public health system of both sites . The public health system in DNH is enhanced because it falls directly under the federal government by bypassing provincial bureaucracy , and receives a higher health budget per capita [33–35] than the provinces . In comparison to DNH , Umbergaon has more PHCs per population covered; the average population screened for leprosy by a Primary Health Center ( PHC ) in Umbergaon was 43% more than DNH PHC ( Table 1 ) . The actual screening ( active and passive ) coverage was reported to be very high in both sites , approximating the total population of these areas . In the year 2015–16 , the leprosy program performed two active case detection surveys in both sites . Currently both sites fall under the Leprosy Case Detection Campaign ( LCDC ) , which was launched in early 2016 under the NLEP [36] . Furthermore , the population screened by Umbergaon PHCs is far more than the public health norms for tribal PHCs , i . e . 86% more in Umbergaon and 26% in DNH [37] . Typically , a PHC should cover a population of 20 , 000 in hilly , tribal , or difficult areas and 30 , 000 populations in plain areas [37] . Both sites provide free of charge leprosy outpatient department ( OPD ) services at all public health facilities , but the health systems vary with regard to infrastructure , availability , accessibility , and quality of services . A household survey was conducted between June and October , 2016 by means of a structured questionnaire . The data were collected by two experienced staff members , post-graduates in public health . The patient , or head of the household , or most knowledgeable person in the household was asked to report on patient demographics , HH socioeconomic status , accessibility of health services , treatment seeking history and OPD expenditure . Respondents were asked to report on the last three OPD visits , either in a public or private facility , in the last 6 months . The database was created in Excel . The analysis included only those patients who mentioned at least 1 OPD visit out of 3 . The costs were categorized as direct and indirect expenditure . The direct part included the expenditure on consultation , investigations and medicines & supplies . The indirect part constituted expenditure on transport , food , and days lost during illness of the patient and attendant . We calculated the transportation expenditure by multiplying to-and-fro distance from house to the nearest health facility , using the government transportation rate [38] . The wage loss was analysed by means of the human capital approach [39] . The wage losses for patients and attendants per illness episode were calculated by using government minimum wage rates [40] . There were 20 ( 8% ) patients who paid at least 1 OPD visit , but failed to report any loss of productive days . For these , we imputed half a day wage loss per visit under the assumption that at least half a day ( 4 hours ) is required to travel and avail services for each illness episode . But attendant’s productive day loss could be zero , as not all patients required attendants . We reported separately the days lost by child patients ( age < 16 years ) as ‘school days lost’ , but while calculating indirect expenditure , all patients and attendants were assumed to be 16 years and older . The results are presented in US dollars ( USD ) using the conversion rate of INR 67 for 1 dollar for the year 2016 [41] . The analyzed expenditure was exclusively of outpatient services . In order to answer our objectives , i . e . expenditure and patient’s health seeking behaviour differences in DNH and Umbergaon , we used an integrated analytical approach . The data distribution was evaluated by observing normality plots . The distribution of the direct expenditure variables were not normally distributed due to abundance of zeros and highly skewed for non-zero values , which is common in cost data [42] . The indirect expenditure variables were skewed , but not zero inflated . We compared four different distribution models , i . e . Poisson , negative binomial , zero inflated Poisson , and zero inflated negative binomial distribution [43] . The ‘zero inflated negative binomial regression’ was selected for direct expenditure variables , and ‘negative binomial regression’ for indirect and total expenditure variables . We estimated the mean expenditure for each variable , followed by association measurement between expenditure and patient’s household characteristics . Only significant ( p <0 . 05 ) variables were modelled together for multivariate regression analysis ( Generalized Linear Model ) . The magnitude of total expenditure was compared against the individual’s monthly income . The total per visit expenditure was defined catastrophic for an individual , if it exceeded 10% of the quarterly income [44 , 45] . We assumed that at least one visit to the health centre in a quarter is necessary for regular check-up of leprosy . However as per NLEP norms , patients should visit the health center every month , which rarely happens . In practice , monthly MDT is delivered by staff at the patient’s doorstep and health facility visits occur only during severe illnesses to avoid any wage loss .
A total of 240 patient households ( 120 in each group ) were approached to capture their characteristics and OPD visit details in the last 6 months . The area-wise household characteristics are summarized in Table 2 . The mean age ( DNH: 25 , Umbergaon: 24 ) showed a young and comparable population in both sites . The average monthly income ( DNH: USD 81 , Umbergaon: USD 97 ) , expenditure ( DNH: USD 73 , Umbergaon: USD 83 ) and saving ( DNH: USD 1 Umbergaon: USD 1 ) per earning member showed a poor economic status in both sites . The respondents differed prominently on characteristics such as distance to the nearest health facility , type of housing , OPD frequency and type of facility visited . Paucibacillary ( PB ) leprosy was more prevalent in both sites than multibacillary ( MB ) leprosy . Collectively in the three visits , 69% of the respondents in Umbergaon and 14% of the respondents in DNH had not paid any visit , and were therefore dropped for further analysis . The three visits expenditure was aggregated to obtain an average per visit . The details of direct and indirect expenditure are shown in Table 3 . DNH and Umbergaon were comparable on demographic and socioeconomic parameters , however , they statistically significantly differed with regard to health seeking behaviour . As a behaviour , OPD visit frequency is higher , and a government facility is more preferred in DNH as compared to Umbergaon . All the presented expenditure estimates are per visit . The mean consultation fee in DNH and Umbergaon was comparable ( DNH: USD 1 . 2 , Umbergaon: USD 1 . 6 ) . The mean expenditure on medicines and supplies ( USD 7 ) was 80% higher in DNH than Umbergaon ( USD 4 ) . Only 2 respondents reported investigation expenditure in Umbergaon and none in DNH . Only 1 respondent in Umbergaon and 2 respondents in DNH reported expenditure on food . The mean medical direct expenditure per visit ( DNH: USD 6 . 5 , Umbergaon: USD 5 . 4 ) was not statistically significantly different between the sites . In indirect expenditure , the mean wage loss for patients was the highest item ( DNH: USD 5 . 2 , Umbergaon: USD 7 . 3 ) , followed by attendant wage loss ( DNH: USD 2 . 7 , Umbergaon: USD 3 . 7 ) . Transportation expenditure ( DNH: USD 0 . 8 , Umbergaon: USD 1 . 4 ) differed significantly ( p ≤ 0 . 01 ) in the two groups . The details on association of expenditures with patient’s household characteristics are shown in Table 4 . The proportion of patients with catastrophic expenditure in DNH was 88% less than in Umbergaon . If catastrophic expenditure occurred , then direct expenditure rose three-fold in DNH and two-fold in Umbergaon , ( DNH: coef . 2 . 92 , 95% CI: 1 . 86–3 . 98; Umbergaon: coef . 1 . 00 , 95% CI: 0 . 23–1 . 77 ) . In DNH , the direct expenditure decreased statistically significantly more than two-fold ( coef . -2 . 49 , 95% CI: -3 . 74 to -1 . 24 ) with the increase in age groups , whereas a decrease in indirect expenditure against age was not statistically significant ( coef . -0 . 40 , 95% CI: -0 . 92 to 0 . 12 ) . Umbergaon’s indirect expenditure decreased statistically significantly more than half ( coef . -0 . 79 , 95% CI: -1 . 49 to -0 . 09 ) among patients who visited both ( government and private ) facilities in comparison to those who visited only private facilities . For total expenditure , age and type of facility remained statistically significant factors , whereas catastrophic expenditure remained statistically significant only in DNH . Therefore these factors were considered for the next level of analysis , i . e . multivariate regression . Table 5 presents the association when only statistically significant variables ( p < 0 . 05 ) are modelled together with total expenditure ( direct + indirect ) . When modelled separately for both sites , all the variables in Umbergaon turned statistically not-significant . Age however , remained a statistically significant factor ( p = 0 . 03 ) in DNH . The overall model ( Omnibus Test ) was statistically significant in DNH ( p = 0 . 001 ) , but not in Umbergaon ( p = 0 . 06 ) . Furthermore , the same model was applied jointly for DNH and Umbergaon ( n = 140 ) , which was overall highly significant ( p ≤ 0 . 001 ) . The age ( p = 0 . 019 ) and type of facility ( p = 0 . 002 ) were statistically significant , but catastrophic expenditure became statistically not-significant . Catastrophic coefficients however , indicated that catastrophic expenditure groups ( in both the areas ) had risk of spending ( total expenditure ) almost twice , compared to non-catastrophic groups .
Our study explored the leprosy patient’s financial burden due to primary care outpatient services . Primary care is an important aspect of disease control under a public health program , therefore costs at this level are important for policy and planning . Moreover , a high out of pocket expenditure indicates public health systems inefficiency , and act as barrier to access services [46] . The results show that the sampled patients were mainly in their economically productive lifetime , indicating leprosy imposing a high economic burden . The leprosy patients of DNH went more frequently to the OPD , and preferred a government facility as compared to Umbergaon . Furthermore , the total expenditure ( direct + indirect ) was statistically significantly lower in DNH than Umbergaon . The age of the leprosy patients and type of health facilities were the major predictors of total expenditure . The higher the age , the higher the expenditure , and private health facilities were more expensive than government facilities , at both sites . As a limitation , our study only considered direct and indirect costs , however skin anesthesia ( a common phenomenon ) , neuropathic pain [47 , 48] , poor mental health [49] and stigma [49 , 50] can be significant factors , which can elevate the total expenditure further . We could not focus on these parameters under patient characteristics , and recommend to explore this in detail in future . Next , the households belong to poor socioeconomic groups , which correlates with other studies [9 , 13 , 22] , but we drew the sample from government records , which often caters mainly to poor . Also , adequate representation of patients who are diagnosed and treated completely in private facilities cannot be ascertained . The relatively small sample size is also a limitation of this study . The sample size turned out to be low ( reduced power ) because of high zero visits , meaning that patients often did not visit the outpatient clinics according to the official schedule . Moreover , to minimize recall bias , we only included the patients of the most recent one year , which was a small cohort . Many patients were not traceable due to migration . Furthermore , we computed catastrophic expenditure based on the income , rather than consumption pattern , which is a more rigorous method . The study is cross-sectional and there is no insight on how patients adapt over time . We recommend to repeat the survey after an appropriate time gap . Also , OPD expenditure is not as high as hospitalization , therefore often failed to be recalled . We do not reject the possibility of recall bias , but we further reduced this by averaging the expenditure from last three visits . Although we have quantified health seeking behaviour , this study does not identify the underlying reasons for these patterns , which would further necessitate qualitative studies . So far , sound evidence is lacking on the private sector uptake of leprosy cases , therefore we compared the patient’s selection of health facilities for primary leprosy care . We observed that the government is mostly preferred over private health facilities ( government 80 . 8% vs . private 1 . 7% ) in an enhanced health system ( DNH ) . In a non-enhanced health system ( Umbergaon ) however , private is equally preferred ( private 15% vs . government 11 . 7% ) . Moreover , in a non-enhanced health system ( Umbergaon ) patients have poor health seeking behaviour ( zero OPD visits in last 6 months: Umbergaon 69% vs . DNH 14% ) . Contrary to the high number of subjects reporting zero visits , the predicted probability of zero direct medical expenditure ( Umbergaon 0 . 35 vs . DNH 0 . 88 ) is lower in Umbergaon , and vice versa in DNH . It means that patients in Umbergaon avoid visiting any health facility , but if they visit then end up paying more than in DNH , therefore out of pocket direct medical expenditure acts as a potential barrier to access leprosy health care . The indirect expenditure is the largest cost impoverishing component for patients . Next , the indirect expenditure with transportation and total expenditure in an enhanced health system ( DNH ) is lower than non-enhanced health system ( Umbergaon ) . Usually , a high variation is expected in indirect expenditure and transportation , because in many instances they are not paid out of pocket and are presumptive e . g . wage loss . This can lead to over or under reporting . For example , many people use their own vehicle or are supported by others , and often fail to report this . This in turn leads to unrealistic and non-comparable estimates , which are of low utility for policy purposes . Therefore , we used standard government labour market and transportation rates in both areas for comparable results , which are appropriate for the sampled socioeconomic groups . Our study identifies the linkage between socioeconomic factors and expenditure increase . The total expenditure peaked at the 19–35 age category , which correlates with the human capital approach , i . e . the productive age group is more weighted than early or old age [39 , 51] . Next , private health facilities are significantly more expensive than government facilities , therefore one of the reasons for higher total expenditure in Umbergaon than DNH . We conclude that the condition of public health systems has a direct relationship with the patient’s expenditure , and the better the public health system , the lesser the expenditure from the leprosy patient’s pocket . Next , the condition of public health system has a major effect on the patient’s health seeking behaviour , i . e . selection of health facility and services uptake . If a health system is weak , then leprosy patients are forced to seek private health care , which is more expensive and imposes a significant financial burden on the leprosy affected population , proven to be catastrophic . If a public health system is enhanced , then patients prefer to avail government health facility services . We recommend to invest in health system strengthening to reduce the economic burden of leprosy . | Leprosy leads to low quality of life even after cure . The anaesthetic hands and feet leading to ulcers and deformities , stigma and poor mental health are just a few challenges . After declaration of leprosy elimination at global level , the research activities reduced significantly , and the health economics aspect was not an exception . The knowledge on economic burden of a disease helps in prioritization , policy making and advocacy . Our study is a step towards quantifying the economic burden of leprosy . Currently the aim is to eliminate leprosy at national level , therefore the countries need more information to plan high impact activities . Moreover , the patient’s perspective is important as they are the end-point recipients . Our study explores the patient’s financial burden due to leprosy ( outpatient services ) , which is a significant indicator of a public health program’s success . If invested properly , the public health system has potential to reduce the economic burden of public health diseases . Our study is an attempt to link the patient’s perspective with the health system performance . This will help to encourage health systems strengthening . | [
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"health"... | 2018 | Household expenditure on leprosy outpatient services in the Indian health system: A comparative study |
What happens when the brain awaits a signal of uncertain arrival time , as when a sprinter waits for the starting pistol ? And what happens just after the starting pistol fires ? Using functional magnetic resonance imaging ( fMRI ) , we have discovered a novel correlate of temporal expectations in several brain regions , most prominently in the supplementary motor area ( SMA ) . Contrary to expectations , we found little fMRI activity during the waiting period; however , a large signal appears after the “go” signal , the amplitude of which reflects learned expectations about the distribution of possible waiting times . Specifically , the amplitude of the fMRI signal appears to encode a cumulative conditional probability , also known as the cumulative hazard function . The fMRI signal loses its dependence on waiting time in a “countdown” condition in which the arrival time of the go cue is known in advance , suggesting that the signal encodes temporal probabilities rather than simply elapsed time . The dependence of the signal on temporal expectation is present in “no-go” conditions , demonstrating that the effect is not a consequence of motor output . Finally , the encoding is not dependent on modality , operating in the same manner with auditory or visual signals . This finding extends our understanding of the relationship between temporal expectancy and measurable neural signals .
How long before the traffic light changes from red to green ? When will the person on the other end of the line pick up the phone ? Is the kettle about to whistle ? To allow preparation , planning , and efficient allocation of resources in the face of uncertain timing , brains actively maintain expectations about the possible timing of future events [1]–[4] . Specifically , they extract temporal expectations when the arrival time of a stimulus is distributed with a probabilistic temporal structure . The fact that brains learn temporal structure is exemplified by the finding that reaction time ( RT ) is modulated by changes in the temporal probability distribution between a warning signal ( “ready” ) and the imperative signal ( “go” ) [5]–[9] . For example , when the go signal is equally probable to appear at any one of a number of possible times , the RT is found to be faster for longer waiting periods . By the 1950s , the monotonically decreasing relationship of RT to the readiness period led to the hypothesis that RT depended on the a posteriori probability of the go cue [10] rather than the a priori probability; in other words , what matters is the probability that the cue will happen now given that it has not already occurred . The function describing this a posteriori probability distribution is called the hazard function [11] . The relation of RT to the hazard function has been verified by manipulating the probability distributions of the go-cue appearance times , and comparing the behavioral outcomes to the a posteriori functions [12]–[15] . The learning of temporal structure is also apparent in neural signals measured in single unit electrophysiology [14] , [16]–[19] and EEG [20]–[22] . These studies have reported increasing neural signals that build over the course of the readiness period and typically resemble the hazard function . What remains unknown , however , is how learned temporal expectations relate to different signals in the brain , such as the blood oxygenation level dependent ( BOLD ) signal in functional magnetic resonance imaging ( fMRI ) . Given the possible decoupling between action potentials and the fMRI signal [23] , [24] , it remains unknown whether neuroimaging would reveal a similar climbing activity or something quite different . A less well-studied phase of the evolution of readiness-related movement is the transition between the readiness state and the baseline , post-“go” state . Given the relatively high level of electrical activity just before the go cue , one might expect large chemical changes to occur for the brain to resume its baseline state . These changes might be visible through a measurement technique such as fMRI . Several fMRI experiments have explored motor movements to temporally uncertain cues [7] , [25] , [26] , but no event-related experiment has directly explored , to our knowledge , the pre- and post-go fMRI correlates of the temporal uncertainty itself , in which the only variable is the time of the go-cue . We report here the results of such an experiment , in which participants in the fMRI scanner reacted as quickly as possible to a cue following a variable readiness period . Using this ready-go task , we looked for correlates of the readiness period in the BOLD response . Our experiment also allowed us to monitor the less well-studied transition between the time of the readiness period to the time of the baseline waiting . As will be shown below , we found that activity in the supplementary motor area ( SMA ) and superior temporal gyrus ( STG ) was larger after longer periods of readiness . Strikingly , and contrary to the expectations from electrophysiology , we did not find any evidence of climbing activity in these areas . Rather , a large rise in the fMRI signal appeared immediately after the appearance of the go cue . The magnitude of the post-go signal was related to the probability of the wait time; we determined this by modulating the probability distribution in different trial blocks . We found the response to be well-fit by a cumulative hazard function , suggesting that the SMA and STG compute probabilistic expectations about waiting time . Electrophysiological evidence from monkey and human corroborate a role for the SMA in computing expectations about waiting time [16] , [19] , [20] , [27] , [28] , although the form of the fMRI signal presented here differs in that it appears at the conclusion of the trial , as opposed to building up during the trial . Altogether , these results suggest a network of brain areas which construct temporal expectations in order to optimize reactions . These results further support the recent understanding that electrophysiological measures do not always yield a clear-cut prediction of the associated fMRI signals [24] , [29] .
Participants engaged in a reaction time experiment ( Figure 1A ) . At the beginning of each trial , a gray ring ( ready signal ) appeared and remained on a black screen . After a readiness period of several seconds , the gray ring became filled with green ( go signal ) . Participants were asked to press a button as quickly as possible when it became green . Readiness periods of 4 , 6 , 8 , 10 , or 12 s were randomized from trial to trial , according to a probability distribution ( uniform , in this case ) , which remained constant throughout the block . Intertrial intervals were also randomized between 4 and 12 s . Participants' reaction times were found to be a function of waiting time ( Figure S1 and Text S1 ) , a well known effect ( known as variable foreperiod effect ) that demonstrates the participants had learned the timing structure of the task [5]–[9] . To search for expectation-related activity in the fMRI signal , we designed a regressor to extract signals that were larger after longer waiting times , but was agnostic to the detailed timecourse of the signal ( see Methods ) . At a threshold value of p<0 . 01 ( false discovery rate [FDR] corrected for multiple comparisons ) , we found significant activity in two brain regions ( Figure 1B ) : the SMA ( peak at 0 , 4 , 52 , in Montreal Neurological Institute [MNI] space ) , t = 5 . 63 , ventral and slightly rostral to the midline , locating most voxels in the SMA but with some overlap in the preSMA [30] and [29] and STG ( peak at 60 , 9 , −9 , MNI , t = 5 . 63 ) . The SMA has been previously implicated in time perception [21] , [22] , [28] and the timing of intention [31]–[33] . The STG has also been implicated in time and memory paradigms [28] , although less prominently in the literature . To understand the timecourse of the fMRI signal in these two regions , we plotted the activity in these two areas . We found that the signals in both the SMA and STG rose suddenly just after the appearance of the go signal ( Figure 1C ) . ( Due to hemodynamic delay , this rise presumably results from events occurring just around the time of the go cue . ) More strikingly , the amplitude of this rise was highly significantly correlated with the readiness period , i . e . , how long the participant had to wait ( Figure 1D ) . We found no evidence of expectation-related activity before the go-cue . This result surprised us , and we designed several other regressors that hypothesized the existence of signals that grew over the course of the waiting period ( see Methods ) . The only significant climbing or sinking activity found in our task was in the visual cortices , and can be explained exclusively by the properties of our visual stimulus ( see “No Evidence for Motor-Related Climbing Activity , ” below ) . Therefore , we conclude that the expectation-related neural activity available to the fMRI technique appears largely after the conclusion of the waiting period . While the significant differences in the fMRI signal between 8–12 s ( Figure 1C and 1D ) are not mirrored in the reaction time ( Figure S1 and Text S1 ) , it could nevertheless be possible that some aspect of the motor act played a role . To address whether the delayed fMRI signal is a consequence of motor output , we designed a second experiment ( Figure 2A ) , which was almost identical to the first one except that the gray circle turns green ( go signal ) or red ( no-go signal ) , each with probability 0 . 5 . We found the same pattern of readiness period-dependent amplitude in both types of trials: a longer readiness period causes a larger post-go fMRI response ( Figure 2B ) . Incorrect trials ( trials in which participants pressed the button after a no-go signal , or in which they failed to press the button after a go signal ) are only ∼3% of the total number of trials and they are not included in the analysis . Response inhibition is known to activate the SMA , which may contribute to the SMA activation in the no-go trials . However , there is no reason to expect response inhibition to show differential activity for the readiness period , which is the novel result in this case . The go/no-go results demonstrate that the differential fMRI amplitude is not simply a consequence of motor output . The post-go signal is modulated by the duration of the waiting period , and persists in the absence of a motor act . This suggests that it is a function of either expectancy or the duration of the waiting period itself . If the signal depends on expectancy , then it should lose its dependence on the duration of the readiness period in the absence of uncertainty . To test this prediction , we conducted an experiment in which a numeric display counted down the remaining seconds of the readiness period; the go signal occurred when the countdown reached zero ( Figure 3A ) . As in the previous experiments , five possible readiness periods were randomly interleaved . In the absence of uncertainty about the arrival time of the go signal , the amplitude of the fMRI signal no longer correlated with the readiness period ( Figure 3B ) . This is consistent with previous observations that heart rate increasingly slows during a waiting paradigm , but does not slow if the readiness period is counted down , i . e . , there is no uncertainty about arrival time [34] . We have shown that the signal appearing after the go cue is modulated by the expectancy of an uncertain cue , since it disappears in the absence of uncertainty . This predicts that the probability distribution of the timing of the go cue will have an effect on the post-go signal . To determine whether the temporal probability distribution influences the fMRI amplitude , or whether it is instead based solely on the total time waited , we conducted another experiment in which we manipulated the probability distribution of the readiness period ( Figure 4 ) . Three different distributions gave rise to different patterns of fMRI amplitudes ( Figure 4A ) , suggesting a relationship between expectancy and the blood flow response . To elucidate this relationship , we proposed and tested four models ( Figure 4B ) : ( 1 ) The fMRI amplitude depends only on the length of the readiness period , not on the probability distribution; ( 2 ) The amplitude depends on a linear combination of readiness period and probability; ( 3 ) The amplitude depends on the conditional probability ( or hazard function ) , i . e . , the probability that the go signal occurs at time t given it has not yet happened by t; ( 4 ) The activity depends on the cumulative conditional probability , i . e . , the integral of the hazard function from time 0 to t . The results of the modeling are shown in Figure 4B . As seen by the r2 values , the cumulative hazard model appears to best explain the data . We note , however , that the hazard function by itself provides a qualitatively good fit as well , capturing some features of the data better than the cumulative hazard . It may be that the true signal is some combination of the two , representing a kind of leaky or forgetful accumulation . Further experiments will be required to address this possibility . To determine if the effect we have described depends on the sensory modality , we repeated our original experiment with auditory cues . Here , a brief double beep was the ready signal , and a brief single beep was the go signal . The fMRI signal in both regions was almost identical in the auditory and visual conditions ( Figure 5 ) . This indicates that the readiness-period-dependent activity is not reliant on visual cues , but is a function of expectation more generally . The pattern of activation we have reported was unexpected , given that previous electrophysiological [35]–[39] and fMRI studies [25] have reported climbing activity during the readiness period . We thus set out to understand where climbing activity could be found in our task . In a brain-wide search for climbing activity ( see Methods ) , only bilateral Brodmann Area 18 ( BA18 , Figure 6 ) revealed a climbing fMRI signal during the readiness period ( Figure 6A ) . To determine whether the climbing activity in BA18 ( Figure 6A ) relates to motor preparation , we conducted a passive control experiment , identical to the first experiment except that participants did not press a button at the go signal . We found the same pattern of climbing activity in these regions in the passive control condition ( Figure 6C ) , indicating that the climbing activity BA18 is not due to motor preparation . This conclusion is further supported by the lack of climbing activity in BA18 in the auditory condition ( unpublished data ) . Similarly , we found a broadly distributed “sinking” fMRI signal , which was especially significant in the cuneus ( Figure 6B ) ; its presence in the passive control condition revealed that it did not depend on the motor preparation ( Figure 6D ) . In summary , we did not find evidence for climbing or sinking activity associated with motor preparation in our experiment .
We have reported a BOLD signature of the readiness period ( Figure 1 ) . As measured by fMRI , activity in SMA and STG rises to a level that reflects the timing expectations from the previous waiting period . Our results are consistent with electrophysiological findings in monkey [14] , [17]–[19] , and human [21] , [22] , which show expectancy of the cue reflected in the brain activity . However , they differ in one important respect: the electrophysiology finds expectancy-related activity building during the readiness period [16] , [20] , [40]–[42] , whereas our data reflect a delayed and accumulated signature of the expectancy . While other fMRI studies have shown uncertainty-related signals in motor areas ( e . g . temporal and spatial uncertainty-related activity in premotor cortex and pre-SMA using a block design [26] and forebrain areas such as the middle frontal gyrus and cingulate [7] ) , the results shown here are the first , to our knowledge , from a simple reaction-time task to a single target , using an event-related design , which can reveal the exact temporal profile of the expectancy signal . Because the fMRI signal reported here appears at the end of the readiness period , our data support the possibility that it represents a final integration of the hazard-like signals that have been measured electrophysiologically in early visual areas [17] , lateral intraparietal cortex [14] , [18] , or the SMA itself [19] . It is particularly telling that our results are found in the SMA and STG . The SMA is known to be involved in time estimation , as are nearby parts of the anterior cingulate cortex [2] . The STG has also been implicated in time and memory paradigms [28] . However , in previous studies the dorsolateral prefrontal cortex ( DLPFC ) has been implicated in foreperiod time estimation , as evidenced by the reduction of foreperiod-related reaction time increase in patients with lesions present in that location [8] . In one recent study by Coull et al . [28] , the STG , SMA , and DLPFC were coactivated during a time estimation task , but only SMA and STG were significantly activated during the retrieval process . It is possible that the lack of DLPFC activation in our study means that SMA and STG are activated after the conclusion of an event requiring temporal estimation , while the DLPFC is only activated during the estimation process . Of what potential use is such a delayed reflection of expectancy to the brain ? It has been suggested to us that it may act as a prediction error signal , adjusting temporal expectations each time the brain experiences a new temporal event—and adjusting even more when the event is extremely improbable . This theory is appealing on the surface , particularly if you look at the response to the skew distribution ( Figure 4 ) , which is highest when the probability is low . This hypothesis awaits further theory and experiment . In the meantime , we more cautiously propose only that the activation represents a metabolic product , or by-product , of accumulated expectation-related activity . Why have these effects only become apparent with the fMRI technique ? Electrophysiology is highly biased toward recording from large excitatory pyramidal cells , and it may be that while these cells' activity climbs throughout the readiness period , inhibitory interneuronal activity concomitantly drops . Note that attentional modulation in V4 is found in two types of neurons: “out” cells , whose firing rate decreases during expectancy , and “in” cells , whose firing rates increase [17] . Assuming that the fMRI signal correlates with firing rate , declining and increasing firing rates in neighboring cells could theoretically counterbalance each other , resulting in a flattened fMRI response . Another possible source of the difference between our findings and previous reports lies in the details of the tasks . Experiments that have explored the readiness period with electrophysiology [14] , [19] and fMRI [25] , [26] have used tasks involving movements to or attention toward multiple locations in visual space . In contrast , the task we describe here is simpler , involving only a fingerpress to a nonvisible button . It could be that attending to or planning more complicated movements toward multiple targets in visual space recruits circuitry that exhibits climbing activity , but which is not needed for a simple fast-reaction . A recent fMRI study by Curtis and Connolly ( 2008 ) shows evidence of climbing activity in saccade-related areas [25] . While it is hard to reconcile the differences between our two reports , they may relate to the fact that we used keypresses instead of saccades , that our task structure was simpler ( target location never varied ) , and that our delay range was twice the size of theirs . Interestingly , when we examine their data carefully , it appears that their plots from the transverse parietal sulcus show evidence of a post-go , duration-dependent amplitude similar to ours ( Figure S2 and Text S1 ) . A final possible source of the difference between our post-cue fMRI signal and the building signals from the electrophysiology literature is the difference in measurement modalities . As yet , there is no consensus on the relationship of the fMRI signal to electrical activity in the brain [23] . We could entertain the speculative possibility that the metabolic signal measured by fMRI may not always be directly coupled to the information-carrying signal measured electrically . As the brain maintains a state of readiness , electrical activity uses resources . So as not to disrupt the delicate balance in activity required to maintain vigilance , the brain may “pay back” the energy debt with oxygenated blood flow only after the readiness period has ended . Further experiments will be required to determine whether it is possible to disconnect the signaling cascade between energy consumption and increased blood oxygenation . Like other recent demonstrations [24] , [43] , [44] , our data may show that fMRI signal and single unit spiking can be decoupled . If the hypothesis that fMRI-measured metabolic activity could be decoupled from electrically measured spiking activity proved true , it would have far-reaching implications . By comparing spiking data to fMRI results on the same tasks , we could begin to get an idea of how the brain balances metabolic and computational needs on an energy budget . Given the numerous factors that comprise the fMRI signal [45] , [46] , future experiments with diverse technologies will be necessary to determine the physiological basis of the effect we report here .
20 participants ( 11 male , average age 27 . 7 y ) participated in the main experiment , the go/no-go experiment , and the U-distribution experiment; 21 participants ( ten male , average age 27 . 5 y ) participated in the skewed-distribution experiment , the countdown experiment , and the auditory experiment . 15 participants ( seven male , average age 28 . 3 y ) participated in the passive control experiment . Each experiment consisted of 50 trials . For experiments other than the passive control , if participants pressed the button too slowly ( reaction time longer than 600 ms ) , or if they pressed the button before the color changed to green , or if they pressed a button when the color turned red , they would see an error message . Participants were told they would be paid as a function of the number of errors they made . Erroneous trials were removed prior to further analysis . To balance hand usage , half of the participants used their right thumbs to press the button and the other half used their left thumbs in each experiment except the passive control . High-resolution T1-weighted scans were acquired using an MPRage sequence in a 3-Tesla scanner ( Siemens ) . Functional run details: echo-planar imaging , gradient recalled echo; repetition time ( TR ) = 2 , 000 ms; echo time ( TE ) = 40 ms; flip angle = 90°; 64×64 matrix , 29 4-mm axial slices , yielding functional 3 . 4 mm×3 . 4 mm×4 . 0 mm voxels . Data analysis was performed using software package SPM2 ( http://www . fil . ion . ucl . ac . uk/spm/software/spm2 ) and visualized using xjView ( http://www . alivelearn . net/xjview/ ) . Motion correction to the first functional scan was performed using a six-parameter rigid-body transformation [47] . The average of the motion-corrected images was coregistered to each individual's structural MRI using a 12-parameter affine transformation . The images were spatially normalized to the MNI template by applying a 12-parameter affine transformation , followed by a nonlinear warping using basis functions [47] . Images were then smoothed with an 8-mm isotropic Gaussian kernel and highpass filtered in the temporal domain ( filter width of 128 s [48] ) . We performed a general linear model regression on the data . Two regressors were delta functions occurring at the time of the go cue . One of these regressors corresponded to short wait periods ( hrfs convolved with delta functions timed on go cues following readiness periods of <8 s ) , and the other corresponded to long wait periods ( >8 s ) . A third regressor was added—an hrf convolved with delta functions timed on the ready cue—to account for the variance in the data created by that stimulus . A paired t-test was performed between beta values from the long and short readiness period regressors . Regions that survived the threshold ( p<0 . 01 , FDR corrected for multiple comparisons [49] , cluster size >15 voxels ) were subjected to further region of interest ( ROI ) analysis . To search for climbing activity ( Figure 6 ) , we used several methods . ( 1 ) First , note that our original two regressors ( described above ) were designed to pull out climbing activity . Indeed , this method did pull out some of the activations shown on Figure 6 , but in the opposite direction from Figure 1 , and at much lower significance values . ( 2 ) Consistent with the reasoning from our original regressor , if a voxel displayed climbing activity during the readiness period , then the fMRI signal at the end of the readiness period ( i . e . , at the go cue ) will be larger after longer readiness periods . However , unlike our original analysis , a more intuitive notion of climbing activity in the fMRI is that it should peak at the time of the go cue , not afterward . To search for voxels that satisfied this condition , we compared the amplitude exactly at the time of the go cue , without convolving with the hrf . This timing ensured that we were analyzing the result of activity during the delay period , rather than afterward . For each voxel , we chose the fMRI signals at the timing of go cue and performed a linear regression on the previous readiness period . We then performed a t-test on the beta values across participants . This analysis remains agnostic to the temporal pattern of the climbing activity , and only concentrates on where the activity ends up , just before the go cue appears . The result of this analysis is shown in Figure 5 . The time series indicate that this method successfully pulls out activity that is greater for longer waiting periods . ( 3 ) Similar to Method 1 , except that we performed a contrast between the BOLD amplitudes at the time of go for long waiting ( 10 and 12 s ) and for short waiting ( 4 and 6 s ) . Whereas Method 1 hypothesizes a linear relationship between wait time and the height to which the activity might climb , this analysis remains agnostic to the exact functional form . Method 2 is the same as our main regressor , but without convolving with the hrf . The voxels produced by this latter analysis were qualitatively similar to those shown in Figure 6: BA18 and cuneus , but no significant activity ( p< . 001 ) anywhere else , including in the lateral intraparietal sulcus . ( 4 ) We also performed GLM analyses using either box-car or triangle regressors subtending the width of the readiness period . These methods successfully pulled out the areas that showed climbing activity as in Figure 6 . These methods also revealed some other areas , such as several nuclei in the thalamus and basal ganglia , and the SMA and STG . Subsequent ROI analysis on these other areas showed that there was no climbing activity , although there was significant readiness-related activity appearing after the go-cue . Box-car or triangle approaches are not efficient at selectively revealing climbing activity because they will identify any regions whose activity is higher during the readiness period than during the intertrial interval . Time course analysis of the identified areas showed only transient visual responses to the ready cue , rather than climbing activity . In the ROI analysis , the raw fMRI signal was extracted from each voxel in the region . Then the signal was averaged across voxels . The baseline was determined by a moving average with a window of +/−50 data points ( i . e . , +/−100 s ) . The baseline-subtracted signal was used for all region-of-interest time-course plots , and labeled according to percent change from the moving baseline . The signal amplitude was defined as the average of the signal at 4 s and 6 s data point after the go ( or no-go ) signal . To determine the relationship between the temporal probability distribution of the go signal and the fMRI amplitude , we used linear regression to fit four models to the fMRI data ( Figure 4B ) . In the equations below , y = the mean BOLD signal amplitude; t = time between ready and go signals ( readiness period ) ; P ( t ) = probability of go signal arriving at time t; and β is a fitting coefficient . Model 1: The fMRI amplitude depends only on the length of the readiness period , not on the probability distribution: y = β1t + β0 . Model 2: The amplitude depends on a linear combination of readiness period and probability: y = β1t + β2P ( t ) + β0 . Weights were determined by fitting . Model 3: The amplitude depends on the conditional probability ( or hazard function ) , i . e . , the probability that the go signal occurs at time t given it has not yet happened by t: . Model 4: The activity depends on the cumulative conditional probability , i . e . , the sum of the hazard function from time 0 ( beginning of each trial ) to t ( the time “right now” ) : We used two methods to investigate whether the cumulative hazard model fits the data significantly better than the hazard model: ( 1 ) t-test on residuals . After fitting the models , we calculated the residual for each model on each data point . Then for each data point , we calculated the difference of the absolute values of the residuals from the hazard model and the cumulative hazard model . We then performed a one sample t-test on these residual differences . ( 2 ) Distribution of correlation coefficient . We calculated the probability ( p-value ) that the observed sample correlation coefficient ( r2 = 0 . 96 from cumulative hazard model ) is from a population correlation coefficient ( r2 = 0 . 85 , the value we found for hazard model ) . The distribution of sample correlation coefficient r , given population correlation coefficient ρ and sample size N , is formulated as follows [50]:where Г is gamma function . We then calculated the area under this distribution curve where r2>0 . 96 , which is the p-value . Similar results were found with both methods; please see Figure 4B . | Like the sprinter waiting for the starting pistol , all animals develop expectations about when events will occur in time . We explored the neural correlates of readiness and expectation using functional magnetic resonance imaging ( fMRI ) , and found areas of the brain in which the fMRI signal remains at baseline during the waiting period and rises sharply after a cue to react ( a “go” cue ) . Strikingly , the amplitude of the rise reflects a function of the probability of an event occurring at that time . The dependence on probability remains even in the absence of a motor act ( that is , not pressing a button when the go cue appears ) . When the arrival time of the go cue is known in advance , the expectation-dependent signal disappears , indicating that this brain response reflects expectation , not simply elapsed time . These results match up with prior studies of expectation in the brain , with one important difference: previously , electrophysiology experiments showed that expectation is encoded by a build-up of spiking activity as the waiting period progresses , while our fMRI data reveal a signature of expectation that becomes apparent after the waiting concludes . We discuss the apparent mismatch between these different technologies for measuring expectation-related activity in the brain . | [
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] | 2009 | Ready…Go: Amplitude of the fMRI Signal Encodes Expectation of Cue Arrival Time |
Closely related African trypanosomes cause lethal diseases but display distinct host ranges . Specifically , Trypanosoma brucei brucei causes nagana in livestock but fails to infect humans , while Trypanosoma brucei gambiense and Trypanosoma brucei rhodesiense cause sleeping sickness in humans . T . b . brucei fails to infect humans because it is sensitive to innate immune complexes found in normal human serum known as trypanolytic factor ( TLF ) 1 and 2; the lytic component is apolipoprotein-L1 in both TLFs . TLF resistance mechanisms of T . b . gambiense and T . b . rhodesiense are now known to arise through either gain or loss-of-function , but our understanding of factors that render T . b . brucei susceptible to lysis by human serum remains incomplete . We conducted a genome-scale RNA interference ( RNAi ) library screen for reduced sensitivity to human serum . Among only four high-confidence ‘hits’ were all three genes previously shown to sensitize T . b . brucei to human serum , the haptoglobin-haemoglobin receptor ( HpHbR ) , inhibitor of cysteine peptidase ( ICP ) and the lysosomal protein , p67 , thereby demonstrating the pivotal roles these factors play . The fourth gene identified encodes a predicted protein with eleven trans-membrane domains . Using chemical and genetic approaches , we show that ICP sensitizes T . b . brucei to human serum by modulating the essential cathepsin , CATL , a lysosomal cysteine peptidase . A second cathepsin , CATB , likely to be dispensable for growth in in vitro culture , has little or no impact on human-serum sensitivity . Our findings reveal major and novel determinants of human-serum sensitivity in T . b . brucei . They also shed light on the lysosomal protein-protein interactions that render T . b . brucei exquisitely sensitive to lytic factors in human serum , and indicate that CATL , an important potential drug target , has the capacity to resist these factors .
The African trypanosomes are flagellated protozoan parasites comprising several species of the genus Trypanosoma , which cause devastating diseases in humans and livestock . One key feature that distinguishes members of this group is their sensitivity to innate trypanolytic factors ( TLFs ) found in human serum . T . b . brucei and related species cause nagana in livestock but these parasites are rapidly lysed by human TLFs [1] , [2] . T . b . gambiense and T . b . rhodesiense , on the other hand , although sharing >99% genome sequence identity with T . b . brucei [3] , have evolved distinct mechanisms to escape lysis by human serum; these are the causative agents of human African trypanosomiasis ( HAT ) , also known as sleeping sickness , in Western and Eastern Africa , respectively . T . b . gambiense is responsible for 97% of reported cases of HAT [4] . There are two classes of TLF found in normal human serum , TLF-1 , which is a component of high density lipoprotein [5] , [6] , and TLF-2 , which is an apolipoprotein-A1/IgM complex [7] , [8]; the active lytic component in both TLFs is apolipoprotein-L1 ( APOL1 ) [9] . Both TLFs also contain haptoglobin-related protein , which , in the case of TLF-1 , mediates binding to the T . b . brucei haptoglobin-haemoglobin receptor ( HpHbR ) and uptake into the cell [10] , [11] . Following uptake , APOL1 is inserted into endosomal and lysosomal membranes , where Bcl-2-like pore-formation is thought to be responsible for osmotic swelling and lysis [12] , [13] . Human TLF resistance mechanisms of T . b . gambiense and T . b rhodesiense have now been described , and these involve reduced TLF binding/uptake , APOL1 sequestration , or reduced APOL1 toxicity , possibly due to membrane stiffening . Reduced TLF binding/uptake operates in T . b . gambiense due to reduced expression of HpHbR and/or mutations in HpHbR [14]–[16] . Endosomal sequestration of APOL1 operates in T . b . rhodesiense due to the expression of a serum resistance-associated protein ( SRA ) related to a glycosyl-phoshatidylinositol membrane-anchored variant surface glycoprotein ( VSG ) [2] , [17] . Expression of a VSG-related protein also confers TLF-resistance to T . b . gambiense [18] , [19] , but in this case the VSG-like T . b . gambiense-specific glycoprotein or TgsGP may protect cells from APOL1 by stiffening endosomal membranes rather than through direct interaction with , or sequestration of , APOL1 [19] . The lysosomal membrane protein , p67 [20] and inhibitor of cysteine peptidase ( ICP ) [19] have also been shown to contribute to human TLF susceptibility using loss-of-function approaches in T . b . brucei . While HpHbR plays a role in TLF binding/uptake , the mechanism by which p67 contributes to human serum sensitivity in T . b . brucei remains unknown . Depletion of p67 causes lysosomal dysfunction , but does not increase lysosomal pH [20]; acidification has been proposed to be important for the insertion of APOL1 into membranes and the resulting lytic activity [12] , [13] , [21] . The role of the individual cysteine peptidases , the targets of ICP , has not previously been investigated , although T . b . brucei and T . b . gambiense cells exposed to a cysteine peptidase inhibitor display increased accumulation of TLF-1 [2] and APOL1 [19] , strongly suggesting that a cysteine peptidase contributes to the destruction of APOL1 . Cysteine peptidase inhibition by ICP likely similarly increases APOLI accumulation , explaining increased human serum resistance following ICP knockdown [19] . Thus , gain-of-function , through the expression of modified VSGs , or loss of TLF-receptor function , have contributed to the emergence of human-infective African trypanosomes . However , other undiscovered resistance mechanisms are thought to operate in these parasites [22]; expression of TgsGP does not confer human serum resistance to T . b . brucei [23] , and the main route of entry for TLF-2 in T . b . brucei is thought to be independent of HpHbR [10] , [19] . We sought to confirm those factors known to render T . b . brucei susceptible to lysis by human serum and to screen for additional factors . A genome-scale RNA interference library screen for increased resistance to human serum identified all three known genes and only one additional gene , encoding a novel putative trans-membrane channel , with high-confidence . This library was previously shown to yield read-outs representing approximately 5-fold genome coverage , or more than 99% of the >7 , 000 non-redundant protein coding sequences in the T . b . brucei genome [24] , and an approach related to the one described here was used to identify efficacy determinants for all five current anti-HAT drugs [25] . We next explored the unexplained role of the cysteine peptidase inhibitor in this process , and show that ICP impacts human serum resistance by specifically modulating the activity of the lysosomal cysteine peptidase , cathepsin-L ( CATL ) .
Natural hosts for bloodstream form ( BSF ) T . b . brucei include bovids , and these parasites are typically propagated in a culture medium containing 10% bovine serum . In this culture environment , the half maximal effective growth-inhibitory concentration ( EC50 ) of normal human serum ( NHS ) against cultured BSF T . b . brucei was less than 0 . 00025% ( Figure 1A ) , revealing the exquisite sensitivity of these parasites to lytic factors in NHS . To identify T . b . brucei factors that contribute to the trypanolytic activity of NHS , we selected a multi-genome coverage BSF T . b . brucei RNAi library in 0 . 0005% NHS ( see Figure 1B ) . Using this loss-of-function approach , knockdown of factors that normally contribute to human serum sensitivity will generate cells with increased resistance to this toxin . Under RNAi-inducing conditions , population growth was severely curtailed for six days in the presence of NHS; the human serum was added to the growth medium 24 h after inducing RNAi with tetracycline ( Figure 1C ) . A population that displayed tetracycline-dependent tolerance of this concentration of NHS emerged thereafter ( Figure 1D ) , and was harvested for DNA extraction and RNA interference target sequencing ( RIT-seq ) two days later . Using a modified RIT-seq [24] methodology ( see Materials and Methods ) , we generated and mapped individual sequence reads representing the human serum-enriched RNAi target fragments , about 0 . 5 million reads in total . Approximately 24% of these reads incorporated a 14-bp RNAi construct signature found at the junction with each gene-specific RNAi target fragment , and this allowed us to focus on only ‘high-confidence hits’: genes identified in the screen by more than 99 reads per kilobase per CDS ( Figure 2A ) , with more than 99 reads containing the RNAi construct signature , and at least two independent RNAi target fragments ( Table 1 ) . We previously applied similarly stringent criteria to define the key efficacy determinants of the anti-HAT drugs [25] . As detailed above , three T . b . brucei genes have been shown to play a role in trypanolysis by NHS . Remarkably , we identified only four high-confidence hits in our screen . The presence of the three known genes within this set ( Figure 2A ) , haptoglobin-haemoglobin receptor ( HpHbR ) [11] , inhibitor of cysteine peptidase ( ICP ) [19] , and the lysosomal membrane protein , p67 [20] , provides excellent validation for the RNAi-screening approach . The schematic in Figure 2B shows the four high-confidence loci identified in the screen with mapped sequence reads . The novel high-confidence hit ( Tb927 . 8 . 5240 ) encodes a ‘conserved hypothetical’ protein ( Figure 2A and Table 1 ) . Although it is likely membrane-associated , as it contains 11 putative trans-membrane domains , we have been unable to establish its sub-cellular localisation by C-terminal epitope tagging ( data not shown ) . Specific stem-loop RNAi depletion of Tb927 . 8 . 5240 in three independent cell lines , confirmed by quantitative reverse transcriptase PCR ( Figure 3A; Text S1 ) , had no significant effect on bloodstream-form population growth over seven days ( Figure 3B ) , but resulted in a 2 . 3-fold average increase in NHS EC50 , demonstrating its contribution to NHS-sensitivity ( Figure 3C , D ) . The additional genes highlighted in blue in Figure 2A are listed in Table 1 . These failed to fulfil the stringent criteria for further analysis detailed above . The only exception being Tb927 . 8 . 6870 whose knockdown has previously been shown to lead to a significant gain of fitness [24]; we subsequently confirmed that loss of this protein did not influence sensitivity to NHS ( data not shown ) . ICPs are conserved in protozoal and bacterial pathogens [26] . The T . b . brucei and T . b . gambiense ICP genes are almost identical and are predicted to encode proteins of 13 . 5 kDa . They are thought to block cysteine peptidase activity by occupying the substrate-binding cleft [27] , and to play a role in regulating parasite infectivity and VSG coat exchange during differentiation [28] . African trypanosomes express two cathepsins , CATB and CATL [29] , which are highly conserved between T . b . brucei and T . b . gambiense , and at least one ( CATL ) localises to the lysosome [30] . We used chemical and genetic approaches to explore the potential roles of T . b . brucei CATB and CATL in resisting lysis by human serum . Initially , we tested the dual CATB/L inhibitor , FMK024 , in combination with NHS against T . b . brucei . Isobologram and EC50 analyses revealed that this inhibitor fails to synergise with NHS in cell-killing assays ( Figure 4A , B ) . Indeed , the addition of increasing amounts of FMK024 causes little change in parasite sensitivity to NHS ( Figure 4B ) , suggesting that the inhibitory function of endogenous ICP may be modulated as a consequence of changes in protease activity elicited by exogenous inhibitor . FMK024 applied at 10 or 20 µM ( 62 . 5 and 125-fold higher than the highest concentration used here ) has been shown to cause lysosomal accumulation of TLF in T . b . gambiense [19] and of APOL1 in SRA-expressing T . b . brucei [2] , respectively . It should be noted , however , that such high concentrations of FMK024 would likely lead to total inhibition of lysosomal cathepsin activity , and it is unlikely that ICP modulation would have any impact . Indeed , FMK024 treatment is lethal at these concentrations in our EC50 assays , independent of NHS exposure ( see below ) . We next used RNAi to knockdown CATB or CATL individually in T . b . brucei . Specific protein depletion was confirmed by western blot , and subsequent analyses revealed that only CATL activity appears to be particularly important for robust growth ( Figure 5A , B ) . Previous findings suggested that CATB but not CATL was essential for growth [31] , [32]; however , our results are consistent with the recent chemical and genetic validation of CATL as a more appropriate drug target [25] , [29] . Although we used a sub-lethal knockdown in the case of CATL , we were able to obtain substantial protein depletion compatible with continued growth [25] ( Figure 5B ) . Consistent with the results obtained above using chemical inhibition of cathepsin activity , both knockdowns failed to synergise with NHS in killing T . b . brucei ( Figure 5C , D ) . These data suggest that if a protease can resist lysis by human serum , its activity is suppressed . The results above show either that repression of cathepsin activity by ICP renders T . b . brucei sensitive to human serum and that cathepsin knockdown is compensated for by down-regulation of ICP activity , or that CATB and CATL play no role in resistance to lysis by human serum . To distinguish between these possibilities , we generated icp null T . b . brucei [33] ( Figure 6A , B ) . As previously shown for a distinct cathepsin inhibitor [28] , the icp null strains displayed a minor but significant increase in FMK024 EC50 ( Figure 6C , D ) , confirming up-regulation of a cathepsin activity required for robust growth , most-likely that due to the essential CATL ( see above ) . The icp null strains were , on average , 7 . 2-fold less sensitive to NHS ( Figure 6E , F ) , validating this RNAi screening output and also consistent with a recent report [19] . In striking contrast to the situation in wild-type T . b . brucei , isobologram and EC50 analyses revealed strong synergy between FMK024 and NHS in killing icp null T . b . brucei ( Figure 7A ) . Indeed , in the presence of 5 to 160 nM FMK024 , the NHS sensitivity was almost completely reversed to that of wild-type cells ( Figure 7B ) . These results suggest that one or both of the cathepsins can indeed confer resistance to lysis by human serum , but only effectively in the absence of ICP . We next set out to determine which of the cathepsins is responsible for this phenotype . In order to assess the contribution of the individual cathepsins to resisting NHS , we generated strains for the inducible RNAi-mediated knockdown of either CATB or CATL in an icp null background . Once again , we had to use a sub-lethal knockdown in the case of CATL ( see Figure 5B ) . CATB knockdown in these strains had no impact on NHS-sensitivity ( Figure 7C , D ) . Hence , although CATB may have a role in the degradation of other host-derived proteins , including transferrin [32] , our data suggests that it does not target human serum lytic factors . In contrast , CATL knockdown was associated with a highly significant increase in sensitivity to NHS ( Figure 7E , F ) . Failure to completely reverse the NHS-resistance phenotype following CATL RNAi , may be explained by a second contributing factor or , more likely in our view , is because these experiments had to be carried out under partial knockdown conditions . We conclude that ICP increases sensitivity to NHS primarily by inhibiting CATL activity .
T . b . gambiense and T . b . rhodesiense can resist the APOL1-based trypanolytic factors found in normal human serum , while T . b . brucei fails to do so . We report here an RNAi library screen in bloodstream-form T . b . brucei for resistance to human serum and identify all three known genes , as well as a novel gene , that increase T . b . brucei susceptibility to this innate immune defence mechanism . We go on to show that one of these genes , encoding inhibitor of cysteine peptidase , acts by modulating the essential activity of CATL , a lysosomal cysteine peptidase . These findings illuminate the interactions between ICP , CATL and human serum , and have important implications for human infectivity , as well as for therapies based on cathepsin inhibitors [34] or serum lytic factors [35] . Finally , we have revealed a novel role for a putative trans-membrane domain protein , Tb927 . 8 . 5240 , in determining sensitivity to NHS . A loss-of-function phenotype , associated with HpHbR [14]–[16] , contributes to human serum resistance in T . b . gambiense , the most prevalent cause of sleeping sickness . As expected , our RNAi library screen for human serum resistance identified the gene encoding this protein and also the gene encoding the lysosomal membrane protein , p67 , also previously linked to this phenotype through experimental loss-of-function analysis [20] . This confirmed the power and utility of the RNAi-screening approach . Our screen also identified the gene encoding ICP , which was recently linked to human serum sensitivity by others [19] , and a fourth , novel gene ( Tb927 . 8 . 5240 ) , encoding a predicted multi-pass trans-membrane protein , with an almost identical homolog in T . b . gambiense . These outputs indicate a remarkably low rate of false positives , and suggest a similarly low rate of false negatives when using a multi-genome coverage RNAi library to identify high-confidence hits in T . b . brucei ( see Materials and Methods ) . To improve our understanding of sensitivity to human serum in African trypanosomes , we focussed on the role of the cysteine peptidase inhibitor , ICP . Our chemical and genetic evidence are entirely consistent , and reveal CATL as the cathepsin primarily responsible for the decreased sensitivity to human serum seen following ICP deletion . Specifically , chemical inhibition or knockdown of the individual cathepsins in an icp null background revealed that only CATL can resist human serum; CATB depletion had no detectable effect on this phenotype . CATL has been shown to accumulate in the lysosome [30] , and is responsible for proteolysis of the transferrin receptor [36] and of anti-parasite IgG [28] . The lysosome is also the major site of action of APOL1 [13] , the lytic component of both TLF1 and TLF2 . Thus , CATL may target TLF , and possibly APOL1 , for destruction in the lysosome ( Figure 8 ) . ICP , therefore , naturally maintains sensitivity to human serum , possibly by restricting the proteolytic degradation of TLF ( or APOL1 ) in the lysosome . This is consistent with previous pulse chase experiments that found little proteolytic degradation of the lytic factor and its components in T . b . brucei [37] , thereby allowing APOL1 to form membrane-spanning pores , leading to lysosomal swelling and cell lysis . Unmasking of the CATL activity only in the absence of ICP confirms natural control of this cathepsin , as suspected , by ICP . Using a similar RNAi-screening approach , uptake of the anti-trypanosomal drug , suramin , was shown to be via receptor-mediated endocytosis in T . b . brucei [25] . The identification of only p67 by both screens suggests distinct uptake and trafficking factors and mechanisms involved in suramin uptake following association with the type-I trans-membrane glycoprotein , ISG75 [25] , and TLF-uptake following association with the GPI-anchored HpHbR [11] . Interestingly , CATL has now been linked to both suramin efficacy [25] and human serum toxicity ( this study ) but , while CATL can protect T . b . brucei from killing by human serum , it sensitises T . b . brucei to killing by suramin . This suggests that suramin , a napthylamine , is liberated in active form by lysosomal proteolysis , while we suggest that TLF ( APOL1 ) is degraded by lysosomal proteolysis . Trypanosomal cathepsins are targets of ongoing drug development [29] , [38] , [39] . Although it was previously suggested that CATB was an appropriate drug target [31] , more recent genetic and chemical evidence indicates that CATL is the essential cysteine peptidase of T . b . brucei and the most appropriate target [25] , [29] . Our current findings also support this view . In this context , it is worth considering the potential impact of therapy targeting the essential cysteine peptidase activity . Our results indicate little impact of exposure to such inhibitors on human serum sensitivity in T . b . brucei . However , cysteine peptidases may be more active in T . b . gambiense [19] and/or T . b rhodesiense , possibly due to selective pressure through TLF exposure , and CATL inhibition could act synergistically with TLF in this case , increasing sensitivity to lytic activity and presenting a novel rational approach to therapy . On the other hand , T . b . gambiense and T . b . rhodesiense rely upon lysosomal/endosomal VSG variants to resist the toxic effects of APOL1 . Reduced proteolysis of these factors [19] could increase parasite resistance to human serum , meaning that targeting CATL could represent a risky therapeutic strategy . Indeed , FMK024 exposure leads to an accumulation of SRA in the lysosome of T . b . brucei engineered to express this VSG-variant [2] . It will clearly be important to develop an improved understanding of the interplay among these factors in human-infective trypanosomes . We link four factors to human serum sensitivity using a genome-scale loss-of-function screen in T . b . brucei . These include all three expected factors , based on previous reports , and a novel putative trans-membrane channel . It is interesting to note that , in the case of ICP , we uncovered a gain-of-function phenotype using a loss-of-function screen; this is possible when one protein antagonises the action of another . Our findings indicate that CATL can resist lysis by human serum , and this has important implications , since CATL is a promising potential drug target . In addition , the novel link to a putative trans-membrane channel presents an excellent candidate that may facilitate TLF transit . Notably , the gene encoding TgsGP is not present in T . b . gambiense group 2 [40] , indicating a distinct human serum resistance mechanism in these parasites , and the main route of entry for TLF2 in T . b . brucei is thought to be independent of HpHbR [11] , [19] . The outputs from our screen and our studies on ICP and CATL shed light on mechanisms of toxin delivery and stability in African trypanosomes and should facilitate studies aimed at understanding the multiple mechanisms employed by T . b . gambiense and T . b . rhodesiense to resist lytic factors in humans and other primates .
MITat 1 . 2 clone 221a 2T1 bloodstream-form T . b . brucei were maintained and manipulated as previously described [33] . Transformants were selected in blasticidin ( 10 µg/ml ) , hygromycin ( 2 . 5 µg/ml ) or G418 ( 2 µg/ml ) , as appropriate . For growth assays , cells were seeded at ∼105/ml , counted using a haemocytometer , and diluted back every 24 hours , as necessary , for up to seven days in the absence of antibiotics . To determine NHS EC50 , cells were seeded at 2×103 ml−1 in 96-well plates in a 2-fold dilution series of NHS ( pooled mixed gender; Sera Laboratories International ) , starting from 0 . 01%; assays were carried out in the absence of antibiotics . After ∼3 days growth , 20 µl of 125 µg/ml resazurin ( Sigma ) in PBS was added to each well and the plates incubated for a further 6 hours at 37°C . Fluorescence was determined using a fluorescence plate reader ( Molecular Devices ) at an excitation wavelength of 530 nm , an emission wavelength of 585 nm and a filter cut-off of 570 nm [41] . To analyse the combined effect of NHS and FMK024 treatment , isobologram analysis was carried out using a checkerboard approach , as previously described [42] . Data were processed in Excel , and non-linear regression analysis carried out in GraphPad Prism . The bloodstream-form T . b . brucei RNAi library [24] was thawed into 100 ml HMI-11 media ( Life Technologies ) containing 10% foetal bovine serum ( FBS; Sigma ) at a density of approximately 1×105/ml . RNAi was induced in 1 µg/ml tetracycline for 24 hours prior to the addition of 0 . 0005% NHS; RNAi induction and NHS selection were maintained throughout . Daily counts were carried out using a haemocytometer , and the total population was maintained at no lower than 20 million cells for the duration of selection . Once robust growth had been achieved , the inducibility of the selected phenotype was tested [25] ( Figure 1D ) and genomic DNA prepared for RNAi target identification . The RNAi cassettes remaining in the NHS-selected library were specifically amplified from genomic DNA using the LIB2f/LIB2r primers [43] producing a ladder of bands ranging in size from 0 . 25–1 . 5-kbp following agarose gel-electrophoresis ( data not shown ) . High-throughput sequencing of the amplified DNA was carried out on an Illumina platform ( Beijing Genome Institute ) . Using paired 150-bp sequencing reads; presence or absence of a 14-bp RNAi-construct signature was recorded in the FASTQ header line . Sequence reads were then trimmed to remove lower-quality sequences and mapped to the T . b . brucei reference genome ( release 4 . 2 ) using bowtie [44] . BAM files were processed using the SAMtools bioinformatics suite [45] . The maps were explored visually in Artemis , and plots were derived using the Artemis graph tool and processed in Adobe Photoshop Elements 8 . 0 . Stacks of reads that included the 14-bp signature on the positive strand were used to define RNAi target fragment junctions and to assign high-confidence hits as those identified by >1 RNAi target fragment . ICP deletion was carried out as described [28] , except that targeting fragments were cloned in pBSD , and the blasticidin-S-deaminase cassette was then replaced with a neomycin phosphotransferase cassette to generate pBSDΔICP and pNPTΔICP constructs . We C-terminally cMyc-tagged an endogenous copy of CATB at a native allele [46] . A 990 bp CATB C-terminal fragment minus the stop codon was cloned into pNATx12MYC [46]; the construct was linearised with PstI prior to transfection . Stem-loop RNAi constructs targeting CATB ( Tb927 . 6 . 560 ) , CATL ( Tb927 . 6 . 960-1060 ) or Tb927 . 8 . 5240 were generated in pRPaiSL [46]; 206 bp ( CATB ) , 578 bp ( CATL ) and 417 bp ( Tb927 . 8 . 5240 ) target fragments were designed using the RNAit primer design algorithm to minimise off-target effects [47] . pRPaiSL constructs were linearised with AscI to enable targeted integration at the rDNA spacer ‘landing pad’ locus in 2T1 bloodstream form T . b . brucei [33] . Details of all oligonucleotides are available on request . Linearised constructs were transferred to icp null or wild-type 2T1 T . b . brucei using a nucleofector apparatus ( Lonza ) in conjunction with cytomix or T-cell nucleofection solutions . Protein expression following RNAi depletion was analysed by SDS-PAGE and western blotting with anti-CATL and anti-cMyc , using standard protocols [48] . For each cell line and treatment , 2 µg RNA was DNase-treated and reverse-transcribed using the Superscript VILO cDNA synthesis kit ( Invitrogen ) . 100 ng ( RNA-equivalent ) cDNA was subjected to qPCR using the Quantitect SYBR Green PCR kit ( Qiagen ) and primer pairs specific for telomerase reverse transcriptase ( TERT; Tb927 . 11 . 10190 ) and Tb927 . 8 . 5240 ( details of primer sequences are available on request ) . TERT was used as a reference for normalisation of gene expression , as previously described [49] . qPCR reactions were carried out in a Rotor-gene 3000 ( Corbett Research ) , using the following cycling conditions: 95°C ( 15 minutes ) , followed by 40 cycles of 94°C ( 15 seconds ) , 58°C ( 30 seconds ) , and 72°C ( 30 seconds ) . Standard curves , derived from a series of 10-fold dilutions of the target PCR products , were used to determine reaction efficiency . Fold-change in gene expression was calculated by the ΔΔCt method [50] . | The interplay among host innate immunity and resistance mechanisms in African trypanosomes has a major impact on the host range of these tsetse-fly transmitted parasites , defining their ability to cause disease in humans . A genome-scale RNAi screen identified a highly restricted set of four genes that sensitise trypanosomes to human serum: those encoding the haptoglobin-haemoglobin receptor , a predicted trans-membrane channel , a lysosomal membrane-protein and the cysteine peptidase inhibitor . An analysis of the cysteine peptidases revealed cathepsin-L as the protease regulated by the inhibitor – and with the capacity to render the parasite resistant to lysis by human serum . These findings emphasise the importance of parasite factors for the delivery and stability of host toxins . They also shed light on the control of proteolysis by parasites and potential unanticipated consequences of therapies that target the parasite proteases . | [
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"protozoology... | 2014 | Cathepsin-L Can Resist Lysis by Human Serum in Trypanosoma brucei brucei |
The mucosal changes associated with female genital schistosomiasis ( FGS ) encompass abnormal blood vessels . These have been described as circular , reticular , branched , convoluted and having uneven calibre . However , these characteristics are subjective descriptions and it has not been explored which of them are specific to FGS . In colposcopic images of young women from a schistosomiasis endemic area , we performed computerised morphologic analyses of the cervical vasculature appearing on the mucosal surface . Study participants where the cervix was classified as normal served as negative controls , women with clinically diagnosed FGS and presence of typical abnormal blood vessels visible on the cervical surface served as positive cases . We also included women with cervical inflammatory conditions for reasons other than schistosomiasis . By automating morphological analyses , we explored circular configurations , vascular density , fractal dimensions and fractal lacunarity as parameters of interest . We found that the blood vessels typical of FGS are characterised by the presence of circular configurations ( p < 0 . 001 ) , increased vascular density ( p = 0 . 015 ) and increased local connected fractal dimensions ( p = 0 . 071 ) . Using these features , we were able to correctly classify 78% of the FGS-positive cases with an accuracy of 80% . The blood vessels typical of FGS have circular configurations , increased vascular density and increased local connected fractal dimensions . These specific morphological features could be used diagnostically . Combined with colourimetric analyses , this represents a step towards making a diagnostic tool for FGS based on computerised image analysis .
The parasite Schistosoma ( S . ) haematobium deposits eggs in the urogenital tract causing urogenital schistosomiasis , and in females , it may cause the clinical syndrome known as female genital schistosomiasis ( FGS ) [1] . Studies have shown that 58–75% of women with detectable excretion of S . haematobium eggs in urine may have genital manifestations [1 , 2] . Likewise , in endemic areas , as many as 41% of women without detectable eggs in urine have been found to have genital lesions [1] . Genital lesions associated with S . haematobium ova are observed as grainy sandy patches , homogenous yellow sandy patches and rubbery papules [3 , 4] . In addition there is often the presence of abnormal blood vessels and occasionally these blood vessels are seen alone [1 , 3 , 4] . It has been hypothesized that the increased vascularity represents neovascularization [5] . However , a histopathological study on cervical biopsies did not find active neovascularization around schistosome eggs [6] . One case report presenting clinical images alongside the histological correlates showed dilated and tortuous venules containing viable schistosome eggs surrounded by a thrombus [7] . Clinically , these abnormal blood vessels have been described as being circular , reticulated , branched , convoluted and of uneven calibre [1 , 3 , 4] . FGS causes genital bleeding , pelvic discomfort and infertility [3 , 8] . There is also cross-sectional evidence that urogenital schistosomiasis increases the odds of having human immunodeficiency virus ( HIV ) by 2 . 9–4 . 0 times [9–11] . The diagnosis of FGS is based on the clinical identification of the characteristic genital lesions and abnormal blood vessels by visual inspection [12] . In areas where urogenital schistosomiasis is co-endemic with HIV , taking biopsies is of ethical concern due to the unnecessary risk of HIV transmission imposed on the patient by the iatrogenic lesion [3] . Urinary and genital egg excretion are poor proxy markers of lesions and systemic antigen / antibody tests do not provide information on the anatomical site of the morbidity [3] . Therefore , there is no adequate objective point-of-care diagnosis for FGS , making it necessary to explore alternative diagnostic tools to support the clinical diagnosis . A safe , simple and reliable diagnosis for FGS is essential to provide patients with proper care and insight into this chronic condition [3] . Treatment for the active infection must be sought but the patient must also be made aware of the chronic nature of the lesions and the potential higher susceptibility to HIV . For many patients , it will be of enormous value to have an explanation for their genital symptoms and this may prevent repeated and unnecessary treatments for STIs based on a syndromic diagnosis . Telemedicine is an approach that currently brings healthcare expertise to the point-of-care in the fields of pathology , dermatology and radiology [13] . We have previously suggested that the emerging smart phone availability in developing countries may be used as a platform to capture and interpret the characteristic sandy patches with computerized colour analyses as a possible approach to a simple diagnosis at the point of care [14 , 15] . Morphological vessel analysis may represent an additional approach to the diagnostic problem , either by itself or as a supplement to the colourimetric analysis . Such a diagnostic tool could be made freely available and easy to distribute to remote , rural areas as a software application , e . g . for smartphones or laptops . Many health clinics in low-resource settings already use digital cameras in their cervical cancer screening programs [16 , 17] . In these clinics it would not represent any additional cost to implement a free , software-based diagnostic tool for FGS detection . We hypothesize that computerized morphological analyses may be used to objectively identify and quantify the abnormal blood vessels associated with FGS . In this study we explore the morphological features of cervical blood vessels observed in three groups: ( 1 ) in cases with FGS , ( 2 ) in endemic controls with other genital pathology and ( 3 ) in healthy endemic controls .
The study was granted permission by the European Group on Ethics in Science and New Technologies ( 2011 , Ref: IRSES-2010:269245 ) , the Biomedical Research Ethics Administration , University of KwaZulu-Natal ( March 2012 , Ref: BF029/07 ) , the regional Department of Health ( DOH ) , Pietermaritzburg , KwaZulu-Natal ( February 2009 , Ref: HRKM010-08 ) and the Norwegian ethics committee , REC South East ( 2007 and 2011 , Ref: 469-07066a1 . 2007 . 535 ) , and the district Departments of Health and Education , KwaZulu-Natal in September 2012 and November 2012 , respectively . Participant details were kept confidential and each was allocated a unique number . All colposcopic images were non-identifiable: They only depict the uterine cervix and contain no names . All participants signed written , informed consent forms prior to investigation and were informed of the right to withdraw at any moment if they so wished . All participants were tested for human immunodeficiency virus , abnormal cytology and sexually transmitted infections . Test results were given to study participants who wanted their results . Counselling , referral and treatment were in accordance with standard DOH , South African guidelines . Anti retroviral therapy is free of charge in South Africa . The study participants were recruited as part of a larger study exploring FGS in young women in South Africa between 2011–2013 . Participants were recruited from rural schools north and south of Durban , KwaZulu-Natal . These are areas endemic for urogenital schistosomiasis [18] . Sexually active , non-pregnant young women aged 16 and above were recruited . Recruitment was not based on symptoms or test results . Trained research assistants interviewed all participants in the local language ( isiZulu ) . The questionnaire included questions on sexual behaviour , pregnancy and contraception . Gynaecological investigation was performed in those who consented . All clinical findings were recorded in electronic format along with a schematic representation of the lesion appearance , size and location ( if present ) . As reported previously , images were captured colposcopically [14 , 15] . We searched the database ( n = 1715 ) for images that fulfilled the following criteria: the cervix should be in the field of view , there should be no foreign material in the field of view ( swab , spatula , acetic acid etc . ) and the exposure and focus should be adequate for visualisation of the cervical surface and its features . We defined three groups based on the clinician's evaluation and subsequent laboratory findings: ( 1 ) women with a normal appearing cervix and no schistosome egg excretion in urine , ( 2 ) women with abnormal blood vessels typical of FGS who had egg excretion in urine or presence of sandy patches and ( 3 ) women with a cervix presenting signs of inflammation ( oedema , swelling and / or rubor ) but no clinical findings typical of FGS and no schistosome egg excretion in urine . Each group consisted of randomly selected participants from the database . A single urine sample was collected between 10 a . m . and 2 p . m . on the day of the clinical examination . Merthiolate-formalin solution ( 2% ) was added to 10 mL of the sample . The sample was centrifuged and the pellet was deposited on two slides . Two independent technicians screened each of the slides by light microscopy [19] . Traditional Pap smears were done by the investigating clinician , preserved with a commercial cytological spray-fixative , then stained and analysed by cytotechnologists . Smears were reported using the Bethesda System of Reporting [20] , and the categories of atypia included . Cellular atypia was classified as atypical squamous cells of unknown significance ( ASCUS ) , low- and high-grade squamous cell intraepithelial lesions ( LSIL and HSIL ) . The number of neutrophils and degree of inflammation were graded as none , mild , moderate or marked . A syndromic protocol was used to diagnose and treat findings at the point of investigation in alignment with the practice in rural clinics . Patients were contacted and asked if they had been treated and helped with further management of the disease once laboratory results were available . Patients with cellular atypia were referred to their local hospital for further management . Cervico-vaginal lavage ( CVL ) was collected by spraying 10 mL of saline four times onto the ectocervical mucosa followed by withdrawal back into a syringe . The CVL was analysed for Trichomonas vaginalis using an in-house real-time PCR technique ( Laboratory of Infection , Prevention and Control , University of KwaZulu-Natal , Durban , South Africa ) . Chlamydia ( C . ) trachomatis and Neisseria gonorrhoea were analysed using strand displacement assay on a ProbeTec machine ( Becton , Dickinson and Company [BD] , Franklin Lakes , New Jersey , USA ) . The CVL was also centrifuged , smeared on a slide and scored using the Nugent's criteria for bacterial vaginosis . Treponema pallidum was analysed using rapid plasma reagin ( RPR ) on serum ( Macro Vue 110 , BD , Franklin Lakes , New Jersey , USA ) and positive samples were confirmed using treponema pallidum haemagluttination assay ( TPHA , Immutrep , Omega diagnostics Group PLC , Alva , United Kingdom ) . Herpes simplex type 2 antibodies were detected in serum using ELISA ( Ridascreen HSV 2 IgG , Davies Diagnostics , Randburg , South Africa ) . HIV was detected in serum using a rapid antibody test ( Core One Step HIV 1/2 test kit , Kendon laboratories , Durban , South Africa ) . Positive tests were confirmed using a different rapid antibody test ( Sensa Tri-Line HIV Test Kit , Pantech ( Pty ) Ltd , Durban , South Africa ) . All image processing and analyses were performed using ImageJ version 1 . 49 ( open source , free software from National Institutes of Health , US ) . Plugins for ImageJ were written in Java ( Oracle Corporation , Redwood Shores , US ) to perform the specific analyses . A macro was written to automate the execution of all the analyses and to record all the results . Numeric results were recorded in a text file and images were generated to allow for visual verification of the analyses ( an example is given in Fig 1F ) . Colposcopic images often contain non-mucosal elements such as parts of the speculum , medical instruments and skin that should not be subject to the image analysis . As reported previously , we therefore applied automated detection of the region of interest ( ROI ) prior to analysis , using a previously described method , which identifies the cervix as the central area in the image having the highest values in the "a-channel" ( of the "Lab colour space" ) [14] . In order to do morphological analyses on the cervical blood vessels , the blood vessel structures were identified by splitting the original colour image into the "green channel" ( of the "RGB colour space" ) and the "saturation channel" ( of the "HSV colour space" ) . The blood vessels , which appear bright red , have very low values of green and will therefore appear dark in the green channel . Furthermore , the blood vessels have high values of saturation and will therefore appear bright in the saturation channel . However , the ectocervix is convex and the surface is not evenly illuminated by the colposcope . It was therefore necessary to equalize the green and saturation channels . By generating an inverted image , which was subsequently smoothed using a Gaussian blur filter and then calculating the sum ( addition ) with the original image , the irregular illumination of the ectocervix was eliminated . The product ( multiplication ) of the inverted green channel and the saturation channel resulted in an image where the blood vessels had higher values than the initial images ( Fig 1B and S3 Fig ) . This resulting image was used for the subsequent analyses and is henceforth referred to as the processed image . Template matching allows for the identification of structures resembling a pre-defined template [21] . In ophthalmology , template matching algorithms have been developed to identify the optical nerve [21 , 22] . A circular template was generated to resemble the characteristic circular shape of the vessels as indicated by experienced clinicians ( S6C Fig ) . For the template matching , the vascular structures were isolated from the processed image by removing all pixels below the mean value of grey ( Fig 1C and S6B Fig ) . Template matching by convolution is a very processor-intensive process if applied as a pixel-by-pixel approach in the image domain , which would be impractical for a cell-phone application . Therefore , template matching was performed by converting the template and the image to the frequency domain by the fast Fourier transform [23] , multiplying them and finally converting the result back to the image domain ( multiplication in the frequency domain corresponds to convolution in the image domain ) . In the resulting image , areas with circular configurations have higher intensity ( Fig 1D and S6D Fig ) . A threshold level was set to remove pixels below the 97 . 5th percentile of intensity ( S6E Fig ) . The final image contains clustered pixels representing the centres of the matched circular structures ( Fig 1D and S6F Fig ) . The number of circles identified was recorded for each image . For the remaining morphological analyses , the processed image was converted to a binary image by an algorithm based on the Niblack [24] method for local adaptive thresholding , where the local threshold T ( x , y ) = μ ( x , y ) + k * σ ( x , y ) , where μ and σ are the local mean value and standard deviation , respectively , within a sliding , circular window with a 50 pixel radius . Instead of a constant k-value determined empirically by trial-and-error [25] ( S4E Fig ) , we inferred the optimal k-value for each image by first estimating the most likely distributions of foreground and background by using an expectation-maximisation ( EM ) algorithm ( k-means clustering ) ( S4F Fig ) . However , local adaptive thresholding may result in noise in areas with low contrast . We therefore only applied the Niblack threshold if the local standard deviation exceeded the mean standard deviation of all possible windows . If it did not , the area was defined as "low-contrast" , and the threshold was set to the most likely foreground grey value ( as estimated by the EM-algorithm ) . Furthermore , local adaptive thresholding may produce perimeter artefacts when applied on an isolated structure laid over a background , due to artificially high contrast between background and structure ( S4E Fig ) . This was the case in our approach since we performed all analyses within a ROI . We therefore also used the most likely foreground grey value as threshold value for pixels whose window ( 50-pixel radius ) fell within the perimeter of the ROI . Noise was removed from the resulting binary image by using a median filter with a radius of 4 pixels . An example of a resulting binary image is shown in Fig 1E . After smoothing , the structures were skeletonised to a single pixel width , since in this context we are interested in the spatial configuration of the vessels . The skeletonisation was done using a lookup table to repeatedly remove pixels from the edges of objects in the binary image , analysing 3x3 pixel grids [26] . The skeletonised images were first used for calculating the distance between vessels and the total number of vessels per image . Distinct vessels were defined as not being connected by an 8-neighbourhood relationship . The distance between blood vessels was defined as the distance from any given vessel to its’ closest neighbour in a straight line . The skeletonised blood vessels were superimposed on the original colour image ( Fig 1F ) to allow for visual verification by the clinician . Experienced clinicians confirmed that the patterns portrayed in Fig 1F are recognized as typical in FGS cases ( personal communication , EFK and HNGA ) . Blood vessels may be considered fractals; objects whose details under magnification resemble the structure as a whole ( S1 Text and S1 Fig and S2 Fig ) [27] . The calculated fractal dimension of a network of vessels increases with increasing complexity [27] . A single point has a fractal dimension of zero , a straight line has a fractal dimension of one and a plane has a fractal dimension of two . However , a convoluted vessel in a plane will have non-integer fractal dimension ( D ) between that of a line ( D = 1 . 0 ) and a plane ( D = 2 . 0 ) . Analysis of local connected fractal dimensions ( LCFD ) allows for identification of areas with higher or lower fractal dimensions within a fractal [27] . In ophthalmology , it was possible to identify patients with occlusion of the retinal artery by analysis of LCFD [27] . Another study found that patients with cerebral lacunar strokes had lower fractal dimensions of the retinal vessels compared to patients with minor cortical strokes [28] . Fractal lacunarity is a counterpart to the fractal dimension describing the heterogeneity of a fractal in terms of the size and distribution of holes or gaps [29] . If a fractal has large gaps or holes , it has high lacunarity . In gynaecology , fractal dimension and fractal lacunarity have been used to classify the uterine vessels seen in hysteroscopic images of patients with endometrial cancer and abnormal uterine bleeding [30] . We used the box counting method [29] , with boxes doubling in size from 2–128 pixels , to estimate the general fractal dimension and lacunarity for the vascular network ( S5 Fig ) . The LCFDs were calculated using the free ImageJ plugin FracLac version 2015Marb6206 ( Charles Sturt University , New South Wales , Australia ) . Statistical analyses and graphs were produced using IBM SPSS Statistics Version 19 ( IBM Company , Chicago , USA ) . A sample size calculation showed that we needed a minimum of 36 cases in each group in order to be able to demonstrate a difference of 10% or more within a 95% interval of confidence if the standard deviation is 15 or less ( arbitrary units ) . We decided to include 50 cases in each of the three groups . Group characteristics were compared using the Kruskal-Wallis analysis of variance ( age , days since last menstrual period and days since last intercourse ) and the Chi-square test ( pregnancy , hormonal contraception , STIs and findings in Pap-smear ) . Comparisons of morphological characteristics were done using bivariate logistic regression; comparing the normal cervical appearance to those with blood vessels typical of FGS and those with cervical inflammation . A multivariable logistic regression model was constructed using all the morphological characteristics and the group characteristics that differed significantly between the groups within an 85% interval of confidence . Variables were eliminated from the model one by one ( backwards elimination ) based on a minimum significance level of 0 . 15 and only if the model's likelihood ratio did not change significantly ( p < 0 . 05 ) . The final regression model was used to construct a ROC-curve to find the optimal cut-off value for identifying images with abnormal blood vessels typical of FGS , by identifying the point of the curve closest to the upper left corner . Classification accuracy was calculated using the cut-off value found on the ROC-curve .
The group characteristics are presented in Table 1 . The women were similar in all respects except for the use of hormonal contraceptives , the prevalence of C . trachomatis and Herpes simplex . These variables were therefore considered when constructing the multivariable regression model . The morphological analyses presented in Table 2 show that women with FGS have significantly more circular blood vessels and a higher density of vessels are visible on the surface . In addition the fractal dimensions were higher in women with FGS . In women with FGS , we found that the strongest morphological predictor of pathology was the presence of circular configurations in the vascular network ( Table 3 ) . We also found increased vascular density and increased vessel complexity ( as estimated by LCFD ) in women with FGS ( Tables 2 and 3 and Fig 2 ) . In the multivariable analysis , the number of blood vessels , general fractal dimension , general fractal lacunarity and peak LCFD were eliminated from the regression model along with the possible confounders; hormonal contraceptives , C . trachomatis and Herpes simplex ( Table 3 ) . The final regression model was used to generate a ROC curve ( Fig 3 ) and the optimal cut-off value was -0 . 037 . Using this cut-off value for the regression model , the model’s classification accuracy was calculated ( Table 4 ) . Finally , by defining the images with blood vessels typical of FGS as positive cases and the combined set of images with normal cervical appearance and cervical inflammation as negatives , the overall ability to classify the image correctly was 78% for positive cases and 80% for negative cases .
It has been reported that abnormal blood vessels typical of FGS present with specific morphological features [3] . Our findings support this observation and confirm that assessment of vessel appearance is of clinical significance when diagnosing FGS . Furthermore , our findings suggest that computerised image analyses of blood vessels visible on the cervical surface may play a role in developing a diagnostic tool for FGS , possibly together with colour analyses of sandy patches [14 , 15] . The World Health Organization recommends criteria for point-of-care tests: Affordable , Sensitive , Specific , User-friendly , Rapid and robust , Equipment-free and Deliverable to end-users ( ASSURED ) [31–33] . No such diagnostic tools exists for FGS and , to our knowledge , none are in the pipeline . Cellular phones are increasingly available in schistosomiasis endemic areas and a software-based diagnostic tool can be made freely available ( for download ) for use on existing devices such as smartphones , tablets or laptops . The software can be designed in a user friendly way and it can analyse the images instantly on the device , at the point of care ( < 10 seconds using current laptops ) . However , it needs to be verified whether such a method is sufficiently accurate and robust when applied in a low-resource setting by local health professionals . All the image analyses performed by this research group have been done using the Java-framework provided by ImageJ , which is open source and available on a number of platforms . It can therefore easily be deployed on any unit capable of running ImageJ . For implementation on Android devices , the necessary Java-libraries would simply need to be bundled in the application package . For other devices ( not running Java ) , implementation might prove to be more laborious as the methods might need to be rewritten to conform to the operating system’s base language . The current paper explores the possibility of using the morphological features of the abnormal blood vessels associated with FGS but this research group has previously published methods for diagnostics based on image analysis using colour to detect sandy patches [14 , 15] . The significance of these various lesions in terms of the pathophysiology and morbidity of FGS is not well understood . They may represent different aspects of the disease , different degrees of severity or progression . A diagnostic algorithm should include all the characteristic lesions and future studies may try to decipher their individual significance . Combined , they might also provide increased diagnostic accuracy [15] . We found a significantly higher number of circular features in the vascular network of patients with FGS . Furthermore , we found decreased distance between vessels and increased LCFD in women with FGS , indicating that the cervical vascular network is denser and morphologically more complex than in other diseases or in normal cervices . Increased LCFD is a morphological feature that requires computer analysis and will therefore only be clinically relevant when the diagnostic software has been introduced . However the two other findings ( circular vessels and increased vessel density ) can be recognised by a trained clinician and therefore represent objective , clinical observations that complement and support diagnosis of FGS that is based on inspection . The circular vessel configuration which is seen more frequently on cervices of women with FGS could represent an area where an egg granuloma acts as a foreign body that locally prevents the growth of blood vessels or pushes them aside as the granuloma grows . Alternatively , the occlusion of a blood vessel by a schistosome worm-pair; its eggs and/or egg-induced thrombosis could cause dilatation and varicose-like distortion of the vessel [7] . In ophthalmology , the retinal vasculature has areas with increased LCFDs in patients with occlusion of the central vein or retinal artery [27] . Our finding of increased LCFDs in women with FGS therefore supports the argument that occlusion of small vessels may in fact represent an important feature in urogenital schistosomiasis . We were not able to assess vessel calibre , as the images did not provide sufficient detail for this . Uneven calibre has been proposed as one of the characteristic features of FGS . However , this is difficult to assess without high magnification colposcopy and may therefore not be suitable for a low-cost , simple diagnostic approach . Furthermore , the analyses in this study were performed on images acquired colposcopically . However , colposcopes are generally not available in clinics in endemic areas [34] . Previous attempts at performing computerised colour analyses on images of simulated low quality have shown good results [14] . Simple , handheld cameras have been evaluated for use in visual inspection with acetic acid ( VIA ) in cervical cancer screening programmes [35 , 36] . Similarly , this method should be evaluated on images acquired using simple devices such as handheld cameras or mobile devices . One obstacle that will need to be addressed when using simple handheld devices , is even illumination of the field . This is provided when using a colposcope , but for handheld devices it might be necessary to use an external light source such as a flashlight or a lamp . Furthermore , where colposcopes are available , these are primarily used for cancer screening . It would therefore be prudent not to depend on such equipment for the diagnosis of FGS , as there could be a false reassurance in regards to excluding cancer as a differential diagnosis if the colposcope is sometimes used for the diagnosis of FGS without targeted screening for cancerous lesions . The analyses of colposcopic images are also limited by the narrow depth of field ( the area in focus ) provided by the colposcope . Since the ectocervix is generally convex in shape , only parts of its surface can be within the depth of field at once when photographed by a colposcope . Furthermore , it is rarely possible to visualise all the surfaces of the lower genital tract , especially the fornices and the vaginal wall . This may result in false negative cases in which lesions are missed . However , this would skew our results towards the null-hypothesis , thus strengthening our findings . The participants in this study are young women aged 16–27 and cervical appearance may differ in older women due to transformation of the ectocervical columnar epithelium by metaplasia into squamous epithelium ( the transformation zone ) with increasing age [37] . Blood vessels typical of FGS appear in circular configurations , have increased density and increased local connected fractal dimensions ( LCFD ) . Future studies should assess these findings alongside the colourimetric analyses of the sandy patches in images acquired using a simple digital camera . Furthermore , the digital application should be explored as a supplement to the visual inspection . | Female genital schistosomiasis ( FGS ) is a disease of the female genitalia caused by a water-borne parasite . The parasite lays eggs that may be found in the genital organs and these eggs cause local inflammation and subsequent lesions . These lesions are called sandy patches and they are often accompanied by abnormal blood vessels . Sandy patches can be hard to see and clinicians have suggested that the typical blood vessels may serve as supporting or independent diagnostic indicators of FGS . Clinicians have described the specific features of the vessels as: appearing as circular shapes , forming a network and having branches . In this study , we examined the shape and appearance of cervical blood vessels by computer image analysis . We found that the blood vessels in women with FGS appear more often as circular shapes , at higher density and with more complex shapes compared to those in healthy women and in women with inflammation of the cervix for other reasons than FGS . Our findings suggest that cervical vessel appearance can contribute to the diagnosis of FGS . It could also be used in a future diagnostic tool using computer analysis . Further research is needed to determine if FGS can be diagnosed objectively . | [
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"immunodeficien... | 2016 | Characteristics of Blood Vessels in Female Genital Schistosomiasis: Paving the Way for Objective Diagnostics at the Point of Care |
PRDM family members are transcriptional regulators involved in tissue specific differentiation . PRDM5 has been reported to predominantly repress transcription , but a characterization of its molecular functions in a relevant biological context is lacking . We demonstrate here that Prdm5 is highly expressed in developing bones; and , by genome-wide mapping of Prdm5 occupancy in pre-osteoblastic cells , we uncover a novel and unique role for Prdm5 in targeting all mouse collagen genes as well as several SLRP proteoglycan genes . In particular , we show that Prdm5 controls both Collagen I transcription and fibrillogenesis by binding inside the Col1a1 gene body and maintaining RNA polymerase II occupancy . In vivo , Prdm5 loss results in delayed ossification involving a pronounced impairment in the assembly of fibrillar collagens . Collectively , our results define a novel role for Prdm5 in sustaining the transcriptional program necessary to the proper assembly of osteoblastic extracellular matrix .
PRDM proteins constitute a family of transcriptional regulators characterized by the presence of a N-terminal PR- domain that shares 20–30% similarity to the SET domain of histone methyltransferases and a variable number of zinc-finger domains typically involved in protein-DNA or protein-protein interaction [1] . Members of this family influence tissue specific differentiation as demonstrated for Prdm1 in lymphoid cell maturation [2] , and Prdm16 in brown fat development [3] . Moreover , several members of the family are deregulated in pathological settings , most notably cancer , by acting either as oncogenes or tumor suppressors [1] . PRDM5 localizes to human chromosome 4q26 and encodes , aside from the PR domain , 16 C2H2 zinc fingers . PRDM5 has previously been reported to lack intrinsic histone methyltransferase activity but to predominantly repress transcription by recruiting G9a and HDACs enzymes to target genes [4] . Furthermore , PRDM5 has been indicated as a potential tumor suppressor in various cancers [5]–[7] , but its role in mammalian development and normal physiology has not been addressed . In zebrafish , Prdm5 loss induces morphogenic defects due to impairment of convergent extension movements at the gastrulation stage , likely resulting from deregulation of the WNT inhibitor Dkk1 [8] . Recently , mutations in PRDM5 were detected in Brittle Cornea Syndrome ( BCS ) [9] , a connective tissues disease characterized by thinning of the cornea and a wide spectrum of additional symptoms including dermal and skeletal defects [10] . Bone is composed of a highly specialized , mineralized collagenous matrix that provides tensile strength to the skeletal system . Collagen I is the major component of osteoblasts matrix , composed of a heterotypic triple helix derived from Col1a1 and Col1a2 chains typically in a 2∶1 stoichiometric ratio [11] , [12] . Approximately 40 collagen genes are annotated in mammalian genomes encoding around 28 proteins and , of these , type I collagen is part of the subfamily of fibrillar collagens [13] . Collagen chains are synthesized and assembled as triple helical procollagen molecules . Extracellular proteinase cleavage of N- and C-terminal telopeptides leads to mature tropocollagen that is further assembled into fibrils and fibers [14] . The latter process is regulated by other extracellular macromolecules including proteoglycans from the Small Leucine Repeat family ( SLRP ) , such as Decorin and Fibromodulin [15] , [16] . A number of transcription factors have been discovered as regulators of collagen I genes ( reviewed in [17] , [18] ) , such as Sp1 [19] , Cebpβ [20] or members of the AP1 family [21] . Furthermore , a number of transcription factors are known to be key regulators of bone development , such as Runx2 [22] , which controls the expression of a multitude of extracellular matrix ( ECM ) genes essential for both the chondrogenic and osteogenic programs [23] . We present here a novel molecular function for Prdm5 in sustaining transcription of key ECM genes . Prdm5 is highly expressed in the osteoblast region of developing bones in vivo and genome wide mapping of Prdm5 occupancy in osteoblastic cells identifies all collagens and a number of SLRP genes as direct targets for Prdm5 . Interestingly , Prdm5 binds predominantly within the exonic regions of collagen genes and its presence dictates the amount of intragenic RNA polymerase II . Indeed , Prdm5 sustains transcription of Collagen I genes by maintaining RNA polymerase II occupancy throughout the Col1a1 gene , while the binding to a distal enhancer element upstream of Decorin gene suggests a further role in chromatin organization . Osteoblasts lacking Prdm5 display decreased Collagen I and Decorin expression leading to reduced Collagen I fiber assembly in vivo . Downregulation of these key extracellular matrix genes likely participates in the delayed ossification and decreased bone mineral density observed in Prdm5 mutant mice . Our data defines novel roles for Prdm5 as a transcriptional modulator of collagen genes by influencing RNA polymerase II occupancy , as well by binding to enhancer-like elements in osteoblastic cells .
To address a possible role in mammalian development for Prdm5 , a gene-trap mouse model featuring the integration of a β-galactosidase-neomycin ( β-geo ) cassette in intron 2 of the Prdm5 gene was generated ( Prdm5LacZ ) . This cassette is preceded by a splice acceptor site to direct exon 2-β-geo splicing and ends with a poly-A site to terminate transcription ( Figure 1A ) . In mutant cells , expression of the Prdm5 locus results in the production of a fusion transcript between the first two exons of Prdm5 ( ≈60 amino acids ) and the β-geo cassette with a resulting fusion protein of approximately 135 kDa in size ( Figure S1A ) . To validate the effectiveness of the gene-trap system , we quantified the levels of the wt Prdm5 allele in Prdm5LacZ/LacZ embryonic fibroblasts and found it to reach a maximum of 10% relative to the expression in wt littermates ( Figure S1A ) . In adult organs , except for brain , testis and lung , we observed Prdm5 levels reduction to be at least 85% in the tissues tested ( Figure S1B ) . In contrast to the essential role in zebrafish [8] , Prdm5LacZ/LacZ mice are viable and fertile and the mutant allele segregates according to Mendelian ratios ( Figure S1C ) . Gross pathology analysis did not reveal obvious abnormalities and no notable differences in weight were detected between mutant mice and wild type littermates up to the age of 56 weeks ( Figure S1D ) . To characterize the expression pattern of Prdm5 , we tracked the β-galactosidase expression driven by the endogenous Prdm5 promoter by whole mount X-gal staining at various developmental stages . At E10 . 5–12 . 5 the LacZ reporter was expressed in a diffuse staining pattern along meso-endodermal derived regions with higher intensity in the heart ( Figure 1B and 1C ) . At E14 . 5 LacZ staining accumulated in limbs and snout regions and in particular in cartilaginous templates ( Figure 1D ) . From E16 . 5 a specific staining pattern was observed in skeletal elements , particularly in long bones and ribs ( Figure 1E ) . In these tissues LacZ was highly expressed in the osteoblastic regions including the trabecular compartment and periosteum/perichondrium ( arrows in Figure 1F ) . LacZ staining on sections from E16 . 5 embryo tibia revealed that the Prdm5 promoter is active in a subpopulation of cells in the osteoblast region ( periosteum and trabecular area ) ( Figure 1G ) , whereas no signal was detected in the hypertrophic or proliferative chondrocytes zones ( Figure 1G ) . Moreover , LacZ staining of calvariae of Prdm5LacZ/LacZ mice at P0 indicated that Prdm5 expression in osteoblasts is not restricted to long bones but can be detected also in skull sutures and weakly in calvariae ( Figure 1H ) . Robust PRDM5 expression in osteoblasts was further confirmed in primary human osteoblast cells isolated from healthy donors , compared to a panel of human immortalized cell lines of different origins ( Figure S1E ) . Moreover we found comparable Prdm5 expression levels in mouse primary calvarial osteoblasts , the osteoblastic MC3T3 cell line and primary embryonic fibroblasts ( Figure S1F ) . In summary , in vivo expression analyses confirmed Prdm5 as consistently expressed in osteoblastic compartments in the mouse . Since Prdm5 is highly expressed in osteoblastic cells , we chose the MC3T3 cell line model to investigate the roles of Prdm5 during osteogenic differentiation . Cells were transduced with lentiviral shRNA constructs against Prdm5 , which resulted in efficient reduction of both Prdm5 transcript and protein levels ( Figure 2A ) . Prdm5 depletion did not significantly affect proliferation of MC3T3 cells as assessed by BrdU labeling ( data not shown ) but led to a significant reduction in matrix mineralization as measured by Alizarin red staining of calcium nodules upon induction of osteogenic differentiation ( Figure 2B ) . In line with this , overexpression of PRDM5 induced the opposite phenotype resulting in increased nodule formation ( Figure 2C and 2D ) . In parallel , the significance of Prdm5 in chondrogenesis was evaluated by knocking down Prdm5 in the ATDC5 chondrogenic cell line ( Figure S2A ) . In this system , Prdm5 loss did not affect chondrogenic differentiation , as evaluated by measuring glycosaminoglycan deposition ( Figure S2B ) . To investigate transcriptional changes imposed by Prdm5 loss in primary osteoblasts , expression levels of a series of osteogenic markers in Prdm5 wild type and mutant calvarial osteoblasts were measured by qRT-PCR . Significant reduction was observed for transcripts encoding Osteocalcin ( Bglap1 ) and Bone sialoprotein ( Ibsp ) , both late osteoblast markers , while transcript levels for early markers such as Osteopontin ( Spp1 ) , Osterix ( Sp7 ) and Runx2 were unchanged ( Figure 2E ) . When assayed for mineralization activity , no difference in matrix calcification was detected by Alizarin red staining in calvarial osteoblasts from cohorts of WT and mutant animals ( Figure S2C and S2D ) . However , this phenotype may depend on cellular adaptation in culture , since treatment of wild type calvarial osteoblasts with a siRNA oligo which efficiently reduces Prdm5 levels , resulted in decreased matrix mineralization after 14 days of osteogenic stimulation ( Figure S2E ) . Collectively , the data indicate that Prdm5 exerts a cell-autonomous function in the osteogenic pathway . To unveil the molecular functions of Prdm5 in osteoblastic cells and identify direct target genes , chromatin immunoprecipitation followed by deep sequencing ( ChIP-seq ) was performed for Prdm5 in the MC3T3 cell line . Two different Prdm5 polyclonal antibodies were generated and western blot analysis of Prdm5 wild type and mutant mouse embryonic fibroblasts revealed that these antibodies recognize distinct epitopes ( Figure S3A ) , and both were confirmed as suitable for ChIP experiments ( Figure S3B ) . Data from ChIP-seq analyses with the two antibodies were overlaid resulting in 1712 common loci we defined as high confidence Prdm5 target regions ( Figure S3C and Table S1 ) . Interestingly , 29% of Prdm5 peaks resided in promoter regions , while 39% of the peaks resided inside the body of genes ( Figure 3A ) . Across all genes , Prdm5 binding was distributed throughout the length of target genes with the highest density around the TSSs ( Figure 3B ) . A de novo motif finding algorithm for Prdm5 peak centers identified a putative consensus sequence for Prdm5 binding ( Figure 3C ) . This sequence bears strong similarity to a Prdm5 consensus previously identified by in vitro random oligonucleotide selection experiments ( Figure S3D ) [4] . To confirm whether DNA fragments containing the identified sequence motif were directly recognized by Prdm5 , in vitro pulldown assays using biotinylated DNA oligonucleotide probes were performed . Overexpressed HA-PRDM5 readily bound to DNA probes containing the consensus motif ( a region of Col1a1 exon 33 , containing 3 motifs with p-score 0 . 96 ) , whereas the binding was impaired by mutation of the first and last two guanines of the consensus motifs ( Figure 3C ) . Gene activity in MC3T3 cells was also estimated by performing ChIP-seq on the same chromatin preparation for total RNA polymerase II , histone H3 lysine 4 trimethylation ( H3K4me3 ) and H3 lysine 9 trimethylation ( H3K9me3 ) , allowing for a correlation of Prdm5 binding to gene activity . Prdm5 bound genes were enriched either for the presence of H3K9me3 or H3K4me3 , with a strong preference for Prdm5 target genes to present H3K4me3 peaks around their TSS , when compared to the average of 100 permutations of a size-matched set of random genes ( Figure 3D ) . These results indicate that Prdm5 may act both as a transcriptional repressor and activator in a promoter-dependent fashion and that in MC3T3 cells the majority of Prdm5 target genes are actively transcribed . Indeed , Prdm5 target genes were also associated with RNA polymerase II occupancy ( to a similar extent as H3K4me3 ) ( Figure 3D ) and expression analysis from microarray data of MC3T3 cells showed that genes bound by Prdm5 are characterized by a general increase in expression signal with respect to the total of the genes represented on the microarray ( Figure 3E ) . Annotation of the Prdm5 bound loci and detailed analysis followed by ChIP-qPCR validation on independent samples with both Prdm5 antibodies strikingly revealed that 42 of 43 collagen genes in the mouse genome contained at least one Prdm5 peak ( Figure 4A ) . Moreover , the results were validated in primary wt and LacZ/LacZ calvarial osteoblasts , where Prdm5 enrichment was strongly reduced in mutant cells ( Figure S4A and S4B ) . When genomic regions bound by Prdm5 were subsequently annotated according to biological processes , a strong enrichment was observed for genes associated with collagen fibril and extracellular matrix organization , as well as bone development ( Figure 4B ) . Prdm5 binding to collagen genes occurred almost exclusively in the gene body with approx . 60% of peaks centered in exonic regions ( Figure 4C ) . Importantly , Prdm5 occupancy in the body of collagen genes correlated with the amount of bound RNA polymerase II in the same regions ( Figure 4D ) , suggesting a role for Prdm5 in sustaining transcriptional activity of the collagen gene family . Very high enrichment for Prdm5 binding was observed in the two genomic loci corresponding to the collagen I genes Col1a1 and Col1a2 ( Figure 4D and Figure S4C ) . Prdm5 knockdown by means of two siRNA oligos demonstrated that Prdm5 occupancy in Col1a1 and Col1a2 genes was functionally relevant , as reduction in Prdm5 levels led to a decrease in transcript and protein levels of both type I collagen genes ( Figure 4E and Figure S4D ) . This effect was observed also in primary osteoblasts upon genetic ablation of Prdm5 ( Figure S4E ) . Given the close correlation between Prdm5 occupancy and RNA polymerase II presence , we measured the occupancy of the latter along the whole length of the Col1a1 gene in Prdm5 wild type and mutant osteoblasts . While RNA polymerase II levels were unchanged in LacZ/LacZ cells at the Col1a1 TSS , we observed a significant drop in RNA polymerase II levels in mutant Prdm5 osteoblasts between +6 . 2 kb and the end of the Col1a1 gene ( Figure 4F ) . Towards understanding the mechanism , we hypothesized that Prdm5 could affect RNA polymerase II by direct interaction . Indeed , overexpressed HA-PRDM5 co-immunoprecipitated with endogenous RNA polymerase II and with higher affinity to the elongating form of RNA polymerase II as evident from analysis using a phospho-serine 2 specific RNA polymerase II antibody ( Figure 4G ) . In summary , Prdm5 targets virtually all the collagen genes in the mouse genome and high Prdm5 occupancy inside the Col1a1 gene body promotes RNA polymerase II occupancy and transcription . Analyses of the annotation of Prdm5 bound loci revealed that the Prdm5 target repertoire extends to genomic regions encoding other ECM genes involved in collagen fibrillogenesis , such as Periostin ( Postn ) and genes from the SLRP family , such as Decorin ( Dcn ) , Fibromodulin ( Fmod ) , Biglycan ( Bgn ) and Epiphycan ( Epc ) . Also in this case , Prdm5 occupancy on selected targets was validated in independent samples from MC3T3 cells ( Figure 5A ) , as well as primary calvarial osteoblasts ( Figure S5A and S5B ) . Since Decorin is well known to regulate collagen fibrillogenesis , we analyzed the influence of Prdm5 on Decorin expression . Indeed , we observed that Prdm5 knockdown resulted in decreased Decorin transcription ( Figure 5B ) . This effect could be reproduced in Prdm5LacZ/LacZ calvarial osteoblasts ( Figure 5C ) . While cell-associated Decorin protein levels were only mildly decreased upon Prdm5 knockdown ( Figure 5D ) , the amount of secreted Decorin detected in cell culture media from Prdm5 siRNA treated cells was strongly reduced ( Figure 5D ) . A closer inspection revealed that the Prdm5 binding site assigned to Decorin gene was 100 kilobases distant from its TSS , suggesting the binding to a distal enhancer ( Figure S5C ) . Chromatin immunoprecipitation for H3K4me1 and H3K27ac confirmed that Prdm5 bound a site upstream of Dcn with a chromatin signature corresponding to an enhancer element ( Figure 5E ) . Our data show that Prdm5 targets SLRP family members and likely regulates Decorin via a distal enhancer . Collagen I is the main component of osteoblastic ECM [11] and Decorin is known to regulate collagen I fibrillogenesis [16] . The observed Prdm5 regulation of Collagen I and Decorin genes prompted us to characterize their deregulation in vivo and the resulting phenotype in Prdm5LacZ/LacZ mice . qRT-PCR analyses revealed that the Col1a1 and Col1a2 transcripts were significantly reduced upon Prdm5 loss in E16 . 5 limbs ( Figure S6A ) . Moreover , decreased Collagen I was observed by in situ hybridization in the periosteum at E16 . 5 ( data not shown ) , as well as by immunofluorescence microscopy ( Figure 6A ) . While Decorin transcript levels were unchanged in whole E16 . 5 mutant limbs ( Figure S6B ) , immunofluorescence staining displayed reduction of Decorin protein , particularly in the periosteum and invading osteoblasts region ( Figure 6A ) , indicating an osteoblast-restricted Prdm5 regulation of Decorin . Given that both molecules are involved in collagen fiber formation , fibrillar collagen levels were evaluated in Prdm5LacZ/LacZ embryonic limbs by picrosirius red staining . Using bright field microscopy , a decreased staining of collagen could be appreciated in the mutants ( Figure S6C ) . Moreover , using polarized light to visualize specifically assembled collagen fiber birefringency , a marked decrease in the presence and organization of collagen fibers was observed in Prdm5LacZ/LacZ embryonic limbs ( Figure 6A ) . Histological examination revealed a shorter osteoblast compartment in mutant animals ( Figure 6B ) , suggesting a delay in the ossification process . Likewise , Von Kossa stainings revealed decreased calcification in mutant limbs further pointing to an impaired ossification process in Prdm5 mutants ( Figure 6C ) . To quantitate the delayed ossification , wild type and Prdm5LacZ/LacZ E18 . 5 embryos were analyzed by micro-CT ( μCT ) scanning . Quantification of total bone volume demonstrated a significant reduction in the ossification process in mutant embryos ( Figure 6D ) . However , at E16 . 5 , no overt differences in the expression of various bone formation markers were observed ( Figure S6D ) . To measure the impact of the embryonic ossification defect in young mice hind limbs from cohorts of WT and Prdm5LacZ/LacZ mice of both genders were analyzed by peripheral Quantitative Computed Tomography ( pQCT ) . Images of distal metaphyseal sections from CT-scans of femurs at 5 weeks of age demonstrated a decrease in bone mineral density ( Figure 6E ) . Quantification of total bone mineral density , total mineral content and total bone area in large cohorts of mice demonstrated a statistically significant reduction in all three parameters in Prdm5LacZ/LacZ mice of both genders ( Figure 6F and Table S2 ) . Separate measurements of the cortical and trabecular compartments revealed a more robust reduction in all measured parameters in cortical regions than trabecular areas ( Table S2 ) , coinciding with the areas where downregulation of Collagen I and Decorin was predominantly observed in mutant embryo limbs . In summary , Prdm5LacZ/LacZ animals display a significant reduction in collagen levels and fibrillogenesis , likely resulting in the observed osteopenic phenotype .
In this study , we uncover a novel function for Prdm5 in promoting the transcription of key extracellular matrix genes in osteoblastic cells . We find that Prdm5 is specifically expressed in the osteoblastic compartment of developing bones and exerts its function along the osteogenic lineage by promoting osteogenic differentiation in culture . Mechanistically , we demonstrate that Prdm5 targets ECM gene families such as collagens and small leucine-rich proteoglycans . By association with RNA polymerase II , Prdm5 sustains the transcription of collagen I genes , while the regulation of Decorin expression is mediated via binding to a distal enhancer-like element . Prdm5 regulation of these genes occurs in vivo in developing limbs resulting in the decreased bone mineral density observed in Prdm5LacZ/LacZ animals . Members of the PRDM family display tissue specific patterns of expression [24] , in agreement with a role in tissue specific differentiation . In line with this , Prdm1 is known to be a master regulator of lymphoid differentiation [2] , Prdm16 to control brown fat development [3] , Prdm14 to regulate embryonic stem cell pluripotency and germ cell differentiation [25] , [26] and Prdm9 to determine meiotic recombination hotspots [27] . So far Prdm5 has not been characterized in the context of mammalian development . Our study thus provides the first evidence of a role for Prdm5 in tissue specific differentiation extending the concept of PRDM proteins as regulators of specific tissues and in agreement with the idea of functional specialization of PRDM members during expansion of the family in vertebrates [28] . The identification of high Prdm5 expression in osteoblasts and its function in osteogenic differentiation in vitro permitted us to evaluate its molecular functions in a relevant cellular context . Indeed , it is noteworthy that Prdm5 silencing does not restrict chondrogenic differentiation in vitro suggesting cell type specificity in Prdm5 action . By genome wide mapping of Prdm5 binding sites in a pre-osteoblastic cell line , we demonstrate a unique capacity of Prdm5 to bind the whole family of collagen genes and especially to bind these genes within the gene body . This is an unprecedented feature for a transcriptional regulator , i . e . binding the gene bodies of all the members of such a large gene family . Moreover , we observed Prdm5 occupancy in genomic regions encoding for non-collagen proteins with collagenous domains ( e . g . C1q family ) , suggesting that either Prdm5 consensus sequence is overrepresented in genomic regions encoding for collagenous domains , or that simply Prdm5 binds common regulatory elements shared by specific gene families . Indeed we detected Prdm5 binding to several members of the SLRP family as well as a number of genes encoding for essential extracellular matrix components ( complete list in Table S1 ) , demonstrating that Prdm5 potentially regulates a wide but specific transcriptional program necessary for proper extracellular matrix formation . In this study , we focus on fibrillar collagens , particularly Collagen I genes; these were highly enriched for Prdm5 binding and are essential constituent of osteoblastic matrix . A number of transcription factors have been shown to regulate Collagen I genes and the location of their binding sites on Col1a1 and Col1a2 promoters have been shown to determine the expression in different osteoblast subtypes [29] , [30] . Very little is known concerning the regulation of Col1a1 and Col1a2 gene expression by factors binding downstream of their promoter , except for a repressor region located within intron 1 that can recruit GATA and IRF proteins to block enhancer stimulation of promoter activity [31] , [32] . To our knowledge , Prdm5 is the first example of a transcriptional modulator able to bind a consensus sequence found inside collagen genes , particularly Col1a1 and Col1a2 . Interestingly , upon Prdm5 loss in osteoblasts , we observe decreased RNA polymerase II occupancy throughout the gene body of the Col1a1 gene , while at the TSS , RNA polymerase II occupancy remains unchanged . This suggests that Prdm5 is sustaining transcription of the Col1a1 gene by affecting polymerase processivity . This hypothesis is further supported by the observed interaction between Prdm5 and RNA polymerase II . The higher enrichment for the processive , “elongating” , form of RNA polymerase II phosphorylated on Serine 2 of its C-terminal domain , argues in favor of Prdm5 directly sustaining RNA polymerase II processivity although further analyses are required to clearly define the underlying mechanism . Since Prdm5 binds predominantly exonic regions of collagen genes , and splicing is known to occur co-transcriptionally [33] , there may be a role for Prdm5 in the coupling of splicing to transcription . However , we failed to detect an altered Col1a1 splice pattern in Prdm5 mutant osteoblasts ( data not shown ) , making this hypothesis less likely . The correlation between Prdm5 binding levels within collagen genes and RNA polymerase II occupancy suggests that Prdm5 in certain contexts may act as a transcriptional activator in contrast to the previously described role of PRDM5 acting predominantly as a transcriptional repressor [4] . Interestingly , we observe major enrichment for Prdm5 target genes to be transcriptionally active , presenting both H3K4me3 and RNA Polymerase II ( Figure 3D ) , suggesting a predominant role for Prdm5 in transcriptional activation in osteoblastic cells . The Prdm5 target repertoire extends also to SLRP genes , including Decorin ( Dcn ) , Fibromodulin ( Fmod ) , Biglycan ( Bgn ) and Epiphycan ( Epc ) . Members of this family are involved in correct type I collagen fibers assembly [15] . Specifically , we found a Prdm5 binding site residing 100 kb upstream from the Dcn TSS . Decorin is the closest gene within a range of 760 kb and the Prdm5 binding site displays the chromatin signature of an enhancer element , suggesting a previously undiscovered role for Prdm5 in transcriptional enhancement or chromatin organization . Decorin has been shown to bind directly collagen I [34] and , in bone tissues , mice lacking Decorin display decreased collagen fiber diameter , although they do not show pronounced skeletal defects [35] . Our data show a marked decrease in fibrillar collagen staining , as evaluated by collagen fibers birefringency , indicating that downregulation of both Collagen I transcripts as well as Decorin might contribute to the skeletal phenotype observed . Of direct relevance , mutations in PRDM5 were recently detected in Brittle Cornea Syndrome [9] . Brittle Cornea Syndrome is a generalized connective tissue disease characterized by impairment of ECM formation and patients develop a number of other symptoms , aside from ocular defects , such as skin hyperelasticity , joint hypermobility and skeletal defects [10] , [36] . While no studies so far have causally linked PRDM5 to this disease , our data demonstrating that Prdm5 regulates the expression of fibrillar collagens are in line with the defects in ECM production and assembly characteristically observed in BCS patients . The distinct expression pattern observed for Prdm5 in developing skeleton prompted us to evaluate a bone phenotype but future studies will be needed to understand if Prdm5LacZ/LacZ mice develop also corneal , skin and joint defects resembling BCS or related diseases such as Ehlers-Danlos syndrome . In this regard , considering the capability of Prdm5 to bind genomic loci encoding multiple collagen molecules , it may be that Prdm5 affects the levels of specific collagen molecules in a context-specific fashion . These features support the role for Prdm5 as an important regulator of extracellular matrix genes transcription during the process of bone formation , and extend the need for studies characterizing this protein in different clinical settings .
To generate the Prdm5LacZ strain , ES cell clone AV0702 from the Sanger Institute Gene Trap project was microinjected into C57BL/6 blastocysts . The integration site of the β-geo cassette was established using long range PCR with primers spanning different regions of intron 2 and a genotyping strategy was devised accordingly . All experiments were performed on mice backcrossed for at least 6 generations into the C57BL/6 strain and comparisons between WT and mutant animals always refer to littermates . All animal experimentation was performed with approval from Danish authorities ( Dyreforsøgstilsynet , protocol number 2006/562-43 ) and the Regierung von Oberbayern ( Government of Upper Bavaria ) . For whole mount X-gal staining , embryos were deskinned ( after E15 ) and fixed in 0 . 25% glutaraldehyde ( Sigma ) . Stainings were performed by incubation in staining solution containing 0 . 02% NP40 , 0 . 01% Sodium Deoxycholic acid , 2 mM MgCl2 , 20 mM Tris-HCl ( pH 7 . 4 ) , 50 µM K-Ferrocyanide , 50 µM K-Ferricyanide , 1 mg/mL X-gal in PBS ( chemicals purchased from Sigma ) . Stained embryos were post-fixed in 4% paraformaldehyde and cleared in increasing concentrations of glycerol in 1% KOH . Images were acquired with a Leica D-Lux 3 on Leica S6D stereoscope . Von Kossa staining was performed by staining dehydrated sections in 1% AgNO3 under UV light , followed by incubation with 5% Sodium thiosulfate . Picrosirius red stainings were performed as described [37] . Images were acquired under polarized light using a BX51 Olympus microscope . In-situ hybridization was performed as previously described [38] and protocols for immunofluorescence stainings are described in Text S1 . Primary human osteoblasts ( kindly provided by Bente Langdahl , Århus University , Denmark ) were isolated from bone biopsies of healthy donors . MC3T3 cells were maintained in Alpha-MEM ( Gibco ) with 10% FBS ( Hyclone ) and 1% penicillin-streptomycin ( Gibco ) . ATDC5 cells were maintained in DMEM∶F12 ( Gibco ) media supplemented with 5% FBS , 10 µg/ml human transferrin ( Roche ) and 30 nM sodium selenite ( Sigma ) . Calvarial osteoblasts were derived as previously described [21] . Differentiation protocols and transfection/transduction techniques are detailed in Text S1 . For co-immunoprecipitation experiments HEK293 cells were transfected with indicated plasmids and , 48 hours after , lysed in ELB buffer ( 150 mM NaCl , 50 mM HEPES , 0 . 1% Igepal ) and incubated with HA-agarose beads ( Sigma ) overnight . After washes , proteins were recovered by boiling beads in SDS Laemmli buffer . For whole cells lysate immunoblotting , cells were harvested and lysed in RIPA buffer and subjected to standard SDS-PAGE . Protocols and antibodies used are detailed in Text S1 . Total RNA was extracted from cell pellets using the RNeasy Plus Mini Kit ( Qiagen ) according to the manufacturer's instructions . cDNA was synthetized using TaqMan Reverse Trancription Reagents ( Applied Biosystems ) . qRT-PCR was performed with the One Step plus Sequence Detection System ( Applied Biosystems ) using Fast SYBR green master mix reagent ( Applied Biosystems ) . Gene expression levels were normalized to the average of at least two housekeeping genes . qPCR primers sequences are listed in Table S3 . For MC3T3 microarray data , RNA was amplified and labeled using TotalPrep RNA Amplification Kit ( Ambion ) and hybridized to MouseWG-6 v2 . 0 Expression BeadChip array ( Illumina ) according to manufacturer's recommendation . Chromatin immunoprecipitation assay ( ChIP ) protocol and antibodies used are detailed in Text S1 . Libraries for sequencing were obtained using the ChIP-seq DNA sample prep kit ( Illumina ) according to manufacturer recommendations and samples were sequenced on a Genome Analyzer II sequencer ( Illumina ) . Primers for ChIP-qPCR experiments are listed in Table S3 . Microarray and ChIP-seq analyses are detailed in Text S1 . E18 . 5 embryos were scanned using a micro CT scanner ( model 1172 , Skyscan , Belgium ) at 50 kV , 200 µA and a 0 . 5 mm aluminium filter . Adult mice at 5 weeks of age were analyzed by pQCT using Stratec XCT Research SA+ ( Stratec Medizintechnik GmbH , Germany ) at the German Mouse Clinic [39] . Analyses details are provided in Text S1 . | Bone provides the essential tensile strength of the skeletal system , constitutes an important storage for minerals , and hosts the initial differentiation stages of the hematopoietic system . In addition , bones are important endocrine organs affecting organismal metabolism . Consequently , many human diseases arise from defects in bone formation or homeostasis . Hence , deciphering the molecular mechanisms underlying bone formation is essential for understanding the basis of bone and extracellular matrix-associated diseases . Here , we provide a detailed characterization of the cellular and molecular functions of the transcription factor Prdm5 during murine bone formation in vivo and find that Prdm5 is expressed in skeletal structures during development and that its loss impacts the ossification process , leading to a decrease in bone mineral density . A genome-wide mapping of Prdm5 binding sites in pre-osteoblastic cells reveals an unprecedented role for a transcription factor in targeting virtually all members of the Collagen and SLRP gene families . Interestingly , Prdm5 predominantly binds exonic regions of collagen genes and associates with RNA Polymerase II to sustain Collagen I transcription . | [
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] | 2012 | Prdm5 Regulates Collagen Gene Transcription by Association with RNA Polymerase II in Developing Bone |
The early mammalian embryo utilizes histone H3 lysine 27 trimethylation ( H3K27me3 ) to maintain essential developmental genes in a repressive chromatin state . As differentiation progresses , H3K27me3 is removed in a distinct fashion to activate lineage specific patterns of developmental gene expression . These rapid changes in early embryonic chromatin environment are thought to be dependent on H3K27 demethylases . We have taken a mouse genetics approach to remove activity of both H3K27 demethylases of the Kdm6 gene family , Utx ( Kdm6a , X-linked gene ) and Jmjd3 ( Kdm6b , autosomal gene ) . Male embryos null for active H3K27 demethylation by the Kdm6 gene family survive to term . At mid-gestation , embryos demonstrate proper patterning and activation of Hox genes . These male embryos retain the Y-chromosome UTX homolog , UTY , which cannot demethylate H3K27me3 due to mutations in catalytic site of the Jumonji-C domain . Embryonic stem ( ES ) cells lacking all enzymatic KDM6 demethylation exhibit a typical decrease in global H3K27me3 levels with differentiation . Retinoic acid differentiations of these ES cells demonstrate loss of H3K27me3 and gain of H3K4me3 to Hox promoters and other transcription factors , and induce expression similar to control cells . A small subset of genes exhibit decreased expression associated with reduction of promoter H3K4me3 and some low-level accumulation of H3K27me3 . Finally , Utx and Jmjd3 mutant mouse embryonic fibroblasts ( MEFs ) demonstrate dramatic loss of H3K27me3 from promoters of several Hox genes and transcription factors . Our results indicate that early embryonic H3K27me3 repression can be alleviated in the absence of active demethylation by the Kdm6 gene family .
The mammalian embryo undergoes drastic changes in cellular specification and gene expression programs throughout development . These changes are facilitated by post-translational modifications to histones , which provide an epigenetic mechanism to coordinate initiation and maintenance of lineage specific transcriptional profiles that can be inherited through multiple cellular divisions . In embryonic stem cells and other pluripotent progenitors , crucial developmental genes are maintained in a quiescent state . A bivalent epigenetic signature defines this large class of genes . These promoters are maintained in a repressive chromatin state through histone H3 lysine 27 trimethylation ( H3K27me3 ) , however the presence of an active chromatin modification ( H3K4me3 ) suggests that these genes are poised for rapid induction as development dictates [1]–[4] . Bivalent promoters have been identified in ES cells , the early embryo , lineage progenitors , and the germline [4]–[15] . With specification or differentiation , these bivalent promoters can be resolved to either a univalent H3K4me3 active state or a H3K27me3 repressed state . In numerous cell culture model systems , histone demethylases are required to remove H3K27me3 to promote gene activation , suggesting that H3K27me3 demethylation is essential in embryonic development [16]–[30] . H3K27me3 demethylases are members of the KDM6 , Jumonji-C ( JmjC ) domain family of histone demethylases . The three KDM6 proteins , JMJD3 ( KDM6B , encoded by an autosomal gene ) , UTX ( KDM6A , X-chromosome ) , and UTY ( Y-chromosome ) , all share a well-conserved JmjC histone demethylation domain [31] . Within this protein family , JMJD3 and UTX demethylate H3K27 tri-methyl and di-methyl residues , whereas human UTY demonstrates greatly reduced catalytic activity [27] , [31]–[34] . Mouse UTY , despite maintaining 82% similarity to the X-chromosome homologue UTX , does not demethylate H3K27me3 due to mutations in the catalytic active site of its JmjC domain [31] . UTX and JMJD3 are individually involved in early embryonic specification events in cell culture [17]–[19] , [22] , [32] , leading to the hypothesis that H3K27me3 demethylases function in early embryonic differentiation events . However , mouse mutagenesis suggests otherwise , as embryos deficient for individual demethylases survive to term . Jmjd3−/− homozygotes exhibit post-natal lethality due to neonatal respiratory deficits [35] . Utx−/y hemizygous males survive to adulthood and exhibit a normal lifespan [31] . In contrast , mutation of the Polycomb Repressive Complex 2 ( PRC2 ) that methylates H3K27 yields precocious expression of early embryonic developmental genes and arrest in gastrulation [36]–[39] . Utx−/− homozygous females and Utx−;Uty− hemizygous males are both mid-gestational lethal with developmental delay and defects in embryonic heart development [31] . Therefore , the mid-gestational cardiovascular lethality that is driven by loss of UTX/UTY is due to demethylase independent function of these proteins . It is not clear if an early embryonic demethylase dependent function exists for the KDM6 family as some redundancy may exist between JMJD3 and UTX . To study the role of the KDM6 family in early embryonic development we generated mutations designed to eliminate all KDM6 H3K27me3 demethylase activity in the developing mouse embryo . Male Utx−/y;Jmjd3−/− embryos devoid of KDM6 H3K27 demethylation survived to term . Mid-gestational Utx−/y;Jmjd3−/− embryos appeared phenotypically normal with characteristic features of embryonic day 10 . 5 ( E10 . 5 ) embryos . We utilized several model systems ( embryoid body , retinoic acid , mouse embryonic fibroblasts ) to demonstrate that H3K27me3 can be removed from the promoters of repressed genes in the absence of active KDM6 demethylation . We conclude that KDM6 demethylases are not essential for early embryonic development and that H3K27me3 repression can be alleviated in the absence of active KDM6 demethylation .
To remove H3K27 demethylase activity in the mouse embryo we generated mutant alleles in both Utx and Jmjd3 . We previously characterized the generation of the Utxfl allele that flanks exon 3 with loxP sites [31] . Cre mediated deletion of exon 3 ( UtxΔ ) created a frameshift in the coding sequence and is null for UTX protein . We now characterize a targeted allele , Jmjd3tm1Mag ( Jmjd3fl ) that integrates loxP sites 5′ to exon 14 and 3′ to exon 20 ( Figure S1A ) . As verified by Southern blotting , PCR genotyping , and RT-PCR ( Figure S1B , S1C , and S1D ) , Cre mediated deletion of this portion of the coding sequence ( Jmjd3Δ ) removed the JmjC catalytic H3K27 demethylase domain ( Figure S1A ) . Similar to published reports , Jmjd3Δ/Δ homozygous pups died at birth with respiratory defects ( Figure S1E ) . Jmjd3Δ/Δ homozygous embryos appeared phenotypically normal at mid-gestation ( Figure S1F ) ; however , several phenotypes manifested late in embryonic development which will be described elsewhere . While Jmjd3Δ/Δ homozygous pups were not observed at weaning , they were readily recovered at E18 . 5 ( Figure 1A ) . We next attempted to derive UtxΔ/y;Jmjd3Δ/Δ embryos whereby all KDM6 H3K27 demethylation is lost , while retaining the demethylase independent function of wild-type UTY . Similar to Utx−/y mutation alone [31] , both UtxΔ/y;Jmjd3+/Δ and UtxΔ/y;Jmjd3Δ/Δ embryos survived to E18 . 5 ( Figure 1B′ and 1B″ ) . However , there was some reduction in observed UtxΔ/y;Jmjd3Δ/Δ embryos relative to expected Mendelian frequencies . Expected genotype frequencies of UtxΔ/y;Jmjd3Δ/Δ embryos were obtained at E14 . 5 , so some redundancy may exist between Utx and Jmjd3 in late embryonic viability . At mid-gestation , all combinations of male Utx and Jmjd3 mutation were largely indistinguishable from controls ( Figure 1D ) . UtxΔ/y;Jmjd3Δ/Δ embryos demonstrated normal features of E10 . 5 embryos , such as normal size and somite numbers ( 35-40 ) , prominent fore and hind-limb buds , and developed branchial arches ( including separation of arch 1 into maxilar and mandibular components , Figure 1D″″ ) . As Utx−/y post-natal lethality is more pronounced on the C57BL6/J ( B6 ) background [31] , we backcrossed UtxΔ and Jmjd3Δ alleles . On a B6 background , UtxΔ/y;Jmjd3Δ/Δ embryos remained viable at both E14 . 5 and E18 . 5 timepoints ( Figure 1B′″ ) . Given that deposition of maternal UTX into the Drosophila embryo contributes to demethylation activity in early development [40] , we tested if deletion of the UTX and JMJD3 maternal pool enhances mouse phenotypes . Utxfl/Δ;Jmjd3fl/Δ;VasaCre female mice ( with oocytes carrying deletion of Utx and Jmjd3 ) were crossed with Utxfl/y;Jmjd3fl/Δ;VasaCre male mice ( with sperm carrying deletion of Utx and Jmjd3 ) and resulting E10 UtxΔ/y;Jmjd3Δ/Δ embryos ( Figure S2A′ ) had completely recombined Utx and Jmjd3 floxed alleles ( Figure S2B ) and phenocopied those derived from Utx+/Δ;Jmjd3+/Δ heterozygous mothers ( Figure 1D″″ ) . Utx and Jmjd3 knockout was confirmed by quantitative RT-PCR ( Figure S3A ) , and at E10 . 5 , UtxΔ/y;Jmjd3Δ/Δ embryos did not exhibit altered Hox expression levels or elevated global levels of H3K27me3 ( Figure S3B , C , D ) . Comparative H3K27me3 immunofluorescence of E10 . 5 Utx+/y;Jmjd3+/Δ and UtxΔ/y;Jmjd3Δ/Δ embryos sectioned onto the same slide revealed similar H3K27me3 levels within heart myocardium ( Figure S3E ) and ISL1 positive motor neurons within the proximal spinal chord ( Figure S3F ) . However , mouse embryonic fibroblasts ( MEFs ) derived from these embryos had minor , yet statistically significant elevations in H3K27me3 levels ( Figure S3G , H ) . Overall , in the absence of KDM6 H3K27 demethylation , embryos can clearly survive through gastrulation and exhibit normal patterning at E10 . 5 . Notably , the phenotypes of UtxΔ/Δ;Jmjd3+/Δ and UtxΔ/Δ;Jmjd3Δ/Δ female embryos were similar to UtxΔ/Δ homozygous mutation alone , as these embryos are all lethal after E10 . 5 ( Figure 1C ) and exhibit similar features of developmental delay ( Figure 1E ) . Additionally , maternal loss of UTX and JMJD3 demethylation had no contribution to phenotypic severity ( Figure S2A″ ) . Taken together , our data indicate that Utx/Uty are epistatic to Jmjd3 , which primarily functions in later developmental stages . We established ES cell differentiation models to study the time-course of H3K27me3 demethylation in the absence of UTX and JMJD3 . We utilized a CAGGCre-ER transgenic system that will induce allelic recombination with the addition of tamoxifen [41] . Following 2 days of tamoxifen treatment ( +TX ) , Utxfl/y;Jmjd3fl/fl;CreER male or Utxfl/fl;Jmjd3fl/fl;CreER female ES lines demonstrated complete deletion of floxed exons and loss of endogenous protein ( Figure S4A and S4B ) . A 140-KD background band is present in Figure S4B and is not lost in Utxfl/y;Jmjd3fl/fl;CreER ES +TX . To ensure that this is not an alternative Utx product , we analyzed its presence in UtxGT1/y ES cells [31] , where any alternative products should be gene trapped . Even though UtxGT1/y ES cells did trap Utx transcripts preventing expression across the JmjC domain ( Figure S4C ) it did not affect the level of background bands ( Figure S4B ) , indicating that these are indeed non-specific bands . Furthermore , western blot with a second , independent UTX antibody produced a clean blot with no UTX band in Utxfl/y;Jmjd3fl/fl;CreER ES +TX samples ( Figure S4D ) . We induced embryoid body ( EB ) differentiation as outlined in Figure 2A . By 4 days in culture , Utxfl/y;Jmjd3fl/fl;CreER +TX EBs looked identical to untreated controls ( Figure 2B ) . Utxfl/fl;Jmjd3fl/fl;CreER female EBs +TX were small and displayed a disorganized outer endodermal layer with cells protruding or sloughing off of the EB ( Figure 2B ) . In contrast to aggregate EB differentiation , hanging drop EB differentiation utilized smaller starting ES cell numbers in a defined drop volume , but still produced similar EB phenotypes ( Figure S5A ) . Embryoid bodies exhibit a characteristic decrease in global H3K27me3 levels as differentiation progresses [32] , [42] . Histones were extracted from EBs to determine if this process occurs in the absence of UTX and JMJD3 demethylation . Relative to global levels of H3K27me3 in ES cells , all EBs , even Utxfl/fl;Jmjd3fl/fl;CreER female EBs +TX demonstrated a reduction in H3K27me3 ( Figure 3C ) . Fluorescent quantitative western blotting verified that both male and female +TX EBs exhibit loss of H3K27me3 levels ( Figure S5B , C ) . Therefore , early EB differentiation events coincide with downregulation of H3K27me3 levels in the absence of all KDM6 . RT-PCR across deleted exons verified that even after 8 days in culture , wild type Utx and Jmjd3 expression was absent , and Uty expression was not diminished in TX treated cells ( Figure 2D ) . Male Utxfl/y;Jmjd3fl/fl;CreER EBs +TX demonstrated normal activation of primitive ectoderm ( Fgf5 expression ) , mesoderm ( Flk1 ) , and endoderm ( Gata6 , Figure 2E ) . In contrast , Utxfl/fl;Jmjd3fl/fl;CreER female EBs +TX initiated differentiation and induced primitive ectoderm ( Fgf5 ) , but failed to specify meso-endoderm ( Brachyury T , illustrated as T ) , mesoderm ( Flk1 ) , and endoderm ( Gata6 , Figure 2E ) . Utxfl/y;Jmjd3fl/fl;CreER ES +TX were plated to derive single cell colonies of mutant clones , and constitutive propagation of this mutant ES line over several weeks did not affect the ability of the cells to differentiate into EBs ( Figure S5D , E ) . Overall , the severe deficits of EB differentiation in Utxfl/fl;Jmjd3fl/fl;CreER +TX cells does not recapitulate the mild phenotypes of UtxΔ/Δ;Jmjd3Δ/Δ female embryos ( Figure 1E″ ) . To study the role of KDM6 in H3K27me3 demethylation , we utilized Retinoic acid ( +RA ) differentiation of ES cells . As Utxfl/fl;Jmjd3fl/fl;CreER EB +TX appeared capable of initiating ectoderm specification , RA differentiation towards a neuro-ectodermal lineage can be studied in this cellular model whereby all active demethylation by KMD6 members has been removed . We utilized a 2 day RA differentiation timecourse outlined in Figure 3A . H3K27me3 ChIP was performed on 4 individual replicates of WT ES ( Utxfl/fl;Jmjd3fl/fl;CreER ES −TX ) , KO ES ( Utxfl/fl;Jmjd3fl/fl;CreER ES +TX ) , WT RA ( Utxfl/fl;Jmjd3fl/fl;CreER RA −TX ) , and KO RA ( Utxfl/fl;Jmjd3fl/fl;CreER RA +TX ) . Two of the 4 replicates of each group were pooled together and the resulting 2 replicates of each group were subject to high throughput sequencing . H3K4me3 ChIP-seq was also performed on 2 replicates of WT RA and KO RA . The model-based analysis for ChIP-seq ( MACS ) algorithm identified enrichment peaks of H3K27me3 and H3K4me3 in each group , and edgeR statistical analysis software identified genes undergoing H3K27me3 demethylation in WT ( WT ES vs . WT RA ) and KO ( KO ES vs . KO RA ) RA differentiation . Overall , 1044 WT ES promoters ( Transcription Start Site: TSS +/−1 KB ) and 1141 KO ES promoters demonstrated H3K27me3 peaks . Of these promoters , 945 and 1055 ( WT and KO respectively ) also had a RA H3K4me3 peak , signifying that the majority of these promoters are bivalent . EdgeR identified 54 WT promoters ( from 50 unique genes , some having alternative promoters ) and 109 KO promoters ( 103 genes ) that demonstrated significant loss of H3K27me3 with RA differentiation ( Figure 3B and Table S1 ) with many genes overlapping in both datasets . Many Hox genes lost H3K27me3 in both WT and KO RA differentiation . Tracks of H3K27me3 and H3K4me3 ChIP-seq were uploaded into the UCSC genome browser . With RA differentiation , the proximal Hoxa cluster ( Figure 3C ) from Hoxa1 through Hoxa6 demonstrated widespread loss of H3K27me3 in ES to RA differentiation of both WT and KO cells . This shift in histone profile correlated with large peaks of H3K4me3 at proximal Hoxa promoters , demonstrating gene activation events . Similar large-scale loss of H3K27me3 occurs from the proximal Hoxb ( Hoxb1-Hoxb6 ) , Hoxc ( Hoxc4-Hoxc6 ) , and Hoxd ( Hoxd1-Hoxd4 ) clusters ( Figure S6A , B , C ) . In addition to Hox genes , many other transcription factors such as Foxa1 , Gata3 , Meis2 , and Nr2f2 demonstrated loss of promoter H3K27me3 in KO RA treatment ( Figure 4A and Table S1 ) . H3K27me3 ChIP-qPCR confirmed the loss of H3K27me3 in the absence of KDM6 demethylation ( Figure 4B ) . Notably , all genes tested exhibited similar WT and KO loss of H3K27me3 with RA differentiation . Only Hoxb1 demonstrated a slight , significant increase in H3K27me3 for KO RA compared to WT RA , but overall Hoxb1 did exhibit a tremendous decrease in H3K27me3 in KO RA compared to KO ES . Furthermore , RT-PCR expression analysis confirmed that the genes demonstrating loss of H3K27me3 efficiently induced transcriptional activation in RA KO cells ( Figure 4C ) . Utxfl/fl;Jmjd3fl/fl;CreER ES +TX were plated to derive single cell colonies of mutant clones , and constitutive propagation of this mutant ES line over several weeks did not affect the ability of the cells to activate transcription ( Figure S5F ) . H3K27 demethylases physically associate with the MLL complex family of H3K4 methyl-transferases . Two members of this complex ( ASH2L and RBBP5 ) were expressed at normal levels in KO cells ( Figure S7A ) . One alternative explanation for loss of H3K27me3 in the absence of demethylation is that the PRC2 H3K27 methylation complex is down-regulated in differentiated cells or displaced from targeted promoters in a demethylase independent manner . While the EZH2 H3K27 methyl-transferase maintained high expression in RA differentiated cells ( Figure S7B ) , the protein is displaced from promoters experiencing H3K27me3 loss in the absence of KDM6 demethylation ( ) . In summary , repressed genes can demonstrate loss of H3K27me3 and initiate expression in the absence of KDM6 . MACs analysis of H3K4me3 ChIP-seq of WT RA and KO RA cells identified enrichment peaks at 19 , 140 and 19 , 367 respective promoters ( TSS +/−1 KB ) . EdgeR comparison of WT RA to KO RA identified 161 promoters ( 147 genes ) that exhibited significant ( FDR<0 . 05 ) reduction in KO H3K4me3 ( Figure 5B , Table S2 ) . The majority of these were small fold changes across a wide range in overall peak intensity . Of these 161 promoters , only 27 ( 26 genes ) had an ES WT or KO H3K27me3 peak , so the majority of these genes are not regulated by H3K27 methylation . A few genes that exhibited KO H3K4me3 reductions and had a H3K27me3 peak are illustrated in the UCSC genome browser image of Figure 5A . RT-PCR confirmed that several genes with reduced KO H3K4me3 demonstrated reduced expression ( Crabp2 , Pax6 , Wnt6 , Ccnd2 , Figure 5C ) . Several genes that had been denoted as experiencing normal H3K27me3 loss and gene activation in KO RA samples ( Hoxb1 , Foxa1 ) experienced normal KO RA H3K4me3 up-regulation relative to the ES cell state ( Figure 5D ) . However , ChIP-qPCR did confirm genes identified in ChIP-seq to be deficient in RA KO H3K4me3 ( Crabp2 , Wnt6 , Figure 5D ) . We next examined whether KO RA H3K4me3 affected genes can have associated increases in H3K27me3 . ChIP-qPCR of Crabp2 and Wnt6 demonstrated increased KO RA H3K27me3 to ES comparable levels ( Figure 5E ) . To better analyze the distribution of H3K27me3 and K3K4me3 we performed a meta-analysis examining the overall distribution of these histone modifications across all promoters with a corresponding MACS peak . These meta analyses ( Figure 6A–G ) were plotted with 95% confidence intervals centered on the mean normalized read counts . ES cells and RA differentiated cells both had a broad K27me3 distribution across promoters with a drop-off near the TSS ( Figure 6A , B ) . H3K4me3 enrichment peaked downstream of the TSS ( Figure 6C ) , and there was very close overlap between WT and KO profiles of both H3K27me3 and H3K4me3 . Genes with significant reductions in H3K27me3 after RA differentiation , had visible differences in relative H3K27me3 sequence reads between ES and RA samples for both WT and KO ( Figure 6D ) . In comparing WT RA to KO RA , there was very close overlap near the TSS ( +/−1 KB ) ; however , upstream of the TSS ( −2 KB to −1 KB ) KO RA exhibited a significant enrichment in the mean H3K27me3 levels per gene . Comparison of WT ES to KO ES across this same region also demonstrated significantly increased H3K27me3 levels ( Figure 6D ) . Although H3K27me3 was elevated for these KO promoters , there was a complete overlap in H3K4me3 distribution ( Figure 6E ) , further supporting data that this gene category was efficiently activating transcription in KO RA cells ( Figure 4C ) . Thus , with RA differentiation , KO cells can experience dramatic reductions in H3K27me3 at specific promoters , and although there is minor H3K27me3 accumulation upstream of the TSS , transcription is not compromised . Meta-analysis of promoters exhibiting H3K4me3 reductions in KO RA cells verified that this dataset was significantly deficient in H3K4me3 downstream of the TSS ( Figure 6F ) . The H3K27me3 profile of this dataset revealed that these genes were not subject to dramatic K3K27me3 loss in WT ES to WT RA differentiation ( Figure 6G ) . However , there was a small , but significant H3K27me3 elevation in RA KO relative to RA WT from TSS +0 . 5 KB to +1 . 5 KB . Because identifying a small subset of data from a graph for statistical analysis amounts to cherry-picking and is not without bias , we performed a genome-wide comparison of WT RA to KO RA H3K27me3 levels with edgeR . Genome-wide cross-comparison of WT RA vs . KO RA did not identify any promoters ( TSS +/−1 KB ) exhibiting a significant increase in KO H3K27me3 . We also compared all KO RA H3K27me3 MACS peaks ( peak center +/−0 . 5 KB ) , including those not found at TSSs , for normalized sequence read enrichment over WT RA . This analysis identified 74 KO RA H3K27me3 MACS peaks ( out of 4504 total MACS peaks ) that were enriched in sequence reads over WT ( Table S3 ) . These peaks resided in varying proximity to 64 unique genes; however , only 7 of these genes demonstrated compromised transcription based on a reduction in TSS H3K4me3 levels ( Table S3 ) . Overall , with KDM6 loss of demethylation , a small subset of genes have minor reductions in H3K4me3 and reduced transcription , and a fraction of these experience elevated H3K27me3 . To examine loss of H3K27me3 repression in a differentiated primary tissue , we utilized mouse embryonic fibroblasts ( MEFs ) . Primary MEFs were cultured from E13 . 5 Utxfl/fl;Jmjd3fl/fl;CreER embryos and treated with tamoxifen as indicated in Figure 7A . Relative to ES cells , a panel of representative Hox genes ( Hoxa3 , Hoxc4 , Hoxa13 and Hoxd13 ) demonstrated elevated expression levels in MEFs ( Figure S8A ) . Following tamoxifen treatment , the growth of Utxfl/fl;Jmjd3fl/fl;CreER MEFs slowed dramatically , while MEFs without Cre continued to proliferate . Regardless , Utxfl/fl;Jmjd3fl/fl;CreER MEFs +TX largely did not experience reductions in Hox expression relative to untreated controls ( Figure 7B ) . Only the most distal genes within the Hox A and D clusters ( Hoxa13 and Hoxd13 ) demonstrated a slight but significant reduction in expression with loss of UTX and JMJD3 . Hox H3K27 methylation in Utxfl/fl;Jmjd3fl/fl;CreER MEFs +TX matched their expression profile as the few distal genes that demonstrated mild expression deficiencies ( Hoxa13 and Hoxd13 ) also exhibited a significant increase in H3K27me3 ( Figure 7C ) . Primary MEFs were also cultured from E13 . 5 UtxΔ/y;Jmjd3Δ/Δ embryos to assay function in both establishment and maintenance of a H3K27 demethylated state . Similar to transient TX induced KDM6 loss , UtxΔ/y;Jmjd3Δ/Δ MEFs had significantly reduced expression of more distal Hox genes ( Hoxa13 , Hoxd13 , Figure 7D ) relative to Utx+/y;Jmjd3+/Δ controls . H3K27me3 ChIP of UtxΔ/y;Jmjd3Δ/Δ MEFs only revealed some accumulation on Hoxa13 while other Hox genes were unaffected ( Figure 7E ) . Notably , several Hox genes demonstrated significant reduction in H3K27me3 levels relative to ES cells ( Hoxa3 , Hoxc4 , Hoxa6 , Hoxd12 ) in both control and UtxΔ/y;Jmjd3Δ/Δ MEFs ( Figure 7E ) . Some proximal Hox genes actually demonstrated an increase in KO MEF Hox expression ( Hoxa3 , Hoxc4 and Hoxa6 ) , but this may be an artifact of the decreased growth rate of these cells as the H3K27me3 profile of these genes is unaffected . Furthermore , several other transcription factors ( Wnt5a , Zeb2 , Smarcd3 ) also exhibited near-complete loss of H3K27me3 even though all KDM6 demethylases had been removed throughout embryonic development . Notably these genes experience loss of localized H3K27me3 even though total H3K27me3 protein levels ( Figure S3G , H ) and EZH2 levels ( Figure S8B , C ) were elevated ( H3K4me3 levels were not affected , Figure S8C ) . Therefore , H3K27me3 repressed genes can establish promoter states cleared of this repressive chromatin in the absence of KDM6 demethylases .
A tremendous dichotomy exists in the field of H3K27 demethylases . H3K27me3 results in gene repression throughout the early embryo , yet enzymes that catalyze its removal are individually not essential for male embryonic viability . These findings are unexpected given that numerous genes crucial for early embryonic gastrulation events [43]–[52] experience H3K27me3 de-repression during development [4] , [53] , [54] including but not limited to GATA , TGF-β/BMP , WNT , FGF , and T-box transcription factor networks . Cell culture model systems have implicated that UTX and JMJD3 function in activation of several of these pathways [17]–[19] , [22] , [32] . We now demonstrate UtxΔ/y;Jmjd3Δ/Δ embryos devoid of all KDM6 demethylation remarkably survive to term and appear phenotypically normal at mid-gestation . UtxΔ/Δ;Jmjd3Δ/Δ embryos ( lacking the demethylase independent function of UTY ) survive through gastrulation and albeit smaller in size , can develop E10 . 5 features . Therefore , KDM6 is not crucial for alleviating the H3K27me3 repression of genes needed for early embryonic gastrulation events . Even within individual cellular and organismal models , several studies have produced conflicting reports . UTX mediated H3K27 demethylation is reported to function in cellular reprogramming and germ cell development [55] , however surviving Utx mutant male mice are fertile [31] , [56] . UTX is reported to be essential for appropriate expression of germ layer markers in male ES cell differentiation [19] , [56] , yet differentiation deficits can largely be rescued by UTY or a catalytically inactive form of UTX [32] , [57] . UTX is essential for efficient Hox H3K27me3 demethylation and gene activation [27] , [29] , [30] , [57] , [58] , yet Utx null male ES cells can largely remove Hox H3K27me3 and demonstrate normal transcriptional activation [56] . The discrepancies in these reports may be accounted for by differences in cell type , genetic background , intrinsic growth differences in ES cell clones , differential JMJD3 redundancy , or differential UTY expression [as has been reported [31] , [32] , [56] , [59] . We take advantage of mutant inducible alleles to enable comparison of control and knockout of the entire KDM6 family within the same ES cell clone with identical growth rate and genetic background . Similar to the normal appearance of mid-gestation UtxΔ/y;Jmjd3Δ/Δ embryos , KDM6 mutant male ES cells could differentiate normally into all EB germ layers . Mutant female ES cells null for any KDM6 demethylation demonstrated dramatic reduction in both global levels of H3K27me3 ( with EB differentiation ) and local levels of H3K27me3 from proximal Hox clusters and from promoters of other transcription factors ( with RA differentiation ) . While there was a low level significant H3K27me3 accumulation upstream of these promoters in RA KO cells , these genes were largely cleared of H3K27me3 and experienced normal transcriptional activation , similar to findings in Utx male knockout studies alone [56] . Utx and Jmjd3 mutant MEFs demonstrated mild H3K27me3 accumulation and reduced expression only within the most distal regions of the Hox cluster . Similarly , Zebrafish UTX loss of function produces modest deficiencies in distal Hox expression [27] . EZH2 protein levels were mildly upregulated in Kdm6 mutant MEFs and may account for altered distal Hox gene regulation . Relative to ES cells , UtxΔ/y;Jmjd3Δ/Δ MEFs exhibited substantial reductions in promoter H3K27me3 of several Hox genes and developmental transcription factors . Thus in the absence of KDM6 H3K27 demethylation , H3K27me3 loss can be both initiated and maintained in developmental situations . Our study raises intriguing questions regarding early embryonic removal of H3K27me3 . Thus far , only UTX and JMJD3 have demonstrated the ability to demethylate H3K27me3 . It is unlikely that another JmjC protein can demethylate H3K27me3 . The KDM7 family including JHDM1D and PHF8 can demethylate both H3K9 and H3K27 dimethyl residues , but does not demethylate trimethyl residues [60] , [61] . The PHF8 active site cannot sterically accommodate trimethyl residues [62] . In contrast , UTX positions H3K27me3 farther from the active site to properly position the larger residue modifications [63] . Furthermore , UTX amino acid Y1135 bonds with a methyl group of H3K27me3 and is essential for demethylation [31] , [63] . This residue is not conserved in the KDM7 family . A tyrosine at this position is conserved for members of the KDM4 family of H3K9 and H3K36 trimethyl demethylases . However , this family of proteins has a catalytic core buried within a deep pocket , and residues downstream of H3K27 do not encode enough flexibility to fit this modification in the active site [64] . It is possible that a novel family of proteins may actively demethylate H3K27me3 utilizing distinct chemistry . Alternatively , H3K27me3 in the early embryo may be replaced by passive mechanisms , as histones can be turned over multiple times within each cell cycle [65] . PRC complexes remain bound to chromatin during DNA replication and associate with the replication fork in dividing cells to direct methylation of H3K27me3 on newly incorporated daughter strand histones [66]–[68] . Thus , in a passive model for H3K27me3 replacement , displacement of the PRC2 complex during replication allows for incorporation of un-methylated H3K27 . In a similar fashion , DNA methylation in the mouse pre-implantation embryo and germline may be removed via passive replication dependent mechanisms via displacement of DNA methyl-transferase from sites of replication [69] , [70] . The role of the KDM6 family in development is not clear . Passive H3K27me3 removal may dominate in rapidly dividing cells such as in the early embryo . Active H3K27me3 demethylation may prove more essential for rapid response to specific environmental or developmental cues , particularly in more static cellular populations . Alternatively , rather than facilitating drastic gene induction , H3K27 demethylases may act to fine-tune transcriptional activity to promote accurate robust temporal and spatial patterns of gene expression . Accordingly , UTY associates with a wide array of chromatin and transcriptional machinery that may promote proper gene expression output [31] . In this sense , KDM6 members may encode a reader function to recruit transcriptional complexes to repressed genes and/or to displace PRC2 without the need for active demethylation . Point mutagenesis in the UTX and JMJD3 catalytic domains further emphasizes demethylase independent roles for the KDM6 family [32] , [71] , [72] . Going forward , genetic experiments analyzing crosstalk between chromatin modifying factors and structure/function analysis within the mammalian embryo are required to define specific function of the KDM6 family in embryonic development .
All mouse experimental procedures were approved by the University of North Carolina Institutional Animal Care and Use Committee . The Utxfl allele is described [31] . The Jmjd3tm1Mag ( Jmjd3fl ) allele was derived by targeting E14 ES cells . The Jmjd3 targeting construct was generated by BAC recombineering to insert a LoxP site in intron 13 and a FRT-Neomycin-FRT-LoxP cassette in intron 20 of Jmjd3 . After successful targeting , the Neomycin cassette was removed by electroporation of a pCAGG-FLP construct . The resulting Jmjd3+/fl ES cells were injected into C57BL/6J blastocysts . Resulting chimeras were mated to CD1 females to assess germline transmission , and were maintained on either a mixed CD1 background or were backcrossed to C57BL/6J . UtxΔ and Jmjd3Δ alleles were generated by crossing floxed alleles to the VasaCre transgene that restricts Cre activity to the germline [73] . These progeny were then mated to propagate the UtxΔ and Jmjd3Δ alleles . To generate higher proportions of desired genotypes in the Utx Jmjd3 genetic interaction cross , Utx+/Δ;Jmjd3+/Δ female mice were mated with either Utxfl/y;Jmjd3fl/Δ;VasaCre or Utx+/y;Jmjd3fl/Δ;VasaCre males . Embryos were PCR genotyped from yolk sac samples for Utx or Jmjd3 and were sexed by a PCR genotyping scheme to distinguish Utx from Uty . All primer sequences are listed in Table S4 . Utxfl/fl;Jmjd3fl/fl;CreER and Utxfl/y;Jmjd3fl/fl;CreER ES cell lines were generated from E3 . 5 blastocysts in crosses utilizing CAGGCre-ER transgenic mouse line [41] . ES cells were cultured as described [36] . ES cells were split off of feeder MEFs and treated with 1 µg/mL 4-hydroxytamoxifen ( 4-OHT ) for 3 days and were allowed to recover for 1 day . In EB differentiation experiments , 106 ES cells were cultured in 10 mL of ES culture media lacking LIF on agarose coated Petri dishes . Hanging drop EBs were set up with 25 µL drops of ES cells at a concentration of 20 , 000 cells per mL . In RA differentiation experiments , ES cells were plated following tamoxifen recovery , and the next day were cultured without LIF in 1 µM Retinoic Acid . E13 . 5 MEFs were generated as described [31] . MEFs were passaged 1x and treated with 0 . 5 µM 4-OHT for 2 days , then were passaged and cultured for an additional 3 days . RNA was isolated with Trizol and cDNA was synthesized with Multiscribe reverse transcriptase . Gene expression was analyzed by qRT-PCR ( Bio-Rad SsoFast EvaGreen , CFX96 real time system ) . All RT-PCR was normalized to Gapdh expression and graphed relative to control samples . All primer sequences are listed in Table S4 . Nuclear lysates , histone extracts , and western blotting was performed as described [31] utilizing anti-RBBP5 ( Bethyl Labs A300-109A , 1∶5000 ) , anti-ASH2L ( Bethyl Labs A300-107A , 1∶3000 ) , anti-H3K27me3 ( Millipore 07-449 , 1∶2000 ) , anti-H3 ( Abcam ab1791 , 1∶10 , 000 ) , anti-GAPDH ( Sigma G9545 , 1∶10000 ) , anti-UTX [29] , or anti-UTX ( Bethyl Labs A302-374A , 1∶4000 ) antibodies . ChIP was performed as described [74] and graphed relative to % of total ChIP input DNA for each immunoprecipitation . 5×106 cells were sonicated by a Branson Sonifier at 15% duty cycle ( 0 . 7 s on 0 . 3 s off ) . For some experiments , chromatin was sonicated in a chilled water bath by a Bioruptor sonifier on high setting for 30 s with 60 s rest . Rabbit IgG ( Sigma , I5006 ) , anti-H3K27me3 ( Abcam ab6002 , 2 . 5 µl ) , anti-H3K4me3 ( Abcam ab8580 , 2 µl ) , or EZH2 ( Cell Signaling 5246 , 3 µl ) antibodies were used for ChIP . All ChIP primers are listed in Table S4 . Immunofluorescence experiments were performed as described [31] with anti H3K27me3 ( Cell Signaling 9733S , 1∶500 ) or ISL1 ( DSHB 39 . 4D5-S , 1∶200 ) ChIP DNA and Input DNA were ligated to Truseq adapters as described [75] . Samples were multiplexed and sequenced with the HiSeq 2000 Analyzer ( UNC High Throughput Sequencing Facility ) . The quality of the sequences reads was evaluated with FastQC ( http://www . bioinformatics . babraham . ac . uk/projects/fastqc/ ) . Reads were then mapped to the B6 genome using Bowtie ( http://bowtie-bio . sourceforge . net/index . shtml ) . Significant enrichment ( peaks ) were called using MACS ( http://liulab . dfci . harvard . edu/MACS/index . html ) , with the input ChIP-seq datasets for the background model , on pooled replicates . Peak lists were filtered using an FDR cutoff of 0 . 05 . We then identified peaks that were within 1 Kb of transcriptional start sites ( TSSs ) , as annotated in the UCSC genome browser for mm9 . Read counts for a particular locus were normalized to the total number of sequence reads generated for each sample . We used edgeR ( http://www . bioconductor . org/packages/2 . 12/bioc/html/edgeR . html ) to determine if there was a bias in the number of H3K27me3 or H3K4me3 reads at MACS positive promoters between various samples . Metaplots were drawn using custom Python scripts and R , and t-tests were performed using the average read count per gene within the ranges specified in the text . ChIP-seq datasets were submitted to GEO ( accession GSE58391: http://www . ncbi . nlm . nih . gov/geo/query/acc . cgi ? acc=GSE58391 ) . | H3K27me3 represses developmental genes at initial embryonic stages . The KDM6 family , comprised of UTX and JMJD3 , are the only known proteins that demethylate H3K27me3 and they are hypothesized to catalyze the rapid removal of repressive chromatin in early mammalian development . However , we report that male embryos carrying mutations in both Utx and Jmjd3 survive to term and appear phenotypically normal at mid-gestation . We utilize several cell culture models to demonstrate that H3K27me3 is lost from repressed promoters in the absence of active KDM6 demethylation . Our data indicate that KDM6 H3K27me3 demethylation is not essential in the early embryo and that H3K27me3 loss from developmental genes occurs via novel mechanisms . | [
"Abstract",
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] | 2014 | KDM6 Demethylase Independent Loss of Histone H3 Lysine 27 Trimethylation during Early Embryonic Development |
In non-motile fungi , sexual reproduction relies on strong morphogenetic changes in response to pheromone signaling . We report here on a systematic screen for morphological abnormalities of the mating process in fission yeast Schizosaccharomyces pombe . We derived a homothallic ( self-fertile ) collection of viable deletions , which , upon visual screening , revealed a plethora of phenotypes affecting all stages of the mating process , including cell polarization , cell fusion and sporulation . Cell fusion relies on the formation of the fusion focus , an aster-like F-actin structure that is marked by strong local accumulation of the myosin V Myo52 , which concentrates secretion at the fusion site . A secondary screen for fusion-defective mutants identified the myosin V Myo51-associated coiled-coil proteins Rng8 and Rng9 as critical for the coalescence of the fusion focus . Indeed , rng8Δ and rng9Δ mutant cells exhibit multiple stable dots at the cell-cell contact site , instead of the single focus observed in wildtype . Rng8 and Rng9 accumulate on the fusion focus , dependent on Myo51 and tropomyosin Cdc8 . A tropomyosin mutant allele , which compromises Rng8/9 localization but not actin binding , similarly leads to multiple stable dots instead of a single focus . By contrast , myo51 deletion does not strongly affect fusion focus coalescence . We propose that focusing of the actin filaments in the fusion aster primarily relies on Rng8/9-dependent cross-linking of tropomyosin-actin filaments .
Sexual reproduction is carried out by most eukaryotes and permits the alternation of haploid and diploid life stages . It relies on the formation of differentiated haploid cell types that are able to meet and fuse to form a zygote , which eventually returns to the haploid state through meiosis . Many of these events rely on morphological changes , especially in organisms without cell motility . Yeast model systems have been used over decades to uncover basic principles of cell organization , yet no systematic screening of their sexual reproduction process has been performed . Here , we have used the fission yeast Schizosaccharomyces pombe to systematically screen for viable gene deletions causing a morphological abnormality in the sexual reproduction process . We anticipated this screen would shed light on the processes of cell polarization , cell-cell fusion and sporulation . All natural S . pombe isolates live as haploid cells , and many , such as the h90 lab strain , are self-fertile ( homothallic ) [1 , 2] . These cells , which can be of two distinct mating types , P and M , regularly switch mating type by recombination of the silent mating cassette into the active site after cell division , thus resulting in a near genetically identical population that can reproduce sexually [3] . Sexual differentiation is initiated by nitrogen starvation , which leads to the expression of pheromones and cognate receptor on the two cell types . Pheromone signaling involves a GPCR-MAPK signal transduction cascade , which in turn reinforces sexual differentiation and initiates the morphological program of mating [4] . Upon sensing low pheromone levels , cells initially polarize secretion towards a cortical patch assembled around the active form of the small GTPase Cdc42 [5] . This patch dynamically forms at various cortical locations and disassembles over time , but cells do not grow . Pheromone secretion and sensing are thought to occur at the patch , which is stabilized through unknown molecular mechanisms upon higher local pheromone perception , such that two neighboring cells become locked together when their patches meet [6] . Paired cells then grow towards each other to form a pre-zygote , with cell wall still separating the two partner cells . To achieve cell fusion , the cell wall needs to be digested at the zone of cell-cell contact to allow plasma membrane fusion . This relies on the fusion focus , a dedicated actin aster nucleated by the formin-family protein Fus1 , which promotes the convergence on a small cortical zone of secretory vesicles transported by type V myosin motors [7–9] . In particular , these motors transport glucanases , enzymes that hydrolyze the bonds linking the cell wall glucan polymer [7] . Over the course of the fusion process , the fusion focus forms from an initially broad distribution at the cell projection tip , and stabilizes into a single focus in opposing locations in the two partner cells . This stabilization stems from a positive feedback between concentration of pheromone signal at the secretion zone and local enrichment of the pheromone signal transduction machinery , which immobilizes the fusion focus through unknown mechanism [10] . In turn , spatial stabilization permits the focused delivery of glucanases for local cell wall digestion . Formation of the fusion focus is likely to require several actin-binding proteins , in addition to Fus1 . In particular , profilin Cdc3 and tropomyosin Cdc8 are enriched on the structure and necessary for cell-cell fusion [11 , 12] . Type V myosins also localize on the fusion focus and contribute to its focalization [7 , 13] . There are two such myosins in fission yeast [14 , 15]: Myo52 is the main cargo transporter for both cell polarization and cell fusion [7 , 16–18] , and moves processively on tropomyosin-decorated actin filaments [19]; Myo51 is more unusual , as many of its functions are independent of its cargo-binding tail [7 , 20 , 21] . In addition , Myo51 is a single-headed motor protein , and both in vivo and in vitro experiments have shown that only motor ensembles were capable of processive movement [21 , 22] . In vivo , a dimer of two coiled-coil proteins , Rng8 and Rng9 , associates with Myo51 , regulates its localization during mitotic growth , and was proposed to contribute to Myo51 processivity by forming higher-order oligomers in vivo [21] . In vitro , the Rng8/9-Myo51 complex was also shown to bind tropomyosin-decorated F-actin independently of the motor domain , thus forming a bivalent F-actin-binding complex cross-linking and sliding actin-tropomyosin filaments relative to one another [22] . Despite these recent advances , how these motors or other actin-binding proteins function to focus an actin aster is not established . Upon local cell wall digestion , plasma membranes fuse . Though multi-pass transmembrane proteins such as Prm1 have been suggested to participate in this process in several fungal species , the mechanism remains completely elusive [23–25] . As the fusion pore then expands , the neck connecting the now fused cells is remodeled to create an elongated zygote in which the two parental haploid nuclei fuse . The diploid nucleus then enters meiosis to return the genome to its haploid state , forming four meiotic products , each of which is packaged in a stress-resistant spore . Sporulation is a very morphologically demanding process in which new plasma membrane and new wall is laid down , initiated from the spindle pole associated with each of the four genomic meiotic products [26] . Previous forward-genetic screens have identified a number of sterile , fusion-defective and sporulation-deficient mutants , and a targeted genome-wide screen for sporulation-defective deletion strains was published in the course of this work [27] . However , there has not been any systematic reverse-genetic screen of the mating process . Here , we present the results of a visual screen for morphological abnormalities during the mating process in fission yeast . Our screen led us to identify the Rng8/9 dimer and its interaction with tropomyosin as critical for the formation of the actin fusion focus . We propose that cross-linking of tropomyosin-actin filaments serves to focalize filaments in the fusion focus .
To systematically screen the collection of viable deletions for mating defects , we converted the available heterothallic h+ deletion library [28] to a homothallic h90 collection by applying a modified version of the SpSGA method [29] . We first integrated a nourseothricin resistance cassette ( natMX ) 6kb away from the expressed mat1 mating-type cassette , between the genes mag2 and rpt6 , in an otherwise wildtype homothallic h90 strain . Because the genomic region located between the expressed mat1 locus and silent mat loci represents a genetic distance of only 1cM [30] , the h90 trait and natMX largely co-segregate , allowing for selection for the h90 trait at the population level . We then robotically crossed this h90-natMX strain to all kanMX-marked deletion strains of the h+ collection in 384-well plate format . Mating was induced on solid medium with low nitrogen for 4 days at 25°C . Vegetative haploid cells that had not mated and diploid cells that had not sporulated were killed by incubation at 42°C for 4 days [29] . We note that diploid killing was efficient , as azygotic tetrads , which stem from the sporulation of diploid cells rather than zygotes formed by cell-cell fusion , were observed in only 76/2270 strains upon the visual screening described below . Spore germination was triggered by replica plating on solid rich medium ( YE ) . A second replication step to solid medium containing both G418 and nourseothricin selected for homothallic h90 deletion-carrying strains . Finally , strains were saved at -80°C in YE 25% glycerol ( Fig 1A ) . From 2270 deletion strains of the h+ deletion collection , we recovered 2134 h90 derivatives . The 136 that we could not recover are likely to be either sterile ( for example ste4Δ , ste6Δ , ste7Δ , ste20Δ , ras1Δ , wee1Δ ) or too sick to have efficiently crossed , and thus did not give spore progeny in the scheme above . We did not investigate those further at present . To find mutants affecting the mating process , we visually screened the h90 mutants after a 2-day incubation on solid medium lacking nitrogen ( MSL-N ) . The visual screen was performed in replica by two independent investigators with deletion names undisclosed , in order to eliminate any bias . Remarkably , out of the 2134 screened mutants , 543 mutant showed a visible phenotype during the mating process ( Fig 1B ) . Ten distinct phenotypes were recorded: these included early mating polarization defects , such as ( i ) the presence of cells extending growth projections not meeting a partner cell , ( ii ) aberrant shmoo shapes , ( iii ) placement , or ( iv ) length , or ( v ) the presence of abnormally large unmated cells; ( vi ) fusion defects , in which paired cells were observed with cell wall at the contact site; and post-fusion phenotypes , such as ( vii ) sporulation defects , in which asci had abnormal spore numbers or shapes , ( viii ) abnormally large asci , or ( ix ) promiscuous cells , in which mutants appeared to mate ( or attempt to mate ) with multiple partners . Finally , we recorded ( x ) the presence of dead cells in the mating assay , which may be caused by cell lysis upon deregulated fusion attempts [10] . In addition to these ten classes , we assigned mutants in which cell pairs were rare and/or individual cells did not appear to be arrested as small cells to a ( xi ) low mating efficiency class . We also scored for ( xii ) multiseptation , in which cells showed multiple septa , though this phenotype may not be starvation-specific . For each of these categories , the severity of the phenotype was gauged on a scale from 1 to 10 . We note that some deletions were labeled with several distinct phenotypes . A summary of these categories , with the number of identified mutants , is represented in Fig 1C . Representative images for some phenotypic classes are shown in Fig 1D . The full description of each phenotypic class , as well as the complete table of mutants with their recorded phenotypes , is available as supplementary material ( S1 and S2 Tables ) . We focused our analysis on the fusion defects class of 273 mutants affecting the cell-cell fusion process ( S3 Table ) . We compared these mutants with a list of genes involved in cell-cell fusion compiled from the literature ( Fig 2A ) . As expected , we identified fus1Δ and prm1Δ as fusion defective [9 , 23] . Deletions of myo51 , myo52 and cfr1 have also been shown to lead to fusion defects [7 , 13 , 31] , but these strains were absent from the screened library , as were of course deletion of the essential tropomyosin Cdc8 and profilin Cdc3 , also required for fusion [11 , 12] . We also did not identify dni1Δ and dni2Δ , likely because these genes are required for fusion only at elevated temperatures [32] . This suggests our screen identified all of the identifiable , previously known genes involved in cell fusion . Comparison of our list of fusion-defective mutants also identified several homologues to S . cerevisiae cell fusion factors ( Fig 2B; see Discussion ) . Amongst all deletions with an arbitrary score of 3 or above , we performed a GO Slim analysis of the gene products , which revealed that 12 . 5% are components of the cytoskeleton , an enrichment relative to the 7 . 4% within the whole genome . The enrichment of cytoskeletal components in fusion-defective mutants is interesting because fusion relies on a dedicated aster-like actin structure , the fusion focus [7 , 10] . To further explore novel fusion-defective mutants affecting the cytoskeleton , we first used publically available data ( pombase . org ) to discard from the list of cytoskeleton components mutants implicated in chromatin remodeling , spore formation , or with a known localization in the nucleus . This left us with 8 fusion-defective , cytoskeleton-related mutants ( Fig 2C ) , amongst which was the pheromone-dependent formin Fus1 [9] . All 8 strains were verified by PCR for correct deletion of the corresponding gene . The others include the actin capping protein Acp2 , previously involved in actin cytoskeleton organization during mitotic growth [33 , 34] , the centractin family actin like protein Arp1 , part of the dynactin complex previously implicated in dynein-dependent nuclear movement during meiotic prophase ( horsetail movement; [35] ) , the actin monomer-binding protein twinfilin twf1 involved in regulation of polarized growth [36] , and the BAR-domain protein Hob3 , which was previously known to regulate cytokinesis in part through regulation of Cdc42 GTPase [37] . A recently described regulator of the type V myosin Myo51 , Rng8 , was also selected [21] . We also included Rng9 , the Rng8 binding partner [21] , in the subsequent analysis although it was not identified in the screen . To monitor the fusion deficiency of the selected mutants , we used two distinct assays . First , we reproduced the screen conditions by placing cells on MSL-N plates for 24h and counting the percentage of non-fused pairs after transfer to a microscope slide ( Fig 2C , left ) . In this three-dimensional assay , multiple layers of cells are able to mate with each other . We also used our previously established protocol to quantify fusion efficiency after 24 hours on MSL-N agarose pads , where cells are trapped in a two-dimensional monolayer for the duration of the sexual reproduction ( Fig 2C , middle ) [38] . While only fus1Δ was fully fusion-defective , all mutants showed some fusion defect in at least one of the two assays . We note that , with one exception , the fusion defect was more severe in the three-dimensional assay . This may be due to differences in pheromone distribution or oxygen availability between the two conditions . We also investigated the fusion efficiency on pads of the selected mutants in a heterothallic background with a fus1Δ partner , which is fully fusion-deficient . This more stringent test assesses the capacity of the mutant to overcome the fusion deficiency of its partner cell . In this set-up , again all mutants were more fusion-defective than wildtype cells , with 4 mutants highly fusion defective ( fusion efficiency < 20% ) : rng8Δ , acp2Δ , twf1Δ and slm1Δ ( Fig 2C , right ) . Deletion of rng9 yielded a similar phenotype as rng8Δ . All five deletion strains displayed defects in fusion focus organization , as labeled with Myo52-tdTomato ( Fig 2D ) : acp2Δ and slm1Δ displayed aberrant localization of the fusion focus , with the focus often detached from the cell projection tip in acp2Δ and out of alignment in slm1Δ . rng8Δ , rng9Δ and twf1Δ showed wider Myo52-tdTomato signals ( see Fig 3A and 3B for quantifications ) , suggestive of a defect in fusion focus focalization . Fluorescence tagging of each of the five genes at endogenous locus revealed that all accumulated at the fusion site , albeit with different localization patterns . Acp2 and Twf1 appeared to primarily decorate actin patches as previously shown for Acp2 during vegetative growth [34] . Slm1 was highly concentrated at the fusion focus , but was also decorating the cortex of the entire projection tip . By contrast , Rng8 and Rng9 accumulated in a concentrated location at the fusion site ( Fig 2D ) , which coincided with the Myo52-labelled fusion focus ( S1 Fig ) . In summary , we successfully identified several new genes affecting the fusion process in fission yeast . As all five deletion strains above readily reveal a defect in fusion focus organization , and all encoded proteins localize at the fusion site , we conclude that the screen was highly successful in detecting genes directly involved in the regulation of cell fusion . By extension , this also suggests that many other fusion-defective deletion strains will also reveal interesting new cell fusion phenotypes . Because Rng8 and Rng9 localize to the fusion focus and appear to be required for its focalization , we extended our analysis of their function for the dynamics of the fusion focus during the fusion process , using high-temporal resolution time-lapse microscopy . In rng8Δ , rng9Δ and double rng8Δ rng9Δ mutants mated with wildtype cells , the major fusion focus components Myo52-tdTomato and formin Fus1-sfGFP occupied a zone about twice as wide as in wildtype cells , when measured on sum Z-projections , though the total signal detected at the cell-cell contact site was unchanged ( Fig 3A and 3B ) . Time-lapse imaging of Myo52-tdTomato in single focal planes further showed that rng8Δ , rng9Δ and double rng8Δ rng9Δ mutants display multiple stable Myo52 dots at the shmoo tip ( Fig 3C and 3D ) . Whereas two dots are occasionally observed in wildtype cells as the fusion focus forms when the signal matures from a broad crescent-like localization to a single dot ( S2 Fig ) , we never observed several stable dots in wildtype cells . By contrast , in rng8/9 mutants , most cells exhibited 2 , 3 or more dots that were spatially stable over > 1 minute at the cell cortex ( Fig 3C and 3D ) . This phenotype , as well as fusion efficiency ( S3 Fig ) , were indistinguishable in single and double mutants , consistent with Rng8 and Rng9 forming an obligate dimer [21 , 22] . Our further analysis was thus conducted only on the rgn8Δ single mutant . We conclude that the Rng8/9 dimer is required for the formation of a single fusion focus structure . Stabilization of the fusion focus relies on accumulation of the pheromone signaling machinery on the structure [10] . In wildtype cells , both M-factor transporter Mam1 and components of the pheromone transduction pathway , including the MAP2K Byr1 , strongly accumulate on the fusion focus . In rng8Δ cells , these components were present at the fusion site , though over a wider region , similar to our description of Fus1 and Myo52 above ( Fig 3E ) . Because of weaker signal intensity , we were unable to confidently determine whether Byr1 and Mam1 also systematically form several distinct stable dots , or have a more continuous , broad localization , though in some instances , several dots of Mam1 could be clearly distinguished ( Fig 3E ) . This suggests each dot becomes stabilized through the normal pheromone signaling-dependent pathway [10] . This is consistent with the idea that Rng8 is required not for the immobilization of the fusion focus , but for the coalescence of the actin aster to a single structure prior to stabilization . The fusion focus serves for the local release of cell wall digestive enzymes [7] . In wildtype cells , the glucanase Exg3-sfGFP can be clearly observed at the fusion focus . In rng8Δ cells , Exg3 could also be detected at the fusion site ( Fig 3E ) , but only in about half of the cells and often over a wider zone , consistent with the idea that this glucanase is secreted over a broader region upon fusion focus coalescence defects . This defect is consistent with the lower efficiency of rng8Δ cells in digesting their cell wall , especially when mated with fus1Δ partners ( Fig 2D ) . We conclude that the Rng8/9 dimer is critical for the coalescence of the acto-myosin fusion focus into a single aster-like structure , required for local release of cell wall digestive enzymes . Previous work has implicated the Rng8/9 dimer in the regulation of the single-headed myosin Myo51 . Indeed , Rng8/9 associates with Myo51 in vivo and in vitro and promotes Myo51 cluster formation , Myo51 is not detected on actin cables and only very weakly at the cytokinetic ring in rng8Δ and rng9Δ cells , and these and myo51Δ mutants have similar defects in contractile ring assembly [21 , 22] . One proposed model is that Rng8/9 forms an integral part of the Myo51 motor for most or all of its cellular functions and is strictly required for its processivity [21] . We thus examined in detail the phenotype and localization of Myo51 during cell fusion . Similar to the situation during cytokinesis [21] , Myo51 localization at the fusion focus was strongly reduced , though not completely abolished , in rng8Δ and rng9Δ cells ( Fig 4A and 4B ) . In addition , myo51Δ cells are partly fusion defective and strongly fusion incompetent when mated with fus1Δ partners [7] , similar to rng8Δ and rng9Δ cells . However , in contrast to rng8Δ and rng9Δ cells , the Myo52-labelled fusion focus was not significantly broader in myo51Δ than in wildtype cells ( Fig 4C–4E ) . In addition , the vast majority of myo51Δ cells formed a single Myo52 dot , with only about 30% forming ≥2 dots ( Fig 4F ) . While this is significantly different from the wildtype situation , where about 15% of cells are observed with ≥2 dots , this does not recapitulate the rng8/9Δ phenotype where about 95% of cells form ≥2 dots . These data indicate that the fusion focus clustering defect of rng8/9 mutants is not solely due to a loss of Myo51 function . In agreement with this , rng8Δ and myo51Δ showed additive phenotypes in fusion efficiency , with the double mutant significantly less fusion-competent than either single mutant . Expectedly , rng8Δ was also additive with myo52Δ ( Fig 4G ) . Similar results were observed with the rng9Δ myo51Δ double mutant ( S4 Fig ) . Rng8 localization was also significantly broader , though not weaker , at the fusion site in myo51Δ ( Fig 4H–4J ) , suggesting that one role of Myo51 myosin is to concentrate the Rng8/9 dimer in the fusion focus . In conclusion , the myosin V Myo51 and the Rng8/9 dimer each have independent function during fusion and mutually contribute to concentrate the other on the fusion focus . Recent in vitro work has shown that the Rng8/9-Myo51 complex binds tropomyosin-decorated actin filaments independently of the Myo51 motor domain [22] . This binding was proposed to anchor the complex to tropomyosin-decorated filaments to favor their transport along other actin filaments bound by the motor domain . This prompted us to examine the role of tropomyosin Cdc8 in actin focus formation . Cdc8 was previously shown to be necessary for cell fusion and to localize at the fusion site [11] . Cdc8-GFP , expressed under the inducible nmt41 promoter [39] , indeed accumulated at the fusion site in both wildtype and rng8Δ cells to similar levels , though it occupied a zone about twice as wide in rng8Δ cells , as described above for other fusion focus components ( Fig 5A–5C ) . We also confirmed that cells of the temperature-sensitive cdc8-382 mutant [40] , though able to form pairs , were highly fusion-deficient at the semi-permissive temperature of 33°C ( Fig 5D ) . These data confirm an important role of tropomyosin in cell fusion . We then used a collection of point mutations in predicted surface-exposed Cdc8 residues conserved in fungi [41 , 42] to screen for non-conditional mutants that would hinder cell fusion when homothallic . This identified two alleles each carrying a single point mutation , cdc8R121A and cdc8E104A , with reduced fusion efficiency ( Fig 5D ) . The phenotype of cdc8R121A was very severe , with only about 10% successful fusion . The cdc8R121A mutation causes significant actin cytoskeleton organization defects during vegetative growth , including weak actin cables , dispersed patches and defective cytokinetic ring , and reduces the affinity of tropomyosin for actin about 30-fold in vitro [42] . During mating , both Myo52-tdTomato and Myo51-3YFP failed to concentrate at a single focal point at the fusion site in this strain , though they were enriched at the zone of cell-cell contact , strongly suggesting that the global organization of the actin cytoskeleton is affected and the fusion focus does not form . We conclude that the fusion defect observed in cdc8R121A cells is due to strongly reduced actin-tropomyosin interaction . The second fusion-defective allele , cdc8E104A , displayed a much milder fusion problem , similar to that observed in rng8Δ ( Fig 5D ) . This allele was shown to have some very mild cell polarization defects during vegetative growth , but does not affect actin binding [42] . Remarkably , the localizations of Myo52 and Myo51 during mating strongly resembled those observed in rng8Δ cells: most cdc8E104A cells exhibited 2 or 3 Myo52 dots that were spatially stable at the cell-cell contact site ( Fig 5E–5G ) , though we note the phenotype was not quite as severe as that of rng8Δ ( see Fig 3D ) . In addition , Myo51 was present in significantly reduced amounts ( Fig 5H ) . The similarity of the cdc8E104A and rng8Δ phenotypes suggests that cdc8E104A affects Rng8/9 function . Indeed , Rng8 was strongly delocalized from all actin structures: it could not be detected on actin cables and only weakly on the cytokinetic ring during vegetative growth , as well as on the fusion focus during mating ( Fig 5I and 5J ) . As observed in wildtype background , we note that this localization was not further weakened by deletion of Myo51 ( Fig 5I and 5J ) . These results suggest that the fusion defects observed in cdc8E104A stems from a loss of binding with the Rng8/9 dimer . Two pieces of data suggest that interaction of the Rng8/9 dimer with both tropomyosin and myosin V Myo51 contribute to focalization of the fusion focus . First , construction of a double mutant cdc8E104A myo51Δ exhibited more severe de-clustered focus phenotype than either single mutant ( Fig 5F ) , identical to rng8Δ ( see Fig 3D ) . Second , epistasis analysis showed that the triple cdc8E104A myo51Δ rng8Δ mutant was not more fusion-defective than the double myo51Δ rng8Δ mutant , suggesting the cdc8E104A mutation does not affect other components than Rng8 and Myo51 ( Fig 5K ) . By contrast both cdc8E104A rng8Δ and cdc8E104A myo51Δ double mutants were significantly more fusion-defective than the corresponding single mutants ( Fig 5K , compare to Figs 4G and 5D ) , suggesting the cdc8 mutant weakens the interaction of both Rng8/9 and Myo51 with actin filaments sufficiently to abolish the function of the complex . We conclude that Rng8/9 acts through both tropomyosin and myosin V Myo51 to organize the fusion focus .
Systematic gene deletion collections in both budding and fission yeasts have enabled important advances in the understanding of fundamental cellular processes [28 , 43 , 44] . To facilitate the discovery of genes with function in the sexual reproduction process , we derived a self-fertile ( homothallic ) version of the collection of viable deletions in fission yeast . Because both partner cells carry the same deletion , this approach is more sensitive in identifying genes important for the mating process , whose presence in one of the two partners may be sufficient for functionality . This allowed the discovery of >200 genes involved in cell-cell fusion , a process previously noted for its robustness [4] . This approach also ensured that diploid zygotes were homozygote mutant , leading to the discovery of sporulation-deficient mutants . A similar strategy , using a homothallic derivative of the deletion collection to screen for sporulation-defective mutants through absence of iodine staining , which specifically stains spores , was published during the course of our work [27] . Our list of sporulation-defective mutants overlaps with that described in this work , but is more extensive ( S4 and S5 Tables ) , likely because visual screening permitted identification of more subtle phenotypes , for instance of abnormal spore number . Besides these two large phenotypic classes , a large number of deletions strains were identified with defect in cell polarization , and categorized in several phenotypic classes . Cell polarization in response to pheromone , leading to cell-cell pairing , is a complex process involving an exploratory patch of active Cdc42 GTPase that serves as site of pheromone release and signaling [5 , 6] . We note that genes involved in cell polarization during vegetative growth , though present in the deletion collection , were not prominent the shmoo shape defects class , suggesting that regulatory mechanisms of polarized growth are in part distinct , as also previously suggested [45] . Mutants with aberrantly placed shmoos , absent from cell sides , or formed in absence of a partner may be caused by a defect in the Cdc42 exploratory polarization mechanism , or may reflect an alteration in pheromone signaling or perception , which modulates exploratory polarization [5 , 6] . Our screen also identified a large number of mutants with a decreased mating efficiency or forming multiple septa . These two categories were not further investigated and we cannot exclude that some of these mutants have general defects in cell growth and division rather than specifically in the sexual lifecycle . Finally , one unexpected and very interesting category of mutants is the promiscuous class . While wildtype cells always mate with a unique partner , yielding diploid zygotes , these mutants showed multiple cell projections to several partner . While time-lapse microscopy will be required to ascertain whether cells shmoo in all direction at the same time or sequentially , and whether they fuse or only attempt to with several partners , we confirmed that deletion of the master regulators of meiosis mei2 and mei3 [46–48] show successive fusion with multiple partners . This phenotype was so extensive in the screen that asci were not readily identified and thus the absence of spores was missed . The mere existence of this category of mutants indicates the existence of regulatory mechanisms that arrest mating in zygotes and thus ensure the alternation of haploid and diploid generations ( A . Vjestica , LM and SGM , manuscript in preparation ) . In summary , our visual screening of a homothallic derivative of the collection of viable gene deletions exposes a host of novel gene functions that begin revealing new biology and provides a rich basis for future research . This homothallic deletion collection also represents a novel resource that can be further screened for more specific phenotypes . We focused on the class of fusion-defective mutants , which represents the largest well-defined phenotypic class . The identified mutants may affect any of the multiple steps required to achieve cell-cell fusion , from signaling , cell-cell adhesion , cytoskeletal organization , cell wall digestion to plasma membrane fusion . We note that no other deletion than fus1Δ showed a fully penetrant phenotype . This may be due to three main reasons . First , there is significant redundancy between components and/or pathways , as also noted in the study of cell-cell fusion in budding yeast and Drosophila myoblasts [4] . For instance , neither Myo51 nor Myo52 is essential for fusion , yet double deletions fully abrogate it [7] . Second , some components may be re-used several times during the mating process , such that their deletion blocks mating at an earlier stage than fusion . This is for instance the case of the pheromone-MAPK cascade , essential for sexual differentiation , but which re-localizes to the fusion focus to signal fusion commitment [10] . Finally , fusion may rely on components otherwise essential for viability , which could not be identified in this screen . For instance , fusion requires a dedicated actin structure , the fusion focus , which , besides its formin nucleator Fus1 , is built from components also necessary during cell division [7 , 11 , 12] . However , this screen provides a very large entry-point into the fusion process . It is interesting that the homologues of several genes or pathways required for cell fusion in S . cerevisiae were identified as fusion-defective in our screen ( Fig 2B ) . These include in particular the BAR adaptor Hob3 , which binds the Cdc42 guanine nucleotide exchange factor Gef1 and helps promotes GTP exchange on Cdc42 [37] , and Gef1 itself . The S . cerevisiae homologue of Hob3 , Rvs161p , regulates fusion through interaction with Fus2p [49] . While Fus2p has no identifiable sequence homolog in S . pombe , it directly binds active Cdc42p , and both Cdc42p and its guanine exchange factor Cdc24p are required for fusion [50 , 51] . The Cdc42 GEF Bud3p also contributes to cell fusion in S . cerevisiae [52 , 53] . We also found that the PAK kinase Shk2 is required for fusion , arguing that a common set of proteins around Cdc42 regulates cell fusion in both organisms . Similarly , the deletions of Tea1 and Tea4 , important regulators of cell polarity delivered to cell poles by microtubules during mitotic growth [54–56] , are present in the fusion-defective class . In S . cerevisiae , the homologue of Tea1 , Kel1p , promotes cell fusion through regulation of Fus2p localization [57 , 58] . Finally , we identified one of the M-factor-coding genes mfm1 in the fusion-defective class . This is consistent with the notion that fusion commitment in S . pombe requires a sharply graded pheromone signal [10] , and similar to findings S . cerevisiae where repression of mfa1 , coding for a-factor , or mutation of its transporter lead to cell fusion defects [59 , 60] . Finally , as noted previously , formin activities ( Fus1 in S . pombe and likely Bni1 in S . cerevisiae ) and the multi-pass transmembrane protein Prm1 are required for fusion in both species [4 , 9 , 23 , 24 , 61] . Together , these findings suggest that the process of cell-cell fusion is likely to be highly conserved between these two distant ascomycete species . The phenotype of rng8Δ and rng9Δ is distinct from previously reported phenotypes: the fusion focus is partly de-clustered , yet each dot is spatially stable and appears to accumulate pheromone-signaling components . Formation of the fusion focus in wildtype cells initiates from a broad distribution of Myo52 at the cell projection cortex , which coalesces into a single focus [7] . Intermediate multi-dots stages resembling the rng8Δ phenotype can be transiently observed , but the small clusters are not maintained over time and immobilization happens only for a single structure . We suggest that Rng8/9 normally acts before fusion focus stabilization to ensure the formation of a singular actin aster . The outcome of the de-clustered focus is that cell wall digestive enzymes are not released at a single location . In the wildtype situation , cell wall hydrolytic enzymes ( glucanases ) are released specifically at the fusion focus , while glucan synthases are broadly localized , yielding a probable gradient of cell wall hydrolytic activity [7] . When the fusion focus is de-clustered , this gradient likely cannot be well established . Consistently , the glucanase Exg3 was difficult to detect . The consequence is that in crosses to fus1Δ , rng8Δ cells are largely unable to overcome the homogeneous release of hydrolytic enzymes by their partner , and thus fusion fails . By contrast , when mated to wildtype or itself , rng8Δ cells often succeed in cell wall digestion , likely because there is one dominant focus . The Rng8/Rng9 complex has emerged as an important regulator of the type V myosin Myo51 [21 , 22] . Myo51 is an unusual myosin V: in vitro work has shown it is largely monomeric , has a low duty-ratio and is unable to move continuously on actin as a single molecule [22 , 62] . Similarly , dim punctae of Myo51 ( thought to represent dimers ) do not move processively on actin cables in vivo [21] . However , assemblies of several Myo51 molecules display processive movements both in vivo and in vitro . Two hypotheses have been proposed for the role of Rng8/9 . Rng8 and Rng9 co-purify as oligomers from cells and these proteins convert non-processive Myo51 punctae into processive larger assemblies in vivo . Thus a first model is that Rng8/9 converts Myo51 into a processive motor through cluster formation [21] . Recent in vitro work has shown that Rng8/9 also provides an ATP-independent binding site for the Myo51-Rng8/9 complex to bind tropomyosin-decorated actin , independently of the Myo51 motor domain . This immobilizes the complex when bound to a single filament , but promotes filament bundling or sliding , depending on assay conditions , when two distinct filaments are connected [22] . Thus , a second hypothesis is that Rng8/9 anchors Myo51 to a neighboring actin filament , in a tropomyosin-dependent manner , to favor filament bundling and/or sliding . Our data lend strong in vivo support for the importance of the Rng8/9-tropomyosin interaction in the assembly of the fusion focus . Tropomyosin was known to be critical for cell fusion [11] , and we have confirmed , through use of the cdc8R121A allele , which displays 30-fold lower actin binding [42] , that tropomyosin-actin binding is indeed essential . We now show that rng8 deletion and cdc8E104A , a tropomyosin point mutant that strongly compromises Rng8 localization to actin structures but does not affect actin binding ( our data and [42] ) , yield almost indistinguishable phenotypes in fusion focus de-clustering . These data predict that the highly conserved region around tropomyosin E104 [42] serves as specific binding site for Rng8/9 , though this will need to be confirmed through in vitro reconstitution studies . We note that the additive phenotype of the rng8Δ cdc8E104A double mutant suggests that this region on tropomyosin also plays a role in Myo51 binding . Because Rng8 localization to actin structures was also strongly compromised in cdc8E104A vegetative cells , it will be interesting to investigate the possible cytokinetic defects and epistasis of cdc8E104A in comparison to rng8Δ , to generalize these findings to all actin structures . By contrast , the interaction between Rng8/9 and Myo51 appears less critical for fusion focus organization . Myo51 likely plays a small role , but its deletion shows only very weak de-clustering phenotype and is strongly additive to rng8Δ in terms of fusion efficiency . In addition , the observation that Rng8 fails to be enriched on the fusion focus in myo51Δ cells suggests the prime function of the Myo51-Rng8/9 interaction during fusion may be to concentrate Rng8/9 at the fusion site . We conclude that Rng8/9 binding to tropomyosin-decorated actin is critical to focus the actin fusion structure . The fusion focus may be in some ways considered an analogous actin-based structure to the microtubule-based mitotic spindle pole . Spindle pole focusing strongly depends on minus-end directed motor proteins [63] , but also of non-motor microtubule-associated proteins . In particular , the non-motor spindle matrix protein NuMA has activities very analogous to those of Rng8/9 in spindle pole focusing: NuMA forms dimers or oligomers , and binds both the pole-directed dynein complex and microtubules directly . Thus , it may focus spindle poles through two possible scenarios: by forming a dynein-NuMA complex that provides two MT binding sites to cross-link and slide MTs passed each other or through NuMA oligomers that directly cross-link MTs [64–66] . Our data suggests that the Rng8/9 complex functions in the fusion focus much like NuMA at the spindle pole . With membrane-proximal Fus1 nucleating actin filaments that are decorated by tropomyosin , Rng8/9-tropomyosin interaction may promote filament-filament interactions and focus formation in two complementary ways . Formation of a complex with Myo51 may allow concentration of Rng8/9 and sliding of filaments ( as proposed in [22] ) towards the membrane-proximal barbed end . This would contribute to the coalescence of actin filaments to a single focal point , though our data suggest this contribution is modest . Alternatively , and likely more prominently , Rng8/9 may form oligomeric assemblies that crosslink tropomyosin-decorated actin filaments in absence of motor . As oligomers were not detected in vitro [22] , their formation may be indirect or require specific post-translational modification . Cross-linking of filaments may selectively stabilize these filaments , thus leading to progressive structure focalization . The Rng8/9-dependent mode of fusion focus clustering may represent one of several mechanisms . Future study of the here-identified collection of deletion promises to reveal fundamental mechanisms of cytoskeletal organization and cell fusion .
Strains used in this study are listed in S6 Table . For assessing exponentially growing cells , cells were grown in Edinburgh minimal medium ( EMM ) or minimal sporulation media with nitrogen ( MSL+N ) supplemented with amino acids as required . For assessing mating cells , liquid or agar minimal sporulation media without nitrogen ( MSL-N ) were used [38 , 67] . All live-cell imaging was performed on MSL-N agarose pads [38] . Mating assays were performed as in [5 , 7 , 38] . Briefly , pre-cultures of cells were grown at 25°C to OD600 = 0 . 4–1 in MSL + N ( for heterothallic crosses , cells were mixed in equal parts ) , diluted and grown for 18–20 h to OD600 = 0 . 4–0 . 6 at 30°C in MSL + N . Cells were pelleted by centrifugation and washed three times in MSL-N and mounted onto MSL-N 2% agarose pads and sealed with VALAP . Pads were then incubated for either 1 h at 25°C before imaging in overnight movies or overnight at 18°C before imaging . Fusion efficiency was measured as in [7 , 10] . The haploid S . pombe deletion mutant library was purchased from Bioneer ( South Korea ) . The deletion strains are marked with a G418-resistance kanMX cassette in an h+ strain background ( h+ ade6-M210 ura4-D18 leu1-32 ) . To examine phenotypic changes during mating , an h90 library was created by crossing the collection of deleted mutants with a homothallic strain carrying a Nat-resistance natMX cassette at the h90 locus ( YSM2945 h90 mag2-natMX-rpt6 ) . This strain was made by a PCR based approach using primers osm1023 ( 5’-caacaagagctgcgttgactgctttttttttgctatataatccagatgcagattattttaaaatactaatccaaatatCGGATCCCCGGGTTAATTAA ) and osm1024 ( 5’ttaatgggttgtttgtcagtcgttgatttagtcctgaatatacataaggaaaagttaatccagggtggagtcgactctGAATTCGAGCTCGTTTAAAC- ) to amplify the natMX cassette from pFA6a-NatMX6 . This product was designed to recombine into the intergenic region between the mag2 and rpt6 open reading frames at the mat locus ( homology is underlined ) . Before performing the phenotypic analysis , the collection was amplified and frozen down at -80°C . For amplification , the deletion strains were inoculated in 200μl MSL+N in 384-well plates with the help of a Tecan robot and incubated at 30°C with shaking for 2 days . Pre-cultures of h90 mag2-natMX-rpt6 cells were grown at 25°C to OD600 = 0 . 4–1 in MSL+N , diluted and grown for 18–20 h to OD600 = 0 . 4 at 30°C in MSL+N . 25μl of each deletion strain cultures were mixed with 25μl of the h90 strain in a 384-well plate and 2μl of the mixture were spotted on EMM-ALU plates containing low nitrogen amounts ( 24mM NH4Cl ) with the help of a Tecan robot . Plates were incubated at 25°C for 4 days to allow mating and sporulation , and then shifted to 42°C for 4 days to kill un-sporulated diploid and un-mated haploid cells . The EMM-ALU plates were replica plated on YE with the help of a Singer robot and incubated for 2 days at 30°C to allow spore germination and colony growth . YE plates were replica plated on YE plates containing both G418 and nourseothricin ( 250μg/ml G418 , 100μg/ml Nat ) and incubated for 2 days at 30°C to select for h90 deletion strains . To freeze down the collection , mutants were inoculated from YE-G418/Nat plates in 200μl YE in 96-well plates with the help of a Tecan and a Singer robot . Cells were grown at 30°C for 2 days and 100μl YE containing 50% glycerol was added with the help of a Tecan robot before freezing down the strains at -80°C . For phenotypic analysis of h90 deletion strains , the homothallic mutants were first spotted on YE and growth at 25°C for 2 days , and then replica plated on MSL-N and incubated at 25°C for 2 days . Mutants were visually screened on a small table-top Leica microscope with 40x magnification for mating defects . Practically , cells were picked up with a toothpick and resuspended in 2μl MSL-N on a glass slide and coated with a coverslip . The analysis was done in duplicate by 2 independent investigators and phenotypic defects were classified and scored between 1 and 10 . Mutants with score ≥ 5 were screened a second time to confirm the phenotypic defect . We note that diploid killing during h90 collection generation was largely efficient as we observed a few azygotic tetrads ( issued from the sporulation of a diploid , rather than a freshly formed zygote ) in only 76 strains through the entire visual screen . GO enrichments were performed using GO term finder ( http://go . princeton . edu/cgi-bin/GOTermFinder The spinning-disk microscope system , previously described [16] was used throughout the study . Optical slices were acquired every 0 . 6 μm , and all panels show maximum projections , unless otherwise indicated . For zone size measurements , fusion efficiency and number of Myo52 dots at fusion site ( Figs 2D , 3B , 3D , 4B , 4C , 4F , 4I , 5C , 5D , 5F , 5G and 5K ) , the plugin ObjectJ in ImageJ ( National Institutes of Health ) was used . Fluorescence intensities of Myo51-GFP , Rng8-GFPand nmt41-cdc8-GFP in Figs 3B , 4D , 4G , 5B , 5I and 5J were measured in ImageJ using a manually drawn area around the shmoo tip in sum projections of seven slices over 4-μm total depth . Background fluorescence was measured and subtracted from the original measurements . Kymographs in Figs 3C and 5H were constructed in ImageJ version 1 . 47 ( National Institutes of Health ) by drawing a 3-pixel-wide line at the cell tip . Fig were assembled with Adobe Photoshop CS5 and Adobe Illustrator CS5 . All error bars are standard deviations . All experiments were done a minimum of three independent times , and statistical analysis was done across repeats of the same experiment . | Sexual reproduction is a common process in most eukaryotic species . In those with non-motile gametes , such as most fungi , important morphological changes underlie this process . We report on a systematic screen for mutants with morphological abnormalities during sexual reproduction in the fission yeast , Schizosaccharomyces pombe , a widely used model for the study of fundamental cellular processes . The results of this screen expose a host of novel gene functions required for cell polarization , cell-cell fusion and production of progeny through sporulation . We then focused on the large class of genes required for the fusion of the two gametes into a single zygote . Cell fusion requires the assembly of an intracellular actin cytoskeleton-based structure , named the fusion focus , which concentrates the delivery of enzymes for cell wall digestion to a precise site . We show that fusion focus coalescence into a single aster requires the action of the Rng8/9 dimer . Our work indicates that cross-linking of tropomyosin-decorated actin filaments by the Rng8/9 dimer is critical to actin filament focusing . | [
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"... | 2017 | A systematic screen for morphological abnormalities during fission yeast sexual reproduction identifies a mechanism of actin aster formation for cell fusion |
In storing and transmitting epigenetic information , organisms must balance the need to maintain information about past conditions with the capacity to respond to information in their current and future environments . Some of this information is encoded by DNA methylation , which can be transmitted with variable fidelity from parent to daughter strand . High fidelity confers strong pattern matching between the strands of individual DNA molecules and thus pattern stability over rounds of DNA replication; lower fidelity confers reduced pattern matching , and thus greater flexibility . Here , we present a new conceptual framework , Ratio of Concordance Preference ( RCP ) , that uses double-stranded methylation data to quantify the flexibility and stability of the system that gave rise to a given set of patterns . We find that differentiated mammalian cells operate with high DNA methylation stability , consistent with earlier reports . Stem cells in culture and in embryos , in contrast , operate with reduced , albeit significant , methylation stability . We conclude that preference for concordant DNA methylation is a consistent mode of information transfer , and thus provides epigenetic stability across cell divisions , even in stem cells and those undergoing developmental transitions . Broader application of our RCP framework will permit comparison of epigenetic-information systems across cells , developmental stages , and organisms whose methylation machineries differ substantially or are not yet well understood .
Organismal development is characterized by a shift from the phenotypic flexibility of embryonic cells to the canalized identities of differentiated cells . To achieve stable gene-regulatory states in terminally differentiated cells , organisms ranging from Archaea to humans use a variety of epigenetic mechanisms , including DNA methylation . Perturbation of the state of DNA methylation at various loci in differentiated cells is associated with several human cancers [1–3] . In turn , restoring epigenetic flexibility of some loci has proven challenging during efforts to create induced pluripotent stem ( iPS ) cells [4] . Together , these findings highlight the importance of shifting ratios of epigenetic flexibility and stability in establishing cellular identity . There exists an extensive literature documenting changes in single-locus and genome-wide methylation frequencies at various stages of development [5 , 6] . Most genomic regions in primordial germ cells ( PGCs ) , for example , are known to undergo dramatic and rapid shifts in DNA methylation frequency [7] . It is now clear that mammalian stem cells can utilize active demethylation [8] , highlighting the potential for both gain and loss of cytosine methylation to impact the overall methylation frequency and , perhaps , stability of a given genomic region during development . High concordance of methylation in differentiated cells , with matching states for parent and daughter DNA strands at individual CpG/CpG dyads , is considered to be a hallmark of conservative epigenetic processes [9–13] . For earlier stages of development , however , questions remain regarding the extent of concordance . For example , do methylation patterns in dividing embryonic stem cells arise entirely by random placement of methyl groups , or is concordance favored to some degree ? Recent work has begun to address these questions [7 , 14–18] . Shipony et al . [16] analyzed DNA methylation patterns in populations of cultured cells established from single founder cells . Under this approach , the degree of stability was inferred from the extent of congruence among single-stranded patterns collected from cultured descendant cells . The observation of substantial pattern diversity among cells separated by many rounds of division led Shipony et al . [16] to conclude that the bulk of methylation in human embryonic stem ( ES ) and induced pluripotent stem ( iPS ) cells arises through “dynamic”—that is , non-conservative—DNA methylation processes rather than through the “static”—that is , conservative—processes that were emphasized in earlier studies [10 , 11 , 19] . Using data collected by hairpin-bisulfite PCR [13] , which yields double-stranded DNA methylation patterns , other studies suggested that dynamic processes contribute substantially to DNA methylation in cultured mouse ES cells , but perhaps not to the exclusion of the conservative processes that dominate at many loci in adult differentiated cells [7 , 14 , 15 , 17 , 18] . To fully characterize the balance between conservative and non-conservative methylation processes , it is necessary to quantify the extent to which the arrangement of methylation in a given set of patterns deviates from the null assumption of random placement . To assess and visualize such deviations , we here introduce a new metric , Ratio of Concordance Preference ( RCP ) , which utilizes double-stranded methylation data . Here , as previously , we use the term double-stranded DNA methylation pattern to refer to the overall pattern of methylation on both top and bottom strands of an individual double-stranded DNA molecule . Double-stranded patterns provide information on the extent of matching between methylation states on parent and daughter strands , which are separated by exactly one round of DNA replication . RCP requires no assumptions about the enzymatic mechanisms of methylation and demethylation , and so enables comparison across diverse species and developmental stages . Jeltsch and Jurkowska [20] have emphasized the balance of methylating and demethylating processes—rather than the propagation of specific methylation patterns—as the primary determinant of the nature of the patterns present in a given cellular population at a given time . In this framework , RCP can be thought of as a metric for quantifying the extent to which the set of patterns produced by a given system of methylating and demethylating processes deviates from the set of patterns expected if methyl groups are placed entirely at random . In parameterizing RCP , we use the term “conservative” , in lieu of “static” as used previously [16] , to describe processes that preferentially establish concordant as opposed to discordant methylation states . We consider non-conservative processes , described previously as “dynamic” [16] , as having one of two forms: “random” processes , which add or remove methyl groups with equal preference for concordance and for discordance , and “dispersive” processes , which preferentially establish discordant methylation states . We validate our RCP framework by confirming its ability to identify systems in which contributions from conservative processes are nearly complete or nearly absent , as well as systems on the continuum between these extremes . We apply this new framework to our authenticated , double-stranded DNA methylation patterns , both published and previously unpublished , collected by dideoxy sequencing from DNA of human and murine cells . To expand the data available for this initial RCP analysis , we also examine double-stranded methylation patterns from three recent publications [14 , 15 , 17] . To improve our understanding of transitions between stem and differentiated cells , we ask: ( i ) how strong are preferences for concordant DNA methylation states in cultured stem cells ? ; ( ii ) do concordance preferences change as cultured cells shift between stem and differentiated states ? ; and ( iii ) in the developing embryo , do stem cells of various potencies have preferences that mirror those in cultured stem cells ?
We have developed the Ratio of Concordance Preference ( RCP ) to assess the strategy of binary information transfer , with focus on the degree to which exact information is conserved . We apply our RCP framework to DNA methylation in mammalian cells . Our goal is to infer whether and how much the system of processes that established a given set of methylation patterns prefers concordant to discordant methylation states . This general formulation is free of assumptions about the molecular mechanisms whereby methylation is added to and removed from DNA . In our data from double-stranded DNA molecules from human and mouse , methylation occurs principally at the CpG motif . This symmetric motif may be written as CpG/CpG , which we here term “CpG dyad” . CpG dyads have opportunities for methylation on both strands . The methylation state of a dyad thus takes one of three forms: fully methylated , at frequency M , with methylated cytosines on both strands; hemimethylated , at frequency H , with a methylated cytosine on only one strand; and unmethylated , at frequency U , with neither cytosine methylated . The RCP framework can also be extended to non-CpG methylation at symmetric nucleotide motifs . To infer concordance preference for sets of double-stranded methylation patterns , we use the overall frequency of methylation , m , and the frequency of unmethylated dyads , U , of each data set . Because m is derived from the three dyad frequencies , the pair ( m , U ) encompasses the full information available from the implicit dyad frequencies , M and H . RCP evaluates the extent of deviation from expectations under a random model in which the system has no preference for either concordant or discordant placement of methyl groups , and is defined as: RCP = U ( U + 2 m - 1 ) 1 - U - m ( 1 ) RCP can also be expressed in a form more familiar in biology if dyad frequencies are considered as genotype frequencies for a gene with two alleles . RCP2 is 4MU/H2 , which is expected to equal 1 under the Hardy-Weinberg equilibrium [21 , 22] . Thus , RCP can be considered as a measure of deviation from random expectations . The random expectations , for which RCP = 1 , are met both with truly random placement of methyl groups , and with equal contributions from processes operating with strong preference for concordance and processes operating with strong preference for discordance . Under either of these circumstances , the frequency of unmethylated dyads is given by U = ( 1 − m ) 2 , leading to dyad frequencies as expected under the binomial distribution ( Fig 1a and 1b dashed curve; Fig 1c ) . A system in which methyl groups are added de novo without regard to the methylation state of the other strand [23] , such as one dominated by the activity of mammalian Dnmt3s , behaves largely in accordance with random expectations . One set of deviations from the random expectation is characterized by preference for concordant placement of methyl groups , such that the two classes of concordant dyads—fully methylated and fully unmethylated—are more frequent than expected under the random model . This situation occurs under conservative systems of methylation where strong contributions from maintenance-like processes , such as the activity of Dnmt1 in mammals [11 , 13 , 24] , lead to high frequencies of concordant dyads . In the extreme form of this deviation from random , methyl groups are observed only in fully methylated dyads ( Fig 1d ) , such that unmethylated dyads occur at frequency U = 1 − m ( upper diagonal line in Fig 1a and 1b ) . The other set of possible deviations from random is characterized by preference for discordant placement of methyl groups , leading to an overabundance of hemimethylated dyads . This situation occurs under dispersive systems of methylation such as those that yield transient hemimethylation following DNA replication and prior to daughter-strand methylation , and perhaps in genomic regions undergoing demethylation during periods of epigenetic transition . When methylation is maximally dispersive and methylation frequency m is less than 0 . 5 , all dyads with methylation will be hemimethylated ( Fig 1e ) , such that U = 1 − 2m ( lower diagonal line in Fig 1a and 1b ) ; when m is greater than 0 . 5 , not all methyl groups can be accommodated in hemimethylated dyads , and so a combination of hemimethylated and fully methylated dyads—but no unmethylated dyads—is expected ( lower horizontal line in Fig 1a ) . The two extreme deviations from random form the boundaries of the comprehensive space of possible configurations of methylation at symmetric motifs ( Fig 1a ) . Sets of double-stranded methylation patterns fall on the continuum between the extreme expectations ( Fig 1b ) , and can be located within this space to characterize the strategy of information transfer employed to give rise to a given data set , ranging from conservative to dispersive . As noted above , a system with an RCP value of 1 has no preference for either concordance or discordance of methylation , and is analogous to the distribution of genotype frequencies at a two-allele locus in a population that is at Hardy-Weinberg equilibrium [21 , 22] . An RCP value of 2 indicates two-fold preference for concordance , while an RCP of 1 2 indicates two-fold preference for discordance . RCP approaches infinity for systems that have complete preference for concordant dyads . At the other extreme , RCP approaches 0 ( i . e . , 1 ∞ ) for systems that have complete preference for discordant dyads . For the examples analyzed here , data for different loci and cells range from complete concordance to near-random , along the RCP spectrum . Complete discordance is found as a transient condition of adenine methylation at the ori locus in Escherichia coli , and serves to regulate the timing of reinitiation of DNA synthesis [25 , 26] . Adenine methylation in E . coli generally occurs at symmetric sites , such as the GATC motif within the ori locus , and can be assessed by PacBio sequencing [27] . Thus , a broad spectrum of concordance preference can exist in organisms , and can be quantified and evaluated by RCP . For large and intermediate-size data sets , the resolution of RCP is high across the range of possible methylation frequencies , although the resolution declines as m approaches 0 or 1 , such that RCP cannot be inferred for completely methylated or unmethylated genomic regions . Nonetheless , RCP can usually be inferred with high confidence using data from only a few hundred dyads . Our new approach therefore requires far fewer sequences to estimate concordance preference than do methods that focus on inferring rates for specific enzyme activities [24 , 28] . We apply RCP to investigate further the conclusion of Shipony et al . [16] that methylation in cultured stem cells is dominated by non-conservative processes , with little or no preference for concordance . Using double-stranded methylation patterns collected by our group , by Arand et al . [14 , 17] , and by Zhao et al . [15] , we assess and compare methylation concordance in cultured human and murine stem cells , as well as in murine cells undergoing early developmental transitions that give rise to totipotent embryonic cells . Our previous work with human single-copy loci in uncultured , differentiated cells revealed a substantial role for maintenance methylation , a conservative process , with a comparatively minor role for non-conservative de novo processes [24 , 28] . We therefore anticipated that RCP analysis of double-stranded methylation patterns from such cells would indicate substantial preference for concordant methylation states . Data published previously for G6PD , FMR1 , and LEP , in uncultured differentiated cells and new data presented here for FMR1 in cultured , human differentiated cells represent blood , connective , and adipose tissues . We applied RCP analysis to these data sets and found 13 . 2- to 85 . 7-fold preferences for concordant methylation . This confirms , as anticipated , that methylation is predominantly conservative in these differentiated cells ( Fig 2a; see table accompanying Fig 2 for approximate 95%CIs ) . We note that there is a good correspondence between RCP and hemi-preference ratio , a statistic we computed for the same data sets in the previous study [24] ( further discussion in S2 Text ) . We also found a substantial role for conservative methylation processes at single-copy loci in both cultured and uncultured murine differentiated cells . Data sets from Arand et al . [14] for Afp , Igf2 , Snrpn , and Tex13 from murine embryonic fibroblasts ( MEFs ) , and from Stöger [29] for Lep from somatic tissues , gave RCP point estimates indicating a greater than 18-fold preference for concordant methylation ( Fig 2b ) . Do multi-copy sequence families also have high preference for concordant methylation in differentiated cells ? We inferred RCP for four repeat families—B1 , IAP , L1 , and mSat—using murine data collected by Arand et al . [14] . Three of these families were found to have preference for concordant methylation in the same range inferred for single-copy loci ( RCP point estimates between 14 . 4 and 18 . 3; Fig 2b ) . The fourth—mSat—had an RCP estimate of 7 . 33 , lower than other families and single-copy loci examined in MEFs , but still indicative of strong preference for concordant methylation . For human cells , data from two independent lines of cultured embryonic fibroblasts were available for the repeat family L1 . Inferred RCP values were within the range found for single-copy loci in both human and murine differentiated cells ( Fig 2a ) . Overall , we find appreciable preference for concordance across a diverse group of data sets from differentiated cells . These sets span a more than five-fold range in methylation frequency , underscoring the independence of RCP from m , and , more generally , highlighting the capacity of methylation systems to propagate specific epigenetic states even when methylation is sparse . We conclude that preference for concordant methylation , albeit to variable degrees , is present in differentiated cells across broad classes of genomic elements , cell and tissue types , and culture states . We next ask whether substantial preference for concordance , as we infer above for differentiated cells , is also evident in data from cultured stem cells . In doing so , we compare our findings using RCP to the expectation from Shipony et al . [16] that methylation in such stem cells occurs primarily through non-conservative , random processes . The broadest data set available for our analysis comes from the near-genome-wide double-stranded methylation data presented by Zhao et al . [15] . These data give an inferred RCP of 5 . 22 for “all CpGs” in DNA from undifferentiated , cultured murine ES cells ( Fig 3a; S5 Table ) . For other classes of genomic elements in these near-genome-wide data [15] , we infer RCP values of 4 . 31 or greater ( S5 Table ) . These RCP values are significantly higher than 1 , the value predicted under Shipony et al . ’s proposal of dynamic methylation ( p < 10−16 , maximum likelihood comparison tests ( MLCTs ) ; S8 Text ) . We next ask whether our inference of appreciable concordance preference in the murine ES cell line used by Zhao et al . [15] reflects a general property of cultured lines of undifferentiated stem cells , both murine and human . For the murine ES line , J1 , double-stranded methylation data collected by Arand et al . [14] were available for four single-copy loci and four repeat families . Seven of the eight genomic regions—Igf2 , Snrpn , Tex13 , B1 , IAP , L1 , and mSat—had RCP values greater than 3 . 69 ( with minimum 95%-CI lower bound of 2 . 31 ) , still indicative of substantial preference for concordant methylation ( Fig 3a ) . One single-copy locus , Afp , had a methylation level too high , 0 . 99 , to permit reliable inference of RCP . Murine double-stranded methylation patterns for the four repeat families were available for two more stem cell lines , E14 and WT26 [14] . These additional repeat-family data sets , too , had RCP values significantly greater than 1 , although one data set , mSat in WT26 , had an RCP value closer to 1 than did others ( p = 0 . 045 , one tailed bootstrap test ( BT ) ; S7 Text ) . Data were available for a single-copy locus , Lep , for a fourth murine ES line , CGR8 . Here , too , RCP was significantly greater than 1 ( p < 10−16 , one-tailed BT ) . Human stem cell lines also exhibited aprpeciable preference for concordant methylation . All six of the human stem and iPS cell lines that we examined , when grown under non-differentiating conditions , gave RCP point estimates for the repeat family L1 that are between 3 . 41 and 5 . 20 . For all of these cell lines , outer bounds of the approximate 95% confidence intervals fall between 2 . 34 and 12 . 5 ( Fig 3b; S3 Table ) . Together , these values reveal concordance preference that is reduced relative to differentiated cells , but still greatly exceeds expectations under random placement of methyl groups ( p < 10−16 , one-tailed BT ) . We now consider the possibility that spontaneous differentiation had produced subpopulations of cultured stem cells that might account for the inference of RCP values substantially greater than 1 at the seven different loci and genomic elements examined . Our calculations revealed that a possible subpopulation of differentiated cells operating at much higher RCP than that of undifferentiated cells would need to comprise more than 50% of the population to account for our finding ( S9 Text ) . Morphological inspection of the cultured human stem cells under non-differentiating conditions did not suggest the presence of a substantial subpopulation of differentiated cells in any of these lines . We conclude that RCP values significantly greater than 1 are a consistent feature of cultured embryonic stem cells , and exist across a broad set of stem cell lines , genomic locations and element categories . Our finding of substantial preference for methylation concordance in data from cultured , undifferentiated stem cells contrasts with the inference of Shipony et al . [16] that DNA methylation in such cells is dominated by non-conservative , random processes . This disparity led us to ask whether our approach here for data acquisition and analysis is indeed capable of identifying sets of methylation patterns established under exclusively random processes , which are expected to yield RCP values of 1 ( see “Ratio of Concordance Preference is Defined …” , above ) . To assess this capacity , we consider methylation patterns from two murine embryonic stem cell lines that have impaired maintenance methylation: a Dnmt1 knockout ( KO ) line and an Np95 KO line . The Dnmt1 enzyme is principally responsible for addition of methyl groups to daughter-strand CpGs complementary to CpGs methylated on the parent strand [11 , 24 , 30]; Np95 facilitates interaction of Dnmt1 with these hemimethylated sites [31] . Absence of either protein is therefore predicted to markedly diminish maintenance activity . If our approach is able to detect essentially random placement of methyl groups , RCP values in these knockout lines should be ∼1 for loci for which Dnmt1 , aided by Np95 , is principally responsible for conservative methylation . Significant reductions in RCP were inferred for all single-copy loci and repeat families examined in Dnmt1 and Np95 KO lines [14 , 32] , compared to the parent stem-cell lines . Some reductions were sufficient to bring RCP values in the knockout lines to that expected for random placement of methyl groups: one single-copy locus—Afp—in the Dnmt1 KO line and one repeat family—B1—in both knockout lines had RCP values not significantly different from 1 ( Afp in Dnmt1 KO: 1 . 16 , p = 0 . 10; B1 in Dnmt1 KO: 1 . 14 , p = 0 . 17; B1 in Np95 KO: 1 . 02 , p = 0 . 38; one-tailed BTs; Fig 4 ) . These findings in the two mutant cell lines reveal that RCP analysis is , indeed , able to detect methylation established with random placement of methyl groups , and thus with little or no preference for concordance or discordance . The ability of RCP to detect random methylation has important implications for our work . First , we can conclude that our inference of persistent preference for concordant methylation in cultured stem cells reflects a bona fide property of those cells , rather than an artifact of our approach . Second , we can infer from our finding of RCP >1 for nine of the twelve data sets examined in the Dnmt1 and Np95 KO lines that methyltransferases other than Dnmt1 can contribute to conservative methylation . This inference is consistent with earlier conclusions that contributions of Dnmt3s can include low levels of maintenance activity [19 , 24 , 33] . Nonetheless , knocking out one or both of Dnmt3s generally increased the relative contributions of conservative processes ( S2 Fig; S10 Text ) , highlighting the de novo properties of the Dnmt3s . Our initial examination of RCP values in differentiated cells as compared to cultured stem cells suggests that RCP is altered through the differentiation process ( Figs 2 and 3 ) . Would significant RCP increases be observed for individual cell lines transitioning between differentiation states ? We first asked whether RCP values change when undifferentiated human ES and iPS cells are grown under differentiating conditions ( see Materials and methods ) . We inferred RCP at the promoter of L1 elements of cultured human iPS and ES cells , inferring values for two different passages of the latter cell line . Upon differentiation , RCP values for all three of these cell lines increased significantly ( p = 0 . 004 , H9p37; p = 0 . 025 , H9p81; p = 0 . 0005 , FSH iPS; two-tailed permutation tests ( PTs ) ; S7 Text ) , and approached the lower boundary of the confidence region inferred for single-copy loci in differentiated somatic cells ( Figs 2 and 5a ) . Using near-genome-wide data for cultured murine cells [15] , we inferred significant RCP increases upon cell differentiation for most genomic elements ( p < 10−16 , MLCTs ) , with the exception of low-complexity and satellite DNAs ( S5 Table ) . These RCP increases were greatest at promoters , CG islands , and CG shores , and were more modest at other regions . We conclude that the onset of differentiation in cultured human and murine cells is associated with a shift towards a greater role for conservative processes . Does the dedifferentiation that occurs in culture upon production of an iPS line from a differentiated cell have an opposite effect on concordance preference ? To address this question , we compare methylation at L1 elements in three iPS lines to that in the two cultured human fibroblast lines from which they were derived . As predicted , RCP values for all three iPS lines were much reduced compared with values observed for the parent fibroblast lines ( p < 10−16 , two-tailed PTs; Fig 5b ) . Dedifferentiation in tissue culture is thus associated with a shift in DNA methylation toward a greater role for non-conservative processes . It will be useful to investigate whether changes in methylation systems as measured by RCP drive or merely reflect the cellular differentiation process . The ∼3-fold-or-greater preference for concordant methylation we infer in many different cultured ES and iPS cell lines ( Fig 3a; S3 Table ) far exceeds the concordance expected under the null hypothesis that methyl groups are placed at random . Here we ask whether this appreciable preference for concordance is an artifact of growing stem cells in culture , or whether it is shared by uncultured stem cells taken directly from an embryo . We first consider whether totipotent cells from an embryo have evidence of conservative processes . We applied RCP to double-stranded methylation patterns collected by Arand et al . [17] for three multi-copy loci in mouse embryos: L1 , mSat , and IAP . Our analyses revealed that these totipotent embryonic cells , from post-replicative zygote to morula stage ( through 3 days post conception , dpc ) , also exhibit moderate preference for concordance . Each of the eighteen data sets we considered yielded an RCP point estimate greater than 1 , and a confidence interval that excludes 1 ( p < 0 . 005; Fig 6a; S4 Table ) . Pluripotent stem cells from mouse embryos ( gastrula , 3 . 5 dpc ) also exhibit moderate preference for concordant methylation for all three of the multi-copy loci examined ( p < 10−16; Fig 6a; S4 Table ) . Thus , we conclude that moderate preference for concordance is an epigenetic feature of uncultured embryonic stem cells of disparate developmental potential , and is not an artifact of the establishment of embryonic stem cells in culture . Though RCP values for stem cells from embryos clearly indicate some preference for concordance , the extent of this preference is lower than for differentiated cells at most of the loci examined ( Figs 2 and 5 ) . Does this lower preference for concordance originate in gametes , or does it instead arise post-fertilization ? To address this question , we expanded our inference of RCP values for sperm and oocytes from exclusively L1 ( Fig 2b ) to all three loci analyzed by Arand et al . [17] . At the three multi-copy loci , RCP values for gametes are within the range observed for other differentiated cells , with average point estimates ranging from 13 . 4 to 45 . 0 ( Fig 6b; S4 Table ) . This high preference for concordance in gametes implies that the lower RCP values characteristic of zygotes and stem cells must arise post-fertilization rather than in gametes . To pinpoint the timing of this transition to lower RCP values observed in stem cells , we consider data from post-fertilization nuclei and cells [17] . Data available for pronuclear stages 1 , 2 , and 3 revealed high RCP values , similar to those observed in gametes . In pronuclear stages 4-5 , however , there was an abrupt transition to lower RCP values in the range observed for totipotent stem cells ( Fig 6; S4 Table ) . Is this transition dependent on the DNA replication event that occurs from pronuclear stage 3 to stages 4-5 ? To address this question , we assess data from Arand et al . [17] , in which aphidicolin was used to block DNA replication in the fertilized egg . Our RCP analysis reveals that methylation patterns at L1 and mSat in these treated cells , while having somewhat lower RCP values relative to pronuclei at earlier stages , had not undergone the major reduction in RCP that we infer for unmanipulated pronuclei at stages 4-5 ( p < 10−16 , two-tailed PTs; S4 Table ) . Thus , the shift to lower RCP in stem cells following fertilization appears to require either DNA replication or some later event that is itself replication-dependent . This conclusion is consistent with the inference of Arand et al . , using a different metric [17] , that DNA replication in the zygote plays a pivotal role in methylation dynamics . This change from high RCP values in gametes and early pronuclei to lower values in post-replicative zygotes and descendant stem cells was markedly abrupt . Are other major transitions in RCP similarly abrupt , or do some occur gradually , perhaps over many cell divisions ? Murine primordial germ cells ( PGCs ) , in their maturation to differentiated gametes , offer an opportunity to approach this question [34 , 35] . Using data from Arand et al . [17] , we infer that RCP values for PGCs increased by factors ranging from 2 . 5 to 5 during their progression from 9 . 5 dpc to 13 . 5 dpc . This increase was not sudden , but occurred over the four-day period , and so spanned an interval of substantial cell proliferation [34] ( Fig 6b ) . The murine embryo data thus provide examples of both abrupt and gradual transitions in RCP through development ( Fig 6c ) . The RCP values for PGCs at 9 . 5 dpc , the earliest stage for which data were reported by Arand et al . [17] , were strikingly low: 1 . 40 for L1 , 1 . 57 for mSat , and 2 . 38 for IAP . Nonetheless , confidence intervals for all three loci indicated RCP values greater than 1 ( p < 2 × 10−5 ) , the value expected under wholly random placement of methyl groups , indicating persistent , low-level preference for concordance . This low , residual preference for concordance in maturing PGCs perhaps reflects both the epigenetic memory needed to maintain the poised state of stem cells , and the epigenetic flexibility required for the production of differentiated gametes . The first few rounds of PGC division involve developmental reprogramming and commitment [35] , and establishment of lineage-specific gene expression patterns . The 3 . 5-fold average increase of RCP across these divisions ( Fig 6; S4 Table ) mirrors the 3 . 6-fold average increase in RCP values that occur when cultured ES cells are subjected to differentiating conditions ( Fig 5; S3 Table ) . There is , however , a critical difference between the trajectories for proliferating PGCs and differentiating ES and iPS cells in culture . When cultured cells were differentiated , their methylation frequencies increased . By contrast , methylation frequencies for PGCs declined across early rounds of division [36] . Seisenberger et al . [7] , Arand et al . [17] , and von Meyenn et al . [18] concluded that this reduction in methylation frequency is driven by partial impairment of maintenance methylation . Our RCP framework permits a closer look at the likely extent of this proposed maintenance impairment . If maintenance methylation were completely absent and no other methylation processes were active , passive , fully dispersive demethylation would occur . This would halve methylation frequencies and leave methyl groups only in hemimethylated dyads , yielding an RCP value of 0 . By contrast , data from PGCs yielded RCP values significantly greater than 0 , and even 1 . Indeed , only cells treated with S-Adenosylmethionine-ase ( RCP point estimate: 0 . 20 , approximate 95% confidence interval: 0 . 15—0 . 26; S4 Table ) yielded values close to 0 . This is not surprising , as S-Adenosylmethionine-ase either impairs or eliminates a cell’s ability to methylate DNA , and so reveals RCP trajectories that would be observed with complete or nearly complete suspension of all methylation processes . Together these findings confirm that , while the RCP framework can detect very low RCP values , maturing PGCs retain conservative methylation processes , and that these processes occur at levels sufficient to outweigh any dispersive effects of passive demethylation . Because RCP makes no explicit enzymatic or mechanistic assumptions about the methylation machinery , it permits quantification and comparison of strategies for symmetric methylation across cell types , developmental periods , and organisms , despite variation in exact mechanisms . Application of RCP to double-stranded DNA methylation patterns reveals that preference for concordance in DNA methylation is a persistent though quantitatively variable feature of mammalian cells of disparate developmental potential . Specifically , we find that: ( i ) in cultured human and murine ES and iPS cells , preference for concordance is lower than in differentiated cells , but not absent; ( ii ) for cultured human stem cells , cellular differentiation is characterized by increasing preference for concordance , whereas , for cultured differentiated cells , dedifferentiation is characterized by declining preference for concordance; and ( iii ) during early murine development , transitions in RCP mirror those found in cultured cells , with pluripotent and totipotent stem cells showing appreciable concordance preference throughout . We also observe that substantial changes in RCP can be either abrupt , requiring only one DNA replication event , or gradual , occurring over multiple rounds of replication . Although preference for concordance is substantial throughout early murine development , there is an instance of concordance preference near the expectation under entirely random processes . We infer RCP values close to , albeit significantly different from , 1 in the early primordial germ cell stage at the three repetitive element families examined by Arand et al . [17] ( Fig 6 ) . The instance of low , yet present , concordance preference may reflect both the epigenetic stability required to maintain the poised state of the stem cells and the epigenetic flexibility needed en route to production of functional gametes . Flexibility , indicated by RCP values near 1 , may result from near-random processes or instead from a balance of conservative and dispersive methylation . Existing data and conclusions of Seisenberger et al . [7] , Arand et al . [17] and von Meyenn et al . [18] are more consistent with the latter interpretation . Our finding of moderate contributions from conservative DNA methylation processes in human and murine stem cells is seemingly contrary to the conclusion of Shipony et al . [16] that “dynamic” processes are dominant in cultured stem cells , even in regions where dense methylation is maintained . This apparent disparity may have arisen from differences between the temporal scales assayed by Shipony et al . ’s approach and our own . The method of single-cell isolation and clonal expansion used by Shipony et al . estimates epigenetic memory from single-stranded data collected after 15 to 21 rounds of cell division . In contrast , our approach utilizes double-stranded DNA data to examine epigenetic memory over a single round of DNA replication . Evidence of preference for concordance , apparent in our comparison of DNA strands separated by one replication event , will be muted in comparisons of more distantly related molecules . Short-term epigenetic memory , perhaps important for guiding cell-fate trajectories at early developmental stages , is at least partially achieved through preference for concordant DNA methylation . By contrast , over larger numbers of cell divisions , as sampled by Shipony et al . [16] , such as for stem cells dividing in culture , preference for concordant methylation may be less important than other mechanisms of epigenetic memory . For example , regulation of promoter activity by DNA methylation can occur via an ensemble effect rather than by methylation of specific CG dyads within a promoter [37] . In such cases , propagation of exact methylation patterns may be less important than the density of methylation that influences gain or loss of methylation and states of transcriptional activity over many cell divisions [38] . Epigenetic mechanisms other than DNA methylation also contribute to epigenetic memory at various timescales . RCP analysis in combination with histone-modification data from ENCODE [39] and Roadmap [40] will provide unprecedented opportunities to infer interactions between DNA-methylation machinery and histone modification , the developmental timing of epigenetic stability , and its variation across the genome . The value of RCP analysis will be enhanced and broadened by emerging DNA sequencing technologies that yield longer , more informative double-stranded methylation patterns . Longer sequence reads will enable inference of RCP for single cells , permitting study of cell-cell epimosaicism , such as arises in cancer [2] and other syndromes characterized by epigenetic heterogeneity and change [41 , 42] . Some of these methods also reduce data corruption arising through errors in bisulfite conversion and amplification , and can distinguish between methyl- and hydroxy-methyl cytosine [43 , 44] . High-resolution RCP estimates available through these advances will provide new insight into the flexibility and potential sensitivity of individual loci and cell types to environmental conditions encountered during embryogenesis and beyond .
Many of the sets of human DNA methylation patterns analyzed here were presented in previous publications , which include information on University of Washington Human Subjects approval for collection and use . These data include G6PD and FMR1 from leukocytes of normal individuals [24 , 28]; FMR1 from males with fragile X syndrome [41]; LEP from male leukocytes and from female lymphocytes and adipose tissue [24 , 29] . Human methylation patterns presented here for the first time were collected from: ( i ) FX iPS cell lines 1 and 2 , which were developed at the University of Washington ISCRM facility from fibroblasts ( line GM07730 , Coriell Cell Repositories , Camden , NJ ) of a male with a fragile X “full mutation” , using published methods [45]; ( ii ) iPS cell line IMR90 , which was developed at the University of Washington ISCRM facility from the IMR90 somatic line established from fibroblasts ( obtained from ATCC ) of a normal female , using published methods [45]; ( iii ) FSH iPS cell line , which was developed at the University of Washington ISCRM facility from fibroblasts of an individual with Facioscapulohumeral dystrophy ( FSHD ) , as previously described in [46]; and ( iv ) H9 human ES cells from NIH Embryonic Stem Cell Registry ( WA09 , H9 number 0062 ) . Overview of the mathematical foundation is given in Results and Discussion , and developed further in S1 Text . The six human ES and iPS cell lines for which we collected methylation patterns were derived from either embryos or fibroblasts described as normal [47] or from fibroblasts of individuals with disorders not known to affect the basic biochemistry of DNA methylation . Cells were cultured in Dulbecco’s modified Eagle’s medium/Ham’s F-12 medium containing GlutaMax supplemented with 20 percent serum replacer ( SR ) , 1 mM sodium pyruvate , 0 . 1 mM nonessential amino acids , 50 U/ml penicillin , 50 μg/ml streptomycin and 10 ng/ml basic fibroblast growth factor ( all from Invitrogen ) , and 0 . 1 mM β-mercaptoethanol ( Sigma-Aldrich ) . hESCs were grown on γ-irradiated primary mouse embryonic fibroblasts ( MEFs ) and passaged using dispase ( 1 . 2 U/ml; Invitrogen ) . They were passaged onto Matrigel ( Corning ) without feeders in mTeSR1 ( Stem Cell Technologies ) for the final passages prior to analysis . Cells were differentiated by passage onto Matrigel in Dulbecco’s modified Eagle’s Medium supplemented with 20 percent fetal bovine serum and pen/strep . Images of our cultured stem cells grown under differentiating conditions confirmed their pluripotency . Methylation patterns from murine ES cells , and the origin and culturing of these cells , have previously been described [14 , 15 , 17 , 32] . The DNA methylation patterns collected in our lab and analyzed here , both those published previously and those presented here for the first time , were collected using the hairpin-bisulfite PCR approach [13] , with barcodes and batchstamps to authenticate each sequence [48] . Details for collection of each data set are given in S2 Table . The data presented by Arand et al . [14 , 17] , and Zhao et al . , [15] and analyzed here , were collected in the absence of molecular batch-stamps and barcodes , raising the possibility that the reliability of those data sets is undermined by PCR clonality . However , both groups used alternate strategies that revealed that PCR clonality was not rampant . Zhao et al . found that essential features of data sets did not differ appreciably between the “real” data set collected conventionally , using PCR , and a test , PCR-free data set that excluded opportunities for clonality by including only one read from each locus , providing no evidence of impacts from PCR clonality ( Hehuang Xie , personal communication ) . In turn , Arand et al . used molecular codes for several of their data sets , and , for the few data sets collected in the absence of such codes , observed appreciable heterogeneity among patterns , also hinting that data were not appreciably impacted by clonality ( Julia Arand , personal communication ) . | As stem cells differentiate , they acquire epigenetic marks that activate some genes and silence others , eventually producing the profiles that define specific cell lineages . While existing approaches can reveal the differentiation state of a given cell or the activity state of a given gene , none can locate an individual genomic region along the epigenetic continuum between flexible and fixed . To address this challenge , we introduce a new framework to infer epigenetic stability from the concordance of DNA methylation patterns on the two strands of individual DNA molecules . For cells of all developmental potentials , we find that top- and bottom-strand methylation patterns match far more often than expected by chance alone . As cells differentiate , the fidelity of pattern transfer increases , thereby resulting in higher epigenetic stability; dedifferentiation is characterized by declining stability . Our metric has the potential to identify genomic regions that remain sensitive to environmental signals well beyond the interval of lineage specification . | [
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"a... | 2017 | Epigenetic memory via concordant DNA methylation is inversely correlated to developmental potential of mammalian cells |
Pax6 is a developmental control gene essential for eye development throughout the animal kingdom . In addition , Pax6 plays key roles in other parts of the CNS , olfactory system , and pancreas . In mammals a single Pax6 gene encoding multiple isoforms delivers these pleiotropic functions . Here we provide evidence that the genomes of many other vertebrate species contain multiple Pax6 loci . We sequenced Pax6-containing BACs from the cartilaginous elephant shark ( Callorhinchus milii ) and found two distinct Pax6 loci . Pax6 . 1 is highly similar to mammalian Pax6 , while Pax6 . 2 encodes a paired-less Pax6 . Using synteny relationships , we identify homologs of this novel paired-less Pax6 . 2 gene in lizard and in frog , as well as in zebrafish and in other teleosts . In zebrafish two full-length Pax6 duplicates were known previously , originating from the fish-specific genome duplication ( FSGD ) and expressed in divergent patterns due to paralog-specific loss of cis-elements . We show that teleosts other than zebrafish also maintain duplicate full-length Pax6 loci , but differences in gene and regulatory domain structure suggest that these Pax6 paralogs originate from a more ancient duplication event and are hence renamed as Pax6 . 3 . Sequence comparisons between mammalian and elephant shark Pax6 . 1 loci highlight the presence of short- and long-range conserved noncoding elements ( CNEs ) . Functional analysis demonstrates the ancient role of long-range enhancers for Pax6 transcription . We show that the paired-less Pax6 . 2 ortholog in zebrafish is expressed specifically in the developing retina . Transgenic analysis of elephant shark and zebrafish Pax6 . 2 CNEs with homology to the mouse NRE/Pα internal promoter revealed highly specific retinal expression . Finally , morpholino depletion of zebrafish Pax6 . 2 resulted in a “small eye” phenotype , supporting a role in retinal development . In summary , our study reveals that the pleiotropic functions of Pax6 in vertebrates are served by a divergent family of Pax6 genes , forged by ancient duplication events and by independent , lineage-specific gene losses .
Development is critically dependent on a core set of developmental regulator genes , most of which are highly conserved across metazoans and carry out pleiotropic functions as part of multiple gene regulatory networks . Variation in the functional output from these genes is an important factor in evolutionary divergence between species , yet their essential and pleiotropic role precludes dramatic changes in their primary sequence . Instead it is believed that duplication of key developmental control gene loci , in combination with variation in their spatio-temporal domains and expression levels are major components of this process [1]–[4] . Duplication of gene loci provides an initial freedom from selective pressure to allow divergence between gene loci . Pax6 is a developmental control gene with an essential function in the development of eyes throughout the animal kingdom [5] , [6] . Its ability to induce the full program for eye formation from ocular and non-ocular imaginal discs in Drosophila embryos has revealed it as the first of a small set of master regulators for eye development [7]–[9] . In vertebrates the key role of Pax6 in eye formation is equally well established . In addition Pax6 plays important roles in development and maintenance of the endocrine pancreas , the olfactory system and the central nervous system ( CNS ) where it is required for multiple cellular processes including maintenance of the neuronal progenitor pool at early developmental stages , and neurogenesis at later stages [10] . It is also required for cell migration and axon guidance in parts of the brain ( reviewed in [11] , [12] ) . In humans heterozygous disruption of the gene gives rise to the congenital eye malformation aniridia through haploinsufficiency , in some cases accompanied by additional phenotypes such as epilepsy , defective interhemispheric auditory transfer , anosmia or diabetes [13]–[16] , while homozygous loss of gene function is incompatible with life [17] . In mice and rats heterozygous mutants have small eyes and exhibit many of the same features as found in aniridia patients [18] , [19] . Homozygous mutants die at birth with severe brain malformation and complete lack of eyes and nasal structures [19] . Overexpression of the gene also causes eye malformations [20] , [21] , indicating that Pax6 dosage is critical for correct eye development . In mammals a single Pax6 gene carries out the wide variety of developmental regulatory functions . This is achieved by strict control of its expression through a complex , extended cis-regulatory domain containing a large number of tissue-specific enhancers [22]–[29] . While some cis-elements are found upstream or within introns of the gene , most of the characterized long-range control elements are found in the downstream region . The importance of distant cis-regulatory elements for Pax6 gene expression has been highlighted by the existence of aniridia patients with chromosomal abnormalities ( deletions/translocations ) that separate these elements from the body of the gene [30]–[32] . Investigation of the locus beyond the patient breakpoints by DNaseI hypersensitivity mapping led to the identification of a region containing several cis-regulatory elements , embedded within the introns of an adjacent gene , Elp4 , forcing synteny conservation between the genes [25] , [33] , [34] . In addition to a large array of distal enhancers , the single mammalian Pax6 gene uses at least three different promoters , P0 , P1 and Pα , and the resulting transcripts produce three protein isoforms , Pax6 , Pax6 ( +5a ) and Pax6ΔPD [35]–[37] . The canonical Pax6 isoform encodes a paired and homeodomain containing transcription factor with a PST-rich transactivation domain at the C-terminus . Inclusion of an alternative exon , exon 5a , results in a protein with an interrupted paired domain that recognizes a different DNA binding sequence [35] . The paired-less ΔPD isoform is produced from a transcript initiating at an internal promoter Pα located in intron 4 of the gene [27] . The resulting protein contains the paired-type homeodomain and transactivation domain , but lacks the N-terminal paired domain . The function of this isoform is unknown , but overexpression has been shown to cause a microphthalmia phenotype in mice [24] , [38] , [36] . Apart from its DNA-binding capacity the homeodomain is also suggested to function in protein-protein interactions and could be involved in dimerisation [39] . In zebrafish the role of Pax6 is fulfilled by duplicate Pax6 genes , Pax6a and Pax6b , thought to have arisen by the fish-specific whole genome duplication event ( FSGD ) . The FSGD is estimated to have taken place around 320 million years ago in the teleost fish lineage [40] , and is often cited as the main contributing factor in the emergence of the large diversity of teleost fish , which make up nearly half of all vertebrate species [41]–[43] . The FSGD is a third genome wide duplication event ( 3R ) that follows two earlier rounds ( 1R , 2R ) of whole genome duplications ( WGD ) that occurred very early in the evolution of vertebrates [44] , though debate about the nature and timing of these WGD events still continues . As proposed nearly 40 years ago , genome duplication events are powerful drivers of evolution [45] . Genome or gene duplication events provide an initial freedom from selective pressure , and thus create an opportunity for modification or mutation of gene duplicates , as well as for alteration of the cis-regulatory landscape around the duplicate gene loci , while critical functions are maintained by the other copy under selective pressure . The various ways that can lead to retention of both gene copies following a duplication event are explained by the Duplication-Degeneration-Complementation ( DDC ) model [46] . Commonly , particularly in genes with a single function , one of the duplicates will start to accumulate mutations and degenerate beyond recognition over time , leaving the other copy to fulfill its single function ( non-functionalization ) [47]; Retention of both duplicates is more likely in pleiotropic genes , a category that includes many developmental regulatory genes . A number of scenarios can lead to such an outcome: one of the duplicates may acquire a novel function ( neo-functionalization ) , the functions of the ancestral gene may become divided between the duplicates ( sub-functionalization ) , or a combination of these ( neo-subfunctionalization ) [46]–[48] . The relative contribution of each of these possibilities is likely to be different for each gene locus and between species . In many cases the functional divergence of gene duplicates is driven by changes in their cis-regulatory domains . In recent years identification of cis-regulatory elements has been greatly facilitated by comparative analysis of sequence conservation between distantly related species [49] . Compared to surrounding neutral sequences , sequences with important regulatory function are maintained under selective pressure and stand out as conserved non-coding elements ( CNEs ) . However , functionally conserved regulatory regions with little or no sequence conservation have also been identified [28] , [50] , while sequence-similar enhancers can drive dissimilar expression patterns [51] , [52] fuelling the debate on whether sequence conservation is necessary for functional conservation . It is now thought that a massive appearance of novel CNEs has occurred early in the evolution of jawed vertebrates [53] . Comparisons with available sequence from the jawless vertebrate lamprey suggests it contains far fewer CNEs that are also shorter and less well conserved , while very few conserved non-coding elements can be identified in amphioxus [54] , or ascidians ( Ciona ) . In addition to the large-scale acquisition of ancient enhancers during the early gnathostome period [55] , additional novel CNEs have been recruited at later stages in the evolution of specific lineages [56] . On the other hand , some ancient CNEs have been lost independently in different bony vertebrate lineages [57] . Thus absence of sequence conservation in teleosts at the position of a conserved element in the tetrapod locus could either indicate the loss of that element in fish species , or gain of the element in the tetrapod lineage . Two Pax6 genes were previously identified in the zebrafish genome [58] , and comparative analysis of their genomic loci suggested their evolution has largely followed the DDC model of divergence and complementation [59] . This led us to ask whether duplicate copies of Pax6 could also be identified in other teleost fish species and how the duplicate copies may have diverged in those species . Here we show that duplicate Pax6 genes are present in several other teleost species such as medaka , stickleback , fugu and Tetraodon ( acanthopterygians ) . Examining the patterns of non-coding sequence conservation around the duplicate loci reveals a strong difference in the evolutionary divergence of the Pax6 loci in the acanthopterygians when compared to the zebrafish Pax6a/b divergence . While in zebrafish both loci have retained a large and overlapping portion of the cis-regulatory repertoire , the difference in the cis-regulatory domains of the duplicates in other teleosts is much more dramatic . Comparison with the mammalian locus indicates conservation of the ancient cis-regulatory landscape at the Pax6a loci , and a complete absence of conserved cis-elements at the Pax6b loci . In combination with a loss of the potential to encode the alternative exon5a this suggested a different evolutionary origin for the Pax6b loci in the acanthopterygians . To relate our observations to a more ancestrally diverged species , we proceeded to obtain genomic sequence for the Pax6 locus of the elephant shark ( Callorhinchus milii ) , a cartilaginous fish . Cartilaginous fishes are the most basal group of living jawed vertebrates and hence constitute a critical outgroup for bony vertebrates . The elephant shark is particularly attractive for comparative studies into the evolution of cis-regulatory landscapes in different jawed vertebrate lineages . Initial low coverage ( ∼1 . 4× ) sequencing of its relatively small genome ( 910 Mb ) revealed a greater complement of conserved non-coding sequences between the elephant shark and human genome than between human and zebrafish [60] . Surprisingly , screening of our elephant shark BAC library indicated the existence of a second Pax6 locus in this species . Sequence analysis of the BAC containing this locus revealed that this gene is a paired-less Pax6 gene , which we named Pax6 . 2 . To determine whether the existence of this gene indicates a shark-specific duplication , or is the result of an ancient duplication event predating the split between cartilaginous fishes and bony vertebrates , we searched the genomes of other species for the presence of additional Pax6 genes using synteny relations from the elephant shark Pax6 . 2 locus . This approach revealed the presence of Pax6 . 2 orthologs in Xenopus , lizard , zebrafish and other teleosts . Thus the zebrafish genome contains 3 Pax6 genes . Further evidence for the shared ontogeny of these orthologs comes from identification and analysis of conserved cis-elements located near the genes . We show that these elements share both sequence and functional conservation , and the study reveals them as ancient enhancers linked to Pax6 regulation from the earliest stages of vertebrate evolution . Based on our phylogenetic analyses we present a model for the evolutionary history of the Pax6 gene family in vertebrates . In this model the two rounds of WGD at the base of the vertebrate lineage gave rise to four Pax6 genes . One of these was lost early on , while a variable subset of the remaining three has been retained in different species as a result of independent divergences and gene losses in different lineages . In the teleost lineage the FSGD produced further duplicates of the three Pax6 genes of which variable subsets remain in contemporary species .
To identify duplicate Pax6 genes in teleost fishes other than zebrafish , we searched the genomes of four other teleost fish species for which genomic sequences were available in the Ensembl database: medaka ( Oryzias latipes ) , stickleback ( Gasterosteus aculeatus ) , green spotted pufferfish ( Tetraodon nigroviridis ) and fugu ( Takifugu rubripes ) . We found evidence for the presence of duplicated Pax6 gene loci in these four species of acanthopterygians . We compared the genes from these five teleost fish species with the Pax6 gene from a selection of other vertebrate species . Alignment of the amino acid sequences of the encoded proteins demonstrates a high level of similarity between the duplicated fish proteins and tetrapod Pax6 in all protein domains , including the paired domain , homeodomain and PST-rich transactivating regions ( Figure 1A ) . The two major isoforms of full length Pax6 in tetrapods , Pax6 and Pax6 ( +5a ) , differ by a 14 amino acid insertion into the paired domain , encoded by an alternative exon 5a [35] . This alternative exon is present in the Pax6a gene of all five teleost fishes , and it is also found in the zebrafish Pax6b gene . Comparisons of the alternative exon between human and the fish species indicate significant variation between the peptide encoded by the exon 5a , both with respect to the amino acid sequence and length of the peptide ( Figure 1A ) . However , while exon 5a is found in both zebrafish Pax6 duplicates , the exon is notably absent from the second Pax6 gene in the other four teleost species ( Figure 1A ) . The region between exons 5 and 6 of the Pax6b genes in these fishes lacks any sequence homology to the exon , and manual searching of translated sequence in all reading frames failed to detect evidence for the presence of this exon . This indicates that the Pax6b genes of medaka , stickleback , fugu and Tetraodon do not have the ability to encode a Pax6 ( +5a ) isoform , while both zebrafish Pax6a and Pax6b have retained this ability . In tetrapods translation of full length Pax6 strictly starts at the ATG initiator codon located in exon 4 . It has been noted that in teleost fish translation can also start in exon 2 , creating an N-terminal extension to the encoded Pax6 protein [37] , [58] , [61] . Alignment of available ESTs and Genewise protein predictions shows most teleost Pax6a and Pax6b genes have the ability to code for this N-terminal protein extension , suggesting this teleost specific feature was acquired early in evolution and has been retained throughout the divergence of teleost Pax6 genes ( Figure 1A ) . We next downloaded the sequence scaffolds around the genes , and performed sequence alignments using PipMaker [62] using the human genomic region as reference sequence , to examine divergence of the paralogous genomic loci in the teleost species ( Figure 1B ) . Examining the patterns of sequence conservation around the gene duplicates reveals a much more dramatic divergence between the paralogous loci in the four teleost fish , when compared to the relatively balanced sub-partitioning of conserved elements around the Pax6 duplicates in zebrafish . While in zebrafish both loci have retained a large and overlapping portion of the cis-regulatory repertoire , the divergence in the other teleosts has led to conservation of most of the ancient cis-regulatory landscape only at the Pax6a loci . The acanthopterygian Pax6b loci on the other hand have experienced a dramatic divergence or loss of cis-elements , such that , with one exception ( see below ) , no recognizably conserved non-coding sequences remain in the locus in comparison with the mammalian or zebrafish Pax6 loci ( Figure 1B ) . Furthermore , the blocks of sequence conservation in the 3′UTR are also absent from the acanthopterygian Pax6b , while found sub-partitioned between the zebrafish Pax6a and Pax6b loci . The lack of alternative exon 5a , the absence of CNEs and the differences in synteny conservation around the genes ( see below ) strongly suggest that the Pax6 duplicates of medaka , stickleback , fugu and Tetraodon originate from a separate duplication event compared to the zebrafish duplicates . To distinguish between these separate sets of Pax6 genes we will refer to the canonical Pax6 gene as Pax6 . 1 in species with multiple Pax6 loci . Thus all fish Pax6a genes will be termed Pax6 . 1 , while the duplicate zebrafish Pax6a and Pax6b genes will be redefined as Pax6 . 1a and Pax6 . 1b . The second full-length Pax6 gene found in acanthopterygians will hereafter be referred to as Pax6 . 3 . As the near complete lack of CNEs between the Pax6 . 1 and Pax6 . 3 loci could suggest non-functionalization of the acanthopterygian Pax6 . 3 genes , we carefully inspected the coding sequences of the genes . All Pax6 . 3 genes contain open reading frames that encode clear Pax6 homologs . The conservation of ORFs in all four acanthopterygian species examined suggests that the gene is functional , which is further supported by the existence of ESTs for the Pax6 . 3 gene in medaka ( GenBank BJ013007 and AM298948 ) . To look for the expression pattern of Pax6 . 3 , a probe was made from one of the medaka ESTs ( clone MF01SSA182E11 ) and used for RNA in situ hybridizations in early medaka embryos ( Figure 1C–1K ) . At stage19 , weak expression of Pax6 . 3 was observed in the anterior diencephalon , whereas the posterior diencephalon and posterior part of the optic vesicle showed stronger expression ( Figure 1D ) . Broader expression was seen for medaka Pax6 . 1 in the diencephalon , hindbrain and entire optic vesicle at this stage ( Figure 1C , and [63] ) . At stage 22 , the Pax6 . 3 expression domain in the diencephalon appears widened and persists in the posterior optic cup ( Figure 1F ) , while Pax6 . 1 expression is maintained throughout the optic cup , diencephalon and hindbrain ( Figure 1E ) . Expression of Pax6 . 3 persists in the diencephalon at stage 27 and 30 , but eye expression was no longer observed ( Figure 1H , 1K ) . In contrast Pax6 . 1 expression is maintained in the diencephalon , hindbrain and eyes at stage 27 ( Figure 1G ) , and is restricted to the ganglion cell layer and inner nuclear layer of the neural retina at stage 30 ( Figure 1I ) . This restricted expression pattern of medaka Pax6 . 3 mRNA in combination with the presence of an intact ORF suggests that the gene is functional , and is subject to regulated control of expression . We therefore generated a sequence alignment of the teleost Pax6 gene loci , using the stickleback Pax6 . 3 locus as baseline sequence ( Figure S1 ) . The alignment indicated the presence of a small number of CNEs that are conserved specifically between the Pax6 . 3 loci . As expected no non-coding conservation was found with the Pax6 . 1 loci , with exception of one small region of conserved sequence ( E-200 , see below ) . To assess how the presence or absence of particular CNEs correlates with functional cis-regulatory activity we focused on intron 7 of the Pax6 gene . We have previously studied the murine intron 7 in transgenic mice and shown it to contain a number of tetrapod conserved enhancers [23] . These elements show a variable pattern of conservation in the fish loci ( Figure 2A ) . As it contains a divergent complement of CNEs and , importantly , is flanked by the clearly recognizable landmarks of exons 7 and 8 to demarcate the region , we considered intron 7 particularly well-suited to study the correlation between sequence conservation patterns and functional enhancer activity . We cloned the full intron 7 sequences from the zebrafish Pax6 . 1a and Pax6 . 1b and medaka Pax6 . 1 and Pax6 . 3 genes and made reporter constructs for analysis in transgenic zebrafish . We also made reporter constructs for individual intron 7 CNEs from the zebrafish Pax6 . 1a locus to assess their contributions to the full intron 7 expression pattern . Analysis of the individual 7CE1 , 2 and 3 elements indicated that expression in the diencephalon is contributed by the 7CE2 element ( Figure 2D , 2E ) and expression in the hindbrain by 7CE3 ( Figure 2F , 2G ) . Reporter analysis of the 7CE1 element did not reveal any consistent expression pattern in transient transgenic fish . The 7CE2 and 7CE3 expression patterns in diencephalon and hindbrain are in agreement with the expression sites observed with the murine elements in reporter transgenic mice . However , we found no evidence for 7CE1 driven expression in the eye , or for consistent ectopic activity in the heart for 7CE2 as found in transgenic mice previously [23] . Next we examined reporter expression driven by the full intron 7 sequences from the Pax6 gene duplicates of zebrafish and medaka . We found that zebrafish Pax6 . 1a intron 7 ( Dr6 . 1a-int7 ) drives strong reporter expression in the hindbrain and diencephalon of transgenic fish , but again no consistent expression was observed in the eyes ( Figure 2H , 2J , 2K , 2L , 2N , 2O ) . Reporter expression driven by Pax6 . 1b full intron 7 ( Dr6 . 1b-int7 ) is seen in the hindbrain only ( Figure 2I , 2J , 2K , 2M , 2N , 2O ) . The fluorescence in the fin buds seen in Figure 2M , 2N , 2O is due to the site of integration and was not observed in other transgenic fish . The use of a dual fluorescence reporter system allows direct comparison of the expression patterns of two constructs in the same transgenic fish . Close examination of the reporter fluorescence patterns in the hindbrain of zebrafish transgenic for both the Pax6 . 1a full intron 7 and Pax6 . 1b full intron 7 constructs indicates that while the intron 7 sequences from the zebrafish Pax6 . 1a and Pax6 . 1b loci both drive expression in the hindbrain , the patterns are not fully overlapping . The zebrafish Pax6 . 1a region drives strong expression throughout the width of the hindbrain neural tube , while expression driven by the Pax6 . 1b region is more strongly concentrated along the midline . Furthermore , Pax6 . 1b intron 7 driven expression extends along the length of the neural tube from the hindbrain towards the caudal end , while Pax6 . 1a intron 7 driven expression is strong in the hindbrain segment but diminishes in level more caudally ( Figure 2J , 2N , 2O ) . Alignment of the full zebrafish and medaka intron 7 sequences indicates conservation of the 7CE2 and 7CE3 elements in the medaka Pax6 . 1 locus and a lack of conservation in the medaka Pax6 . 3 locus ( Figure 2A ) . We analyzed reporter expression patterns for the medaka intron 7 constructs from both loci in transgenic zebrafish . Reporter fluorescence driven by medaka Pax6 . 1 intron 7 ( Ol6 . 1-int7 ) was seen in hindbrain and diencephalon in a pattern that closely overlapped with zebrafish Pax6 . 1 intron 7 ( Figure 2P , 2R ) . Next we assayed reporter expression driven by medaka Pax6 . 3 intron 7 . Surprisingly , while having no conservation to the intron 7 sequences of the tetrapod or teleost Pax6 . 1 genes , Ol6 . 3-int7 consistently elicited reporter expression in the eyes of transgenic zebrafish . The retinal expression driven by Ol6 . 3-int7 correlates with the Pax6 . 3 RNA in situ signal in the eye of early medaka embryos , though it extends more anteriorly as well ( Figure 2Q , 2R , 2S ) . In later stage embryos reporter fluorescence was also seen in the lens . As sequence alignment had shown the presence of a Pax6 . 3 loci specific conserved element in intron 7 ( Figure 2B ) , we made transgenic zebrafish with the medaka Pax6 . 3 7CE element on its own , and again observed reporter expression in the eye ( Figure 2S ) , suggesting this Pax6 . 3 locus-specific CNE drives Pax6 . 3 expression in the eye . The regulated expression of Pax6 in mammals depends on a wide genomic domain containing a large number of cis-regulatory elements [22]–[28] . Several of these are located at large distances from the promoters and coding region of the gene [24] , [25] , [26] . The distant downstream region in particular has been shown to be essential for Pax6 expression as its heterozygous removal through deletion or translocation leads to the eye malformation aniridia in human patients [30] , [31] , [25] , [64] . Alignments of the wider Pax6 locus between mammalian and fish Pax6 . 1 loci show conservation of most proximal CNEs , but absence of many of the distal ones in fish . We considered whether the absence of clear sequence conservation in teleost fish at the relative position of a conserved element in tetrapods would indicate the loss of that element in fish , or the gain of that element in the tetrapod lineage . To help distinguish between these possibilities we set out to obtain an outgroup for comparative studies . The elephant shark is a cartilaginous fish with a relatively small genome , situated at the base of the jawed vertebrate lineage , having split off from the bony vertebrate lineage before the split between the ray-finned fish and tetrapods [65] . We searched the 1 . 4× coverage sequence of the elephant shark genome [66] for the Pax6 gene by BLAST . To our surprise the search identified two scaffolds each containing a different Pax6 fragment . PCR primers were designed for these fragments and used to identify positive BAC clones ( 23H6 and 37E6 ) from a genomic BAC library . After complete sequencing the BAC clones were found to encode two different Pax6 genes belonging to separate gene loci ( Figure 3A ) . The first elephant shark Pax6 ( hereafter referred to as Pax6 . 1 ) gene is highly homologous to the mammalian Pax6 gene , both in terms of gene structure and protein conservation ( Figure 3B , 3C ) . The second elephant shark Pax6 gene lacks the N-terminal exons of the canonical Pax6 gene and encodes a Pax6 protein lacking the paired-box DNA-binding domain ( Figure 3B , Figure S2 ) . We have termed this novel paired-less Pax6 gene as Pax6 . 2 . We next used the genomic sequence to design probes to rescreen our BAC library and walk outward from the Pax6-containing BACs . In total we obtained 477 kb of genomic sequence for the Pax6 . 1 locus and 156 kb of sequence for the Pax6 . 2 locus . A number of flanking genes were present in the BAC contigs ( Figure 3A ) and allowed analysis of synteny around the genes . Synteny around the elephant shark Pax6 . 1 gene is fully conserved to the human PAX6 locus , with all genes present in our BAC contig found in equivalent positions to their order in the mammalian locus ( Figure 3A , Figure 7B ) , clearly indicating a common ancestry of elephant shark Pax6 . 1 and mammalian Pax6 . The elephant shark Pax6 . 2 gene is adjacent to a reticulocalbin gene ( Rcn3 ) , but none of the other genes in the Pax6 . 2 locus is syntenic with the mammalian Pax6 locus ( Figure 3A , Figure 7D ) . Next we looked for tissue-specific expression of elephant shark Pax6 . 1 and Pax6 . 2 . rtPCR analysis using RNA from 13 different adult elephant shark tissues revealed expression of Pax6 . 1 in brain , eye and pancreas , with a weaker signal in intestine , in accordance with the expression of Pax6 . 1 in other organisms . Elephant shark Pax6 . 2 has a more limited expression in the eye and kidney ( Figure 3D ) . In mammals a paired-less Pax6 protein isoform , equivalent to the elephant shark Pax6 . 2-encoded protein , is produced from an internal promoter ( Pα ) in intron 4 of the single Pax6 gene [38] . To determine whether the existence of the Pax6 . 2 gene in elephant shark would be to act as substitute for the internal transcript of the mammalian gene ( or vice versa ) we investigated whether a similar α-transcript is also produced from the elephant shark Pax6 . 1 gene . We found an elephant shark Pax6 . 1α transcript in the brain and eye , but not in pancreas ( Figure 3E ) . While the expression of Pax6 . 2 in the eye is unsurprising for a Pax6 homolog , it is intriguing to see expression in the kidney , suggesting a novel function has been acquired by elephant shark Pax6 . 2 in this tissue . Multispecies sequence alignments with the elephant shark Pax6 . 1 genomic sequence reveal a large number of highly conserved non-coding elements in the locus . In accordance with a general observation [57] the number and conservation level of non-coding elements around Pax6 is significantly higher when comparing the elephant shark Pax6 . 1 and mammalian Pax6 locus , than when either is compared to the teleost Pax6 . 1 loci . In particular , clear conservation with elephant shark is observed for several mammalian long-range CNEs that appear absent in teleosts , both in the distal upstream and downstream regions , indicating these are ancient non-coding elements that have been secondarily lost in teleosts ( Figure 3F ) . We focussed on the region upstream of Pax6 . As all extragenic aniridia patient breakpoints identified so far disrupt the Pax6 downstream region [32] , [67] , regulatory activity in the upstream region has remained poorly investigated . Comparative sequence analysis between mammals and the elephant shark Pax6 . 1 locus reveals the presence of a number of long-range CNEs in this region . Many of these CNEs are not found in teleosts , and are therefore candidate Pax6 enhancers that have been lost in fish . Analysis of these CNEs will be described elsewhere . Here we characterize one element of particularly prominent sequence conservation , located approximately 200 kb upstream of human Pax6 , which has been named E-200 . The E-200 element displays strong sequence conservation between elephant shark and human , but is also detected in the Pax6 . 1 loci of several teleosts . Moreover , in fugu and stickleback a low level of sequence conservation is also seen in the Pax6 . 3 loci ( Figure 4A , Figure S3 ) . The location of the element upstream of Pax6 , between Pax6 and Rcn1 , suggests Pax6 as its most likely target gene , but synteny conservation around the Pax6 . 1 locus leaves the possibility that other genes in the region , notably Wt1 and Rcn1 , might be the actual targets . The conservation to several fish duplicate loci provides an opportunity to check linkage between the element and these genes . We found that in all gene loci containing the E-200 element , it was linked to Pax6 , while linkage to Wt1 or Rcn1 was only found where Pax6 and Wt1 or Rcn1 are both present ( not shown ) . To determine the function of this element we first made transgenic zebrafish , using the human element . We observed expression of the fluorescent reporter in the olfactory bulbs , olfactory tracts and the hindbrain regions of transgenic embryos ( Figure 4B–4G ) . Next we generated transgenic mice with the human E-200 element . At early developmental stages ( E9 . 5–E11 . 5 ) no consistent staining pattern was seen . From E12 . 5 expression appeared in the olfactory tract regions and the upper rhombic lip of transgenic mice ( 4 expressing/10 total transgenic ) . The staining in the eye in Figure 4I was not consistent between all expressing lines and is most likely due to site of integration . By E15 . 5 expression was found around the olfactory bulbs , in the lateral olfactory tracts ( LOTs ) and started to appear in the cerebellum ( Figure 4J ) . At E17 . 5 strong staining was seen in the cerebellum , as well as around the olfactory bulbs and LOTs . Staining was also observed in the precerebellar neuroepithelium ( PCN ) , migratory streams and precerebellar nuclei ( Figure 4K–4M ) . The E-200 element is a long-range enhancer located around 200 kb upstream of the PAX6 P0 promoter . It is not present on the human YAC that was used in previous reporter transgenic studies on the long range regulation of PAX6 [24] . Reporter fluorescence in the cerebellum of all transgenic lines carrying the YAC ( Figure 4O , 4P ) is weak or absent compared to the expected level as demonstrated by the fluorescence from a targeted insertion of YFP into the endogenous Pax6 gene ( Figure 4N; Kleinjan et al . in preparation ) . This suggests the presence of the long-range E-200 element is required to achieve appropriate expression of Pax6 in the cerebellum . In contrast , fluorescence in other sites of E-200 activity is not noticeably lower in the YAC transgenics , suggesting sufficient redundancy of cis-regulatory activity in these tissues ( Figure 4N–4P ) . The importance of the E-200 enhancer for cerebellar expression is in accordance with the conservation of this ancient enhancer linked to Pax6 since early vertebrate evolution . The elephant shark Pax6 . 1 locus with its high level of sequence homology and synteny conservation to the mammalian Pax6 loci has provided insight into the ancient history of the Pax6 cis-regulatory domain . In addition to the Pax6 . 1 locus , our elephant shark BAC library screening yielded a BAC contig containing a second Pax6 locus . The BACs were fully sequenced to reveal a novel Pax6 homolog lacking the N-terminal exons that encode the paired box in canonical Pax6 isoforms . This second elephant shark Pax6 gene was named Pax6 . 2 . We aligned genomic sequence from the Pax6 . 2 locus with other Pax6 loci to identify putative CNEs in the locus . This revealed one clear CNE with conservation to the Pax6 . 1 locus ( Figure 5A ) . This element is located upstream of the Pax6 . 2 gene but has homology to the intronic neural retina enhancer ( NRE ) located in intron 4 of canonical Pax6 . 1 [27] , [68] . Interestingly , in addition to retinal-specific enhancer activity the NRE element also serves as an internal promoter ( Pα ) in the mouse and zebrafish Pax6 . 1 genes , and transcripts initiated from this promoter give rise to paired-less Pax6 isoforms in these species [38]; [37] . To test whether the elephant shark Pax6 . 2 CNE ( eshark6 . 2NRE ) has enhancer activity we generated a number of mouse transgenic reporter lines with the element driving LacZ expression ( 4 expressing/8 total transgenics ) . Staining was found in the developing retina from E9 . 5 onwards in a pattern that closely resembles the expression of the murine NRE element [27] . No staining is seen at E9 . 5 ( Figure 5B ) . Expression starts at E10 . 5 in two lateral domains on either side of the optic cup ( Figure 5C ) , spreading wider from E11 . 5 ( Figure 5D ) to the full developing retina from E12 . 5 ( Figure 5E ) , and continuing in the retina at E14 . 5 and E17 . 5 ( Figure 5F , 5G ) . To assess the functional equivalence of the conserved NRE elements from the elephant shark Pax6 . 1 and Pax6 . 2 loci , we produced transgenic zebrafish with the CNEs driving GFP and mCherry fluorescent reporter genes . Both CNEs drove a clean and overlapping expression pattern in the retina ( Figure 5H–5J ) . This confirms the elephant shark Pax6 . 1 and Pax6 . 2 NREs as neuroretinal enhancers that derive from an ancestral element that was present before the duplication event that created the elephant shark Pax6 . 1 and Pax6 . 2 loci . The existence of a second , paired-less Pax6 gene in elephant shark suggested two possibilities: a cartilaginous fish-specific duplication event after the split from the bony vertebrate lineage; or an ancient duplication event that occurred in a gnathostome ancestor . We reasoned that if the duplication had occurred in a gnathostome ancestor , we might be able to find orthologs of this paired-less Pax6 gene in some species of bony vertebrates . We therefore searched the genomes of bony vertebrates for additional Pax6 loci with similarities to elephant shark Pax6 . 2 in gene structure , locus synteny and cis-element content . Remarkably we found novel paired-less Pax6 genes in the genomes of frog ( Xenopus tropicalis ) , Anolis lizard and teleost fishes ( zebrafish , stickleback , medaka , and fugu ) . Evidence for the existence of Pax6 . 2 orthologs was also found in cod , sea bass and Nile tilapia ( data not shown ) . Despite extensive searches , no Pax6 . 2 gene was found in birds or mammals . Thus in many fish species three Pax6 genes exist , the canonical Pax6 . 1 as well as the newly identified Pax6 . 2 and re-defined Pax6 . 3 genes . The zebrafish genome also harbors three Pax6 genes , but in this case the trio consists of the fish specific duplicates of canonical Pax6 . 1 ( Pax6 . 1a and Pax6 . 1b [58] , [59] ) and the novel paired-less Pax6 . 2 gene . To visualize the relation between the members of the newly defined Pax6 gene family we generated a phylogenetic tree using the Neighbor Joining method [69] . This phylogenetic tree supports the classification of gnathostome Pax6 genes into three clades , with zebrafish Pax6a and Pax6b both in the Pax6 . 1 clade . The paired-less Pax6 . 2 genes form their own clade and the acanthopterygian Pax6 . 3 genes make up the most distant clade ( Figure 6A ) . Comparison of synteny relationships around the Pax6 family members of different species provides further insight into the divergence of the gene loci . The well known synteny block around the mammalian Pax6 gene is fully conserved in the elephant shark Pax6 . 1 contig . Synteny is also largely conserved in the Pax6 . 1 loci of acanthopterygian fishes , but a subpartitioning of genes is observed at the zebrafish Pax6 . 1a and Pax6 . 1b loci ( Figure 6B ) . In contrast , synteny conservation around the Pax6 . 3 gene in acanthopterygians is limited and only encompasses the adjacent Dnajc24 gene in medaka , fugu and stickleback ( Figure 6C ) . Closer examination of the Dnajc24 genes reveals that conservation between orthologs from the same locus is higher than across loci . In particular , zebrafish Dnajc24 is more related to mammalian Dnajc24 than to medaka or stickleback Dnajc24 . Synteny around the elephant shark Pax6 . 2 locus and the Xenopus , lizard and zebrafish loci provides evidence that they are of common descent . In these species the Pax6 . 2 gene is found in close synteny with Rcn3 ( reticulocalbin 3 ) , Nosip ( nitric oxide synthase interacting protein ) , Prrg2 ( proline rich G-carboxyglutamic acid 2 ) and Cpt1 ( Figure 6D ) . No Pax6 . 2 ortholog was found in the Nosip/Rcn3 locus in birds or mammals ( Figure 6D ) . In acanthopterygian fish species the Pax6 . 2 gene is also absent from the Nosip/Rcn3 locus , but in these species a Pax6 . 2 ortholog is present adjacent to the Mapk7 , Prss22 and Mmp25 genes . The locus also harbors Trpm4 , Irf3 and Prr12 paralogs suggesting a link with the Nosip/Rcn3 locus . This locus is well conserved in zebrafish , except for a lack of Pax6 . 2 . These observations strongly suggest that after the FSGD duplicate copies of the Pax6 . 2 gene ( Pax6 . 2a and Pax6 . 2b ) must have persisted for some time in the basal teleost genome until after the split between the zebrafish and acanthopterygians lineages . Subsequently , one copy of the gene was lost reciprocally from the two loci in zebrafish and the acanthopterygians . In zebrafish , Pax6 . 2a was retained alongside Rcn3 and Nosip , while in acanthopterygians the reciprocal duplicate ( Pax6 . 2b ) was retained in the more derived locus between the Prss22 and Mmp25 genes ( Figure 6D , Figure S4 ) . Having identified a Pax6 . 2 homolog in zebrafish we performed rtPCR for this novel Pax6 gene to check for expression . cDNA was generated from zebrafish embryos covering the first five days post fertilization ( 1–5 dpf ) . rtPCR results show that Pax6 . 2 is expressed in zebrafish embryos at all stages examined . rtPCR for Islet-1 , known to be expressed at these stages was used as control ( Figure 7A ) . Alignment of Pax6 . 2 proteins from various species shows clear homology between the genes , but indicates a higher similarity between zebrafish Pax6 . 2 and the acanthopterygian Pax6 . 2 genes ( Figure 7B ) . To assess the tissue-specific expression pattern of zebrafish Pax6 . 2 we performed RNA in situ hybridization analysis on fixed zebrafish embryos from 1 dpf to 5 dpf . The staining pattern reveals Pax6 . 2 to have a highly restricted expression . At 24 hpf staining is seen more widely in the head region of embryos ( Figure 7C ) . The expression becomes limited to the developing retinae only from the next stages examined ( 48 hpf to 5 dpf ) ( Figure 7D , 7G–7I ) . We used Optical Projection Tomography ( OPT , [70] ) to visualize the in situ expression pattern at 2 dpf , which confirmed the restricted expression of Pax6 . 2 in the retina only ( Figure 7E , 7F , Video S1 ) , where it appears limited to the inner nuclear layer , potentially marking the amacrine cells . Finally we performed morpholino knock-down experiments to investigate the potential function of Pax6 . 2 . Injections of a Pax6 . 2 morpholino into zebrafish oocytes resulted in zebrafish embryos with relatively smaller eyes compared to embryos injected with a control morpholino ( Figure 7J ) . To quantify this observation we titrated the morpholino concentration and repeated the injections with the optimal dose of Pax6 . 2 and control morpholinos . Embryos were fixed at 2 dpf and tested for the presence of Pax6 . 2 transcript by in situ hybridization . Pax6 . 2 ISH signal was unaffected in control morpholino injected embryos . The majority of Pax6 . 2 morpholino injected embryos had completely lost Pax6 . 2 according to ISH signal , while the remainder showed partial ISH signal loss . We measured the eye diameter of Pax6 . 2 morphants relative to total body length of the embryos . A clear deficiency in eye size was seen in the Pax6 . 2 morphants in comparison with control morpholino injected embryos , indicating an essential role for the paired-less Pax6 . 2 protein in eye development ( Figure 7K , Figure S5 ) . Finally , we performed sequence alignments using PipMaker to identify CNEs in the Pax6 . 2 gene loci . A distinct region of sequence homology outside the exons of the gene was found in the upstream regions of zebrafish , stickleback , medaka and fugu ( Figure 8A ) . Conservation of the CNE between zebrafish and the other teleosts is seen despite their origin from reciprocal Pax6 . 2 duplicate loci . A smaller sub-region of the CNE also showed conservation to the elephant shark Pax6 . 2 upstream region . Intriguingly , this short conserved fragment maps to the edge of the elephant shark Pax6 . 2 NRE element , but has no distinguishable homology to the NRE sequence in intron 4 of Pax6 . 1 genes . To examine the putative functional activity of the Pax6 . 2 CNE region , a longer fragment covering the homology region of the teleost CNEs , and a shorter fragment centered around the zebrafish to elephant shark homology region , were cloned from the zebrafish Pax6 . 2 locus and inserted into fluorescence reporter constructs for the production of transgenic fish . Fluorescence was seen in the retinae of transgenic fish at 72 hpf with both the long ( GFP ) and short ( mCherry ) fragments ( Figure 8B ) . In addition the long fragment showed some minor expression in the forebrain region in a subset of transgenics . Fluorescence signal was restricted to the inner nuclear layer ( INL ) , in accordance with the RNA in situ pattern of Pax6 . 2 ( Figure 7G ) . This suggests that sequence divergence at the NRE in separate branches of the Pax6 gene family has led to subtle differences in the spatial detail of its retinal enhancer activity . It confirms the ancient role of the NRE element as a retinal enhancer in the ancestral Pax6 locus . In summary , we have discovered a novel , paired-less Pax6 gene in the genomes of multiple species . In zebrafish Pax6 . 2a is expressed in the inner nuclear layer of the retina and we have identified a conserved enhancer driving this expression pattern .
The genome is a remarkable repository of biological information . Within its sequence it contains not only a complete set of instructions for embryonic development of the organism , maintenance of adult homeostasis and the response to environmental interactions , but also a record of the evolutionary history of its genes and associated sequences . By comparison of genomic sequences from multiple contemporary species of divergent lineages attempts can be made to reconstruct the ontogeny/phylogeny of specific genes and their regulatory landscapes . It is well established that early vertebrate evolution was accompanied by two rounds of whole genome duplications ( 2R ) [44] , while a third round ( 3R ) has occurred later specifically in the teleost lineage of bony fish around 320 million years ago [40] . Duplication events are recognized as powerful drivers of evolutionary change as they provide enhanced opportunity for the subsequent modification or mutation of gene duplicates , and/or the alteration of their cis-regulatory landscapes , while the other copy maintains critical functions under selective pressure [45] , [48] . We have previously shown that divergence of the cis-regulatory landscapes around the duplicate genes of the developmental regulator Pax6 in the zebrafish has led to their subfunctionalization [59] . In this study we demonstrate that duplicate Pax6 loci also exist in other vertebrate species . Unexpectedly , we have uncovered that these duplicates form a diverse family of Pax6 genes that are derived from multiple independent duplication events . These duplications were followed by multiple independent gene losses in separate vertebrate lineages , such that a variable subset of family members has been retained in contemporary vertebrate species . We show that while the genomes of mammals and birds contain only a single Pax6 gene , other species have two ( elephant shark , Xenopus tropicalis , Anolis lizard ) or even three Pax6 genes ( zebrafish , stickleback , medaka , other teleost species ) . The various Pax6 family members are characterized by differences in their protein structure and in the composition of their cis-regulatory landscapes . In mammals a multitude of key functions in development and maintenance of the eye , brain and pancreas are carried out by a single Pax6 gene [10] . A number of variant protein isoforms encoded by this single mammalian gene are thought to implement different , complementary subsets of Pax6 activity [71]–[73] . The canonical Pax6 protein contains two DNA binding domains: an N-terminal paired domain followed by a paired-type homeodomain . A proline-serine-threonine rich transactivation domain is located at the C-terminus [13] , [19] . An alternative isoform , Pax6 ( +5a ) is made by inclusion of an alternatively spliced exon 5a resulting in a 14 amino acid insertion in the paired domain leading to recognition of a different binding sequence [35] . A third isoform , Pax6ΔPD , produced from a transcript initiated at an internal promoter ( Pα ) located in intron 4 of the gene lacks the entire paired domain [27] , [38] . Reporter transgenic studies of a BAC engineered to express dsRed from the Pα promoter have shown that Pax6ΔPD is expressed in a highly restricted expression pattern [36] , [37] . In mouse Pax6ΔPD is found in the retina and olfactory bulbs , while in the zebrafish it is only seen in the amacrine cells in the retina . The role of this isoform is currently unclear . Inspection of the Pax6 genes of several ray-finned fish species indicated that the ability to encode the alternative exon 5a is present only in the Pax6 . 1 genes of the fish species examined . Sequence comparison between the 5a exons from multiple species shows that it is less conserved than the rest of the paired-box , both in amino acid composition and length ( Figure 1A ) , suggesting that the main function of this peptide might be disruption of the paired box , putting less stringency on the actual sequence itself . In contrast , the other Pax6 copies of the teleost species examined completely lack the alternative exon 5a . The exception is zebrafish where both Pax6 duplicates have a well conserved exon 5a . Moreover , the conspicuous sub-partitioning of CNEs between the duplicate zebrafish Pax6a and Pax6b loci is not seen in the multiple gene loci of medaka , stickleback , Tetraodon and pufferfish , where instead the loci are devoid of any recognizable sequence conservation between them outside of the exons of the Pax6b loci , apart from a short conserved fragment at the E-200 cis-element . Thirdly , in zebrafish the ubiquitous Elp4 gene has been retained next to one of the Pax6 copies ( Pax6 . 1b ) while the long-range enhancers of the DRR have mostly been conserved in the other copy ( Pax6 . 1a ) [59] . In the acanthopterygians both the Elp4 gene and the long-range enhancers are found adjacent to the Pax6 . 1 gene , while the other Pax6 duplicate is located in a different synteny region . Taken together these observations strongly suggest that the Pax6 duplicates of zebrafish and those of the other teleosts derive from different duplication events . The near total lack of CNE conservation suggests that the acanthopterygian Pax6 duplicates have a more ancient evolutionary origin [57] , [74] . Based on these observations we propose to refer to the zebrafish duplicates as Pax6 . 1a/b and refer to the acanthopterygian duplicates as Pax6 . 1 and Pax6 . 3 . To gain more insight into the evolutionary origin of the fish Pax6 loci we screened a BAC library from the elephant shark as an outgroup for comparative studies . Contrary to expectation we identified two separate Pax6 loci in this cartilaginous fish , which we designated as Pax6 . 1 and Pax6 . 2 . The elephant shark Pax6 . 1 locus is highly similar to the tetrapod Pax6 locus and the Pax6 . 1 loci of ray-finned fish . In contrast , the second elephant shark Pax6 locus encodes a Pax6 gene lacking the N-terminal exons of the canonical Pax6 and is predicted to produce a Pax6 homolog without the paired domain . It is thus similar to the Pax6ΔPD isoform derived from the internal Pα promoter of mammalian Pax6 . The presence of a separate paired-less Pax6 gene in the elephant shark genome suggested that it might be fulfilling the equivalent role of the Pα-derived mammalian paired-less Pax6 isoform . However , we show that a paired-less isoform is also produced from the elephant shark Pax6 . 1 gene . Nevertheless , persistence of the gene suggests it does serve a unique function and it is possible that its specific expression not only in the eye but also in the kidney accounts for its retention in the elephant shark genome . The identification of two Pax6 gene loci in the elephant shark raised two possibilities: Either the duplication of the Pax6 locus occurred uniquely in the cartilaginous fish lineage after the split from the bony vertebrate lineage , or the duplicate loci had arisen before the split between cartilaginous and bony fish lineages . We resolved this question by looking for potential Pax6 . 2 homologs in non-cartilaginous species , using the genes in synteny with the elephant shark Pax6 . 2 gene in our searches . Sequence analysis of our elephant shark Pax6 . 2 BAC contig revealed the presence of an adjacent reticulocalbin gene , Rcn3 , as well as the genes Nosip , Prrg2 , Cpt1a . A search for loci containing these genes in other vertebrate genomes led us to the identification of novel Pax6 . 2 orthologs in several species , including frog ( Xenopus tropicalis ) , lizard ( Anolis lizard ) and many fish species including medaka , stickleback and zebrafish . This clearly indicates that the duplication that gave rise to the Pax6 . 2 gene must have occurred before the split between cartilaginous and bony fish . Although the presence of a Pax6 . 2 in teleosts means that the gene was present during the FSGD , we could only find a single Pax6 . 2 gene in the fish genomes examined , indicating the second Pax6 . 2 duplicate has been lost . Under the DDC model [46] , [48] non-functionalization of one copy of gene duplicates is often seen for genes with a single function , and accordingly we show by in situ hybridization that Pax6 . 2 has a highly specific expression restricted only to the neuroretina of developing fish embryos . Nevertheless we do find evidence for the original presence of duplicated Pax6 . 2 genes in early teleost fish by comparisons of synteny around the zebrafish Pax6 . 2 locus with synteny around the Pax6 . 2 loci of medaka , stickleback and fugu . While in zebrafish Pax6 . 2 is found in a synteny block with the Nosip and Rcn3 genes in common with the elephant shark , frog and lizard , the gene is located in a different synteny block in medaka , stickleback and fugu . This indicates that reciprocal duplicate copies of the gene were lost in zebrafish versus the acanthopterygian species . Despite being reciprocal duplicates ( which we refer to as Pax6 . 2a for zebrafish and Pax6 . 2b for the acanthopterygians ) , both gene loci share a well conserved CNE in their upstream region that also shows some homology to the elephant shark Pax6 . 2 upstream region . In reporter transgenic zebrafish both the full-length fish CNE and a shorter fragment around the elephant shark-zebrafish conserved region drive highly specific expression in the inner nuclear layer of the retina in accordance with the RNA in situ pattern for Pax6 . 2 . The retention of a Pax6 . 2 gene in multiple species suggests functional importance and our morpholino knock-down experiment in zebrafish embryos demonstrates a role for Pax6 . 2 ( Pax6c ) in eye development . Nevertheless the Pax6 . 2 gene has eventually been lost in the avian and mammalian lineages . It is currently unclear whether this suggests a change in the molecular networks for eye development between species , or redundancy in the availability of a paired-less form of the Pax6 transcription factor . Despite the absence of Pax6 . 2 a paired-less Pax6 isoform is produced in birds and mammals , generated from a transcript initiating at an internal promoter Pα in intron 4 of the canonical Pax6 . 1 gene [37] , [38] . Expression of this paired-less Pax6 . 1 isoform ( pax6ΔPD ) has been shown to be specific to the eye in zebrafish and mouse [38] . However , these alternative ways of producing a paired-less isoform are not mutually exclusive as the Pax6 . 1 paired-less isoform is also produced in zebrafish [37] and elephant shark ( this study ) which have nonetheless retained the Pax6 . 2 gene . The genomic region around mammalian Pax6 contains a large number of cis-regulatory elements [22]–[28] . Functional constraint on these elements imposes a strong demand on the conservation of their sequence , and consequently many cis-regulatory elements can be identified as CNEs . However , significant divergence of regulatory sequence following duplication can occur with or without concomitant changes in expression pattern . In extremis this can result in conservation of functional activity despite the disappearance of recognizable sequence conservation [75] . Our analyses of reporter expression driven by individual CNEs versus the full zebrafish intron 7 sequences show that the regulatory activity residing in the intron is contributed by the 7CE2 and 7CE3 elements . Loss of the conserved sequences of the 7CE2 element from zebrafish Pax6 . 1b intron 7 correlates with absence of expression in the diencephalon , suggesting that regulatory activity is not maintained in the absence of sequence conservation . Curiously no specific expression was observed at the stages examined for the 7CE1 element despite its conservation in both loci , suggesting the 7CE1 CNE must fulfill some other , unknown function . In contrast , analysis of reporter expression driven by intron 7 of medaka Pax6 . 3 in comparison with the patterns directed by the introns 7 of both zebrafish Pax6 . 1a and Pax6 . 1b loci and medaka Pax6 . 1 , suggest that this region does show conservation of functional activity despite lack of sequence conservation . However , our new observations on the more ancient ontogeny of the Pax6 . 1 and Pax6 . 3 loci suggest that most enhancer elements have formed independently in the Pax6 . 1 and Pax6 . 3 loci , and that the presence of enhancers located in similar positions ( e . g . intron 7 ) in the acanthopterygian Pax6 . 1 and Pax6 . 3 loci is most likely coincidental . The independent acquisition of cis-regulatory elements in the Pax6 . 1 and Pax6 . 3 loci , which would be predicted if the duplication of the loci occurred before the large-scale appearance of cis-regulatory elements during the early stages of gnathostome evolution [53] ? ? [74] , is supported by sequence alignments using stickleback Pax6 . 3 as baseline , which reveal a number of Pax6 . 3 loci-specific CNEs in addition to the 7CE ( 6 . 3 ) element as further candidate Pax6 . 3 enhancers that are not found in the Pax6 . 1 loci ( Figure S1 ) . Sequence alignments between the three Pax6 sub-family members support the independent acquisition of most cis-regulatory elements after the WGD events . The large number of CNEs conserved between mammalian and elephant shark Pax6 . 1 loci indicates that the majority of Pax6 . 1 enhancers must have appeared in the timeframe between the WGD and divergence of cartilaginous and bony fish , with few additional cis-elements having appeared since . However , we also show that a limited number of CNEs are present in multiple branches of the Pax6 gene family . Comparisons of the elephant shark Pax6 . 2 locus with multiple Pax6 . 1 loci revealed a single conspicuous CNE . Intriguingly , the homologous element maps to the neuro-retina enhancer ( NRE ) in Pax6 . 1 intron 4 that coincides with the internal Pα promoter [27] . We show that the sequence conservation of this CNE extends to function as reporter expression driven by the elephant shark 6 . 2 NRE element in transgenic mice and zebrafish is very similar to the retinal expression driven by the mouse NRE element [27] . Using transgenic zebrafish we show that both elephant shark 6 . 1NRE and 6 . 2NRE elements drive an identical expression pattern in the neuroretina . This conservation of sequence and function of the NRE indicates the element was already present in the ancestral gene locus before the WGD events that led to separate Pax6 . 1 and Pax6 . 2 genes . Another ancient enhancer that must have been present before the 1R/2R WGD events is located in the region upstream of Pax6 , between the Pax6 and Rcn1 genes . This highly conserved element , E-200 , is present in all Pax6 . 1 loci including the tetrapod , elephant shark Pax6 . 1 and teleost Pax6 . 1 loci . A small central fragment of this element is also conserved in two of the teleost Pax6 . 3 loci , medaka and Tetraodon ( Figure S1 ) , and was subsequently also found in both Pax6 . 1 and Pax6 . 3 loci of the Nile tilapia . It is the only non-coding sequence conserved between the acanthopterygian Pax6 . 3 loci and the fish/mammalian Pax6 . 1 loci . Both mouse and zebrafish reporter transgenesis revealed expression from the E-200 element in the hindbrain/cerebellar region , olfactory bulbs and lateral olfactory tracts . Reporter expression in the cerebellum was of particular interest as we had previously noted that a large YAC reporter transgene was deficient in driving expression in the cerebellum of transgenic mice . As the PAX6 genomic region contained in the YAC does not extend to the E-200 element we propose that the lack of cerebellar expression from the YAC is due to the absence of this element , though further long-range elements could also be involved . The presence of the E-200 CNE near Pax6 . 3 clearly links the element to Pax6 since the Pax6 . 3 loci do not contain Rcn1 or Wt1 . In summary , we demonstrate that the locus for the developmental regulator Pax6 has undergone multiple duplication events , followed by variable divergence or loss of the gene duplicates . Divergences between the loci have affected both the coding region as well as the cis-regulatory landscapes in lineage specific ways , resulting in a family of variant Pax6 genes in vertebrate genomes . The existence of multiple variant Pax6 genes and proteins also occurs in other parts of the animal kingdom . In C . elegans two different classes of mutation , vab-3 and mab-18 , are known to affect different isoforms from the same Pax6 gene . One of these , the mab-18 isoform , encodes a paired-less isoform that causes a male fertility phenotype due to a sensory defect in the male sensory organ [76] . The Drosophila genome contains four Pax6 orthologs , occurring in two sets of adjacent gene pairs . The eyeless and twin-of-eyeless pair encode the canonical Pax6 homologs , whose absence causes the eyeless phenotype [7] , [77] . A second pair of Pax6-like genes , the eyegone and twin-of-eyegone gene pair , have an incomplete paired box and are considered to be the functional equivalent in Drosophila of the mammalian Pax6 ( +5a ) isoform [78] . Based on the phylogenetic relationships of the various Pax6 genes in vertebrates and their conservation of synteny and cis-regulatory domains , we propose the following model to explain the evolution of the family of Pax6 genes in jawed vertebrates ( Figure 9 , Figure S6 ) . The 1R and 2R that occurred in the stem vertebrate lineage gave rise to four copies of Pax6 ( Pax6 . 1 to Pax6 . 4 ) , one of which ( Pax6 . 4 ) was lost before the diversification of gnathostomes . Of the remaining three genes one evolved into the canonical Pax6 ( Pax6 . 1 ) , as represented by the well-studied contemporary mammalian Pax6 locus . The second gene lost its 5′ exons encoding the paired domain and evolved to encode a paired-less form of Pax6 ( Pax6 . 2 ) expressed in a highly restricted pattern in the retina . This gene was subsequently lost independently in the mammalian and chicken lineages . The third copy ( Pax6 . 3 ) was lost independently in the elephant shark lineage and in the common ancestor of tetrapods but retained in the ray-finned fish lineage . The origin of the Pax6 family at the 1R/2R is consistent with the paucity of CNEs between the Pax6 member loci as the WGDs occurred before the rapid and large-scale appearance of cis-regulatory sequences at the base of the jawed vertebrate lineage [53] , [74] . The stem ray-finned fish lineage that diverged from the common ancestor of the tetrapods contained three Pax6 loci ( Pax6 . 1 , Pax6 . 2 and Pax6 . 3 ) . The 3R that occurred in this lineage before the teleost radiation resulted in duplicate copies of each of these gene loci ( Pax6 . 1a/Pax6 . 1b; Pax6 . 2a/Pax6 . 2b; and Pax6 . 3a/Pax6 . 3b ) . Among teleosts , zebrafish retained both copies of canonical Pax6 . 1 due to cis-regulatory subfunctionalization , while the acanthopterygian ancestor lost one of its Pax6 . 1 duplicates , resulting in a single copy of the canonical Pax6 ( Pax6 . 1a ) locus in medaka , stickleback and fugu . Of the duplicate copies of the paired-less form of Pax6 , one copy ( Pax6 . 2a ) was lost in the acanthopterygian ancestor , while the reciprocal copy ( Pax6 . 2b ) was lost in the zebrafish lineage . This has resulted in zebrafish retaining the Pax6 . 2a copy while medaka , stickleback and fugu retaining Pax6 . 2b . In the case of the third Pax6 gene ( Pax6 . 3 ) , one of the two duplicate copies was lost before the divergence of the zebrafish and acanthopterygian lineages , whereas the second copy was lost in the zebrafish lineage after the split from the common ancestor of the acanthopterygians . Thus , no copies of the Pax6 . 3 locus remain in zebrafish , whereas medaka , stickleback and fugu contain only one copy of this gene . At present this model only presents a rough schematic of the progression of the Pax6 gene family through vertebrate evolution , but future availability of whole genome sequences for additional vertebrate species will allow a more detailed model to emerge . The lamprey and hagfish genome sequences in particular could provide useful information on the Pax6 duplications at the 1R and 2R events . In light of the presumed presence of the NRE and E-200 elements in the ancestral , pre-WGD Pax6 locus we made alignments with the amphioxus ( Branchiostoma floridae ) and Ciona Pax6 loci , but no sequence conservation apart from the coding exons was found . Our model highlights the fact that the many pleiotropic functions of the key developmental regulator Pax6 are shared between different members of a family of genes and isoforms in various species , and may be helpful in further dissection of species-specific differences in development and morphological variation . It therefore remains of great interest to continue the analysis of the cis-regulatory landscapes around Pax6 genes from multiple species to trace the time-frame of acquisition of their cis-regulatory hardwiring and link the presence and divergence of enhancer elements with differences in expression patterns and in anatomical and developmental features .
All mouse experiments were approved by the University of Edinburgh ethical committee ( TR-11-08 ) and performed under UK Home Office license number PPL 60/3785 . Genomic sequences were collected from Ensembl release 65 , December 2011 [79] for these species: Human GRCh37 assembly ( February 2009 ) , Zebrafish Zv9 ( Apr 2010 ) , Medaka HdrR ( Oct 2005 ) , Tetraodon TETRAODON 8 . 0 ( Mar 2007 ) , Stickleback BROAD S1 ( Feb 2006 ) , Fugu FUGU 4 . 0 ( Jun 2005 ) . Sequences were manipulated using programs from the EMBOSS package [80] . Where necessary , missing regions of interest were incorporated following Blast searches [81] using human or fish Pax6 sequences . Ensembl gene annotation and protein predictions were used , in some cases supplemented with manual annotation using Genewise [82] for gene prediction from genomic sequence , with human or fish Pax6 protein as template . Other sources of information ( proteins , ESTs ) were used to further refine gene predictions and search for small exons , including exon 5a and 5′ non-coding exons . Protein sequences were aligned with the CLUSTALW program [83] and edited and displayed using the Genedoc software www . psc . edu/biomed/genedoc [84] . Genomic sequences were aligned , annotated and displayed using the PipMaker tools ( http://bio . cse . psu . edu/pipmaker/ ) [62] . Evolutionary sequence comparison of the elephant shark Pax6 loci with other species was prepared using the ‘glocal’ alignment program SLAGAN [85] with a window size of 100 bp and a minimal sequence identity of 70% and visualized using VISTA [86] . A neighbour-joining ( NJ ) tree for the Pax6 protein alignment was generated using MEGA ( version 5 . 0 . 5; http://www . megasoftware . net/ ) [87] . A Poisson substitution model was used for distance calculation and 1000 bootstrap replicates were used for node support . The tree was viewed and edited using TreeView ver . 1 . 6 . 6 [88] . The DNA prepared from 92 , 160 clones of an elephant shark BAC library ( IMCB_Eshark BAC library; unpublished ) were pooled in three dimensions and used for identifying BAC clones by three-step PCR screening . The 1 . 4× coverage sequence of the elephant shark genome [66] was searched for the Pax6 gene by BLAST . The search identified two scaffolds each containing a different Pax6 fragment . PCR primers were designed for these fragments and used to identify positive BAC clones ( 23H6 and 37E6 ) . These BACs were sequenced completely . BACs overlapping these seed-BACs were identified by PCR screening and sequenced completely . Altogether , four BACs were sequenced to obtain the sequence of Pax6 . 1 locus ( 200B18 , 50G15 , 23H6 and 108J23 ) ( GenBank JX135563 ) while two BACs were sequenced for the Pax6 . 2 locus ( 87E22 and 37E6 ) ( GenBank JX135564 ) . BAC clones were sequenced using the standard shotgun sequencing method and gaps were filled by PCR amplification and primer walking . Sequencing was done using the BigDye Terminator Cycle Sequencing Kit ( Applied Biosystems , USA ) . Sequences were processed and assembled using Phred-Phrap [89] and Consed [90] . Repetitive sequences were identified and masked using CENSOR at default settings [91] . Protein-coding genes were predicted using a combination of ab initio ( e . g . FGENESH ) and homology-based methods . Sequences for the human , chicken , lizard , Xenopus and zebrafish Pax6 loci and genes were extracted from the UCSC Browser ( http://genome . ucsc . edu/ ) . RT–PCR was performed using primers for Pax6 . 1 and Pax6 . 2 exons designed to encompass at least one intron . cDNA from 13 different tissues of elephant shark ( brain , eye , gills , heart , kidney , liver , muscle , ovary , pancreas , spleen , intestine , testis and uterus ) were used as template . Actin was amplified as a control to check for the quality of cDNA . The cycling conditions were 95°C for 2 mins , followed by 35 cycles of 95°C for 30 secs , 60°C for 30 secs and 72°C for 2 mins . 5′RACE was performed using the SMART cDNA amplification kit ( BD Clontech , USA ) and Advantage 2 PCR enzyme mix ( BD Clontech , USA ) . The RACE products were sequenced either directly or after cloning into modified pBluescript . CNEs selected for analysis in transgenic reporter assays were cloned by PCR amplification of the fragment containing the CNE plus flanking sequence from genomic DNA using Phusion high-fidelity polymerase ( NEB ) . attB4 and attB1r sequences were included in the PCR primers for use with the Gateway recombination cloning system ( Invitrogen ) . For zebrafish transgenic studies the amplified fragment was first cloned into the Gateway pP4P1r entry vector and sequenced using M13 forward and reverse primers for verification . Test elements in the pP4P1r vector were combined with a pDONR221 construct containing either a gata2 promoter-eGFP-polyA or a gata2 promoter-mCherry-polyA cassette , and recombined into a destination vector with a Gateway R4-R2 cassette flanked by Tol2 recombination sites [59] , [92] , [93] . For mouse transgenic LacZ reporter studies the selected fragments were PCR amplified using primers containing NotI and SalI restriction sites and cloned into pGEM-T Easy vector ( Promega ) . Fragments were then transferred into the hsp68-LacZ containing p610+ vector using the NotI and SalI sites . For the elephant shark 6 . 2 NRE fragment the selected regions were amplified using primers containing Gateway compatible attB4 and attB1r sites , and cloned directly into an hsp68-LacZ vector containing a P4-P1r entry cassette . The forward primer also included an AscI site to allow subsequent micro-injection fragment isolation . The following primers were used: Medaka pax6 . 1 intron 7: 5′-GCCCAACCAAGGTGAGCCTC-3′ and 5′-TTGGCAGCCATCTGAAGGTG Medaka pax6 . 3 intron 7: 5′-GCTGGGACCACACTCTCCTCCA-3′ and 5′-TGGAGTTCACCGAGATGCCGT-3′ Zebrafish pax6 . 1a intron7: 5′-CCAATCAAGGTATGGCTGT-3′ and 5′-TGACTGTTGGCAACCATCTGA-3′ Zebrafish pax6 . 1b intron7: 5′-CCAAATCAAGGTGAGACAGCCA-3′ and 5′-TCCTGTTGCTGGCAACCGTCT-3′ Zebrafish pax6 . 1a 7CE1: 5′-CCAATCAAGGTATGGCTGT-3′ and 5′-GTTATGCCCTAAATCAAAGGCGT-3′ Zebrafish pax6 . 1a 7CE2: 5′-GTCCATAGGCTGTTAGTTTGGGT-3′ and 5′-ACTGCACGTATTTCCCCCTAG-3′ Zebrafish pax6 . 1a 7CE3: 5′-GCCACTGGTGTCTAACAAC-3′ and 5′-TTACAGCACTTTTCAGGCC-3′ Medaka pax6 . 1 7CE2: 5′-TGGCTCCAATCCCCGTTATAGGA-3′ and 5′-AAGGATGCCGCATGTGAGGGT-3′ Elephant shark pax6 . 1 7CE2: 5′-CTTCGACCATCAGCTGACAG-3′ and 5′-TCGGTCACTTTATGCCCACA-3′ Medaka pax6 . 3 7CE: 5′-GAAATGTGACAGCTGACAGGGT-3′ and 5′-CTTCATTTGGGGACTGAACAG-3′ Cm6 . 2NRE into p610+ and Tol2: Cm6 . 2NRE forw: 5′-attB4-gcctcgcttcaaggccgatct-3′ Cm6 . 2NRE rev: 5′-attB1r-gccgtgcgggataaggtaga Cm6 . 1 NRE into Tol2: Cm6 . 1NRE forw: 5′-attB4-gctagaaccttcgcatctg Cm6 . 2NRE rev: 5′-attB1r-gcatggcaaggctgcatgc Zebrafish pax6 . 2_CNE1 into Tol2: Drpax6 . 2_CNE1 forw: 5′-attB4-CCCTCATCCTCCCTCACATCT Drpax6 . 2_CNE1 rev_short:5′-attB1r-TGTGACGTTGCGAGTGCGT Drpax6 . 2_CNE1 rev_long:5′-attB1r-GCTCATACTGCGGTCCCAGA Production of transgenic mice by micro-injection into mouse oocytes was performed according to standard procedures . For analysis , embryos were collected at the appropriate stages , washed in PBS and fixed for 1 hour in a solution of 1% formaldehyde; 0 . 2% glutaraldehyde; 2 mM MgCl2; 5 mM EGTA and 0 . 02% NP-40 in PBS . After fixation the embryos were washed in PBS containing 0 . 02% NP-40 , before being stained for several hours at 37°C in the dark in a solution containing 5 mM K3Fe ( CN ) 6; 5 mM K4Fe ( CN ) 6 . 3H2O; 2 mM MgCl2; 0 . 01% sodium deoxycholate; 0 . 02% NP-40 and 0 . 1% 5-bromo-4-chloro-3-indolyl-β-D-galactopyranoside ( X-gal ) . Embryos were photographed on a Leica MZ FLIII Microscope fitted with a Hamamatsu Orca-ER digital camera and a CRI micro-color filter . Table S1 contains details of the number of independent transgenic lines analysed and the observed sites of reporter gene expression . Mapping of adjacent genes onto Pax6 synteny regions was done using the Ensembl and UCSC genome browsers , with additional information obtained using the Genomicus website v66 . 01 [79] ( http://www . dyogen . ens . fr/genomicus-66 . 01/cgi-bin/search . pl ) . Zebrafish Pax6 . 2 in Ensembl: zgc193504; Ensembl identifier: ENSDARG00000053364; Location chromosome 3: 32 , 694 , 591–32 , 702 , 244 . RNA was isolated from pooled wild type zebrafish embryos from 1 dpf to 5 dpf using Tri-Reagent ( Sigma ) . rtPCR was performed using Superscript III . PCR primers generating a fragment spanning several introns were designed for Pax6 . 2 and Isl1 . rtPCR primers for zebrafish Pax6 . 2: forw: 5′-CTCAATGCACAGTCGGAGTG-3′ rev: 5′-TGCTGATTGAAGCTCTGCTGGT-3′ rtPCR primers for zebrafish Isl1: islet1_fw CGGCGCACATATTCACATAC islet1_rv TAAGCTTTAATACGACTCACTATAGGGAGAACGGACACGAACACATGAAA RNA in situ hybridization on fish embryos was performed as previously described [94] . The medaka Pax6 . 1 RNA in situ probe was generated from the cDNA clone AJ000938 [63]; The RNA in situ probe for medaka Pax6 . 3 was generated from EST clone MF01SSA182E11 ( Genbank BJ013007 and BJ027294 ) . The RNA in situ probe for zebrafish Pax6 . 2 was generated from the cDNA with primers: T7: 5′-TAATACGACTCACTATAGGTGCTGATTGAAGCTCTGCTGGT-3′ 5′-CTCAATGCACAGTCGGAGTG-3′ A zebrafish Pax6 . 2 antisense morpholino oligonucleotide was obtained from Gene Tools , LLC , with the following sequence: 5′ GTCATACATCAAATGTCACCTGTGA 3′ , directed against the translation start site of the gene . As control we used the Gene ToolsLLC standard negative control morpholino: 5′ CCTCTTACCTCAGTTACAATTTATA 3′ . The morpholinos were injected into 1 to 2-cell stage of at least 100 embryos to deliver an approximate amount of 2 . 5 ng per embryo . Zebrafish were maintained in a recirculating water system according to standard protocol [95] . Embryos were obtained by breeding adult fish of standard stains ( AB and WIK ) and raised at 28 . 5°C as described [95] . Embryos were staged by hours post fertilization ( hpf ) as described [96] . Reporter plasmids were isolated using Qiagen miniprep columns and were given extra purification via a Qiagen PCR purification column ( Qiagen ) , and diluted to 50 ng/microliter with DNAse/RNAse free water . tol2 transposase RNA was synthesized from a NotI-linearized pCS2-TP plasmid [93] using the SP6 mMessage mMachine kit ( Ambion ) , and similarly diluted to 50 ng/microliter . Equal volumes of the reporter construct ( s ) and the transposase RNA were mixed immediately prior to injections to give an injection solution containing 25 ng/microliter of DNA and 25 ng/microliter of transposase RNA . 1–2 nl of the solution was micro-injected per embryo into the cytoplasm of 200 embryos at the 1- to 2-cell stage . Embryos were screened for mosaic fluorescence at 1–5 days post-fertilization ( dpf ) and raised to adulthood . Germline transmission was identified by mating of sexually mature adults to wild-type fish and examining their progeny for fluorescence . Positive embryos were raised to adulthood and lines were maintained by outcrossing . Fish showing the best representative expression pattern for each construct were selected for confocal imaging . A summary table detailing numbers of independent lines analysed for each construct and their expression sites is included in Table S1 . Embryos for imaging were treated with 0 . 003% PTU ( 1-phenyl 2-thio-urea ) from 24 hpf to prevent pigmentation . Embryos selected for imaging were anaesthetised with tricaine and mounted in 1% low-melting agarose . Images were taken on a Zeiss LSM510 confocal microscope and processed using Fiji software . | Pax6 is a highly conserved transcription factor with key roles in eye , brain , pancreas , and olfactory system development . In mammals multiple Pax6 isoforms are encoded by a single Pax6 gene , embedded within a complex regulatory landscape . Here we provide evidence for the presence of multiple Pax6 loci in other vertebrate species . We show that two Pax6 genes ( Pax6 . 1 and Pax6 . 2 ) are present in the genome of elephant shark ( a cartilaginous fish ) . Pax6 . 1 is highly similar to mammalian Pax6 in terms of structure of the gene locus , protein sequence , and expression pattern; whereas the second gene , Pax6 . 2 , codes for a protein lacking the paired domain . We identify orthologs of Pax6 . 2 in other vertebrate genomes , such as lizard , Xenopus , and teleost fishes , and show it is important for eye development in zebrafish . Additionally , we have characterised a third Pax6 ( Pax6 . 3 ) present only in some teleost fishes . Phylogenetic analyses indicate that the evolutionary history of the Pax6 gene family in vertebrates is a result of ancient duplications followed by independent gene losses in different lineages . Sequence comparison of the cis-regulatory landscapes around the genes has led to the identification of novel Pax6 enhancers that provide a link between the diverged Pax6 family members . | [
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"functio... | 2013 | Sequencing of Pax6 Loci from the Elephant Shark Reveals a Family of Pax6 Genes in Vertebrate Genomes, Forged by Ancient Duplications and Divergences |
Skin epithelial stem cells operate within a complex signaling milieu that orchestrates their lifetime regenerative properties . The question of whether and how immune cells impact on these stem cells within their niche is not well understood . Here we show that skin-resident macrophages decrease in number because of apoptosis before the onset of epithelial hair follicle stem cell activation during the murine hair cycle . This process is linked to distinct gene expression , including Wnt transcription . Interestingly , by mimicking this event through the selective induction of macrophage apoptosis in early telogen , we identify a novel involvement of macrophages in stem cell activation in vivo . Importantly , the macrophage-specific pharmacological inhibition of Wnt production delays hair follicle growth . Thus , perifollicular macrophages contribute to the activation of skin epithelial stem cells as a novel , additional cue that regulates their regenerative activity . This finding may have translational implications for skin repair , inflammatory skin diseases and cancer .
Epithelial homeostasis relies on the capability of epithelium to self-renew over a lifetime because of the presence of diverse reservoirs of stem cells ( SCs ) . These reside in anatomically distinct niches that provide them with a specialized microenvironment , which are becoming increasingly well-defined in the largest and most accessible mammalian organ , the skin [1] . Besides its epithelial components , the skin contains both resident and migratory immune cell populations , whose major role is mainly attributed to its function as a central line of defense for fighting infection , as well as promoting skin repair upon injury and external assaults [2] . During wound repair , coordinated and carefully balanced crosstalk between epithelial and inflammatory cells occurs to restore skin homeostasis [2]–[4] . Failure in this communication is associated with major wound healing defects , inflammatory disorders , and malignant transformation [5] , [6] . The exact functional relationship of specific immune cell populations in the activation of epithelial progenitor cells in adult mammalian skin is , however , still poorly defined . Moreover , how resident immunocytes interact with epithelial SCs in vivo is not fully understood . Such interactions can be optimally studied in the best-characterized reservoir of adult skin epithelial SCs , the hair follicle ( HF ) bulge [7] , [8] . The bulge is located around the level of insertion of the arrector pili muscle into the HF epithelium below the sebaceous gland , enjoys a relative immune privilege [9]–[11] , and is ensheathed by a specialized mesenchyme , the connective tissue sheath ( CTS ) [12]–[14] , which is richly endowed with macrophages and mast cells that home into this skin compartment early during HF development [15] . Bulge SCs ( HF-SCs ) are the essential prerequisite for the cyclic regeneration of HFs , during which it switches from phases of growth ( anagen ) via regression ( catagen ) to relative quiescence ( telogen ) [7] , [16] . HF entry into anagen requires the activation of HF-SCs and of progenitors located in the secondary hair germ ( HG ) that expand to give rise to a new anagen HF [17]–[19] . Important for the activation of HF-SCs at the end of telogen is the close and dynamic interaction with a specialized condensate of inductive fibroblasts , the dermal papilla ( dp ) , which provides a specialized microenvironment [14] . Recently , other intercellular interactions within the HF niche and with its mesenchymal environment have become appreciated as key elements of HF-SC activation [12] , [13] . These elements include signals in the niche itself that arise from the HF-SC progeny [20] , and signals of the tissue macroenvironment arising from dermal fibroblasts , adipocytes [21] and preadipocytes [22] , and nerve fibers [23] . However , despite their prominence in the HF mesenchyme , including in the peri-bulge CTS [15] , the role of perifollicular macrophages in HF-associated epithelial-mesenchymal interactions has remained unclear . Recent studies have contributed greatly to our understanding of the key role of two major signaling pathways in the intrinsic activation of HF-SCs and the entry of HF into anagen . These pathways are the stimulatory Wnt/β-catenin signaling pathway [24] , [25] , and the inhibitory bone morphogenetic protein ( BMP ) signals arising from the dp that uphold HF-SCs in a quiescent state [24] , [25] . Interestingly , these signals are also exploited by the skin macroenvironment , which generates synchronized cyclic waves of BMP activity that decline when Wnt expression waves arise , thereby controlling HF cycling . These cyclic waves respectively subdivide telogen into refractory and competent phases for HF regeneration [21] . Remarkably , HF growth stimulatory signals can also be propagated during the transition from telogen to anagen via neighboring HFs [26] . Whether immune cells located in the perifollicular macroenviroment , such as macrophages , contribute to the establishment of the refractory and competent phases of telogen , or in the propagation of the HF growth stimulatory cues is much less clear . It is now firmly established that mature HFs have a distinctive immune system [11] , [27] . Indeed , both the HF bulb and the HF bulge represent areas of immune privilege [9] , [11] , [28] , whose collapse gives rise to distinct inflammatory hair loss disorders [10] , [29] . Interestingly , HFs are constantly in close interaction with immune cells , namely intraepithelially located T lymphocytes and Langerhans cells , and macrophages and mast cells located in the HF's CTS [15] , [30]–[32] . The HF epithelium also may serve as portal for the entry of immune cells into the epidermis , such as dendritic cells [33] , as a habitat for both fully functional and immature Langerhans cells [34] and as a potent source of chemokines that regulate dendritic cell trafficking in the skin [33] . Prior studies have shown that intracutaneous immune cell populations fluctuate substantially in number and activities during synchronized HF cycling [27] , [33] , [35]–[41] . While it is known that this fluctuation results in major changes in skin immune responses ( e . g . , inhibition of contact hypersensitivity in anagen skin [35] ) , and in the intracutaneous signaling milieu for various immunomodulatory cytokines and chemokines [33] , [42] , it is insufficiently understood whether these hair cycle-associated changes are a consequence of HF cycling or if they actively regulate the latter and/or the hair cycle-associated activity of HF-SCs . For example , perifollicular mast cells and macrophages have been implicated in the regulation of HF growth through anagen and the entry into catagen [15] , [36]–[41] , [43] . Namely , timed release of the catagen-inducing growth factor , Fgf5 , by perifollicular macrophages may regulate the anagen-catagen switch [36] , [44] , while clustering of macrophages around isolated HFs may serve to delete selected pilosebaceous units [30] . Most recently , it has been shown that loss of γδT cells , which are required for HF neogenesis induced upon wounding [4] , results in hair cycling abnormalities [42] . Whereas these studies have implicated immune cells in HF cycling , their role in the spatio-temporal cyclic activation of HF-SCs , specifically in the physiological entry of telogen HFs into anagen , remains to be defined . Using the murine hair cycle as a model system and focusing on macrophages , we have addressed this important , as yet uncharted aspect of HF-immunocyte interactions . These studies define a new role for skin-resident macrophages in the activation of HF-SCs .
To evaluate the association of HF-SC activation with specific populations of skin-resident inflammatory cells , we first performed immunofluorescence analyses in mouse backskin sections isolated from matched areas of defined phases of spontaneous murine HF cycling . These analyses were performed from the telogen through the anagen phase of the first ( Figure S1A ) , and the second postnatal hair cycle ( Figure 1A ) . The telogen phase of the first HF cycle lasts only for 1–2 days , whereas the second telogen starts around postnatal day 44 ( P44 ) and last for 3–4 weeks . Thus , we subdivided the second telogen in three telogen stages , the early telogen stage ( Te , Postnatal day 44 , P44 ) , mid telogen ( Tm , P55 ) , late telogen ( Tl , P69 ) , and included an anagen stage ( AVI , P82 ) according to the classification of Muller Rover [45] , to perform our comparative analyses ( Figure 1A ) . The second telogen corresponded to the refractory and competent telogen phases [21] , as supported by the analysis of BMPs and Wnts transcript levels ( Figure S2 ) . We observed that the number of Langerhans cells ( Langerin ) , mast cells ( toluidine blue ) , and T-lymphocytes ( CD3 ) were not significantly different in these stages ( Figures 1B , S1C , and S1D ) . However , the number of myeloid cells ( F4/80 , CD11b , and Gr1 ) increased at Tm and progressively decreased at Tl before the onset of HF-SC activation as observed by immunofluorescence ( Figure 1B and 1C ) and fluorescence-activated cell sorting ( FACS ) analyses ( Figure S3 ) . This global decrease was observed in the dermis ( no perifollicular ) but also in macrophages located near the distal ( close to the epidermis ) and proximal portion of HFs as Te progresses to anagen ( Figure 1D and 1E ) . Moreover , analyses of skin whole mount stainings and 3-D reconstructions showed that ∼50% of HFs in telogen exhibited F4/80+ cells , and only 10% of HFs displayed dense perifollicular inflammatory cell clusters ( PICCs ) as previously defined ( Figure S4 ) [30] . Interestingly , in the short transition from telogen to anagen of the first postnatal HF cycle , a decrease in F4/80 and CD11b , but not in Gr1 positive cells was also observed ( Figure S1B ) . We also confirmed that through the first anagen phase ( from AIIIa to AVI ) there was an increase in the numbers of these cells , consistent with previous reports [15] , [36] . Since different populations of macrophages reside in skin , we performed flow cytometry ( FACS ) analyses in total skin samples during the second telogen ( Figure 1A ) to obtain a more detailed analysis of their phenotype and number . To analyze the number of F4/80+ cells , mature resident macrophages were gated from either CD11b+ or Gr1+ ( Ly6G+ ) cells ( Figures 1E and S3A ) . This allowed us to differentiate CD11b+Gr1−F4/80+ macrophages ( I′ ) , from the myeloid CD11b−Gr1+F4/80+ population ( II′ ) . These analyses showed that CD11b+F4/80+Gr1− macrophages gradually decreased from Te to Tl , whereas CD11b−F4/80+Gr1+ myeloid cells increased in number at Tm , followed by a significant decrease at Tl ( Figure 1E ) . Of note , no changes were observed in either the number of CD11c+ cells in total murine skin , or of F4/80+ cells present within this dendritic cell population ( Figure S3B ) . Next , we asked whether the observed numeric reduction of macrophages towards the end of telogen and before anagen induction ( Figure 1B and 1E ) was due to macrophage apoptosis . TUNEL analyses of skin sections co-stained with F4/80 revealed the presence of F4/80+/TUNEL+ cells at HF distal , proximal , and no perifollicular regions ( Figures 1F and S1F ) . In addition , TUNEL analyses in FACS-isolated CD11b+Gr1−F4/80+ cells from total skin showed a significant increase in apoptosis , when isolated from skin that progressed from Tm to Tl ( Figure 1F ) , consistent to the subG1 peak observed in their cell cycle profile ( Figure S1G ) . Taken together , these data suggest that the telogen-anagen switch of the hair cycle is associated with an apoptosis-driven reduction of skin-resident macrophages . Our results raised the intriguing hypothesis that the observed decrease in mature skin resident macrophages may be related to HF-SC activation and anagen induction . To probe this possibility and characterize the relevance of macrophages in the activation HF-SCs , we attempt to use inducible LysMCre-diptheria toxin receptor ( DTR ) mice , which express DTR in myeloid cells [46] . After DT administration , myeloid cells are susceptible to ablation . However , although this model is well-characterized under conditions of wound repair [47] , we did not observe the expression of LysM+ resident cells in skin using the reporter mice LysMCre-Katushka under steady state conditions , as compared to the expression in the bone marrow derived macrophages ( BMDMs ) , liver , and spleen ( Figure S5 ) . This observation may be explained by the fact that at least two different lineages of macrophages exist in mice , one derived from hematopoietic SCs , and the other derived from the yolk sac closely associated with epithelial structures [48] . Thus , we turned to chemical targeting via clodronate-induced macrophage apoptosis [49] in early telogen skin , to mimic the reduction in macrophage numbers . We focused on the second HF cycle , which is routinely exploited in hair research to dissect hair cycle-regulatory signals [18] , [24] , [50]–[52] . We performed subcutaneous injections of clodronate-encapsulated liposomes ( CL-lipo ) , which are specifically engulfed by macrophages and induce their apoptosis [49] , [53] . Because of its selectivity , this cell ablation system is widely used to explore the role of macrophages in other systems [54]–[56] . First , empty PKH67-labeled liposomes were subcutaneously injected as controls , and backskins from matched areas were collected to avoid HF regional differences in skin [21] , [52] . The specific uptake of the injected PKH67-liposomes by skin-resident macrophages was confirmed by double immunofluorescence analyses of PKH67 labeled membranes and F4/80 ( Figures 2A and S6A ) . Next , we examined the effectiveness of the treatment at different time points after its administration ( Figure 2B ) , and observed that F4/80+ cell numbers in skin were significantly reduced at T2 and T4 at HF distal , proximal , and no-perifollicular regions ( Figures 2C and S6B ) . TUNEL analyses showed an increase in F4/80+ apoptotic cells starting from T1 ( Figure S6C ) . This reduction was also observed for CD11b+ and Gr1+ cells ( Figure S6D ) . Overall , the final number of resident macrophages was similar to the one at physiological Tm and Tl stages ( Figure 1B ) . We then assessed the effect of experimentally decreasing macrophage numbers at Te on hair growth . Strikingly , histological analyses revealed that as soon as macrophage levels were reduced ( T2 ) , HF entered into anagen ( Figure 2D ) . At T4 , while HFs in control animals were still in telogen ( P52 ) , nearly 100% of the HFs of CL-lipo-treated mice entered into anagen , as shown by quantitative hair cycle histomorphometry ( Figure 2E ) . These differences were phenotypically noticeable by the premature appearance of the hair coat in the previously shaved backskin of CL-lipo-treated mice , when compared with controls ( T5 ) ( Figure 2F ) . Of note , the observed anagen-promoting effects of macrophage reduction in HF growth does not seem to be strain specific , since it can also be observed in another mouse strain in the areas of CL-lipo injection ( Figure S6E and S6F ) . Next we analyzed the effect of experimentally decreasing macrophage numbers on bulge HF-SCs , which are characterized by their slow cycling properties ( label retaining cells [LRCs] ) [17] , [57] , whereas their progeny divides rapidly to expand and migrate [18] , [19] giving rise to the matrix progenitor cells and the generation of fully mature HFs [18] , [19] , [58] . To this end , we performed pulse-chase strategies using doxycycline-regulated keratin 5 ( K5 ) tTA ( TetOff ) -Histone H2B-GFP mice [17] . After finishing the chase at P56 , we treated the mice for two alternate days with CL-lipo and observed a proportion of LRCs outside the bulge when compared to controls ( Figures 3A and S7A ) . Moreover , the precocious entry of HFs into anagen occurred with no obvious alterations in HF differentiation . Immunostaining analyses confirmed the presence of Ki67+ proliferative cells in the hair matrix along with the expression of P-cadherin ( P-cad ) , as well as the distribution of the companion layer marker keratin 6 ( K6 ) and the extracellular matrix protein tenascin C ( TenC ) , all in the expected HF locations ( Figure 3B ) . The expression of K6irs , K34 , GATA3 , and the inner root sheet marker trichohyalin ( AE15 ) was also analyzed in total skin at mRNA level ( Figure 3C ) . Globally , these data suggest that the reduction of macrophages during telogen induces a precocious exiting and differentiation of HF-SCs . As CL-lipo-induced toxicity and inflammation might have generated this effect , we systematically probed this possibility . Since the rate of intraepithelial HF apoptosis is a very sensitive indicator of HF damage ( dystrophy ) [59] , [60] , it is important to note no major signs of apoptosis were observed in epithelial cells compared to controls ( Figure S6G ) . Furthermore , no changes were observed in the number of other immune cells , including T-cells ( CD3 ) , mast cells , and B-cells ( Pax5 ) in skin ( Figure S6D ) , supporting that CL-lipo treatment was macrophage-selective . This was further corroborated by the observation that subcutaneous CL-lipo treatment did not impinge on the number of monocytes and macrophages of bone marrow , spleen , or peripheral blood ( Figure S7B and S7C ) . This finding was in line with the observation that CL-lipo induced neither an increase in the expression of the prototypic pro- and anti-inflammatory cytokines , interleukin-10 ( IL10 ) and -12 ( IL12 ) , respectively , in skin ( Figure S7D ) . In addition , no changes in the expression of the proinflammatory molecule ICAM1 were observed in skin , even after 2 and 4 d post treatment ( T2 and T3 ) ( Figure S7E ) . However , ICAM1 of the HF epithelium increased at late stages upon CL-lipo treatment ( T4 ) , consistent with the documented upregulation of ICAM-1 expression in anagenVI HFs just before their entry into catagen [61] . Due to the recognized fundamental role of Wnt/β-catenin signaling in HF-SC activation and HF growth [24] , [62]–[66] , we next analyzed the distribution of β-catenin after CL-lipo treatment by immunofluorescence . Interestingly , nuclear β-catenin was detected in HFs early after CL-lipo treatment ( T2 ) ( Figure 4A ) . In addition , under the background of TCF/Lef:H2B-GFP transgenic mice [67] , the CL-lipo treatment induced signs of H2B-GFP expression in few CD34+ bulge cells and in the HG at T2 , not observed in Lipo controls ( Figure 4B ) . This level of activation is consistent with physiological levels as previously documented [68] . We also performed RT-PCR analyses in FACS-isolated HF-SCs ( Figure 4C ) and observed an increase in their number and in the relative mRNA expression levels of the Wnt signaling related genes Lef1 [68] , [69] , and mOVO1 [70] and Axin2 [71] starting from T2 , without any changes in the expression levels of the HF-inhibitory proteins BMP2 and BMP4 ( Figure 4D ) [18] , [21] , [25] , [72] . As expected these increases were also observed in total skin at late stages of anagen when the matrix forms and HFs differentiate ( Figure 4E ) . These data support an association between macrophages and the β-catenin/Wnt signaling in the activation of HF-SCs . To obtain mechanistic insight into how macrophages control the activation of HF-SCs under physiological steady-state conditions , we performed microarray analysis of the CD11b+Gr1−F4/80+ skin resident macrophages at physiological Te , Tm , and Tl in order to characterize changes in their gene expression profile as HFs progress from telogen to anagen . Figures 5A and S8A show the results of the comparison between late and early telogen ( Tl/Te ) . Interestingly , genes involved in the regulation of HF-SC behavior were found to be the most upregulated ones in macrophages before the onset of HF-SC activation , among them Wnt7b and Wnt10a ligands that can activate canonical β-catenin/Wnt signaling . Moreover , the expression of pro-apoptotic genes was higher at Tl when compared to Te , consistent with the observed increase in macrophage apoptosis ( Figures 1F , S1F , and S1G ) , correlating apoptosis with the expression of Wnts . In addition , we confirmed that skin resident macrophages are highly heterogeneous . Indeed , immunofluorescence analysis revealed that some macrophages coexpressed markers of both M1/M2 phenotypes , such as iNOS ( M1 ) and Arg1 ( M2 ) , under these uninflamed conditions ( Figure S8B–S8D ) . In total skin , no changes were detected in the mRNA expression of cytokines such as IL10 and IL12a , two key cytokines that are important for the alternative and inflammatory properties of macrophages , respectively ( Figure S8E ) . We next validated the increase in the expression levels of Wnt7b and Wnt10a preceding the onset of anagen . We first performed quantitative reverse transcription ( RT ) -PCR assays in FACS-sorted macrophages isolated from physiological Te , Tm , Tl , and anagen stages . Consistent with the microarray data , the mRNA expression levels of both Wnt7b and Wnt10a increased as HF transitioned from Te to A ( Figure 5B ) . This increase appeared to reflect primarily expression changes within macrophages , since Gr1+ cells did not display any changes in Wnt7b and Wnt10a expression ( Figure S8F ) . Wnt7b mRNA levels were maintained at the beginning of anagen , while Wnt10a levels decreased to ∼50% ( Figure 5B ) . Interestingly , immunofluorescence analyses revealed the presence of clusters of perifollicular macrophages ( Figures 5C and S4 ) , reminiscent of PICCs [30] , and during the progression of telogen these exhibited both Wnt7b and Wnt10a expression in close proximity to the HFs and less pronounced in the no perifollicular zone ( Figure 5D and 5E ) . Although technical limitations in obtaining sufficient macrophage numbers precluded the biochemical analysis of Wnt7b and Wnt10a protein levels in macrophages during these stages , these results demonstrate an intriguing association between macrophage-derived Wnt expression and HF-SC activation . To investigate whether both Wnt7b and Wnt10a can be produced autonomously by macrophages , we turned to in vitro studies . As expected , the in vitro treatment of BMDM with CL-lipo was able to stimulate apoptosis in a large fraction of macrophages ( ∼35% ) . Most interestingly , this resulted in the release of cell-accumulated Wnt7b and Wnt10a into the media ( BMDM conditioned media [CM] ) ( Figure S9A–S9C ) . To further assess the effect of apoptosis on the expression and release of Wnts , we cultured BMDM derived from the LysMCre+/T iDTRKI/KI mice , or control BMDMKI/KI ( Figure S9D ) . DT treatment triggered the apoptosis of LysMCre+/T iDTRKI/KI BMDM , but not control cells ( Figure S9E ) . Surviving cells , apoptotic cells , and their respective supernatants were collected and analyzed by immunoblot . This showed that Wnt7b protein levels in cell lysates slightly increased in apoptotic LysMCre+/T iDTRKI/KI BMDM ( Figure S9E ) . However , both Wnts were increased in the CM when compared to controls ( Figure S9F ) . We then stimulated fresh control BMDM cells with the previously described surviving ( LysMCre+/+ iDTRKI/KI BMDM ) , apoptotic cells ( LysMCre+/T iDTRKI/KI BMDM ) , or their respective CM . The stimulation of fresh BMDM with apoptotic BMDM upregulated the expression of Wnt10a ( Figure S9G ) , whereas no effect in the expression of Wnts was observed upon stimulation with their CM ( Figure S9G ) . Overall , these murine macrophage cell culture data suggest that macrophage apoptosis goes along with the release of Wnts and that close intercellular interactions between macrophages are important for apoptotic macrophages to further stimulate the expression of Wnts of neighboring macrophages . Next , we probed the causal association of macrophages with HF-SC activation in vitro by assessing the effect of the BMDM CM in cultured HF-SC . To this end , we FACS-isolated CD34+K15-GFP+ cells from the backskin of K15-GFP mice ( Figure S10A ) [73] . HF-SCs were cultured and stimulated with CM of BMDM treated with CL-lipo or control liposomes ( Lipo ) ( Figure S10A ) . Consistent with the in vivo data reported above ( Figure 4 ) , treatment of HF-SCs with media conditioned by CL-lipo BMDM significantly and reproducibly induced the expression of canonical Wnt downstream targets in HF-SCs , including CycD1 , Lef1 , and axin2 ( Figure S10B ) . As control for specificity , we treated HF-SCs directly with CL-lipo or Lipo , and no phagocytic uptake was observed by HF-SCs , neither changes in the expression of the analyzed transcripts ( Figure S10B ) . In addition , immunofluorescence studies revealed the expression of K1 and K10 differentiation markers , without an increase in Ki67+ cells when compared to controls ( Figure S10C ) , in agreement with previous data indicating the capacity of HF-SCs to differentiate into epidermal lineages in vitro [74] . Overall , these findings suggest that macrophages contribute to the activation of HF-SCs . To investigate the involvement of macrophage-derived Wnts in the activation of HF-SCs and anagen induction under physiological conditions , we subcutaneously injected liposomes containing the specific hydrophobic small molecule inhibitor of Wnts , IWP-2 . IWP-2 is a bona-fide broad Wnt inhibitor that specifically prevents palmitoylation of Wnt proteins , thereby blocking Wnt their processing and activity [75]–[77] . It was to our great advantage that this inhibitor is embedded and retained in the liposome membrane . As shown in Figure 2A , the delivery and uptake of liposomes selectively occurs in phagocytic macrophages . Moreover , IWP2-liposomes have been successfully used to block Wnt activity derived from macrophages in other systems [78] . Using this approach , we performed treatments at different telogen stages ( Figure 6A , Te , Tm , and Tl ) . Strikingly , the sustained inhibition of Wnts starting at Tm was sufficient to delay the HF-SC entry into anagen and prevented the reduction of macrophage numbers ( Figure 6B and 6C ) . Of note , the treatment with IWP-2 liposomes at Te ( Figure 6D ) or at Tl ( Figure 6E ) , did not have an effect in HF-SCs and HG proliferation , and HF growth when compared to controls . Overall , these results indicate that macrophages contribute to the activation of HF-SCs , leading to a permissive state that allows HF entry into anagen . Inhibition of the processing of Wnts derived from macrophages via IWP2-liposomes dampened the anagen-inducing effect of CL-lipo treatment , as documented by histological and immunofluorescence analysis of P-cad ( enriched in the HG ) ( Figure 6F and 6G ) , and by the quantitative mRNA expression of HF-differentiation markers in total skin ( Figure 6H ) . Under these conditions , the treatment with IWP-2 liposomes also abrogated the reduction of macrophage numbers ( Figure 6I ) . Taken together , our results suggest that the apoptosis-associated secretion of Wnts by perifollicular macrophages contributes to the activation of epithelial HF-SCs , allowing HF entry into anagen .
While previous studies have already pointed to a link between macrophages and the regulation of HF cycling , in particular during the anagen-to-catagen transition [15] , [30] , [36] , the current study provides the first evidence , to our knowledge , that a selective reduction in the number of macrophages induces premature anagen entry . Moreover , our data suggest that changes in the release of Wnt signals by perifollicular macrophages may contribute to the establishment of the refractory and competent phases of telogen , and to the propagation of cues that induce anagen . Finally , we show that apoptotic macrophages can activate epithelial HF-SCs in a Wnt-dependent manner , and that inhibition of Wnts derived from macrophages delays anagen . Conceptually , this finding reveals that skin-resident macrophages function as important mesenchymal regulators of epithelial HF-SC function under physiological conditions and identifies a novel link between macrophages and HF cycling . Given , however , the many similarities between anagen development and wound healing on the one hand [79] , and the key role of skin macrophages in wound repair on the other [47] , it is not surprising that macrophages turn out to be involved not only in matrix scavenging during HF regression [43] , but also in HF-SC activation and anagen induction . Thus , our study underscores the importance of macrophages as modulators of tissue regeneration and organ remodeling , well beyond their function as phagocytes , and highlights that the murine hair cycle offers an excellent model for further dissection of these physiological roles . The fact that a reduction in skin macrophage numbers exerts strong hair cycle-modulatory effects corresponds to the previously reported hair cycle-accelerating effects of γδ T cell deletion [42] , and points to the need for systematic re-examination of the role of immunocytes in hair growth control . This line of research should facilitate the development of novel therapeutic strategies for the manipulation of undesired human hair loss or growth that target perifollicular immunocytes , such as macrophages . Particularly important will be the studies focusing on human inflammatory permanent alopecias characterized by irreversible HF-SC damage and macrophage infiltration of the bulge [10] . We noted that ∼50% of the HFs of the second postnatal telogen exhibited perifollicular F4/80+ cells . Previous findings of a much smaller percentage of perifollicular macrophage clusters ( PICCs ) ( ∼2% ) [30] likely reflect differences in the hair cycle stage analyzed ( first postnatal anagen and during the transition of anagen-to-catagen ) [30] . Furthermore , our analyses revealed that the number of macrophages declines as telogen progresses from the refractory to the competent phases of telogen ( Figures 1 and S1 ) , probably after performing their phagocytic functions during the basement membrane resorption of involuting catagen HFs [43] . This scenario seems to be different when growing anagen HFs progress to catagen , as previously reported during the first HF cycle [15] , [36] , and confirmed here ( Figure S1B ) . Future work in this field should strive to use genetic mouse models to selectively decrease skin macrophage numbers , rather than having to rely on the clodronate method . However this process is difficult , given the differential origins of macrophages [48] , [80] , [81] . Our results stress the need to analyze the characteristics of skin resident macrophages and their differential roles in homeostasis ( fate-mapping studies , linear tracing ) to generate useful genetic mouse models not available to date . The macrophage expression profiles identified in our studies underscored the highly heterogeneous phenotype of skin macrophages [82]–[84] . In the context of M1 and M2 macrophages [82] , [85] , they seem to comprise unpolarized populations since they co-express both M1/M2 markers in uninflamed , not wounded conditions . However , a clear upregulation of the expression levels of Wnt7b and Wnt10a was observed in macrophages as telogen progresses to anagen . Intriguingly , our observation that apoptosis upregulates the expression of Wnts is fully consistent with observations documented in other systems , including e . g . , Hydra and liver models [55] , [86] . Wnt7b activity has been implicated in regenerative processes including macrophage-dependent control of cell fate decisions in the vasculature [87] , lung development [88] , and macrophage-dependent kidney wound repair [89] . Moreover , Wnt10a is upregulated during HF development [90] , and Wnt10a missense mutations have been associated with the human syndromes odonto-onycho-dermal dysplasia [91] and Schöpf–Schulz–Passarge [92] , [93] , both characterized for malformations in ectodermal structures . Macrophages have been extensively implicated in the development of several tissues , as well as in homeostasis and cancer [85] , [94]–[96] . They have been directly implicated in the regulation of other adult SC niches such as the hematopoietic SCs [97] , [98] , mammary SCs [99] , and liver [55] . However , macrophage functions have specific roles depending on the tissue context [94] . Hence , dissecting the roles of skin-resident macrophages in homeostatic HF regenerative conditions adds a new relevant facet of skin biology . It is an important first step in understanding the functions of macrophages in other contexts such as skin repair , skin inflammatory diseases , and cancer . In skin repair , it has been recently documented that macrophages play differential roles as wounds heal [47] . Interestingly , their infiltration upon wounding is required for HF growth [100] . It is well-established that HF-SCs transiently contribute to the epidermal lineage after injury to support cutaneous wound healing [17] , [101]–[103] , and that large full thickness wounds induce HF neogenesis [4] , [101] . Hence , future research should target the involvement of different skin epithelial progenitor cells , macrophages , and macrophage derived Wnts in these contexts . In addition , since adult skin HF-SCs , their immediate progeny , and basal progenitor cells have been identified as cells of origin of skin carcinomas [104] , [105] , the elucidation of HF-SC interactions with macrophage-derived Wnts in the context of tumorigenesis [85] , [106] is an important question for future studies . Our study delineates that macrophage-derived Wnts activate HF-SCs and HF entry into anagen . In addition , our results raise the possibility that non-apoptotic perifollicular macrophages operate as an “immunocyte brake” on HF-SC activation , which is only released by the macrophage apoptosis-associated release of Wnts . This finding begs the next question to be addressed in subsequent studies: What triggers and regulates perifollicular macrophage apoptosis during telogen ? For example , does this numeric decline only reflect the natural completion of the finite macrophage life span , or does the HF epithelium ( including its SCs ) actively participate in the reduction of macrophages ? Overall , we surmise that the outcome of HF-SC activation via macroenviromental signals is regulated by a whole host of tightly regulated signaling loops between HF-SCs , adipocytes , immune cells , the vasculature , and now , based on our findings , with macrophages . Determining whether these molecular signals are orchestrated along with the intrinsic HF-SC regulatory cues will be valuable to define the multiple hierarchies that underlie HF regeneration . Once powerful tools of molecular biology at hand in mice become applicable to human hair research , including novel in situ-imaging tools to assess HF-SC activation in humans [107] , new translationally and therapeutically relevant insights into the macrophage-epithelial SC connection and its role in tissue remodeling , organ repair , and hair diseases may be achievable .
All protocols related to animal research were approved by the Animal Experimental Ethics Committee of the Carlos III Health Institute , in strict compliance with institutional guidelines and the international regulations for Welfare of Laboratory Animals . Experiments were performed with 6- to 12-week old Crl:CD1 ( ICR ) and FVB/N female mice . Mice were sacrificed at specific postnatal days ( P ) , and their dorsal skins were dissected and processed for analyses . To reduce the number of skin-resident macrophages , 1 mg of clodronate-encapsulated liposomes were administered to mice via daily subcutaneous injections during two alternated days ( Encapsula Nanosciences ) . CL-lipo are the one of the most effective , specific , and extensively used agents to deplete phagocytic monocytes and macrophages via apoptosis [49] , [53] . The specific Wnt inhibitor IWP-2 ( Roche Diagnostics ) was encapsulated in liposomes ( Encapsula Nanosciences ) and 50 µg were injected subcutaneously [75] , [78] . The K5 tTA ( TetOff ) -histone H2B-GFP mice [17] , the K15-GFP mice ( Jackson Lab ) [103] , the Katushka reporter mice [108] , and the TCF/Lef:H2B-GFP transgenic mice ( Jackson Lab ) [67] have been previously described . Doxycycline treatments were initiated in 28 d postnatal mice [17] , and maintained until the collection of samples after the performance of subcutaneous injections of CL-lipo and Lipo at specified times . Total RNAs from FACS isolated skin-resident macrophages , pooled from three littermate mice per point , were purified using the Absolutely RNA reverse transcription system ( Stratagene ) . These samples were provided to the CNIO Genomics Core Facility to perform the quantification , assessment of RNA quality , labeling , hybridization , and scanning process . Briefly , 0 . 05–1 ng RNA were subjected to a preliminary amplification step with a TransPlex Whole Transcriptome Amplification WTA2 kit ( Sigma ) . 250 ng of sample were reverse transcribed using the Agilent Oligonucleotide Array-Based CGH for Genomic DNA Analysis - ULS Labeling for Blood , Cells , Tissues or FFPE ( with a High Throughput option ) . The recommendations from Sigma for the integration of TransPlex WTA with the Agilent microarray workflow were followed , such as the omission of Cot-1 DNA . 250 ng of cDNA were non-enzymatically labeled with either Cy3 or Cy5 fluorophores using the ULS technology ( Kreatech ) , and labeled samples were hybridized to the Mouse Gene Expression G3 8×60 K array ( Agilent ) at 65°C for 40 h . Hybridized chips were scanned using a G2505C DNA microarray scanner ( Agilent ) and the obtained images were quantified using the Feature Extraction Software 10 . 7 ( Agilent ) . Probesets were considered as differentially expressed when the absolute fold change was ≥10-fold . Unsupervised clustering analysis ( UPGMA ) was performed using Pearson correlation . The microarray data from this publication have been submitted to the GEO database http://www . ncbi . nlm . nih . gov/geo/info/linking . html and assigned the identifier GSE58098 . Backskins were minced into small pieces and digested in PBS , 1% BSA , 0 . 5 mg/ml DNase I , and 0 . 5 mg/ml collagenase II and IV for 1 h at 37°C . Single cell-suspensions were obtained via pipette mechanical dissociation of total skin ( epidermis and dermis ) followed by filtration through 40 µm cell strainers . Cells were washed in PBS , blocked using the mouse seroblock FcR reagent ( CD16/CD32; BD Pharmigen ) , and stained for FACS analysis in ice-cold PBS , 0 . 5% BSA , 0 . 3 mM EDTA using the following antibodies: CD11b-PerCPCy5 . 5 ( rat mAb Clone M1/70 , 45-0112 eBioscience ) , F4/80-APC-eFluor780 ( rat mAb Clone BM8 , 47-4801 eBioscience ) , Gr1-PECy7 ( rat mAb Clone RB6-8C5 , 25-5931 eBioscience ) . To isolate HF-SC , backskins from K15-GFP mice were digested with 0 . 25% trypsin-EDTA in PBS for 14 h at 4°C . Cell suspensions were processed as mentioned above , and stained for 30 min at 4°C using the following antibodies: CD34-PE ( rat mAb Clone RAM34; BD Pharmigen ) , CD49f-APC ( rat mAb Clone eBioGoH3; eBioscience ) , and P-cad-APC ( rat mAb Clone 106020; R&D systems ) . Cells were sorted on a FACSAria Ilu using the CellQuest Pro software ( BD Biosciences ) , or analyzed using a FACSCanto and the FlowJo software ( TreeStar ) . For Sub-G1 analysis sorted cells were fixed in 70% EtOH and stained with propidium iodide ( Becton Dickinson ) . For TUNEL analyses , cytospin preparations of FACS-sorted cells were processed and stained according to the in situ Cell Death Detection kit , Fluorescein ( Roche ) . The FCS files from this publication have been deposited in the Dryad repository http://dx . doi . org/10 . 5061/dryad . 2822t [109] . All quantitative data are presented as mean ± SEM . Results are representative of at least three independent experiments . To determine the significance of the data obtained for two groups , comparisons were made using two-tailed , unpaired Student's t test . For all statistical analysis a confidence level of p≤0 . 05 was considered to be statistically significant . | The cyclic life of hair follicles consists of recurring phases of growth , decay , and rest . Previous studies have identified signals that prompt a new phase of hair growth through the activation of resting hair follicle stem cells ( HF-SCs ) . In addition to these signals , recent findings have shown that cues arising from the neighboring skin environment , in which hair follicles dwell , also participate in controlling hair follicle growth . Here we show that skin resident macrophages surround and signal to resting HF-SCs , regulating their entry into a new phase of hair follicle growth . This process involves the death and activation of a fraction of resident macrophages— resulting in Wnt ligand release —that in turn activate HF-SCs . These findings reveal additional mechanisms controlling endogenous stem cell pools that are likely to be relevant for modulating stem cell regenerative capabilities . The results provide new insights that may have implications for the development of technologies with potential applications in regeneration , aging , and cancer . | [
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] | 2014 | Macrophages Contribute to the Cyclic Activation of Adult Hair Follicle Stem Cells |
Skeletal muscle necrosis is a common manifestation of viperid snakebite envenomations . Venoms from snakes of the genus Bothrops , such as that of B . asper , induce muscle tissue damage at the site of venom injection , provoking severe local pathology which often results in permanent sequelae . In contrast , the venom of the South American rattlesnake Crotalus durissus terrificus , induces a clinical picture of systemic myotoxicity , i . e . , rhabdomyolysis , together with neurotoxicity . It is known that molecules released from damaged muscle might act as ‘danger’ signals . These are known as ‘alarmins’ , and contribute to the inflammatory reaction by activating the innate immune system . Here we show that the venoms of B . asper and C . d . terrificus release the mitochondrial markers mtDNA ( from the matrix ) and cytochrome c ( Cyt c ) from the intermembrane space , from ex vivo mouse tibialis anterior muscles . Cyt c was released to a similar extent by the two venoms whereas B . asper venom induced the release of higher amounts of mtDNA , thus reflecting hitherto some differences in their pathological action on muscle mitochondria . At variance , injection of these venoms in mice resulted in a different time-course of mtDNA release , with B . asper venom inducing an early onset increment in plasma levels and C . d . terrificus venom provoking a delayed release . We suggest that the release of mitochondrial ‘alarmins’ might contribute to the local and systemic inflammatory events characteristic of snakebite envenomations .
Snakebite envenomation is a neglected tropical disease that affects each year hundreds of thousands of individuals in tropical and sub-tropical areas of the world [1][2] . In addition to death , many snake bitten patients develop permanent physical and psychological sequelae which greatly affect their quality of life [3][4][5][6] . In the Americas , species of the family Viperidae are responsible for the vast majority of snakebite envenomations [7][5][8] . In Latin America , most cases are inflicted by species of the genus Bothrops , among which the lance-head vipers B . asper and B . atrox are very important in Central and South America , respectively [7] . In addition , the rattlesnake Crotalus durissus is notorious in South America for inflicting severe envenomations [7][9] . The pathophysiology of envenomations by B . asper ( BaV ) and C . durissus ( CdV ) and their predominant toxins has been investigated at experimental and clinical levels [10][11][12][13][9] . These venoms induce strikingly different pathophysiological patterns . BaV , similarly to other Bothrops spp venoms , induce local pathological alterations associated with edema , myonecrosis , dermonecrosis , blistering and hemorrhage [12] . In addition , systemic alterations , i . e . coagulopathies , hemorrhage , acute renal failure and cardiovascular shock , may ensue in moderate and severe cases [11][13] . Such a complex array of local and systemic alterations is mostly induced by the action of metalloproteinases , phospholipases A2 ( PLA2 ) and PLA2 homologues , and serine proteinases , among other components [12][13][14][15] . These envenomations present prominent local inflammatory response , associated with the activation of innate immune mechanisms , which might contribute to the pathogenesis of tissue damage [16] . In contrast to the effects of BaV , the pathophysiological manifestations induced by CdV are characterized by minor local alterations and prominent systemic effects , mostly neurotoxicity , systemic myotoxicity , i . e . rhabdomyolysis , acute renal failure and coagulopathies [9] . Around 60% of CdV is comprised by the dimeric PLA2 complex ‘crotoxin’ [17] , which is composed by a basic PLA2 chain , crotoxin B , and a non-enzymatic acidic subunit , crotoxin A or crotapotin [18] . Cotapotin prevents the binding of crotoxin B subunit to non-specific sites and thus contributes to the high toxicity of this toxin [18] . Crotoxin exerts presynaptic neurotoxicity and systemic myotoxicity , which results in the release of large amounts of myoglobin from damaged muscle fibers , with the consequent impact on the kidney , provoking acute renal failure , which is a common finding in envenomations by this species [19] . Thus , envenomations by BaV and CdV represent different paradigms of tissue damage which greatly differ in the extent of the local inflammatory and pathological responses and in the systemic manifestations . On the basis of such different pathophysiological patterns , these venoms constitute valuable experimental tools to assess various aspects of local and systemic muscle damage and inflammation . Snakebite envenomations trigger complex pathogenetic processes that include a range of defense reactions in the bitten organism , whose mechanisms are ill known , but resemble in several aspects muscle trauma [20][21] . It has been long known that following tissue injury such as mechanical traumas , there is a massive release of molecules that act as “danger signals” , activating the host response [22] ATP is the prototype of these molecules , and when it is released from damaged or stressed cells to the extracellular space it acts via binding to an array of purinergic receptors [23][24][25][26] . We have recently found that both Asp49 and Lys49 PLA2 myotoxins from BaV induce the release of ATP and K+ from muscles ex vivo and muscle cells in culture , and that this ATP extends the range of damage caused by these toxins [27] . ATP plays also a major role in the pathogenesis and symptoms following traumatic accidents [28][29] . Very recently , it was demonstrated that traumatic injuries also induce the release of DNA and N-formylated proteins from the mitochondria of damaged tissues [30] . These molecules , known as ‘alarmins’ [31][32] are able to activate neutrophils because they are recognized via receptors highly conserved during evolution as they are devoted to the innate immune response towards microbial molecules [30][33] . On the basis of the pathological manifestations induced by BaV and CdV , we have investigated whether envenomations by these archetypal venoms induce the release of mitochondrial molecules , by evaluating the release of mitochondrial DNA and cytochrome c in isolated skeletal muscles and after in vivo injection of the venoms in mice .
The venom of B . asper was a pool obtained from more than 40 adult specimens collected in the Pacific region of Costa Rica; venom was lyophilized and stored at -20°C . Venoms were dissolved in 10 mM Hepes and 150 mM NaCl with 50% glycerol and sterilized by filtration through 0 . 22 µm GV Durapore® ( Millipore ) . C . d . terrificus venom was from Latoxan ( Valence , France ) . CD-1 mice received standard food and had free access to food and water . All experimental procedures involving animals were carried out in accordance with the Italian Animal Welfare Act and were approved by the local authority veterinary service . Tibialis anterior muscles were isolated from CD-1 mice weighing 25–30 g and immediately transferred to vials containing 1 ml of incubation buffer ( 139 mM NaCl , 12 mM NaHCO3 , 4 mM KCl , 2 mM CaCl2 , 1 mM MgCl2 , 1 mM KH2PO4 , and 11 mM glucose , pH 7 . 4 ) oxygenated ( 95% O2 , 5% CO2 ) at 37°C . BaV and CdV ( 50 µg/ml ) were added to the bath for the indicated time period , and the same volume of vehicle alone ( 10 mM Hepes and 150 mM NaCl with 50% glycerol ) was added to the contralateral muscle used as control . At the end of incubation time , the supernatants were treated with RNAse A ( 100 mg/ml ) to avoid RNA contamination and mtDNA was extracted using DNeasy Blood & Tissue kit ( Qiagen ) following manufacturer's instructions . Groups of three CD-1 mice were injected intramuscularly into the right leg with BaV ( 5 mg/kg ) , CdV ( 0 . 15 mg/kg ) or the same volume of vehicle . The different dosages due to the higher toxicity of CdV were chosen to ensure that all animals survived during a 24 hr period . After 1 hr or 24 hrs , mice were sacrificed and immediately bled using up to 10 U/ml of heparin ( Roche ) to avoid interference with the following analyses . Plasma was separated and processed for mtDNA extraction using DNeasy Blood & Tissue kit ( Qiagen ) following manufacturer's instructions , after the treatment with RNAse A as previously described . Primers for mouse cytochrome B ( forward 5′-TGATGAAACTTTGGGTCCCTTC-3′ and reverse 5′-ATAAGCCTCGTCCGACATGAA-3′ ) , and mouse cytochrome C oxidase subunit III ( forward 5′-GTCCCACTACTTAATACTTC-3′ and reverse 5′-GGTGAAGTAAAGTCCTAGT-3′ ) were synthesized by Invitrogen . Primer sequences have no significant homology with DNA found in any bacterial species published on BLAST . Samples that produced no PCR products after 33 cycles were considered ‘undetectable’ . Real-time qPCR was performed using iCycler® thermal cycler ( Bio-Rad ) . Amplification conditions were: 10 min at 95°C , 40 cycles: 10 sec at 95°C , 30 sec at 52°C . A melting curve analysis , consisting of an initial step at 65°C for 10 sec and a slow elevation of temperature ( 0 . 5°C/s ) to 95°C , was performed at the end of the amplification cycles to check for the absence of primer dimers and non-specific products using iQ SYBR Green supermix ( Biorad ) . Results were expressed as detection folds of target genes in venom treated samples compared to control samples . Tibialis anterior muscles were isolated from CD-1 mice and immediately transferred to vials containing 1 ml of the previously described oxygenated incubation buffer at 37°C . BaV or CdV venoms ( 50 µg/ml ) were added to the bath for the indicated time period , and the same volume of vehicle alone was added to the contralateral muscle used as control . Samples of incubation medium were taken at different time points and protein concentrations were determined with the BCA Protein Assay ( Pierce ) . The same quantification was done on plasma samples taken from injected mice . For each sample , 2 . 5 µg of total protein ( for ex vivo experiments ) or 50 µg ( for plasma analysis ) were loaded on 12% SDS-polyacrylamide gels , run at room temperature at 20 mA and transferred at 200 mA to a nitrocellulose in a refrigerated chamber . Membranes were incubated with an anti-cytochrome C antibody ( BD Biosciences ) following manufacturer's instructions . Chemiluminescence was developed with Luminata™ Crescendo ( Millipore ) or ECL Advance western blotting detection system ( GE Healthcare ) , and emission was measured with ChemiDoc XRS ( Bio-Rad ) . Band intensities were quantified on the original files with the software Quantity One ( Bio-Rad ) . None of the bands reached signal saturation .
Envenomations by viperid snakes , such as those induced by B . asper , are often characterized by prominent tissue damage and inflammation at the site of venom injection . These venoms contain myotoxic PLA2s and PLA2 homologues which induce rapid alterations to the plasma membrane of the skeletal muscle cells , followed by irreversible cell injury [34][35] . The venom of C . d . terrificus contains large amounts of the neuro- and myotoxic PLA2 complex crotoxin , which induces local and systemic myotoxicity [36][37] . These myotoxins are not known to enter into cells , but they do cause rapid change in plasma membrane permeability , evidenced by a rapid loss of cytosolic markers , e . g . LDH and CK [38][39][40][41] . The incubation of mouse tibialis anterior muscle with either BaV or CdV resulted in a similar extent of LDH release ( Fig . S1 ) . Recently , it was shown that traumatic injuries induce the release of mitochondrial DNA , which , owing to its similarity to bacterial DNA , causes activation of innate immune cells [30] . This finding prompted us to test the possibility that BaV and CdV are able to induce the same effects . We used quantitative real-time PCR to evaluate mtDNA release from isolated tibialis anterior muscles treated with BaV or CdV . Fig . 1 shows that both venoms rapidly induce a rapid release of mtDNA from the treated muscle . BaV is more effective than CdV in both cases the amount of released mtDNA increased with time . Mitochondria are compartmentalized by two highly specialized membranes which create two separate spaces: the matrix , where mtDNA is located , and the intermembrane space , where Cyt c is present . Both mtDNA and Cyt c can act as alarmins [42] therefore we also investigated the release of Cyt c . Fig . 2 shows that , following treatment of tibialis anterior muscles with BaV or CdV , Cyt c is rapidly released; its presence in the medium is detectable soon after 15 min from addition of venoms to the bathing solution . In order to extend the analysis of alarmin release in the context of the whole animal , venoms were injected intramuscularly in mice , followed by the quantification of mtDNA and Cyt c in the plasma . Mitochondrial alarmins were detected in the plasma of envenomated mice , as it has been described for traumatized patients [30] . The amount of mtDNA in the plasma was measured by real-time PCR after 1 and 24 hrs from injection . Fig . 3 shows that the pattern of mtDNA increase in the plasma differs among the two venoms , with a higher peak at 1 hr in the case of BaV injection and a higher concentration at 24 hrs for CdV . Cyt c release was also detected in the blood of patients who experience massive cell death , such as in systemic inflammatory response syndrome [43] . We next used Western blotting to detect Cyt c because other immunoassays , such as sandwich ELISA , may not give a reliable response in the presence of serum . Indeed , serum leucine-rich alpha-2-glycoprotein-1 binds to Cyt c and inhibits its recognition by specific antibodies [44] , Such interference can be bypassed by using Western blotting . Fig . 4 shows that Cyt c was increased in the plasma of mice injected with either BaV or CdV 1 hr after injection , and its levels remained high after 24 hrs compared to control mice .
Muscle injury almost invariably leads to release of intracellular molecules , some of which constitute alarm signals which induce an innate immune reaction following their binding to specific receptors in various cell types [31] . This represents a general and fundamental defense response [45][46] . The first of such intracellular molecules to be identified was ATP , which binds to a variety of purinergic receptors [25] . Very recently , mitochondria have emerged as a source of alarmins , such as mtDNA , as well as N-formylated proteins which bind to Toll-like receptors and to the formyl-peptide receptors and induce neutrophil activation [30] . These molecules are quite similar to their bacterial counterparts which are well characterized inducers of innate immune reactions [47][48][49] . Activation of neutrophils contributes to a variety of inflammatory and tissue repair events . Here , we have shown that BaV and CdV rapidly induce the release of both mtDNA and of Cyt c which can be detected both in the plasma of injected mice and in the medium of isolated muscles after incubation with the venoms . It has been previously reported an important cytokine release in envenomated mice , therefore we did not analyzed this aspect of immune response [50] [51][16][52][53][54][55] . The two venoms were found to differ significantly in their kinetics of alarmin release in injected mice . BaV was found to be very rapid in inducing the release of both types of mitochondrial molecules , whilst CdV was rapid in causing Cyt c release , but slower in that of mtDNA . As mtDNA is located in the matrix and Cyt c in the inter-membrane space , these data highlight possible differences in the way these venoms affect mitochondria in muscle fibers . In ex vivo experiments using the tibialis anterior muscle , BaV induces a more drastic damage of mitochondria with alteration of permeability of both the outer and the inner membranes , whilst CdV seems to damage predominantly the outer membrane and , to a lesser extent and later on , the inner membrane . In the same model , both venoms induce a release of LDH from cytosol , which was more pronounced in the case of BaV . The basis for the differences in mtDNA release by these venoms is puzzling , since both their main myotoxic components , i . e . B . asper PLA2 myotoxins and C . d . terrificus crotoxin act primarily by disrupting the integrity of skeletal muscle sarcolemma , inducing a calcium influx that generates a series of intracellular degenerative events [34] . Some of the most notorious ultrastructural consequences of the action of these toxins are observed in mitochondria , such as high amplitude swelling , disruption of cristae , appearance of flocculent densities and precipitates of hydroxyapatite [37] [56] . Despite these ultrastructural similarities in damaged mitochondria , our observations are likely to reveal more subtle differences in the mode and kinetics with which these venoms affect this organelle , a subject that needs to be further investigated . For instance , there might be variations in the release of mtDNA via inner-outer mitochondrial membrane specialized junction sites [57] . In addition , and perhaps most importantly , one should consider the involvment of other components of the two venoms in the envenomation process . For instance , viperid snake venoms , including those of B . asper and C . durissus , contain DNAses [58] , which might degrade released mtDNA . Moreover , BaV myotoxins are able to affect types I , IIA and IIB muscle fibers , whereas crotoxin is more selective towards oxidative types I and IIA fibers [36]; since tibialis anterior muscle is predominantly constituted by type II fibers [59] such difference might have implications in the mtDNA release . Differences in the mechanism of action of crotoxin and BaV myotoxins were shown by their different myotoxic response to the pretreatment of animals with calcineurin [60] , an observation that might be related to the variable specificity towards different muscle fiber types . Our in vivo approch allowed the analysis of alarmin release in the whole animal , i . e . in a model that resembles the actual circumstances of snakebite . Intramuscular injection of these venoms in mice revealed marked differences in the kinetics of mitochondrial marker release . In the case of BaV , similar plasma concentration of Cyc c was observed at 1 and 24 hr , whereas the release of mtDNA was significantly higher at 1 hr . In contrast , CdV induce a higher Cyt c release at 1 hr , but a peak of mtDNA release at 24 hr . These differences can be interpreted in the light of previous observations on the myotoxic action of Bothrops sp myotoxins and crotoxin . The former induces predominantly local myotoxicity , i . e . muscle necrosis at the site of venom injection , with a very rapid increase in plasma CK activity , followed by a rapid drop . In contrast , crotoxin induces a more prolonged increment of CK activity in plasma , associated with systemic myotoxicity [36][40] . The late increment in mtDNA in plasma is compatible with the predominantly systemic myotoxicity of CdV . Our findings on the release of alarmins from muscle tissue damaged by these venoms have implications in terms of the local and systemic inflammatory events associated with snakebite envenomations . The rapid and higher release of mtDNA from muscles treated with B . asper venom correlates with the prominent local inflammatory scenario characteristic of tissue injected with this venom , in which there is increase of eicosanoids , cytokines , matrix metalloproteinases and other inflammatory mediators [16][53][54][55][50] , and a prominent influx of neutrophils and macrophages [51][52] . In this context , the role of mtDNA and other alarmins in eliciting such strong inflammatory response needs to be assessed . In contrast , in the case of CdV , local inflammatory events are minor , as shown at experimental and clinical levels , probably due to the anti-inflammatory activity of this venom [61][62] . This may be also related with the observed delay in mtDNA release in vivo and with the lower release of this alarmin from muscle ex vivo . On the other hand , systemic manifestations of envenomations by Bothrops spp . are associated with evidence of systemic inflammatory events , as revealed by increments in the plasma levels of some cytokines and nitric oxide after the administration of a lethal dose of B . asper and B . jararaca venoms in mice [63][50] . In the case of CdV , it is suggested that the drastic systemic myotoxicity induced by this venom , with the release of alarmins and other danger signals from damaged muscles , is likely to play a role in the onset of systemic inflammation , an issue that remains to be investigated . It is known that mitochondrial DAMPs are released following various types of tissue injury , causing systemic inflammation [42] . We hypothesize that , in addition to the direct action of snake venom components on various tissues , the release of mitochondrial alarmins from damaged cells is likely to contribute to the onset of local and systemic inflammatory events which , in severe envenomations , may induce manifestations that resemble those of systemic inflammatory response syndrome ( SIRS ) [64] . In the light of the emerging fundamental role of mitochondria in innate immune response , it would be important to characterize this interplay and the different alarmins that might be involved [65][66] . This novel perspective of the action of snake venoms opens therapeutic windows of action aimed at reducing the effects of such alarmins as a way to decrease the severity of snakebite envenomations because it is possible that the injection of antibodies directed against mitochondrial DNA and cytochrome c given soon after envenomation may have therapeutic value . | Every year , hundreds of thousands of people in tropical and sub-tropical areas of the world are bitten by poisonous snakes and may develop permanent damages . This is a major tropical disease which is largely neglected by scientific and clinical investigators . Snakes of Bothrops and Crotalus genus are responsible of most cases in Latin America . Here for the first time , we have shown that these venoms cause the release of both mitochondrial DNA and cytochrome c , two well known alarmins . Moreover , the kinetic of these processes are in agreement with the different pathophysiological profiles exhibited by Bothrops and Crotalus envenomations . These elements suggest a correlation between snake evenomations and sterile inflammatory syndrome . Alarmins are reported to have a fundamental role in innate immune response and inflammation; they might contribute to the local and systemic inflammatory events characteristic of these envenomations opening a new prospective in the study of these complex pathologies . | [
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] | 2012 | Envenomations by Bothrops and Crotalus Snakes Induce the Release of Mitochondrial Alarmins |
A well-accepted model of episodic memory involves the processing of spatial and non-spatial information by segregated pathways and their association within the hippocampus . However , these pathways project to distinct proximodistal levels of the hippocampus . Moreover , spatial and non-spatial subnetworks segregated along this axis have been recently described using memory tasks with either a spatial or a non-spatial salient dimension . Here , we tested whether the concept of segregated subnetworks and the traditional model are reconcilable by studying whether activity within CA1 and CA3 remains segregated when both dimensions are salient , as is the case for episodes . Simultaneously , we investigated whether temporal or spatial information bound to objects recruits similar subnetworks as items or locations per se , respectively . To do so , we studied the correlations between brain activity and spatial and/or temporal discrimination ratios in proximal and distal CA1 and CA3 by detecting Arc RNA in mice . We report a robust proximodistal segregation in CA1 for temporal information processing and in both CA1 and CA3 for spatial information processing . Our results suggest that the traditional model of episodic memory and the concept of segregated networks are reconcilable , to a large extent and put forward distal CA1 as a possible “home” location for time cells .
In the early 1980s , Mishkin and colleagues proposed a very influential model of episodic memory according to which spatial and non-spatial information emerging from the dorsal and the ventral visual pathways would be integrated into episodes at the level of the hippocampus [1 , 2] . This model considers information related to the features of objects and their location as non-spatial and spatial information , respectively , while the temporal information bound to these objects is not considered even though this dimension constitutes a key feature for the memory of episodes [3] . Clear empirical evidence for the integration of this spatial and non-spatial information at the level of the hippocampus and possible mechanisms underlying such an integration are still missing . In addition , it is not known whether such an integration would still take place if only one of the dimensions of the memory is salient , i . e . , when the integration of both dimensions is not “necessary . ” Moreover , the cortical areas constituting the last relay of the “extended” ventral and dorsal pathways , namely the lateral entorhinal cortex ( LEC ) and the medial entorhinal cortex ( MEC ) , respectively , preferentially project at distinct proximodistal levels of the hippocampal subfield CA1 . Indeed , the LEC that essentially processes non-spatial information preferentially projects to the distal part of CA1 ( away from the dentate gyrus [DG] , i . e . , close to the subiculum; Fig 1A ) . In contrast , the MEC , more sensitive to spatial content , preferentially projects to the proximal part of CA1 ( close to the DG and CA2 ) [4–13] . In addition , the proximal and distal parts of CA3 send segregated projections to CA1 . Distal CA1 primarily receives projections from the proximal part of CA3 ( close to the DG ) and proximal CA1 from distal CA3 ( away from the DG , i . e . , close to CA2 ) [14–18] . Furthermore , the distal part of CA3 receives projections from the enclosed blade of the DG , which is tuned to spatial information , as well as from the crest and the exposed blade . Moreover , entorhinal cortex ( EC ) cells send most of their inputs at this level because EC cells synapse at the level of the lacunosum moleculare , which is quasi nonexistent at the proximal levels of CA3 . In comparison , the proximal part of CA3 receives fewer projections from the enclosed blade of the DG and fewer entorhinal inputs , among which LEC inputs which preferentially deal with non-spatial content [19–23] . Altogether , these findings led us to recently suggest the existence of distinct “spatial” and “non-spatial” hippocampal subnetworks segregated along the proximodistal axis of the hippocampus that would preferentially be engaged either when only the spatial dimension or only the non-spatial dimension of a memory is salient , i . e . , when the integration of both dimensions is not “necessary” ( Fig 1B and 1C ) [24 , 25] . These networks were termed “spatial” and “non-spatial” subnetworks with regards to their relative ability ( i . e . , not absolute ) to process non-spatial and spatial information , i . e . , the “non-spatial” subnetwork processes non-spatial information over spatial information , whereas the “spatial” network favors the processing of spatial information over non-spatial information . Evidence for a functional segregation along the proximodistal axis of CA1 and CA3 is sparse , but its existence is supported by recent electrophysiological and Arc imaging studies . An electrophysiological study from the Moser laboratory reported a stronger engagement of proximal CA1 over distal CA1 for the processing of spatial stimuli [10] . Conversely , we showed a stronger recruitment of distal CA1 over proximal CA1 for the processing of non-spatial ( odor-based ) information in a previous Arc imaging study [24] . In addition , activity differences along the proximodistal axis of CA1 were reported to be attenuated with aging and proximodistal theta activity coherence to be reduced in the dorsal hippocampus of a rodent animal model of epilepsy [26–27] . Furthermore , some of these reports and others also showed a preferential involvement of proximal CA3 for the retrieval of non-spatial memory and that of distal CA3 for the processing of spatial locations [24–25] . Finally , a proximodistal segregation of CA3 was also reported in terms of pattern completion and pattern separation [28–29] . Still , very little is known about these hippocampal subnetworks . Specifically , it is unclear whether non-spatial information other than objects or odors , such as temporal information , would also preferentially recruit the proximal CA3–distal CA1 “non-spatial” network . This hypothesis is substantiated by the fact that studies focusing on temporal bridging have indeed targeted distal CA1/the distal half of CA1 [30–38] . However , their focus was not the investigation of proximodistal differences in CA1; therefore , whether temporal information also preferentially engages the “non-spatial” subnetwork remains to be thoroughly tested . Also , it is not known whether spatial information related to items such as objects ( i . e . , object-in-place information ) would primarily engage the distal CA3–proximal CA1 “spatial” network , as is the case for locations . Finally , it is not clear whether the concept of segregated information processing in the hippocampus and the traditional model of episodic memory are supported by distinct neural substrates or whether they are variations of one and the same principle supported by the same neural networks that are recruited depending on the nature of the salient dimensions of the memory ( Fig 1B–1D ) . To address these questions , we investigated which areas—among the distal and proximal parts of CA1 and CA3—are tuned to temporal information , spatial information , or both types of information . To do so , we used a spontaneous object-recognition memory task that allows for the evaluation of distinct discrimination ratios for the retrieval of the temporal aspect of a memory ( “when” the objects were presented ) and that of its spatial aspect ( “where” the objects were located ) [39–42] , Fig 2A ) . Since performing electrophysiological recording simultaneously in 4 brain areas remains a major challenge and since the coordinates of the proximal and distal parts of CA1 and CA3 vary greatly along the transverse axis of the hippocampus because of its folding , we favored a high-resolution imaging approach ( i . e . , to the cellular level ) over lesion/inactivation/optogenetic approaches because the latter approaches would be unlikely to yield the spatial resolution necessary to tease apart the specific function of the proximal and distal parts of CA1 and CA3 in mice . This molecular imaging technique is based on the detection of the RNA of the Immediate Early Gene ( IEG ) Arc that is commonly used to map brain activity in the medial temporal lobe [45–47] and is tightly linked to plasticity processes [48] . In addition , Arc is more sensitive to memory demands than other IEGs [24 , 49 , 50] and allows for each cell activated at test to be detected . Arc RNA is visualized with the help of fluorescent tags , which allow for the percentage of cells engaged at test to be evaluated ( Fig 3A–3D ) .
Procedures were approved by the Ruhr Universität Bochum Institutional Animal Use Committee and the LANUV ( 8 . 87–51 . 04 . 20 . 09 . 323 ) . Adult male C57BL/6 mice ( n = 26 ) —single-caged and kept under a reversed light/dark cycle—were tested during their active phase . The apparatus was a 32 × 32 × 41 cm open field , placed in a dimly lit room . Extra-maze cues , as well as cues on the outside wall of the open field , served as spatial references . A video camera ( Sony , HDR/CX500E ) recorded the animals’ behavior for off-line analysis . Six copies of 2 different metallic objects were used for testing so that objects used during the test phase were duplicates of those during the study phases . Pilot studies showed that animals could distinguish between the 2 objects and had no aversion or preference for either object . The location of the recent , old , stationary , and displaced objects was counterbalanced between animals . The habituation procedure occurred on 4 consecutive days , following a procedure described in Dere and colleagues [39] . In short , animals were habituated to the empty open field for 20 min during days 1 and 2 . To encourage mice to explore all areas of the box ( divided in 9 quadrants ) and minimize the development of a spatial bias , 1 chocolate sprinkle was placed in the center of each quadrant . The absence or displacement of sprinkles and/or the presence of droppings in each quadrant at the end of each 20-min session were assessed and revealed that mice had explored each quadrant during each session . On days 3 and 4 , animals were habituated to the presence of objects , which were not used on the testing day in conditions that mirrored those of the testing day ( three 10-min trials , two 50-min delay periods ) . Animals were tested in groups of 9 , plus 1 home-caged control that was placed in the same room but did not perform the task . On day 5 , the testing procedure followed that of days 3 and 4 , but the test phase was adapted for an optimal detection of Arc pre-mRNA ( 6-min test phase; Fig 2A ) . During study phase 1 and 2 , animals were exposed to a set of 4 identical objects . During the first study phase , objects formed a triangle . During the second study phase , a different set of 4 identical objects formed a square . At test , duplicates of the objects previously studied were used . Two of the objects that had been the most recently explored ( i . e . , explored during study phase 2 ) were placed at the location they occupied then ( the “recent stationary” objects ) . In addition , one of the objects that had been experienced earlier ( i . e . , during study phase 1 ) was also placed at the location it occupied then ( the “old stationary” object ) , while another object of the same set was placed in a novel location ( the “old displaced” object ) . After each trial , the open field and stimuli were cleaned with water and a solution containing 10% ethanol . Based on animals’ natural preference for novelty [51] , a successful memory for a given spatial location ( e . g . , a successful spatial discrimination ) is observed when the “displaced old” object is explored more than the “stationary old” object , and a successful memory for the temporal context in which the object was experienced ( e . g . , a successful temporal discrimination ) is reflected by a longer exploration of the “stationary” old object compared with that of the average of the 2 “recent” objects [39–42] . A response pattern according to which mice explore the old displaced object more than the old stationary object and concomitantly the old stationary object more than recent objects suggests that mice have the ability to establish an integrated memory for events comprising information about “what , ” “where , ” and “when” [39] . The exploration time for an object was defined as the time spent in exploring an object , i . e . , directing the nose at a distance <2 cm to the object and/or touching it with the nose , as originally described in Ennaceur and Delacour ( 1988 ) [51] . The animals’ exploratory behavior was recorded during each phase for off-line analysis and was used to calculate spatial and temporal discrimination indices at test ( spatial and temporal D2s , respectively ) . Performance was scored manually by 2 independent experimenters blind to experimental conditions and averaged . The scores of both experimenters were highly correlated ( r = 0 . 879 ) . Specifically , D2 scores were calculated for each animal with the following equations: spatial D2 = ( exploration time displaced old object − exploration time stationary old object ) ÷ total exploration time for both old objects; temporal D2 = ( exploration time stationary old object − average exploration time both recent objects ) ÷ ( exploration time stationary old object + average exploration time both recent objects ) . Following the standard protocol for detection of Arc , animals were euthanized immediately after the test phase , and as Arc pre-mRNA was detected , only Arc intranuclear signal was observable [49 , 52–54] . In short , brains were removed , flash frozen in isopentane , and stored at −80°C until sectioning . Brains were sectioned with a cryostat ( Leica CM 3050 S; 8-μm–thick coronal sections ) , mounted on Polylysine slides ( Thermo Scientific ) , and stored at −80°C until in situ hybridization . Arc pre-mRNA probes were synthesized using the digoxigenin-labeled UTP kit ( Roche Diagnostics ) . Following a similar fluorescent in situ hybridization ( FISH ) protocol as Nakamura and colleagues ( 2013 ) [24] , slides were fixed with 4% buffered paraformaldehyde and rinsed with 0 . 1 M PBS . Slides were treated with an acetic anhydride/triethanolamine/hydrochloric acid mix , rinsed , and briefly soaked with a prehybridization buffer . The tissue was hybridized with the digoxigenin-labeled Arc probe overnight at +65°C . Following hybridization , slides were rinsed with buffer solutions and treated with an antidigoxigenin-horseradish peroxidase ( HRP ) conjugate ( Roche Molecular Biochemicals ) and a cyanin-5 substrate kit ( CY5 , TSA-Plus system , Perkin Elmer ) . Nuclei were counterstained with 4’ , 6’-diamidino-2-phenylindole ( DAPI; Vector Laboratories ) . To detect Arc , 1 slide per animal was processed . Slides contained 8 nonconsecutive brain sections ( approximately −3 . 00 mm AP; Fig 2B ) [44] , and images from 3 nonadjacent sections distant approximately 200 microns ( i . e . , covering approximately 400 microns ) at this AP level were acquired . The number of activated neurons was evaluated on approximately 90 neurons per image on 3 nonadjacent sections ( i . e . , on approximately 270 neurons per area of interest ) . Of note , the distal CA3 window is located in the central portion of CA3 , and not more ventrally , because the very ventral portion of CA3 belongs to proximal CA3 ( close to the DG ) . Images were captured with a Keyence Fluorescence microscope ( BZ-9000E; Japan ) . Images were taken with a 40× objective ( z-stacks of 0 . 7-μm–thick pictures; see example Fig 3A–3D ) . Exposure time and light intensity were kept similar for image acquisition . As first described in the seminal work of Guzowski and colleagues [49] , contrasts were set to optimize the appearance of intranuclear foci [43 , 44 , 51 , 52] . To account for stereological considerations , neurons were counted on 8-μm–thick sections that contained 1 layer of cells , and only cells containing whole nuclei were included in the analysis [55] . The quantification of Arc expression was performed in the median 60% of the stack in our analysis because this method minimizes the likelihood of taking into consideration partial nuclei and decreases the occurrence of false negative . This method is comparable to an optical dissector technique that reduces sampling errors linked to the inclusion of partial cells into the counts and stereological concerns because variations in cell volumes no longer affect sampling frequencies [56] . Also , as performed in a standard manner in Arc imaging studies , counting was performed on cells ( >5 μm ) thought to be pyramidal neurons or interneurons because small non-neuronal cells such as astrocytes or inhibitory neurons do not express Arc following behavioral stimulation [57] . The designation “intranuclear-foci–positive neurons” ( Arc-positive neurons ) was given when the DAPI-labeled nucleus of the presumptive neurons showed 1 or 2 characteristic intense intranuclear areas of fluorescence . DAPI-labeled nuclei that did not contain fluorescent intranuclear foci were counted as “negative” ( Arc-negative neurons ) [49] . Percentage of Arc-positive neurons was calculated as follows: Arc-positive neurons ÷ ( Arc-positive neurons + Arc-negative neurons ) × 100 . The home-caged group was generated to control for Arc baseline expression , which is known to be low ( S1 Fig and S4 Data ) . All statistical analyses were implemented in the R statistical package ( version 3 . 4 . 2 ) . To assess the relationship between Arc expression and the spatial and temporal discrimination indices D2space and D2time , 2 complementary analyses were conducted that led to comparable results: ( i ) fitting a linear mixed model to the Arc expression using the continuous discrimination indices and ( ii ) standard correlation analyses for each region separately . For the first analysis , we estimated a linear mixed model that is conceptually comparable to a linear regression or partial correlations but explicitly models the repeated measurement of Arc expression from the same animals in the 4 brain regions and thus allows a comparison of the estimated effects across brain regions , as well as a comparison of the effects of both discrimination indices directly [58] . We used the “mixed” function in the “afex” package ( version 0 . 18 ) [59] , which in turn uses the “lme4” package ( version 1 . 1 ) [60] for the estimation; p-values were computed using the Satterthwaite approximation of the degrees of freedom when assessing the significance of the fixed effects as well as using parametric bootstrapping , as implemented by the “mixed” function . The linear mixed model consisted of fixed effects for categorical variables “region” ( CA1 and CA3 ) and “proximodistal” ( proximal and distal ) and the two discrimination indices ( D2time and D2space ) and their interactions . We specified a random intercept per animal as a random factor to explicitly model the repeated measurement of Arc expression . To conduct post hoc comparisons , we computed area-specific mean activity and the slopes of temporal and spatial discrimination indices of the fixed effects using the “lsmeans , ” “lstrends , ” and “cld functions” in the “lsmeans” package ( version 2 . 27 ) [61] . Whether these area-specific effects were significantly different from 0 was assessed by inspecting the 95% CI—if the interval does not include 0 , the effect is considered significantly different from 0 . By modeling the influence of the increase in both discrimination indices concurrently , we also estimated the increase in Arc expression when both the spatial and temporal discriminations were successful . Specifically , the slope for “space+time”—D2space+time—which quantifies this increase , was estimated by calculating the sum of the slopes of spatial and temporal discrimination indices . For visualization purposes , contour lines were used to represent the relative relationship between the discrimination indices and the Arc activity as predicted by the fitted model . Contour lines are extrapolated beyond experimental data points by visualizing the model prediction at those hypothetical discrimination ratios . Each line represents the set of spatial and temporal discrimination indices for which the mixed model predicts the same level of Arc activity . Note that these lines are parallel because the underlying model assumes a linear combination of the discrimination indices D2time and D2space . A non-linear model including quadratic terms and the interaction of the 2 discrimination indices gave comparable results , therefore only the simpler linear model is reported here . For the second analysis ( ii ) , we calculated standard correlation coefficients between the Arc expression and the spatial and temporal discrimination indices , respectively . This straightforward analysis minimizes potential problems related to misspecifying the above mixed model that could lead to higher rates of false positives [62] but does not explicitly model the influence of both discrimination indices at the same time ( i . e . , correlations between Arc expression and the spatial D2 ignore the potential influence of temporal D2 , and vice versa ) .
Patterns of object exploration varied between animals , leading to a substantial spread of the temporal and spatial discrimination indices ( Fig 4 ) . Discrimination indices did not correlate with the total objects exploration time during study phases 1 and 2 ( 66 . 48 s ± 6 . 19 s [D2time: r = 0 . 21; p = 0 . 34; and D2space: r = 0 . 056; p = 0 . 806] and 66 . 26 s ± 7 . 49 s [D2time: r = −0 . 07; p = 0 . 75; and D2space: r = −0 . 015; p = 0 . 95] , respectively] ) nor at testing ( 48 . 86 s ± 4 . 05 s [D2time: r = 0 . 17; p = 0 . 46; and D2space: r = 0 . 11; p = 0 . 64]; and see also S1 Table and S1 Data ) , indicating that differences in total object exploration time per se could not account for the differences in discrimination indices reported in the present study . To assess the relationship between Arc expression and the spatial and temporal discrimination indices , D2space and D2time , the following 2 complementary analyses were conducted: ( 1 ) fitting a linear mixed model to the Arc expression using the continuous discrimination indices and ( 2 ) performing standard correlation analyses between Arc expression and the discrimination indices . A contour plot of predicted Arc expression as a function of the spatial and temporal D2s ( Fig 4 ) showed that , while the recruitment of all 4 areas varied with the spatial D2 ( albeit to different degrees ) , distal CA1’s engagement varied to a larger extent with the temporal D2 , as indicated by the contour lines for distal CA1 being more vertical than horizontal . In contrast , the contour lines for proximal CA1 and CA3 and distal CA3 ( being more horizontal than vertical ) reflected a stronger sensitivity for spatial discrimination . In addition , statistical comparisons of the slope of D2time showed that Arc expression varied with the temporal D2—especially in distal CA1 ( b = 11 . 32 ) and to a lesser extent in distal CA3 ( b = 6 . 95 ) —but failed to do so in other areas ( proximodistal by D2time interaction: χ2 ( 1 ) = 11 . 13; p = 0 . 002; all other effects: all p > 0 . 12 ) ( see also S1A and S1B Table ) . Moreover , further post hoc comparisons revealed that activity levels increased more as the temporal discrimination became higher in distal CA1 than in proximal CA1 ( b = 0 . 30 ) or CA3 ( b = 3 . 67 ) ( both p < 0 . 005 ) and that distal CA3 activity varied more with D2time than proximal CA3 activity ( p = 0 . 048 ) . Notably , investigation of the CIs of the slopes underlined the robustness of the findings for distal CA1 , as the standard 95% CI of the slope of D2time excluded 0 only in distal CA1 ( i . e . , the slope differed from 0 ) , while a more relaxed 90% CI was necessary to get similar results for distal CA3 . In other words , the slope of D2time differed from 0 for distal CA1 but not for distal CA3 , suggesting a more robust tuning of distal CA1 than distal CA3 to temporal information . In summary , under standard statistical criteria , the present results suggest that especially distal CA1 is sensitive to the retrieval of temporal information . In contrast to the D2time slopes , comparisons of the spatial D2 slopes showed that Arc expression increased in all areas as a function of spatial discrimination , although the extent to which this was the case differed by area ( D2space effect: χ2 ( 1 ) = 17 . 98; p = 0 . 001; region by D2space interaction: χ2 ( 1 ) = 5 . 20; p = 0 . 030; region by proximodistal by D2space interaction: χ2 ( 1 ) = 10 . 16; p = 0 . 002; no other interaction effect: p > 0 . 050; see also S1 Table ) . Indeed , post hoc comparisons showed that Arc expression in distal CA1 ( b = 7 . 56 ) increased the least with increasing spatial discrimination and that this increase was not significantly different from 0 ( i . e . , the standard 95% CI for the slope of D2 space included 0 , but a less strict 90% CI did not ) . In addition , the D2space slopes for the areas part of the “spatial” subnetwork—distal CA3 ( b = 24 . 52 ) and proximal CA1 ( b = 16 . 62—were larger than those part of the “non-spatial” subnetwork—distal CA1 ( b = 7 . 56 ) and proximal CA3 ( b = 13 . 49 ) ( distal CA3 versus proximal CA3: p = 0 . 013; distal CA3 versus distal CA1: p = 0 . 0002; proximal CA1 versus distal CA1: p = 0 . 037 ) . Thus , these results indicate that proximal CA1 and CA3 , and distal CA3 , are most tuned to spatial information , whereas distal CA1 is least tuned to spatial information . Finally , estimating the influence of both discriminations simultaneously ( i . e . , predicting how Arc activity changes when both dimensions are recalled as captured by the slope of “D2space+time” ) revealed that all areas were recruited at a comparable level ( main effect of D2space+time: F ( 1 , 19 ) = 15 . 41; p = 0 . 0009; no other significant effects , all p > 0 . 05; see S1C Table ) . Altogether , the linear mixed-model approach indicates that Arc activity in the distal CA1 most strongly relates to retrieving temporal information and that proximal CA1 and CA3 and distal CA3 are especially tuned to spatial information . As observed with the linear mixed-model approach , distal CA1 correlated with the temporal discrimination index ( r = 0 . 475; p = 0 . 026; Fig 5 ) but not with the spatial discrimination index ( p = 0 . 65; S2 Fig ) . In contrast , all other areas correlated with the spatial discrimination index ( proximal CA1: r = 0 . 723; p < 0 . 0001; proximal CA3: r = 0 . 675; p = 0 . 0006; distal CA3: r = 0 . 720; p = 0 . 0002; Fig 5 ) but not with the temporal discrimination index ( proximal CA1: p = 0 . 17; proximal CA3: p = 0 . 14; distal CA3: p = 0 . 66; S2 Fig ) . In summary , these analyses show , in line with the mixed-modeling results , that distal CA1 is especially tuned to temporal information and proximal CA1 and CA3 as well as distal CA3 are tuned to spatial information .
One question we addressed in this study is whether the temporal content of an event is preferentially processed by the proximal CA3–distal CA1 “non-spatial” subnetwork as it was the case for other non-spatial information , such as odors [24] . This appears to be the case at the level of distal CA1 because Arc expression increased in this area as the temporal discrimination ratio did ( Fig 4 ) . In addition , the slope of temporal D2 was higher in distal CA1 than in proximal CA1 ( or any other areas ) , showing for the first time that the temporal context of an event is topographically organized along the proximodistal axis of CA1 . These results also indicate that processing temporal information recruits the same part of the “non-spatial” subnetwork as other non-spatial information , such as odors [24] . Moreover , Arc expression in distal CA1 correlates only with temporal discrimination ratios ( and not with spatial ratios; S2 Fig ) , further supporting the idea of a selective role of distal CA1 in the processing of temporal information . The recruitment of distal CA1 is unlikely to solely reflect the processing of object information as activity patterns are strikingly different between areas despite the fact that the same objects’ information ( in time or space ) is processed . In contrast to CA1 , CA3 was not engaged to a critical extent in processing temporal information , indicating that the temporal content is differentially computed than object or odor information at this level . These findings provide further support to the lesion , in vivo electrophysiology , and optogenetic studies that have indicated a preferential role of CA1 in temporal information processing over that of CA3 and suggest that distal CA1 is likely to be the home location of the “time cells” recently identified in CA1 [31–38 , 63 , 64] . As a support for the latter hypothesis , a thorough review of these studies showed that distal CA1/the distal half of CA1 was indeed targeted in these reports . The hypothesis of a preferential involvement of distal CA1 in the processing of time is also indirectly supported by evidence from a trace eye-blinking conditioning study showing that reversible inactivation of the LEC ( which preferentially projects to distal CA1 ) impairs the retrieval of a memory for an association between temporally discontiguous stimuli [65] . Likewise , in vivo electrophysiology and IEG studies showed that the perirhinal cortex , which provides major inputs to the LEC , plays an important role for temporal-order memory and for object memory across large delays [66–68] . This might indicate that the LEC is the source of temporal information provided to distal CA1 . Preliminary data from the Moser laboratory using population-level analyses of electrohysiological recordings partly support this hypothesis by reporting that LEC’s involvement within this frame depends on tasks’ demands , with free foraging tasks eliciting a stronger temporal representation in the LEC than continuous alternation/back-and-forth running tasks [69]; of note , such tasks’ demand dependency in the LEC were also reported in recent lesion and Arc imaging studies , albeit for the processing object and space information [70 , 71] . Our findings of a preferential involvement of distal CA1 in time processing depart from the standard model of episodic memory which , by extrapolation , predicts that temporal information would rather be processed by proximal CA1 because it mainly receives projections from the MEC , a part of the “where–when” pathway [2 , 4] . Even though the effect of the reversible inactivation of the MEC on temporal encoding in CA1 might be controversial [65 , 72] , the latter hypothesis is supported by some electrophysiology studies that brought evidence of an involvement of the MEC in the integration of elapsed time and distance and in the temporal organization of CA1 activity [73 , 74] . Thus , further studies comparing directly LEC and MEC function within this frame will be necessary to clarify the nature and the extent of the contribution of the LEC and the MEC to temporal information processing and , by extension , the role of the distal and proximal parts of CA1 within this frame . The second question of the present study was to assess whether the processing of spatial information bound to objects was topographically organized along the proximodistal axis of the hippocampus as it was shown for locations [25] , i . e . , whether it would also preferentially recruit the “spatial” hippocampal subnetwork . Our results show that , in addition to increasing with the temporal discrimination ratio , Arc expression in distal CA1 also increased as a function of the spatial discrimination index , indicating a relative tuning of distal CA1 to spatial information ( Fig 4 ) . However , and possibly as a further token of a preferential involvement of distal CA1 in the processing of temporal information , distal CA1 was the least tuned to the spatial discrimination when compared to all other areas . Indeed , the slopes of the spatial discrimination index for distal CA3 and proximal CA1 and CA3 were all larger than that of distal CA1 . A key involvement of these regions was further supported by standard correlations and mixed-model analyses showing that Arc expression in proximal CA1 and both parts of CA3 correlated with spatial but not with temporal discrimination indices . This result confirms the central role of CA1 and CA3 in spatial memory as well as the existence of a functional segregation between the CA1 and CA3 subfields [30 , 75 , 76] . Moreover , because distal CA1 receives preferential projections from the LEC and proximal CA1 from the MEC , our findings are , by extension , in agreement with in vivo electrophysiology and Fos imaging studies that have shown that the LEC and the MEC are involved in the processing of object-in-place information [12 , 77–79] . These studies , however , did not directly assess the contribution of the proximal and distal parts of CA1 to the memory for object in place , but see Ito and Schuman [13] . In addition , our results show that processing spatial information bound to objects recruits the same part of the “spatial” subnetwork as processing locations because proximal CA1 was more tuned to spatial discrimination than distal CA1 , and they indicate that the processing of object-in-place information is also topographically organized along the proximodistal axis of CA1 . This finding , together with recent studies reporting a stronger engagement of proximal CA1 in the case of contextual changes and a weaker recruitment for non-spatial memory , shows that CA1’s functional segregation holds in various experimental settings and that the mechanism sustaining spatial information processing in CA1 could be the same when the information processed is related to a context or to an object ( the object’s location ) [24 , 10] . In CA3 , a robust proximodistal segregation was also observed in terms of processing spatial information because distal CA3 was more tuned to spatial information than proximal CA3 . This engagement of CA3 for spatial information processing is in line with previous lesion and electrophysiology studies—which , however , did not dissociate the contribution of proximal and distal parts of CA3 [80 , 81] . For example , lesions of CA3 impair object–place or odor–place–paired associations [82] , and in vivo electrophysiological studies showed that spatial firing patterns in CA3 distinguish different environments in a foraging task [38] . Conversely , lesions of CA3 did not affect performance on an object–trace–odor task [63] . This stronger involvement of distal CA3 over proximal CA3 in dealing with object-in-place information matches results of a previous finding reporting a similar pattern for the processing of locations with a high-demand memory task [24] , indicating that the proximodistal functional segregation in CA3 also holds independently of the type of spatial information processed ( i . e . , locations or object-in-place ) . Thus , altogether , these data show that , at the exception of the temporal information in CA3 , the retrieval of spatial ( locations ) or non-spatial ( temporal ) information bound to objects engages the same parts of CA1 and CA3 as retrieving information related to objects/odors or locations alone , respectively , indicative of a robust segregation of the spatial and non-spatial information along the proximodistal axis of CA1 and CA3 . Finally , in the present study , we also asked whether the concept of a segregated processing of spatial and non-spatial information in the hippocampus and the standard concept of an integration of this information at this level are “compatible” and based on the same networks . To be “compatible , ” we hypothesized that , during memory retrieval , one of the subnetworks ( “spatial” or “non-spatial” ) would be recruited over the other when only one dimension of the memory is salient ( spatial or non-spatial ) . In contrast , all areas would be activated to comparable levels when both dimensions are salient , i . e . , no proximodistal differences would be observable in this case . Here , we report that , at the exception of the temporal information in CA3 , proximodistal differences fitting the description of the “spatial” or “non-spatial” subnetworks were detected when animals discriminated on the basis of only spatial or temporal information as captured by the comparisons of the slopes of spatial or temporal discrimination indices , respectively . In addition , all areas were engaged to a similar extent when animals successfully discriminated based on the concurrent retrieval of both dimensions as substantiated by the comparisons of the slopes of the discrimination indices for space + time . Thus , these results indicate that the “segregated” and the “integrated” views of information processing in the hippocampus might be , to a large extent , based on the same principle ( s ) and networks but might differ in the nature and the number of dimensions of the memory to be retrieved . The present study focused on assessing the tuning of the proximal and distal parts of CA1 and CA3 to spatial and temporal information . Assessing whether the spatial and the non-spatial dimension of the memory are combined or kept segregated when both dimensions are retrieved , identifying the specific processes underlying the patterns of activity reported , or the basis of interindividual differences in behavioral performance ( i . e . , whether mice preferentially processed temporal and/or spatial information or failed to do so ) are beyond the scope of the study and will require further investigations . Moreover , despite the fact that Arc expression was reported to better reflect behavioral task demands than other IEGs , such as c-fos and zif268 , and not simply stress levels or motor activity [24 , 49 , 50] , the latter processes and others might still partially contribute to the levels of Arc expression observed at test . For this reason , it was crucial to keep experimental conditions ( handling , number of stimuli , locomotor activity , etc . ) identical across animals . Since under this condition it could be ruled out that between-area differences could not stem from differences in total objects exploration times ( comparable for phase 1 , 2 , and 3 ) or from neophobia ( all objects were experienced prior to the testing phase ) , between-area comparisons of Arc expression are expected to reflect the processing of spatial and/or temporal information . Furthermore , the proximodistal differences in patterns of activity reported here are unlikely to be a by-product of the anatomical levels at which CA1 and CA3 are imaged because proximodistal differences at these levels were also reported independently of whether the septal level , the temporal level , or the transverse axis of the hippocampus ( at which the proximal and the distal parts of CA1 and CA3 are located at different dorsoventral levels ) were imaged in a previous study [24] . In summary , these findings complement our recent studies that revealed that spatial information ( location ) and non-spatial information ( odors ) can be processed in a segregated manner within the hippocampus [24 , 25] by showing that temporal and spatial information bound to objects engage , at least part of , the same subnetworks . In addition , we identified the distal part of CA1 as a potential “hub” for time cells and showed that the new concept of segregated processing of spatial and non-spatial information within the hippocampus is , to a large extent , reconcilable with the traditional view of an integration of this information at the level of the hippocampus . | Departing from the most influential model of episodic memory ( the two-streams hypothesis ) , we have recently proposed a new concept of information processing in the hippocampus according to which “what” one remembers and “where” it happens might be processed by distinct subnetworks segregated along the proximodistal axis of the hippocampus , a brain region tied to memory function , instead of being systematically integrated at this level . Here , we focused on the processing of temporal and/or spatial information in the proximal and distal parts of CA1 and CA3 in mice to test whether the two concepts are reconcilable . To do so , we used an imaging method with cellular resolution based on the detection of the RNA of the Immediate Early Gene ( IEG ) Arc , which is tied to synaptic plasticity and memory demands , and correlated imaging results with memory performance . Our data confirm the existence of subnetworks segregated along the proximodistal axis of CA1 and CA3 that preferentially process spatial and non-spatial information and suggest a key involvement of distal CA1 in temporal information processing . In addition , they show that the two models are complementary to a large extent and posit the “segregated” model as a viable alternative for the two-streams hypothesis . | [
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"analy... | 2018 | The memory for time and space differentially engages the proximal and distal parts of the hippocampal subfields CA1 and CA3 |
Interim results from the Guinea Ebola ring vaccination trial suggest high efficacy of the rVSV-ZEBOV vaccine . These findings open the door to the use of ring vaccination strategies in which the contacts and contacts of contacts of each index case are promptly vaccinated to contain future Ebola virus disease outbreaks . To provide a numerical estimate of the effectiveness of ring vaccination strategies we introduce a spatially explicit agent-based model to simulate Ebola outbreaks in the Pujehun district , Sierra Leone , structurally similar to previous modelling approaches . We find that ring vaccination can successfully contain an outbreak for values of the effective reproduction number up to 1 . 6 . Through an extensive sensitivity analysis of parameters characterising the readiness and capacity of the health care system , we identify interventions that , alongside ring vaccination , could increase the likelihood of containment . In particular , shortening the time from symptoms onset to hospitalisation to 2–3 days on average through improved contact tracing procedures , adding a 2km spatial component to the vaccination ring , and decreasing human mobility by quarantining affected areas might contribute increase our ability to contain outbreaks with effective reproduction number up to 2 . 6 . These results have implications for future control of Ebola and other emerging infectious disease threats .
The 2014–15 Ebola virus disease ( EVD ) epidemic in West Africa was the largest Ebola outbreak ever documented with a total of 28 , 646 cases and 11 , 323 deaths reported as of March 30 , 2016 [1 , 2] . At the start of the epidemic , no licensed vaccines were available for Ebola . In July 2015 , Henao-Restrepo and colleagues [3 , 4] demonstrated 100% ( 95% confidence interval ( CI ) : 74 . 7–100 . 0 ) efficacy of the rVSV-ZEBOV vaccine against EVD using a ring vaccination cluster randomised trial in Guinea . Rings , i . e . , clusters , were defined as the contacts and contacts of contacts of confirmed EVD cases . Ring vaccination strategies were instrumental in the elimination of local outbreaks of smallpox during the eradication phase [5] . Several modelling studies evaluating targeted smallpox vaccination strategies have been performed ( see for instance [6 , 7] ) . Modelling results highlighted the time from symptom onset to case isolation and the fraction of contacts identified by contact tracing as the most important factors determining the success of ring vaccination strategies . Questions remain about whether a ring vaccination strategy can be effective in containing EVD outbreaks , such as the EVD flare-up observed in West Africa in 2016 [2] . We use a spatially explicit agent-based model of EVD transmission based on a detailed synthetic population of Sierra Leone ( see Methods and SI ) [8 , 9] . The model is calibrated to reproduce the most important features of the EVD outbreak in Pujehun district , that can be considered typical in terms of both transmissibility and key time periods . Specifically , the observed basic reproduction number was R0 = 1 . 63 , in the range of values estimated for West Africa of 1 . 6–2 . 2 [8 , 10–13] . Furthermore the average generation time of 13 . 7 days , and the average incubation time of 9 . 7 days are similar to the WHO estimates of 15 . 3 days and 11 . 4 days [10] , respectively . Here we examine the effectiveness of ring vaccination with the rVSV vaccine in containing the spread of EVD . We focus on possible future EVD outbreaks reemerging in West Africa . We assume , however , that the existing infrastructure for managing the 2014–15 EVD epidemic has at least partly dissolved . Results apply also to the emergence of EVD in different African countries where this infrastructure is not present at all . In this context , we assume that ring vaccination will be the primary containment strategy . Specifically , we consider the following paradigm for containing future EVD outbreaks: i ) isolation of index cases and identification of contacts and contacts of contacts of index cases and ii ) vaccination of contacts and contacts of contacts . Additional non-pharmacological interventions , early isolation of secondary cases through contact tracing , will eventually be implemented on top of vaccination . We focus on ring vaccination’s ability to contain an early outbreak by reporting the epidemic prevention potential ( EPP [17–19] see Methods ) . The EPP reflects the probability of an intervention containing an outbreak . We consider different levels of uncertainty and different values of the effective reproduction number Re , the average number of secondary cases generated by a primary infector . This analysis allows us to identify the main determinants of the probability of outbreak containment , and expands upon previous modeling work [20 , 21] as we consider the important impact of varying the ring definition ( contacts , contacts of contacts , and spatial components ) , as well as the performance of ring vaccination assuming different levels of Re and contact tracing .
Our model ( see the S1 File for details ) considers the Pujehun district of Sierra Leone . The model population of 375 , 000 individuals was assigned to one central town ( population 30 , 000 ) and neighbouring villages , reflecting district-level data from the Demographic and Health Survey [22] . Individuals are assigned to specific households , and households are linked to create “extended households” as are typical in rural Africa . The model is an extension of a model used to simulate interventions during the 2014 outbreak [9] . We used microsimulations to explicitly model Ebola transmission within households and extended households ( 35 . 9% and 38 . 5% of transmission in Pujehun district , respectively; 74 . 4% of transmission combined ) and in the general community , including non-household and health care-related contacts ( 25 . 6% of transmission ) [9] . Ebola transmission occurring during burial ceremonies is captured within these estimates . The extended household defines the set of contacts and contacts of contacts that could be identified through contact tracing . As a baseline we assume that all contacts of the extended household ( 74 . 4% of transmission combined ) can be identified through contact tracing . We also consider a more optimistic scenario where we assume that 90% of contacts can be identified through contact tracing . This assumption stems from the observation that most of non-family transmission events in Pujehun district were observed among friends [9] and thus they could be potentially traceable , at least to some extent . The relative proportions of transmissions are consistent with findings from other West African regions [8 , 15 , 16] . The model allows for heterogeneity in transmission [9 , 14] and for variation in age-specific risk of infection [9] . Because we used a heterogeneous transmission model and included the contact structure of the population , the distribution of secondary cases per index case has a long tail with non-negligible probabilities for 10 or more secondary cases . In Pujehun the distribution of secondary cases was overdispersed , resembling a negative binomial with dispersion parameter k = 0 . 45 , comparable to k = 0 . 18 observed in Conakry , Guinea [14] . Furthermore , most of the transmission events occurred among close contacts , with 74 . 3% of cases exposed in family or extended family , similar to the 72% estimated for Conakry , Guinea [15] and to the 71 . 4% observed in Montserrado , Liberia [16] . In our model we considered Re values for EVD from 1 . 4 to 2 . 6 , which extends beyond the plausible range of values estimated in West Africa ( 1 . 6 to 2 . 2 ) [8 , 10–13] . In fact , the transmission potential for future EVD outbreaks , possibly originating in different regions of Africa , could be different from that observed in West Africa . For instance , it could be either decreased or increased by human behaviour , by the ability of health care workers to limit transmission in health care facilities , and by burial procedures . Key model parameters and their assumed values are summarised in Table 1 . We measure the impact of ring vaccination on simulated outbreaks in terms of EPP [17] , defined as EPP = 1 − pI /pNI , where pI and pNI are the probabilities of an uncontained outbreak when an intervention is used ( e . g . ring vaccination ) or no intervention is used , respectively . Here an outbreak is considered uncontained if the number of cases exceeds 300 , though the results are consistent if this threshold is varied by up to 30% . Because the probability of an uncontained outbreak increases with Re , the EPP measures the impact of an intervention in preventing an uncontained outbreak , standardising by the background probability of an uncontained outbreak . An EPP of 1 indicates that an intervention always contains an otherwise uncontained outbreak , while an EPP of 0 indicates that the intervention never contains an outbreak that would have been uncontained . We provide estimates of the number of vaccine doses required to implement ring vaccination . In particular , we report the number of vaccine doses required for successful containment only . Indeed , for an uncontained outbreak , it is likely that the epidemic would invade other districts and neighbouring countries . Instead of local containment , intervention measures would likely focus on outbreak mitigation , and vaccination strategies would be integrated with other intervention options .
By assuming baseline values of model parameters ( see Table 1 ) , the probability of an uncontained outbreak in the no-intervention scenario is shown in Fig 1A . The no-intervention scenario for a randomly mixing population considers a situation with little or no readiness of the health care systems—a reasonable assumption for the very early phase of the outbreak—and with an effective reproductive number that accounts for the baseline practices for transmission control . The outbreak probability increases from about 23% for Re = 1 . 4 to 54% for Re = 2 . 6 . Outbreak probabilities are lower than what would be theoretically predicted by p = 1 − 1/Re . This is expected due to the heterogeneity in transmission [24] . The impact of ring vaccination is reported in Fig 1B . The EPP of ring vaccination is near 1 when Re ≤ 1 . 4 . The EPP of ring vaccination declines as Re increases , decreasing to approximately 0 . 40 when Re = 1 . 8 , and to nearly 0 when Re ≥ 2 . 4 . The probability of an uncontained outbreak by assuming baseline ring vaccination increases from about 0 . 3% for Re = 1 . 4 to 53% for Re = 2 . 6 . When Re = 1 . 6 , our model returns an estimated vaccine effectiveness ( see S1 File ) consistent with the 75 . 1% effectiveness observed in the Guinea ring vaccination trial [4] ( see S1 File ) . On average , 14 rings ( max 169 ) and 847 vaccine doses ( max 10 , 659 ) are required to contain an outbreak when Re = 1 . 6 ( Fig 1C and 1D ) . The mean number of cases with baseline ring vaccination ranges from 15 . 5 ( 95%CI:1–121 ) for Re = 1 . 4 to 2 . 0 ( 95%CI:1–12 ) for Re = 2 . 6: in fact , for small values of Re it is possible to contain the outbreak with ring vaccination even after a few generations of cases , while for large values of Re the outbreak either will be contained early or it will be not contained . These results suggest that ring vaccination strategies with baseline intervention parameters can be highly effective and affordable for containing an EVD outbreak when Re ≤ 1 . 6 . Results of an extensive sensitivity analysis on all parameters regulating EVD transmission and interventions are discussed in the S1 File . Briefly , results show that achieving high vaccine coverage within the ring ( ≥ 80% ) , adding a spatial component to the ring definition ( 2 km ) , decreasing human mobility , and decreasing the time from symptom onset to isolation to 2–3 days ( e . g . through contact tracing ) can drastically increase the EPP ( Fig 2 ) . For values of Re > 1 . 6 , outbreak containment will likely require additional interventions or higher vaccine coverage and earlier outbreak detection . One option is to add a spatial ( S ) component to the ring vaccination strategy , vaccinating all eligible individuals within a fixed radius around the index case , ( C&CC+S ) with 65% coverage . Outbreak containment can be further improved if other interventions are simultaneously implemented , including reducing time to isolation of cases ( 2–3 days from onset to hospitalisation ) , increasing ring vaccination coverage to 90% of eligible individuals , and reducing public access to infected areas . We refer to this potentially feasible combination as “improved health systems” and estimate its added impact in Fig 3A . When these interventions are added , the EPP is nearly 1 for all values of Re . The combinations of interventions discussed above all seem implementable , at least to some extent , considering that i ) vaccine safety and efficacy have been demonstrated in children; ii ) the average time spent in the community by EVD cases was reduced to 2 days in the last part of the 2014–15 EVD epidemic in West Africa; iii ) a spatial ring of about 2 km requires targeting a very limited number of villages; iv ) reducing human mobility can be achieved through roadblocks ( e . g . , through checkpoints with medical screening , as done during the 2014–15 EVD epidemic in West Africa or defining quarantine areas . We compare ring vaccination with preemptive and reactive mass vaccination strategies in Fig 3B as these strategies have been considered as alternatives for containing EVD [21] . We consider preemptive mass vaccination covering 25% and 50% of all eligible individuals in the region ( corresponding to 93 , 750 and 187 , 500 vaccine doses , respectively ) . We model reactive vaccination as a large spatial ( S ) ring covering 65% of eligible individuals in an area 20km around the index case . Our results suggest that reactive mass vaccination may be more effective than preemptively mass vaccinating 25–50% of the eligible population , and requires significantly fewer vaccine doses , especially when Re < 1 . 8 . For instance , if Re = 1 . 6 , an average of 43 , 027 vaccine doses overall ( upper 95%CL: 188 , 772 ) are required to contain an outbreak using reactive mass vaccination .
We have shown that ring vaccination of contacts and contacts of contacts using the highly efficacious rVSV-ZEBOV vaccine can effectively contain an EVD outbreak when Re ≤ 1 . 6 . Containment is likely to occur for values of Re up to 1 . 8 if the outbreak is readily detected and the vaccine coverage in the rings is as high as 80% . Adding a 2km spatial component to the ring definition , corresponding to targeting 2 . 7 villages on average ( SD: 1 . 3 ) , further enhances the effectiveness of ring vaccination , and reinforcement of the healthcare system plus ring vaccination can all but eliminate the probability of an uncontained outbreak . Specifically , shortening the time from symptoms onset to hospitalisation to 2–3 days on average through contact tracing procedures , adding a 2km spatial component to the ring definition , and decreasing human mobility through quarantine of affected areas would result in likelihood of containment close to 1 for values of Re up to 2 . 6 . Alternatively , for values of Re larger than 1 . 8 , reactive mass vaccination in a 20km radius around the index case greatly decreases the probability of an uncontained outbreak and reduces the public health burden while requiring a fraction of the doses necessary for preemptive mass vaccination . However , even in the case of larger values of Re ( e . g . Re = 1 . 84 as observed in Liberia [8] ) it should be considered that most initial transmission in health care settings , that was relevant in Liberia [8] , could be avoided by preventive vaccination of health care workers; thus contributing to reduce the initial Re and to increase the likelihood of containment with ring vaccination . Moreover , given the experiences of previous Ebola outbreaks where no vaccine was available ( e . g . , the 2014 outbreak in Nigeria ) and of occasional flare-ups in West Africa that have been rapidly brought under control with traditional control strategies [16] , it is likely that traditional non-pharmaceutical measures will still be considered , together with ring vaccination , to manage future EVD outbreaks , thus contributing to further reduce Re . Our model does not consider all these measures explicitly ( only hospitalisation of cases is explicitly simulated ) . While this is a limitation of our study , we accounted for the direct effects of these additional measures . Indeed , the considered reduction of the time from symptom onset to hospitalisation can be interpreted as the result of contact tracing procedures; the considerable reduction of human mobility can be interpreted as the result of quarantine of affected areas . While the model has limitations , including sensitivity to assumptions about hospitalisation rate , number of Ebola beds , and time until the outbreak is first detected , the results are informative . Our results should also be discussed in the light of previous modeling works . In [20] the authors evaluate the impact of vaccinating only contacts of cases . The study was published before the publication of the original papers describing the rVSV vaccination trial in West Africa [3 , 4] , where a different definition of ring vaccination , considering also contacts of contacts , has been used . Difference with our results may be traced back to the fact that our analysis evaluates vaccination strategies including contacts and contacts of contacts . In [21] , authors observe that ring vaccination might not lead to containment of future EVD outbreaks . However , results depend on the assumption that cases missed by contact tracing transmit the infection much more than cases in known clusters of transmission ( 7 and 0 . 66 cases on average respectively ) . In particular this implies that the basic reproductive number increases proportionally to the percentage of missed cases . The authors themselves recognize this as a study limitation . We integrate into the model information on the percentage of cases generated in family or extended family ( 72% of transmission in Conakry , Guinea [15] , 71 . 4% in Montserrado , Liberia [16] , and 74 . 3% of transmission in Pujehun district , Sierra Leone [9] ) that allows us to set the lower limit of the percentage of traceable cases . Our approach is supported by the analysis conducted in [16] where authors found that 71 . 4% ( 15/21 ) of cases were listed as contacts . Our results indicate that the efforts using ring vaccination to contain EVD flare-ups in Guinea and Liberia should be successful . Plans are underway to create a mobile stockpile of rVSV-ZEBOV vaccine at the World Health Organisation ( WHO ) to contain future Ebola outbreaks [25] . The GAVI alliance has pledged funds to buy 300 , 000 doses of rVSV-ZEBOV vaccine for such a stockpile [26] . Based on the results here , the planned stockpile of 300 , 000 doses should be sufficient to implement ring vaccination policies for containing a timely detected Ebola outbreak at the source . If the outbreak is left unchecked and eventually invades other regions/countries obviously much more vaccine doses would be needed in the mitigation and eradication effort . Strategies based on spatial vaccination or mass vaccination might require a greater effort , especially in the case of outbreaks in urban settings . Targeted vaccination interventions , as outlined here , should be adapted for other emerging infectious disease threats , as was done in the past for smallpox [27] . The use of these control strategies , both for assessing effectiveness and actual containment , is part of the WHO plan for dealing with future emerging infectious disease threats [28] . The work presented here should be instrumental in moving this process forward . | When the 2014–15 Ebola outbreak in West Africa began , no licensed vaccines for the disease were available . The rVSV-ZEBOV vaccine was developed during the course of the epidemic and underwent a clinical trial demonstrating 100% efficacy when vaccinating contacts and contacts of contacts of confirmed Ebola cases ( an approach called ring vaccination ) . However , the trial did not provide any understanding on whether this vaccination strategy can be effective in containing future Ebola virus disease outbreaks . Through a modelling study on a region of Sierra Leone , we provide numerical estimates for the effectiveness of ring vaccination: we show that outbreaks with moderate transmission potential , with no more than 1 . 6 secondary cases generated by an index case on average , can be successfully contained; more extensive vaccination ( e . g . , including spatial rings around index cases ) and reinforcement of the healthcare system would increase the likelihood of containment even if the virus were more transmissible than in the past . Our results provide implications for control plans of possible future Ebola outbreaks . | [
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"soci... | 2016 | Containing Ebola at the Source with Ring Vaccination |
Rift Valley fever ( RVF ) , a re-emerging mosquito-borne disease of ruminants and man , was endemic in Africa but spread to Saudi Arabia and Yemen , meaning it could spread even further . Little is known about innate and cell-mediated immunity to RVF virus ( RVFV ) in ruminants , which is knowledge required for adequate vaccine trials . We therefore studied these aspects in experimentally infected goats . We also compared RVFV grown in an insect cell-line and that grown in a mammalian cell-line for differences in the course of infection . Goats developed viremia one day post infection ( DPI ) , which lasted three to four days and some goats had transient fever coinciding with peak viremia . Up to 4% of peripheral blood mononuclear cells ( PBMCs ) were positive for RVFV . Monocytes and dendritic cells in PBMCs declined possibly from being directly infected with virus as suggested by in vitro exposure . Infected goats produced serum IFN-γ , IL-12 and other proinflammatory cytokines but not IFN-α . Despite the lack of IFN-α , innate immunity via the IL-12 to IFN-γ circuit possibly contributed to early protection against RVFV since neutralising antibodies were detected after viremia had cleared . The course of infection with insect cell-derived RVFV ( IN-RVFV ) appeared to be different from mammalian cell-derived RVFV ( MAM-RVFV ) , with the former attaining peak viremia faster , inducing fever and profoundly affecting specific immune cell subpopulations . This indicated possible differences in infections of ruminants acquired from mosquito bites relative to those due to contact with infectious material from other animals . These differences need to be considered when testing RVF vaccines in laboratory settings .
Rift Valley fever ( RVF ) is a disease of ruminants and man caused by the mosquito transmitted Rift Valley fever virus ( RVFV ) , genus Phlebovirus , family Bunyaviridae [1] . This spherical shaped , enveloped virus has a negative-sense single-stranded RNA genome made up of 3 segments . The large ( L ) segment encodes for the viral RNA-dependent RNA polymerase while the medium ( M ) segment encodes the external glycoproteins ( Gn and Gc ) and the non-structural protein ( NSm ) . The small ( S ) segment is ambisense , coding for the nucleoprotein ( N ) in the antigenomic sense and the non-structural protein ( NSs ) in the genomic direction [2] . RVF outbreaks are frequently reported in Sub-Saharan African countries where the disease is endemic . These include Kenya , Tanzania , Somalia , South Africa , Sudan , Uganda , Madagascar and Senegal . However , outbreaks were also reported in Egypt , Yemen and Saudi Arabia indicating an expanding range for this disease [3] . RVFV is transmitted primarily by Aedes and Culex mosquitoes , with the latter serving as a magnifying host during outbreaks [2] . In addition to infectious mosquito bites , humans can also acquire RVF through contact with blood of diseased animals [4] , [5] . Outbreaks of RVF in endemic countries usually coincide with conditions such as periods of heavy rainfall and flooding , which favour heavy breeding of mosquito vectors [6] , [7] . RVF is characterized by large abortion storms and close to 100% mortality in newborn sheep , goats and cattle resulting in severe adverse socio-economic effects [8] . These animals carry high titres of virus ( 6 log10 to 8 log10 PFU/mL ) in their blood resulting in fever , inappetence , nasal discharges and diarrhoea [3] . However , adult sheep , goats and cattle are more resistant to RVFV and experience lower mortality rates between 10–30% [3] . Human RVF usually manifests as a mild and self-limiting fever , but in some patients may progress to a haemorrhagic fever , neurological disorder or blindness [2] , [3] . Innate and adaptive immune responses contribute to the clearance of RVFV in infected animals [3] , [9] . Evidence for the role of innate immunity is mostly based on results from experimental models [9]–[12] . Interferon alpha ( IFN-α ) is believed to protect against RVFV because monkeys that secreted this cytokine within 12 h of being challenged with RVFV did not develop disease [11] . However , RVFV NSs protein inhibits IFN-α and IFN-β production/induction , thereby enabling early replication and viremia [12]–[14] . Anti-RVFV antibodies are detectable 4 to 8 days following infection [15]–[17] . Neutralising antibodies are believed to be crucial for the protection of infected animals [2] , [11] . Although ruminants have since been recognized as the primary animal hosts , there is little knowledge of the pathogenesis of RVFV in goats . In 2–3 months old goats experimentally infected with RVFV , viremia was detected 24 h post subcutaneous inoculation and lasted for 3 days [18] . These goats also had a mild transient increase in rectal temperature . Mild fever was equally observed in goats inoculated by inhalation and virus could be recovered from throat washes 2 days after inoculation [18] . In addition , virus was apparently transmitted to contact goats . Clinical signs varied in severity depending on the route of inoculation and included lethargy , diarrhoea and occlusion of the eyes . All the goats died between days 9 and 70 post inoculation possibly due to RVF but secondary infections could have also contributed to these deaths . Gross and histopathology lesions were observed in the liver , lungs , kidneys , spleen and brain of infected goats [18] . An attenuated live RVFV vaccine ( Smithburn strain ) has also been shown to cause abortion in vaccinated pregnant goats and pathology in the liver , kidney and other organs of vaccinated kids [19] . There is still a remarkable paucity of data on RVFV innate and cell mediated immune responses in sheep , goats and cattle . Knowledge of the pathogenesis and immune response to RVFV in these domestic ruminants is crucial for rational design of new vaccines and/or evaluation of existing vaccines for veterinary and human use . Therefore , to better understand RVF in small ruminants , we performed experimental infection of goats with RVFV . The C-type lectins , DC-SIGN and L-SIGN have been identified as probably receptors for arthropod borne viruses ( arboviruses ) [20] . Similarly , DC-SIGN has recently been identified as a receptor for Phleboviruses including RVFV [21] . Furthermore , insect cell-derived arboviruses belonging to the Alphavirus genus were more infectious to monocyte-derived dendritic cells ( MoDCs ) compared to mammalian cell-derived virus [20] , [22] possibly due to their stronger recognition and binding to the C-type lectin receptors . In addition , insect cell-derived Alphavirus was poor at inducing type 1 interferon responses in MoDCs , further enhancing its ability to replicate in these cells [22] . These data collectively suggest that there might be differences between insect cell-derived and mammalian cell-derived arbovirus in in vivo infectivity and disease pathogenesis in susceptible animals . To investigate this , we inoculated goats with insect cell-derived and mammalian cell-derived RVFV and monitored in vivo differences in the course of infection . In addition , we evaluated RVFV from these 2 sources for differences in in vitro infectivity of MoDCs .
All animal experiments were carried out in enhanced biosafety level 3 ( BSL3+ ) at the National Centre for Foreign Animal Disease ( NCFAD ) Winnipeg , Manitoba . All protocols for animal use , under animal use document ( AUD ) number C-09-004 , were approved by the Canadian Science Center for Human and Animal Health , Winnipeg , Manitoba , Canada Animal Care Committee . Only the NCFAD veterinarian and trained animal care personnel were allowed access to the animals . Care was taken to minimise animal suffering , respecting the Canadian Council on Animal Care guidelines for animal manipulations . RVFV strain ZH501 [23] was kindly provided by Dr Heinz Feldmann , National Microbiology Laboratory , Winnipeg , Canada . The mammalian cell-derived RVF virus ( MAM-RVFV ) was propagated on Vero E6 cells ( American Tissue Culture Collection , ATCC , Manassas , VA , USA ) . Infection of Vero E6 cells with RVFV was done in dulbecco's modification eagle's medium ( DMEM ) supplemented with 0 . 3% bovine serum albumin ( BSA , Wisent , QC , Canada ) at an MOI of 0 . 1 and the cultures maintained in DMEM with 0 . 3% BSA at 37°C , 5% CO2 and 95% relative humidity . The virus eventually used as inoculum for goats was from the 4th passage in Vero E6 cells . Insect cell-derived RVFV ( IN-RVFV ) was obtained by propagating the passage 3 RVFV from Vero E6 cells above in a mosquito cell line ( C6/36 , ATCC ) . C6/36 cells were infected at an MOI of 0 . 1 and maintained at 28°C in a 1∶1 mixture of EMEM ( Wisent ) and ESF-921 ( Expression Systems , Woodland , CA , USA ) supplemented with 2 . 5% FBS , 25 mM HEPES and 1 mM sodium pyruvate . The IN-RVFV eventually used as inoculum for goats was from the 2nd passage in C6/36 cells . The sequences for the M and S segments of MAM-RVFV and IN-RVFV were compared for any differences that might result from propagation in the different cell lines . The M segment was selected for sequencing because it was recently shown that a single nucleotide substitution in the glycoprotein ( Gn ) can have a significant effect on the virulence of RVFV [24] . In addition , the NSs protein encoded by the S segment is also of importance in the virulence of RVFV [13] , [14] , [25] . For sequencing , viral RNA was isolated as previously described [26] and RT-PCR performed using published primers and protocol [27] . The RT-PCR products were purified and then cloned using the cloneJet2 . 1/blunt vector and the CloneJet PCR cloning kit ( Fermentas , Canada ) . Three positive clones per gene segment were identified and sequenced and a consensus sequence obtained as previously described [28] . Vero E6 cells were used to determine the titres of RVFV derived from both cell lines . Briefly , serial 10 fold dilutions of virus in 200 µL DMEM were transferred onto a 24-well plate containing confluent Vero E6 cell monolayer . After 1 h , at 37°C , 5% CO2 and 95% relative humidity , an overlay of 1 . 75% carboxymethylcellulose in DMEM containing 0 . 3% BSA ( CMC overlay ) was added to all wells and plates incubated as above . After 4–5 days cells were fixed with 10% formalin , stained with 0 . 5% crystal violet and plaques counted . Healthy 4 month old Boer-cross goats were obtained from breeders in Manitoba , Canada and allowed 10 days to acclimatize to BSL3+ containment at NCFAD , during which they were monitored daily for any signs of disease . After acclimatization , the goats were divided into 2 groups ( 4 per group ) and housed in separate cubicles . One group was inoculated with 5 log10 PFU of IN-RVFV and the 2nd group with 5 log10 PFU of MAM-RVFV per animal by the subcutaneous route . Daily monitoring was continued and rectal temperatures recorded . Blood for serum samples and for peripheral blood mononuclear cells ( PBMCs ) isolation was collected prior to and daily for the first 7 days post infection with RVFV . Additional sampling was done at 14 , 21 and 30 DPI . Serum samples were stored at −70°C . Blood for PBMCs isolation was collected in EDTA-treated vacutainers prior to and daily for the first 7 days post infection ( DPI ) of goats with RVFV . PBMCs were purified from this blood using Ficoll-Paque Plus ( GE Healthcare Bio-Sciences AB , Uppsala , Sweden ) with minor modifications to manufacturer's protocol . Briefly , blood was mixed with an equal volume of sterile phosphate buffered saline ( PBS , pH 7 . 2 , Sigma ) , layered over Ficoll-Paque Plus and centrifuge at 800 g for 30 min with the centrifuge brake off . The PBMC layer was collected and washed twice with PBS . The cells were then resuspended in FACS buffer ( PBS containing 0 . 1% BSA and 0 . 1% sodium azide ) and stained for flow cytometry using antibodies known to cross react with goat cell surface markers [29] . Approximately 106 PBMCs/tube were each stained with mouse anti bovine CD5:FITC ( clone CC17 ) , mouse anti sheep CD8:RPE ( clone 38 . 65 ) , mouse anti bovine CD21:RPE ( cloneCC21 ) all from AbD Serotec ( Oxford , UK ) or mouse anti CD172a ( SWC3 , clone DH59B ) from VMRD ( Pullman , WA , USA ) on ice for 30 min . Isotype control antibodies were included to check for non-specific binding . Cells were washed twice with FACS buffer and for CD172a ( unlabelled primary antibody ) , rat anti mouse IgG1:FITC ( AbD Serotec ) was added for another 30 min on ice . For RVFV detection , PBMCs from infected goats were permeabilized using BD cytofix:cytoperm reagent ( BD Biosciences , San Diego , CA , USA ) according to manufacturer's protocol . An optimal amount of rabbit polyclonal anti RVFV NSm1 antibody was then added to the cells and incubated on ice for 30 min . The rabbit polyclonal anti RVFV NSm1 antibody ( R1108 ) was produced by the EvoQuest Team , Invitrogen ( Carlsbad , California , USA ) using a synthetic NSm1 polypeptide . Antibody from a naïve rabbit was used as isotype control . Cells were washed twice with BD perm/wash buffer , then stained with Alexa Fluor 594 donkey anti rabbit IgG ( Invitrogen , Oregun , USA ) for 30 min on ice , followed by 2 more washes with BD perm/wash buffer . After the final wash in all staining protocols , cells were fixed overnight in 10% phosphate-buffered formalin before running on the FC500 two laser flow cytometer ( Beckman Coulter ) . At least 25 , 000 events were acquired per sample and data analysed with the CXP analysis software ( Beckman Coulter ) . Peripheral blood mononuclear cells isolated from naïve goats as described above were resuspended in RPMI supplemented with 10% FBS , 100 U/mL penicillin , 100 µg/mL streptomycin , 200 µM/mL glutamax , 10 mM HEPES and 0 . 5 µM 2-mercaptoethanol ( complete medium ) and incubated in cell culture flasks at 37°C overnight for monocytes to attach . Non-adherent cells were removed , adherent monocytes washed twice with sterile PBS and then incubated at 37°C , 5% CO2 and 95% relative humidity in complete medium containing 1 in 10 dilution of recombinant bovine GM-CSF and 0 . 1 µg/mL recombinant bovine IL-4 ( both from Serotec ) . These conditions have been shown to differentiate bovine monocytes into MoDCs [30] . As controls , adherent monocytes were also cultured in complete medium only ( MΦ ) . Medium was supplemented after 3 days and MoDCs and MΦ harvested after 7 days . Flow cytometry for CD14 , CD172a and CD11c surface markers was performed as described above . For RVFV infection , approximately 5×105 MoDCs were exposed to either IN-RVFV or MAM-RVFV at 0 . 1 MOI in RPMI without FBS for 1 h at 37°C , 5% CO2 and 95% relative humidity . The cells were then washed , resuspended in complete medium and incubated at 37°C for 24 h after which supernatants were harvested . The amount of virus in culture supernatants was measured by plaque assay on Vero E6 cells as described earlier . Recall cell-mediated immunity ( CMI ) was determined by measuring RVFV-specific IFN-γ response [31] in PBMCs from goats at DPI 21 . Antigen-specific induction of IFN-γ is one of the accepted methods in immunology for detecting CMI . PBMCs were isolated as described above and resuspended in complete medium . PBMCs were adjusted to 107/mL , 100 µL added per well of a 96-well plate and duplicate wells stimulated with IN-RVFV or MAM-RVFV at 0 . 1 MOI to a final volume of 200 µL/well . Complete medium was added to negative control wells while ConA was used as positive control . Plates were incubated at 37°C , 5% CO2 and 95% relative humidity for 48 h , supernatants harvested and stored at −70°C for subsequent IFN-γ ELISA as described below . RVFV RNA was extracted from serum using the TriPure Isolation reagent ( Roche ) according to the manufacturer's protocol . The purified RNA was stored at −70°C . Primers ( Invitrogen ) and probe ( Applied Biosystems ) designed to target nucleotides 2912 to 2981 of the RVFV L gene segment [26] , [32] were used for quantitative real-time reverse transcriptase polymerase chain reaction ( qRT-PCR ) as previously described [26] . Antibody pairs known to cross-react with goat IL-12 and IFN-γ were obtained from AbD Serotec and used as previously described [29] . Based on the cross-reactivity of other bovine and ovine antibodies with related targets in goats [29] , [33] , there was a high probability that other sheep and bovine cytokine ELISA antibodies will also cross-react with goat . We therefore obtained cytokine ELISA kits for sheep TNF-α , IL-6 and IL-1β from TSZ ELISA ( Framingham , MA , USA ) and bovine IFN-α from USCN Life Science Inc . ( Wuhan , China ) and used them with goat serum according to the manufacturers' instructions . To test the in vitro antiviral effect of ruminant IFN-γ against RVFV , recombinant bovine IFN-γ ( RB- IFN-γ , Thermo Scientific ) and Mardin-Darby bovine kidney ( MDBK ) cells were used . Approximately 2×105 cells/well in 250 µL AMEM were added to a 24-well plate and an equal volume of various concentrations of RB- IFN-γ added in quadruplicates . Medium only was added to cells in the control wells . Plates were incubated at 37°C , 5% CO2 and 95% relative humidity for 24 h and checked for confluence . Well contents were emptied and 100 PFU of RVFV in 200 µL added to all wells except the cell controls . After 1 h at 37°C , CMC overlay was added to all wells and plates incubated at 37°C , 5% CO2 and 95% relative humidity . On day 3 after addition of virus , cells were fixed with 10% formalin and stained with 0 . 5% crystal violet . Plaques were counted in all wells and the percent plaque inhibition calculated . Neutralising antibody response to RVFV was determined by plaque reduction neutralization test ( PRNT ) modified from a previously described protocol [34] . Serial 2-fold dilutions of serum in DMEM were made starting from 1 in 20 to obtain triplicates of 100 µL/well for each serum sample . 100 µL of DMEM containing 100 PFU of RVFV was added to each serum dilution , mixed and incubated at 37°C , 5% CO2 and 95% relative humidity for 1 h . 200 µL of the virus/serum mixture was then transferred onto a 24-well plate containing confluent Vero E6 cell monolayer and incubated for another 1 h . CMC overlay was then added to all wells and plates incubated at 37°C , 5% CO2 and 95% relative humidity . Assay of negative and positive control sera as well as a back titration of the virus was performed at the same time as the test sera . After 5 days the cells were fixed with 10% formalin , stained with 0 . 5% crystal violet and plaques counted . The reciprocal of the highest serum dilution that prevented at least 70% CPE was taken as the PRNT70 titre for that sample . Data from multiple time points was analyzed by ANOVA with the Dunnett multiple comparisons test using GraphPad InStat version 3 . 06 ( GraphPad Software , San Diego , CA ) . Differences between groups for data collected at a single time point were analysed using the Student t-test . A p ≤ 0 . 05 was considered statistically significant .
The M gene sequences of MAM-RVFV and IN-RVFV were identical to each other ( data not shown ) as well as to a published sequence for the M segment ( GenBank accession number DQ380200 ) of RVFV ZH501 strain [27] . Similarly , the gene sequences for the S segment of MAM-RVFV , IN-RVFV and a GenBank publication ( accession number DQ380149 ) [27] were identical to each other . All the goats infected with RVFV developed viremia starting at DPI 1 . In IN-RVFV-infected goats , peak viremia was attained at DPI 1–2 and by DPI 4 all goats were aviremic ( Figure 1A ) . On the other hand , MAM-RVFV-infected goats had peak viremia at DPI 3 and at DPI 4 , 50% of the goats were still viremic ( figure 1A ) . Indeed , on DPI 1 and 3 the difference in viremia between the 2 groups reached statistical significance ( p<0 . 02 ) . Peak viremia in MAM-RVFV-infected goats was higher than for IN-RVFV-infected goats but this difference was not statistically significant . By DPI 5 , no virus could be detected in the blood of all the goats . The only clinical sign observed was a slight increase in rectal temperature in IN-RVFV infected goats . Following infection with IN-RVFV , rectal temperatures rose to 39 . 9–40 . 3°C , with maximum temperatures corresponding to peaks of viremia at DPI 1–2 ( Figure 1B ) . In MAM-RVFV-infected goats , the increase in rectal temperature was barely noticeable , with a maximum of 39 . 9°C in 1 goat at DPI 2 , and not exceeding 39 . 5°C in the rest of the goats ( Figure 1B ) . However , there was no significant difference in rectal temperatures between the 2 groups . All goats survived through out the duration of the experiment . Monocyte/DC , T lymphocytes , cytotoxic T cells and B cells were identified with antibodies against CD172a , CD5 , CD8 and CD21 surface markers respectively . Frequencies of these cells in naïve goats ranged from 11 . 1–19 . 3% ( CD172a+ monocytes/DC ) , 15 . 8–35 . 4% ( CD5+ T cells ) , 5 . 7–20 . 1% ( CD8+ T cells ) and 8 . 1–20 . 9% ( CD21+ B cells ) . Following infection there was a drop in CD172a+ monocytes/DC starting on DPI 2 in both IN-RVFV and MAM-RVFV infected goats ( Figure 2 ) . However , this decline in CD172a+ monocytes/DC , expressed as a percentage of baseline frequencies , was more pronounced and statistically significant ( p<0 . 01 on DPI 2 and 4 , p<0 . 05 on DPI 3 ) in IN-RVFV-infected goats compared to MAM-RVFV-infected goats in which the drop never attained statistical significance ( figure 2 ) . On the other hand , CD5+ T cells and CD8+ T cells reduction was less than 20% in goats infected with MAM-RVFV while goats infected with IN-RVFV suffered approximately 40% drop ( Figure 2 ) . Conversely , in MAM-RVFV-infected goats , CD21+ B cell frequencies increased by approximately 2 fold on DPI 1 and 2 ( p<0 . 05 and p<0 . 01 respectively ) , returning to within baseline values on DPI 3 but never dropping below baseline frequencies ( Figure 2 ) . On the contrary , in IN-RVFV-infected goats , the changes in CD21+ B cell frequencies were not statistically significant , only increasing slightly on DPI 3 but declining to 30% below baseline frequencies on DPI 4 and 5 ( Figure 2 ) . However , by DPI 14 , CD21+ B cell frequencies were above baseline values in both groups . To investigate whether the decline in frequencies of identified PBMC subsets was as a result of permissiveness to RVFV , PBMC from infected goats were examined for the presence of virus by intracellular staining for the non-structural protein ( NSm1 ) and flow cytometry . At DPI 1 , 1 . 4 to 2% of PBMCs in MAM-RVFV and IN-RVFV-infected goats were positive for RVFV which increased to 3 to 4% on DPI 3 ( Figure 3 ) . More PBMCs stained for NSm1 in IN-RVFV-infected than in MAM-RVFV-infected goats , reaching statistical significance at DPI 1 ( p ≤ 0 . 05 ) . However , this difference was not statistically significant at DPI 3 . Since goat MoDCs have not been previously described , we first confirmed that the cells derived from goat monocytes with bovine GM-CSF and IL-4 had the phenotype of related bovine MoDCs [30] , [35] . These cells had the morphology of DC and were CD14 negative , CD11c and CD172a low as opposed to MΦ that were CD14+ , CD11c and CD172a high ( supplementary figure 1 ) . When these cells were infected with RVFV at MOI 0 . 1 , approximately 1 log10 PFU/mL more virus ( p<0 . 05 ) was obtained from IN-RVFV-infected MoDCs compared to MAM-RVFV at 24 h post infection ( Figure 4 ) . RVFV infection in goats was characterized by 2 cytokine response patterns . Serum levels of IL-12 and IFN-γ peaked early post-infection while TNF-α , IL-6 and IL-1β levels peaked later . Serum IL-12 levels peaked at DPI 1 in both IN-RVFV-infected and MAM-RVFV-infected goats ( Figure 5 ) . The increase in IL-12 response for IN-RVFV-infected goats reached statistical significance on DPI 1 and 2 compared to baseline ( p<0 . 01 ) . On the contrary , the increase in IL-12 response for MAM-RVFV-infected goats did not reach statistical significance . The peak IL-12 response was significantly different between IN-RVFV-infected and MAM-RVFV-infected goats ( p = 0 . 03 ) . However , when all infected goats were analysed together , the IL-12 response was significant at DPI 1 ( p<0 . 01 ) and DPI 2 ( p<0 . 05 ) . Maximum levels of serum IFN-γ was reached in IN-RVFV-infected goats at DPI 2 but this was delayed until DPI 4 in MAM-RVFV-infected goats ( Figure 5 ) . The IFN-γ response reached statistical significance on DPI 2 in IN-RVFV-infected goats ( p<0 . 05 ) and DPI 4 in MAM-RVFV-infected goats ( p<0 . 05 ) compared to baseline . There was no significant difference in peak IFN-γ response between the 2 groups . Serum TNF-α , IL-6 and IL-1β levels rose slightly at DPI 1 followed by a significant increase ( p<0 . 05 ) at DPI 6 ( Figure 5 ) . There were no significant differences between IN-RVFV-infected and MAM-RVFV-infected goats with regards to TNF-α , IL-6 and IL-1β response . Minute levels of IFN-α ( ≤5 pg/ml ) were detected in serum from some naïve goats but these levels did not increase early post infection ( Figure 5 ) . Due to the high serum IFN-γ response in RVFV-infected goats , direct antiviral effect of this cytokine on RVFV was tested in vitro using recombinant bovine IFN-γ . IFN-γ had minimal effect against RVFV , with only 21% plaque inhibition at 1000 ng/mL ( data not shown ) . In addition , this inhibition was dose dependent , with none observed at 8 ng/mL concentration . In vitro RVFV-induced IFN-γ secretion by PBMCs from convalescent goats was used to determine specific cell-mediated immunity ( CMI ) [31] . PBMCs harvested from convalescent goats at DPI 21 secreted high levels of IFN-γ in response to RVFV re-exposure ( Figure 6 ) . This IFN-γ response was almost identical between the IN-RVFV-infected and MAM-RVFV-infected goats irrespective of which virus ( IN-RVFV or MAM-RVFV ) was used for in vitro re-stimulation of PBMCs . In addition , the response to the non-specific mitogen , ConA , was similar in both groups . Unstimulated cells secreted significantly less IFN-γ compared to the cells exposed to either virus ( p<0 . 02 ) . Antibody response , based on PRNT70 , commenced on DPI 5 with low titres in most of the goats . Antibody titres rose to a maximum at DPI 21–30 in all goats . However , PRNT70 titres for IN-RVFV infected goats at DPI 7 , 14 and 21 were significantly lower ( p<0 . 05 ) compared to MAM-RVFV infected goats ( Table 1 ) . There was no significant difference in antibody response between the 2 groups at DPI 30 .
Cattle , sheep and goats have long been recognized as the natural hosts of RVFV . The clinical manifestation and pathology of natural and experimental RVF in cattle and sheep have been reported [8] , [31] , [36]–[38] . To the best of our knowledge , only one report of experimental infection in goats is published , and it did not address the innate immune response to the virus in goats [18] . Pathology following vaccination of goats with an attenuated strain of RVFV has been studied . However reports from other models reveal that this is not the same as infection with the virulent strain [19] . In this report we attempted to address some aspects of the innate and adaptive immune response to RVFV in goats . In addition , we compared these parameters between insect cell-derived and mammalian cell-derived RVFV . As in the previous report [18] , the incubation period for RVFV in goats was 24 h . A similar incubation period is recorded for sheep , cattle , non-human primates and humans [3] . Peak viremia at DPI 1–3 was similarly reported in goats [18] and other susceptible species [3] , [11] , [31] . There were no mortalities and the only clinical sign we observed in these RVFV-infected goats was a mild fever in a subset of animals . Therefore , experimental infection of goats with RVFV produces a fairly typical disease course similar to what has been observed in other ruminants of a similar age group [3] , [18] , [31] . We observed a significant decline in CD172a+ cells ( monocytes and dendritic cells ) in RVFV-infected goats . There was also a pronounced decline in T cells ( CD5+ ) and a transient decline in cytotoxic lymphocytes ( CD8+ ) in IN-RVFV infected goats . Only a slight decline in the CD5 population was observed for MAM-RVFV infected goats . It has been suggested that RVFV can directly cause necrosis in infected cells as part of the disease pathogenesis [25] , [39] and RVFV has been isolated from human PBMCs in a natural outbreak [40] . RVFV has also been shown to infect human monocytes/macrophages [25] , [41] . Furthermore , RVFV was detected in Kupffer cells ( resident liver macrophages ) [39] . The differential effect of IN-RVFV and MAM-RVFV on PBMCs could be due to their differential ability to infect PBMC subsets . Indeed , PBMCs from IN-RVFV-infected goats had significantly higher percentage of RVFV NSm1 positive cells than in their MAM-RVFV-infected counterparts at DPI 1 which might be linked to the observation of a more profound decline in CD172a+ , CD5+ and CD8+ cells in IN-RVFV infected goats . This is further supported by our in vitro data which shows that IN-RVFV infects MoDCs more readily than does MAM-RVFV . Furthermore , RVFV has previously been shown to infect MoDCs [21] . In addition , in arboviruses , insect cell-derived alphaviruses infect MoDCs more efficiently than mammalian cell-derived ones . The presence of high mannose carbohydrates in the viral glycoproteins is thought to enable the former to readily bind receptors on target cells [20] , [22] . Contrary to the other cell subsets , CD21+ B cell frequencies increased post infection and never dropped below baseline in MAM-RVFV infected goats , while the slight increase in CD21+ B cell frequencies in IN-RVFV infected goats was followed by a decline below baseline frequencies . The amplification of B cells probably prepared the immune system for the more robust antibody production in MAM-RVFV infected goats as opposed to in IN-RVFV infected ones . To the best of our knowledge , cytokine response to RVFV in ruminants has not been investigated . Here we report the detection of IL-12 , IFN-γ , TNF-α , IL-6 and IL-1β in serum of RVFV-infected goats . Also of significance , is the absence of detectable IFN-α , one of the most potent antiviral cytokines . Experimental models have demonstrated a role for IFN-α in RVFV clearance [11] and the virus has developed mechanisms , via the NSs protein , to inhibit IFN-α response in infected cells [12]–[14] , [25] . The presence of other cytokines but not IFN-α in RVFV-infected goats suggests that the virus may have specifically blocked its production/induction . This would create a window for high viremia to be attained which usually occurs within 24 h of infection . On the other hand , IL-12 and IFN-γ peaked at DPI 2–4 suggesting an otherwise functional innate immune response to RVFV in goats . In previous reports in sheep , RVFV was cleared from blood several days before the detection of neutralising antibodies indicating that innate immunity was likely responsible for this early protection [31] . IL-12 is known to activate bovine and ovine NK cells to secrete IFN-γ [42] which in turn activates NK cells to better cytotoxicity [43] . The response pattern in the current report suggests that IL-12 might have promoted the IFN-γ response , possibly from NK cells though other cells including macrophages and DC also secrete IFN-γ [44] . In previous studies [10] , monkeys were protected from RVF when human IFN-γ was administered 24 h prior to infection . In addition to promoting NK cell cytotoxicity and downstream adaptive immune responses , IFN-γ is known to activate pathways that can directly inhibit virus [43] . However , using recombinant bovine IFN-γ , we did not detect any significant direct antiviral effect on RVFV replication in MDBK cells . Indeed , there was no antiviral effect at titres equivalent to the maximum serum IFN-γ response in RVFV-infected goats . Furthermore , it has been demonstrated that human IFN-γ has minimal in vitro antiviral effect against RVFV [45] . It is therefore , possible that IFN-γ and IL-12 may have played a role in the rapid clearance of viremia in RVFV-infected goats by activating NK cells , even though a direct antiviral effect of these cytokines can not be ruled out . This will be investigated in subsequent experiments . The other pro-inflammatory cytokines may have also played a role in RVFV clearance despite reaching peak levels on DPI 6–7 . Recent data from humans suggests that a strong pro-inflammatory response is linked to survival of RVF [25] . The detection of neutralising antibodies starting at DPI 5 reported here has been similarly observed in natural and experimental infections in other animal models and humans [2] , [15]–[17] . Neutralising antibodies are believed to be crucial for the early protection against RVFV [2] . Based on our observations in goats , the initial protection could be primarily due to innate immunity ( mediated by cytokines and possibly NK cells ) . Nevertheless , neutralising antibodies are responsible for long term protection from subsequent challenge [2] . Adaptive cell mediated immunity may also be involved in long term protection from RVFV as suggested by the high IFN-γ response following restimulation of cells from convalescent goats ( this report ) and sheep [31] . Experimental trials in mice have also suggested that cell mediated immunity is important for post-vaccinal protection against RVFV [46] . In conclusion , experimental RVF in goats closely resembles natural and experimental infection in other ruminant hosts . Apparently , the virus infects DCs and monocytes and inhibits IFN-α response thereby allowing rapid replication . However other arms of innate and possibly adaptive immunity combine to protect animals from RVFV shortly after infection . The source of virus appears to influence events during infection , with IN-RVFV attaining peak viremia more rapidly , infecting more PBMCs , inducing slight fever and higher levels of early cytokines but lower levels of neutralising antibodies at onset of seroconversion . These findings seem to suggest that infections acquired from mosquito bites could differ somewhat from those due to contact with infectious material . However , this is far from conclusive considering the small sample size of 4 goats per group and the fact that in a natural setting things are much more complex , with other factors such as dose of infection , age and immune status likely to influence the course of disease . In addition , considering that these are outbred animals , genetic factors could also have contributed to the observed differences . Nevertheless , all 8 goats responded to RVFV by secreting cytokines irrespective of the source of virus . More work is required in goats and other ruminants to check if these results can be similarly observed in these species . | Rift Valley fever ( RVF ) is a mosquito-transmitted disease of ruminants and man , which occurs in Africa , Saudi Arabia and Yemen but could spread to other areas . There isn't much information on some aspects of the immune response to this disease and how it affects cells of the immune system in the natural animal hosts . To fill in some of this knowledge gap , we studied RVF in goats experimentally infected with the RVF virus . We also compared RVF virus grown in an insect cell-line and that grown in a mammalian cell-line for differences in the course of infection . Virus was present in the blood of the goats one day after infection . Some goats had fever coinciding with the time when the virus level in the blood was highest . Some cells in the blood dropped in number possibly as a direct effect of virus . Infected goats secreted cytokines ( interferon gamma and interleukin-12 ) , which possibly contributed to protection against RVF . Virus from an insect cell-line appeared to have more obvious effects in infected goats suggesting that differences may exist in infections of ruminants acquired from mosquito bites compared to those due to contact with infectious material from other animals . | [
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"biology",
"immune",
"response",
"v... | 2012 | Innate Immune Response to Rift Valley Fever Virus in Goats |
Genomic and genetic analyses have demonstrated that many species contain multiple chemotaxis-like signal transduction cascades that likely control processes other than chemotaxis . The Che3 signal transduction cascade from Rhodospirillum centenum is one such example that regulates development of dormant cysts . This Che-like cascade contains two hybrid response regulator-histidine kinases , CheA3 and CheS3 , and a single-domain response regulator CheY3 . We demonstrate that cheS3 is epistatic to cheA3 and that only CheS3∼P can phosphorylate CheY3 . We further show that CheA3 derepresses cyst formation by phosphorylating a CheS3 receiver domain . These results demonstrate that the flow of phosphate as defined by the paradigm E . coli chemotaxis cascade does not necessarily hold true for non-chemotactic Che-like signal transduction cascades .
Rhodospirillum centenum is a photosynthetic member of the Azospirillum clade , members of which associate with root rhizospheres in a broad range of plants . These aerobic nitrogen fixating organisms are capable of promoting plant growth by the donation of both fixed nitrogen and plant hormones [1] . Inoculating fields and/or seeds with Azospirillum sp . have significantly enhanced crop yields of a wide diversity of cultivars including corn and wheat [2] , [3] . An additional feature of this group is the capability of forming metabolically dormant cysts that promotes survival during droughts [4] . Encystment involves several morphological transitions during which cells round up and form a thick outer exopolysaccharide coat termed the exine layer [5] . The formation of cysts also correlates with the appearance of intracellular poly-β-hydroxybutyrate ( PHB ) granules that are presumably used as energy reserves [6] . Once water and nutrients are available , cysts germinate by reforming vegetative cells that emerge from the exine coat [5] . Azospirillum species are morphologically similar to myxospores synthesized by Myxobacteria . Both groups are soil-dwelling , Gram-negative proteobacteria that form highly desiccation resistant resting cells . In Myxococcus xanthus a two-component system ( TCS ) comprised of a membrane bound histidine kinase ( HK ) CrdS , which phosphorylates a DNA binding response regulator ( RR ) CrdA to control myxospore development . The Che-like Che3 signaling cascade negatively regulates CrdA by functioning as a phosphatase [7] . As is the case with Myxobacteria , cyst formation in R . centenum also utilizes a novel chemotaxis-like signal transduction cascade ( Che3 ) to control the timing of development [8] . The R . centenum che3 gene cluster ( Figure 1 ) is comprised of eight genes coding for homologs of CheA ( CheA3 ) , CheW ( CheW3a and CheW3b ) , CheB ( CheB3 ) , CheR ( CheR3 ) , a methyl-accepting chemorecepter ( MCP3 ) and CheY ( CheY3 ) . CheA3 is a CheA-CheY hybrid ( Figure 1 ) belonging to Class II HKs , which include homologs of the E . coli CheA with a conserved histidine residue located in a histidine phosphotransfer ( Hpt ) domain rather than a dimerization and hisitidine phosphotransfer ( DHp ) domain found in Class I HKs . In addition to CheA3 , the che3 cluster also codes for a second HK ( CheS3 ) . CheS3 has two REC domains followed by a PAS ( Per , Arnt , Sim ) domain and a HWE Class I HK domain ( Figure 1 ) ; however , only one of the CheS3 REC domains contains a predicted phosphorylatable aspartate ( D54 in REC1 , Figure 1 ) with the comparable position in the second REC being substituted by an alanine ( A191 in REC2 , Figure 1 ) . Clearly the presence of a second HK and two additional phosphorylatable REC domains in the R . centenum Che3 cascade indicates that the flow of phosphate is more complex in this signaling pathway than for the E . coli Che signaling cascade . In the classic Escherichia coli chemotaxis model , CheA is tethered to the MCP-CheW complex and its autophosphorylation at a conserved His in the Hpt domain is enhanced upon repellents binding to MCP and inhibited upon binding of attractants . CheA phosphorylates a conserved Asp in CheY; phosphorylated CheY in turn binds to the flagellum's rotor causing reversal of flagellar rotation . Similar to the smooth-swimming and tumbling phenotypes exhibited in E . coli chemotaxis mutants , in-frame deletions of individual che3 genes produce distinctly opposing phenotypes [8] . Deletions of cheS3 , cheY3 , or cheB3 lead to a hyper-cyst phenotype characterized by premature formation of cysts , whereas null mutants of mcp3 , cheW3a , cheW3b , cheR3 , or cheA3 produce hypo-cyst strains that are defective for cyst development [8] . These genetic studies indicate that CheS3 and CheY3 may constitute cognate partners in a TCS that suppresses encystment , and that CheA3 either inhibits phosphorylation of the CheS3-CheY3 TCS or is part of a separate pathway . Here we report that CheY3 indeed accepts phosphates from CheS3 and not CheA3 , and that CheA3 derepresses cyst formation by phosphorylating the REC1 domain of CheS3 .
We previously reported that deletions of hybrid histidine kinase ( HHK ) genes cheA3 and cheS3 lead to opposing defects in the timing of cyst formation [8] . Specifically , a deletion of cheA3 resulted in severely defective encystment , while a deletion of cheS3 resulted in enhanced encystment . We also observed that a cheY3 null mutation is indistinguishable from the hypercyst phenotype exhibited by a null mutation of cheS3 . In order to further probe the importance of the linked CheA3 and CheS3 REC domains we introduced alanine substitutions at the predicted Asp sites of phosphorylation and recombined these mutations into the native R . centenum chromosomal loci ( Figure 1 ) . Mutated strains were subsequently assayed for cyst development by growth on either nutrient-rich CENS medium that promotes vegetative growth or on cyst-inducing CENBA medium . Phase contrast microscopy was then used to visually assess cyst production coupled with flow cytometry quantitation of vegetative/cyst cell populations ( Figure 2 ) . As observed in previous studies , growth of wild type cells in CENS medium visibly leads to >99% vegetative cells ( Figure 2A ) , whereas growth in CENBA medium produces large cyst clusters ( Figure 2B ) . Separation of individual vegetative cells from cyst clusters using flow cytometry indicates that the large population of vegetative cells present in CENS medium form a tight pattern near the origin of a side scatter ( SSC ) versus forward scatter ( FSC ) flow cytometry plot ( Figure S1 ) . In contrast , wild type cells grown in CENBA medium , which microscopically have a large number of cysts clusters , shows a distinct “comet tail” comprised of larger cyst cells that separate from the tight clustering of smaller single vegetative cells during flow cytometry ( Figure S1 ) . The tight clustering of vegetative cells is indicative of a high degree of uniformity of cell size ( ∼1 µm ) [9] and internal complexity whereas the “comet tail” distribution of the cyst cell population shows that there is a wider distribution of sizes ( 2–8 µm ) [10] present with varying internal complexity due in part to varying numbers and sizes of large PHB storage granules inside cysts [10] , [11] . Because each cyst cluster typically contains 2 to 6 cells , the number of cyst cells is significantly higher ( estimated to be ∼4-fold higher ) than what is measured by flow cytometry quantitation of cyst clusters . Flow cytometry analysis of wild type cells grown on cyst inducing CENBA medium show that ∼10% of the cell culture can be separated from the vegetative cell population as larger cyst clusters ( Figure 2B ) . In contrast , growth of the ΔcheA3 mutant in cyst inducing CENBA shows a two-log reduction in cyst formation ( Figure 2B ) to a level that is comparable with that of wild type cells growth in vegetative CENS medium ( Figure 2A ) . Not surprisingly , the cheA3:H49A HK mutant resembles a ΔcheA3 mutant , as this strain also contains a large predominance of vegetative cells irrespective of growth on nutrient-rich CENS or cyst-inducing CENBA medium . Interestingly , the cheA3:D663A REC mutant exhibits an opposing phenotype in that it forms large numbers of cysts in both CENS and CENBA growth media ( Figure 2 ) . Indeed the level of cyst production by the cheA3:D663A REC mutant exceeds that of wild type cells grown in CENBA . The cyst deficient phenotypes exhibited by the ΔcheA3 and cheA3:H49A mutants are markedly contrasted by the ΔcheS3 and cheS3:H453A HK mutant strains that produce cysts in both CENS and CENBA medium . Interestingly , similar to what was observed in the CheA3 HK and REC mutant strains , the cheS3:D54A REC mutant exhibits a cyst defective phenotype that is opposite of the hypercyst phenotype exhibited by the ΔcheS3 and cheS3:H453A HK mutant strains ( Figure 2 ) . The opposing encystment phenotypes produced by the cheA3 and cheS3 HK and REC domain mutations indicates that the REC domains have regulatory control over the linked HK domains in both kinases . Similar to the ΔcheS3 and cheS3:H453A mutants , both the ΔcheY3 , and cheY3:D64A mutants produced cyst cells when grown in both vegetative CENS and cyst inducing CENBA growth media ( Figure 2 ) . Finally , to determine the hierarchy of CheA3 and CheS3 within the Che3 signaling cascade , we constructed ΔcheA3ΔcheS3 and ΔcheA3ΔcheY3 double mutants and assayed for encystment . These double mutations resulted in hyper-cyst strains that resemble the ΔcheS3 and ΔcheY3 phenotypes ( Figure 2 ) , suggesting that CheA3 functions upstream of CheS3 and CheY3 in this developmental signaling pathway . HHKs are generally able to undergo four reactions in the presence of ATP and divalent metal cations: ( 1 ) autophosphorylation , where the conserved His residue within the HK domain is phosphorylated by the adjacent catalytic and ATP-binding domain ( CA ) using ATP as a substrate; ( 2 ) autodephosphorylation of the phospho-His residue within the HK domain; ( 3 ) phosphotransfer , where the REC domain dephosphorylates phospho-His and transfers the phosphate to its conserved Asp; and ( 4 ) autodephosphorylation of the phospho-Asp residue within the REC domain to yield inorganic phosphates ( Pi ) ( Figure S2 ) . In addition , phosphoryl group transfer from a response regulator back to its cognate HK is also possible . This reverse reaction has been observed in the EnvZ-OmpR TCS [12] as well as in phosphorelay systems involving a Hpt domain where the forward phosphorylation reaction ( His1→Asp1→His2→Asp2 ) is partially reversible ( Asp2→His2→Asp1→Pi ) [13] . In the presence of ATP , HHKs may therefore exist as a mixture of four different phosphorylation states as illustrated in Figure 3A: unphosphorylated , His-phosphorylated ( His∼P ) , Asp-phosphorylated ( Asp∼P ) , and His-and-Asp-phosphorylated ( His∼P/Asp∼P ) . In order to characterize potential phosphorylation states of wild type CheA3 and CheS3 , we isolated CheA3 and CheS3 with hexahistidine tags at their N-termini and performed in vitro phosphorylation assays . In early experiments we observed little radioactive labeling on CheA3 with [γ-33P] ATP in buffers containing Na+ and Mg2+ , which made it difficult to biochemically characterize CheA3 . Earlier studies showed that potassium but not sodium stimulates autophosphorylation of E . coli CheA [14] . Additionally , the Salmonella typhimurium CheY∼P autodephosphorylates at a high rate in the presence of Mg2+ leading to a low amount of 32P protein labeling , whereas in the presence of Ca2+ autodephosphorylation is impeded leading to a high level of 32P labeling [15] . To test whether different metal ions affected HHK phosphorylation , we performed kinase assays on wild type CheA3 , CheS3 and on CheA3 , CheS3 REC domain mutants in 14 buffers containing 25 mM Tris pH 7 . 5 and varying in 100 mM monovalent and 6 mM total divalent salt compositions ( Table S1 , Buffers 1–14 ) . As shown in Figure 3B , CheA3 exhibited nearly undetectable labeling in Buffers 1 and 3–7 , all of which contain NaCl as a monovalent salt . CheA3 labeled considerably better in all K+-containing buffers with maximum labeling observed in Buffer 9 containing Ca2+ as the sole divalent ion . When D663 was replaced with an alanine , 33P labeling was greatly improved in nearly all buffer conditions ( Figure 3B ) . The enhanced labeling of CheA3:D663A compared with wild type CheA3 suggests that the N-terminal HK domain transfers the phosphate to D663 in the REC domain , which subsequently undergoes rapid autodephosphorylation . The D663A REC domain mutation would thus effectively trap the phosphate at H49 , thereby allowing increased accumulation of phosphates . Regarding the enhanced phosphorylation of wild type CheA3 observed in Buffer 9 , we propose that phosphate is captured at both H49 and D663 residues due to Ca2+ mediated inhibition of receiver domain autodephosphorylation . This conclusion is further supported by acid-base stability assays described below . Unlike CheA3 , CheS3 shows no particular metal ion preference ( Figure 3B ) . CheS3:D54A exhibits much lower 33P incorporation in Buffers 2 and 9 , which contain Ca2+ as the only divalent metal ion . HHKs are found in most bacterial genomes [16] with the role of the linked REC domain not well established in most cases . However , in several studies it has been shown that the HK domain favors intramolecular phosphotransfer to the linked REC domain [17]–[19] . We tested whether intramolecular phosphotransfer occurs in CheA3 and CheS3 by determining the phosphorylation states of the HK and REC domains . To capture the His∼P , Asp∼P , and His∼P/Asp∼P forms of these phospho-kinases , we used an acid-base stability assay based on differential pH sensitivity of His and Asp phosphorylated residues . Specifically , His∼P ( Figure 3A-2 ) bonds are labile in acidic conditions but stable in basic conditions [20] while acylphosphates like Asp∼P ( Figure 3A-3 ) are both acid- and base-labile [21] . In this experiment , we phosphorylated CheA3 and CheS3 in Buffer 9 ( containing Ca2+ as the only divalent cation ) for 30 min , denatured the phospho-proteins with SDS and treated samples with Tris buffer , HCl , or NaOH . Samples were then assayed for 33P-labeling by SDS-PAGE , with the assumption being that phosphorylation is preserved in a buffered solution with a physiological pH ( Tris pH 7 . 5 ) and thus would represent 100% phosphorylation of the kinases before acid or base treatment . In Figure 4A we show that ∼50% of wild type CheA3∼P was hydrolyzed by exposure to 0 . 1 M HCl and that it increased to ∼90% hydrolysis by exposure to 1 M HCl . This is contrasted by >90% hydrolysis of phosphate observed with the mutant ( CheA3:D663A∼P ) in both low and high HCl concentrations . The different stability profiles of the wild type CheA3 and D663A mutant suggest that Asp∼P likely exists in the wild type CheA3∼P . This is confirmed by treatment with NaOH , which dephosphorylates only Asp∼P . In this case nearly 100% CheA3:D663A∼P withstood high pH while the phosphate on wild type CheA3 is extremely labile ( Figure 4A ) . This demonstrates that CheA3:D663A∼P is indeed only phosphorylated on a His residue and that wild type CheA has the majority ( >90% ) of its phosphate located at D663 . Collectively these data suggest that the phosphate group flows from the HK domain to the REC domain within wild type CheA3 . This conclusion is also confirmed by observing direct transfer of phosphate from CheA3:D663A∼P to a truncated version of CheA3 comprised of only the C-terminal receiver domain ( CheA3-REC ) ( Figure 4C ) . Intermolecular phosphoryl transfer to CheA3-REC was also detected using the wild type CheA3∼P as the donor ( Figure S3A ) that has a linked REC domain competing with intermolecular phosphoryl transfer to the truncated REC domain . Tethered receiver domains in HHKs can either function as an intermediate within a multicomponent phosphorylation cascade , or as a phosphate sink , removing phosphate from the HK domain to impede it from phosphorylating an untethered cognate REC domain . We believe the latter is the case with CheA3 as the half-life of the phosphate on the CheA3:D663A mutant is nearly 3-fold higher ( 80 min , Table 1 ) than is observed with wild type CheA3 ( 31 min , Table 1 ) . Taken together , it appears that the REC domain in CheA3 functions to modulate the phosphorylation state of the HK domain by accepting a phosphate that is then rapidly lost by hydrolysis . In contrast to the acid and base stability of CheA3 , CheS3∼P is only acid-labile ( Figure 4B ) . Furthermore , substitution of the predicted D54 phosphorylation site to an alanine in the first REC domain does not alter pH sensitivity . These results indicate that His∼P ( Figure 3A-2 ) is the primary autophosphorylation form of CheS3∼P . Because CheS3:D54A showed reduced 33P incorporation in Buffer 9 ( Figure 3B ) , we repeated this assay with CheS3∼P and CheS3:D54A∼P prepared in Buffer 5 ( containing both Ca2+ and Mg2+ ) in order to rule out any ion effects imparted upon the phosphorylation equilibriums discussed above ( Figure S2 ) . We observed the same results of high HCl sensitivity and NaOH resistance regardless of the buffer conditions ( Figure S4 ) . In agreement with this conclusion , no phosphoryl transfer was detected from CheS3∼P to a truncated version of CheS3 comprised of only the N-terminal CheS3-REC1 domain ( Figure 4D ) . Interestingly , despite evidence against CheS3 intramolecular phosphoryl transfer , the >4 hour stability of CheS3:D54A∼P is substantially greater than the 55 min stability observed with CheS3∼P ( Table 1 ) suggesting that D54 may play a role in promoting autodephosphorylation of the HK domain . Based on the CheA-CheY paradigm from E . coli , we tested the ability of CheA3 to phosphorylate CheY3 . In our assays CheA3∼P and the more stable CheA3:D663A∼P mutant did not exhibit any detectable ability to transfer a phosphate to CheY3 ( Figure 5A , 5B ) in Buffer 9 . Since the E . coli CheY and other response regulators exhibit a wide range of binding affinities to divalent metals ( Kd of 0 . 4–47 mM under pH 6 . 0–10 . 0 have been reported [15] , [22]–[24] ) , we also assayed CheA3 phosphorylation of CheY3 in Buffers 15–21 with higher ( 18 mM ) total divalent metal concentrations ( Table S1 ) . This assay condition also failed to obtain phosphoryl transfer from CheA3∼P or CheA3:D663A∼P to CheY3 ( Figure S5 ) . In contrast to the hypo-cyst phenotype exhibited by null mutation of cheA3 , null mutations in cheS3 and cheY3 both exhibit indistinguishable hyper-cyst phenotypes ( Figure 2 ) indicating that CheS3 might be the cognate kinase of CheY3 . To test whether CheS3 can phosphorylate CheY3 we phosphorylated CheS3 for 30 min and then added CheY3 . Upon addition of CheY3 , rapid phosphoryl transfer from CheS3∼P to CheY3 was observed within 30 sec ( Figure 5C ) . We also observed that CheS3:D54A is capable of phosphorylating CheY3 ( Figure 5D ) and that the H453A point mutation renders CheS3 unable to autophosphorylate ( Figure S6 ) . Thus , the phosphoryl group appears to transfer directly from H453 from CheS3 to CheY3 . We also note that CheY3 appears to have a fast autodephosphorylation rate similar to chemotaxis CheYs [25]–[27] . Since the REC1 domain of CheS3 is not phosphorylated by the tethered HK domain , we questioned whether CheA3 participates in the CheS3 pathway by phosphorylating the REC1 domain of CheS3 . We initially performed a phosphotransfer assay using CheA3∼P as the phospho-donor and did not observe CheS3-REC1 phosphorylation in Buffer 9 ( Figure S3B ) or Buffer 15 ( Figure S3C ) . We reasoned that it may be difficult to observe an in vitro intermolecular transfer of phosphate from CheA3 to CheS3 as the intramolecular transfer from the HK domain of CheA3 to the tethered REC domain of CheA3 may outcompete this reaction . We therefore repeated the assay using the CheA3:D663A mutant as the tethered mutated REC domain would not compete with this intermolecular transfer . As shown in Figure 5E , CheA3:D663A does indeed transfer a phosphate to the CheS3-REC1 domain . This transfer from CheA3 to CheS3-REC1 also demonstrates a level of specificity typically exhibited between cognate HK-RR partners , as phosphate does not flow from CheS3 to CheA3-REC ( Figure 5F , Figure S3D ) . As shown in Figure 2 , a D54A mutation in the CheS3 REC1 domain that would be unable to accept a phosphate in the REC domain exhibits a cyst deficient hypo-cyst phenotype . This is opposite of the hyper-cyst phenotype exhibited by a H453A mutation ( Figure 2 ) that would disrupt CheS3 kinase activity . These opposing phenotypes suggest that phosphorylation of the CheS3 REC1 domain by the HK domain from CheA3 would have an inhibitory effect on autophosphorylation of CheS3 or a stimulating effect on autodephosphorylation of CheS3 . This conclusion is also supported by genetic and epistasis studies which indicates that cheS3 null mutants are hyper-cyst and also epistatic to the hypo-cyst phenotype exhibited by cheA3 null mutants ( Figure 2 ) .
Chemotaxis and chemotaxis-like signaling pathways represent some of the more complex multicomponent signal transduction systems present in prokaryotes . A recent bioinformatic analysis of 450 non-redundant prokaryotic genomes found that 245 contained at least one chemotaxis-like protein [28] . In these 245 genomes there are a total of 416 chemotaxis-like systems that contain at least an MCP , CheA , and CheW homologs , which together are considered a minimum chemotaxis core [28] . Together , Che-like signal transduction cascades are known to control three classes of function: flagellar motility , type IV pili-based motility ( TFP ) , and alternative cellular functions ( ACF ) [28] . The ACF class comprises approximately 6% of all the identified chemotaxis systems , regulating cellular processes such as cell development [29] , [30] , biofilm formation [31] , exopolysaccharide production [32] , cell-cell interactions [33] , [34] , and flagellum biosynthesis [35] . In fact , most identifiable Che-like signal transduction cascades are yet to be genetically disrupted so the function of many of these pathways remains to be elucidated . Chemotaxis systems either exhibit typical chemotaxis architecture as found in E . coli , or have evolved to include additional auxiliary proteins and/or multi-domain hybrid components . Only a few of the more complex Che-like systems containing auxiliary proteins have been biochemically and genetically assayed for the flow of phosphate among protein components . Consequently , it remains unclear whether the CheA-CheY paradigm from E . coli will hold true for the many other , and often more complex , Che-like cascades from other species . Clearly the results of this study indicate that the Che3 cascade from R . centenum differs from this paradigm in that CheA3 functions to regulate the CheS3-CheY3 TCS . In some respects this is similar to the Che3 cascade from M . xanthus where a CheA homolog controls developmental program by acting as a phosphatase to the DNA binding RR CrdA [7] . HHKs with appended REC domains are often present in organisms that adopt complex life styles such as M . xanthus [36]–[39] and R . centenum [29] , [40] , allowing for added layers of regulation within signaling systems . In some cases , intramolecular phosphoryl transfer occurs within HHKs . For example , RodK from M . xanthus has three REC domains that are all essential for fruiting body formation but the HK domain selectively transfers a phosphate to its third REC domain [36] . In E . coli , the HK and REC domains of RcsC are involved in a HK→REC→Hpt→REC phosphorelay , which regulates capsular synthesis and swarming [41] . In other cases , the receiver domain can either prevent the HK from autophosphorylating , presumably by an occluding mechanism [42] , or enhance gene expression by interacting with the cognate response regulator of the HHK [43] . Cysts are a dormant , non-growing state needed for survival in poor growth conditions , so the decision to form or impede this developmental pathway must involve multiple inputs and checkpoints . In the R . centenum Che3 cascade , there are three receivers that are capable of accepting a phosphate from two HHKs ( CheB3 is not discussed here since CheB homologs are typically involved in MCP modification and not downstream signaling ) . CheA3 and CheS3 are HHKs containing respective C-terminal and N-terminal REC domains whereas CheY3 is a stand-alone receiver without an identifiable output domain . The presence of three REC domains and two HK domains encoded in this gene cluster potentially makes the Che3 signaling cascade quite complex with the possibility of multiple inputs and check points , which are presumably necessary to control the decision to induce cyst formation . We showed that CheA3∼P is acid- and base-labile , indicating that an intramolecular phosphoryl transfer occurs between the tethered HK and REC domains . This transfer is inhibited when D663 is substituted with an Ala , giving rise to a His-phosphorylated CheA3:D663A∼P that is stable at high pH . The phosphate on CheA3:D663A is much more stable than observed with wild type CheA3 , indicating that the tethered REC domain likely functions as a phosphate sink , attenuating phosphorylation of its own HK domain . Fused REC domains serving as phosphate sinks are not unprecedented . CheAY2 , a CheA-CheY hybrid in Helicobacter pylori has also been shown to use its REC domain as a phosphate sink by rapidly dephosphorylating the linked kinase domain [27] . Unlike CheA3 , the REC1 domain of CheS3 appears to serve a different function . CheS3∼P is acid-labile and base-resistant and also does not phosphorylate its receiver truncation ( CheS3-REC1 ) in vitro . This indicates that the CheS3 HK domain does not phosphorylate its own REC1 domain . While it is unclear whether the CheS3 REC1 domain directly interacts with the HK domain , it is evident that the REC1 domain greatly affects the phosphorylation state of H453 . This is evidenced by the half-life of CheS3:D54A∼P that is prolonged by many hours relative to wild type CheS3∼P ( Table 1 ) . Furthermore , the CheS3:D54A mutant has an opposing in vivo phenotype from a CheS3:H453A mutant thereby indicating that the CheS3 REC1 domain has regulatory control over phosphorylation of the CheS3 HK domain . Based on these results , we propose that D54 stimulates autodephosphorylation of the C-terminal HK domain by a mechanism other than transferring and accepting phosphates from the CheS3 HK domain . Although we do not yet have molecular details on how Asp-phosphorylated CheS3 inhibits the HK domain of CheS3 , genetic and biochemical results clearly suggest that CheA3 promotes cyst formation by phosphorylating the REC1 domain in CheS3 . It is likely that Asp-phosphorylated REC1 domain causes a conformational adoption that either inhibits CheS3 autophosphorylation or accelerates autodephosphorylation of the tethered HK domain . The results of this study allow us to establish a working model for the Che3 signal transduction cascade in R . centenum ( Figure 6 ) . Under cyst non-inducing conditions , CheA3 has low basal level of kinase activity that directs intramolecular phosphate flow in the direction of His→Asp→Pi . The REC1 domain of CheS3 remains unphosphorylated so the HK domain of CheS3 operates at a high level of activity that effectively transfers phosphoryl groups to CheY3 . CheY3∼P subsequently activates downstream components that repress cyst formation ( Figure 6A ) . Upon starvation or desiccation ( cyst inducing conditions ) , a signal is sensed by MCP3 , which fully activates the kinase activity of CheA3 ( Figure 6B ) . Activated CheA3 is now able to phosphorylate the REC1 domain of CheS3 thereby turning off the HK domain of CheS3 leading to unphosphorylated CheY3 that induces cyst formation ( Figure 6B ) . This model also readily explains the opposing phenotypes of the cheA3:D663A and cheS3:D54A REC mutant strains ( Figure S7 ) . In the cheA3:D663A REC mutant , intramolecular phosphoryl transfer , which acts as a CheA3 phosphate sink , would be blocked . The resulting elevated phosphate concentration at the CheA3 HK domain would subsequently lead to elevated phosphoryl transfer from CheA3 to the REC1 domain of CheS3 under both vegetative and cyst inducing growth conditions . Constitutive phosphorylation of the REC1 domain of CheS3 by CheA3:D663A would lead to a reduction in the HK activity of CheS3 and subsequent reduction in phosphorylation of CheY3 . Thus , the cheA3:D663A strain should have a cyst defective phenotype under all growth conditions , which is what is observed ( Figure S7A and B ) . For the cheS3 REC1 mutant , CheA3 is no longer capable of phosphorylating the CheS3 REC1 domain due to the D54A substitution ( Figure S7C ) . Therefore the CheS3 HK domain is able to autophosphorylate and phosphorylate CheY3 under all growth conditions . This would result in constitutive repression of cyst formation , which is also observed ( Figure S7C and D ) . Even though details of the Che3 phosphorylation cascade have been revealed , several features of this pathway still require clarification . First , based on the E . coli chemotaxis model , CheA3 should be activated by an extracellular signal received by MCP3 , the nature of which is currently unknown . Second , it is unclear whether CheS3 is regulated only from phosphorylation by CheA3 or if it also directly senses changes in metabolism during encystment via a PAS domain . Third , the outputs and the downstream components of the Che3 signal transduction cascade remain elusive . One possibility is that CheY3 passes its phosphate onto unidentified downstream components . Also not yet reconciled is how the Che3 pathway is integrated with the cGMP signaling in R . centenum . This signaling nucleotide is synthesized as cells transition from vegetative growth into the cyst developmental phase [44] . While this is a newly identified signaling pathway , a cGMP responsive CRP-like transcription factor has been identified and is required to induce cyst development [44] . How these two seemingly independent pathways together control the induction and timing of cyst formation constitutes a significant challenge in our understanding of this Gram-negative developmental pathway .
cheS3 was PCR amplified with 500 bp of flanking DNA as two fragments using wild type cells as template for colony PCR with primer pairs listed in Table S2 . PCR amplified fragments were separately cloned and sequenced in pTOPO . Using a Quikchange ( Stratagene ) point mutagenesis kit , the D54A mutation was made within the 5′ cheS3 fragment harboring plasmid , whereas a H453A mutation was made in the plasmid harboring the 3′ cheS3 fragment using primers described in Table S2 . Suicide vector constructs for cheS3 containing D54A or H453A mutations were then constructed by ligating the appropriate 5′ and 3′ cheS3 fragments directly into pZJD29a using external BamHI and XbaI sites and were internally joined by a BbsI site common to both fragments . After sequence confirmation , plasmids were mated from E . coli S17-1 ( λpir ) into an R . centenum ΔcheS3 strain [8] . Initial recombinants were selected for on CENSGm and second recombinants with chromosomal cheS3 point mutants were identified by phenotypic ( GmS/SucR ) and colony PCR analyses . Suicide vector constructs for cheA3:H49A , cheA3:D663A , and cheY3:D64A were similarly constructed using point mutagenesis primers detailed in Table S2 , with cheA3 internally ligated using a ClaI site and cheY3 cloned as one fragment . See Table S3 for a complete list of R . centenum strains used in this study . Two types of media were used to assay for encystment: CENS was used for vegetative growth [45] , and CENBA for inducing cyst formation [46] . Encystment uninduced cells were prepared by overnight growth in CENS at 37°C . Encystment induced cells were prepared by washing overnight CENS cultures twice in CENBA , subculturing 1∶40 into CENBA and then incubating at 37°C for 3 days . For microscopic observations , phase-contrast microscopy was performed on a Nikon E800 light microscope equipped with a 100× Plan Apo oil objective . For flow cytometry , CENS and CENBA cultures were diluted in 40 mM phosphate buffer and sonicated briefly ( ∼1 sec ) at lower power to disaggregate cyst cells . All samples were stained in 2 µM Syto-9 ( Life Technologies/Molecular Probes , Grand Island , NY ) for 1 . 5 hours . Syto-9 is a permeant DNA stain that was shown microscopically to penetrate both vegetative and cyst cells similarly ( data not shown ) . Initially fluorescent calibration beads of 880 nanometers and 10 microns were used to set the limits for background . After staining , cells were diluted ∼1∶10–1∶20 in 40 mM phosphate buffer just prior to running to achieve ∼1000 events per second on a Becton Dickenson FACS Calibur flow cytometer running CellQuest Pro data collection software using an argon laser ( 488 nm ) . 100 , 000 events were collected per sample with two biological replicates analyzed for each bacterial strain grown in each media . Forward and side scatter ( SSC vs FSC ) were plotted in logarithmic scales . Hypo-cyst ΔcheA3 and hyper-cyst ΔcheS3 strains were used to determine the appropriate gating to use for vegetative cells versus cyst cells . FlowJo version 10 ( Tree Star , Inc . ) was used to analyze the data and plot the data for publication . Statistical analysis was performed using Prism version 5 . 0 ( GraphPad Software , Inc . ) . Coding regions of CheS3 , CheA3 , CheY3 , and the receiver domains of CheA3 and CheS3 ( CheA3-REC and CheS3-REC1 ) were PCR amplified from R . centenum genomic DNA with primers listed in Table S1 . Gel-purified PCR products were cloned into pBluescript SK+ or pGEM-T , sequenced , then subcloned into the NdeI and XhoI sites in vector pET28a . pET28a plasmids for overexpression of CheS3 and CheA3 point mutants were generated using the appropriate pZJD29a vector as template for PCR using primers detailed in Table S1 . All pET28a constructs were transformed into E . coli BL21 Rosetta 2 ( DE3 ) cells ( Novagen ) . See Table S3 for a complete list of E . coli strains used in this study . For overexpression , overnight cultures of E . coli Rosetta 2 ( DE3 ) cells were subcultured 1∶100 into 1 L LB medium and shaken at 37°C to an OD600 of 0 . 5 . Protein overexpression was induced at an isopropyl β-D-1-thiogalactopyranoside concentration of 0 . 4 mM and cultures were incubated overnight at 16°C with gentle agitation . Cells were pelleted by centrifugation and stored at −80°C until further use . For purification of all proteins , cell pellets were resuspended and lysed by ultrasonication in lysis buffer ( 20 mM Tris-HCl pH 7 . 5 , 500 mM NaCl , 25 mM imidazole and 10% glycerol ) . Purification was performed on 1 mL HisTrap HP ( GE Healthcare ) columns using an FPLC system . His-tagged proteins were eluted in 20 mM Tris-HCl ( pH 7 . 5 ) buffers with a gradient of 25–500 mM imidazole . Fractions containing purified proteins were dialyzed into a storage buffer ( 25 mM Tris-HCl pH 7 . 5 , 100 mM NaCl in 30% glycerol ) and stored at −20°C until further use . Twenty-one Tris buffers containing common mono- and divalent metal ions were used in this study for HHK phosphorylation and phosphotransfer assays ( see the full list of buffer compositions in Table S1 ) . All kinase reactions and phospho-transfers were performed in 0 . 2 mM final ATP concentration except for the half-life determination experiments . All reactions were stopped by addition of 6× SDS-PAGE sample loading buffer . All phospho-proteins were separated by SDS-PAGE and gels were examined by autoradiography on a Typhoon 9100 scanner ( GE Healthcare ) located in the Indiana University Physical Biochemistry Instrumentation Facility . In the metal ion dependency assays ( shown in Figure 3B and Figure S3 ) , isolated kinases were diluted in the indicated buffers to 2–5 µM . Kinase reactions were initiated by adding 1/20 volume of ATP/[γ-33P] ATP mix in 25 mM Tris pH 7 . 5 and allowed to proceed for 30 min at room temperature . For phosphoryl transfer to CheY3 shown in Figure S3 , 1/10 volume of 65 mM CheY3 was also added to each reaction mixture at the end of 30 min autophosphorylation for another 30 min incubation at room temperature . In assays assessing intermolecular phosphoryl transfer shown in Figure 4C , Figure 5 , and Figure 6 , ATP mixes and protein dilutions were made in same buffer as indicated in the text . 2–5 µM kinases were first phosphorylated in 0 . 2 mM ATP for 30 min followed by addition of 1/10 volume of 65 µM CheY3 or receiver domain truncations ( CheS3-REC1 or CheA3-REC ) . The time of receiver addition was set to time 0 . Phosphoryl transfer was then assessed at various time intervals . To determine the half-lives of phosphorylated kinases , 2–5 µM CheA3 and CheA3:D663A were pre-autophosphorylated in the presence of 10 µM ATP mix in Buffer 9 for 50 min before passing through Bio-Rad Micro Spin 6 chromatography columns to remove excess ATP . Dephosphorylation was monitored at room temperature by removing 10 µL of the filtrates at various time intervals . Phosphorylation of the kinases was quantified using ImageJ software by integrating the grayscale density of the radioactive bands . % Kinase phosphorylation was plotted over 300 min and data points were fitted to one phase exponential decay using Prism . Half-lives of CheS3 and CheS3:D54A were measured with the same protocol with the exception that Buffer 5 was used in place of Buffer 9 . The phosphorylation state of all CheS3 and CheA3 variants was determined by assaying phosphoprotein stability under acidic or basic conditions using a non-filter based assay [47] . Kinases were allowed to autophosphorylate at room temperature for 30 min , after which phosphoproteins were denatured by adding 0 . 1 volume of 20% SDS . Aliquots were withdrawn and mixed with equal volumes of 0 . 1 or 1 . 0 M Tris pH 7 . 5 , HCl or NaOH and incubated for 30 min at 37°C before being neutralized with 1 . 0 M Tris-HCl pH 7 . 5 . Samples were then mixed with 6× loading dye and resolved by SDS-PAGE and assayed for phosphorylation by autoradiography . Phosphorylation of the kinases was quantified using ImageJ software by integrating the grayscale density of the radioactive bands . | Bacteria use chemotaxis and chemotaxis-like signal transduction pathways to quickly sense and adapt to a constantly changing environment . The purple photosynthetic bacterium Rhodospirillum centenum is able to withstand long periods of desiccation by forming metabolically dormant cyst cells , the development of which is regulated by the Che3 chemotaxis-like pathway . Using a combination of genetic and biochemical approaches , we demonstrate that hybrid histidine kinase ( HHK ) CheA3 encoded in the che3 gene cluster is essential for cyst formation while another HHK CheS3 inhibits cyst formation . We further show that the appended receiver domains of these kinases regulate their respective histidine kinase domains and are critical in controlling the timing of cyst formation . Finally , we demonstrate that CheA3 functions upstream of CheS3 and promotes cyst formation by phosphorylating CheS3 . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2013 | Phosphate Flow between Hybrid Histidine Kinases CheA3 and CheS3 Controls Rhodospirillum centenum Cyst Formation |
Secondary metabolism and development are linked in Aspergillus through the conserved regulatory velvet complex composed of VeA , VelB , and LaeA . The founding member of the velvet complex , VeA , shuttles between the cytoplasm and nucleus in response to alterations in light . Here we describe a new interaction partner of VeA identified through a reverse genetics screen looking for LaeA-like methyltransferases in Aspergillus nidulans . One of the putative LaeA-like methyltransferases identified , LlmF , is a negative regulator of sterigmatocystin production and sexual development . LlmF interacts directly with VeA and the repressive function of LlmF is mediated by influencing the localization of VeA , as over-expression of llmF decreases the nuclear to cytoplasmic ratio of VeA while deletion of llmF results in an increased nuclear accumulation of VeA . We show that the methyltransferase domain of LlmF is required for function; however , LlmF does not directly methylate VeA in vitro . This study identifies a new interaction partner for VeA and highlights the importance of cellular compartmentalization of VeA for regulation of development and secondary metabolism .
Small bioactive secondary metabolites are molecules that have great importance to humankind and can be broadly characterized by their impact on human health . Members of the filamentous fungal genus Aspergillus are prolific producers of secondary metabolites , both useful ( penicillin , lovastatin ) and detrimental ( aflatoxin , sterigmatocystin , gliotoxin ) , therefore they are excellent organisms to study the genetic regulation of secondary metabolism . Genes responsible for the production of secondary metabolites are often clustered on chromosomes , vaguely reminiscent of bacterial operons , and these gene clusters are co-regulated [1] . Relatively recently a global regulator of secondary metabolism , LaeA , was described in the Aspergilli [2] . LaeA has since been shown to be part of the velvet complex , composed of LaeA , VeA , VelB , that couples secondary metabolism with developmental processes including asexual and sexual development [3] . Moreover , LaeA has been found to direct formation of a second velvet-like complex composed of VelB and VosA [4] . Both complexes function to orchestrate secondary metabolism with developmental differentiation in a light dependent fashion [3]–[5] . The core components of the velvet complex are found in all filamentous fungi studied to date and function to regulate important pathways , including pathogenicity in both plants and humans . For example , null mutants of A . fumigatus laeA produce fewer secondary metabolites and are hypovirulent in the mouse model of invasive aspergillosis [6] , [7] while both VeA and LaeA homologs in the plant pathogens A . flavus , Fusarium fujikuroi , F . verticillioides , and Cochliobolus heterostrophus are involved in regulation of virulence and toxin production [8]–[12] . Recent work in F . graminearum has identified that both the veA and velB homologs are virulence factors [13]–[16] , however these data indicate the heterotrimeric LaeA-VeA-VelB complex might be slightly different in this organism , as FgVeA did not interact with FgLaeA or FgVelB in a yeast-two-hybrid assay [13] , [15] . Taken together , the velvet complex control of secondary metabolism and development appears to be conserved in filamentous fungi [5] , however its cellular operational mechanism remains an enigma . Current knowledge of the velvet complex functionality in Aspergillus centers on the importance of VeA as a bridging factor between VelB and the putative methyltransferase LaeA . Together , this heterotrimeric complex regulates developmental differentiation in response to light . LaeA is a constitutively nuclear protein that harbors a methyltransferase domain required for function [2] , [17] and VelB is a velvet–like protein that forms a heterodimer with VeA [3] . In A . nidulans , VeA-VelB is required for sexual development , while VeA-LaeA is required for production of the mycotoxin sterigmatocystin [3] . An important aspect of VeA is its subcellular localization in response to illumination . Stinnett et al . [18] first reported that VeA is found in the cytoplasm under light conditions and is mainly nuclear under dark conditions , while the truncated VeA1 is blind to light and fails to accumulate in the nucleus in the dark . It has also been demonstrated that transcription of veA is relatively constant over all developmental stages [19] and this correlates with protein levels [4] . Therefore , the subcellular location of VeA has the potential to control protein interaction partners as well as to direct developmental and chemical responses to environmental cues . While VelB-VeA-LaeA has been shown to be a stable complex that interacts in the nucleus , VeA interacts with several other proteins , including the red light sensing protein FphA , and thus indirectly with the blue light sensing proteins LreA and LreB [20] , [21] . The VeA-family of proteins ( VeA , VelB , VelC , VosA ) all contain a characteristic velvet domain [5] , while VosA also has a characterized C terminal transcriptional activation domain [5] , [22] . Bayram and Braus [5] have speculated that the velvet domain may function as a protein-protein interaction domain . Calvo [23] and others ( i . e . [5] ) hypothesize that VeA could function as a scaffold protein directing transcriptional response to changes in environmental cues , such as illumination . Working under this hypothesis , the velvet complex may contain additional accessory proteins that could influence development and secondary metabolism . We used a reverse genetics approach to identify several putative methyltransferases in A . nidulans that have sequence homology to LaeA , and then set out to determine if any of these putative methyltransferases were linked to the velvet complex . Here we describe the LaeA-like methyltransferase , LlmF , that is a negative regulator of sexual development and secondary metabolism in A . nidulans . We report that LlmF interacts with VeA and functions to mediate subcellular localization of VeA . This study identifies a new interaction partner of VeA while illustrating the importance of cellular compartmentalization as a form of regulating secondary metabolism and development .
Since LaeA has been shown to regulate many but not all secondary metabolite clusters and VeA has several interaction partners , including LaeA , VelB , and FphA [23] , we hypothesized that other LaeA-like methyltransferases could play a role in velvet complex developmental regulation . The primary amino acid sequence of LaeA ( AN0807 ) indicates that it contains an S-adenosyl methionine ( SAM ) binding domain [2] that is required for function [17] . To determine if there are other putative LaeA-like methyltransferases in A . nidulans , predicted amino acid sequences were obtained for all SAM binding domain proteins from the Aspergillus nidulans genome database at the Broad Institute and aligned with known methyltransferases from S . cerevisiae , Sc . pombe , and A . flavus . A bootstrapped phylogenic tree was inferred from this analysis ( Figure 1 ) . This analysis identified nine putative ORFs that have sequence homology to LaeA and no homologies to previously characterized yeast methyltransferases ( LlmA – AN2165 , LlmB – AN8945 , LlmC – AN7933 , LlmD – AN5416 , LlmE – AN5091 , LlmF – AN6749 , LlmG – AN5874 , LlmI – AN8833 , and LlmJ – AN9193 ) . One of these putative ORFs , llmE ( AN5091 ) , has previously been characterized and resides in a location that is transcriptionally repressed by telomere position effect [24] . In order to ascertain functions of the LaeA-like methyltransferase ( Llm ) proteins , transcriptional profiling from a wild type A . nidulans strain ( RDIT9 . 32 ) was conducted at several distinct developmental growth time points ( Figure 2 ) . Northern analysis of the llm genes show that some are transcribed at nearly all developmental stages ( llmA , llmB , and llmI ) , while others are transcribed at very low levels ( llmD , llmF , llmG , and llmJ ) , and llmC is mainly transcribed during late asexual development ( Figure 2 ) . To assess the roles of each Llm on secondary metabolism , null mutants were created for all of the putative Llm's and confirmed by Southern blot ( Figure S1 and data not shown ) . Preliminary characterization of secondary metabolite production indicated that ΔllmF produced increased levels of sterigmatocystin ( Figure 3 ) , whereas the other eight Llm's had minor impacts on sterigmatocystin ( Figure S2 , [24] ) . Therefore we chose to focus our efforts on characterization of LlmF ( AN6749 ) . While llmF appears to be expressed at low levels throughout development , there is an increase in llmF transcription during later stages of both vegetative and asexual growth conditions , while there is no increase of llmF during sexual development ( Figure 2 ) . To gain further insight into llmF regulation of secondary metabolism , llmF was over-expressed with the constitutive gpdA promoter ( data not shown ) . We assessed sterigmatocystin production in the llmF mutants , and oppositely to ΔlaeA mutants , deletion of llmF results in increased sterigmatocystin levels . Conversely , over-expression ( OE ) of llmF reduced sterigmatocystin production ( Figure 3 ) . Interestingly , we did not detect an increase in sterigmatocystin production in a ΔllmF mutant harboring the veA1 allele ( Figure 3B ) . To test the requirement of LaeA and VeA in LlmF regulation of sterigmatocystin; double mutants were created and these analyses suggest that both LaeA and VeA are required for negative regulation of sterigmatocystin by LlmF ( Figure 3 ) . Since LlmF mediated regulation of sterigmatocystin was dependent on the velvet complex , we hypothesized that LlmF could interact directly with LaeA or VeA . A cDNA was cloned for LlmF ( Figure S3 ) and a directed yeast-two-hybrid approach was taken to ascertain protein-protein interactions . These results indicated that LlmF interacts with VeA but not the truncated VeA1 or LaeA ( Figure 4A ) . However , the yeast-two-hybrid assay is historically prone to false-positives and in addition we have noticed inconsistencies with VeA1 in this assay , for example Bait-LaeA does not interact with Prey-VeA1 ( Figure 4A ) . Therefore , we also assessed the LlmF-VeA interaction with an in vitro GST pull-down assay with recombinantly expressed GST-LlmF and His6-VeA-S-tag ( Figure 4B ) . As an assay control , GST-VelB and GST-LaeA were also used to pull-down His6-VeA-S-tag ( Figure 4B ) . Finally , we performed an in vivo pull-down experiment using tandem affinity purification ( TAP ) tagged LlmF combined with S-tagged VeA and VeA1 . After purification of TAP-LlmF , both VeA-S-tag and VeA1-S-tag were detected via immunoblotting ( Figure 4C ) . Unlike the yeast-two-hybrid results , the in vivo pull-down data suggest that LlmF interacts with both VeA and the truncated VeA1 under these conditions . Previous studies on LaeA had indicated that it was a likely methyltransferase based on site directed mutagenesis of the S-adenosyl methionine ( SAM ) binding domain , which resulted in a non-functional protein [17] . A multiple sequence alignment [25] of A . nidulans LlmF , A . nidulans LaeA , A . flavus LaeA , A . fumigatus LaeA , Cochliobolus heterostrophus LaeA , and Fusarium fujikuroi LaeA confirm that all of these proteins contain a SAM binding domain which can be further classified into conserved motifs as previously described [26] , [27] ( Figure 5A ) . We tested the functionality of the SAM binding domain by using an ultraviolet ( UV ) light cross-linking experiment of 3H-SAM ( Figure 5B ) . As a control , GST and GST-LaeA were included in the experiment and these results indicate that both LaeA and LlmF have the ability to bind SAM ( Figure 5B ) . Competitive inhibition of the binding site was achieved by co-incubation of 3H-SAM with S-adenosyl homocysteine ( SAH ) and under these conditions a reduction in 3H-SAM binding was observed in both GST-LlmF and LlmF . GST-LlmF but not GST-LaeA showed a reduction in 3H-SAM binding under these conditions , which could suggest that GST-LaeA binds SAM more tightly than LlmF . In order to assess the role of the SAM binding site of LlmF , we constructed a SAM binding site mutant in vivo by site directed mutagenesis of motif I ( Figure 5A ) . Mutation of two conserved glycine residues to alanine residues in motif I rendered LaeA non-functional [17] , therefore we mutated the same residues in LlmF ( G91A and G93A ) . To analyze the effect of this mutation in vivo , llmFG91A , G93A ( llmFSAM ) was driven by the gpdA promoter in a ΔllmF background . As abnormalities in sexual development - ranging from cleistothecial morphological aberrancies to alterations in sexual to asexual spore ratios - are clearly and consistently observed in veA , velB and laeA mutants [4] , [28] , we investigated the impacts of llmF on sexual development . Macroscopic observations during sexual developmental induction of ΔllmF and OE llmF mutants showed that ΔllmF favored sexual development and OE llmF asexual development . Additionally , the OE llmFSAM mutant displayed a phenotype more similar to the ΔllmF mutant ( Figure 6A ) . To more accurately measure llmF effect on sexual development , ascospores and conidia were quantified from sexually induced culture conditions and represented as a ratio of ascospores to conidia ( Figure 6B ) . The ΔllmF strain produced an increased ratio of ascospores to conidia and consistent with the negative regulation of sexual development the OE llmF strain produces decreased ratio of ascospores to conidia . Mirroring the macroscopic images , the OE llmFSAM mutant produced a similar ratio to the ΔllmF strain ( Figure 6B ) . Moreover , we measured production of sterigmatocystin from these four strains . This further confirms that LlmFSAM is not functional as the OE llmFSAM mutant produced levels of sterigmatocystin intermediate to wild type and ΔllmF , in contrast to the reduced levels of the OE llmF strain ( Figure 6C ) . Finally , a northern blot from total RNA isolated from the same conditions confirmed the strains were correct and the OE llmFSAM construct was properly expressed ( Figure 6D ) . Taken together these data indicate that LlmF is a negative regulator of sexual development and secondary metabolism and the SAM binding site of LlmF is required for function . Since the velvet complex has been implicated in transcriptional control of secondary metabolism and development , we hypothesized that the observed phenotypes could be explained by differential transcription of velvet complex members in the ΔllmF and OE llmF backgrounds . Specifically , we hypothesized that LlmF could negatively regulate transcription of veA , laeA , or velB which could explain the increased secondary metabolism and sexual development in the ΔllmF background . To test this hypothesis , a northern blot was done on RNA isolated from asexual and sexual developmental induced cultures . These data refute this hypothesis , as LlmF has minimal effect on transcription of veA , laeA , or velB ( Figure 7 ) . This is in contrast to the impact of loss or over-expression of velvet complex members on each other in which deletions of veA , velB , and laeA have previously been shown to substantially increase transcription of the other members of the complex and , where examined , over-expression reduced expression of other gene members [3] , [11] . However , consistent with the conidial phenotype of llmF mutants , the key asexual developmental activator brlA shows decreased expression in the ΔllmF strain and increased expression in the OE llmF strain ( Figure 7 ) . VeA has previously been shown to be a light regulated protein; in the light VeA is localized mainly in the cytoplasm , however in the dark VeA is almost exclusively nuclear [18] . On the other hand , LaeA is located in the nucleus independent of light but requires nuclear VeA for control of secondary metabolism and some aspects of sexuality [2] , [3] . Since VeA is required for LaeA function , it seemed plausible that LlmF and LaeA could be competing for VeA binding , either directly or indirectly . Additionally , llmF mutants do not show phenotypes in a mutant veA1 background suggesting that nucleo-cytoplasmic localization of VeA could be altered compared to wild type . To test this hypothesis , we first tagged LlmF with GFP at both the N and C terminus independently . By phenotypic analysis , C terminal LlmF-GFP constructs were nonfunctional; therefore we used the functional N terminal GFP-LlmF strains and determined LlmF was located primarily in the cytoplasm independent of light ( Figure 8A ) . Additionally , the localization of GFP-LlmF in a veA1 background was tested and displayed similar localization ( Figure 8A ) . While LaeA is constitutively nuclear and LlmF cytoplasmic , we reasoned that competition for VeA binding could be assessed by the subcellular localization of VeA . To test this hypothesis , VeA-GFP was visualized in ΔllmF and OE llmF genetic backgrounds . Interestingly , VeA-GFP was mis-localized in response to light conditions in both the ΔllmF and OE llmF backgrounds . Specifically , slightly more VeA accumulated in the nucleus under light conditions in a ΔllmF background compared to wild type whereas VeA failed to accumulate in the nucleus under dark conditions in an OE llmF background , phenocopying the VeA1-GFP localization pattern ( Figure 8B and 8C ) . These results indicate that increased nuclear VeA could be responsible for the increased production of sterigmatocystin in ΔllmF strains and the cytoplasmic location of VeA in the OE llmF background the reason for decreased sterigmatocystin and sexual development in this strain . Nuclear import of VeA in response to light is mediated by importin α ( KapA ) [18] , [29] . Additionally , VelB is hypothesized to be a cytoplasmic protein that enters the nucleus through its interaction with VeA [3] . Hence , the model for VeA nuclear import is as follows: KapA recognizes and binds the nuclear localization signal of VeA and along with VelB , the KapA-VeA-VelB transient complex is transferred to the nuclear pore . To determine if LlmF could be altering VeA localization through disruption of VeA-VelB interaction or KapA-VeA interaction , we tested for the ability for LlmF to interact with either KapA or VelB . Figure 9A illustrates that neither KapA nor VelB are interaction partners for LlmF in the yeast-two-hybrid assay . These data also indicate that KapA is capable of recognizing VelB in the absence of VeA , however previous data suggests that VelB requires VeA for nuclear import [3] . Since LlmF interacted with only VeA and not VelB or KapA , we hypothesized that VeA-LlmF interaction could be interfering with KapA recognition and subsequent nuclear import . As previous data have indicated that KapA recognizes the VeA-VelB dimer for nuclear import [3] , [29] , to see if LlmF and VelB interacted with VeA in the same domains , we mapped the protein interaction site of VeA-LlmF using the directed yeast-two-hybrid assay . Testing the interaction of full length VeA with 5 different truncations of LlmF showed that only full length LlmF is capable of interacting with VeA in this assay ( Figure 9B ) . Similarly , when 5 different truncations of VeA were tested as interaction partners with LlmF , similar results were obtained in which full length VeA is required for interaction with full length LlmF ( Figure 9C ) . Simultaneously , we were able to refine the interaction domains of VeA-LaeA and VeA-VelB . Previously Bayram et al . [3] showed that VelB interacts with the N terminus of VeA ( 1–300 aa ) while LaeA interacts with the C terminus of VeA ( 276–573 aa ) . Here our data suggest that VelB interacts with the N terminus of VeA ( 1–235 aa ) , however the first 28 aa are necessary for this interaction as VelB did not interact with just the velvet domain of VeA ( 29–235 ) ( Figure 9C ) . We were also able to show that LaeA can interact with the C terminal 115 amino acids of VeA ( Figure 9C ) . Since our in vivo LlmF SAM binding site mutant was not functional ( Figure 6 ) , we tested for interaction between VeA and LlmFSAM , and found LlmFSAM interacted with VeA ( Figure 9D ) . Taken together , these data suggest that LlmF-VeA interaction is relatively weak in comparison to the heterotrimeric complex of VelB-VeA-LaeA . Since a mutation in the SAM binding site of LlmF did not disrupt its ability to interact with VeA ( Figure 9D ) but did render the protein inactive in vivo ( Figure 6 ) , we hypothesized that LlmF could be directly methylating VeA or other components involved in nuclear import of VeA , such as VelB and KapA . To test this hypothesis , recombinant LlmF was incubated with tritiated SAM ( 3H SAM ) in the presence of GST , His6-VeA-GST-S-tag , GST-VelB , and GST-KapA and subsequently , methylation was measured by fluorography . As a positive control , GST-RmtA was incubated with its substrate of histone H4 as previously described [30] . These data indicated that in vitro LlmF does not methylate histone H4 , VeA , VelB , or KapA ( Figure 10A and 10B ) .
The multifaceted regulatory network that controls developmental differentiation and secondary metabolism in fungi is dependent on the velvet complex . Here we describe LlmF , a LaeA-like methyltransferase that constitutes a new interaction partner for VeA . LlmF is a negative regulator of sexual development and secondary metabolism through its control of VeA subcellular localization . These results provide strong evidence for a complex system regulating VeA subcellular compartmentalization as an important layer of control for development and secondary metabolism . Using an in silico approach we identified several loci from the A . nidulans genome annotation that have sequence homology to LaeA ( Figure 1 ) , one of which ( LlmF ) was able to interact with VeA in a yeast-two-hybrid assay , an in vitro GST pull-down assay , and an in vivo pull-down experiment ( Figure 4 ) , thus identifying LlmF as a potential LaeA mimic or competitor . Deletion and overexpression ( OE ) LlmF mutants established that LlmF exhibited properties opposite of those of LaeA , specifically that LlmF repressed both sterigmatocystin and sexual development ( Figure 3 and Figure 6 ) . Interestingly , we also observed that in strains where llmF was overexpressed , sexual development was decreased in the dark , a phenotype reminiscent of the veA1 allele . Using double mutants of ΔllmF with veA1 , ΔlaeA , and ΔveA it was apparent that LlmF control of secondary metabolism and development required LaeA and the full length VeA protein . Jiang et al . [13] also reported finding putative methyltransferases other than LaeA that were capable of interacting with VeA in F . graminearum , suggesting that LlmF may be conserved in other filamentous fungi . Compartmentalization of proteins in eukaryotic cells is vital for proper growth and development . For example , several DNA binding transcription factors have been shown to shuttle between the cytoplasm and nucleus thereby directing gene transcription through subcellular localization [31]–[36] and proper localization of metabolic enzymes to organelles such as the peroxisome or mitochondria are critical for cellular function [37]–[39] . Here we observe the consequences of mis-localization of VeA mediated by LlmF for fungal development . Previous studies showed that VeA shuttles between the cytoplasm and nucleus in response to light [18] . VeA is hypothesized to act as a scaffold protein and mediate developmental pathways in response to illumination through regulation of its subcellular location [5] , [23] . When the fungus is exposed to conditions favoring asexual development , e . g . light , VeA is located mainly in the cytoplasm . However , when there is no light , there is increased nuclear transport of the VeA-VelB heterodimer via the importin α ( KapA ) , where they interact with the nuclear LaeA to induce sexual development and secondary metabolism ( Figure 11 ) . Our data implicate LlmF as a VeA cytoplasmic retention molecule contributing to proper location of VeA at the right developmental time point . Deletion of the red light sensing phytochrome photoreceptor FphA results in increased VeA accumulation in the nucleus under light conditions , reminiscent of the ΔllmF background [20] . Blumenstein et al . [40] report that FphA is a cytoplasmic protein and functions to repress sexual development under red light . This would be consistent with the phenotypes observed with ΔllmF , however subsequent bimolecular fluorescence complementation ( BiFC ) assays suggest that FphA interacts with VeA in the nucleus [21] . It is also important to note that In vivo tandem affinity tag purification ( TAP ) of VeA resulted in co-purification of VelB , LaeA , and KapA [3] , however did not pull-down LlmF or FphA . A plausible explanation for this phenomenon is that different culture conditions were used , most notably Bayram et al . [3] used sexual developmental culture conditions in the TAP purification of VeA . We suggest that these data indicate that LlmF ( and potentially other proteins ) may form a transient interaction with VeA in the cytoplasm thereby controlling its subcellular localization , while the stable LaeA-VeA-VelB complex forms in the nucleus . Our data present evidence that cytoplasmic proteins interacting with VeA ( LlmF and possibly FphA ) control VeA localization , leading to downstream impacts on development and secondary metabolism . Here we present a model ( Figure 11 ) where VeA retention by LlmF likely involves post-translational modifications precluding nuclear localization of VeA with a possible secondary effect of occlusion of KapA or VelB from cytoplasmic VeA . Post-translational modifications are known to both inhibit and enhance nuclear uptake depending on the cargo protein . For example , phosphorylation enhances the nuclear localization of the large tumor antigen of simian-virus 40 ( SV40 ) ; conversely phosphorylation inhibits nuclear transport of Msn2p , a yeast transcriptional regulator of stress responses [31] and similarly inhibits nuclear transport of AflR [41] . Recently MpkB ( Fus3 ) has been shown to be the kinase responsible for phosphorylating VeA , however VeA localization was not altered in the ΔmpkB background . [42] . More relevant to the putative methyltransferase ability of LlmF , methylation has also been linked to nuclear transport , as methylation of arginine residues in the NLS of RNA helicase A by the PRMT1 is required for transport into the nucleus [43] . To address if the putative methyltransferase ability of LlmF contributed to VeA localization , we constructed a SAM binding domain mutant of LlmF . Using the yeast-two-hybrid assay we determined that LlmFSAM was still capable of binding to VeA , however was not functional in vivo . Although this does not preclude a role for LlmF in blocking KapA/VelB access to VeA , this result does suggest that the main role of LlmF in directing VeA localization involved a methylation activity . Thus we tested the ability of LlmF to methylate the known proteins involved in VeA nuclear import , which are VeA , VelB , and KapA . LlmF was unable to methylate any of these proteins in an in vitro methylation assay , which suggests another methylation substrate of LlmF is involved in VeA import . Understanding the dynamics of the velvet complex cellular compartmentalization is crucial towards identifying regulatory networks of the fungal cell . Since VeA protein levels are constant over all developmental stages of the fungus , the subcellular localization of VeA plays a large role in proper response to environmental cues , i . e . development and secondary metabolism . It is not surprising then , that several mechanisms could exist to ensure proper localization of VeA such as mediation by LlmF . Future studies on proteins or small molecules that alter the cellular location of VeA could provide a novel form of controlling production of secondary metabolites , which has implications for reduction of contaminating toxins in food supplies as well as increasing production of beneficial metabolites for industrial applications .
Bioinformatic analysis of the A . nidulans genome was done using a combination of the Broad Institute Aspergillus Comparative database ( http://www . broadinstitute . org/annotation/genome/aspergillus_group/ ) and the Aspergillus Genome Database [46] . SAM binding domain containing proteins were identified by retrieving all predicted proteins in the genome that contained an annotated methyltransferase domain from the Aspergillus Comparative database at the Broad Institute . The resulting 80 protein sequences were then manually culled and those that corresponded to polyketide synthases ( 15 ) or resided inside secondary metabolite gene clusters ( 9 ) were removed from the analysis . Clr4p from Schizosaccharomyces pombe , StcP from A . flavus , and 36 previously described methyltransferase from Saccharomyces cerevisiae were manually added from PubMed to the analysis . A ClustalW alignment and inferred phylogenetic tree was completed by the use of MegAlign Software ( DNASTAR ) . Bootstrapping was performed using 1000 trials to determine tree branch lengths using MegAlign . To assess the function of 8 LaeA-like methyltransferases ( AN2165 , AN8945 , AN7933 , AN5416 , AN6749 , AN5874 , AN8833 , and AN9193 ) gene disruption constructs were created to independently replace the putative ORFs with the A . fumigatus pyrG gene . Gene replacement constructs were created using fusion PCR [47]–[49] . Briefly , PCR products corresponding to approximately 1 kb upstream and downstream of the ORF were amplified from genomic DNA , subsequently gel purified , and then PCR-fused to flank either side of the A . fumigatus pyrG gene . The fusion PCR products were then used to transform RJMP1 . 49 [50] according to previously described procedures [51] with a minor modification of embedding protoplasts in molten 0 . 75% agar . Single gene replacement mutants were identified by PCR and subsequent Southern analysis ( Figure S1 and data not shown ) . Prototrophic gene replacement strains as well as double mutants were constructed by sexual recombination ( Table S1 ) . Creation of VeA and VeA1 S-tagged strains were achieved via insertion of the C terminal S-tag construct from pAO81 [48] into RJMP1 . 27 and RJMP1 . 1 . An llmF over-expression vector ( pJMP22 ) was constructed by PCR fusion of the gpdA promoter to the ORF of llmF and subsequently an EcoRI-NotI fragment was cloned into the pyroA targeting vector pJW53 [52] . A SAM binding domain mutant ( LlmFG91A , G93A ) was constructed by quick-change mutagenesis ( Stratagene ) of pJMP22 to construct pJMP105 . C-terminal and N-terminal llmF GFP fusions were constructed by insertion of GFP ( amplified from pFNO3 and pSK505 respectively ) into pJMP22 via PCR mediated insertion [53] to construct pJMP23 ( OE llmF-GFP ) and pJMP102 ( OE GFP-GA5-llmF ) . The N terminal TAP tag was PCR amplified from pME2968 [54] and used to replace the GFP fragment in pJMP102 via PCR mediated insertion , yielding pJMP106 ( OE TAP-GA5-llmF ) . Over-expression ( OE ) of llmF , GFP , llmFSAM , and TAP fusions was accomplished by transformation of pJMP22 , pJMP23 , pJMP102 , pJMP105 , and pJMP106 into RJMP1 . 59 . Strains confirmed by Southern blot ( data not shown ) were subsequently crossed to prototrophy ( Table S1 ) . Cultures for analysis of sporulation and production of secondary metabolites were set up by overlay inoculation of 1×106 spores in molten GMM top agar containing 0 . 75% agar and subsequent incubation at 37°C . Three 10 mm cores were taken from each plate and homogenized in 3 mL of sterile water . Analysis of sterigmatocystin was done from cultures grown in constant light and constant dark for 4 days . Secondary metabolites were extracted with an equal volume of ethyl acetate and the organic layer was dried down . The dried extract was resuspended in 100 µL of ethyl acetate , 10 µL was spotted on silica backed thin layer chromatography plates ( Whatman #4410-221 ) , and separated using toluene: ethyl acetate: acetic acid ( 8∶1∶1 ) as a solvent . To visualize sterigmatocystin , the TLC plates were dried and sprayed with 15% aluminum chloride in ethanol and imaged under UV light ( 254 nm ) . Sporulation was measured as previously described [24] by counting ascospores and conidia with a hemocytometer from sexual induced overlay-inoculated cultures that were grown for 5 days on GMM . To determine if LlmF could physically interact with VeA , a directed yeast-two-hybrid system was used based on the LexA DNA binding domain [55] , which has previously been used to map interaction sites of the VelB-VeA-LaeA complex [3] . Total RNA was extracted from WIM126 grown in both asexual and sexual developmental conditions , the RNA was pooled and cDNA was constructed . A PCR product was obtained using LlmF gene specific primers ( Table S3 ) and subsequently cloned into pACT2 ( Clonetech ) and confirmed by sequencing . This cDNA was subsequently moved into the ‘bait’ vector ( pTLexA ) and the ‘prey’ vector ( pGAD424 ) . The appropriate plasmids were then transformed into the Saccharomyces cerevisiae L40 host [56] according to previously described protocols [57] , and protein-protein interactions were measured using the histidine growth reporter as well as the lacZ X-gal colorimetric reporter . Heterologous expression and subsequent purification of proteins was conducted in E . coli BL21 ( λDE3 ) using a combination of GST fusion pGEX ( GE Healthcare ) and N terminal 6X histidine - C terminal S-tag fusion vector pRSF-1b ( EMD Biosciences ) . Briefly , GST fusions were constructed for LaeA , LlmF , VelB , and KapA which were purified from cell lysates using glutathione sepharose 6B ( GE healthcare ) following manufacturers recommendations . LlmF was cleaved from GST-LlmF using the Thrombin Cleavage Capture Kit ( EMD Biosciences ) . An E . coli codon-optimized version of VeA was obtained from Reinhard Fischer , which was subsequently PCR amplified and cloned into pBluescript II SK- ( pJMP70 ) . An EcoRI-XhoI fragment from pJMP70 was sub-cloned into pRSF-1b ( EMD Biosciences ) that yielded a His6-VeA-S-tag fusion protein , which was purified using Ni-NTA resin ( Qiagen ) according to manufacturer's recommendations . A C terminal GST tag from pJMP89 was inserted into the XhoI site of pJMP126 to construct pJMP134 ( His6-VeA-GST-S-tag ) , which was subsequently tandem purified with Ni-NTA resin followed by glutathione sepharose 6B ( GE healthcare ) . GST pull-down experiments were conducted essentially as previously described [45] . Briefly , 10 µg of purified GST tagged proteins ( GST-LaeA , GST-VelB , GST-LlmF ) , 25 µL of glutathione sepharose 4B ( GE healthcare ) , and 50 µL of purified His6-VeA-S-tag were co-incubated for 3 hours at 4°C in PBS buffer ( 140 mM NaCl , 2 . 7 mM KCl , 10 mM Na2HPO4 , 1 . 8 mM KH2PO4 , 1 mM DTT , pH 7 . 3 ) . The resin was subsequently washed 4 times with PBS buffer , boiled for 10 minutes in 2X NuPage LDS sample buffer ( Invitrogen ) , electrophoresed on a 9% Bis-Tris polyacrylamide gel , transferred to nitrocellulose membrane , and stained with 0 . 1% Ponceau S solution ( Sigma ) . Immunodetection of His6-VeA-S-tag was performed using a Rabbit α-S-tag antibody at 1∶2 , 000 dilution ( Immunology Consultants Laboratory , Inc ) followed by Goat anti-Rabbit-HRP 1∶15 , 000 dilution ( Pierce ) and chemiluminescence detection with Pierce West Pico Substrate ( Pierce ) . One-liter liquid shaking cultures of GMM were inoculated with 5×105 spores/mL and grown for 30°C at 230 RPM for 36 hours . Mycelia was harvested by filtration through miracloth ( EMD Biosciences ) , frozen in liquid nitrogen , and ground via cryo-compaction using a mixer mill ( Retsch MM 400 ) . Tandem affinity purification was conducted similarly as previously described [54] with a few minor modifications . Ground mycelia were extracted in buffer B250 ( 100 mM Tris-HCl , 250 mM NaCl , 10% glycerol , 1 mM EDTA , 1 mM DTT , 1 mM PMSF , 0 . 05% Tergitol-NP40 , pH 7 . 5 , and Roche Complete Protease inhibitors ) and crude lysate was obtained by centrifugation at 47 , 810 x g for 30 minutes . The clarified crude lysate was incubated with 350 µL of IgG Sepharose 6 Fast Flow ( GE Healthcare ) for 3 hours on a rocking platform at 4°C and subsequently loaded into a 10 mL chromatography column ( BioRad Poly-Prep ) . The IgG Sepharose was washed twice with 10 mL of buffer W250 ( 40 mM Tris-HCl , 250 mM NaCl , 1 mM PMSF , 1 mM DTT , 0 . 1% Tergitol-NP40 , pH 8 . 0 ) , once with 10 mL of buffer W150 ( 40 mM Tris-HCl , 150 mM NaCl , 1 mM PMSF , 1 mM DTT , 0 . 1% Tergitol-NP40 , pH 8 . 0 ) , and once with 10 mL of buffer TCB ( 40 mM Tris-HCl , 150 mM NaCl , 0 . 5 mM EDTA , 1 mM DTT , 0 . 1% Tergitol-NP40 , pH 8 . 0 ) . TEV cleavage was done by incubating the washed IgG Sepharose in 1 mL of TCB with 80 µL of rTEV ( kind gift from Ivan Rayment , UW-Madison ) overnight at 4°C on a rocking platform . The eluate was mixed with 500 µL of equilibrated calmodulin sepharose 4B ( GE Healthcare ) in 6 mL of CBB ( 40 mM Tris-HCl , 150 mM NaCl , 1 mM magnesium acetate , 1 mM imidazole , 2 mM CaCl2 , 10 mM 2-mercaptoethanol , 0 . 1% Tergitol-NP40 , pH 8 . 0 ) and incubated for 1 hour at 4°C on a rocking platform . The calmodulin sepharose was subsequently washed three times with 1 mL of CBB with 0 . 02% Tergitol-NP40 and finally eluted twice with 500 µL of CEB ( 40 mM Tris-HCl , 150 mM NaCl , 1 mM magnesium acetate , 1 mM imidazole , 20 mM EGTA , 10 mM 2-mercaptoethanol , pH 8 . 0 ) . The eluate was TCA precipitated , resuspended in NuPAGE LDS sample buffer ( Invitrogen ) , electrophoresed in a 10% Bis-Tris polyacrylamide gel , and transferred to Immobilon-P PVDF membrane ( Millipore ) . Immunodetection of VeA and VeA1-S-tag was accomplished using Rabbit-α-S-tag at a 1∶2 , 000 dilution followed by Goat-α-Rabbit-Cy5 ( GE Healthcare ECL Plex ) at a 1∶2 , 000 dilution and imaged using a Typhoon FLA9000 fluorescent imager . The blot was stripped in 62 . 5 mM Tris-HCl , pH 6 . 5 , 2% SDS , 100 mM 2-mercaptoethanol at 50°C for 30 minutes and washed twice in TBS ( 50 mM Tris-HCl , 150 mM NaCl , pH 7 . 4 ) . The blot was then re-probed for detection of TAP-LlmF with Rabbit-α-calmodulin ( Millipore ) at a 1∶1 , 000 dilution and detected with the ECL Plex system as described above . The ability of recombinant LaeA and LlmF to bind the methyl group donor S-adenosyl methionine ( SAM ) was determined through an in vitro ultraviolet-light ( UV ) crosslinking assay as previously described [58] . Briefly , 5 µg of recombinantly purified GST , GST-LaeA , GST-LlmF , and LlmF were incubated with 6 µL of 1 . 0 µCi/mL of 3H-SAM ( Perkin Elmer ) at room temperature for 20 minutes followed by irradiation with UV light on ice for an additional 30 minutes . To demonstrate active site binding , the competitive inhibitor S-adenosyl-homocysteine ( SAH ) was used at 1 µM . The reactions were stopped by addition of SDS-PAGE sample buffer and electrophoresed on a 10% Tricine-SDS-PAGE gel [59] . Proteins were transferred to a nitrocellulose membrane ( Protran ) and bound 3H-SAM was measured by 48-hour exposure to a tritium phosphor storage screen ( GE Healthcare ) following manufacturers recommendations . Localization of proteins was visualized with a C terminal GFP fusion of VeA [18] and N terminal GFP fusion of LlmF driven by the gpdA promoter . Cells were prepared as previously described with minor modifications [60] . Briefly , approximately 5×104 conidia were inoculated in liquid GMM medium over sterile cover slips in petri dishes at 30°C overnight . Cover slips containing adherent germlings were transferred to glass slides with 1 µL of Hoechst 33258 ( 1 mg/mL ) and imaged with a Zeiss AxioImager A10 equipped with a Zeiss EC Plan-NEOFLUAR 40X/1 . 3 Oil DIC objective , a series 120 X-Cite light source ( EXFO ) , Zeiss filter set 10 for GFP , Zeiss filter set 00 for mRFP , and Zeiss filter set 49 for Hoechst . Microscope settings were identical for all samples and GFP quantification was achieved using the Zeiss AxioVision 4 . 7 software of 50 nuclei and 50 cytoplasmic areas for each strain . Total RNA was extracted using TriZol ( Invitrogen ) using manufacturers recommendations . Detection of llm transcripts was achieved by analyzing mRNA from wild-type A . nidulans ( RDIT9 . 32 ) grown under several different developmental conditions ( Figure 2 ) . Mycelia from sexual developmental induction cultures was scraped from the surface of solid media plate with a glass slide , lyophilized overnight , and subsequently total RNA was extracted using TriZol ( Figure 6D ) . Vegetative growth was conducted by inoculation of 1×106 spores/mL in 50 mL of liquid GMM at 37°C and 250 rpm . Asexual and sexual development was induced by transfer of mycelia grown for 24 hours in liquid shake to solid GMM plates and further incubated in either constant light ( asexual induction ) or constant dark ( sexual development ) at 37°C . Expression of velvet complex members was assayed from mycelia grown under asexual developmental conditions for 24 hours after transfer to solid media and sexual developmental conditions for 48 hours after transfer to solid media ( Figure 7 ) . 32P-labeled probes were made using standard techniques [45] and primers are listed in Table S3 . Methylation assays were conducted essentially as previously described [30] , with the following minor modifications . Five micrograms of purified LlmF was incubated with 5 µL of 1 . 0 µCi/mL of 3H-SAM ( Perkin Elmer ) and 5 µg of putative substrate protein in 1X methyltransferase buffer ( 50 mM HEPES , 100 mM NaCl , 2 mM DTT , pH 7 . 5 ) for 1 hour at 30°C . The reactions were stopped by addition of 4X sample buffer and the entire reactions were electrophoresed via Bis-Tris SDS-PAGE . Gels were subsequently stained with Coomassie Brilliant Blue R-250 , impregnated with En3Hance fluorography enhancing solution ( Perkin Elmer ) , dried , and exposed to a tritium phosphor storage screen ( GE Healthcare ) for 2 weeks . | In recent years there has been increased interest in bioactive small molecules produced by filamentous fungi . Members of the genus Aspergillus are prolific producers of natural products such as penicillin , the cholesterol lowering drug lovastatin , in addition to several toxins , the most famous being aflatoxin . The genetic regulation of fungal natural products is coupled with developmental differentiation through a conserved protein complex termed the velvet complex . The founding member of the complex , velvet ( VeA ) , is a light-regulated protein that shuttles between the cytoplasm and nucleus in response to illumination . Once in the nucleus , VeA interacts with the putative methyltransferase LaeA to positively regulate production of secondary metabolites and with VelB to induce sexual development . We have identified a new interaction partner of VeA that has sequence homology to LaeA . The putative LaeA-like methyltransferase LlmF controls the subcellular localization of VeA in response to light , thereby regulating the downstream outputs of secondary metabolism and development . While the mechanism of the velvet complex remains an enigma , our data suggest that manipulation of protein subcellular localization is an approach that can be used to control production of secondary metabolites . | [
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] | 2013 | Secondary Metabolism and Development Is Mediated by LlmF Control of VeA Subcellular Localization in Aspergillus nidulans |
The cell-cycle field has identified the core regulators that drive the cell cycle , but we do not have a clear map of the dynamics of these regulators during cell-cycle progression versus cell-cycle exit . Here we use single-cell time-lapse microscopy of Cyclin-Dependent Kinase 2 ( CDK2 ) activity followed by endpoint immunofluorescence and computational cell synchronization to determine the temporal dynamics of key cell-cycle proteins in asynchronously cycling human cells . We identify several unexpected patterns for core cell-cycle proteins in actively proliferating ( CDK2-increasing ) versus spontaneously quiescent ( CDK2-low ) cells , including Cyclin D1 , the levels of which we find to be higher in spontaneously quiescent versus proliferating cells . We also identify proteins with concentrations that steadily increase or decrease the longer cells are in quiescence , suggesting the existence of a continuum of quiescence depths . Our single-cell measurements thus provide a rich resource for the field by characterizing protein dynamics during proliferation versus quiescence .
Cellular proliferation is driven by the mitotic cell cycle , a highly regulated process consisting of DNA synthesis ( S phase ) and mitosis ( M phase ) , separated by gap phases ( G1 and G2 ) . Decades of cell-cycle research have led to in-depth understanding of the biochemical processes involved in cell-cycle progression , but the temporal dynamics of these processes , and how they differ in non-cycling cells , are less well characterized . Simplified diagrams of cell-cycle dynamics are sometimes depicted in textbooks [1 , 2 , 3] , but these diagrams are not always in agreement , typically only Cyclin dynamics are represented , and information on protein behavior during quiescence is absent . Thus , although the cell cycle is one of the most dynamic processes in biology , we lack quantitative information about the chronology of key events during cell-cycle progression versus cell-cycle exit . An abbreviated explanation of the events surrounding cell-cycle entry and cell-cycle progression follows , with Fig 1A serving as a simplified network diagram . In quiescent or resting cells , Cyclin-Dependent Kinase ( CDK ) activities are low or off , and the master regulator of cell-cycle entry , the retinoblastoma protein ( Rb ) , is in a non-phosphorylated state in which it binds and inhibits the E2F transcription factor . Cell-cycle entry can be triggered when resting cells receive extracellular mitogenic signals . Mitogenic signaling leads to Erk-dependent activation of transcription factors , such as c-Myc [4] and Ets-1 [5] , which in turn up-regulate Cyclin D . Cyclin D binds its cognate Cyclin-Dependent Kinases , CDK4 and CDK6 , which initiate hypo-phosphorylation of Rb . In the textbook model , this initial hypo-phosphorylation of Rb liberates the E2F transcription factor , a key driver of genes involved in the G1/S transition , including Cyclin E [6 , 7] . Transcriptional up-regulation of Cyclin E drives Cyclin-Dependent Kinase 2 ( CDK2 ) /Cyclin E activity , leading to “hyper” phosphorylation of all 14 sites on Rb , and liberating additional E2F in a positive feedback loop . However , this model was recently called into question by the observation that E2F target genes were only up-regulated at the time of Rb hyper-phosphorylation and not with the initial hypo-phosphorylation [8] . Nevertheless , it is generally accepted that Rb hyper-phosphorylation marks passage through the Restriction Point ( R-point ) [9] , defined as the time at which cells no longer require mitogens to complete the rest of the cell cycle [10] . Concordantly , activation of CDK2 was shown via single-cell time-lapse microscopy to mark cells that had passed the R-point [11] . At the beginning of S phase , Cyclin A protein levels begin to rise , and Cyclin A/CDK2 becomes the dominant source of CDK activity driving cells through S phase . DNA replication is initiated when origins of replication , previously prepared for replication by licensing factors such as Cdt1 , fire due to phosphorylation by Dbf4-dependent kinase and CDK activities [12] . To prevent relicensing and re-replication of DNA , Cdt1 is degraded at the start of S phase by the E3 ubiquitin ligases SCFSkp2 and CRL4Cdt2 [13] . Any residual Cdt1 is bound and inhibited by Geminin , the levels of which rise during S and G2 [14 , 15] . Toward the end of S phase , Cyclin B levels rise rapidly , giving rise to Cyclin B/CDK1 activity that propels cells into mitosis [16] . The anaphase-promoting complex/cyclosome ( APC/C ) triggers exit from mitosis and is responsible for resetting the cell cycle at the end of mitosis via the degradation of Cyclin A , Cyclin B , Geminin , and many other substrates [17] . Cell-cycle progression is also controlled by protein inhibitors of CDKs , including p21 and p27 , the ubiquitination and degradation of which promote S phase entry [18 , 19 , 20 , 21 , 22] . Cells can also temporarily exit the cell cycle by transitioning to a resting state , termed quiescence or G0 . Relative to our knowledge of G1 , S , G2 , and M , the G0 phase remains poorly understood , both in terms of when and how cells transition into and out of G0 and in terms of a molecular definition of G0 . Although there are multiple forms of quiescence , a universal feature of quiescence is lack of progression through the cell cycle [23] . Previous efforts to characterize quiescence in human cells have used serum starvation , contact inhibition , or loss of adhesion to induce quiescence , identifying a set of genes expressed across all three modes of quiescence induction , as well as sets of genes specific to the initiating quiescence signal [24 , 25] . Indeed , synchronization procedures have been shown to induce stress responses specific to the synchronization procedure used [26 , 27 , 28] . Characterization of quiescent cells from unperturbed populations has been hindered by the lack of a molecular marker to identify living quiescent cells . The recent development of a sensor for CDK2 activity enables the identification of live cells that are in quiescence [11] . This sensor consists of an mVenus-tagged section of DNA Helicase B ( DHB-mVenus ) containing CDK2 phosphorylation sites close to a nuclear localization sequence ( NLS ) and a nuclear export sequence ( NES ) ( S1A Fig ) . Phosphorylation of the sensor by CDK2 masks the basic residues of the NLS and unmasks the NES , causing translocation of the sensor to the cytoplasm in a manner that is correlated with CDK2 activity . The cytoplasmic:nuclear ratio of this sensor thus serves as a readout for CDK2 activity . Cells early in the cell cycle show nuclear localization of the sensor and low CDK2 activity , whereas cells toward the end of the cell cycle show cytoplasmic localization of the sensor and high CDK2 activity . S phase begins when the cytoplasmic:nuclear ratio of the sensor is approximately 1 . Addition of a CDK2 inhibitor at any time during the cell cycle causes an immediate drop in CDK2 activity , visualized by rapid nuclear translocation of the sensor [11] . When single-cell traces of CDK2 activity from asynchronously cycling cells are aligned to the time of mitosis , a bifurcation in CDK2 activity becomes apparent , which corresponds to the proliferation-quiescence cell fate decision [11] . One subset of cells completes mitosis with residual CDK2 activity ( cytoplasmic:nuclear ratio of the sensor ≥ 0 . 5 ) , which then steadily increases over the course of the cell cycle ( CDK2inc cells ) . Another subset of cells completes mitosis with low or no CDK2 activity and enters quiescence ( CDK2low cells; cytoplasmic:nuclear ratio of the sensor < 0 . 5 ) . This quiescence is transient in nature . Indeed , CDK2low cells experience a second cell fate decision in which they can continue to remain quiescent or emerge from quiescence and re-enter the cell cycle . Cells that emerge from quiescence can be identified by a renewed increase in CDK2 activity ( CDK2emerge cells ) . Thus , upon completion of mitosis , cells can become proliferating CDK2inc cells or quiescent CDK2low cells . CDK2low cells can remain CDK2low for variable amounts of time or re-enter the cell cycle by becoming CDK2emerge cells . Entry into the CDK2low state occurs in all cell lines examined thus far , even under optimal culture conditions ( full-growth media at subconfluent densities ) . While it is known that the bifurcation in CDK2 activity is regulated by p21 [11] , our understanding of why cells enter the CDK2low state is incomplete . We recently showed that 50% of the transits through the CDK2low state can be explained by replication errors carried over from the previous ( mother ) cell cycle [29] . The trigger for entry into the CDK2low state in the other 50% of CDK2low cells remains unknown , but it is possible that these cells are also experiencing an unidentified stress . Because cells enter the CDK2low state without any exogenous trigger , we refer to CDK2low cells that exist under optimal culture conditions as “spontaneously” quiescent , to contrast with other well-established types of quiescence in which cells are “forced” into quiescence ( e . g . , serum starvation or contact inhibition ) . Despite substantial knowledge about the mechanism of cell-cycle transitions , we do not have a clear picture of overall cell-cycle dynamics detailing the rise and fall of protein levels and appearance and disappearance of protein post-translational modifications . In large part , this is because biochemical approaches in synchronized cells typically monitor only a few protein species at low time resolution . Proteomic surveys of the cell cycle have provided a more global view of cell-cycle events in mammalian cells but also suffer from low temporal resolution [26 , 30] . Furthermore , any method that relies on cell synchronization to enrich for cells at a specific cell-cycle stage is likely to exert stress on cells , which pollutes actual cell-cycle regulation with regulatory mechanisms operative as cells emerge from an arrested state . In addition , bulk analysis approaches blur heterogeneity in cell-cycle behavior , potentially resulting in incorrect interpretations of biological data . In contrast , time-lapse microscopy can offer single-cell measurements at millisecond temporal resolution in asynchronous cells but is limited by the difficulty of designing live-cell fluorescent readouts of multiple cell-cycle regulators and by the challenges of automated image processing and cell tracking . Most recently , immunofluorescence ( IF ) staining of fixed-cell snapshots has been used to infer cell-cycle kinetics of a handful of proteins [31 , 32 , 33] , but without distinguishing proliferating from quiescent cells . Given that spontaneously quiescent cells appear in varying proportions in all cycling populations examined thus far , failure to distinguish proliferating cells from spontaneously quiescent cells leads to increased apparent cell-to-cell variability and decreased accuracy in quantifying protein behavior . Here we combine the best of live-cell microscopy and antibody-based measurement to map key molecular events during cell-cycle progression versus spontaneous cell-cycle exit . By categorizing cells by their CDK2 activity trajectory ( CDK2inc , CDK2low , CDK2emerge ) and computationally aligning their IF signal as a function of time-since-anaphase , we reduce cell-to-cell variability in protein measurements and eliminate potential artifacts from synchronization procedures . In this way , we identify several unexpected differences in protein levels and modification states between cells that are progressing through the cell cycle and have increasing CDK2 activity ( CDK2inc cells ) and cells that are quiescent ( CDK2low ) . One noteworthy example is Cyclin D , which is well known ( and confirmed here in MCF10A cells ) to be expressed at low levels in cells forced into quiescence by serum starvation or contact inhibition , but which we show is more abundant in spontaneously quiescent CDK2low cells compared with proliferating CDK2inc cells . We also identified 4 proteins with concentrations that steadily increase or decrease the longer the cells are in spontaneous quiescence . This result suggests that there exists a continuum of quiescence depths . Together , our single-cell data provide a chronology of key events during the active cell cycle and reveal key molecular differences between forced quiescence , spontaneous quiescence , and proliferation .
We used 2 complementary single-cell methods to chronicle the dynamics of key cell-cycle regulators . The first method uses 4-color IF snapshot images to categorize individual cells as G1 , S , G2 , M , or G0/quiescent . This approach has the advantage of being readily applicable to any cell line without the need to insert fluorescent sensors or perform time-lapse microscopy but does not explicitly carry time-dependent information . By co-staining cells with Hoechst ( to measure DNA content ) and EdU ( a marker for DNA synthesis ) [34] , we could subdivide the cell cycle into 5 categories ( Fig 1B–1D and S1B Fig ) : cells with 2N DNA content and no EdU incorporation were classified as G0 or G1; cells with near 2N DNA content and intermediate EdU signal were classified as early S phase; cells with high EdU signal were classified as S phase; cells with near 4N DNA content and intermediate EdU signal were classified as late S phase; and cells with 4N DNA content and no EdU incorporation were classified as G2 or M ( Fig 1B ) . To further distinguish cells in G0 from cells in G1 , we co-stained cells with an antibody against phospho-Rb at either Serine 780 or Serine 807/811 . These sites are phosphorylated by CDK2 and thus can serve as a fixed-cell readout of CDK2 activity . The phospho-Rb signal is bimodally distributed , representing hypo- and hyper-phosphorylated Rb ( Fig 1C ) . Newly born cells with hypo-phosphorylated Rb were previously shown to be in the CDK2low state , whereas newly born cells with hyper-phosphorylated Rb are in the CDK2inc state [11] . Therefore , EdU-negative cells with 2N DNA content and hypo-phosphorylated Rb are classified here as G0/quiescent , and EdU-negative cells with 2N DNA content and hyper-phosphorylated Rb are classified here as G1 ( Fig 1C ) . To distinguish cells in G2 from cells in M , we used an antibody against phospho-Histone H3 ( pHH3 ) , a well-established marker for mitosis . EdU-negative cells with 4N DNA content that were pHH3-negative were classified as G2 , and cells that were pHH3-positive were classified as mitotic ( Fig 1D ) . We used 3 fluorescent channels to stain cells with Hoechst , EdU , and either phospho-Rb or pHH3 ( S1C Fig ) , and used the fourth channel to measure 1 of 14 proteins of interest in MCF10A human mammary epithelial cells . We also validated our results in Hs68 human foreskin fibroblasts . We avoided use of cancer cell lines , which often have mutations in the core cell-cycle regulatory network . The second method involves time-lapse microscopy over 24 hours of MCF10A cells expressing Histone 2B ( H2B ) fused to mTurquoise and the CDK2 sensor fused to mVenus . Immediately after the last frame was taken , cells were fixed with para-formaldehyde , processed for IF , and reimaged . Custom MATLAB-based cell-tracking scripts were used to extract single-cell traces of CDK2 activity , with a custom “jitter correction” to re-register the images before and after IF ( see Materials and methods ) . In this way , we can match each cell’s IF staining to its history . The H2B signal is used to automatically identify the frame of anaphase for each cell , which enables automated alignment of all CDK2 activity traces ( and consequently each cell’s IF signal ) to each cell’s final anaphase of the movie . The resulting plot demonstrates the bifurcation in CDK2 activity that is evident as cells complete mitosis and assume either a CDK2inc , CDK2low , or CDK2emerge state ( Fig 1E ) [11] . Another subset of cells has no mitoses during the course of the 24-hour movie , of which a further subset has low CDK2 activity for the entire 24-hour imaging period . Although these cells are not cycling , they are also not senescent ( S2A–S2C Fig ) and thus appear to be in a prolonged quiescence ( Fig 1F ) . Indeed , we confirmed that these cells can emerge from this prolonged quiescence ( S2D Fig ) . In our unperturbed MCF10A cells , 95 . 6% ± 5 . 4% of the total population divided at least once during the 24-hour imaging . Of the total population , 79 . 0% ± 6 . 2% entered the CDK2inc state after mitosis , 8 . 8% ± 2 . 6% remained CDK2low after mitosis , and 7 . 8% ± 1 . 7% entered the CDK2low state after mitosis but built up their CDK2 activity before the end of the imaging period ( CDK2emerge ) ( Fig 1E ) . Among the 4 . 4% that did not divide during the course of the movie , 52 . 3% ± 17 . 7% stayed in a prolonged quiescence ( representing 2 . 3% ± 0 . 8% of the total population , Fig 1F ) and 47 . 7% ± 17 . 7% ( or 2 . 1% ± 0 . 8% of the total population ) were observed to build up CDK2 activity before the end of the imaging period ( S1 Movie and S2D Fig ) . For CDK2emerge cells , automated identification of the time point when cells begin building up CDK2 activity after being in a CDK2low state allows automated alignment of CDK2emerge traces to this event ( Fig 1G ) , which we have previously argued represents the R-point [11 , 35] . Alignment of the CDK2 activity traces in these various ways allows for the staging of IF-based protein levels or modification states as a function of time-since-anaphase , or time-since-R-point . Cells treated with EdU for 15 minutes at the end of a 24-hour time-lapse sequence illustrate the power of this approach—CDK2inc cells display the classic “rainbow” pattern of EdU as a function of time-since-anaphase , allowing us to identify and label G1 , S , and G2 phases of the cell cycle in our time-lapse + IF experiments ( Fig 1H , blue ) . CDK2low cells ( Fig 1H , red ) and prolonged quiescent cells ( Fig 1H , purple ) display no EdU signal . A moving average through the CDK2inc and CDK2low subpopulations further illustrates the effect ( Fig 1I ) . CDK2emerge cells aligned to the time at which CDK2 activity begins to increase show a pattern similar to the CDK2inc cells but with less clarity due to the difficulty of automating the identification of the first frame of CDK2 activity rise ( relative to the easy automatic identification of the first frame of anaphase; Fig 1J ) . This plot shows that CDK2emerge cells begin S phase at a similar time after the initial CDK2 activity buildup as CDK2inc cells . These 2 methods were used to chronicle the dynamics of 14 proteins during cell-cycle progression and spontaneous quiescence . The proteins were chosen because of the availability of selective antibodies , their role as core cell-cycle regulators ( Cyclin A2 , Cyclin B1 , Cyclin E , Cyclin D1 , p21 , p27 , Cdt1 , Geminin , total Rb , and phospho-Rb ) , or as important signaling inputs to the cell cycle ( cMyc , Fra1 , phospho-cJun , and p53 ) . Nine proteins were highly dynamic over the course of the cell cycle ( Cyclin A , Cyclin B , Cyclin E , Cyclin D , p21 , Cdt1 , Geminin , cMyc , and phospho-Rb; Figs 2–5 and S3 Fig ) , whereas others tested were relatively invariant over the cell cycle in the cell types examined here ( p27 , total Rb , p53 , Fra1 , and phospho-cJun; S4 and S5 Figs ) . Using multi-color IF in MCF10A cells , we began by inferring the dynamics of various cell-cycle proteins using ( 1 ) a density scatter plot of signal intensity versus DNA content ( Fig 2 , Column 1 ) ; ( 2 ) a contour plot of signal intensity versus DNA content , in which cells are grouped into 7 cell-cycle phases , as described in Fig 1B–1D and S1B Fig ( Fig 2 , Column 2 ) ; and ( 3 ) a histogram of signal intensity in G0/quiescent cells ( 2N , EdU-negative , hypo-phosphorylated Rb ) versus G1 cells ( 2N , EdU-negative , hyper-phosphorylated Rb ) , as defined in Fig 1C ( Fig 2 , Column 3 ) . We also repeated these experiments in a second cell type , non-immortalized Hs68 human foreskin fibroblasts ( S3 and S4 Figs ) . Cyclin A2 and Cyclin B1 , two of the best-understood cell-cycle proteins , behaved in textbook fashion and serve as a proof-of-principle . In cycling cells , Cyclin A2 rose linearly during S and G2 , consistent with previous reports ( Fig 2A , scatter and contour plots; and Fig 3A ) [31 , 32 , 33 , 36 , 37] . Cyclin B1 levels did not begin to rise until late S but then rose supra-linearly , as previously reported ( Fig 2B , scatter and contour plots; and Fig 3B ) [16 , 31 , 32] . Cyclins A2 and B1 were both degraded in mitosis [38 , 39] , and both were undetectable in G0 and G1 cells ( Fig 2A and 2B , histograms; and Fig 3A and 3B ) . When Cyclin E levels were plotted against DNA content , we detected a subtle “N”-shaped pattern in which Cyclin E rose in G1 and fell in S phase , as expected ( Fig 2C , scatter plot; [31 , 36 , 40 , 41] ) . The rise in G1 , and fall in early S phase , of Cyclin E is also detected in the time-lapse + IF data for CDK2inc cells ( Fig 3C ) . In contrast with Cyclins A2 and B1 , which remained “off” in CDK2low cells , Cyclin E levels rose steadily in CDK2low cells ( Fig 3C ) . This is surprising because Cyclin E is overexpressed in several cancers and Cyclin E/CDK2 activity is a major driver of cell-cycle progression [42] . Therefore , we expected Cyclin E levels to be lower in spontaneously quiescent cells compared with proliferating cells . We note , however , that these high levels of Cyclin E in G0/quiescent cells are not accompanied by high CDK2 activity and thus are not able to stimulate cell-cycle progression; by definition , we identify these quiescent cells because of their lack of CDK2 activity ( CDK2low ) . This lack of CDK2 activity despite high levels of Cyclin E is likely due to the accompanying high levels of p21 in these cells ( see below ) . Thus , a likely explanation for the high levels of Cyclin E in G0/quiescent cells may be that Cyclin E in these cells has not been subjected to S phase–mediated degradation , which depends on CDK2 activity [40 , 41] . We also observed that the Cyclin E antibody utilized here , the widely used clone HE12 , detects a strong nonspecific signal in MCF10A cells , in addition to detecting Cyclin E ( S6A and S6B Fig ) . Thus the difference in Cyclin E signal between CDK2low and CDK2inc cells may be partly obscured by the nonspecific signal . The patterns displayed by Cyclin D1 were also unexpected . MCF10A cells express Cyclin D1 , D2 , and D3 , with Cyclin D1 at the highest level of the three [43] . Thus Cyclin D1 is the prevalent D-type cyclin in our cells , and the antibody used in this study is selective for Cyclin D1 ( S6A and S6B Fig ) . When Cyclin D1 levels were plotted against DNA content , we detected a “U”-shaped pattern in which Cyclin D1 is high in cells with 2N DNA content , low in S phase , and elevated again in cells with 4N DNA content ( Fig 2D , scatter and contour plots ) . This pattern has been reported previously [44 , 45] but is not widely appreciated . Upon closer inspection , the EdU-negative cells with 2N DNA content reveal highly heterogeneous expression of Cyclin D1—cells with hypo-phosphorylated Rb ( G0 cells ) have much higher levels of Cyclin D1 than cells with hyper-phosphorylated Rb ( G1 cells ) ( Fig 2D , histogram ) . Like Cyclin E , this is surprising because Cyclin D is considered a driver of the cell cycle and is overexpressed in several cancers [46]; therefore , its levels are expected to be higher in proliferating cells than in quiescent cells . When we examined our time-lapse + IF data , we observed the same phenomenon—cells born into the quiescent CDK2low state had high Cyclin D1 levels , whereas CDK2inc cells that were actively progressing through the cell cycle again displayed a “U”-shaped pattern , with Cyclin D1 levels being moderate in G1 , low in S phase , and moderate again in G2 ( Fig 3D ) . In addition , prolonged quiescent cells also have high Cyclin D1 levels ( Fig 3D , purple ) . By way of explanation , we considered the possibility that Cyclin D1 levels appear higher in G0 cells simply because Cyclin D1 in these cells has not been subjected to S phase-mediated degradation [47 , 48] . However , the moving average of Cyclin D1 levels indicated that CDK2low cells have higher levels of Cyclin D1 than CDK2inc cells , even in cells 2 hours after birth , before S phase-mediated degradation could play a role . We also note that CDK2low cells have more Cyclin D1 than CDK2inc cells ever have , at least on average . However , high levels of Cyclin D do not necessarily correspond to high CDK4/6 activity [49 , 50] , and there is as yet no single-cell assay to measure CDK4/6 activity in these cells . An alternative explanation for the high Cyclin D1 levels in CDK2low cells is that Cyclin D1 protein levels are stabilized by high levels of p21 in these cells [51 , 52 , 53] . Indeed , p21 displays the same “U”-shaped pattern as Cyclin D1 does when plotted against DNA content ( Fig 2E , scatter and contour plots ) . As with Cyclin D1 , cells with hypo-phosphorylated Rb ( G0/quiescent cells ) have high levels of p21 , whereas EdU-negative , 2N DNA content with hyper-phosphorylated Rb ( G1/proliferating cells ) have very low levels of p21 ( Fig 2E , histogram ) . Moreover , time-lapse + IF data revealed that p21 levels are high in newly born G0/CDK2low cells and very low in newly born G1/CDK2inc cells , as reported previously ( Fig 3E ) [11] . CDK2emerge cells show initially high levels of p21 that then decay around the time that CDK2 activity turns back on ( Fig 3E , green ) , consistent with the notion that a decay in p21 enables a rise in CDK2 activity . CDK2inc cells maintain very low levels of p21 throughout all of G1 and S phase ( Fig 2E , contour plot; and Fig 3E , blue ) . While these data are consistent with our previous studies [11 , 29] , these results differ from the common notion that p21 levels are generally high in G1 cells [54] . A likely explanation for this discrepancy is that many previous studies used various treatments ( e . g . , nocodazole or serum starvation ) for cell synchronization , which exert stress on cells and can increase p21 levels [55 , 56] . Furthermore , immunoblotting does not allow fine-grained analysis of p21 heterogeneity or temporal behavior . More recent single-cell experiments tracking exogenous YFP-p21 in U2OS osteosarcoma cells detected newly born cells with and without YFP-p21 [57] . However , without a live-cell marker to distinguish G0 from G1 , it is not possible to know if the newly born cells with elevated p21 are actually passing through a G0/CDK2low state rather than going straight to G1 . Similarly , the cells born without detectable p21 could represent a G1/CDK2inc subpopulation . The dynamics of Cdt1 are expected to have some similarities to p21 because both proteins are substrates of the E3 ubiquitin ligase CRL4Cdt2 [13] , a feature reflected in our IF data ( Fig 2F , scatter and contour plots ) . However , in direct contrast to p21 , Cdt1 levels are high in G1 cells and lower in G0/quiescent cells ( Fig 2F , histogram ) . Time-lapse + IF data show a similar trend , revealing that any residual Cdt1 present in CDK2low cells is quickly degraded to the basal level seen in S phase cells ( Fig 3F ) . The levels of Geminin , an inhibitor of Cdt1 , are out of phase with Cdt1 , as expected [13 , 58 , 59] . Geminin levels are undetectable in quiescent CDK2low cells and begin to rise in early S phase , consistent with Geminin’s role as a substrate of the APC/C ( Figs 2G and 3G ) [35 , 58] . However , unlike Cyclin A2 , which rises steadily and linearly , Geminin levels plateau by mid-to-late S phase , a feature seen in both IF and time-lapse + IF data , suggesting an additional layer of transcriptional regulation . We also examined the cell-cycle dynamics of c-Myc , a key protein that links MAPK signaling to cell-cycle entry [60] . More recently , c-Myc has been shown to act as a “transcription amplifier” as opposed to a classic transcription factor [61 , 62] . Here we show that c-Myc is strongly cell-cycle regulated . Immunofluorescence reveals that c-Myc levels are higher in G1 cells than in G0/quiescent cells ( Fig 2H , histogram ) , consistent with a pro-proliferation role for c-Myc . CDK2low cells maintain low c-Myc levels as long as they remain in the CDK2low state but then up-regulate c-Myc upon emerging from the CDK2low state ( Fig 3H ) . c-Myc levels rise steadily in S and G2 phases ( Fig 2H , scatter and contour plots; and Fig 3H ) . Phospho-Rb is bimodally distributed among EdU-negative cells with 2N DNA content ( Fig 1C ) [11] . The switch from hypo- to hyper-phosphorylated Rb marks passage through the R-point [9 , 63 , 64] , and while this event is often cited as occurring in mid- to late G1 [9 , 63] , we have shown previously that MCF10A cells are born into a state of either hypo- or hyper-phosphorylated Rb immediately upon completion of mitosis [11] . Here we extend this result by confirming that the same is true using an antibody against Rb phosphorylation at another site , Serine 780 ( Fig 3I ) —cells born into the quiescent CDK2low state have hypo-phosphorylated Rb , whereas cells born into the cell cycle-committed CDK2inc state have hyper-phosphorylated Rb . This phospho-Rb-S780 signal continues to rise as CDK2inc cells progress through the cell cycle . Examination of the CDK2emerge cells provides additional information by revealing that cells present with hyper-phosphorylated Rb as soon as the rise in CDK2 activity can be detected , indicating that hyper-phosphorylation of Rb occurs prior to or concurrently with activation of CDK2 ( Fig 3I , green ) . Given the surprising behavior of several proteins in spontaneous quiescence ( e . g . , rising Cyclin D1 , Cyclin E , and p21 levels ) , we compared our results in spontaneously quiescent cells with quiescence induced by well-established methods , namely serum starvation ( Fig 4A and 4B ) and contact inhibition ( S6C Fig ) . By both quantitative western blotting and IF , we were able to reproduce the canonical protein dynamics upon serum starvation or contact inhibition in which the levels of Cyclin D1 , Cyclin E , p21 , and all other proteins examined , fell as a function of time in quiescence . We also validated the selectivity of the antibodies used for IF via siRNA knockdown ( S6A and S6B Fig ) and provide sample images for each IF stain ( S7 Fig ) . We next sought to further validate the unexpected dynamics of Cyclin D1 using an antibody-independent method . We used CRISPR-mediated genome editing of MCF10A cells to tag Cyclin D1 at its endogenous locus with mCitrine , a yellow fluorescent protein , and subsequently transduced the cells with H2B-mTurquoise and mCherry-tagged CDK2 sensor . Western blotting and PCR revealed that both alleles of Cyclin D1 were tagged with mCitrine ( S8A and S8B Fig ) and IF revealed a linear correlation at the single-cell level between the mCitrine-Cyclin D1 signal and an antibody stain against Cyclin D1 ( S8C Fig ) . In agreement with our time-lapse + IF results for Cyclin D1 , single-cell tracking of the mCitrine-Cyclin D1 cell line showed that CDK2low cells have elevated Cyclin D1 levels compared with CDK2inc cells ( Fig 4C red traces , and Fig 4D bottom panel ) , and that the levels of Cyclin D1 for CDK2inc cells are moderate in G1 , low in S phase , and moderate again in G2 ( Fig 4C blue traces , and Fig 4D top panel ) . These results explain why Cyclin D1 expression was recently reported to be a poor predictor of the time spent between mitosis and S phase [45] . Given that c-Myc levels are low and Rb is hypo-phosphorylated ( and thus that E2F transcription is inhibited ) in the spontaneously quiescent CDK2low cells , what factors could be driving the high levels of Cyclin D1 ? Since these 2 major cell-cycle transcription factors are likely off in CDK2low cells , we hypothesized that the high Cyclin D1 levels in these cells could be due to a lack of degradation . Indeed , Cyclin D1 levels are strongly regulated not only by transcription but also by protein degradation via cullin-RING ligases ( SCF with various F-box proteins ) [65] . Because the majority of cullin-RING ligases require covalent modification by NEDD8 for holoenzyme ubiquitin ligase activity , their activity can be inhibited by blocking their neddylation with the small molecule MLN4924 [66] . We therefore filmed mCitrine-Cyclin D1 cells before and after an acute treatment with 1 . 4 μM of MLN4924 and selected for analysis only those cells that received drug 1–2 hours after mitosis ( during G0/G1 ) . Consistent with our hypothesis , inhibition of cullin-RING ligases caused an increase in Cyclin D1 in CDK2inc cells to a level that was comparable with that in CDK2low cells . Thus , lack of Cyclin D1 degradation in CDK2low cells is a major contributor to the high levels of Cyclin D1 seen in these cells . Cyclin D1 is well known for its short half-life . These results suggest that the stability of Cyclin D1 varies with cell-cycle phase—the half-life of Cyclin D1 is short in CDK2inc cells but much longer in CDK2low cells . Together , these validation experiments lend confidence in our overall approach and in the unexpected findings in this work . To compare the relative protein dynamics in proliferating versus quiescence cells , we normalized and overlaid the moving average data from Fig 3 for CDK2inc and CDK2low cells ( Fig 5A; note that normalizing the signals masks differences in dynamic range among proteins ) . Proteins were grouped into 2 plots according to their behavior in quiescent CDK2low cells—Group 1 contains signals that are “off” in quiescent cells ( Fig 5A , top ) , and Group 2 contains signals that change dynamically over time in quiescent cells ( Fig 5A , bottom ) . The identification of 4 proteins in Group 2 that either steadily increase ( Cyclin D1 , Cyclin E , p21 ) or steadily decrease ( Cdt1 ) the longer a cell has been quiescent suggests that quiescence is not just a single static state but rather that certain aspects of a cell’s proteome evolve as a function of time spent in quiescence ( at least over the 24-hour period that we measured ) . We then schematized these results to create diagrams that depict the chronology and dynamics of cell-cycle events ( Fig 5B ) . The 5 proteins in Group 1 all increase their levels as cells progress through the proliferation cycle , albeit with different dynamics . Cyclin A2 starts to accumulate in S phase and continues to increase until M phase . Geminin begins to accumulate at the same time but plateaus in G2 . Cyclin B1 and c-Myc remain low until late S phase . Rb phosphorylation on Serine 780 steadily increases throughout the whole proliferative cycle . All of these proteins reset at mitosis and maintain low levels in quiescent cells . The dynamics of Group 2 proteins are more variable . Cyclin D1 and Cdt1 turn on in G2 after being low or off in S phase . Cyclin D1 increases further if cells go into G0 , and degrades when CDK2inc cells re-enter the cell cycle . Cdt1 decreases slowly when cells enter the CDK2low state and decreases rapidly when CDK2inc cells enter S phase . Cyclin E starts to increase at the completion of mitosis and continues to increase throughout G0 and G1; Cyclin E levels drop because of degradation at the G1/S transition but remain elevated in G0/quiescent cells . p21 levels are low in proliferating cells but increase steadily once cells enter quiescence . Such diagrams provide a quantitative resource for understanding the dynamics of cell-cycle proteins relative to one another .
Using single-cell time-lapse microscopy and IF , combined with automated image processing and cell tracking , we have characterized the dynamics of key cell-cycle proteins in unperturbed proliferating and spontaneously quiescent cells and compared these with cells forced into quiescence by serum starvation or contact inhibition . Our measurements provide a rich resource for those focused on the cell cycle , or on any biological process that is impacted by the cell cycle , by providing a map of standard cell-cycle behavior in non-tumorigenic cells . Unlike most characterizations of cell-cycle behavior , which use chemical synchronization such as nocodazole or double thymidine block , our data come from asynchronous , unperturbed single cells . We are therefore able to chart , at high time resolution , both mean population behavior as well as cell-to-cell variability in protein levels and modification states . All cultured populations of somatic human cells that we have examined thus far actually contain mixtures of proliferating and spontaneously quiescent cells . This generates extensive cell-to-cell variability , which would obscure even single-cell IF data aligned by time-since-anaphase , if one were unable to distinguish the proliferating , quiescent , and emerging populations using the CDK2 sensor . When we classified proteins based on their behavior in quiescent CDK2low cells , we identified a set of 4 proteins ( Cyclin D1 , Cyclin E , p21 , and Cdt1 ) , whose concentrations increase or decrease the longer cells are in quiescence . This suggests that quiescence is not a homogenous “off” state , but rather that the quiescent cell state changes continually , at least over our 24-hour observation period . These data support the existence of a continuum of quiescence depths . It is well documented that the levels of Cyclins D and E are dramatically reduced in cells forced into quiescence via serum starvation [42 , 67] . Here we compared the dynamics of multiple key cell-cycle proteins , including Cyclin D1 and Cyclin E , in forced versus spontaneous quiescence . In contrast to the declining levels of Cyclin D1 and Cyclin E in serum-starved or contact-inhibited cells , the levels of Cyclin D1 and Cyclin E rise while cells are in the quiescent CDK2low state . We confirmed this result using endogenously tagged mCitrine-Cyclin D1 and further showed that the high levels of Cyclin D1 in CDK2low cells arise because of reduced cullin-RING ligase-mediated protein degradation in the CDK2low state . Similarly , high levels of Cyclin E in CDK2low cells likely arise because this Cyclin E has not been subjected to S phase–mediated degradation , which depends on CDK2 activity [40 , 41] . Examination of cells emerging from a transient quiescence ( CDK2emerge cells ) reveals that CDK2emerge cells recapitulate the protein dynamics of cells that immediately enter the CDK2inc state after mitosis . Put another way , the protein dynamics of CDK2inc cells that are born committed to the cell cycle with elevated CDK2 activity are similar to the protein dynamics of CDK2emerge cells that commit to the cell cycle at variable times after dividing . This result argues that the beginning of the active cell cycle is marked by the increase in CDK2 activity and that any time cells spend prior to the activation of CDK2 represents a period of cell-cycle exit that we have referred to as G0/quiescence . Which signaling events are causes of , and which are simply consequences of , entry into quiescence ? The full answer will require extensive analysis using acute perturbations of the proteins in question , but based on the data presented here , we can already speculate that the behavior of proteins with levels that are similar in newly born CDK2inc and CDK2low cells is likely to simply be a consequence of entry into quiescence ( e . g . , Geminin , Cyclin A2 , and Cyclin B1 ) . In contrast , proteins with levels that are already distinct in newly born CDK2inc and CDK2low cells have already been shown to be causative ( e . g . , p21 [11] ) or have the potential to be causative in the proliferation-quiescence decision ( e . g . , Cyclin D1 and phospho-Rb ) . In summary , the experimental and computational approaches employed here enable the creation of chronological maps of protein dynamics during cell-cycle progression and cell-cycle exit in asynchronous single cells , revealing several differences compared with previous results generated from synchronized cells . These maps will be informative for mathematical modeling of the cell cycle and can also serve as a benchmark for comparing the cell cycle of non-transformed cells with the cell cycle of various cancer cells . Our work also highlights the fact that there are multiple molecularly distinct states of quiescence , depending on the initiating trigger . Together , our data provide new information for answering fundamental questions about normal cellular control over proliferation and add new molecular knowledge to the poorly documented state ( s ) of G0/quiescence .
MCF10A human mammary epithelial cells were maintained in DMEM/F12 ( ThermoFisher ) supplemented with 5% horse serum ( Invitrogen ) , 20 ng/ml epidermal growth factor ( EGF , Sigma-Aldrich ) , 0 . 5 mg/ml hydrocortisone ( Sigma-Aldrich , St . Louis , MO ) , 100 ng/ml cholera toxin ( Sigma-Aldrich ) , 10 μg/ml insulin ( Invitrogen ) , and penicillin/streptomycin . For serum starvation media , the horse serum , EGF , and insulin were removed , and 0 . 3% BSA was added . For live-cell time-lapse imaging , phenol-red free DMEM/F12 was used . Hs68 primary human foreskin fibroblasts were cultured in DMEM with 10% FBS and penicillin/streptomycin . Both cell lines were purchased from ATCC . Hs68 cells can be propagated for 42 passages according to ATCC and are not immortalized; cells were received at passage 12 and were used within 13 passages of receipt . MCF10A cells expressing the CDK2 sensor ( DHB-mVenus ) and tagged histone H2B ( H2B-mTurquoise ) are as described [11] . Integration of the mCitrine-encoding gene into the CCND1 locus was carried out using CRISPR technology [68] . A CRISPR-Cas9 ribonucleoprotein ( RNP ) complex was generated using the CRISPR-Cas9 System from IDT . The RNP contains crRNA ( GGAGCUGGUGUUCCAUGGCUGUUUUAGAGCUAUGCU ) annealed to tracrRNA and Cas9 nuclease . The RNP was electroporated into MCF10A cells using the Neon system from Life Technologies following the manufacturer’s protocol with 2 pulses , 30 ms at 1150 V . Single cells were sorted by flow cytometry into 96-well plates and grown into clones . Western blot and IF against Cyclin D1 protein , as well as PCR of the CCND1 gene , were carried out as validation . Data from clone 2A7 is shown in this work ( S8 Fig ) . For functional validation , cells were treated with Mek inhibitor ( PD0325901 , S1036 from Selleckchem ) at 100 nM for 32 hours , or treated for 32 hours followed by a Mek inhibitor washout for 6 hours . To confirm a similar response to inhibition of degradation for both mCitrine-Cyclin D1 and endogenous Cyclin D1 , the mCitrine-Cyclin D1 line and parental wild type MCF10A line were treated with MLN4924 ( Active Biochem , A-1139 ) at 1 . 4 μM or Bortezomib ( Cayman Chemical , 10008822 ) at 1 μM for 2 hours ( S8A Fig ) . siRNA oligos were synthesized by Dharmacon: CCNA2 ( MU-003205-02-002 ) , CCNE1 ( MU-003213-02-0002 ) , CCNE2 ( MU-003214-02-0002 ) , CDKN1A ( MU-003471-00-0002 ) , CCND1 ( MU-003210-05-0002 ) , RB1 ( MU-003296-03-0002 ) or IDT: CCNB1 ( hs . Ri . CCNB1 . 13 . 1 ) , GMNN ( hs . Ri . GMNN . 13 . 1 ) , CDT1 ( hs . Ri . CDT1 . 13 . 2 ) , MYC ( hs . Ri . MYC . 13 . 2 ) , and Negative Control DsiRNA ( 51-01-14-04 ) . The oligos were electroporated into MCF10A cells following manufacturer’s instruction ( Neon system , Life Technologies ) . Cells were fixed for IF or lysed for western blotting 20 hours ( for short-live proteins: Cyclin A2 , Cyclin B1 , Cyclin E , Cyclin D1 , c-Myc , p21 , Geminin , and Cdt1 ) or 48 hours ( for longer-live proteins: Rb ) after the electroporation . Antibodies used in this study are p21 Waf1/Cip1 ( CST #2947 ) at 1:250 , phospho-Rb ( Ser807/811 ) ( CST #8516 ) at 1:250 , phospho-Rb 780 ( BD Biosciences #668385 ) at 1:250 , p21 ( BD Biosciences #556430 ) at 1:250 , total Rb ( a gift from Julien Sage ) at 1:200 , p53 ( DO-1 ) ( Santa Cruz sc-126 ) at 1:100 and p53 ( Ab-1 ) ( Calbiochem OP03 ) at 1:100 , Fra-1 ( Santa Cruz #28310 ) at 1:200 , Cyclin E clone HE12 ( Zymed #32–1600 ) at 1:400 , Cyclin D1 clone SP4 ( Thermo Scientific RM-9140-S0 ) at 1:250 , Cyclin A2 ( Santa Cruz #751 ) at 1:500 , phospho-Histone H3 ( Ser10 ) ( CST #9706 and #9701 ) at 1:200 , p27 ( BD Bioscience #610241 ) at 1:100 , Geminin ( CST #5165 ) at 1:250 , Cyclin B1 ( CST #4138 ) at 1:100 , c-Myc ( CST #5605 ) at 1:250 , CDT1 ( CST #8064 ) at 1:200 , phospho-c-Jun ( Ser73 ) ( CST #3270 ) at 1:800 , and Alexa Fluor-488 , -546 , -647 secondary antibodies ( ThermoFisher ) at 1:500 . For Cyclin E IF , cells were fixed in −20°C methanol for 5 minutes and then washed twice with PBS . For all other antibodies , cells were fixed with 4% paraformaldehyde and then washed twice with PBS . Cells were then incubated with a blocking/permeabilization buffer ( 10% FBS , 1% BSA , 0 . 1% TX-100 and 0 . 01% NaN3 for antibodies against Cyclin E , p21 , Cdt1 , Geminin , Fra1 , p53 , and phospho-c-Jun ) for an hour at room temperature , or sequentially permeabilized with 0 . 2% TX-100 for 15 minutes at 4°C and blocked with 3% BSA for an hour at room temperature ( for antibodies against Cyclin A2 , Cyclin B1 , Cyclin D1 , c-Myc , p27 , and total Rb ) . Primary antibody staining was carried out overnight at 4°C in the corresponding blocking buffer and visualized using secondary antibodies conjugated to Alexa Fluor-488 , -546 , or -647 . Where phospho-Rb and phospho-Histone H3 antibodies were used in conjunction with an antibody for a protein of interest in Fig 2 , cells were processed using the method appropriate for the protein of interest . Where indicated , cells were incubated in media containing 10 μM EdU for 15 minutes , and then fixed and processed according to manufacturer’s instructions ( ThermoFisher #C10340 ) . Images were acquired on an ImageXpress Micro XLS widefield microscope ( Molecular Devices ) with a 10X 0 . 45NA objective and processed using custom scripts in MATLAB . Cells were plated at least 24 hours prior to imaging in phenol red-free full-growth media in a 96-well plate ( Greiner bio-one #655090 ) such that the density would remain subconfluent until the end of the imaging period . Images were acquired every 12 minutes on an ImageXpress Micro XLS widefield microscope ( Molecular Devices ) with a 10X 0 . 45NA objective; CFP exposure = 75 ms; YFP exposure = 200 ms . Cells were imaged in a humidified , 37°C chamber at 5% CO2 . Images were processed as described in Cappell et al . , 2016 ( [35] ) , with a general description reproduced here: Mean nuclear intensities were measured by averaging the background-subtracted pixel intensities in each nucleus as defined by a nuclear mask . The nuclear mask was established by performing segmentation on H2B-mTurquoise- or Hoechst-stained images as follows . Log-transformed images were convolved with a rotationally symmetric Laplacian of Gaussian filter and objects were defined as contiguous pixels exceeding a threshold filter score . In order to segment cells in contact with their nearest neighbor , a custom segmentation algorithm was implemented to detect and bridge concave inflections in the perimeter of each object ( hereafter referred to as the “deflection bridging algorithm” ) . The deflection bridging algorithm was implemented on every identified object in the first imaging frame and then only adaptively in subsequent frames . This was accomplished by iteratively tracking cells in each frame , detecting probable merge events ( as discussed below ) and selectively implementing the deflection bridging algorithm on putative merged objects . Local background subtraction was performed on images of sensors or antibodies that were nuclear in subcellular distribution . For local background subtraction , the nuclear mask was expanded by 25 μm and the background for each cell was calculated as the median pixel intensity of local nonmasked pixels . For cytoplasmically localized sensors or antibodies , the nuclear mask was dilated by 50 μm , and the global background was calculated as the mode intensity of all nonmasked pixels . As before , CDK2 activity was calculated as the ratio of cytoplasmic to nuclear mean DHB fluorescence , with the cytoplasmic component calculated as the mean of the top 50th percentile of a ring of pixels outside of the nuclear mask . Tracking of cells between frames was implemented by screening the nearest future neighbor for consistency in total H2B-mTurquoise fluorescence ( “conservation of mass” ) . Because the stage jittered slightly after fixation and IF in the time-lapse + IF dataset , we implemented the following jitter correction procedure to ensure precise matching of the CDK2 activity trace of each cell to its IF intensity: We first subtracted the image at a specific time from the image in the next frame to get a “difference score” between 2 images . We then repeated the process , with 1 image moving in a 2-dimensional manner , to get multiple “difference scores” when the stage jittered . The position with the lowest score indicated the amount of jittering and the images were aligned accordingly . “Conservation of mass” was further exploited to detect merges or splits , which allowed recovery of overlapping traces . Mitosis events ( called at anaphase ) were called when the total H2B fluorescence of the 2 nearest future neighbors of a given cell were both between 45% and 55% of the total H2B fluorescence of the past cell . The R-point was defined as the time CDK2 activity first began to rise . Computationally , this involves calculating slopes of CDK2 activity using windows of 6–10 time points and then maximizing a linear function for time-since-mitosis , CDK2 activity , and CDK2 slope ( long times-since-mitosis , low CDK2 activity , and high CDK2 slope ) . The tracking code is available for download here: https://github . com/scappell/Cell_tracking . Traces were computationally classified , and manually verified , as CDK2inc ( blue ) , CDK2low ( red ) , or CDK2emerge ( green ) based on CDK2 activity at 2 hours after mitosis: CDK2inc traces must remain ≥ 0 . 5 for all frames post-anaphase; CDK2low traces must remain < 0 . 5 for all frames post-anaphase; CDK2emerge traces initially enter the CDK2low state and then emerge—these traces must remain < 0 . 5 for at least 3 hours post-anaphase before rising . | The cell cycle is by nature highly dynamic , but we lack a standardized map of how core cell-cycle regulators change over time . In this study , we used time-lapse microscopy to track the dynamics of key cell-cycle proteins in individual human cells and found several unexpected patterns , even for well-studied proteins such as Cyclin D1 . Our data provide a rich resource for those focused on the cell cycle , or on any biological process that is impacted by the cell cycle , by providing a series of maps of protein dynamics during cell-cycle progression and cell-cycle exit . | [
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"prepara... | 2017 | A map of protein dynamics during cell-cycle progression and cell-cycle exit |
Recent functional neuroimaging evidence suggests a bottleneck between learning new information and remembering old information . In two behavioral experiments and one functional MRI ( fMRI ) experiment , we tested the hypothesis that learning and remembering compete when both processes happen within a brief period of time . In the first behavioral experiment , participants intentionally remembered old words displayed in the foreground , while incidentally learning new scenes displayed in the background . In line with a memory competition , we found that remembering old information was associated with impaired learning of new information . We replicated this finding in a subsequent fMRI experiment , which showed that this behavioral effect was coupled with a suppression of learning-related activity in visual and medial temporal areas . Moreover , the fMRI experiment provided evidence that left mid-ventrolateral prefrontal cortex is involved in resolving the memory competition , possibly by facilitating rapid switching between learning and remembering . Critically , a follow-up behavioral experiment in which the background scenes were replaced with a visual target detection task provided indications that the competition between learning and remembering was not merely due to attention . This study not only provides novel insight into our capacity to learn and remember , but also clarifies the neural mechanisms underlying flexible behavior .
We continuously learn novel events ( memory encoding ) and remember past events ( memory retrieval ) : this fact is so intricately woven into the fabric of our personal lives that we easily take it for granted . Yet , this central aspect of daily life is not as straightforward as it might seem . In fact , many influential models of memory assume that encoding and retrieval cannot occur at the same time and that the two processes compete for neural resources [1–3] . In line with a competition , recent functional neuroimaging studies have indicated opposing levels of brain activity during encoding and retrieval . In particular , successful retrieval has been associated with increased activity in the posterior cingulate cortex ( PCC ) [4 , 5] , whereas successful encoding has been associated with decreased activity in this same region [6–8] . Given that global activity in a particular brain region cannot increase and decrease at the same time , these findings lead to the hypothesis that successful learning and successful remembering may compete when both processes happen concurrently . In two behavioral experiments ( our Behavioral Experiments 1 and 2 ) and one functional MRI ( fMRI ) experiment , we investigated the behavioral and neural consequences of this potential bottleneck in the human memory system . The study used a novel paradigm that forces encoding and retrieval to happen within a brief period of time . The experimental task involves three phases: a word encoding phase ( Figure 1A ) , a word retrieval/scene encoding phase ( Figure 1B ) , and a scene retrieval phase ( Figure 1C ) . During the word encoding phase , participants rapidly encode words by processing their meaning ( living/nonliving decisions ) . During the word retrieval/scene encoding phase , participants perform an old/new word recognition task including words presented at the word encoding phase intermixed with new words . The key difference with a standard old/new word recognition test is that , while recognizing the words , participants incidentally encode spatial scenes that are presented in the background . To ensure simultaneous encoding and retrieval , participants are allowed maximally 1 . 2 s to make the recognition judgment , and both the word and scene disappear immediately after the recognition response is made . Subsequently , visually masking noise is presented to avoid further visual processing . Participants are instructed to perform the retrieval task as quickly as possible without making errors . During the scene retrieval phase , learning of the spatial scenes is measured with a standard old/new recognition test . When combined with fMRI , this paradigm allows the measurement of both the activity associated with successful retrieval ( old words classified as old versus new ) and with successful encoding ( scenes subsequently remembered versus forgotten ) during one single task . As a result , there are four relevant trial types: word retrieval is unsuccessful but scene encoding is successful ( R–E+ ) , both word recognition and scene encoding are unsuccessful ( R–E– ) , both word recognition and scene encoding are successful ( R+E+ ) , and finally , word recognition is successful but scene encoding is unsuccessful ( R+E– ) . Critically , the paradigm is not simply measuring potential interference between viewing scenes and making recognition responses , but specifically measures interference between successful encoding and successful retrieval . Potential interference from perceptual or motor processes is subtracted out , because all trials have scenes in the background and all involve recognition responses . This study tested three predictions . First , as a behavioral consequence of the bottleneck , we predicted that learning and concurrent remembering should compete . In other words , we expected that encoding of the spatial scenes would be significantly poorer when simultaneous word retrieval was successful compared with when retrieval was unsuccessful . Second , based on fMRI studies of encoding and retrieval indicating opposing levels of brain activity in PCC [4–8] , we predicted that activity in this region would show an interaction between memory phase ( encoding versus retrieval ) and outcome ( successful versus unsuccessful ) . We predicted that PCC activity should be highest during successful retrieval and unsuccessful encoding , and lowest during unsuccessful retrieval and successful encoding . Finally , we predicted that the behavioral effect would be coupled with suppression of brain activity in areas associated with successful encoding of spatial scenes , including the visual cortex and medial temporal lobe ( MTL ) .
Overall memory performance as defined by d-prime was 0 . 95 ± 0 . 13 for the word recognition and 0 . 70 ± 0 . 07 for recognition of the spatial scenes . In addition , the response bias criterion C [9] indicated that participants maintained a generally conservative response criterion during both word ( C = 0 . 52 ± 0 . 08; t = 6 . 94 , p = 0 . 0001 ) and scene ( C = 1 . 16 ± 0 . 08; t = 15 . 3 , p < 0 . 0001 ) retrieval . This positive response bias was conform our specific instructions to respond only “old” when certain . Response times ( RTs ) during the word recognition task indicated that encoding and retrieval happened ( almost ) concurrently , because the word recognition responses were very fast ( R–E+ = 871 ± 13 ms; R–E– = 862 ± 11 ms; R+E+ = 878 ± 13 ms; R+E– = 872 ± 7 ms ) . Importantly , none of the four trial types showed any significant difference in RT ( all p > 0 . 10 ) . Thus , exposure time to the spatial scenes was identical for all conditions and cannot account for the difference in subsequent memory performance . We also addressed a critical concern: despite the fact that the response times for the four critical trial types did not differ , one could still argue that retrieval success results in greater attentional capture than retrieval failure , which in turn could account for the observed reduction in scene encoding . To address this important issue , we conducted a follow-up behavioral experiment in which we replaced the scene encoding with a visual attention task ( see Materials and Methods and Figure 4 ) . Memory for the words as defined by d-prime ( 1 . 01 ± 0 . 08 ) was similar to the previous experiments ( Behavioral Experiment 1: t = 0 . 33 , p = 0 . 75; fMRI Experiment: t = 0 . 92 , p = 0 . 38 ) . D-prime was also used as a measure of visual attention , as assessed by the detection of a small target concurrent with word recognition . Overall , all participants showed clear evidence of successful target detection ( d-prime = 2 . 07 ± 0 . 63 ) , and again , they used a conservative response criterion for both word retrieval ( C = 0 . 31 ± 0 . 11; t = 2 . 78 , p = 0 . 019 ) and visual attention ( C = 1 . 09 ± 0 . 13; t = 8 . 23 , p < 0 . 0001 ) . Mean reaction times for the four critical trial types , which in this case combined word recognition ( hits = R+/ misses = R– ) with target detection ( hits = T+ / misses = T– ) were 892 ± 17 ms for R–T+ , 872 ± 20 ms for R–T– , 838 ± 18 ms for R+T+ , and 843 ± 15 ms for R+T– . Although a two-sample t-test indicated that these reaction times were comparable to the ones in Behavioral Experiment 1 and the fMRI Experiment ( all p > 0 . 10 ) , a within-group paired t-test indicated a significant difference between R–T+ and R+T+ ( t = 2 . 36 , p = 0 . 037 ) , and a trend between R–eT+ and R+T– ( t = 2 . 13 , p = 0 . 056 ) . Although we did not find this in the first two experiments , slower reaction times for misses than for hits are a common finding in memory studies , and are taken to reflect a more demanding and extended search process [16] . Importantly , in order to assess whether the competition between encoding and retrieval was merely a result of attentional differences between retrieval hits and misses , we calculated the proportion of successfully detected targets depending on whether or not the accompanying word was correctly recognized . In this case , the results actually showed the opposite effect compared with concurrent word retrieval and scene encoding: the d-primes for target detection were significantly higher ( t = 2 . 67 , p = 0 . 022 ) when a word was simultaneously remembered ( 2 . 18 ± 0 . 15 ) , compared with when a word was forgotten ( 1 . 99 ± 0 . 16; see Figure 2C ) . Thus , these findings indicate that retrieval misses actually capture more visual attention than hits , and consequently , that an attentional explanation cannot easily account for the competition between learning and remembering , which was observed in Behavioral Experiment 1 and the fMRI Experiment .
Using a novel paradigm that forces encoding and retrieval to happen within a brief period of time ( Figure 1 ) , we provide evidence for a competition within our memory system between learning and remembering . We also provide evidence indicating a possible role for mid-VLPFC in resolving the memory competition . Finally , we show that the memory competition cannot merely be explained by an attentional account . The rationale for this study was derived from recent observations indicating opposite levels of activity in PCC during successful encoding and retrieval [4–8] . We confirmed these cross-experiment observations by showing an interaction between encoding- and retrieval-related activity in the PCC . As shown in Figure 3A , this interaction reflected less PCC activity for E+ than E– trials , but more activity for R+ than R– trials . To our knowledge , this is the first study to demonstrate the opposite involvement of PCC in encoding and retrieval within the same experiment , subjects , and trials . We also report a new memory effect: learning ( successful encoding ) and remembering ( successful retrieval ) compete when both processes happen within a brief period of time ( Figure 2A ) . We replicated this finding in a subsequent fMRI study ( Figure 2B ) , which also revealed a neural correlate of the behavioral memory effect: successful encoding activity in visual cortex and medial temporal lobe was suppressed when concurrent retrieval was successful ( Figure 3B ) . Further study of the specific circumstances under which this memory effect takes place is still required . For instance , it remains unclear what the temporal order ( does retrieval affect encoding or vice versa ? ) and time window of successful encoding and retrieval processes should be , for the interference to occur . Interestingly , there is other behavioral evidence indicating that retrieval can induce forgetting [17–19] . Learned information tends to be forgotten when it is semantically related to other information that is rehearsed by means of repeated retrieval . Such retrieval-induced forgetting is thought to be the result of inhibitory control processes that reduce semantic interference by suppressing competing memory traces [17–19] . Yet , in retrieval-induced forgetting paradigms , the negative effect of retrieval involves old memories that have already been stored , whereas here , it involves the concurrent encoding of novel information . Thus , in general , the current findings and those obtained in retrieval-induced forgetting paradigms cannot be easily compared . Despite the encoding/retrieval competition , on several trials , all participants were actually able to both remember and learn . Follow-up fMRI analyses showed that these trials were accompanied by selective activity in the left mid-VLPFC ( Figure 3C ) . A subsequent correlation analysis indicated a negative relationship showing that more activity in left mid-VLPFC was coupled with less encoding suppression . Together , these findings suggest a role for the left mid-VLPFC in resolving the competition between learning and remembering . Given that encoding and retrieval were forced to occur within a brief period of time , we propose that the role of left mid-VLPFC involves the facilitation of rapid switching between the encoding and retrieval processes . A role of left mid-VLPFC in rapid memory switching fits well with evidence implicating this region in flexible behavior and cognitive control . Outside the domain of memory , several studies have linked left mid-VLPFC activity to situations requiring flexible switching between different task sets or rules . For example , a recent fMRI study showed that activity in left mid-VLPFC is linked to task-switching [20] . In this study , people performed two semantic classification tasks ( large/small or man-made/natural ) . When a task-switch was required , trial-by-trial fluctuations of left mid-VLPFC activity were associated with faster responses , while right frontal activity was associated with a sustained increase in reaction times ( independent of the task ) . Based on these results , the authors concluded that the left mid-VLPFC is associated with rapid and efficient task-switching . Complementing these fMRI data , a recent clinical study reported that patients with damage to mid-VLPFC show substantial impairments when rules are switched during an oculomotor task [21] . Within the domain of memory , a recent review associated left mid-VLPFC ( BA 45 ) specifically with a post-retrieval selection process , which operates to resolve conflict among retrieved representations [22] . This idea is based on the finding that this region shows greater activity with increasing numbers , or strength , of retrieved competitors [23 , 24] . Here , we confirm that left mid-VLPFC shows greatest activity in situations where conflict is largest ( R+E+ ) . Yet , the current study extends these findings in an important way . First , we show that left mid-VLPFC activity is not only associated with competition during retrieval , but also , with the conflict that arises when retrieval is competing for resources with concurrent encoding . Second , by showing a negative coupling between left mid-VLPFC activity and the encoding suppression effect in the visual cortex and MTL , we provide new evidence that this region is not merely associated with high-conflict memory conditions , but actually aids in resolving conflict . Finally , we addressed a crucial issue regarding the possible role of attention in the competition between learning and remembering . Despite the fact that the response times for the four critical trial types did not differ , one could still argue that retrieval success results in greater attentional capture than retrieval failure . This aspect , in turn , could account for the observed reduction in scene encoding . Yet , the results of Behavioral Experiment 2 ( Figure 2C ) contradict this explanation . In fact , when the scene-encoding task was replaced with a visual attention task the retrieval effect showed a reversal: the chance of detecting the target dot was significantly smaller when retrieval failed ( R– ) than when retrieval succeeded ( R+ ) . Hence , these results indicate that retrieval failure is actually accompanied by greater engagement of selective attention than retrieval success . Overall , this study not only provides novel insight into our capacity to learn and remember , but also increases our general understanding of the neural mechanisms underlying flexible behavior . Virtually all interactive situations we encounter in our daily lives require rapid switching between learning and remembering . For example , normal social communication requires that we process the new information another person is providing . While listening , we are already retrieving information in preparation of an appropriate reply . Other every-day examples are driving through an unfamiliar city while rapidly interpreting familiar traffic signs , and encountering various store products during shopping while remembering what we need . In this respect , it is interesting to note that conditions that compromise mid-VLPFC function , such as normal aging [25] , are also associated with impairments in these every-day activities . On a final note , although the opposite levels of activity in PCC during encoding and retrieval formed the rationale of the study , it should be mentioned that , given the relatively low spatial resolution of fMRI , one should be careful when interpreting this finding in terms of a neural bottleneck regarding encoding and retrieval processes . A single voxel can contain thousands of neurons , some of which can increase in activity while others decrease . These changes could easily sum to zero in terms of fMRI signal . Thus , while the overall signal within a voxel cannot increase and decrease at the same time , fMRI does not allow determining whether different neural signals within the voxel are simultaneously increasing and decreasing . Also , we should state that we are not claiming that encoding and retrieval are fundamentally distinct processes that always compete . Actually , according to transfer-appropriate processing [26] and reactivation accounts [2 , 27] , the overlap between encoding and retrieval processes forms the most important determinant of memory performance . The present data merely indicate that encoding and retrieval compete for neural resources when these processes are forced to occur within a brief period of time and involve different sources of information . In conclusion , the present study yielded five main findings . First , we confirmed and extended previous evidence indicating opposing levels of activity in PCC during learning and remembering . Second , in line with a competition in our memory system , we report a new memory effect: successful retrieval has a detrimental effect on memory encoding when both processes happen within a brief period of time . Third , we found that this behavioral effect is coupled with suppression of encoding-related brain activity . Fourth , we identified a region within left mid-VLPFC that was negatively correlated with the encoding suppression effect . This finding suggests that this region may facilitate rapid switching between encoding and retrieval processes . Finally , a follow-up behavioral study provided indications that the competition between learning and remembering is not due to attention , but truly reflects a memory phenomenon . More generally , these findings show that , although learning and remembering compete , there are certain conditions in which this bottleneck in our memory system can be resolved .
Participants . Nine participants ( five female ) , with a mean age of 24 years , were recruited from the University of Amsterdam to participate in this experiment . Participants were right-handed , native Dutch speakers with no history of neurological problems and were paid EUR€20 for participation . Participants gave their informed consent and the study met all criteria for approval of the Academic Medical Center Medical Ethical Committee . Stimuli . The stimulus material consisted of 600 words and 720 spatial scenes . All words were nouns selected from the MRC Psycholinguistic database ( http://www . psy . uwa . edu . au/mrcdatabase/uwa_mrc . htm ) and subsequently translated to Dutch . Words ranged from five to 11 letters long and were of moderate frequency . The spatial scenes consisted of colorful bitmap images ( color: 24-bit , resolution: 500 × 375 , format: BMP ) . All images displayed outdoor or indoor scenes with a spatial environment and were selected from an internet database ( http://www . flickr . com ) . Stimuli were generated by a Pentium PC and presented using E-Prime software ( Psychology Tools Inc . ) . The images were displayed on a computer monitor , and responses were collected via a keyboard . Procedure . The behavioral task was designed with the intention to be applied within the context of an fMRI study at a later stage ( see fMRI Experiment . ) . The task consisted of three phases , a word encoding phase ( Figure 1A ) , a word retrieval/scene encoding phase ( Figure 1B ) , and a scene retrieval phase ( Figure 1C ) . During the word encoding phase , participants studied 500 words presented on a computer screen while making semantic decisions about the study items ( living versus nonliving ) . Responses were made via a button-press with the right hand , and after the participant responded , the stimulus was instantly removed . The duration of each trial was 1 , 200 ms . , and the inter-trial-interval ( ITI ) lasted 500 ms . Participants were uninformed that they would later be asked to recall the words during the subsequent word retrieval/scene encoding phase . During the word retrieval/scene enceoding phase , participants performed a word recognition task . The words consisted of the items previously presented during the word encoding phase ( old words ) , as well as words that were not seen at study ( new words ) . The key difference with a standard old/new word recognition test is that , while recognizing the words , participants incidentally encoded spatial scenes presented in the background . Similar to the word encoding phase , participants were uninformed that they would later be asked to recall the spatial scenes . Specifically , participants were told that the images were merely there to provide a memory context , that they should focus on the word recognition task , and that they should respond as quickly and accurately as possible . Signifying the effectiveness of our instructions , participants all indicated that they did not anticipate a subsequent retrieval test including the background scenes . In order to ensure a stable contrast between words and scenes , the words were presented on top of a small rectangle overlaying the center of the background image . Participants performed 600 recognition trials , which lasted maximally 1 , 200 ms . After the participant responded , the stimuli were instantly removed and followed by a 100-ms visual mask containing Gaussian noise to prevent additional visual processing . The ITI varied between 500–3 , 200 ms . During the scene retrieval phase , memory for the spatial scenes encoded during the previous phase was tested with a scene recognition task . Presentation of the scenes was self-paced and occurred on the same computer as used in the word encoding phase . During both word and scene retrieval , we presented five times more “old” than “new” items ( words 500 old versus 100 new; scenes 600 old versus 120 new ) . There were two reasons for the high number of old relative to new items . First , initial pilot studies had indicated that concurrent scene encoding was very difficult , resulting in a relatively low number of remembered scenes . Second , we were only interested in retrieval of old items and not in classification of new items . Thus , we presented more old items to ensure a sufficient number of events for each of the four trial types in a future fMRI experiment . Because the skewed distribution of old and new items could potentially lead to a liberal response bias towards old items , we instructed participants to make an “old” response only when they were absolutely certain . Confirming that participants followed our instructions appropriately , a response bias analysis ( C = −0 . 5 × ( ZFA-rate + ZHIT-rate ) ) [9] showed that they used a generally conservative response criterion ( see Results ) . After finishing the experiment , we questioned the participants regarding their experience . None of the participants reported that he or she was aware of the high number of old items . Participants . Fifteen additional participants ( seven female ) recruited from the University of Amsterdam with a mean age of 24 participated in this experiment . Again , all participants were right-handed , native Dutch speakers with no history of neurological problems and were paid EUR€40 for participation . Four participants were excluded based on an extremely low memory performance ( d-prime < 0 . 20 for spatial scenes ) . Stimuli . The stimulus material consisted of the same 600 words and 720 spatial scenes as used in Behavioral Experiment 1 . The experimental task was also identical to the previous experiment ( Figure 1A ) , except that the word retrieval/scene encoding phase was performed inside the MRI scanner . “Localizer” task . Preceding the word retrieval/scene encoding phase , participants were presented in the scanner with a “localizer” task involving passive viewing of either 80 spatial scenes , 80 four-letter words , or a fixation cross . These stimuli were distributed over 12 30-s blocks ( scenes-words-fixation; scenes-words-fixation; scenes-words-fixation; scenes-words-fixation ) . The “localizer” task was used to identify brain regions generally involved in scene versuse word processing , and none of the stimuli wase used in any of the other experiments . Data acquisition . fMRI images were collected with a Phillips Intera 3 . 0T using a standard SENSE head coil and a T2* sensitive gradient echo sequence ( 96 × 96 matrix , time of repetition ( TR ) 2 , 000 ms , echo time ( TE ) 30 ms . , flip angle ( FA ) 80° , 34 slices , 2 . 3 mm × 2 . 3 mm voxel size , 3-mm thick transverse slices ) . Stimuli were projected on a screen at the front end of the scanner and observed via a mirror mounted on the head coil . The participant's head was fixed by foam and the participants wore earplugs to reduce scanner noise . The behavioral responses were collected by an MR-compatible four-button box ( Lumitouch ) . fMRI analysis . Data from the “localizer” task and the fMRI Experiment were analyzed using SPM2 ( Statistical Parametric Mapping; http://www . fil . ion . ucl . ac . uk/spm ) . Time-series were corrected for differences in acquisition time and realigned . The images were spatially normalized using the MNI echo planar imaging ( EPI ) template included in SPM2 and resliced to a resolution of 3 × 3 × 3 mm . Next , the functional images were spatially smoothed using an 8-mm isotropic Gaussian kernel . Block-related activity in the “localizer” task was assessed by convolving a boxcar function representing the onsets eand offsets of each block with the hemodynamic response function ( HRF ) . Trial-related activity in the fMRI Experiment was assessed by convolving a vector of the onset times of the stimuli with the HRF . The general linear model ( GLM ) , as implemented in SPM2 , was used to model the effects of interest as well as other confounding effects ( scanner drift and motion ) . Statistical parametrical maps were identified for each participant by applying linear contrasts to the parameter estimates ( beta weight ) applying to the events of interest , resulting in a t-statistic for every voxel . Random effects analyses were employed to calculate group effects . For the fMRI Experiment , the events of interest were determined by the performance on the memory tasks . Hits and misses for words during the scan-phase were coded as retrieval hit ( R+ ) and retrieval miss ( R– ) , while hits and misses for the scenes , during the subsequent scene retrieval , were coded as encoding hits ( E+ ) and encoding misses ( E– ) . These responses combined resulted in a sufficient number of events ( > 30 events ) for each of the four relevant trial types in the fMRI analyses ( mean: R–E+ = 31 ± 8; R–E– = 181 ± 21; R+E+ = 37 ± 8; R+E– = 222 ± 26 ) . Although the fMRI analysis focused specifically on the old items , new items and omitted responses were also included in the GLM . Encoding-retrieval interaction in PCC . In order to re-examine previous fMRI studies that consistently found increased activity in PCC for successful as compared to unsuccessful memory retrieval [4 , 5] , we calculated the difference in brain activity between R+E– and R–E– trials ( p < 0 . 001 , uncorrected ) . Since no encoding occurred , and only the level of retrieval varied , the resulting difference between these trials can only be attributed to retrieval success . To examine whether the PCC would show an interaction between stage and outcome , we recombined the PCC activity for the four different trial types to reflect unsuccessful encoding ( E– = [R–E– and R+E–] ) , successful encoding ( E+ = [R–E+ and R+E+] ) , unsuccessful retrieval ( R– = [R–E– and R–E+] ) and successful retrieval ( R+ = [R+E– and R+E+] ) . Next , we conducted a stage ( encoding/retrieval ) × outcome ( successful/unsuccessful ) repeated measures ANOVA based on mean cluster activity in PCC . Suppression of successful encoding activity . To test the prediction that successful retrieval leads to suppression of successful encoding activity , we used a three-step approach . In the first step , we used the “localizer” task to identify regions related to visual processing of scenes vs . those involved in the general processing of words ( scenes > words at p < 0 . 001 , uncorrected ) . In step two , we looked within these areas for regions that were reliably associated with encoding success , defined as R–E+ > R–E– ( p < 0 . 001 , uncorrected ) . Similar to the previous retrieval analysis , no retrieval occurred for these trials and only the level of encoding varied . Thus , the resulting difference between these trials can only be attributed to encoding success . In the final step , we tested whether the mean encoding success activity of the remaining regions was significantly reduced when successful retrieval happened concurrently . Participants . Twelve additional participants ( eight female ) recruited from the University of Amsterdam , with a mean age of 25 , participated in this experiment . Similar to the previous two experiments , all participants were right-handed , native Dutch speakers , reported no history of neurological problems , and were paid EUR€10 for participation . Procedures . The settings for the word recognition task were identical to the previous experiments , except that the scene encoding task was replaced by a visual attention task , and accordingly , there also was no subsequent scene recognition task ( see Figure 4 ) . During the word retrieval phase , participants simultaneously performed a visual attention task . On half of the retrieval trials , which were randomly selected , a small target dot ( 0 . 5° ) appeared ( for 13 ms ) at a random location 9° from the centre of the screen , sometime between 50–300 ms after word onset . Similar to the previous experiments , participants were told to focus on the recognition task and to make their recognition responses as quickly and accurately as possible . After the recognition response , participants were asked to indicate , without time limit , whether they had just perceived a dot or not . Similar to the previous experiments , we instructed the participants to only respond positive ( old or target detected ) when they were certain . Response bias-measures [9] confirmed that participants followed our instructions ( see Results ) . | This study provides clear evidence for a bottleneck in our memory system between learning new and remembering old information . The ability to continuously learn and remember is usually taken for granted . Virtually all interactive situations we encounter require concurrent learning and remembering . For example , normal social communication requires that we process the new information that another person is providing . While listening , we are usually already retrieving information in preparation of an appropriate reply . Other examples include driving through an unfamiliar city while interpreting familiar traffic signs , or encountering novel products during shopping while remembering what we need . Although these examples clearly illustrate the importance of the simultaneous occurrence of learning and remembering , this study shows that remembering and learning compete for resources when both processes happen within a brief period . The study also examined the neural consequences of the competition between learning and remembering using functional MRI ( fMRI ) . In line with the behavioral competition , the neuroimaging results showed a clear suppression of learning-related brain activity as a result of concurrent remembering . Finally , the study provides evidence that a specific region in the prefrontal cortex can resolve the bottleneck , possibly by allowing rapid switching between learning and remembering . | [
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] | 2009 | When Learning and Remembering Compete: A Functional MRI Study |
Rapid conduction of action potentials along motor axons requires that oligodendrocytes and Schwann cells myelinate distinct central and peripheral nervous system ( CNS and PNS ) domains along the same axon . Despite the importance of this arrangement for nervous system function , the mechanisms that establish and maintain this precise glial segregation at the motor exit point ( MEP ) transition zone are unknown . Using in vivo time-lapse imaging in zebrafish , we observed that prior to myelination , oligodendrocyte progenitor cells ( OPCs ) extend processes into the periphery via the MEP and immediately upon contact with spinal motor root glia retract back into the spinal cord . Characterization of the peripheral cell responsible for repelling OPC processes revealed that it was a novel , CNS-derived population of glia we propose calling MEP glia . Ablation of MEP glia resulted in the absence of myelinating glia along spinal motor root axons and an immediate breach of the MEP by OPCs . Taken together , our results identify a novel population of CNS-derived peripheral glia located at the MEP that selectively restrict the migration of OPCs into the periphery via contact-mediated inhibition .
Traditionally , the CNS and PNS have been thought of as two , distinct halves of one organ system that are fused into a functional unit by bundles of motor and sensory axons . Where these axons cross between the CNS and PNS are known as transition zones ( TZs ) . These specialized structures are recognized by glia , such that oligodendrocytes and Schwann cells , the myelinating glia of the CNS and PNS , respectively , stay segregated at these locations [1]–[4] . However , recent studies have demonstrated that at least some components of the PNS originate from precursors within the spinal cord and can freely pass through these TZs [5] , [6] . These data , taken together with the descriptions of ectopic glial populations in both the CNS and PNS when myelin is disrupted [7]–[12] , led us to hypothesize that there are normally mechanisms in place that selectively monitor the glial boundary between the spinal cord and periphery and are essential for specifically maintaining the strict segregation of myelinating glia observed at these locations . In mammals , neural crest-derived boundary cap cells ( BCCs ) reside at the junction between the CNS and PNS at motor exit points ( MEPs ) and have been shown to restrict motor neurons from migrating into the PNS [9] , [11] , [13] , [14] . However , their role in glial restriction is less understood as oligodendrocytes and astrocytes have been described in the PNS in both their presence and absence , suggesting that these cells may not be the only population responsible for restricting glial migration into the periphery [7] , [10] , [14] . Consistent with this , electron microscopy studies have described the cell populations at the MEP TZ as morphologically distinct from those at the dorsal root ( sensory ) TZ [1] , [15] . Furthermore , elegant neural crest ablation studies in chick have demonstrated that even in the absence of neural crest and all of its derivatives , including BCCs , a population of glial cells is still found along spinal motor nerve roots , demonstrating that they originate from a nonneural crest progenitor [16]–[19] . All of these studies led us to hypothesize that there may be a second glial population associated with spinal motor root axons that is distinct from neural crest-derived BCCs/glia and that it is this population that is responsible for segregating myelinating glia at the MEP . With the goal of determining how myelinating glial segregation is achieved at the MEP during development , we used live imaging in zebrafish to visualize the development of this boundary . Prior to the onset of myelination , we observed oligodendrocyte progenitor cells ( OPCs ) extend membrane processes into the periphery via the MEP . Immediately upon contact with sox10+ glia along spinal motor root axons , these processes retracted back into the spinal cord . Characterization of the cells that OPC processes contacted during these sampling events revealed that they were distinct from neural crest-derived glia , as they originated within the spinal cord and developed normally even in the absence of neural crest . These CNS-derived cells expressed sox10 , olig2 , foxd3 , and wif1 and were distinct from previously described perineurial glia , Schwann cells , OPCs , and BCCs . Specific ablation of these CNS-derived peripheral glia not only eliminated all peripheral myelinating glia along spinal motor roots , but also disrupted the MEP TZ , leading to the ectopic exit of OPCs from the spinal cord . From these data , we conclude that CNS-derived peripheral glia are responsible for restricting OPCs to the spinal cord via contact-mediated inhibition . Together , our studies ( 1 ) identify a novel population of CNS-derived spinal motor nerve-associated myelinating glia that we propose calling MEP glia and ( 2 ) introduce the phenomenon of contact-mediated inhibition between glia across TZs as a mechanism by which the strict segregation of myelinating glia is achieved during development .
The mechanisms that mediate how myelinating glial cells are segregated at the MEP TZ are poorly understood . One possibility is that glial cells on either side of the MEP physically interact during development to establish the tight interdigitated glial boundary that has previously been described [1] , [20] . To test this hypothesis , we sought to investigate if OPC membrane processes contacted peripheral glia during development . In zebrafish , OPCs associate with the central segment of motor axons located inside the spinal cord , whereas peripheral glia are located along the peripheral portion of motor axons after they extend out of the spinal cord ( Figure 1A ) . Using time-lapse imaging in 60 h postfertilization ( hpf ) wild-type Tg ( sox10:eos ) embryos , which have sox10 regulatory sequences driving Eos in both central and peripheral glial cell lineages , we observed short ( ∼9 µm ) sox10+ OPC-membrane processes extend out of the spinal cord via the MEP ( Figure 1B and Video S1 ) . The OPC membrane processes were very transient , and we typically observed them in the periphery for no longer than 10 min ( Figure 1B ) . Orthogonal images ( yz plane ) of these data confirmed that OPC processes physically contacted peripheral spinal motor root sox10+ glia and after contact quickly retracted back into the spinal cord ( Figure S1 ) . Between 54 and 72 hpf , we typically observed OPC peripheral sampling one to two times per nerve ( n = 8 nerves ) . However , after this stage , OPCs began to myelinate spinal cord axons , and we rarely observed membrane processes in the periphery later than 72 hpf ( Figure 1 and Video S1 ) . These data introduce the phenomenon of OPC peripheral sampling and contact-mediated inhibition with peripheral glia , which has previously only been observed between two OPCs within the CNS [21] , [22] . Therefore , we hypothesize that this interaction is fundamental to restricting OPCs to the spinal cord at the MEP TZ . As a first step towards identifying the cells that appear to repel peripherally sampling OPC membrane processes at the MEP TZ , we used in vivo time-lapse imaging to carefully define the glial populations at this boundary . Previous reports in both zebrafish and mouse describe the ventral migration of sox10+ neural crest cells along the lateral edge of the spinal cord during early development [23]–[26] . When we continued imaging between 48 and 72 hpf , after neural crest migration had ceased [26] , we observed a cell in a distinct , more dorsal and medial location from the neural crest initiate expression of sox10 ( Eos ) at 56 hpf , change its morphology to squeeze through the MEP TZ , and migrate ventrally along spinal motor root axons ( Figure S2 ) . When we first visualized this cell , it appeared to be in a position that was consistent with it being inside the spinal cord ( Figure S2 ) . To better determine if this sox10+ cell originated within the spinal cord , we imaged developing motor nerves in laterally mounted Tg ( sox10:eos ) embryos from 48 to 72 hpf and then digitally rotated the images 90 degrees to view the data in transverse cross-section ( Figure 2 ) . Viewing the data in this manner allowed us to see a sox10+ cell located within the ventral spinal cord migrate ventrally towards the MEP , where it altered its morphology to pinch through the TZ ( Figure 2 and Video S2 ) . This morphological change is a behavior we previously observed by perineurial glia and is consistent with the hypothesis that they are exiting the spinal cord [6] , [27] . Between 48 and 72 hpf , we observed sox10+ cells exiting the spinal cord in this manner at 58% of the MEP TZs we imaged . From these data , we hypothesize that after neural crest migration ceases , sox10+ cells within the spinal cord exit the CNS at the MEP and sit immediately adjacent to sox10+ neural crest cells along spinal motor root axons . To determine if the sox10+ cells we observed exiting the spinal cord at the MEP were distinct from previously described neural crest-derived glia and not simply misrouted neural crest cells , we used fate-mapping and neural crest ablation . Using Tg ( sox10:eos ) embryos for fate-mapping [26] , where the mature Eos protein , when exposed to ultraviolet ( UV ) light , shifts its emission from a green fluorescent state ( 516 nm ) to a red fluorescent state ( 581 nm ) [28] , we first exposed the entire animal to UV light at 48 hpf , when neural crest cells were present along the motor nerve but the later born sox10+ cells were not yet visible ( Figure S3A ) . Interestingly , at approximately 56 hpf , we observed a sox10+ cell ( green ) at the MEP ( Video S3 ) . This cell divided and generated unconverted sox10+ cells ( green ) that associated only with motor root axons , and by 72 hpf , nonneural crest-derived sox10+ cells ( green ) were loosely ensheathed around both the dorsal and ventral motor root projections ( Figure 3A and Video S3 ) . Ultimately , by 80 hpf , both motor and sensory axons were ensheathed by sox10+ cells , with developing sensory root axons populated only by previously photoconverted , neural crest-derived sox10+ ( yellow ) cells and motor roots ensheathed solely by unconverted , nonneural crest-derived sox10+ ( green ) cells ( Figure 3A , B and Video S3 ) . We confirmed this spatial and temporal segregation of sox10+ cells along motor versus sensory roots at the MEP using two independent sox10 transgenic lines , Tg ( sox10:megfp ) and Tg ( sox10:mrfp ) [21] , [29] , in combination with the Tg ( neurod:gfp ) [30] and Tg ( olig2:dsred2 ) [6] transgenes , which label sensory and motor axons , respectively ( Figure S4 ) . From these data , we conclude that sox10+ neural crest cells first associate with outgrowing motor axons and then reposition posterior to the spinal motor root , giving rise to the DRG and its associated glia during early development . All spinal motor root-associated sox10+ glial cells then arise from a distinct , later-born , nonneural crest-derived sox10+ progenitor that we hypothesize arises from a precursor in the spinal cord . As an independent confirmation that the cells we observed exiting the spinal cord at the MEP were not neural crest cells , we used laser ablation to remove neural crest cells after their migration had ceased , at 48 hpf , along individual developing spinal motor nerve roots in Tg ( sox10:eos ) embryos that were exposed to UV light immediately prior to ablation . When neural crest-derived cells closest to the MEP were ablated , we observed a sox10+ cell initiate expression in the spinal cord and migrate ventrally out of the spinal cord and associate with a spinal motor root axon ( Figure 3C ) . Interestingly , in these embryos , the DRG never developed , supporting the hypothesis that the neural crest population and the spinal cord population of peripheral sox10+ glia are distinct and cannot compensate for each other . These results are consistent with the hypothesis that the sox10+ glial cell at the MEP is not neural crest-derived . We next reasoned that if sox10+ glia along the motor root were derived from the spinal cord , they would express spinal cord-specific markers . During the course of our imaging , we noticed that the cell that initiates sox10 expression is located in the ventral spinal cord near the MEP ( Figure 2 ) . In this region of the spinal cord , precursors in the gliogenic pMN domain express olig2 and give rise to motor neurons , interneurons , and OPCs [21] , [31]–[33] . Using Tg ( olig2:dsred ) embryos , which have olig2 regulatory sequences driving expression of DsRed in pMN precursors and their descendants [6] , we time-lapse imaged between 48 and 72 hpf . In these studies , we observed olig2+ cells exit the spinal cord at the MEP , divide , and remain associated with spinal motor root axons ( Figure 4A and Video S4 ) . These data are consistent with our hypothesis that sox10+ spinal motor root glia are CNS-derived and confirm our previous data that demonstrate that they are not misrouted neural crest cells . To independently confirm that the sox10+ cells we describe originate from precursors in the CNS , we disrupted the development of specific ventral spinal cord domains and scored the presence of sox10+ glia along motor root axons by labeling sox10+ motor root glia with the photoconversion technique described above ( Figure S3A ) . There are two gliogenic precursor domains in the ventral spinal cord: ( 1 ) the p3 domain , which expresses nkx2 . 2a and gives rise to CNS-derived perineurial glia and V3 interneurons [21] , [32] , and ( 2 ) the pMN domain [31] , [33] . To inhibit a cascade essential for specification of both the p3 and pMN domains , we used cyclopamine ( CA ) , a potent sonic hedgehog ( Shh ) signaling antagonist [6] , [34] . In contrast to control embryos , embryos treated with CA from 8 hpf and imaged at 72 hpf had no motor-associated sox10+ cells , consistent with the hypothesis that spinal motor root glia originate within the ventral spinal cord ( Figure 4C ) . However , a caveat to these studies is that antagonizing Shh affects all cellular components associated with spinal motor nerves , including motor neurons and their associated glia . Therefore , to more specifically perturb individual precursor domains , we injected morpholino oligonucleotides ( MOs ) into single-cell embryos designed to block translation of either nkx2 . 2a or olig2 [6] , [31] , [35] . In nkx2 . 2a MO-injected embryos , we observed sox10+ cells along motor axons at 72 hpf in a pattern indistinguishable from control embryos ( Figure 4B , C ) . These data are consistent with the hypothesis that the sox10+ cells we observed exiting the spinal cord at the MEP were not perineurial glia because they do not require nkx2 . 2a for their development [6] . In contrast , at 72 hpf in olig2 MO-injected embryos , motor root-associated sox10+ cells were absent from 61% of nerves ( Figure 4B , C ) . Taken together , these data are consistent with our previous imaging data and support the hypothesis that sox10+/olig2+ cells originate from olig2+ precursors in the ventral spinal cord and are distinct from nkx2 . 2a+ perineurial glia ( Figure 4D , E ) . Our data demonstrate that the CNS-derived sox10+ glia we observe along spinal motor root axons are distinct from previously described CNS-derived perineurial glia and neural crest-derived cells ( Figures 3 and 4 ) . To rule out the possibility that they are OPCs that have ectopically exited the spinal cord , we assayed whether the cells that exited the spinal cord express foxd3 , a marker that is not expressed by OPCs but is expressed by all known sox10+ peripheral glia [36] . Using Gt ( foxd3:mcherry ) embryos , which have the coding sequence for mCherry inserted into the endogenous foxd3 locus and have been reported to exactly mimic endogenous foxd3 expression , which includes expression in the ventral spinal cord [36] , we imaged Gt ( foxd3:mcherry ) ;Tg ( gfap:egfp ) embryos from 48 to 72 hpf . In these embryos , gfap regulatory sequences label radial glial cells and their endfeet , which are located along the lateral edge of the spinal cord and serve as a landmark for the boundary between the CNS and PNS ( Figure 5 ) [37] . At approximately 56 hpf , foxd3+ cells in the ventral spinal cord migrated towards the MEP , squeezed through the TZ , and continued to migrate into the periphery along spinal motor root axons ( Figure 5 and Video S5 ) . While in the spinal cord , these foxd3+ cells did not display the highly branched filopodial-like morphology that is typical of OPCs ( Figure 5 ) [21] . Based on these molecular and morphological findings , we conclude that the glial cells we observe exiting the CNS originate from the spinal cord as a novel , uncharacterized glial progenitor that expresses foxd3 , sox10 , and olig2 . Therefore , we propose calling them MEP glia to denote their location and distinguish them from neighboring glial populations . To begin to investigate the development of MEP glia , we first determined the developmental timing of foxd3 , sox10 , and olig2 expression using transgenic embryos that expressed [Gt ( foxd3:mcherry ) , Tg ( olig2:dsred ) , and Tg ( sox10:eos ) ] . This analysis revealed that MEP glia express olig2 before they exit the spinal cord and continue to show DsRed fluorescence until approximately 72 hpf ( Figures 4 and 6 ) . mCherry expression from the Gt ( foxd3:mcherry ) transgene was observed as early as 46 hpf before they migrated into the periphery and continued until 8 d postfertilization ( dpf ) when we concluded our imaging ( Figure 6A ) . Lastly , we detected sox10 expression in MEP glia after they initiated expression of both olig2 and foxd3 , at approximately 50 hpf , shortly before they exited the spinal cord . However , this expression was transient , as we only detected eos expression out until approximately 8 dpf ( Figure 6A ) . To gain further insight into MEP glial specification , we investigated if they were generated from the same early ventral spinal cord precursors that generate OPCs . Previous studies have demonstrated that the pMN glial precursors that produce OPCs are dependent on Notch signaling [37] . To test if MEP glia are specified from Notch-dependent pMN precursors , we treated Tg ( sox10:eos ) animals with DAPT at 24 hpf and used the photoconversion paradigm described above at 48 hpf to differentially label MEP glia ( Figure S3A ) . When we imaged these DAPT-treated larvae at 72 hpf , MEP glia were absent from spinal motor roots ( Figure 6B , C , E ) . Treatment with DAPT at 46 hpf also resulted in a significant reduction in the number of MEP glia along motor roots ( Figure 6B , D , E ) . Based on these studies , we hypothesize that MEP glia are generated from the same early spinal cord precursors that develop between 24 and 46 hpf and generate OPCs . Taken together , our data are consistent with the hypothesis that MEP glia are a novel peripheral glial cell population . Therefore , we sought to identify more selective markers to allow for more in-depth characterization . We started by using in situ hybridization to determine if genes that have previously been described as markers of BCCs and/or Schwann cells were expressed by MEP glia . Of the six BCC markers that we tested ( wif1 , cdh7 , krox20 , sema6a , sema6d , sema6dl ) ( Table 1 ) , only one , wnt inhibitory factor 1 ( wif1 ) , showed consistent expression at the MEP ( Figure 6F ) [9] . Prior to 48 hpf , we never detected wif1 expression along the spinal motor nerve root , which is consistent with our previous imaging and fate mapping data describing the development of MEP glia ( Figure 6F ) . However , we did detect expression in previously reported tissues , including the lateral line ( Figure 6F ) . At 48 and 56 hpf , in a pattern that was consistent with the regular spacing of spinal motor nerves , we saw expression along motor root axons ( Figure 6F ) . These temporal expression data are consistent with the hypothesis that wif1 labels MEP glia . To further confirm that wif1 labels MEP glia , we assayed wif1 expression in embryos lacking these cells . As mentioned above , MEP glia are absent in DAPT-treated larvae , and consistent with the hypothesis that wif1 labels MEP glia , we observed significantly reduced wif1 staining at the motor root in these larvae ( Figure 6H ) . As an independent confirmation , we also assayed wif1 expression in genetic mutants that affect MEP glial development . In embryos harboring a mutation in the receptor tyrosine kinase erbb3b , there is a complete absence of sox10+ glia along the spinal motor nerve [38] . Therefore , we hypothesized that MEP glia must be absent . To confirm this , we used the above described photoconversion experiment to demonstrate that MEP glia are absent in Tg ( sox10:eos ) ;erbb3b mutants ( Figure S5A ) . When we assayed for wif1 expression , we also observed a significant reduction of wif1+ cells along the motor root in erbb3b mutants ( Figure 6G ) . Based on the temporal and spatial expression of wif1 and its absence in embryos that lack MEP glia , we propose that wif1 is a promising marker for MEP glia . In summary , we report that MEP glia express the spinal cord precursor marker olig2 , the Schwann cell markers sox10 and foxd3 , and the BCC marker wif1 . Taken together , these data are consistent with the hypothesis that the sox10+ cells we observe exiting the spinal cord at the MEP are distinct from previously described OPCs , Schwann cells , and BCCs ( Table 1 ) . Previously , glial cells along spinal motor root axons were thought to be a homogenous population of neural crest-derived glia [3] , [39] . Our data , however , demonstrate that the motor root is ensheathed by glia that originate from the spinal cord . To characterize MEP glia and investigate the extent of their ensheathment along spinal motor root axons , we used fate-mapping to track MEP glial cell derivatives . To do this , we photoconverted Tg ( sox10:eos ) embryos at 48 hpf as described above and imaged at 80 hpf , once ensheathment of axonal segments had begun . Along the motor root , we observed only MEP glia and their derivatives ( Figure 7A ) . However , further distally along these same axons , we observed neural crest-derived Schwann cells ( Figure 7A ) . These two glial populations seamlessly ensheathed but were distinctly localized , separated only by a node-like gap ( Figure 7A ) . Based on these data , we conclude that MEP glia and their derivatives ensheath only the spinal motor root . We next asked if MEP glial derivatives were a transient population or if they remained along axons past development . To investigate this question , we photoconverted single MEP glial derivatives at the motor root and tracked the location of these single cells over several days . When individual cells were photoconverted at 4 dpf and imaged each day until 8 dpf , they remained in nearly the exact same location for the duration of the study ( Figure 7B ) . We never observed cell death during this temporal window and did not detect any additional cell divisions ( Figure 7 ) . We also did not observe migration beyond what was required to ensheath the motor root ( Figure 7C ) . Based on this evidence , we hypothesize that MEP glia generate cells that permanently ensheath the mature motor root . We next asked if other peripheral glia were competent to ensheath the motor root in the absence of MEP glia . To do this we used a nitrogen-pulsed laser ablation system to specifically ablate these cells [40] after they exited the CNS , but before they divided , and assayed the presence of sox10+ glial cells along motor axons later in development . When the sox10+ cell at the MEP was ablated at 55 hpf and imaged at 76 hpf in Tg ( sox10:eos ) embryos , the majority of motor roots had no sox10+ glia that had a morphology consistent with MEP glia ( Figure 8A , C ) . Sensory glia adjacent to ablated MEPs , however , were unperturbed ( Figure 8A ) . In the reciprocal experiment , when sox10+ neural crest cells were ablated at 48 hpf , CNS-derived sox10+ motor root glia were still present ( Figure 3C ) . Based on these data , we conclude that MEP glia exclusively ensheath the motor root . Our above results demonstrate that the only sox10+ glia that ensheath the root are MEP glia and their derivatives . To determine if they myelinate these spinal motor root axons , we first performed in situ hybridization on 4 dpf larvae with a riboprobe specific for myelin basic protein ( mbp ) . In a pattern consistent with the regular spacing of spinal motor nerves , we detected mbp expression along motor roots at 4 dpf ( Figure 7D ) . Because MEP glia are the only sox10+ cell type found along the spinal motor root , we conclude that MEP glial derivatives myelinate spinal motor root axons . Consistent with this , we did not detect any mbp expression along spinal motor roots in DAPT-treated embryos that lack MEP glia ( Figure 7E ) . To independently confirm these findings , we imaged Gt ( foxd3:mcherry ) ;Tg ( mbp:egfp ) embryos , which use mbp regulatory sequences to drive expression of membrane-tethered EGFP in all myelinating glia in both the CNS and PNS [41] . At 4 dpf , when mbp+ membranes are first seen along spinal motor axons , they are tightly associated with foxd3+ cells along spinal motor root axons ( Figure 7F ) , consistent with the hypothesis that MEP glia myelinate motor axon roots . We then confirmed this cellular arrangement at 5 dpf with an antibody specific to zebrafish MBP ( Figure 7G ) [27] . Taken together , we conclude that MEP glia and their derivatives ensheath and myelinate spinal motor root axons . Our initial observation of OPC peripheral sampling at the MEP led us to hypothesize that PNS-located glia restrict OPCs from exiting the spinal cord . To test if MEP glia were the specific cells that served this repulsive function , we ablated them after they exited the spinal cord ( ∼55 hpf ) , but before they divided , and then time-lapse imaged embryos for 24 h . In these experiments , we used the photoconversion technique we describe above to specifically label the MEP glia for ablation with the nitrogen-pulsed laser . In embryos where MEP glia had been ablated , sox10+ cells with morphology identical to OPCs exited the spinal cord ( Figure 8B , C and Video S6 ) . We confirmed that the sox10+ cells that migrated into the PNS were OPCs by ablating the MEP glia in Tg ( olig2:dsred ) ;Tg ( sox10:eos ) embryos [21] , [27] . These results support the hypothesis that the strict segregation of myelinating glia at the MEP TZ is achieved by contact-mediated inhibition between OPCs and MEP glia . To complement these laser-ablation experiments , we investigated if OPCs exited the CNS in erbb3b mutant embryos [25] , [38] , which lack MEP glia ( Figure 6G ) . We acknowledge that these mutants also lack neural crest-derived glial cells [25] . However , our laser-ablation results demonstrate that the neural crest-derived population of glial cells is not required to restrict OPCs to the spinal cord , as we never observed ectopic OPCs in the periphery when we specifically ablated neural crest-derived glia ( Figure 3C ) . Consistent with our previous results , in Tg ( nkx2 . 2a:megfp ) ;Tg ( sox10:mrfp ) ;erbb3b homozygous mutant embryos , we observed GFP+/RFP+ OPCs in the periphery ( Figure 8D ) . Based on these two complementary approaches , we conclude that MEP glia are required to restrict OPCs to the spinal cord . To further this analysis and investigate the long-term consequence of MEP glial ablation , we analyzed the motor root in erbb3b mutants later in larval development . First , we examined if ectopically located OPCs along the motor root myelinated peripheral motor axons . To do this , we used time-lapse imaging to characterize their behavior in Tg ( nkx2 . 2a:megfp ) ;Tg ( sox10:mrfp ) ;erbb3b homozygous mutants . These experiments showed that PNS-located OPCs transitioned from an exploratory behavior to a more static and less dynamic behavior by 75 hpf , consistent with their ensheathing activities ( Figure S5B ) [21] . To determine if they also myelinated motor axons , we labeled erbb3b homozygous mutants with an antibody to MBP . At 8 dpf , we observed significant MBP staining along motor root axons ( Figure 8E ) . Because these mutants lack MEP glial derivatives and Schwann cells , any MBP staining along the motor nerve must be generated from ectopic OPCs [25] , [38] . To determine if they maintain the ability to produce CNS myelin in the periphery , we assayed for expression of plp1a , a component of CNS myelin . At 4 dpf in erbb3b mutant larvae , we observed ectopically located plp1a+ cells in the periphery via in situ hybridization ( Figure 8F ) . We did not observe this staining in wild-type control animals ( Figure 8F ) . We also did not observe any axonal debris or defasciculation at the motor root of these animals , which has previously been described [38] . We therefore propose that in the absence of MEP glia , OPCs ectopically myelinate the peripheral motor root with central myelin without causing any obvious axonal or neuronal phenotypes . Our data demonstrate that MEP glia physically repel OPC processes and we hypothesized that this contact-mediated inhibition is what establishes the strict segregation of myelinating glia at the MEP TZ . If this hypothesis is correct , then we reasoned that OPCs would sample the periphery for longer periods if they did not encounter MEP glia at the TZ . To test this hypothesis , we time-lapse imaged embryos in which we ablated the MEP glial cell derivatives closest to the TZ and assayed the behavior of OPC processes that extended into the periphery . Along motor nerves where the CNS-derived sox10+ glial cell closest to the MEP was ablated at 56 hpf , but its descendants further distal along on the nerve were intact , we observed OPC processes in the periphery for longer than 60 min ( Figure 9A , B ) . These processes broadly surveyed the PNS and extended as far as the horizontal myoseptum ( Figure 9A ) . We also noticed in ablated animals that OPCs frequently contacted neural crest-derived sensory glia ( Movie S6 ) . However , this contact did not result in retraction back into the spinal cord ( Movie S6 ) . Additionally , if the MEP glial derivatives prevented OPC migration by simply providing a physical barrier , then once OPC processes sampled the periphery in its absence , OPC cell bodies should migrate into the periphery . However , we observed OPC processes retracting back into the spinal cord only after they contacted MEP glial derivatives at the horizontal myoseptum ( Figure 9A ) , suggesting that OPC peripheral migration is not solely inhibited by a physical barrier , but more likely repelled by a contact-mediated inhibition signal provided by CNS-derived MEP glial derivatives . Based on these data , we conclude that CNS-derived MEP glia and their descendants are essential for establishing and maintaining myelinating glial segregation at the MEP TZ through contact-mediated inhibition .
Although initially surprising , this feature has been observed in nonvertebrates like Drosophila , where ensheathing glia along motor axons originate inside the ventral nerve cord and migrate into the periphery [43] . Similarly , in zebrafish and mice , perineurial glia migrate from the floor plate to the MEP , where they pinch through the TZ and exit the spinal cord to ensheath motor nerves and ultimately form the mature perineurium [6] , [44] . Our time-lapse imaging supports the hypothesis that MEP glia also originate within the spinal cord . Using multiple transgenic lines to label these cells and the border of the spinal cord , we show that foxd3+/olig2+/sox10+ cells migrate through the MEP TZ and associate with spinal motor root axons . We acknowledge that our MO experiments do not distinguish between the two models in that these cells are generated from the olig2+ domain versus that their development requires other cells that are impacted by perturbation of olig2 . However , because the MEP glia migrate from a region close to the pMN and express olig2 , we believe there is a strong possibility they are generated from pMN domain precursors . The absence of MEP glia in DAPT-treated animals further endorses this possibility . We believe this cell has been missed in previous studies because it expresses multiple neural crest markers ( e . g . , sox10; foxd3 ) and because mutants that disrupt neural crest association with the nerve also impact the development of this cell ( e . g . , erbb3 , erbb2 , mont blanc;mother superior ) [25] , [27] . Because of these previously published results , we considered the possibility that the cell was a misrouted neural crest cell but believe our experiments strongly rule out this possibility . First , the transgenes we use to label neural crest [e . g . , Tg ( sox10:eos ) , Gt ( foxd3:mcherry ) ] have been well characterized to label all neural crest cells , and therefore , it is unlikely that MEP glia are nonlabeled neural crest cells that turn on sox10+/foxd3+ in the spinal cord [26] , [36] . A second possibility is that MEP glia are generated from a neural crest cell that migrates into the spinal cord as a sox10+/foxd3+ cell , turns off this expression , and then reinitiates sox10 and foxd3 expression before it migrates out of the spinal cord . Given that the Eos protein perdures for longer than 24 h in our experiments , this possibility seems unlikely . In summary , we show that MEP glia express a cocktail of glial progenitor markers ( e . g . , foxd3 , sox10 , olig2 , wif1 ) that have not previously been described in the same glial cell . We therefore named these glia based on their morphological and positional association with the MEP . In elegant experiments in which the entire neural crest was removed from chick embryos , ensheathing cells still developed along spinal motor axons in chick [16]–[18] . These ensheathing cells were hypothesized to be derived from the spinal cord and remained at the motor root even in the absence of neural crest [16]–[18] . These results are consistent with our data that show MEP glia ensheath motor root axons even after neural crest ablation ( Figure 3 ) . In rodents , studies have described morphologically distinct glial cells at the MEP and dorsal root TZ , suggesting that more than one cell type may be present at the TZ [1] , [15] . Additionally , in a rodent model of remyelination , Olig2+ progenitors in the spinal cord can produce peripheral glial subtypes [45] . Although this remyelination study did not demonstrate that the Olig2-derived cells exit the spinal cord , their presence is consistent with the possibility that they may also exist during earlier stages of development . Future studies exploring this possibility are needed to definitively determine whether MEP glia are present in other vertebrates . However , given our data and the evidence previously described in chick , we hypothesize this is a strong possibility . In vertebrates , glial cells at the spinal cord TZs are important to maintain CNS/PNS cellular segregation [10] . However , it is not clear how these cells communicate across the TZ given that they are largely segregated to their specific domains . We show here using in vivo time-lapse imaging in zebrafish that OPCs communicate with peripheral glial cells by extending thin , dynamic processes into the PNS , a phenomenon that would have been nearly impossible to observe in any other model organism . These OPC processes , however , retract when they contact MEP glia . We believe this heterotypic repulsion event between OPCs and MEP glia mediates the tight glial boundary at the MEP and is consistent with EM analysis of the myelin interphase at spinal cord TZs . Contact-mediated repulsion of glial membrane has been visualized in the CNS between two OPCs [21] , [22] and this homotypic repulsion ensures that oligodendrocytes nonredundantly ensheath spinal cord axons [21] . We report here that repulsion can also occur between distinct classes of glia across the MEP TZ . The common origin of these cells and shared molecular characteristics may suggest a similar mechanism of repulsion is activated in both homotypic and heterotypic retraction and future studies investigating the nature of these interactions are required to understand the underlying molecular mechanisms of these two contact-mediated inhibition types . Together our results indicate that glial cells found on the peripheral side of the MEP originate in the CNS , ensheath spinal motor root axons , and are essential to maintain the basic architecture of the nervous system by restricting OPCs to the spinal cord .
All animal studies were approved by The University of Virginia Institutional Animal Care and Use Committee ( Protocol No . 3782 ) . Zebrafish embryos and larvae were anesthetized using Tricaine , also known as Mesab or MS-222 ( 3-aminobenzoic acid ester ) . Euthanasia used an overdose of Tricaine . The following zebrafish strains were used in this study: AB* , Tg ( neurod:egfp ) nl1 [28] , Tg ( olig2:dsred2 ) vu19 [6] , Tg ( sox10 ( 7 . 2 ) :megfp ) , Tg ( sox10 ( 7 . 2 ) :mrfp ) vu234 [6] , [21] , Tg ( nkx2 . 2a:megfp ) vu17 [21] , Tg ( sox10 ( 4 . 9 ) :eos ) , Tg ( sox10 ( 4 . 9 ) :nls-eos ) [26] , Tg ( Xla . Tubb:DsRed ) [46] , Gt ( foxd3-mcherry ) ct110aR [36] , Tg ( neurog1:gfp ) w61 , Tg ( gfap:egfp ) [47] , Tg ( mbp:egfp-caax ) [41] , and erbb2bst61 and erbb3bst48 [38] . Abbreviations used for each line are denoted in Table S1 . Embryos were produced by pairwise matings , raised at 28 . 5°C in egg water , and staged by hpf and dpf [48] . Embryos used for immunohistochemistry and live imaging were treated with 0 . 004% phenylthiourea ( PTU ) in egg water to reduce pigmentation . All lines used were stable , germline transgenics . All animals for imaging were manually dechorinated at 24 hpf and treated with PTU as described above . At specified stages , embryos were anesthetized with 3-aminobenzoic acid ester ( Tricaine ) , immersed in 0 . 8% low-melting point agarose , and mounted on their sides in glass-bottomed 35 mm Petri dishes ( Electron Microscopy Sciences ) . Images were captured with a 25× multi-immersion objection ( numerical aperture = 0 . 8 ) , a 40× water objective ( numerical aperture = 1 . 1 ) , or a 63× water objective ( numerical aperture = 1 . 2 ) mounted on a motorized Zeiss AxioObserver ZI microscope equipped with a Quorum WaveFX-XI spinning disc confocal system ( Quorum Technologies Inc . ) . Z-stacks were collected that covered the span of the nerves . Three-dimensional and single-plane datasets were processed in MetaMorph . Supporting videos were annotated and created using ImageJ . Cell tracking annotation was done with the MTrackJ plugin . Photoshop was used to enhance brightness and contrast of images . Animals were treated with PTU and mounted for in vivo imaging as described above . To photoconvert all Tg ( sox10:eos ) cells , embryos were exposed to UV light through a DAPI filter for 20–30 s using a 20× objective . For single-cell photoconversion , a MicroPoint laser with LD390/Stillbeme 420 ( 404 nm ) dye was used . Embryos were treated with 50 µM CA diluted in egg water at 8 hpf . Zebrafish embryos were treated with 100 µM DAPT [565784; N- ( 3 , 5–difluorphenyl-L-alanyl-2-phenyl glycine-1 , 1-dimethethyl ) ester; EMD Chemicals] diluted in 1% DMSO in PTU egg water at the designated time . Control embryos were placed in 1% DMSO in egg water . nkx2 . 2a MO and olig2 MO were diluted from a stock solution of 3 mM , diluted in 2× injection buffer to create a working concentration of 0 . 5 mM , and injected into single-cell embryos . All MO-injected and drug-treated animals were mounted as discussed above for live imaging . Fifty nerves in five different embryos were scored for each condition of CA , wild-type , and nkx2 . 2a MO-injected and 88 nerves in 10 different animals were scored in olig2 MO-injected embryos . Animals were fixed with AB fix [4% Paraformaldehyde and 1×PBST ( 1% TritonX ) ] for 3 h at 23°C and then washed in 1×PBST ( 5% TritonX ) , ddH20Tx ( 5% TritonX ) , and acetone for 5 min each at 23°C and then an additional acetone wash at −20°C . 1×PBST ( 5% TritonX ) with 5% goat serum was used to block for at least an hour . Animals were incubated in primary antibody overnight at 4°C . The primary antibodies used in this study include the following: Sox10 , 1∶5 , 000 [49]; Acetylated Tubulin , 1∶10 , 000 ( Sigma ) ; HuC , 1∶100 ( Invitrogen ) ; MBP , 1∶250 [27] . Animals were washed extensively with 1×PBSTx before the secondary antibody was added . These antibodies include Alexa antibodies ( 1∶600 ) : goat anti-rabbit 568 , goat anti-mouse 568 , goat anti-rabbit 647 , and goat anti-mouse 647 . After extensive washes , animals were stored in 50% glycerol/50% 1×PBS until imaged and mounted under a bridged coverslip . Larvae were fixed in 4% paraformaldehyde for 24 h , stored in 100% methanol at −20°C , and processed for in situ RNA hybridization . Plasmids were linearized with appropriate restriction enzymes and cRNA preparation was performed using Roche DIG labeling reagents and the appropriate RNA polymerase . After in situ hybridization , embryos were either imaged whole mount or embedded in 1 . 5% agar/30% sucrose and frozen in 2-methylbutane chilled by immersion in liquid nitrogen . Transverse sections ( 20 µm ) were collected on microscope slides using a cryostat microtome and covered with 75% glycerol . Images were obtained using a Zeiss AxioCam CCD camera mounted on a Zeiss AxioObserver Z1 microscope equipped with Zeiss AxioVision software . All images were imported into Adobe Photoshop . Adjustments were limited to levels , contrast , color match settings , and cropping . Single-cell ablations were done with a MicroPoint Laser in conjunction with a coumarin dye ( 440 nm ) with a 63× objective . Once a pre-ablation image was captured , a region of interest ( ROI ) was created based off of the merged-color image to specifically ablate cells . As a control for the ablation , regions surrounding the experimental ROI were ablated , including anterior to the nerve , posterior to the nerve , and dorsal to the MEP . In all control paradigms , OPCs did not exit the spinal cord . To count cells in experimental and control larvae , composite Z image stacks were compiled using Metamorph software . Cell counts were taken from lateral views of the spinal cord . Individual Z images were sequentially observed and cells counted within the entire Z stack . All graphically presented data represent the mean of the analyzed data . Statistical analyses were performed with GraphPad Prism software . The level of significance was determined by using a Chi-squared two-tailed test using a confidence interval of 95% . | The nervous system is often thought as two distinct halves: the central nervous system ( CNS ) , which consists of the brain and spinal cord , and the peripheral nervous system ( PNS ) , which includes the nerves that control movement and sense the environment . The cells within these two halves , however , do not commonly mix . To address how cells are segregated within these two compartments of the nervous system , we used live , transgenic zebrafish embryos to watch nerve development . Our study shows that CNS-residing myelinating glia ( nonneuronal cells that wrap around nerves to ensure nerve impulse conduction ) are restricted from entering the PNS by a cell we call motor exit point ( MEP ) glia . MEP glia originate from within the CNS , and then migrate into the PNS , divide , and produce cells that ensheath and myelinate spinal motor root axons . Ablation of MEP glia causes CNS glia to migrate inappropriately into the PNS , disrupting the normal boundary that is present between the CNS and PNS . Overall , the identification and characterization of MEP glia identifies an aspect of peripheral nerve composition that may be pertinent in human health and disease . | [
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"... | 2014 | Contact-Mediated Inhibition Between Oligodendrocyte Progenitor Cells and Motor Exit Point Glia Establishes the Spinal Cord Transition Zone |
PML is a progressive and mostly fatal demyelinating disease caused by JC virus infection and destruction of infected oligodendrocytes in multiple brain foci of susceptible individuals . While JC virus is highly prevalent in the human population , PML is a rare disease that exclusively afflicts only a small percentage of immunocompromised individuals including those affected by HIV ( AIDS ) or immunosuppressive drugs . Viral- and/or host-specific factors , and not simply immune status , must be at play to account for the very large discrepancy between viral prevalence and low disease incidence . Here , we show that several amino acids on the surface of the JC virus capsid protein VP1 display accelerated evolution in viral sequences isolated from PML patients but not in sequences isolated from healthy subjects . We provide strong evidence that at least some of these mutations are involved in binding of sialic acid , a known receptor for the JC virus . Using statistical methods of molecular evolution , we performed a comprehensive analysis of JC virus VP1 sequences isolated from 55 PML patients and 253 sequences isolated from the urine of healthy individuals and found that a subset of amino acids found exclusively among PML VP1 sequences is acquired via adaptive evolution . By modeling of the 3-D structure of the JC virus capsid , we showed that these residues are located within the sialic acid binding site , a JC virus receptor for cell infection . Finally , we go on to demonstrate the involvement of some of these sites in receptor binding by demonstrating a profound reduction in hemagglutination properties of viral-like particles made of the VP1 protein carrying these mutations . Collectively , these results suggest that a more virulent PML causing phenotype of JC virus is acquired via adaptive evolution that changes viral specificity for its cellular receptor ( s ) .
JC virus ( JCV ) is highly prevalent in the human population with over 70% of people showing anti-JCV antibody responses and up to 40% of the population displaying persistent viral shedding in the urine ( reviewed in [1] ) . These epidemiological data indicate that the virus establishes chronic infection in a large fraction of the human population . Though normally asymptomatic , factors leading to immune deficiency , such as HIV or immunosuppressive drug therapy , can trigger an uncontrolled infection and replication of JCV in oligodendrocytes causing their death and resulting in progressive multifocal leukoencephalopathy ( PML ) . Despite such a high infection rate and viral occurrence , JC virus causes PML in a very small fraction of immune deficient patients , including 4–5% of AIDS patients [2] and less than 1% of patients with lymphoproliferative diseases [3] . No pharmaceutical treatment option for PML currently exists and the only chance for patient survival is afforded by reconstitution of the patient's own immune response via HAART in AIDS or via drug tapering in pharmaceutically immunocompromised individuals . Identification of genetic and environmental risk factors influencing the development of PML is of great importance both for finding of therapeutic interventions and for the development of early diagnostic methods to help reducing the risks associated with immunosuppressive therapies . Both host and viral genetics may contribute to PML . Earlier studies focusing on viral genetic factors identified duplications and rearrangements in the regulatory region of the viral genome [4]–[8] . Several studies also reported presence of several mutations in VP1 protein in the JC virus isolated from PML patients [8]–[10] . No comprehensive analysis of an association of changes in protein coding genes of JC virus with PML has been reported . Pathogenicity of viruses ranging from influenza virus [11] , [12] to the mouse polyomavirus [13] , [14] , a close relative of human JCV , was shown to be determined by amino acid sequences involved in the binding of a viral capsid protein to sialylated glycan receptors . Changes in the affinity and specificity of the virus for its cellular receptor ( s ) affect viral infectivity and transmission , hence playing a crucial role in virulence . For example , a study of the mouse polyomavirus showed that VP1 amino acid changes rather than changes in the non-coding regulatory region are responsible for the increased pathogenicity of the virus [15] , [16] . Consequently , we focused on VP1 protein and its relationship to PML . We relied on methods of molecular evolution to determine the presence of putative adaptive changes in the VP1 amino acid sequence associated with PML . The advantage of this approach over simple statistical association of sequence variants with the disease , is that it takes into account the phylogenetic relationship of viral strains and also allows identification of functionally significant amino acid positions by examining the rate of sequence evolution .
JCV VP1 gene sequences were downloaded from GenBank ( Table S1 ) and used to construct a phylogenetic tree for a random subset of sequences isolated from healthy individual and full-length sequences isolated from distinct PML patients ( Figure 1A ) . We used the PhyML maximum likelihood method [17] with F84 substitution model [18] , [19] . Application of several methods incorporated in the PHYLIP package such as maximum likelihood method , distance-based and parsimony-based methods of phylogenetic reconstruction produced similar results . Viral sequences isolated from PML patients do not cluster on the phylogenetic tree and are broadly distributed among viral types and geographic origins of the samples ( Figure 1A ) . This is further supported by the Slatkin-Maddison test for group separation ( p = 0 . 38 ) [20] . In agreement with earlier studies [8] , [21] , [22] , PML causing viruses are not limited to a specific viral phylogenetic type . Next , we analyzed sequences from viruses isolated from PML patients as well as those from healthy subjects with the goal of determining whether PML associated evolutionary selective pressure is acting on the viral VP1 gene . This analysis utilized the PAML package [23] designed to identify the presence of codons evolving under positive selection . PAML evaluates multiple evolutionary models using the parametric likelihood ratio test . We tested several models including a model of neutral evolution , a nearly neutral model allowing for purifying ( i . e . negative ) selection , and a heterogeneous model that allows some codon positions to evolve under positive selection and other codon positions to evolve under negative selection or neutrally ( Table 1 ) . We also tested a number of more complex models . In the case of VP1 sequences from JCV isolated from healthy subjects , the nearly neutral evolutionary model involving a mixture of neutrally evolving codons and codons under purifying selection clearly outperformed the purely neutral model ( p-value 7 . 0×10−6 ) . However , no statistical support was found for more complex models including models with positive selection . In contrast , for VP1 sequences isolated from PML patients , allowing codons to evolve under positive selection resulted in a highly significant increase in the model likelihood ( Table 1 ) . The model with three categories of sites including sites evolving under purifying selection , neutral sites and sites under positive selection explained the data significantly better than the nearly neutral model limited only to neutral sites and the sites under purifying selection ( p-value 2 . 5×10−7 ) . More complex models did not show significant improvement over the simplest model with three categories of codons . Four codon positions ( corresponding to amino acids 55 , 60 , 267 and 269 ) were identified as evolving under positive selection in the PML sampling of full length sequences ( Table 1 ) . Bayesian posterior probabilities for positive selection computed by PAML were above 0 . 5 for these codon positions . The posterior probability for positive selection in codon 269 was close to 1 . To increase the power of analysis , we added partial VP1 sequences from JC virus isolated from PML patients . The addition of partial sequences revealed signal of positive selection in codon 265 ( Table 1 ) . Interestingly , we never observed two VP1 mutations in the same JCV isolate . Analysis by the Spidermonkey [24] method revealed epistatic interactions between positions 55 and 269 and between position 60 and 269 ( with posterior probabilities 0 . 88 and 0 . 70 respectively ) . This may reflect “diminishing return” epistatic interactions , i . e . subsequent mutations are not beneficial and possibly detrimental on the background of a single mutation . All substitutions in these five codons are clearly associated with PML . At least 52% of JC viruses ( or 36 out of 69 sequences , including partial sequences ) isolated from PML patients have at least one of these mutations , whereas none of these substitutions have been observed in 253 full length viral sequences from healthy subjects ( Table S2 ) . The strongest signal of positive selection in the PML sample was detected for the codon encoding amino acid at position 269 . Figure 1B shows that multiple independent mutations of Ser269 to aromatic residues phenylalanine and tyrosine were observed in VP1 from PML associated viruses . The existence of multiple independent mutations is not an artifact of phylogenetic reconstruction because lineages with mutant variants are separated by multiple branches with over 90% support by bootstrap analysis and support of the likelihood ratio test implemented in PhyML [17] . These lineages correspond to different , previously identified , phylogenetic types of JC virus and are from diverse geographic locations [21] , [22] . To get an insight into a functional role of the five identified amino acid positions , we constructed a three-dimensional molecular model of the JC virus VP1 bound to NeuNAc– ( α2 , 3 ) –Gal– ( β1 , 3 ) –[ ( α2 , 6 ) -NeuNAc]–Glc-NAc tetrasaccharide based on the crystal structure of MPyV VP1/oligosaccharide complex [25] . The structural model shown in Figure 2A suggests that all PAML-identified amino acids are clustered on the surface of the VP1 protein at the sialic acid binding site and are likely to be involved in sialic acid binding . Additionally , we predicted that L55F , K60M , S267F , and S269F substitutions may induce steric clashes with the modeled saccharide leading to a decrease in the affinity of the interaction . Affinity to sialic acid was related to viral pathogenicity in multiple studies of flu virus , mouse polyomavirus , and mouse minute virus [11]–[14] , [26] . Particularly , pathogenicity of mouse polyomavirus , a close relative of the JC virus , was mapped to a VP1 amino acid substitution at position 296 [13] , a position orthologous to position 269 in human JC virus that showed the strongest signal of positive selection in PML-causing viral isolates in our study . As shown in Figure 2B , serine 269 of the human JC virus and valine 296 of the mouse polyomavirus occupy identical locations in the sialic acid binding pocket . We note that positions 61 , 66 , 123 , 129 , 223 and 271 are all limited to the PML sample ( Table S2 ) and also line up with the sialic acid binding pocket ( Figure 2B ) . It is possible that those residues went undetected by the PAML analysis due to the small sample size and that the development of PML is accompanied by positive selection for amino acids involved in sialic acid binding in a majority of cases . The length of the phylogenetic tree in our analysis is short thus limiting power to detect positive selection [27] , [28] . Likelihood ratio test for detecting positive selection using a short tree is conservative [27] , and Bayes Empirical Bayes analysis is of limited power [28] . Thus , additional PML-specific VP1 mutations can also be positive selected . Mutations at residue 107 are also found exclusively in the PML sample . However , it did not show evidence of positive selection according to PAML and is not located in the sialic acid binding pocket . In order to experimentally verify the role that these substitutions play in sialic acid binding by the VP1 capsid , we recombinantly produced viral like particles ( VLP ) from VP1 protein encoded by several different naturally occurring viruses . We generated VLPs from viral VP1 sequences encoding substitutions with one of the two strongest signals of positive selection identified by PAML , one with phenylalanine at position 269 ( F269 ) and another one with phenylalanine at position 55 ( F55 ) . As controls we used two different VP1 genes that do not harbor any of the identified PML-associated mutations , one from a healthy individual ( WT ) and another one from a PML patient ( Mad-1 ) ( Table S3 ) . Viral hemagglutination of red blood cells ( RBCs ) has been shown to be a reliable measure of sialic acid binding by polyomaviruses [16] , [29] . We tested all four VLPs in a hemagglutination assay . Strikingly , both F55 and F269 variants displayed more than 8000-fold lower HA activity than either control VLP ( Table 2 ) . Specifically , the F55 variant completely failed to agglutinate human type O RBCs even at 200 µg/ml , the highest concentration tested , and the F269 variant displayed very low HA activity as it caused hemagglutination only at concentrations above 25 µg/ml . At the same time both L55 and S269 carrying variants ( WT and Mad-1 ) caused hemagglutination of RBCs at concentrations down to 0 . 375 ng/ml and 6 . 25 ng/ml , correspondingly . We note that the F55 mutant has the single amino acid difference with its corresponding wild type variant ( WT ) . Therefore the change in hemagglutination can be specifically attributed to this amino acid replacement . In addition to the change in position 269 the F269 mutant variant has two additional amino acid positions that are different from its corresponding control variant ( Mad-1 ) . Both of those amino acid changes are not PML specific ( Table S3 and Table S2 ) and are unlikely to explain the difference in hemagglutination . While the Mad-1 isolate had originated from a PML patient [30] it does not contain any of the PML-specific mutation which correlates well with its ability to hemagglutinate RBCs . The lack of PML-genic mutations in this PML isolate suggests that VP1 mutations are not an exclusive mechanism leading to PML development . Although we do not know at the moment how these amino acid substitutions affect viral infectivity per se , it is reasonable to assume that a virus harboring such substitutions is adequately infectious as it was sufficiently abundant in the CNS of PML patients to be isolated . Therefore , it is tempting to speculate that changes in glycan specificity would allow JCV to loose its specificity to sialated glycans expressed outside of the CNS ( e . g . RBCs ) . Thus , such a virus would avoid getting trapped on “pseudoreceptors” in the periphery and travel unhindered from sites of viral shedding to enter the brain . Mutated virus must still maintain its specificity to glycans expressed on oligodendrocytes . This would be consistent with the observation from the mouse polyomavirus model where a mutation in a position orthologous to position 269 of JCV affected viral ability to bind RBCs and also lead to the dramatic increase in viral dissemination through the animal with a lethal outcome [15] , [16] . Furthermore , there are several reports of JCV detection in tonsils of many asymptomatically infected individuals [31] , [32] . Although this observation was taken as a support for the JCV infection of tonsil cells , it could be alternatively explained by the viral trapping in lymphoid tissues . That would be consistent with JCV binding to sialic acid in the tonsil tissue [33] . An alternative but not mutually exclusive hypothesis would be that PML associated VP1 mutations increase JCV tropism for brain white matter cells leading to the increased viral infectivity and replication in oligodendrocytes . Finally , another non-mutually exclusive explanation of the role these mutations in PML might be immune-escape by the virus . It is theoretically possible that out of the polyclonal immune response directed against the VP1 molecule only a limited number of antibodies directed against the cell receptor binding site ( i . e . sialic acid ) would provide protection against the spread of the viral infection . Mutation of an amino acid within an epitope crucial for the protective immunity could allow virus to bind to its target cells and spread uninhibited . Given the large number of mutations that are specific for PML it is likely that not a single mechanism but rather a multiplicity plays a role in PML etiology in different PML cases . How do these mutations occur in PML and why , despite a very high prevalence of JCV , do only a small proportion of immune deficient patients develop PML ? Absence of clustering of the mutations on the viral phylogenetic tree suggests that they arise independently in individual patients rather than persist in the general populations as pathogenic viral variants . It is worth noting that this hypothesis appears to be strongly supported by the original observation of Loeber and Dorries [6] where the investigators reported the isolation of two viral strains from kidney and brain of the same PML patient . The genome of the virus isolated from the brain was almost identical to that isolated from the kidney with two exceptions; presence of phenylalanine instead of leucine in position 55 and a rearrangement of the regulatory region . Previously no significance could be attached to the L55F mutation and that observation led to the generation of the hypothesis on the sole importance of viral control region rearrangement in “PML-genic” adaptation of the virus . Based on our findings we would like to propose that VP1 mutations play a very significant role in the mechanism of PML emergence . Once a specific mutation affecting sialic acid binding occurs it allows virus to spread to the brain and infect oligodendrocytes . The fact that the mutant virus was not detected in the kidney [6] may suggest that that particular change in glycan binding does not offer any selective advantage to the mutated virus in kidney . The mutations might have occurred and hence allowed the virus to establish the residence in the brain under the conditions of immune suppression shortly or long before the PML . Since no viral replication was detected in brains of asymptomatic individuals we believe it is unlikely that compartmentalized evolution ( i . e . intra CNS ) prior to PML development could account for the presence of mutated VP1 in CNS of PML patients . However , the issue of JCV latency in normal brain still remains controversial so it is still formally possible that non-mutated virus had entered the brain and mutations arose in the brain and not periphery , e . g . kidney . It appears that the healthy immune system effectively controls viral activation in the brain . However , as soon as the immune system fails in the misfortunate individual harboring such a mutated virus , the virus begins actively proliferating in oligodendrocytes causing PML . It is also possible that a healthy immune system efficiently suppresses newly developed mutants in their peripheral site ( e . g . kidney ) and prevents them from spreading and infecting new target cells . Thus the timing of PML development may be mutation limited and the interplay with environmental or host genetic factors contributed to the non-deterministic development of PML . Alternatively , PML development may be controlled by interactions of VP1 mutations with additional genetic alterations of the virus including rearrangement of the viral regulatory region as it might give the virus additional selective advantage in increasing viral replication in oligodendrocytes . Altogether our findings suggest that JCV VP1 mutations affecting its receptor specificity may be responsible for PML pathology . These results pave the way for the discovery of novel anti-polyomavirus therapeutics and diagnostics of diseases caused by these viruses . The exact role that these mutations play in etiology of PML as well as how and where they arise requires further extensive investigation that would involve VP1 sequence analysis of longitudinal and time matching samples from different organs ( e . g . urine , blood , CSF ) and from a variety of PML patients .
35 full length VP1 sequences of JC viruses isolated from PML patients and 253 full length VP1 sequences of JC viruses isolated from healthy subjects were downloaded from Genbank . In addition , 20 partial VP1 sequences were available from Genbank enabling the analysis of the total of 55 sequences for positions 43–287 . In addition to these 55 VP1 sequences isolated from PML patients Table S1 also contains information from twelve more partial sequences available from a publication by Sala et al . [34] . We note that all viral samples isolated from PML patients originated from brain or CSF tissues except one sample isolated from kidney ( Table S1 ) . All viral samples isolated from healthy subjects originated from urine . Multiple sequence alignments were constructed using TCoffee [35] . A number of PML sequences were isolated from the same individual . Since we were studying evolution of viral sequences we accepted same patient isolated sequences for our analysis as long as they differed from each other by ≥1 nucleotide . However , we excluded identical “clonal” sequences from our analysis . This resulted in the final set of 28 full-length VP1 sequences and 42 partial VP1 sequences isolated from PML patients . All information on the origin and clonality of sequences is contained in Table S1 . Phylogenetic trees were built using the PhyML maximum likelihood method [17] with F84 substitution model [18] , [19] and using several methods included in the PHYLIP package ( Felsenstein , J . 2005 . PHYLIP version 3 . 6 . Distributed by the author . Department of Genome Sciences , University of Washington , Seattle ) . VP1 sequences isolated from PML patients and random subsets of sequences isolated from healthy subjects were further analyzed using PAML [23] . We examined multiple models of sequence evolution ( M0–M8 ) . We used likelihood ratio test for difference between models M1 and M2 to test for positive selection . Residues with Bayes Empirical Bayes posterior probabilities exceeding 0 . 5 in the analysis of either full-length or partial set are reported in Table 1 . We used Spidermonkey [24] to analyze epistatic interaction . Spidermonkey was run through the Datamonkey web server [36] . Slatkin-Maddison test was used to evaluate separation of PML-casing JC viruses and JC viruses isolated from healthy subjects [20] . We used HyPhy package to compute the Slatkin-Maddison test [37] . The significance of group separation was determined using the permutation test ( 1000 permutations ) . Hemagglutination assay was performed as previously described [38] , [39] . Briefly , human type O blood was washed twice and suspended in Alsever's buffer ( 20 mM sodium citrate , 72 mM NaCl , 100 mM glucose , pH 6 . 5 adjusted with acetic acid ) at a final concentration of ∼0 . 5% . Serial two-fold dilutions of VLPs were prepared in Alsever's buffer and an equal volume of RBCs was added into each well of a 96-well “U” bottom microtiter plate and incubated at 4°C for 3–6 hr . Minimum HA concentration is the lowest concentration of VLP protein that still agglutinated RBCs . Genes encoding the VP1protein from JC virus strains BAE00117 , AAT09831 and AAQ88264 were created synthetically and cloned into the Gateway pDEST8 ( Invitrogen ) shuttle vector for transfer into the pFASTBAC baculovirus expression system for baculovirus expression in SF9 cells . Purification of VLPs was performed from roughly 100 grams of frozen cell pellets from 5 liters of culture . Cells were resuspended in 500 ml of PBS containing 0 . 1 mM CaCl2 . The cells are disrupted by passing the cell suspension twice through a Microfuidics Microfluidizer . Cell debris was removed by pelleting at 8000×G for 15 minutes . The supernatant volume was adjusted to 720 ml with PBS/CaCl2 and loaded onto 5 ml 40% sucrose cushions . Virus-like particles were twice pelleted through the sucrose cushions in a SW28 rotor at 100 , 000×G for 5 hours . The VLP pellets were resuspended in PBS/CaCl2 and then treated with 0 . 25% deoxycholate for 1 hour at 37°C followed by the addition of 4 M NaCl/0 . 1 mM CaCl2 for 1 hour at 4°C . Precipitated material was removed by centrifugation at 8000×G for 15 minutes . The resulting supernatant was concentrated and buffer exchanged by ultrafiltration through a Pelicon-2 500 , 000 MWCO membrane ( Millipore ) . The concentrated VLPs were applied to the center of a 25–40% step gradient of Optiprep ( Sigma ) and banded at 190 , 000 g for 17 hours in a type 50 . 2 rotor . VLP bands were collected and then concentrated and buffer exchanged in an Amicon stirred cell with a 300 , 000 MWCO membrane . VLP quality was determined by gel electrophoresis and electron microscopy ( Figure S1 ) . Protein concentration was determined by the Micro BCA assay ( Pierce ) . Electron microscopy was performed at the Department of Cell Biology at Harvard Medical School . VLP samples were placed on carbon grids , briefly washed in water and negatively stained with uranyl acetate and allowed to dry . The grids were viewed and imaged on a Technai G2 Spirit BioTWIN TEM . A homology model of the JCV VP1 protein pentameric unit was built with MODELER [40] using the structure of MPyV VP1 ( Protein Data Bank ID: 1VPS [25] as a template . The model of NeuNAc– ( α2 , 3 ) –Gal– ( β1 , 3 ) –[ ( α2 , 6 ) -NeuNAc]–Glc-NAc tetrasaccharide was build based on the structure of NeuNAc– ( α2 , 3 ) –Gal– ( β1 , 3 ) –[ ( α2 , 6 ) -NeuNAc]–Glc-NAc bound to MPyV VP1 [25] . The model of the JCV VP1/NeuNAc– ( α2 , 3 ) –Gal– ( β1 , 3 ) –[ ( α2 , 6 ) -NeuNAc]–Glc-NAc tetrasaccharide was extensively refined in CHARMM [41] and was analyzed using PyMOL visualization software ( The PyMOL Molecular Graphics System ( 2002 ) DeLano Scientific , Palo Alto , CA , USA . http://www . pymol . org ) . The National Center for Biotechnology Information ( NCBI ) ( http://www . ncbi . nlm . nih . gov/sites/entrez ? dbprotein ) Protein database accession numbers for JCV VP1 sequences from non-PML patients . BAC66394 , BAC66418 , BAC66382 , BAB11716 , BAB11722 , AAK28466 , AAK28460 , AAK28478 , BAC66400 , BAC66388 , BAD06126 , BAC66406 , AAK97970 , AAK97964 , BAC81952 , BAC81958 , AAM89309 , AAM89303 , BAC81922 , BAC81916 , BAC81910 , BAC81904 , AAM89297 , BAD11896 , BAC81946 , BAE45426 , BAE45360 , BAD06120 , BAE45432 , BAA01962 , BAE45420 , BAE45414 , BAE45384 , BAE45378 , BAE45372 , AAK98036 , BAE45402 , BAE45408 , BAE45396 , BAE45444 , BAD06024 , BAE75838 , BAE75832 , BAE75826 , BAE75820 , BAE75814 , AAK98030 , AAK98024 , AAK98018 , AAK98010 , AAK98006 , AAK98000 , BAE45438 , BAE45390 , BAD06108 , BAD06102 , BAD06096 , BAD06090 , BAD06084 , BAD06048 , BAD06030 , BAD06018 , BAD06054 , BAD06042 , BAD06036 , AAG30857 , BAE45366 , AAN85455 , BAD06150 , AAN85449 , AAK98042 , BAD06174 , BAD06156 , BAD06072 , BAD06060 , AAN85473 , BAC81840 , BAF40841 , BAF40835 , BAF40829 , BAF40823 , BAF40811 , BAF40847 , BAF40781 , BAF40817 , BAF40799 , BAF40793 , BAF40787 , BAF40745 , AAN85467 , AAN85461 , BAC81834 , BAF40751 , BAF40805 , BAA01961 , BAD98972 , BAD98966 , BAD06227 , BAC66430 , BAC66412 , BAD91887 , BAD21235 , BAD27118 , BAC66424 , BAA01958 , BAB11710 , BAD21265 , BAD21259 , BAD21253 , BAD21241 , BAD21229 , BAD21247 , BAD21283 , BAD21271 , BAD21295 , BAD21289 , BAA01959 , BAA01960 , BAD11848 , BAD11842 , AAM89339 , AAM89327 , BAD11836 , BAC81852 , BAC81858 , BAD06144 , AAG37198 , AAM89315 , BAD06138 , BAD11890 , BAD11884 , BAD11878 , BAD11872 , BAD11866 , AAK97994 , BAB11698 , BAC81940 , BAC81964 , AAK97946 , BAD06066 , BAF40769 , BAC81870 , BAC81864 , BAC81934 , BAC66376 , BAC81874 , BAC81846 , AAK97940 , BAC81898 , BAC81892 , AAK97922 , AAK97916 , AAK97910 , AAK97982 , BAF40763 , BAD06078 , AAK97958 , BAD11860 , BAF40757 , BAD06162 , AAM89321 , BAD11854 , AAK97928 , BAD11830 , BAF40775 , BAB11704 , BAC81928 , AAK97988 , BAD11902 , BAD11824 , BAD06233 , BAC81886 , BAC81880 , AAM89345 , BAD06168 , AAM89333 , BAD06132 , BAC82365 , AAK97952 , BAA01964 , BAA01963 , AAK97934 , BAD06114 , AAK97976 , BAD21277 , AAR13077 , BAE02908 , AAR12957 , AAR02463 , AAR02457 , BAE03058 , AAR89235 , BAE02896 , AAR89241 , BAE02890 , BAE03064 , BAE03070 , BAE03082 , AAG34673 , AAG34667 , AAR89205 , AAR89217 , AAR13659 , BAE03088 , BAE03160 , AAQ88264 , AAR89187 , AAR89283 , AAK28472 , AAR06661 , AAR89253 , AAR89247 , AAR89199 , AAR89193 , AAR89229 , AAR89223 , AAR89265 , AAR32743 , AAR89277 , BAE03166 , BAE02920 , BAE02914 , BAE03112 , BAE03106 , BAE03100 , BAE03094 , BAE03076 , BAE02944 , BAE02998 , BAE02992 , BAE02986 , BAE02980 , BAE02974 , BAE02968 , BAE02962 , BAE03016 , BAE02902 , BAE03040 , AAR89211 , AAR89271 , BAE02956 , BAE02938 , BAE02932 , BAE03148 , BAE02950 , BAE03004 , BAE03154 , BAE03142 , BAE03136 , BAE03130 , BAE03124 , BAE03118 , BAE02926 . | JC virus is a highly prevalent human polyomavirus . Infection with this virus is generally benign and asymptomatic despite viral persistence in the kidney of many people . However , in immunocompromised individuals , very rarely , the infection can progress to become a potentially deadly brain disease called Progressive Multifocal Leukoencephalopathy ( PML ) . The discrepancy between very high viral prevalence and low incidence of PML suggests that there could be some unique viral characteristics that regulate the progression from the asymptomatic infection to the PML . Identification of such factors will help us to understand the basis of PML development and hopefully will lead to the creation of new diagnostic and treatment tools for managing PML . In this work , we demonstrate that the part of the viral surface protein that is thought to be responsible for viral interaction with cellular receptors and infection acquires specific mutations that appear to be critical for the development of PML . These mutations are found more frequently than by simple chance and therefore are thought to be “positively selected . ” Based on these results , we hypothesize that the specific mutations in the viral VP1 protein that we have identified are critical for the evolution of JC virus to the version associated with PML . | [
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"virol... | 2009 | Adaptive Mutations in the JC Virus Protein Capsid Are Associated with Progressive Multifocal Leukoencephalopathy (PML) |
ATM is a central regulator of the cellular responses to DNA double-strand breaks ( DSBs ) . Here we identify a biochemical interaction between ATM and RSF1 and we characterise the role of RSF1 in this response . The ATM–RSF1 interaction is dependent upon both DSBs and ATM kinase activity . Together with SNF2H/SMARCA5 , RSF1 forms the RSF chromatin-remodelling complex . Although RSF1 is specific to the RSF complex , SNF2H/SMARCA5 is a catalytic subunit of several other chromatin-remodelling complexes . Although not required for checkpoint signalling , RSF1 is required for efficient repair of DSBs via both end-joining and homology-directed repair . Specifically , the ATM-dependent recruitment to sites of DSBs of the histone fold proteins CENPS/MHF1 and CENPX/MHF2 , previously identified at centromeres , is RSF1-dependent . In turn these proteins recruit and regulate the mono-ubiquitination of the Fanconi Anaemia proteins FANCD2 and FANCI . We propose that by depositing CENPS/MHF1 and CENPX/MHF2 , the RSF complex either directly or indirectly contributes to the reorganisation of chromatin around DSBs that is required for efficient DNA repair .
DNA damage can result in mutations leading to either cell death or cancer , and multiple repair pathways exist that are specific to distinct DNA lesions [1] , [2] . DNA double-strand breaks ( DSBs ) are particularly toxic lesions repaired by two major pathways , termed homologous recombination ( HR ) or nonhomologous end joining ( NHEJ ) , that utilise either homology-dependent or -independent mechanisms . Additional biological responses to DNA damage include altered transcriptional programmes , transient cell cycle delays termed checkpoints , apoptosis , and senescence . Collectively these responses are termed the DNA damage response ( DDR ) . Ataxia telangiectasia , mutated ( ATM ) and ATM and Rad3-related ( ATR ) , a pair of related protein kinases , are central to the DDR [3] . ATM is directly recruited to DSBs via the Mre11–Rad50–NBS1 ( MRN ) complex , whereas ATR , with its partner ATR-interacting protein ( ATRIP ) , is indirectly recruited via the single-stranded DNA ( ssDNA ) generated during DSB processing . ATM and ATR initiate signalling cascades by phosphorylating many target proteins , including checkpoint kinase 1 and 2 ( Chk1 and Chk2 ) , which initiate a secondary wave of phosphorylation events . Additional posttranslation modifications , including ubiquitinylation , SUMOylation , poly ( ADP-ribosylation ) , acetylation , and methylation , are also required for a successful DDR . DNA is packaged around the core histone proteins H2A , H2B , H3 , and H4 to form nucleosomes and nucleosomes in turn interact with many other nonhistone proteins to form chromatin , which must be dynamically remodelled for a successful DDR [4] . Remodelling of chromatin requires a multitude of chromatin remodelling enzymes and encompasses not only nucleosome removal or sliding but also modification of core histones or their replacement by histone variants . For example , SNF2H ( also termed SMARCA5 ) is an ATP-dependent translocase that is the catalytic component of at least four chromatin-remodelling complexes . These include ( 1 ) the ACF/WCRF complex composed of SNF2H and the ACF/WCRF protein , also known as BAZ1A [5]; ( 2 ) the CHRAC complex composed of SNF2H and the CHRAC1 , POLE3 , and ACF1 proteins [6]; ( 3 ) the RSF complex composed of SNF2H and RSF1 [7] , [8]; and ( 4 ) the WICH complex composed of SNF2H and the BAZ1B , DEK , DDX21 , ERCC6 , MYBBP1A , and SF3B1 proteins [9] . An important connection between the ATM and ATR kinases and the ACF/WCRF , CHRAC , RSF , and WICH complexes has been established in a screen for substrates of these kinases [10] . Additionally , the ACF/WCRF complex is required for DSB repair [5] and the WICH complex has been implicated in the DDR [11] . More recently , the BAZ1B component of the WICH complex was shown to be required for the activation of ATM and phosphorylation of H2AX at tyrosine residue 142 [12] . Although a direct connection to DNA repair has yet to be made for the RSF1 protein , it is required for the stabilisation of the CENPA complex and correct assembly of centromeric chromatin [7] , [8] . Interestingly , the CENPS–CENPX centromeric chromatin complex , composed of histone fold proteins that most resemble histones H3 and H4 , has recently been shown to participate in the repair of DNA interstrand cross-links ( ICLs ) via the Fanconi Anaemia ( FA ) pathway [13] , [14] . CENPS and CENPX have also been termed MHF1 and MHF2 for FANCM-interacting Histone Fold protein 1 and 2 . Additionally , overexpression of RSF1 in an ovarian cancer cell line has also been reported to induce DNA damage and genomic instability [15] . Patients with FA are defective in a pathway required for the repair of DNA ICLs , causing elevated genome instability and cancer risk [16]–[18] . The FA pathway regulates the mono-ubiquitination of two related proteins , FANCD2 and FANCI , that in turn coordinate the recruitment of several nucleases required to unhook the ICL , resulting in an unhooked cross-linked nucleotide on one DNA molecule and a DSB on the other . Translesion synthesis ( TLS ) allows bypass of the unhooked cross-linked nucleotide , necessary for generating a template suitable for HR-dependent DSB repair . Nucleotide excision repair ( NER ) then removes the nucleotide with the cross-linked adduct . Initiation of the FA pathway requires the multifunctional FANCM–FAAP24 heterodimer , which recognises ICLs , recruits the FA core complex , and contributes to both stabilisation of stalled replication and ATR-dependent signalling . We used a proteomic screen to identify proteins that interact with chicken Atm and focussed on Remodelling and Spacing Factor 1 ( Rsf1 ) , a subunit of a chromatin-remodelling factor . We show that human RSF1 and ATM directly interact and map the regions of interaction between these proteins . RSF1 has been identified as a likely ATM substrate after ionising radiation ( IR ) [10] , although its role in the DDR had not been characterised . We have defined a role for human RSF1 in the repair of DNA DSBs by both NHEJ and HR . Interestingly , the RSF1 protein directly interacts with the histone-related CENPS/MHF1 and CENPX/MHF2 proteins , previously implicated in centromere function and the FA pathway . We find that RSF1 is required for localization of the CENPS/MHF1–CENPX/MHF2 complex , followed by FANCD2 and FANCI to sites of DNA damage . Similarly , RSF1 is required for the efficient mono-ubiquitination and chromatin retention of FANCD2 and FANCI after IR . Our data suggest that ATM-dependent regulation of the RSF chromatin-remodelling complex is required during DSB repair for the sequential recruitment of centromeric and FA proteins to facilitate efficient DSB repair .
We used a novel HFSC-affinity tag ( Figure S1A ) together with gene targeting in chicken DT40 cells ( Figure 1A ) to generate a cell line expressing HFSC-Atm as the sole source of the chicken Atm protein . Southern blotting confirms that both Atm alleles were successfully targeted using a strategy that results in minimal genetic alteration to the Atm locus ( Figure 1A and 1B ) . Expression from the WT Atm promoter produces HFSC-Atm at WT levels ( Figure 1C ) . Clonogenic survival assays confirmed that HFSC-Atm cells survived IR as well as WT cells ( Figure 1D ) . SILAC quantitative proteomic analyses both before and after IR were performed to identify Atm-interacting proteins . Known ATM-interacting proteins were identified ( Table 1 and see Table S1 for a full list of the proteins identified ) . We noticed that several chicken chromatin-remodelling factors were enriched in our screen , including Rsf1 , a protein without a characterized role in the DDR . We validated the chicken Atm–Rsf1 complex by co-immunoprecipitation of human RSF1 with human ATM using U2OS osteosarcoma cells ( Figure 2A ) . Although a well-characterised DNA-damage–dependent ATM interactor , NBS1 [19] , [20] , co-immunoprecipitated with ATM after IR , HP1β , an abundant chromatin protein , also implicated in the DDR [21] , did not . RSF1 , although chromatin-bound both before and after IR ( Figure S2F ) , only co-immunoprecipitated with ATM after IR . Similarly , the SNF2H ( or SMARCA5 ) catalytic subunit of the RSF complex also co-immunoprecipited with ATM after IR . The interaction between ATM and the RSF complex is not only dependent upon IR but also upon ATM kinase activity ( Figure 2A ) and could also be detected in extracts from HEK293 human embryonic kidney cells ( Figure S2A and S2B ) . The equivalent interaction detected between chicken Atm and both Rsf1 and Snf2H/Smarc5 was also IR-dependent ( Table 1 ) . RSF1 has been reported to be a substrate of ATM in vitro [10] , and here we show that RSF1 phosphorylation in vivo is also ATM-dependent ( Figure 2B ) . Additionally , using the anti-pS1423BRCA1 antibody used by Matsuoka and colleagues [10] to detect phosphorylation of additional ATM/ATR substrates , we show that phosphorylation of RSF1 is largely ATM-dependent ( Figure S2G ) . Moreover , as the C-terminal consensus PIK kinase sites more closely match the BRCA1-S1423 epitope , our data suggest that it is these two C-terminal sites , rather than the N-terminal consensus PIK kinase site , that is phosphorylated in vivo . Human SNF2H is also a component of the ACF1/WRCF , CHRAC , and WICH chromatin remodelling complexes , whereas RSF1 is specific to the RSF complex alone [7] , [8] . Of note , the BAZ1A ( also termed ACF1 ) and BAZ1B components of the ACF/WCRF and WICH complexes , respectively , were also identified in our human ATM immunoprecipitates ( Figure S2A , S2B , and S2C ) and their chicken homologues , by mass spectrometry ( Table 1 ) . Our data are consistent with a previously unreported IR-dependent interaction between ATM and RSF1 . Depletion of the ACF1/WRCF complex , including SNF2H , has already been shown to promote sensitivity to damaging agents such as IR , MMS , and camptothecin , and mild sensitivity to UVC [5] . To assess the role of the RSF complex in the DDR , we performed clonogenic survival assays using IR and MMS treatments with single and double siRNA-dependent “knockdowns” of RSF1 and SNF2H ( Figure 2D ) . Depletion of RSF1 results in similar IR sensitivity as depletion of SNF2H . Individual RSF1 or SNF2H depletion also resulted in sensitivity to MMS , although MMS sensitivity appeared more pronounced for the RSF1 knockdown , whereas the double knockdown appeared to have even greater MMS sensitivity , approaching that of ATM inhibition . Cells individually depleted for RSF1 and SNF2H were also mildly sensitive to the interstrand crosslinking reagent MMC ( Figure S2D ) . RSF1-depleted cells were only weakly sensitive to UVC , whereas SNF2H-depleted cells displayed the expected mild sensitivity to UVC ( Figure S2E ) . These data demonstrate that RSF1 functions in the cellular response to DNA damage . In addition to its role in DSB repair [2] , ATM has a well-characterized role in the G2/M checkpoint [22] . As measured by accumulation of a mitotic marker ( histone H3S10 phosphorylation ) , single and double depletion of RSF1 and SNF2H resulted in entry into the G2/M checkpoint with normal kinetics that was similar to the scrambled siRNA control , whereas ATM-inhibited cells never entered the checkpoint ( Figure 3A ) . However , unlike control cells , which re-entered the cell cycle upon completion of repair , RSF1- and SNF2H-depleted cells remained arrested for the duration of the experiment . Normal entry into the G2/M checkpoint followed by defective exit is consistent with either defective DSB repair or checkpoint recovery . To distinguish between these possibilities , we monitored the γ-H2AX histone modification found at DSBs [23] by both Western blotting and immunofluorescence microscopy ( Figure 3B and 3C and Figure S3A ) . The γ-H2AX signal was lost 4–8 h after irradiation , whereas in singly and doubly depleted RSF1 and SNF2H cells , it persisted for at least 24 h . These data indirectly indicate a DSB repair defect in the absence of RSF1 and SNF2H . We then monitored DSBs directly using neutral comet assays to confirm this result directly ( Figure 3D and 3E ) . Comet tails , corresponding to broken DNA , that are detected immediately after IR were rapidly lost in control cells , indicative of DSB repair . These tails persist throughout the experiment in cells singly or doubly depleted for RSF1 and SNF2H . Essentially equivalent results were obtained by pulse-field gel electrophoresis ( Figure S3B ) . Thus , both of these physical techniques confirmed defective DSB repair in RSF1- and SNF2H-depleted cells , consistent with our clonogenic survival , checkpoint , and γ-H2AX assays . Lack of RSF1 has also been reported to destabilise the centromeric histone H3 variant CENPA within centromeric DNA as it facilitates its removal by salt extraction [8] . Recruitment of CENPA to both I-Sce1–induced DSBs and laser-induced DNA damage has also been reported [24] . Although we are unable to detect CENPA localisation to IR-induced foci ( IRIF ) by immunofluorescence , we observed an IR- and RSF1-dependent interaction between ATM and CENPA ( Figure S4A ) , although only after 1% PFA cross-linking . However , the interaction between RSF1 and CENPA was independent of IR ( Figure 4A ) . Thus , we were unable to demonstrate a direct link between RSF1 and CENPA at DSBs . As RSF1 is required for the stabilisation of CENPA into centromeric chromatin , we wondered if it could play a similar role for other centromeric proteins at DSBs . CENPS/MHF1 and CENPX/MHF2 are two additional centromeric proteins that are known to interact with FANCM and have also been localised to sites of laser-activated psoralen-induced ICLs in S-phase cells [14] . Interestingly , these two proteins form a tetrameric complex resembling the histone H3–H4 tetramer [25] . Depletion of either CENPS/MHF1 ( resembling H3 ) or CENPX/MHF2 ( resembling H4 ) has been shown to result in defective FANCM recruitment , defective FANCD2 and FANCI mono-ubiquitination , and defective resolution of ICLs [13] , [14] . We hypothesised that the role of RSF1 in response to IR-induced DNA damage could be the recruitment of the histone fold proteins CENPS/MHF1 and CENPX/MHF2 to nucleosomes or nucleosome-like structures that occur in the vicinity of DSBs . This in turn may lead to the recruitment and mono-ubiquitination of FANCI/FANCD2 at DSBs , which in turn contribute to effective repair of breaks . In support of this hypothesis , both FANCI and FANCD2 are known ATM substrates and required for DSB resolution [10] , [26] . Furthermore , our proteomic analysis of chicken Atm-interacting proteins also suggested a possible interaction with FancI ( Table 1 ) . RSF1 co-immunoprecipitates with activated ATM ( Figure 2A ) , and we confirmed this interaction in RSF1 immunoprecipitates ( Figure 4A and 4C ) . Consistent with our recruitment hypothesis , RSF1 immunoprecipitates prepared from IR-treated cells contained the CENPS/MHF1 and CENPX/MHF2 proteins . We mapped the region of RSF1 that interacts with CENPS/MHF1 and CENPX/MHF2 in vitro using recombinant proteins ( Figure 4D ) . Both of these histone-related proteins interacted with the C-terminus of RSF1 , which contains the sites of ATM-dependent phosphorylation ( Figure 2B and Figure S2G ) . Interestingly , the FANCD2 and FANCI proteins also interacted with RSF1 after IR ( Figure 4A ) . Furthermore , and consistent with the RSF1 protein being exclusively bound to chromatin ( Figure 2B , see also Figure 4B and Figure S4B ) , it was primarily the “long” forms , known to be mono-ubiquitinated and chromatin retained forms of FANCD2 and FANCI [27] , that co-immunoprecipitated with RSF1 ( Figure 4A and 4C ) . We determined the dependency of FANCD2 and FANCI recruitment and mono-ubiquitination upon RSF1 by chromatin fractionation in the presence and absence of RSF1 ( Figure 4B and Figure S4B ) . In un-irradiated cells that contain RSF1 , the FANCD2 and FANCI proteins can be found as both soluble and chromatin retained proteins , with the mono-ubiquitinated form being largely on the chromatin . After IR , both FANCD2 and FANCI are primarily mono-ubiquitinated and retained in the chromatin fraction in cells containing RSF1 . However , upon depletion of RSF1 , both chromatin recruitment and mono-ubiquitination of FANCD2 and FANCI are abrogated . Importantly , expression of FLAG-tagged mouse Rsf1 rescues FANCD2 foci and mono-ubiquitination when endogenous RSF1 is depleted , confirming the specificity of our depletion conditions ( Figure S4C and D ) . Also , using an anti-Flag monoclonal antibody , we could not localise mouse Rsf1 to IRIF , suggesting that either insufficient Rsf1 is localised to IRIFs to be detected or that the role of Rsf1 at DSBs is transient . Thus , RSF1 is required for efficient mono-ubiquitination and retention of FANCD2 and FANCI on damaged chromatin . To address the sequence of RSF1-dependent molecular events , we repeated the RSF1 immunoprecipitation after depletion of either CENPS/MHF1 or CENPX/MHF2 ( Figure 4C ) . In the absence of these proteins , ATM could still be detected in RSF1 immunoprecipitates , indicating that CENPS/MHF1 and CENPX/MHF2 are not required for the ATM–RSF1 interaction . However , the interaction between RSF1 and FANCD2 and FANCI could not be detected after knockdown of either CENPS/MHF1 or CENPX/MHF2 . Consistent with a previous report [14] , mono-ubiquitination of FANCD2 and FANCI was abrogated when either CENPS/MHF1 or CENPX/MHF2 were depleted . We also noticed that in these immunoprecipitation experiments , in the absence of CENPX/MHF2 , some CENPS/MHF1 was still detected in the RSF1 immunoprecipitates but not vice versa . This suggests that the subunit of the CENPS/MHF1–CENPX/MHF2 complex that interacts directly with RSF1 is CENPS/MHF1 . A direct interaction between CENPS/MHF1 and RSF1 is consistent with CENPS/MHF1 being a histone fold protein that most resembles histone H3 protein and RSF being a chromatin remodelling complex that preferentially recognises histone H3 and the H3-like CENPA [8] , [25] . Thus far , our data are consistent with DSB-dependent ATM kinase activity being required for an interaction between ATM and RSF1 on chromatin; RSF1 then recruits the CENPS/MHF1–CENPX/MHF2 complex , which in turn recruits FANCD2 and FANCI . Of note , the role of RSF1 appears to be specific to DSBs , as sensitivity of RSF1-depleted cells to MMC is subtle and FAND2 foci after MMC treatment are unaffected by RSF1 knockdown ( Figure S2D , H , and I ) . To determine the specificity of RSF1 for either of the two major DSB repair pathways , NHEJ and HR , we initially performed clonogenic survival assays on cells depleted of RSF1 or CENPS/MHF1 and treated with ICRF-193 or Olaparib ( Figure 5A ) . ICRF-193 is an inhibitor of topoisomerase 2 and generates DSBs that are repaired specifically by NHEJ [28] , [29] , whereas Olaparib is a PARP inhibitor that prevents repair of single-strand breaks , resulting in DSBs in the S phase that are normally repaired by HR [30] , [31] . Both of these drugs resulted in sensitivity in both RSF1- and CENPS/MHF1-depleted cells . In order to have a more direct and robust quantification of the NHEJ and HR pathways , we utilised established NHEJ and HR assays that are based upon expression of a GFP reporter after induction of a site-specific DSB by the I-SceI endonuclease [32] , [33] . Depletion of RSF1 and/or CENPS/MHF1 resulted in impaired repair in both of these assays ( Figure 5B ) . Intriguingly , we also noticed defective recruitment of CtIP to IRIF upon depletion of RSF1 ( Figure S5C ) . These data are consistent with RSF1-dependent recruitment of CENPS/MHF1 being required for efficient DSB repair by both major DSB repair pathways . Previously , the recruitment of FANCM and efficient mono-ubiquitination of FANCD2 after induction of DNA ICLs was shown to be dependent upon MHF1 [14] . We therefore investigated IR-dependent focal recruitment of CENPS/MHF1 , CENPX/MHF2 , FANCD2 , and FANCI after knockdown of RSF1 ( Figure 6 ) . Note that our extraction protocol distinguishes between the more dynamic recruitment of CENPS/MHF1 and CENPX/MHF2 to centromeres relative to their more stable recruitment to IRIFs ( Figure S6A to D ) . Although RSF1-depleted cells are proficient for recruitment of ATM and 53BP1 ( Figure 6A ) into IRIF , as well as for γ-H2AX ( Figure 6B ) IRIF , they are deficient for CENPS/MHF1 ( Figure 6B ) and CENPX/MHF2 ( Figure 6C ) IRIF . As expected , this then results in loss of FANCD2 ( Figure 6D ) and FANCI ( Figure 6E ) IRIF . Quantification of cells with at least 10 foci revealed that although ATM , γ-H2AX , or 53BP1 IRIF were unaffected by RSF1 depletion , CENPS/MHF1 , CENPX/MHF2 , FANCD2 , and FANCI foci were reduced 3–4-fold relative to the undepleted control cells ( Figure 6G ) . The recruitment of CENPS/MHF1 and CENPX/MHF2 into IRIF contrasts with our failure to observe CENPA in IRIF , despite the recruitment of CENPA to kinetochores being readily apparent although clearly distinct from CENPS/MHF1 or NBS1 at IRIF ( Figure S6G ) . In fact , depletion of CENPS/MHF1 does not disrupt kinetochore formation as assessed by CENPA recruitment , nor did it perturb mitotic arrest and release after nocodazole addition and removal ( Figure S6H ) , suggesting that the residual levels of CENPS/MHF1 and CENPX/MHF2 after knockdown are sufficient for their function at kinetochores . We also confirmed that CENPS/MHF1 and FANCI IRIF are mainly co-localised ( Figure S6E ) . Next , we determined the dependence of FANCD2 and FANCI foci on CENPS/MHF1 and CENPX/MHF2 . Depletion of CENPS/MHF1 or CENPX/MHF2 results in loss of FANCD2 IRIF ( Figure 6F ) and FANCI ( Figure S6F ) . Thus , our immunofluorescence data are in agreement with our biochemical data ( Figure 4C ) and together suggest a hierarchical recruitment of these proteins to DSBs . Together , our data suggest a novel role for RSF1 in DSB repair in which this chromatin remodelling activity is required for recruitment of the CENPS/MHF1–CENPX/MHF2 histone fold proteins to the vicinity of IR-induced DNA lesions . These proteins are in turn required for both FANCD2–FANCI recruitment and their efficient mono-ubiquitination .
The ATM–RSF1 interaction is dependent upon IR and has been observed in both chicken DT40 cells and human cell lines . Importantly , this interaction is also dependent upon the kinase activity of the ATM kinase , which is consistent with the previous identification of RSF1 as a substrate of the ATM kinase [10] . Using GST–ATM fusions [36] we have mapped the region of ATM that interacts with RSF1 to the C-terminal FATC domain , a region also reported to interact with TRF1 in this assay [37] . RSF1 depletion results in sensitivity to IR and MMS but only moderate sensitivity to MMC and UVC . A role in DSB repair was suggested by persistence of the γ-H2AX modification and the failure of RSF1-depleted cells to exit the G2/M checkpoint . We confirmed defective DSB repair using two physical techniques , the comet assay and pulse-field gel electrophoresis . Moreover , using assays specific to either direct end joining or homology-directed repair of induced DSBs , our results indicate that RSF1 is required for efficient DNA repair by either of these two mechanisms . Together , our data indicate that RSF1 is a new player in the DDR required for the efficient repair of DSBs . Recent reports have shown that after DNA ICLs , two proteins , FANCM-interacting histone fold proteins 1 and 2 ( MHF1 and MHF2 ) , are recruited to these lesions , resulting in the stabilisation of FANCM and the subsequent recruitment and mono-ubiquitination of FANCD2 and FANCI [13] , [14] . Previously , these proteins had been implicated in centromere function and termed CENPS and CENPX , respectively [38] . Structurally , CENPS/MHF1 and CENPX/MHF2 form a tetramer that resembles the histone H3–H4 tetramer [25] . RSF1 is a chromatin-remodelling factor with ATPase activity required for the establishment of centromeric CENPA , which in turn is required for the subsequent localisation of CENPS/MHF1 and CENPX/MHF2 to centromeres [8] , [38] . This role led us to determine whether RSF1 might be required for the recruitment of CENPS/MHF1 and CENPX/MHF2 to DSBs . RSF1 appears to specifically interact with CENPS/MHF1 as loss of CENPX/MHF2 does not abolish the RSF1 interaction with CENPS/MHF1 , whereas loss of CENPS/MHF1 does abolish the interaction . This is also consistent with crystallographic studies indicating that although CENPS/MHF1 is not a histone variant , it is a histone fold protein that most closely resembles histone H3 and RSF1 is known to preferentially bind to histone H3 and CENPA [7] , [8] . Using GST–RSF1 fusion proteins and recombinant CENPS/MHF1 and CENPX/MHF2 , we have also demonstrated a direct interaction between RSF1 and these histone fold proteins . CENPS/MHF1 and CENPX/MHF2 interact with the C-terminus of RSF1 , a region containing sites of in vivo ATM-dependent phosphorylation . Importantly , using depletion of CENPS/MHF1 and CENPX/MHF2 , we have also shown that these proteins are subsequently required for the recruitment and mono-ubiquitination of FANCD2 and FANCI at DSBs . Note that previous reports have also demonstrated FANCD2 and FANCI localization to DSBs produced during the S phase [17] , [27] . Although there are connections between the FA pathway and replication-coupled , homology-directed DSB repair [16] , [18] , the precise role of activated FANCD2 and FANCI in DSB repair has not yet been characterised . However , it is likely that coordinated ubiquitination , which regulates recruitment of specific factors to the mono-ubiquitin moiety via a plethora of ubiquitin binding domains ( UBDs ) , and de-ubiquitination of FANCD2 and FANCI are required for efficient repair . A role for centromeric proteins in DSB repair has also been suggested by the reported localisation of CENPA to laser-induced and I-SceI–induced site-specific DSBs [24] . Unfortunately , under our experimental conditions we could not detect CENPA localisation to sites of IRIF , although its localisation to kinetochores was readily apparent . Nor could we detect an interaction between ATM and CENPA by either mass spectrometric analysis or by co-immunoprecipitation . However , we could detect RSF1 , CENPS/MHF1 , and CENPA in ATM immunoprecipitates prepared from cells treated with formaldehyde , an agent that crosslinks proteins that are in close proximity . Our data do not rule out a possible role for CENPA at DSBs . However , future studies will be required to determine the precise role of CENPA , if any , in DSB repair . In summary , we have identified RSF1 as a new player in the DDR response that is required for repair of DSBs . Our data are consistent with a model ( Figure 7 ) in which DSB-activated ATM results in RSF-dependent recruitment of the CENPS/MHF1–CENPX/MHF2 complex , which in turn is required to recruit and activate FANCD2 and FANCI . Although this sequence of events is not required for DSB-dependent checkpoint signalling , it is required for DSB repair , probably in constructing a chromatin environment permissive for repair . This is likely to be a highly dynamic process requiring transient complexes between DNA and CENPS/MHF1–CENPX/MHF2 complexes .
Cells were grown at 39°C to a maximum density of 1×106 cells/ml in RPMI ( Lonza ) supplemented with 10% foetal calf serum ( Lonza ) , 1% chicken serum ( Lonza ) , and 1% penstrep ( Lonza ) . For transfection , 1×106 cells were collected and resuspended into 0 . 5 ml PBS and transferred to transfection cuvettes ( Bio-rad catalog number 165–2088 , 0 . 4 cm electrode gap ) , and 5–15 µg of linearised DNA was added . After an incubation ( 10 min/RT ) , electroporation was performed using a gene pulsar apparatus ( Bio-rad , 550 V , 25 µF ) . Cells were then grown for two doubling times ( approximately 16–24 h ) . The media was replaced with fresh RPMI media containing the required drug for selection , and the cells were aliquoted into 4× 96-well plates . When the clones grew big enough to be visible , they were transferred into 24-well plates ( containing 1 ml of media in each well ) . Upon confluence they were split into 12-well dishes ( 4 ml in total ) , and once confluent , 2 ml was harvested and frozen at −80°C in freezing media ( serum plus 10% DMSO ) and 2 ml ( ∼1 . 5×106 cells ) harvested for genomic DNA extraction . We transfected 20 nmol of siRNA ( Dharmacon ) per 35 mm tissue culture dish of cells ( Oligofectamine , Invitrogen ) onto cells at 70% confluence according to the manufacturer's instructions . After 48 h , the siRNA transfection was repeated and the cells were harvested the next day . For siRNA sequences , see Table 2 . The 1 . 5×106 cells were collected and resuspended in 500 µl TAIL buffer ( Tris-HCl pH 8 . 8 , 50 mM , EDTA pH 8 100 mM , NaCl 100 mM , SDS 1% , 3 µl of a 20 mg/ml Proteinase K solution for every 0 . 5 ml TAIL buffer ) in Eppendorf tubes , and the cells were incubated overnight at 37°C . The Eppendorf tubes were shaken vigorously for 5 min , 200 µl of saturated NaCl ( 6 M ) was added to each , and the tubes were shaken vigorously for a further 5 min . Debris was removed by centrifugation ( 14 , 000 rpm/30 min at 4°C ) , and 700 µl of ice-cold isopropanol was added to each supernatant and mixed by gentle inversion of the tube . Genomic DNA was pelleted by centrifugation ( 14 , 000 rpm/10 min ) and washed with 300 µl of 70% ice-cold ethanol . The genomic DNA pellet was briefly air dried and then resuspended in 60 µl TE buffer at pH 7 . 5–8 . 0 , plus 2 µl of a 5 mg/ml RNAse A . Southern blotting was performed according to the manufacturer's ( DIG-PCR-DNA labelling and probing , Roche ) instructions The 5×106 cells were harvested and resuspended in 100 µl of Nucleofector solution ( Amaxa ) , to which 75 µg of endotoxin-free pANMerCreMer plasmid DNA was added . The mix has been transferred to an Amaxa cuvette for “nucleofection . ” Nucleofected cells were added to 10 ml of RPMI containing 100 nM 4-OH-Tamoxifen and after growth for 24 h plated into 96-well plates at 0 . 5/1/1 . 5 cells per plate . After 7–8 d , subclones were picked and replated under selection for further analyses . A total of 1 l of WT and HFSC-ATM cells were grown in petri dishes to a maximum confluency of 1×106 cells/ml , harvested , resuspended in 0 . 5 l of the conditioned media , and irradiated with 10 Gy . After 1 h recovery at 39°C , they were washed ( 1× PBS; ice-cold ) and resuspended in 2 ml Lysis Buffer [50 mM Tris-HCl , pH 7 . 5; 150 mM NaCl; 0 . 5% NP-40; 1× Protease inhibitors ( Roche tablet ) ; 1× phosphatase inhibitors ( SIGMA ) ] at 4°C for 30 min . Chromatin was solubilised by adding MgCl2 ( to a final concentration of 1 mM ) and Benzonase ( 250 unit/ml , Sigma ) and undergoing incubation for 45 min at 4°C . The reaction was stopped by addition of EDTA ( to a final concentration of 1 mM ) and incubation on ice for 5 min . Debris was pelleted ( 100 , 000 g/60 min/1 h ) and the supernatant harvested and quantified by Bradford assay . Precisely the same amount of total cell lysates for the two samples were mixed ensuring a 1∶1 ratio and purified using a Gravity Flow Strep-tagII column ( Iba Tagnology ) , following the manufacturer's instructions . The eluted fraction containing the protein was lyophilised and sent on dry ice to Dundee Cell Products ( Scotland ) for mass spectromeric analysis . Equal amounts of protein from unlabelled and labelled samples were combined prior to protein digestion . Briefly , samples were reduced in 10 mM DTT and alkylated in 50 mM Iodoacetamide prior to boiling in loading buffer , and then separated by 1D SDS-PAGE ( 4%–12% Bis-Tris Novex mini-gel , Invitrogen ) and visualized by colloidal Coomassie staining ( Novex , Invitrogen ) . The entire protein gel lanes were excised and cut into 10 slices each . Every gel slice was subjected to in-gel digestion with trypsin overnight at 37°C . The resulting tryptic peptides were extracted by formic acid ( 1% ) and acetonitrile , lyophilized in a speed-vac , and resuspended in 1% formic acid . Trypsin-digested peptides were separated using an Ultimate 3000 RSLC ( Thermo Scientific ) nano-flow LC system . On average 0 . 5 µg was loaded with a constant flow of 5 µl/min onto an Acclaim PepMap100 nano-Viper C18 trap column ( 100 µm inner-diameter , 2 cm; Thermo Scientific ) . After trap enrichment , peptides were eluted onto an Acclaim PepMap RSLC nano-Viper , C18 column ( 75 µm , 15 cm; ThermoScientific ) with a linear gradient of 2%–40% solvent B ( 80% acetonitrile with 0 . 08% formic acid ) over 65 min with a constant flow of 300 nl/min . The HPLC system was coupled to a linear ion trap Orbitrap hybrid mass spectrometer ( LTQ-Orbitrap Velos , Thermo Scientific ) via a nano-electrospray ion source ( Thermo Scientific ) . The spray voltage was set to 1 . 2 kV , and the temperature of the heated capillary was set to 250°C . Full-scan MS survey spectra ( m/z 335–1800 ) in profile mode were acquired in the Orbitrap with a resolution of 60 , 000 after accumulation of 1 , 000 , 000 ions . The 15 most intense peptide ions from the preview scan in the Orbitrap were fragmented by collision-induced dissociation ( normalized collision energy , 35%; activation Q , 0 . 250; and activation time , 10 ms ) in the LTQ after the accumulation of 10 , 000 ions . Maximal filling times were 1 , 000 ms for the full scans and 150 ms for the MS/MS scans . Precursor ion charge state screening was enabled , and all unassigned charge states as well as singly charged species were rejected . The lock mass option was enabled for survey scans to improve mass accuracy [39] . Data were acquired using the Xcalibur software . The raw mass spectrometric data files obtained for each experiment were collated into a single quantitated data set using MaxQuant ( version 1 . 2 . 2 . 5 ) [40] and the Andromeda search engine software [41] . Enzyme specificity was set to that of trypsin , allowing for cleavage N-terminal to proline residues and between aspartic acid and proline residues . Other parameters used were as follows: ( i ) variable modifications , methionine oxidation , protein N-acetylation , gln → pyro-glu; ( ii ) fixed modifications , cysteine carbamidomethylation; ( iii ) database , target-decoy human MaxQuant ( ipi . HUMAN . v3 . 68 ) ; ( iv ) heavy labels , R6K4 and R10K8; ( v ) MS/MS tolerance , FTMS , 10 ppm; ITMS , 0 . 6 Da; ( vi ) maximum peptide length , 6; ( vii ) maximum missed cleavages , 2; ( viii ) maximum of labelled amino acids , 3; and ( ix ) false discovery rate , 1% . Peptide ratios were calculated for each arginine- and/or lysine-containing peptide as the peak area of labelled arginine/lysine divided by the peak area of nonlabelled arginine/lysine for each single-scan mass spectrum . Peptide ratios for all arginine- and lysine-containing peptides sequenced for each protein were averaged . U2OS or HEK293 cells were grown to 80%–90% confluency in a single 10 cm petri dish . Cells were trypsinized and harvested , the pellet was washed in 1×PBS ( ice-cold ) , and resuspended in 0 . 5–1 ml of lysis buffer [50 mM Tris , pH 7 . 5; 150 mM NaCl; 0 . 5% NP-40; 5% glycerol; 1× Protease inhibitors ( Roche tablet ) ; 1× phosphatase inhibitors ( Sigma ) ] supplemented with 1 µl per 1 mL Benzonase ( 250 units/ml , Sigma ) to solubilize chromatin and incubated at 4°C for 45 min . After incubation , lysates were cleared by centrifugation for 30 min at 4°C , 14 , 000 rpm , and quantified by Bradford assay . For salt extraction of chromatin bound proteins , cell pellets were resuspended in 200 µl of lysis buffer containing 400 mM NaCl and incubated at 4°C for 20 min . Additional 400 µl of lysis buffer ( without salt ) were added , and lysates were cleared by centrifugation ( 14 , 000 rpm , 30 min , 4°C ) . For immunoprecipitation , equal amounts of total protein extracts ( typically 10 mg ) were used for each sample and typically 1 µg of primary antibody per mg of extract was added and left in ice for 2 h . We added 40 µL pre-equilibrated protein G beads ( GE Healthcare ) and left it at 4°C with gentle agitation for a further 2 h . The beads were gently pelleted ( 1 , 000 rpm/5 min/4°C ) , washed six times with 1× lysis buffer , and resuspended in 50 µL of sample loading buffer ( Invitrogen ) . Pulldown assays were performed according to [37] . Briefly GST–ATM fusion plasmids [36] , GST–RSF1 fragments , and MBP–MHF1/2 were transformed into Rosetta cells . A 20 ml overnight culture was used to inoculate 1 l of LB-Amp ( 50 µg/ml ) –Chloramphenicol ( 50 µg/ml ) , and at OD600 , 0 . 5–0 . 7 , 0 . 4 mM IPTG ( final ) was added and incubated overnight at 20°C . Cells were harvested , resuspended in 30 ml of lysis buffer ( 50 mM Tris [pH 7 . 9] , 100 mM KCl , 1% Triton X-100 , 2 mM DTT , 0 . 1 mM PMSF , complete protease inhibitor tablet [Roche] ) , and sonicated three times for 30 s on ice . The lysate was cleared by centrifugation at 50 , 000 g at 4°C and incubated with 200 µl of equilibrated glutathione beads for 2 h at 4°C . The beads were washed three times for 10 min each ( washes 1 and 3 , PBS , 1% Triton X-100 , 2 mM DTT , 0 . 1 mM PMSF , 1 mM benzamidine , 1 complete protease inhibitor tablet [Roche]; wash 2 , 300 mM NaCl , 50 mM Tris [pH 7 . 9] , 2 mM DTT , 0 . 1 mM PMSF , 1 mM benzamidine , 1 complete protease inhibitor tablet [Roche] ) and a fourth time in wash 4 ( 50 mM Tris [pH 7 . 9] , 100 mM KCl , 50% glycerol , 2 mM DTT , 0 . 1 mM PMSF ) . GST–RSF1 fusion proteins were eluted in 500 µl of wash 4 ( see pulldown assay ) containing 15 mM glutathione ( reduced form ) . Five micrograms of GST fusion proteins or GST alone were incubated with 2 µg of MBP–MHF1 or MBP–MHF2 beads in binding buffer ( 150 mM NaCl , 100 mM KCl , 50 mM Tris [pH 8 . 0] , 1% NP40 , 0 . 1% SDS , 100 µg/ml BSA ) at 4°C for 1 h . Beads were collected by centrifugation at 5 , 000 rpm at 4°C and washed three times for 10 min each with binding buffer , and bound protein was eluted by boiling the samples in Laemmli buffer . GST–RSF1 fusion proteins were detected by immunoblotting . Cell extracts were prepared as for immunoprecipitations , except benzonase was not added during cell lysis and the cells were resuspended in 0 . 1 ml of lysis buffer . The supernatants were collected as soluble ( “S” ) fractions and the pellets ( “C” ) resuspended in 0 . 1 ml of lysis buffer supplemented with 1 µl per 1 ml Benzonase ( 250 units/mL , Sigma ) , together with 1 mM ( final concentration ) of MgCl2 , to solubilize chromatin and incubated at 4°C for 45 min . Lysates were cleared ( 14 , 000 rpm , 30 min , 4°C ) and quantified by Bradford assay . Mock and treated cells ( 2×106 cells ) were harvested , resuspended in 1 ml 1× PBS , fixed by adding 3 mL of 70% ethanol , and the cells stored at −20°C . The cells were pelleted; washed in PBS; resuspended in 50 µl of PBS containing 0 . 25% Triton X-100 , 1% BSA , and 1 µl phosphoH3-S10 antibody ( Millipore ) ; and incubated for 2 h at RT . Cells were washed once more; resuspended in 50 µl PBS containing 0 . 25% Triton X-100 , 1% BSA , and goat anti-rabbit IgG FITC conjugate ( 1∶50 dilution , Jackson ImmunoResearch ) ; and incubated ( 1 h/RT ) in the dark . Cells were then resuspended in 0 . 3 ml of PBS containing propidium iodide at 25 µg/ml and RNaseA at 250 µg/ml and incubated ( 30 min/RT ) in the dark . Cells positive for phospho-H3S10 were quantified on a FACSCanto ( BD Biosystem ) using FACSdiva software ( BD Biosystem ) . Cell were grown on poly-D-lysine coverslips , removed from culture , and permeabilised in 100 mM NaCl , 300 mM sucrose , 3 mM MgCl2 , 10 mM Pipes , pH 7 . 5 , 0 . 4% Triton-X for 10 min at 4°C . Cells were then fixed with 4% paraformaldehyde ( PFA ) for 15 min at room temperature and washed once with 1× TBS . After blocking for an hour at 37°C with 1% BSA , the primary antibody was added at an appropriate concentration in 1% BSA and incubated at 37°C for 1 h ( anti–pATM-S1981 was used at 1∶200 , anti–γ-H2AX was used at 1∶1 , 000 , all antibodies from Bethyl laboratories were used at 1∶50 , anti-FANCD2 antibody at 1∶20 , and anti-MHF1 and anti-MHF2 [14] at 1∶200 ) . The appropriate secondary antibody ( either FITC or TRITC conjugated ) was used at 1∶400 in 1× TBS at 37°C for 1 h in the dark . Images were acquired using a wide field Olympus Biosystem microscope and the Velocity software . The antibody against chicken Atm was raised by Pocono Rabbit Farm ( Canada ) ; ATM human antibody , SNF2H , BAZ1A , RIF1 , and FANCI were all purchased from Bethyl Laboratories; and the RSF1 monoclonal antibody , phospho-ATM-S1981 , and γ-H2AX were from Millipore and NBS1 antibody from Novus . Human ATR and FANCD2 antibody were from Santa Cruz . Histone H3 . 1 , Actin , and BAZ1B were purchased by Abcam . CENPA antibody was a kind gift from Dr . Kevin Sullivan . MHF1 and MHF2 were a kind gift from Dr . Weidong Wang ( Baltimore , Maryland ) , and the FANCD2 antibody was a kind gift from Professor Minoru Takata ( Kyoto , Japan ) . Methyl cellulose medium was poured into 10 cm tri-section dishes ( Iwaki Cell Biology ) , and cells were plated in triplicate as follows: for 0 and 2 Gy , 50 cells were plated; for 4 Gy , 500 cells were plated; and for 10 Gy , 5 , 000 cells were plated . After irradiation , cells were incubated at 39°C for 7–9 d and the number of colonies was counted . After either siRNA ( Dharmacon ) or ATM inhibitor ( KU55933 , Selleckchem; added 1 h before irradiation ) treatment at the concentration recommended by the respective supplier , cells were counted and 500 cells were plated in 6 cm dishes for each dose used . After irradiation , cells were incubated at 37°C for 8–10 d , the media was removed , and the colonies visualized by staining with 0 . 25% dimethyl methylene blue ( Sigma ) and 50% ethanol for 45 min at room temperature . In the case of ICRF-193 and Olaparib treatment , drugs were added directly to the media and the cells were incubated for 8–10 d . Media was then discarded , and colonies were stained as indicated above . We modified a published [42] protocol . Briefly , 1×106 cells were harvested , resuspended in 50 µl ice-cold PBS , and mixed with an equal volume of 1% LMP agarose ( Sigma ) . The mixture of agarose and cells was poured in a casting mold ( Bio-rad ) and allowed to solidify at room temperature . The plugs containing the cells were extruded into 3 ml of Lysis Buffer ( 10 mM Tris-HCL , pH 7 . 5 , 50 mM EDTA , 1% Sarcosyl , and 2 mg/ml Proteinase K ) and incubated for 48 h at 50°C . An 0 . 8% InCert agarose ( BioRad ) gel was cast around the plugs , and the gel was run for 30 h at 14°C , 4 V/cm with a switch time every 300 s . Neutral Comet Assay was performed according to the manufacturer's ( Neutral Comet Assay , Trevigen ) protocol . NHEJ assays were performed as previously described in [32] , and HR assays were performed as described in [33] . | DNA carries all the information necessary for life; thus damage or loss of genetic material can result in cell death or cancer . The worst-case insult to genetic information is a DNA double-strand break , caused by agents either within the cell ( e . g . , by-products of respiration , errors of DNA replication ) or from outside ( e . g . , ionizing radiation ) . Ataxia telangiectasia kinase ( ATM ) and the Fanconi anaemia proteins perform housekeeping roles in the cell , recognising aberrant DNA structures and promoting their repair . Mutations that affect these proteins are responsible for the eponymous genetic syndromes that are characterised by elevated mutation rate , increased cancer risk , developmental defects , and shortened life span . In this work we identify and characterise a novel link between these two central players in the DNA damage response . We show that the Remodelling and Spacing Factor 1 ( RSF1 ) protein , which can reorganise the compaction of DNA to allow access for other proteins , requires ATM for its function after DNA damage . Specifically , RSF1 recruits two centromeric histone-like proteins that in turn promote mono-ubiquitination and recruitment to sites of damage of FANCD2 and FANCI—two proteins that belong to the Fanconi anaemia pathway . Absence of RSF1 results in defective repair of double-strand DNA breaks , prolonged arrest of the cell cycle , and cell death . Our study suggests that ATM-dependent regulation of the RSF chromatin-remodelling complex is necessary during double-strand break repair to recruit centromeric histones and then Fanconi anaemia proteins . | [
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] | 2014 | The RSF1 Histone-Remodelling Factor Facilitates DNA Double-Strand Break Repair by Recruiting Centromeric and Fanconi Anaemia Proteins |
During adolescence , the integration of specialized functional brain networks related to cognitive control continues to increase . Slow frequency oscillations ( 4–10 Hz ) have been shown to support cognitive control processes , especially within prefrontal regions . However , it is unclear how neural oscillations contribute to functional brain network development and improvements in cognitive control during adolescence . To bridge this gap , we employed magnetoencephalography ( MEG ) to explore changes in oscillatory power and phase coupling across cortical networks in a sample of 68 adolescents and young adults . We found a redistribution of power from lower to higher frequencies throughout adolescence , such that delta band ( 1–3 Hz ) power decreased , whereas beta band power ( 14–16 and 22–26 Hz ) increased . Delta band power decreased with age most strongly in association networks within the frontal lobe and operculum . Conversely , beta band power increased throughout development , most strongly in processing networks and the posterior cingulate cortex , a hub of the default mode ( DM ) network . In terms of phase , theta band ( 5–9 Hz ) phase-locking robustly decreased with development , following an anterior-to-posterior gradient , with the greatest decoupling occurring between association networks . Additionally , decreased slow frequency phase-locking between frontolimbic regions was related to decreased impulsivity with age . Thus , greater decoupling of slow frequency oscillations may afford functional networks greater flexibility during the resting state to instantiate control when required .
The transition from adolescence to adulthood is characterized by significant enhancements in brain function , supporting increased cognitive control and normative decreases in impulsivity [1 , 2] . Developmental task-based functional magnetic resonance imaging ( fMRI ) studies indicate that core regions supporting cognitive control ( e . g . , anterior cingulate cortex [ACC] and anterior insula [aIns] ) are engaged in adolescence during cognitive tasks , but their blood oxygen level–dependent ( BOLD ) signal activation [3 , 4] and connectivity with other brain regions continue to increase into adulthood [5–7] . As such , brain networks supporting cognitive control are present prior to adolescence; however , the successful instantiation of cognitive control continues to improve [8] . Developmental resting-state fMRI ( rs-fMRI ) studies analyzing whole-brain connectivity patterns parallel this principle , such that the organization of functional brain networks is relatively stable by childhood [7 , 9 , 10] , while integration ( between-network functional connectivity ) continues to refine well into late adolescence and early adulthood , supporting improvements in cognitive control [7] . The majority of developmental research on resting-state functional networks has utilized fMRI ( see [11] for a review ) , providing the field a window into the development of resting-state networks at infra-slow frequencies ( 0 . 01–0 . 10 Hz ) . However , much less is known about the development of these networks at faster frequencies ( i . e . , 1–10 Hz oscillations ) known to support the cognitive constructs that demonstrate a protracted development [12] . Because fMRI is not sensitive to this timescale of oscillation , magnetoencephalography ( MEG ) serves as a complementary tool to understand resting-state network development by allowing us to explore this relatively faster oscillatory range . The correlation between electrophysiology and BOLD has been studied in both human and nonhuman primates , with a consistent finding of correlations between modalities in broadband gamma activity ( 40–100 Hz ) within local neuronal pools during tasks [13 , 14] . Oscillations in this frequency range play a role in enabling local neuronal synchronization , whereas slower frequency ( 4–14 Hz ) oscillations have been shown to support long-distance integration [15 , 16] . For example , synchronization of slow frequency oscillations within the frontoparietal ( FP ) network [17] are associated with cognitive control and have been shown to improve behavioral performance on control tasks [18 , 19] . Additionally , theta band activity ( 4–10 Hz ) intensifies when control demands are increased [20] . Hence , slow frequency oscillations across control regions may contribute to top-down modulation of processing networks [12 , 21 , 22] . For example , long-range interactions from frontal to visual association regions during working memory retention and mental imagery evolved most strongly in the theta and alpha frequency range [23 , 24] . Moreover , evidence suggests that the prefrontal cortex leads the posterior parietal cortex in sustained visual attention tasks in the theta band [25] . Slower frequency oscillations , often in the theta band , have been shown to organize local neural activity in the gamma band , such that neurons tend to have greater firing rates in the trough of an ongoing slow frequency oscillation , providing a temporal template for neuronal communication [22 , 26] . As such , the phase of slower frequency oscillations , especially within the theta band , may be critical for coordination of neural activity over long distances [22 , 27] . In addition to task states , the electrophysiological correlates of control networks defined by BOLD fMRI during the resting state are becoming clearer . Resting-state BOLD networks correlate to the alpha and beta band , as measured with MEG [28] . There is additional evidence suggesting that correlations with BOLD may be greater at even slower frequencies , such as delta and theta bands ( 1–10 Hz ) [29] . Recently , Hacker and colleagues characterized the spatial correspondence in humans of resting-state BOLD fMRI and band-limited power using electrocorticographic recordings , discovering frequency-specific oscillations within association networks in the slow frequency range ( 3–14 Hz ) [30] . In sum , association networks map onto slower frequency oscillations ( 4–14 Hz ) that may support coordinating activity of other brain networks . Electrophysiological ( i . e . , electroencephalography [EEG]/MEG ) studies have begun to offer insight into development changes in cortical oscillations . The majority of research concerning electrophysiological maturation across development has used EEG , finding age-related decreases in total power ( total amount of activity across broadband frequencies ) [31] and absolute power in each frequency band [31–34] . Additional work has shown that there is a redistribution of relative power ( power in a given band in relation to total power across all frequencies ) from lower to higher frequency bands [35] , with frontal regions reaching adult levels of power after more posterior processing regions [31 , 32 , 36] . Similar posterior-to-anterior gradients have been observed using EEG measures of coherence , an index of regional coupling including both phase and amplitude components [37] . Notably , the curvilinear decreases in the delta and theta bands ( i . e . , 0 . 5–7 Hz ) are highly correlated with gray matter volume decreases during adolescence [38] . Using MEG , increased amplitude correlations have been observed both within and between functional brain networks at rest throughout adolescence [39] . Although these studies have begun highlighting developmental trajectories of neural oscillations , the poor spatial specificity of EEG and lack of brain/behavior relationships utilizing MEG/EEG have limited our understanding of the regional and functional network development of oscillations and their potential contribution to cognitive development . We sought to bridge this gap in the understanding of adolescent development , linking the age-related changes in brain network oscillations to cognitive development . In a sample of 68 adolescents and young adults ( aged 14–31 years ) , we employed MEG to explore intrinsic properties related to oscillatory developmental within and between cortical networks , with regard to both power and phase . Specifically , within frequency intervals related to interareal neural interactions ( 1–49 Hz ) [40 , 41] , we examined regional and network-level oscillatory power and functional coupling of well-defined brain networks using the phase-locking value ( PLV ) , similar to recent approaches [42] . Unlike correlation or coherence measures , the PLV ignores the amplitude ( power ) relationship between 2 oscillators . This enhances the ability to analyze phase relationships between brain regions , which is known to support interareal communication between large neuronal pools [26] . Interareal phase relationships in the theta band increase across multiple components of cognitive control [12] , including working memory [43] , error commission [44] , and conflict . Similar to previous EEG studies , we found a redistribution of regional power from slower delta band oscillations to faster beta band oscillations , with greater decreases in delta band power anteriorly in the cortex and greater increases in beta band power posteriorly . In terms of phase , we demonstrate age-related decreases in phase-locking of slow frequency ( 5–9 Hz ) oscillations during adolescence , which followed a robust anterior-to-posterior gradient , with the greatest age-related changes in midline frontal regions , an area known have protracted cognitive development throughout adolescence [1 , 3 , 7] . Using a priori network membership , we show that the greatest developmental slow frequency decoupling occurred in higher-order association networks , relative to processing networks . Finally , we demonstrate that decoupling of slow frequency oscillations between anterior prefrontal regions and the anterior temporal lobe is related to self-reported impulsivity , a developmentally sensitive measure of cognitive control known to decrease robustly throughout adolescence .
In order to probe developmental changes in functional brain regions and networks , we used a previously defined functional parcellation established from rs-fMRI [45] to parcellate the cortical surface into 333 regions of interest ( ROIs ) in a sample of 68 individuals aged 14 to 31 years . For each ROI at each frequency ( 1–49 Hz; 1 Hz intervals ) , we calculated relative power to probe regional age-related changes in regional power and a PLV between each ROI pair to determine the age-related differences in degree of coupling between the phases of the oscillations between regions ( see Fig 1 for workflow overview ) . First , we averaged the PLV matrices at each frequency across both ROI dimensions for each frequency and subject . This resulted in one global cortical PLV for each frequency , for each subject . There was no significant main effect of age predicting PLV ( β = −0 . 0004 , t = −1 . 255 , χ2 ( 1 ) = 1 . 576 , p = 0 . 209 ) . However , there was a significant age by frequency interaction predicting PLV ( χ2[48] = 125 . 56 , p < 0 . 001 ) . A significant negative relationship between global PLV and age at each frequency interval between 5 and 9 Hz ( all p < 0 . 05 , false discovery rate [FDR] corrected ) emerged , suggesting that phase relationships between regions in the 5–9 Hz frequency band become less coupled throughout adolescence ( Fig 2A ) . No other frequency intervals showed a significant age-related change in PLV ( all p > 0 . 05 ) . Similar to the PLV analysis , for each subject , we computed relative power at each frequency ( 1–49 Hz in 1 Hz intervals ) for each ROI ( see Methods for details ) . Similar to the PLV analysis , we obtained a measure of global power by averaging relative power across each ROI for each frequency . We observed a significant negative relationship between delta band power ( 1–3 Hz ) and age ( all p < 0 . 05 , FDR corrected ) , such that delta band power decreased with age ( Fig 2B ) . Conversely , beta band power ( 14–16 Hz and 22–26 Hz ) significantly increased with age ( all p < 0 . 05 , FDR corrected ) , supporting previous developmental EEG studies noting a shift in power distribution , such that slower wave oscillations tend to shift towards relatively higher frequencies at rest [31 , 32 , 36] . There was no evidence for a significant relationship between 5–9 Hz power and age ( t = −0 . 36 , p = 0 . 71 ) . Moreover , we did not observe a significant relationship between PLV and power ( t = −0 . 01 , p = 0 . 99 ) . These results further support the notion that phase and power are largely orthogonal , providing complementary information in regard to the development of neural oscillations . To determine the anatomical locus of PLV decreases with age in the 5–9 Hz band , we averaged each individual subject’s PLV matrices in the 5–9 Hz frequency interval . Next , we regressed age onto each ROI pair’s PLV , controlling for motion and power ( see Methods ) and extracted the beta weight for age from each model . This resulted in a pairwise matrix of beta weights ( beta matrix ) , representing the rate of change across development in slow frequency PLV for each ROI pair . We examined whether age-related changes in PLV demonstrated anatomical gradients across the cortex . To that end , we obtained a summary rate of change for each ROI by summing down the columns of the beta matrix and regressing each ROIs summed beta weight against its y-coordinate ( in Montreal Neurological Institute [MNI] coordinate space ) in each hemisphere and x-coordinate , separately . Average distance from each ROI to every other ROI and ROI surface area were included as nuisance regressors in all regression models to control for distance-dependent artifacts ( i . e . , anatomically proximal regions have artificially inflated PLV ) . Along the anterior-to-posterior axis , we observed a significant negative relationship between the summed beta weights and the y-coordinate ( t = −13 . 19 , p < 10−10 ) , indicating a strong anterior-to-posterior gradient of PLV change , such that frontal regions showed greater decreases in theta band PLV ( i . e . , more decoupling ) with age than posterior regions ( Fig 3A and 3B ) . Regions undergoing the greatest decrease in PLV ( top 5% ) over development are rank ordered in Table 1 . In the lateral-to-medial gradient , we observed a significant negative relationship between the summed beta weights and the x-coordinate in the left hemisphere ( t = −6 . 97 , p < 10−10 ) but only a trend in the right hemisphere ( t = 2 . 01 p = 0 . 05 ) , indicating slow frequency PLV decreased more rapidly with age along the medial wall . In sum , the greatest rate of decrease in slow frequency PLV occurred in midline frontal regions . In addition to the PLV analysis , we also characterized regional changes in power throughout adolescence . For each region , we summed the beta weights across frequencies demonstrating a significant Power × Age relationship in Fig 2B , for delta and beta bands separately . Similar to slow frequency PLV , delta band power demonstrated a significant anterior-to-posterior gradient ( t = −10 . 33 , p < 0 . 0001 ) , with the largest age-related decreases in delta power occurring in frontal regions , especially in the frontal operculum ( Fig 4A ) . In contrast to delta power , developmental beta band increases in power followed a posterior-to-anterior gradient ( t = 15 . 86 , p < 0 . 0001 ) , such that the greatest developmental increases in beta band power occurred in medial and lateral parietal regions ( Fig 4B ) . Of note , the posterior cingulate cortex , a hub of the default mode ( DM ) network , demonstrated the greatest age-related increase in beta band power . Power in the 5–9 Hz frequency interval did not demonstrate any significant age-related increases or decreases ( t = −0 . 36 , p = 0 . 71 ) , nor did 5–9 Hz power demonstrate any significant developmental anterior-to-posterior gradients ( t = −1 . 70 , p = 0 . 09 ) . To assess developmental changes in the anterior-to-posterior gradient of PLV in other frequency bands , for each subject and each ROI , we regressed age onto PLV and extracted the resulting beta weight for age . Beta weight matrices were generated for each frequency interval ( see Methods ) , summed , and regressed against the ROI’s y-coordinate . We then extracted the beta weight from the y-coordinate regressor in each regression model and plotted this as a function of frequency ( Fig 3C ) . Slow frequency age-related decreases in PLV were most prominent at 6 Hz . To quantify these results statistically , we tested for significant differences in the correlation between ROI beta weights and anterior-to-posterior gradients between a given frequency interval ( in 5 Hz bins ) by comparing the slopes ( i . e . , beta weights ) of the regression models from each frequency interval to the 6–10 Hz interval ( see Methods for more details ) . A significant difference would be reflected in a z-statistic > 1 . 645 , p < 0 . 05 , one-tailed , indicating that the 6–10 band had a significantly greater negative slope between the summed beta weights for PLV × Age and the anatomical y-coordinate of the region . We did not find evidence for a significant difference for the alpha range ( intervals from 11–15 Hz; z = 0 . 13 , p > 0 . 05 ) . However , for frequencies less than 6 Hz and greater than 15 Hz , we did find a significant interaction ( all z > 1 . 645 , p < 0 . 05 ) , indicating that the greatest gradients in PLV occur within the theta and alpha band regime . To quantify developmental changes in the anterior-to-posterior gradient of power across all frequency bands , for each subject and each ROI , we regressed age onto power and extracted the resulting beta weight for age . As in the PLV analysis , beta weight matrices were generated for each frequency interval ( see Methods ) and were regressed against the ROI’s y-coordinate . We observed a negative gradient in the delta regime , whereas a positive gradient existed in the beta band ( Fig 4C ) . Thus , age-related decreases in delta band power were most prominent in frontal regions , whereas age-related changes in beta band power were most prominent in posterior regions . Next , we aimed to determine whether our developmental effect of an anterior-to-posterior gradients of PLV and power differences with development were specific to the resting state versus a task state . To this end , we analyzed data from the maintenance period of a working memory paradigm in a subset of our sample ( n = 28; details of MEG task methods and results in Methods ) . After extracting pairwise PLVs and regional power for each subject and frequency band within the 5–9 Hz band , we averaged across frequency bands , resulting in 1 phase-locking matrix per subject . Paralleling the resting-state analysis , we regressed age on each pairwise PLV across subjects , controlling for subject head motion . We extracted the beta weight from the age regressor , resulting in a beta weight matrix , representing linear effects of age on changes in PLV during working memory maintenance . To test for an anterior-to-posterior effect as was observed during the resting state , we summed down the columns and regressed the ROI’s y-coordinate on this summed linear age effect . We did not observe an anterior-to-posterior gradient during working memory maintenance ( t = −0 . 02 , p = 0 . 98 ) . Moreover , we did observe the anterior-to-posterior gradient in this subset of subjects ( t = −9 . 31 , p < 10−10 ) during rest . These findings suggest that the strong decreases in 5–9 Hz phase-locking in frontal regions likely are specific to the resting state . Similar to PLV , the age-related effects in delta and beta power were specific to the resting state . We calculated power during the maintenance period of the working memory task across the delta ( 1–3 Hz ) and beta band ( 14–16 Hz and 22–26 Hz ) . For each frequency interval and each ROI , we regressed age against power and extracted the beta weights from the age regressor . For each frequency interval , we regressed the y-coordinate against the beta weights . We did not observe an anatomical gradient within the delta band or beta band during the maintenance period of the task ( all p > 0 . 05 , FDR corrected ) , suggesting that age-related effects in power are also specific to the resting state . Together , these results indicate that adolescence is characterized by frequency-specific changes in PLV and power that are specific to the resting state . In addition to specific regional changes in PLV , we aimed to characterize developmental changes in PLV as a function of networks [45] . For each network combination ( e . g . , DM-DM , DM-FP , etc . ) , we obtained the mean beta weight of the linear effect of age on PLV for all ROI pairs of the networks being compared . The resulting heat map is shown in Fig 5A . We then performed a one-way ANOVA to quantitatively assess whether some networks experienced a greater rate of change in PLV with age compared to others . Here , we submitted summed beta weights of within-network interactions ( e . g . , DM to DM ) to the ANOVA . As determined by the ANOVA test , there was a significant difference in the summed beta weight for age effects at the network level ( F[12 , 320] = 9 . 57 , p = 10−10 ) . A subsequent post hoc analysis revealed that the negative linear age effect was greatest for the salience ( SAL ) network compared to any other network ( p < 0 . 05 ) ( Fig 5B ) . More generally , a t test between the beta weights within association networks and the beta weights within processing networks revealed that PLV within association networks decreased with age significantly more compared to processing networks ( t = −6 . 51 , p < 0 . 001 ) . To make inferences concerning significant developmental differences in delta band and beta band power at the network level , we performed a one-way ANOVA on the beta weights by grouping the regions according to a priori network affiliation for the delta and beta regime , separately . With respect to the delta band , we found a significant difference in the average beta weight for age effects at the network level ( F[12 , 320] = 22 . 71 , p = 10−36 ) . A subsequent post hoc analysis revealed that age-related decreases in delta power within networks were greatest for the auditory , SAL , cinguloopercular , and FP networks ( all post hoc comparisons were corrected for multiple comparisons using the Tukey method ) . For complete post hoc results , see Table 2 . With respect to beta band power , we also found a significant difference in the average beta weight for age-related differences at the network level ( F[12 , 320] = 12 . 52 , p = 10−20 ) . A subsequent post hoc analysis revealed that age-related increases in beta power were greatest for somatomotor , auditory , and visual networks . For complete post hoc results , see Table 3 . After determining the gradient and locus of decreased phase coupling from adolescence to adulthood , we analyzed specific ROI pairs driving this decrease . Specifically , we aimed to determine the specific pairwise interactions that contributed to the greatest rate of 5–9 Hz oscillatory decoupling . We first identified the top 5% of ROIs that showed the greatest rate of 5–9 Hz decoupling ( developmental hubs ) from the regional analysis . From those ROIs , we extracted the top 5% of negative beta weights and plotted the connections , with ROIs grouped by networks ( Fig 6 ) , as assigned by [45] . All ROIs from the regional analysis were within higher-order association networks , with 8 belonging to the DM network , 3 belonging to the FP network , 1 belonging to the SAL network , 1 belonging to the ventral attention ( VA ) network , and 3 belonging to an undefined network , though all regions were within anterior portions of the frontal lobe and are considered part of the limbic network in other parcellations ( e . g . , ref [46] ) . With the exception of 2 links , all links from these developmental hubs were to regions of other association networks , indicating that pairwise decreases in 5–9 Hz coupling are largely specific to association networks . We have demonstrated a strong decrease in 5–9 Hz PLV within midline frontal regions . Given the role of anterior prefrontal cortex and anterior temporal lobes in impulse control [47] and the role of theta ( 4–10 Hz ) oscillations in cognitive control [12] , we sought to determine whether decreases in frontal slow frequency PLV were related to decreased impulsivity throughout adolescence . The UPPS-P Impulsive Behavior Scale is a validated self-report 59-item measure of impulsivity [48] . Items are endorsed on a 4-point scale from 1 ( agree strongly ) to 4 ( disagree strongly ) . After appropriate reverse scoring , scores for each item range from 1 ( non-impulsive answer ) to 4 ( high level of self-reported impulsivity ) . The UPPS-P can provide scores from specific subscales ( e . g . , Urgency , Lack of Premeditation , Lack of Perseverance , Sensation Seeking ) . In the current analysis , we utilized a total impulsivity measure ( mean across all items ) to increase the precision of each subject’s estimate . Within our sample , total impulsivity scores from the UPPS-P scale ( M = 2 . 02 , SD = 0 . 35; Range [1 . 32 , 2 . 75] ) were consistent with normative variability in impulsivity as reported in previous work [49] . Furthermore , the Cronbach α for the total impulsivity measure in our sample was 0 . 93 , indicating excellent internal consistency . Total impulsivity was negatively associated with age ( β = −0 . 333 , t = −2 . 74 , p = 0 . 008 ) , such that impulsivity decreased significantly with development . To obtain a cluster of regions that significantly decreased in PLV as a function of age , we submitted the individual subject matrices to the network-based statistic ( NBS ) [50] . The NBS is a common tool used in rs-fMRI studies to identify clusters of suprathreshold links displaying a similar effect ( e . g . , increasing or decreasing PLV with age ) . It seeks to control family-wise error rate when mass univariate testing occurs , as in the case of running regression analyses on each ROI pair . Briefly , a test statistic is generated for each ROI pair’s PLV as a function of age . A cluster is identified using a breadth first search , followed by permutation testing to significance based on a cluster’s size . A cluster composed of 49 regions with 122 links survived the permutation test ( 1 , 000 resamples; red links in Fig 7A ) . Similarly , we performed a median split on impulsivity to break the sample into a high impulsivity group and a low impulsivity group . Individual subject matrices were once again submitted to the NBS , controlling for age . A cluster composed of 13 regions with 14 links survived the permutation test ( 1 , 000 resamples; orange links in Fig 7A ) . Three links comprising 5 distinct regions overlapped between the 2 clusters ( PLV × Age and PLV × Impulsivity; yellow links in Fig 7A ) . For statistical confirmation of overlap between PLV and age with PLV and impulsivity , we subsequently submitted to 3 separate mediation analyses . The fist link ( L1 ) was between the left superior frontal gyrus ( MNI coordinates: −15 . 05 , 64 . 73 , 13 . 29 ) and the right inferior frontal gyrus ( MNI coordinates: 25 . 07 , 7 . 38 , −16 . 41 ) , the second link ( L2 ) was between the left temporal gyrus ( MNI coordinates: −50 . 60 , 9 . 26 , −18 . 71 ) and right medial frontal gyrus ( MNI coordinates: 12 . 40 , 25 . 55 , −16 . 38 ) , and the third link ( L3 ) was between the left middle temporal gyrus ( MNI coordinates: −44 . 87 , 7 . 38 , −34 . 85 ) and the right medial frontal gyrus ( MNI coordinates: 12 . 40 , 25 . 55 , −16 . 38 ) . As a separate means of dimensionality reduction more focused on the a priori network organization , as well as the strong 5–9 Hz decoupling within the SAL network , we also tested mean SAL network PLV as a mediator between age and impulsivity . Mean SAL network PLV was not associated with UPPS-P total impulsivity scores while co-varying age ( β = −0 . 183 , t = −1 . 45 , p = 0 . 152 ) . In addition to PLV , we also tested delta band power and beta band power for meditation in the relationship between age and impulsivity . Neither delta ( minimum p = 0 . 47 , FDR corrected ) nor beta-power ( minimum p = 0 . 90 , FDR corrected ) in any node significantly mediated the relationship between age and impulsivity . Together , these results indicate that resting-state slow frequency phase-locking , not power , contributes to age-related decreases in impulsivity . Mediation analysis on each link separately revealed that partialing out the variance of each of the 3 ROI pairs significantly attenuated the relationship between age and impulsivity ( indirect pathway [path ab] , L1: β = −0 . 133 [95% CI −0 . 244 to −0 . 017] , p = 0 . 03; L2: β = −0 . 154 [95% CI to −0 . 322 , −0 . 023] , p = 0 . 02; L3: β = −0 . 130 [95% CI , −0 . 251 to −0 . 036] , p = 0 . 003 ) . For statistics on individual paths , see Fig 7B . These findings suggest the observed age-related decreases in impulsivity is , in part , accounted for by the decoupling of slow frequency oscillations during the resting state between the anterior prefrontal cortex and the anterior temporal lobe . However , care should be taken when interpreting the mediation effects , as links demonstrating significant mediation did not survive multiple comparisons corrected when all PLV × Age links were tested together . Regardless , overlapping links between brain/behavior and brain/age relationship suggest that slow frequency PLV , in part , contributes declining impulsivity during adolescence .
Interactions between functional brain networks demonstrate a protracted development well into adolescence and early adulthood [6 , 7 , 10] and have been shown to support the maturation of cognitive control [7] . However , the development of resting-state network oscillations and their contribution to cognitive development have not been explored . We found a decrease in theta band ( 5–9 Hz ) phase coupling that was strongest in midline frontal regions , especially in association networks . In parallel , many of the strongest pairwise decrease in resting-state theta coupling occurred between regions affiliated with the DM , FP , and SAL networks . Furthermore , decreased slow frequency coupling between anterior frontal and temporal lobe regions was related to decreased impulsivity with development , providing an oscillatory contribution for decreased impulsivity throughout development . In terms of oscillatory power , we found a redistribution of power from slower delta oscillations to faster beta oscillations . These findings support and extend prior resting-state EEG [31 , 34] , and concurrent EEG-fMRI studies [51] have reported significant developmental decreases in delta power and increases in beta power [35] . Here , we extend these findings through source localization enabling characterizing of these developmental changes in terms or regions and functional networks . Specifically , there were significant age-related decreases in delta power , most strongly in frontal and opercular regions comprising the SAL and cinguloopercular networks . Conversely , there were significant age-related increases in beta power , most prominent in processing networks . The posterior cingulate cortex , a hub of the DM , demonstrated the greatest age-related increase in beta band power . The DM network demonstrates a protracted development in BOLD connectivity [52] , supporting increased specialization and integration of this network with other functional networks [53] . A canonical feature of electrophysiological estimates of power and phase during the resting state is the dominance of oscillations in posterior regions of the brain . The negative slope of age-related decreases as a function of the posterior-to-anterior gradient suggests that frontal regions are becoming more decoupled broadly but most prominently , and statistically significantly , for the 5–9 Hz ( theta ) band . The post hoc analysis in which we tested for significant differences in the correlation between ROI beta weights and anterior-to-posterior gradients between a given frequency interval ( in 5 Hz bins ) statistically supports the notion that the anterior-to-posterior gradient is most prominent for the 5–15 Hz frequency interval , which includes the theta ( 5–9 Hz ) interval in which we observed a significant negative relationship between PLV and age . Thus , the gradient analyses , in conjunction with Fig 3A , provide evidence that theta band ( 5–9 Hz ) decoupling is most prominent in midline prefrontal regions . Similar to early electrophysiological work using EEG to study coherence between cortical lobes [54] , we found a protracted development of control networks within the 5–9 Hz frequency interval , particularly within the SAL network , comprised of the anterior cingulate and aIns . Both of these regions are anatomical and functional hubs of the cortex [55 , 56] , with anatomical connections to several major brain networks . Generally , theta band oscillations have been shown to organize higher frequency activity , providing a temporal template for neuronal communication [22 , 26] . Thus , the phase of theta band oscillations may be critical for the coordination of neural activity [22 , 27] . Supporting this supposition , a large body of evidence suggests oscillations arising from the SAL network entrain disparate control networks when the need for control is realized [12] . Because adolescence is marked by substantial reductions in behavioral variability that is reliant on control networks [4 , 57 , 58] , we propose that age-related frontal theta decoupling during the resting state may support the enhanced ability for adults to reliably instantiate control and coordinate regulatory control networks . In support of this , BOLD connectivity studies have found increases in the spatial variability of control and attention networks with development but stability of processing networks [53] . A cluster of frontolimbic regions in anterior prefrontal and anterior temporal lobes also displayed slow frequency decoupling with development . Interactions between these frontolimbic regions and the SAL network had the greatest rate of decoupling of any within- or between-network comparison ( Fig 5A ) . Frontolimbic connectivity is often prescribed a role in impulse control , and when structurally lesioned , leads to greater impulsivity [59 , 60] . Additionally , recent diffusion tensor imaging and fMRI evidence suggests that frontolimbic connectivity decreases both structurally and functionally throughout adolescence [61 , 62] . Here , we showed evidence that several interactions between frontolimbic regions were related to impulsivity and also demonstrated significant slow frequency decoupling , confirmed by a mediation analysis . Theta band ( 5–9 Hz ) oscillations may be the mechanism by which these regions communicate to execute impulse control given the role of theta oscillations in the instantiation of cognitive control [12] . Lending support to this proposal , theta band activity tends to flow from frontal regions to more posterior regions [63] , suggesting a possible causal association . Phase-locking should be largely unaffected by power within the same frequency band ( but see ref [64] ) . While age-related changes in PLV and power are related to overarching processes of brain maturation through adolescence , they inform different levels of neural processing . While frequency changes reflect local circuit modifications , PLV reflects the possible interareal effects of these circuit modifications , specifically with regard to coupling across brain regions . Distinct circuit and systems-level modifications are evident through adolescence that would have direct effects on both frequency and coupling ( see [65] for a review ) . At the circuit level , power may be directly affected by maturation inhibitory circuitry supported by increases in GABA , particularly parvalbumin interneurons within the prefrontal cortex [66–68] , resulting in greater power within the beta/gamma frequency range [69] . In parallel , and likely indirectly related , there are systems-level changes in specialization of existing connections , such as age-related decreases in frontolimbic connectivity [10 , 61] , that would contribute to the decoupling of slow wave oscillations affecting PLV . As such , developmental decreases in phase-locking may reflect stochastic resonance and/or neural flexibility [70] . If the brain were to maintain a rigid configuration of interactions at this timescale during rest , the ability to explore and switch between brain states would be undermined . Indeed , a prominent theory on the nature of resting state proposes that it serves to allow the sampling of multiple network configurations along an anatomical backbone [71 , 72] . If this is the case , functional brain networks require flexibility in the form of imperfectly coupled oscillators ( i . e . , variability ) to maintain dynamics in networks at this timescale ( millisecond ) . Several studies have found evidence for increased cortical variability throughout development [70 , 73 , 74] . Our findings here support these fMRI-based findings in that decreased phase-locking may represent an overall age-related increase in variability [40 , 75 , 76] , as well as an overall increase in signal complexity . A potential limitation of the current study is the depth sensitivity of MEG . The signal-to-noise ratio ( SNR ) falls with increasing distance from the MEG sensors . However , this limitation exists across all subjects , and thus all ages considered in this study . Given this limitation , we were able to demonstrate decreases in theta band phase-locking within medial wall structures that showed specificity to the resting state versus a working memory task-state . In sum , our results support and extend previous electrophysiological work characterizing the development of oscillatory power , such that power is redistributed from slower frequency oscillations to faster frequency oscillations . Slow frequency delta oscillations decreased most with age in the frontal operculum , whereas faster beta band oscillatory power increased most strongly in processing networks and the posterior cingulate cortex . Additionally , we found evidence that developmental decreases in slow frequency coupling between control networks supports the transition from adolescence to adulthood that may be related to age-related improvements in impulse control . Age-related decreases in coupling of these oscillations during the resting state may be a mechanism of increased neural flexibility that occurs during adolescence [57 , 73 , 74] . As such , future studies should probe frontal theta as a mechanism by which control instantiation is refined during adolescence , using tasks that probe cognitive flexibility , such as task switching and rapid instructed task learning paradigms [77] .
All subjects gave written informed consent; parent or guardian consent was obtained for all subjects aged 14 to 17 years . The University of Pittsburgh Institutional Review Board ( IRB protocol number: PRO10090478 ) approved the study , adhering to the Declaration of Helsinki . Subjects were compensated monetarily for their participation in the study . Of the 81 adolescents and adults we recruited for this study , we include data from 68 subjects , ranging in age from 14 to 31 years ( M = 22 . 51 , SD = 5 . 55 ) . Thirteen subjects were dropped due to unavailable ECG and/or electrooculogram ( EOG ) data . Based on a questionnaire , none of the subjects—nor their first-degree relatives—currently or previously had a psychiatric or neurological disorder . For each subject , we acquired a structural MRI to coregister MEG data for analyses in source space . Data from the 68 remaining subjects were pooled from 2 separate protocols within the lab and thus had slightly different structural MR sequences , which would not affect subsequent processing steps . For 28 subjects , structural images were acquired using a sagittal magnetization-prepared rapid gradient-echo sequence ( repetition time [TR] = 2 , 100 ms , echo time [TE] = 3 . 43 ms , flip angle = 8° , inversion time [TI] = 1 , 050 ms , voxel size = 1 mm isotropic ) . For the other 40 subjects included in the second protocol , structural images were acquired using a sagittal magnetization-prepared rapid gradient-echo sequence ( TR = 2 , 200 ms , TE = 3 . 58 ms , flip angle = 9° , TI = 1 , 000 ms , voxel size = 1 mm isotropic ) . Resting-state MEG data ( 300 seconds ) were acquired using an Elekta Neuromag Vectorview MEG system ( Elekta Oy ) comprising 306 sensors arranged in triplets of 2 orthogonal planar gradiometers and 1 magnetometer , distributed to 102 locations . The MEG scanner was located inside a 3-layer magnetically shielded room within the University of Pittsburgh Medical Center . The data were acquired continuously with a sampling rate of 1 , 000 Hz . Head position relative to the MEG sensors was measured continuously throughout the recording period to allow off-line head movement correction . Two bipolar electrode pairs were used to record vertical and horizontal EOG signals to monitor eye movement . A potential confound of developmental studies using MEG is that head size is smaller in younger subjects . Given the sensor locations in the MEG helmet are fixed , smaller heads will by definition have lower signal to noise , as they are further from the sensors . On average , head size is fully developed by 10 years of age [78] , which is well below the age of our youngest subject ( 14 years ) . We regressed age onto intracranial volume ( ICV ) and did not observe a significant relationship between ICV and age ( t = −1 . 05 , p = 0 . 29 ) . Additionally , we regressed ICV onto global theta band ( 5–9 Hz ) PLV and did not observe a significant relationship between ICV and global theta band PLV ( t = −0 . 02 p = 0 . 96 ) . For artifact removal , we first manually visually inspected every channel across the resting state run for noisy or flat channels and squid jumps . MEG data were then preprocessed off-line using the temporal signal space separation ( tSSS ) method ( 10 second correlation window , 0 . 98 correlation limit ) , which uses spatial and temporal features to separate signals into components generated within the MEG helmet and components from outside the helmet , which must be artifactual [79 , 80] . This method greatly increases the SNR of the resulting data [81] . tSSS also performs head movement compensation by aligning sensor-level data to a common reference [82] . This head motion correction procedure also provides estimates of head motion relative to sensor coordinates that we subsequently used for head motion estimates for each subject . Lastly , the raw time series data were down-sampled to from 1 , 000 Hz to 250 Hz . An independent components analysis ( ICA ) approach was used to automatically detect and attenuate heartbeat , eye blink , and eye movement artifacts . ICA was performed on each channel using the Infomax algorithm , with the number of components selected to account for 95% of the variance . The Pearson correlation of the components and the ECG or EOG channel is used to identify artifactual sources through an iterative thresholding method ( as implemented in minimum-norm estimate [MNE] Python [83] ) and subsequently manually inspected . After removal of the artifactual sources , the data were reconstructed from the remaining components . MEG sensor data were then projected from the sensors on to the cortical surface to estimate source activities , using the MNE procedure . First , the geometry of each participant's cortical surface was reconstructed from the respective structural MRI using FreeSurfer [84 , 85] . The solution space for the source estimation was then constrained to the gray/white matter boundary by placing 5 , 124 dipoles per hemisphere . A forward solution for the constructed source space was calculated using a single compartment boundary-element model . The noise covariance matrix was calculated from a 2-minute empty room scan , in which we acquired data with no subject present . The noise covariance matrix and the forward solution were then combined to create a linear inverse operator to project the resting-state MEG sensor data to the cortical surface . We then warped individual subject data from native space to FreeSurfer average space to facilitate between-subject interpretation of specific regions and networks . We extracted the time series of resting-state MEG data from a recent parcellation of 333 ROIs covering the entire cortical surface [45] . This atlas was chosen because it comprises major cortical functional networks , including control networks , processing networks , and the DM network and covers the entire cortical surface . Developmental changes in these networks have been observed in fMRI studies [6 , 7] and are thus candidates for electrophysiological developmental changes at the timescales of which MEG is sensitive . For each pair-wise relation between ROIs for each subject , a PLV was calculated for each frequency of interest ( 1–49 Hz in 1-Hz intervals ) . Phase-locking is a measure of the propensity for 2 signals to maintain a constant phase separation with each other ( i . e . , synchrony ) . Therefore , the PLV provides a measure of temporal variability between 2 MEG signals [40] . Here , we binned the data into 100 three-second chunks and obtained 1 PLV across the time windows using a multitapers method with digital prolate spheroid sequence ( DPSS ) windows ( 3 tapers ) , as implemented in MNE python ( mne . spectral . connectivity ) . Three seconds is a sufficiently long segment of data to obtain a reliable estimate of oscillations as low as 1 Hz , as a common recommendation for the minimum number of cycles per window to achieve reliable frequency estimates is 3 [86] . To calculate the PLV at each frequency , 2 time series are spectrally decomposed at a given frequency , given by the equation PLV=1N|∑n=1Nei ( θ1 ( n ) −θ2 ( n ) ) | where N is the number of sampled time points and θ1 and θ2 are the phase values at time point n . The PLV was calculated for each ROI pair , resulting in 55 , 278 PLVs for each frequency and for each subject . A single averaged PLV was then computed by averaging all of the PLVs , ranging from 0 to 1 , representing a random phase relationship and fixed phase relationship , respectively . For each ROI , power was calculated using the Welch method ( pwelch function in MATLAB ) on the 100 three-second chunks of data , with an overlap of 50% . The relative power at each frequency interval in the range of 1–49 Hz ( 1 Hz bins ) was calculated by dividing the power at a given frequency by the total power ( summed power ) in the 1–49 Hz interval . This value represents the relative magnitude of each frequency in relation to the total signal . After ROI × ROI PLV individual subject matrices were calculated at each frequency , individual subject matrices were concatenated forming a 333 × 333 × 49 × 68 four-dimensional matrix . First , we asked whether there were developmental changes in PLV across a broadband frequency range ( 1–49 Hz ) . To this end , we averaged the four-dimensional matrix along the first 2 dimensions of the upper triangle , resulting in a single PLV value at each frequency for each subject . A linear mixed-effects model with maximum likelihood estimation was used to examine main effects and interactions predicting PLV . Age and frequency were entered as fixed effects , and random intercepts were estimated for each subject . Significance values for fixed effects were obtained through a likelihood ratio test between models with and without the effects in question ( chi-squared test ) . To test individual frequencies for PLV × Age effects , we regressed PLV against age within each frequency bin and corrected for multiple comparisons using FDR [87] . For visualization purposes in Fig 2A , we performed a median split by age . First , we asked whether global ( across all ROIs ) relative power at any frequency interval demonstrated a significant age effect . After relative power was determined for each ROI at each frequency interval , we averaged power across all ROIs for each subject . We then performed a linear regression analysis at each frequency interval ( 1–49 Hz; 1-Hz bins ) and corrected for multiple comparisons using an FDR correction [87] . For visualization purposes in Fig 2B , we performed a mediation split by age . Once we determined the frequency ranges of significant age effects in phase-locking ( theta band: 5–9 Hz ) and power ( delta band: 1–3 Hz; beta band 14–16 and 22–26 Hz ) , we sought to determine the specific regions in which phase-locking and power were significantly changing with age . For the analysis of power , for each ROI , we ran linear regression models to determine the rate of change in power within each frequency band as a function of age and extracted the beta weight value from the age regressor . This resulted in a beta weight matrix ( ROI × Frequency ) . We then summed across frequencies within the range of significant effects ( e . g . , 1–3 Hz for delta band power ) for each ROI . For the phase-locking analysis , we ran linear regression models to determine the rate of change in PLV within the theta band as a function of age , controlling for potential confounds , including motion , power , and distance ( see below ) . This resulted in a 333 × 333 matrix of beta weights from the age regressor , representing the rate of change in phase-locking for every ROI pair . To obtain a summary statistic for each ROI , we summed down each column of the matrix , resulting in 333 summed beta weights , which we use to characterize the summed rate of change with age for every ROI across the cortical surface . This process was repeated across frequencies of interest ( 1–49 Hz ) by averaging across frequencies in 5 Hz bins ( i . e . , 1–5 Hz , 6–10 Hz , … , 46–49 Hz ) . We were interested in general trends across the cortical surface . To this extent , we calculated the center of mass for every ROI to obtain a center coordinate and to also get a measure of Euclidean distance between each ROI pair . We the regressed the y-coordinate of the ROI onto the summed beta weights for each ROI ( for power and phase analyses separately ) , controlling for average distance between ROIs and ROI surface area . The average distance between ROIs was included as a nuisance regressor to attenuate the effects of volume conduction . For the PLV analysis , this process was also repeated at each frequency interval and across 5 Hz frequencies bins in the range of 1–49 Hz to determine the specificity of the anterior-to-posterior gradient to the theta band . Specifically , we tested for a significant difference between the slope of each regression model ( i . e . , beta weights ) versus the model including the theta band ( 6–10 Hz for this analysis ) using the following formula [88]: z=β1−β2SEβ12+SEβ22 where z is equal to the test statistic ( values > 1 . 645 correspond to p < 0 . 05 , one-tailed ) , β1 is equal to the regression coefficient of the y-coordinate in the 6–10 Hz interval , β2 is equal to the regression coefficient of the y-coordinate in the test interval ( e . g . , 1–5 Hz ) , SEβ12 is the squared standard error of the β1 coefficient , and SEβ22 is the squared standard error of the β2 coefficient . Next , we wanted to identify any trends in specific ROI pairs driving regional decreases in phase-locking . First , we sorted ROIs according to the magnitude of the summed beta weights . We then further probed the top 5% of these ROIs ( n = 16 ) , which represents the 16 ROIs undergoing the greatest amount of developmental decrease in phase-locking . Of those 16 ROIs , we further thresholded each ROI’s specific interactions with other ROIs to maintain only the top 5% of each ROIs pairwise beta weight ( n = 16 pairwise interactions for each of the 16 ROIs ) , resulting in a total of 256 pairwise beta weights demonstrating the greatest rate of ROI-ROI decrease in phase-locking . We wanted to ensure any age-related changes we observed in PLV was not due to changes in the total amount of activity ( power ) in an area within any given frequency band [64] . First , we extracted a power estimate for each ROI . Specifically , we calculated relative power ( see “Power calculation” ) . We then extracted relative power in the 5–9 Hz frequency band within subjects by taking the mean power within this frequency range for each ROI and dividing by broadband total power ( 1–49 Hz ) for each ROI . For each ROI within each subject , this procedure resulted in relative theta band power . We then averaged across subjects to obtain a mean relative theta band power for each ROI . This value was then plotted against each ROIs y-coordinate to determine the anterior-to-posterior gradient in power across the cortex . Because a significant anterior-to-posterior gradient in power was observed ( more power in posterior regions ) , we included as nuisance regressors the power of each ROI , the interaction between each ROI pair , the log-transformed power of each ROI , and the log-transformed interaction term of each ROI pair into the age models for each ROI pair . Additionally , matching the PLV analysis pipeline , we regressed power onto age at every frequency interval ranging from 1–49 Hz in 1 Hz increments . During MaxFilter preprocessing , continuous head position estimates are calculated , and any large or sudden head movements are recorded . While MaxFilter performs head movement correction by aligning sensor data to a common reference , it does not account for artifacts generated by head movements , and we wanted to ensure any effects were not a result of head motion artifacts . After extracting the estimated movements from the MaxFilter output , we used the translation vector and rotation matrix for the head position relative to the sensor array ( obtained from coregistration ) to calculate a three-dimensional head movement vector relative to each sensor at each time point . The norm of this movement vector was averaged across sensors to obtain a single measure of head motion . This motion estimate for each subject was included as a nuisance regressor in all regression models involving the analysis of age-related changes in PLV . Prior to the neuroimaging visit ( M = 43 . 61 days , SD = 43 . 33 days ) , a subsample of participants ( n = 62 ) completed the UPPS-P Impulsive Behavior Scale [48 , 89–92] , either in an online screening ( n = 28 ) or a separate behavioral visit ( n = 34 ) . In the current analysis , total impulsivity scores were estimated according to procedures outlined by [48] . We then regressed age onto this total impulsivity score and observed a significant negative linear relationship between total impulsivity and age ( see Results ) . To determine overlap between links demonstrating a significant PLV × Age relationship and a significant PLV × Impulsivity relationship in a nonarbitrary , data-driven manner , individual subject theta band PLV matrices were submitted to the NBS [50] , and a t test was run between adolescents and adults to extract a cluster of regions with a significant decrease in theta PLV with age . We then performed the NBS on the relationship between impulsivity and theta PLV , controlling for age . A total of 3 connections overlapped between the 2 models and were subsequently confirmed using mediation analysis . To examine whether differences in PLV may account for age-related differences in impulsivity , mediation analysis was performed on PLV values within connections that had significant associations with ( 1 ) age and ( 2 ) impulsivity ( while controlling for age ) , as defined above . Significance values for indirect effects were obtained using 5 , 000 draws in a bootstrap procedure [93] . To determine whether resting-state delta band or beta band power mediated the relationship between age and impulsivity , similar to the PLV analysis , we tested each ROI across these 2 frequency bands for mediation effects . Significance values for indirect effects were obtained using 5 , 000 draws in a bootstrap procedure , as was done previously . The spatial working memory task was modeled on the classic Sternberg working memory paradigm . Cue stimuli were yellow circles appearing in 1 of 8 possible locations . Each trial began with fixation followed by a presentation of 3 frames ( 300 ms each ) showing one cue stimulus at a time in either the same location or 3 different locations . A blank grid was inserted between the frames for 200 ms to decrease chunking and motion perception . A 1 , 500 ms ( 50% of trials ) , 3 , 000 ms ( 25% of trials ) , or 4 , 500 ms ( 25% of trials ) delay period was used to minimize habituated preparatory responses . Following the delay period , subjects made a button press to indicate whether a frame showing 4 circles located among 8 possible locations had occurred in any of the previous cue locations ( 50% of trials ) or were all in novel locations ( 50% of trials ) . A total of 144 high load trials and 144 low load trials were distributed across 12 runs , with the order randomized within runs . Intertrial fixation intervals ranged between 1 , 000 and 4 , 500 ms , with a short break between runs . The task was designed and run using E-Prime ( Psychology Software Tools , Inc . , Pittsburgh , PA ) . MEG data were first manually inspected for flat or noisy channels that can arise due to sensor malfunction , and these channels were removed from further analysis , as excessively noisy or flat channels may adversely impact further preprocessing steps and data analysis . The maximum number of channels excluded within a single participant was 23 . As we did with the resting-state data , we attenuated environmental noise using the MaxFilter software to apply tSSS [80] . If at any time during a trial the total displacement of MEG sensors relative to the head was greater than 5 mm , the trial was rejected from all future analyses . Across all participants , only 38 total trials were dropped for head motion , with at most 4 trials dropped for head motion within a single participant . The remaining preprocessing steps were applied using tools in the MNE Python package [83] . First , the data were band-pass filtered to the frequency range of interest ( 1–49 Hz ) using a 10-second overlap-add FIR filter . Cardiac , eye blinks , and eye movement ( saccade ) artifacts are not identified by tSSS because they originate from the subject's body , so we used an ICA method to attenuate these artifacts , similar to the resting-state methods . The shapes of the automatically detected artifactual components were checked visually to verify the selection of artifactual components , and the selection of components was then amended in the rare cases that the automatic procedure failed to identify components that showed clear EOG or ECG patterns . Finally , trials were screened for remaining sensor jumps , muscle artifacts , or saccade artifacts by checking for magnetometer amplitudes that exceeded 2 . 5 × 10−10 T or gradiometer amplitudes that exceeded 4 × 10−10 T/m; no further trials were rejected by these criteria . During the experiment , trial event onset times were recorded into a digital stimulus channel through the E-Prime software . The event timings and codes from this channel were checked against E-Prime log files to remove spurious events that occurred in some runs due to software timing synchronization glitches . Based on this verified trial event data , trials with incorrect or omitted responses were removed because we are interested only in trials during which working memory was successfully engaged . In addition , a total of 10 trials across all participants were rejected due to mismatches between stimulus channel event codes and timing reported by E-Prime , with at most 4 trials dropped from a single subject for this reason . After preprocessing , we extracted the first 1 , 500 ms of the maintenance period from the task and calculated the PLV between each of the 333 ROIs in the 5–9 Hz frequency range , following the resting-state analysis pipeline . For each ROI pair , we then regressed the PLV onto age , controlling for subject head motion . Next , the beta weight from the age regressor was extracted from each model , and beta weight matrices were constructed . As in the resting-state analysis , we summed down the columns of the matrix to get a summed beta weight representing the total linear age effect . We then regressed this value for ROI against the ROI’s anatomical y-coordinate and did not observe any anterior-to-posterior effects ( t = −0 . 02 , p = 0 . 98 ) . | During the transition from adolescence to adulthood , humans have decreases in impulsivity and increases in cognitive control . These behaviors are supported by a distributed set of brain regions , including the prefrontal cortex , that can be studied by with a variety of brain-imaging tools . Magnetoencephalography ( MEG ) is an approach that allows us to study spontaneous brain activity at the millisecond timescale , providing unique insight into local neural activity ( power ) and interactions between brain regions ( estimated through phase-locking ) . Neural circuits exhibit oscillatory activity across a broad range of frequencies . Relatively slower-frequency ( 4–10 Hz ) oscillations are thought to support cognitive control . We found that , during the transition from adolescence to adulthood , power was redistributed from slower frequencies to higher frequencies , with the greatest increase in faster frequency power in the posterior cingulate cortex . We also found that the phase-locking of prefrontal cortex theta band ( 5–9 Hz ) oscillations decreases during adolescence . Mediation analysis of self-reported impulsive behavior suggests that band phase-locking contributes to decreases in impulsivity . This activity pattern may be an intrinsic marker for the ability for control-related brain regions to engage downstream processing networks . Our results indicate that spontaneous neural activity continues to be refined systematically during adolescence and contributes to cognitive maturation . | [
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"n... | 2018 | Adolescent development of cortical oscillations: Power, phase, and support of cognitive maturation |
The inability of sodium antimony gluconate ( SAG ) -unresponsive kala-azar patients to clear Leishmania donovani ( LD ) infection despite SAG therapy is partly due to an ill-defined immune-dysfunction . Since dendritic cells ( DCs ) typically initiate anti-leishmanial immunity , a role for DCs in aberrant LD clearance was investigated . Accordingly , regulation of SAG-induced activation of murine DCs following infection with LD isolates exhibiting two distinct phenotypes such as antimony-resistant ( SbRLD ) and antimony-sensitive ( SbSLD ) was compared in vitro . Unlike SbSLD , infection of DCs with SbRLD induced more IL-10 production and inhibited SAG-induced secretion of proinflammatory cytokines , up-regulation of co-stimulatory molecules and leishmanicidal effects . SbRLD inhibited these effects of SAG by blocking activation of PI3K/AKT and NF-κB pathways . In contrast , SbSLD failed to block activation of SAG ( 20 µg/ml ) -induced PI3K/AKT pathway; which continued to stimulate NF-κB signaling , induce leishmanicidal effects and promote DC activation . Notably , prolonged incubation of DCs with SbSLD also inhibited SAG ( 20 µg/ml ) -induced activation of PI3K/AKT and NF-κB pathways and leishmanicidal effects , which was restored by increasing the dose of SAG to 40 µg/ml . In contrast , SbRLD inhibited these SAG-induced events regardless of duration of DC exposure to SbRLD or dose of SAG . Interestingly , the inhibitory effects of isogenic SbSLD expressing ATP-binding cassette ( ABC ) transporter MRPA on SAG-induced leishmanicidal effects mimicked that of SbRLD to some extent , although antimony resistance in clinical LD isolates is known to be multifactorial . Furthermore , NF-κB was found to transcriptionally regulate expression of murine γglutamylcysteine synthetase heavy-chain ( mγGCShc ) gene , presumably an important regulator of antimony resistance . Importantly , SbRLD but not SbSLD blocked SAG-induced mγGCS expression in DCs by preventing NF-κB binding to the mγGCShc promoter . Our findings demonstrate that SbRLD but not SbSLD prevents SAG-induced DC activation by suppressing a PI3K-dependent NF-κB pathway and provide the evidence for differential host-pathogen interaction mediated by SbRLD and SbSLD .
Kala-azar , caused by Leishmania donovani ( LD ) , is regarded as the most severe form of leishmanial infection , which can be fatal in patients when left untreated . In the absence of an effective vaccine , treatment with pentavalent antimonial compounds such as sodium antimony gluconate ( SAG ) remains as the first-choice therapy for kala-azar . However , therapeutic utility of SAG is now jeopardized by the emergence of antimony-resistant strains of LD [1] , which is becoming a major concern of the World Health Organization ( www . who . int/infections-disease-report/2000 ) . Resistance to antimonial drugs , as observed in leishmanial infection , is marked by two independent “checkpoints” . The first is associated with the impaired biological reduction of the pentavalent antimony ( SbV ) prodrug to a toxic trivalent ( SbIII ) form , although the site ( macrophage ( Mφ ) and/or parasite ) and mechanism of reduction ( enzymatic or nonezymatic ) are undefined . The second checkpoint involves a regulatory mechanism promoting reduced influx and/or enhanced efflux/sequestration of active drug that lowers its intracellular accumulation [2] , [3] . Importantly , these two events are largely dependent on the intracellular level of thiol compounds such as glutathione ( γglutamylcysteinylglycine , GSH ) and parasite-specific trypanothione , which in turn are regulated by both host- and LD-γglutamylcysteine synthetase , a rate-limiting enzyme in glutathione biosynthesis [2]–[5] . Although the increased expression of γglutamylcysteine synthetase ( γGCS ) gene in antimony-resistant strains of LD is controversial [3]–[6] , inhibition of γGCS by buthionine sulfoxamine ( BSO ) reverses SbIII resistance in LD [7] . Therefore , γGCS expression contributes to antimony resistance in LD by regulating intracellular thiol level . In addition to the mechanisms noted above , the unresponsiveness of kala-azar patients to treatment with SAG is also believed to be a consequence of skewed type-2 immune response that suppresses interferon ( IFN ) γ-mediated protective immunity [8] . Nonetheless , IFNγ production by T cells is reduced in non-responders compared to SAG-responders [8] , [9] . The endogenous production of IFNγ and importantly , its principal inducer IL-12 , determine the anti-leishmanial efficacy of SAG in a fully immunocompetent host infected with LD [10] , [11] . Following LD infection , the early production of IL-12 is exclusively mediated by dendritic cells ( DCs ) [12] . This tempted us to speculate a possible involvement of DCs in regulating “SAG responsiveness” versus “unresponsiveness” in kala-azar patients . DCs normally play a key role in initiating and regulating Leishmania-specific T cell reactivity [13] , [14] . However , the T cell stimulatory capacity of DCs depends on their state of activation and maturation . In contrast to mature DCs , immature DCs exhibit a reduced capacity to stimulate T cells due to low expression of MHC and co-stimulatory molecules , and the lack of production of proinflammatory cytokines . Gene expression associated with the development , activation , maturation and antigen-presenting cell ( APC ) function of DCs is largely regulated by the transcription factor NF-κB [15]–[18] . For instance , inhibition of NF-κB activation suppresses DC maturation and APC function [19] , [20] . NF-κB is a hetero- or homo-dimeric complex of structurally related proteins p50 , p52 , p65 ( RelA ) , cRel and RelB . In resting cells , NF-κB is sequestered in the cytoplasm by the inhibitory proteins IκBα , IκBβ and IκBε [21] . However , cellular activation with wide range of stimuli such as LPS , TNFα and IL-1phosphorylates and thereby activates a multisubunit complex IκB kinase ( IKK ) consisting of IKKα/IKK1 , IKKβ/IKK2 and IKKγ/NEMO [22] . Subsequently , activated IKK promotes downstream events , for example , phosphorylation followed by polyubiquitination and 26S proteasome-mediated degradation of IκB proteins [21] . NF-κB dimers then translocate to the nucleus , and bind to consensus sequences to induce gene transcription . Notably , the phosphatidylinositol 3-kinase ( PI3K ) /AKT pathway has been demonstrated in a variety of models to regulate NF-κB activation [20] , [23] , [24] . Studies demonstrated that stimulation with SAG induces the PI3K/AKT pathway and enhances production of proinflammatory cytokines and leishmanicidal effector molecules in Mφ [25] . Furthermore , SAG stimulates NF-κB activation in different cell types , such as CD4+ T cells and peripheral blood mononuclear cells [26] . Importantly , blockade of NF-κB activation is shown to impair γGCS expression in murine Mφ-like cell line [27] . However , direct role of NF-κB in transcriptional regulation of murine γGCS promoter is undefined . With this in mind , the current study was initiated to define the role of SAG in murine DC activation and its regulation by LD isolates with SAG-resistant ( SbRLD ) and SAG-sensitive ( SbSLD ) phenotype . We demonstrate that SbRLD but not SbSLD infection suppresses SAG-induced activation/maturation and γGCS expression of DCs by inhibiting NF-κB activation in a PI3K/AKT-dependent manner .
Although Mφs are regarded as a “primary target” for leishmanial infection , recent studies indicate DC infection with various Leishmania spp . including LD [28] , [29] . Indeed , LD infection was observed in both immature bone marrow-derived DC ( BMDC ) ( CD11c+CD8α- ) and splenic DC ( sDC ) ( Figure 1A ) . To determine the leishmanicidal effect of SAG on intracellular SbRLD and SbSLD in DCs , BMDCs and sDCs were infected with GFP expressing promastigotes of SbSLD strain 2001 ( GFP-2001 ) or SbRLD strain R5 ( GFP-R5 ) for 3 hours , stimulated with SAG ( 20 µg/ml ) for 24 hours , and the frequency of infected DCs measured via flow cytometry . A comparable level of DC infection was observed with both GFP-2001 and GFP-R5 ( Figure 1B ) . However , the percentage of BMDCs or sDCs infected with GFP-2001 ( SbSLD ) was reduced by 5 to 9-fold following SAG treatment ( Figure 1B ) . In marked contrast , SAG treatment failed to exhibit any significant effect on GFP-R5 ( SbRLD ) infection in DCs ( Figure 1B ) . Furthermore , analyses via Giemsa staining demonstrated that intracellular amastigotes of other SbRLD strains exhibit similar resistance to the SAG-induced leishmanicidal effect in DCs . For instance , a significant reduction in both percentage of infected BMDCs and intracellular parasite number were observed in AG83 ( SbSLD ) - and to a lesser extent in 39 ( SbRLD ) -infected BMDCs after SAG treatment ( 10 and 20 µg/ml ) for 24 and 48 hours ( Figure S1 ) . Titration of parasites demonstrated that parasite to DC ratio ( multiplicity of infection; MOI ) of 10∶1 was the optimum ratio for maximum LD infection in DCs ( data not shown ) . Therefore , this MOI was used for all subsequent experiments unless otherwise stated . Next , the regulation of SAG-induced activation and maturation of DCs by SbRLD and SbSLD was investigated . For this purpose , BMDCs and sDCs were infected with SbRLD and SbSLD promastigotes for 3 hours , washed and cultured with or without SAG ( 20 µg/ml ) for an additional 48 hours . The activation and maturation of DCs were determined by analyzing MHC and co-stimulatory molecule expression and secretion of cytokines . Infection of BMDCs and sDCs with SbRLD strains 39 or GE1F8R induced more IL-10 production as compared with SbSLD strains AG83 or 2001 ( Figures 1C and S2A ) . Interestingly , IL-10 secretion from SbRLD-infected DCs was not affected by SAG treatment ( Figures 1C and S2A ) . In contrast , SAG treatment significantly inhibited IL-10 secretion by SbSLD-infected DCs ( Figures 1C and S2A ) . Furthermore , SAG-stimulated secretion of proinflammatory cytokines such as IL-12p70 and TNFα from DCs were inhibited by SbRLD and not SbSLD infection ( Figures 1D-E and S2B-C ) . Finally , SAG treatment up-regulated CD40 , CD80 , CD86 , MHC-I ( H2Kd ) and MHC-II ( IAd ) expression in BMDCs infected with SbSLD but not SbRLD ( Figure 1F ) . Consistent with work by other groups [30] , [31] , co-stimulatory molecule and MHC expression of untreated BMDCs remained unaltered following SbRLD or SbSLD infection ( Figure 1F ) . Together , these results demonstrate that SAG treatment protects DCs from SbSLD but not SbRLD infection . Moreover , stimulation with SAG fails to activate and mature SbRLD-infected DCs , while SbSLD-infected DCs are still capable of activation and maturation upon SAG treatment . Since NF-κB is a key regulator of maturation and APC function of DCs , the effect of SAG treatment on NF-κB activation was investigated . BMDCs were treated with SAG for varying times and DNA binding activity of nuclear NF-κB was determined via electrophoretic mobility shift assay ( EMSA ) . Relative to untreated BMDCs , a 23-fold increase in NF-κB DNA binding activity was initially observed by 0 . 3 hours , which persisted up to 1 hour after SAG treatment ( Figure 2A ) . Notably , OCT-1 DNA binding was unaltered despite SAG treatment indicating that SAG-induced enhancement of nuclear DNA binding was NF-κB-specific ( Figure 2A ) . Furthermore , supershift analysis using antibodies specific for each Rel family member demonstrated that SAG stimulation of BMDCs induced DNA binding of NF-κB complexes consisting of the p50 , p65 and RelB subunits ( Figure 2B ) . In contrast to SAG , BMDC treatment with varying concentrations ( 25 to 200 µg/ml ) of sodium gluconate for 0 . 3 hours , or 200 µg/ml of sodium gluconate for various times failed to induce DNA binding activity of NF-κB ( Figure 2C-D ) . Consistent with the EMSA data , SAG treatment for 0 . 3 , 0 . 5 and 1 hour induced degradation of IκB proteins in BMDCs ( Figure 3A ) . Importantly , SAG-induced IκB degradation corresponded to enhanced IκBα phosphorylation ( Figure 3B ) , which could be due to increased activity of upstream IKK complex . To test this hypothesis , BMDCs were stimulated with SAG for 0 . 3 , 0 . 5 and 1 hour . IKK signalosome was immunoprecipitated from cytoplasmic extracts and kinase activity of the complex determined by measuring phosphorylation of an IκBα-GST substrate in vitro . BMDCs stimulated with SAG for 0 . 3 , 0 . 5 and 1 hour exhibited approximately 3 . 6 to 4 . 7-fold increase in IKK activity compared to untreated BMDCs ( Figure 3C ) . In comparison , the level of IKK1 and IKK2 proteins were similar in all BMDC extracts ( Figure 3C ) . The SAG-induced NF-κB DNA binding , IκBα degradation and IKK activity were also observed in sDCs ( Figure S3 ) . Of note , SAG treatment failed to activate the mitogen-activated protein kinase ( MAPK ) pathway in BMDCs . In contrast to LPS stimulation , phosphorylation of p38MAPK , ERK1/ERK2 and JNK was not detected in SAG-treated DCs ( Figure 3D-F ) . Collectively , these findings demonstrate that stimulation with SAG induces activation of the IKK complex , phosphorylation and degradation of IκB proteins and downstream nuclear DNA binding of NF-κB in both BMDCs and sDCs , and that the induction of these events in DC is contributed by antimonial moiety of SAG . Furthermore , among different signaling pathways , which are known to regulate DC activation/maturation , NF-κB signaling is selectively induced by SAG treatment . The effect ( s ) of SbRLD and SbSLD infection on SAG-stimulated NF-κB activation in DCs was determined . BMDCs were infected with either promastigotes or amastigotes of 39 ( SbRLD ) or 2001 ( SbSLD ) for varying times , stimulated with SAG for 0 . 3 hours and nuclear NF-κB DNA binding activity to H2K-specific probe measured via EMSA . SAG-induced NF-κB activity was completely inhibited in BMDCs upon infection with either 39 promastigotes ( 39Pm ) or amastigotes ( 39Am ) ( SbRLD ) at all times of LD infection analyzed ( Figure 4A-B ) . In contrast , BMDC infection with 2001 promastigotes ( 2001Pm ) or amastigotes ( 2001Am ) ( SbSLD ) for up to 6 and 3 hours , respectively , failed to inhibit SAG-stimulated NF-κB DNA binding ( Figure 4A-B ) . SAG-induced NF-κB DNA binding activity was also inhibited in 39Pm ( SbRLD ) -infected sDCs ( Figure S4A ) . The ability of SbRLD to block SAG-stimulated NF-κB DNA binding in DCs was not LD strain specific . For example , BMDC infection with promastigotes of SbRLD strain GE1F8R ( GE1F8RPm ) , unlike SbSLD strain AG83 ( AG83Pm ) , completely prevented SAG-induced NF-κB DNA binding ( Figure S4B ) . Our finding that SAG-induced NF-κB activity is inhibited selectively in SbRLD-infected BMDCs was further confirmed by temporal analysis of IκB protein degradation and activation of IKK . BMDC infection with either 2001Pm or 2001Am ( SbSLD ) for up to 6 or 3 hours , respectively , had no significant effect on SAG-induced IκB degradation ( Figure 4C-D ) . In contrast , IκB degradation stimulated by SAG was persistently inhibited by 39 ( SbRLD ) regardless of the duration of BMDC infection and form of parasite ( Figure 4C-D ) . SAG-induced IκBα degradation was similarly inhibited in sDCs infected with 39Pm ( SbRLD ) and BMDCs infected with promastigotes of a different SbRLD strain ( Figure S4C-D ) . Interestingly , inhibition of SAG-induced IκB degradation corresponded with a reduction in IκBα phosphorylation in BMDCs infected with SbRLD promastigotes ( Figure 4C , E ) . Furthermore , SAG-induced IKK activation as determined by in vitro IKK activity or phosphorylation of IKK1 and IKK2 was inhibited in extracts prepared from BMDCs and sDCs infected with SbRLD but not SbSLD promastigotes ( Figures 4F and S4E-F ) . BMDC infection with SbRLD and not SbSLD amastigotes also blocked SAG-stimulated IKK activity ( Figure 4G ) . Additionally , pretreatment of BMDCs with parasite antigen ( s ) ( SbRLDsAg ) or culture supernatant ( SbRLDs ) of SbRLD inhibited SAG-induced NF-κB DNA binding activity , IκB degradation and IKK activity; whereas culture supernatant of SbSLD ( SbSLDs ) or SbSLD-derived antigen ( s ) ( SbSLDsAg ) did not ( Figure 5 ) . As demonstrated in Figure 4A-D; SAG-induced NF-κB activation was inhibited in BMDCs infected at a MOI 10∶1 ( promastigote or amastigote to DC ) with SbSLD promastigotes or amastigotes for 24 or 6 hours , respectively , similar to SbRLD-infected BMDCs . Accordingly , we tested whether the increased intracellular parasite number at these time points of infection rendered 20 µg/ml of SAG insufficient to activate NF-κB . In fact , number of intracellular 2001 ( SbSLD ) or 39 ( SbRLD ) was significantly increased if BMDCs were infected with promastigotes for 24 hours rather than 6 hours ( Figure S5A ) . Likewise , BMDCs infected with amastigotes of the above LD strains for 6 hours exhibited increased intracellular parasite number compared to BMDCs infected for 3 hours ( Figure S5B ) . Notably , SAG ( 20 µg/ml ) -induced NF-κB DNA binding and IκBα degradation were detected despite the presence of intracellular parasites in BMDCs infected with 2001Pm and 2001Am ( SbSLD ) for 6 and 3 hours , respectively ( Figures 4A-D and S5A-B ) . Therefore , these two time points of BMDC infection were selected as a “reference” to analyze the basis of defective SAG-induced NF-κB activation in BMDCs infected with 2001Pm or 2001Am ( SbSLD ) for 24 or 6 hours , respectively . Initially , the association of increased intracellular parasite number with impairment of SAG-induced NF-κB activation was verified in both BMDCs infected with 2001Pm or 2001Am ( SbSLD ) for 24 or 6 hours , respectively . For this purpose , BMDCs were infected with 2001Pm ( SbSLD ) or 39Pm ( SbRLD ) for 24 hours at varying MOIs and stimulated with SAG ( 20 µg/ml ) for 0 . 3 hours . Despite LD infection for fixed duration ( 24 hours ) , this approach established varying levels of intracellular parasite number , which was elevated in BMDCs infected at MOI 10∶1 compared to other MOIs ( Figure S6A ) . BMDC infection with both 2001Pm ( SbSLD ) and 39Pm ( SbRLD ) at a MOI 10∶1 inhibited SAG-induced NF-κB DNA binding activity and IκBα degradation ( Figure 6A-B ) . However , SAG-induced NF-κB DNA binding activity and IκBα degradation were observed only in 2001Pm ( SbSLD ) -infected BMDCs but not 39Pm ( SbRLD ) -infected BMDCs when BMDC infection was done at MOIs 2 . 5∶1 and 5∶1 ( Figure 6A-B ) . Notably , at each of these MOIs both 2001Pm ( SbSLD ) -infected BMDCs and 39Pm ( SbRLD ) -infected BMDCs had comparable level of intracellular parasite number ( Figure S6A ) . Using identical MOIs for BMDC infection , similar results were obtained when the intracellular parasite number and SAG-induced NF-κB activation were analyzed in BMDCs infected for 6 hours with 39Am ( SbRLD ) and 2001Am ( SbSLD ) ( Figures 6C-D and S6B ) . These findings suggest that irrespective of the form of parasite , 2001 ( SbSLD ) and 39 ( SbRLD ) differentially regulate SAG-induced NF-κB signaling in DCs with low intracellular parasite number . It is possible that with increased intracellular parasite number 2001 ( SbSLD ) , similar to 39 ( SbRLD ) , developed the capacity to inhibit SAG-induced NF-κB activation and that occurred when BMDCs were infected at a MOI 10∶1 with 2001Pm or 2001Am ( SbSLD ) for 24 and 6 hours , respectively . However , this possibility was ruled out when NF-κB activation in response to 20 and 40 µg/ml of SAG treatment was analyzed in BMDCs infected for 6 and 24 hours with 2001Pm ( SbSLD ) or 39Pm ( SbRLD ) at a MOI of 10∶1 . The effect of SAG ( 40 µg/ml ) stimulation was also verified in BMDCs infected similarly with 2001Am or 39Am for 3 and 6 hours . Stimulation with both 20 and 40 µg/ml of SAG induced NF-κB DNA binding and IκBα degradation in BMDCs infected with 2001Pm ( SbSLD ) for 6 hours ( Figure 6E-F ) . In contrast , BMDCs infected for 24 hours with 2001Pm ( SbSLD ) exhibited enhanced NF-κB DNA binding and IκBα degradation only when stimulated with 40 µg/ml of SAG ( Figure 6E-F ) . Similarly , the inhibition of SAG-induced NF-κB DNA binding and IκBα degradation due to BMDC infection with 2001Am ( SbSLD ) for 6 hours was overcome by increasing the dose of SAG from 20 to 40 µg/ml ( Figure 6G-H ) . On the contrary , 39Pm/39Am ( SbRLD ) continued to suppress NF-κB DNA binding and IκBα degradation at various durations of infection tested irrespective of dose of SAG used for stimulation ( Figure 6E-H ) . Together , these results demonstrate that SAG-induced NF-κB signaling is impaired by SbRLD infection of DCs . Stimulation with SAG induces PI3K/AKT activation in Mφ [25] . Furthermore , PI3K/AKT regulates the NF-κB pathway in DCs via IKK [19] , [20] . Therefore , the possibility that SAG-induced activation of NF-κB in DCs is PI3K/AKT-dependent was investigated . Initially , the effect of SAG stimulation on AKT activation was assessed by measuring phosphorylation of AKT . Compared to unstimulated BMDCs , SAG treatment induced a 5 to 7-fold increase in AKT phosphorylation in BMDCs ( Figure 7A ) . Notably , SAG-induced AKT phosphorylation was not observed in BMDCs pretreated with PI3K inhibitors wortmannin ( Wort ) or Ly294002 ( Ly ) ( Figure 7A ) . Next , the effect of PI3K inhibitors on SAG-induced NF-κB signaling was determined . Pretreatment with Wort or Ly effectively blocked SAG-induced IKK activity , IκBα degradation and nuclear NF-κB DNA binding in BMDCs ( Figure 7B-D ) . Importantly , infection of BMDCs and sDCs with 39Pm ( SbRLD ) but not 2001Pm ( SbSLD ) for 3 hours inhibited SAG ( 20 µg/ml ) -induced AKT phosphorylation ( Figures 7E and S7 ) . SAG ( 20 µg/ml ) -induced AKT phosphorylation was also inhibited due to BMDCs infection for 1 and 3 hours with 39Am ( SbRLD ) but not 2001Am ( SbSLD ) ( Figure 7F ) . Similar to 39Pm ( SbRLD ) -infected BMDCs , SAG ( 20 µg/ml ) -induced AKT phosphorylation , however , was not observed if BMDCs were infected with 2001Pm ( SbSLD ) for 24 hours ( Figure 7G ) . Interestingly , AKT phosphorylation was observed in these 2001Pm ( SbSLD ) -infected BMDCs but not 39Pm ( SbRLD ) -infected BMDCs upon stimulation with of 40 µg/ml of SAG ( Figure 7G ) . Since SbRLD infection stimulated high IL-10 secretion by DCs ( Figures 1C and S2A ) , the possibility that SbRLD inhibited SAG-induced PI3K/AKT ( Figures 7E-F and S7 ) and NF-κB pathways ( Figures 4 and S4 ) in an IL-10-dependent manner was investigated by using a neutralizing αIL-10 Ab . Temporal analyses demonstrated that significant IL-10 production by BMDCs was initially detected after an infection for 12 hours with SbRLD but not SbSLD promastigotes ( Figure 7H ) . Compared to SbSLD-infected BMDCs , IL-10 production was significantly increased in BMDCs infected with SbRLD for 24 and 48 hours ( Figure 7H ) . Strikingly , SAG-induced AKT phosphorylation and NF-κB DNA binding activity were not restored in BMDCs infected with SbRLD for 3 and 24 hours despite αIL-10 Ab treatment ( Figure 7I-J ) . However , αIL-10 Ab treatment effectively prevented inhibition of LPS-induced NF-κB DNA binding in BMDCs pretreated with IL-10 ( Figure S8 ) . Therefore , this finding ruled out the involvement of IL-10 in suppression of SAG-induced PI3K/AKT and NF-κB pathways in SbRLD-infected BMDCs . Consistent with previous report [5] , an overexpression of ATP-binding cassette ( ABC ) transporter MRPA ( PGPA ) was observed in SbRLD strains 39Pm and GE1F8RPm ( Figure S9A ) . Whether MRPA plays any role in mediating the inhibitory effects of SbRLD on SAG-induced PI3K/AKT and NF-κB activation in DC was then investigated . Accordingly , SAG-induced AKT phosphorylation and NF-κB activation in BMDCs infected for 3 hours with 39Pm ( SbRLD ) , 2001Pm ( SbSLD ) and isogenic 2001Pm expressing MRPA ( 2001Pm-MRPA ) ( Figure S9B ) were compared . The latter was developed by transfecting 2001Pm ( SbSLD ) with a DNA construct expressing MRPA . A complete blockade of SAG-induced AKT phosphorylation and NF-κB DNA binding activity was observed in 39Pm ( SbRLD ) -infected BMDCs ( Figure 8A-B ) . In contrast , SAG-induced AKT phosphorylation and NF-κB DNA binding activity were detected in 2001Pm ( SbSLD ) -infected BMDCs ( Figure 8A-B ) . However , infection of BMDCs with 2001Pm-MRPA inhibited SAG-induced AKT phosphorylation and DNA binding activity of NF-κB in BMDCs , albeit partially ( Figure 8A-B ) . Next , a direct role for PI3K in SbRLD and SbSLD regulation of SAG-induced proinflammatory cytokine secretion and leishmanicidal effects in DCs was investigated using Wort or Ly . In contrast to 39Pm ( SbRLD ) -infected BMDCs , SAG-stimulated IL-12 and TNFα production were observed in both uninfected and 2001Pm ( SbSLD ) -infected BMDCs ( Figure 9A-B ) . However , pretreatment of uninfected and 2001Pm ( SbSLD ) -infected BMDCs with Wort or Ly significantly inhibited SAG-induced secretion of IL-12 and TNFα ( Figure 9A-B ) . Furthermore , PI3K inhibitors prevented SAG ( 20 µg/ml ) -induced reduction of percentage of infected BMDCs and intracellular parasite number in BMDCs infected for 3 hours with 2001Pm ( SbSLD ) ( Figure 9C-D ) . Importantly , BMDCs infected with 2001Pm ( SbSLD ) for 24 hours exhibited a significant reduction in both percentage of infected BMDCs and intracellular parasite number only when treated with 40 but not 20 µg/ml of SAG ( Figure S10 ) . Treatment of these 2001Pm ( SbSLD ) -infected BMDCs with Wort or Ly blocked the leishmanicidal effects of SAG ( 40 µg/ml ) ( Figure S10 ) . In contrast to 2001Pm ( SbSLD ) -infected BMDCs , SAG-induced leishmanicidal effects were not observed in 39Pm ( SbRLD ) -infected BMDCs regardless of duration of infection and dose of SAG ( Figures 9C-D and S10 ) . In addition , BMDC infection for 3 hours with 2001Pm-MRPA , unlike 2001Pm ( SbSLD ) , partly but significantly suppressed SAG-induced leishmanicidal effects ( Figure 9E-F ) . Collectively , these data demonstrate that blockade of PI3K/AKT pathway by SbRLD impairs SAG-induced NF-κB signaling , DC activation and leishmanicidal function and that is IL-10-independent . Furthermore , these inhibitory effects of SbRLD are partly contributed by MRPA . Previous studies have demonstrated an association of antimony resistance of leishmanial parasite with γGCS heavy-chain ( γGCShc ) gene expression of host [4] . The latter encodes the catalytic subunit of γGCS [32] . In fact , a comparative analysis demonstrated that SAG-induced murine γGCShc ( mγGCShc ) expression was unaffected in 2001Pm ( SbSLD ) -infected BMDCs but selectively inhibited in 39Pm ( SbRLD ) -infected BMDCs ( Figure 10A ) . The molecular basis for SbRLD-mediated suppression of mγGCShc expression in DC was then explored . Despite SAG stimulation , the inhibition of mγGCShc expression could be due to suppression of NF-κB activation in SbRLD-infected BMDC . To investigate this possibility , the regulatory role of NF-κB in mγGCShc promoter activity was initially ascertained . An approximately 1 . 0 kb DNA sequence upstream of the transcriptional start site of mγGCShc gene ( Mus musculus chromosome 9 genomic contig , NT_039474 . 7; GI:149260095 ) was selected as the promoter region using Ensembl and UCSC browsers . The mγGCShc promoter was found to contain a putative NF-κB binding site -904GGGGAAACTT-895 that differs from the consensus sequence GGGRNNYYCC at positions 7 , 9 and 10 ( Figure 10B ) . ChIP analysis demonstrated that SAG treatment of BMDCs induced NF-κB binding to −991/−673 region of mγGCShc promoter that includes the sequence -904GGGGAAACTT-895 ( Figure 10B-C ) . Furthermore , DNA binding of NF-κB complexes consisting of p50 , RelB and p65 subunits specifically to the sequence -904GGGGAAACTT-895 in SAG-treated BMDCs was confirmed via EMSA using mγGCShc probes containing wild-type sequence -904GGGGAAACTT-895 ( WT-mγGCShc probe ) or mutant sequence -904CTCTAAGAAT-895 ( Mut-mγGCShc probe ) ( Figure 10D ) and supershift analysis ( Figure 10E ) . Next , the role of NF-κB binding site -904GGGGAAACTT-895 in regulation of promoter activity of mγGCShc gene was tested via luciferase reporter assay using p987-luc and Mut p987-luc , the reporter constructs of mγGCShc promoter fragment containing wild-type and mutant NF-κB binding site , respectively . Compared to control vector ( pEGFP-C1 ) transfected cells , expression of NF-κB subunit p65 strongly induced luciferase activity of p987-luc ( Figure 10F ) . This enhanced luciferase activity of p987-luc was completely blocked upon co-transfection with pEGFP-dominant negative IκBα ( pEGFP-IκBαΔN ) encoding the NF-κB-specific inhibitor , IκBαΔN ( Figure 10F ) . The lack of luciferase activity of Mut p987-luc despite p65 expression ( Figure 10F ) further indicated that the sequence -904GGGGAAACTT-895 is required for NF-κB-mediated transcriptional activation of mγGCShc gene . Interestingly , SAG-induced NF-κB DNA binding to WT-mγGCShc probe was inhibited in 39Pm ( SbRLD ) -infected BMDCs ( Figure 10G ) . In contrast , SAG-induced NF-κB DNA binding to WT-mγGCShc probe was readily detected in 2001Pm ( SbSLD ) -infected BMDCs ( Figure 10G ) . These findings suggest that SbRLD suppresses SAG-induced mγGCShc expression in DC by inhibiting NF-κB DNA binding to the mγGCShc promoter .
Antimonial drugs activate innate effector cells to promote an anti-leishmanial effect [25] . However , regulation of antimonial drug-mediated immune activation by SbRLD and SbSLD is ill-defined . This is of particular interest in view of the lack of efficacy of antimonial compounds reported for SAG-unresponsive kala-azar patients . Recent studies indicated that DCs play a key role in regulating anti-leishmanial immune response [12]–[14] , [33] . Accordingly , the role of SAG in activation of DCs , its regulation by SbRLD and SbSLD and the molecular mechanism involved therein were investigated . Here we provide evidence that SbRLD and SbSLD differentially regulate activation of DCs . Furthermore , SAG-induced signaling pathway associated with DC activation is selectively targeted by SbRLD infection . In an agreement with an earlier report [28] , both BMDCs and ex vivo sDCs were infected in vitro with LD promastigotes ( Figure 1A ) . The “SAG-resistant” phenotype did not significantly affect the efficiency of LD infection , but did impact the susceptibility of LD to the leishmanicidal effects of SAG . In contrast , SAG treatment significantly impaired DC infectivity of SbSLD including reduction in both intracellular parasite number and percentage of infected DCs ( Figures 1B and S1 ) . The differential response of SbRLD and SbSLD towards SAG treatment was also noted in their ability to regulate activation and maturation of DCs . In contrast to SbSLD , SbRLD infection inhibited SAG-induced proinflammatory cytokine secretion and up-regulation of co-stimulatory molecule and MHC expression in DCs ( Figures 1D-F and S2B-C ) . Noteworthy is that SbRLD induced increased IL-10 secretion by DCs compared to SbSLD ( Figures 1C and S2A ) . This finding reinforces the inherent ability of SbRLD and SbSLD to differentially immunoregulate DC activation . Previous studies demonstrated that IL-10 , a potent suppressor of anti-leishmanial immunity , minimizes responsiveness to SAG [34] , [35] . Therefore , increased IL-10 production may play a critical role in disease pathogenesis in the host infected with SbRLD . The second important finding arising from this study is that both promastigotes and amastigotes of SbRLD and SbSLD differentially regulate SAG-induced NF-κB activation in DCs . Indeed , SbRLD but not SbSLD infection blocks SAG-induced NF-κB signaling by suppressing IKK activation , and IκB protein phosphorylation and degradation ( Figures 4 and S4 ) . In this regard , it should be noted that SAG stimulation of uninfected DCs induced concomitant degradation of all three IκB proteins ( Figure 3A ) , although degradation of IκBε generally occurs with delayed kinetics upon cellular activation [36] , [37] . This finding , however , is consistent with a number of studies reporting rapid degradation of IκBβ and IκBε depending on the type of cell and the nature of the stimulation [19] , [20] , [36]–[39] . Nevertheless , the suppression of SAG-induced IκB protein degradation by SbRLD ultimately impaired nuclear NF-κB DNA binding activity ( Figures 4 and S4 ) . Surprisingly , BMDC infection at a MOI 10∶1 with SbSLD promastigotes or amastigotes for 24 or 6 hours , respectively , also inhibited SAG ( 20 µg/ml ) -induced NF-κB activation ( Figure 4 ) . SAG ( 20 µg/ml ) -induced NF-κB activation was restored in these BMDCs but not SbRLD-infected BMDCs upon lowering the MOIs ( <10∶1 ) for BMDC infection , which established reduced levels of intracellular parasite number compared to MOI 10∶1 ( Figures 6A-D and S6 ) . This finding suggests that intracellular parasite number plays a critical role for differential regulation of SAG-induced NF-κB activation by SbRLD and SbSLD . The early inhibition of NF-κB activation in SbSLD amastigote versus promastigote-infected BMDCs ( Figure 4 ) is in agreement with the fact that DCs internalize amastigotes more efficiently than promastigotes [40]–[42] . However , SbRLD and SbSLD still retain their ability to differentially regulate SAG-induced NF-κB activation in BMDCs with high intracellular parasite number . This conclusion is supported by results demonstrating that despite stimulation with 40 µg/ml of SAG , NF-κB activation was blocked in BMDCs infected for above durations with SbRLD amastigotes or promastigotes at a MOI 10∶1 but readily observed in BMDCs infected similarly with SbSLD ( Figure 6 ) . Here , the SAG dose was increased from 20 to 40 µg/ml keeping in mind that SAG therapy requires multiple dosing schedules to ensure enough antimony accumulation in tissues of kala-azar patients [43] . Furthermore , equivalent and/or increased concentrations of SAG have previously been used by other groups [44] , [45] . Under identical conditions , the recurrence of NF-κB activation in SbSLD-infected BMDCs by increasing the dose of SAG from 20 to 40 µg/ml ( Figure 6 ) further suggested that 20 µg/ml of SAG was insufficient to activate NF-κB in these BMDCs due to high intracellular parasite number . Noteworthy is that the inhibitory effect on NF-κB activation was not dependent on live SbRLD . For instance , parasite antigens derived from SbRLD ( SbRLDsAg ) and SbRLD culture supernatant ( SbRLDs ) but not the SbSLD-derived antigens ( SbSLDsAg ) or culture supernatant of SbSLD ( SbSLDs ) efficiently inhibited SAG-induced NF-κB activation ( Figure 5 ) . These findings suggest that the inhibition of NF-κB activation is specific for SbRLD/SbRLD-derived antigen ( s ) /factor ( s ) secreted by SbRLD . Strikingly , the inhibition of NF-κB activation correlated with suppression of SAG-induced DC activation by SbRLD infection ( Figures 1 , 4 and S2 ) . Studies involving gene transfer of a modified IκBα recombinant into immature DC demonstrated that blockade of NF-κB activation alone prevents up-regulation of co-stimulatory molecule expression and production of proinflammatory cytokines [16] , [18] . Based on these reports coupled with our own observations , we conclude that the SbRLD blocks SAG-induced NF-κB signaling to prevent DC activation and maturation . Our results further suggest that SbRLD inhibits IKK and NF-κB activation by blocking SAG-induced PI3K/AKT signaling . SAG stimulation of DCs induced PI3K activation as measured by phosphorylation of AKT , a downstream signaling mediator of PI3K ( Figures 7A and S7 ) . Blockade of PI3K/AKT activation by Wort or Ly completely suppressed SAG-stimulated IKK activity and NF-κB signaling ( Figure 7A-D ) , indicating a direct involvement of the PI3K/AKT pathway in NF-κB activation by SAG in DCs . Importantly , PI3K/AKT activation is negatively regulated by Src homology phosphotyrosine phosphatase ( SHP ) -1 , which dephosphorylates PI3K [46] . Furthermore , SHP-1activity is inhibited by SAG [47] . Therefore , blockade of SHP-1activity by SAG may indirectly promote PI3K phosphorylation and activation of downstream AKT , IKK and NF-κB in DCs . Similar to uninfected DCs , SAG treatment induced PI3K/AKT activation in DCs infected with SbSLD promastigotes for 3 hours and SbSLD amastigotes for 1 and 3 hours ( Figures 7E-F and S7 ) . Importantly , PI3K inhibitors impaired SAG ( 20 µg/ml ) -induced NF-κB pathway , DC activation and leishmanicidal effects in BMDCs infected with SbSLD promastigotes for 3 hours ( Figures 9 and S11 ) . These results suggest the inability of SbSLD to regulate SAG-induced PI3K/AKT and NF-κB pathways . Consequently , SAG continues to exhibit leishmanicidal effects in SbSLD-infected DCs . The inability of SbSLD to regulate SAG-induced leishmanicidal effects was maintained despite BMDC infection for 24 hours with SbSLD promastigotes . This was apparent when increased dose of SAG ( 40 µg/ml ) was used for treatment ( Figure S10 ) . In fact , treatment with 40 µg/ml of SAG restored AKT phosphorylation and therefore exhibited leishmanicidal effects in a PI3K-dependent manner in these SbSLD-infected BMDCs ( Figures 7G and S10 ) . Interestingly , SbRLD infection mimicked the effects of the PI3K inhibitors in that all SAG-induced events as mentioned above were also blocked by SbRLD regardless of duration of infection , form of parasite and dose of SAG ( Figures 7 , 9 , S10 and S11 ) . One intriguing possibility is that IL-10 produced by SbRLD-infected DCs mediated SbRLD-induced suppression of PI3K/AKT and NF-κB pathways ( Figures 1C , 4 , 7 , S2A and S7 ) . This correlation can be made because IL-10 inhibits AKT activation and NF-κB pathway in DCs [19] . Furthermore , the inhibitory effects of IL-10 on DCs can be mediated in an autocrine manner [48] . However , this is unlikely since SAG-induced NF-κB activation was inhibited even in BMDCs infected with SbRLD for 1 and 3 hours , when IL-10 production was not detected ( Figures 4 and 7H ) . Moreover , neutralization of IL-10 produced by BMDCs upon SbRLD infection for 24 hours failed to block SbRLD-induced inhibition of PI3K/AKT and NF-κB pathways ( Figure 7H-J ) . Therefore , SbRLD infection of BMDCs for up to 24 hours inhibits SAG-induced PI3K/AKT and NF-κB pathways in an IL-10-independent manner and eventually impairs DC activation . Another key finding is that the suppression of NF-κB activation by SbRLD but not SbSLD inhibits not only DC activation but also SAG-induced mγGCShc expression in DC ( Figure 10 ) . Importantly , regulation of host γGCShc expression and therefore host GSH level by SbRLD plays a key role for antimony resistance in LD infection [4] . Although regulation of γGCShc expression by NF-κB was shown in a murine Mφ-like cell line by blocking NF-κB activation [27] , our observation establishes a direct role for NF-κB in mediating the promoter activity of the mγGCShc gene ( Figure 10C-F ) . Interestingly , SbRLD blocked SAG-induced mγGCShc expression in DC by preventing NF-κB binding to the mγGCShc gene promoter ( Figure 10G ) . This suggests a key role for NF-κB in SbRLD-mediated suppression of mγGCShc expression in DC . Our findings ( Figures 10A and S12 ) are consistent with the recent work by Carter and colleagues demonstrating that SbRLD transcriptionally down-regulate host γGCShc expression and up-regulate their own γGCShc ( LD-γGCShc ) expression [4] . Whereas SbRLD-induced inhibition of host γGCS expression reduces host GSH level and impairs reduction of SbV to toxic SbIII form; elevated expression of LD γGCS by SbRLD restores GSH level that promotes efflux of SAG and confers protection against oxidative stress [4] . The mechanism of antimony resistance in clinical LD isolates is unknown and may differ from laboratory-derived resistant parasites [3] . The true markers of clinical antimony resistance in LD isolates are still lacking [2] . A gene , PG1 , is reported to confer antimony resistance in clinical isolates of LD [45] , [49] . In addition , enhanced expression of several other genes including MRPA and proteophosphoglycans ( PPG ) was demonstrated in antimony-resistant compared to antimony-sensitive field isolates ( Salotra P , Singh R , Nakhasi H . 2005 . Clinical Microbiology and Infection . Vol 11 , Suppl 2: 47 ) [5] , [50] . As an initial effort to determine whether any SbRLD-specific factor ( s ) mediated the suppression of SAG-induced NF-κB signaling and leishmanicidal effects in DCs , the role for MRPA was investigated . Results obtained using 2001Pm and its isogenic strain expressing MRPA ( 2001Pm-MRPA ) showed that the inhibitory effect of 2001Pm-MRPA on SAG-induced PI3K/AKT and NF-κB pathways and leishmanicidal activities mimics that of SbRLD to some extent ( Figures 8 and 9 ) . However , the real bearing of this observation in naturally occurring antimony-resistant LD isolates is still questionable and needs detailed investigation further . Moreover , the effects of SAG are likely to be inhibited in DCs by other SbRLD-specific factor ( s ) also . The relative contribution of these parasite-specific factors in SbRLD-mediated suppression of DC activation is currently under investigation . Furthermore , an association of antimony resistance with genetic variation among LD strains has been proposed [51] . Recent studies demonstrated that due to high genetic polymorphism , strain 39 is remarkably distinct not only from antimony-sensitive strain 2001 but also from other antimony-resistant clinical LD isolates exhibiting homology with antimony-sensitive parasites [51] . On the other hand , the antimony-sensitive strains 2001 and Dd8 exhibit significant genetic similarity [51] . The extreme genetic polymorphism might be a potential cause of antimony resistance in strain 39 [51] . These reports together with our findings emphasize the notion that antimony resistance of clinical LD isolates is “multifactorial” [3] . SAG unresponsiveness in kala-azar patients also entails a number of host-regulated events including dominance of a type-2 T cell response and altered host gene expression [3] , [4] , [8] , [9] . Our findings demonstrate that SAG treatment induces PI3K-dependent NF-κB activation in DCs , which is blocked by SbRLD but not SbSLD infection . Dysregulation of SAG-induced NF-κB activation favors persistent survival of SbRLD in DCs despite SAG treatment by: 1 ) inhibiting NF-κB-dependent mγGCS expression , a key mediator of SbV reduction to SbIII , and 2 ) preventing DC activation and maturation required for the initiation of the anti-leishmanial immune response . Notably , a heterogeneous response to SAG treatment may be observed in humans . This possibility is raised by a report demonstrating that SAG treatment of monocyte-derived DCs restores their capacity to respond to LPS in ∼60% of type 1diabetes patients [52] . Importantly , some variability in SAG responsiveness is also reported in kala-azar patients [53] . It is speculated that the genetic differences among individuals may influence the response following SAG therapy in the patients infected with same Leishmania species and living in the same endemic area [54] . Further studies are needed to define how genetic variation , if any , influences the outcome of SAG treatment in kala-azar patients .
BALB/c mice and golden hamsters ( Mesocricetus auratus ) were maintained and bred under pathogen-free conditions . Use of both mice and hamsters was approved by the Institutional Animal Ethics Committees of Institute of Microbial Technology and Indian Institute of Chemical Biology , India . All animal experimentations were performed according to the National Regulatory Guidelines issued by CPSEA ( Committee for the Purpose of Supervision of Experiments on Animals ) , Ministry of Environment and Forest , Govt . of India . SbRLD [GE1F8R ( MHOM/IN/89/GE1 ) , 39 , R5] and SbSLD [AG83 ( MHOM/IN/83/AG83 ) , 2001] strains are gifts from Dr . Neeloo Singh ( Central Drug Research Institute , India ) and Dr . Shyam Sundar ( Banaras Hindu University , India ) and were maintained in golden hamsters as described [45] , [55]–[57] . Amastigotes were obtained from spleens of infected hamsters as described [58] . Subsequently , amastigotes were transformed into promastigotes and maintained as described [59] . GFP-2001 and GFP-R5 are gifts from Dr . Neeloo Singh and were maintained in M199 complete medium ( 10% FBS , penicillin/streptomycin ) with 720 µg/ml geneticin disulfate ( G418 ) ( Sigma , St . Louis , MO ) [60] . Soluble antigens were prepared from SbSLD and SbRLD promastigotes ( 109/ml ) as described [59] . 2001Pm ( SbSLD ) at mid log or stationary phase were washed twice with electroporation buffer ( 21 mM HEPES , pH 7 . 05; 137 mM NaCl; 5 mM KCl; 0 . 7 mM NaH2PO4; 6 mM glucose ) . The promastigotes were resuspended in ice-cold electroporation buffer to a final concentration of 107/ml . An aliquot ( 400 µl ) of parasite suspension was mixed with 35–40 µg of chilled pGEM 7ZF α-neo-α L . tarentolae MRPA or pGEM 7ZF α-neo-α DNA ( kind gifts from Dr . Marc Ouellette , Laval University , Canada ) , transferred to a 2-mm gap cuvette and electroporated using BIO-RAD Gene-Pulser X cell instrument at 450 V and 500 µF ( 3 . 5 to 4 milli-seconds pulse time ) . After electroporation , parasites were immediately placed on ice for 10 minutes and cultured at 22°C for 24 hours in Schneider's insect medium with 1500 µg/ml paromomycin and 10 µM Biopterin . Subsequently , 40 µg/ml of G418 was added to the parasite culture . After 24 hours , 1 ml of this promastigote culture was transferred to a new flask containing 5 ml of fresh medium with 10 µM biopterin and 120 µg/ml G418 . The culture was maintained for one month under drug pressure ( once per week ) to obtain the stable transfectants . The mRNA expression of MRPA in these stable transfectants was verified via RT-PCR . BMDCs and sDCs were prepared from male or female BALB/c mice between 8–12 weeks of age as described [19] . Flow cytometric analyses indicated >85% and ∼90% purity of BMDCs and sDCs , respectively , based on CD11c expression . DCs ( 5×106/well ) were infected in vitro at specified MOIs either with amastigotes of SbRLD or SbSLD; or promastigotes of stationary phase SbRLD , SbSLD or respective GFP-LD for indicated times in a 6-well plate in RPMI 1640 complete medium ( 10% FBS , penicillin/streptomycin , L-glutamine , sodium pyruvate , non-essential amino acids , 2-mercaptoethanol ) . Subsequently , DCs were washed , resuspended in RPMI 1640 complete medium and stimulated with SAG ( 10 , 20 and 40 µg/ml ) of clinical grade or sodium gluconate ( 25 , 50 , 100 and 200 µg/ml ) for specified times . The doses of SAG mentioned here and for all experiments represent the concentration of SbV . DC infection with GFP-SbRLD or GFP-SbSLD was determined via flow cytometry . SAG containing 20 µg/ml of SbV , and 35 µg/ml of sodium gluconate had equivalent molar concentration . Sodium gluconate was purchased from Acros Organics , New Jersey , USA . SAG was obtained as kind gift from Albert David Ltd . , Kolkata , India . For other experiments , DCs ( 2 . 5×105/ml ) were adhered on 22×22 mm cover slips , infected with promastigotes/amastigotes of SbSLD or SbRLD and treated with SAG for indicated times . The number of intracellular parasites in DCs was determined via Giemsa staining . In some experiments , DCs ( 5×106/well ) were infected with SbSLD or SbRLD promastigotes for 3 hours or left uninfected . Alternatively , infection of DCs ( 5×106/well ) with LD promastigotes was done for specified times . DCs were then treated or not with Wort ( 200 nM ) or Ly ( 50 µM ) ( Cell Signaling Technology , Beverly , MA ) 1 hour prior to SAG stimulation as described [19] . In some cases , DCs ( 5×106/well ) were infected with SbSLD or SbRLD promastigotes for 3 and 24 hours or left uninfected . Neutralizing αIL-10 monoclonal Ab ( 10 µg/ml ) /isotype control rat IgG2b Ab ( 10 µg/ml ) ( BD Biosciences , San Jose , CA ) were added at 2nd hour of BMDC infection . After infection , DCs were washed and stimulated with SAG for 0 . 3 hours . DCs ( 5×106/well ) were pretreated for 3 hours with 50 µg/ml soluble antigens derived from SbRLD ( SbRLDsAg ) or SbSLD ( SbSLDsAg ) and stimulated with SAG for 0 . 3 hours in a 6-well plate . Alternatively , SbRLD or SbSLD promastigotes ( 106/ml ) were grown in M199 complete medium till the parasite concentration reached ≥107/ml . The respective culture supernatants of SbRLD ( SbRLDs ) and SbSLD ( SbSLDs ) were then collected . Subsequently , DCs ( 5×106/well ) were cultured for 3 hours in RPMI 1640 complete medium containing SbRLDs or SbSLDs at specified complete medium to supernatant ratios and stimulated with SAG for 0 . 3 hours as above . In some experiments , BMDCs ( 5×106/well ) were pretreated with murine IL-10 ( 50 ng/ml ) ( PeproTech , Rocky Hill , NJ ) for 24 hours as described [19] , in the presence or absence of 10 µg/ml of αIL-10Ab/isotype control Ab and stimulated with LPS ( 500 ng/ml ) for 0 . 5 hours . Nuclear and cytoplasmic extracts were prepared from DC as described [61] . EMSA was performed as described [62] using 32P-labeled DNA probes containing NF-κB binding sites derived from MHC-I H2K promoter: 5′-CAGGGCTGGGGATTCCCCATCTCCACAGTTTCACTTC-3′ [20] . In some experiments , DNA probes specific for murine γGCS heavy-chain ( mγGCShc ) promoter containing wild-type or mutant NF-κB binding sites as represented by WT-mγGCShc probe , ′-CGGTTCTGAAGGTGGGGAAACTTCTGAAGAAACTT-3′5and Mut-mγGCShc probe , 5′-CGGTTCTGAAGGTCTCTAAGAATCTGAAGAAACTT-3′ ( NF-κB binding site is underlined and mutated bases are in italics ) respectively , were used . A double stranded OCT-1 DNA probe , 5′-TGTCGAATGCAAATCACTAGAA-3′ was used as control . Supershift EMSAs were carried out as described [19] using following Abs: αp50 , αRelB ( Active Motif , CA ) ; αp65 ( Abcam plc . Cambridge , UK ) ; αp52 , αcRel , rabbit IgG ( Santa Cruz Biotechnology , Santa Cruz , CA ) . Bands were visualized using a phosphoimager ( Bio-Rad Molecular Imager FX , Hercules , CA ) . Western blotting was carried out as described [20] . Blots were probed with Abs specific for: IκBα , IκBβ , IκBε , IKK1 , IKK2 ( Santa Cruz Biotechnology ) ; pIκBα , pIKK1 ( Ser180 ) /pIKK2 ( Ser181 ) , pAKT ( Ser473 ) , AKT , pSAPK/JNK ( Thr183/Tyr185 ) , SAPK/JNK , phospho-p38MAPK ( Thr180/Tyr182 ) , p38MAPK , pERK1/pERK2 ( Thr202/Tyr204 ) , ERK1/ERK2 ( Cell Signaling Technology ) ; β-actin ( Sigma ) . Binding of secondary HRP-labeled goat-αrabbit ( Santa Cruz Biotechnology ) or goat-αmouse Abs ( Sigma ) was analyzed using SuperSignalR West Pico or West Dura Chemiluminescent Substrate ( Pierce , Rockland , IL ) . IKK signalosome was immunoprecipitated from 700 µg of a whole DC lysate using Protein A/G agarose beads ( Santa Cruz Biotechnology ) and rabbit polyclonal αIKK1 Ab . In vitro kinase reaction was performed and kinase activity of immunoprecipitated IKK complex determined as described [20] . The following monoclonal antibodies used for flow cytometry were purchased from eBioscience ( San Diego , CA ) : PE-αmouse CD11c , FITC-αmouse CD11b , FITC-αmouse CD40 , FITC-αmouse CD86 , FITC-αmouse CD80 , FITC-αmouse H2Kd and FITC-αmouse IAd . The fluorescence of stained cells was analyzed on a FACSCalibur ( BD Biosciences ) using Cell Quest Pro software . DCs ( 1×106/ml ) were infected with promastigotes of SbRLD or SbSLD for 3 hours or left uninfected , washed and stimulated with SAG for additional 48 hours in a 24-well plate . Alternatively , DCs ( 1×106/ml ) were infected with promastigotes of SbRLD or SbSLD for varying times or left uninfected . The culture supernatants were analyzed for IL-12 , TNFα and IL-10 productions in triplicate using ELISA kits ( BD Biosciences ) following the manufacturer's instructions . BMDCs ( 5×106/well ) were infected with SbRLD or SbSLD for 3 hours or left uninfected , stimulated with SAG for 3 hours and RNA prepared using RNeasy minikit reagent ( QIAGEN ) . The mRNA expression of mγGCShc , LD-γGCShc , murine glyceraldehyde-3-phosphate dehydrogenase ( mGAPDH ) and LD-tubulin genes were determined via reverse transcription-PCR using platinum quantitative RT-PCR Thermoscript One Step system kit ( Invitrogen , Carlsbad , CA ) , and primers: LD-γGCShc 5′-TATCAAGTCTCGCTACGACT-3′ , 5′-CGGAGTCCTTCAGAAGTT-3′; LD-tubulin 5′-ACATCACGAACTCGGTGTTT-3′ , 5′-TTCGTCTTGATCGTCGCAAT-3′; mγGCShc 5′-AGAACAATCGCTTTAGGATCA-3′ , 5′-AGAAGATGATCGATGCCTTC-3′; mGAPDH 5′-AGATTGTTGCCATCAACGAC 3′ , 5′-ATGACAAGCTTCCCATTCTC-3′ [4] . RNA was isolated from LD promastigotes and mRNA expression of MRPA was detected by analyzing the amplification of 179 bp cDNA fragment of MRPA via reverse transcription-PCR using primers: 5′-GCGCAGCCGTTTGTGCTTGTGG-3′ , 5′-TTGCCGTACGTCGCGATGGTGC-3′ [5] . mRNA expression of LD-tubulin was used as loading control . BMDCs ( 5×106/well ) were stimulated with SAG for 0 . 3 hours or left untreated . ChIP was performed using ChIP-IT kit ( Active Motif ) following the manufacturer's instructions . After immunoprecipitation using rabbit IgG or NF-κB Abs such as αp50 , αRelB and αp65 , followed by DNA extraction; PCR was performed to amplify −991/−673 region of mγGCShc promoter using primers: P1 , 5′-CCAGTTCCCAGAGCCTTCCG-3′ and P2 , 5′-TTGTACGACTCCACATGGCATG-3′ . For a negative control , mGAPDH promoter was amplified by using primers: 5′-CACCCTGGCATTTTCTTCCA-3 and 5′-GACCCAGAGACCTGAATGCTG-3′ [63] . An approximately 1 . 0 kb ( −987/+25 ) long 5′-flanking sequence of mγGCShc gene was amplified by PCR using murine genomic DNA ( Promega , Madison , WI ) and cloned into pGL3-Basic vector . Using this resulting construct , p987-luc , and a QuickChangeII PCR-based site-directed mutagenesis kit ( Stratagene , Cedar Creek , TX ) ; the construct ( Mut p987-luc ) containing a mutant NF-κB binding site , similar to that described in EMSA studies , in −987/+25 region of mγGCShc promoter was generated . Both constructs were confirmed by sequencing . NIH3T3 cells were transiently transfected with a DNA mixture containing p987-luc or Mut p987-luc ( 0 . 266 µg ) , pRL-CMV ( 0 . 200 µg ) , pEGFP-p65 ( 0 . 266 µg ) and/or pEGFP-IκBαΔN ( IκBα with amino acids 1–36 deleted ) ( 0 . 266 µg ) using lipofectamine LTX ( Invitrogen ) . The latter two expression vectors are gifts from Dr . Johannes Schmid ( Medical University of Vienna , Austria ) and Dr . Susan Kandarian ( Boston University , USA ) respectively [64] , [65] . The DNA amount in each transfection was kept constant . Cells were grown for 24 hours after transfection . The luciferase activity of the cell lysates was determined using Dual Luciferase Reporter Assay System ( Promega ) and GLOMAX luminometer ( Promega ) following the manufacturer's instructions . The level of luciferase activity was normalized to the level of Renilla luciferase activity . | Kala-azar , a life-threatening parasitic disease caused by Leishmania donovani ( LD ) , is widening its base in different parts of the world . Currently , there is no effective vaccine against kala-azar . The antimonial drugs like sodium antimony gluconate ( SAG ) have been the mainstay of therapy for this disease . Recently , due to the emergence of antimony-resistance in parasites , SAG often fails to cure kala-azar patients , which is compounding the disaster further . It is still unknown how infection with LD exhibiting antimony-resistant phenotype , in contrast to antimony-sensitive phenotype , is handled by the kala-azar patients upon SAG treatment . This demands an understanding of the nature of host immune responses against these two distinct categories of parasites . Accordingly , we compared the impact of infection with LD exhibiting antimony-resistant versus antimony-sensitive phenotype on dendritic cells ( DCs ) . DCs upon activation/maturation initiate anti-leishmanial immunity . We showed that parasites with antimony-resistant but not antimony-sensitive phenotype prevented SAG-induced DC activation/maturation by blocking activation of NF-κB . The latter is a key signaling pathway regulating DC activation/maturation . Our studies for the first time provide both a cellular and molecular basis for differential response of host cells to parasite isolates with antimony-resistant and antimony-sensitive phenotype , which may influence the outcome of the disease . | [
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"diseases/anti... | 2010 | Leishmania donovani Isolates with Antimony-Resistant but Not -Sensitive Phenotype Inhibit Sodium Antimony Gluconate-Induced Dendritic Cell Activation |
Cellular decisions are determined by complex molecular interaction networks . Large-scale signaling networks are currently being reconstructed , but the kinetic parameters and quantitative data that would allow for dynamic modeling are still scarce . Therefore , computational studies based upon the structure of these networks are of great interest . Here , a methodology relying on a logical formalism is applied to the functional analysis of the complex signaling network governing the activation of T cells via the T cell receptor , the CD4/CD8 co-receptors , and the accessory signaling receptor CD28 . Our large-scale Boolean model , which comprises 94 nodes and 123 interactions and is based upon well-established qualitative knowledge from primary T cells , reveals important structural features ( e . g . , feedback loops and network-wide dependencies ) and recapitulates the global behavior of this network for an array of published data on T cell activation in wild-type and knock-out conditions . More importantly , the model predicted unexpected signaling events after antibody-mediated perturbation of CD28 and after genetic knockout of the kinase Fyn that were subsequently experimentally validated . Finally , we show that the logical model reveals key elements and potential failure modes in network functioning and provides candidates for missing links . In summary , our large-scale logical model for T cell activation proved to be a promising in silico tool , and it inspires immunologists to ask new questions . We think that it holds valuable potential in foreseeing the effects of drugs and network modifications .
Understanding how cellular networks function in a holistic perspective is the main purpose of systems biology [1] . Dynamic models provide an optimal basis for a detailed study of cellular networks and have been applied successfully to cellular networks of moderate size [2–5] . However , for their construction and analysis they require an enormous amount of mechanistic details and quantitative data which , until now , has been often lacking in large-scale networks . Therefore , there has been considerable effort to develop methods based exclusively on the often well-known network topology [6 , 7] . One may distinguish between studies on the statistical properties of graphs [8–10] and approaches aiming at predicting functional or dysfunctional states and modes . For the latter , a large corpus of methods has been developed for metabolic networks mainly relying on the constraints-based approach [11 , 12] . However , for signaling networks , methods facilitating a similar functional analysis—including predictions on the outcome of interventions— have been applied to a much lesser extent [6] . Here we demonstrate that capturing the structure of signaling networks by a recently introduced logical approach [13] allows the analysis of important functional aspects , often leading to predictions that can be verified in knock-out/perturbation experiments . Logical networks have until now been used for studying artificial ( random ) networks [14] or relatively small gene regulatory networks [15–18] . In contrast , herein we study a large-scale signaling network , structured in input ( e . g . , receptors ) , intermediate , and output ( e . g . , transcription factors ) layers . Compared with gene regulatory networks , the behavior of signaling networks is mainly governed by their input layer , shifting the interest to input–output relationships . Addressing these issues requires partially different techniques , as compared with gene regulatory networks . We use a special and intuitive representation of logical networks ( called logical interaction hypergraph ( LIH ) ; see Methods ) , which is well-suited for this kind of input–output analysis . By applying logical steady state analysis , one may predict how a combination of signals arriving at the input layer leads to a certain response in the intermediate and the output layers . Additionally , this approach facilitates predictions of the effect of interventions and , moreover , allows one to search for interventions that repress or provoke a certain logical response [13] . Furthermore , each logical network has a unique underlying interaction graph from which other important network properties such as feedback loops , signaling paths , and network-wide interdependencies can be evaluated . Importantly , we consider here a logical model to be constructed by collecting and integrating well-known local interactions ( e . g . , a kinase phosphorylates an adaptor molecule ) . The logical model is then employed to derive global information ( e . g . , stimulation of a receptor leads to the activation of a certain transcription factor via several logical connections ) . Thus , the available data on the global network behavior is not used to construct the model; instead , it is used to verify the model . The model may then be employed to predict global responses that have not yet been studied experimentally . Here , we apply the logical framework to a carefully constructed model of T cell receptor ( TCR ) signaling . T-lymphocytes play a key role within the immune system: cytotoxic , CD8+ , T cells destroy cells infected by viruses or malignant cells , and CD4+ T helper cells coordinate the functions of other cells of the immune system [19] . The importance of T cells for immune homeostasis is due to their ability to specifically recognize foreign , potentially dangerous , agents and , subsequently , to initiate a specific immune response . T cell reactivity must be exquisitely regulated as either a decrease ( which weakens the defense against pathogens with the consequence of immunodeficiency ) or an increase ( which can lead to autoimmune disorders and leukemia ) can have severe consequences for the organism . T cells detect foreign antigens by means of the TCR , which recognizes peptides only when presented upon MHC ( Major Histocompatibility Complex ) molecules . The peptides that are recognized by the TCR are typically derived from foreign ( e . g . , bacterial , viral ) proteins and are generated by proteolytic cleavage within so-called antigen presenting cells ( APCs ) . Binding of the TCR to peptide/MHC complexes and the additional binding of a different region of the MHC molecules by the co-receptors ( CD4 in the case of T helper cells and CD8 in the case of cytotoxic T cells ) , together with costimulatory molecules such as CD28 , initiates a plethora of signaling cascades within the T cell . These cascades give rise to a complex signaling network , which controls the activation of several transcription factors . These transcription factors , in turn , control the cell's fate , particularly whether the T cell becomes activated and proliferates or not [20] . Therefore , we chose to focus on a limited number of receptors that are known to be central to the decision making process . The high number of kinases , phosphatases , adaptor molecules , and their interactions give rise to a complex interaction network which cannot be interpreted via pure intuition and requires the aid of mathematical tools . Since no sufficient basis of kinetic data is available for setting up a dynamic model of this network , we opted to use logical modeling as a qualitative and discrete modeling framework . Note that there are kinetic models dealing with a smaller part of the network ( e . g . , [5 , 21 , 22] ) , as well as models of the gene regulatory network governing T cell activation [23] . We recently introduced our approach for the logical modeling of signaling networks [13] , and , to exemplify it , we presented a small logical model for T cell activation ( 40 nodes ) . However , this model only served to demonstrate applicability and was too incomplete to address realistic complex input–output patterns . In contrast , the model presented herein has been significantly expanded to 94 nodes and refined by a careful reconstruction process ( see below ) . It is thus realistic enough to be verified with diverse experimental data and to test its predictive power . In this report , the large-scale logical model describing T cell activation and the analysis performed therewith will be presented . First we will show that a number of important structural features can be identified with this model . Then we will show that the model not only reproduces published data on wet lab experiments , but it also predicts non-intuitive and previously unknown responses .
We have constructed a logical model describing T cell signaling ( see Methods and Figure 1 ) , which comprises the main events and elements connecting the TCR , its coreceptors CD4/CD8 , and the costimulatory molecule CD28 , to the activation of key transcription factors in T cells such as AP-1 , NFAT , and NFκB , all of which determine T cell activation and T cell function . In general , the model includes the following signaling steps emerging from the above receptors: the activation of the Src kinases Lck and Fyn , followed by the activation of the Syk-related protein tyrosine kinase ZAP70 , and the subsequent assembly of the LAT signalosome , which in turn triggers activation of PLCγ1 , calcium cascades , activation of RasGRP , and Grb2/SOS , leading to the activation of MAPKs [20] . Additionally , it includes the activation of the PI3K/PKB pathway that regulates many aspects of cellular activation and differentiation , particularly survival . For the activation of elements that play an important role , but whose regulation is not well-known yet ( e . g . , Card11 , Gadd45 ) , an external input was added . These elements can be considered as points of future extension of the model . As mentioned above , our model , which is documented in a detailed manner in Tables S1 and S2 , is based upon local interactions ( e . g . , kinase ZAP70 phosphorylates the adaptor molecule LAT ) that are well-established for primary T cells in the literature . We did not use the known global information ( e . g . , stimulation of a receptor leads to the activation of a certain transcription factor ) for the model construction . Instead , in simulations , the local interactions give rise to a global behavior which can be compared with available experimental observations ( and was thus used to verify the model ) . Each component in the logical model can be either ON ( “1” ) or OFF ( “0” ) . We consider a compound to be ON only if it is fully activated and able to trigger downstream events properly; otherwise , it is OFF . Furthermore , we consider two timescales [13]: early ( τ = 1 ) and late ( τ = 2 ) , involving processes occurring during or after the first minutes of activation , respectively ( the time-scale for each interaction is given in Table S2 ) . Some key regulatory processes such as the degradation of signaling proteins mediated by the E3 ubiquitin ligase c-Cbl [24–26] occur after a certain time , and are thus assigned τ = 2 . Therefore , as will be shown later , analysis of signal propagation during the early events reveals which elements become activated , and the consideration of the late events allows a rough approximation to the dynamic behavior ( sustained versus transient ) of the network . The model comprises 94 different compounds and 123 interactions that give rise to a complex map of interactions ( Figure 1 ) . It is , to the best of our knowledge , the largest Boolean model of a cellular network to date . The first step in our analysis was to examine the interaction graph underlying the logical model . The former can be easily derived from the latter when a special representation of Boolean networks is used ( see Methods ) . The interaction graph is less constrained than the Boolean network since it only captures direct ( positive or negative ) effects of one molecule upon another . Thus , unlike the logical model , the interaction graph cannot describe how different causal effects converging at a certain species are combined . For example , in an interaction graph we may say that A and B have a positive influence on another node C; the logical network is more precise because it expresses that A AND B ( or A OR B ) are required to activate C . Accordingly , compared with the logical model , an interaction graph requires less a priori knowledge about the network under study which comes at the price that functional predictions are limited . Nevertheless , as demonstrated in this section , a number of important functional features can be revealed from the graph model . First we studied global properties of the graph . As expected , the graph is connected ( i . e . , neglecting the arc directions , there is always a path from one node to all others ) . However , the directed graph contains as a core one strongly connected component with 33 nodes ( i . e . , for each pair ( a , b ) of nodes taken from this component there is a path from a to b and from b to a ) . This structural organization is related with the bow-tie structure found in other cellular networks ( e . g . , [7 , 27] ) and implies that the rest of the network ( not contained in the strongly connected component ) mainly consists in relatively simple input and output layers ( including branching cascades ) feeding to and from this component . We continued the interaction-graph-based analysis by computing the feedback loops . Feedback loops are of major importance for the dynamic behavior and functioning of biological networks . Negative feedback loops control homeostatic response and can give rise to oscillations , while positive feedbacks govern multistable behavior ( connected to irreversible decision-making and differentiation processes ) [15 , 28–30] . The interaction graph underlying the logical T cell model has 172 feedback loops , 89 thereof being negative . Remarkably , all feedback loops are only active in the second timescale because each loop contains at least one process of the second timescale . The elements of the MAPK cascade are involved in 92% of the feedback loops . This is due to the fact that there is a connection from ERK to the phosphatase SHP1 from the bottom to the top of the network [5] . Due to this connection , the resulting feedback can return to ERK via many different paths , thereby leading to a high number of loops . Indeed , if the ERK → SHP1 connection is not considered , the number of loops is reduced dramatically from 172 to 13 ( with only 11 being negative ) , all located in the upper part of the network . c-Cbl is involved in ∼85% of them , thus underscoring the importance of c-Cbl in the regulation of signaling processes [25 , 26] . There are 4 , 538 paths , each connecting one of the three compounds from the input layer ( TCR , CD4/CD8 , CD28 ) with one compound in the output layer ( transcription factors and other elements controlling T cell activation ) . The high number of negative paths ( 2 , 058 ) can be traced back to the presence of two negative connections ( via DGK and Gab2 ) . In fact , considering the early signaling events within the network , where DGK and Gab2 are not active yet , the number of paths is reduced to 1 , 530 , with only six of them being negative . These paths are from the TCR and CD28 to negative regulators of the cell cycle ( p21 , p27 , and FKHR ) , having thus a positive effect on T cell proliferation . These and other global effects can be graphically inspected via the dependency matrix [13 , 31] , depicted in Figure 2 . Importantly , when considering the timescale τ = 1 , there is no ambivalent effect ( i . e . , via positive and negative paths ) between any ordered pair ( A , B ) of species , i . e . , A is either a pure activator of B ( only positive paths from A to B ) , or a pure inhibitor of B ( only negative paths from A to B ) , or has no direct or indirect influence on B at all . For example , during early activation , the TCR can only have a positive effect upon AP1 ( the array element ( TCRb , AP1 ) in Figure 2 is green ) . Note that this changes for timescale τ = 2 where , in several cases , a compound influences another species in an ambivalent manner . An important aspect that can be studied with a logical model is signal processing and signal propagation and the corresponding response ( activation/inactivation ) of the nodes upon external stimuli and perturbations ( see Methods ) . One starts the analysis of a scenario by defining a pattern of input stimuli , possibly in combination with a set of nodes that are knocked-out or knocked-in . Then , by an iterative evaluation of the Boolean rules in each node , the signal is propagated through the network , switching each node ON or OFF , respectively ( see [13] and Methods ) . For example , since CD28 ( an input ) is ( permanently ) ON in the scenario shown in Figure 1 , it will ( permanently ) activate node X , which will in turn ( permanently ) activate Vav1 , and so forth . In the same scenario , since the input CD4 is OFF , Lckp1 and therefore Abl , ZAP70 , and other components cannot become activated and therefore are in the OFF state . In the ideal case , each node can be assigned a uniquely determined state that follows from a given input pattern . In terms of Boolean networks , the set of determined node values then represents a logical steady state . In some cases , in particular when negative feedback loops are active , only a fraction of the elements can be assigned a unique steady state value , whereas other ( or even all ) nodes might oscillate [15] . However , since in the T cell model all negative feedback loops become active only during timescale τ = 2 ( as described above ) , a complete logical steady state follows for arbitrary input patterns when considering τ = 1 . Using this kind of logical steady state analysis , we first analyzed the activation pattern of key elements upon different stimuli ( activation of the TCR and/or CD4 and/or CD28; Table 1 ) for timescale τ = 1 . The model was able to reproduce data from both the literature and our own experiments , providing a holistic and integrated interpretation for a large body of data . The model also predicted a non-obvious signaling event , namely that the activation of the costimulatory molecule CD28 alone leads not only to the activation of PI3K—which is to be expected from a large body of literature dealing with CD28 signaling showing that PI3K binds to the motif YxxM of CD28 [32 , 33]—but also to the selective activation of JNK , but not ERK . The model predicts a pathway from CD28 to JNK which gives a holistic explanation for this result: the pathway does NOT involve the LAT signalosome , activation of PLCγ1 , and Calcium flux , but clearly depends on the activation of the nucleotide exchange factor Vav1 which activates MEKK1 via the small G-protein Rac1 ( Figure 1 ) . Clearly , the activating pathway shown in Figure 1 could be identified by a visual inspection of the map ( note that we have intentionally drawn the network in such a way that this route can be easily seen ) . However , in large-scale networks the identification of long-distance pathways by simply following all possible routes becomes infeasible and is particularly complicated if AND connections are involved . Furthermore , since the CD28-induced JNK activation pathway was not expected , one would probably not have searched specifically for this pathway , while the algorithm reveals the whole response of the network . The prediction made by the model is particularly surprising in light of published data which either suggest that CD28 stimulation alone does NOT activate JNK [34 , 35] or induces only a weak activation [36] . Driven by this surprising prediction , we performed the corresponding experiments in vitro . As shown in Figure 3A , stimulation of mouse primary T cells with a non-superagonistic CD28 antibody induced an evident and sustained JNK phosphorylation , thus confirming almost perfectly the predicted binary response . Note , the model also predicted that JNK activation does not depend on the activation of PI3K . Again , this prediction was verified by applying a pharmacological inhibitor of PI3K ( Figure 3D ) . The discrepancies with the literature could be due either to the different cellular systems ( primary T cells versus T cell lines ) or to the different stimulation conditions . The nature of the kinase involved in CD28-mediated signaling remains unclear . Indeed , application of the Src-kinase inhibitor PP2 that inactivates both Lck + Fyn [37] , showed that Src-kinases , which were proposed to mediate CD28 signaling [38] , are dispensable for the CD28-mediated activation of JNK ( Figure 4 ) . To fit the Src-kinase inhibitor data with the model , it would have been possible to simply bypass the Src-kinase and to draw a causal connection from CD28 to Vav . Such a connection would indeed be justified since it is well established that triggering of CD28 leads to the activation of Vav ( [39]; for more details , see Table S2 , reactions 35 and 48 ) . However , we preferred to include a to-be-identified kinase X that gets activated by CD28 ( Figure 1 ) , in order to keep within the model the information that there is a component to be identified . Potential candidates for kinase X would be members of the Tec-family of PTKs . However , it is difficult to study the signaling properties of these kinases in primary non-transformed cells since specific inhibitors for Tec kinases are not yet available and the corresponding knock-out mice show defects in thymic development . Therefore , as we focused during model generation on well-established data from primary T cells and excluded data obtained from knockout mice showing alterations of thymic development , we did not include it . The ability of the model to recapitulate the T cell phenotype of a variety of previously described knock-out mice was also tested ( Table 1 ) . Indeed , the model could reproduce the phenotype of several knock-outs and again reported a rather unexpected result: activation of the TCR in Fyn-deficient cells selectively triggers the PI3K/PKB pathway . This prediction was subsequently tested using peripheral primary T cells prepared from spleen of Fyn-deficient mice . As shown in Figure 3B , the wet-lab experiments corroborated the model result again . However , there was an experimental result which the model could not reproduce: TCR-mediated JNK activation is blocked by an inhibitor of PI3K ( Figure 3C ) . In fact , this result is not in accordance with the network because PI3K has no influence upon JNK ( see dependency matrix , Figure 2 ) . To identify potential connections that would explain the experimental data , we applied the concept of Minimal Intervention Sets ( MISs; see Methods ) . A MIS is a irreducible collection of actions ( e . g . , activation or inactivation of certain compounds ) , that , if applied , guarantees that a certain goal ( a desired behavior ) is fulfilled [13] . Here , we computed the MISs by which JNK becomes activated under the experimentally obtained constraint ( see Figure 3C ) that PI3K is OFF ( describing the effect of the PI3K inhibitor ) , ZAP70 is ON , and that the TCR has been activated . These MISs ( Table 2 ) thus provide a list of minimal combinations of elements that should be directly or indirectly affected by PI3K and thus allow us to explain the observed response of JNK upon inhibiting PI3K . Some of them are obvious , e . g . , the first MIS in Table 2 suggests that JNK activation could be directly interacting with PI3K or elements that are located downstream of PI3K ( e . g . , PIP3 ) . There is currently no convincing experimental evidence for an effect of PI3K on JNK , though . Other MISs in Table 2 suggest that a PI3K-mediated activation of Vav ( both 1 and 3 isoforms ) is involved , which would be an attractive possibility to explain the experimental data . Indeed , Vav possesses a PH domain which can bind to PIP3 , and this mechanism could be important for Vav activation [40] , thus making it a reasonable extension of the model . Another molecule that could be involved in PI3K-mediated activation of JNK is the serine/threonine kinase HPK1 ( see Figure 1 and Tables S1 and S2 ) . Interestingly , HPK1 is phosphorylated by Protein Kinase D1 ( PKD1 ) [41] , a kinase whose activation depends on PKC ( which in turn is dependent on DAG , downstream of PI3K ) for activation . Since the regulation and functional roles of both PKD1 and PKC ( with the exception of the θ isoform ) are not yet well-established in T cells , we did not include them in the model , but a connection PI3K → PIP3 → Itk → PLCγ → DAG → PKC → PKD1 → HPK1 would be plausible ( in which the path from PKC to HPK1 via PKD1 would be new ) . An alternative could be a Rac-dependent activation of HPK1 [42]; however , this is again a not-well-established connection and thus was not considered . Definitely , the model requires a direct or indirect connection from PI3K to JNK , and additional experiments are required to assess which of the candidate links predicted by the MISs are relevant in peripheral T cells . This particular example illustrates another useful and important application of our approach: the model not only reveals that a link is missing , but also suggests candidates that can be verified experimentally . Thus , MIS analysis is capable of guiding the experimentalist and helps to plan the corresponding experiments . As an additional application of MISs , we computed combinations of failures ( constitutive activation or inactivation of elements caused for example by mutations ) which lead to sustained T cell activation without external stimuli . These failure modes would cause uncontrolled proliferation and thus may be connected to diseases such as leukemia or autoimmunity . Interestingly , components occurring in the MISs with few elements ( Table 3 ) are in fact known oncogenes: ZAP70 [43] , PI3K [44] , Gab2 [45] , and PLCγ1 [46] ( and SLP76 is directly involved in PLCγ1 activation ) . Strongly related to the idea of MISs is a systematic evaluation of the network response if the model is confronted with failures . By considering a failure as something that happens to the cell by an internal or external event ( e . g . , a mutation ) , we may assess the robustness—one of the most important properties of living systems [47]—of the network . In contrast , if we consider the failure as an error that has been introduced during the modeling process ( due to incomplete knowledge ) , then we are assessing the sensitivity of the model with respect to the predictions it makes . Accordingly , to study robustness and sensitivity issues , we ( i ) removed systematically each single interaction from the network , ( ii ) recomputed the scenarios given in Table 1 , and ( iii ) compared the new predictions with the 126 original predictions ( Table 1 ) , ranking the interactions according to the number of introduced changes produced ( Table 4 ) . As an average value , 4 . 76 errors were introduced per simulated failure , which corresponds to 3 . 78% of the total numbers of predictions . The most sensitive interactions are mainly located in the upper part of the network and activate components such as the T cell receptor ( TCRb ) , ZAP70 , LAT , Fyn , or Abl . It is intuitively clear that the network is very sensitive to failures ( again , caused either by internal/external events or modeling errors ) in these upper nodes because all pathways branching downstream are governed by them . Accordingly , the validation of our model ( with the data from Table 1 ) is most sensitive to modeling errors in the upper part of the network . We also note that species that can be activated by more than one interaction ( e . g . , PI3K ) are significantly less sensitive to single interaction failures since alternative pathways exist . Regarding robustness , it is worth emphasizing that in the worst case about 30% of the original predictions are affected after removal of an interaction , indicating that there is no “all-or-nothing” interaction in the network . We have also performed the same analysis for the removal of a species ( instead of an interaction ) which basically led to the same results ( unpublished data ) . However , the removal of a node can be seen as a stronger intervention in the network than deleting an interaction , as the former simulates the simultaneous removal of all interactions pointing at that species . Accordingly , deleting nodes implies some stronger deviations from the original predictions . So far we have analyzed which elements within the signaling network get activated upon signal triggering ( i . e . , for the first timescale τ = 1 ) . This is due to the fact that a large corpus of data for these conditions is available ( see Table 1 ) . However , it is important to note that the model is also able to roughly predict the dynamics upon different stimuli and conditions . The modus operandi goes as follows: first , one computes the steady state values with no external input ( τ = 0 ) . Subsequently , the steady state for τ = 1 is computed as described above . Finally , one computes the state of the “slow” interactions ( those only active at τ = 2 ) as a function of the values at τ = 1 , and subsequently recomputes the steady states . This provides the response at late events , τ = 2 . The results obtained can be plotted in a time-dependent manner ( Figure 5 ) . Here , one can also investigate the effect of different knock-outs . For example , the absence of PAG has no effect on key downstream elements of the cascade , due to the redundant role of other negative regulatory mechanisms ( specifically , the degradation via c-Cbl and Cbl-b , and Gab-2–mediated inhibition of PLCγ1 ) . Only a multiple knock-out of these regulatory molecules leads to sustained activation of key elements . Thus , these results point to a certain degree of redundancy in negative feedbacks for switching off signaling . This sort of qualitative analysis of the dynamics shows the ability of the Boolean approach to reproduce the key dynamic properties ( transient versus sustained ) of a signaling process .
In this contribution , a logical model describing a large signaling network was established and analyzed . We set up a comprehensive Boolean model describing T cell signaling and performed logical steady state analyses unraveling the processing of signals and the global input–output behavior . Moreover , by converting the logical model into an interaction graph , we extracted further important features , such as feedback loops , signaling paths , and network-wide interdependencies . The latter can be captured in a dependency matrix ( as in Figure 2 ) which provides thousands of qualitative predictions that can be falsified in perturbation experiments . The logical model reproduces the global behavior of this complex network for both natural and perturbed conditions ( knock-outs , inhibitors , mutations , etc . ) . Its validity has been proven by reproducing published data and by predicting unexpected results that were then verified experimentally . Table 1 summarizes the results of 14 different scenarios , in which the logical model predicted 126 states . For 44 of them , experimental data was available ( 15 from literature and 29 from our own experiments ) confirming the predictions , except in the case discussed above . Furthermore , we clearly show that the concept of intervention sets allows one ( a ) to identify missing links in the network , ( b ) to reveal failure modes that can explain the effects of a physiological dysfunction or disease , and ( c ) to search for suitable intervention strategies , while keeping track of potential side effects , which is valuable for drug target identification . Compared with a kinetic model based on differential equations , a Boolean approach is certainly limited regarding the analysis of quantitative and dynamical aspects , and it certainly cannot answer the same questions . However , to establish such a model requires mainly the topology and only a relatively small amount of quantitative data; hence , a combination of information which is currently available in large-scale networks . Although the model itself is qualitative ( i . e . , discrete ) , it enables us not only to study qualitative aspects of signaling networks , but it can also be validated by semi-quantitative measurements such as those in Figures 3 and 4 . In summary , with the network involved in T cell activation as a case study , our approach proved to be a promising in silico tool for the analysis of a large signaling network , and we think that it holds valuable potential in foreseeing the effects of drugs and network modifications . Although sometimes the results of a logical model may ( afterward ) appear to be obvious ( as in the case of the CD28-mediated JNK connection ) , it enables an exhaustive and rigorous analysis of the information processing taking place within a signaling network . Such a systematic analysis becomes infeasible for a human being in large-scale systems . In addition , the LIH can represent the situation of varying cofactor functions; for example , that two substances A AND B are required to activate a third substance C , but activation of C in the presence of A and a fourth substance D requires B not to be present . Certainly , the logical model for T cell activation is far from complete . We are just at the beginning of the reconstruction process and other receptors and their pathways need to be included . However , we feel that already in its current state , the model may prove useful to inspire immunologists to ask new questions which may first be answered in silico . Furthermore , the model may also provide a framework for those who may endeavor to quantitatively model TCR signaling .
We began construction of the signaling network for primary T cells by collecting data from the literature and from our own experiments providing well-established connections ( Tables S1 and S2 ) . As a first ( intermediate ) result , we obtain an interaction graph . Interaction graphs are signed directed graphs with the molecules ( such as receptor , phosphatase , or transcription factor ) as nodes and signed arcs denoting the direct influence of one species upon another , which can either be activating ( + ) or inhibiting ( − ) . For example , a positive arc leads from MEK to ERK because the first phosphorylates and thereby activates the second ( Figure 1 ) . From the incidence matrix of an interaction graph we can identify important features such as feedback loops as well as signaling paths and network-wide interdependencies between pairs of species ( e . g . , perturbing A may have no effect on B as there is no path connecting A to B ) . Algorithms related to these analyses are well-known [48] and were recently presented in the context of signaling networks [13] . However , from interaction graphs we cannot conclude which combinations of signals reaching a species along the arcs are required to activate that species . For example , in Figure 1 , Jun AND Fos are required to form active AP1 . For a refined representation of such relationships , we use a logical ( or Boolean ) model in which we introduce discrete states for the species ( here the simplest ( binary ) case: 0 = inactive or not present; 1 = active or present ) and assign to each species a Boolean function . Here we use a special representation of Boolean functions known as disjunctive normal form ( DNF , also called “sum of product” representation ) which uses exclusively AND , OR , and NOT operators . A Boolean network with Boolean functions in disjunctive normal form can be intuitively drawn and stored as a hypergraph ( LIH ) [13] , which is well-suited for studying the information flows and input–output relationships in signal transduction networks ( Figure 1 ) . In this hypergraph , each hyperarc connects its start nodes with an AND operation ( indicated by a blue circle in Figure 1 ) and each hyperarc represents one possibility for how its end node can be activated or produced ( note that hyperacs may also have only one start node , i . e . , they are then “graph-like” arcs ) . Red branches indicate species that enter the hyperarc with their negated value . For example , PLCγ-1 ( PLCga in Figure 1 ) AND NOT DGK activates DAG ( see Figure 1 ) . Note that each LIH has a unique underlying interaction graph ( which can be easily derived from the LIH representation by splitting the AND connections ) , whereas the opposite is , in general , not true . Within this logical framework we may study the effect of a set of input stimuli ( typically ligands ) on downstream signaling by computing the logical steady state [13] that results by propagating the signals through the network from the input to the output layer . It seems worthwhile to remark that the updating assumption ( synchronous versus asynchronous [14 , 15] ) —which must usually be made when dealing with dynamic Boolean networks—is not relevant here as we focus on the logical steady states , which are equivalent in both cases . Sometimes a logical steady state is not unique or does not exist due to the presence of feedbacks loops . However , many feedback loops become active only in a longer timescale justifying setting them OFF in the first wave of signal propagation ( allowing them to be switched ON for the second timescale ) . This has been used here for several feedback loops ( see main text and Table S2 ) . The effect of knocking-out a species can be tested by re-computing the ( new ) logical steady state for the respective stimuli . MISs satisfying a given intervention goal can be computed by systematically testing sets of permanently activated or/and deactivated nodes [13 , 31] . All mathematical analyses and computations have been performed with our software tool CellNetAnalyzer [31] , a comprehensive user interface for structural analysis of cellular networks . CellNetAnalyzer and the T cell model can be downloaded for free ( for academic use ) from http://www . mpi-magdeburg . mpg . de/projects/cna/cna . html . Human or mouse T cells were purified using an AutoMACS magnetic isolation system according to the manufacturer's instructions ( Miltenyi , http://www . miltenyibiotec . com ) . Mouse T cells were stimulated with 10 μg/ml of biotinylated CD3ɛ ( a subunit of the TCR ) antibody ( 145–2C11 , BD Biosciences , http://www . bdbiosciences . com/ ) , 10 μg/ml of biotinylated CD28 antibody ( 37 . 51 , BD Biosciences ) , CD3 plus CD28 mAbs , or with CD3 plus 10 μg/ml of biotinylated CD4 ( GK1 . 5 , BD Biosciences ) followed by crosslinking with 25 μg/ml of streptavidin ( Dianova , http://www . dianova . de ) at 37 °C for the indicated periods of time . Human T cells were stimulated with CD3ɛ mAb MEM92 ( IgM , kindly provided by Dr . V . Horejsi , Prague , Czech Republic ) or with CD3 plus CD28 mAbs ( 248 . 23 . 2 ) . Cells were lysed in buffer containing 1% NP-40 , 1% laurylmaltoside ( N-dodecyl β-D-maltoside ) , 50 mM Tris pH 7 . 5 , 140 mM NaCl , 10mM EDTA , 10 mM NaF , 1 mM PMSF , 1 mM Na3VO4 . Proteins were separated by SDS/PAGE , transferred onto membranes , and blotted with the following antibodies: anti-phosphotyrosine ( 4G10 ) , anti-ERK1/2 ( pT202/pT204 ) , anti-JNK ( pT183/pY185 ) , anti-phospho-Akt ( S473 ) ( all from Cell Signaling , http://www . cellsignal . com/ ) , anti-ZAP70 ( pTyr 319 , Cell Signaling ) , anti-ZAP70 ( cloneZ24820 , Transduction Laboratories , http://www . bdbiosciences . com/ ) , or against β-Actin ( Sigma , http://www . sigmaaldrich . com/ ) . Where PI3K and src-kinase inhibitors were used , T cells were treated with 100 nM Wortmannin ( Calbiochem , http://www . emdbiosciences . com ) or 10 μM PP2 ( Calbiochem ) for 30 min at 37 °C prior to stimulation . All experiments have been repeated three times and reproduced the shown results . | T-lymphocytes are central regulators of the adaptive immune response , and their inappropriate activation can cause autoimmune diseases or cancer . The understanding of the signaling mechanisms underlying T cell activation is a prerequisite to develop new strategies for pharmacological intervention and disease treatments . However , much of the existing literature on T cell signaling is related to T cell development or to activation processes in transformed T cell lines ( e . g . , Jurkat ) , whereas information on non-transformed primary T cells is limited . Here , immunologists and theoreticians have compiled data from the existing literature that stem from analysis of primary T cells . They used this information to establish a qualitative Boolean network that describes T cell activation mechanisms after engagement of the TCR , the CD4/CD8 co-receptors , and CD28 . The network comprises 94 nodes and can be extended to facilitate interpretation of new data that emerge from experimental analysis of T cell activation . Newly developed tools and methods allow in silico analysis , and manipulation of the network and can uncover hidden/unforeseen signaling pathways . Indeed , by assessing signaling events controlled by CD28 and the protein tyrosine kinase Fyn , we show that computational analysis of even a qualitative network can provide new and non-obvious signaling pathways which can be validated experimentally . | [
"Abstract",
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"Results",
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] | [
"immunology",
"mammals",
"computational",
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] | 2007 | A Logical Model Provides Insights into T Cell Receptor Signaling |
Compartmentalized HIV-1 replication within the central nervous system ( CNS ) likely provides a foundation for neurocognitive impairment and a potentially important tissue reservoir . The timing of emergence and character of this local CNS replication has not been defined in a population of subjects . We examined the frequency of elevated cerebrospinal fluid ( CSF ) HIV-1 RNA concentration , the nature of CSF viral populations compared to the blood , and the presence of a cellular inflammatory response ( with the potential to bring infected cells into the CNS ) using paired CSF and blood samples obtained over the first two years of infection from 72 ART-naïve subjects . Using single genome amplification ( SGA ) and phylodynamics analysis of full-length env sequences , we compared CSF and blood viral populations in 33 of the 72 subjects . Independent HIV-1 replication in the CNS ( compartmentalization ) was detected in 20% of sample pairs analyzed by SGA , or 7% of all sample pairs , and was exclusively observed after four months of infection . In subjects with longitudinal sampling , 30% showed evidence of CNS viral replication or pleocytosis/inflammation in at least one time point , and in approximately 16% of subjects we observed evolving CSF/CNS compartmentalized viral replication and/or a marked CSF inflammatory response at multiple time points suggesting an ongoing or recurrent impact of the infection in the CNS . Two subjects had one of two transmitted lineages ( or their recombinant ) largely sequestered within the CNS shortly after transmission , indicating an additional mechanism for establishing early CNS replication . Transmitted variants were R5 T cell-tropic . Overall , examination of the relationships between CSF viral populations , blood and CSF HIV-1 RNA concentrations , and inflammatory responses suggested four distinct states of viral population dynamics , with associated mechanisms of local viral replication and the early influx of virus into the CNS . This study considerably enhances the generalizability of our results and greatly expands our knowledge of the early interactions of HIV-1 in the CNS .
While HIV-1 can be detected in both the cerebrospinal fluid ( CSF ) and brain tissue during the weeks after initial exposure [1–7] , it is unknown when the virus actually begins replicating independently in the central nervous system ( CNS ) . Independent viral replication within the CNS has two important implications . First , HIV-1 replication can lead to CNS dysfunction and injury , and while combination antiretroviral therapy ( cART ) has markedly reduced the incidence of HIV-associated dementia ( HAD ) , the prevalence of milder HIV-associated neurological disorders ( HAND ) has increased [8 , 9] in the cART era . Second , independent CNS replication may also provide a reservoir distinct from that found in CD4+ T cells in the blood and lymphoid tissue . We do not know the time course of the virologic events that lead to neurological dysfunction and the potential establishment of a CNS reservoir , or the extent to which these long-term outcomes are predicted by the initial aspects of virus-host interaction . While extensive independent , or compartmentalized , CSF/CNS replication is associated with severe HIV-1 clinical CNS dysfunction [1 , 10–13] , genetically distinct virus can be detected in the CNS throughout the course of infection [4 , 10] . Thus far , two types of compartmentalization have been defined: one in which a few variants are rapidly expanded giving a CSF viral population of low complexity ( clonal amplification ) consisting of variants that require high levels of CD4 for entry ( R5 T cell-tropic ) . The second type is characterized by a complex CSF viral population consisting of variants that can enter cells expressing low levels of CD4 ( macrophage-tropic ) , indicative of a more prolonged period of isolated replication and evolution of the entry phenotype . Additionally , we have recently shown that after vertical transmission to children , CNS compartmentalization can be established via two mechanisms: the early sequestration of one of multiple transmitted variants in the CNS , or the later establishment of compartmentalized CNS virus originating from the periphery [14] . In a previous study , we demonstrated CSF HIV-1 compartmentalization in human subjects during the first year of HIV-1 infection in adults [4] . However , that study only examined viral population sequences from CSF and plasma in a small number of subjects ( eight ) , limiting the generalizability of our findings . Furthermore , the previous study had sparse assessment of longitudinal samples , and included no analysis of sources of compartmentalized HIV-1 within the CSF . For the current study , we used single genome amplification ( SGA ) and phylogenetic analysis to assess viral populations in the CSF in the presence and absence of cellular inflammation ( i . e . pleocytosis ) in cross-sectional and often longitudinal paired blood plasma and CSF samples obtained during the first two years of HIV-infection in ART-naïve subjects . We also extended our analytical approach to include Bayesian Evolutionary Analysis by Sampling Trees ( BEAST ) to assess time to most recent common ancestor ( TMRCA ) of CSF and blood HIV-1 populations [15] , providing new insights on the timing of establishment of early compartmentalized populations , and we assessed the entry phenotypes of selected clones , further confirming the nature of the transmitted virus as R5 T cell-tropic [16] . Based upon a complex interplay between HIV-1 RNA concentration , viral compartmentalization , and CSF white blood cell ( WBC ) count , we suggest at least four different patterns to characterize the relationship between virus in the blood and virus in the CSF/CNS during the early period after infection . The current study considerably enhances the generalizability of our results and provides an unprecedented view of the early interactions of HIV-1 in the CNS .
We analyzed the HIV-1 RNA concentrations in paired blood plasma and CSF samples collected from 72 adult subjects enrolled in an observational neurological study of primary HIV-1 infection , defined as within one year of initial infection . All subjects were infected with HIV-1 subtype B and were ART-naïve at all study intervals , except for one subject , 9018 , who was treated with tenofovir , emtricitabine , and atazanavir between the first and second analyzed time points . Paired follow-up samples were assessed for 37 subjects with longitudinal samples available within the initial two years post infection ( p . i . ) . In total , 144 paired samples were available for analysis . Baseline demographic and clinical characteristics at enrollment for the entire cohort ( n = 72 ) and for the subset that had sufficient CSF viral RNA concentrations ( defined as greater than 1 , 000 copies of viral RNA/ml ) to allow adequate sampling of the viral population via SGA ( n = 33 ) are shown in Table 1 . For the 33 subjects whose samples were analyzed by SGA , a total of 55 blood plasma/CSF sample pairs were analyzed including the longitudinal samples ( Table 2; three time points for subject 9018 and one time point for subject 9040 beyond 2 years p . i . were analyzed but were not included in any overall population analysis . ) Following SGA and phylogenetic analysis , compartmentalization was assessed by three approaches . The choice to use multiple approaches was based on the recent findings of Zarate et al . [17] illustrating that different methods of assessing compartmentalization often yield divergent results . Thus , we assessed CNS compartmentalization using three methods—the tree-based Slatkin-Maddison test ( SM ) [18] and two distance-based methods , Wright’s measure of population subdivision ( Fst ) [19 , 20] and the Nearest-neighbor statistic ( Snn ) [21] . CNS lineages were interpreted as being significantly compartmentalized if all three tests were significant ( P values < 0 . 05 ) . We define CNS phylogenetic states as ( Fig . 1 ) : i ) equilibrated , with similar populations between the blood and CSF , with no evidence of independent CNS replication ( Fig . 1A ) ; and ii ) compartmentalized , with a genetically distinct CSF population as indicated by three statistically significant measures of compartmentalization ( Fig . 1B ) . In our analyses , compartmentalized populations typically included clonally amplified variants often with more genetically diverse variants ( Fig . 1B , Sub . 9040 ) , and sometimes with the presence of recombinants between two clonally amplified variants ( Fig . 1B , Sub . 9096 ) . In order to determine how often our statistical assessment of CNS compartmentalization was due to the presence of clonally amplified viruses , we performed additional analyses in which we collapsed clonally amplified sequences into a single sequence and repeated the tests of compartmentalization . We determined that of the eight sample pairs that displayed both clonal amplification and CNS compartmentalization , three were significantly compartmentalized after collapsing the clonal sequences . This suggests that clonal amplification may drive the statistical assessment of compartmentalization or may be a symptom of ongoing CNS replication . Under this latter scenario , we propose that ongoing viral replication in the CNS may produce diverse , CNS-specific lineages and trigger an influx of T cells that amplify some of these lineages . Table 2 shows the clinical and virologic assessment for each subject who had at least one time point analyzed by SGA , and S1 Table shows this information for the 39 subjects who had no time points analyzed by SGA . We also considered what role cellular inflammation ( pleocytosis ) might play in determining both the HIV-1 RNA concentrations and the nature of the viral population in the CSF , specifically whether an equilibrated population might exist with higher CSF HIV-1 RNA concentrations due to an influx of cells , including infected cells , during an inflammatory response . For our analyses , we chose a cut-off of 10 WBC/μl to define a state of CSF pleocytosis , as this is two-times the published upper limit of normal values of CSF WBC ( 5 cells/μl ) [22] ensuring that the measured pleocytosis was a robust marker for an inflammatory response . In order to assess temporal patterns of CNS viral replication and inflammation , we treated all 144 paired samples from the 72 subjects as independent observations ( a limitation of the analysis but one that allowed us to categorize the samples by time post infection ) . We divided the samples into the following three windows: acute , 0–4 months p . i . ; early , 5–12 months p . i . ; or established , 13–24 months p . i . . The choice of these times also allowed us to bin the data into groups with reasonable sample sizes . Regardless of length of time since HIV-1 infection , the CSF viral RNA concentration was less than 1 , 000 copies/ml in approximately two-thirds of samples ( Fig . 2A ) , suggestive of little local production of virus in the CNS , at least as assessed by viral load . Analysis of the viral populations in the remaining samples showed that in approximately 30% of the paired samples the sequence composition of the viral population in the CSF was similar to the viral population in the blood ( i . e . equilibrated ) , and pleocytosis was detected in the CSF of one-quarter to one-half of the samples with these equilibrated populations ( Fig . 2A ) . Compartmentalized viral populations were also detected but exclusively after the first 4 months , in 11% of samples in the early group ( total n = 70 ) and 3% of the established group ( total n = 30 ) . However , those samples in which pleocytosis was detected were significantly less likely to have viral RNA levels in the CSF of less than 1 , 000 copies/ml compared to the total group of samples ( see below ) . The percentages of samples in each phylogenetic group with pleocytosis ( Fig . 2B ) and without pleocytosis are noted ( S1 Fig . ) . We next assessed factors associated with the CSF viral load . We first examined subjects without evidence of inflammation ( i . e . no pleocytosis ) and either low viral load in the CSF ( less than 1 , 000 copies/ml ) or an equilibrated population as evidence of no sustained local replication . In these subjects the HIV-1 RNA concentration in the CSF was proportionally 1–2% of the level in the blood ( Spearman’s rank correlation coefficient = 0 . 48 , P<0 . 0001 ) ( Fig . 2C ) . We could not determine whether this proportional relationship was maintained for those samples in which the CSF viral load was undetectable ( <50 copies/ml ) , although there was a trend for these samples to be from subjects with low plasma HIV-1 RNA concentrations ( Fig . 2C ) . We hypothesize that this low level of virus in the CSF is due to the normal trafficking of T cells into the CNS , including infected CD4+ T cells that release the observed virus . Pleocytosis was detected in 36% of all subjects ( Table 2 and S1 ) . Consistent with our prior findings in HIV-infected subjects , lymphocytes were the predominant cell type in subjects with and without elevated levels of cellular inflammation [23] . When pleocytosis was detected , the HIV-1 RNA concentration was twice as likely ( 64% ) to be above 1 , 000 copies/ml in the CSF compared to the overall population of which two-thirds were below 1 , 000 copies/ml . Additionally , when pleocytosis was present and the CSF viral load was high enough for SGA analysis , the viral populations were most often equilibrated ( Fig . 2D , open circles ) , with a CSF viral load that was significantly higher than for equilibrated populations without pleocytosis ( P = 0 . 0008 , Mann-Whitney Test ) ( Fig . 2D ) . This suggests that the influx of infected CD4+ T cells associated with pleocytosis brings virus into the CSF/CNS from the blood . There was a trend toward increased CSF:blood albumin ratio ( a marker for reduced blood-brain barrier integrity ) in the presence of pleocytosis , which could contribute to an influx of virus ( Table 2 ) . However , there was a similar ( and statistically significant ) increase in CSF:blood albumin ratio in the compartmentalized subjects that did not account for the increase in CSF HIV-1 RNA concentration compared to the samples with equilibrated populations without pleocytosis ( Fig . 2D; see below ) , which was instead due to local virus production . These data suggest that increased viral burden in the CNS can result from two factors: independent CNS replication , generating compartmentalized CSF populations , or an influx of infected cells as the result of the inflammatory response of pleocytosis , producing a viral population in the CSF that is similar to that in the blood . It is possible that much of the pleocytosis seen in these subjects is in response to HIV-1 replication in the CNS where the influx of infected cells from the blood produces elevated levels of virus that obscure the detection of a lower level of the locally produced and compartmentalized virus responsible for inducing the inflammation . Other agents that induce pleocytosis should have a similar effect on viral load in the CSF and this was seen in an incident of neurosyphilis in subject 9018 when sampled at day 687 p . i . ( Table 2 ) . However , we note that pleocytosis is not always associated with higher viral load ( Table 2 and S1 ) , indicating a more complex and perhaps dynamic relationship between pleocytosis and viral load . Little evidence for local CNS replication was detected until after 4 months of infection ( Fig . 2A ) , suggesting that detectable CNS-compartmentalized populations are present at greater frequency with a longer time since HIV-1 exposure . As noted above , CSF samples with compartmentalized populations had elevated viral RNA loads when compared to the samples with only equilibrated populations in the absence of pleocytosis ( Fig . 2D ) , consistent with local production of virus with the detection of compartmentalization . We used cross sectional analyses to examine when these markers of local replication and inflammation were observed . We estimated the percentage of samples with no evidence of viral involvement in the CNS from the number with a CSF viral RNA concentration less than 1 , 000 copies/ml ( Fig . 2A; unanalyzed samples ) and the number with equilibrated populations in their CSF and little to no pleocytosis ( Fig . 2A; equilibrated ( − ) ) . In contrast , we estimated the percentage of samples with evidence of viral involvement in the CNS from the number with equilibrated populations in their CSF and pleocytosis ( Fig . 2A; equilibrated ( + ) ) and the number with compartmentalized populations in their CSF ( Fig . 2A; compartmentalized ) . In these analyses we interpret equilibrated populations with pleocytosis/inflammation as an indirect marker of local viral replication , i . e . the inflammatory response to local viral replication . Based on these analyses we determined that the vast majority of samples collected during the three time periods ( 0–4 , 5–12 and 12–24 months p . i . ) had no evidence of CNS involvement ( 82 , 78 and 90% , respectively ) , while the remaining samples ( 18 , 22 and 10% , respectively ) had evidence of CNS involvement . However , if viral replication and its associated markers ( e . g . pleocytosis ) are transient or produce small signals , these values will underestimate the actual proportion of subjects with viral replication in their CNS . We used a longitudinal analysis to evaluate the persistence of viral replication in the CNS . Of the 37 subjects with longitudinal sampling , the majority ( 17 of 37 ) had low CSF viral loads at all sampling time points and were not analyzed by SGA ( S1 Table ) . If we focus on the 20 subjects that had higher CSF viral loads ( >1 , 000 copies of HIV-1 RNA/ml ) and were analyzed by SGA , we observe that 9 ( 45% ) had equilibrated populations with minimal to no pleocytosis at all time points analyzed ( Fig . 3A ) . The remaining 11 subjects ( 55% or 30% of all longitudinally sampled subjects ) all showed evidence of pleocytosis and/or compartmentalized viral replication at one or more time points within the initial two-year period ( Fig . 3B ) and 6 ( 30% or 16% of all longitudinally sampled subjects ) had one of these states at two or more time points ( Fig . 3B , subjects below dotted line ) . Thus , 55% of longitudinally sampled subjects analyzed by SGA showed evidence of viral replication and/or marked pleocytosis in the CNS at one or more time points , and 30% showed evidence of persistent viral replication in the CNS . Finally , if the initial sample showed evidence of compartmentalization or an equilibrated population with pleocytosis then subsequent samples were significantly more likely to also be compartmentalized or have pleocytosis than if the initial sample was not in one of these states ( P = 0 . 001 ) . In two subjects , 9040 and 9021 , a compartmentalized CNS population was observed at enrollment and for all analyzed longitudinal time points , spanning a period of 753 and 201 days p . i . , respectively ( one time point beyond 2 years p . i . was analyzed for subject 9040 but was not included in any overall population analysis ) . Further analysis of these subjects identified distinct trends of how HIV-1 becomes established in the CNS . One pattern was seen in the viral evolution in subject 9040 ( Fig . 4A ) . In this case a compartmentalized , clonally amplified population present at the initial time point ( day 165 ) was replaced with a second compartmentalized , clonally amplified variant at day 352 , but the sampling included a recombinant between the first and second clonally amplified variants . Several recombinants between these two early populations were maintained through day 918 , however , the overall population was equilibrated at this last time point . Using BEAST analysis to estimate number of generations of the viral population , the time to most recent common ancestor ( TMRCA ) of the blood population at the initial time point was estimated to be 209 days , reasonably consistent with the reported date of transmission ( 165 days prior to sampling ) . We also estimated that the initial clonally amplified CSF population was established 33 days prior to sampling ( approximately 170 days after transmission ) , followed by a subsequent clonal amplification event and recombination between the two lineages . These data showed the early establishment of a lineage within the CNS that persisted over a period of at least 2 years . To our knowledge , this was the first study to show the maintenance and evolution of a compartmentalized viral population within the CNS over a long duration of time starting during early infection . A second trend was seen for subject 9021 ( Fig . 4B ) . Again , the reported date of transmission , 140 days prior to the first sampling date , was reasonably close to the transmission bottleneck estimated using BEAST at 159 days prior to sampling . In this subject one compartmentalized , clonally amplified lineage was detected in the CSF at the first sampling time point with an estimated age of 102 days , or starting 57 days post infection . This lineage was not present at the second sampling time point ( at 341 days ) but was replaced by a different compartmentalized , clonally amplified variant with an estimated age of 55 days . Thus for this subject we observed a permissive environment for viral replication in which variants were successively and independently amplified within the CNS . We detected compartmentalization as early as 140 days p . i . ( Table 2 ) . Using BEAST to estimate the time to most recent common ancestor ( TMRCA ) we were able to show that often these CSF populations were established much earlier . Four subjects with longitudinal sampling ( 11 samples total ) had a compartmentalized CSF population detected between 5–12 months post infection ( Table 2 ) ; three of these subjects had an initial clonally amplified CSF population ( 7146 , 9021 and 9040; Fig . 4 ) . When we determined the estimated TMRCAs of these CSF populations , we estimate the initial clonally amplified populations were all established within approximately the first four months after infection and two were established within the first two months of infection ( Table 2 ) . These data show that the CNS compartment is permissive for HIV-1 replication in at least a subset of subjects from very early times after infection . We have recently shown that after vertical transmission to children , CNS compartmentalization can be established early via the sequestration of one of multiple transmitted variants in the CNS [14] . When we reanalyzed data from a previously described subject ( 7146 , Fig . 4C ) [4] using BEAST , we showed that the phenomenon of transmission of two variants with one sequestered in the CSF/CNS shortly after transmission also occurs in adults . In this case the two transmitted variants diverged from each other in the donor ( BEAST-estimated TMRCA of 965 days but with a reported transmission date of 156 days prior to sampling ) while the transmitted variants diversified in the recipient . One lineage that was present in both the blood and CSF went through a bottleneck ( presumably the transmission bottleneck ) at 134 days prior to sampling , again consistent with the reported transmission date of 156 days prior to sampling . The other variant was sequestered in the CNS with an estimated bottleneck of 85 days , appearing early as a clonally amplified variant . In addition , a series of recombinants between these two lineages appeared in both the blood and CSF over time . This additional mechanism for establishing a compartmentalized viral population within the CNS early following transmission was also observed for subject 9018 ( Table 2 ) . Macrophage-tropic HIV-1 variants can infect cells expressing low levels of CD4 while R5 T cell-tropic viruses are selected for replication in cells with high levels of CD4 for entry [24–31] . Macrophage-tropic HIV-1 is seen most reliably as a compartmentalized CSF/CNS population in a subset of individuals with HAD . To further our understanding of viral characteristics in the CNS early during infection , we analyzed the entry phenotype of viruses isolated from our adult primary infection cohort . Affinofile cells , on which CD4 and CCR5 surface expression can be differentially induced [32] , are a more reproducible model for entry tropism analysis compared to primary cells [33] . We assessed entry phenotypes by measuring the ability of pseudotyped reporter viruses to enter Affinofile cells expressing either high or low levels of CD4 . Viruses pseudotyped with Env proteins derived from 24 subjects , representing all phylogenetic states and a wide range of days p . i . , all required high levels of CCR5 and CD4 for efficient entry and were considered R5 T cell-tropic ( Fig . 5A-B ) . However , Env proteins from CSF samples containing compartmentalized viral lineages ( all collected more than 4 months post infection ) were significantly better at entering cells expressing low CD4 than Env proteins derived from equilibrated CSF samples ( ANOVA; P<<0 . 001 ) . While this enhanced ability to enter low CD4 cells did not near the level of a macrophage-tropic Env protein ( Fig . 5A-B , Ba-L ) , the detectably elevated levels suggest that compartmentalized lineages may be adapting to enter low CD4 cells in the CNS ( discussed below ) . In contrast , viruses isolated from the CSF of adults within four months of infection are uniformly poor at infecting low CD4 cells , indicating that they have been selected for replication in T cells . This is consistent with multiple studies showing that macrophage-tropic viruses are not transmitted [16 , 27 , 28 , 34–39] . Together these results indicate that the CNS is initially exposed to R5 T cell-tropic variants and that viruses in the CNS remain R5 T cell-tropic for the first two years of infection , but the data provide suggestive evidence that the evolution of macrophage tropism may begin during this period . We also assessed the infectivity of a subset of the pseudotyped viruses on monocyte-derived macrophages ( MDMs ) generated from three separate donors . Infectivity was first assessed on Affinofile cells expressing high levels of CD4 , with equal levels of infectious virus then added to each of the MDM preparations . There was general concordance between infectivity on Affinofile cells and infectivity on MDMs , although the level of infectivity differed significantly between the three donors ( S2 Fig . ) . Viruses representing subjects with equilibrated populations and with low infectivity on Affinofile cells with low CD4 ( Fig . 5A ) had low infectivity on MDM ( from subjects 9027 , 9045 , 9055 , 9063 , and 9073; S2 Fig . ) . Viruses from four of five subjects with CNS compartmentalization were also assessed for their ability to enter Affinofile cells expressing low levels of CD4 and MDMs . Both blood- and CSF-derived viruses from one subject ( subject 9096 ) were observed to have intermediate infectivity on low CD4 Affinofile cells ( Fig . 5B ) and MDMs ( S2 Fig . ) . Similarly , two of the compartmentalized subjects ( 9018 and 9021 ) had CSF-derived viruses with elevated infectivity of low CD4 Affinofile cells ( Fig . 5B ) and MDMs ( S2 Fig . ) . Finally , both blood- and CSF-derived viruses from one compartmentalized subject ( subject 7146 ) were unable to efficiently enter both low CD4 expressing Affinofile cells and MDMs ( S2 Fig . ) . Thus infectivity of MDMs is generally consistent with the conclusions derived from infection of Affinofile cells although the variability of infectivity of MDMs between donors precludes an accurate assessment of the range of CD4 entry phenotypes that can be observed using Affinofile cells .
Independent HIV-1 replication in the CNS has been associated with neurological disorders [10 , 40 , 41] and may represent a distinct reservoir from that found in the blood and lymphoid tissue [42 , 43] . We examined the virologic characteristics associated with early CNS infection through analysis of paired cross-sectional and longitudinal blood plasma and CSF samples from a large cohort of 72 ART-naïve subjects infected with HIV-1 for less than two years . Our current study significantly builds upon a previous preliminary study by our group [4] , enabling us to propose a model with four distinct states to describe the relationship between viral populations in the CSF/CNS and viral populations within the peripheral blood during early HIV-1 infection . These states are based upon details revealed by the current study on mechanisms of establishment of viral compartmentalization within the CNS , relationships between cellular inflammation , HIV-1 RNA levels and phylogenetic state , and insight into longitudinal maintenance and evolution of compartmentalization . The first state ( Fig . 6A ) was observed in subjects with little evidence of CNS replication or pleocytosis , with CSF HIV-1 RNA concentrations proportionally 1–2% of the viral load in the periphery ( Fig . 2B ) . In many of these subjects , the CSF HIV-1 RNA level was very low , below the limit of detection of standard assays . Minimal CSF viral burden has been observed in a prior report on a portion of this primary infection cohort [5] . With little or no pleocytosis , HIV-1 is likely entering the CSF/CNS at low levels via incomplete partitioning of virus at the blood-brain barrier , or low level trafficking of immune cells , including small numbers of infected CD4+ T cells . In this circumstance the viral population is very similar to the population in the blood . It is possible that some HIV-1 is replicating independently in the CNS at low levels in these subjects , but we were not able to detect these putative genetic variants above the low level background of virus recently imported from the periphery into the CSF/CNS . An argument in favor of even this low level viremia in the CSF being the result of T cell trafficking is the observation that in neuro-asymptomatic subjects with CD4+ T cells below 50 cells/ul in the blood the viral load in the CSF is on average lower than in subjects with higher CD4+ T cell counts [44 , 45] . In a second state ( Fig . 6B ) , we observed a relationship between equilibrated viral populations with elevated viral load and high levels of pleocytosis ( Fig . 2C ) . These equilibrated populations were most likely the result of the release of virus from increased numbers of infected CD4+ T cells trafficking from the periphery into the CNS . Though pleocytosis of > 10 cells/ul might have been due to a variety of inflammatory conditions ( e . g . neurosyphilis as documented in one individual ) , it is most likely in response to HIV-1 replication in these PHI subjects . We screened for syphilis in this cohort , and detailed clinical and imaging assessment did not reveal other contributing causes of pleocytosis . Furthermore , other ‘background’ non-HIV causes of CSF WBC ≥ 10 cells/ul are unlikely in these subjects , as our parallel studies of 54 HIV-uninfected volunteers recruited from the similar local community demonstrated median CSF WBC counts of 1 cell/ul ( IQR 0–2 ) , and none of these 54 subjects had a CSF WBC as high as 10 [5] . In the setting of pleocytosis , while low levels of local CNS replication may have been occurring , the virus imported from the periphery by infected CD4+ T cells dominated the population as it raised the CSF HIV-1 RNA concentration by release of virus imported from the blood . If the inflammatory immune response was successful , pleocytosis might eventually result in low CSF viral loads , a condition observed in a small subset of subjects with pleocytosis but very low levels of virus in the CSF ( S1 Table ) . Pleocytosis was also observed in several subjects with an intermediate viral population phenotype and half of the subjects with compartmentalized viral populations ( Fig . 2D ) , suggesting pleocytosis may result in dynamic changes in the viral population in the CSF . An association between equilibrated compartments and high pleocytosis was also observed in a previous study analyzing four HIV-infected subjects during therapy interruption [46] . In a third state ( Fig . 6C ) , we observed clonally amplified CSF populations of low complexity ( Fig . 1 and 4 ) representing the recent expansion of identical or nearly identical variants that required high levels of CD4 for entry ( R5 T cell-tropic; Fig . 5 ) . High levels of pleocytosis were observed in approximately half of the subjects with clonally amplified CSF populations , making it possible that the influx of activated CD4+ T cells may also have provided cellular targets for further transient amplification of a CSF variant . We [47] ( Dukhovlinova et al . , in preparation ) and others [48–50] have observed clonal amplification in the genital tract as well as in the CSF both early [4 , 14] and at later times in infection [41] . Clonal amplification appears to be a distinct type of virus-host interaction where infection of a population of CD4+ T cells in a compartment is a low probability event and when it occurs there is transient rapid expansion of the viral population . Due to the daily rapid turnover of the CSF viral RNA load , the elevated CSF viral RNA load that is often observed during clonal amplification , and the fact that these clonally amplified lineages generate their own diversity that can persist within the CNS , it is highly unlikely that clonally amplified virus represents virus produced from a single cell . The detection of clonally amplified populations in the CSF within the first year of infection has allowed us to estimate the establishment of these populations within the CNS to within the first 2–6 months ( Table 2 , Fig . 4 ) , and such amplified populations were detected in 8% of subjects in this study within the first year . In the final state , we observed more genetically complex compartmentalized viral replication within the CSF/CNS ( Fig . 6D ) indicative of persistent replication beyond a single clonal amplification event . In an effort to get a more complete view of the interaction of the virus within the CNS at these early times of infection we have interpreted the presence of persistent replication in the CNS based on four criteria: i ) sequential clonal amplification events that indicated a permissive CNS environment for viral replication ( Fig . 4B ) ; ii ) overlapping clonal amplification events that gave rise to compartmentalized recombinants showing continuous replication between the sampled time points ( Fig . 4A ) ; iii ) intermittent compartmentalization and pleocytosis suggesting an inflammatory immune response to ongoing replication ( Fig . 3B ) ; and iv ) sequestration of a transmitted variant within the CNS ( Fig . 4C ) . Collectively these markers defined approximately 30% of subjects in the first two years as having evidence of viral replication in the CNS in at least one time point , and 16% having evidence of replication and/or inflammation at multiple time points within this period . This suggests that the CNS compartment is permissive for HIV-1 replication in at least a subset of subjects from a very early period after infection . Entry tropism analysis revealed that all compartmentalized variants required high levels of CD4 for entry . It is now widely described in the literature that macrophage-tropic variants utilize low levels of CD4 for entry [24–31] , are not transmitted , and that the transmitted virus is R5 T cell-tropic [16 , 27 , 28 , 34–39] , an understanding further supported by our phenotypic analysis ( Fig . 5 ) . Our finding that the viruses involved in this early persistent CNS replication were adapted to replication in CD4+ T cells is distinct from previous studies of individuals with HAD where genetically complex compartmentalized CSF populations that had been replicating as an isolated population had evolved to replicate in macrophages/microglia [41] . Thus , adaptation to use low levels of CD4 for entry , a hallmark of macrophage tropism , is not a feature of the transmitted virus and does not evolve during the early stages of CNS infection in adults , at least as reflected in the compartmentalized virus detected in the CSF . However , we do note that the compartmentalized viruses from the CSF show a small but statistically significant increase in the ability to enter cells with low levels of CD4 compared to CSF virus from equilibrated subjects ( Fig . 5B ) . One explanation for this small difference is that the virus in the CNS is carrying out at least a portion of its replication in a cell with low levels of CD4 which allows for at least a low level of selection for a low CD4 entry phenotype . We found no consistent differences in glycosylation site count or positions , or consistent sequence changes in sites previously described as being associated with macrophage tropism in comparing the viral sequences from the plasma to the compartmentalized sequences in the CSF ( S2 Table and S3 ) . The only CNS tissue that is readily sampled in volunteer human subjects is CSF , which , though not identical to brain , is produced within the brain in the choroid plexus , and reflects brain inflammation and infection in the context of CNS infections including HIV-1 . Measures of immune activation , HIV-1 burden , and neural injury detected in CSF are markers of brain involvement in HIV-1 that correlate to clinical and pathologic disease [51] . While the cellular source of HIV-1 RNA detected in the CSF is not certain and may differ during different stages of infection [52] , compartmentalization of HIV-1 detected in CSF associates with clinical dementia in humans [10] and immunopathology in the brain in rhesus macaques [53] . Despite limitations of generalizing CSF findings to those of the CNS more broadly , our studies have used the best methods available in living humans to assess HIV-1 populations derived from the CNS in a unique cohort of subjects enrolled during primary HIV-1 infection . Our results show that in cross-sectional analysis over the first two years of HIV-1 infection , 30% of subjects have evidence of either local viral replication in the CNS or a robust CNS inflammatory response , and that in approximately 16% of subjects this CNS involvement can persist over time . We have found that the viral population in the CSF is dynamic as the result of local replication and/or the influx of virus in infected CD4+ T cells as part of an inflammatory response . This early viral replication in a subset of subjects may represent an inability to protect the CNS from infection , potentially leading to HAND later in infection , and may also define a distinct reservoir of infected cells within the body . Longitudinal follow-up of these subjects to examine the long-term impact of the presence of early active HIV-1 replication in the CNS will help to define the significance of these findings for clinical neurologic disease outcomes and compartmentalized viral reservoirs in the setting of HIV-1 .
The study was approved by the Institutional Review Boards at UCSF , Yale University , and the University of North Carolina at Chapel Hill . All study participants were adults ( age ≥ 18 years ) . Written informed consent was obtained from all participants . We assessed samples obtained through an observational longitudinal neurological study of primary HIV-1 infection to determine viral characteristics associated with early HIV-1 CNS infection . Subjects were referred from the community and were eligible if they met prospectively determined criteria for laboratory confirmation of primary HIV-1 infection , as previously described [4] . Subjects were screened at study enrollment for systemic syphilis by blood RPR testing . Subsequent blood and CSF samples were tested for RPR and VDRL , respectively , if an outside test suggested syphilis exposure or CSF WBC was markedly elevated compared to that in an earlier longitudinal sample . No subjects had clinical evidence of other inflammatory neurologic disorders such as multiple sclerosis or CNS opportunistic infections based on interview and examination by an HIV-1 neurologist at each visit . A total of 57 of the 72 subjects volunteered to participate in magnetic resonance imaging of the brain for the overall study protocol; scans were reviewed by a neuroradiologist and none revealed evidence of encephalitis , tumor or opportunistic infection . Blood and CSF samples were collected at enrollment , six weeks , and every six months thereafter . This analysis included samples obtained up to two years post-infection from subjects enrolled prior to 4/1/2012 . CSF and plasma HIV-1 RNA concentrations were determined as described [4]; paired samples were selected for further SGA analysis if CSF HIV-1 RNA was greater than1 , 000 copies/ml ( to ensure adequate sampling ) . Samples with lower viral loads could be analyzed if larger volumes were committed to concentrate the virus , but we chose to use a cut-off of 1 , 000 viral RNA copies/ml for these studies . Primary study endpoints included SGA of the HIV-1 env gene for viral genetic compartmentalization and phenotypic analyses , CSF and blood HIV-1 RNA concentrations , measures of CSF cellular inflammatory response ( white blood count , WBC ) and blood brain barrier disruption ( CSF:plasma albumin ratio ) . When collected , CSF samples were initially placed on wet ice and delivered to the lab for processing within one hour . For virology analyses , CSF samples were centrifuged at 1200 x g for 10 min to remove contaminating cells or cellular debris , and the supernatant was subsequently aliquoted and stored at −70°C for later assay . Viral RNA was isolated as previously described from the CSF supernatant [4] . Briefly , RNA was isolated from samples ( 140 μl ) with viral loads >10 , 000 copies/ml using the QIAmp Viral RNA Mini kit ( Qiagen ) . To increase template number , samples with viral loads <10 , 000 copies/ml were first pelleted by ultracentrifugation . cDNA was generated using an oligo-d ( T ) primer . Single genome amplification/template endpoint dilution PCR [38] of the env gene through the 3’ LTR U3 end was conducted using the cDNA as template as previously described [4 , 14] . Sequences for full-length env were generated ( samples analyzed previously were sequenced from the start of V1 through the ectodomain of gp41 [4] ) . Phylogenetic analysis were conducted in a manner similar to our previous study [14] . In brief , DNA sequences were aligned ( MUSCLE ) [54–56] using EBI web tools [57] , and phylogenetic trees were generated ( neighbor-joining method , MEGA 4 . 0 [58] ) . Phylogenetic states were determined by statistical evaluation using the Slatkin-Maddison ( SM ) test [18] as previously described [14] , Wright’s measure of population subdivision ( Fst ) [19 , 20] and the Nearest-neighbor statistic ( Snn ) [21] . CSF populations were defined as being compartmentalization if all three statistical tests ( SM , Fst and Snn ) yielded significant results ( P values < 0 . 05 ) or equilibrated if one or more of tests yielded non-significant results . Low bootstrap values were used ( ≥35 ) because of the overall low diversity of the viral populations early after infection . Clonally amplified lineages ( short branch lengths with bootstrap values ≥ 99 and a clade of ≥ 3 variants ) were also identified . No contamination occurred between samples ( S3 Fig . ) . Sequences for subjects 9002 ( 338 d . p . i . ) , 9007 , 9018 ( 200 d . p . i . ) , 9025 , 9037 , 9039 , 9040 ( 165 d . p . i . ) , and 7146 were generated in our previous study [4] . A Bayesian Markov Chain Monte Carlo ( MCMC ) approach using BEAST v . 1 . 6 . 1 [15] estimated the TMRCA for each viral population . A substitution rate of 1 . 5x10−5 substitutions/site/generation and standard deviation of 3 . 0x10−6 were fixed under a lognormal relaxed clock ( uncorrelated ) model . The rate was calculated via tip dating , using a consensus sequence ( set as day 0 ) , and the estimated days post infection . The HKY nucleotide substitution model had estimated base frequencies and a gamma-distributed rate heterogeneity ( 4 gamma categories ) . A coalescent Bayesian Skyline tree prior with a Piecewise-constant skyline model was used ( 10 groups ) . The MCMC algorithm was run for 30 million generations , logging every 1000 and with a 10% burn-in . The results from at least two independent runs were combined , and the effective sample size for all estimates was >200 . A generation time of 1 . 0 day was used . Full length HIV-1 env genes were re-amplified from the first-round SGA products as previously described [41] . The PCR product was cloned into the pcDNA3 . 1D/V5-His-TOPO expression vector ( Invitrogen ) using the pcDNA 3 . 1 directional TOPO expression kit ( Invitrogen ) . 293T cells were cultured in Dulbecco’s modified Eagle medium ( DMEM ) supplemented with 10% fetal bovine serum ( FBS ) and 100 mg/ml of penicillin and streptomycin . 293-Affinofile cells [32] , generously provided by Dr . Ben-Hur Lee , were maintained in DMEM supplemented with 10% dialyzed FBS ( 12–14 kD dialyzed; Atlanta Biologicals ) and 50 mg/ml blasticidin ( D10F/B ) . Env-pseudotyped luciferase reporter viruses were generated as previously described [14] . Briefly , 293T cells were cotransfected with an env expression vector and the pNL4-3 . LucR-E- HIV-1 backbone ( obtained from the NIH AIDS Research and Reference Reagent Program , Division of AIDS , NIAID , NIH ) using the Fugene 6 transfection reagent and protocol ( Roche ) . Transfection medium was replaced with fresh culture medium five hours post-transfection and the cells were incubated at 37°C for 48 hours , after which viral supernatants were filtered with 0 . 45 μM filters ( Millipore ) and stored at −80°C . 293-Affinofile cell [32] CD4 and CCR5 receptor expression was induced with doxycycline ( doxy; Invitrogen ) and ponasterone A ( ponA; Invitrogen ) , respectively , as previously described [14] . Briefly , cells were induced at two conditions: CD4high/CCR5high ( 6 ng/ml doxy and 5 μM ponA , respectively ) and CD4low/CCR5high ( 0 ng/ml doxy and 5 μM ponA ) . CD4 and CCR5 receptor expression was measured using quantitative fluorescence-activated cytometry ( qFACS ) following staining with either phycoerythin ( PE ) -conjugated anti-human CD4 antibody ( clone Q4120 , BD Biosciences ) or PE-conjugated mouse anti-human CCR5 antibody ( clone 2D7 , BD Biosciences ) , and surface levels were calculated using QuantiBRITE beads ( BD Biosciences ) . As described previously [14] , Env-pseudotyped luciferase reporter viruses were first titered on 293-Affinofile cells [32] expressing CD4high/CCR5high . For viral infections , black tissue culture plates ( 96 wells ) were coated with 10% poly-L-lysine and seeded with 293-Affinofile cells ( 1 . 85 x 104 cells/well ) . Eighteen to 24 hours later , expression of CD4 and CCR5 was induced at CD4high/CCR5high and CD4low/CCR5high . Eighteen to 24 hours later , the induction medium was removed and replaced with 100 μl of fresh , warmed culture medium containing Env-pseudotyped virus . The plates were spinoculated [59] at 2 , 000 rpm for 2 hours at 37°C , and incubated for 48 hours at 37°C . Infection medium was removed , cells were lysed , and luciferase activity was assayed using the luciferase assay system ( Promega ) . Clone sequences were not compared to the original parental sequence prior to pseudotyping and Affinofile cell infection . Instead , entry tropism data for each parental amplicon included three replicates from 2–3 clones derived from the same parental amplicon . In this analysis we assume any PCR-introduced error would either not change the entry phenotype or would create a nonfunctional protein which would not be included in the subsequent analysis . The concordance of the entry phenotype of the replicate clones was taken to represent the phenotype of the amplicon sequence . Compartmentalization was assessed statistically using the Slatkin-Maddison test for gene flow [18] , Wright’s measure of population subdivision ( Fst ) [19 , 20] and the Nearest-neighbor statistic ( Snn ) [21] . Differences between groups were examined for statistical significance using the Mann-Whitney Test . The one exception was our analysis examining whether env genes derived from samples with and without CSF compartmentalized lineages differed in their ability to enter Affinofile cells expressing low levels of CD4 expression . We used a linear model to perform this analysis ( performed in [R] ) and used the stepAIC function to perform stepwise model selection . All correlations employed Spearman’s rank correlation coefficient . For all statistical tests , P values less than 0 . 05 were considered significant . The HIV-1 env nucleotide sequences determined in this study have been deposited in GenBank under accession numbers KM353586-KM355197 | Early HIV-1 CNS replication likely provides a foundation for brain injury and a potentially important tissue reservoir . To explore the character and timing of emergence of early HIV-1 CNS replication , we examined paired cerebrospinal fluid ( CSF ) and blood samples from 72 ART-naïve adults , with one-half having longitudinal samples , during the first two years following HIV-1 subtype B infection . In a cross sectional analysis over the first two years of infection , 10–25% of subjects had evidence of either local viral replication in the CNS , defined by the presence of CSF compartmentalization , or a robust inflammatory response , and in approximately 16% of subjects this CNS involvement persisted over time . In some subjects , one of two transmitted viruses replicated predominantly within the CNS , providing insight into how HIV-1 can establish independently replicating populations early in different parts of the body . Based on their entry phenotype , all viruses were selected for replication in CD4+ T cells , although this phenotype was slightly altered in the compartmentalized virus . Overall , we suggest four states to model the nature of HIV-1 CNS infection , which imply distinct mechanisms of virus/host interaction within the CNS during early infection . | [
"Abstract",
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"Methods"
] | [] | 2015 | Compartmentalized Replication of R5 T Cell-Tropic HIV-1 in the Central Nervous System Early in the Course of Infection |
Glucokinase ( GCK ) catalyzes the rate-limiting step of glucose catabolism in the pancreas , where it functions as the body's principal glucose sensor . GCK dysfunction leads to several potentially fatal diseases including maturity–onset diabetes of the young type II ( MODY-II ) and persistent hypoglycemic hyperinsulinemia of infancy ( PHHI ) . GCK maintains glucose homeostasis by displaying a sigmoidal kinetic response to increasing blood glucose levels . This positive cooperativity is unique because the enzyme functions exclusively as a monomer and possesses only a single glucose binding site . Despite nearly a half century of research , the mechanistic basis for GCK's homotropic allostery remains unresolved . Here we explain GCK cooperativity in terms of large-scale , glucose-mediated disorder–order transitions using 17 isotopically labeled isoleucine methyl groups and three tryptophan side chains as sensitive nuclear magnetic resonance ( NMR ) probes . We find that the small domain of unliganded GCK is intrinsically disordered and samples a broad conformational ensemble . We also demonstrate that small-molecule diabetes therapeutic agents and hyperinsulinemia-associated GCK mutations share a strikingly similar activation mechanism , characterized by a population shift toward a more narrow , well-ordered ensemble resembling the glucose-bound conformation . Our results support a model in which GCK generates its cooperative kinetic response at low glucose concentrations by using a millisecond disorder–order cycle of the small domain as a “time-delay loop , ” which is bypassed at high glucose concentrations , providing a unique mechanism to allosterically regulate the activity of human GCK under physiological conditions .
Human pancreatic glucokinase ( GCK ) is the body's principal glucose sensor [1] . GCK is a 52 kDa monomeric enzyme that catalyzes the formation of glucose-6-phosphate from glucose and ATP [2] . This chemical transformation represents the rate-limiting step of glucose catabolism in the pancreas , allowing GCK activity to regulate the rate at which insulin is secreted from β-cells [3]–[5] . The importance of this enzyme in maintaining glucose homeostasis is emphasized by several disease states associated with GCK dysfunction . Loss-of-function mutations , of which more than 600 have been described , cause either maturity onset diabetes of the young type II ( MODY-II ) or permanent neonatal diabetes mellitus ( PNDM ) [6] . A small number of gain-of-function mutations have also been identified in patients with the potentially fatal disease , persistent hypoglycemic hyperinsulinemia of infancy ( PHHI ) [7]–[19] . Functional characterization indicates that most PHHI-associated variant enzymes display a reduced level of positive cooperativity toward glucose . Interestingly , many of the PHHI-associated substitutions co-localize to a common region of the GCK scaffold that is distant from the active site [7]–[19] . In recent years , pharmaceutical research has directed significant efforts toward developing synthetic allosteric activators that target GCK as a strategy to lower blood glucose levels in type 2 diabetic patients [20] . At least one GCK activator has advanced to phase II clinical trials as an antidiabetic agent , yet the functional role and molecular basis of action of such molecules is poorly understood [21] . Similarly , the mechanism of hyperactivity associated with PHHI-linked GCK variants is unclear . GCK's unique kinetic features are responsible for its physiological role in maintaining glucose homeostasis . The steady-state velocity shows a sigmoidal dependence upon glucose concentration , with a Hill coefficient of 1 . 7 [2] . This positive cooperativity enables GCK to sensitively respond to small perturbations in blood glucose concentrations , whereby the midpoint of this steady-state response , K0 . 5 , approximates physiological blood sugar levels ( 4–10 mM ) . The kinetic cooperativity of GCK is mechanistically distinct from other modes of allostery , which involve polypeptide oligomerization or require multiple ligand binding sites [22]–[25] . Two theoretical mechanisms—the ligand-induced slow transition ( LIST ) and mnemonic models—have been put forth to explain kinetic cooperativity in monomeric GCK [26] , [27] . In both models , cooperativity is postulated to result from slow conformational transitions that accompany glucose binding and/or product release . The models differ , however , in the relative degree of conformational heterogeneity displayed by the enzyme at various stages along the reaction coordinate . According to the LIST mechanism , two separate catalytic cycles are possible resulting from two distinct conformations of the enzyme . In contrast , the mnemonic model postulates a single catalytically active enzyme conformation with the ability to “remember” its active state for only a short period of time following turnover . Although data have accumulated over the years in support of each mechanism , a consensus has yet to be reached [28]–[33] . X-ray crystallographic structures reveal that GCK adopts a prototypic hexokinase fold , consisting of a small and large domain separated by a variable opening angle dependent upon substrate association ( Figure 1A ) [28] . The kinetic mechanism of GCK is strictly ordered [2] , with glucose binding first , accompanied by a large structural rearrangement from an open to a closed structure ( Figure 1B ) . Binding of ATP does not induce significant additional changes to the structure of the glucose-bound state ( Figure 1C ) [34] . The crystal structures also identify a common binding site for synthetic GCK activators at a location within the small domain that is approximately 20 Å removed from the glucose binding site . Differences observed between available crystal structures demonstrate the ability of GCK to sample discrete conformations , but they do not explain the dynamic basis of allosteric regulation as set forth in the LIST and mnemonic models [28] , [29] , [34]–[38] . Herein , we describe the results of the first investigation of the functional dynamics of GCK at atomic detail by high-resolution NMR of specifically labeled side chains . We characterize the conformational dynamics of the wild-type enzyme as it progresses along the reaction coordinate and explain the molecular mechanism of kinetic cooperativity . We also uncover the molecular basis of activation observed in PHHI-associated variants or when a synthetic activator associates with the enzyme . Our findings suggest a model for GCK cooperativity involving a slow disorder–order cycle of an intrinsically disordered domain that is operational under low glucose concentrations but that is bypassed at elevated glucose concentrations .
The large size and dynamic nature of GCK , combined with the poor spectral dispersion even upon perdeuteration , prevented the use of traditional NMR approaches for backbone resonance assignment and structural analysis [32] . Instead , we focused on selected side chains only , a strategy that has proven effective for studies of other challenging protein systems and large complexes [39] , [40] . For this purpose , we introduced 13C spin probes in the Cδ1 methyl groups of 17 isoleucine side chains and 15N spin probes at the Nε sites of three tryptophan side chains [39]–[41] . The labeled residues are quite uniformly distributed throughout the enzyme's structure . The large domain contains one Trp and 10 Ile residues , while two Trp and seven Ile residues reside in the small domain ( red and yellow spheres in Figure 1A–C ) . Together these probes permit the study of internal dynamics throughout the protein . Importantly , the methyl resonances can retain narrow line widths even in high-molecular weight proteins through the methyl-TROSY effect manifested in the 2D 1H-13C HMQC experiment used here [39] , [40] . Site-specific assignment of Ile and Trp resonances was achieved by single-site substitutions with Val and Phe , respectively , followed by the recording of 2D 1H-13C HMQC and 1H-15N HSQC spectra to identify missing cross-peaks ( Figure S1 ) . To achieve a global portrait of the enzyme's structure and dynamics prior to glucose association , we collected 1H-13C HMQC spectra of 13CH3-Ile labeled GCK . The 1H-13C HMQC of unliganded GCK displays a high degree of cross-peak overlap and heterogeneous peak intensities ( Figures 1D and S2 ) . This behavior is consistent with previously reported , unassigned 1H-15N TROSY spectra of GCK specifically labeled on Ile backbone atoms [32] . Nine Ile residues located in the large domain and two Ile side chains situated in the small domain are observable in unliganded GCK . The 2D 1H-15N HSQC spectrum of unliganded 15N-Trp labeled GCK reveals only a single cross-peak . Mutagenesis demonstrated that this cross-peak is dominated by contributions from W167 ( Figure S3 ) . Notably , the only small domain residues observable in the unliganded spectra—I159 , I163 , and W167—all reside in a loop that is absent in the X-ray structure of unliganded GCK . The sharp cross-peaks originating from these three residues , along with the nearly degenerate chemical shifts of the Ile 159 and 163 , reflect the presence of extensive rapid motional averaging and indicate that this loop is disordered , both in the crystal and in solution ( Figure S4 ) [42] , [43] . To investigate whether the absence of the resonances of five isoleucines belonging to the small domain results from motions of these side chains occurring on the intermediate exchange regime ( µs – ms time scale ) , we collected 1H-13C HMQC spectra of unliganded GCK at variable temperatures . Across a range of temperatures ( 283–313 K ) compatible with retention of enzyme activity , no additional cross-peaks were observed that could be attributed to the five missing small domain isoleucine side chains ( Figure S5 ) . We tested whether the five missing isoleucine cross-peaks might reside in the intrinsically disordered side chain region of the 1H-13C HMQC spectrum , underneath the sharp , intense peaks of I159 and I163 , by constructing a variant in which I159 and I163 were replaced with leucines . These substitutions had a minimal impact upon the kinetic properties of the enzyme ( Table S1 ) ; however , the removal of I159 and I163 did not eliminate all peak intensity in the region of the spectrum where disordered side chains are expected . Therefore , residual intensity observed in the I159L–I163L double variant could stem from some of the remaining isoleucine side chains in the small domain ( Figure S6 ) . Together these results show that the majority of the isoleucines of the small domain are subject to conformational exchange with an exchange rate kex that fulfills the NMR coalescence condition kex≈2 . 2Δv , where Δv is the chemical shift change between conformational substates of unliganded GCK . At least two isoleucines , I159 and I163 , remain fully disordered in the unliganded form of GCK . Upon addition of glucose , the intensity of the intrinsically disordered region of the 1H-13C HMQC spectrum decreases and new cross-peaks originating from I110 , I126 , I130 , I189 , and I211 become clearly visible ( blue peaks in Figure 1E ) . In contrast , residues in the large domain are much less affected by glucose binding ( gray peaks ) . In the presence of glucose , the cross-peaks of I159 and I163 dramatically increase their line widths and shift to new positions ( Figures 1E and S2 ) , reflecting the formation of the 151–179 β-hairpin , a well-defined structural element in the crystal structure 1V4S [28] . In the 1H-15N HSQC spectrum of the 15N-tryptophan-labeled GCK–glucose complex , three well-resolved cross-peaks corresponding to W99 , W167 , and W257 are observed ( Figure 2G ) , consistent with the glucose-induced structural organization observed in the 1H-13C HMQC spectra of 13CH3-Ile labeled enzyme . Addition of the ATP analogue AMP–PNP to the binary complex perturbs the spectrum only slightly , indicating that AMP–PNP weakly impacts the structure and dynamics of the binary complex ( Figure 1F ) . Although PHHI is usually associated with single amino acid replacements , we employed our previously identified hyperactive quadruple variant to fully characterize the structural and functional impacts of activating mutations [44] . This hyperactive variant contains a redesigned α13-helix with sequence ALIAAAV . Similar to other activating PHHI-linked variants , the α13-helix variant displays a decreased glucose K0 . 5 value , a reduced level of cooperativity , and an increased equilibrium affinity for glucose compared to wild-type GCK [44] . Specifically , the glucose KD value of the α13-helix variant is 50 µM , a value similar to glucose Km values of the noncooperative GCK isozymes , hexokinases I–III . In contrast to wild-type GCK , the 1H-13C HMQC of the unliganded α13-helix variant displays cross-peaks originating from Ile residues in both the small and large domains ( Figure 2E ) . Under saturating glucose conditions , the α13-helix variant exhibits a spectrum that closely resembles the wild-type glucose-bound spectrum ( Figure S7 ) . These spectral characteristics are not specific to the hyperactive α13 variant , as similar effects were observed with the single-site activating variant , S64P ( Figure S8B ) . In general , the 1H-13C HMQC spectra of activated variants reveal varying degrees of structural stabilization relative to the wild-type enzyme . We observed a correlation between increases in glucose affinity caused by individual activating GCK variants , a systematic sharpening of cross-peaks , and the appearance of a larger number of resolved cross-peaks in the 1H-13C HMQC spectra in their unliganded state ( Figure S8 ) . These data demonstrate that activating PHHI-associated substitutions alter enzyme dynamics and promote a conformational ensemble that more closely resembles the glucose-bound state . Binding of the allosteric activator , which reduces the glucose K0 . 5 value and eliminates cooperativity , induces changes in the 2D 1H-13C HMQC spectrum similar to that produced by activating variants ( Figure 2 ) . Well-dispersed cross-peaks originating from Ile residues in both the large and small domain are observed in the presence of the activator . The only differences between the NMR spectra of glucose-bound GCK in the absence and presence of the activator arise from residues near the activator binding site , such as I211 ( Figure S9 ) , suggesting local perturbations only . From these data , we conclude that allosteric activators stabilize the small domain and alter GCK dynamics . Our results also demonstrate that small-molecule-mediated GCK activation does not require prior formation of the binary GCK–glucose complex , a finding that could have important therapeutic implications . The 151–179 loop is disordered in unliganded wild-type GCK , as evidenced by the fact that the chemical shifts and peak intensities of I159 , I163 , and W167 fall within the disordered side chain region ( Figure S4 ) . This loop becomes structured in the unliganded α13-helix variant as shown by the 2D 1H-15N HSQC and 2D 1H-13C HMQC spectra in Figure 2E and H . Notably , the chemical shift of W167 in the unliganded α13-helix variant is identical to that observed in the wild-type GCK-glucose complex ( Figure 2G and H ) , indicating that the loop conformation adopted by the variant is similar to that produced upon glucose binding . The crystal structure reveals a possible mode of communication between the activator , the α13-helix , and the 151–179 loop ( Figure 2A ) [28] . One face of the activator binding site is comprised of the α13-helix residues V452 , V455 , and A456 , and two of these residues , V452 and A456 , interact with the loop residue I159 . In the presence of the activator , or when an activating substitution is introduced into the α13-helix , the interactions between I159 , V452 , and A456 are stabilized . In turn , this stabilization is relayed to the glucose binding site via two additional loop residues , T168 and K169 , which form hydrogen bonds with the O1 and O6 atoms of bound glucose . Structural organization of either the α13-helix or the 151–179 loop can be achieved by glucose binding , activator association , or a hyperactive substitution . PHHI variants or the allosteric activator promote a population shift toward a more structured state , which involves a major reorganization of the small domain . This effect , which is evidenced by increased spectral dispersion and loss of line broadening compared to the unliganded wild-type enzyme , abrogates kinetic cooperativity . The differential glucose binding affinities of wild-type GCK and the α13-helix variant ( KD = 5 mM and 50 µM , respectively ) suggest that a substantial thermodynamic barrier separates the closed GCK conformation from the unliganded state . In the wild-type enzyme , this barrier is overcome by glucose binding , which triggers the disorder–order transition . In an activated variant , or in the presence of a synthetic activator , the small domain is stabilized , which decreases the free energy penalty of the conformational change and allows glucose binding energy to manifest itself in the form of a lower KD value . The differential glucose binding affinities of wild-type and activated GCK also suggest that the high-affinity conformation represents ≤1% of the total unliganded ensemble . The experimental data presented here provide direct evidence that the small domain of GCK is highly dynamic in the absence of ligand . Some evidence of GCK structural plasticity has emerged from X-ray structures determined in the presence and absence of various ligands; however , since crystal structures represent high-resolution snapshots of protein states , they neither reveal time-scale information nor how different states are dynamically related to each other . Optical spectroscopy , on the other hand , provides time-scale information at single sites without reporting on local structure . Indeed , the application of transient state fluorescence spectroscopy to GCK revealed the existence of glucose-induced structural rearrangements that span multiple time scales , but these studies failed to provide a unified , structure-based mechanism of GCK cooperativity [45]–[48] . Here we used all native Ile and Trp side chains to probe the structural-dynamic behavior of GCK at 20 different sites distributed throughout the protein . These data , obtained in solution under physiological conditions in the absence and presence of glucose and activator , provide temporal information for wild-type GCK and its variants with high spatial resolution . Based on this new type of information , we propose a refined model for allostery in monomeric GCK . The model that emerges from our data demonstrates that GCK cooperativity may result from dynamic structural modulations of the intrinsically disordered small domain . In the absence of ligand , the enzyme exists as an ensemble of conformations , which interconvert on a millisecond time scale that coincides with enzyme turnover ( kcat∼60 s−1 ) ( Figure 3 ) . Upon glucose association the small domain becomes ordered , as reflected in the sharpening of the NMR resonances and the increase of chemical shift dispersion of Ile residues . After formation of the GCK–glucose binary complex , ATP binds and catalysis proceeds with little additional reorganization . Following product release , ordered unliganded GCK persists until , on the millisecond time scale , the small domain undergoes an order–disorder transition , allowing access to a “time delay loop . ” Under low glucose concentrations , the delay loop is operational , leading to slow turnover and kinetic cooperativity ( Figure 3 , red ) . Under high glucose concentrations , or when GCK is activated , the delay loop is effectively bypassed , turnover is fast , and cooperativity is eliminated ( Figure 3 , green ) . The putative involvement of slow conformational changes in the generation of kinetic cooperativity in enzymes has long been appreciated [49] . In the case of GCK , the generation of a sigmoidal steady-state response , which is key to this enzyme's sensitivity to oscillating physiological glucose levels , requires a time delay slower than 1/kcat . The absence of resonances from Ile residues located in the small domain prevents quantitative analysis of the underlying rate constants associated with the disorder–order transition . However , typical Ile and Trp side-chain chemical shift ranges point to a rate constant kex between 5 s−1 and 100 s−1 in order to explain the disappearance of the cross-peaks from the small domain by coalescence . This disorder–order transition rate satisfies the conditions needed to account for the existence of kinetic cooperativity in GCK [26] , [27] . Protein structural organization occurring in the millisecond time regime is not uncommon [50] , and here this phenomenon appears to contribute to the generation of GCK cooperativity . As with other intrinsically disordered proteins [51] , [52] , it is possible that the dynamic nature of the small domain also plays a role for the emergence of new functional attributes , including regulation of GCK activity by multiple interacting partners [53]–[55] and posttranslational events [56] , [57] .
Recombinant human pancreatic GCK was produced as an N-terminal hexa-histidine-tagged polypeptide in Escherichia coli strain BL21 ( DE3 ) . Bacterial cultures were inoculated to an initial OD600 nm of 0 . 06 and were grown at 37°C in minimal medium supplemented with ampicillin ( 150 µg/mL ) , thiamine hydrochloride ( 25 µg/mL ) , 15NH4Cl ( 1 g/L ) , Ca ( OH ) 2 ( 0 . 1 mM ) , MgSO4 ( 1 mM ) , and glycerol ( 1% ) ( w/v ) . When the OD600 nm reached 0 . 85 , IPTG ( 1 mM ) was added to induce gene expression and growth was continued for 12 h . The specific incorporation of 15N and 13C labels in the Trp and Ile residues , respectively , was achieved following the protocols by Muchmore et al . [41] and Tugarinov et al . [39] . Cells were harvested by centrifugation at 8 , 000 g , and 5 g of wet cell pellet was resuspended in 17 mL of buffer A containing HEPES ( 50 mM , pH 7 . 6 ) , KCl ( 50 mM ) , imidazole ( 40 mM ) , dithiothreitol ( 10 mM ) , and glycerol ( 25% w/v ) . Cells were lysed using a French Press and subjected to centrifugation at 25 , 000 g at 4°C for 1 h . The supernatant was immediately loaded onto a 5 ml HisTrap Fast Flow Affinity Column ( GE Healthcare ) previously equilibrated in buffer A . Following loading , the column was washed with 10 column volumes of buffer A followed by 5 columns of buffer A containing 65 mM imidazole . GCK was eluted with buffer A containing 250 mM imidazole , and the enzyme was dialyzed at 4°C against 1L of potassium phosphate buffer ( 25 mM , pH 8 ) , containing KCl ( 25 mM ) and dithiothreitol ( 10 mM ) . GCK was then concentrated to ∼600 µM using an Amicon centrifugal concentrator ( MWCO = 10 , 000 ) . Protein was injected onto a Superdex 200 16/60 gel filtration column ( Amersham-Pharmacia ) pre-equilibrated with potassium phosphate buffer ( 25 mM , pH 8 . 0 ) , containing KCl ( 25 mM ) and DTT ( 10 mM ) . The gel filtration column was run at a flow rate of 0 . 12 mL/min , and fractions that contained the highest A280 nm readings were pooled and used immediately in the NMR experiments . Site-directed mutagenesis was performed using the QuikChange protocol ( Stratagene ) . Mutagenesis reactions contained human glk template DNA ( 400 ng ) , Pfu Turbo enzyme ( 2 . 5 units ) , cloned Pfu Turbo reaction buffer ( 1× ) , and mutagenic primers ( 125 ng ) . GCK activity was measured spectrophotometrically at 340 nm by coupling the production of ADP to the oxidation of NADH via the combined action of pyruvate kinase and lactate dehydrogenase . Assays were conducted at 25°C in reaction mixtures containing HEPES ( 250 mM , pH 7 . 6 ) , KCl ( 50 mM ) , NADH ( 0 . 25 mM ) , dithiothreitol ( 10 mM ) , pyruvate kinase ( 15 units ) , lactate dehydrogenase ( 15 units ) , ATP ( 0 . 1–50 mM ) , MgCl2 ( 1 . 1–51 mM ) , and glucose ( 0 . 05–100 mM ) . Data were fitted to the Hill equation or the Michaelis-Menten equation depending on the substrate under investigation . Assays were initiated by the addition of ATP and were conducted in duplicate for each substrate concentration . The kinetic constants reported are the average of data obtained from at least two independent preparations of enzyme . Assays were conducted before and after NMR measurements to verify retention of enzyme activity during the time course of the experiment . All NMR data were collected with a Bruker Avance III spectrometer operating at 800 MHz proton field and equipped with a TCI cryogenic probe . The GCK NMR samples were prepared in potassium phosphate buffer ( 25 mM , pH 8 . 0 ) , containing KCl ( 25 mM ) , DTT ( 10 mM ) , deuterated glycerol ( 5% v/v ) , and D2O ( 10% v/v ) . For all experiments of glucose-bound GCK , glucose was added to a total concentration of 200 mM . 1H-13C HMQC experiments were recorded as matrices of 2048×390 ( in Figure 1 ) or 2048×256 ( in Figure 2 ) complex data points . Unless otherwise stated , 1H-15N HSQC experiments were recorded as matrices of 2048×128 complex data points . All spectra were apodized with a cosine function in each dimension prior to zero-filling . NMR data processing and spectral analyses were performed with NMRPipe [58] and the CCPN-Analysis software [59] . As a control , the enzymatic activity of GCK was measured before and after each NMR experiment . Site-specific assignments of Ile and Trp resonances were mainly achieved by single-site substitution with Val/Leu and Phe , respectively , followed by the recording of 2D 1H-13C HMQC and 1H-15N HSQC spectra to identify missing cross-peaks ( Figure S7 ) . Assignments of Ile residues in the α13-helix variant could be directly transferred from their wild-type assignments due to identical peak positions , except for I159 and I163 , which were assigned by site-directed mutagenesis . Ile residues in the GCK–activator complex were assigned based on identical cross-peak positions with respect to the wild-type spectrum . Assignments for W99 , W167 , and W257 in wild-type GCK and for W167 in the α13-helix variant were performed by individually replacing Trp by Phe . | Glucokinase is a key metabolic enzyme that functions as the body's principal glucose sensor . Glucokinase regulates the rate at which insulin is secreted by the pancreas by using a unique but poorly understood cooperative kinetic response to increasing glucose concentrations . The physiological importance of this enzyme is underlined by the fact that mutations in the glucokinase gene lead to maturity-onset diabetes of the young type II ( MODY II ) , permanent neonatal diabetes mellitus ( PNDM ) , and hypoglycemic hyperinsulinemia of infancy ( HI ) . In this study , we use cutting-edge high-resolution nuclear magnetic resonance methods to understand how the kinetic properties of glucokinase contribute to glucose homeostasis . We also seek to understand how a class of recently discovered small-molecule drugs , which hold promise as therapeutics for type 2 diabetes , function to enhance glucokinase activity . Our results suggest that glucokinase samples a range of conformational states in the absence of glucose . However , in the presence of glucose or a small-molecule activator , the enzyme population shifts towards a more narrow , well-structured ensemble of states . Our findings provide a new model for glucokinase cooperative kinetics , which relies on a slow order–disorder transition in response to glucose concentrations . These results also reveal a universal mechanism of glucokinase activation , which may inform the development of new antidiabetic agents . | [
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"biochemistry",
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] | 2012 | Order–Disorder Transitions Govern Kinetic Cooperativity and Allostery of Monomeric Human Glucokinase |
Chronic immune activation and inflammation ( e . g . , as manifest by production of type I interferons ) are major determinants of disease progression in primate lentivirus infections . To investigate the impact of such activation on intrathymic T-cell production , we studied infection of the human thymus implants of SCID-hu Thy/Liv mice with X4 and R5 HIV . X4 HIV was observed to infect CD3−CD4+CD8−CXCR4+CCR5− intrathymic T-cell progenitors ( ITTP ) and to abrogate thymopoiesis . R5 HIV , by contrast , first established a nonpathogenic infection of thymic macrophages and then , after many weeks , began to replicate in ITTP . We demonstrate here that the tropism of R5 HIV is expanded and pathogenicity enhanced by upregulation of CCR5 on these key T-cell progenitors . Such CCR5 induction was mediated by interferon-α ( IFN-α ) in both thymic organ cultures and in SCID-hu mice , and antibody neutralization of IFN-α in R5 HIV-infected SCID-hu mice inhibited both CCR5 upregulation and infection of the T-cell progenitors . These observations suggest a mechanism by which IFN-α production may paradoxically expand the tropism of R5 HIV and , in so doing , accelerate disease progression .
HIV disease progression is marked by chronic immune activation associated with accelerated destruction of T cells in the periphery and diminished production of new T cells from progenitors in the thymus and elsewhere [1] , [2] . Although the detection of X4 HIV as the predominant viral species in peripheral blood is clearly associated with a higher risk of disease progression , about half of patients progress to AIDS in the presence of R5 viruses alone [3] , [4] or with only the transient appearance of X4 virus [5] . Since it is just a small fraction of CD4+ target cells that express the CCR5 coreceptor [6] , the mechanisms underlying such intrinsic R5 virus pathogenicity remain unclear . Given the association between high levels of T-cell activation and more rapid disease progression in untreated HIV-infected individuals [7] , however , it is possible that such activation might induce the upregulation of CCR5 and expand the tropism of R5 HIV to include essential T-cell progenitors that are normally spared . To address the hypothesis that R5 HIV infection might lead to such an indirect expansion of tropism in vivo , we investigated the course of R5 HIV infection in the SCID-hu Thy/Liv mouse model of human T-cell production . This small animal model , in which severe combined immunodeficient ( C . B-17 SCID ) mice are implanted with human fetal thymus and liver under the kidney capsule , supports multilineage human hematopoiesis , including T lymphopoiesis , for periods up to one year [8] and represents a venue in which to study the effects of HIV on human thymopoiesis in vivo . After inoculation with X4 HIV , a key population of ITTPs ( CD3−CD4+CD8−CXCR4+CCR5− ) is rapidly infected and destroyed , impeding thymocyte maturation and depleting the implants of thymocytes within 4–5 weeks [9] , [10] . In contrast , rapid destruction of the thymic organ is not observed after infection with the R5 isolate Ba-L , which follows a biphasic process involving nonpathogenic replication in medullary stromal macrophages followed by cytopathic replication in thymocytes after 6 weeks of infection [11] . CCR5 is expressed at much lower levels than CXCR4 ( <5% versus 30–40% of thymocytes ) at all stages of T-cell development in the thymus [6] , [12] , [13] , and this may explain the decreased pathogenicity of R5 HIV in that organ . We demonstrate here that R5 HIV causes eventual depletion of thymocytes that is associated with de novo IFN-α-mediated upregulation of CCR5 on ITTP , rendering these key progenitor cells permissive for R5 HIV infection and depletion . Moreover , we show that monoclonal antibody ( MAb ) neutralization of IFN-α in SCID-hu Thy/Liv mice inhibits CCR5 induction after HIV infection and prevents infection of ITTP with R5 HIV . The observation that IFN-α may be a driving force behind expanded HIV tropism in vivo offers a proximal mechanism for the relationship between immune activation and disease progression and suggests that immunomodulatory agents that suppress the production or the effects of IFN-α may serve to slow disease progression in the HIV-infected host .
The human thymus implants of SCID-hu Thy/Liv mice were inoculated with the X4 HIV clone NL4-3 , the R5 HIV isolate Ba-L , or a chimeric R5 clone of NL4-3 containing the V1-V3 env regions of Ba-L ( 81A ) and monitored for viral replication and thymocyte depletion at 21 and 42 days . As expected from our previous work in the Thy/Liv model [11] , [14] , [15] , [16] , viral replication resulted in time-dependent increases in implant HIV RNA , p24 , Gag-p24+ thymocytes , and MHC class I expression on CD3intCD4+CD8+ ( double-positive , DP ) thymocytes ( Figure 1A ) . Viral replication was accompanied by time-dependent decreases in implant cellularity , thymocyte viability , percentage of DP thymocytes , and CD4/CD8 ratio ( Figure 1B ) that were more rapid and of greater magnitude for X4 than for R5 HIV , a finding consistent with the far greater of expression of CXCR4 than CCR5 on human thymocyte subpopulations [6] . The slow but evident pathogenicity of R5 HIV may be dependent upon inductive events that take place after infection . For instance , progressive sequence variation in the env gene may enable a “switch” of envelope glycoproteins to a pathogenic X4 phenotype . Alternatively , R5 viral pathogenesis may proceed in a time-dependent manner through infection of ITTP , which constitute a minor but key thymocyte progenitor subpopulation , in a manner analogous to X4 thymic pathogenesis [10] . Since we have previously found that an R5-to-X4 phenotypic switch is not detectable during thymic infection with Ba-L [11] , we more closely evaluated the possibility that ITTP , which are normally CCR5-negative [6] , [12] , might be infected at some time point after virus inoculation . Intracellular Gag-p24 staining in concert with surface staining for CD3 , CD4 , and CD8 revealed that ITTP were infected by Ba-L and 81A at day 42 but not day 21 ( Figure 1C ) . This finding was unexpected because ITTP do not normally express CCR5 [6] and were thus not considered targets of R5 HIV infection , in marked contrast to the susceptibility of ITTP to X4 HIV infection as a consequence of high-level expression of CXCR4 [6] . Reasoning that CCR5 expression might be indirectly induced by HIV infection , we evaluated CCR5 expression on thymocyte subpopulations after HIV inoculation and found , at day 42 but not day 21 , statistically significant increases in the percentage of CCR5-expressing ITTP [to 6 . 4±1 . 5% ( P = 0 . 017 ) for Ba-L and to 3 . 2±0 . 2% for 81A ( P = 0 . 001 ) versus a mean of 1 . 3±0 . 2% for mock-infected implants] ( Figure 1D and E ) . Less dramatic , but still statistically significant increases in CCR5-positive CD3+CD4−CD8+ ( single-positive , SP8 ) thymocytes were also observed , as has been reported previously in NOD/SCID-hu BLT mice infected intravaginally with HIV and attributed to a heightened state of immune activation [17] . Significant increases in the percentage of CCR5+ ITTP were also observed in X4 NL4-3-infected implants ( Figure 1D ) . Treatment of SCID-hu Thy/Liv mice with 3TC ( lamivudine ) inhibited the induction of CCR5 on thymic progenitors and prevented Ba-L-mediated thymocyte depletion ( data not shown ) . These results indicate that induction of CCR5 in HIV-infected Thy/Liv implants occurs in a time-dependent manner that is dependent on active HIV ( R5 or X4 ) replication . Previous reports have demonstrated that CCR5 expression can be increased on several cell types after treatment with cytokines including IL-2 [18] , IL-4 [19] , IL-10 [20] , [21] , IL-15 [22] , TGF-β [23] , and IFN-γ [24] , and with HIV Tat [25] . When human thymic organ cultures were incubated with these and other cytokines , significant induction of CCR5 expression on human thymocytes was only observed after treatment with IFN-α ( Figure 2A ) . Analysis of CCR5 expression on thymocyte subpopulations demonstrated statistically significant upregulation on ITTP ( Figure 2B ) , the same key subpopulation found to upregulate CCR5 in the HIV infected thymic implant and which we have previously reported to express the IFN-α/β receptor [26] . This receptor is expressed at high levels on ITTP and at progressively lower levels on more mature thymocytes ( e . g . , DP , SP4 , and SP8 thymocytes ) [26] . The ability of IFN-α to induce expression of CCR5 is consistent with the presence of STAT-binding sites at nt −55 and −116 in the CCR5 promoter; mutation of the proximal STAT site nearly abolishes promoter activity [27] . To determine whether IFN-α can induce expression of CCR5 on ITTP in vivo , we treated groups of SCID-hu Thy/Liv mice in three separate cohorts ( A , B , and C ) with IFN-α2b ( Intron A or pegylated interferon alfa-2b ) by once-daily intraperitoneal ( i . p . ) injection for 6 or 13 days . Significant increases in the percentage of CCR5+ ITTP were observed at both time points , normalizing to pretreatment levels after discontinuation of IFN-α ( Figure 2B and C ) . Treatment with IFN-α for 13 days had no effect on the percentage and absolute number of ITTP or other more mature thymocyte subpopulations present in the implants ( data not shown ) , so it is unlikely that the increase in CCR5+ cells is the result of either IFN-α-mediated apoptosis of CCR5-negative ITTP or an increased rate of CCR5+ ITTP cell division . Of note , the percentage of CCR5+ ITTP in IFN-α-treated mice ( means in the three cohorts: 6–20% , range: 3–37% ) ( Figure 2B and C ) tended to be higher than that found in Ba-L-infected mice at day 42 ( mean: 6% , range: 0–12% ) ( Figure 1D and E ) , a difference that may be the result of virus-mediated depletion of infected CCR5+ progenitors . To examine more closely the relationship between CCR5+ induction on ITTP , thymic organ infection , and thymocyte depletion , we studied two additional SCID-hu Thy/Liv cohorts ( D and E ) inoculated with Ba-L plus two cohorts ( G and H ) inoculated with the R5 isolate , CC1/85 . Data for these cohorts were analyzed together with the data obtained from the Ba-L and 81A-infected mice shown in Figure 1 ( cohort F ) . Implant viral loads measured 42–49 days after inoculation were within 1 . 0 log10 across all six infected groups ( means of 4 . 4–5 . 4 log10 copies HIV RNA and 80–800 pg p24 per 106 cells ) ( Figure 3A ) . For the two additional SCID-hu cohorts inoculated with Ba-L ( D and E ) , implants collected at much later time points ( up to one year ) after inoculation showed progressively more severe thymocyte depletion , while mock-infected implants remained intact with ∼80% DP thymocytes ( Figure 3B ) . As we have reported previously [11] , such depletion became noticeable 6 weeks after inoculation with Ba-L; we accordingly focused on implants collected from the five infected cohorts at this time ( i . e . , days 42–49 ) ( Figure 3C ) . Although the decreases in implant cellularity , thymocyte viability , and percentage of DP thymocyte were often not statistically significant when individual experiments were compared ( likely the result of the small number of mock-infected mice ) , animals in the R5 HIV-infected cohorts showed a trend towards decreases in each of these parameters . Concomitantly , there were increases in the percentage of CCR5+ ITTP compared to mock-infected mice , and the percentages of CCR5+ ITTP were comparable to the percentages of ITTP that were Gag-p24+ ( Figure 3D ) . To better document the relationship between CCR5 expression on ITTP and thymocyte depletion , data for each individual implant were plotted to show the correlation between the percentage of CCR5+ ITTP and viral load ( Figure 4A ) as well as the percentage of CCR5+ ITTP and thymocyte depletion ( Figure 4B ) . Not only are the correlations highly significant for infected implants in statistical terms ( e . g . , P<0 . 0001 for CCR5+ ITTP versus both Gag-p24+ ITTP and thymocyte viability ) , but the proportion of CCR5+ ITTP corresponds closely to that of infected ITTP ( Figure 4A ) . In contrast , there was no correlation between CCR5+ ITTP and markers of thymocyte depletion for mock-infected implants ( Figure 4B ) . Accordingly , it is highly likely that induction of CCR5 expression on ITTP is a causal event precipitating thymocyte depletion after HIV infection . To show definitively that upregulation of CCR5 on ITTP was mediated by IFN-α we treated three cohorts ( I , J , and K ) of SCID-hu Thy/Liv mice with a broadly neutralizing mouse MAb against multiple human IFN-α subtypes . Mice were treated by three times weekly i . p . injection , beginning 2 days before Ba-L , 81A , or NL4-3 inoculation and continuing until implant collection . For mice infected with Ba-L , neutralization of IFN-α was found to result in a lower percentage of CCR5+ ITTP ( P<0 . 05 in cohort I and P<0 . 01 in cohort J ) , a lower percentage of Gag-p24+ total live thymocytes ( P<0 . 05 in both cohort I and J ) , and a lower percentage of Gag-p24+ ITTP ( P<0 . 01 in cohort I and J ) ( Figure 5 ) . In cohort K , we directly compared the effects of IFN-α neutralization on HIV 81A ( R5 ) and NL4-3 ( X4 ) infection . This experiment was carried out with the expectation that infection of ITTP would be inhibited after 81A , but not after NL4-3 , inoculation . We found that this was indeed the case: there was a 93% reduction ( P = 0 . 005 ) in Gag-p24+ ITTP after IFN-α-treatment in 81A-infected mice yet an insignificant 25% reduction ( P = 0 . 501 ) in Gag-p24+ ITTP in treated NL4-3-infected mice . This was accompanied by expected reductions in CCR5+ ITTP for both viruses ( 89% reduction for 81A; P = 0 . 004 and 67% reduction for NL4-3; P = 0 . 083 ) . Given our previous data showing that infection of ITTP leads to interruption of thymopoiesis [10] , these results indicate that IFN-α-induced upregulation of CCR5 on ITTP is likely to result in diminished production of T cells from the thymus .
R5 isolates of HIV have been associated with disease progression in HIV-infected individuals [28] . Likewise , as we have shown here , R5 HIV can be pathogenic in the SCID-hu Thy/Liv model of human thymopoiesis . Even though there is little CCR5 expression in the human thymus , R5 HIV was found to induce delayed but significant depletion of developing DP thymocytes and reduction in implant cellularity , and progression of R5 infection was found to correlate with the induction of CCR5 expression on early thymic progenitor cells . Such induction , in turn , is mediated by IFN-α both in vitro and in vivo . This finding is in contrast to a previous report showing that R5 HIV infection of thymic organ cultures induced CCR5 on CD4+ thymocytes through the production of IL-10 and TGF-β [29] . The ability of HIV to induce expression of its own coreceptor through the major antiviral cytokine , IFN-α likely evolved to dampen this antiviral defense mechanism , a counterbalancing act that has been likened to a détente through which virus and host achieve conditions for coexistence [30] . The above results indicate that expanded tropism of R5 HIV in the infected human thymus ( to ITTP and DP thymocytes ) is a secondary event that occurs after the induction of IFN-α production , most likely from plasmacytoid dendritic cells ( pDC ) . These cells function as part of the innate immune response by secreting large quantities of IFN-α after contact or infection with a wide range of viruses , including HIV [31] , [32] , [33] . IL-3Rα+ pDC reside in the medulla of the human thymus [34] , and we have previously shown that these cells produce IFN-α in response to HIV infection in both human thymic organ culture and in SCID-hu Thy/Liv mice [26] . Intrathymic pDC express both CXCR4 and CCR5 and are themselves targets for HIV replication [35] , although it is not known if infection of these cells plays a role in IFN-α secretion . In sum , interactions between R5 HIV and pDC might lead indirectly to upregulation of CCR5 on cells that are normally not permissive for R5 infection . If so , these data point to a critical role for pDC-mediated IFN-α secretion in R5 HIV pathogenesis in the thymus of the SCID-hu mouse . There is a low frequency of CCR5+ pDC in the CD3−CD4+CD8− thymocyte population ( unpublished observations ) , but we believe our results are due to upregulation of CCR5 on the T-lineage component of this population for the following reasons: First , in vitro IFN-α treatment results in upregulation of CCR5 on ITTP and DP ( Figure 2A ) , cell populations that are T-lineage and that express high levels of the IFN-α/β receptor [26] . In vivo , the same phenomenon occurs ( Figure 2B ) . Second , The fraction of CCR5+ ITTP is similar to the fraction of p24+ ITTP ( Figure 3D ) , and there is a significant relationship between the two when analyzed in a large number of animals ( Figure 4A ) . Finally , neutralizing anti-IFN-α antibody blocks the upregulation of CCR5 on the ITTP population ( Figure 5 ) . All of these data ( especially the data in Figure 5 ) are most consistent with IFN-α induction of CCR5 on the CD3−CD4+CD8−CCR5− ITTP and the CD3+CD4+CD8+CCR5− DP populations , both of which are permissive for infection and replication of HIV . These data also illustrate the importance of cell-cell interactions that can occur in lymphoid tissue after HIV infection with profound influence on the course of disease progression and that are not easily replicated in dispersed cell cultures . In addition , available in vitro culture systems do not persist for the periods of time required to measure the impact of these interactions on HIV pathogenesis . The observations in this study thus underscore the need for a closer evaluation of the dynamics of HIV infection within lymphoid organs and provide experimental justification for such tissue analysis within HIV-infected human subjects . The finding that IFN-α can enhance HIV infectivity is surprising , especially given the potent antiviral activity against HIV we and others have reported in IFN-α-treated thymic organ cultures [26] , [36] . These counterposing effects of IFN-α may occur simultaneously in pDC-containing tissue , thereby contributing to the slow progression of thymocyte depletion usually seen after R5 infection . Persistently high levels of IFN-α and of IFN-inducible genes are associated with more rapid disease progression in SIV-infected macaques [37] , [38] , [39] . In contrast , nonpathogenic SIV infections are associated with transient IFN-α responses , possibly due to the inability of the virus to activate pDC [40] . There is likely a complicated set of kinetics at play during HIV infection of the Thy/Liv implant in vivo , including but not limited to: the rate of viral replication and spread; the rate of induction of IFN-α in pDC; the rate of upregulation of CCR5 on thymocytes that express the IFN-α/β receptor; the rate at which these cells are infected and destroyed by R5 HIV; the rate at which they are replenished from earlier , CCR5− progenitors; and , not least , the rate at which more mature DP thymocytes are depleted . We presume that the late events observed after HIV infection represent a sum total of these and other counterposing rates , resulting eventually in complete depletion of double-positive thymocytes ( e . g . , by day 300 in Figure 3B ) . IFN-α has been shown to inhibit thymic T-cell differentiation in both the mouse [41] and human [42] . IFN-α-mediated inhibition of T-cell development may have also contributed to the depletion of thymocyte subsets observed in this study; however , we found that treatment of the mice with IFN-α for 13 days had no effect on the percentage and absolute number of ITTP or other more mature thymocyte subpopulations present in the Thy/Liv implants . It is possible that more prolonged exposure of the implants to IFN-α over months of HIV infection may have more deleterious cumulative effects on T-cell maturation than relatively short-term IFN-α treatment . The role of chemokine coreceptor utilization in HIV disease progression has been studied extensively . The switch of viral phenotype from R5 to X4 has a profound and negative effect on absolute CD4 cell counts [43] and has been implicated as a determining factor in accelerated disease progression [5] . However , it appears that R5 HIV [28] and SIV [44] have the capacity to be pathogenic in their own right . HIV can also evolve in vivo with increased affinity for CCR5 , thus acquiring the ability to infect cells expressing low levels of the coreceptor and potentially increasing pathogenicity [45] , [46] . We present evidence here that CCR5 induction resulting from IFN-α secretion by pDC plays a significant role in the pathogenesis of R5 HIV in the human thymus implant of the SCID-hu Thy/Liv mouse . Given the close structural and functional similarities between this model and the intact human thymus [8] as well as prior evidence that HIV can infect the thymus in humans [47] , [48] , [49] , [50] , [51] , it is likely that these observations are relevant not only to the HIV-infected child with abundant thymic tissue but also to the HIV-infected adult , in whom residual thymic function can continue to play a role in the de novo production of naïve T cells [1] . Since pDC are resident throughout the lymphoid system and migrate to inflamed lymph nodes [52] , the expansion of R5 HIV tropism described here in the human thymus may also occur in other organs of the hematolymphoid system . Indeed , recent data indicate that IFN-α treatment causes significant increases in CCR5 mRNA expression in PBMC cultures from both HIV-infected and uninfected individuals [53] , [54] , and IFN-α treatment of patients with uveitis resulted in increases of CCR5 expression on peripheral blood CD4+ T cells [55] . Even if these events are restricted to thymic pDC , residual thymic function that persists in some adults with HIV disease [1] might thereby be abrogated . Alone or together , such interactions between HIV , pDC , and normally CCR5-negative target cells might underlie disease progression induced by R5 viruses in vivo .
The following reagents were obtained through the AIDS Research and Reference Reagent Program , Division of AIDS , NIAID , NIH: pNL4-3 [56] from Dr . Malcolm Martin , HIV-1Ba-L [57] from Dr . Suzanne Gartner , Dr . Mikulas Popovic and Dr . Robert Gallo , and p81A-4 [58] ( Cat#11440 ) from Dr . Bruce Chesebro . CC1/85 [59] was generously provided by Drs . Shawn Kuhmann and John Moore . Ba-L is a low-passage isolate that has been propagated exclusively in human monocyte/macrophages [57] , and CC1/85 is a well-characterized patient isolate that has also been minimally lab adapted [59] , [60] . Working stocks of NL4-3 and 81A were prepared by lipofectamine ( Invitrogen ) transfection of 293T cells and collection of supernatants on day 2 . Ba-L stock was generated in monocyte-derived macrophages with the supernatant collected on day 8 , and CC1/85 stock was generated in phytohemagglutinin ( PHA ) -activated peripheral blood mononuclear cells ( PBMC ) with the supernatants collected on day 4 . Virus stocks were titrated by limiting dilution for 50% tissue culture infectious doses ( TCID50 ) in PHA-activated PBMC with p24 detection by ELISA on day 7 as previously described [61] . Human fetal thymus and liver were obtained through services provided by a nonprofit organization ( Advanced Bioscience Resources ) in accordance with federal , state , and local regulations . Coimplantation of thymus and liver pieces under the kidney capsule to generate SCID-hu Thy/Liv mice and inoculation of the Thy/Liv implants with HIV was performed as described [14] , [62] . Male C . B-17 SCID ( model #CB17SC-M , homozygous , C . B-Igh-1b/IcrTac-Prkdcscid ) mice were obtained at 6–8 weeks of age from Taconic , and cohorts of 50–60 SCID-hu Thy/Liv mice were implanted with tissues from a single donor . Implanted mice were maintained in a barrier facility under pathogen-free conditions and inoculated 18 weeks after implantation with 50 µl of stock virus ( 1 , 000 TCID50 ) or conditioned medium from PBMC cultures ( mock infection ) by direct injection into the implant . All procedures with mice were approved by the UCSF Institutional Animal Care and Use Committee . The Thy/Liv implants were collected from euthanized mice at the indicated time points , placed into sterile PBS-FBS , and dispersed through nylon mesh into a single cell suspension . Cells were counted and processed for p24 ELISA , branched DNA assay , and flow cytometry as previously described [14] , [15] . Dispersed implant cells were stained with MAbs against CD3 , CD4 , CD8 , MHC class I , CCR5 , and intracellular Gag-p24 . Pellets containing 106 cells were resuspended in 50 µl of a MAb mixture containing phycoerythrin cyanine dye CY7-conjugated anti-CD4 ( BD Biosciences ) , phycoerythrin cyanine dye CY5 . 5-conjugated anti-CD8 ( Caltag Laboratories ) , allophycocyanin cyanine dye CY7-conjugated anti-CD3 ( eBiosciences ) , allophycocyanin-conjugated anti-CD195 ( CCR5 , clone 2D7 ) ( BD Biosciences ) , and phycoerythrin-conjugated anti-W6/32 ( DakoCytomation ) in PBS containing 0 . 8 mg/ml human IgG ( Biodesign International ) . Cells from one implant were also stained with conjugated , isotype-matched antibodies to control for nonspecific antibody binding . Cells were incubated for 30 min in the dark and washed two times with PBS/2% FBS . Cells were resuspended in 200 µl of a fixation/permeabilization mixture containing 1 . 25% human IgG ( Biodesign International ) , 1 . 2% paraformaldehyde ( Sigma ) , and 0 . 5% polyoxyethylenesorbitan ( Tween 20 , Sigma ) in PBS/2% FBS . Cells were incubated for 60 min in the dark , washed two times with PBS/2% FBS , and then resuspended in 50 µl of PBS containing fluorescein isothiocyanate-conjugated anti-p24 ( Beckman Coulter ) and 0 . 8 mg/ml human IgG ( Biodesign International ) . In addition , a “fluorescence minus one” ( FMO ) control was prepared in which the anti-p24-FITC was omitted from the antibody mixture to allow for discrimination of Gag-p24+ from Gag-p24− cells . Cells were incubated for 30 min in the dark , washed twice with PBS/2% FBS , resuspended in 200 µl of PBS/2% FBS in 1 . 5-ml tubes , and analyzed on an LSR II ( BD Biosciences ) with FlowJo software ( Tree Star ) . Optimization of fluorescence compensation for correction of fluorescence spectral overlaps emitted from the fluorescent conjugated antibodies was achieved by staining cells with each antibody alone plus anti-mouse Ig kappa chain and negative control BD CompBeads ( BD Biosciences ) , as directed by the manufacturer . After collecting 100 , 000 total cell events , percentages of marker-positive ( CD4+ , CD8+ , and DP ) thymocytes in the implant samples were determined by first gating on a live lymphoid cell population identified by forward- and side-scatter characteristics and then by CD3 expression . In addition , the fraction of cells positive for Gag-p24 and CCR5 was determined for all thymocyte subpopulations in each implant ( Figure S1 ) . W6/32-positive mean fluorescence intensity ( MFI ) of DP thymocytes was determined for each sample , and CD4/CD8 ratios were calculated by dividing the percentage of CD4+ cells by the percentage of CD8+ cells for each individual implant . SCID-hu Thy/Liv mice from three cohorts ( A , B , and C ) were treated with 106 IU recombinant interferon alfa-2b ( Schering ) , 10 µg pegylated interferon alfa-2b ( Schering ) , or sterile water by once-daily i . p . injection for 6 or 13 days . Implants were collected and stained for flow cytometry either 1 or 7 days after the last IFN-α injection . SCID-hu Thy/Liv mice from three cohorts ( I , J , and K ) were treated with a mouse MAb with broadly neutralizing activity against multiple human IFN-αs ( clone 9F3 . 18 . 5 [63] , 500 µg every other day by i . p . injection ) kindly provided by Drs . Andrew C . Chan and Kerstin Schmidt ( Genentech ) beginning 2 days before implant injection with Ba-L or 81A . The 9F3 MAb does not neutralize IFN-β [63] . Fetal thymus was dissected into small pieces and plated on sterile filters ( Millipore ) placed on gelatin sponges ( Pharmacia and Upjohn ) in 700 µl Yssel's medium containing 1% human serum ( Gemini Bio-Products ) in 24-well plates . Cultures were incubated in the presence of various cytokines or HIV Tat at concentrations shown previously to induce CCR5 upregulation , e . g . , at 10 ng/ml for IL-10 [21] , IL-15 [22] , HIV Tat [25] , and TGF-β [23]; 20 ng/ml for IL-4 [19] and IFN-γ [24]; and 20 IU/ml for IL-2 [18] . In the case of IFN-α , a dose of 1 , 000 IU/ml was selected on the basis of dose-ranging experiments , although CCR5 upregulation was observed at lower ( 300 IU/ml ) IFN-α concentrations ( data not shown ) . Cytokine-treated thymus cultures were dispersed after 3 days , and cells were stained with MAbs to CD3 , CD4 , CD8 , and CCR5 for flow cytometry as described above . Results are expressed as means±SEM . Nonparametric statistical analysis was performed by use of the Mann-Whitney U test ( StatView 5 . 0 , Abacus Concepts ) , and correlation P values were generated by the correlation Z test ( StatView ) . | Human immunodeficiency virus ( HIV ) , a lentivirus , is the causative agent of AIDS . Chronic immune activation and inflammation are major determinants of disease progression in primate lentivirus infections and are associated with the production of type I interferon . To investigate the impact of type I interferon on HIV infection , we studied the human thymus implants of SCID-hu Thy/Liv mice infected with HIV that uses either CXCR4 ( X4 HIV ) or CCR5 ( R5 HIV ) as a coreceptor . X4 HIV was observed to infect T-cell progenitors in the thymus and to disrupt T-cell production by that organ . R5 HIV , by contrast , first established a nondisruptive infection of thymic macrophages and then began to infect intrathymic T-cell progenitors . We report here that the tropism of R5 HIV is expanded and T-cell disruption enhanced by increased expression of CCR5 on these key T-cell progenitors . Such CCR5 induction was mediated by interferon-α ( IFN-α ) in both thymic organ cultures and in SCID-hu mice . Moreover , antibody neutralization of IFN-α in R5 HIV-infected SCID-hu mice inhibited both CCR5 upregulation and infection of the T-cell progenitors . These observations suggest a mechanism by which IFN-α may paradoxically expand the tropism of R5 HIV and accelerate disease progression . | [
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"resistance"... | 2010 | IFN-α-Induced Upregulation of CCR5 Leads to Expanded HIV Tropism In Vivo |
Botulinum neurotoxin serotype A ( BoNT/A ) causes transient muscle paralysis by entering motor nerve terminals ( MNTs ) where it cleaves the SNARE protein Synaptosomal-associated protein 25 ( SNAP25206 ) to yield SNAP25197 . Cleavage of SNAP25 results in blockage of synaptic vesicle fusion and inhibition of the release of acetylcholine . The specific uptake of BoNT/A into pre-synaptic nerve terminals is a tightly controlled multistep process , involving a combination of high and low affinity receptors . Interestingly , the C-terminal binding domain region of BoNT/A , HC/A , is homologous to fibroblast growth factors ( FGFs ) , making it a possible ligand for Fibroblast Growth Factor Receptors ( FGFRs ) . Here we present data supporting the identification of Fibroblast Growth Factor Receptor 3 ( FGFR3 ) as a high affinity receptor for BoNT/A in neuronal cells . HC/A binds with high affinity to the two extra-cellular loops of FGFR3 and acts similar to an agonist ligand for FGFR3 , resulting in phosphorylation of the receptor . Native ligands for FGFR3; FGF1 , FGF2 , and FGF9 compete for binding to FGFR3 and block BoNT/A cellular uptake . These findings show that FGFR3 plays a pivotal role in the specific uptake of BoNT/A across the cell membrane being part of a larger receptor complex involving ganglioside- and protein-protein interactions .
Botulinum neurotoxin serotype A ( BoNT/A ) is produced by Clostridium botulinum and is a member of the Clostridial neurotoxin family that includes BoNT/A-G and Tetanus neurotoxin ( TeNT ) . BoNT/A causes transient muscle paralysis by entering motor nerve terminals ( MNTs ) where it cleaves nine amino acids from the C-terminus of the soluble N-ethylmaleimide-sensitive factor attachment receptor ( SNARE ) protein SNAP25 ( SNAP25206 ) to yield SNAP25197 [1] . Intact SNAP25 is required for neurotransmitter release and cleavage of SNAP25 disrupts exocytosis , which blocks neurotransmitter release [2]–[5] . BoNT/A has become a useful pharmacological and biological tool . Because of its high potency and specificity for pre-synaptic nerve terminals , BoNT/A at picomolar concentrations , is used to treat a wide range of neuromuscular disorders [6]–[8] , pain disorders including migraine [9] , and excessive sweating [10] . The key to the exceptional specificity of BoNT/A is believed to be the mechanism of uptake across the presynaptic membrane of neurons that involves a combination of low and high affinity interactions known as the double receptor model [11]–[13] . The low affinity receptor for BoNT/A is the ganglioside GT1b with a binding pocket within the C-terminal portion of the receptor binding domain [12] , [14] , [15] . According to the APR receptor model [13] , an array of presynaptic receptors ( APRs ) , clustered in microdomains at the presynaptic membrane , are responsible for specific uptake of neurotoxins , including BoNT/A . It is the binding to high density ganglioside GT1b that mediates the initial binding step and via a low affinity interaction concentrates BoNT/A on the cell surface . GT1b has been shown to bind BoNT/A with a KD∼200 nM in vitro [16] . Once anchored in the membrane , lateral movements within the plasma membrane facilitate intermolecular interaction of BoNT/A with additional lower density but higher affinity protein receptors , including the three isoforms of Synaptic Vesicle ( SV ) glycoprotein 2 , SV2A ( ENSG00000159164 ) , B ( ENSG00000185518 ) and C ( ENSG00000122012 ) that are exposed on the outer plasma membrane after fusion of synaptic vesicles to the presynaptic membrane [17]–[22] . BoNT/A specifically recognizes the fourth luminal domain ( LD4 ) of SV2 [17] , [18] . The specific sequence in the BoNT/A binding domain that interacts with SV2 has not been identified [23] . Glycosylated SV2A , B , and C have also been identified as receptors for BoNT/F [22] , [24] and glycosylated SV2A and B have been identified as receptors for BoNT/E [20] . BoNT/D was reported to enter neurons via two ganglioside binding sites , one site at a position previously identified in BoNT/A , B , E , F , and G , and the other site resembling the second ganglioside-binding pocket of TeNT [25] . Recently , BoNT/D has also been shown to use SV2 ( all three isoforms ) to enter hippocampal neurons , but BoNT/D bound SV2 via a mechanism distinct from BoNT/A and E [26] . Surprisingly , SV2A and SV2B have also been reported to mediate binding and entry of TeNT into central neurons [27] . Analysis of the first crystallographic structure of BoNT/A revealed a ganglioside binding site with structural homology to that within TeNT [28] , [29] ( Figure 1A ) . A potential protein binding site was also identified with structural homology to basic fibroblast growth factor ( FGFb or FGF2; ENSG00000138685 ) , agglutinin , and the toxin abrin . The report of a potential FGF2 protein binding site within BoNT/A served as the basis for the identification of FGFR3 ( Fibroblast Growth Factor Receptor 3 , ENSG00000068078 ) as a receptor for BoNT/A . FGFR3 [30] , [31] is one of four receptor-tyrosine kinases ( FGFR1–4 ) that act as receptors for FGFs . FGFRs are composed of an extra-cellular ligand-binding domain consisting of three immunoglobulin-like loops ( L1–L3 ) , a transmembrane domain , and a split cytoplasmic tyrosine kinase domain . FGFRs are activated by dimerization induced by ligand binding that enables the cytoplasmic kinase domains to transphosphorylate one another at specific tyrosine residues [32]–[35] . FGFR1–3 , but not FGFR4 , exist in three different splice variants that differ in the C-terminal half of L3 and determine their individual ligand affinity and specificity . The splice variants are referred to as “a” , “b” , and “c” [36]–[39] . The “b” and “c” variants are expressed on the cell surface , while the “a” splice variant , which lacks the transmembrane domain [40] , becomes a secreted extra-cellular FGF-binding protein [41] . Among the 22 known FGFs , FGF1 ( ENSG00000113578 ) , members of the subfamilies FGF8 ( FGF8 , 17 , 18 ) and FGF9 ( FGF9; ENSG00000102678 , 16 , 20 ) have been shown to function as ligands for both FGFR3b and c but with different levels of affinity . FGF2 , and the subfamilies FGF4 ( FGF4 , 5 , 6 ) and FGF19 ( FGF19 , 21 , 23 ) have been shown to function as ligands for FGFR3c [39] , [42] . Moreover , FGFs bind their receptors in the presence of one or more low affinity co-factors including heparin sulfate ( HS ) , gangliosides , neuropilin-1 , Klotho , and anosmin that function to modulate receptor activity [43]–[48] . The studies presented in this manuscript identify FGFR3 expressed in motor neurons at MNTs as a functional protein receptor for BoNT/A . The C-terminal binding domain of BoNT/A , HC/A , binds to the second and third extra-cellular ligand binding domain of FGFR3 and results in the phosphorylation of FGFR3 . It is demonstrated that cellular uptake of BoNT/A is dependent on the level of FGFR3 expression . Native ligands for FGFR3; FGF1 , FGF2 , and FGF9 compete for binding to FGFR3 and block BoNT/A uptake in a cell-based assay . Moreover , peptides derived from the FGFR3 subtype b and c extra-cellular domain block BoNT/A uptake in neuronal cells . Both FGFR3 subtype b and c bind to rHC/A , but FGFR3b has the highest affinity with a KD∼15 nM in vitro . These data suggest that FGFR3 is a potential high affinity component of a receptor complex for BoNT/A on the presynaptic membrane .
Analysis of the BoNT/A crystal structure ( Figure 1A ) revealed that the HC/A subdomain has structural homology to basic fibroblast growth factor ( FGF ) [28] . To investigate the interaction of BoNT/A and FGFR , pull-down assays were performed with Neuro-2a and PC-12 cell lines that have been shown to take up BoNT/A with high efficacy after differentiation by serum starvation and trophic factors , and Nerve Growth Factor ( NGF ) for PC-12 cells [49] , [50] . Figure S1A shows a representative experiment of how differentiation increases BoNT/A uptake in PC-12 cells . BoNT/A uptake was determined by treatment of cells with BoNT/A , followed by incubation and Western blot analysis of the SNAP25197 cleavage product . After optimization of differentiation and treatment conditions , differentiated Neuro-2a and PC-12 cells were treated with BoNT/A and EC50 values of 60±5 pM and 47 . 1±13 pM , respectively were determined ( Figure S1B ) . A complex containing BoNT/A and its receptor was isolated using three alternative pull-down methods , the results from two of these methods are shown here . First , Sulfo-SBED BoNT/A was used in a biotin transfer experiment to pull down the receptor from intact Neuro-2a cells . Antibodies against FGFR3 detected a band of the correct molecular weight for FGFR3 as part of a 250 kDa complex with BoNT/A . Figure S1C , D , and E demonstrate that a 250 kDa protein complex was isolated and that specific bands for BoNT/A and FGFR3 within this complex could be detected using antibodies specific to BoNT/A or FGFR3 . Second , a complex containing both BoNT/A and FGFR3 was isolated from Neuro-2a cells treated with biotin labeled BoNT/A and the cross linking reagent Bis ( Sulfosuccinimidyl ) suberate ( data not shown ) . Finally , the recombinant binding domain of BoNT/A , His-rHC/A , was used to pull down FGFR3 from differentiated PC-12 cell lysates without the use of cross-linking reagents , demonstrating a strong interaction ( Figure 1B ) . Having identified FGFR3 as a binding partner for BoNT/A , we investigated the role of FGFR3 as a functional receptor for BoNT/A . Competition experiments utilizing native ligands for FGFR3; FGF1 , FGF2 , and FGF9 [39] , [42] , demonstrated that these ligands competed for binding to FGFR3 and blocked BoNT/A uptake in a cell-based assay with differentiated Neuro-2a cells ( Figure 1C–D ) . rHC/A , was used as a positive control and produced a strong blockade of BoNT/A uptake . As a negative control , FGF10 ( ENSG00000070193 ) , which is not a ligand for FGFR3 , but closely related to the other FGF ligands tested , was used . Pre-incubation with FGF10 did not affect BoNT/A uptake . The experimental data from at least four independent experiments were compiled and fitted to a non-linear exponential decay model; Y = 100*e- CC*log ( concentration ) . The Competition Constant ( CC ) for each fitted curve was calculated and demonstrated similar competition of the three FGF ligands . The data strongly suggest that BoNT/A utilizes FGFR3 to gain entry into neuronal cells since native FGFR3 ligands blocked its uptake . The hypothesis that BoNT/A acts as an agonist for FGFR3 was further supported by demonstrating that treatment with rHC/A resulted in phosphorylation of FGFR3 , achieving similar levels of activation as cells treated with identical concentrations of FGF2 ( Figure 1E–F ) . The ligand binding site for FGFR3 has been identified as the second and third extra-cellular loops of FGFR3 ( Figure 2A ) [39] , [51] , [52] . To further verify the functional role of FGFR3 as a receptor for BoNT/A , we demonstrated that pre-incubation of BoNT/A with a peptide spanning the second and third extra-cellular loops of FGFR3b ( FGFR3b Loop 2 , 3 ) inhibited BoNT/A uptake presumably via binding to the receptor binding domain of BoNT/A ( Figure 2C ) . Inhibition , although to a lesser extent , was also observed using the peptide spanning the luminal domain ( LD4 ) of SV2C , SV2C529–579 ( Figure 2C ) . SV2C529–579 ( Figure 2B ) has previously been reported as the minimal peptide region for binding to BoNT/A [17] . As a positive control for inhibition , BoNT/A was pre-incubated with a neutralizing monoclonal antibody directed to the binding domain of BoNT/A , Anti-HC/A . As a negative control , Synaptotagmin II ( aa1–20 , Syt II1–20 ) , the receptor for BoNT/B [53]–[56] was used . The experimental data from at least three independent experiments were compiled and fitted to a non-linear exponential decay model; Y = 100*e- IC*log ( concentration ) . The Inhibition Constant ( IC ) for each fitted curve was calculated and demonstrated that FGFR3b Loop 2 , 3 inhibited BoNT/A uptake and was a more effective uptake inhibitor than SV2C529–579 ( Figure 2D ) . Initial experiments designed to explore the combined effect of FGFR3b Loop 2 , 3 and SV2C529–579 showed that the peptides bound with good affinity in vitro ( data not shown ) . To address the question as to whether FGFR3 and SV2 interact in neurons , we performed a series of Co-IPs experiments . We tested if an antibody to FGFR3 could pull-down SV2 isoforms from a differentiated Neuro-2a cell lysate , and vice versa , antibodies to SV2 isoforms could pull-down FGFR3 . An interaction between FGFR3 and SV2 was detected using the Anti-SV2B ( sc-28956 ) antibody , which recognizes SV2B and , to a lesser extent , SV2A and SV2C . No bands were detected when using antibodies for SV2A or SV2C ( data not shown ) . The result suggests that FGFR3 and SV2B interact in differentiated Neuro-2a cells ( Figure 2E–F ) . To characterize the binding of FGFR3 and SV2C to rHC/A , the binding affinity of the two receptor surrogate peptides , FGFR3b Loop 2 , 3 and SV2C529–579 to rHC/A was tested in a Surface Plasmon Resonance ( SPR ) binding assay . FGFR3b Loop 2 , 3 bound to rHC/A with an average KD = 15 . 0±3 nM , n = 4 , ka = 1 . 77E+04 1/Ms , kd = 2 . 40E-04 1/s ( Figure 3B–C ) . This is similar to what has been reported earlier upon binding of FGFR2b Loop 2 , 3 to FGF2 , KD = 12 . 8±0 . 3 nM [57] . SV2C529–579 bound to rHC/A with an average KD = 105±6 nM , n = 3 , ka = 2 . 34E+03 1/Ms , kd = 2 . 47E-04 1/s ( Figure 3A , C ) . The difference in affinity between FGFR3b Loop 2 , 3 and SV2C529–579 is due to a 10 times faster association , ka is estimated to be 10 times higher for FGFR3b Loop 2 , 3 versus SV2C529–579 . It can be seen on the curves as a more shallow slope and longer time to equilibrium for SV2C versus FGFR3b Loop 2 , 3 ( Figure 3A versus 3B ) . In order to compare the binding affinity of FGFR3b Loop 2 , 3 to rHC/A to the binding affinity of native ligands for FGFR3 , the binding affinity of FGFR3b Loop 2 , 3 to FGF2 and FGF9 was also measured in the SPR binding assay . FGFR3b Loop 2 , 3 bound to FGF2 with an average KD = 12 . 3±4 nM , n = 3 , ka = 1 . 65E+04 1/Ms , Kd = 1 . 59E-04 1/s . FGFR3b Loop 2 , 3 bound to FGF9 with an average KD = 31 . 2±1 nM , n = 3 , ka = 2 . 92E+03 1/Ms , kd = 9 . 25E-05 1/s ( Figure 3C–E ) . Having identified rHC/A as an agonist ligand for FGFR3 ( Figure 1E–F ) and shown that rHC/A binds to FGFR3b Loop 2 , 3 in vitro with similar affinity as native ligands for FGFR3 , we evaluated if FGFR3 would facilitate uptake of rHC/A and native ligands in a similar fashion . We utilized HEK 293 cells as a model system , because they express FGFR3 but no measurable levels of any of the SV2 isoforms ( Figure S1G ) . Consequently , uptake of rHC/A via SV2 should be absent in these cells . HEK 293 cells do not express SNAP25 and therefore SNAP25 cleavage could not be used as a measure for BoNT/A uptake . Instead , uptake was measured as an increase in intracellular fluorescence after addition of fluorescently labeled rHC/A or FGF2 , a native ligand for FGFR3 . The results showed slightly less uptake of rHC/A compared to FGF2 , but similar kinetics ( Figure S1H ) . The slightly higher uptake of FGF2 compared to rHC/A could be due to FGF2 having more receptor targets , since it is a general ligand for FGFRs . These data suggest that FGFR3 can mediate BoNT/A uptake independently of SV2 . To explore the binding sites of FGFR3b Loop 2 , 3 and SV2C529–579 on the binding domain of BoNT/A , we performed a series of dual binding experiments using the BIAcore . We tested if the peptides and anti-HC/A , the neutralizing monoclonal antibody previously used in the cell based inhibition assay ( Figure 2C & D ) , could bind to rHC/A simultaneously . rHC/A was captured by anti-HC/A monoclonal and FGFR3b Loop 2 , 3 or SV2C529–579 were flowed across . The results show that binding of anti-HC/A monoclonal blocks binding of FGFR3b Loop 2 , 3 , but not SV2C529–579 to rHC/A in vitro ( Figure 3F–G ) , demonstrating that FGFR3 and SV2 bind to different sites on the BoNT/A binding domain . Interestingly , these data also suggest that inhibition of BoNT/A uptake by the neutralizing monoclonal anti-HC/A antibody in the cell based assay is due to blockage of FGFR3 binding . These results demonstrate that FGFR3b Loop 2 , 3 and SV2C529–579 can both inhibit the activity of BoNT/A in a cell-based assay , but FGFR3b Loop 2 , 3 is a stronger inhibitor than SV2C529–579 . They show that in an in vitro binding assay , the binding affinity for FGFR3b Loop 2 , 3 upon binding to rHC/A is higher , due to an estimated 10 times faster association , than the binding affinity for SV2C529–579 upon binding to rHC/A . The binding affinity for FGFR3b Loop 2 , 3 to rHC/A , is similar or identical , to the binding affinity for FGFR3b Loop 2 , 3 upon binding to FGF2 and FGF9 , two native ligands for FGFR3 . Also , uptake of rHC/A in HEK 293 cells , that express FGFR3 , but not SV2 , is comparable to uptake of FGF2 , supporting a case for uptake of BoNT/A via FGFR3 independent of the presence of SV2 . Finally , dual in vitro binding studies using a neutralizing antibody to HC/A , show that the FGFR3 and SV2C peptides bind to rHC/A at different sites , FGFR3 at a site close to or overlapping the binding site for the anti- HC/A , and SV2C in a site distal from the anti- HC/A binding site . Different binding sites for FGFR3 and SV2 would allow a multi-receptor complex to form . Differentiation of neuronal cells increases BoNT/A uptake ( Figure S1A and B ) . It has been suggested that the increased sensitivity in differentiated PC-12 cells is due to increased expression of the SNAP25b subtype that is most sensitive to BoNT/A [50] . Since the increased sensitivity could also be a result of increased expression of a receptor for BoNT/A , we studied the expression of FGFR3 as well as SV2A , B , and C before and after differentiation in both Neuro-2a and PC-12 cells . FGFR3 expression levels were similar in both cell lines and the amount of FGFR3 was unchanged after differentiation . Neuro-2a cells expressed mostly SV2C , while PC-12 cells expressed all three SV2 isoforms . Surprisingly , differentiation resulted in decreased expression of SV2 isoforms in both cell lines ( Figure S1F ) . Assuming FGFR3 is a functional receptor for BoNT/A , one would expect overexpression of FGFR3 to result in increased binding of BoNT/A on the cell membrane . If receptor binding is a rate-limiting step , this should also result in increased sensitivity to BoNT/A . Experiments to test the sensitivity to BoNT/A were performed under non-depolarizing conditions , where the exposure of SV2 on the cell surface is presumed to be limited . Overexpression of FGFR3 in PC-12 and Neuro-2a cells increased the sensitivity to BoNT/A and produced higher efficacy ( increased maximal signal ) , in a Western blot SNAP25197 cell-based assay , while overexpression of SV2C did not ( Figure 4A–B ) . FGFR3 overexpression also increased binding of transfected cell membranes to rHC/A in a SPR binding assay , while overexpression of SV2C did not ( Figure S2A and C ) , suggesting that if there is more FGFR3 on the cell surface more BoNT/A will bind , while more SV2C does not increase BoNT/A binding . Human neuroblastoma SH-SY5Y cells were also evaluated in the SPR binding assay because they have low sensitivity to BoNT/A [58] and express very little endogenous SV2C . Even in this situation , there was no effect as a result of over expressing SV2C ( Figure S2B ) . We also demonstrated , utilizing shRNA , that reduced expression of FGFR3 resulted in reduced sensitivity to BoNT/A . A 65% reduction of FGFR3 protein expression resulted in a 5 . 7-fold decrease in potency and a ∼5-fold increase in EC50 when compared to control cells ( Figure 2C ) . No change in the protein expression levels of either SV2A , B , or C was detected in those samples . A separate experiment with siRNAs for FGFR3 and SV2C demonstrated that a 4 . 2-fold reduction in SV2C mRNA resulting in a 2-fold reduction in protein levels did not cause a reduction in BoNT/A uptake ( Figure S2E–F ) . While a 3-fold reduction of FGFR3 mRNA resulting in a 2-fold reduction in protein levels reduced sensitivity to BoNT/A causing a 3-fold shift in relative potency when compared to control cells ( Figure S2D and F ) , confirming that , under non-depolarizing conditions , binding to FGFR3 is a rate-limiting step in BoNT/A uptake . The interaction between FGFR3 and rHC/A was also observed in a photobleaching experiment using the FRET partners AF-488 and TMR . We detected an increase in the fluorescent signal from the AF-488 labeled rHC/A ( donor ) after photobleaching the TMR labeled FGFR3 ( acceptor ) . The data shows that FGFR3 and rHC/A are proximal enough within PC-12 cells to FRET , suggesting that FGFR3 not only binds BoNT/A on the cell surface , but it is also trafficking with BoNT/A within the cells . There was little change in the fluorescence observed when the experiment was performed with TMR labeled SV2C as the acceptor ( Figure 4E–G ) . BoNT/A causes transient muscle paralysis through presynaptic blockade of acetylcholine release at the neuromuscular junction . If FGFR3 functions as a receptor for BoNT/A in vivo , then it would be reasonable to presume that FGFR3 should be expressed at the MNTs . The expression pattern of the FGFR3 receptor was examined on cross-sections of rat skeletal muscle to look for potential co-expression with SV2C , SNAP25 , and nicotinic acetylcholine receptors ( nAChRs ) . Overall , immuno-reactive ( IR ) staining for SV2C and SNAP25 were co-expressed exclusively at neuromuscular junctions ( NMJs ) throughout the muscle ( Figure 5A , A–D ) . These NMJs were specifically defined by using fluorescently labeled α-bungarotoxin ( α-Bgt ) nAChRs . In contrast , FGFR3-IR was not only detected at NMJs , but also in extra-synaptic structures , such as myoblasts and blood vessels ( Figure 5A , E ) . At the NMJs however , the FGFR3 staining pattern corresponded to that of SNAP25 and nAChRs ( Figure 5A , E–H ) . To verify expression of SV2C and FGFR3 within BoNT/A sensitive NMJs , we treated rat Tibialis Anterior ( TA ) muscles with BoNT/A and analyzed the staining patterns for SV2C and FGFR3 together with IR-staining for cleaved SNAP25 ( SNAP25197 ) . Focusing on individual synapses , we observed overlapping patterns for SV2C-IR and SNAP25197-IR that were adjacent to the pattern of post-synaptic nAChR expression ( Figure 5A , I-L ) . Similarly , the patterns for FGFR3-IR and SNAP25197-IR at the NMJ were overlapping and appeared adjacent to the pattern of nAChR expression ( Figure 5A , M–P ) . Saline-treated rat muscles showed no immuno-staining for SNAP25197 ( Figure 5B ) . These qualitative results demonstrate that FGFR3 receptors are present on MNTs and are co-expressed with SV2C and SNAP25 . We have shown that FGFR3b Loop 2 , 3 binds to BoNT/A with low nanomolar affinity . To further identify the binding site for BoNT/A and to test whether the two subtypes of FGFR3 , subtype b and c , bound with similar affinities , we constructed eight deletion mutants of FGFR3 , containing either FGFR3 Loop 1 , 2 , 3 ( long or short version ) , Loop 2 , 3 , or Loop 3 of both subtypes ( Figure 6A ) . The difference between FGFR3b and FGFR3c lies in the most C-terminal part of Loop 3 ( Figure S3A ) . All the deletion mutant FGFR3 peptides were able to inhibit BoNT/A uptake in a cell-based inhibition assay , presumably via binding to the receptor binding domain of BoNT/A and preventing binding to cells ( Figure 6B–C ) . However , in a SPR binding assay a significantly lower affinity was observed for the peptides spanning only Loop 3 compared to the peptides spanning Loop 2 , 3 or Loop 1 , 2 , 3 . The association ( on-rate ) of the peptides spanning only Loop 3 was ∼10 times lower than the on-rate of the longer peptides , while the dissociation ( off-rate ) was similar ( Figure 6E and S3B–C ) . The similar off-rate can explain why the peptides are able to inhibit equally well BoNT/A binding to the receptor in the cell-based inhibition assay . In the cell-based assay sufficient time ( 20 min ) is available for even slow associating peptides to bind and the ability to inhibit relies more on a slow dissociation . In the SPR binding assay , on the other hand , binding is observed in real time ( 5–10 min ) . Based on the lower on-rate of the Loop 3 peptides observed in the SPR binding assay , Loop 2 , 3 , which is the binding region for native FGF ligands , was identified as the minimal optimal binding region for BoNT/A . FGFR3b bound with slightly higher affinity than FGFR3c ( Figure 6D ) .
In this study we identified FGFR3 as a high affinity protein receptor for BoNT/A . Pull-down experiments with neuronal cells resulted in the identification of a protein complex containing BoNT/A and FGFR3 . Native ligands for FGFR3; FGF1 , FGF2 , and FGF9 compete with rHC/A for binding to the receptor and binding of rHC/A results in phosphorylation of FGFR3 , demonstrating that BoNT/A acts as an agonist ligand for FGFR3 . Since ligand binding and activation of FGFRs are known to result in receptor-mediated endocytosis of both receptor and ligand [59] , we propose that binding of BoNT/A to FGFR3 also results in endocytosis and that FGFR3 may mediate BoNT/A uptake in both stimulation independent and stimulation dependent manners . This hypothesis is supported by the fact that depolarization of nerve cells increases uptake ( stimulation dependent ) , while at the same time BoNT/A uptake can take place in resting neurons ( stimulation independent ) [3] , [4] , [60]–[63] . This is also supported by the observation that the uptake , but not the initial binding step , is altered by nerve stimulation [64] . Motor neurons at MNTs take up BoNT/A with high affinity , resulting in inhibition of exocytosis and muscle paralysis . Thus , MNTs should presumably express a BoNT/A receptor ( s ) , and our results clearly demonstrated that both FGFR3 and SV2C are present at MNTs . These data support the hypothesis that FGFR3 functions as a high affinity receptor for BoNT/A uptake , and that most likely , SV2 is only available as a receptor for BoNT/A after depolarization and vesicular exocytosis . Using a SPR binding assay , we demonstrated that a peptide spanning the second and third extra-cellular loops of FGFR3 , FGFR3b Loop 2 , 3 , binds to rHC/A with a KD∼15 nM and that a peptide spanning the luminal domain of SV2C , SV2C529–579 , binds to rHC/A with a KD∼100 nM in vitro . The observed ∼15 nM affinity for binding of rHC/A to FGFR3b Loop 2 , 3 was similar or identical to the affinity for binding of two native ligands for FGFR3 , FGF2 and FGF9 to FGFR3b Loop 2 , 3 in the same assay . Also , comparable uptake of rHC/A and FGF2 was observed in HEK 293 cells , a cell line that express FGFR3 and not any of the SV2 isoforms , suggesting that FGFR3 can mediate uptake of BoNT/A independently of SV2 . A recent publication [63] clearly supports our findings . The authors observed limited co-localization of SV2C and HC/A or BoNT/A after treatment of spinal cord motor neurons under resting conditions and this co-localization did not significantly increase under depolarizing conditions . Moreover , inhibition of exocytosis by pre-treatment with BoNT/D did not prevent the internalization of HC/A . The authors concluded that BoNT/A may exploit an alternative pathway ( s ) , largely independent of stimulated synaptic endo-exocytosis , to enter neuronal cells in both resting and depolarizing conditions . Pre-incubation of BoNT/A with the FGFR3 and SV2C peptides before treatment of cells , blocked uptake in neuronal cells , presumably by interacting with the binding domain of BoNT/A and preventing binding to the receptor on cells . In accordance with the observed lower affinity for SV2C529–579 compared to Loop 2 , 3 of FGFR3 , the FGFR3 peptide produced a stronger blockade than the SV2C peptide . These data suggest that FGFR3 may function as a high affinity receptor for BoNT/A and that SV2C may function as a medium affinity receptor . SPR experiments demonstrated that the FGFR3b and SV2C peptides bind to different sites on HC/A , FGFR3 in a site overlapping the epitope of a neutralizing monoclonal antibody to HC/A ( 6B1 , provided by Dr . L . Smith , USAMRIID ) and SV2C in a site distal from both . So far the binding site for SV2 has not been identified , but it has been suggested that SV2 binds to the C-terminal half of the binding domain , HCC , similar to how Synaptotagmin II binds to BoNT/B [23] . Different binding sites for FGFR3 and SV2 on the binding domain of BoNT/A would allow formation of a multi-receptor complex . Interestingly , Co-IP experiments show that FGFR3 and SV2 can interact in live Neuro-2a cells , suggesting a step-wise binding and/or formation of a multi-receptor BoNT/A complex . We concur with others in the field that the specificity of BoNT/A for neuronal cells and specially motor neurons , which is higher than binding to a single receptor can explain , is due to the fact that uptake of BoNT/A is a multi-step process involving at least two crucial steps [13] , [23] . The first crucial step is binding to gangliosides like GT1b ( KD∼200 nM ) that are abundantly present in the outer leaflet of the plasma membrane of neuronal cells . This initial step increases the local concentration of BoNT/A and allows it to diffuse in the plane of the membrane to bind its protein receptor ( s ) [15] , [16] , similar to what has been observed for heparin sulfate and FGF2 [65] . BoNT/A that is diffusing within microdomains of the plasma membrane will be presented to FGFR3 and/or SV2 , bind to the receptor , and undergo endocytosis representing a second crucial step . There are several lines of evidence suggesting that the initial binding to gangliosides is critical to specifically accumulate BoNT/A on the membrane of neuronal cells . For example , It has been shown [66] that , in the absence of GT1b , Neuro-2a cells are insensitive to BoNT/A and that knockout mice defective in the production of polysialogangliosides show reduced sensitivity to BoNT/A and BoNT/B [20] , [26] , [67] . Moreover , a mutant version of HC/A , W1266L & Y1267S that does not bind to GT1b , does not extend paralysis time caused by BoNT/A in murine phrenic nerve-hemidiaphragm preparations demonstrating an impaired ability to bind to neuronal cells [68] . Here we propose that only after BoNT/A is anchored at the neuronal membrane the second crucial step , binding to FGFR3 and/or SV2 , can occur . This explains how BoNT/A can specifically enter motor neurons by recognizing FGFR3 , a receptor also expressed by non-neuronal cells that lack gangliosides in their membranes . As evidence for a second crucial step , we demonstrate that , in Neuro-2a cells , if either FGFR3 or SV2C binding is blocked , BoNT/A uptake is impaired . BoNT/A uptake is affected by the cellular levels of FGFR3 expression . We demonstrated that overexpression of FGFR3 increased binding of membrane extracts to rHC/A as well as BoNT/A uptake in three different neuronal cell lines , while down-regulation of FGFR3 reduced uptake of BoNT/A . In contrast , no changes in BoNT/A uptake were observed when increasing or decreasing the expression of SV2C , suggesting that FGFR3 , but not SV2C represents a rate-limiting step in BoNT/A uptake under resting conditions . This is consistent with our finding that FGFR3 , but not SV2C , co-localized with BoNT/A in un-stimulated PC-12 cells . By testing eight deletion mutant peptides of the FGFR3b and c extra-cellular domain in the SPR binding assay , we identified the extra-cellular Loop 2 , 3 of FGFR3 as the minimal optimal binding site for rHC/A . Native ligands for FGFR3 also bind to Loop 2 , 3 [39] , [51] , [52] and these data demonstrate that the binding site for rHC/A overlaps the binding site for native ligands of FGFR3 . The affinity measurements also demonstrated that FGFR3b bound with slightly higher affinity than FGFR3c , the KD for the subtype b peptides was ∼15 nM , while the KD for the subtype c peptides was ∼25 nM . The FGFR3c subtype is the subtype expressed in the nervous system , while expression of the FGFR3b subtype is restricted to epithelial structures [69] , [70] . It is therefore more likely that BoNT/A utilizes the FGFR3c subtype in vivo to gain access into neuronal cells . In conclusion , this paper presents evidence for FGFR3 as a high affinity receptor for BoNT/A , potentially being part of a larger receptor complex involving sugar- and protein-protein interactions . FGFR3 is present in the target motor neurons . Overexpression of FGFR3 in several neuronal cells increases efficacy and sensitivity to BoNT/A while decreased FGFR3 expression renders the cells less sensitive . BoNT/A binds to FGFR3 at the same extra-cellular region and with the same affinity as native ligands for FGFR3 and functions as an agonist ligand inducing FGFR3 phosphorylation . Moreover , BoNT/A uptake can be blocked by native FGFR3 ligands or by peptide fragments containing the extra-cellular region of FGFR3 . Together , these results expand our knowledge of BoNT/A uptake in neuronal cells and present a potential new pathway mediating BoNT/A entry and trafficking into neurons under both resting and depolarizing conditions .
Unless otherwise stated tissue culture reagents were from Invitrogen ( Carlsbad , CA ) PC-12- Rat pheochromocytoma cell line ( CRL-1721; ATCC ) was cultured in collagen IV plates ( 354528; BD ) . Growth media: RPMI media with 2 mM GlutaMAX , 5% Fetal Bovine Serum ( heat-inactivated ) , 10% Equine Serum , 10 mM HEPES , 1 mM Sodium Pyruvate , 100 U/ml Penicillin , and 100 µg/ml Streptomycin . Differentiation media: RPMI media with 2 mM GlutaMAX , 1× B27 supplement , 1× N2 supplement , 10 mM HEPES , 1 mM Sodium Pyruvate , 50 ng/ml NGF , 100 U/ml Penicillin , and 100 µg/ml Streptomycin . Neuro-2a- Murine neuroblastoma cell line ( CCL-131; ATCC ) was cultured in Costar Tissue Culture Flasks ( CLS3150; Corning ) . Growth media: EMEM with 2 mM GlutaMAX , 0 . 1 mM Non-Essential Amino-Acids , 10 mM HEPES , 1 mM Sodium Pyruvate , 100 U/ml Penicillin , 100 µg/ml Streptomycin , and 10% Fetal Bovine Serum . Differentiation media: EMEM with 2 mM GlutaMAX , 0 . 1 mM Non-Essential Amino-Acids , 10 mM HEPES , 1× N2 supplement , and 1× B27 supplement . SH-SY5Y- Human neuroblastoma cell line ( 94030304; ECACC ) was cultured in Costar Tissue Culture Flasks ( CLS3150; Corning ) . Growth media: EMEM with 2 mM GlutaMAX/F12 , 0 . 1 mM Non-Essential Amino-Acids , 10 mM HEPES , 1 mM Sodium Pyruvate , 100 U/ml Penicillin , 100 µg/ml Streptomycin , and 10% Fetal Bovine Serum . Differentiation media: EMEM with 2 mM GlutaMAX , 0 . 1 mM Non-Essential Amino-Acids , 10 mM HEPES , 1× N2 supplement , and 1× B27 supplement . HEK 293- Human Embryonic Kidney 293 cells ( CRL-1573; ATCC ) were cultured in Costar Tissue Culture Flasks ( CLS3150; Corning ) . Growth media: EMEM with 2 mM GlutaMAX , 0 . 1 mM Non-Essential Amino-Acids , 10 mM HEPES , 1 mM Sodium Pyruvate , 100 U/ml Penicillin , 100 µg/ml Streptomycin , and 10% Fetal Bovine Serum . For differentiation , PC-12 , Neuro-2a , and SH-SY5Y cells were plated in 96-well plates at 5×104 cells/well in 100 µl differentiation media for three days . FGFR3b/c peptides and rHC/A were expressed from pET-29 b ( + ) in E . Coli , Acella Electrocompetent BL21 ( DE3 ) ( 42649; Edge Biosystems ) . Expression was induced by 1 mM IPTG ( V3955; Promega ) at either 37°C for 16 hours ( FGFR3b/c peptides ) or at 16°C for 16 hours ( rHC/A ) . For purification of rHC/A , the supernatant was collected after centrifugation and the protein was purified using the MagneHis Protein Purification System ( V8500; Promega ) . FGFR3b/c peptides were purified from inclusion bodies . After expression , cells were first lysed for 1 hour in five times the cell wet weight in lysis buffer containing 50 mM Tris-HCl pH 8 . 0 , 10 mM EDTA , 100 mM NaCl , 10 mM DTT , 5% ( v/v ) glycerol , protease inhibitor ( P1860; Sigma ) , 150 mU/ml rLysozyme ( 71110; EMD Chemicals ) , and 50 mU/ml benzonase nuclease ( 70746; EMD Chemicals ) and then sonicated for 5 minutes . Pellets were collected by centrifugation and washed three times , first time with wash buffer ( 50 mM Tris-HCl pH 8 . 0 , 100 mM NaCl , 10 mM DTT , 5% glycerol and 2% Triton X-100 ) plus 10 mM EDTA , second time with wash buffer only , and third time with wash buffer plus 2 M urea . The inclusion bodies were dissolved in 50 mM Tris-HCl pH 8 . 0 , 500 mM NaCl , 10 mM DTT , 8 M urea , 10 mM imidazole and the peptides were isolated using the Magne-His Protein Purification Resin ( V8560; Promega ) . Wash buffer: 50 mM Tris-HCl pH 8 . 0 , 500 mM NaCl , 10 mM DTT , 8 M urea , and 20 mM imidazole . Elution buffer: 50 mM Tris-HCl pH 8 . 0 , 500 mM NaCl , 10 mM DTT , 8 M urea , and 500 mM imidazole . After elution , the buffer was exchanged to 50 mM Tris-HCl pH 8 . 0 , 1 mM EDTA , 3 . 8 mM GSH , 1 . 2 mM GSSH and 1 M arginine using a FastDialyzer fitted with 5 kDa MWCO cellulose acetate membranes ( Harvard Apparatus ) . The assay was performed according to the protocol from Pierce ( 21277; Pierce ) . 150 µg of rHC/A ( 26 mg/ml stock conc . ) was used as “Bait” protein and 500 µl of differentiated PC-12 cell lysate ( from 1 . 5×106 cells ) was used as “Prey” protein . As negative controls , samples without either “Bait” or “Prey” protein were run in parallel . The eluted samples were analyzed by SDS-PAGE and Western blot analysis . 10 µg BoNT/A was reacted with 2 mM Sulfo-SBED ( 33073; Thermo Scientific ) ( solubilized at 125 mM in DMSO ) in 0 . 1 ml PBS for 2 hours . The reaction was stopped by addition of 0 . 1 µl 0 . 4 M Tris . As a control 10 µg of BSA was also reacted with 2 mM Sulfo-SBED . Sulfo-SBED BoNT/A and BSA were added to 1×108 Neuro-2a cells and mixed by rotisserie at 4°C for 4 hours . The reagent was photoactivated for 15 minutes with a UV light source . The cells were washed 4 times with cold TBS and then lysed by incubation for 2 hours in T-X-100 lysis buffer ( 50 mM Tris , 150 mM NaCl , 1% Triton X-100 , 10 mM EDTA , pH 7 . 2 ) . The biotinylated proteins were precipitated using Monomeric Avidin ( Thermo Scientific ) , washed 4 times in the TX100 lysis buffer and then analyzed by SDS-PAGE and Western Blot Analysis . Samples were dissolved in 2× SDS-PAGE loading buffer ( LC2676; Invitrogen ) , heated to 95°C for 10 min , resolved in 12% 26-well Criterion gels ( 345-019; Bio-Rad ) or 12% Bis-Tris Novex NuPage gels ( NP0341BOX; Invitrogen ) , transferred to 0 . 45 µm nitrocellulose membranes ( 62-0233; Bio-Rad ) , blocked for 1 hour in TBS buffer ( 170-6435; BioRad ) plus 0 . 1% Tween 20 ( 161-0781; BioRad ) ( TBS-T ) and 2% blocking agent ( RPN418V; GE Healthcare ) , and incubated overnight with primary antibody , either; anti-SNAP25197 ( Allergan ) rabbit polyclonal antibody diluted to 1 µg/ml , anti-HC/A ( Allergan ) rabbit polyclonal antibody diluted to 1 µg/ml , anti-FGFR3 ( 1∶500 , sc-123; Santa Cruz Biotechnology ) , anti-FGFR3 ( 1∶1000 , Ab133644; Abnova ) , anti-SV2A , ( 1∶200 , sc-28955; Santa Cruz Biotechnology ) , anti-SV2B ( 1∶200 , sc-28956; Santa Cruz Biotechnology ) , anti-SV2C ( 1∶500 , sc-28957; Santa Cruz Biotechnology ) or anti-Syntaxin ( 1∶200 , sc-12736; Santa Cruz Biotechnology ) in TBS-T plus 2% blocking agent . Secondary antibody was anti-rabbit IgG H+L HRP conjugate ( 81-6120; Invitrogen ) , anti-rabbit IgG veriBlot for IP secondary antibody ( HRP ) ( ab131366 , Abcam ) ( used for IP only ) , and anti-mouse IgG H+L HRP conjugate ( 62-6520; Invitrogen ) diluted 1∶5000 in TBS-T plus 2% blocking agent . Membranes were developed using ECL Plus Western Blotting System Detection Reagents ( RPN2132; GE Healthcare ) . The Chemiluminescence was captured using a Typhoon 9140 ( GE Healthcare ) set to the following parameters: 455 nm excitation laser and detector set to all wavelengths below 520 nm emissions . The intensity of the gel bands were calculated using Image Quant software TL V2005 ( GE Healthcare ) . The data was analyzed using PLA and SigmaPlot v 10 . 0 ( Systat Software Inc . ) . Intensity values were plotted against concentration of BoNT/A in log scale and fitted to a 4-parameter logistics function ( Y = Y0+a/[1+ ( X/X0 ) b] ) without constraints . Based on the fitted curves the EC50 values , corresponding to “X0” , were determined . Cells were transfected with pcDNA3 . 1 ( + ) ( V790-20; Invitrogen ) , FGFR3c ( EX-Y0098-M50; Genecopoeia ) , SV2C ( EX-S2660-M050; Genecopoeia ) , RNAi Hi GC ( 12935-400; Invitrogen ) , FGFR3 siRNA-88 ( FGFR3RSS331488; Invitrogen ) , FGFR3 siRNA-89 ( FGFR3RSS331489; Invitrogen ) , SV2C-1 siRNA ( AM16708; Ambion ) . Membrane extractions were performed with a Native Membrane Protein Extraction kit ( 444810; Calbiochem ) . Total protein concentration was measured using Bradford Reagent ( 500-0205; Bio-Rad ) . Differentiated Neuro-2a cells transfected with FGFR3 were treated with 0 . 5 nM or 50 nM FGF2 ( 233-FB; R&D Systems ) or rHC/A ( 26 mg/ml stock concentration ) for 10 minutes . Membrane extracts were prepared and 100 µg of total protein was incubated with 40 µl of a 50% slurry of anti-phosphotyrosine conjugated beads ( 16-101; Millipore ) for 24 hours at 4°C . Samples were washed 4 times with MEB buffer ( 50 mM Tris pH 7 . 5 , 150 mM NaCl ) containing phosphatase inhibitor cocktail 1 and 2 ( P2850 and P5726; Sigma ) and complete protease inhibitor cocktail ( 11 873 580 001; Roche ) and analyzed by SDS-PAGE and Western blot analysis , using antibody against FGFR3 . Differentiated cells ( see Cell Lines and Growth Conditions ) were treated with 0–30 nM BoNT/A ( 0 . 41 mg/ml stock concentration ) in differentiation media for 6 or 24 hours followed by overnight or two day incubation in toxin-free media . Cell lysates were analyzed by SDS-PAGE and Western blot analysis , using antibody against cleaved SNAP25 , anti-SNAP25197 ( Allergan ) . For competition , before treatment with 1 nM BoNT/A ( 150 kDa , Metabiologics ) , Neuro-2a cells were pre-treated for 30 min with increasing concentrations of FGF1 , FGF2 , FGF9 , FGF10 ( negative control ) ( 132-FA; 233-FB; 273-F9 , and 345-FG; R&D Systems ) , or rHC/A ( Figure 1A , positive control ) . For inhibition , before treatment onto cells , 1 nM BoNT/A ( 150 kDa , Metabiologics ) was incubated for 20 min with increasing concentrations of either; FGFR3b/c deletion mutant peptides ( Figure 6A ) , SV2C529–579 ( JPT Peptide Technologies; aa529–279 , H-NTYFKNCTFIDTVFDNTDFEPYKFIDSEFKNCSFFHNKTGCQITFDDDYSA-NH2 , Figure 2B ) , monoclonal anti-HC/A 6B1 ( Provided by Dr . L . Smith , USAMRIID; positive control ) , or Synaptotagmin II1–20 ( JPT , aa1–20 , H-MRNIFKRNQEPIVAPATTTA-NH2; negative control ) . The competitor/inhibitor was added at concentrations of 2 , 5 , 20 , 50 , and 200 molar excess of BoNT/A . Cells were incubated with BoNT/A plus competitor/inhibitor for 2 hours . The toxin containing media was then removed and replaced with fresh media followed by overnight incubation . Cells lysates were analyzed by SDS-PAGE and Western blot analysis , using antibody against cleaved SNAP25 , Anti-SNAP25197 . Blots were quantified and the amount of SNAP25197 produced at each concentration , as a measure of BoNT/A uptake , was used to calculate the percent competition/inhibition . The amount of BoNT/A uptake for each competitor/inhibitor was compared to the amount of BoNT/A uptake after pre-treatment/pre-incubation with the negative control . Each experiment was conducted at least three independent times and each dose was tested in triplicates in each individual experiment , the percent average for each of the three or more independent experiments were used to generate inhibition curves . The curves were fitted to a non-linear exponential model; Y = 100×e −b*log ( concentration ) , where “b” was defined as either the competition constant ( CC ) or the inhibition constant ( IC ) . Differentiated Neuro-2a cells were washed with PBS and then lysed by incubation at 4°C for 30 minutes in lysis buffer containing 20 mM Tris , 150 mM NaCl , 1% Triton X-100 , 1 mM EDTA , and 1 mM EGTA pH 7 . 2 plus complete protease inhibitor cocktail ( 11 873 580 001; Roche ) . The supernatant was collected by centrifugation and the total protein concentration was measured using Bradford Reagent ( 500-0205; Bio-Rad ) . The Co-IP reaction was performed by mixing 1 mg of cell lysate with 10 µg antibody in a total volume of 1 ml . The reaction was incubated at 4°C overnight . As negative controls , a sample without antibody ( lysate only ) and a sample without lysate ( antibody only ) were prepared in parallel . Then 100 µl Protein A/G Magnetic Beads ( 88802; Thermo Scientific ) was added and the reaction was incubated at 4°C for 1 hour . Three times the beads were sedimented using a dynamag-2 magnet ( Invitrogen; 12321D ) and washed with PBS . Finally , the beads were re-suspended in 2× SDS-PAGE running buffer and Western Blot was performed . Cell lysate was run in parallel . Purified rHC/A ( 0 . 4 mg ) was dialyzed against 4 L of 50 mM HEPES pH 7 . 0–7 . 2 150 mM NaCl in a 0 . 5 ml dialysis unit ( Harvard Apparatus ) for 16 hours at 4°C using a 25 kDa cut-off cellulose acetate membrane . FGF2 ( 0 . 2 mg ) ( 233-FB/CF; R&D Systems ) was re-suspended in 0 . 5 ml of 50 mM HEPES pH 7 . 2 , 150 mM NaCl . rHC/A was labeled with either Alexa Fluor 488 C5-maleimide ( A10254; Invitrogen ) ( cell imaging and photobleaching ) or Alexa Fluor 633 C5-maleimide ( A20342; Invitrogen ) ( rHC/A uptake ) and FGF2 was labeled with Alexa Fluor 633 C5-maleimide ( 10∶1 molar ratio free label to protein ) overnight at 4°C in the dark . To remove free label , the proteins were either dialyzed again , using the conditions listed above , or ran on a PD-10 desalting column ( 17-0851-01; GE Healthcare ) . The column was equilibrated with 50 mM HEPES pH 7 . 2 150 mM NaCl . The concentrations of rHC/A and FGF2 were determined by measuring the UV absorbance at 280 nm using a Beckman Coulter DU 800 . Cells were plated at 20 , 000 cells per well in a Cell Carrier microplate ( Perkin Elmer ) in culture media and allowed to attach overnight . Cells were treated with 1 µg/ml Cell Tracker Green CMFDA ( C2925; Invitrogen ) and Hoechst 33342 ( H10295; Invitrogen ) for 30 minutes prior to adding fluorescently labeled rHC/A or FGF2 . After removing the staining media , 0 . 1 ml of 0–25 nM of Alexa Fluor 633-rHC/A or -FGF2 was added . Fluorescence was measured using the Operetta High Content Imaging System ( Perkin Elmer ) , set to the following parameters: 20× WD objective , 9 fields , non-confocal , 15% excitation , Blue ( Ex 380–410/Em 430–460 ) , Green ( Ex 460–490 nm/Em 500–550 nm ) and Far Red ( Ex 630–645 nm/Em 660–900 nm ) . Uptake , measured as increasing amounts of Far Red signal in the cells , was monitored for 15 hours , with 30 minutes time points . The results were analyzed using Harmony 3 . 1 software . PC-12 cells transfected with Halo tagged FGFR3 or SV2C were plated on Collagen IV coated glass bottom dishes ( P35GCOL-0-10-C; MatTek ) and differentiated for 3 days . The cells were incubated with 5 µM Halotag TMR ligand ( G8251; Promega ) for 15 minutes and washed 3 times for 10 minutes with fresh media . Cells were then treated with 1 µM Alexa Fluor 488 labeled rHC/A . After 2 hours incubation , the cells were fixed using 5% paraformaldehyde . Cells were imaged using a LSM710 confocal microscope and analyzed using ZEN 2009 software ( Carl Zeiss INT , Germany ) . The Alexa Fluor 488 label and TMR star labels were imaged using the following respective settings: excitation 488 nm/emission 500–510 nm , excitation 561 nm/emission 595–620 nm . The TMR was photobleached by exciting the fluor with the 561 nm laser 100 times for 0 . 1 s with 5% laser power . The amount of fluorescence intensity of the donor fluor ( AF-488 ) was measured before and after photobleaching of the acceptor ( TMR ) . Sprague-Dawley rats ( 200–250 g; Charles River ) were injected with 10 units of BOTOX ( Allergan ) into the tibialis anterior ( TA ) muscle of the right hind limb . Animals receiving injections of 0 . 9% saline into their TA muscle served as controls . Rats were sacrificed 3 days following injections and their TA muscles were harvested . Muscles were embedded in OCT compound , frozen in liquid nitrogen and stored at −80°C . Prior to staining , muscles were cross-sectioned ( 10 µm ) using a cryostat ( Leica ) , mounted onto microscope slides and stored at −20°C until use . Frozen , slide-mounted muscle sections were thawed to room temperature and immediately fixed with 2% paraformaldehyde for 10 min . Sections were blocked with 5% normal serum in PBS , pH 7 . 4 for 60 minutes and then incubated with primary antibodies for 3 hours at room temperature: rabbit anti-SV2C ( 1∶400 , sc-28957; Santa Cruz Biotechnology ) , rabbit anti-FGFR3 ( 1∶200 , sc-123; Santa Cruz Biotechnology ) , mouse anti-SNAP25 ( 1∶200 , SMI-81 , Covance ) , and mouse anti-SNAP25197 ( 1∶200 , Allergan ) . Muscle nicotinic acetylcholine receptors ( nAChR ) were labeled with α-bungarotoxin ( α-Bgt ) Alexa-Fluor 647 conjugate ( 1∶500 , Invitrogen ) . Sections were then washed and incubated with secondary antibodies for 30 minutes at room temperature . Following a final wash , slides were coverslipped and analyzed . Images were acquired using a Zeiss LSM-710 confocal microscope ( Carl Zeiss INT ) . Experiments were performed on a BIAcore 3000 instrument ( GE Healthcare ) . Ligands , rHC/A , anti-HC/A 6B1 ( Provided by Dr . L . Smith , USAMRIID ) , FGF2 , or FGF9 ( 233-FB; and 273-F9; R&D Systems ) , were immobilized on a CM5 chip ( BR-1003-99 , GE Healthcare ) using an amine coupling kit ( BR-1000-50 , GE Healthcare ) . Analytes , either SV2C529–579 ( JPT Peptide Technologies , dissolved in 100% DMSO ) , FGFR3b/c deletion mutant peptides ( Figure 6A ) , rHC/A , or membrane extracts were injected over the ligand surfaces at concentrations ranging from 0–5000 nM , or for the membrane extractions at 5 µg/ml . The flow rate was set to 20 or 30 µl/min . Running buffer: HBS-EP buffer ( BR-1006-91 , GE Healthcare ) . The surfaces were re-generated by two 1-min injections at 30 µl/min of 10 mM Glycine , pH 1 . 5 ( rHC/A ) or 1-min injections at 30 µl/min of either; 10 mM Glycine , pH 1 . 5 and 0 . 125% SDS ( FGFR3 ) , 10 mM Glycine , pH 1 . 5 and 20 mM CHAPS ( Membrane extracts ) , or 10 mM NaOH ( SV2C ) . The sensorgram curves were evaluated using the BIAevaluation 3 . 0 software . The curves were fitted to a 1∶1 Langmuir binding model ( A + B ↔ AB , where A is the analyte and B is the ligand immobilized on the sensor surface ) . Based on the fitted curves the association constant , ka , the dissociation constant , kd , and the equilibrium constant , KD ( KD = kd/ka ) were determined . The FGFR3b/c peptide curves were also visually compared using the “normalization” wizard in the BIAevaluation 4 . 1 software . To assess the significance of the differences from the BoNT/A cell-based competition/inhibition assays and the SPR Binding Analysis assays t-tests were performed using online Graphpad software; www . graphpad . com/quickcalcs/ttest1 . cfm ? Format=SEM ( GraphPad Software Inc ) . FGFR3 ( ENSG00000068078 ) , SV2A ( ENSG00000159164 ) , SV2B ( ENSG00000185518 ) , SV2C ( ENSG00000122012 ) , FGF1 ( ENSG00000113578 ) , FGF2 ( ENSG00000138685 ) , FGF9 ( ENSG00000102678 ) , and FGF10 ( ENSG00000070193 ) . | ▸ Recombinant HC/A binds to the two extra-cellular loops of FGFR3b with a KD∼15 nM ▸ Recombinant HC/A acts as an agonist ligand for FGFR3 ▸The level of BoNT/A uptake is dependent on FGFR3 expression ▸ FGFR3 is expressed in motor nerve terminals | [
"Abstract",
"Introduction",
"Results",
"Discussion",
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"Methods"
] | [
"medicine",
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"disorders",
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"neuroscience",
"neuropharmacology",
"drugs",
"and",
"devices",
"neurology",
"neurotransmitters",
"biology",
"neuroscience"
] | 2013 | Identification of Fibroblast Growth Factor Receptor 3 (FGFR3) as a Protein Receptor for Botulinum Neurotoxin Serotype A (BoNT/A) |
Strongyloidiasis , caused by an intestinal helminth Strongyloides stercoralis , is common throughout the tropics . It remains an important health problem due to autoinfection , which may result in hyperinfection and disseminated infection in immunosuppressed patients , especially patients receiving chemotherapy or corticosteroid treatment . Ivermectin and albendazole are effective against strongyloidiasis . However , the efficacy and the most effective dosing regimen are to be determined . A prospective , randomized , open study was conducted in which a 7-day course of oral albendazole 800 mg daily was compared with a single dose ( 200 microgram/kilogram body weight ) , or double doses , given 2 weeks apart , of ivermectin in Thai patients with chronic strongyloidiasis . Patients were followed-up with 2 weeks after initiation of treatment , then 1 month , 3 months , 6 months , 9 months , and 1 year after treatment . Combination of direct microscopic examination of fecal smear , formol-ether concentration method , and modified Koga agar plate culture were used to detect strongyloides larvae in two consecutive fecal samples in each follow-up visit . The primary endpoint was clearance of strongyloides larvae from feces after treatment and at one year follow-up . Ninety patients were included in the analysis ( 30 , 31 and 29 patients in albendazole , single dose , and double doses ivermectin group , respectively ) . All except one patient in this study had at least one concomitant disease . Diabetes mellitus , systemic lupus erythrematosus , nephrotic syndrome , hematologic malignancy , solid tumor and human immunodeficiency virus infection were common concomitant diseases in these patients . The median ( range ) duration of follow-up were 19 ( 2–76 ) weeks in albendazole group , 39 ( 2–74 ) weeks in single dose ivermectin group , and 26 ( 2–74 ) weeks in double doses ivermectin group . Parasitological cure rate were 63 . 3% , 96 . 8% and 93 . 1% in albendazole , single dose oral ivermectin , and double doses of oral ivermectin respectively ( P = 0 . 006 ) in modified intention to treat analysis . No serious adverse event associated with treatment was found in any of the groups . This study confirms that both a single , and a double dose of oral ivermectin taken two weeks apart , is more effective than a 7-day course of high dose albendazole for patients with chronic infection due to S . stercoralis . Double dose of ivermectin , taken two weeks apart , might be more effective than a single dose in patients with concomitant illness . ClinicalTrials . gov NCT00765024
Infection with the intestinal helminth Strongyloides stercoralis remains a common problem throughout the tropics , including Thailand [1] , [2] . It is estimated that 30 to 100 million people are infected worldwide [1] . Most infected individuals are asymptomatic or developed minimally symptomatic chronic infection through autoinfection [3] . Potentially fatal disseminated infections , due to an acceleration of the autoinfection cycle , are seen in immunocompromised patients , such as those with concurrent human T-lymphotropic virus-1 ( HTLV-1 ) infection , or those on corticosteroid therapy [3] , [4] . Other recognized risk factors for disseminated strongyloidiasis include malignancies especially lymphoma , organ transplantation and diabetes mellitus [5] , [6] . Gastrointestinal symptoms associated with strongyloidiasis include diarrhea , abdominal discomfort , nausea/vomiting and anorexia . The diagnosis of strongyloidiasis should be suspected if there are clinical signs and symptoms , or eosinophilia [7] . Definitive diagnosis of strongyloidiasis is usually made on the basis of detection of larvae in the stool [8] . The combination of diagnostic approaches such as repeated direct microscopic examination of fecal smear , fecal concentration methods such as formol-ether concentration ( FEC ) , and modified Koga agar plate culture have been used to improve the likelihood of detecting this parasite [7]–[11] . In the past , the treatment of choice for strongyloidiasis has been thiabendazole , but this drug has unpleasant side effects and is no longer available . Albendazole , another broad-spectrum antihelmintic agent , was previously shown to be effective against S . stercoralis [12]–[15] . More recent reports suggest ivermectin , a macrolide-like agent developed primarily for the treatment of onchocerciasis , is as effective as thiabendazole [16] and superior to albendazole against intestinal strongyloidiasis [17]–[21] . Although a single dose of ivermectin 200 microgram/kilogram body weight ( µg/kg ) was shown to be effective in uncomplicated chronic strongyloidiasis , repeated treatment at two or three week intervals was thought to be necessary to eliminate larvae generated by autoinfection [22] . A preparation of oral ivermectin licensed for human use has recently become available in Thailand . However , albendazole remains the most widely used antiparasitic drugs for the treatment of this infection in this country . The purpose of the present study was to assess the safety and efficacy of a single dose of ivermectin ( 200 µg/kg ) , or two doses of ivermectin given 2 weeks apart , and a 7-day course of high dose albendazole for the treatment of chronic strongyloidiasis in adult patients who were at high risk of hyperinfection or disseminated infection .
This was a prospective open-label , randomised , controlled study conducted between July 2008 and April 2010 at Siriraj Hospital , Faculty of Medicine Siriraj Hospital , Mahidol University , Bangkok , Thailand . The study was approved by the Ethical Committee on Research Involving Human Subjects , Siriraj Hospital , Faculty of Medicine , Mahidol University , Thailand . All patients were informed about the purpose of the trial and gave written informed consent before enrollment . The study enrollment was stopped in December 2009 after 100 eligible patients had been recruited . Adult patients ( >18 years ) were recruited from Siriraj Hospital if characteristic rhabditiform larvae of S . stercoralis were present on fecal microscopy . Exclusion criteria included a history of allergic reaction to either study medication , treatment within the month prior to the study with any drug known to have anti-strongyloides activity , pregnancy or lactation and any suggestion of disseminated strongyloidiasis . Computer generated , simple , random allocation sequences were prepared for 3 study groups by the investigator team . These were sealed in an opaque envelope and numbered . The investigator ( YS ) assigned study participants to their respective treatment group after opening the sealed envelope . Once an eligible patient was identified and informed consent was obtained , the patient was randomly allocated to one of the following group ( 1∶1∶1 ratio ) : Baseline evaluation included history , detailed physical examination , and laboratory investigations such as complete blood count ( CBC ) , urinalysis , and biochemistry . Patients were requested to collect two consecutive fecal samples at every hospital visit . The coprodiagnosis for the detection of S . stercoralis larvae using direct smear , formol-ether concentration method [9] , and modified Koga agar plate culture method [10] was performed for each patient at the Infectious Diseases and Tropical Medicine Laboratory , Division of Infectious Diseases and Tropical Medicine , Faculty of Medicine Siriraj Hospital , Mahidol University , Thailand . Patients were required to make seven hospital visits to complete the study: at baseline evaluation and initiation of treatment , at 2 weeks after initiation of treatment , then at 1 month , 3 months , 6 months , 9 months , and 1 year after treatment . Patients who completed 1 year of follow-up were invited for further follow-up visits every 3 months or at their convenience .
One hundred and fifty one patients had detectable rhabditiform larvae of S . stercoralis on fecal microscopy during the study period . One hundred patients were enrolled ( 36 , 32 , and 32 patients in albendazole , ivermectin-I , and ivermectin-II groups respectively ) . Ten patients were excluded from analysis because they did not receive or complete the study treatment ( 3 in albendazole group , 2 in ivermectin-II group ) , or they were lost to follow-up immediately after treatment ( 3 in albendazole group , 1 each in ivermectin-I and ivermectin-II respectively ) . Overall , 90 patients were eligible for the modified intention to treat analysis . Detail of the total number of enrollment , randomization , follow-up and inclusion in the final analysis comparing among the three treatment groups is shown in Figure 1 . The demographic data , concomitant diseases , baseline clinical and laboratory investigations are shown in Table 1 and 2 . All except one patient had an associated medical problem , including concurrent other parasitoses . These patients also had abnormal serum aspartate aminotranferase ( AST ) and alanine aminotransferase ( ALT ) levels prior to entering the study due to their underlying conditions . The intensity of initial infection of the three study groups was similar , i . e . S . stercoralis larvae were found from the direct fecal examination in 24 ( 80% ) , 25 ( 80 . 6% ) , and 28 ( 96 . 6% ) in albendazole , Ivermectin-I , and ivermectin–II groups , respectively ( P = 0 . 123 ) . Larvae were also detected from modified Koga agar plate culture in 22/26 ( 84 . 6% ) patients in the albendazole group , in 22/26 ( 84 . 6% ) patients in the ivermectin-I group , and in 24/29 ( 82 . 8% ) patients in the ivermectin-II group , respectively ( P = 0 . 976 ) . Diarrhea was detected in half of the patients and it was relieved after treatment in most patients . Abnormal bowel movement at second week of follow-up was reported in 4 patients in the albendazole group , 2 patients in the ivermectin-I group , and 3 patients in the ivermectin-II group , respectively ( P = 0 . 641 ) . S . stercoralis larvae were detected in one patient in the ivermectin-I group at third month of follow-up . In ivermectin-II group , S . stercoralis larvae were detected at second week prior to the second dose of ivermectin in two patients . No patients had reinfection/relapse after the second dose of ivermectin treatment . In albendazole treated patients , S . stercoralis larvae were detected at second week of follow-up in 2 patients , at first month of follow-up in 2 patients , between 3–6 months of follow-up in 3 patients , and between 6–12 months of follow-up in 4 patients . All of the relapses/ reinfections found during follow-up were clinically inapparent . Parasitologically , parasite elimination was documented in 19 ( 63 . 3% ) albendazole treated patients , in 30 ( 96 . 8% ) single-dose ivermectin treated patients , and 27 ( 93 . 1% ) two-dose ivermectin treated patients ( P = 0 . 006 ) ( Table 3 ) . Cox regression analysis showed that albendazole treated group had 14 . 7 times ( 95%CI 1 . 8–111 . 9 ) , and 5 . 7 times ( 95%CI 1 . 3–25 . 7 ) higher risk for reinfection/ relapse of strongyloidiasis than ivermectin-I and ivermectin-II group , respectively . Kaplan- Meier Plot compares the parasitological cure rate between these study groups is shown in figure 2 . No hyperinfection syndrome or disseminated infection was found among these patients during the study period . S . stercoralis larvae were detected after treatment using FEC in 8 patients , and by modified Koga agar plate culture only in 6 of them . All patients with relapse/reinfection were retreated with two doses of ivermectin in two weeks apart . Overall albendazole and ivermectin were well tolerated . Transient elevation of AST , and ALT levels was detected in one patient in ivermectin-II group . The AST and ALT levels returned to normal 2 weeks after the second dose of ivermectin treatment . Severe nausea and vomiting was reported in one patient in the albendazole group . Fifteen patients died after enrollment ( 5 patients in each treatment group ) . Causes of death were not related to the study drugs , and were considered to be due to an underlying disease or its complications ( solid tumor in 5 , hematologic malignancies in 3 , diabetes mellitus , or systemic lupus erythrematosus ( SLE ) , or hypertension with complications such as myocardial infarction or sepsis in 7 patients ) . The median duration from enrollment to death was 2 weeks ( range 2–14 weeks ) in the albendazole group , 5 weeks ( range 2–38 weeks ) in the ivermectin-I group , and 2 weeks ( range 1–27 weeks ) in the ivermectin-II group , respectively .
Strongyloidiasis remains a significant health problem in many developing countries , mainly due to the potential for lethal disseminated disease [1] , [5] . Gastrointestinal symptoms associated with strongyloidiasis found in this study included diarrhea , abdominal discomfort , nausea/vomiting and anorexia . Chronic infection with S . stercoralis was clinically inapparent in half of the patients at enrollment , and in all of relapses/ reinfections found during follow up . Peripheral eosinophilia ( >500 eosinophils/µL . ) was detected in half of the patients at enrollment . S . stercoralis larvae were detected after treatment using FEC in 8 patients , and by modified Koga agar plate culture in 6 patients . This information confirmed that fecal examination , including culture and/or serology , every 3–6 months of follow-up should be recommended for early detection and treatment of latent infection to prevent hyperinfection or disseminated disease in these patients [3] , [5] . Results of this study corroborate the results from previous randomised controlled studies on the higher efficacy of ivermectin compared to various dosage regimens of albendazole for treating chronic strongyloidiasis [17]–[21] . A summary of results from these previous controlled trials of ivermectin treatment for chronic strongyloidiasis is shown in Table 4 . Although these studies were conducted in different geographical areas and population groups , i . e . in children and adults , they were considered to be within a community-based setting , such as schools or primary care clinic . The duration of follow-up varied from 3 weeks to 12 months . The present study was conducted in a tertiary hospital . The majority of patients had known risk factors for disseminated strongyloidiasis , and approximately one-third of them received corticosteroid or chemotherapy . Results of this study confirmed that ivermectin was also effective in this population who were at high risk of severe infection . Albendazole remains an option of treatment for chronic strongyloidiasis in many countries in South East Asia , where oral ivermectin is not widely available . Cure rates of a regimen consisting of albendazole 400 mg daily for three to five days varied from 38–87% in those without underlying diseases [14] , [17]–[20] . In this study , the cure rate was found to be 63% when a 7-day course of high dose albendazole was used . The efficacy of albendazole varied widely even when the same dose and duration of treatment was used . Differences in duration of follow-up examinations could be one explanation , and re-infection from the environment may also be a factor when the efficacy is monitored for an extended period in endemic areas . The study which reported the highest cure rate ( 87% ) was conducted in Okinawa , Japan [19] , where the chance of re-infection from the environment was less likely to occur compared to other studies conducted in endemic areas [17] , [18] , [20] , [21] . Two patients in the ivermectin-II group had detectable S . stercoralis larvae in the second week prior to the second dose of ivermectin treatment . One patient in ivermectin-I group also had detectable S . stercoralis larvae 3 months after treatment . This observation supports the recommendation that repeated doses of ivermectin should be the preferred treatment in patients with chronic strongyloidiasis who have an underlying or concomitant illness [22] . The limitation of this study was the high loss to follow-up rates over time . High mortality associated with the concomitant illnesses was an unavoidable cause of concern in this study . The median duration of follow up was 19 weeks in albendazole group , 39 weeks in ivermectin-I , and 26 weeks in ivermectin-II group . The non-significant shorter duration of follow up found in albendazole treatment group was due to the significant higher rate of treatment failure compared to ivermectin . However , the study still had sufficient power to detect a difference between albendazole and ivermectin treatments . This study , however , was too small to detect any but the most severe and common side- effects of both albendazole and ivermectin . Only one of albendazole treated patients and one treated with ivermectin had transient changes in transaminases , a well-recognized and reversible adverse event . In conclusion , this clinical study confirms that both a single and a double dose of oral ivermectin taken at a two-week interval is more effective than a 7-day course of high dose of albendazole for patients with chronic infection due to S . stercoralis . | Strongyloidiasis , caused by an intestinal helminth Strongyloides stercoralis , is common throughout the tropics . We conducted a prospective , clinical study to compare the efficacy and safety of a 7-day course of oral albendazole with a single dose of oral ivermectin , or double doses , given 2 weeks apart , of ivermectin in Thai patients who developed this infection . Patients were regularly followed-up after initiation of treatment , until one year after treatment . Ninety patients were studied ( 30 , 31 and 29 patients in albendazole , single dose , and double doses ivermectin group , respectively ) . The average duration of follow-up were 19 ( range 2–76 ) weeks in albendazole group , 39 ( range 2–74 ) weeks in single dose ivermectin group , and 26 ( range 2–74 ) weeks in double doses ivermectin group . Parasitological cure rate were 63 . 3% , 96 . 8% and 93 . 1% in albendazole , single dose oral ivermectin , and double doses of oral ivermectin respectively . No serious adverse event associated with treatment was found in any of the groups . Therefore this study confirms that both a single , and a double dose of oral ivermectin taken two weeks apart , is more effective than a 7-day course of high dose albendazole for patients with chronic infection due to S . stercoralis . | [
"Abstract",
"Introduction",
"Materials",
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] | [
"infectious",
"diseases/neglected",
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] | 2011 | Efficacy and Safety of Single and Double Doses of Ivermectin versus 7-Day High Dose Albendazole for Chronic Strongyloidiasis |
Chronic kidney disease ( CKD ) is an important public health problem with a genetic component . We performed genome-wide association studies in up to 130 , 600 European ancestry participants overall , and stratified for key CKD risk factors . We uncovered 6 new loci in association with estimated glomerular filtration rate ( eGFR ) , the primary clinical measure of CKD , in or near MPPED2 , DDX1 , SLC47A1 , CDK12 , CASP9 , and INO80 . Morpholino knockdown of mpped2 and casp9 in zebrafish embryos revealed podocyte and tubular abnormalities with altered dextran clearance , suggesting a role for these genes in renal function . By providing new insights into genes that regulate renal function , these results could further our understanding of the pathogenesis of CKD .
Chronic kidney disease ( CKD ) affects nearly 10% of the global population [1] , [2] , and its prevalence continues to increase [3] . Reduced estimated glomerular filtration rate ( eGFR ) , the primary measure used to define CKD ( eGFR<60 ml/min/1 . 73 m2 ) [4] , is associated with an increased risk of cardiovascular morbidity and mortality [5] , acute kidney injury [6] , and end stage renal disease ( ESRD ) [6] , [7] . Using genome-wide association studies ( GWAS ) in predominantly population-based cohorts , we and others have previously identified more than 20 genetic loci associated with eGFR and CKD [8]–[11] . Although most of these genetic effects seem largely robust across strata of diabetes or hypertension status [9] , evidence suggests that some of the loci such as the UMOD locus may have heterogeneous effects across these strata [11] . We thus hypothesized that GWAS in study populations stratified by four key CKD risk factors - age , sex , diabetes or hypertension status - may permit the identification of novel eGFR and CKD loci . We carried this out by extending our previous work [9] to a larger discovery sample of 74 , 354 individuals with independent replication in additional 56 , 246 individuals , resulting in a total of 130 , 600 individuals of European ancestry . To assess for potential heterogeneity , we performed separate genome-wide association analyses across strata of CKD risk factors , as well as in a more extreme CKD phenotype .
Meta-analyses of GWAS on the 22 autosomes were performed for: 1 ) eGFR based on serum creatinine ( eGFRcrea ) and CKD ( 6 , 271 cases ) in the overall sample , 2 ) eGFRcrea and CKD stratified by the four risk factors , and 3 ) CKD45 , a more severe CKD phenotype defined as eGFRcrea <45 ml/min/1 . 73 m2 in the overall sample ( 2 , 181 cases ) . For the stratified analyses , in addition to identifying loci that were significant within each stratum , we performed a genome-wide comparison of the effect estimates between strata of the four risk factors . A complete overview of the analysis workflow is given in Figure S1 . All studies participating in the stage 1 discovery and stage 2 replication phases are listed in Tables S1 and S2 . The characteristics of all stage 1 discovery samples by study are reported in Table S3 , and information on study design and genotyping are reported in Table S4 . Results of the eGFRcrea analyses are summarized in the Manhattan and quantile-quantile plots reported in Figures S2 and S3 . A total of 21 SNPs from the discovery stage were carried forward for replication in an independent set of 56 , 246 individuals ( Tables S5 and S6 ) . These SNPs were selected for replication for the following ( Figure S1 ) : 5 reached genome-wide significance in either eGFRcrea overall or stratified analyses , 1 based on a test of direction-consistency of SNP-eGFR associations across the discovery cohorts for eGFRcrea overall , 4 demonstrated a P value≤10−6 and high between-study homogeneity ( I2<25% ) in the CKD45 analysis ( Table S7 ) , and 11 demonstrated between-strata P value≤5×10−5 along with a P value≤5×10−5 for association with eGFRcrea in at least one of the two strata ( Table S8 ) . While none of the loci identified for CKD45 or the test for between-strata difference analyses replicated , all 6 loci identified from the eGFRcrea overall analysis , stratified analyses , and the direction test did ( Table 1 ) . These 6 loci were identified and replicated in the overall analysis ( rs3925584 , located upstream of the MPPED2 gene; rs6431731 near the DDX1 gene ) , in the diabetes-free sub-group ( rs2453580 in an intron of the SLC47A1 gene ) , in the younger age stratum ( rs11078903 in an intron of the CDK12 gene; rs12124078 located near the CASP9 gene ) , and the direction test ( rs2928148 , located in the INO80 gene , see Methods for details ) . In the combined meta-analysis of all 45 studies used in the discovery and replication stages , all six SNPs met the genome-wide significance threshold of 5×10−8 , with individual P values ranging from 4 . 3×10−8 to 8 . 4×10−18 ( Table 1 ) . The imputation quality of these SNPs is reported in Table S9 , and Figure S4 shows the regional association plots for each of the 6 loci . We also confirmed all previously identified renal function loci in the current data ( Table S10 ) . Brief descriptions of the genes included within the 6 new loci uncovered can be found in Table S11 . Forest plots for the associations between the index SNP at each of the 6 novel loci and eGFR across all discovery studies and all strata are presented in Figures S5 and S6 . Most of the 6 new loci had similar associations across strata of CKD risk factors except for the CDK12 locus , which revealed stronger association in the younger ( ≤65 years of age ) as compared to the older age group ( >65 years of age ) . We further examined our findings in 8 , 110 African ancestry participants from the CARe consortium [12] ( Table 2 ) . Not surprisingly , given linkage disequilibrium ( LD ) differences between Europeans and African Americans , none of the 6 lead SNPs uncovered in CKDGen achieved significance in the African American samples . Next , we interrogated the 250 kb flanking regions from the lead SNP at each locus , and showed that 4 of the 6 regions ( MPPED2 , DDX1 , SLC47A1 , and CDK12 ) harbored SNPs that achieved statistical significance after correcting for multiple comparisons based on the genetic structure of each region ( see Methods for details ) . Figure 1 presents the regional association plots for MPPED2 , and Figure S7 presents the plots of the remaining loci in the African American sample . Imputation scores for the lead SNPs can be found in Table S12 . We observed that rs12278026 , upstream of MPPED2 , was associated with eGFRcrea in African Americans ( P value = 5×10−5 , threshold for statistical significance: P value = 0 . 001 ) . While rs12278026 is monomorphic in the CEU population in HapMap , rs3925584 and rs12278026 have a D′ of 1 ( r2 = 0 . 005 ) in the YRI population , suggesting that these SNPs may have arisen from the same ancestral haplotype . We also performed eQTL analyses of our 6 newly identified loci using known databases and a newly created renal eSNP database ( see Methods ) and found that rs12124078 was associated with cis expression of the nearby CASP9 gene in myocytes , which encodes caspase-9 , the third apoptotic activation factor involved in the activation of cell apoptosis , necrosis and inflammation ( P value for the monocyte eSNP of interest = 3 . 7×10−13 ) . In the kidney , caspase-9 may play an important role in the medulla response to hyperosmotic stress [13] and in cadmium-induced toxicity [14] . The other 5 SNPs were not associated with any investigated eQTL . Additional eQTL analyses of 81 kidney biopsies ( Table S13 ) did not reveal further evidence of association with eQTLs ( Table S14 ) . Of the 6 novel loci identified , 2 ( MPPED2 and DDX1 ) were in regions containing only a single gene , and 1 ( CASP9 ) had its expression associated with the locus lead SNP . Thus , to determine the potential involvement of these three genes during zebrafish kidney development , we independently assessed the expression of 4 well-characterized renal markers following morpholino knockdown: pax2a ( global kidney ) [15] , nephrin ( podocyte ) [16] , slc20a1a ( proximal tubule ) [17] , and slc12a3 ( distal tubule ) [17] . While we observed no abnormalities in ddx1 morphants ( Figure S8 ) , mpped2 and casp9 knockdown resulted in expanded pax2a expression in the glomerular region in 90% and 75% of morphant embryos , respectively , compared to 0% in controls ( P value<0 . 0001 for both genes; Figure 2A versus 2F and 2K; 2B versus 2G and 2L; and 2P ) . Significant differences were also observed in expression of the podocyte marker nephrin ( Figure 2C versus 2H and 2M; 80% and 74% abnormalities for mpped2 and casp9 , respectively , versus 0% in controls , P value<0 . 0001 for both genes ) . For mpped2 , no differences were observed in expression of the proximal or distal tubular markers slc20a1a and slc12a3 ( P value = 1 . 0; Figure 2D versus 2I and 2E versus 2J ) . Casp9 morphants and controls showed no differences in proximal tubular marker expression ( Figure 2D versus 2N ) , but abnormalities were observed in distal tubular marker expression in casp9 knockdown embryos ( 30% versus 0%; Figure 2E versus 2O; P value = 0 . 0064 ) . Casp9 morphants displayed diminished clearance of 70 , 000 MW fluorescent dextran 48 hours after injection into the sinus venosus compared to controls , revealing significant functional consequences of casp9 knockdown ( Figure 2Q–2V ) . No clearance abnormalities were observed in mpped2 morphants . The occurrence of abdominal edema is a non-specific finding that is frequently observed in zebrafish embryos with kidney defects . We examined the occurrence of edema in mpped2 and casp9 knockdown embryos at 4 and 6 days post fertilization ( dpf ) , both in the absence and presence of dextran , and observed a significant increase in edema prevalence in casp9 with ( P value<0 . 0001 ) and without ( P value = 0 . 0234 ) dextran challenge but not in mpped2 morphants ( Figure 2W ) . In order to further demonstrate differences in kidney function in response to knockdown of mpped2 and casp9 , we injected the nephrotoxin gentamicin which predictably causes edema in a subset of embryos . Casp9 morphants were more susceptible to developing edema compared to both controls and mpped2 morphants ( Figure 2X ) . In addition , edema developed earlier and was more severe , encompassing a greater area of the entire embryo ( Figure S9 ) . Together , these findings suggest that casp9 and mpped2 knockdowns result in altered kidney gene expression and function . Specifically , abnormal expression of pax2a and nephrin in casp9 morphants in addition to dextran retention and edema formation suggest loss of casp9 impacts glomerular development and function . The lead SNP at the MPPED2 locus is located approximately 100 kb upstream of the gene metallophosphoesterase domain containing 2 ( MPPED2 ) , which is highly evolutionary conserved and encodes a protein with metallophosphoesterase activity [18] . It has been recognized for a role in brain development and tumorigenesis [19] but thus far not for kidney function . To determine whether the association at our newly identified eGFRcrea loci was primarily due to creatinine metabolism or renal function , we compared the relative associations between eGFRcrea and eGFR estimated using cystatin C ( eGFRcys ) ( Figure S10 , File S1 ) . The new loci showed similar effect sizes and consistent effect directions for eGFRcrea and eGFRcys , suggesting a relation to renal function rather than to creatinine metabolism . Placing the results of these 6 loci in context with our previously identified loci [8] , [9] ( 23 known and 6 novel ) , 18 were associated with CKD at a 0 . 05 significance level ( odds ratio , OR , from 1 . 05 to 1 . 26; P values from 3 . 7×10−16 to 0 . 01 ) and 11 with CKD45 ( OR from 1 . 08 to 1 . 34; P values from 1 . 1×10−5 to 0 . 047; Figure S11 and Table S15 ) . When we examined these 29 renal function loci by age group , sex , diabetes and hypertension status ( Tables S16 , S17 , S18 , and S19 ) , we observed consistent associations with eGFRcrea for most loci across all strata , with only two exceptions: UMOD had a stronger association in older individuals ( P value for difference 8 . 4×10−13 ) and in those with hypertension ( P value for difference 0 . 002 ) , and CDK12 was stronger in younger subjects ( P value for difference 0 . 0008 ) . We tested the interaction between age and rs11078903 in one of our largest studies , the ARIC study . The interaction was significant ( P value = 0 . 0047 ) and direction consistent with the observed between-strata difference . Finally , we tested for associations between our 6 new loci and CKD related traits . The new loci were not associated with urinary albumin-to-creatinine ratio ( UACR ) or microalbuminuria [20] ( Tables S20 and S21 ) , with blood pressure from the ICBP Consortium [21] ( Table S22 ) or with myocardial infarction from the CARDIoGRAM Consortium [22] ( Table S23 ) .
We have extended prior knowledge of common genetic variants for kidney function [8]–[11] , [23] by performing genome-wide association tests within strata of key CKD risk factors , including age , sex , diabetes , and hypertension , thus uncovering 6 loci not previously known to be associated with renal function in population-based studies ( MPPED2 , DDX1 , CASP9 , SLC47A1 , CDK12 , INO80 ) . In contrast to our prior genome-wide analysis [8] , [9] , the majority of the new loci uncovered in the present analysis have little known prior associations with renal function . This highlights a continued benefit of the GWAS approach by using large sample sizes to infer new biology . Despite our hypothesis that genetic effects are modified by CKD risk factors , most of the identified variants did not exhibit strong cross-strata differences . This highlights that many genetic associations with kidney function may be shared across risk factor strata . The association of several of these loci with kidney function in African Americans underscores the generalizability of identified renal loci across ethnicities . Zebrafish knockdown of mpped2 resulted in abnormal podocyte anatomy as assessed by expression of glomerular markers , and loss of casp9 led to altered podocyte and distal tubular marker expression , decreased dextran clearance , edema , and enhanced susceptibility to gentamicin-induced kidney damage . These findings demonstrate the potential importance of these genes with respect to renal function and illustrate that zebrafish are a useful in vivo model to explore the functional consequences of GWAS-identified genes . Despite these strengths , there are some limitations of our study that warrant discussion . Although we used cystatin C to separate creatinine metabolism from true filtration loci , SNPs within the cystatin C gene cluster have been shown to be associated with cystatin C levels [8] , which might result in some degree of misclassification in absolute levels . While we used standard definitions of diabetes and hypertension in the setting of population-based studies , these may differ from those definitions used in clinical practice . In addition , we were unable to differentiate the use of anti-hypertension medications from other clinical indications of these agents or type 1 from type 2 diabetes . The absence of association between our six newly discovered SNPs and the urinary albumin to creatinine ratio , blood pressure , and cardiovascular disease may have resulted from disparate genetic underpinnings of these traits , the overall small effect sizes , or the cross-sectional nature of our explorations; and we were unable to differentiate between these potential issues . Finally , power was modest to detect between-strata heterogeneity . With increased sample size and stratified analyses , we have identified additional loci for kidney function that continue to have novel biological implications . Our primary findings suggest that there is substantial generalizability of SNPs associations across strata of important CKD risk factors , specifically with hypertension and diabetes .
Serum creatinine and cystatin C were measured as detailed in Tables S1 and S2 . To account for between-laboratory variation , serum creatinine was calibrated to the US nationally representative National Health and Nutrition Examination Study ( NHANES ) standards in all discovery and replication studies as described previously [8] , [24] , [25] . GFR based on serum creatinine ( eGFRcrea ) was estimated using the four-variable MDRD Study equation [26] . GFR based on cystatin C ( eGFRcys ) was estimated as eGFRcys = 76 . 7× ( serum cystatin C ) −1 . 19 [27] . eGFRcrea and eGFRcys values<15 ml/min/1 . 73 m2 were set to 15 , and those >200 were set to 200 ml/min/1 . 73 m2 . CKD was defined as eGFRcrea <60 ml/min/1 . 73 m2 according to the National Kidney Foundation guidelines [28] . A more severe CKD phenotype , CKD45 , was defined as eGFRcrea <45 ml/min/1 . 73 m2 . Control individuals for both CKD and CKD45 analyses were defined as those with eGFRcrea >60 ml/min/1 . 73 m2 . In discovery and replication cohorts , diabetes was defined as fasting glucose ≥126 mg/dl , pharmacologic treatment for diabetes , or by self-report . Hypertension was defined as systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg or pharmacologic treatment for hypertension . Genotyping was conducted as specified in Table S4 . After applying quality-control filters to exclude low-quality SNPs or samples , each study imputed up to ∼2 . 5 million HapMap-II SNPs , based on the CEU reference samples . Imputed genotypes were coded as the estimated number of copies of a specified allele ( allelic dosage ) . Additional , study-specific details can be found in Table S1 . A schematic view of our complete analysis workflow is presented in Figure S1 . Using data from 26 population-based studies of individuals of European ancestry , we performed GWA analyses of the following phenotypes: 1 ) loge ( eGFRcrea ) , loge ( eGFRcys ) , CKD , and CKD45 overall and 2 ) loge ( eGFRcrea ) and CKD stratified by diabetes status , hypertension status , age group ( ≤/>65 years ) , and sex . GWAS of loge ( eGFRcrea ) and loge ( eGFRcys ) were based on linear regression . GWAS of CKD and CKD45 were performed in studies with at least 25 cases ( i . e . all 26 studies for CKD and 11 studies for CKD45 ) and were based on logistic regression . Additive genetic effects were assumed and models were adjusted for age and , where applicable , for sex , study site and principal components . Imputation uncertainty was accounted for by including allelic dosages in the model . Where necessary , relatedness was modeled with appropriate methods ( see Table S1 for study-specific details ) . Before including in the meta-analysis , all GWA data files underwent to a careful quality control , performed using the GWAtoolbox package in R ( www . eurac . edu/GWAtoolbox . html ) [29] . Meta-analyses of study-specific SNP-association results , assuming fixed effects and using inverse-variance weighting , i . e . : the pooled effect is estimated as , where is the effect of the SNP on the outcome in the ith study , K is the number of studies , and is the weight given to the ith study . The meta-analyses were performed using METAL [30] , with genomic control correction applied across all imputed SNPs [31] if the inflation factor λ>1 at both the individual study level and after the meta-analysis . SNPs with minor allele frequency ( MAF ) <1% were excluded . All SNPs with a meta-analysis P value≤5×10−8 for any trait or any stratum were deemed genome-wide significant [32] . In the eGFRcrea analyses , after excluding loci that were previously reported [8] , [9] , we selected for replication all SNPs with P value<5×10−8 in any trait or stratum that were independent ( defined by pairwise r2<0 . 2 ) , in the primary association analysis . This yielded five SNPs in five independent loci . The same criterion was applied to the CKD analysis , where no SNPs passed the selection threshold . Given the smaller number of cases with severe CKD resulting in less statistical power , a different selection strategy was adopted for the CKD45 analysis: selected for replication were SNPs with discovery P value≤5×10−6 , MAF≥5% , and homogeneous effect size across studies ( I2≤25% ) . Four additional SNPs were thereby selected for replication from the CKD45 analysis . In addition to identifying SNPs for replication based on the genome-wide significance threshold from a fixed effect model meta-analysis , we performed a “direction test” to identify additional SNPs for which between-study heterogeneity in effect size might have obscured the overall association that was nevertheless highly consistent in the direction of allelic effects . Under the null hypothesis of no association , the a priori probability that a given effect allele of a SNP has either a positive or negative association with eGFRcrea is 0 . 5 . Because the meta-analysis includes independent studies , the number of concordant effect directions follows a binomial distribution . Therefore , we tested whether the number of discovery cohorts with the same sign of association ( i . e . direction of effect ) was greater than expected by chance given the binomial distribution and a null expectation of equal numbers of associations with positive and negative sign . The test was only applied for eGFRcrea in the overall analysis . Multiple testing was controlled by applying the same P value threshold of 5×10−8 as in the overall GWAS . Given that no SNP met this criterion , we selected for replication one novel SNP with the lowest P value of 4 . 0×10−7 . Based on the results of the stratified GWAS of eGFRcrea and CKD , for each SNP we tested the hypothesis whether the effect of a SNP on eGFRcrea or CKD was the same between strata ( null hypothesis ) , i . e . diabetes versus non-diabetes subjects , hypertensive versus normotensive , younger versus older , females versus males . We used a two-sample test defined as Z = ( b1−b2 ) / ( SE ( b1 ) 2+SE ( b2 ) 2 ) 0 . 5 , with b1 and b2 indicating the effect estimates in the two strata and SE ( b1 ) and SE ( b2 ) their standard errors [33] . For large samples , the test statistic follows a standard normal distribution . SNPs were selected for replication if they had a between-stratum difference P value≤5×10−5 , an association P value≤5×10−5 in one of the two strata , and MAF≥10% . Independent loci were defined using the same criteria as described above . Eleven further SNPs , one per locus , were selected for replication from the between-strata difference test . Replication was performed for a total of 21 SNPs including 5 from the overall and stratified eGFRcrea analyses , 1 from the direction test on eGFRcrea , 4 from the overall CKD45 analysis , and 11 from the between-strata difference test . Replication studies used the same phenotype definition , and had available genotypes from imputed in silico genome-wide SNP data or de novo genotyping . The same association analyses including the identical stratifications were performed as in discovery studies . Details can be found in the Tables S2 , S5 and S6 . Study-specific replication results for the selected SNPs were combined using the same meta-analysis approach and software as in the discovery stage . One-sided P values were derived with regard to the effect direction found in the discovery stage . Based on the P value distribution of all SNPs submitted for replication ( the 10 from eGFRcrea and CKD45 and the 11 from the between strata difference test ) , we estimated the False Discovery Rate as a q-value using the QVALUE [34] package in R . SNPs with q-value<0 . 05 were called significantly replicating , thus specifying a list of associations expected to include not more than 5% false positives . Finally , study-specific results from both the discovery and replication stage were combined in a joint inverse-variance weighted fixed-effect meta-analysis and the two-sided P values were compared to the genome-wide significance threshold of 5×10−8 to test whether a SNP was genome-wide significant . Between-study heterogeneity of replicated SNPs was quantified by the I2 statistic [35] . For de novo genotyping in 10 , 446 samples from KORA F3 , KORA F4 , SAPHIR and SAPALDIA , the MassARRAY system at the Helmholtz Zentrum ( München , Germany ) was used , using Assay Design v3 . 1 . 2 and the iPLEX chemistry ( Sequenom , San Diego , USA ) . Assay design failed for rs1322199 and genotyping was not performed . Ten percent of the spectra were checked by two independent , trained persons , and 100% concordance between investigators was obtained . SNPs with a P value<0 . 001 when testing for Hardy-Weinberg equilibrium ( rs10490130 , rs10068737 , rs11078903 ) , SNPs with call rate <90% ( rs500456 in KORA F4 only ) or monomorphic SNPs ( rs2928148 ) were excluded from analyses without attempting further genotyping . The call rates of rs4149333 and rs752805 were near 0% on the MassARRAY system . These SNPs were thus genotyped on a 7900HT Fast Real-Time PCR System ( Applied Biosystems , Foster City , USA ) . Mean call rate across all studies and SNPs ranged from 96 . 8% ( KORA F4 ) to 99% ( SAPHIR ) . Duplicate genotyping was performed in at least 14% of the subjects in each study with a concordance of 95–100% ( median 100% ) . In the Ogliastra Genetic Park Replication Study ( n = 3000 ) de novo genotyping was conducted on a 7900HT Fast Real-Time PCR System ( Applied Biosystems , Foster City , USA ) , with a mean call rate of 99 . 4% and 100% concordance of SNPs genotyped in duplicate . Twenty-nine SNPs , including the 6 novel loci reported in the current manuscript along with 23 previously confirmed to be associated with renal function [9] , were tested for differential effects between the strata . The same Z statistics as described for discovery ( above ) was used and the Bonferroni-adjusted significance level was set to 0 . 10/29 = 0 . 003 . SNP-by-age interaction , for the one SNP showing significantly different effects between strata of age , was tested in the ARIC study by fitting a linear model on log ( eGFRcrea ) adjusted for sex , recruitment site , the first and the seventh genetic principal components ( only these two were associated with the outcome at P value<0 . 05 ) . Both the interaction term and the terms for the main effects of age and the SNP were included in the model . To assess genome-wide between-strata differences , with alpha = 5×10−8 and power = 80% , the maximum detectable difference was 0 . 025 when comparing nonDM versus DM and 0 . 015 when comparing nonHTN versus HTN . Similarly , when testing for between-strata differences the 29 known and new loci ( Bonferroni-corrected alpha = 0 . 003 ) in the combined sample ( n = ∼125 , 000 in nonDM and n = ∼13 , 000 in DM ) we had 80% power to detect differences as large as 0 . 035 . For each of the 6 lead SNPs identified in our European ancestry samples , we extracted eGFR association statistics from a genome-wide study in the CARe African ancestry consortium [12] . We further investigated potential allelic heterogeneity across ethnicities by examining the 250 kb flanking region surrounding each lead SNP to determine whether other SNPs with stronger associations exist in each region . A SNP with the smallest association P value with MAF>0 . 03 was considered the top SNP in the African ancestry sample . We defined statistical significance of the identified lead SNP in African ancestry individuals based on a region-specific Bonferroni correction . The number of independent SNPs was determined based on the variance inflation factor ( VIF ) with a recursive calculation within a sliding window of 50 SNPs and pairwise r2 of 0 . 2 . These analyses were performed using PLINK . For each replicating SNP , we obtained association results for urinary albumin-to-creatinine ratio and microalbuminuria from our previous genome-wide association analysis [20] , and for blood pressure and myocardial infarction from genome-wide association analysis from the ICBP [21] and CARDIoGRAM [22] consortia , respectively . Significant renal SNPs were searched against a database of expression SNPs ( eSNP ) including the following tissues: fresh lymphocytes [36] , fresh leukocytes [37] , leukocyte samples in individuals with Celiac disease [38] , lymphoblastoid cell lines ( LCL ) derived from asthmatic children [39] , HapMap LCL from 3 populations [40] , a separate study on HapMap CEU LCL [41] , peripheral blood monocytes [42] , [43] , adipose [44] , [45] and blood samples [44] , 2 studies on brain cortex [42] , [46] , 3 large studies of brain regions including prefrontal cortex , visual cortex and cerebellum ( Emilsson , personal communication ) , liver [45] , [47] , osteoblasts [48] , skin [49] and additional fibroblast , T cell and LCL samples [50] . The collected eSNP results met criteria for statistical significance for association with gene transcript levels as described in the original papers . A second expression analysis of 81 biopsies from normal kidney cortex samples was performed as described previously [51] , [52] . Genotyping was performed using Affymetrix 6 . 0 Genome-wide chip and called with GTC Software ( Affymetrix ) . For eQTL analyses , expression probes ( Affymetrix U133set ) were linked to SNP probes with >90% call-rate using RefSeq annotation ( Affymetrix build a30 ) . P values for eQTLs were calculated using linear multivariable regression in both cohorts and then combined using Fisher's combined probability test ( see also [52] ) . Pairwise LD was calculated using SNAP [53] on the CEU HapMap release 22 . Zebrafish were maintained according to established IACUC protocols . Briefly , we injected zebrafish embryos with newly designed ( mpped2 , ddx1 ) or previously validated ( casp9 [54] ) morpholino antisense oligonucleotides ( MO , GeneTools , Philomath OR ) at the one-cell stage at various doses . We fixed embryos in 4% PFA at the appropriate stages for in situ hybridization ( http://zfin . org/ZFIN/Methods/ThisseProtocol . html ) . Different anatomic regions of the kidney were visualized using a panel of 4 established markers: pax2a ( global kidney marker ) [15] , nephrin ( podocyte marker ) [16] , slc20a1a ( proximal tubule ) [17] , and slc12a3 ( distal tubule marker ) [17] . Abnormalities in gene expression were independently scored by two investigators . We compared the number of abnormal morphant embryos to control embryos , injected with a standard control MO designed by GeneTools , with the Fisher's exact test , at the Bonferroni-corrected significance level of 0 . 0125 , i . e . : 0 . 05/4 markers . We documented the development of gross edema at 4 and 6 days post-fertilization in live embryos . We performed dextran clearance experiments following previously described protocols [55] . Briefly , 80 hours after MO injection , we anesthetized embryos in 4 mg/ml Tricaine in embryo water ( 1∶20 dilution ) , then positioned embryos on their back in a 1% agarose injection mold . We injected an equal volume of tetramethylrhodamine dextran ( 70 , 000 MW; Invitrogen ) into the cardiac sinus venosus of each embryo . We then returned the embryos to fresh embryo water . Using fluorescence microscopy , we imaged the embryos at 2 hours post-injection ( 82 hpf ) to demonstrate equal loading , then at 48 hours post-injection ( 128 hpf ) to evaluate dextran clearance . Embryos were injected with control , mpped2 , or casp9 MOs at the one-cell stage . At 48 hpf , embryos were manually dechorionated , anesthetized in a 1∶20 dilution of 4 mg/ml Tricaine in embryo water , and oriented on a 1% agarose injection mold . As previously described [56] , embryos were injected with equal volumes of 10 mg/ml gentamicin ( Sigma ) in the cardiac sinus venosus , returned to fresh embryo water , and subsequently scored for edema ( prevalence , time of onset ) over the next 3 days . | Chronic kidney disease ( CKD ) is an important public health problem with a hereditary component . We performed a new genome-wide association study in up to 130 , 600 European ancestry individuals to identify genes that may influence kidney function , specifically genes that may influence kidney function differently depending on sex , age , hypertension , and diabetes status of individuals . We uncovered 6 new loci associated with estimated glomerular filtration rate ( eGFR ) , the primary measure of renal function , in or near MPPED2 , DDX1 , SLC47A1 , CDK12 , CASP9 , and INO80 . CDK12 effect was stronger in younger and absent in older individuals . MPPED2 , DDX1 , SLC47A1 , and CDK12 loci were associated with eGFR in African ancestry samples as well , highlighting the cross-ethnicity validity of our findings . Using the zebrafish model , we performed morpholino knockdown of mpped2 and casp9 in zebrafish embryos and revealed podocyte and tubular abnormalities with altered dextran clearance , suggesting a role for these genes in renal function . These results further our understanding of the pathogenesis of CKD and provide insights into potential novel mechanisms of disease . | [
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] | 2012 | Genome-Wide Association and Functional Follow-Up Reveals New Loci for Kidney Function |
The structural mechanisms by which receptor tyrosine kinases ( RTKs ) regulate catalytic activity are diverse and often based on subtle changes in conformational dynamics . The regulatory mechanism of one such RTK , fibroblast growth factor receptor 2 ( FGFR2 ) kinase , is still unknown , as the numerous crystal structures of the unphosphorylated and phosphorylated forms of the kinase domains show no apparent structural change that could explain how phosphorylation could enable catalytic activity . In this study , we use several enhanced sampling molecular dynamics ( MD ) methods to elucidate the structural changes to the kinase’s activation loop that occur upon phosphorylation . We show that phosphorylation favors inward motion of Arg664 , while simultaneously favoring outward motion of Leu665 and Pro666 . The latter structural change enables the substrate to bind leading to its resultant phosphorylation . Inward motion of Arg664 allows it to interact with the γ-phosphate of ATP as well as the substrate tyrosine . We show that this stabilizes the tyrosine and primes it for the catalytic phosphotransfer , and it may lower the activation barrier of the phosphotransfer reaction . Our work demonstrates the value of including dynamic information gleaned from computer simulation in deciphering RTK regulatory function .
Receptor tyrosine kinases ( RTKs ) occupy a central role in cellular regulation , acting as intermediaries in relaying signals from extracellular ligands to major signaling pathways in the cell [1–3] . Although the structural elements of RTKs are well-conserved [4] , their functions are widely divergent . This is due to the subtle differences in the sequences and dynamic properties of structural elements underlying kinase activity [5] . The similarities between the various RTKs combined with their divergent behaviors presents a unique challenge in designing drugs to target specific RTKs whose constitutive activity has pathologic consequences , without generating off-target effects caused by reduced activity of other kinases [6 , 7] . This endeavor has had profound successes [8] but still requires additional effort , particularly with regard to filling the gaps in our structural knowledge of these proteins . RTKs , like all kinases , have an N-lobe and C-lobe , with the active site generally in the pocket buried between them [4 , 9] . In order to avoid pathologic constitutive activity , RTKs have several autoinhibitory mechanisms in place that prevent the substrate from accessing the active site or prevent the phosphotransfer from taking place [10–13] . Some of these regulatory mechanisms involve the extracellular , transmembrane or juxtamembrane domains of the kinase preventing association of two kinase domains and their resultant autophosphorylation . Other mechanisms are contained within the kinase domain itself and involve regulatory regions whose dynamics may either favor or disfavor catalytic activity . One regulatory region is the nucleotide-binding loop , often referred to as the P-loop , at the tip of the N-lobe near the active site , that binds the ATP molecule that donates a phosphate group to the substrate [4 , 9] . A second regulatory region is the αC helix that makes contact with the activation loop and often undergoes large movements to form the catalytically active state of the kinase . A third regulatory region , which is usually post-translationally modified to alter its regulatory behavior , is the activation loop . The activation loop usually contains one or multiple tyrosine residues that are available to be phosphorylated by other enzymes or , in many cases , autophosphorylated . This phosphorylation leads to altered dynamics of the activation loop residues resulting in greater catalytic activity of the kinase [14–17] . The fibroblast growth factor receptors ( FGFRs ) are a superfamily of RTKs that activate the MAP kinase and PI3 kinase pathways [18 , 19] . Binding of an activator of the fibroblast growth factor family in concert with heparan sulfate stabilizes the dimerization of two receptors’ extracellular domains , leading in turn to the apposition of the receptors’ intracellular kinase domains . As in other RTKs , the kinase domain contains an activation loop with two adjacent tyrosine residues . Apposition of the kinase domains enables the activation loops to undergo trans-autophosphorylation , rendering the kinases catalytically active and able to perform phosphorylation of tyrosine residues in FGFR kinase substrates including PLC-γ [20–22] and additional sites on FGFR kinases [23–25] . In this work , we focus on the FGFR2 kinase , for which a wealth of experimental structural information is available , including crystal structures of the wild type kinase [25 , 26] , of mutant kinases [15 , 26 , 27] , and NMR chemical shift data [15] . Previous work suggests that the FGFR2 kinase activation loop toggles between two states , inactive and active , and that mutation of activation loop residues can perturb the balance between these two states to increase the time that the kinase is in the activated state , even without phosphorylation [15] . Crystal structures illustrate several structural changes that occur when FGFR2 kinase is activated . These include rearrangement of the activation loop , a small rotation of the N-lobe toward the C-lobe , and dissolution of a network of hydrogen bonds between side chains in a triad of residues known as the “molecular brake” [26 , 28] . Genomic point mutations in the activation loop , the αC helix , or the molecular brake in utero frequently lead to developmental disorders [26 , 29–31] , while somatic mutations may lead to cancer [29 , 30 , 32] . Surprisingly , in contrast to most RTKs , there is little apparent motion of the αC helix in the FGFR kinases upon activation , with crystal structures showing that the helix moves together with the rest of the N-lobe . This suggests that the bulk of structural change in the activated kinase is concentrated in the activation loop structure . Thus it is especially crucial to investigate the details of activation loop rearrangement in order to understand FGFR2 kinase function . Despite the many crystal structures of FGFR2 [33] , a mechanism to explain how phosphorylation of the activation loop residues leads to catalytic activity has not yet surfaced . In FGFR1 , the activation loop residues Arg661 and Pro663 block the active site in the inactive structure , but in the active structure change conformation to allow a substrate to bind [11] . This led to the hypothesis that phosphorylation of the activation loop alters its structure to move these two residues away from the active site , allowing substrate phosphorylation . However , neither the inactive nor the active crystal structure of FGFR2 ( PDBs 2PSQ and 2PVF , respectively [26] ) shows any activation loop residues in the active site . In this study , we use molecular dynamics ( MD ) simulation to probe the dynamics of FGFR2 kinase and propose a mechanism to explain the regulatory role of activation loop phosphorylation .
In order to visualize the process by which the inactive structure of the activation loop undergoes conformational transition ( s ) into the active structure , we used the string method in collective variables [34] . The string method finds the minimum free energy path ( MFEP ) connecting two states at the end points , in this case the inactive and active structures of the kinase . The MFEP is the most likely pathway that the system will use to transition from the inactive structure to the active structure [35] . As collective variables , we used the Cα atoms of the activation loop residues and the αC helix , as well as important activation loop side chain atoms , as described in Methods . In addition , we included the Nδ2 atom of Asn549 and the Cδ atom of Glu565 , as these two atoms are part of the network of hydrogen bonds termed the “molecular brake , ” which has been proposed to play a regulatory role in FGFR2 kinase activation [26] . The resultant MFEP demonstrates that the activation loop backbone structure changes in four steps ( Fig 1 ) . In step ( 1 ) , residues 660 through 663 move closer to the αC helix and the kinase’s N-lobe . Concurrently , the αC helix moves closer to the C-lobe . This apparently facilitates the formation of hydrogen bonds between the Nζ atom of Lys526 in the αC helix and the hydroxyl groups of Thr660 and Thr661 . In step ( 2 ) , the Ile654 side chain moves away from Arg649 , clearing space for the side chain of pTyr657 . This motion is accompanied by the sliding of the pTyr656 and pTyr657 backbone along the loop connecting the αEF and αF helices . In step ( 3 ) , the pTyr656-pTyr657 backbone rotates to form the short antiparallel β-hairpin with Val679 and Tyr680 seen in the active crystal structure . This rotation accommodates two important sidechain motions , namely the inward migration of pTyr657 and Lys659 , which allow for the formation of the network of hydrogen bonds in the active structure of FGFR2 kinase . Finally , in step ( 4 ) , residues 660 through 663 move outward . The major sidechain motion involved in the activation pathway is the inward motion of pTyr657 to make contact with Arg649 , Arg625 and Lys659 . However , we observed another important sidechain motion that occurs during the activation process , namely the motion of Arg664 toward ATP ( Fig 2A ) . In the inactive conformation , and in the first 19 frames of the activation process , Arg664 points outward or makes contact with Glu527 , enabled by proximity of the αC helix to the activation loop facilitated by the backbone motion of step ( 1 ) . In the active conformation , however , Arg664 makes contact with the γ-phosphate of ATP stabilizing its position . We observed that the simulated motion of Arg664 toward ATP is synchronous with the motion of pTyr657 toward Arg649 ( Fig 2B ) . Additionally , the dissolution of the hydrogen bond between Asn549 and Glu665 , part of the regulatory “molecular brake” thought to prevent autoactivation of the kinase [26] , occurs one frame after motion of pTyr657 ( Fig 2C ) . This suggests that these two conformational changes might be structurally related as well , although a structural mechanism for this coupling is not readily apparent from this simulation study . In order to test our results , we performed the same algorithm but with an alternate set of CVs based on interatomic distances , discussed further in S1 Text . We calculated the free energy as a function of the collective variables chosen in this string method study [34] . The plot of the potential of mean force ( PMF ) along the activation pathway indicates that there are two free energy wells corresponding to the inactive and active conformations ( Fig 2D ) . The activation barrier occurs at frame 21 , the same frame during which pTyr657 rotates inward and Arg664 approaches ATP , confirming that these two structural changes define the inactive and active states . In order to pinpoint general features of inactive and active conformations of the activation loop , without reference to a particular pathway , we ran a metadynamics simulation [36] . This generated a large pool of conformations similar to the inactive and active crystal structures as well as intermediate or related conformations . This used two contact map collective variables as the basis of the metadynamics simulations . Essentially , each collective variable corresponds to the number of interatomic contacts in the activation loop that are similar to contacts in the inactive or active structures , respectively; more details are discussed in Methods . The metadynamics simulation trajectories confirm the presence of two large free energy wells , roughly corresponding to inactive and active conformations of the protein ( Fig 3A ) . The simulation was run for a long enough time to generate a large number of stable conformations with significantly divergent activation loop structures ( see S1 Fig ) , rather than until convergence of the free energy landscape , which would likely have required unrealistic amounts of simulation time . Clustering of the resulting pool of conformations based on a hierarchical agglomerative clustering scheme produced a final set of clusters in which no two conformations in any cluster were more than 3 . 0 Å apart , measured by RMSD of the activation loop backbone Cα atoms . This resulted in a total of 56 clusters . We then connected clusters whose conformations were no more than 3 . 8 Å apart ( Fig 3B ) . We observed that eight of the 56 clusters represented “active” conformations , in which pTyr657 was rotated inward and made contact with Arg649 , Arg625 and Lys659 . In each of these clusters , two features were notable at the kinase’s active site ( Fig 3D ) . First , the sidechains of Leu665 and Pro666 were rotated away from the active site . It is reasonable to conclude that this orientation of these side chains is necessary to allow catalysis because it enables the substrate tyrosine to insert near ATP and the presumed catalytic base , Asp626 . A similar observation was made with regard to FGFR1 , for which rearrangement of the activation loop prevents Arg661 and Pro663 from blocking the active site [11] . Second , in all eight of these clusters , Arg664 was pointed inward and made contact with the γ-phosphate of ATP , confirming that formation of this contact links with the inward motion of pTyr657 . An additional 11 out of 56 clusters featured both of these structural changes at the active site , namely Arg664 pointing into the active site and Leu665 and Pro666 pointing out of the active site . In these clusters , however , pTyr657 does not point inward to make contact with Arg649 . Despite this , the backbone conformations of these clusters strongly resemble those of the eight clusters in which pTyr657 points inward . The average graph distance between each of these 11 clusters ( active site ready , pTyr657-out ) and the nearest pTyr657-in cluster is 2 . 4 Å , compared to 2 . 9 Å for all pTyr657-out clusters . This suggests that the backbone conformation common to both groups of clusters enables both Arg664 to point inward , and Leu665 and Pro666 to point outward from the ATP site . In turn , inward rotation of pTyr657 , and the subsequent formation of contacts between pTyr657 and Arg649 , Arg625 , and Lys659 , stabilizes this backbone conformation in order to preserve the catalytically permissive conformation of the activation loop near the active site . We examined the collective variable values for conformations in each of the three groups of clusters—active conformations , conformations with the pre-catalytic active site and the active-like backbone , and inactive conformations ( Fig 3C ) . Notably , conformations with the active-like backbone form one of the smaller free energy wells ( inside the brown dotted outline in Fig 3A ) comprising the large free energy well corresponding to the inactive state . This free energy well is adjacent in CV space to the free energy well corresponding to the active state , suggesting that the active-like backbone structures are in an intermediate state between the fully inactive state and the active state . The phosphorylation of pTyr657 in the activation loop shifts the conformational dynamics of the loop to favor motion of Arg664 toward ATP in this simulation . We performed NMR experiments to examine the effect of activation phosphorylation on loop dynamics , by monitoring the chemical shift of the Arg664 HSQC cross-peak ( Fig 4 ) . When ATP was added to the unphosphorylated FGFR2 kinase , a chemical shift perturbation was seen for the Arg664 peak , indicating that the presence of ATP altered the chemical environment of Arg664 . We attribute this to the Arg664 residue in fast exchange between the outward-pointing conformation and the inward-pointing conformation . As indicated by our simulations , the presence of ATP changes the distribution through electrostatic interactions with the Arg664 side chain . However , when ATP was added to the phosphorylated FGFR2 kinase , a larger chemical shift perturbation was seen for the Arg664 peak . HSQC peaks for R664 in spectra of the apo kinases ( ATP-free phosphorylated and unphosphorylated ) are similar , and the observed chemical shift perturbations in the ATP-bound samples lie along a straight line . These shift perturbations reflect change in the population between two endpoints [15] . The greater magnitude of the perturbation for the phosphorylated kinase is consistent with the simulation , with phosphorylation of the activation loop altering loop dynamics to enable greater interaction between the Arg664 guanidinium moiety and ATP . Conformations featuring an inward-pointing pTyr657 also show Arg664 in the active site in simulation , raising the likelihood that Arg664 is involved in mediating FGFR2 kinase activity . To test this , we generated two mutants of FGFR2 kinase , R664A and R664W . Kinetic assays were performed on the wild-type kinase and on each of these mutants ( Fig 5 ) . These assays showed that mutation of Arg664 to alanine or tryptophan caused a 52% and 60% decrease in autophosphorylation activity , respectively . Neither mutation has been demonstrated to definitively cause any pathology , but the R664W mutation has been found in a human colorectal tumor specimen [37] , and bioinformatics analysis suggests that the mutation is highly deleterious to the protein’s function [37 , 38] . Both mutations abolish the interaction between Arg664 and ATP , thus apparently reducing with the kinase’s catalytic activity . The remaining unanswered question is precisely what role Arg664 plays in FGFR2 kinase catalytic activity . A previous crystallographic study of an FGFR3 mutant [24] also showed the homologous residue Arg655 in a similar position near the kinase’s active site , interacting with the γ-phosphate . The authors of that study proposed that the arginine residue stabilizes the position of the substrate tyrosine residue via π-cation interactions . To investigate this possibility in FGFR2 kinase , we performed MD simulations of FGFR2 kinase with a substrate peptide bound at the active site . Two simulations were performed , one simulation in which Arg664 was kept in the active site using a one-sided harmonic restraint , and another in which Arg664 was kept out of the active site using a one-sided harmonic restraint . The simulations showed that the positioning of the substrate tyrosine was indeed stabilized by the presence of Arg664 ( S1 Movie ) . The tyrosine residue is neatly sandwiched by two arginine residues , Arg664 and Arg630 . We observed that the root-mean-square fluctuations of the substrate tyrosine as well as of the ATP residue are higher for the simulation in which Arg664 was outside the active site ( Fig 6 ) . We also performed a third simulation with a restraint confining Arg664 to interact with Asp530 , thus being close to the active site but not fully inside , as seen in several crystal structures [15 , 26 , 27 , 39] . This simulation demonstrated an intermediate degree of substrate tyrosine confinement , though the ATP thermal motion was similar to that seen in the Arg664-out simulation ( Fig 6 ) . To investigate whether Arg664 plays a role in the phosphotransfer reaction , we performed a series of QM/MM calculations in which the system transitioned from the reactant to the product state . At each step , the ESP-derived partial charges of the QM region atoms were calculated . The charges of the migrating phosphate group , the two Mg2+ ions , and the atoms of the guanidinium moiety are shown in Fig 7 . As the phosphate group migrates toward the substrate tyrosine , its total charge and the charges of each individual phosphate oxygen become more positive , while the charges of the Mg2+ ions and protons of the guanidinium moiety of Arg664 become more negative . This is in accordance with our hypothesis that Arg664 , like Mg2+ , enables the progress of the phosphotransfer reaction by stabilizing the electron density of the phosphate group . More extensive QM/MM calculations are still needed to further explore the role of Arg664 on the phosphotransfer reaction .
Our work demonstrates that phosphorylation of the activation loop tyrosine residues alters FGFR2 kinase dynamics , allowing both the entry of the substrate tyrosine , and repositioning of Arg664 in the active site , and leading to facilitation of the catalytic reaction . Although there are numerous crystal structures of FGFR2 kinase , it has not been possible to infer mechanistic detail thus far because the static structures captured by X-ray crystallography do not encompass dynamic motions of the activation loop . For example , in one structure , the Arg664 side chain was not fully resolved ( PDB 3CLY ) [25] , while in others its position appears to be influenced by the presence of ammonium sulfate ( PDB 2PZP [26] and 1GJO [39] ) , and/or seen to form contacts with Asp530 ( PDB 4J95 , 4J96 , 4J97 , 4J98 , 2PVY , 2PWL , 2PY3 , 2PZ5 , 2PZP , 2PZR , 2Q0B , 3B2T , 1OEC ) [15 , 26 , 27 , 39] , as we observed in intermediate structures in the string method trajectory . The position of Arg664 seen in our simulations was observed previously in a crystal structure of the highly homologous FGFR3 kinase ( PDB 4k33 ) [24] , but not previously in FGFR2 kinase . Quite recently , after our simulations were completed , a crystal structure of FGFR2 kinase in complex with PLC-γ has been published showing Arg664 in contact with ATP and Leu665 and Pro666 facing outward [40] . Using string method and metadynamics simulations , we have found that this conformation is stabilized specifically by phosphorylation of the tyrosine residues in the activation loop . Moreover , MD simulations and kinase activity assays illustrate the functional role of Arg664 in kinase activity . Our results illustrate the need to complement these valuable crystal structures with dynamic information gleaned from simulation studies . The pathway generated by the string method algorithm may also reveal several important features of FGFR2 kinase activation . Notably , the first step in the MFEP is the motion of residues 660 to 663 and the αC helix toward one another . This proximity enables hydrogen bonds to form between Lys526 and the hydroxyl and backbone carbonyl groups of Thr660 and Thr661 . The importance of this motion in the pathway and its resultant proximity between the activation loop and the αC helix may contribute to the stable positioning of the substrate tyrosine . The role of the Lys526 residue has been established in studies demonstrating the significant gain of function caused by the K526E mutation responsible for Crouzon syndrome [26] . In this mutant , the Glu526 residue would be unable to form hydrogen bonds with Thr660 and Thr661 . However , the K526E mutant can enhance catalytic activity through a similar mechanism to the wild-type , by formation of hydrogen bonds between the αC helix and activation loop . Glu526 can form hydrogen bonds with Arg664 , reminiscent of contacts in the wild-type structure between Arg664 and Asp530 . As our simulations indicate , the presence of Arg664 near the αC helix contributes to stability of the substrate tyrosine’s position , so the K526E mutant is likely to support this activating mechanism as well . Previous studies indicated that the K526E mutant significantly increases catalytic activity in both the unphosphorylated and phosphorylated state [26] . Since we hypothesize that in the phosphorylated state , Arg664 favors interaction with ATP , we propose that the K526E mutant favors Arg664 interacting with Glu526 predominantly when the phosphotyrosine residues are pointed outward , not interacting with Arg649 and Arg625 . Since previous studies [15] and the current simulations indicate that the tyrosine-out state is predominant , even in the phosphorylated state , it is reasonable that the K526E mutation will significantly increase catalytic activity regardless of whether the kinase is phosphorylated . The major limitation of the string method algorithm in this system is that the activation loop visits a large range of conformations , which are not all on the MFEP . Our metadynamics simulation explored a wide range of conformations , including some that diverged significantly from crystallographically observed structures . In particular , 13 of the 56 clusters contained structures in which pTyr656 , not pTyr657 , was pointed inward , making contact with Arg649 and Arg625 ( S2 Fig ) . This conformation is of particular interest because previous studies in FGFR1 kinase have shown that Tyr653 ( homologous to Tyr656 in FGFR2 ) is phosphorylated before Tyr654 ( homologous to Tyr657 in FGFR2 ) [41] . Additionally , the monophosphorylated kinase , in which only Tyr653 is phosphorylated , has only a 50–100 fold increase in catalytic activity for trans-autophosphorylation compared to a 500–1000 fold increase in catalytic activity in the bisphosphorylated kinase relative to the unphosphorylated kinase [41] . Thus , understanding the structure of this monophosphorylated kinase might hold the key to designing inhibitors that selectively bind to this structure , which exists for some time before the bisphosphorylated kinase , is generated . While there are no experimentally-derived structures of a monophosphorylated kinase , our simulation-derived ensemble of pTyr656-inward structures which resemble the active conformation of the monophosphorylated kinase provides a foundation for exploring the unique features of these conformations of intermediate catalytic activity . Surprisingly , the conformations from the ensemble either did not feature Arg664 in the active site or had Leu665 and Pro666 blocking the active site . Further studies are needed to examine the structural features of the monophosphorylated kinase that enable catalytic activity . The activation loop represents a formidable challenge in understanding RTK structure and dynamics , as it adopts not one structure but a large range of conformational states . As a result , many of the current experimental techniques are unable to probe completely the conformational space accessible to the activation loop . Within the range of crystal structures of FGFR2 kinase , the activation loop adopts many different conformations ( S1 Fig ) . FGFR2 kinase is an especially useful system for investigating activation loop dynamics because other domains do not move significantly upon activation . Whereas in many RTKs , the αC helix undergoes movement upon activation , emphasizing its role in creating the catalytically active conformation of the active site , the αC helix in FGFR2 kinase does not move independently of the N lobe . Moreover , the N lobe structural change illustrated in crystal structures is itself subtle . We did not observe in our simulations any definite increase in proximity between the lobes in the active conformations compared to the inactive conformations . This suggests that interpreting the subtle differences between the inactive and active crystal structures warrants considerable caution . Because global conformational motions of the kinase lobes or secondary structures are not apparent , any determinants of catalytic activity are likely to be concentrated in the activation loop , making it a good choice for understanding how activation loop dynamics lead to kinase activation . Elucidating the structural mechanism by which phosphorylation of the activation loop enables catalytic activity is an important step toward designing specific inhibitors of FGFR2 kinase and other RTKs . Our work offers a model for activation loop dynamics , supported by experimental data , which may prove useful in better analyzing the dynamic changes that activate RTKs .
In order to generate input structures for the string method , we used the crystal structures of the inactive and active conformations of the FGFR2 kinase domain ( PDB entries 2PSQ and 2PVF [26] , respectively ) , superimposing them so as to minimize the RMSD between the structures . We used UCSF Chimera [42] to add missing terminal residues in each structure so that the final structures included residues 458 through 768 ( seen in Fig 1 ) . We used MODELLER [43] to add missing , low electron-density non-terminal loops , generating five structures for each missing loop and choosing the structure with the lowest score . The carbon atom of AMP-PCP in the catalytically active structure was changed to oxygen so that the bound ligand was ATP . Since the crystal structure of the catalytically inactive kinase does not include ATP , it was added to the structure based on its position in the active kinase . All crystallographic water molecules and other precipitant molecules in the crystal structures were removed , as was the peptide substrate from the structure of the active kinase . The LEAP program [44] was used to generate the remainder of each structure . LEAP added phosphate groups to the tyrosine residues of the activation loop and the kinase hinge . Parameters for the phosphotyrosine residue and ATP were based on [45] and [46] respectively . In each of these structures , residue 491 , which had been mutated in the crystal structure from Cys to Ala , is reverted to Cys . The correct number of Na+ counter ions were added to each structure , as well as enough TIP3P solvent to create a 10 Å buffer between the protein edge and the box wall . For all simulations , the AMBER99SB force field [47] was used . Hydrogen bonds were constrained using the SHAKE algorithm [48] . Long-range electrostatics were computed using the particle mesh Ewald algorithm [49] . All molecular dynamics simulations used a 2 fs time step . The simulation boxes containing the inactive and active conformations were each minimized using NAMD [50] for 1000 steps of conjugate gradient minimization , keeping 500 kcal mol-1Å-2 restraints on the CA atoms of the protein , followed by 2500 steps of minimization without restraints . The initial path for the string method in collective variables is derived from the zero-temperature string ( ZTS ) method [51 , 52] , which produces the minimum energy path of the conformational transition between the inactive and active structures . It has been shown that the minimum energy path is a good choice for input to the string method in collective variables , as the minimum energy path ( MEP ) produced by the ZTS method is likely to be similar to the minimum free energy path ( MFEP ) produced by the string method in collective variables [35] . Before implementing the ZTS method , the water molecules from the inactive and active structures are removed . A pathway of four structures is created by inserting two linearly interpolated structures between the inactive and active structures . These four structures then undergo 100 iterations of the ZTS method . In each iteration , each structure is minimized in AMBER [44] with 20 steps of steepest descent minimization , using an infinite cutoff for short-range interactions , followed by reparametrization of the string of structures so that they are equally spaced from one another along the string in conformational space . After 100 iterations , the number of structures in the string is doubled by interpolating one structure between each pair of successive structures , and two structures between the middle pair of structures in the string , and the procedure is repeated . This continues until the ZTS method runs for a string of 256 structures . Thirty-two equally spaced structures are extracted from this path ( starting with image 7 and ending with image 255 , the last image in the path ) for input into the string method in collective variables . LEAP is run on each of these 32 structures to add back Na+ counter ions and water molecules as before , followed by rotation and translation of the box to align the protein molecules in each box to one another . Each structure is then minimized in NAMD for 2000 steps with 10 kcal mol-1Å-2 restraints on the protein atoms , followed by gradual heating to 300 K over 600 ps with the same restraints using a Langevin thermostat with a damping coefficient of 1 ps-1 . Each structure is equilibrated in the NPT ensemble for 2 ns using a Berendsen barostat with a target of 1 bar and a compressibility of 4 . 57 × 10−5 bar-1 . The resulting structures are used as input for the string method algorithm . The collective variables ( CVs ) for the string method include the Cα atoms of the αC-helix ( residues 526–541 ) and the activation loop ( residues 644–683 ) , as well as sidechain atoms of residues postulated to be important in the mechanism of activation ( two sidechain atoms of the “molecular brake” [26] , Asn549:Nδ2 and Glu565:Cδ; the phosphorus atoms of the phosphotyrosine residues of the activation loop; the Cζ atom of Arg649 in the activation loop which makes contact with pTyr657 in crystal structures of the active conformation; and the Nζ atoms of Lys658 and Lys659 which make contact with pTyr656 and pTyr657 ) . During the simulations , these atoms are constrained to target values ( denoted z1* , z2* , … , zn* for each of the n collective variables ) with a 1 . 0 kcal mol-1Å-2 restraint , with the initial target values extracted from the equilibrated structures . MD simulations are run for each image in the string independently . After every 10 steps , the target values zi* are evolved according to the equation zi* ( t+dt ) =zi* ( t ) −γ−1m−1∂F∂zidt ( 1 ) where γ is a friction coefficient given by 125 ps-1 , m is the mass ( taken for simplicity to be identical to the mass of a carbon atom ) and F is the free energy . The derivative of free energy with respect to a given CV is approximated by the average value ∂F∂zi=k ( 〈zi* ( t ) −zi〉 ) ( 2 ) where zi is the instantaneous value of the CV and <…> denotes the ensemble average over 10 steps . The target values are thus updated for each CV for each image , which together form a string , a path in CV space . After the update step , the string is reparameterized such that the new target values are still on the same string in CV space , but equidistant from one another; this is easily performed by calculating the optimal distance between target values for each image and changing the target values , as noted in [35] . This process is continued until the set of target values does not change significantly over time ( represented by asymptotic behavior of the RMSD of target values from their initial values; see S3 Fig ) , suggesting that the string now represents a minimum free energy path in collective variable space . Throughout the simulations , we prevented translation and rotation of the protein by adding 0 . 5 kcal mol-1Å-2 restraints on the backbone atoms of the protein except those in the αC-helix or the activation loop . In order to visualize the final pathway , we ran simulations with 20 kcal mol-1 Å-2 constraints on the restrained atoms to guide them toward the final target values . The PMF is calculated by running simulations with 1 kcal mol-1 Å-2 constraints on the restrained atoms at the final values from the string method algorithm . This allows calculation of ∂F/∂zi for each CV , then enabling the generation of a PMF curve whose equation is given by F ( α ) =∫0α∑i∂F∂zi∂zi∂αdα ( 3 ) We calculate the value of ∂zi/∂α using centered differences ( or forward or backward differences for the starting and ending frames , respectively ) , and we calculate the integral using the trapezoidal method . A second run of the string method in collective variables was run with a different set of CVs . For this second run , the CVs were interatomic distances between the centers of mass of residues in the αC-helix and activation loop , as well as sidechain atoms of the “molecular brake . ” The overall conclusions from this run were similar and are summarized in the supporting information , and S1 Table , and S4 and S5 Figs . The starting and ending target values of the CVs pertaining to the activation loop were used to run metadynamics simulations [36] using distances in contact map space from the active and inactive states as the CVs . We calculated interatomic distances between all atoms in the activation loop whose coordinates were CVs in the string method simulations . We then selected the subset of those distances which changed between the inactive state ( frame 0 ) and the active state ( frame 31 ) from being less than 8 Å to greater than 8 Å , or vice versa , and in which the greater distance was at least 1 . 5 times larger than the smaller distance . This subset , containing 31 interatomic distances , was used to define the contact map . Then we used distances in contact map space as the collective variables in a metadynamics simulation . For a given conformation , d= ( ∑r ( 1− ( ( r−d0 ) /r0 ) 61− ( ( r−d0 ) /r0 ) 12 ) ) 1/2 ( 4 ) where r is one of the 31 interatomic distances , r0 = 8 Å , and d0 is the reference contact distance in the inactive or active state . As the metadynamics simulation progressed , every 500 steps , a 2D Gaussian hill with height 0 . 7 kcal mol-1 and width 0 . 1 was added , centered at the current value of the contact map distance from the active and inactive conformations , respectively . We used well-tempered metadynamics [53] , with a bias temperature of 4200 K , which determined the height of the Gaussian at each step . A grid with spacing 0 . 002 was used to store the Gaussian hills . Additionally , the metadynamics simulation was significantly accelerated by using 10 simultaneous walkers [54] which shared a collective set of Gaussian biases . The total simulation time for all walkers exceeded 3 μs . The metadynamics simulation was performed using NAMD 2 . 9 [50] with PLUMED 2 . 1 [55] . All calculations were performed on local workstations as well as TACC Stampede and Maverick [56] . Constructs of FGFR2 kinase for NMR and kinetics studies were based on [15] . Human full-length FGFR2 cDNA was purchased from Sino Biological Inc . ( Beijing , China ) , and the kinase domain fragment was extracted by restriction digest with EcoRI and XhoI , generating residues 458 through 768 , which were subsequently cloned into the pRSFDuet vector . Subsequent mutations were introduced into the construct via site-directed mutagenesis using a QuikChange II XL kit , and sequences were confirmed by DNA sequencing . All constructs used in this study included a C491A mutation that aided in protein expression [15] . Protein expression was carried out in BL21-DE3 RIPL cells . Cells were grown either in Terrific Broth ( Sigma-Aldrich ) or in M9 minimal media supplemented with 15N NH4Cl for NMR studies , and were induced at OD 0 . 6–0 . 8 with 1 mM IPTG overnight at 20°C . Cells were lysed and protein was purified using TALON metal affinity resin ( Clontech ) . To generate non-phosphorylated sample , trace phosphorylation was removed by alkaline phosphatase ( FastAP , Thermo Scientific ) , followed by purification by size-exclusion chromatography . To prepare phosphorylated sample , 10 mM ATP and 5 mM MgCl2 were added to FGFR2 kinase and autophosphorylation was allowed to occur overnight at 4° followed by exhaustive dialysis to remove excess ATP . For NMR studies , we used constructs in which all tyrosine residues except Tyr657 in the activation loop , shown to be sufficient for full catalytic activity [15] , were mutated to phenylalanine . Additionally , we used the A648T mutation to improve protein expression and stability for the NMR experiments . NMR HSQC spectra of FGFR2 kinase with the A648T mutation were obtained from a sample of 150 μM protein in a buffer consisting of 20 mM HEPES pH 7 . 4 and 150 mM KCl . Assignments for the A648T construct were transferred from published assignments [15] . The assignment of the HSQC cross peak corresponding to R664 was confirmed using selective un-labeling experiments by adding 14N-arginine to the growth media , as well as using selective labeling experiments by adding 13C-glycine and 15N NH4Cl to the growth media , generating a spectrum which contained cross peaks from residues immediately C-terminal to the glycine residues in an 1H-15N HNCO plane . In kinetic assays , the tyrosine residues of the kinase domain were kept intact , with C491A as the only mutation retained to allow for protein expression . Kinetic assays of autophosphorylation were performed by coupling the hydrolysis of ATP to the oxidization of NADH through enzymes in the glycolytic pathway , as discussed in [57] . The assay contained 500 nM of unphosphorylated FGFR2 kinase , along with 1 mM ATP , 20 mM MgCl2 , 1 mM phosphoenolpyruvate , 45–70 units LDH , 30–50 units PK , and 416 μM NADH . The kinase activity was monitored by measuring absorbance at 340 nm , which reflects the amount of NADH in the sample that has not yet been oxidized . The starting structure for MD simulations of the kinase with the bound substrate peptide was taken from a structure of the kinase performing autophosphorylation ( PDB 3CLY [25] ) . After making copies of the unit cell using UCSF Chimera [42] , a portion of the substrate-acting kinase is retained , with the sequence TTNEEYLDL , while the remainder of that copy of the kinase is discarded . The ACP molecule was changed to ATP , and missing non-terminal segments of the enzyme-acting kinase were built using MODELLER as described above . Missing atoms were added with LEAP , followed by addition of Na+ counter ions and solvent to generate a box with an 8 Å margin surrounding the protein on all sides . The box was minimized in AMBER with 500 steps of steepest descent minimization followed by 1500 steps of conjugate gradient minimization , all with 500 kcal mol-1Å-2 restraints on the protein . This was followed by minimization with restraints on only the Cα atoms , using 500 steps of steepest descent and 500 steps of conjugate gradient minimization . The box was heated in AMBER to 300 K over 20 ps , with 10 kcal mol-1 Å-2 restraints on the Cα atoms , and NPT equilibration was performed for 2 ns , with 5 kcal mol-1 Å-2 restraints on the atoms of the active site ( including Asp626 , Asp644 , Arg664 , the substrate tyrosine , ATP , the two Mg2+ ions , and five water molecules which were all within 5 Å of both Mg2+ ions ) . These simulations used the same parameters used for the simulations described above . To generate starting configurations for simulations for comparison of tyrosine stabilization by Arg664 positioning , we ran preparatory simulations to move Arg664 toward a given position while the active site atoms were kept fixed with a 5 kcal mol-1 Å-2 restraint . To study the effect of Arg664 near the active site , Arg664 was moved toward ATP by placing a harmonic restraint on the Arg664:Cζ—ATP:Pγ distance , with an equilibrium value of 4 . 5 Å , whose force constant increased linearly over 200 ps from 0 to 10 kcal mol-1 Å-2 , followed by another 300 ps of simulation with the restraint constant . During the subsequent production simulations in which the root-mean-square fluctuations of ATP and the substrate tyrosine were measured , a half-harmonic potential was placed , with a force constant of 5 kcal mol-1 Å-2 , whenever the distance increased beyond 6 Å . To study the effect of having Arg664 far away from the active site , a second simulation was run to move Arg664 away , using a similar harmonic restraint as above but with an equilibrium value of 25 Å; the production runs included a half-harmonic restraint activated when the distance went below 10 Å . To study the effect of having Arg664 bound to Asp530 , a preparatory simulation included a harmonic restraint on the Arg664:Cζ—Asp530:Cγ distance with an equilibrium value of 4 . 5 Å , followed by production runs with a half-harmonic potential activated if the distance increased beyond 6 Å . The starting structure for QM/MM studies was identical to that used in the substrate positioning simulation to study the effect of positioning Arg664 in the active site . The QM region included the three phosphate groups of ATP; two Mg2+ ions; the sidechains of Asp626 , Asp644 , Arg664 and the substrate tyrosine; and five water molecules that were within 5 Å of both Mg2+ ions . The rest of the system was treated at the MM level using the same AMBER force field . The QM region was studied using density functional theory with the B3LYP exchange correlation functional , using the cc-pVDZ basis set [58] . Link atoms were used to connect the two regions . All QM/MM calculations were performed using NWChem 6 . 3 [59] . First , the geometry was optimized using an alternating optimization scheme , in which the QM region undergoes 10 steps of optimization , followed by optimization of the MM solute region while the QM region is represented by ESP-derived charges , and then optimization of the solvent . This alternating optimization scheme continues until convergence . After optimization , we used the reaction coordinate driving method [60] to drive the system from the reactant state to the phosphorylated product state . We used the reaction coordinate RC = d1 − d2 − d3 , where d1 is the ATP:Pβ–ATP:Pγ distance , d2 is the ATP:Pγ—Tyr:OH distance , and d3 is the Tyr:HH—Asp626:Oδ2 distance . The system was optimized at each step with harmonic restraints on the reaction coordinate that successively increased its value until the reaction completed . | Receptor tyrosine kinases are proteins integral to relaying signals from outside the cell to activators inside the cell that stimulate cell growth and development . Therefore , when these proteins show intrinsic activity independent of extracellular signaling , they can frequently cause developmental abnormalities , if the unchecked activity occurs before birth , or cancer , if the unchecked activity occurs later in life . Understanding what causes these proteins to become active upon receiving an extracellular signal will be helpful in pinpointing how they can exhibit activity without the extracellular signal . To study this phenomenon , we examined one receptor tyrosine kinase , FGFR2 kinase , and used computer simulation to identify what conformational changes occur in this protein upon activation . We then identified the function of these conformational changes in enabling the enzyme’s catalytic reaction to occur . Our results demonstrate the value of incorporating simulation data in analyzing the mechanisms of receptor tyrosine kinase activation , and suggest important features of this enzyme that should be considered in future drug development . | [
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"factors... | 2017 | Effects of FGFR2 kinase activation loop dynamics on catalytic activity |
Accumulated evidence demonstrated that long non-coding RNAs ( lncRNAs ) play a pivotal role in tumorigenesis . However , it is still largely unknown how these lncRNAs were regulated by small ncRNAs , such as microRNAs ( miRNAs ) , at the post-transcriptional level . We here use lncRNA HOTTIP as an example to study how miRNAs impact lncRNAs expression and its biological significance in hepatocellular carcinoma ( HCC ) . LncRNA HOTTIP is a vital oncogene in HCC , one of the deadliest cancers worldwide . In the current study , we identified miR-192 and miR-204 as two microRNAs ( miRNAs ) suppressing HOTTIP expression via the Argonaute 2 ( AGO2 ) -mediated RNA interference ( RNAi ) pathway in HCC . Interaction between miR-192 or miR-204 and HOTTIP were further confirmed using dual luciferase reporter gene assays . Consistent with this notion , a significant negative correlation between these miRNAs and HOTTIP exists in HCC tissue specimens . Interestingly , the dysregulation of the three ncRNAs was associated with overall survival of HCC patients . In addition , the posttranscriptional silencing of HOTTIP by miR-192 , miR-204 or HOTTIP siRNAs could significantly suppress viability of HCC cells . On the contrary , antagonizing endogenous miR-192 or miR-204 led to increased HOTTIP expression and stimulated cell proliferation . In vivo mouse xenograft model also support the tumor suppressor role of both miRNAs . Besides the known targets ( multiple 5’ end HOX A genes , i . e . HOXA13 ) , glutaminase ( GLS1 ) was identified as a potential downstream target of the miR-192/-204-HOTTIP axis in HCC . Considering glutaminolysis as a crucial hallmark of cancer cells and significantly inhibited cell viability after silencingGLS1 , we speculate that the miR-192/-204-HOTTIP axis may interrupt HCC glutaminolysis through GLS1 inhibition . These results elucidate that the miR-192/-204-HOTTIP axis might be an important molecular pathway during hepatic cell tumorigenesis . Our data in clinical HCC samples highlight miR-192 , miR-204 and HOTTIP with prognostic and potentially therapeutic implications .
Hepatocellular carcinoma ( HCC ) ranks among the 10 most common cancers worldwide and showed the highest incidence in Asia [1 , 2] . Remarkably , more than half of all HCC patients were diagnosed in China [1] . Chronic infection with the hepatitis B or C viruses ( HBV or HCV ) , exposure to dietary aflatoxin B as well as alcohol abuse have been identified as major risk factors of this malignancy . However , only a portion of exposed individuals finally developed HCC , indicating that genetic makeup may also contribute to HCC etiology [1 , 2] . Long noncoding RNAs ( lncRNAs ) constitute a class of endogenous RNAs ranging in size from several hundred to tens of thousands of nucleotides ( nt ) [3–5] . Different from their shorter counterparts , such as microRNAs ( miRNAs ) , the role of most lncRNAs in human cancers is still largely unknown . Accumulating data have established the participation of several lncRNAs during tumorigenesis and progression of HCC . For instance , lncRNA HOTTIP , HULC , MALAT1 , HOTAIR , lncRNA-HEIH , HBx-LINE1 and lncRNA-hPVT1show their capability to promote HCC proliferation as oncogenes [6–14] . Conversely , lncRNA H19 , MEG3 and lncRNA-Drehmay act as tumor suppressors [15–17] . In addition , multiple lncRNAs ( i . e . lncRNA-LET , lncRNA-ATB , lncRNA-Dreh , MALAT1 , HOTAIR and MVIH ) are involved in controlling HCC invasion and metastasis [10 , 11 , 17–20] . The HCC-related lncRNA HOTTIP is a 3764 nt , spliced and polyadenylated ncRNA , which is transcribed from 330 bases upstream of the 5’ tip ofHOXA13 ( Chromosome 7p15 . 2 ) [6 , 21] . During development , HOTTIP RNA is mainly expressed in distal anatomic sites and controls activation of distal HOXA genes in vivo [21] . Through directly binding the adaptor protein WDR5of the WDR5/MLL complex , HOTTIP drives histone H3 lysine 4 trimethylation ( H3K4me3 ) and gene transcription across the HOXA gene locus . In mice , HOTTIP knockout leads to defects of resembling HoxA11 andHoxA13 inactivation , demonstrating its essential part in controlling development of lumbo-sacral anatomic regions [21] . After analyzing 52 snap-frozen needle HCC biopsies and matched non-neoplastic counterparts , Quagliata et al found that HOTTIP is significantly up-regulated in HCC and HOTTIP/HOXA13 expression is associated with patients’ metastasis and survival . Additional gain and loss of function experiments demonstrated that silencing HOTTIP inhibits HCC proliferation , highlighting its role as an oncogene during hepatocarcinogenesis [6] . However , fine regulation of lncRNA HOTTIP expression in HCC is still largely unknown . Intriguingly , miRNAs may directly interact with lncRNAs and knock-down their expression [22 , 23] . However , how HOTTIP is regulated by miRNAs at the posttranscriptional level remains largely unclear . In the current study , we for the first time identified the negative regulation of lncRNA HOTTIP by miR-192 and miR-204 via the Argonaute 2 ( AGO2 ) -mediated RNAi pathway . Ectopic expression of miR-192/-204 or HOTTIP siRNA significantly suppresses glutaminase ( GLS1 ) expression , thereby inhibiting HCC growth in vitro and in vivo .
Potential miRNA candidates targeting HOTTIP was predicted by the miRCode software ( www . miRCode . org ) [24] . As shown in S1 Table , there are a total of 62 miRNA matching sites in HOTTIP gene . Considering that matching sites with higher evolutionary conservation across species might be more functionally vital , we evaluated seven candidate miRNAs ( miR-138 , miR-18 , miR-192 , miR-215 , miR-19 , miR-204 , and miR-211 ) which show >80% conservation among primates ( 8 species excluding human ) in this study ( Table 1 ) . After transfection with the RNA mimics of the seven miRNAs and two HOTTIP siRNAs ( siHOTTIP-1 and siHOTTIP-2 ) into SMMC7721 , HepG2 and Hep3B cells , we firstly examined endogenous lncRNA HOTTIP expression changes ( Fig 1A ) . About 70~80% decreased HOTTIP expression was observed in HCC cells with overexpression of siHOTTIP-1 or siHOTTIP-2 compared to NC-RNA-transfected cells ( both P<0 . 01 ) . In HepG2 cells , miR-192 , miR-204 , miR-18 , miR-19 and miR-211 could down-regulate HOTTIP expression ( all P<0 . 05 ) . In SMMC7721 cells , miR-192 and miR-204 can significantly inhibit HOTTIP expression ( both P<0 . 05 ) . Similar results were also observed in Hep3B cells . Considering the consistency in all three cell lines , we only investigated miR-192 and miR-204 in the following studies . To further validate this regulatory relationship , inhibitors of both miRNAs were delivered into SMMC7721 , HepG2 and Hep3Bcell lines to antagonizeendogenousmiR-192/-204 expression . As expected , significant increased HOTTIP levels could be found in HCC cells ( all P<0 . 05 ) ( Fig 1B ) . Since miR-192 and miR-204 showed similar regulatory behaviors as HOTTIP siRNAs , we speculated that miR-192/-204 may regulate HOTTIP expression via the RNAi pathway at the post-transcriptional level . This would suggest that both miR-192/-204 and HOTTIP exist in the RISC complex ( RNA-induced silencing complex ) . Since AGO2 is a key component of the RISC complex , we therefore performed RNA immunoprecipitation with the AGO2 antibody . We firstly confirmed that the AGO2 protein could be precipitated from the cellular extract ( Fig 1C ) . In RNA extracted from the precipitated AGO2 protein , we could detect both miR-192/-204 and HOTTIP with a2~2 . 5-folds enrichment compared to IgG ( Fig 1C ) . To examine the potential miRNA-lncRNA interaction , a 2280bp human HOTTIP3' partial region was subcloned after the firefly luciferase gene ( named as pGL3-HOTTIP ) ( Fig 2A ) and co-transfected into SMMC7721 and HepG2 cells withmiR-192 mimics , miR-204 mimics or NC RNA . MiR-192 produced a 58 . 3% or33 . 3% decreased luciferase activity compared to NC RNAinSMMC7721 or HepG2cells ( both P<0 . 05 ) ( Fig 2B ) . Similarly , there was a 47 . 9%or 38 . 1% decrease in luciferase activity in both cell lines with miR-204overexpression compared to NC RNA ( both P<0 . 01 ) ( Fig 2B ) . An analogous reporter with point substitutions disrupting the target sites of miR-192 or miR-204 ( named as pGL3-Mut192 or pGL3-Mut204 ) ( Fig 2A ) was also co-transfected with two miRNA mimics or NC RNA . However , no significant decreased luciferase activity caused by miR-192 or miR-204was observed compared to NC RNA ( all P>0 . 05 ) ( Fig 2B ) . We found that suppressing HOTTIP by miR-192 and miR-204 can significantly reduce viability of SMMC7721 , HepG2 and Hep3B cells ( Fig 3A ) . Either miRNAs or HOTTIP siRNAs showed similar inhibition impact on SMMC7721 cell growth at 72h after RNA delivery ( miR-192: 17 . 9% , miR-204: 20 . 5% , siHOTTIP-1: 23 . 1% , siHOTTIP-2: 23 . 1%; all P<0 . 05 ) . Similar results were observed in HepG2 at 72h after transfection ( miR-192: 36 . 4% , miR-204: 31 . 8% , siHOTTIP-1: 47 . 7% , siHOTTIP-2: 43 . 1%; all P<0 . 01 ) . The suppressive effects of both miRNAs on HCC cell proliferation were also validated in Hep3B cell line ( miR-192: 45 . 1% , miR-204: 37 . 8% , siHOTTIP-1: 43 . 9% , siHOTTIP-2: 51 . 2%; all P<0 . 01 ) . Interestingly , there was a combined effect on inhibition of cell proliferation when miR-192 and miR-204 mimics were co-transfected into HCC cells ( SMMC7721: 35 . 9% , HepG2: 54 . 5% , Hep3B: 60 . 9%; all P<0 . 01 ) . When the pCMV-HOTTIP plasmid was transfected into HCC cells with miR-192 , miR-204 or both miRNAs over-expression , suppressed HCC cell proliferation could be rescued ( S1 Fig ) . After inhibitors of both miRNAs were delivered into HCC cells , cell proliferation was stimulated ( Fig 3B ) . Antagonizing endogenousmiR-192 expression led to 23 . 7% , 42 . 1% or34 . 6% increased SMMC7721 , HepG2 orHep3B cell growth at 72h ( all P<0 . 05 ) . There was a 15 . 8% , 34 . 2% or 25 . 6% increase of SMMC7721 , HepG2 or Hep3B proliferation after inhibition of endogenousmiR-204 expression ( all P<0 . 05 ) . As shown in Fig 3C , combined effects of miR-192/-204 with SAHA ( suberoylanilidehydroxamic acid , also known as Vorinostat ) on HCC viability were also observed . Colony formation assays also support the tumor suppressor nature of both miRNAs ( Fig 3D ) . Consistent with cell viability assays , miR-192 and miR-204 , alone and in combination , are able to inhibit colony formation significantly ( all P<0 . 05 ) . The cell proliferation suppression via HOTTIP inhibition may be attributed to apoptosis . At 72h after transfection , HOTTIP siRNAs , miR-192 or miR-204 could induce significantly apoptosis ( all P<0 . 05 ) ( Fig 3E ) . However , both miRNAs cannot induce obvious cell cycle arrest ( S2 Fig ) . We also examined impacts of miR-192/-204 on migration ability of HCC cells through wound healing assays . However , no difference in migratory behavior was observed in miRNA-treated cells versus controls ( S3 Fig ) . We firstly evaluated cellular localization of lncRNA HOTTIP in HCC cells . Cells were fractionated into nuclear and cytoplasmic fractions and RNA was extracted separately . HOTTIP was detected predominantly in the nuclear fraction as U6 RNA did in HCC cells ( Fig 4A ) . Considering the exclusive localization of HOTTIP in the nuclei and AGO2 generally interacts with RNAs exported to cytoplasm , we examined if expression of 'nuclear' HOTTIP-lncRNA could be inhibited by miRNA-192/-204 via qRT-PCR using nuclear and cytoplasmic RNAs isolated from cells treated with miRNAs . As shown in Supplementary Figure 4 , we found that miRNA-192/-204 could directly silence HOTTIP expression in either nucleus or cytoplasm . Considering HOXA13asone of 5’ end HOX A genes ( known HOTTIP target genes ) , we then measured its expression in HCC cells . In line with previous studies , significantly down-regulated HOXA13 mRNA expression in both HCC cell lines after silencing HOTTIP by either siRNAs or miR-192/-204 ( all P<0 . 05 ) ( Fig 4B ) . To further disclose the potential molecular mechanism how miRNAs influence HCC viability via suppressing lncRNA HOTTIP , we profiled whole genome mRNA expression of HepG2 cells transfected with NC RNA , miR-192 , miR-204 or siHOTTIP-1 ( Fig 4 ) . Compared to NC RNA , there were 152 , 114 or 207 differentially expressed genes caused by miR-192 , miR-204 or siHOTTIP-1 . Among these genes , a total of 19 genes were consistently de-regulated by any of these three small RNAs ( Fig 4C and 4D ) . Gene Ontology analyses indicate that most genes are involved in positive or negative regulation of cell proliferation as well as cell death control ( S2 Table ) , which is in agreement with the role of miR-192 and miR-204 on HCC cell proliferation . We then validated microarray profiling identified 19 genes using qRT-PCR ( Fig 4E ) . Among these successfully validated downstream genes , we chose GLS1 as the candidate gene to investigate its considering its importance in glutaminolysis and tumorigenesis . As shown in S5 Fig , overexpression of lncRNA HOTTIP does enhance GLS expression in SMMC7721 , HepG2 and Hep3B cells . Interestingly , we found that silencing its expression could significantly inhibit proliferation of HCC cells , in both a dose-dependent and time-dependent way ( all P<0 . 05 ) ( Fig 4F ) . We also examined impacts of GLS1 suppressing oncolony formation of HCC cells , which also support the oncogenenature of GLS1 ( Fig 4G ) . To determine relationship between HOTTIP and miR-192/-204 in vivo , we detected expression of miR-192 , miR-204 and HOTTIP in 48 tumor-normal pairs ( S3 Table ) . There was significantly higher HOTTIP expression in HCC samples than normal specimens ( median , 1 . 7×103 versus 891 . 0 , P<0 . 01 ) ( Fig 5A ) . On the contrary , less miR-192 or miR-204 could be detected in HCC tissues compared to adjacent normal tissues ( median , 1 . 8×104 versus 4 . 5×104 or , 6 . 7 versus 13 . 6; both P<0 . 01 ) ( Fig 5B ) . We also found significant negative correlation between HOTTIP and miR-192 or miR-204 in tissues ( Spearman’s correlation: HOTTIP versus miR-192: r = -0 . 2 , P<0 . 05; HOTTIP versus miR-204: r = -0 . 2 , P<0 . 05 ) ( Fig 5C ) . We then evaluate the impacts of miR-192 , miR-204 and HOTTIP expression on HCC prognosis . HCC patients with high HOTTIP expression had much shorter overall survival time than those with low HOTTIP expression ( median , 14 . 5 versus 28 . 5 months; P = 0 . 018 ) ( Fig 5D ) . However , individuals with high miR-192 or miR-204 level showed better prognosis compared to ones with low expression of each miRNA on multivariate survival analysis ( miR-192: median , 26 . 5 versus 14 . 0 months; P = 0 . 013; miR-204: 26 . 0 versus 15 . 0 months; P = 0 . 017 ) ( Fig 5D ) . We found that the growth of tumors from both miR-192 and miR-204 up-regulated HepG2 xenografts or xenografts with stable transfection of HOTTIP siRNA constructs was significantly inhibited compared with that of tumors formed from control xenografts after 9 days ( Fig 6A and 6B ) . There were no significant differences of mice weight between controls or miRNAs treated groups ( Fig 6C ) . qRT-PCR data showed that miR-192 and miR-204 or HOTTIP siRNA could significantly inhibit HOTTIP expression in xenografts ( Fig 6D ) .
LncRNA HOTTIP is an important oncogene in HCC [6] . However , its post-transcriptional fine-regulation was still unclear . To the best of our knowledge , we here for the first time revealed that two miRNAs ( miR-192 and miR-204 ) can suppress oncogene HOTTIP expression and HCC viability via the AGO2-mediated RNAi pathway . Consistent with this notion , a significant negative correlation between both miRNAs and HOTTIP exists in HCC tissue specimens . Interestingly , the dysregulation of the three ncRNAs was associated with overall survival of HCC patients , indicating their potential as prognostic markers . In vivo xenografts data highlight that this miRNA-mediated epigenetic regulation might be therapeutically relevant for HCC . Mammalian miRNA target sites primarily locate in mRNA 3’-UTR [25 , 26] , since active translation may interrupt miRNA binding within the protein-coding regions [27] . LncRNAs are more readily accessible to miRNAs as a whole because of no proteins translated . Consistent with this hypothesis , several lncRNAs , such asPTENP1 , HULC , GAS5 , loc285194 , HOTAIR as well as HOTTIP , have been identified as miRNA targets in various cancers [7 , 22 , 23 , 28 , 29] , which provide further layers of understanding lncRNA regulation during carcinogenesis . It has been found that miR-192 and miR-204 function as tumor suppressors in multiple cancers including HCC . As one of the P53-inducable miRNAs [30 , 31] , miR-192 takes part in cancer development and progression through targeting DHFR , TYMS , RB1 , ZEB2 , BCL2 and VEGFA [32–36] . Additionally , miR-192 is one of plasma miRNAs that provided a high diagnostic accuracy of early-stage HCC , indicating its clinical relevance [37] . Several target genes of miR-204 , including HOXA10 , MEIS1 , FOXC1 , MAP1LC3B , BCL2 , NTRK2 , SOX4 and EphB2 , have been identified in different cancers [38–42] . However , the role of miR-204 in HCC is still unclear . We revealed that miR-204 suppresses oncogene HOTTIP expression in HCC , which is consistent with its tumor suppressor role in other malignancies . Although Quagliata et al found that HOTTIP and HOXA13 are involved in HCC development by associating their expression to metastasis and survival in HCC patients [6] , they found that siRNA-HOTTIP treated cells do not display any significant impairment of their migratory behavior [6] . This is in line with our observations that miR-192/-204 did not influence HCC migration . Significantly inhibited cell proliferation might be largely due to apoptosis after delivery of miR-192 or miR-204 into HCC cells . One possible explanation is that HOTTIP inhibition by miR-192 or miR-204 may lead to abnormal glutaminolysis and then apoptosis . Cancer cells tend to take up more glucose than most normal cells despite the availability of oxygen , which is called the Warburg effect [43] . Glutaminolysis is another hallmark of cancer cells in addition to aberrant glucose metabolism [44] . Mitochondrial GLS1 plays an essential part in glutaminolysis through catalyzing the conversion of glutamine to glutamate [45] . Glutamate is further catabolized in the Krebs cycle to produce ATP , nucleotides , certain amino acids , lipids , and glutathione [46] . Many cancer cell lines including HepG2 display addiction to glutamine and are sensitive to glutamine starvation or dysregulation of the glutaminolysis genes , such as GLS1 [46 , 47] . Interestingly , down-regulated GLS1expression was observed after HCC cells transfected with miR-192 , miR-204 or HOTTIP siRNA . Silencing GLS1 expression in HCC cells resulted in obviously retardant cell proliferation and colony formation . Therefore , we speculate that the miR-192/-204-HOTTIP axis may interrupt glutaminolysis of HCC and , thus , suppress cell viability . Although Ago2 commonly locates in cytoplasm , Ago2 and RNAi factors Dicer , TRBP , and TRNC6A/GW182were also found in the human nucleus and can mediate functional RNAi in nucleus[48] . Moreover , mature miRNAs can be transported from cytoplasm to nucleus by importin 8[49] . That is , there are essential machinery for Ago2-miRNA mediated RNA silencing in human nucleus , which explained why HOTTIP mainly existing in the nuclei could physically interact with Ago2 . Similar miRNAs regulation mechanisms were also observed in other nucleus lncRNAs . For instance , nucleus lncRNA MALAT1 is a well-known oncogene and could be directly regulated by several miRNAs [50–52] . In summary , we identified lncRNA HOTTIP as a novel target of miR-192 and miR-204 . This posttranscriptional regulation showed significant impact on proliferation of HCC cells . The identification of GLS1 as a potential downstream gene of the miR-192/-204-HOTTIP axis highlights the involvement of glutaminolysis in HCC . In view of our present results showing attenuated miR-192/-204 expression and enhanced HOTTIP expression in human HCC clinical specimens and their association with patient survival , we hypothesize that the miR-192/-204-HOTTIP axis may be an attractive target for prognostic and therapeutic interventions in HCC .
For Human Subject Research , this study was approved by the Institutional Review Board of Huaian No . 2 Hospital ( approval number: 20140305 ) . Written informed consent was obtained from each subject at recruitment . For Animal Research , all experiments were performed according to the guidelines approved by the Institutional Review Board of Beijing Institute of Radiation Medicine for the care and use of laboratory animals ( approval number: 14–51201 ) . SMMC7721 , HepG2 and Hep3B cells were cultured in RPMI-1640 or DMEM media with 10% fetal bovine serum ( Hyclone ) at 37°C with 5% CO2 . All miRNA mimics ( miR-138 , miR-18 , miR-192 , miR-215 , miR-19 , miR-204 and miR-211 ) , miRNA inhibitors ( miR-192 and miR-204 ) and small interfering RNA ( siRNA ) duplexes ( siHOTTIP-1 and siHOTTIP-2 ) were products of Genepharma ( Shanghai , China ) . The negative control RNA duplex ( NC ) for miRNA mimics , miRNA inhibitors or siRNAs ( Genepharma , Shanghai , China ) was nonhomologous to any human genome sequence . All trasfections of small RNAs were done with Lipofectamine RNAi Max ( Invitrogen ) . After isolation from culture cells or clinical tissues with Trizol reagent ( Invitrogen ) , each RNA sample was treated with RNase-Free DNase to remove genomic DNA ( Invitrogen ) . These RNA samples were then reverse transcribed into cDNAs using Revert Ace kit ( TOYOBO , Osaka , Japan ) . Human miRNAs and U6 were detected with their specific stem-loop RT-PCR primers ( Ribobio , Guangzhou , China ) [53] . HOTTIP , HOXA13 , and other potential HOTTIP downstream gene expression were measured through the SYBR-Green qRT-PCR . The expression of individual gene was calculated relative to the β-actin or GAPDH expression [53–55] . The Imprint RNA Immunoprecipitation Kit ( Sigma , St . Louis , USA ) was used in RNA immunoprecipitation with the AGO2 antibody ( Cell signaling , Rockford , USA ) . The AGO2 antibody was then recovered by protein A/G beads . HOTTIP , miR-192 and miR-204 RNA levels in the precipitates were measured by qRT-PCR . The pGL3-Control plasmid ( Promega , Madison , USA ) was digested with XbaI ( Promega ) . The long restricted DNA products were recovered and treated with Mung Bean Nuclease ( Promega ) to degrade single-stranded extensions from the ends of DNA and leave blunt ends . The sequence corresponding to the wild-type HOTTIP 3’end ( 1561-3840nt ) was amplified with HepG2 cDNA using Pyrobest DNA Polymerase ( TaKaRa ) . The PCR primer pair used was: 5’-AAGGCGGTTTTACATACTGGTC-3’/ 5’-TAGCACCTGTAGTTGCCCATTCC-3’ . The PCR products with blunt ends were ligated into the appropriately digested pGL3-Control ( Promega ) containing the firefly luciferase gene as a reporter . The resultant plasmid , designated pGL3-HOTTIP , was sequenced to confirm the orientation and integrity . The HOTTIP reporter gene plasmid with mutant miR-192 binding site or mutant miR-204 binding site was constructed with QuikChange Site-Directed Mutagenesis kit ( Stratagene , La Jolla , CA ) . These mutant plasmids were confirmed by DNA sequencing and named as pGL3-Mut192 or pGL3-Mut204 . SMMC7721 and HepG2 cells ( 6×104 ) were seeded in 24-well plates and transfected with both 50 ng of reporter constructs ( pGL3-Control , pGL3-HOTTIP , pGL3-Mut192 or pGL3-Mut204 ) plus 20 nmol/L small RNAs ( miR-192 mimics , miR-204 mimics or NC RNAs ) using Lipofectamine 2000 ( Invitrogen ) when grown to 50% confluence . To standardize transfection efficiency , pRL-SV40 ( 1 ng ) ( Promega ) containing renilla reniformis luciferase was cotransfected . Both firefly luciferase activity and renilla luciferase activity were detected at 48h after transfection using a luciferase assay system ( Promega ) . For each luciferase construct , three independent transfections were done ( each in triplicate ) . Fold increase was calculated by defining the activity of the pGL3-Control vector as 1 . SMMC7721 , HepG2 and Hep3B cells ( 1×105 ) were seeded in 12-well plates and transfected with 20 nmol/L miR-192 mimics , miR-204 mimics , HOTTIP siRNAs ( siHOTTIP-1 and siHOTTIP-2 ) , miR-192 inhibitors , miR-204 inhibitors or NC RNA ( Genepharma ) , respectively . Cells were then harvested by trypsin digestion , washed by cold PBS twice , dyed with trypan blue and counted under microscopy at 24h , 48h and 72h after transfection . Cells were transfected with 20nmol/L miR-192 mimics , miR-204 mimics , or NC and harvested 48h after transfection . After washing with cold PBS twice , cells were fixed with ethanol at -20°C overnight and washed with cold PBS twice again . After treated with RNase A at 37°C for 0 . 5h and dyed with PI , the samples were detected with the FACSCalibur flow cytometer ( FCM ) ( BD Biosciences ) . During apoptosis assays , nonadherent and adherent cells were collected at 72h after transfection . Apoptosis was determined using the Alexa Fluor 488 annexin V/Dead Cell Apoptosis Kit ( Invitrogen ) with the FACSCalibur FCM . A total of 1 , 500 SMMC7721 or HepG2 cells were seeded into a 6-well cell culture plate and transfected with 20 nmol/L miR-192 mimics , miR-204 mimics , siHOTTIP-1 , or NC RNA , respectively . 10 nmol/L miR-192 mimics and 10 nmol/L miR-204 mimics were co-transfected into HCC cells . After 10 days , cells were washed with cold PBS twice and fixed with 3 . 7% formaldehyde . After cells were dyed with crystal violet , colony number in each well was counted . When the cell layer reached ~90% confluence , a wound was scratched by a 10μl pipette tip . Cells were then cultured at 37°C for another 48h . The average extent of wound closure was quantified . The cytosolic and nuclear fractions of SMMC7721or HepG2 cells were collected using the nuclear/cytoplasmic Isolation Kit ( Biovision , San Francisco , CA ) . We performed the detailed experimental procedures according to the manufacturer’s instructions . Total RNA from HepG2 cells transfected with 20 nmol/L NC RNA , miR-192 mimics , miR-204 mimics or siHOTTIP-1 was extracted . Whole genome gene expression of these samples was measured using OneArray Plus chips ( Phalanx Biotech Group ) . Differential expressed genes between the NC RNA group and the miR-192 group , the NC RNA group and the miR-204 group , or the NC RNA group and the siHOTTIP-1 group were identified separately . The differentially expressed genes were identified following the criteria log2 ( Fold change ) ≥ 0 . 585 and P<0 . 05 . The microarray data have been deposited at the National Center for Biotechnology Institute Gene Expression Omnibus ( GEO ) repository under accession number GSE60912 . There were a total of 48 HCC patients recruited in the current study . All patients received curative resection for HCC in Huaian No . 2 Hospital ( Huaian , Jiangsu Providence , China ) between February 2008 and December 2012 . Prior to the surgery , no patients received any local or systemic anticancer treatments . All patients were postoperatively followed after surgery until May 2014 , with a median follow-up of 18 months ( range , 5–72 months ) . The relevant clinic-pathological characteristics of the studied subjects are shown in S5 Fig . This study was approved by the Institutional Review Board of Huaian No . 2 Hospital . At recruitment , written informed consent was obtained from each subject . To evaluate the tumor suppressor role of miR-192 and miR-204 in vivo , we firstly cloned miR-192andmiR-204 mature sequence or siHOTTIP sequence after the CMV promoter in a tandem manner into pcDNA3 . 1 vector . The plasmids were named as pcDNA3 . 1-miR-192-miR-204 or pcDNA3 . 1-siHOTTIP and transfected into HepG2 cells . After G418 ( Geneticin ) selection , we isolated a stable cell clone with relative high expression of miR-192 and miR-204 and another stable cell clone with significant silencing of lncRNA HOTTIP . Five-week-old female nude BALB/c mice were purchased from Vital River Laboratory ( Beijing , China ) . 1×108HepG2 cells with stable transfection of pcDNA3 . 1-miR-192-miR-204 , pcDNA3 . 1-siHOTTIPor pcDNA3 . 1 vector were inoculated subcutaneously into fossa axillaris of 6 nude mice ( n = 3 per group ) . Tumor volumes were measured every day after tumor volumes equaled to or were greater than 80 mm3 . All procedures involving mice were approved by the institutional Review Board of Beijing Institute of Radiation Medicine . The difference between two groups was calculated using Student’s t test . One-way analysis of variance was used to comparing differences between three or more groups . Spearman’s correlation was used to test the significance of association between miR-192 or miR-204 expression and HOTTIP expression . Association between miRNAs or HOTTIP and overall survival was examined using Kaplan-Meier plots and Cox proportional hazard regression analyses . A P value of less than 0 . 05 was used as the criterion of statistical significance . All analyses were performed with SPSS software package ( Version 16 . 0 , SPSS Inc . ) or GraphPad Prism ( Version5 , GraphPad Software , Inc . ) . | Accumulated evidence demonstrated that long non-coding RNAs ( lncRNAs ) play a pivotal role in tumorigenesis . Here , we for the first time demonstrated how microRNAs ( miRNAs ) impact onco-lncRNA HOTTIP expression and its biological significance in hepatocellular carcinoma ( HCC ) . We identified miR-192 and miR-204 as two miRNAs suppressing HOTTIP expression via the Argonaute 2-mediated RNA interference pathway . The dysregulation of the three ncRNAs was associated with overall survival of HCC patients . The posttranscriptional silencing of HOTTIP by miR-192 , miR-204 or HOTTIP siRNAs could significantly suppress viability of HCC cells in vitro and in vivo . Besides one of the known target gene HOXA13 , glutaminase was identified as a potential downstream target of the miR-192/-204-HOTTIP axis in HCC . Our data will have high impact on our understanding of how miRNAs are involved in the fine-regulation of lncRNAs and the potential translation in clinic . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2015 | fMiRNA-192 and miRNA-204 Directly Suppress lncRNA HOTTIP and Interrupt GLS1-Mediated Glutaminolysis in Hepatocellular Carcinoma |
Upon infection of mammalian cells , enterohemorrhagic E . coli ( EHEC ) O157:H7 utilizes a type III secretion system to translocate the effectors Tir and EspFU ( aka TccP ) that trigger the formation of F-actin-rich ‘pedestals’ beneath bound bacteria . EspFU is localized to the plasma membrane by Tir and binds the nucleation-promoting factor N-WASP , which in turn activates the Arp2/3 actin assembly complex . Although N-WASP has been shown to be required for EHEC pedestal formation , the precise steps in the process that it influences have not been determined . We found that N-WASP and actin assembly promote EHEC-mediated translocation of Tir and EspFU into mammalian host cells . When we utilized the related pathogen enteropathogenic E . coli to enhance type III translocation of EHEC Tir and EspFU , we found surprisingly that actin pedestals were generated on N-WASP-deficient cells . Similar to pedestal formation on wild type cells , Tir and EspFU were the only bacterial effectors required for pedestal formation , and the EspFU sequences required to interact with N-WASP were found to also be essential to stimulate this alternate actin assembly pathway . In the absence of N-WASP , the Arp2/3 complex was both recruited to sites of bacterial attachment and required for actin assembly . Our results indicate that actin assembly facilitates type III translocation , and reveal that EspFU , presumably by recruiting an alternate host factor that can signal to the Arp2/3 complex , exhibits remarkable versatility in its strategies for stimulating actin polymerization .
Enterohemorrhagic Escherichia coli ( EHEC ) are an important source of diarrheal illness worldwide and are the leading cause of pediatric renal failure in the United States . O157:H7 is the most common EHEC serotype associated with serious illness and includes many of the most virulent strains [1] . During colonization , EHEC induce striking morphological changes of the intestinal epithelium , resulting in the formation of attaching and effacing ( AE ) lesions . These structures are characterized by the effacement of microvilli and intimate attachment of EHEC to the epithelial cell surface . The adherent bacteria also reorganize the host cell cytoskeleton into filamentous ( F- ) actin pedestals . In addition to EHEC , several related pathogens , including enteropathogenic E . coli ( EPEC ) , also generate AE lesions and actin pedestals on intestinal epithelial cells during the course of infection [1] . Importantly , mutations in any of these bacteria that abolish their ability to generate AE lesions prevent their colonization [2] , [3] , [4] , [5] . Moreover , an EHEC mutant that is capable of intimate attachment but selectively defective for actin pedestal formation does not expand its initial infectious niche in experimentally-infected rabbits [6] . The capacity to generate actin pedestals depends on the translocation of bacterial effector proteins into mammalian host cells via a type III secretion system ( T3SS ) [7] , [8] . This macromolecular structure spans the inner and outer bacterial membranes , extends from the bacterial surface , and includes a long filamentous appendage that contacts the mammalian cell surface and functions as a conduit for effector secretion . The tip of this filament includes translocator proteins that form pores in target cell membranes and promote the entry of effectors into the mammalian cell . The EHEC- and EPEC-encoded type III secretion apparatuses are homologous to the T3SSs found in a wide range of pathogens , many of which also trigger actin rearrangements in the host cell . For example , type III translocated effectors of Shigella , Salmonella , and Yersinia induce cytoskeletal changes that can promote bacterial entry into the host cell . Actin assembly may also affect type III translocation , because several effectors that misregulate signaling pathways that control the actin cytoskeleton have a significant influence on the efficiency of translocation by Shigella and Yersinia [9] , [10] . For AE pathogens , the T3SS delivers effectors that activate the WASP and N-WASP actin nucleation-promoting factors to promote pedestal formation [11] , [12] , [13] . WASP , which is expressed in hematopoietic cells , and its homolog N-WASP , which is ubiquitously expressed , stimulate the Arp2/3 complex , a group of seven proteins that collectively nucleate actin into filaments [14] , [15] . The C-terminal WCA ( WH2-connector-acidic ) domain of N-WASP directly binds and activates the Arp2/3 complex , but this domain is normally sequestered by its intramolecular interaction with an internal regulatory element , the GBD ( GTPase-binding l;domain ) . Binding of the GTPase Cdc42 to the GBD disrupts these autoinhibitory GBD-WCA interactions , and frees the WCA domain to activate Arp2/3-mediated actin assembly . Other factors , including the SH2/SH3 domain-containing adaptor proteins Nck1-2 , also activate N-WASP , but bind to a proline-rich domain ( PRD ) that lies between the GBD and WCA regions [16] , [17] . One effector essential for intimate attachment and actin pedestal formation by AE pathogens is the Tir ( translocated intimin receptor ) protein [18] , [19] . Upon type III translocation into the mammalian cell , Tir becomes localized in the plasma membrane with a central extracellular domain that binds the bacterial outer membrane adhesin intimin [20] . N- and C-terminal to the intimin-binding domain are two transmembrane segments and the intracellular domains of Tir . For canonical EPEC strains of serotype O127:H6 , Tir is the only effector required for pedestal formation , as simply clustering Tir in the plasma membrane is sufficient to recruit the Nck adaptor proteins and trigger F-actin assembly [21] . In contrast to canonical EPEC strains , EHEC strains of serotype O157:H7 require a second translocated effector , in addition to Tir , to trigger pedestal formation . EHEC Tir recruits this effector , named EspFU ( also known as TccP ) [22] , [23] , indirectly , as the host protein intermediates IRTKS and IRSp53 are responsible for linking EspFU to Tir during actin pedestal assembly [24] , [25] . EspFU contains a C-terminal region with multiple 47-residue proline-rich repeats that each bind to the GBD of N-WASP and directly displace the WCA domain to allow it to activate the Arp2/3 complex [26] , [27] . Whereas a single EspFU repeat is capable of activating N-WASP , tandem repeats synergize during actin polymerization by promoting N-WASP dimerization , which allows it to bind Arp2/3 with much higher affinity than monomeric N-WASP [27] , [28] , [29] . EHEC is unable to generate pedestals on N-WASP-deficient cells [12] , and the fact that EspFU targets N-WASP to promote actin assembly provides a highly plausible explanation for this finding . Nevertheless , the observations that actin assembly influences type III translocation by other pathogens raised the possibility that N-WASP may also contribute to an earlier step in the process of pedestal formation . In fact , we show here that N-WASP and actin assembly are important for the translocation of Tir and EspFU into mammalian cells by EHEC O157:H7 . Intriguingly , when delivered into cells by EHEC-independent means , Tir and EspFU are fully capable of stimulating actin pedestal formation in the absence of N-WASP . These results add an additional layer of complexity to our understanding of the interactions between EHEC and its host cells , and highlight the functional versatility of EspFU .
N-WASP deficiency in cultured mammalian cells is known to block actin pedestal formation by EHEC [12] . An obvious rationale for this requirement is that N-WASP promotes actin polymerization in the pedestal , as suggested by the observation that EspFU recruits , binds and activates N-WASP [22] , [23] . However , given the evidence that actin polymerization might also facilitate the delivery of effectors into the host cell [9] , [10] , we examined a role for N-WASP during type III effector translocation by EHEC using genetically modified murine fibroblast-like cells ( FLCs ) [30] . Consistent with the previous characterization of wild type ( NW+/+ ) and N-WASP knockout ( NW−/− ) cell lines , immunoblotting demonstrated that N-WASP was expressed only in the wild type cells ( Figure 1A , left ) . We also investigated the expression of the N-WASP homolog WASP , which is also a target of EspFU [26] , and found that neither WASP mRNA or protein was detected in NW−/−cells ( Figure 1A , right ) . As reported using an independently derived N-WASP-deficient cell line [12] , EHEC generated actin pedestals on wild type , but not knockout cells ( Figure 1B ) . To assess Tir translocation , we fused the C-terminus of the EHEC Tir molecule to the TEM-1 β-lactamase ( Bla ) . The translocation of this fusion protein into host cells can be detected by β-lactamase-mediated cleavage of a FRET reporter , resulting in a change in fluorescent wavelength emission from green ( 520 nm ) to blue ( 460 nm ) , as previously described [31] . Such fusions have been used extensively for assessing Tir translocation [32] , and maintain Tir function , as our Tir-Bla fusion complemented a bacterial Tir deletion for pedestal-forming function on NW+/+ cells ( Figure S1A ) . After infection of wild type or N-WASP-deficient FLCs with EHEC expressing the Tir-Bla fusion , the percentage of blue cells was scored visually by fluorescent microscopy ( Figure S1B ) and expressed as a translocation index . By this measure , the translocation of Tir by EHEC into N-WASP-knockout cells occurred ∼3-fold less efficiently than into wild type cells after a 6h infection ( Figure 1C ) . The requirement for N-WASP for efficient translocation was not restricted to Tir , because the level of translocation of an EspFU-Bla fusion into N-WASP-knockout cells was also diminished relative to wild type cells , albeit not quite as low as translocation of Tir-Bla ( Figure 1C ) . In accordance with these results , we found that treatment of HeLa cells with wiskostatin , an inhibitor of N-WASP , significantly impaired translocation of the EspFU-Bla fusion into host cells ( Figure S1C ) . Given that the Tir-Bla translocation index relies on binary scoring of ( green vs . blue ) cells by visual inspection , it may not reflect the true severity of the defect in Tir translocation into NW−/− cells . The deficiency in the translocation of Tir into N-WASP-deficient cells by EHEC is predicted to result in a decrease in the amount of Tir clustered beneath bound bacteria . Therefore , to examine Tir localization , we infected wild type or knockout cells with EHECΔtir harboring pHA-TirEHEC , which encodes an N-terminally HA-tagged Tir that can be detected with an anti-HA antibody and visualized microscopically . Whereas Tir foci were readily observed beneath EHEC bound to wild type cells , they were not detected beneath EHEC on N-WASP-knockout cells ( Figure 1D ) , consistent with a significant defect in Tir translocation . To test whether the requirement for N-WASP for efficient translocation reflects a role for F-actin assembly in promoting translocation , we examined Tir localization beneath bound bacteria after treatment with cytochalasin D , which binds actin filament ends and prevents polymerization . Microscopic visualization revealed that cytochalasin D treatment resulted in a loss of foci of HA-tagged Tir beneath bacteria bound to HeLa cells ( Figure 1E ) . In addition , cytochalasin D and latrunculin A , which binds actin monomers and triggers depolymerization , each partially inhibited of translocation of Tir-Bla fusion protein into HeLa cells ( data not shown ) . Collectively , these data suggest that N-WASP-mediated actin polymerization facilitates EHEC-mediated effector translocation . We next tested whether impaired Tir translocation into N-WASP-knockout FLCs results in a measurable effect on the ability of Tir to promote bacterial attachment . We infected wild type or N-WASP-knockout cells with the intimin-deficient EPECΔeae or EHECΔeae mutants to allow for translocation of Tir , and then , after killing these bacteria with gentamicin and removing them by washing , challenged these cells with non-pathogenic GFP-expressing E . coli strains that harbor pIntEPEC or pIntEHEC plasmids to express intimin . Previous studies have shown that E . coli/pInt , but not E . coli/vector , attach to monolayers primed with EPEC or EHEC strains that translocate Tir , but not to unprimed monolayers [33] , [34] , thus allowing a specific measure of native intimin binding to translocated Tir . A bacterial binding index , defined as the percentage of cells with at least five adherent GFP- and intimin-expressing bacteria , was determined microscopically . Bacterial binding to N-WASP-knockout cells primed with EHECΔeae was approximately 3-fold lower than to primed wild type cells ( Figure 2A ) . EPEC generates pedestals on cultured cells more efficiently than EHEC [35] , so we tested whether EPEC might correspondingly translocate Tir into N-WASP-knockout cells more efficiently . In fact , bacterial binding to N-WASP-deficient cells primed with EPECΔeae was indistinguishable from binding to EPECΔeae-primed wild type cells ( Figure 2A ) . To test whether the difference between EHEC and EPEC in functional Tir translocation was due to allelic differences in their respective Tir proteins , we primed wild type or N-WASP-knockout FLCs with EPECΔtir-eae expressing either HA-TirEPEC or HA-TirEHEC , and then challenged cells with E . coli expressing the corresponding intimin ligand . Alternatively , we primed cells with EHECΔtir-eae expressing either HA-TirEHEC or HA-TirEPEC prior to challenge . We found that EPEC was capable of translocating either Tir variant into N-WASP-knockout cells to promote intimin-mediated attachment at nearly wild type levels . In contrast , priming with EHEC expressing either HA-TirEHEC or HA-TirEPEC gave binding values two- to three-fold lower than wild type ( Figure 2B ) . These observations indicate that Tir translocation by EHEC is more dependent on N-WASP than Tir translocation by EPEC , irrespective of the genetic origin of the Tir molecule . The observations that EHEC does not efficiently translocate Tir or EspFU into N-WASP-deficient cells , raised the intriguing possibility that the defect in EHEC pedestal formation on these cells was due to inefficient effector translocation into cells rather than a lack of Tir-EspFU signaling within the cell . Since , in the functional assay described above , EPEC translocated Tir into N-WASP knockout cells better than EHEC , we adopted a heterologous expression system using KC12 , an EPEC derivative that has been chromosomally engineered to express HA-tagged EHEC Tir [22] , [36] , for achieving delivery of EHEC Tir and EspFU into N-WASP-knockout cells . Importantly , although translocation of TirEHEC-Bla and EspFU-Bla into N-WASP-deficient cells by KC12 occurred with somewhat delayed kinetics compared to wild type cells ( Figure S2 ) , the defect in translocation was mild at 6 h postinfection ( Figure 3A ) . To determine if type III translocation by KC12 was reflected in the localization of Tir beneath bound bacteria , we infected N-WASP-knockout cells with KC12/pEspFU , a strain that expresses a myc-tagged EspFU harboring six C-terminal repeats and generates actin pedestals in manner that is mechanistically indistinguishable from canonical EHEC strains [22] . HA-Tir foci were observed with somewhat delayed kinetics and lower frequency in NW−/− than NW+/+ FLCs , but nearly 50% of KC12/pEspFU bound to N-WASP-knockout cells generated Tir foci by 5 h postinfection ( Figure 3B ) . Given that KC12/pEspFU was only partially diminished for Tir and EspFU translocation , we sought to determine whether this strain could generate actin pedestals on N-WASP knockout cells . Remarkably , upon infection of NW−/− FLCs , numerous actin pedestals were formed by KC12/pEspFU ( Figure 3C , top row ) , indicating that EHEC Tir and EspFU are capable of signaling to the actin cytoskeleton in the absence of N-WASP . Pedestal formation required EspFU , because KC12 lacking pEspFU failed to generate pedestals in these cells ( Figure 3C , bottom row ) . To quantify the efficiency of actin pedestal formation , we infected wild type and N-WASP-knockout cells with KC12/pEspFU , visually identified sites of HA-Tir localization beneath bound bacteria , and then calculated the percentage of those Tir foci that were associated with actin pedestals . This specific scoring method circumvented the inhibitory effects of N-WASP deficiency on effector entry ( Figure 1C; Figure 2 ) and HA-Tir localization in cells ( Figure 3B ) , and specifically measured intracellular signaling after Tir translocation . KC12/pEspFU and the control strain EPECΔtir/pHA-TirEPEC , which generates pedestals using the Nck-N-WASP-dependent pathway [13] , [36] , [37] , both formed pedestals efficiently on wild type cells: after infection for 3h , >95% of Tir foci were associated with pedestals , while at 5h this level reached >98% ( Figure 3D ) . In NW−/− FLCs , EPECΔtir/pHA-TirEPEC , which utilizes Nck adaptor proteins to activate N-WASP , was totally incapable of generating pedestals ( Figure 3D ) , consistent with results utilizing an independently generated N-WASP knockout cell line [13] . In contrast , 80% of KC12/pEspFU-associated Tir foci triggered actin pedestals at 3h , and this level rose to 95% at 5h postinfection . Thus , the more efficient delivery of EHEC Tir and EspFU by the EPEC-derived strain KC12 results in a surprisingly effective ability to induce pedestal formation in the absence of N-WASP . IRTKS , along with the closely related protein IRSp53 , regulates actin dynamics at the plasma membrane [38] , and functions as a linker between EHEC Tir and EspFU during N-WASP-promoted pedestal formation [24] , [25] . Given that EspFU localized to sites of bacterial attachment in N-WASP-knockout cells ( Figure 3C ) , we assessed whether IRTKS plays a role in EspFU recruitment in the absence of N-WASP by examining the distribution of IRTKS in N-WASP-knockout cells infected with KC12/pEspFU . Immunofluorescence microcopy indicated that IRTKS localized near the tips of pedestals ( Figure 4 , top row ) , where it colocalized with EspFU ( middle row ) , consistent with a role in linking Tir and EspFU during N-WASP-independent signaling . Moreover , when these cells were infected with KC12 lacking EspFU , IRTKS still localized to sites of bacterial attachment , suggesting that even in the absence of EspFU , N-WASP , and actin pedestals , the Tir-binding activity of IRTKS is sufficient to promote IRTKS recruitment ( Figure 4 , bottom row ) . Thus , N-WASP does not have any apparent effects on the signaling events that occur between type III effector translocation and EspFU recruitment to Tir . For pedestal formation by EHEC on wild type cells , recruitment and membrane clustering of a complex of Tir , IRTKS and EspFU is sufficient to trigger pedestal formation [24] . However , we have also shown that membrane clustering of HN-Tir-EspFU-[R1-6] , a fusion in which the C-terminal cytoplasmic domain of Tir is replaced by six C-terminal repeats of EspFU , is fully functional for pedestal formation [26] , [28] , indicating that clustering of EspFU alone is sufficient to stimulate this signaling pathway . To similarly determine the potential requirements of EspFU , Tir and IRTKS during N-WASP-independent actin pedestal formation , we tested whether HN-Tir-EspFU-[R1-6] could trigger actin assembly in N-WASP-knockout cells . After transfection with a plasmid encoding HN-Tir-EspFU-[R1-6] , we infected NW−/− FLCs with EPECΔtir and treated cells with an anti-HA antibody to visualize the fusion protein and with phalloidin to stain F-actin . These bacteria readily generated actin pedestals on cells expressing HN-Tir-EspFU-[R1-6] , but not cells expressing HN-TirΔC , which lacks a C-terminal signaling domain ( Figure 5A ) , indicating that the EspFU repeats are essential for actin pedestal formation in these cells . To test whether pedestal formation on N-WASP-knockout cells requires any proteins other than the Tir-EspFU fusion , we next treated HN-Tir-EspFU-[R1-6]-expressing cells with the non-pathogenic E . coli strain that expresses intimin . These bacteria , which are incapable of type III secretion and serve to simply cluster the HN-Tir-EspFU-[R1-6] fusion protein , generated actin pedestals on N-WASP-knockout cells in a manner indistinguishable from those formed on wild type cells ( Figure 5B and [26] , [28] ) . In contrast , a control HN-Tir fusion protein lacking the C-terminal repeats of EspFU was unable to elicit pedestals . Thus , we conclude that , as is the case for pedestal formation in N-WASP-proficient cells , the central role of Tir and IRTKS in N-WASP-knockout cells is to promote the clustering of the EspFU repeats beneath the plasma membrane . Moreover , in the absence of N-WASP , EspFU remains the most essential component of the signaling pathway that leads to actin pedestal assembly . The interaction of EspFU with N-WASP or WASP results in the activation of the Arp2/3 complex and actin nucleation in vitro [22] , [26] , [27] , [39] . To examine the potential role of Arp2/3 in pedestals generated in the absence of N-WASP , we first assessed whether this complex is recruited to sites of pedestal formation in N-WASP-knockout cells . Immunofluorescence microscopy using anti-Arp3 antibodies revealed recruitment of the Arp2/3 complex in pedestals formed by KC12/pEspFU in N-WASP knockout cells as well as wild type cells ( Figure 6A ) , suggesting that Arp2/3 is likely involved in actin pedestal formation under both circumstances . To test for a functional role of the Arp2/3 complex in pedestal formation , we took advantage of the fact that overexpression of the N-WASP WCA domain results in sequestration and/or ectopic activation of the Arp2/3 complex [14] , [15] , [40] . Whereas 95% of cells expressing a GFP control protein contained pedestals upon infection with EPECΔtir/pHA-TirEPEC or KC12/pEspFU , <5% of wild type FLCs expressing GFP-WCA harbored pedestals ( Figure 6B and data not shown ) , confirming the importance of proper Arp2/3 activity in actin pedestal assembly . Moreover , this dominant negative GFP-WCA construct also blocked actin pedestal formation by KC12/pEspFU in N-WASP-knockout FLCs ( Figure 6B ) . Finally , genetic depletion of the Arp2/3 subunits Arp3 and ARPC4 abolished pedestal formation on wild type HeLa cells , which are predicted to support both N-WASP-dependent and N-WASP-independent pedestal formation ( Figure S3 ) . Consistent with previous reports , we found that EspFU derivatives were unable to directly activate the Arp2/3 complex to promote actin polymerization in vitro ( Figure S4; [23] , [27] ) . Collectively , these data suggest that in generating pedestals in N-WASP-deficient cells , EspFU recruits an alternate host factor ( or factors ) that triggers Arp2/3-mediated actin assembly . WASP and N-WASP are members of a family of nucleation promoting factors ( NPFs ) that activate Arp2/3 , a family that includes WAVE proteins , WASH , and WHAMM [41] . IRSp53 , which has been shown to link Tir and EspFU in some cells [25] can bind and activate WAVE2 [38] . In addition , WAFL is a protein with a predicted Arp2/3-binding acidic peptide that associates with actin filaments and has been implicated in endosomal trafficking [42] . To investigate whether these factors could be involved in N-WASP-independent actin pedestal formation , we determined whether they localized to actin pedestals generated in an N-WASP-independent manner . NW−/− FLCs ectopically expressing GFP fusions to WAVE2 , WASH , WAFL , WHAMM , or ( as a control ) N-WASP were infected with KC12/pEspFU and phalliodin-stained to visualize actin pedestals . Pedestals were efficiently formed in the presence of all NPFs , and as expected , GFP-N-WASP distinctly localized to pedestals ( and often to their tips ) beneath bound bacteria ( Figure 7A , top row , and data not shown ) . None of the other NPFs localized in a similar fashion ( Figure 7A ) . GFP-WAVE2 faintly and diffusely localized to sites of bacterial attachment ( Figure 7A , second row ) , but this localization was also observed around bacteria that were not associated with actin pedestals ( data not shown ) . Furthermore , WAVE2 was not required for N-WASP-independent pedestal formation , because KC12/pEspFU generated pedestals normally on NW−/− FLCs in which WAVE2 expression was stably knocked down by more than 95% ( Figure 7B ) . Together with the observation that EspFU does not directly activate Arp2/3 , these data are consistent with the model that EspFU is capable of utilizing an alternate NPF to activate Arp2/3 in NW−/− FLCs . Allosterically activated N-WASP is associated with more potent actin assembly when multimerized [29] , [43] , [44] , [45] , an observation explained by the ability of dimeric N-WASP to bind the Arp2/3 complex with much higher affinity than monomeric N-WASP [29] . Nevertheless , when Tir-EspFU fusions harboring different numbers of repeats are clustered beneath the plasma membrane using anti-Tir antibody-coated particles , a single EspFU repeat is capable of triggering actin pedestal formation in N-WASP-proficient cells [26] , [28] . This prompted us to examine the role of the repeat quantity in N-WASP-independent actin assembly . To directly compare a requirement for different numbers of repeats during EspFU-mediated assembly in the presence or absence of N-WASP , we used S . aureus and anti-Tir antibodies to cluster HN-Tir-EspFU fusions harboring various numbers of repeats in wild type and N-WASP-knockout FLCs . We then measured the fraction of cells that contained actin pedestals . Whereas in wild type FLCs , a single repeat resulted in pedestal formation levels of ∼45% ( “R1” , Figure 8A , black bars [28] ) , this derivative generated no pedestals in N-WASP-knockout cells ( Figure 8A , gray bars ) . ( Note that the experiments with wild type and N-WASP-knockout cells were performed in parallel , but those using wild type cells were published previously [28] and are shown in Figure 8A for ease of comparison . ) Clustering of Tir-EspFU fusions harboring two to six repeats in N-WASP-knockout FLCs resulted in cellular pedestal formation efficiencies of approximately 50–55% , which is significantly less than the levels of 75–90% that were observed in wild type cells ( Figure 8A; [28] ) . To further investigate the relationship between number of repeat units and N-WASP-independent actin polymerization we sought to measure pedestal formation when EspFU is present in the cytosol and Tir is independently translocated into the plasma membrane . Under these conditions , ∼90% of wild type cells expressing any GFP-EspFU construct containing at least two repeats generated pedestals in response to infection with KC12 ( Figure 8B; [28] ) . To similarly examine pedestal formation when EspFU must act in concert with Tir in the absence of N-WASP , we infected GFP-EspFU-expressing N-WASP-knockout cells with KC12 ( Figure S5 ) . Only ∼50% of cells expressing the four- and six-repeat truncations generated pedestals , and just 15% of cells expressing the three-repeat derivative formed pedestals ( Figure 8B ) . No pedestals were observed in cells expressing fewer than three repeats ( Figure 8B ) . In addition , in cells expressing EspFU derivatives harboring three or more repeats , pedestal formation was less efficient without N-WASP . Thus , N-WASP deficiency is associated with a more stringent requirement for multimeric EspFU variants in order to trigger actin assembly , and even for multi-repeat EspFU derivatives that do trigger assembly in N-WASP-knockout cells , the efficiency of pedestal formation was somewhat reduced . The EspFU repeat contains an N-terminal region that , upon WASP binding , adopts an α-helical conformation that interacts with a hydrophobic groove in the GBD [26] . Thus , alanine substitution of three conserved hydrophobic residues in the EspFU α-helix abolished N-WASP recruitment and actin assembly in mammalian cells [26] . To test whether this region of the EspFU repeat plays an essential role in N-WASP-independent actin assembly , we constructed a Tir-EspFU fusion comprising two EspFU repeats that each harbored the V4A/L8A/L12A triple alanine substitution ( referred to as VLL/AAA; Figure 9A ) . Tir-EspFU-2RVLL/AAA and the corresponding wild type variant , Tir-EspFU-2RWT , were expressed in NW−/− FLCs and clustered in the membrane using an EPEC strain that expresses intimin but not Tir or EspFU , and the cells stained with an anti-HA antibody to visualize the clustered fusion proteins and with phalloidin to stain F-actin ( Figure 9B ) . Clustering of Tir-EspFU-2RWT but not Tir-EspFU-2RVLL/AAA induced robust pedestal formation under bound bacteria ( Figure 9B , top row ) , indicating that the WASP/N-WASP-binding region of EspFU is critical for N-WASP-independent actin pedestal formation .
N-WASP is required for actin pedestal formation by EHEC [12] , and the observation that EspFU directly binds and activates this nucleation-promoting factor provided an obvious explanation for this requirement . However , we now show that N-WASP is also important for an earlier step in actin pedestal formation , type III translocation of Tir and EspFU . We evaluated three properties of Tir that would reflect proper translocation into mammalian host cells . We assessed entry of Tir-Bla reporter proteins into the cytosol , quantified the ability of intimin-expressing bacteria to bind to primed host cells containing translocated Tir , and directly visualized the localization and clustering of Tir in the plasma membrane . These approaches each revealed that Tir translocation was diminished in N-WASP-knockout cells . The translocation defect was not restricted to Tir , because EHEC-mediated delivery of an EspFU-Bla fusion protein was also lower in N-WASP-knockout cells . Given that F-actin assembly promotes type III translocation of effectors by other pathogens [9] , [10] , it seems likely that the ability of N-WASP to promote actin assembly contributes to translocation by EHEC . Consistent with this possibility , translocation was significantly impaired by cytochalasin D or latrunculin A , which inhibit actin assembly , or by wiskostatin , an inhibitor of N-WASP [46] . These results raise the possibility that one of the functions of Tir- and EspFU-driven actin polymerization is to promote efficient translocation of one or more of the other 20–30 EHEC effectors . Interestingly , multiple pathogens encode type III secreted proteins that modify the actin cytoskeleton and have been shown to influence type III translocation . For example , the Shigella type III translocon protein IpaC stimulates Src recruitment and actin polymerization at sites of bacterial entry , and its inactivation diminishes type III translocation [10] . The Yersinia effectors YopE and YopT induce misregulation of Rho-family GTPases , inhibit signaling from these cytoskeletal regulators , and are postulated to temporally limit the phase of high efficiency type III translocation [9] , [47] , [48] , [49] , [50] . For EHEC , low levels of Tir translocation still occurred when actin polymerization was disrupted ( Figure 1C ) , and multiple reports have demonstrated that EHEC mutants defective in pedestal formation are still capable of translocation [22] , [39] , [51] , [52] , indicating that actin assembly is not absolutely required for this process . This residual level of translocation may also explain the observation that for N-WASPdel/del cells , an independently derived N-WASP-deficient embryonic fibroblast cell line , Tir is translocated by an EHECΔespFU mutant efficiently enough to recruit ectopically expressed GFP-EspFU beneath sites of bacterial attachment [25] . Although it has now been shown that actin assembly promotes type III translocation by several pathogens , the specific function ( s ) of assembly is not clear . For EHEC , pedestal formation may increase the area of bacterium-host cell contact and/or the stability of bacterial binding , thereby enhancing effector translocation . Alternatively , type III translocation by several pathogens , including EPEC , is thought to occur at lipid microdomains [53] , [54] , [55] , and it has been postulated that actin assembly may facilitate the recruitment of such domains to bound bacteria [9] . Interestingly , we found that although EPEC-mediated translocation of Tir into mammalian cells was somewhat delayed and diminished by N-WASP-deficiency , this defect was not large enough to have a discernable defect in intimin-mediated bacterial binding . The reasons for the lower N-WASP-dependence of translocation by EPEC are not known , but EPEC exhibits particularly robust type III secretion in vitro and generates pedestals more efficiently on cultured cells than does EHEC [35] . We utilized KC12/pEspFU , an EPEC strain engineered to express TirEHEC and EspFU , to more efficiently deliver EHEC Tir and EspFU into N-WASP knock out cells . Surprisingly , these effectors were capable of generating actin pedestals with ultimately high efficiency: 95% of Tir foci beneath cell-bound KC12/pEspFU were associated with pedestals in N-WASP-knockout cells after 5h infection . Thus , the defect in EHEC pedestal formation on N-WASP-knockout FLCs is apparently not due to an inability of Tir and EspFU to stimulate actin polymerization once delivered to the mammalian cell . The N-WASP-independent pathway of pedestal formation shares several parallels with pedestal formation in wild type cells . Tir and EspFU are the only bacterial effectors required , since ectopic expression of the two proteins in N-WASP-knockout cells , followed by Tir clustering , was sufficient to induce localized actin assembly ( data not shown ) . IRTKS , which has been shown to link EspFU to Tir in N-WASP-proficient cells [24] , [25] , was recruited to sites of bacterial attachment on N-WASP-knockout cells . Moreover , the central role of the C-terminal cytoplasmic domain of Tir is to promote IRTKS-mediated recruitment of EspFU , because a Tir fusion protein in which this Tir domain is replaced by EspFu was competent for triggering actin polymerization . Finally , the Arp2/3 complex , the actin nucleator that acts in conjunction with N-WASP , was recruited to sites of pedestal formation in N-WASP-knockout cells . Inactivation of Arp2/3 function blocked pedestal formation on both wild type and N-WASP-knockout cells , indicating that this nucleator is required for all pathways of pedestal formation . EspFU was unable to directly activate the Arp2/3 complex in vitro , suggesting that , in addition to recruiting and activating N-WASP , EspFU also recruits and activates another regulator of actin assembly that directly or indirectly activates the Arp2/3 complex . Interestingly , a triple amino acid substitution in EspFU that disrupts binding of EspFU to WASP/N-WASP abolished pedestal formation in N-WASP-knockout cells , suggesting that the putative alternate regulator of actin assembly may recognize the same or an overlapping segment of EspFU . This finding is consistent with the hypothesis that one of the WASP-related nucleation promoting factors may participate in this pathway . However , GFP-tagged derivatives of WAVE2 , WASH and WHAMM were not efficiently recruited to pedestals in N-WASP-knockout cells ( Figure 7 ) ; although WAVE2 demonstrated a modest degree of colocalization with bacteria , pedestals were formed efficiently on N-WASP-deficient cells genetically depleted for WAVE2 ( Figure S4 ) . Interestingly , KC12/pEspFU did not form pedestals on N-WASPdel/del cells , suggesting that this independently derived N-WASP-deficient cell line [13] may lack the putative alternate actin assembly factor ( D . V . , J . L . , unpub . obs . ) . One can imagine several scenarios by which N-WASPdel/del cells might aid in the identification of the factor ( s ) responsible for driving actin polymerization in the absence of N-WASP , a finding that might provide new insights into the normal regulation of actin assembly in mammalian cells . Notably , pedestal formation by this N-WASP-independent pathway occurred somewhat less efficiently than when both N-WASP and the putative factor are present , because clustering of Tir-EspFU fusion protein generated pedestals 25–30% less efficiently on knockout cells than on wild type cells . In addition , pedestal formation on N-WASP-knockout cells showed a more stringent requirement for multiple EspFU repeats . Whereas clustering of a single EspFU repeat was sufficient to stimulate actin pedestals in the presence of N-WASP [26] , [28] , pedestal formation was only triggered upon clustering of two or more repeats in the absence of N-WASP . In addition , while two repeats are required to complement an espFU-deficient strain for pedestal formation on wild type FLCs [28] , three repeats were required to detect pedestals in NW−/− FLCs , and four or more repeats were required for maximal levels of complementation . A correlation between the number of EspFU repeats and stimulation of actin assembly , both in vitro and in vivo , has been observed previously [27] , [28] , [29] , [39] . Assuming that at least three repeats are required for N-WASP-independent pedestal formation and that an N-WASP-independent pathway for actin assembly confers a selective advantage in nature , one would predict that the vast majority of EspFU alleles found among E . coli isolates would carry at least three repeats . In fact , of 435 EPEC or EHEC strains in which espFU was detected by PCR , 433 ( or >99 . 5% ) of espFU alleles appeared , by length of the PCR product , to encode three or more proline-rich repeats [56] . Therefore , future characterizations of the N-WASP-independent mechanism of actin pedestal formation will enhance our understanding of the role of EspFU in the survival , propagation , or pathogenesis of EHEC .
All EHEC strains used in this study were derivatives of TUV93-0 , a Shiga toxin-deficient version of the prototype 0157:H7 strain EDL933 [36] . The parental EPEC strain was the 0127:H6 prototype JPN15/pMAR7 . EPEC KC12 [36] , EPECΔtir [36] , EPECΔtir-eae [36] and EHECΔeae [57] , EHECΔtir-eae [57] were described previously . Non-pathogenic laboratory strains of E . coli harboring plasmids encoding EHEC or EPEC intimin ( pInt ) have also been described [33] . These strains were transformed with a separate plasmid for expression of GFP ( a gift from A . Poteete ) . For beta-lactamase ( Bla ) translocation assays , plasmids pMB196 ( pTirEHEC-Bla ) and pMB200 ( pEspFU-Bla ) were constructed as follows: PCR products encoding Tir and EspFU with their endogenous promoter were amplified with primers flanked with EcoRI and KpnI restriction sites , digested with the appropriate enzymes and cloned into the similarly digested plasmid pMM83 [58] . Plasmids used for expression of GFP-EspFU and HA-Tir-EspFU fusion proteins in mammalian cells were described previously [28] . For dominant negative transfection , the WCA domain of rat N-WASP was amplified by PCR and cloned into the KpnI-EcoRI sites of plasmid pKC425 [59] . All E . coli strains were grown in LB media at 37°C for routine passage . Before infection of mammalian cells , EHEC and EPEC were cultured in DMEM containing 100 mM HEPES pH 7 . 4 , in 5% CO2 to enhance type III secretion . HeLa cells and FLCs were cultured in DMEM containing 10% FBS , 2mM glutamine and 50 µg/ml penicillin/streptomycin . Transfection of plasmid DNA was performed as previously described [52] . Total RNA from N-WASP-knockout cells was isolated using TRIzol reagent ( Invitrogen ) . A first strand cDNA was synthesized using the M-MLV ( Moloney Murine Leukemia Virus ) Reverse Transcriptase ( RT ) ( Invitrogen ) . Primers WASP_F ( 5′-GTGCAGGAGAAGATACAAAAAAGG-3′ ) and WASP_R ( 5′-GATCCCAGCCCACGTGGCTGACATG-3′ ) were used in a 40 cycle PCR reaction to detect WASP cDNA . cDNA from activated B cells , which express abundant WASP , was used as a positive control . Murine WAVE2 sequence ( 5′-GAGAAAGCATAGGAAAGAA-3′ ) was cloned into the Hpa1 and Xho1 sites of plasmid Lentilox 3 . 7 ( pLL 3 . 7 ) to generate WAVE2 RNAi stem loops . The virus was packaged into 293T cells using a four-plasmid system and was collected 48 hours after transfection . To knockdown WAVE2 , N-WASP-deficient cells were transformed with the lentivirus containing the WAVE2 RNAi stem loop . Knockdown efficiency was evaluated by western blot of the transformed N-WASP KO cells using anti-WAVE2 antibody ( Santa Cruz Biotechnology ) . N-WASP-deficient cells transformed with the empty lentiviral vector were used as control . Infections of HeLa cells and FLCs with EHEC and EPEC strains were performed as described in earlier work [36] . To evaluate intimin-mediated bacterial attachment in priming-and-challenge assays , FLCs were infected ( “primed” ) for 3h with EPECΔeae , or EPECΔtir-eae mutant harboring plasmids encoding HA-TirEPEC or HA-TirEHEC , or for 5h with EHECΔeae , or EHECΔtir-eae mutant harboring plasmids encoding HA-TirEPEC or HA-TirEHEC . These strains translocate Tir but do not form pedestals , and were removed from the cell monolayers after gentamicin treatment and washing . The primed cells were then infected ( “challenged” ) for 1h with non-pathogenic laboratory strains of E . coli harboring plasmids encoding either EHEC or EPEC intimin ( pInt ) and a plasmid that expresses GFP . A bacterial binding index , defined as the percentage of cells with at least five bound GFP-expressing bacteria , was determined microscopically ( Figure 2 ) . To determine the translocation index of Bla fusions into NW+/+ or NW−/− FLCs , cells were infected for 6 hours with EPEC or EHEC strains harboring Tir-Bla or EspFU-Bla fusions . Infected monolayers were washed with PBS and incubated for 1–2 hours at room temperature after addition of CCF2-AM ( Invitrogen ) supplemented medium . CCF2-AM treated cells were fixed and analyzed microscopically using a 20× objective . The percentage of blue cells , reflecting effector translocation , was estimated for 10–20 fields per experiment . For studies involving chemical inhibitors of actin assembly , DMSO , wiskostation or cytochalasin D ( Sigma ) was added 1 hour before infection . To determine the effect of wiskostatin on effector translocation , HeLa cells were infected with EHEC/pEspFU-Bla at a density of 2×107 bacteria/well in DMEM containing either DMSO or 6 µM wiskostatin . Plates were spun at 200 RCF for 5 minutes and then incubated at 37°C in 5% CO2 for 90 minutes . Cells were washed twice with PBS , overlaid with 100 µl of CCF2/AM loading solution in PBS , and then incubated for two hours at room temperature . Plates were transferred to a Synergy 2 microplate reader ( BioTek ) and excited at 400 nm ( 10-nm band-pass ) and the emission signal was read at 460 nm ( 40-nm band-pass ) and 528 nm ( 20-nm band-pass ) . After subtracting out background , the 460/528 nm ratio was calculated to determine the level of effector translocation . Upon treatment with cytochalasin D , HeLa cells were infected with EHEC/pHA-Tir and samples processed for detection of Tir foci and F-actin pedestals by immunofluorescence microscopy , as described below . Infected cells were fixed in 2 . 5% paraformaldehyde for 35 minutes and permeabilized with 0 . 1% Triton-X-100 in PBS as described previously [36] . Bacteria were visualized using DAPI ( 1 µg/ml; Sigma ) , and F-actin was detected using 4 U/ml Alexa568-phalloidin ( Invitrogen ) . To visualize HA-Tir derivatives , EspFU-myc , IRTKS , or IRSp53 , cells were treated with mouse anti-HA tag mAb HA . 11 ( 1∶500; Covance ) , mouse anti-myc 9E10 mAb ( 1∶250; Santa Cruz Biotechnology ) , or mouse anti-IRTKS mAb ( 1∶100; Novus Biologicals ) prior to treatment with Alexa488-conjugated goat anti-mouse antibody ( 1∶150; Invitrogen ) . To visualize the Arp2/3 complex , cells were treated with rabbit anti-Arp3 antibodies ( 1∶150; gift from R . Isberg , Tufts University ) prior to treatment with Alexa488-conjugated goat anti-rabbit antibody ( 1∶150; Invitrogen ) . To determine the pedestal formation efficiency of EPEC variants expressing HA-tagged Tir ( Figure 3D ) , the percentage of sites of translocated Tir ( HA-Tir foci ) that were associated with intense F-actin staining in FLCs were counted . To determine the pedestal efficiency in mammalian cells expressing HA-Tir-EspFU fusions or GFP-EspFU derivatives , which were identified by anti-HA or GFP fluorescence , the percentage of cells harboring at least 5 adherent S . aureus particles ( Figure 8A ) or KC12 bacteria ( Figure 8B ) that were associated with actin pedestals was quantified . At least 50 cells were examined per sample . Cells expressing extremely high fluorescence levels of EspFU were refractory to pedestal formation and were not included in these analyses . In vitro actin polymerization assays were performed using 500 nM EspFU derivative , 2 . 0 µM actin ( 7% pyrene-labeled ) and 20 nM recombinant Arp2/3 complex , in the presence of 20 nM N-WASP/WIP complex or not , and polymerization was measured as described previously [28] . Cells were collected in PBS plus 2mM EDTA , washed with PBS , and lysed in lysis buffer [50mMTris-HCl , pH 8 . 0 , 150mM NaCl , 1% Triton X-100 , 1mM Na3VO4 , 1mM PMSF , and 10µg/mL each of aprotinin , leupeptin , and pepstatin ( Sigma ) ] before mixing with sample buffer . Samples were boiled for 10 min , separated by 10% SDS/PAGE , and transferred to PVDF membranes . Membranes were blocked in PBS containing 5% milk before treatment with anti N-WASP , anti-WASP ( Santa Cruz Biotechnology ) , anti-Nck1 ( Upstate ) , anti-Arp3 , or anti-tubulin DM1A ( Thermo Scientific ) antibodies . Following washes , membranes were treated with secondary antibodies and developed [36] . | The food-borne pathogen enterohemorrhagic E . coli ( EHEC ) O157:H7 can cause severe diarrhoea and life-threatening systemic illnesses . During infection , EHEC attaches to cells lining the human intestine and injects Tir and EspFU , two bacterial molecules that alter the host cell actin cytoskeleton and stimulate the formation of “pedestals” just beneath bound bacteria . Pedestal formation promotes colonization during the later stages of infection . N-WASP , a host protein known to regulate actin assembly in mammalian cells , was previously shown to be manipulated by Tir and EspFU to stimulate actin assembly , and to be required for EHEC to generate actin pedestals . Surprisingly , we show here that N-WASP promotes the efficient delivery of Tir and EspFU into mammalian cells , and that when we utilized a related E . coli to enhance type III delivery of Tir and EspFU , actin pedestals assembled even in its absence . Thus , EHEC stimulates at least two pathways of actin assembly to generate pedestals , one mediated by N-WASP and one by an unidentified alternate factor . This flexibility likely reflects an important function of pedestal formation by EHEC , and study of the underlying mechanisms may provide new insights into the pathogenesis of infection as well as the regulation of the actin cytoskeleton of mammalian cells . | [
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] | 2010 | Enterohemorrhagic E. coli Requires N-WASP for Efficient Type III Translocation but Not for EspFU-Mediated Actin Pedestal Formation |
Metagenomics has transformed our understanding of the microbial world , allowing researchers to bypass the need to isolate and culture individual taxa and to directly characterize both the taxonomic and gene compositions of environmental samples . However , associating the genes found in a metagenomic sample with the specific taxa of origin remains a critical challenge . Existing binning methods , based on nucleotide composition or alignment to reference genomes allow only a coarse-grained classification and rely heavily on the availability of sequenced genomes from closely related taxa . Here , we introduce a novel computational framework , integrating variation in gene abundances across multiple samples with taxonomic abundance data to deconvolve metagenomic samples into taxa-specific gene profiles and to reconstruct the genomic content of community members . This assembly-free method is not bounded by various factors limiting previously described methods of metagenomic binning or metagenomic assembly and represents a fundamentally different approach to metagenomic-based genome reconstruction . An implementation of this framework is available at http://elbo . gs . washington . edu/software . html . We first describe the mathematical foundations of our framework and discuss considerations for implementing its various components . We demonstrate the ability of this framework to accurately deconvolve a set of metagenomic samples and to recover the gene content of individual taxa using synthetic metagenomic samples . We specifically characterize determinants of prediction accuracy and examine the impact of annotation errors on the reconstructed genomes . We finally apply metagenomic deconvolution to samples from the Human Microbiome Project , successfully reconstructing genus-level genomic content of various microbial genera , based solely on variation in gene count . These reconstructed genera are shown to correctly capture genus-specific properties . With the accumulation of metagenomic data , this deconvolution framework provides an essential tool for characterizing microbial taxa never before seen , laying the foundation for addressing fundamental questions concerning the taxa comprising diverse microbial communities .
Microbes are the most abundant and diverse life form on the planet . Recent advances in high-throughput sequencing and metagenomics have made it possible to study microbes in their natural environments and to characterize microbial communities in unprecedented detail . Such metagenomic techniques have been used to study communities inhabiting numerous environments , ranging from the bottom of the ocean [1] , [2] and the roots of plants [3] , [4] to the guts of mammals [5] . In particular , human-associated microbial communities have attracted tremendous attention , with several large-scale initiatives aiming to characterize the composition and variation of the human microbiome in health and disease [6]–[8] . Such studies have demonstrated a strong link between the microbiome and the health of the host , identifying marked compositional shifts in the microbiome that are associated with a variety of diseases [9]–[12] . Using a variety of experimental techniques and bioinformatic protocols [13] , [14] , metagenomics-based surveys can now characterize both the taxonomic and gene composition of the microbiome . Specifically , amplicon sequencing of conserved genes , such as the 16S ribosomal RNA gene , can be used to determine the relative abundance of each taxon [13] , [15] . Obtained 16S sequences are clustered into Operational Taxonomic Units ( OTUs ) , providing a proxy for the set of taxa found in the community [14] , [16] . Alternatively , shotgun metagenomic sequencing can be used to derive short sequences ( reads ) directly from the community without amplification [17] , [18] . These reads can then be mapped to a set of reference genes or orthologous groups ( e . g . , those defined by KEGG [19] or COG [20] ) to translate read count data into relative abundances of functional elements , representing the collective set of genes found in the microbiome . One of the key challenges in metagenomic research is the identification of the taxonomic origin for each shotgun metagenomic read or gene and , ultimately , the reconstruction of the genomes of member taxa directly from these reads . A diverse set of methods have been developed to parse shotgun metagenomic data and to obtain insights into the underlying taxa . These methods can be largely partitioned into several distinct categories , including: alignment to reference genomes , taxonomic classification , assembly , and binning ( Figure S1 ) . For ecosystems that are well-covered by reference genomes , such as the human microbiome [6] , [21] , alignment to reference genomes provides a way to determine the abundance of the various strains , species , or clades in the community [6] , [8] , [22] and can be used to assess strain variation within and between samples [23] ( Figure S1A ) . Taxonomic classification methods , also referred to as taxonomic or phylogenetic binning , provide a less-specific phylogenetic label to each read , usually through a more permissive alignment to known sequences in nucleotide or peptide space [24] , [25] ( Figure S1B ) . These methods can be useful for determining the abundance of specific clades and for assisting with assembly efforts . These techniques , however , are limited by the set of reference genomes available and are only useful when relatively many community members have been previously sequenced . Considering the vast diversity of microbial communities and the challenges involved in isolation and culturing efforts [17] , this approach can be applied on a large scale to only very few microbial communities . When reference genomes are not available , assembly methods can be used to link reads into contigs and scaffolds that are easier to annotate [26] ( Figure S1C ) . Such methods have been used to reconstruct full species [27] , coexisting strains [28] , [29] , and more generally to construct catalogues of genes specific to particular or general ecosystems [6] , [8] , [12] , [30] . Assembly is generally limited by the fraction of reads that can be mapped due to the complexity of most communities and the low coverage of each individual genome . Consequently , de-novo assembly of complete genomes from shotgun metagenomic samples is feasible only in extreme cases of low-complexity communities , very deep sequencing , or in combination with sample filtration techniques [27] , [29] , [31] , [32] . Binning methods similarly aim to cluster reads into distinct groups , but do not necessarily require sequences to overlap ( Figure S1D ) . Binning methods typically partition reads based on frequencies of nucleotide patterns ( k-mers ) [33]–[42] , but can also use abundance and similarity metrics [12] , [30] , [41]–[43] . While these methods utilize every read in a metagenomic sample , they have several significant shortcomings . K-mer methods , for example , are constrained by the short length of each read , the low resolution of nucleotide usage profiling , assume homogeneity of coding bias both across genomes and locally , and may not accurately discriminate highly-related organisms . Furthermore , methods based on clustering do not usually allow reads , genes , or assemblies to be assigned to more than one group , which is problematic for highly conserved regions of a genome and for mapping reads from gene catalogs that use a low threshold on sequence identity [8] . Finally , in addition to the above well-established categories , yet another category of methods for parsing metagenomic data can be defined , which we refer to here as deconvolution . Deconvolution-based methods aim to determine the genomic element contributions of a set of taxa or groups to a metagenomic sample ( Figure S1E ) . These methods profoundly differ from the binning methods described above as a single genomic element , such as a read , a contig , or a gene , can be assigned to multiple groups . An example of such a method is the non-negative matrix factorization ( NMF ) approach [44]–[46] , a data discovery technique that determines the abundance and genomic element content of a sparse set of groups that can explain the genomic element abundances found in a set of metagenomic samples . In this manuscript , we present a novel deconvolution framework for associating genomic elements found in shotgun metagenomic samples with their taxa of origin and for reconstructing the genomic content of the various taxa comprising the community . This metagenomic deconvolution framework ( MetaDecon ) is based on the simple observation that the abundance of each gene ( or any other genomic element ) in the community is a product of the abundances of the various member taxa in this community and their genomic contents . Given a large set of samples that vary in composition , it is therefore possible to formulate the expected relationships between gene and taxonomic compositions as a set of linear equations and to estimate the most likely genomic content of each taxa under these constraints . The metagenomic deconvolution framework is fundamentally different from existing binning and deconvolution methods since the number and identity of the groupings are determined based on taxonomic profile data , and the quantities calculated have a direct , physical interpretation . A comparison of the metagenomic deconvolution framework with existing binning and deconvolution methods can be found in Supporting Text S1 . We begin by introducing the mathematical basis for our framework and the context in which we demonstrate its use . We then use two simulated metagenomic datasets to explore the strengths and limitations of this framework on various synthetic data . The first dataset is generated with a simple error-free model of metagenomic sequencing that allows us to characterize the performances of our framework without the complications of sequencing and annotation error . The second dataset is generated using simulated metagenomic sequencing of model microbial communities composed of bacterial reference genomes and allows us to study specifically the effects of sequencing and annotation error on the accuracy of the framework's genome reconstructions . We finally apply the metagenomic deconvolution framework to analyze metagenomic samples from the Human Microbiome Project ( HMP ) [6] and demonstrate its practical application to environmental and host-associated microbial communities .
Consider a microbial community composed of some set of microbial taxa . From a functional perspective , the genome of each taxon can be viewed as a simple collection of genomic elements , such as k-mers , genes , or operons . The metagenome of the community can accordingly be viewed as the union of these genomic elements , wherein the abundance of each element in the metagenome reflects the prevalence of this element in the various genomes and the relative abundance of each genome in the community . Specifically , if some genomic element is prevalent ( or at least present ) in a certain taxon , we may expect that the abundance of this element across multiple metagenomic samples will be correlated with the abundance of the taxon across the samples . If the abundances of both genomic elements and taxa are known , such correlations can be used to associate genomic elements with the various taxa composing the microbial community [47] , [48] . In Supporting Text S1 , we evaluate the use of a simple correlation-based heuristic for predicting the genomic content of microbiome taxa and find that such simple correlation-based associations are limited in accuracy and are extremely sensitive to parameter selection . This limited utility is mostly due to the fact that associations between genomic elements and taxa are made for each taxon independently of other taxa , even though multiple taxa can encode each genomic element and may contribute to the overall abundance of each element in the various samples . We therefore present here a statistical deconvolution framework , improving upon the simple correlation metric and developing a mathematical model of shotgun metagenomic sequencing . This model quantifies the associations between a genomic element found in a set of samples and all the taxa in the community simultaneously , providing an estimate for the prevalence of this element in the genome of each taxon . Such statistical approaches have proven successful in analyzing gene expression data , allowing , for example , to deconvolve microarray data from mixed tissue samples into cell type-specific expression profiles [49] . Formally , if denotes the abundance of genome k in the community and denotes the prevalence of an element j in genome k ( e . g . , in terms of copy number or length in nucleotides ) , the total abundance of this element in the community can be represented as: ( 1 ) Note that similar models have been used as the basis for simulating shotgun metagenomic sequencing [50]–[53] , and the total abundance of the element in the community is independent of the individual genome sizes . Now , assume that the total abundances of genomic elements , , can be determined through shotgun metagenomic sequencing , and that the abundances of the various genomes , , can be obtained using 16S sequencing or from marker genes in the shotgun metagenomic data [54] , [55] . Accordingly , in Eq . ( 1 ) above , the only terms that are unknown are the prevalence of each genomic element in each genome , , and these are the specific quantities required to functionally characterize each taxon in the community . Clearly , if only one metagenomic sample is available , Eq . ( 1 ) cannot be used to calculate the prevalence of the genomic elements . However , assume M different metagenomic samples have been obtained , each representing a microbial community with a somewhat different taxonomic composition . For each genomic element , we can now write a system of linear equations of the form: ( 2 ) …or more compactly as ( 3 ) where the subscript i denotes the sample and is a normalization coefficient ( see below ) . Given enough samples , , the prevalence of a given genomic element j in each taxon , can be analytically solved by linear regression . Repeating this process for all genomic elements found in the community , we can therefore obtain an estimate of the prevalence of each element ( e . g . each gene ) in each taxon , effectively reconstructing the genomic content of all community members . The normalization constant represents , technically , the total amount of genomic material in the community . Clearly , is not known a priori and in most cases cannot be measured directly . Assume , however , that some genomic element is known to be present with relatively consistent prevalence across all taxa in the community . Such an element can represent , for example , certain ribosomal genes that have nearly identical abundances in every sequenced bacterial and archaeal genome ( see Methods ) . We can then rewrite Eq . ( 3 ) in terms of this constant genomic element , with a total abundance in sample i , : ( 4 ) Assuming that the taxonomic abundances have been normalized to sum to 1 , this simplifies to ( 5 ) We can accordingly substitute in Eq . ( 3 ) with this term , obtaining a simple set of linear equations where the only unknown terms are the prevalence of each genomic element in each taxon , . Metagenomic deconvolution is a general framework for calculating taxa-specific information from metagenomic data . Notably , this framework is modular , comprising four distinct components: ( i ) determination of taxonomic composition in each sample , ; ( ii ) determination of the abundances of genomic elements in each sample , ; ( iii ) selection of a constant genomic element , ; and ( iv ) calculation of the taxa-specific genomic element abundances , , by solving Eq . ( 3 ) . Each of these components can be implemented in various ways . For example , different metagenomic techniques , sequence mapping methods , and annotation pipelines can be used to determine the abundance of various genomic elements in each sample . Genomic elements can represent k-mers , motifs , genes , or other elements that can be measured in the samples and whose taxonomic origin are unknown . Similarly , there are multiple regression methods that can be applied to solve the set of equations obtained and to estimate , including least squares regression , non-negative least squares regression , and least squares regression with L1-regularization ( e . g . , lasso [56] ) . Finally , the taxonomic abundances need not be derived necessarily from 16S sequencing but can rather be determined directly from metagenomic samples [54] , [55] . In this study , we used gene orthology groups ( which we will mostly refer to simply as genes ) , specifically KEGG orthology groups ( KOs ) [19] , as the genomic elements of interest in Eq . ( 3 ) above . In this context , we defined the abundance of a KO in a metagenomic sample , , as the number of reads mapped to this KO , and the prevalence of a KO in a genome , , as the number of nucleotides encoding it in the genome . We accordingly applied our deconvolution framework to predict the length of each KO in each genome , ultimately obtaining ‘reconstructed’ genomes in the form of a list of all the KOs present in a genome and their predicted lengths . We used the 16S rRNA gene as the constant genomic element , , to calculate the normalization coefficient . The length of the 16S gene is largely consistent across all sequenced archaeal and bacterial strains . When the abundances of the 16S gene across shotgun metagenomic samples , , are not available , other genes or groups of genes with a consistent length across the various taxa can also be used . Specifically , in applying our framework to metagenomic samples from the HMP below , we used a set of bacterial and archaeal ribosomal genes to estimate ( Methods ) . Finally , we used least squares and non-negative least squares regression to solve Eq . ( 3 ) and to estimate ( Methods ) . Notably , such regression techniques require that there are at least as many samples as taxa in order for there to be a solution . However , if there are fewer samples than taxa , regularized regression techniques , such as the lasso [56] , can be used . For each dataset presented in this manuscript , we have evaluated the solutions presented by these regression methods and compared their accuracies across the different datasets in Supporting Text S1 . Notably , in many cases , our key goal is to determine which genes are present in ( or absent from ) a given genome , rather than their exact length ( e . g . , in nucleotides ) in this genome . To predict the presence or absence of a gene in a genome , we used a simple threshold-based method . Specifically , we compared the predicted length of each gene to the average length of this gene across sequenced genomes . Genes for which the ratio between these two values exceeded a certain threshold were predicted to be present . For example , we could predict that a gene is present in a genome if it is predicted to have a length greater than 0 . 5 the average length of all sequenced orthologs of this gene . This method will also allow us to correct for inaccuracies in length predictions . In the results reported below , we further demonstrate the robustness of reconstructed genomes to threshold value selection . We first use a simple model of metagenomic sampling to characterize metagenomic deconvolution in the absence of sequencing and annotation errors . To this end , we simulated microbial communities composed of 60 “species” of varying abundances ( see Methods ) . In this model , each species was defined as a collection of “genes” assigned randomly from a total set of 100 gene orthology groups . These genes had no sequence , were assumed to vary in length , and could be present in multiple copies in each genome . 100 model microbial communities were generated with different , but correlated , abundances for each member species ( Figure S2 ) . The relative abundances of each species in the communities were assumed to be known ( e . g . from targeted 16S sequencing ) . Metagenomic samples consisting of 5M reads were generated , simulating shotgun sequencing through a random sampling process weighted by the relative abundance of each gene in the community . Reads were assumed to map without error to the appropriate orthology group , counting towards the observed relative abundance of each gene orthology group in the sample . Full details of the model are given in the Methods . We applied the deconvolution framework described above to predict the length of each gene in each species . Examining the predicted length of a typical gene across all species , we found that we successfully predicted the actual genomic length of this gene among the different species ( Figure 1A ) . Similarly , comparing the predicted lengths of all genes in a typical species to the species' actual genome , we find that our framework accurately reconstructed the genomic content of the species , successfully identifying absent genes and correctly estimating a wide range of gene lengths ( Figure 1B ) . Furthermore , analysis of the predictions obtained for all genes and for all species in the community clearly demonstrates that the metagenomic deconvolution framework can effectively reconstruct gene lengths across all genomes , orthology groups , and copy numbers ( Figure 1C ) . Clearly , the predicted gene lengths described above , while accurate , are not perfect , and may be affected by various sources of noise in the data . Moreover , as noted above , in many cases , we are primarily interested in predicting whether a gene is present in a certain genome rather than in determining its exact length . Converting the predicted gene lengths to gene presence/absence predictions using a threshold of 0 . 5 of the gene length , we find that we are able to correctly predict the presence and absence of all genes in all species with 100% accuracy . We further confirmed that this result is robust to the specific threshold used , with all thresholds values between 0 . 2 and 0 . 8 yielding perfect predictions ( Figure S3 ) . Predictions of a given gene's length across the species vary in accuracy from gene to gene , with some genes having a noticeably higher overall error than others ( Figure 1C ) . By examining the distribution of genes among samples and species , we find that prediction accuracy for a gene is significantly correlated with its level of variation across samples ( Figure 2A ) and across species ( Figure 2B ) , with more variable genes having lower prediction error on average . These patterns in prediction accuracy are not surprising . Since our framework is based on detecting species and gene abundances that co-vary , highly variable genes or species carry a stronger signal and lead to more accurate predictions . Interestingly , however , this seemingly limiting link between prediction accuracy and variation is one of the strengths of our framework , as it provides better accuracy for predicting exactly the genes that are of most interest . Specifically , genes that vary from species to species are those that confer species-specific functional capacity and are those that are most crucial for characterizing novel genomes . Similarly , genes that vary most from sample to sample are those endowing each community with specific metabolic potential and are therefore often of clinical interest . In contrast , genes with little variation from species to species and from sample to sample are likely to include many housekeeping genes , whose presence in each genome is not surprising and can mostly be assumed a priori . Clearly , many microbial communities exhibit high species diversity and are inhabited by an extremely large number of species , challenging deconvolution efforts . Moreover , the abundances of species across samples are not independent: In a given environment , some species may dominate all samples , while other species may tend to be rare across all samples . Interactions between species may also introduce correlations between the abundances of various species . These inter-sample and inter-species correlations might also affect our ability to correctly deconvolve each member species , as they in effect reduce the level of variation in the data . For example , species with highly correlated abundances ( e . g . , the set of dominant species across all samples ) will contribute similarly to the abundances of genes in the various samples and will be hard to discriminate . To explore the impact of the number of species in the community and of correlations between species abundances on metagenomic deconvolution , we used an additional set of simulated communities . Specifically , metagenomic samples were generated with a varying number of species and a varying level of inter-sample correlation in species abundances ( Methods; Figure S4 ) . We find , as expected , that the accuracy ( Figure S5A ) and recall ( Figure S5B ) of deconvolution decreases as the number of species increases ( assuming a constant sampling depth ) . Furthermore , increasing the level of correlation between species abundances across samples similarly results in reduced accuracy and recall ( Figure S5 ) . The simple model presented above allowed us to explore the metagenomic deconvolution framework in ideal settings where reads are assumed to be error free and to unambiguously map to genes . We next set out to examine the application of our framework to synthetic metagenomic samples that incorporate both next-generation sequencing error and a typical metagenomic functional annotation pipeline . To this end , we simulated metagenomic sampling of microbial communities composed of three reference genomes ( Methods ) . We specifically focused on strains that represent the most abundant phyla in the human gut , as determined by the MetaHIT project [8] , and for which full genome sequences were available . Furthermore , these strains represented different levels of coverage by the KEGG database ( which we used for annotation ) , ranging from a strain for which another strain of the same species exists in the database , to a strain with no member of the same genus in the database ( Methods ) . Ten communities with random relative strain abundances were simulated . The relative abundances in each community were assumed be to known through targeted 16S sequencing . For the analysis below , relative abundances ranged over a thousand-fold , but using markedly different relative abundance ratios had little effect on the results ( see Supporting Text S1 ) . Shotgun metagenomic sequencing was simulated using Metasim [50] , with 1M 80-base reads for each sample and an Illumina sequencing error model ( Methods ) . The abundances of genes in each metagenomic sample were then determined using an annotation pipeline modeled after the HMP protocol [47] , with reads annotated through a translated BLAST search against the KEGG database [19] . To assess the accuracy of this annotation process and its potential impact on downstream deconvolution analysis , we first compared the obtained annotations to the actual genes from which reads were derived . Overall , obtained annotation counts were strongly correlated with expected counts ( 0 . 83 , P<10−324; Pearson correlation test; Figure S6 ) . Of the reads that were annotated with a KO , 82% were annotated correctly . Notably , however , only 62% of the reads originating from genes associated with KOs were correctly identified and consequently the read count for most KOs was attenuated . Highly conserved genes , such as the 16S rRNA gene , were easily recognized and had relatively accurate read count ( Figure S6 ) . Full details of this synthetic community model and of the sequencing simulations are provided in Methods . We deconvolved each KO using the obtained abundances to predict the length of each KO in each genome . We found that the predicted lengths were strongly correlated with the actual lengths ( rho 0 . 84 , P<10−324; Pearson correlation test ) , although for most KOs predicted lengths were shorter than expected ( Figure 3 ) . This under-prediction of KO lengths can be attributed to the normalization process . Specifically , as noted above , the detected abundances of conserved genes used for normalization tended to be less attenuated by the annotation pipeline than the abundances of other genes , which were therefore computed to be shorter than they actually were . Notably , some KOs that are in fact entirely absent from the genomes under study were erroneously detected by the annotation pipeline and consequently predicted to have non-negligible lengths in the reconstructed genomes ( Figure 3 ) . To discriminate the error stemming from the annotation pipeline from error stemming directly from the deconvolution process , we reanalyzed the data assuming that each read was correctly annotated . We found that with the correct annotations , predicted KO lengths accurately reflected the actual length of each KO in each genome ( rho 0 . 997 , P<10−324; Pearson correlation test; Figure S7 ) . Importantly , while the error introduced by the annotation pipeline significantly affects the accuracy of predicted KO lengths , the presence ( or absence ) of each KO in each genome can still be successfully predicted by the threshold approach described above ( Figure 4A ) . Specifically , using a threshold of 0 . 1 of the average length of each KO , metagenomic deconvolution reached an accuracy of 89% ( correctly predicting both KO presence and absence ) and a recall of 98% across the various genomes . Figure 4B further illustrates the actual and predicted genomic content of each strain , demonstrating that the method can accurately predict the presence of the same KO in multiple strains , highlighting the difference between the metagenomic deconvolution framework and existing binning methods ( see also Discussion ) . We compared these predictions to a naïve ‘convoluted’ prediction ( see Methods ) , confirming that deconvolution-based predictions were significantly more accurate than such a convoluted null model regardless of the threshold used ( P<10−324 , bootstrap; Figure 4A ) . For example , using a threshold of 0 . 1 as above , convoluted genomes were only 54% accurate . Considering the determinants of prediction accuracy described above , we further confirmed that prediction accuracy markedly increased for highly variable and taxa-specific genes ( Supporting Text S1 ) . Given the noisy annotation process , we again set out to quantify the contribution of annotation inaccuracies to erroneous presence/absence predictions in the reconstructed genomes . As demonstrated in Figure 4B , most KO prediction errors were false positives – KOs wrongly predicted to be present in a strain from which they were in fact absent . Examining such KOs and the annotation of reads in each genome , we found that 99% of the false positive KOs were associated with mis-annotated reads , suggesting that deconvolution inaccuracies in these settings could be attributed almost entirely to erroneous annotation rather than to the deconvolution process itself . We again confirmed that when correct annotations are assumed , both accuracy and recall increase to more than 99% . The analysis above was used to evaluate the impact of sequencing and annotation error on the metagenomic deconvolution framework using simulated metagenomic datasets generated from simple 3-strain communities . In Supporting Text S1 , we further present a similar analysis , using simulated metagenomic samples generated from 20-strain communities and based on the HMP Mock Communities . We show that our framework obtains similar reconstruction accuracies for these more complex communities ( Figure S8 ) . Finally , we considered human-associated metagenomic samples to demonstrate the application of the metagenomic deconvolution framework to real metagenomic data from highly complex microbial communities . These datasets further represent an opportunity to evaluate genome reconstructions obtained by our framework owing to the high-coverage of the human microbiome by reference genomes [6] , [21] that can be used for evaluation . The Human Microbiome Project [6] , [14] has recently released a collection of targeted 16S and shotgun metagenomic samples from 242 individuals taken from 18 different body sites in an effort to comprehensively characterize the healthy human microbiome . These human-associated microbial communities are diverse , with several hundred to several thousand 16S-based OTUs ( operational taxonomical units clustered at 97% similarity ) per sample and a total of more than 45 , 000 unique OTUs across all HMP samples . These OTUs represent bacteria and archaea from across the tree of life , including many novel taxa [57] , and their diversity is in agreement with shotgun metagenomics-based measures [6] . Clearly , the high number of unique OTUs in each sample does not permit deconvolution and genome reconstruction at the OTU level . Moreover , these OTUs do not represent individual species , but rather distinct sequences accurate to only a genus-level phylogenetic classification [6] . Examining the phylogenetic distribution of the taxa comprising the microbiome suggests that certain body sites , such as the tongue dorsum , are dominated by relatively few genera . This allows us to use metagenomic deconvolution at the genus level , predicting the most likely genomic content of the various genera found in the microbiome . Reconstructed genus-level genomes can be viewed as the average genomic content across all present strains in the genus , providing insight into the capacities of the various genera . Moreover , while many species inhabiting the human microbiome have not yet been characterized or sequenced , most human-associated genera include at least a few fully sequenced genomes , allowing us to assess the success of our framework and the accuracy at which reconstructed genera capture known genus-level properties . Notably , however , microbial communities from other environments or from other mammalian hosts often harbor many uncharacterized taxa , even at levels higher than genera [58] , [59] , making a genus-level deconvolution a still biologically relevant goal . We accordingly applied our deconvolution framework to HMP tongue dorsum metagenomic samples ( Methods ) . OTU abundances and taxonomic classification were obtained from the HMP QIIME 16S pipeline [14] . KO abundances were obtained from the HMP HUMAnN shotgun pipeline [19] . In total , 97 tongue dorsum samples had both OTU and KO data available . OTUs were pooled to calculate the relative abundance of each genus in each sample . After pooling , we identified 14 genera that dominated the tongue dorsum . We deconvolved these samples to obtain reconstructed genera and computed KO presence/absence in each reconstructed genus using a threshold of 0 . 25 copies . To evaluate our predictions , we calculated the similarity between the 14 reconstructed genera and every sequenced genome from these genera ( Methods ) . We find that 12 of the 14 reconstructed genera are most similar to genomes from the correct genus ( Figure 5A ) . Interestingly , Capnocytophaga , one of the two reconstructed genera that did not most closely resemble genomes from its own genus , was the least abundant genus and appeared to be most similar to genomes from the Fusobacterium genus , with which it significantly co-occurs in the tongue dorsum [60] . This potentially reflects the sensitivity of deconvolution to highly correlated taxonomic abundances ( see Discussion ) . Furthermore , overall , the observed similarities between each reconstructed genus and sequenced genomes from other genera ( Figure 5A ) largely reflect inter-genus similarities between the genomes from the various genera ( Figure 5B ) . For example , although the reconstructed Prevotella is most similar to sequenced genomes from the Prevotella genus , it also exhibits high similarity to genomes from Porphyromonas and Capnocytophaga , two other genera from the Bacteroidetes phylum with relatively similar genomic content . These findings suggest that our deconvolution framework was able to accurately capture the similarities and the differences between the various genera based solely on variation in KO and OTU abundances across samples . To further study the capacity of genus-level deconvolution to reconstruct and characterize the various genera in the microbiome , we next focused on the set of genes that best distinguish one genus from the other . Clearly , even within a genus , the set of genes present in a genome varies greatly from species to species and from strain to strain . Yet , for each genus , a small number of genes that are present in almost every genome from that genus and that are absent from most other genomes can be found . These genus-specific genes best typify the genus , potentially encoding unique genus-specific capacities . Moreover , since such genes are consistently present or consistently absent within each genus , genus-level deconvolution is not complicated by the genus-level pooling of genomes . We defined genus-specific KOs as those present in 80% of the genomes from a given genus and in less than 20% of all others HMP reference genomes . We found in total 99 such KOs across 4 genera . Examining the reconstructed genera , we found that our framework successfully predicted the presence or absence of these genus-specific KOs ( 90% accuracy and 82% recall; Figure 6 ) . Increasing the stringency for our definition and focusing on the 63 KOs that appeared in 90% of the genomes from a certain genus and in less than 10% of all others genomes further increased the accuracy ( 92% ) and recall ( 94% ) of our reconstructed genera . Predictions obtained using alternative regression methods were similarly accurate ( see Supporting Text S1; Figures 6 , S9 ) . The metagenomic deconvolution framework introduced in this manuscript is a technique for associating genomic elements found in shotgun metagenomic samples with their taxa of origin and for reconstructing the genomic content of the various taxa comprising the community . Many different approaches have been developed to create such groupings of metagenomic features . Broadly , these methods fall into one of two categories , “binning” or “deconvolution” , depending on whether the genomic elements can be assigned to more than one group or not . As demonstrated in Supporting Text S1 ( and see also Table S2 ) , the differences between the metagenomic deconvolution framework and these existing methods originate primarily from the different mathematical frameworks employed by the various methods . Binning methods , such as metagenomic linkage analysis [12] , metagenomic clustering analysis [30] , and MetaBin [43] , are designed to cluster genomic elements that can only exist in one taxon ( or group ) . Specifically , metagenomic linkage analysis clusters genes into groups based on their abundances and phylogeny across sets of metagenomic samples using the CHAMELEON algorithm [61] . Similarly , metagenomic clustering analysis clusters genes into groups based on their abundances across sets of metagenomic samples using the Markov clustering algorithm [62] . MetaBin , on the other hand , clusters individual reads based on their sequence similarities and abundances across sets of metagenomic samples using k-medoids clustering . As these methods all cluster genomic elements into distinct groups , they cannot correctly distribute elements that exist in multiple taxa ( or groups ) , making them less appropriate for addressing questions of core vs . shared genome content ( and see , for example , refs [54] , [63] , [64] ) . As we demonstrate in Supporting Text S1 , these methods accordingly could not be used to reconstruct the genomic content of the three strains present in the simulated metagenomic samples incorporating sequencing and annotation error in terms of the gene orthology groups identified in the samples . In contrast , deconvolution methods , such as non-negative matrix factorization ( NMF ) [44]–[46] and the proposed metagenomic deconvolution framework , are designed to assign genomic elements to multiple taxa . Specifically , NMF is a data discovery and compressed sensing tool that is designed to create a set number of groupings of elements that best fits the observed samples by factoring the feature matrix ( here , the genomic elements found across a set of metagenomic samples ) into two matrices . One matrix represents the abundance of the set of groups in each sample , and the other represents the distribution of genomic elements among these groups . The optimal number of groups can be determined from the fit of the matrix factorization to the original matrix [45] , [46] or the stability of the solutions for a given number of groups [44] . Importantly , while NMF utilizes a mathematically similar approach to the metagenomic deconvolution framework , and can thus theoretically obtain comparable accuracies ( see also Supporting Text S1 ) , the two represent fundamentally different techniques . First , the groups identified by NMF are unlabeled , while those used by the metagenomic deconvolution framework by definition have a distinct taxonomic identity . Furthermore , the optimal number of groups detected in a set of samples by NMF does not necessarily correspond to any phylogenetic groupings present in the set of samples . Indeed , NMF does not group the gene orthology groups present in the simulated metagenomic samples incorporating sequencing and annotation error into strain-specific groupings ( Supporting Text S1 ) . Second , in the metagenomic deconvolution framework , the calculated quantities of genomic elements in each group have a direct physical interpretation ( i . e . gene length or copy number ) , while NMF calculates coefficients without assigning a clearly interpretable meaning . Lastly , NMF functions on the entire set of genomic elements present in a set of samples ( the feature matrix ) as a whole , whereas the metagenomic deconvolution framework solves for the distribution of each genomic element among the various groups independently . This separability allows for custom regression techniques to be used for each genomic element ( for example , regularized regression like lasso can be used for those genomic elements that are sparsely distributed ) and the option to target only those genomic elements of interest .
In this study , we presented a novel framework for deconvolving shotgun metagenomic samples and for reconstructing the genomic content of the member microbial taxa . This metagenomic deconvolution framework utilizes the magnitude by which abundances of taxa and of genomic elements co-vary across a set of metagenomic samples to identify the most likely genomic content of each taxon . Above , we have described the mathematical formulation of this framework , detailed computational considerations for implementing it , characterized its performance and properties on synthetic metagenomic datasets , and demonstrated its practical use on metagenomic samples from the Human Microbiome Project . The metagenomic deconvolution framework represents a fundamentally different approach to associating genomic elements found in shotgun metagenomic samples with the taxa present than the approaches employed by previously introduced methods . For example , methods relying on alignment to reference genomes [6] , [8] , [22] , [24] , [25] are heavily dependent on the availability of sequenced genomes from community members or from closely related species . As metagenomics research expands and researchers set out to characterize new environments inhabited by many novel , diverse , and never before seen species , such methods may be challenged by the scarcity of reference genomes and by the low phylogenetic coverage of many genera across genomic databases . In contrast , our method does not require reference genomes ( see also below ) . Moreover , metagenomic deconvolution uses a mathematical model of shotgun sequencing to directly calculate the desired quantities of genomic elements ( such as gene lengths or copy numbers ) in specific taxa ( such as a strain or genus ) , rather than to create groupings of elements that best fit the measured distribution . Metagenomic deconvolution associates genomic elements with genomes of present taxa by identifying genomic elements that co-vary in abundance with organisms . As demonstrated above , this approach brings about an important advantage: The more variation of a given genomic element across samples and organisms , the more accurately it will be assigned to the various taxa . The deconvolution framework can accordingly be thought to be tuned to best identify those elements that make a taxon or a set of samples unique and that are therefore of most biological interest . Moreover , to a large extent , in analyzing the way gene and taxonomic abundances co-vary across the set of samples under study , it utilizes orthogonal , self-constrained information . Notably , the specific implementation presented in this study utilizes functional read annotation and therefore required a set of annotated reference genes . However , functional annotation is markedly less sensitive to the specific set of reference genomes available than the methods discussed above , since any gene with detectable homology will suffice . Moreover , one can easily imagine a different implementation that clusters the reads contained in the samples themselves without identifying specific orthology groups , making this approach entirely independent from any exogenous genomic data ( see also below ) . These properties of metagenomic deconvolution make it an ideal framework for analyzing metagenomic samples from the many microbial habitats yet to be extensively characterized . A deconvolution-based framework also has some obvious limitations . First , it requires multiple metagenomic samples and information on both taxonomic and gene abundances . While this may have been a significantly limiting factor in the past , with the ever decreasing cost of sequencing technologies and the recently introduced advances in molecular and computational profiling of taxonomic and gene compositions , current studies in metagenomics often generate such data regardless of planned downstream analyses ( e . g . , [6] , [7] ) . Furthermore , if a genomic element is known to be sparsely distributed among the taxa in a collection of samples , then regularized regression techniques , such as the lasso [56] , can be used to predict the presence and absence of the genomic element among the taxa , even if the number of samples is much smaller than the number of taxa . Additionally , as demonstrated above , strong correlations between taxa abundances reduce the amount of variation , decreasing the signal and potentially hindering the accuracy of the deconvolution process . Improved understanding of the assembly rules that give rise to such correlations may help alleviate this problem . Finally , our framework relies on accurate estimations of gene and taxonomic abundances . These estimations may be skewed by annotation errors or by the specific method used to evaluate relative taxonomic abundances . Specifically , 16S copy number variation between taxa in a sample ( even between strains of the same species [65] ) may markedly bias abundance estimates , although this can largely be resolved by estimating the 16S copy number in each taxon using measured copy numbers in sequenced strains [66] . No such correction was performed in this study , as we sought to present a generic implementation of the metagenomic deconvolution framework applicable to analyzing sets of metagenomic samples without the need for coverage by reference genomes . The deconvolution framework presented in this study can serve as a basis for many exciting extensions and can be integrated with other analysis methods . It is easy , for example , to redefine the scale at which both genomic elements and taxa are defined . In analyzing the HMP samples , we partition genes among genera , rather than into individual OTUs . A similar approach can be used to deconvolve higher or lower ( e . g . , strain ) phylogenetic levels or even to deconvolve different taxa at different phylogenetic levels . One can , for example , target particular species for genome reconstruction while resolving others only on the genus level . Similarly , deconvolution can be performed for other genomic elements such as k-mers or other discrete sequence motifs . Deconvolution can also be carried out incrementally , first deconvolving highly abundant taxa or taxa for which partial genomic information is available . The expected contribution of each deconvolved taxon to the overall gene count in the metagenome can then be calculated and subtracted computationally from each sample , effectively generating lower complexity samples and facilitating the deconvolution of additional taxa . A similar approach can also be used to subtract the contribution of fully sequenced strains whose genomic content is known . Notably , in implementing and characterizing the deconvolution framework here , we did not utilize any information about known strains' genomes . Such information can be used in principal to calibrate various parameters and to normalize the obtained results . Most importantly , this metagenomic deconvolution framework can be naturally combined with other binning methods or metagenomic assembly efforts [67] . For example , by treating contigs , or groups of contigs ( such as those generated by metagenomic linkage groups [12] or metagenomic clusters [30] ) as individual genomic elements ( and , Eq . 3 ) , deconvolution can be used to assign these larger-scale genomic fragments to individual taxa and aid in assembly . Such a process would be especially useful in the case of time-series data where the abundances of strains change with time . Finally , the metagenomic deconvolution framework facilitates novel analysis approaches for studying microbial communities . Samples taken from a community can be post-processed in multiple ways to preferentially select for certain taxa ( e . g . filter microbes by size or nutrient requirements ) , essentially creating different views of the same community . Deconvolution can then be used to recombine these views and to reconstruct the genomic content of each taxon . To truly take advantage of the data being produced by metagenomic studies and by forthcoming studies of the metatranscriptome and metametabolome of many microbial communities , tools that can reliably determine the taxonomic origins of each “meta'omic” element are crucial . Metagenomic deconvolution represents both a novel strategy for the analysis of such meta'omic data and a framework for future developments in genome reconstruction and annotation .
Simple models of metagenomic samples were created from collections of model “microbial species” by simulating genomes and shotgun sequencing without the complexities of actual genome sequences or sequencing error . Microbial species were modeled as a set of “genes” , taken from a global set of 100 gene orthology groups ( simply referred to as genes ) . These genes had no sequence; their only property was length , which was chosen at random between 400 and 500 bases , and was fixed across all homologs . Simulations with species-specific variations in gene length showed qualitatively similar results ( see Supporting Text S1 ) . Each of the 100 genes was randomly assigned to between 20 to 80% of the species , with each species containing a minimum of 10 genes . Within a given species , each gene had a 5% chance of duplication , with the rates for higher copy number decreasing exponentially . Each species included a single copy of a “constant gene” with a length of 1500 bases ( see Results ) . Sets of model “microbial communities” were created as a linear combination of model microbial species . Each microbial community in a set had a different , but correlated , species abundance profile , with the abundance of a species j in sample i , determined by the function , , where represents the typical abundance of species j , v is a parameter that governs the amount of inter-sample correlation in the abundance profiles and rij is a Gaussian-distributed random number with mean of 0 and standard deviation of 1 . To examine the robustness of deconvolution to the number of species and the level of inter-sample correlation , 30 different sets of related communities were created , with the number of species ranging from 20 to 100 in steps of 20 , and the correlation parameter v logarithmically distributed , ( Figure S4 ) . The set of communities analyzed in the main text was modeled with 60 species and a correlation parameter of v = 0 . 10 . Model metagenomic samples were generated from each microbial community by simulating a shotgun sequencing sampling: Sequencing reads were created by randomly selecting a gene in the community , weighted by the relative abundance of each gene in the community ( Eq . 3 ) . 5M sequencing reads were generated for each community . Due to the finite sequencing depth and the exponentially distributed species abundances , species whose abundances were below 0 . 5% of the most abundant species in the sample were considered absent from the set of shotgun metagenomic reads and excluded from our analysis . These samples and the related data can be found in Supporting Dataset S1 and on our website ( http://elbo . gs . washington . edu/download . html ) . Deconvolution was performed for species that were present in at least half the samples using least squares , non-negative least squares , and lasso regression using the solvers implemented in MATLAB . The computation times for these deconvolution runs on a four-core 3 . 10 GHz Intel Xeon CPU were 2±1×10−4 s/gene , 4 . 6±0 . 8×10−3 s/gene , and 1 . 63±0 . 05 s/gene for least squares , non-negative least squares , and lasso regression respectively . Adding additional samples required 8×10−7 , 7×10−7 , and 0 . 9 s/gene/sample for least squares , non-negative least squares , and lasso ( for underdetermined systems ) regression , respectively; for overdetermined systems , lasso had a performance increase of 1 . 7×10−2 s/gene/sample . Adding additional species required 2×10−6 , 7×10−5 , and 4×10−2 s/gene/species for least squares , non-negative least squares , and lasso regression , respectively . Simple models of metagenomic samples were created from the fully sequenced genomes of microbial reference organisms to introduce the complexities associated with actual genome sequences and annotation error . 10 model communities were composed as linear combinations of the reference organisms Alistipes shahii WAL 8301 , Ruminococcus champanellensis sp . nov . , and Bifidobacterium longum longum F8 . These strains were chosen because they each had a different level of coverage by the KEGG database used in this study ( see below ) : B . Longum had a different strain of the same species present in the database; R . Champanellensis had only a member of the same genus present; and A . Shahii had no relatives within the same genus present . Complete species genomes were obtained from the Integrated Microbial Genomes database [68] . These communities had species relative abundances assigned randomly , ranging over a thousand-fold; however , the magnitude of the range of relative abundances was shown to have little impact on our results ( Supporting Text S1 ) . Model metagenomic samples were created from each community by simulating 1M shotgun metagenomic sequencing reads with Metasim [50] , using 80-base reads with an Illumina sequencing error model . The abundances of gene orthology groups present in each model metagenomic sample were determined from the set of reads by annotating each read with KEGG orthology groups ( KOs ) through a translated BLAST search against the KEGG Orthology v60 [19] . Reads were annotated with the KO of the best hit with an E-value<1 , similar to the method employed by the HMP [6] . Reads with a best-hit match to a KEGG gene without a KO annotation were not assigned a KO . In cases of e-value ties , the read was assigned the annotations of all the tied matches , with each annotation receiving a fractional count . Reads containing an ambiguous base were not annotated . The abundance of the 16S rRNA KO was determined through a nucleotide BLAST search against a custom database containing the sequences of all 16S rRNA genes in the KEGG database . These samples ( as well as the 20 strain community samples ) and the related data can be found in Supporting Dataset S2 , Supporting Dataset S3 , and on our website ( http://elbo . gs . washington . edu/download . html ) . Deconvolution was performed using least squares , non-negative least squares , and lasso regression for KOs whose average count was greater than 0 . 1% of the most abundant KO using the solvers implemented in MATLAB . The computation times for these deconvolution runs on a four-core 3 . 10 GHz Intel Xeon CPU were s/KO , s/KO , and s/KO for least squares , non-negative least squares , and lasso regression respectively . To evaluate the presence/absence prediction made by our framework , we used a null model in which community members are all assumed to have an identical ( ‘convoluted’ ) genome , directly derived from the set of metagenomic samples . Specifically , the KO lengths in this model corresponded to the average relative abundance of each KO across all samples , normalized by the length and abundance of the 16S KO . Formally , the length of KO j , , was calculated as , where is the average relative abundance of KO j across all metagenomic samples , is the average length of the 16S KO , and is the average relative abundance of the 16S KO . HMP data was downloaded from the HMP Data Analysis and Coordination Center ( DACC ) ( http://www . hmpdacc . org/ ) . OTU abundances and taxonomy were based on the QIIME 16S pipeline [14] . The abundance of each genus was calculated by adding the abundances of all OTUs in that genus . Only genera with relative abundance >5% in at least one sample were considered . KO abundances were based on the HUMAnN pipeline [19] . For samples with technical replicates , the replicate with the greater sequencing depth was used . To reduce annotation error , only KOs present in at least 80% of the tongue dorsum samples were used in the analysis . Since HMP KO abundance data included only proteins , we used a set of 15 ribosomal proteins ubiquitous across Bacteria and Archaea instead of the 16S RNA gene as the constant genomic element in Eq . 5 ( see below ) . Deconvolution was performed for KOs that were present in at least half the samples using least squares , non-negative least squares , and lasso regression using the solvers implemented in MATLAB . The computation times for these deconvolution runs on a four-core 3 . 10 GHz Intel Xeon CPU were s/KO , s/KO , and s/KO for least squares , non-negative least squares , and lasso regression respectively . Genomes for the HMP Reference Organisms were obtained from the Integrated Microbial Genomes – Human Microbiome Project ( IMG/HMP ) database on 5/7/2012 ( http://www . hmpdacc-resources . org/cgi-bin/imgm_hmp/main . cgi ) . In order for the annotations to be compatible with the version of the database used in this study , each organism was annotated through a BLAST search of each ORF against the KEGG genes database with a protocol similar to that used by the IMG [68] . Each ORF was annotated with the KO of the best match gene with an e-value <1×10−5 . In cases of ties , the ORF was annotated with all corresponding KOs , with a proportionally fractional count . ORFs that best matched a KEGG gene with no KO annotation were not annotated . KOs were considered to be present in a genome if this annotation procedure resulted in a copy number ≥0 . 1 . For species with more than one sequenced strain , the average annotation across strains was used . KOs present in at least 75% of HMP reference organisms were considered core KOs and were removed from the analysis . Similarly , KOs present in fewer than 1% of HMP reference genomes were assumed to be spurious annotations and were excluded . One of the components required to deconvolve metagenomic samples is a constant genomic element or gene that can be used as a normalization coefficient for inferring the length ( or copy number ) of all other genomic elements . Ideally , genes used for normalization should be present in all the species in the community , have the same copy number in each genome , and have a consistent length across all species . The 16S rRNA gene is a natural candidate , but other gene orthology groups can be used as well . Specifically , in the main text , we deconvolved tongue dorsum samples from the Human Microbiome Project using a combination of ribosomal protein-coding genes . Ribosomal genes are generally good candidates for normalization since the ribosome is a highly-conserved construct . Using the combined abundances of multiple genes can reduce the potentially deleterious effect of read annotation errors in any one gene . Starting with 31 ribosomal protein-coding KOs present in both bacteria and archaea , we first considered those that were present in at least 1445 ( 98% ) of the 1475 bacteria and archaea in KEGG v60 [19] . Of these KOs , we selected a subset of 15 KOs that had a lower variation in length across all genomes than the 16S gene ( Table S1 ) . These 15 KOs were used jointly as our constant genomic element for normalization , using the sum of the abundances as the constant genomic element abundance and sum of the lengths as the constant genomic element length in Eq . 5 . | Most microorganisms inhabit complex , diverse , and largely uncharacterized communities . Metagenomic technologies allow us to determine the taxonomic and gene compositions of these communities and to obtain insights into their function as a whole but usually do not enable the characterization of individual member taxa . Here , we introduce a novel computational framework for decomposing metagenomic community-level gene content data into taxa-specific gene profiles . Specifically , by analyzing the way taxonomic and gene abundances co-vary across a set of metagenomic samples , we are able to associate genes with their taxa of origin . We first demonstrate the ability of this approach to decompose metagenomes and to reconstruct the genomes of member taxa using simulated datasets . We further identify the factors that contribute to the accuracy of our method . We then apply our framework to samples from the human microbiome – the set of microorganisms that inhabit the human body – and show that it can be used to successfully reconstruct the typical genomes of various microbiome genera . Notably , our framework is based solely on variation in gene composition and does not rely on sequence composition signatures , assembly , or available reference genomes . It is therefore especially suited to studying the many microbial habitats yet to be extensively characterized . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [] | 2013 | Reconstructing the Genomic Content of Microbiome Taxa through Shotgun Metagenomic Deconvolution |
The neuronal calcium sensor proteins GCAPs ( guanylate cyclase activating proteins ) switch between Ca2+-free and Ca2+-bound conformational states and confer calcium sensitivity to guanylate cyclase at retinal photoreceptor cells . They play a fundamental role in light adaptation by coupling the rate of cGMP synthesis to the intracellular concentration of calcium . Mutations in GCAPs lead to blindness . The importance of functional EF-hands in GCAP1 for photoreceptor cell integrity has been well established . Mutations in GCAP1 that diminish its Ca2+ binding affinity lead to cell damage by causing unabated cGMP synthesis and accumulation of toxic levels of free cGMP and Ca2+ . We here investigate the relevance of GCAP2 functional EF-hands for photoreceptor cell integrity . By characterizing transgenic mice expressing a mutant form of GCAP2 with all EF-hands inactivated ( EF−GCAP2 ) , we show that GCAP2 locked in its Ca2+-free conformation leads to a rapid retinal degeneration that is not due to unabated cGMP synthesis . We unveil that when locked in its Ca2+-free conformation in vivo , GCAP2 is phosphorylated at Ser201 and results in phospho-dependent binding to the chaperone 14-3-3 and retention at the inner segment and proximal cell compartments . Accumulation of phosphorylated EF−GCAP2 at the inner segment results in severe toxicity . We show that in wildtype mice under physiological conditions , 50% of GCAP2 is phosphorylated correlating with the 50% of the protein being retained at the inner segment . Raising mice under constant light exposure , however , drastically increases the retention of GCAP2 in its Ca2+-free form at the inner segment . This study identifies a new mechanism governing GCAP2 subcellular distribution in vivo , closely related to disease . It also identifies a pathway by which a sustained reduction in intracellular free Ca2+ could result in photoreceptor damage , relevant for light damage and for those genetic disorders resulting in “equivalent-light” scenarios .
Guanylate-cyclase activating proteins ( GCAPs ) belong to the neuronal calcium sensor ( NCS ) family of proteins that display limited similarity to calmodulin . They confer Ca2+-sensitivity to guanylate-cyclase ( Ret-GC ) activity in retinal photoreceptor cells . GCAP1 and GCAP2 constitute the major species in mammals [1]–[3] . At rod and cone outer segments GCAPs form permanent complexes with Ret-GCs allowing short response times of cyclase modulation to fluctuations in intracellular Ca2+ concentration . GCAPs inhibit cyclase activity in their Ca2+-loaded form at the high free [Ca2+]i characteristic of the dark steady-state , and switch to their activator state as they replace Ca2+ by Mg2+ when light reduces Ca2+ influx upon closing the cGMP-channels [4] . Light exposure results in up to a 10-fold decline in the intracellular free [Ca2+] , from ∼250 nM in darkness to 23 nM in saturating light in mouse rod outer segments [5] . This Ca2+ decrease is first sensed at GC/GCAP complexes comprising GCAP1 and successively at those comprising GCAP2 [Ca2+ EC50 for GCAP1 ∼130 nM; for GCAP2 ∼50 nM , [6]] , in a sequential mode of action referred to as a Ca2+-relay model [7]–[9] . Altogether , the rate of cGMP synthesis upon light exposure is stimulated up to ∼12-fold over its basal levels , serving to restore the cGMP levels and to reopen the channels during the recovery of the light response and light adaptation [10] , [11] . Despite the importance of GCAPs-mediated Ca2+-feedback on cGMP synthesis in the control of sensitivity , deletion of GCAP1 and GCAP2 in mice does not lead to significant effects on retinal morphology , indicating that GCAPs are not essential for the development or maintenance of retinal organization [11] . However , mutations in the GCAP1 and GCAP2 genes have been linked to inherited autosomal dominant retinopathies . Ten heterozygous mutations in the GUCA1A gene encoding GCAP1 have been linked to autosomal dominant cone dystrophy ( adCD ) , cone rod dystrophy ( adCRD ) or macular degeneration ( adMD ) [12]–[20] . One mutation in the GUCA1B gene , G157R , has been associated to autosomal dominant retinal dystrophies ranging from retinitis pigmentosa to macular degeneration [21] . Most of GCAP1 mutations map at EF-hand domains and affect Ca2+ coordination directly , such as D100E and N104K at EF-3 or L151F and E155G at EF-4 [13]–[15] , [20] , or map at the incoming or outgoing α-helixes in EF-3 and EF-4 , such as E89K , Y99C , T114I , I143NT and G159V , causing conformational distortions that make Ca2+ binding less favorable [15] , [17] , [18] . These mutations shift the Ca2+ IC50 of GC activation to higher free [Ca2+] , so that in vitro the mutant proteins fail to switch to the inhibitory state and lead to persistent activation of RetGC in the whole physiological range of [Ca2+]i [15] , [20] , [22]–[24] . In vivo , as demonstrated for the Y99C and E155G GCAP1 mutations , the unabated cGMP synthesis results in abnormally high levels of cGMP and Ca2+ in rods , and the ensuing retinal degeneration can be significantly prevented by conditions that promote constitutive stimulation of PDE6 such as constant light exposure [23] , [25] , [26] . There are aspects of GCAPs that remain less understood , such as their Ca2+-dependent structural changes or the mechanisms that determine their cellular distribution . GCAP1 and GCAP2 are both myristoylated at the NH2-terminus . While myristoylation of GCAP1 not only affects the affinity of GCAP1 for Ret-GC and Ret-GC maximal activation , but also increases the Ca2+ sensitivity of Ret-GC inhibition at EF-4 [27] , myristoylation of GCAP2 affects its overall structural stability without affecting Ret-GC regulation [28] . Both GCAP1 and GCAP2 form homodimers upon Ca2+ dissociation , with the capacity to dimerize in GCAP2 correlating with the ability to activate Ret-GC [29] . However , while in GCAP2 dimerization is reversed by Ca2+ binding , GCAP1 dimerization is resistant to the presence of Ca2+ , implying a difference in their Ca2+-dependent conformational changes [29] . Overall , the Ca2+-free form of GCAP2 shows a higher tendency to aggregate than GCAP1 . In addition , Ca2+-dependent conformational changes in GCAP2 have been shown to correlate with a site-specific phosphorylation at Ser201 , the significance of which is not yet clear as it does not affect Ret-GC regulation in vitro [30] . Regarding their cellular localization , GCAP1 is more abundant at cone than at rod outer segments [31] . GCAP2 localizes primarily to rods and at lower levels in cones . In rods , GCAP2 localization is not restricted to rod outer segments . It is present at rod inner segments at about the same level , and at lower levels in more proximal compartments of the cell [32] , [33] . At the synaptic terminal GCAP2 has been shown to interact with Ribeye , the major structural component of synaptic ribbons , and to lead to significant alterations of synaptic ribbon dynamics when overexpressed in vivo [34] , [35] . The mechanisms that determine GCAPs subcellular distribution are largely unknown , but it was proposed that GCAPs are transported by vesicular trafficking guided by Ret-GCs , in a process assisted by RD3 [36] , [37] . To study whether genetic mutations or light conditions that would preclude Ca2+-binding to GCAP2 would compromise rod cell viability by an analogous mechanism by which GCAP1 EF-hand mutations do , we set to study the effect of expressing in rods a mutant form of GCAP2 impaired to bind Ca2+: GCAP2 with all functional EF hands inactivated ( bEF−GCAP2 ) [38] . Whereas in vitro bEF−GCAP2 shows a similar biochemical behavior as Y99C-GCAP1 [24] , [38] , we show that in vivo it leads to a rapid retinal degeneration by a mechanism independent of cGMP metabolism . In vivo , the protein accumulates at the inner segment , in a form that is largely incompetent to activate the cyclase . It binds to 14-3-3 protein isoforms due to enhanced phosphorylation at Ser201 . We show that the cause of the pathology in bEF−GCAP2 mice is not constitutive activation of the cyclase , but rather the accumulation of the phosphorylated protein at the proximal compartments of the cell , likely in a conformationally unstable form stabilized by 14-3-3 binding , that ultimately causes extensive damage to the cell . We propose that this mechanism will contribute to the pathology of those inherited retinal dystrophies caused by mutations in different genes that share as an initial consequence of the mutation the sustained reduction of the intracellular concentration of Ca2+ , the so-called “light-equivalent damage” scenarios .
To study the relevance of functional EF-hand domains in GCAP2 for protein activity and photoreceptor cell integrity in vivo , we expressed a mutant form of GCAP2 with inactivated EF hands: GCAP2 ( E80Q/E116Q/D158N ) , hereafter referred to as bEF−GCAP2 , in the rod photoreceptors of transgenic mice ( Fig . 1A ) . It was previously shown that inactivation of the three functional EF hands in bGCAP2 abolishes its capacity to bind Ca2+ [38] . To generate transgenic mice we expressed the cDNA of the bovine GCAP2 isoform , so that the transgene product could be distinguished from the endogenous murine form by SDS-PAGE electrophoretic mobility . To discriminate the effect of the mutations in GCAP2 from the effect that overexpression of GCAP2 might have on the cell , we included in the study a control transgenic line that expresses wildtype bovine GCAP2 ( line E , Fig . 1A , B ) . This line was reported to express wildtype bovine GCAP2 at a ∼2∶1 ratio relative to endogenous GCAP2 [11] . We established two independent transgenic lines that expressed different levels of bEF−GCAP2 . Line A expressed bEF−GCAP2 at a ratio of 2 . 76∶1 relative to endogenous GCAP2 , whereas line B had a higher relative level of expression ( 3 . 85∶1 ratio ) , Fig . 1B and Fig . S1 , see Methods . To assess whether bEF−GCAP2 expression in rods causes compensatory changes in the expression levels of other proteins involved in cGMP metabolism , we compared the level of expression of PDE6 and Ret-GCs in retinal homogenates from wildtype and transgenic mice from lines A and B ( Fig . 1C ) . Levels of PDEα , β and γ subunits , or GC1 and GC2 were mostly unaffected in mice from line A , whereas a reduction in all proteins was observed in line B at postnatal day 22 ( p22 ) , which can be explained by the dramatic shortening and disorganization of rod outer segments observed from a very early age in this line ( Fig . 1D ) . Mice expressing bEF−GCAP2 showed a progressive retinal degeneration whose severity correlated with the level of expression of the transgene . Figure 1D shows normal retinal morphology in the control transgenic line E at p40 and at 3 months of age . In contrast , clear signs of retinal degeneration were observed in mice expressing bEF−GCAP2 from lines A and B . Mice from line B , which express the highest levels of bEF−GCAP2 , presented a substantial shortening of rod outer segments and a noticeable reduction of outer nuclear layer ( ONL ) thickness as early as p40 , with ONL thickness reduced to 6–7 rows of nuclei . Mice from line A showed a slower progression of the disease , noticeable at 3 months , when the ONL thickness was reduced to 7–9 rows of nuclei . Because expression of wildtype bGCAP2 did not cause retinal degeneration for up to one year of age in line E ( results not shown ) , the retinal degeneration observed in mice from lines A and B likely results from distinctive properties of the mutant form of GCAP2 impaired to bind Ca2+ . However , due to the different transgene expression levels , we could not exclude that the observed phenotype may result from overexpression of bGCAP2 . To rule out this possibility , we bred the control line E to homozygosity , to obtain a line that expressed bGCAP2 to equivalent levels as mutant line A . This line showed normal outer segment length and organization , as well as normal outer nuclear layer thickness for up to six months of age when raised in cyclic light [34] . From these results we conclude that mutations that impair Ca2+ binding in GCAP2 lead to retinal degeneration in vivo . In order to study the effects of the mutant protein on cell physiology , we bred the transgenic lines to GCAPs−/− mice , to obtain expression of bEF−GCAP2 or control bGCAP2 in the absence of the endogenous protein . The relative levels of expression of the transgene in the independent transgenic lines were maintained in the GCAPs−/− background ( Fig . 2A ) . Expression of bEF−GCAP2 in the GCAPs−/− background slightly accelerated the rate of retinal degeneration observed in the GCAPs+/+ background . Mice from the control lines GCAPs−/− and GCAPs−/− bGCAP2 E showed largely normal retinas with an outer nuclear layer ( ONL ) thickness of 10 rows of nuclei for up to 5 months of age ( Fig . 2B ) , and preserved normal visual function when raised in cyclic light conditions as assessed by electroretinogram ( ERG ) [34] . In contrast , GCAPs−/− expressing bEF−GCAP2 showed a progressive retinal degeneration that correlated with loss of visual function ( Fig . S2 ) . In retinas from line B the ONL was reduced to six rows of nuclei and outer segments were much shorter than normal as early as p30 ( Fig . 2B ) , when the A and B-wave amplitudes of ERG responses were half the size of normal responses from littermate controls ( not shown ) . At 3 months of age the ONL was reduced to 4 rows of nuclei , and by 5 months it was limited to a single row . Mice were unresponsive to light ( flat ERG traces ) by 7 months ( Fig . S2 ) . A slightly slower retinal degeneration was observed in mice from line A that went from a normal outer nuclear layer thickness of 12 rows of nuclei at p30 to about 5 rows by 3 months of age . ERG responses of these mice resembled normal responses at very early ages , but A- and B-wave amplitudes were reduced by half by 4 months , correlating with a dramatic cell loss in these mice between p20 and 5 months of age ( Fig . 2B and Fig . S2 ) . Most of these mice are non responsive to light by ERG by 7–8 months ( Fig . S2 ) . In vitro studies have shown that recombinant bEF−GCAP2 leads to maximal activation of Ret-GCs in reconstitution studies using washed bovine rod outer segment membrane preparations independently of free Ca2+ in the whole physiological range of [Ca2+] [38] . To assay whether the transgenic bEF−GCAP2 protein has the capacity to activate Ret-GC activity in retinal extracts from mice in a similar manner as in in vitro studies we performed guanylate cyclase activity assays in retinal extracts from the mutant or control mice obtained prior to significant retinal degeneration -between p20 and p30 - under conditions of 0 Ca2+ or 2 µM Ca2+ ( Fig . 3 ) . Ca2+-dependent modulation of Ret-GC activity was observed in retinal homogenates from wildtype mice and control GCAPs−/− bGCAP2 E line . As expected , the Ca2+-sensitive guanylate cyclase activity was undetectable in GCAPs−/− retinal extracts , indicating that the guanylate cyclase activity that is measurable in whole mouse retinal extracts originates essentially from photoreceptor cells in a GCAPs-dependent manner . As a control for the presence of functional Ret-GCs in retinal extracts , guanylate cyclase activity was also measured after addition of 3 µM recombinant bGCAP2 , which restored robust activity in a Ca2+ dependent manner . Surprisingly , retinal extracts from GCAPs−/− bEF−GCAP2 B mice resembled those of GCAPs−/− . They showed little detectable retGC activity at either 0 Ca2+ or high Ca2+ . Even though the levels of Ret-GCs and bEF−GCAP2 were reduced to some extent in these retinal extracts due to the shortening of the rod outer segments in this line , the addition of recombinant bGCAP2 showed that there was functional Ret-GCs in these extracts at levels that were sufficient to elicit a measurable activity . The results shown are the average of four independent experiments . These results indicate that while the transgenic bGCAP2 control protein expressed in the GCAPs−/− background reproduced normal activity , the transgenic mutant form of bGCAP2 impaired to bind Ca2+ showed very little detectable activity in vivo . To study whether the bEF−GCAP2 protein reproduced the localization pattern of endogenous GCAP2 in transgenic mice , we immunostained GCAP2 in retinal cryosections . Whereas transgenic bGCAP2 in the control line mimicked the localization of endogenous GCAP2 in wildtype retinas ( staining the outer segment , inner segment , cytosol of outer nuclear layer and outer plexiform layers of the retina , with the signal being most intense at rod outer segments ) ; this pattern was shifted in the case of bEF−GCAP2 , with the signal being most intense at the rod proximal compartments , particularly at the inner segment layer ( Fig . 4 ) . These results show that bEF−GCAP2 , when expressed in the GCAPs−/− background , tend to accumulate at the metabolic compartment of the cell . These results indicate that bEF−GCAP2 in the retinas of transgenic mice has a greatly reduced capacity to activate the cyclase and accumulates at the inner segment of the cell , indicating that the pathology in these mice does not result from unabated cGMP synthesis . Furthermore , the retinal degeneration in bEF−GCAP2 mice could not be prevented by raising the mice in constant light exposure that would counteract the increase in cGMP synthesis by continuous cGMP hydrolysis ( Fig . S3 ) , as was the case in Y99C-GCAP1 mice [26] . Taken together , these results point to a mechanism independent of cGMP metabolism as the molecular basis for the neurodegeneration in these mice . We reasoned that the accumulation of bEF−GCAP2 at the proximal compartments of the cell rather than its absence at the rod outer segment was the cause of the progressive retinal degeneration in these mice , given that the absence of GCAP1 and GCAP2 in GCAPs−/− mice does not affect gross retinal morphology [11] . To address why bEF−GCAP2 fails to be distributed to the rod outer segment and how its retention and accumulation at the inner segment leads to toxicity , we investigated the protein-protein interactions that the mutant form of the protein establishes in a specific manner . Immunoprecipitation assays were conducted with an anti-GCAP2 monoclonal antibody cross-linked to magnetic beads , using Triton X100-solubilized whole retinal extracts from GCAPs−/− bGCAP2 E and GCAPs−/− bEF−GCAP2 B mice . Retinal extracts from GCAPs−/− mice were carried to define the background . The pool of proteins immunoprecipitated in each case was identified by directly subjecting the elution fractions to trypsin-digestion and liquid chromatography-tandem mass spectrometry analysis ( LC-MS/MS ) . We searched for proteins identified in the GCAPs−/− bEF−GCAP2 B sample with an spectral counting at least 1 . 5-fold over the GCAPs−/− bGCAP2 and GCAPs−/− control lines ) . We found that only the distinct isoforms of 14-3-3 proteins fulfilled these criteria , being identified with a considerably higher number of peptides [1 . 33 to 3 . 2-fold higher] in the GCAPs−/−bEF−GCAP2 B than in control samples in at least two independent experiments ( Table 1 ) . Spectral counting of 14-3-3 isoforms were between 1 . 6-fold and 5-fold higher in the GCAPs−/−bEF−GCAP2 B samples than in control samples in the two experiments ( Table S1 ) . Because 14-3-3 proteins typically bind to their targets in response to phosphorylation [39] , and since phosphorylation of GCAP2 has been reported to occur in vitro at a conserved Ser at position 201 in bGCAP2 [30] , we next assayed whether the binding of 14-3-3 to GCAP2 was phosphorylation dependent . We first reproduced the observation that GCAP2 can be phosphorylated in vitro by PKG , with Ca2+-free bGCAP2 being a better substrate for the kinase than Ca2+-loaded bGCAP2 ( Fig . 5A ) . Subsequently , we used recombinant bGCAP2 or bEF−GCAP2 in in vitro phosphorylation reactions with PKG to generate phosphorylated-bGCAP2 or mock-treated bGCAP2 for pull-down assays with bovine whole retinal homogenates ( Fig . 5B ) . As seen in Fig . 5C , 14-3-3 showed preferential binding to the phosphorylated form of bGCAP2 or bEF−GCAP2 in two independent experiments . The observations that 14-3-3 binds more efficiently to bEF−GCAP2 than to bGCAP2 in vivo and that 14-3-3 binds to bGCAP2 in a phosphorylation dependent manner , together with the reported higher efficiency of GCAP2 phosphorylation in its Ca2+-free rather than its Ca2+-bound conformational state led us to hypothesize that bEF−GCAP2 might be abnormally phosphorylated in the living cell . To test this hypothesis we performed a 32Pi -metabolic labeling of GCAPs−/− bGCAP2 and GCAPs−/− bEF−GCAP2 retinas in situ , followed by GCAP2 immunoprecipitation and SDS-PAGE analysis . Following the incorporation of 32Pi into the retinas of dark-adapted mice for 2 h , retinas were either kept in darkness or exposed to 5 min of bright white light and immediately subjected to Triton X100-solubilization and GCAP2 immunoprecipitation . GCAPs−/− retinas were carried as a negative control . Fig . 6A shows equal fractions of the Triton X100-solubilized retinas after 32Pi-incorporation and 5 min dark- or light-exposure . The overall pattern of bands in this panel shows that incorporation of 32Pi into the ATP pool of the retina occurred at comparable levels in all samples , allowing the detection of phosphorylated proteins and changes in the overall phosphorylation pattern caused by light ( e . g . the light-dependent phosphorylation of rhodopsin is observed at 35–37 kDa ) . GCAP2 phosphorylation could not be detected in whole retinal extracts , so these samples were used as inputs for the GCAP2 immunoprecipitation assay shown in Fig . 6B . GCAP2 was phosphorylated to low levels in the GCAPs−/− bGCAP2 sample in the dark , and to a slightly higher extent when the retina was exposed to light . No 24 kDa bands were observed in the GCAPs−/− samples . Strikingly high levels of bEF−GCAP2 phosphorylation were observed in GCAPs−/− bEF−GCAP2 samples ( lines A and B ) . A GCAP2 immunoblot of the 32P-labeled membrane confirmed that comparable levels of GCAP2 were immunoprecipitated in GCAPs−/− bGCAP2 and GCAPs−/− bEF−GCAP2 samples ( Fig . 6C ) . Fig . 6D shows the subsequent immunostaining of the 14-3-3 pan and epsilon isoforms in the same membrane , further confirming the selective binding of 14-3-3 to the phosphorylated mutant form of GCAP2 impaired to bind Ca2+ . GCAP2 phosphorylation was further characterized by isoelectrofocusing gel analysis followed by immunoblotting with a GCAP2 antibody ( Fig . 7 ) . Under room light conditions wildtype C57/B6 mice showed two bands of roughly equal intensity corresponding to the pI of the unphosphorylated ( 4 . 92 ) and singly phosphorylated ( 4 . 85 ) mGCAP2 . The intensity of the 4 . 85 band was greatly diminished when NaF , a broad phosphatase inhibitor , was omitted from the samples , thus confirming the identity of this band as phosphorylated GCAP2 ( Fig . 7A ) . We conclude that about half of the total GCAP2 protein is phosphorylated in wildtype mice under standard room light conditions . The extent to which endogenous mGCAP2 was phosphorylated in wildtype mice under room light conditions was higher than that of bGCAP2 in GCAPs−/− bGCAP2 transgenic mice . To address whether GCAP2 phosphorylation takes place differentially in dark/light conditions , wildtype mice that were adapted to room light for 1 h were dark-adapted for up to 14 h , and GCAP2 phosphorylation was analyzed at 1 , 2 , 3 , 5 and 14 h . Fig . 7B shows that the ratio of unphosphorylated to phosphorylated GCAP2 did not vary substantially during the 14 h dark-adaptation period . If we presume that GCAP2 is preferentially phosphorylated during periods of light exposure when in its Ca2+-free conformation , these results may indicate that a few hours of dark- or light-adaptation are not enough to have a noticeable effect on the overall GCAP2 population . This would not be surprising if only newly synthesized GCAP2 was subjected to the kinase/phosphatase regulation ( see Discussion ) . Isoelectrofocusing of retinal samples from GCAPs−/− bEF−GCAP2 and GCAPs−/− bGCAP2 were performed to assay the steady-state relative levels of non-phosphorylated and phosphorylated GCAP2 ( Fig . 7C ) . Whereas endogenous GCAP2 in wildtype C57/B6 mice showed similar proportions of non-phosphorylated and phosphorylated GCAP2 , the GCAPs−/− bEF−GCAP2 sample showed a larger fraction of phosphorylated GCAP2 and the GCAPs−/− bGCAP2 sample showed the reverse: a larger fraction of non-phosphorylated GCAP2 . These results are consistent with the metabolic labeling results , namely , low levels of phosphorylation in the GCAPs−/− bGCAP2 control line , and much higher phosphorylation levels in the GCAPs−/− bEF−GCAP2 line ( Fig . 7C and Fig . 6B ) . To address whether 14-3-3 binding to phosphorylated GCAP2 might be the cause of its retention at inner segments , we analyzed the localization of the 14-3-3 proteins in retinal sections from GCAPs−/− bGCAP2 and GCAPs−/− bEF−GCAP2 samples . Fig . 8 shows that 14-3-3 epsilon localizes to all cell layers of the retina; the ganglion cell layer , the inner cell layer and the photoreceptor cell layer of the retina . In photoreceptor cells it appears to distribute to the inner segment , the perinuclear region and the synaptic terminal , but it is excluded from the outer segment . This isoform of 14-3-3 colocalized with GCAP2 mainly at the inner segment of GCAPs−/− bGCAP2 samples , but also to the perinuclear region and synaptic terminals in the GCAPs−/− bEF−GCAP2 samples . From these results we infer that the localization pattern of 14-3-3ε in photoreceptor cells would be consistent with a role of GCAP2 phosphorylation and 14-3-3 binding at retaining the mutant form of GCAP2 impaired to bind Ca2+ at the proximal compartments of the cell . To address whether phosphorylation of GCAP2 is what causes the retention of bEF−GCAP2 at the inner segment and proximal compartments of the cell , we expressed a mutant form of bEF−GCAP2 in which Ser201 was mutated to Gly as a transient transgene in rod cells , given that Ser201 is the only residue that was found to be phosphorylated in GCAP2 [30] . The bS201G/EF−GCAP2 cDNA was expressed under the rod opsin promoter by subretinal injection and in vivo electroporation of the DNA in neonatal GCAPs−/− mice as described [40] . Both bGCAP2 and bEF−GCAP2 cDNAs were carried out in parallel in order to compare the localization of the mutants under equivalent experimental conditions . A plasmid expressing the green fluorescent protein ( GFP ) under the Ubiquitin C promoter was coinjected to identify the region around the injection site in which DNA transfection was efficient , and electroporated retinas were analyzed at p28 . Fig . 9 shows that the localization of bGCAP2 and bEF−GCAP2 in the transient transgenic mice obtained by electroporation reproduced the localization observed in stable transgenics: specifically , bEF−GCAP2 was retained at the inner segment and proximal compartments of transfected photoreceptors . bEF−GCAP2 was excluded from the outer segment , which is demarcated by rhodopsin immunofluorescence ( red ) ( Fig . 9 panels E , F and profile from cell N . 6 , Fig . S4 for additional images and profiles ) . In contrast , the mutant bS201G/EF−GCAP2 distributed to the proximal compartments of the cell but also to rod outer segments . As shown in panels H-I of Fig . 9 and in the profile from cell N . 10 , the GCAP2 signal -in green- co-labeled with rhodopsin ( red ) in all transfected cells ( thirteen cells analyzed , 57% of GCAP2 signal co-labeled with rhodopsin on average , see Fig . S4 ) , indicating its redistribution to rod outer segments . On average , 50% of the protein distributed to rod outer segments when bGCAP2 was expressed , whereas virtually all bEF−GCAP2 was retained at the inner segment and proximal compartments . Mutating S201 to Gly in bEF−GCAP2 reverted this retention , resulting in 57% of the protein distributing to rod outer segment ( histogram in Fig . 9J ) . These results indicate that phosphorylation at Ser201 in the mutant form of GCAP2 impaired to bind Ca2+ is what causes its accumulation at the inner segment and proximal compartments of the cell , ultimately leading to toxicity . The finding that GCAP2 locked in its Ca2+-free form ( bEF−GCAP2 ) is retained at the inner segment compartment resulting in toxicity could have important implications for disease , if it meant that endogenous Ca2+-free GCAP2 would be retained at the inner segment in wildtype mice during conditions that promoted a sustained reduction in [Ca2+]i . Mutations in several genes involved in the light response result in the sustained hyperpolarization of the cell and a steady reduction in [Ca2+]i . Null mutations in GUCY2D or RD3 causative of the Lebers Congenital Amaurosis ( LCA ) form of blindness , for instance , would result in reduced levels of cGMP at the rod outer segments , the closure of cGMP-channels and hyperpolarization of the cell , with the ensuing reduction in the influx of Ca2+ to rod inner segment [36] , [37] , [41] . Also associated to LCA , null mutations in RPE65 result in retinal degeneration due to the basal constitutive activity associated to opsin , the apoprotein form of the visual pigment , leading to a sustained hyperpolarization of the cell [42] . These genetic disorders that ultimately cause an effect similar to continuous light exposure , are collectively referred to as “equivalent-light” disorders [43] . Therefore , if GCAP2 was retained at the inner segment under constant illumination conditions , it would be an indication that this pathway could contribute to the pathology of these disorders . Wildtype mice were exposed to constant fluorescent light ( 700 lux ) , or kept in dark cabinets for thirty days , and GCAP2 subcellular distribution was analyzed by immunofluorescence ( Fig . 10 ) . The percentage of GCAP2 co-localizing with rhodopsin was quantified in four mice per condition . After 30 days of light exposure 84% of GCAP2 was retained at the inner segment , in contrast to 45% of GCAP2 retained in mice kept for 30 d in constant darkness , P≤0 , 0001 ( histogram Fig . 10 ) . These results show that a sustained drop in [Ca2+]i in wildtype rod photoreceptors causes GCAP2 retention at the inner segment . This , together with the results obtained from bEF−GCAP2 transgenic mice showing that accumulation of bEF−GCAP2 at the inner segment results in toxicity , points to the sustained retention of Ca2+-free GCAP2 at the inner segment as a pathway that could contribute to the pathology of “light-equivalent” disorders .
We here report that a form of GCAP2 with mutations that impair Ca2+ coordination at the three functional EF-loops ( bEF−GCAP2 ) led to retinal degeneration when expressed in rods in transgenic mice . In vitro the bEF−GCAP2 mutant shows a similar shift in Ca2+ sensitivity of guanylate cyclase regulation as the Y99C , E155G and other GCAP1 mutants that directly or indirectly affect Ca2+ coordination [22] , [24] , [38] . These GCAP1 mutants have been demonstrated to cause retinal degeneration in vivo by leading to persistent activation of the cyclase , causing elevated levels of cGMP and Ca2+ [23] , [25] , [26] . Intriguingly , we found that the retinal degeneration caused by bEF−GCAP2 expression in rods was independent of cGMP metabolism . When guanylate cyclase activity was measured in retinal homogenates from bEF−GCAP2 transgenic mice , instead of constitutive activation of the cyclase we found very diminished cyclase activity independently of the [Ca2+] conditions , which contrasts with the normal cyclase activity observed in homogenates of wildtype and bGCAP2 control-transgenic mice ( Fig . 3 ) . Furthermore , retinal degeneration in bEF−GCAP2 transgenic mice could not be prevented or delayed by raising the mice under constant light exposure ( Fig . S3 ) . These results show for the first time that functional EF-hands in GCAP2 are required for photoreceptor cell integrity in vivo , by a mechanism independent of guanylate cyclase regulation . In contrast to the bGCAP2 control-transgenic protein that reproduced the endogenous mGCAP2 subcellular localization , bEF−GCAP2 largely accumulated at inner segment and proximal compartments of the rod when it was expressed in the GCAPs−/− background ( Fig . 4 ) . At this compartment , bEF−GCAP2 was phosphorylated to a much higher extent than the control transgenic protein in in situ phosphorylation assays as well as under steady state conditions in the intact rod as shown by IEF , and it was found to bind 14-3-3 proteins ( Table 1 , Figs . 5–7 ) . This constitutes the first report that GCAP2 is phosphorylated in vivo , at much higher levels when locked in its Ca2+-free conformation , and that phosphorylation of GCAP2 triggers 14-3-3 binding . We show that 14-3-3 localization in rod photoreceptors is restricted to proximal compartments and excluded from the outer segments ( Fig . 8 ) . Furthermore , we demonstrate that phosphorylation is required for bEF−GCAP2 retention at proximal compartments by showing that replacing Ser201 by Gly in bEF−GCAP2 substantially reverts this retention ( Fig . 9 ) . On average 57% of bS201G/EF−GCAP2 localized to rod outer segments ( Fig . 10 histogram and Fig . S4 , n = 13 cells ) . We believe that the reason that a 100% reversion was not observed is that 14-3-3 shows some affinity for unphosphorylated bEF−GCAP2 as well ( Fig . 5 ) . We therefore infer that 14-3-3 binding to phosphorylated GCAP2 retains the protein at proximal compartments , in what clearly represents an important step in the regulation of GCAP2 subcellular distribution in vivo , somewhat analogous to 14-3-3 regulation of phosducin availability during dark and light adaptation . 14-3-3 proteins are a family of phosphobinding proteins of about 30 kDa that comprises seven homologs in mammals . They exist as homo- or hetero-dimers that are rigid in structure , with each 14-3-3 dimer binding to two different phospho-binding sites either in the same or in two independent target proteins . By masking an epitope , clasping epitopes or promoting the scaffolding of their clients , 14-3-3 proteins exert a diverse range of regulatory roles in metabolism , trafficking or integration of cell survival versus cell death pathways [39] . In the retina , 14-3-3 proteins interact with phosducin at rod inner segments , regulating the amount of free phosducin during dark- and light-adaptation [44] , [45] . Phosducin modulates the amount of Trαβγ heterotrimer through competition with Gtα subunit for binding to the Gtβγ complex . When light exposure activates Gt , releasing Gtβγ from Gtα at rod outer segments , phosducin association to Gtβγ facilitates Gtα and Pd-Gtβγ independent translocation to the inner segment compartment [46] . At the inner segment during dark-adaptation phosducin is simultaneously phosphorylated at Ser-54 and Ser-73 residues by PKA and CaMK , which causes a competing interaction with the 14-3-3 protein that dramatically reduces phosducin binding to Gtβγ [47] . This allows the redistribution of Gtα and Gtβγ to rod outer segments , the former assisted by UNC119 and the latter by PrBP [48] , [49] . At rod outer segments Tr subunits are discharged to membranes and a heterotrimer forms again . How 14-3-3 binding to phosphorylated GCAP2 fits with GCAP2 overall role in photoreceptor cell physiology and inherited retinal dystrophies is only emerging . It is clear from this work that GCAP2 is phosphorylated preferentially in its Ca2+-free form in vivo . Because it is well established that GCAP2 in its Ca2+-free form forms dimers [29] , and that 14-3-3 exists as dimers that bind to two consensus binding sites in client proteins [39] , it seems straightforward to propose that a dimer of 14-3-3 would bind to a dimer of GCAP2 , presumably to stabilize it ( Fig . 11 ) . Because GCAP1 and GCAP2 , unlike recoverin or phosducin , were shown not to redistribute between subcellular compartments during dark- or light-adaptation [50] , we deduce that this mechanism would mainly affect the cytosolic distribution of newly synthesized protein . We propose a model in which the GCAP2 molecules synthesized during the dark period ( predominantly in the Ca2+-loaded state ) would bind to RetGC and be transported to rod outer segments , whereas the GCAP2 molecules synthesized in the light period ( GCAP2 in its Ca2+-free state ) would be phosphorylated and retained at proximal compartments by 14-3-3 binding ( Fig . 11 ) . Such a scenario would result in the phosphorylation and retention to proximal compartments of about 50% of GCAP2 molecules in a physiological situation ( wildtype mice raised in standard cyclic light ) . This is what we observe by IEF ( Fig . 7 ) and by immunolocalization analysis ( Fig . 4 ) . This model would also explain why 12 h of dark-adaptation did not have a noticeable effect on the steady-state phosphorylation levels of GCAP2 ( Fig . 7 ) . The model would predict that wildtype mice reared under constant light exposure for a period of time covering the complete renewal of the rod outer segment would result in massive GCAP2 retention at the inner segment , given that GCAP2 would always be synthesized in a context of low [Ca2+]i , and that is precisely what we have observed after exposing mice to constant light for 30 days ( Fig . 10 ) . In contrast , it would be predicted that wildtype mice reared in constant darkness would result in GCAP2 major localization to the rod outer segment layer . This , however , was not observed . In mice reared in darkness for 30 days GCAP2 distributed about equally between inner and outer segment layers ( Fig . 10 ) . We interpret this result as an indication that some of the protein interactions required for GCAP2 transport to the rod outer segment ( e . g . RetGC , RD3 ) might be rate-limiting . We propose that GCAP2 phosphorylation and 14-3-3 binding constitute a major molecular determinant of GCAP2 subcellular localization upon its synthesis . What is its physiological relevance ? A possibility is that 14-3-3 binding to GCAP2 , by trapping GCAP2 to proximal compartments , might work to secure a reservoir of GCAP2 at these compartments , where GCAP2 may be exerting other roles , e . g . at the synaptic terminal [34] , [35] . Alternatively , the 14-3-3 trapping of Ca2+-free GCAP2 upon its phosphorylation might serve as a protein quality control mechanism , to avoid that an excess of Ca2+-free , aggregation-prone GCAP2 molecules would reach the rod outer segment . Irrespective of its physiological significance , this regulatory enzymatic step is specific of GCAP2 , given that GCAP1 is not phosphorylated , and might have evolved because it is more relevant for rods than cones . Conditions that substantially alter this regulatory mechanism increasing the protein retention at the inner segment of the Ca2+-free form would have toxic consequences for the cell . We propose that toxicity in this scenario would arise from GCAP2 natural tendency to aggregate ( see below ) . GCAP2 phosphorylation and 14-3-3 binding are observed to a more moderate extent in the bGCAP2 control transgenic line ( IEF gel in Fig . 7 ) than in wildtype mice , presumably because bovine GCAP2 is not such a good substrate for the murine kinase as the endogenous murine GCAP2 . In wildtype mice phosphorylated GCAP2 at steady state constitutes about 50% of the total protein , consistent with about 50% of the protein retention at rod proximal compartments . This indicates that GCAP2 phosphorylation and 14-3-3 binding are not in itself toxic for the cell . It is therefore the deregulation of this mechanism– when all GCAP2 molecules are impaired to coordinate Ca2+ and GCAP2 phosphorylation and 14-3-3 binding are happening to a much larger extent- that correlates with severe retinal degeneration in the bEF−GCAP2 line . How does the accumulation of GCAP2-14-3-3 complexes at the rod inner segment lead to cell death ? We hypothesize that accumulation of these complexes might result in pathology due to the formation of misfolded GCAP2 oligomers , in much a similar way to which synuclein , APP , Tau , Huntingtin or ataxin lead to neuronal cell death in Parkinson's ( PD ) , Alzheimer ( AD ) , Huntington's ( HD ) or spinocerebellar ataxia ( SCA ) diseases . GCAP2 shows a natural tendency to aggregate . Structural studies have shown that the Ca2+-free form of GCAP proteins , and particularly of GCAP2 , are difficult to maintain in solution and are prone to aggregation [51] . When expressed in bacteria , recombinant GCAP2 accumulates in inclusion bodies , is only solubilized at high concentrations of guanidinium or urea , and is difficult to maintain in solution after refolding [1] . Dimers and high molecular weight aggregates can typically be distinguished by SDS-PAGE , more prominently for EF−GCAP2 than for the wildtype form of the protein ( e . g . this study , Fig . 5B ) . On the other hand , previous studies have found a close association between 14-3-3 and progressive neurodegenerative diseases . 14-3-3 proteins have been shown to colocalize with AD neurofibrillary tangles that are composed primarily of hyperphosphorylated tau proteins [52] , [53] . In PD , 14-3-3 is detectable in Lewy bodies which accumulate α-synuclein [54]; and 14-3-3 colocalization was also reported for mutant ataxin in SCA [55] . Furthermore , 14-3-3 zeta and epsilon binding to phosphorylated ataxin-1 at S776 was shown to aggravate neurodegeneration by stabilizing mutant ataxin , retarding its degradation and enhancing its aggregation in transfected cells and transgenic flies [55] . The requirement of 14-3-3 zeta for Htt86Q aggregate formation has also been established in cells [56] . We propose that the mutant form of GCAP2 locked in its Ca2+-free conformation results in toxicity in vivo by the progressive formation of soluble high molecular weight oligomers of GCAP2-14-3-3 that are toxic for the cell . Inclusion bodies were not detected in our immunofluorescence assays with the polyclonal or monoclonal anti-GCAP2 antibodies used , or the anti-14-3-3ε monoclonal antibody . It may happen that these antibodies do not recognize inclusion bodies , or that their absence would result from a relatively efficient clearance of the mutant protein and therefore slow formation of putative deposits . In this sense we have observed that inhibition of the proteasome results in an increase of EF−GCAP2 levels ( López-del Hoyo and Méndez , unpublished observation ) . This mechanism of toxicity caused by GCAP2 misfolding may contribute to the pathology of genetic mutations causing “equivalent-light damage” that result in a sustained reduction in the level of intracellular Ca2+: e . g . mutations in the visual cycle resulting in opsin basal constitutive activity ( e . g . null mutations in RPE65 [42] ) . Furthermore , this mechanism of toxicity is likely to contribute to cell death and retinal degeneration in those cases of Lebers Congenital Amaurosis ( LCA ) in which two conditions converge: GCAPs accumulation at the inner segment and a sustained reduction in the level of intracellular Ca2+ . Those conditions are met , for instance , in LCA1 caused by null mutations in RetGC-E ( GUCY2D ) or LCA12 caused by mutations in RD3 , two severe and prevalent inherited retinal dystrophies . In conclusion , we propose that GCAP2 may be a mediator of “equivalent-light” genetic damage , by its natural tendency to aggregate when in its Ca2+-free form , in a process regulated by phosphorylation and 14-3-3 binding . Future studies will be addressed at further characterizing the stoichiometry , solubility and turn-over of GCAP2-14-3-3 complexes , as well as their effects on the normal functions of the cell .
This study was conducted in accordance with the ARVO statement for the Use of Animals in Ophthalmic and Vision Research and in compliance with Acts 5/1995 and 214/1997 for the welfare of experimental animals of the Autonomous Community ( Generalitat ) of Catalonia , and approved by the Ethics Committee on Animal Experiments of the University of Barcelona and the University of Southern California . The GCAP2 expression vectors used to generate transgenic mice were obtained by assembling the 4 . 4 kb mouse opsin promoter with bovine wildtype GCAP2 cDNA or mutant bEF−GCAP2 [GCAP2 E80Q/E116Q/D158N , [38]] cDNA ( 0 . 7 kb ) , and a 0 . 6 kb fragment containing the mouse protamine 1 polyadenylation sequence , into pBluescript II SK ( Stratagene , La Jolla , California ) . The resulting fusion gene , 5 . 7 kb in size , was excised from the plasmid , gel purified and microinjected at 1 µg/ml into the pronuclei of C57Bl6/J×DBA/2J F1 hybrid mouse embryos ( The Jackson Laboratories , Bar Harbor , Maine ) . Injected embryos were implanted into pseudopregnant females , and progenie was screened for founders by PCR amplification of tail genomic DNA with primers: Rh1 . 1: 5′GTGCCTGGAGTTGCGCTGTGGG3′ ( forward ) and p24: 5′TGGCCTCCTCGTTGTCCGGGACCTT3′ ( reverse ) . Founder mice were bred to C57Bl6 mice to maintain the transgene in a pigmented wildtype genetic background , or to GCAPs−/− to generate GCAPs−/− bEF−GCAP2 mice . To detect transgenic GCAP2 expression by immunoblot , retinas from mice of each genotype were obtained at either postnatal day 22 ( p22 ) ( for WT and mice from line B ) or p40 ( lines A and E ) , and were homogenized in 100 µl of homogenization buffer [80 mM TrisHCl , pH 8 . 0 , 4 mM MgCl2 , 0 . 5 mg/ml Pefabloc SC , 0 . 5 mg/ml Complete Mini protease inhibitors ( Roche , Basel , Switzerland ) ] . After addition of SDS Laemmli sample buffer , samples were boiled for 5 min , and fractions corresponding to 1/40 of a retina were resolved by SDS-PAGE in a 12% tris-glycine gel and transferred to nitrocellulose membranes ( Protran , Schleicher & Schuell , Keene , NH ) . Membranes were incubated with polyclonal antibodies to bovine GCAP2 [p24ΔN [1] , a gift from A . Dizhoor , Pennsylvania College of Optometry , Elkins Park , Pennsylvania] , [GC1 and GC2 [57] , a gift from D . Garbers , HHMI and UT Southwestern Medical Center , Dallas] and PDE ( αβγ2 , Cytosignal , Irvine , CA ) . Immunopositive protein bands were detected with a peroxidase-conjugated goat anti-rabbit IgG with the ECL system ( Amersham , UK ) . For determination of the precise level of expression of the transgene ( expressed as a function of the endogenous ) , retinal extracts from mice from bEF−GCAP2 line B and line A ( 2-fold serial dilutions of retinal extracts obtained as described above ) were directly compared to retinal extracts from the bGCAP2 control line ( 2-fold dilutions ) . The expression level of bGCAP2 in this line was previously established as 2-fold the endogenous levels [11] . This same study established that the anti-GCAP2 antibody used recognized bGCAP2 with a 1 . 5-fold higher affinity than mGCAP2 [11] . That is the reason that we compared transgenic bEF−GCAP2 to the transgenic bGCAP2 reference . The 2-fold serial dilutions in each sample were used to obtain the integration values of those bands present in the linear range in the same gel , for a direct comparison . The expression of bEF−GCAP2 line A was determined to be 2 . 76±0 . 12 –fold the endogenous levels ( average ± St Dev , n = 3 ) . The expression of bEF−GCAP2 line B was estimated to be 1 . 4-fold higher than line A , that is , 3 . 85-fold the endogenous levels . For histological analysis of the retina by light microscopy , eyecups were marked for orientation , fixed , embedded in epoxy resin and sectioned at 1 µm thickness as described previously [58] . Retinal morphometry measurements were taken as previously described [58] . Guanylate cyclase activity was assayed in mouse retinal homogenates . Six retinas from dark-adapted mice of each genotype were dissected under infrared illumination , pooled and homogenized in 112 µl of 2× assay buffer ( 100 mM MOPS-KOH pH 7 . 5 , 16 mM NaCl , 200 mM KCl , 2 mM IBMX , 20 mM MgCl2 , 14 mM 2-β-mercaptoethanol ) . From this , 12 . 5 µl aliquots were mixed with either 7 . 5 µl of 1 . 33 mM EGTA ( for a final concentration of 0 . 4 mM EGTA per reaction , the “low Ca2+” condition ) or 7 . 5 µl of 6 . 6 µM CaCl2 ( for a final concentration of 2 µM Ca2+ , the “high Ca2+” condition ) and preincubated at 30°C for 10 min . Reactions were initiated by addition of 5 µl of 5× substrate mix ( 1 . 0 mM GTP , 0 . 2 µCi/µl of [α-32P]GTP , 1 . 0 mM ATP ) , and allowed to proceed for 15 min at 30°C . Reactions were terminated by addition of 500 µl of ice-cold 120 mM Zn ( OAc ) 2 , neutralized with 500 µl of Na2CO3 , kept at −80°C for 15 min and centrifuged at 14 , 000 g , 4°C for 20 min . Radiolabeled cGMP in the supernatants was separated from radiolabeled GTP by alumina column chromatography as described [59] . Protein concentration in retinal homogenates was determined by Bradford . Results are the average and standard deviation of four independent experiments performed in duplicate , with mice that were between p20 and p30 . Guanylate cyclase activity was also determined in all retinal homogenates after the addition of 3 µM recombinant GCAP2 as a control for the presence of active Ret-GCs . To obtain retinal sections for immunofluorescence analysis mouse eyecups were fixed , infiltrated in sucrose or acrylamide , embedded in OCT and cryosectioned as described [34] . Sections were incubated with blocking solution ( 3% normal goat serum , 1% BSA , 0 . 3% Triton X100 in PBS pH 7 . 4 , 1 h at room temperature ) ; primary antibody ( 14 h at 4°C ) , secondary antibody ( 1 h at room temperature ) , and fixed for 15 min in 4% paraformaldehyde prior to being mounted with Mowiol [Calbiochem , Billerica , MA] . An antigen retrieval treatment of retinal sections [incubation in 0 . 05 mg/ml proteinase K in PBS pH 7 . 4 for 2 min at room temperature followed by a heat shock at 70°C for 10 sec] was needed for GCAP2 immunostaining . Antibodies used were: a polyclonal anti-GCAP2 ( 35 ) , monoclonal anti-GCAP2 [mAb2235 , Millipore , Billerica , MA] , rabbit monoclonal anti-14-3-3ε [EPR3918 , abcam , Cambridge , UK] . Secondary antibodies for immunofluorescence were Alexa 488 goat anti-rabbit IgG and Alexa 555 goat anti-mouse IgG [Molecular Probes , Eugene , Oregon] . Images were acquired at a laser scanning confocal microscope ( Leica TCS-SL and TCS-SP2 ) . For GCAP2 immunoprecipitation in order to identify protein interacting partners in the different phenotypes [GCAPs−/− bGCAP2 , GCAPs−/− bEF−GCAP2 and GCAPs−/− control mice] forty retinas per phenotype were pooled and homogenized in HEPES buffer [10 mM HEPES pH 8 . 0 , 5 mM KCl , 135 mM NaCl , 1 . 5 mM MgCl2 , 4 mM EGTA , 1 mM PMSF , 1 mM NaF , 1 mM β-mercaptoethanol , 1% Triton-X100 and protease inhibitor cocktail Complete Mini ( Roche , Basel , Switzerland ) ] , and clarified by centrifugation . Supernatants were incubated with anti-GCAP2 monoclonal antibody-covalently crosslinked to magnetic beads ( Dynabeads , Life Technologies , Carlsbad , California ) for 45 minutes at room temperature ( anti-GCAP2 mAb2235 , Millipore , Billerica , MA ) . Following extensive washing , elution was performed with 0 . 2M Glycine-HCl pH 2 . 5 . Elution fractions were neutralized and concentrated by ethanol precipitation , reduced and alkylated with 45 mM DTT at 60°C followed by 100 mM iodoacetamide at room temperature , dehydrated and rehydrated with sequencing grade trypsin in 25 mM ammonium bicarbonate for 12 h . For LC-MS/MS samples were resuspended in 0 . 1% formic acid and injected into a series Proxeon LC nanoEASY system ( Thermo Fisher Scientific , West Palm Beach , Florida ) coupled to a LTQ-Velos Orbitrap ( Thermo Fisher Scientific , West Palm Beach , Florida ) . The resulting mass spectral peak lists were searched with the Sequest search engine ( v . 2 . 1 . 04 , Matrix Sciences , London , UK ) against the merged BOVIN-MOUSE UP SP r 2011-1 . fasta sequence library . Immunoprecipitation assays and LC-MS/MS analysis with the indicated mouse phenotypes were performed in three independent experiments , with similar results . For in vitro phosphorylation of GCAP2 in the presence of radioactivity , 20 µl reaction mixtures contained 8 . 5 µg of purified recombinant wildtype bGCAP2 or bEF−GCAP2 , purified PKGIα ( 100 units , Calbiochem , Billerica , MA ) and 3 µCi of 33P-γATP ( Perkin Elmer , Massachusetts , USA ) in phosphorylation reaction buffer ( 30 mM Tris-HCl pH 7 . 5 , 5 mM MgCl2 , 5 mM sodium phosphate buffer pH 7 . 5 , 6 mM DTT , 0 . 1 mM EGTA and 10 µM ATP ) . For reactions in Ca2+ or EGTA conditions , the 0 . 1 mM EGTA in the reaction buffer was substituted to 5 mM CaCl2 or 2 mM EGTA , respectively . cGMP was added to 500 µM ( to obtain phosphorylated GCAP2 or P-GCAP2 ) or not added ( mock- controls ) . After incubation for 2 h at 30°C and overnight at 4°C , each reaction mixture was diluted with Laemmli buffer and resolved by 15% SDS-PAGE . Following transfer to a nitrocellulose membrane , an autoradiograph of the 33P phosphorylation products was obtained by 15 min of exposure to a Kodak X-ray film . The nitrocellulose membrane was subsequently incubated with a pAb anti-GCAP2 and IRDye 800CW Goat Anti-rabbit IgG for GCAP2 immunodetection . To obtain phosphorylated bGCAP2 or bEF−GCAP2 for pull-down assays in the absence of radioactivity , the same procedure was used except that 25 µg of bGCAP2 or bEF−GCAP2 protein and 230 units of purified PKGIα were used per reaction tube . The product of each reaction tube was cross-linked to 2 . 5 mg of magnetic beads ( Life Technologies , Carlsbad , California ) and used in pull-down assays with solubilized bovine retina . Each sample was incubated with material corresponding to 1/8 of a bovine retina , previously homogenized in binding buffer ( 10 mM HEPES , 135 mM NaCl , 5 mM KCl , 1 mM PMSF , 1 mM NaF , 1 mM β-mercaptoethanol , 1% Triton X-100 , 4 mM EGTA , 2 mM EDTA , Complete Mini protease inhibitors , pH 7 . 4 ) and pre-cleared by centrifugation . After 1 h incubation at room temperature , beads were washed and bound proteins were eluted under acidic conditions , equilibrated and ethanol precipitated . Samples were resolved by 15% SDS-PAGE and transferred to a nitrocellulose membrane . For Western detection of GCAP2 and 14-3-3 the following antibodies were used: a polyclonal anti-GCAP2 ( 35 ) , a pAb to 14-3-3pan ( JP18649 , IBL International , Hamburg , Germany ) , a mAb to 14-3-3ε ( EPR3918 , abcam , Cambridge , UK ) , a IRDye 800CW Goat anti-rabbit IgG and a IRDye 680CW Goat anti-mouse IgG ( Tebu Bio , Offenbach , Germany ) . Image was acquired at the Odyssey Imaging System ( LI-COR , Lincol , Nebraska USA ) . All mice for in situ phosphorylation assays were 30–36 days old . Mice were dark-adapted for a minimum of 14 h prior to use . Retinas were dissected under infrared light ( two retinas per phenotype per light condition ) and incubated for 90 min in 600 µl of bicarbonate-buffered Locke's solution ( 112 . 5 mM NaCl , 3 . 6 mM KCl , 2 . 4 mM MgCl2 , 1 . 2 mM CaCl2 , 10 mM HEPES , 0 . 02 mM EDTA , 20 mM NaHCO3 , 10 mM glucose , 3 mM sodium succinate , 0 . 5 mM sodium glutamate , 0 . 1% vitamin and amino acids supplement ) containing 1 mCi/ml [32Pi]H3PO4 ( 10 mCi/ml , Perkin Elmer , Massachusetts , USA ) in the dark in a 5% CO2 incubator to allow incorporation of 32P in the endogenous ATP pool . Following incubation , retinas were washed with Locke's solution and immediately homogenized in 200 µl of solubilization buffer [10 mM HEPES , 135 mM NaCl , 5 mM KCl , 1 mM PMSF , 2 mM NaF , 4 mM EGTA , 1 . 5 mM MgCl2 , 2 mM EDTA , 1% Triton X100 , complete mini protease inhibitors ( Roche Applied Sciences , Basel , Switzerland ) , pH 7 . 4] in the dark , or exposed to bright white light for 5 min prior to homogenization . Samples were clarified by centrifugation at 13 , 000 g for 20 min at 4°C and supernatants were transferred to new tubes . From these samples , 10 µl aliquots were resolved by 15% SDS-PAGE to obtain an autoradiograph of the input samples . Visualization of inputs required 4 h of exposure with a Kodak X-ray film . The remaining volume of samples ( 180 µl ) were used to immunoprecipitate GCAP2 with an anti-GCAP2 monoclonal antibody ( anti-GCAP2 mAb2235 , Millipore , Billerica , MA ) coupled to magnetic beads ( Dynabeads , Life Technologies , Carlsbad , California ) as described above . After acidic elution of bound fractions , samples were neutralized and proteins precipitated with ethanol . Protein pellets were resolved by 15% SDS-PAGE and transferred to a nitrocellulose membrane . Visualization of phosphorylated proteins in the bound fractions by autoradiography required 4 days of exposure with a Kodak X-ray film . The membrane was subsequently incubated with a polyclonal antibody anti-GCAP2 and IRDye 800CW Goat Anti-rabbit IgG; and a polyclonal antibody to 14-3-3pan ( JP18649 IBL International , Hamburg , Germany ) and IRDye 680CW Goat Anti-mouse IgG , and scanned at an Odyssey Image Acquisition system ( LI-COR , Lincoln , Nebraska USA ) . Retinas from mice of the indicated phenotypes were dissected under infrared light , and each retina was solubilized in 150 µl of buffer ( 10 mM Hepes pH 7 . 5 , 1 mM MgCl2 , 10 mM NaCl , 0 . 1 mM EDTA , 1% dodecyl-maltoside , 1 mM DTT , 50 mM NaF ) overnight at 4°C . Samples were centrifuged at 14000 rpm for 5 min , 15 µl of the supernatant was loaded onto an isoelectrofocusing gel ( pH range 3–8 ) on a Pharmacia FBE 300 flat bed apparatus , and focused for 2 h at 23W . Proteins were transferred to a nitrocellulose membrane by capillary action and incubated with GCAP2 pAb . Bands were visualized with the ECL system ( Pharmacia ) . The expression vector for the mutant bS201G/EF−GCAP2 was obtained by site-directed mutagenesis of the expression vector described above for bEF−GCAP2 based on the 4 . 4 kb version of the mouse opsin promoter . Site-directed mutagenesis was performed with the QuikChange II site-directed mutagenesis kit ( Agilent , Santa Clara , CA , USA ) using primers: bGCAP2_S201G_Fw: CTCAGCAGAGGCGGAAAGGTGCCATGTTC; bGCAP2_S201G_Rv: GAACATGGCACCTTTCCGCCTCTGCTGAG; Mutagenesis was confirmed by sequencing . Mice were electroporated at p0 according to reference [40] and processed at p28–30 . Briefly , 0 . 5 µl at a concentration of 6 µg/µl of DNA mix in PBS was injected into the subretinal space , by making use of a Nanojet microinjector and micromanipulator ( Drummond Scientific , Broomall , PA ) . The DNA mix consisted of the expression vector for the specific GCAP2 mutant ( bGCAP2 , bEF−GCAP2 or bS201G/EF−GCAP2 ) in circular form and a tracer plasmid ( pL_UG that expresses the green fluorescent protein ( GFP ) driven by the Ubiquitin C promoter , [60] ) also in circular form , at a mass ratio of 2∶1 . Electroporation was performed with a square-wave electroporator ( CUI21 , Nepagene , Japan ) by triggering 5 pulses of 80 V with a 50 ms duration and an interval time of 950 ms . Electroporated pups were raised under standard cyclic light conditions and sacrificed at p28–30 for immunofluorescence analysis . Briefly , eyes were fixed in 4% paraformaldehyde in PBS at pH 7 . 4 , embedded in acrylamide mix and frozen as described [34] . Retinal cryosections were obtained at 22 µm thickness . An antigen retrieval protocol was performed preceding the immunofluorescence studies: glass slides were incubated with proteinase K in PBS pH 7 . 4 ( 0 . 05 mg/ml ) for 2 min and heated at 70°C for 8 sec . Sections were incubated in blocking solution ( 1% BSA , 3% normal goat serum , 0 . 1% Triton X100 , PBS pH 7 . 4 ) ; primary antibody solution ( 1% BSA , 3% normal goat serum , PBS pH 7 . 4 containing 0 . 01 mg/ml polyclonal antibody to GCAP2 and 0 . 00025 mg/ml mAb 1D4 to rhodopsin ) ; and secondary antibody solution ( 1% BSA , 3% normal goat serum , PBS pH 7 . 4 containing Alexa Fluor 647 anti-rabbit IgG ( signal converted to red in figures ) ; and Alexa Fluor 555 anti-mouse IgG ( signal converted to blue in figures ) . Images were acquired in a Leica confocal microscope . GCAP2 and rhodopsin signal profiles were obtained for the individual cells shown by tracing a line along the inner segment compartment , and another line along the outer segment compartment , and plotting the summation of the red and the green signal along both lines from the collection of planes in a z-stack that covers the whole volume of the cell , by using the Leica confocal software ( Leica Microsystems ) . Three-month old C57Bl/6J mice were kept in a ventilated dark cabinet for 30 d , or kept under constant light exposure for the same time ( fluorescent light , 700 lux intensity inside the cage ) , and their eyecups were processed for immunofluorescence analysis . Retinal cryosections were stained with an anti-GCAP2 pAb and anti-rhodopsin mAb 1D4 , by indirect immunofluorescence staining with Alexa 488 goat anti-rabbit IgG and Alexa 555 goat anti-mouse IgG ( Molecular Probes , Eugene , Oregon ) . Z-axis stacks were obtained from four mice per condition at a Leica TCS-SL confocal microscope , and the percentage of GCAP2 signal colocalizing with the rhodopsin signal at the rod outer segment was quantified by ImageJ in three representative planes from each stack , one stack per mouse , four mice per condition . Precisely , for a 63×-objective frame of retina , an ROI was defined to include the inner and outer segment layers , while another ROI was delimited to the outer segment layer based on rhodopsin staining . GCAP2 signal was quantified in each ROI , and the percentage of GCAP2 colocalizing with rhodopsin was expressed as a function of GCAP2 at the inner and outer segment layers ( ImageJ ) . Mean values were obtained and statistical analysis performed with GraphPad Prism 6 . Electroretinogram responses to flash stimuli were recorded on a Nicolet Electrovisual Diagnostic System . Mice were dark-adapted for 12 h and then anesthetized under dim red light by intraperitoneal administration of Ketamine HCl ( 100 mg/kg ) and Xylazine HCl ( 10 mg/kg ) . Phenylephrine HCl ( 2 . 5% ) and Tropicamide ( 0 . 5% ) were applied to the cornea to dilate the pupils , and mice were dark-adapted again for 10 min previous to the recording . Following administration of Tetracaine HCl ( 0 . 5% ) eyedrops as a topical corneal anesthetic , the mice are placed on a heated pad at 37°C in a Faraday cage . The corneal electrode consisted of a carbon-fiber moistened in saline . A 1 ms light flash was delivered through a fiber optic centered vertically over a few millimeter of the corneal surface . Mice from the different genotypes were recorded over the course of eight months under identical conditions . | Visual perception is initiated at retinal photoreceptor cells , where light activates an enzymatic cascade that reduces free cGMP . As cGMP drops , cGMP-channels close and reduce the inward current –including Ca2+ influx– so that photoreceptors hyperpolarize and emit a signal . As the light extinguishes , cGMP levels are restored to reestablish sensitivity . cGMP synthesis relies on guanylate cyclase/guanylate cyclase activating protein ( RetGC/GCAP ) complexes . GCAPs link the rate of cGMP synthesis to intracellular Ca2+ levels , by switching between a Ca2+-free state that activates cGMP synthesis during light exposure , and a Ca2+-bound state that arrests cGMP synthesis in the dark . It is established that GCAP1 mutations linked to adCORD disrupt this tight Ca2+ control of the cGMP levels . We here show that a GCAP2 functional transition from the Ca2+-free to the Ca2+-loaded form is essential for photoreceptor cell integrity , by a non-related mechanism . We show that GCAP2 locked in its Ca2+-free form is retained by phosphorylation and 14-3-3 binding to the proximal rod compartments , causing severe cell damage . This study identifies a pathway by which a sustained reduction in intracellular free Ca2+ could result in photoreceptor damage , relevant for light damage and for those genetic disorders resulting in “equivalent-light” scenarios . | [
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"anima... | 2014 | Functional EF-Hands in Neuronal Calcium Sensor GCAP2 Determine Its Phosphorylation State and Subcellular Distribution In Vivo, and Are Essential for Photoreceptor Cell Integrity |
Persistence of hepatitis B virus ( HBV ) infection requires covalently closed circular ( ccc ) DNA formation and amplification , which can occur via intracellular recycling of the viral polymerase-linked relaxed circular ( rc ) DNA genomes present in virions . Here we reveal a fundamental difference between HBV and the related duck hepatitis B virus ( DHBV ) in the recycling mechanism . Direct comparison of HBV and DHBV cccDNA amplification in cross-species transfection experiments showed that , in the same human cell background , DHBV but not HBV rcDNA converts efficiently into cccDNA . By characterizing the distinct forms of HBV and DHBV rcDNA accumulating in the cells we find that nuclear import , complete versus partial release from the capsid and complete versus partial removal of the covalently bound polymerase contribute to limiting HBV cccDNA formation; particularly , we identify genome region-selectively opened nuclear capsids as a putative novel HBV uncoating intermediate . However , the presence in the nucleus of around 40% of completely uncoated rcDNA that lacks most if not all of the covalently bound protein strongly suggests a major block further downstream that operates in the HBV but not DHBV recycling pathway . In summary , our results uncover an unexpected contribution of the virus to cccDNA formation that might help to better understand the persistence of HBV infection . Moreover , efficient DHBV cccDNA formation in human hepatoma cells should greatly facilitate experimental identification , and possibly inhibition , of the human cell factors involved in the process .
Currently , more than 350 million people suffer from chronic HBV infection . Chronic hepatitis B frequently progresses to liver cirrhosis and hepatocellular carcinoma , a leading cause of cancer-related morbidity and mortality worldwide [1] , [2] . HBV is a small enveloped hepatotropic DNA virus which replicates by reverse transcription of an RNA intermediate , the pregenomic ( pg ) RNA ( for review: [3] , [4] ) , to yield encapsidated , partially double-stranded rcDNA to which the viral polymerase is covalently bound [5] . Upon infection , rcDNA is transported to the host cell nucleus where it is converted into cccDNA ( Figure S1 ) . Episomal cccDNA then acts as template for all viral transcripts . These include the subgenomic RNAs encoding the surface proteins , and the pgRNA that serves as mRNA for the polymerase protein and the capsid , or core , protein . Binding of polymerase to the RNA stem-loop structure ε initiates packaging of one pgRNA molecule per newly forming capsid and its reverse transcription . The first product is single-stranded ( ss ) DNA of minus polarity; due to the unique protein-priming mechanism , its 5′ end is , and remains , covalently linked to the polymerase . The pgRNA is concomitantly degraded , except for its 5′ terminal ∼15–18 nucleotides which serve as primer for plus-strand DNA synthesis , resulting in rcDNA and , as a side-product , some double-stranded linear ( dl ) DNA . DNA-containing capsids are then enveloped by surface proteins and cellular lipids and secreted as virions . Alternatively , they are redirected to the nucleus to increase cccDNA copy number by a mechanism termed intracellular recycling; many estimates for cccDNA copies per infected hepatocyte are in the range of 5 to 50 [6] . This amplification prevents loss during cell division of the cccDNA which can not be replicated semiconservatively [7] . Thus , cccDNA formation and recycling are central to establish and maintain persistent infection , and they limit the efficacy of antiviral nucleot ( s ) ides in the treatment of chronic hepatitis B , as these do not directly target cccDNA ( for review: [8] ) . However , despite its central importance the molecular pathway driving the conversion of HBV rcDNA to cccDNA is poorly understood . In vivo studies face numerous challenges . Liver biopsies from human patients are scarce , affected by the natural history of infection , and they sample only a small volume of the liver; recent estimates for cccDNA content in infected human liver vary from 0 . 01 to 1 . 4 [9] to 0 . 1 to 10 copies per hepatocyte [10] , with large patient-to-patient variation . Kinetic studies during acute infection , doable exclusively in chimpanzees , showed peak values of around 10 cccDNA copies per infected cell but much lower numbers before and after [11] . In well controllable experimental settings , on the other hand , such as transfected cell lines [12]–[14] or HBV-transgenic mice [15] , [16] , HBV produces little if any cccDNA . DHBV is a related animal virus that is widely used as a model to study HBV infection [17] . Like HBV , DHBV produces cccDNA in cultured duck hepatocytes and in vivo [7] , [18] , with reported mean values of 2 . 9 to 8 . 6 copies per hepatocyte [19] though also with temporal and cell-to-cell fluctuations ( from one to >36 copies per cell ) . Importantly , DHBV transfected into the chicken hepatoma line LMH also generates well detectable amounts of cccDNA . Initially in primary duck hepatocytes , then using that system , Summers and colleagues had first shown that knocking out surface protein expression , and thus virion secretion , dramatically increased cccDNA copy numbers per nucleus to about 200–400 molecules [20] , [21] . Recent studies in stably or transiently transfected human cell lines suggest that preventing HBV surface protein expression also stimulates cccDNA formation , but to a much lower degree; instead , a “protein-free” form of rcDNA ( pf-rcDNA ) accumulated [12] , [13] . The term protein-free ( which we will adhere to here ) was operationally defined by the partitioning of this rcDNA form into the aqueous phase upon phenol extraction without prior proteinase K ( PK ) treatment ( which artificially degrades the protein ) ; polymerase-linked DNA partitions into the organic phase . “Protein-free” does therefore not imply the complete absence of any amino acid from the DNA . Though not finally proven , several lines of indirect evidence suggest that pf-rcDNA is a precursor to cccDNA [12] , [13]; not the least , removal of the bound polymerase is a sine qua non for cccDNA formation . Caveats are that nicked cccDNA , generated to some extent during preparation and naturally protein-free , has the same electrophoretic mobility as pf-rcDNA . Furthermore , Southern blots from infected liver nuclei have generally shown only little rcDNA versus cccDNA [22] . However , in such samples one usually looks at an established pool of cccDNA whereas the recent cell culture studies monitored initial cccDNA formation . Potential precursors accumulating under these conditions may not be detectable anymore in in vivo samples . At any rate , the initial presence of protein-bound rcDNA inside virions and eventually of nuclear cccDNA , associated with histones [23] , requires as intermediate steps nuclear transport of the rcDNA genome , its release from the viral capsid and removal of the bound polymerase to allow generation of precisely one genome length equivalents of the plus- and the minus-strand before final ligation into cccDNA ( Figure S1B ) . The order of events is not firmly established . Intact nucleocapsids may deliver the protein-bound rcDNA to the nucleus where its release from the capsid and polymerase removal are mediated by host factors; this view is supported by the minimalistic genomes of hepadnaviruses ( only ∼3 kb ) and by data from nuclear transport model systems [24] , [25] . Alternatively , the nucleocapsid itself may contain corresponding activities such that polymerase removal could precede capsid release , possibly already in the cytoplasm . Some evidence in favor of this view has recently been forwarded [13] , [26] . Apart from these mechanistic aspects it appears , in essence , that DHBV in the avian LMH cells produces much more cccDNA than HBV in human hepatoma cells . One conceivable explanation are cell-specific differences . For instance , the routinely used human HepG2 and Huh7 hepatoma cell lines may lack enzymatic activities required for cccDNA formation that are present in the avian cells . Alternatively , the different efficiencies in cccDNA formation may be a feature of the respective viruses . In order to address this question we took advantage of the principal ability of hepadnaviruses to replicate in hepatoma cell lines of heterologous species origin . After transfection HBV is capable of producing rcDNA in LMH cells and the same holds for DHBV in HepG2 and HuH7 cells [27] , [28] . However , cccDNA formation in such cross-species transfections has not yet been addressed . Here we performed such experiments and found that , unexpectedly , the major contribution to cccDNA formation comes from the virus rather than from the cell .
Detection of cccDNA by Southern blotting can severely be hampered by the presence of ssDNA species which have a similar electrophoretic mobility and are often present in excess . A further problem in transient transfections is the highly abundant plasmid DNA . We therefore developed an assay that essentially eliminates ssDNA and plasmid DNA by double-digestion with the restriction enzyme Dpn I and Plasmid safe DNase ( PsD ) . Dpn I requires bacterially methylated DNA to be active and selectively restricts the transfected plasmid . PsD digests single-stranded ( ss ) and double-stranded linear ( dl ) but not circular molecules such as cccDNA . Although it has been surmised that rcDNA is a substrate for PsD [9] , our own preliminary data suggested this holds only for very immature rcDNA forms . To enhance cccDNA production , we used plasmids coding for surface-deficient HBV and DHBV . Because cccDNA is enriched in the nucleus , we separated nuclei from cytoplasm by treating the cells with the mild detergent NP-40 and subsequent centrifugation . To identify encapsidated DNAs , we incubated the cytoplasmic extracts with micrococcal nuclease ( MN ) which digests free nucleic acids but not those protected inside capsids . Finally , because protein-bound DNA is neither recovered upon phenol extraction nor using the silica column adsorption ( QIAamp ) method employed here , all initial DNA preparations included a PK treatment . The results for DHBV in LMH and HBV in HepG2 cells are shown in Figure 1 . Treatment of the cytoplasmic samples with MN revealed the common replicative intermediates , i . e . rcDNA , dlDNA and ssDNA . Digestion with Dpn I only produced a similar pattern , except that additional plasmid-derived bands ( Pla ) were visible . Nuclear DNA treated with Dpn I alone produced a similar pattern , yet as expected , knock-out of surface protein expression enhanced the cccDNA signal , particularly for DHBV . Additional treatment of nuclear DNA with PsD removed all bands except those at the rcDNA and cccDNA positions; the equal signal intensities before and after PsD treatment demonstrated that mature rcDNA was not appreciably attacked by PsD . For HBV , a band at the cccDNA position was exclusively visible in the surface-deficient background ( Figure 1B ) . However , the nuclear rcDNA signal was much more enhanced , in line with recent reports [12] , [13] . Comparable results were obtained in Huh7 cells ( Figure S2A ) . Together , these data demonstrated that the applied procedure enabled the reliable detection of cccDNA and rcDNA , without interference from other virus- or plasmid-derived nucleic acids . Furthermore , they confirmed that DHBV in avian cells produces much more cccDNA than HBV in human cells . Faint bands with cccDNA-like mobility were also detectable in the cytoplasmic fractions of those samples containing well visible nuclear cccDNA; ethidium bromide staining of the agarose gel used to generate the blot revealed indeed some chromosomal DNA in the cytoplasmic samples , indicating an incomplete separation of two fractions . This prompted us to employ a more efficient separation procedure in later experiments ( see below ) . Next we performed analogous experiments with DHBV transfected into the human cell lines , and HBV transfected into LMH cells ( Figure 2 ) . For DHBV , cytoplasmic extracts treated with MN produced a similar pattern of replicative intermediates in HepG2 ( Figure 2A ) and HuH7 cells ( Figure S2B ) as in LMH cells ( Figure 1A ) . HBV in LMH cells , compared to the human cell lines , generated a more complex pattern with a distinct band of an intermediate mobility between rcDNA and ssDNA ( Figure 2B ) . This additional band originates from strongly enhanced splicing of the HBV pgRNA in the chicken cell line ( Köck , Nassal , Thoma; unpublished data ) . The spliced genomes are of linear conformation and therefore accessible to PsD digestion . Most importantly for the current study , the envelope-deficient DHBV produced a strong cccDNA signal in both human cell lines ( Figure 2A and Figure S2B ) , with an intensity equaling that of the nuclear rcDNA as in LMH cells . Conversely , HBV in LMH cells generated a similar pattern as in the human cell lines , with a relatively strong band at the rcDNA yet only a weak band at the cccDNA position ( Figure 2B ) . The HBV specific lack of effect of the envelope knock-out in LMH cells correlated with a much lower abundance of the surface protein-coding mRNAs compared to the human cells ( data not shown ) . Thus wild-type HBV in LMH cells is phenotypically similar to its envelope-deficient counterpart . Together , these data demonstrated that both HepG2 and HuH7 cells are competent to support cccDNA synthesis , yet with strikingly higher efficiency for DHBV than HBV; conversely , LMH cells did not support more efficient cccDNA formation for HBV . These results were reproduced in about twenty independent experiments . Furthermore , this virus-specific difference was neither changed by increasing pgRNA levels via replacement of the HBV core promoter by the CMV promoter , nor by analyzing the cultures at earlier or later time points post transfection ( Figure S3 ) . Thus the virus contributes more profoundly to the efficiency of cccDNA biosynthesis than the cell . More quantitative data on the amounts and intracellular distribution of the different viral DNA were obtained with samples from gradient purified nuclei . Beyond the markedly different levels of cccDNA , the data shown above also revealed distinct levels of nuclear rcDNA , and of the ratios of cccDNA to rcDNA , between DHBV and HBV . A detailed characterization of the nuclear rcDNA was expected to provide clues on the rate-limiting step of HBV cccDNA synthesis . This , however , required the nuclear preparations to be as free from cytoplasmic contamination as possible . We therefore separated the nuclei from the cytoplasm by sucrose density sedimentation [29] . Western blot analyses of nuclear extracts versus total cell lysates showed that , while nuclear histone H3 was detected in either fraction , the cytoplasmic poly ( A ) binding protein ( PABP ) was exclusively present in total cell lysates but not in nuclear extracts ( Figure S4A ) . Co-purification of cytoplasmic capsids with the nuclei was ruled out by the absence of viral DNAs from purified nuclei of non-transfected HepG2 cells that had been mixed with capsid-containing cytoplasmic fractions from HBV- or DHBV-transfected cells and subjected to the same procedure ( Figure S4B ) . Permeability of the nuclei for exogenously added MN , an assay subsequently used to address nuclease sensitivity vs . resistance of the nuclear viral DNAs , was confirmed by dose-dependent generation of chromosomal DNA fragments with sizes of multiples of ∼150 bp , as expected from cleavage between nucleosomes ( Figure S4C ) . Applying this methodology to HepG2 cells transfected with surface-deficient HBV or DHBV constructs revealed that the purified nuclei contained easily detectable signals at the rcDNA position , and for DHBV a strong and for HBV a weak signal at the cccDNA position; as expected , both converged into a single species with dlDNA mobility upon digestion with Eco RI , and heating converted the rcDNA but not the cccDNA signal into a new band with ssDNA mobility ( Figure S5A ) . However , this assay does not discriminate true rcDNA from randomly nicked cccDNA . For distinction , we exploited the defined discontinuities at the 5′ ends of the complete minus-strand and the 3′ terminally incomplete plus-strand DNA ( Figure 3A ) in rcDNA and the requirement of most restriction enzymes for a double-stranded substrate structure . The nuclear , and for comparison also the cytoplasmic , HBV DNA preparations were incubated with Nco I whose recognition site ( CCATGG; nt positions 2654–2659 ) is in the 3′ proximal part of the plus-strand but largely double-stranded already in virion DNA ( e . g . [30] ) ; Fsp I ( TGCGCA; nt positions 3082–3087 ) , recognizing a site in the 5′ proximal plus-strand region that is double-stranded even in DNA with very short plus-strands; and Apa LI ( nt positions 2861–2866 ) , with its recognition site ( GTGCAC ) ending only 5 nt upstream of DR2 ( nt positions 2872–2882 ) where the plus-strand begins . Nicked cccDNA should be linearized by all three enzymes whereas true rcDNA , depending on how far the plus-strand is filled-in , is expected to be partially or completely resistant to Apa LI cleavage . Exactly this was observed , with about 35% of the rcDNA remaining in the Apa LI but not the Nco I and Fsp I treated samples from both the cytoplasm and the nucleus; very similar results were obtained in repeat experiments ( 42 . 2±10 . 7% for the nuclear and 40 . 0±2% for the cytoplasmic rcDNA ) , as well as for protein-free nuclear rcDNA ( 32 . 0±4 . 9%; Figure S5B ) . The differences between different treatments were highly significant ( P<0 . 05 to <0 . 001 ) but those between cytoplasmic vs . nuclear rcDNA were not . Activity of Apa LI in the reactions was demonstrated by the disappearance of the Dpn I fragment from the transfected plasmid DNA that harbors the single virus genome-encoded recognition sites for Apa LI and Fsp I but not Nco I . Furthermore , an admixed DHBV plasmid was completely cut by either enzyme ( Figure S5B ) . Hence , in accord with previous reports [12] , [13] , a substantial fraction of the nuclear HBV rcDNA signal was derived from true rcDNA , confirming that the weak cccDNA signal was not caused by excessive nicking . For a quantitative estimate of the proportion of nuclear versus cytoplasmic HBV and DHBV rcDNA , we compared the amounts of viral DNA in total cells ( nuclei plus cytoplasm ) and in gradient-purified nuclei; to account for all DNA species regardless of encapsidation and protein-linkage status , preparations involved PK treatment and subsequent digestion with Dpn I plus PsD , but not MN . Serial dilutions served to improve the accuracy of quantitation by phosphorimaging; one of three independent experiments used for quantitation is shown in Figure 4A . The signals from the four different amounts of total rcDNA ( 1% , 3% , 10% , and 30% of the whole preparation ) and from the 30% portions of nuclear rcDNA were quantitated and corrected for background by phosphorimaging . Accordingly , the ratios for total vs . nuclear rcDNA were 3 . 6±0 . 44 : 1 for DHBV , and 6 . 8±0 . 26 : 1 for HBV , i . e . about 25–30% of the DHBV and around 15% of the HBV rcDNA were nuclear . Using the known amounts of HBV and DHBV marker DNAs run on the same gels we also estimated the amounts per sample ( one well of a 6-well plate ) of total versus nuclear rcDNA and cccDNA , and the copy numbers per transfected cell ( see Text S1 for details ) ; accordingly , DHBV generated ∼160 pg ( 161 . 6±28 . 3; 200±35 copies ) total rcDNA of which ∼45 pg ( 44 . 8±4 . 5; 56±6 copies ) were nuclear , and HBV produced ∼130 pg ( 130 . 2±7 . 6; 162±10 copies ) total rcDNA of which ∼20 pg ( 19 . 2±1 . 1; 25±2 copies ) were nuclear . Amounts of cccDNA estimated analogously were ∼45 pg ( 42 . 3±3 . 3; 56±5 copies ) for DHBV , and ∼2 pg ( 2 . 1±0 . 9; 2 . 6±1 . 1 copies ) for HBV; cccDNA values for HBV were close to background and therefore difficult to determine more accurately . However , a similar excess of nuclear HBV rcDNA over cccDNA has also been reported for inducible cell lines stably transfected with surface-deficient HBV [12] , [13] . Together these data indicated that less efficient nuclear transport of HBV rcDNA contributes to , but cannot solely be responsible for , the much less efficient cccDNA accumulation . To further investigate the status of the viral DNAs , we treated total lysates and purified nuclei with MN followed by PK , leaving only encapsidated ( or otherwise protected ) DNA species intact . For DHBV , the results were essentially the same ( Figure S6 , panel DHBV ) as those after Dpn I plus PsD treatment ( Figure 4A ) but for HBV the signal at the full-length rcDNA position had nearly disappeared , apparently in favor of faster migrating species ( Figure S6 , panel HBV ) . For a direct estimate of the fraction of MN sensitive nuclear DNA species , viral DNA was isolated from equally sized aliquots of the nuclei by either the Dpn I plus PsD or the MN procedure and analyzed side-by-side ( Figure 4B ) . For DHBV the total amounts of rcDNA obtained in either way were very similar , indicating that most of the nuclear DHBV DNA was present in largely intact nucleocapsids ( as confirmed by anti-capsid immunoprecipitation; see below ) . The nonetheless strong cccDNA signal suggested that once released from the capsid , DHBV rcDNA gets rapidly converted into cccDNA; alternatively , the stably encapsidated nuclear DHBV rcDNA might be a dead-end product . For HBV , in contrast , only the cytoplasmic rcDNA signal was largely resistant to MN whereas in the nuclear sample faster migrating species accumulated ( Figure 4B and Figure S6 ) ; quantitative comparison of the nuclear full-length rcDNA signals with versus without MN treatment from three independent transfections showed that only about 10% ( 11 . 1±6 . 3% ) of the full-length rcDNA was resistant . Hence different from DHBV , most of the nuclear HBV rcDNA was sensitive to MN and therefore no more protected by an intact capsid shell . The nuclease sensitivity of most of the nuclear HBV full-length rcDNA was compatible with its complete release from the capsid; the faster-migrating nuclease resistant species might then represent shorter DNAs that were still fully encapsidated . Alternatively , partial opening of the capsid could have exposed parts of , but not the entire full-length DNA to nuclease attack; finally , partial protection could also have arisen from association with factors other than core protein . We therefore assessed whether the nuclear viral DNAs could be immunoprecipitated by antibodies against the respective core proteins . Purely osmotic procedures released much less core protein from the gradient-purified nuclei than lysis with 0 . 5% SDS which , however , disintegrates capsids and prevents analysis of capsid-associated nucleic acids . Instead we treated the nuclei with 0 . 75× radioimmunoprecipitation ( RIPA ) buffer which destroys the nuclear envelope but leaves the viral nucleocapsids intact [31] . The cytoplasmic lysates serving as reference source for the immunoprecipitations ( IPs ) were likewise adjusted to 0 . 75× RIPA . As a specificity control , HBV samples were incubated with anti-DHBV core antibody and vice versa ( mock-IP ) . Next , DNAs associated with the immunopellets were isolated after prior PK treatment and analyzed by Southern blotting . For DHBV ( Figure 5A ) , the immunoprecipitated DNA from both the cytoplasm and the nuclei , if treated with only Dpn I , generated a similar pattern as that obtained by direct incubation of the extracts with MN ( lanes ø ) , except it contained some fragmented plasmid DNA; this was found in similar amounts in the mock-IP and represented at most 50 pg , i . e . a tiny fraction of the transfected plasmid DNA . MN treatment of the immunopellets completely removed the residual plasmid DNA , as well as a faint band at the cccDNA position seen only in the nuclear immmunopellets , but left most of the viral rcDNA and dlDNA intact . Hence the non-ccc forms of DHBV DNA in the cytoplasm and nucleus behaved alike: both were immunoprecipitable with anti-DHBV core antibody and both were largely protected from nuclease , consistent with their being stably encapsidated in either compartment . For HBV ( Figure 5B ) , the picture in the cytoplasmic samples was similar; the anti-HBV core antibody precipitated the same type of DNAs as obtained by direct MN treatment; residual plasmid DNA was completely removed by MN . The nuclear immunopellet , if treated with Dpn I only , generated a similar pattern as that from the cytoplasm; hence at least part of the nuclear full-length rcDNA was still core protein-associated . However , like direct incubation of the nuclei with MN ( Figure 4B ) , MN treatment strongly reduced the full-length rcDNA signal whereas faster migrating DNA species accumulated , suggesting their resistance was indeed due to protection by the capsid . Comparable results were obtained in Huh7 ( Figure 5B , left panel ) and in HepG2 cells ( Figure 5B , right panel; cytoplasmic samples of this experiment are shown in Figure S7 ) . Together these data indicated that at least a fraction of the nuclear HBV DNA including full-length species was still associated with core protein but , different from DHBV , was no more fully protected . The majority of MN resistant nuclear HBV DNAs migrated reproducibly to a region whose upper boundary would correspond to dlDNA of ∼2 . 4–2 . 7 kb ( Figure 4B ) . One explanation was that these molecules represented naturally shorter DNA derived from spliced pgRNA [32] , [33] which remained protected in intact nucleocapsids . However , a construct encoding a variant HBV genome in which the major splice acceptor site was mutated generated exactly the same pattern of MN resistant nuclear DNA although splicing was indeed suppressed ( data not shown ) . Next we incubated the MN resistant nuclear , and for comparison also cytoplasmic , HBV DNA with restriction enzymes Nco I and Spe I which cut the HBV genome uniquely at positions 2654 and 1961 ( Figure 6A , C ) . Expectedly , the major effect on the cytoplasmic DNA was conversion of the rcDNA to dlDNA , plus generation of small amounts of fragments that most likely derived from dlDNA; ssDNA was not affected . In the nuclear sample , the little full-length rcDNA was linearized as well . The major faster migrating species disappeared completely upon exposure to either enzyme , indicating they contained both recognition sites in double-stranded form . Intriguingly , within the background smear distinct fragments of about 2 . 2 kb ( Nco I ) and 1 . 2 kb ( Spe I ) appeared that were absent from the non-restricted sample , suggesting that MN had generated at least one relatively distinct new DNA end at a fixed distance from the restriction sites . One interpretation was that the MN products of rcDNA lacked about 500 bp roughly between position 3000 and 500 ( see map in Figure 6C ) ; in that case the second Nco I fragment would comprise only around 300 to 400 bp which , together with some heterogeneity in size , would make it difficult to detect . The 1 . 2 kb band in the Spe I treated sample , conversely , could consist of two about equally sized products . To corroborate this assumption , we digested the nuclear MN resistant DNAs with three more single cutter enzymes ( Figure 6B ) : Nsi I and Eco RI ( recognition sites starting at positions 2346 and 1280 , respectively ) , and Bsp EI ( recognition site starting at position 429 in the predicted lacking sequence part ) . As a further control , intact nuclear rcDNA was isolated by the Dpn I plus PsD procedure and digested with the same enzymes which in all cases led to complete linearization ( Figure 6B , left panel ) . In the MN treated nuclear DNA , the rcDNA signal likewise disappeared completely in favor of a new band at the dlDNA position . Importantly , however , Nsi I and Eco RI produced distinct new bands of about 1 . 9 kb ( marked by * ) , whereas for Bsp EI the pattern below the dlDNA position was not detectably different from that of the untreated sample ( lanes ø ) . These data are consistent with MN generating from nuclear HBV rcDNA a relatively distinct mixture of double-stranded linear DNAs that lack approximately the region between position 3000 and 500 ( Figure 6C ) . This , in turn , implies that capsid opening occurs at distinct sites relative to the packaged genome . Together , these data indicated that nuclear HBV genome release from the capsid is efficiently initiated; at most 10% of the full-length rcDNA remained resistant to MN . Furthermore , as shown below , we also found evidence for a fraction of nuclear rcDNA that is completely released from the core protein . Hence poor HBV rcDNA to cccDNA conversion is not caused by a complete block of uncoating dynamics . To test the polymerase linkage status of the different viral DNAs we prepared cytoplasmic extracts and purified nuclei from DHBV and HBV transfected HepG2 cells . Equal aliquots from each sample were then incubated in buffer containing SDS with or without PK , and subjected to conventional phenol extraction . Transfected plasmid DNAs were digested with Dpn I ( Figure 7A ) . Without PK , only very weak signals were seen for both HBV and DHBV in the cytoplasmic fractions ( <10% of the signals with PK ) , in line with a previous report [12] though not with an other [13]; evaluation of 15 independent HBV samples gave a mean value of 9 . 2±2 . 4% . In the nuclei of the DHBV transfected cells , PK treatment had , expectedly , little effect on cccDNA and the plasmid derived Dpn I fragments ( Figure 7A , left panel ) ; but strongly enhanced the rcDNA signal . For nuclear HBV rcDNA , in contrast , the signals obtained without PK were nearly as strong as those from the PK treated aliquot ( Figure 7A , right panel ) . For a semiquantitative estimate we compared the rcDNA signal intensities with versus without PK treatment from two independent experiments; to account for differencies in recovery , these values were normalized for the cccDNA signals ( DHBV ) and the plasmid fragments ( HBV ) , respectively , in the same lanes . Accordingly , the rcDNA signals from the PK treated samples were 3 . 78±0 . 54 fold stronger for DHBV , and 1 . 17±0 . 29 fold stronger for HBV , indicating that around 20% of the nuclear DHBV rcDNA and around 70% or more of the nuclear HBV rcDNA were protein-free . Comparing 11 different pairs of PK treated vs . non-treated nuclear HBV samples yielded a mean value of 66 . 9±13 . 3% protein-free rcDNA . That a major fraction of the rcDNA signals originated from true rcDNA was corroborated by subjecting nuclear HBV DNA obtained with or without prior PK treatment to digestion with Nco I , Apa LI , and FspI . As before ( Figure 3 ) , Nco I and Fsp I converted the PK treated rcDNA nearly completely into dlDNA , whereas about 40% of the rcDNA signal remained upon Apa LI digestion ( Figure S5B ) ; for the protein-free nuclear DNA the mean value was slightly lower ( 32±5% ) , suggesting it contained more completely filled-in plus-strand DNA . However , this difference was not statistically significant . We also assessed the polymerase linkage status of the MN resistant DNAs ( Figure 7B ) . The patterns generated upon prior PK treatment fully matched those previously seen ( Figure 4B , C , S6 ) whereas without PK treatment only faint signals were detectable . For DHBV , the nuclear and cytoplasmic DHBV DNAs were similar in composition and both were largely polymerase-linked . With , but not without PK treatment , nuclear HBV DNA showed the same accumulation of faster migrating species as before ( Figure 4B ) . Hence the MN resistant shorter HBV DNA species as well as the small amounts of resistant full-length rcDNA were mostly protein-linked . This suggested that the relatively high proportion of protein-free species in the total nuclear DNA ( Figure 7A ) was largely accounted for by MN sensitive rcDNA molecules . The IP experiments described above ( Figure 5B ) indicated an association of at least some of the nuclear HBV full-length rcDNA with core protein . Hence failure to completely uncoat the DNA could represent a rate-limiting step in cccDNA formation . We therefore assessed whether the nuclei also contained rcDNA molecules that were no more associated with core protein . To this end , we performed IPs as before yet this time we included the IP supernatants in the analysis . Furthermore , we addressed the polymerase linkage status of such putative species by treating one half of each sample with PK , the other not . Cytoplasmic samples in which the viral DNA is largely present in intact capsids ( Figure 5 ) served as control . Because MN would destroy nonprotected rcDNA , we used Dpn I plus PsD to reduce the background of non-rcDNAs . The specific IP from the cytoplasm generated a strong rcDNA signal in the immunopellet after PK treatment; the signal from the supernatant was only 3–4% as intense ( Figure 8 , lane 2 vs . 4 ) . Conversely , the signal from the mock IP pellet had less than 3% the intensity of that from the supernatant ( lane 6 vs . 8 ) . These data confirmed that the IP was specific and that the amount of anti-HBc antibody was sufficient to precipitate ≥95% of the cytoplasmic rcDNA . The strongly reduced signals without PK treatment further corroborated that 90% or more of the cytoplasmic rcDNA was protein-linked . A different picture was seen in the nuclear samples . The anti-HBc supernatant contained more rcDNA than the immunopellet ( lane 11 vs . 13 ) ; quantification indicated that only about 30% of the rcDNA was precipitated ( 29 . 8±3 . 5% for the PK treated , 34 . 2±3 . 2% for the not treated sample; from duplicate determinations of two independent experiments ) . For the mock IP , only 5 . 0±3 . 9% were found in the pellet ( lane 15 vs . 17 ) . In further contrast to the cytoplasmic samples , yet in line with the previous data ( Figure 7A ) , omitting the PK treatment only modestly reduced the signal intensities in all nuclear samples ( lanes 11 vs . 12; 13 vs . 14; 17 vs . 18 ) , i . e . to 73±16% in the specific immunopellet , to 69±9% in the supernatant , and to 55±7% in the mock IP supernatant . Although the low overall signal intensities precluded a more accurate determination , these data indicated that around two thirds of the nuclear HBV rcDNA were not stably associated with core protein , i . e . probably completely uncoated , and around two thirds of these molecules were no more linked to intact polymerase protein . The data described above were compatible with at least partial release of the nuclear HBV rcDNA from the capsid , allowing cell factors to engage in polymerase removal . A recently proposed alternative is that polymerase removal might precede capsid opening , possibly already in the cytoplasm and mediated by capsid-intrinsic activities [26] . One line of evidence in favor of this proposal was the reported generation of small amounts of protein-free DNA in detergent-stripped DHB virions subjected to prolonged endogenous polymerase reaction ( EPR ) conditions; no results for HB virions were reported . In the EPR , exogenously added dNTPs are utilized by the capsid-borne ( “endogenous” ) polymerase to complete the plus-strand DNA . Because serum virions are secreted from infected hepatocytes , there is very little risk of cross-contamination with nuclear or other cellular factors . Here we performed analogous experiments with HB virions , and for comparison with the published results [26] also with DHB virions . Nucleocapsids of either virus were obtained from highly viremic sera by sedimentation in Nycodenz gradients containing NP-40 detergent . DHBV nucleocapsids were exposed to EPR conditions for 16 h [26] , and the capsid-borne DNAs were isolated via phenol extraction with or without prior PK treatment . The corresponding Southern blot showed ample rcDNA and some dlDNA in the PK treated but not the untreated sample ( Figure 9A , left panel ) , confirming that most of the virion-borne genomes are covalently linked to polymerase . In line with the reported data , a long exposure plus contrast enhancement ( Figure 9A , right panel ) revealed indeed a faint band of apparently protein-free DNA , however exclusively at the dlDNA , not the rcDNA position . By comparison with the dilution series of the PK treated sample , the protein-free dlDNA accounted for less than 0 . 3% of the total capsid-borne virus DNA . Analysis of the HB virion-derived nucleocapsids after PK treatment but prior to the EPR ( Figure 9B ) showed a smear of bands that migrated faster than mature rcDNA from transfected HepG2 cells , indicating a relatively large gap in the HB virion plus-strand DNA; no signal was visible without PK treatment ( Figure 9B ) . When subjected to EPR ( Figure 9C , lanes +dNTP ) under the same conditions as used for DHBV , these species were efficiently converted into rcDNA plus some dlDNA , confirming enzymatic activity of the capsid-borne polymerase . The signal was largely stable towards MN , indicating the vast majority of viral genomes remained protected by the capsid shell . Without PK treatment , no signal was visible , not even upon overexposure ( Figure 9C , right panel ) . Thus if plus-strand completion per se caused any release from the capsid or removal of polymerase from viral DNA , its extent for HBV was even less pronounced than for DHBV . That , in contrast , in the nuclei of the transfected cells most of the HBV rcDNA was sensitive to MN and protein-free ( Figure 4 , 5 ) strongly supports that HBV capsid opening and deproteinization of rcDNA depend largely on the nuclear environment .
The conclusion of efficient DHBV but poor HBV rcDNA to cccDNA conversion is based on the relative intensities of Southern blot signals at the rcDNA and cccDNA positions in nuclear preparations; a ratio of about 1∶1 for DHBV but 10–20∶1 for HBV was observed in more than 20 independent preparations . The selective partial resistance against Apa LI digestion of nuclear HBV rcDNA ( Figure 3 , Figure S5 ) strongly suggests that excessive nicking of HBV ( but not DHBV ) cccDNA is not a major cause for the strong rcDNA versus weak cccDNA signals , consistent with data from stably transfected cells [12] , [13] . Another explanation would be that cccDNA of HBV has a much shorter half-life than that of DHBV . The in vivo half-life of cccDNA may be in the order of weeks to months [11] , [34] , [35] but the rates of synthesis versus degradation are subject to numerous factors , including cell division and immune responses . Closest to our setting are values derived from inducible cell lines in which rcDNA resynthesis was blocked by nucleoside analogs , with estimates of >48 h for DHBV [36] and >10 to 24 d for HBV [37] . Both values are long compared to the time frame of our experiments and , if anything , HBV cccDNA seems to be more stable than DHBV cccDNA . Hence it appears justified to assume that the weak HBV cccDNA signals truly reflect a slow rcDNA to cccDNA conversion rate . Formation of cccDNA must involve nuclear transport of the rcDNA , its release from the capsid and removal of the bound polymerase to allow for the subsequent generation of precisely unit-length plus-strand and minus-strand DNA and ligation of their ends . Regarding transport , the fraction of nuclear versus total rcDNA was about 2-fold higher for DHBV than for HBV ( Figure 4 ) ; assuming that one cccDNA molecule originates from one imported rcDNA molecule , and given the about equal amounts of both species in DHBV transfected nuclei ( Figure 2 , 4 ) this ratio increases to 4∶1 . Hence a lower import efficiency of HBV rcDNA can explain only part of the lower cccDNA accumulation . Irrespective of mechanistic details ( see below ) , the imported rcDNA molecules must eventually be released from the capsid to become accessible for the late repair steps in cccDNA formation . Nearly all of the nuclear , yet little of the cytoplasmic , full-length HBV rcDNA was sensitive to MN ( Figure 4 , 5 , 6 ) , and thus no more protected by an intact capsid shell; hence initiation of uncoating was highly efficient . Curiously though , MN treatment did not induce complete rcDNA degradation; instead , species with intermediate electrophoretic mobility accumulated , suggesting the existence of a distinct uncoating intermediate ( see below ) . Nuclear DHBV rcDNA , in contrast , was as resistant against MN as cytoplasmic rcDNA , implying genome release for DHBV but not for HBV as potentially overall rate-limiting in cccDNA formation . Nuclear ( save cccDNA ) and cytoplasmic DNAs of both viruses occurred in core protein associated form ( Figure 5 ) . DNA of either virus immunoprecipitated from the cytoplasm was largely resistent against MN , consistent with stable encapsidation . For DHBV , this also held for the nuclear immunopellet whereas drastic differences between cytoplasmic and nuclear fractions were revealed for HBV . The anti-HBc antibody ( a monoclonal antibody recognizing a linear epitope exposed on intact capsids yet also on denatured core protein; [38] ) precipitated full-length rcDNA from either fraction , yet selectively the nuclear full-length rcDNA was highly sensitive to MN , though not over its entire length . Hence a fraction of the HBV rcDNA in the nucleus was still associated with core protein and this association was likely responsible for partial nuclease protection . Together , these data indicate that the HBV nucleocapsid structure is drastically altered upon nuclear import such that the packaged rcDNA is at least partially exposed; the surprisingly distinct nature of the resulting rcDNA - core protein complexes is discussed below . Failure of all nuclear HBV rcDNA molecules to be completely released from core protein could have represented the major rate-limiting step in cccDNA formation . However , about two thirds of the nuclear full-length rcDNA could not be immunoprecipitated ( Figure 9 ) although the same amount of antibody precipitated ≥95% of the much more abundant cytoplasmic rcDNA . Hence partial as opposed to complete capsid release contributes to poor HBV rcDNA to cccDNA conversion . Cytoplasmic DNA of either virus not treated with PK generated signals that were less than 10% as intense as those obtained after artificial deproteinization ( Figure 7 , 8 , S5 , S7 ) ; even lower values were reported by Gao and Hu [12] . We can not exclude that these apparently protein-free DNAs are present in genuinely cytoplasmic nucleocapsids [26] but they could as well arise from molecules that during work-up have been subject to fortuitous proteolysis or leakage from ruptured nuclei , as supported by the inability of virion-derived nucleocapsids to generate any significant amount of protein-free rcDNA ( see below ) . Very obvious was , in contrast , the high proportion of protein-free HBV rcDNA in the purified nuclei . Consistently about two thirds were recovered without PK treatment from various samples ( Figure 7 , 8 , S5 ) . The low abundance of nuclear HBV rcDNA prevented detection of significant differences in the polymerase-linkage status of core protein associated versus free rcDNA . We therefore currently assume that a similar proportion of rcDNA molecules lacking intact polymerase is present in either fraction ( Figure 10B ) . Even then , about 40% of the nuclear rcDNA were both “protein-free” and completely released from the capsid . If the individual nuclear species are true precursors of one another , a major block in HBV cccDNA formation must occur further downstream . Given the operational definition of “protein-free” , this could involve removal of amino acid remnants from the polymerase from the minus-strand 5′ end , yet also ( a ) subsequent step ( s ) . Defining the chemical nature of the DNA ends in the protein-free species therefore remains a major objective . For DHBV , the simple model outlined as pathway b ( Figure 10A ) may be valid; however , the stable encapsidation and low degree of deproteinization ( ∼20% ) of the nuclear rcDNA ( Figure 4B , 5 , 7 ) versus high cccDNA content are also compatible with the existence of two kinds of capsids; one from which rcDNA is rapidly released and efficiently converted into cccDNA such that no stable intermediates accumulate ( Figure 10A , pathway b ) , and another in which uncoating is blocked or slowed down , represented by the nuclease resistant rcDNA ( Figure 10A , pathway a ) . Kinetic studies will be required for a distinction . Remarkably though , already 1990 Summers and coworkers [20] observed an accumulation of apparently protein-free rcDNA in primary duck hepatocytes infected with pseudotyped surface protein-deficient DHBV and suspected this might represent an immediate precursor to cccDNA . The exact nature of the partially nuclease resistant HBV rcDNA - core protein complexes in the nucleus is not yet clear; the status of the core protein may further be probed using assembly status dependent antibodies ( for review: [39] ) . Conversely , however , our characterization of the DNA in these complexes revealed several unexpected aspects . First , although MN has non-sequence specific endo- and exonuclease activity , MN treatment generated a reproducible pattern ( Figure 4 , 7 ) of faster migrating DNAs , with a sharp upper boundary at a position where double-stranded DNA of about 2 . 7 kb would migrate . These species did not represent stably encapsidated , splicing-derived shorter DNAs [32] , [33] , [40] but rather double-stranded linear molecules lacking ∼500 bp of viral genome sequence . Most surprisingly , digestion with four different restriction enzymes produced distinct fragments which is only compatible with MN digestion of a defined genome region relative to these restriction sites; accordingly , the MN sensitive region is roughly bordered by the start of the minus-strand DNA and the end of the core protein ORF ( Figure 6 ) . Indeed , the fifth restriction enzyme , Bsp EI , whose single recognition site locates to this region , did not detectably alter mobility of the MN treated DNA although it completely linearized rcDNA . These data strongly suggest that nuclear disassembly of the HBV nucleocapsid shell initiates at specific sites defined by their relative position to the packaged genome , and that these partially opened nucleocapsids may represent a novel , transiently stable uncoating intermediate . Conceivable mechanisms for polymerase removal include nucleolytic cleavage of a piece of rcDNA which carries the protein , or specific cleavage of the Tyr-DNA-phosphodiester linkage; both mechanisms , possibly coupled to proteolysis , have been described for repair of cellular protein-DNA adducts [41]; our unpublished data ( C . Königer , M . Nassal , J . Beck ) indicate that certain Tyrosyl-DNA phosphodiesterases are indeed able to specifically cleave the polymerase from the DNA in vitro . An alternative model proposes that nucleocapsids themselves harbor an intrinsic ability for polymerase removal , perhaps via capsid-associated cellular factors , such that deproteinization as well as partial capsid opening precede nuclear import [13] , [26] . Evidences were the reported presence of substantial amounts of protein-free and partially nuclease sensitive rcDNA in the cytoplasm , and the formation of small amounts of protein-free DNA in DHBV nucleocapsids derived from serum virions upon prolonged EPR conditions . Our results do not support this view . First , in line with results from others [12] we found only a small fraction of the cytoplasmic ( but most of the nuclear ) HBV rcDNA in protein-free form . Second , in our hands the cytoplasmic HBV rcDNA was largely nuclease resistant , whereas most of the nuclear rcDNA was nuclease sensitive ( Figure 4 , 5 ) . Third , we were unable to detect protein-free rcDNA in serum-derived HBV nucleocapsids upon prolonged EPR although the endogenous polymerase was clearly active ( Figure 9 ) . For DHBV , the same conditions led indeed to small amounts of protein-free DNA , as reported [26] . However , protein removal was extremely inefficient ( <0 . 3% ) , and it concerned exclusively dlDNA , not rcDNA ( Figure 9 ) ; notably , this was also observed by the authors when they analyzed cytoplasmic rather than virion-derived nucleocapsids [26] . While dlDNA can be circularized by nonhomologous end joining [42] , most of the resulting molecules carry insertions or deletions , preventing generation of functional progeny virus . Thus capsid-autonomous deproteinization of dlDNA may exist but does not appear to reflect a major pathway in cccDNA synthesis . The exclusive presence and strong enrichment , respectivley , of partially nuclease sensitive and protein-free HBV rcDNA in the nucleus in our experiments ( Figure 4 , 5 ) strongly favors that uncoating and polymerase removal are dependent on nuclear import . Furthermore , the polymerase linkage of the core protein associated MN products ( Figure 7 ) yet overall large fraction of protein-free rcDNA in the nucleus ( Figure 7 , 8 ) suggests that uncoating precedes polymerase removal . Altogether , our data are much more compatible with a nuclear import-dependent , cell factor-mediated generation of protein-free rcDNA ( Figure 10 ) than with a capsid-autonomous process in the cytoplasm . This would be in line with nuclear important-mediated alterations in capsid properties seen in digitonin-permeabilized cells [25] . Moreover , continued inhibition of viral polymerase activity during HBV infection of primary tupaia hepatocytes [30] and of HepaRG cells [43] , the as yet only HBV-infectable human cell line [44] , did not prevent cccDNA formation , further supporting a dominant role for cellular factors . The reasons for the partially discordant results are not obvious; cell type or cell clone specific differences are not excluded . However , while we were able to prepare nuclei essentially free from cytoplasmic contaminants , the reverse was not true . A more substantial nuclear contamination of the cytoplasmic fractions employed by Guo et al . would as well account for many of the seeming discrepancies . The efficient formation of DHBV cccDNA in HepG2 and Huh7 cells demonstrates that also in these cells the underlying pathways are principally operating; this may also hold for human cells of non-hepatic origin , as discussed in a previous publication [12] . Given the similar structures of HBV and DHBV rcDNA it is not obvious as to why conversion into cccDNA would be so much more efficient for DHBV . One option was that the plus-strand DNA in HBV capsids is less extended in comparison to DHBV capsids; however , HBV rcDNA in transfection-derived capsids from HepG2 cells was as mature as DHBV rcDNA ( Figure 9 ) . Another option is that the cellular repair activities operate in a sequence-specific manner because the two viruses share less than 40% sequence identity on the genome level [45] . Such sequence-dependence remains to be explored . Perhaps most conceivable is that viral proteins differentially affect cccDNA formation rates , either directly or in concert with cellular factors . Absence of the surface proteins favored nuclear import for both viruses , yet with accumulation of cccDNA for DHBV , and of rcDNA for HBV . Hence more complex consequences of surface protein - core protein interactions , or an effect of the surface proteins on cellular events affecting cccDNA formation are not excluded . Nuclear import of rcDNA is mediated by the viral core proteins [24]; although the DHBV genome is even smaller than that of HBV its core protein is much larger , including a surface-exposed domain of unknown function and a differently organized C terminal nucleic acid binding domain [46] . Obviously , the rates of nuclear transport and the fates of the intranuclear capsids differed between the two viruses . Even after uncoating and polymerase removal , both proteins , or fragments thereof , in the nucleus could affect further rcDNA processing . Phosphorylation - dephosphorylation events in the core protein nucleic acid binding domains are important during replication of both viruses [33] , [47] , [48] but potentially differing consequences for cccDNA have not yet been addressed . Not the least , mammalian but not avian hepatitis B viruses encode an additional gene product , HBx , whose function is still elusive [49]; however , the ortholog from woodchuck hepatitis virus ( WHV ) appears to be crucial for in vivo infection in the natural host [50] , [51] . If HBx was involved in cccDNA formation , its improper expression or functioning in the human hepatoma cells might limit HBV cccDNA formation . In a preliminary attempt to reveal potential regulatory activities of gene products from one virus on cccDNA production by the other we co-transfected HepG2 cells with the surface-deficient variants of both viruses . HBV had little effect on nuclear DHBV rcDNA and cccDNA formation; vice versa , HBV replication appeared slightly reduced overall , with no enhancement of cccDNA accumulation . In view of the multiple options for positive and negative regulation this may not be too surprising . A more revealing approach will therefore be coexpression of one virus with defined individual gene products from the other . Our study identified several steps downstream of initiation of nuclear uncoating that slow down ( but do not completely prevent ) HBV rcDNA to cccDNA conversion in human hepatoma cell lines . Because the same cells supported DHBV cccDNA formation very well , they can not completely lack the necessary molecular means . One option for the seeming discrepancy to efficient cccDNA formation during HBV infection in vivo is that cellular activities promoting the conversion are limited in these cell lines , another that inhibitory factors are overexpressed; this seems unlikely , though , because HBV cccDNA accumulation was not boosted in the avian LMH cells . Still another option is that rcDNA to cccDNA conversion is intrinsically slower for HBV than for DHBV . Determining cccDNA copy numbers in HBV infected human liver suffers from various experimental restrictions ( see Introduction ) . Hence more telling than the final yields of cccDNA molecules per hepatocyte may be a comparison of the rates of cccDNA accumulation in HBV versus DHBV infection . In experimentally HBV infected chimpanzees , cccDNA levels during the early phase increased exponentially with a doubling time of around 4 days , expectedly paralleled by a corresponding increase in infected hepatocytes [11]; in ducks , the doubling time was only around 16 h [52] . These in vivo data would be compatible with DHBV cccDNA formation occurring at a higher rate yet at this time , a direct correlation with our findings remains speculative . Practically , however , the accumulation in the hepatoma cells of distinct nuclear HBV rcDNA forms that are likely intermediates in the rcDNA to cccDNA pathway will allow to much more thoroughly dissect the underlying molecular mechanisms . Efficient DHBV cccDNA formation in the same cells , on the other hand , provides a unique new tool to facilitate identification , e . g . by RNAi technology , of the human cellular factors involved in cccDNA biosynthesis and the screening for specific inhibitors that directly address the form of viral genome which ensures establishment and persistence of HBV infection .
Virus vectors contained 1 . 5× genome length sequences of HBV ( genotype D , subtype ayw; Genbank accession no . : V01460 ) or DHBV ( DHBV16; accession no . : K01834 ) . Numbering for HBV starts with the first nucleotide of the core open reading frame [53] , for DHBV with the last nucleotide of the unique Eco RI site [54] . Plasmid pCH-9/3091 [55] contains a 1 . 05× genome of the same HBV isolate under control of the cytomegalovirus immediate early ( CMV-IE ) promoter . Surface protein deficient HBV carried mutations at positions 1399 and 1438 , introducing a stop codon in the preS2 ORF and a Met>Thr exchange at the S ORF start . In surface deficient DHBV , a G>A exchange at position 1165 creates a stop codon in the S ORF [56] . In the splicing-deficient HBV construct , A1769 in the major splice acceptor consensus site CAG|G ( A1769 underlined ) was changed to C . HepG2 , Huh7 and LMH cells were cultured essentially as previously described [18] , [33] . Transfections were performed using TransIT-LT1 reagent as recommended by the manufacturer ( Mirus ) . Cells were harvested 3 days post transfection , unless indicated otherwise . Briefly , cells were lysed NP40 lysis buffer , and the nuclei were separated by low speed centrifugation [33] , [57] . Alternatively , nuclei were purified by sucrose gradient sedimentation ( see below ) . Total cell extracts were obtained by lysis in 0 . 5% SDS . After different treatments , including or not including incubation with proteinase K ( PK ) and/or micrococcus nuclease ( MN ) , viral DNAs were isolated using QIAamp silica columns ( Qiagen ) , or by conventional phenol extraction as indicated . Dpn I ( NEB ) and Plasmid-Safe DNase ( Epicentre Biotechnologies ) were applied as suggested by the manufacturers . Viral DNAs on Southern blots were visualized using 32P labeled full-length genome DNA probes . Cells were subjected to detergent lysis and subsequent sucrose step gradient centrifugation , essentially as described [29] . Absence of cytoplasmic contamination from the purified nuclei was assessed by comparing the presence of cytoplasmic poly-A binding protein ( PABP ) and nuclear histone H3 in total versus nuclear extracts . Nonspecific association of viral capsids with nuclei was addressed by mixing capsid-containing cytoplasmic extracts from transfected cells with total lysates from untransfected cells , followed by sucrose gradient purification of the nuclei . Permeability of the isolated nuclei for exogenously added MN was confirmed by fragmentation of the chromosomal DNA . Identity of cccDNA was confirmed by linearization upon incubation with single-cutter restriction enzymes and resistance against heat denaturation . RC-DNA and nicked cccDNA were distinguished by the defined versus randomly positioned discontinuites in the DNA strands . The unique recognition site for Apa LI is located immediately upstream of the plus-strand 5′ end in RC-DNA; plus-strands not extended through this region prevent cleavage of RC-DNA whereas randomly nicked cccDNA is not affected . Cleavability at sites further upstream ( Nco I ) or downstream ( Fsp I ) served as control . For immunoprecipitation ( IP ) of core protein associated DNAs monoclonal antibody 312 against HBV core protein [38] and a polyclonal antiserum raised against recombinant DHBV capsids [58] were used . For IPs from purified nuclei , the nuclei were incubated in 0 . 75× radioimmunoprecipitation ( RIPA ) buffer ( 1× RIPA buffer is 20 mM Tris ( pH 7 . 2 ) , 1% sodium deoxycholate , 1% Triton X-100 , 0 . 1% sodium dodecyl sulfate , 150 mM NaCl ) , and briefly sonicated; cytoplasmic extracts were adjusted to 0 . 75× RIPA as well . IPs were then performed as previously described [58] , with the specific antibody immobilized to protein A or protein G Sepharose ( GE Healthcare ) . Associated DNAs were isolated as described above . Virion-derived nucleocapsids were obtained from highly viremic sera by sedimentation in Nycodenz gradients containing 0 . 5% ( v/v ) NP-40 , and subsequently incubated in EPR buffer containing 1 mM each of the four dNTPs for 16 h , as described [26] . Southern blot signal intensities were determined by phosphorimaging , using AIDA ( Fuji ) or ImageQuant software ( GE Healthcare ) . Background corrections were performed by subtracting from the signal of interest the value obtained for an equally sized area in the same lane . Quantitations from each blot were performed in duplicate . In several cases , dilution series were used to more accurately determine relative amounts of a given species in different compartments or after different treatments . Standard deviations were derived from at least two and mostly more independent experiments and calculated using Microsoft Excel software . Statistical significance was evaluated using Graphpad Prism 5 for Mac software . | Persistent infection with hepatitis B virus ( HBV ) causes chronic hepatitis B which frequently progresses to hepatocellular carcinoma , a leading cause of cancer-mediated mortality worldwide . Persistence requires formation and amplification of covalently closed circular ( ccc ) DNA , an episomal form of the viral genome that is not targeted by current drugs and thus is responsible for the notorious difficulties in therapeutic elimination of infection . Initial generation of cccDNA occurs upon nuclear import of the virion-borne relaxed circular ( rc ) DNA to which the viral polymerase is covalently linked; amplification occurs via intracellular recycling . The underlying molecular pathway is poorly understood . Because HBV infects only primates , in vivo studies are extremely restricted; in vitro , select hepatoma cell lines transfected with HBV support viral replication , however with little if any cccDNA formation . Here , we compared intracellular recycling of HBV and DHBV , a model hepatitis B virus from ducks , in cross-species transfections . Surprisingly , the major contribution to cccDNA formation comes from the virus rather than the cell as DHBV but not HBV rcDNA converted efficiently into cccDNA in the same human cell background . This unexpected difference might help to better understand persistence of HBV infection; efficient DHBV cccDNA formation in human cells provides a new tool to facilitate identification , and possibly targeting , of the human cell factors involved . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"infectious",
"diseases/viral",
"infections",
"gastroenterology",
"and",
"hepatology/hepatology",
"molecular",
"biology"
] | 2010 | Generation of Covalently Closed Circular DNA of Hepatitis B Viruses via Intracellular Recycling Is Regulated in a Virus Specific Manner |
Delivery of effector proteins is a process widely used by bacterial pathogens to subvert host cell functions and cause disease . Effector delivery is achieved by elaborate injection devices and can often be triggered by environmental stimuli . However , effector export by the L . pneumophila Icm/Dot Type IVB secretion system cannot be detected until the bacterium encounters a target host cell . We used chemical genetics , a perturbation strategy that utilizes small molecule inhibitors , to determine the mechanisms critical for L . pneumophila Icm/Dot activity . From a collection of more than 2 , 500 annotated molecules we identified specific inhibitors of effector translocation . We found that L . pneumophila effector translocation in macrophages requires host cell factors known to be involved in phagocytosis such as phosphoinositide 3-kinases , actin and tubulin . Moreover , we found that L . pneumophila phagocytosis and effector translocation also specifically require the receptor protein tyrosine phosphate phosphatases CD45 and CD148 . We further show that phagocytosis is required to trigger effector delivery unless intimate contact between the bacteria and the host is artificially generated . In addition , real-time analysis of effector translocation suggests that effector export is rate-limited by phagocytosis . We propose a model in which L . pneumophila utilizes phagocytosis to initiate an intimate contact event required for the translocation of pre-synthesized effector molecules . We discuss the need for host cell participation in the initial step of the infection and its implications in the L . pneumophila lifestyle . Chemical genetic screening provides a novel approach to probe the host cell functions and factors involved in host–pathogen interactions .
Legionella pneumophila is the causative agent of the acute pneumonia known as Legionnaires' disease [1] , [2] . Upon inhalation , Legionella pneumophila infects and replicates in alveolar macrophages , leading to inflammation and development of the disease . Within host cells , L . pneumophila avoids phagosome-lysosome fusion and manipulates host cell processes to create a specialized phagosome that does not acidify and is suitable for intracellular replication [3]–[5] . The Icm/Dot Type IVB secretion system is required for avoiding phagosome-lysosome fusion and for intracellular multiplication [6] , [7] . The Icm/Dot system mediates translocation of multiple effector proteins that are responsible for transforming the nascent Legionella phagosome into a replicative compartment , called the Legionella-containing vacuole ( LCV ) [8] . After several hours , the LCV acquires characteristics of the endoplasmic reticulum ( ER ) by intercepting small vesicles that traffic between the golgi compartment and the ER [9] . Although most effector proteins have uncharacterized functions , some have been studied in detail and target multiple host cell processes important for the intracellular survival of L . pneumophila [8] , [10] . For example , LepA and LepB mediate non-lytic release of L . pneumophila from protozoan hosts [11] . RalF , DrrA/SidM , LepB and LidA interfere with regulators of ER to Golgi trafficking [12]–[14] . While many other effectors can also interfere with vesicular trafficking by unknown mechanisms [15]–[17] , additional effectors target the host innate immune response [18] , phosphoinositide metabolism [19] or ubiquitination [20] . The early requirement of a functional Icm/Dot system suggests that effectors must be rapidly translocated upon encounter of the host cell in order to alter trafficking of the newly-formed phagosome and prevent its fusion with the lysosome [21] , [22] . Little is known about the processes or signaling events that trigger translocation of bacterial effectors to host cells . For many bacterial pathogens that use a type III secretion system for effector translocation , active release of the effector molecules in the culture supernatants can be triggered in the absence of the host cell [23] . In contrast , for pathogens with type IV secretion system such as H . pylori , Bartonella spp , C . burnetti and L . pneumophila , secretion of effectors has not been detected [24] and it is unclear whether or not these pathogens can secrete as well as translocate effectors . Even though L . pneumophila translocates a large repertoire of effector proteins during the course of the infection , none of these effectors are released until it encounters a target host cell [25] . This suggests that functional activation of the Icm/Dot system requires sensing of an appropriate host cell by L . pneumophila . Effector translocation might be triggered passively by stimuli provided by the host cell . An alternate view is that effector translocation requires the active participation of the host cell . We sought to gain information about the bacterial and host cell factors required for triggering effector translocation by conducting a perturbation study of effector translocation using libraries of small organic molecules with known targets , an approach called chemical genetics [26] , [27] . In this approach , thousands of small molecules with known protein targets are screened to identify which proteins are involved in regulating a particular process . This requires annotated libraries of known inhibitors as well as a high-throughput screening assay for the investigated process . We used a β-lactamase reporter system to monitor type IVB effector translocation and adapted it to high-throughput screening . Screening a collection of three commercial libraries consisting of over 2500 bioactive molecules identified a relatively small number of molecules that inhibit translocation . Many of these inhibitors have eukaryotic targets , and some of these inhibit various stages of actin cytoskeleton assembly required for phagocytosis . We show that the triggering of effector translocation is dependent upon phagocytosis and requires the active participation of the host cell . Also , to gain more insight into the parameters that control effector translocation we developed a kinetic translocation assay , which enables detection of effector translocation in real time . We show that host cell contact is a limiting factor for Icm/Dot-dependent effector translocation and that artificially induced intimate contact using the antibody-Fc receptor interaction can increase effector translocation rates by more than 10-fold . Our results reconcile previously conflicting results and provide evidence that phagocytosis-mediated intimate contact of L . pneumophila with host cells is critical for efficient effector translocation . We propose a model in which L . pneumophila relies on the host cell-dependent phagocytosis to create the intimate binding required to trigger effector translocation .
The β-lactamase translocation reporter system [28] has been widely used to monitor effector translocation by type III secretion systems in various organisms [29]–[32] . We recently reported the use of this system to detect Icm/Dot-dependent effector translocation by L . pneumophila [16] . Host cells are infected with bacteria expressing an effector fused to the C-terminal end of the TEM-1 β-lactamase . The translocated β-lactamase activity in host cells can be quantified using a spectrofluorimeter to measure the concentrations of the cleaved ( Emission at 460 nm ) and intact ( Emission at 530 nm ) β-lactamase substrate CCF4 . We further validated the reporter system by testing the translocation of the previously reported Icm/Dot effector proteins RalF , LepA , LepB , VipA , VipD , LidA as well as the non-translocated fatty acid biosynthetic enzyme , enoyl-CoA reductase ( FabI ) . As expected , β-lactamase activity was detected in J774 cells infected with bacteria ( multiplicity of infection MOI = 50 ) expressing the various TEM-effector fusions but not in J774 cells infected with the bacteria expressing TEM-FabI ( Figure 1A and data not shown ) . In order to determine the sensitivity and the linearity of the assay we infected J774 cells with increasing numbers of bacteria expressing the translocated TEM-LepA fusion protein . When J774 cells are infected with less than 10 bacteria/cell the system seems to behave linearly but above 25 bacteria/cell the system appears to saturate as increases in MOI do not result in a corresponding increase in the Em460/530 ratio ( Figure 1B ) . As a compromise between sensitivity and linearity , we selected MOI = 20 as the standard MOI in subsequent experiments . We also investigated the effect of protein expression levels on translocation efficiency . L . pneumophila expressing TEM-RalF , TEM-LepA or TEM-LegAU13 were grown with varying amounts of IPTG to obtain a range of increased protein expression levels ( Figure 1C ) . In the absence of IPTG no anti-TEM reactive protein could be detected by Western Blot and little or no translocation could be detected . In contrast , translocation of all effectors could be detected when expressed at low levels using 10 µM IPTG . Increasing expression levels resulted in increased translocation up to 50 µM IPTG , thus indicating that effector production is a limiting factor . However , further increases in protein expression levels did not result in increased effector translocation . This plateau in translocation suggests that each effector has a maximal rate of delivery to the host and that when effector protein expression is not limiting , one or more additional unknown factors limit effector translocation . In order to use the β-lactamase translocation reporter assay for chemical genetic screening we miniaturized it to the 384-well format and evaluated its use for high throughput screening ( HTS ) . The Z-factor is a widespread measure of the quality or power of a HTS assay [33] . We found the TEM reporter to be a robust screening assay with a Z factor >0 . 75 ( data not shown ) , thus making it suitable for high-throughput screening of inhibitors of effector translocation . In order to identify processes required for effector translocation , we took advantage of three libraries of small molecule inhibitors with a wide variety of known prokaryotic and eukaryotic targets . The Biomol ICCB Known Bioactives Library is a collection of 480 diverse biologically active compounds with defined biological activity and was developed in collaboration with the Harvard Institute of Chemistry and Cell Biology . The NINDS custom collection of 1 , 040 characterized bioactive compounds was compiled by MicroSource Discovery Systems for the National Institute of Neurological Disorders and Stroke ( NINDS ) . Three quarters of the compounds in the collection are FDA-approved for use in humans . The Prestwick Chemical Library® contains 1 , 120 off-patent compounds , 90% being marketed drugs . The three libraries together represent 2 , 640 molecules ( see Table S1 for complete list ) and cover 46% of FDA-approved active molecules ( 561 compounds ) . We screened the three libraries for molecules that inhibited translocation of the LepA effector from Legionella to macrophages ( Figure 2 ) . We selected hits showing more than 50% inhibition . In spite of its small size the Biomol library showed the highest hit rate ( 8 . 3% ) compared to the larger NINDS and Prestwick libraries ( hit rates of respectively 1 . 2% and 2 . 2% ) . Because of its small size , its diversity and a high hit rate the Biomol library appears to be most suited library for the identification of inhibitors of a particular biological process . Initial screening identified 86 translocation inhibitors which are associated with diverse biological categories ( Figure 3A and Table S2 ) . We excluded those inhibitors whose documented targets are not well established or predicted to be irrelevant for translocation . These included molecules annotated as antifungal , antiviral or anthelmintic as well as known preservatives ( i . e . , thimerosal ) . The remaining 42 inhibitors were retested under non-HTS conditions and one compound was found to be a false positive . Other compounds were found to have been falsely identified as inhibitors because they interfered with the translocation assay itself ( fluorescence quencher , autofluorescent molecules , inhibitors of CCF2/AM loading ) . In order to identify molecules displaying potential off-target effects we determined the IC50 of the remaining 25 inhibitors as exemplified in Figure 3 . For inhibitors with documented IC50 we compared the published values to the determined IC50 for the translocation . This led us to exclude three inhibitors ( DPI , Cantharidin and MBCQ ) which displayed IC50 more than one order of magnitude higher than the documented IC50 . The selected 22 remaining molecules were capable of inhibiting LepA translocation with varying efficiency , ranging from 63 to 100% inhibition ( Table 1 ) . All but one of the molecules identified in this study are inhibitors of eukaryotic processes , revealing an unexpected active role for the host cell in the Icm/Dot effector translocation process . A large class of inhibitors target proteins of the cytoskeleton ( actin and tubulin ) as well as proteins involved in cytoskeleton dynamics ( PI3 kinase , N-Wasp ) . Other molecules target cell surface proteins such as the PDGF receptor or the CD45 tyrosine phosphatase which could be viewed as potential candidate receptors for L . pneumophila internalization . Somewhat surprisingly , no antibiotics were identified as inhibitors of translocation in this study . Accordingly , LepA translocation was not inhibited by antibiotics acting as transcription or translation inhibitors , suggesting that pre-synthesized effectors are exported by the Icm/Dot system at early stages of infection . Even though most inhibitors have a eukaryotic target , one molecule , FCCP , can also target bacterial cells . FCCP acts as a protonophore on the bacterial membrane thus collapsing the proton motive force ( PMF ) . FCCP and CCCP are structurally related protonophores which act as proton carriers discharging both the electric potential ( Δψ ) and concentration ( ΔpH ) components of the PMF . CCCP has been shown to inhibit type III secretion [34] and recent findings demonstrate that the flagellar type III secretion apparatus functions as a proton-driven protein exporter [35] , [36] . CCCP completely inhibits LepA translocation at concentration as low as 5 µM ( Figure 4A ) . Even when L . pneumophila was pretreated with 10 µM CCCP for 30 minutes , translocation was largely restored following washout of CCCP ( Figure 4A ) showing reversibility of the inhibition . L . pneumophila displays pore forming activity on macrophages and red blood cells that is mediated by the Icm/Dot system [37] . Thus , the activity of the Icm/Dot system can also be assayed by red blood cell lysis . RBC lysis is abolished in a dotA mutant but , as effector translocation , it is not inhibited by sodium azide or antibiotics acting as translation inhibitors ( Figure 4B ) . RBC lysis is detectable as early as 15 minutes after L . pneumophila contacts the RBC ( Figure 4C ) . In contrast to sodium azide and antibiotics , CCCP inhibits RBC lysis very efficiently and rapidly . Since CCCP collapses the proton gradient , it is expected to impact ATP synthesis by the ATP synthase . CCCP has a moderate impact on the pre-existing ATP pool , reducing it by about 30% after CCCP addition ( Figure 4D ) . The energy requirement for activity of the Icm/Dot system and effector translocation is poorly understood . Since the IcmO/DotB component of the Icm/Dot system shows ATPase activity it is expected that Icm/Dot activity is ATP-dependent . Inhibition by protonophore also suggest that effector export by the Icm/Dot system is at least partially dependent on the proton motive force . Based on these results , other molecules with protonophore or uncoupling activity are expected to inhibit the Icm/Dot system and effector translocation . We investigated the identified inhibitors of LepA translocation for potential direct inhibition of the Icm/Dot system using the RBC lysis assay ( Figure 5A ) . FCCP showed strong inhibition of RBC lysis as did the calcium ionophore Calcymicin and the calcium channel blocker Nifedipine . Phenoxybenzamine , PI-110 , TPCK , W-7 and Tyrphostin 9 activity also strongly reduced RBC lysis activity . Consistent with these findings , the PDGF receptor inhibitor Tyrphostin 9 has documented uncoupling activity . Interestingly , the NF-kappaB ( NF-κB ) inhibitor CAPE has been previously used to show the requirement of NF-κB for successful L . pneumophila infection and intracellular replication [38] , [39] . This initially suggested a role of NF-κB in effector translocation during initial interaction with the macrophage . However we found that CAPE also directly inhibits Icm/Dot-mediated RBC lysis ( Figure 5A ) . A large number of inhibitors that had no direct effect on Icm/Dot activity are molecules targeting the host cytoskeleton ( Tubulin inhibitors , actin inhibitors , PI3K inhibitors ) . These molecules are likely to alter phagocytosis , a fundamental function of the macrophage . We then investigated the effect of all effector translocation inhibitors on phagocytosis of bacterial particles by using differential , trypan blue-mediated , quenching of fluorescein-labeled E . coli [40] , [41] ( Figure 5B ) . With the exception of FCCP , Nifedipine and Tyrphostin 9 , all the other molecules showed significant inhibition of bacterial uptake ( Figure 5B ) . Inhibition of bacterial uptake was expected for the actin polymerization inhibitors ( Latrunculin B , Cytochalasin B ) and for the PI3 kinase inhibitors ( LY294002 , Wortmannin ) . To a lesser extent , microtubules also play a role in the phagocytosis process [42] where they would be required for activity of PI3K at the site of phagocytosis [43] and may explain the inhibitory activity of Fenbendazole and Albendazole . In contrast , inhibition of bacterial uptake by other molecules such as the inhibitors of NF-κB , CD45 and the serine protease inhibitor or the NO donor Furoxan had not been previously reported . This may be due to a true involvement of the inhibitors targets in the phagocytosis process or to some undocumented off-target effect on phagocytic cells ( see discussion ) . Regardless of the mechanisms of inhibition , the results show that inhibitors of Icm/Dot translocation that do not inhibit Icm/Dot activity itself are enriched in inhibitors of bacterial uptake by the macrophage . This pinpoints a critical role of phagocytosis in Icm/Dot-mediated translocation of LepA by L . pneumophila . Phagocytosis of L . pneumophila by pulmonary macrophages is thought to naturally occur via non-opsonic events and under these conditions L . pneumophila has been found to enter monocytes by coiling phagocytosis [44] . Interaction of L . pneumophila can be stimulated by Legionella specific antibodies [45] , a situation that results in conventional FcR-mediated phagocytosis , but that does not reflect the biologically relevant interaction with host cells . We tested the effect of L . pneumophila-specific antibody on L . pneumophila phagocytosis by J774 cells using differential immuno-fluorescence microscopy [46] . Internalized GFP-expressing L . pneumophila appear green whereas non-internalized L . pneumophila which are accessible to rhodamine-conjugated antibody against Legionella appear red/orange . Opsonization of L . pneumophila resulted in a higher number of internalized bacteria ( Figure 6A ) . We also used differential , trypan blue-mediated , quenching of fluorescein-labeled L . pneumophila to measure the effect of antibody-opsonization on L . pneumophila internalization . In four independent experiments , we found that although the level of phagocytosis by J774 cells was variable , antibody-opsonization of L . pneumophila always increased phagocytosis by two- to three-fold in all cases ( Figure 6B ) . This result is consistent with previous work reporting that monocyte monolayers infected with L . pneumophila contain three times as many bacteria in the presence of antibody [47] . To investigate the role of phagocytosis on effector translocation , we analyzed the effect of inhibitors of actin polymerization and phosphoinositide 3-kinases ( PI3K ) under non-opsonized and artificial , antibody-opsonized conditions . The two inhibitors of actin polymerization , Cytochalasin B and Latrunculin B dramatically reduce uptake of L . pneumophila by J774 cells , either in the presence or absence of antibody ( Figure 6C ) . Phagocytosis of L . pneumophila has been initially reported to be insensitive to PI3K inhibitors in human monocytes [48] . A similar result was obtained in Dictyostelium by comparing phagocytosis of L . pneumophila by wild-type Dictyostelium and a mutant lacking the two known PI3K [19] . Both strains showed similar levels of phagocytosis of wild-type strain JR32 . The requirement for PI3K for phagocytosis by mammalian cells reported here however appears to be different than in Dictyostelium . A recent report shows that phagocytosis of L . pneumophila by the murine monocyte cell line J774 is mediated by PI3K and is therefore sensitive to PI3K inhibitors [49] . Consistent with the later study , we found that phagocytosis of L . pneumophila can be inhibited by PI3K inhibitors LY294002 at 40 µM ( not shown ) and wortmannin at 2 µM ( Figure 6C ) . Importantly , all the tested inhibitors inhibited L . pneumophila phagocytosis even in the presence of antibodies . We then analyzed the impact of the phagocytosis inhibitors on translocation of LepA and RalF under non-opsonized or antibody-opsonized conditions ( Figure 6D and 6E ) . All tested phagocytosis inhibitors have a dramatic impact on translocation of LepA and RalF under non-opsonized conditions . The same inhibitors also inhibit translocation of LepA in the presence of human complement ( data not shown ) . In contrast , translocation of both LepA and RalF is resistant to phagocytosis inhibitors under antibody-opsonized conditions ( Figure 6D and 6E ) . In conclusion , translocation of Legionella effectors requires phagocytosis under standard , non-opsonized or complement-opsonized ( not shown ) conditions . However , the requirement for phagocytosis can be bypassed by the presence of anti-Legionella antibody , suggesting that effector translocation can occur in the absence of phagocytosis by promoting L . pneumophila binding to macrophages via antibody-Fc receptors interaction . As a result of chemical screening we found that the small molecule RWJ-60475 inhibits L . pneumophila effector translocation . This suggested that its known target , the receptor protein tyrosine phosphate phosphatase CD45 , is required for L . pneumophila phagocytosis . To investigate the role of CD45 in L . pneumophila uptake and effector translocation we used siRNA to knock-down expression of CD45 in THP-1 . Although siRNA treatment was effective in significantly lowering expression of CD45 to non-detectable levels , L . pneumophila effector translocation remained unaffected ( Figure S1 ) . However , it has recently been reported that CD45 and another receptor protein tyrosine phosphate phosphatase , CD148 functioned redundantly to regulate B cell and macrophage immunoreceptor signaling [50] . We used bone-marrow derived macrophages ( BMM ) from PtprjTM−/TM− , Ptprc−/− mice which do not express CD45 and CD148 to determine if these tyrosine phosphate phosphatases also functioned redundantly to mediate L . pneumophila binding and uptake . L . pneumophila bound similarly to wild-type and DKO BMM ( Figure 7A ) suggesting that CD45 and CD148 do not constitute receptors for L . pneumophila binding to macrophages . In contrast , uptake of L . pneumophila by CD45/CD148-deficient BMM was significantly reduced ( Figure 7B ) while the CD45/CD148 double knockout ( DKO ) BMM showed unaltered ability to phagocytose E . coli bacteria ( Figure 7B ) . Translocation of the two effectors RalF and LepA in the DKO BMM was reduced to the same extent as uptake ( Figure 7C ) . Antibody opsonization restored effector translocation in the CD45/CD148-deficient BMMs . These results reveal the important role of tyrosine phosphate phosphatases for L . pneumophila entry into macrophages and provide strong genetic evidence that L . pneumophila phagocytosis is a critical event for delivery of Icm/Dot effector proteins . It should be noted that inhibition of bacterial uptake by RWJ-60475 is greater than the inhibition displayed by the CD45/CD148-deficient BMMs and suggests that RWJ-60475 acts on the phosphatase activities of CD148 as well as on other as yet unrecognized tyrosine phosphatases . The fact that phagocytosis is dispensable for translocation when bacteria contact macrophages through the antibody-FcR interaction suggests that either the tight binding of the bacteria to the cells or signaling events due to clustering of the high affinity Fc receptors , are promoting effector translocation . Binding of antibody-coated particles to FcR induces clustering of the receptors and initiates a signal transduction cascade leading to phagocytosis [51] , [52] . Clustering is then followed by phosphorylation of two specific tyrosines on the FcR ITAM domain ( Immunoreceptor Tyrosine-based Activation Motifs ) by enzymes of the Src tyrosine-kinase family [53] . The phosphorylated ITAMs then recruit Syk kinase which is required for efficient phosphorylation of phosphatidylinositol 3-kinase and is critical for signal transduction and phagocytosis mediated by FcR [54] . As initial evidence that FcR signaling is not required for antibody-stimulated effector translocation , we found that the Syk kinase inhibitor R406 [55] does not inhibit LepA translocation in J774 cells ( data not shown ) . To further determine if binding of antibody-opsonized bacteria to the FcR is sufficient to trigger effector translocation , we used CHO cells expressing the human FcγRIIA receptor or a signaling deficient mutant of FcγRIIA , Y2F/Y3F in which the two tyrosines of the ITAM domain have been substituted by phenylalanine [56] . Opsonization of Legionella with antibody strongly stimulated translocation of LepA and RalF in cells expressing the wild-type or signaling deficient FcγRIIA receptors ( Figure 8A ) . Whereas the wild-type FcγRIIA is fully functional and capable of promoting phagocytosis , the Y2F/Y3F mutant can bind antibody but does not support phagocytosis [56] . Consistently , translocation of LepA and RalF in CHO cells expressing either the wild type or the signaling-defective receptors is insensitive to phagocytosis inhibitors ( Figure 8B ) . We conclude that the intimate binding of antibody-opsonized L . pneumophila to FcR on host cells can substitute for naturally occurring phagocytosis to trigger effector translocation . In order to better evaluate the effect of antibody-induced bacterial contact on effector translocation we adapted the β-lactamase reporter to study real time translocation of effectors . The β-lactamase translocation assay has recently been used to analyze real-time effector translocation by the EPEC type III secretion system and allowed a more detailed analysis of the parameters that control effector delivery into host cells [57] . In contrast to the standard β-lactamase translocation assay where CCF4 hydrolysis is measured at the end of the infection , the real-time translocation assay is based on live detection of CCF4 substrate hydrolysis as the TEM-effector fusion is being translocated by the infecting bacterial population . J774 cells were pre-loaded with the β-lactamase CCF4 substrate in presence of probenecid which inhibits organic anion transporters [58] and facilitates loading of CCF4 by inhibiting its active efflux from the cells . Cells were then infected with L . pneumophila strains expressing β-lactamase-effector fusion proteins and placed into a plate reader at 37°C . Hydrolysis of green CCF4 into its blue product by the translocated TEM-hybrid β-lactamases was then monitored by measuring blue ( 460 nm ) and green fluorescence ( 530 nm ) every 2 minutes and is reported as the 460/530 ratio . Hydrolysis of CCF4 was evident after less than 30 minutes in J774 cells infected with TEM-LepA expressing bacteria at a multiplicity of infection of 125 or higher ( Figure 9A ) . As expected , decreases of the MOI led to decreased accumulation rate of the blue CCF4 hydrolysis product , but was still detectable at a MOI of 15 . In contrast , even at high MOI , no translocation was detectable when J774 cells are infected by a dotA mutant expressing TEM-LepA . Accumulation of the CCF4 cleavage product ( P ) per time unit provides the hydrolysis rate of CCF4 by the translocated β-lactamase-effector fusion and an apparent maximum rate ( appVmax ) can then be determined . Regardless of the MOI , the appVmax for the LepA effector is typically reached within 40–50 minutes ( Figure 9A ) . As more β-lactamase-effector fusion is being translocated , the appVmax should be proportional to the MOI and we observed a good correlation of appVmax with MOI up to an MOI of 250 ( Figure 9B ) . We then analyzed the translocation of RalF , LepA and LegA3 by non-opsonized L . pneumophila at a MOI of 125 . Translocation of RalF and LepA could easily be monitored in real time ( Figure 9C ) . Translocation of LegA3 was difficult to detect because the rate of LegA3 translocation is slow and is obscured by the leakage of the CCF4 substrate from J774 cells even in the presence of probenecid ( Figure 9C ) . Analysis of the rate of product formation by the translocated TEM-RalF and TEM-LepA hybrid proteins shows a burst at respectively 44 and 52 minutes post-infection ( Figure 9D ) . Under these conditions , phagocytosis is required for effector translocation and the kinetics of effector translocation may be limited by the kinetics of the phagocytosis process . The absence of phagocytosis requirement when contact is achieved by antibody-FcR interaction may remove this rate-limiting kinetic step . As expected , we found that opsonization of L . pneumophila by antibody dramatically increased translocation efficiency and increased the rate of product formation by more than 10-fold ( Figure 9C and 9D ) . In addition , the translocation rates for the TEM-RalF and TEM-LepA hybrid proteins reached a maximum at respectively 20 and 24 minutes post-infection which is significantly earlier than in the absence of antibody . In addition , the hierarchy of the translocation rates of the different hybrids is maintained in the presence of antibody ( RalF>LepA>LegA3 ) . We conclude that antibody-mediated contact of L . pneumophila with macrophages stimulates translocation by providing the direct intimate contact normally obtained through the rate-limiting phagocytosis process .
Delivery of effector proteins capable of interfering with host cell processes is a mechanism widely used by bacterial pathogens to hijack the function of their target cells and cause disease . Effector delivery is achieved by elaborate effector injection devices such as the Type III secretion system [23] , the Type IV secretion system [24] and the recently recognized Type VI secretion system [59] . Type III and Type VI secretion of the bacterial effectors respond to environmental stimuli and can be triggered in vitro by using various chemicals or media formulations . In contrast , effector secretion by the L . pneumophila Type IV secretion system has not yet been detected unless the bacterium encounters a target host cell [25] . We sought to determine the mechanisms involved in the signaling of effector translocation by L . pneumophila . Chemical genetics has recently appeared as a successful strategy to generate hypotheses regarding underlying biological mechanisms [60] , [61] . We used a combination of three commercially available annotated compound libraries of more than 2 , 500 molecules to understand the mechanisms involved in triggering effector translocation by L . pneumophila . We found that a very limited number of molecules can directly block activity of the Icm/Dot system and that inhibitors of protein synthesis are not effective at inhibiting Icm/Dot-dependent effector translocation and pore forming activity ( Figure 4 ) . Thus , activity of the Icm/Dot system does not rely on de novo synthesis of structural or effector proteins . This reinforces the notion that the Icm/Dot system is in a “locked and loaded” state before L . pneumophila encounters a target cell . Although Icm/Dot-dependent effector translocation and pore forming activity are insensitive to many antibiotics and even to sodium azide , we found that the same Icm/Dot-dependent processes are strongly but reversibly inhibited by the protonophore CCCP . The pH gradient across the bacterial membrane generated by the respiratory chain is used as an energy source to power the flagellar motor and ion antiporters . This proton motive force ( PMF ) has recently been shown to be required for activity of the Type III secretion system which functions as a proton-driven protein exporter [35] , [36] . It is tempting to speculate that the PMF also powers the Icm/Dot system . However , inhibitor-mediated collapse of the PMF also results in a 30% drop of the ATP level which could also explain the loss of Icm/Dot activity . We can think of at least two ways that energy may be required for Icm/Dot- dependent RBC lysis . Energy may be required to assemble a functional TFSS from pre-existing components . Alternatively , PMF may be required to translocate pore-forming protein molecules to the RBC membrane and other target cells . Although PMF would be an immediate and convenient source of energy to assemble or power the Icm/Dot system , the interpretation of experiments using inhibitors of the PMF is challenging and further studies will be required to ascertain the role of PMF in Icm/Dot effector translocation . Only a very limited number of molecules were capable of acting directly on Icm/Dot activities . In contrast , many more molecules acting on the host cells were effective at inhibiting effector translocation . We found known inhibitors of phagocytosis as well as inhibitors of other processes . With the exception of the inhibitors interfering with RBC lysis , all other inhibitors displayed marked inhibition of phagocytosis of inert bacterial particles in some cases for apparently unclear reasons . For example , inhibition of phagocytosis by the two inhibitors of NF-κB , CAPE and parthenolide was unexpected . Interestingly , another NF-κB inhibitor has been found to negatively affect phagocytosis by murine macrophages [62] suggesting a role of NF-κB regulation of phagocytosis of bacterial particles . In spite of extensive literature on NF-κB we did not find more direct evidence supporting the involvement of NF-κB in the phagocytosis process . Similarly , although RWJ-60475 inhibits bacterial uptake , its known target , the receptor protein protein tyrosine phosphate phosphatase CD45 was not previously known to be required for phagocytosis . In addition , effective siRNA knock-down of CD45 in THP-1 cells failed to provide evidence for a requirement of CD45 for L . pneumophila uptake and effector translocation ( data not shown ) . However , we found that macrophages derived from a mutant mouse strain lacking both the CD45 and CD148 protein phosphatases exhibited a defect in L . pneumophila phagocytosis similar to that reported for ingestion of RBC by the same type of cells . This suggests that RWJ-60475 may also act on the phosphatase activity of CD148 or other as yet unrecognized phosphatases . Large-scale use of specific inhibitors is thus a powerful tool to generate hypotheses regarding the factors involved in a given process . However , as illustrated above , the possible effect of the inhibitors on additional undocumented targets must be considered . The strong requirement of phagocytosis for L . pneumophila effector translocation is remarkable . Other bacterial pathogens inject bacterial effectors without the requirement of phagocytosis and some pathogens like Yersinia enterocolitica and enteropathogenic E . coli even utilize type III-dependent effector translocation to inhibit phagocytosis [63]–[65] . We found that when macrophages are given non-opsonized Legionella , addition of actin depolymerizing agents that block phagocytosis severely decreased effector translocation . However , when the same cells were given antibody opsonized-Legionella , the actin depolymerizing agents did not inhibit translocation . We can imagine two different explanations for these results . One explanation is that in the presence of antibodies , binding of the bacteria to the macrophages is so efficient that , as seen by Kirby et al . [37] even in the presence of actin depolymerizing agents , there is a low level of phagocytosis that corresponds to the level of uptake observed in the absence of antibody and inhibitor . An alternative explanation is that the increased level of Legionella binding to the macrophages in the presence of antibody permits translocation even when the bacteria remain outside the cell in the presence of the inhibitors . We favor the second explanation because we found that opsonized Legionella were able to translocate effectors to CHO cells expressing mutant forms of the FcγRIIA receptor that are defective for signaling and cannot promote phagocytosis . Thus , the signaling cascade induced as a result of antibody-FcR binding is not required to trigger Icm/Dot-mediated effector translocation . Under these conditions , it is highly unlikely that the bacteria are being internalized . This supports the idea that artificially-induced intimate contact can trigger translocation in absence of phagocytosis and that phagocytosis is not required per se for translocation . These results provide a resolution for the apparent discrepancy between published work from our lab done with professional phagocytes in the absence of opsonization [25] and work from the Roy lab using CHO ( FcγRIIΑ ) cells and opsonized Legionella [66] . Real-time analysis of effector translocation showed that phagocytosis-dependent translocation is much slower than the phagocytosis-independent translocation triggered by antibody-FcR intimate binding . Presumably phagocytosis-dependent translocation is slower because the kinetics of phagocytosis adds time to the kinetics of effector translocation . The absence of evidence for protrusion of Icm/Dot system suggest that intimate binding may be needed to overcome the physical barrier established by the extracellular structures present on the surface of the bacterial or cellular membranes . Pulmonary macrophage infection by L . pneumophila generally occurs in the absence of pre-immune antibodies . Under in vivo conditions it is then likely that L . pneumophila relies on host cell signaling to stimulate uptake and achieve intimate contact required for effector translocation . Our data support a model in which L . pneumophila relies on the phagocytosis process to generate the intimate contact required for the translocation of pre-synthesized effector molecules ( Figure 10 ) . The phagocytosis requirement for effector translocation by L . pneumophila has consequences for its environmental lifestyle . Indeed , it is believed that amoebae are natural hosts for L . pneumophila providing a critical environment for its replication and survival [67] . L . pneumophila may only translocate its effectors when residing in a phagocytic membrane-bound compartment or once phagocytosis has been initiated . The translocated effectors can thereafter alter this compartment so as to create a vacuolar environment permissive for L . pneumophila replication . In addition , effector translocation will only be triggered by a potential host cell energetically competent to perform phagocytosis . Therefore relying phagocytosis to trigger translocation ensures that it is occurring only under conditions that could result in a successful infection , and thus , avoid delivery of effector to a host cell that cannot support replication . Interestingly , translocation of a Vibrio cholerae type VI secretion effector also requires internalization by host cells [68] . This is also somehow reminiscent of activation of the SPI-2 type III secretion system of Salmonella following internalization by macrophages [69] . Regardless of the secretion system used for translocating effector proteins , bacterial pathogens that interact with phagocytes may have evolved strategies to ensure that translocation occurs only in the phagosomal/endosomal microenvironment . Chemical genetic screening is a successful strategy to identify host cell functions that are required for effector translocation by L . pneumophila . Our study was limited to the initial interaction of the bacteria with host cells but this approach could be applied to the later stages of infection . The commercial availability of annotated libraries of specific inhibitors and FDA-approved drugs will certainly lead to additional studies using chemical genetic screening . Chemical genetic screening should be considered as a additional tool to cellular microbiologists and provides an alternative approach to RNAi-mediated identification of host cell factors required for a bacterial infection .
J774A . 1 and THP-1 cells were obtained from ATCC and routinely cultivated in RPMI 1640 ( Invitrogen ) supplemented with 10% fetal bovine serum ( FBS ) . CHO cells expressing the human FcγRIIA or the signaling deficient mutant of Y2F/Y3F [56] were cultivated in Ham's F12 nutrient mixture ( Invitrogen ) containing 10% FCS and 300 µg/mL G418 . Phagocytosis inhibitors were obtained from Biomol ( Plymouth Meeting , PA ) , solubilized in DMSO and used at the following concentrations : Cytochalasin B ( 10 µM ) , latrunculin B ( 10 µM ) , LY294002 ( 40 µM ) , wortmannin ( 2 µM ) and nocodazole ( 25 µM ) . L . pneumophila strains were grown in liquid media ACES [N- ( 2-acetamido ) -2-aminoethanesulfonic acid]-buffered yeast extract ( AYE ) or on solid media ACES-buffered charcoal yeast extract ( CYE ) plates . Chloramphenicol and kanamycin were used respectively at 5 µg/mL and 50 µg/mL . Rabbit polyclonal anti-Legionella antibodies were obtained by immunizing rabbit with purified major outer membrane protein ( MOMP ) [70] . All of the experiment described here were performed with L . pneumophila Philadelphia-1 derived strain JR32 [71] or with KS79 [16] , a constitutively competent comR mutant of JR32 . A dotA deficient strain of KS79 was constructed by transforming KS79 with genomic DNA extracted from the JR32 dotA::Tn903dIIlacZ strain LELA3118 [71] . Plasmids expressing β-lactamase effector protein fusions were constructed as previously described [16] . Briefly , PCR product of the effector gene was digested with appropriate restriction enzymes and cloned in the KpnI-SmaI-BamHI-XbaI polylinker of pXDC61 . Plasmids were transformed into KS79 or KS79 dotA by natural transformation [72] . Bacterial lysates were prepared from L . pneumophila suspension used for translocation assays ( see below ) . Aliquots were boiled for 5 min . in SDS-PAGE sample buffer and subjected to denaturing polyacrylamide gel electrophoresis . Proteins from SDS-polyacrylamide gels were electrophoretically transferred to nitrocellulose sheets ( Schleicher and Schuell ) and subsequently stained with Ponceau S ( Sigma ) to check the loading of the lanes . Sheets were analyzed by Western blotting with monoclonal antibody directed to the TEM-1 β-lactamase ( 5 µg/mL , QED Bioscience ) as a primary antibody and an anti-mouse peroxidase conjugate ( 20 nG/mL , Pierce ) as secondary antibody . Nitrocellulose sheets were revealed with the SuperSignal® West Dura detection system ( Pierce ) and Biomax films ( Kodak ) . Translocation assay in J774 or CHO FcR cells were performed as previously described [16] . Briefly , 24H prior to infection J774 cells grown in RPMI 1640 ( Invitrogen ) containing 10% FCS were seeded in black clear-bottom 96 well plate at 1×105 cells/well . CHO cells were grown in Ham's F12 nutrient mixture ( Invitrogen ) containing 10% FCS and seeded in black clear-bottom 96 well plate at 5×104 cells/well . When the infections were performed in presence of antibodies or inhibitors , J774 or CHO cells were pre-incubated for 30 min . prior to infection in complete media containing the anti-Legionella antibodies ( 1∶200 dilution ) and/or inhibitors . L . pneumophila strains carrying the various blaM fusions were grown on CYE plates containing choramphenicol ( 5 µg/mL ) and then streaked on CYE plates containing chloramphenicol and 0 . 5 mM IPTG and grown for 24H to induce expression of the hydrid proteins . Bacteria were resuspended in RPMI 1640 or F12 nutrient mixture to obtain varying MOI ( assuming OD = 1 is about 1 . 4×109 cfu/mL ) and each well is infected with 10 µL of the suspension . After centrifugation ( 900 g , 10 min . ) to initiate bacterial-cell contact the plate was shifted to 37°C and incubated for one hour in a CO2 incubator . Cell monolayers were loaded with CCF4 by adding 20 µl of 6× CCF4/AM solution ( LiveBLAzer™-FRET B/G Loading Kit , Invitrogen ) containing 15 mM Probenecid ( Sigma ) . The cells were incubated for 2 hours at room temperature , fluorescence was quantified on an Victor microplate reader ( Perkin-Elmer ) or Infinite M200 plate reader ( TECAN ) with excitation at 405 nm ( 10-nm band-pass ) , and emission was detected via 460-nm ( 40-nm band-pass , blue fluorescence ) and 530-nm ( 30-nm band-pass , green fluorescence ) filters . Translocation was expressed as the ratio of fluorescence emitted at 460 nm and 530 nm ( Emission ratio 460/530 ) . Screening of the bioactives libraries was conducted at the National Screening Laboratory for the Regional Centers of Excellence in Biodefense and Emerging Infectious Disease ( Boston , MA ) . On the day preceding the infection J774 cells in were seeded in black clear-bottom 384 well plate ( Costar ) at 3×104 cells/well in 25 µL of RPMI 1640 containing 10% FCS . L . pneumophila carrying the blaM-LepA fusion was grown on CYE plates containing choramphenicol ( 5 µg/mL ) and then streaked on CYE plates containing chloramphenicol and 0 . 5 mM IPTG and grown for 24H to induce expression of the hybrid protein . Libraries of bioactives were arrayed in 384-well plates at 5 mG/mL in DMSO and 0 . 1 µL of the molecule solution were transferred per well of the plates containing the J774 cells . Bacteria were then resuspended in RPMI 1640 to OD = 0 . 21 ( 3×108 bacteria/mL ) each well is infected with 5 µL of the suspension . After centrifugation ( 900 g , 10 min . ) to initiate bacterial-cell contact the plate was shifted to 37°C and incubated for one hour in a CO2 incubator . Cell monolayers were loaded with CCF4 by adding 6 µl of 6× CCF4/AM solution ( LiveBLAzer™-FRET B/G Loading Kit , Invitrogen ) containing 15 mM Probenecid ( Sigma ) . The cells were incubated for 2 hours at room temperature and fluorescence was quantified on an Victor microplate reader ( Perkin-Elmer ) . Screening was carried out in duplicate . IC50 determination were performed similarly using 2 . 5-fold serial dilution of the considered molecules in 384 well plates . The dose-response data were fitted with the GNU General Public Licensed software QtiPlot using the four parameter logistic model according to the Assay Guidance Manual Version 5 . 0 ( Eli Lilly and Company and NIH Chemical Genomics Center ) . Sheep red blood cell ( RBC ) were washed in PBS and resuspended in RPMI at at 5×107 RBC/mL and 200 µL were distributed in 96 well plates . Legionella from overnight AYE cultures were resuspended in RPMI at 1×109/mL . The RBC were infected with 50 µL of the bacterial suspension ( MOI = 5 ) by centrifugation at 600 g for 5 minutes and then incubated at 37°C for up to one hour . Where indicated , CCCP was added to the bacterial∶RBC mixture immediately prior to centrifugation . After the incubation , the mixtures of bacteria and RBC were resuspended and then centrifuged again at 600 g for 5 minutes . The absorbance of hemoglobin in the supernatants was then measured at 415 nm . Effect of CCCP ( 5 µM ) on bacterial ATP levels was measured on the same bacterial suspension used in RBC lysis experiment . Before addition of CCCP a 20 uL aliquot was removed and added to 2 µL TCA 10% . After a 5 minute incubation , 20 uL of Tris-Acetate 1 M pH 7 . 75 were added followed by the addition of 160 µL ice-cold H2O . The same procedure was used immediately after addition of CCCP and after 15 , 30 and 60 minutes incubation period at 37°C . ATP levels were quantified using Promega ENLITEN® ATP Assay System Bioluminescence Detection Kit . ATP levels after addition of CCCP were expressed relatively to the untreated sample . E coli and L . pneumophila phagocytosis was measured by trypan blue quenching as previously described [40] , [41] . Heat-killed E . coli were fluorescent labeled using fluorescein isothiocyanate ( FITC ) [73] . L . pneumophila were fluorescein-labeled with 5 , 6-Carboxyfluorescein succinimidyl ester ( FSE ) as previously described [22] . In contrast to fluorescein isothiocyanate ( FITC ) the FSE reagent does not compromise bacterial viability and allows labeling of live L . pneumophila [22] . L . pneumophila from 1 mL overnight cultures in AYE were washed three times in 50 mM potassium phosphate ( pH 8 . 0 ) and resuspended in 1 ml 50 mM potassium phosphate ( pH 8 . 0 ) . FSE was solubilized in DMSO at 10 mG/mL and 10 µL were added to the bacterial suspension . The bacterium-FSE mixtures , in 1 . 6-ml plastic centrifuge tubes , were periodically inverted throughout a 20-min incubation at room temperature . The reaction was terminated by resuspending the bacteria in M63 salts and washed three times in M63 salts . Live bacteria were finally resuspended at 2×108 cfu/mL in complete RPMI media and fluorescence of the fluorescein-labeled bacteria ( 10 µL sample ) was quantified on an Victor microplate reader ( Perkin-Elmer ) with excitation at 485 nm ( 10-nm band-pass filter ) and emission at 530-nm ( 30-nm band-pass filter ) . 24H prior to infection J774 cells grown in RPMI 1640 ( Invitrogen ) containing 10% FCS were seeded in black clear-bottom 96 well plate at 1×105 cells/well . Before the infection , media was replaced with fresh complete RPMI 1640 alternatively containing phagocytosis inhibitors and cells were incubated for 30 minutes . Each well is then infected with 10 µL of the bacterial suspension ( MOI = 20 ) . After centrifugation ( 600 g , 10 min . ) to initiate bacterial-cell contact the plate was shifted to 37°C and incubated for 30 min . in a CO2 incubator . The media was then removed media and replaced with 50 µL/well of a trypan blue solution ( 0 . 25 mg/mL trypan blue , 0 . 9% NaCl , 13 mM citrate buffer pH 4 . 4 ) to quench the fluorescence of non-internalized bacteria . After a 1 min . incubation at room temperature fluorescence of the internalized bacteria was quantified on an Victor microplate reader ( Perkin-Elmer ) with excitation at 485 nm ( 10-nm band-pass filter ) and emission at 530-nm ( 30-nm band-pass filter ) . Data were expressed as the percentage of fluorescence of input bacteria that is resistant to trypan blue quenching ( fluorescence input bacteria/fluorescence internalized bacteria ×100 ) . Alternatively , bacterial internalization in the presence of inhibitors is expressed as the percentage of internalization of the untreated sample . Phagocytosis assay by immunofluorescence microscopy were performed as by Hilbi et al . [46] . An IPTG-inducible GFP-expressing plasmid for L . pneumophila was constructed by cloning a EcoRI/HindIII-digested PCR product of gfp+ in pMMB207C giving pXDC31 . Gfp-expressing JR32/pXDC31 strain used for the infections was grown to stationary phase in AYE broth containing 0 . 5 mM IPTG to induce Gfp expression . Before infection , the bacterial cultures were filtered through a 5 µm filter to remove filamentous bacteria and then diluted in RPMI 1640 . J774 cells on polylysine-coated round coverslips in 24-well plates were infected with bacteria at an MOI of 20 . Alternatively J774 cells were preincubated with polyclonal anti-Legionella antibodies ( dilution 1∶200 ) in complete RPMI 1640 for 30 minutes . The bacteria were centrifuged onto the phagocytes ( 700 g , 10 min ) to synchronize infection and incubated for another 30 min at 37°C . Infected macrophages were washed five times with DPBS and fixed for 15 min with DPBS containing 3 . 7% formaldehyde hydrolyzed from paraformaldehyde . The fixed cells were washed three times , blocked for 30 min with 5% non-fat milk in DPBS and incubated for 1 h with a rhodamine-conjugated rabbit anti-L . pneumophila Philadelphia-1 antibody , diluted 1∶100 in blocking buffer . After washing five times , the coverslips were mounted onto microscopy slides using the mounting media Vectashield Hardset ( Vector Laboratories ) . The samples were viewed with a 100X oil immersion phase-contrast objective on an inverted fluorescence microscope ( Nikon Eclipse TE200 ) equipped with fluorescein and Texas red filter sets . THP-1 cells in exponential growth were electroporated with siRNA duplexes to human CD45 ( ptprc ) obtained from Santa-Cruz biotechnology and Qiagen using Amaxa's Nucleofector® technology . THP-1 cells ( 1×106 cells ) were resuspended in 100 µL of Nucleofector® solution V containing 2 µg of siRNA and electroporated with program V-01 . Fresh media containing 10 ng/mL phorbol 12-myristate 13-acetate ( PMA ) was added to the electroporation cuvette and cells were allowed to recover and differentiate in 96-well ( 200 µL/well ) for 48H . Translocation assays were then performed as described for J774 cells . CD45 protein levels were analyzed by western-blot using anti-CD45 polyclonal antibody ( Santa Cruz Biotechnology ) . BMM were obtained from wild-type and PtprjTM−/TM− Ptprc−/− knockout C57BL/6 mice . BMMs were prepared by culturing mouse BM cells in BMM media ( RPMI-1640 with 10% FCS and 10% culture supernatant from L929 CMG cells producing M-CSF ) . Macrophages were used for experiments between days 5 and 8 of culture . For translocation and uptake assays , BMMs at day 5 or 6 were plated in 96-well tissue culture plates ( Costar ) in BMDM media at 1×105 per well . BMM were obtained from two individual mice per genotype . Binding assays were performed with BMM plated at 1×106 cells/well in 24-well plates . Cell monolayers were pre-cooled to 4°C and infected with L . pneumophila JR32 at an MOI of 20 . After centrifugation ( 1000 g , 10 min . , 4°C ) , L . pneumophila was allowed to interact with macrophages for 30 min . at 4°C to prevent phagocytosis . Unbound L . pneumophila were removed by five washes with ice-cold PBS , the cell monolayer was then lysed with 1 mL of distilled water and serial dilutions were spread on CYE plates for enumeration of bound L . pneumophila . 24H prior to infection J774 cells grown in RPMI 1640 ( Invitrogen ) containing 10% FCS were seeded in black clear-bottom 96 well plate ( Corning ) at 1×105 cells/well . The day of the experiment J774 cells were pre-loaded with CCF4 as follow . Cells were washed once with CO2-independent media ( Gibco Invitrogen Corporation , Cat . No . 18045 ) supplemented with 20 mM L-glutamine . Media then was replaced with 100 µL of CO2-independent media supplemented with L-glutamine and 10% FCS ( complete CO2IM ) plus 20 µL of 6X CCF4/AM solution ( 6 µM CCF4/AM , 20 mM probenecid in 5% v/v solution B and 67% v/v solution C prepared as described by the manufacturer , LiveBLAzer™-FRET B/G Loading Kit - Invitrogen ) and cells were incubated 40 min . at 28°C . Solution B and C are from LiveBLAzer™-FRET B/G Loading Kit and are respectively 100 mg/mL Pluronic®-F127 , 0 . 1% acetic acid in DMSO and 24% w/w PEG 400 , 18% TR40 in volume in water . Cells were then washed once with wash media ( 2 µM CCF4/AM - without solution B and C , 4 mM probenecid , 20 mM L-glutamine in CO2-independent media ) and wash media was replaced with 120 µL of complete CO2IM containing 2 µM CCF4/AM , 15% v/v solution C and 4 mM probenecid . Bacteria from CYE plates ( 5 µg/mL chloramphenicol and 0 . 5 mM IPTG ) were resuspended in CO2IM to obtain various MOI ( assuming OD = 1 is about 1 . 4×109 cfu/mL ) and each well is infected with 10 µL of the suspension . After centrifugation ( 900 g , 10 min . ) to initiate bacterial-cell contact the plate was plated into a plate reader ( Infinite M200 , Tecan ) preset at 37°C and the infections took place in the plate reader . Cells were excited at 405 nm and fluorescence of substrate ( CCF4 ) and product ( released coumarin moiety of CCF4 ) was recorded respectively at 530 nm and 460 nm at 120 seconds intervals . Assays were carried out in triplicate wells and data were collected with Magellan software v6 . 4 ( Tecan ) and then automatically processed in Excel ( Microsoft ) essentially as described by Mills et al . [57] : Data from triplicate wells were averaged and fluorescence values of blank ( well without cells ) were subtracted from fluorescence values recorded at 460 nm and 530 nm . The 460/530 nm ratio was calculated and smoothed with a moving average in a 5 points window . The product concentration ( [P] , arbitrary units ) were calculated as previously described [57] : [P] = ( Praw−Pblk ) / ( S0−Sblk ) where Praw is the product fluorescence measured at 460 nm; Pblk , background fluorescence at 460 nm; S0 , measured substrate fluorescence at 530 nm at T = 0; Sblk , background fluorescence at 530 nm . S0 normalizes the well-to-well variation in number of J774 cells . The rate of product formation , AppV , values were extracted from the data by subtracting each [P] ( t ) with its predecessor , [P] ( t-1 ) , divided by 120 seconds , which is the time interval between each two measurements . AppVmax is the highest rate of product formation reached during the translocation process . | Many bacterial pathogens subvert the cellular functions of their host by translocating effector proteins into specific cells . L . pneumophila primarily targets the alveolar macrophage in its human host or the unicellular protozoa in its natural environment . The bacterium uses a Type IVB secretion system called the Icm/Dot system to translocate its effectors . In contrast to other injection devices , effector secretion by the Icm/Dot system cannot be triggered without the involvement of a target cell . We hypothesize that activity of the Icm/Dot system responds to some signaling or functional activation by the target cell . To identify the host cell function required for activity of the Icm/Dot system we used a small molecule-mediated perturbation strategy called chemical genetics . We screened more than 2 , 500 annotated small molecules to identify inhibitors of L . pneumophila effector translocation in the macrophage . Many of these molecules inhibited known host cell factors involved in phagocytosis . We also identified host cell factors specifically required for L . pneumophila phagocytosis . We further show that phagocytosis of L . pneumophila by the macrophage is required to trigger effector translocation by the Icm/Dot system . Our data indicate that participation of the target cell is required to generate an intimate contact that stimulates effector translocation by the Icm/Dot system . The host cell participation in the effector translocation process has implications in the environmental lifestyle of L . pneumophila . We propose that relying on an active host cell process to stimulate translocation provides L . pneumophila with a test for the fitness of the potential host cell . This could prevent the unwanted delivery of L . pneumophila effectors into non-productive hosts . | [
"Abstract",
"Introduction",
"Results",
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"Methods"
] | [
"chemical",
"biology/small",
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"chemistry",
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] | 2009 | Chemical Genetics Reveals Bacterial and Host Cell Functions Critical for Type IV Effector Translocation by Legionella pneumophila |
Gestational alcohol exposure causes fetal alcohol spectrum disorder ( FASD ) and is a prominent cause of neurodevelopmental disability . Whole transcriptome sequencing ( RNA-Seq ) offer insights into mechanisms underlying FASD , but gene-level analysis provides limited information regarding complex transcriptional processes such as alternative splicing and non-coding RNAs . Moreover , traditional analytical approaches that use multiple hypothesis testing with a false discovery rate adjustment prioritize genes based on an adjusted p-value , which is not always biologically relevant . We address these limitations with a novel approach and implemented an unsupervised machine learning model , which we applied to an exon-level analysis to reduce data complexity to the most likely functionally relevant exons , without loss of novel information . This was performed on an RNA-Seq paired-end dataset derived from alcohol-exposed neural fold-stage chick crania , wherein alcohol causes facial deficits recapitulating those of FASD . A principal component analysis along with k-means clustering was utilized to extract exons that deviated from baseline expression . This identified 6857 differentially expressed exons representing 1251 geneIDs; 391 of these genes were identified in a prior gene-level analysis of this dataset . It also identified exons encoding 23 microRNAs ( miRNAs ) having significantly differential expression profiles in response to alcohol . We developed an RDAVID pipeline to identify KEGG pathways represented by these exons , and separately identified predicted KEGG pathways targeted by these miRNAs . Several of these ( ribosome biogenesis , oxidative phosphorylation ) were identified in our prior gene-level analysis . Other pathways are crucial to facial morphogenesis and represent both novel ( focal adhesion , FoxO signaling , insulin signaling ) and known ( Wnt signaling ) alcohol targets . Importantly , there was substantial overlap between the exomes themselves and the predicted miRNA targets , suggesting these miRNAs contribute to the gene-level expression changes . Our novel application of unsupervised machine learning in conjunction with statistical analyses facilitated the discovery of signaling pathways and miRNAs that inform mechanisms underlying FASD .
Transcriptome-level approaches such as RNA-Seq capture an expression-level snapshot of an experimental system . RNA-Seq is an important discovery platform that generates insights for targeted hypothesis development and testing . However , gene-level analysis provides limited insight into transcriptomic regulation , in part because analytical tools often exclude transcripts represented by splicing variants and altered exon representation [1] . Gene-level analyses can also misrepresent fold-changes . For example , a gene may have two upregulated and two downregulated exons , and thus yield in a net result of no fold-change difference in abundance between the treatment and control . Understanding these exon-level differences offers novel insights into regulatory mechanisms that are otherwise lost during gene-level analysis [1] . Additionally , statistical methods that emphasize transcript-level significance create a loss of information when prioritizing transcripts by their p-values . When analyzing the big data sets that emerge from RNA-Seq , it is a cumbersome task to narrow down tens of thousands of exon targets to those having the greatest biological relevance . Although statistical models provide a system for condensing such information to the most statistically significant genes or exons , there often remains several thousand genes or exons having a false discovery rate ( FDR ) below 0 . 1 or even 0 . 05 . Statistical cutoffs alone weakly inform how to prioritize or further narrow a still-extensive data set for follow-up analysis , and the biological importance of a gene or exon does not always correlate with the strength of the p-value . Thus , a more comprehensive approach is necessary to corroborate the statistical findings and thereby reduce , e . g . , an RNA-Seq dataset of 80 , 000 exons to 5–10 candidate genes/exons for functional analysis . One approach is to employ the combination of statistical and machine learning methods to optimize a solution to the most likely biologically relevant information . By utilizing statistical inference approaches in conjunction with the mathematical models provided in unsupervised machine learning algorithms , the rigor of the two models introduces less bias when selecting the few genes/exons of interest . When applying an unsupervised machine learning model to a highly dimensional dataset , such as that from RNA-Seq , mathematically hidden patterns are learned by the algorithm that are otherwise not identifiable by the researcher [2] . Developing such methodologies is essential for analyzing and interpreting transcriptomic responses to an intervention or stressor . One such stressor is alcohol . Prenatal alcohol exposure ( PAE ) is a leading source of neurodevelopmental disability that affects 3% to 5% of U . S . first-graders [3] . Its clinical manifestation , fetal alcohol spectrum disorder ( FASD ) , is typified by growth reduction , deficits in learning and executive function , and a distinct facial appearance [4]; the latter is due to alcohol’s disruption of the neural crest progenitors that form the facial elements [5] . Alcohol alters cellular activity through its direct binding of hydrophilic pockets in select proteins that regulate intracellular signaling; the downstream transcriptional changes enable alcohol to redirect cellular function and fate [6] . Some of these transcription-level changes are mediated by traditional signaling effectors including β-catenin and sonic hedgehog [5] . Other transcriptional changes result from changes in DNA methylation and the altered abundance of both long non-coding RNAs and non-coding micro-RNAs , or miRNAs [7–9]; these latter may have diagnostic utility as biomarkers for alcohol-exposed infants . Using an embryonic avian model that recapitulates the facial deficits that occur in FASD , we utilized RNA-Seq to identify gene expression patterns that potentially inform how alcohol disrupts the development of these neural crest facial progenitors [10 , 11] . Our gene-level analyses of alcohol-exposed early neural folds , which are enriched in neural crest , identified 3422 transcripts having differential expression in response to alcohol , and these mapped to KEGG pathways with enriched representation including ribosomal biogenesis , oxidative phosphorylation , and mTOR , among others [10] . To gain additional insight into these transcriptional changes and their underlying mechanisms , here we apply principal component analysis ( PCA ) and k-means in conjunction with statistical approaches to optimize the discovery of functional exon transcripts . Unsupervised machine learning reduced the biological noise and dimensions of our multivariate RNA-Seq data to a subset of orthogonal variables that best defined the variance among the exon transcripts . This approach identified candidate splicing variants and regulatory motifs that shape cellular responses to alcohol .
The RNA-seq dataset was originally described in Berres et al . [10] . To summarize , it was derived from neural fold-stage ( 4–7 somites ) chicken ( Gallus gallus , strain Special Black ) embryos that were exposed to a pharmacologically-relevant alcohol concentration ( 52 mM for 90 min ) or isotonic saline , followed by a 4 . 5 hr recovery period . The cranial headfolds were isolated 6 hours following the initial alcohol exposure . Following RNA isolation , cDNA synthesis , and quality assurance [10] , paired-end reads ( 75 bp ) were generated on an Illumina Genome Analyzer IIx ( University of Wisconsin Biotechnology Center , Madison , WI ) . The obtained reads were freshly analyzed using the pipeline described below . A schematic of the exon analysis pipeline is shown in Fig 1A . Trimming of the RNA-Seq sequence reads was performed as described in our previous study [10] . The quality of the fastq files was checked in FastQC to ensure there were no overabundant sequences , adapters , or poor sequence quality scores [12] . The fastq sequence files were then aligned to the Gallus gallus 5 . 0 Ensembl reference genome using Bowtie2 [13] , and the resulting SAM file was converted to a BAM file and fed into the subread featureCounts package [14] . Parameters used in the subread featureCounts program included a stringency parameter ( -B ) that ensured the mapping of both paired ends when assigning a count to a specific exon . Additionally , the parameter -f was used to specify feature ( exon ) level counts and not metafeature ( gene ) level counts . Other unique parameters include -p and -s 0 , which correspond to paired end runs and mapping reads either on the forward or reverse strand , respectively . For normalization and statistical analysis , we used the DEXSeq package under the R software v3 . 4 . 4 . DEXSeq is a conservative approach that utilizes a negative binomial distribution with a generalized linear model to adjust for false positive significance values that result from running statistical tests on tens of thousands of exons [1] . The output of the featureCounts program was used as the input for the DEXSeq package . The DEXSeq analysis generated Benjamini-Hochberg ( BH ) adjusted p-values , log2 fold changes , exon base mean expression values , exon usage coefficients , normalized raw counts for each exon , exon coordinates , full and reduced linear regression model statistics , exon transcripts , and exon dispersion estimates , as detailed in the DEXSeq manual [1] . All subsequent statistical and machine learning analyses only utilized BH adjusted p-values below 0 . 1 , or a false discovery rate ( FDR ) of 10% . Due to the DEXSeq analysis pipeline , it is important to note that negative fold changes correspond to genes upregulated by alcohol , and positive fold changes are genes downregulated by alcohol . We isolated upregulated exons and downregulated exons based on the log2 fold change and mapped each exon to its corresponding KEGG pathway ( s ) using the DAVID Functional Annotation Tool v6 . 8 . We applied a principle component analysis with the exon IDs as the observations ( ~7 , 000 exons ) , and all the normalized raw counts and exon usage coefficients as the variables . All exons used in the PCA analysis had a BH adjusted p-value below 0 . 1 from the DEXSeq analysis . The KEGG pathways were used as the supplementary qualitative variable for identification of exon-pathway clusters . We scaled the data using the FactoMineR PCA package to standardize expression values that were measured in different scales ( i . e . exon usage coefficients and read counts ) . A scree plot , a squared cosine quality of representation , and a correlation circle were generated using the factoextra R package . The contribution of an observation to the principal components was calculated using the FactoMineR package , where the squared factor score of the observation was divided by the eigenvalue of the component , resulting in the ratio used for the contribution of an exon [15] . To identify clusters of interest within the dataset , we utilized the Hierarchal Clustering on Principal Components ( HCPC ) algorithm adapted from [16] . The HCPC algorithm under the FactoMineR package combines hierarchal and k-means clustering to partition the observations into the most likely clusters representative of a large multivariate dataset . The HCPC algorithm first uses the Ward criterion for hierarchal clustering on the principal components; the Ward criterion is based on multidimensional variance , making it appropriate for post-PCA clustering [17] . The number of clusters was then determined with initial partitioning of the hierarchal tree , followed by k-means clustering to optimize the final result [17] . In parallel , we performed a separate cluster analysis of the exon dataset using a self-organizing map ( SOM ) / artificial neural network ( ANN ) approach . The optimal number of clusters to partition the dataset was calculated with the wss metric , gap statistic , and silhouette methods . We utilized the Kohonen R package and built our SOM with a 0 . 01 learning rate , 15x10 map , and 15 , 000 epochs . The number of epochs was calculated at the threshold in which the mean distance between an observation and the closest unit neuron decreased and remained stable . The dimensions of the SOM grid were calculated at the point in which the node counts map had a minimized number of empty nodes in the ANN . We then applied hierarchal clustering to view the partitioned clusters . To identify the most likely functionally-relevant miRNAs , we conducted a PCA and k-means clustering analysis on those miRNA-encoding exons having BH adjusted p-values below 0 . 1 . The exon-miRNA loci were identified using the UCSC Gallus gallus 5 . 0 genome browser and included miRNAs that were encoded within a single exon , across two exons , or were within an intron for which the flanking exons were significantly altered . We used miRbase ( release 22 ) to confirm that all these miRNAs were previously validated in vivo [18–20] . The principal component analysis was conducted in the same manner as described above . For the k-means clustering analysis , we utilized the factoextra R package . The optimal number of clusters was determined using the elbow method , in which the within-sum of squares ( wss ) measure was plotted for each value of k clusters ( 1–10 ) . The cutoff of k = 3 was based on the location of the bend in the plot ( S1 Fig ) where the wss measure leveled off and did not add substantial value to the variance explained by the clustering [17] . Calculating the optimal number of clusters using the average silhouette and gap statistic methods yielded an optimal number of k = 2 and k = 4 clusters , respectively , and taking the average between all three methods replicated the k = 3 clusters found with the wss metric . When generating the k-means graph , we ran the algorithm with 50 different random starting points , and the result with the lowest within-cluster variation was selected [17] . The ellipsis drawn around each miRNA cluster was calculated with Euclidean distance . To further validate the miRNAs found in the k-means clusters , we also applied a fuzzy c-means clustering to the dataset . Each miRNA was assigned a probability of belonging to each cluster ( membership coefficient ) . To test for spatial randomness in the data , we assessed the cluster tendency of the miRNA dataset versus a randomly generated dataset using the Hopkins statistic , with a null hypothesis that the dataset was uniformly distributed , and the clustering was due to random chance [21] . A Hopkins statistic ( H ) of 0 . 5 means the data are uniformly distributed because the summations of the mean nearest neighbor distances in the real ∑i=1nxi and randomly generated ∑i=1nyi datasets are close to each other [21] . H=∑i=1nyi∑i=1nxi+∑i=1nyi ( 1 ) Each randomly generated dataset contained the same number of n observations and similar numeric ranges as the exon variables in the miRNA dataset . We also performed a visual assessment of cluster tendency ( VAT ) using the factoextra R package by computing an ordered dissimilarity matrix with a Euclidean distance measure between miRNAs in the dataset . A VAT heatmap was also generated from the random dataset . The SOM neural network analysis could not be applied to the miRNA dataset because it contained too few predictors ( N = 6 ) and observations ( N = 22 ) for it to build a SOM map that contained enough observations per node . This prevented the SOM from properly learning the dataset as it could not reduce the mean distance errors between the observations and the ANN nodes . We identified each miRNA’s gene targets from the TargetScan 7 . 1 Gallus gallus database , and mapped each gene target name to its Ensembl ID using Ensembl’s biomart tool . We ran the resulting Ensembl ID gene list for each miRNA through DAVID’s Functional Annotation Tool v6 . 8 to identify the KEGG pathway clusters shared among the gene targets . In addition , we downloaded the TargetScan 7 . 1 UTR Sequences database and parsed the gene names belonging to the chicken species ID ( 9031 ) . We placed the parsed gene names into biomart and mapped all gene names to their Ensembl gene IDs . This Ensembl gene IDs list ( 10 , 915 genes ) was used as the background genome list in the RDAVID program . Using an approach similar to [20] , we developed the RDAVID program , a custom-built R program ( github . com/abrar-alshaer/RNA-Seq ) that we used to evaluate the likelihood of the miRNA gene targets’ KEGG clusters resulting from random chance . We used the RDAVIDWebService library to programmatically access the DAVID API . In the program , we generated random gene lists of size n ( n = same length of miRNA gene targets list ) by sampling from the background genome list . This process was repeated 1000 times to create 1000 random gene lists of size n . Next , we concatenated all 1000 random lists and mapped the genes to DAVID's Functional Annotation Tool to identify the KEGG pathway clusters and their corresponding p-values . The p-values were obtained using Fisher’s exact test implemented by the DAVID software [22] and plotted by histogram . A schematic of the RDAVID pipeline is shown in Fig 1B .
Using the pipeline depicted in Fig 1A , we identified 6 , 857 exons that had significant differential expression in the comparison of control and alcohol-exposed cranial neural folds . Of these , 4 , 586 were increased and 2 , 271 were decreased in response to alcohol challenge ( GEO accession: GSE115383 ) . These 6 , 857 exons represented 1 , 251 genes , as compared with the 3422 genes we identified as alcohol-responsive when analyzed at the gene level [10] . Of these , 391 genes overlapped between the exon-derived and gene-derived lists ( S1 Table ) . Our initial principal component analysis ( PCA ) attempted to identify pathway-gene interactions at the exon level . However , DAVID’s functional annotation tool does not specifically annotate exons with KEGG classifications; thus , when providing DAVID with an exon list that contains repeated gene IDs , it mapped the repeated genes ( i . e . exons of one gene ) as KEGG classifications with higher fold-enrichments . This led to a hyper-annotation of each exon in which multiple KEGG pathways mapped to incorrect fold-enrichments , further increasing the dataset’s dimensionality and variance such that exon-pathway clusters could not be identified . To resolve this , and because many of the KEGG pathways are subsets of larger biological processes , we instead assigned the DAVID-defined KEGG classifications to one of twenty meta-KEGG clusters based upon biological function , as described in S2 Table , and then repeated the PCA from the DEXSeq output . Analysis of the data using a scree plot , squared cosine quality of representation , and correlation circle affirmed the quality of the algorithm and confirmed that the PCA captured almost all the variance in the dataset within the first and second principal components . The top 50 unique exons IDs contributing to the variance of the principal components ( PC ) , regardless of fold-change , are plotted in Fig 2A and presented in Table 1 , which also includes the contribution of each exon to the variance in dimensions one and two of the PCA . Of these top contributing 50 exons , 40 were downregulated in response to alcohol and only one exon ( within SFRP1 ) was upregulated with a log2 fold change greater than one . Expansion of this analysis to the top 100 or even top 200 exons did not provide additional information to the PCA above that of the top 50 , and again , only 2 of the 100 were upregulated with notable log2 fold changes ( at least greater than 1 ) . These 50 exons represented 42 genes , and of these 13 genes overlapped with the 3 , 422 genes previously identified in our gene-level analysis of this transcriptome set [10] , two of which were the ribosomal proteins RPL39 and RPS20 ( Table 2 ) . Several genes contributed multiple exons to these top 50 and included β-actin ( ACTB , 4 exons ) , cytoplasmic-2-like actin ( ACTG1 , 3 exons ) , glyceraldehyde-3-phosphate dehydrogenase ( GAPDH , 2 exons ) , and claudin-1 ( CLDN1 , 2 exons ) . A separate PCA on the top 50 down-regulated exons ( Fig 2B ) and 50 up-regulated exons ( Fig 2C ) similarly revealed that the up-regulated exons had a weaker impact on the PCA , as reflected in their lower contribution values to the first two dimensions . Thus , the exon-level analysis identified additional exon targets that were not discovered at the gene-level . Moreover , although only 33 . 1% of the differentially-expressed exons were down-regulated , the PCA results suggest that down-regulation was the most significant transcriptional response to alcohol . When we instead used a self-organizing map ( SOM ) approach to cluster our exon-level data , the results replicated our PCA analyses findings and again partitioned the miRNA-encoding exon in ACTB farthest from all other exons ( S2 Fig ) . SOM of the down-regulated and up-regulated exons also generated clusters that were similar to those from the PCA . When we then partitioned the SOM into various clusters using hierarchal clustering , we again replicated the HCPC results ( hierarchal clustering on principal components ) . However , this approach did not add additional information above that obtained from the k-means and HCPC approaches . To place the differentially-expressed exons into a cellular context , and to gain insight into how exonal choice might have emerged , we then asked which KEGG pathways were represented by these top 50 up-regulated and down-regulated exons . We again used the meta-cluster KEGG approach as above , due to the exon annotation limitations of DAVID . In both sets , the most frequently represented KEGG meta-cluster controlled cellular metabolism and encompassed KEGG pathways including mTOR signaling , autophagy , and nitrogen metabolism ( 32 exons up; 26 exons down; Table 3 ) . Other enriched clusters included stress response ( 18 up , 22 down ) , cell adhesion molecules ( 14 up , 23 down ) , ribosomal biogenesis ( 15 up , 10 down ) , and TCA/oxidative phosphorylation ( 10 up , 8 down ) . The ribosome and oxidative phosphorylation KEGG clusters were identified in our previous gene-level analysis [10] , whereas mTOR signaling ( p = 0 . 41; 17 genes ) and focal adhesion ( p = 0 . 078 ) did not achieve significance in that analysis . Within a cluster , the gene lists for both the up-regulated and down-regulated top exons frequently overlapped , and some genes harbored exons that alternately increased and decreased in response to alcohol . For example , seven genes overlapped within the mTOR/autophagy/nitrogen metabolism cluster ( ACTC2L , ACTG1 , EEF1A1 , EIF4G2 , ITGB1 , TUBB4A , TUBB4B ) , six genes overlapped for cell adhesion ( ACTC2L , ACTG1 , CLDN1 , ITGB1 , TUBB4A , TUBB4B ) , and four genes overlapped for ribosome biogenesis ( EEF1A1 , EIF4G2 , RPL39 , SRSF1 ) . Other genes were uniquely represented in the up-regulated ( ACTB , BRCA1 , HSPA8 ) and down-regulated ( HSPA5 , RAN , RAC1 ) exon sets . Thus , alcohol had complex effects upon exon choice within a given gene . Importantly , the PCA approach implicated novel pathways potentially influenced by alcohol , and independently validated those identified in our previous gene-level analysis . Hierarchical clustering of principal components ( HCPC ) of all 6 , 857 exons for both the upregulated ( N = 4 , 586; Fig 3A ) and downregulated ( N = 2 , 271; Fig 3B ) sets identified several clusters and a single distinctive outlier within the downregulated exon set . That downregulated outlier was exon 4 of the β-Actin ( ACTB ) gene and is adjacent the microRNA gga-miR-3533 in exon 5 . Further inspection of the PCA and HCPC results uncovered 30 unique exons with a BH p-value below 0 . 1 that encoded known or predicted miRNAs . Of these , 23 were mapped to the UCSC genome browser , and these represented 19 unique miRNAs . The abundance and annotation for these 23 exons is presented in Table 4 . Most of these miRNA-encoding exons ( 70% ) had a fold-change distinct from the gene-level change , suggesting these exons were differentially regulated . We used the 23 mapped exons to generate a PCA and k-means clustering analysis of the exon transcripts that contain miRNAs in the dataset , to identify which miRNAs explained the most variance among the PCs . Because some of the miRNAs were encoded across spliced exons , or were encoded within an intron , we included any exons that spanned the miRNA locus on the gene . In the first iteration , gga-miR-3064 exon 1 skewed all the other exons to one cluster due to its high normalized transcript abundance; thus , it was excluded from subsequent PCA and k-means clustering analysis . In the reanalysis ( Fig 4A ) , several miRNA-containing exons had high log2-fold changes and a farther distance from the origin , suggesting they may represent functionally relevant miRNAs because they explained more variance among the principal components . Under k-means clustering , the 23 miRNA-containing exons formed three distinct cluster groups ( Fig 4B ) that were primarily defined by shared transcript abundance . The five most abundant miRNA exons grouped into cluster 2 , the three miRNA exons in cluster 3 were the next most abundant , and the fourteen miRNA exons in cluster 1 were the least abundant . We also applied a fuzzy c-means clustering and replicated the same results , except gga-miR-6667 ( exon 15 ) belonged to cluster 3 instead of cluster 1 , and gga-miR-3064 ( exon 13 ) shared a membership coefficient near 50% between clusters 1 and 3 . To test that the miRNA k-means clusters were not due to random chance , we performed a visual assessment of cluster tendency ( VAT ) for a random dataset and for our miRNA exons dataset ( Fig 4C ) . As expected , miRNAs within a PCA-defined cluster also clustered together in the VAT . The VAT revealed additional cluster subgroups , such that gga . mir . 3064 ( exon 11 ) , gga . mir . 6667 , and gga . mir . 6604 were more interrelated , as were gga . mir . 1665 , gga . mir . 6706 ( exon 1 ) , gga . mir . 6619 , gga . mir . 6542 , and gga . mir . 6604 ( exon 28 ) . Certain miRNAs also maintained consistent relationships with miRNAs in another cluster; for example , in the VAT heatmap gga . mir . 3533 shared an opposite relationship with all 14 miRNAs in cluster 1 . This is consistent with the finding of gga-miR-3533 exon 4 as a distinct outlier from all other exons . These groupings suggest relationships within and between miRNAs that may inform their means of regulation or their functional relevance in response to alcohol exposure . We also evaluated the dataset’s spatial randomness using the Hopkins statistic ( H ) . For a randomly generated dataset , H = 0 . 499 and was consistent with a uniformly distributed dataset that was clustered due to random chance . For the miRNA exons dataset , H = 0 . 15 and we rejected the null hypothesis and concluded that the clusters were not due to random chance . To gain insights into the potential biological significance of these differentially represented exon-containing miRNAs , we used TargetScan7 . 1 to extract candidate gene targets for each individual miRNA and mapped these candidate genes into DAVID to identify the KEGG pathways most likely to interact with each miRNA . However , the TargetScan results are predicted targets and most have not been experimentally validated . To eliminate those KEGG pathways that arose from random chance due to false positive gene targets , and thereby identify pathways that were truly enriched , we first ran our RDAVID pipeline ( Fig 1B ) using a randomly generated gene target list of the same size ( n = 1000 ) as the miRNA candidate gene targets list [20] . We repeated this 1000 times and mapped all random gene lists to their KEGG pathways; this did not require the meta-cluster approach because each miRNA represented a single gene . Histograms of p-values for two statistically significant KEGG pathways among the miRNA exons , cell adhesions ( includes focal adhesion and cell adhesion molecules KEGG pathways ) and hedgehog signaling , are presented in Fig 5 . For cell adhesion , p-values for the randomly generated gene-pathways were uniformly distributed ( Fig 5A ) , whereas those for the miRNA dataset were mostly below 0 . 01 ( Fig 5B ) , suggesting the cell adhesion pathway enrichment was not due to false enrichment from the predicted targets . Parallel analysis of the next-most abundant pathways , insulin signaling and endocytosis , yielded similar results and suggested their emergence also did not represent false enrichment . In contrast , for the hedgehog signaling pathway , p-values for the randomly generated gene targets were not uniformly distributed and were similar to the distribution of p-values in our dataset ( Fig 5C ) . This indicated that their presence in the miRNA data set ( Fig 5D ) likely represented a false discovery . The low abundance of these targets likely contributed to this type-1 error . Following this RDAVID analysis , the most significantly enriched KEGG pathways that emerged from the candidate gene target list for each miRNA are presented in S3 Table . Several pathways emerged repeatedly , and the most commonly represented pathways included focal adhesion ( 15 miRNAs ) , regulation of actin cytoskeleton ( 12 ) , insulin signaling ( 10 ) , insulin resistance ( 9 ) , MAPK signaling ( 9 ) , and ErbB signaling ( 8 ) . Although these pathways also were present within all three miRNA clusters identified using k-means , the three clusters differed in the specifics of their pathway enrichment . For the high-abundance miRNAs in cluster 2 ( Fig 6A ) , the most enriched pathway targeted insulin signaling ( 128 genes ) and several pathways crucial to neural crest development including MAPK signaling ( 128 genes ) , focal adhesion ( 117 genes ) , actin cytoskeleton ( 116 genes ) and melanogenesis ( 23 genes ) . Other predicted pathways included known alcohol targets in this model including calcium signaling ( 55 genes ) and Wnt signaling ( 53 genes ) [5 , 10] . The pathways in miRNA cluster 3 ( Fig 6B ) paralleled those of cluster 2 and similarly emphasized insulin signaling ( 90 genes ) , cell migration ( focal adhesion , 88 genes; actin cytoskeleton , 64 genes ) , and MAPK signaling ( 37 genes ) , as well as Wnt signaling ( 35 genes ) and TGF-β signaling ( 34 genes ) . MiRNAs in cluster 1 ( Fig 6C ) had the lowest abundance and a different target profile that emphasized endocytosis ( 44 genes ) , focal adhesion ( 41 genes ) , Wnt signaling ( 38 genes ) , MAPK signaling ( 36 genes ) , and regulation of actin cytoskeleton ( 36 genes ) . Overall , the differentially enriched miRNAs consistently targeted a limited set of pathways crucial for neural crest development . They also targeted pathways known to be dysregulated by alcohol in this cell population , implicating these miRNAs as candidate contributors to those mechanisms .
The most important finding from our study is that the use of exon level analysis in conjunction with unsupervised machine learning generates novel insights that were otherwise lost in gene-level analyses with statistics alone . Reliance on rankings of p-values can lead to prioritizing exons by significance , and this may not directly correlate with functional relevance . Such approaches in analysis of RNA-Seq data make it difficult to select exons of interest with the most likely biological relevance . While statistical tests are often effective at drawing inferences from a dataset , these inferences are based on assumptions from a given model that are likely to best fit the dataset in question [2] . Unlike statistical methods based on a conical model of inference , unsupervised machine learning assumes little to no information about the dataset in question . For example , principal component analysis ( PCA ) reduces the biological noise in the data set and identifies hidden patterns within and between exons to identify correlated variables . By implementing a principal component analysis ( PCA ) , we reduced the dimensionality of our multivariate RNA-Seq dataset into 2–3 principal components that correspond to most of the variance in the data . To further identify relationships among the exons an unsupervised clustering algorithm , such as k-means , provides insight as to which exons share the closest mathematical distance , and this in turn can elucidate biologically relevant relationships . An unexpected problem arose during the pre-processing of the exon data for implementation in the initial PCA analysis , and we discovered a limitation in the application of the DAVID functional annotation tool to exome analysis . Specifically , DAVID’s KEGG pathway annotations do not consider exon level mapping; hence , when assigning exons to KEGG pathways the annotation is collapsed to the gene ID and the KEGG becomes over-enriched . Moreover , since KEGGs are assigned by gene level information without specificity for exon transcripts or splicing variants , each exon receives all the KEGGs for all the exons associated with that gene . For example , if gene X had 10 exons , and gene X mapped to 45 KEGGs , each exon will receive all 45 KEGG annotations , resulting in 450 annotations for one gene ( gene X ) . This creates hyper-annotation of KEGGs to each exon and significantly increases the error due to variance introduced into the machine learning algorithm . It is imperative to note that all machine learning approaches rely on the fine balance between the bias-variance tradeoff . Error due to variance results in underfitting of the machine learning algorithm where the model cannot adequately learn the dataset , therefore causing a higher probability of false prediction of exon classifications in the model [17] . Conversely , error due to bias results in overfitting of the dataset and may cause normally random trends in the dataset to be used as classification criteria in the model algorithm [17] . For this reason , we implemented the meta-KEGG approach to balance the bias-variance tradeoff in our PCA and k-means algorithms . This approach funneled the long list of KEGG annotations for each exon into 1–5 functional classifications , and this better balanced the ratio of bias and variance introduced into the algorithm with our dataset . We further enhanced the rigor of the machine learning models by utilizing only those exons with an FDR adjusted p-value below 0 . 1 . Corroborating these statistical approaches with unsupervised machine learning enhanced the identification of novel differentially expressed exons . In support of the validity of our machine learning approach , as this paper was finalized two new publications describe additional machine learning approaches to analyze RNA-Seq data with respect to alternately-spliced transcripts [23] and the prediction of genetic expression profiles [24] . However , the approach described in [24] utilizes supervised machine learning algorithms to predict environmental exposure from genetic and epigenetic expression profiles . Supervised methods were similarly used in [23] to predict healthy/disease phenotypes , tissue types , and other sample features . These methods differed from our approach as we utilized unsupervised algorithms for discovery of exome-level differential expression patterns , rather than feature prediction; therefore , without previous training of our model we limit assumptions about the RNA-Seq dataset . Application of an unsupervised neural network to the exon dataset obtained similar results; however , this approach was limited to the exome dataset due to the high number of observations . To our knowledge , this is one of a few handful of studies that directly compare gene-level and exon-level outcomes from RNA-Seq , and the first to study this with respect to alcohol exposure . Importantly , the exon-level analysis recapitulated major findings from the gene-level analysis and thus endorses the validity of this machine learning approach for exome discovery . Both approaches identified KEGG pathways representing ribosome biogenesis , oxidative phosphorylation , and spliceosome as having significantly altered enrichment in response to alcohol; expression in these pathways was suppressed [10 , 11] . However , the exon-level analysis generated a richer profile of these expression-level changes , and it captured additional pathways that only trended toward statistical significance in the gene-level analysis , including mRNA surveillance , cell cycle , and protein processing in the endoplasmic reticulum . The comparison of KEGG pathways for up-regulated exons and genes was less concordant and this was explained by the PCA , which found a weaker contribution of the upregulated exons to the data variance . Overall , the exon-level approach confirmed major findings from the gene-level analysis , and it highlighted that gene-level based interpretations do not fully capture the complexity of transcriptomic regulation . Several of these pathways ( cell adhesion , regulation of actin cytoskeleton , cell migration , ribosome biogenesis , mRNA splicing ) were also enriched in two independent microarray analyses of alcohol-exposed mouse neural folds having a parallel developmental stage [25 , 26] , endorsing that these changes represent conserved responses to alcohol across amniotes . An unexpected finding from the exon-level PCA was the identification of a single exon , exon 4 within ACTB , which was highly differentiated from the other top 100 exons . This exon turned out to encode a miRNA , gga-miR-3533 , and additional investigation revealed that many of the top contributing exons that responded to alcohol also encoded miRNAs . Our prior , gene-level analysis of this same data set identified miR-3533 but not these other sixteen miRNAs [10] , likely because the statistical weighting approach minimizes significance when only a single exon or flanking exons is differentially expressed within that gene . Because RNA-Seq directly quantifies exome abundance , our approach enabled the retrospective capture of miRNAs from the same cDNA pool used to quantify mRNA , without the need for specialized extractions or microarrays selective for these short sequences . Endorsing this approach , the majority of these miRNA-encoding exons were differentially expressed relative to their parent genes , and thus were missed when the individual exon responses were collapsed during our prior gene-level analysis . MiRNAs are crucial regulators of gene expression . These small , non-coding RNAs average 21–23 nucleotides in size and typically target specific sequences within the 3’ end of mRNAs to effect translational repression or RNA destabilization; some miRNAs instead bind 5’ mRNA sequences to enhance translation and stability [27] . Because a single miRNA can target multiple transcripts , miRNAs are a powerful mechanism to rapidly redirect cellular activity at the translational level and at a low energetic cost . Non-coding RNAs including miRNAs are significant mediators of alcohol’s action , and they contribute to its pathological sequelae including neurotoxicity , teratogenicity , hepatotoxicity , inflammation , and to mechanisms of addiction , tolerance , and withdrawal [7 , 28 , 29] . MiRNAs also have clinical relevance to FASD , and a panel of miRNAs isolated from the maternal serum exosome strongly predicts the severity of birth outcomes in alcohol-exposed pregnancies [29] . The identification of alcohol-responsive miRNAs within the early cranial neural fold , which is vulnerable to alcohol’s neurotoxicity , is consistent with that work and extends the relevance of miRNA dysregulation to this early embryonic period . The seventeen miRNAs having significantly altered representation in this model were independently validated in chick embryos including these stages [18 , 20] , but have not been previously identified as alcohol-responsive . While most of these miRNAs are unique to G . gallus , miR-3533 is also described for B . taurus , and miR-3064 is orthologous in multiple vertebrate species including human . Six of these miRNAs are located within genes linked with craniofacial and/or neurodevelopmental impairment when mutated in humans: ACTB , CDK10 , CDK6 , INO80 , SZT2 , and ZNF462 [30–35] . Three additional genes , DDX5 , DHX30 and RRP12 , participate in ribosome biogenesis [36–38] . Loss-of-function in ribosome biogenesis causes facial deficits [39] and is mechanistically linked to the alcohol-induced facial deficits and neural crest losses studied here [10] . DHX30 ( MIM: 616423 ) , which harbors miR-6710 in Exon 1 , is an RNA helicase enriched in neural progenitors and is essential for mitochondrial ribosome biogenesis . DHX30 loss-of-function in mouse is embryolethal by day 9 . 5 , and missense mutations within its core helicase produce intellectual disability and facial anomalies [37 , 40] . A second RNA helicase , DDX5 , also houses an alcohol-responsive miRNA , miR-3064 , that is conserved across vertebrates . The DDX5 gene product , also known as p68 RNA helicase , mediates splicing of rRNA , mRNA , and miRNA , and it is a crucial transcriptional regulator [41]; it was also suppressed by alcohol in mouse neural folds [25] . Interestingly , miR-3064 has inhibitory interactions with mRNA encoding human telomerase reverse transcriptase , or hTERT [42] , which promotes cell invasion by upregulating Snai2 . Alcohol induces Snai2 in these cells to accelerate their epithelial-mesenchymal transformation [43] , and the reduced miR-3064 observed here suggests a mechanism that might explain this response . Although these miRNAs have not been specifically linked to facial morphogenesis , their presence suggests an alternate means by which their domicile genes could influence cranial development . The KEGG enrichments identified for these miRNAs largely replicates an independent functional mapping for these chick miRNAs [20] , and many of these pathways are crucial for normal craniofacial development [44 , 45] . Several of the pathways potentially targeted by these alcohol-responsive miRNAs mediate neural crest processes that are vulnerable to alcohol including cell cycle inhibition , apoptotic deletion , reduced induction , and altered migratory capacity [5 , 46] . Furthermore , these enriched pathways were targeted by multiple miRNAs , and this redundancy suggests they are especially important for cellular alcohol responses . As one example , two frequently represented KEGG pathways were Focal Adhesion ( #4510 , 12 miRNAs ) and Actin Regulation ( #4810 , 12 miRNAs ) . Cranial neural crest progenitors migrate from their dorsal neuroepithelial origin to occupy the ventrally positioned facial anlage , and alcohol reduces their migration by reducing focal adhesion formation and disrupting the actin cytoskeleton [5 , 46 , 47] . MiRNA-mediated regulation of cytoskeletal assembly offers a mechanism to explain how these migratory changes can persist long after the alcohol is cleared . Further contributing to these facial deficits is the widespread elimination of neural crest progenitors through alcohol’s activation of calcium-mediated apoptosis [5 , 48 , 49] . We showed previously that the pharmacologically-relevant alcohol level used here stimulates the rapid , G-protein-mediated release of intracellular calcium stores and activation of CaMKII within these cells , and blockade of this calcium transient or CaMKII fully prevents their alcohol-induced apoptosis [48 , 49]; thus , enrichment for multiple miRNAs that may influence calcium signaling are consistent with this mechanism . The majority of these ( gga-miR-6602-5p , gga-miR-6604-5p , gga-miR-6667-5p , gga-miR-6619-5p ) target 5’ sequences in their predicted targets , suggesting an activating translational role [27] and a means by which these calcium signals could have a lasting impact upon these alcohol-exposed cells , and in complementation with CaMKII activation [49] . This calcium transient acts as a non-canonical Wnt signal through the CaMKII-mediated destabilization of nuclear β-catenin , and restoration of the latter’s transcriptionally activity rescues neural crest progenitors from alcohol-mediated apoptosis [5 , 50] . Seven of the alcohol-responsive miRNAs target Wnt signaling ( #4310 ) , reflecting the Wnt pathway’s central role in neural crest survival , migration , and differentiation [44 , 45] . Using a mouse neural crest model , Chen and colleagues showed that alcohol also activates p38 MAPK and decreases expression of miR-125b to stabilize p53 [51 , 52] . While gga-miR-125b did not emerge from this analysis , nine of our miRNAs have enriched selectivity for MAPK signaling ( #4010 ) and offers an additional means to modulate this pathway’s activity . These miRNAs also offer novel insights into how alcohol alters neural crest development and survival . Signaling through ErbB governs neural crest pathfinding and migration , effected in part through downstream phosphorylation of Akt [53 , 54] , and loss of ErbB or its ligand neuroregulin disrupts neural crest migration and cranial ganglia and melanocyte development . Multiple alcohol-responsive miRNAs had predicted sequence specificity for pathways relevant to ErbB activity including ErbB signaling itself ( #4012 , 8 miRNAs ) , ten targeting insulin signaling ( #4910 , 10 miRNAs ) , and melanogenesis ( #4916 , 1 miRNA ) . Although ErbB is not a known alcohol target in the embryo , alcohol-ErbB interactions contribute to mammary oncogenesis [55] and its emergence here is consistent with alcohol’s well-documented suppression of neural crest migration [5 , 47] . Also related to this is the identification of seven miRNAs linked to FoxO ( #4068 ) , a family of transcriptional effectors that operate downstream of ErbB/MAPK , as well as metabolic pathways including insulin and oxidative phosphorylation , to mediate cellular responses to stress . Alcohol upregulates FoxO in models of bone fracture healing [56] and intestinal barrier dysfunction [57] , and its emergence here is consistent with that work . It may also further inform our β-catenin results , as FoxO can bind β-catenin to redirect and limit its Wnt transcriptional activity [58] . Taken together , alcohol’s dysregulation of multiple miRNAs in these neural folds is consistent with its pleiotropic actions and reflects its ability to interact with multiple proteins to redirect cellular activities . Despite this , the pathways enriched as potential miRNA targets represented a core set of signals crucial for normal development of these cells and known to be alcohol-responsive , either in this model or in other cell lineages . The internal consistency of these findings further validates machine-learning as an unbiased approach to elucidate alcohol mechanisms . This work has several limitations , the most notable being that the aforementioned limitations in the DAVID software preclude exon-level KEGG pathway analysis , due to the multiplicative expansion of annotations when multiple exons per gene are represented . Although our work-around clustered the KEGGs into functional clusters and recapitulated our gene-level findings , it was also informed by that prior analysis . Further efforts in omics database management and annotation are needed to address this challenge . The other major limitation is that the predicted gene targets of these miRNAs identified in our in silico approach require functional validation . However , their relevance in this model is endorsed because these predicted pathways target known processes that are crucial to craniofacial morphogenesis and are known targets of alcohol . In conclusion , the application of statistical and machine learning algorithms to a complex exome dataset identified novel mechanistic candidates that were overlooked by approaches that emphasize p-value rank . It represents a method to distill the biological noise in a complex omic system and identify patterns that are otherwise missed , and its serves as a powerful tool for examination of exon/gene-pathway interactions . | Genomic research often yields an overwhelming amount of information . Accurate models for predicting and validating multivariate big data in genomics distill complex relationships and interactions . A prime example is fetal alcohol spectrum disorders , the largest known cause of neurodevelopmental disability affecting nearly 5% of children in the United States . Alcohol exposure during pregnancy leads to complex epigenetic and transcriptomic modifications , subsequently impairing signaling pathways in neural and morphologic development . Identifying transcriptomic mechanisms regulating alcohol’s teratogenicity during embryonic development is crucial for understanding variable phenotypic outcomes . This allows for the advancement of future therapeutic interventions that may mediate alcohol’s effects . Most genomic studies do not incorporate various levels of transcriptomic analysis , spanning gene , exon , and splicing variants , because it is difficult to meaningfully consolidate all those analyses . Therefore , enhancing machine learning approaches that corroborate traditional statistical methods can yield novel relationships , and is important for robust functional experiments that proceed from such genomic studies . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [] | 2019 | Exon level machine learning analyses elucidate novel candidate miRNA targets in an avian model of fetal alcohol spectrum disorder |
Dengue virus ( DENV ) is one of the most important arthropod-borne pathogens that cause life-threatening diseases in humans . However , no vaccine or specific antiviral is available for dengue . As seen in other RNA viruses , the innate immune system plays a key role in controlling DENV infection and disease outcome . Although the interferon ( IFN ) response , which is central to host protective immunity , has been reported to limit DENV replication , the molecular details of how DENV infection is modulated by IFN treatment are elusive . In this study , by employing a gain-of-function screen using a type I IFN-treated cell-derived cDNA library , we identified a previously uncharacterized gene , C19orf66 , as an IFN-stimulated gene ( ISG ) that inhibits DENV replication , which we named Repressor of yield of DENV ( RyDEN ) . Overexpression and gene knockdown experiments revealed that expression of RyDEN confers resistance to all serotypes of DENV in human cells . RyDEN expression also limited the replication of hepatitis C virus , Kunjin virus , Chikungunya virus , herpes simplex virus type 1 , and human adenovirus . Importantly , RyDEN was considered to be a crucial effector molecule in the IFN-mediated anti-DENV response . When affinity purification-mass spectrometry analysis was performed , RyDEN was revealed to form a complex with cellular mRNA-binding proteins , poly ( A ) -binding protein cytoplasmic 1 ( PABPC1 ) , and La motif-related protein 1 ( LARP1 ) . Interestingly , PABPC1 and LARP1 were found to be positive modulators of DENV replication . Since RyDEN influenced intracellular events on DENV replication and , suppression of protein synthesis from DENV-based reporter construct RNA was also observed in RyDEN-expressing cells , our data suggest that RyDEN is likely to interfere with the translation of DENV via interaction with viral RNA and cellular mRNA-binding proteins , resulting in the inhibition of virus replication in infected cells .
Dengue virus ( DENV ) is a mosquito-borne virus belonging to the genus Flavivirus , which is a large family of enveloped , positive-stranded RNA viruses . DENV has four antigenically distinct serotypes ( DENV-1 to -4 ) ; all serotypes are able to cause dengue fever ( DF ) and dengue hemorrhagic fever ( DHF ) in humans . While primary infection with one of the four DENV serotypes is often asymptomatic or causes self-limiting DF , due to the presence of non- or sub-neutralizing antibodies produced during the primary infection , a secondary infection with a different serotype increases the risk of a more severe form of dengue infection , such as life-threatening DHF and dengue shock syndrome ( DSS ) . However , there is currently no effective vaccine or specific antiviral treatment available for dengue prevention and control [1] . At the cellular level , DENV infection begins with entry via receptor-mediated endocytosis , followed by particle disassembly to release an ~11-kb single-stranded RNA genome into the cytoplasm . The viral genomic RNA contains an open reading frame ( ORF ) encoding a single polyprotein , which is flanked by a capped 5’ untranslated region ( UTR ) and a non-polyadenylated 3’UTR , and serves as a template for the translation of a viral precursor protein . The single polypeptide is then cleaved co- and post-translationally into three structural ( C , prM , and E ) and seven non-structural ( NS ) proteins ( NS1 , NS2A , NS2B , NS3 , NS4A , NS4B , and NS5 ) . The structural proteins are used for the assembly of virus particles , while the NS proteins are mainly involved in synthesis of the viral RNA genome and the further translation process during DENV infection [2] . Many host factors have been reportedly implicated in the replication of DENV; however , the biological relevance of those factors in in vivo infection and the pathogenesis of DENV has not been fully addressed [3 , 4] . Meanwhile , it has also become apparent that host cells may harbor factors whose expressions potentially restrict DENV replication . In this regard , the induction of the interferon ( IFN ) response is considered to be the first line of defense against an invading DENV [5] . DENV infection is able to induce the IFN response , probably through the recognition of viral genomic RNA by intracellular receptors such as TLR-3 , RIG-I , and MDA-5 [6–8] , which in turn triggers a cellular antiviral state that suppresses the early replication and subsequent spread of DENV . Several in vitro studies have reported that the establishment of a DENV infection is capable of antagonizing IFN signaling cascades by employing viral NS proteins [9–14] . However , pretreatment of human cells with type I ( IFN-α and IFN-β ) or type II ( IFN-γ ) IFNs has been shown to limit the replication of DENV [15] . Also , mice deficient in IFN receptors [16] or an IFN signaling component , signal transducer , and activator of transcription 2 ( STAT2 ) [17 , 18] are reported to be highly susceptible to DENV infection . Given additional evidence that DHF/DSS patients have higher levels of circulating IFN-α and IFN-γ as compared to DF patients [19–21] , IFN response is likely to play a key role in controlling DENV replication in vivo [22] . The antiviral effect of IFN is known to be mediated by interferon-stimulated genes ( ISGs ) , which disrupt various steps of virus replication [23] . So far , hundreds of genes have been classified as ISGs; among them , a number of ISGs have been demonstrated to restrict divergent families of viruses , including flaviviruses [23–26] . As for DENV , gene overexpression and knockdown studies have reported that several human ISGs , including interferon-inducible transmembrane proteins ( IFITMs ) , ISG15 , ISG20 , Viperin , and BST2 , have suppressive effects against in vitro virus infection [27–32] . Additionally , a recent large-scale screening study using a library of ISG comprising more than 350 genes revealed that at least 10 ISGs were potent cellular inhibitors of DENV replication that modulate DENV infection in the early or late stage of virus replication [33] . Although the precise mechanisms of action of the anti-DENV ISGs are not yet clear , many of them are likely to function as effector molecules that directly interfere with viral components during infection [23] . Therefore , we believe that understanding how IFN-inducible effector molecules restrict virus infection will be the molecular basis for developing new antiviral agents and vaccines against DENV . This study aimed to identify new cellular suppressive factors against DENV infection by a gain-of-function screen using a cDNA library derived from type I IFN-treated human cells . We then found that a previously uncharacterized cellular gene , C19orf66 , named RyDEN ( Repressor of yield of DENV ) , conferred resistance to all serotypes of DENV in human cells . RyDEN was considered to be an ISG whose expression was essential for the full activity of the type I IFN-mediated suppression of DENV replication . Other than its impact on DENV , overexpression of RyDEN in human cells limited the replication of several RNA and DNA viruses . Interestingly , RyDEN was found to form a complex with cellular mRNA binding proteins , PABPC1 and LARP1 , which are required for the efficient replication of DENV . Moreover , RyDEN was likely to interact with DENV RNA and impair the protein translation of viral RNA . Our data demonstrate a novel mechanism of ISG in the inhibition of DENV infection .
It has been demonstrated that pretreatment with type I IFN protects human cells from DENV infection in vitro [15 , 34] . In order to identify anti-DENV effector molecule ( s ) in the IFN response , a pool of cDNA was generated from the mRNA of HeLa cells that had been treated with type I IFN ( a mixture of human IFNα and ω [Sigma] ) and transferred to a lentiviral vector , pYK005C [35] , by the Gateway recombination system ( Fig 1A ) . The mean sizes of the IFN-derived cDNA in the Gateway entry ( i . e . , pDONR22 ) and destination ( pYK005C ) vectors were 1 . 43±0 . 74 and 1 . 29±0 . 63 kbp , respectively ( Fig 1B ) . Infectious lentiviral vectors carrying the cDNA library were produced as a vesicular stomatitis virus G protein ( VSV-G ) pseudotype and used to transduce a human hepatoma cell line , Huh7 . 5 , which exhibited a massive cytopathic effect with DENV-2 infection ( S1 Fig ) . Transduced cells were then challenged with DENV-2 ( Singapore isolate EDEN2 3295 [36] ) at a multiplicity of infection ( MOI ) of 1 , and surviving cells were selected ( Fig 1A ) . From the initial screen , a total of 52 surviving cell clones were collected and further verified for their resistance against DENV infection . Plaque assay revealed that , among the 52 cell clones , inhibition of DENV-2 replication was still observed in 32 clones ( Fig 2 ) . Reduced replication of DENV in the clones was also confirmed by immunofluorescent analysis ( IFA ) using anti-double-stranded ( ds ) RNA antibodies ( Fig 1C ) . PCR amplification and subsequent sequencing analysis using a BLAST search revealed that cDNA from 19 of 32 DENV-resistant clones ( 59 . 3% ) contained an ORF of a previously uncharacterized gene on chromosome 19 , C19orf66 , in the integrated pYK005C vector genome ( Fig 1D and 1E ) . Because the inhibitory effect of C19orf66 on DENV replication was confirmed by the following experiments , we named this gene Repressor of yield of DENV ( RyDEN ) . RyDEN/C19orf66 is an eight-exon gene located on genomic region 19p13 . 2 . This gene spans approximately 7 . 1 kb in the human genome and encodes a 291 amino acid protein in its ORF ( Fig 1E ) . However , the functional characteristic of the protein product of the RyDEN gene is unknown . A secondary structure prediction by the JPred program ( http://www . compbio . dundee . ac . uk/jpred/ ) represented RyDEN as consisting of eight α-helixes and seven β-strands ( Fig 1F ) . The RyDEN amino acid sequence was also predicted to contain a nuclear localization signal ( NLS , 121–137 , by cNLS Mapper [http://nls-mapper . iab . keio . ac . jp/cgi-bin/NLS_Mapper_form . cgi] ) , a nuclear export signal ( NES , 261–269 , by NetNES [http://www . cbs . dtu . dk/services/NetNES/] ) , a zinc-ribbon domain ( 112–135 ) that is defined by CXXC ( H ) -15/17-CXXC [37] and a coiled-coil motif ( 261–286 ) ( Fig 1F ) . In addition , a characteristic glutamic acid ( E ) -rich domain was found in the C-terminal region ( 274–286 , Fig 1F ) . In order to verify the inhibitory action of RyDEN against DENV , the ORF of RyDEN was cloned back into a lentiviral vector as an N-terminal V5-tagged gene and used to create human cell lines ( Huh7 . 5 and HepG2 ) that stably expressed V5-RyDEN ( Fig 3A ) . When the cell lines were infected with three doses of DENV-2 ( MOIs of 0 . 1 , 1 , and 10 ) , virus replication was significantly suppressed , reducing the virus titer by ~43-fold , as compared to the control protein ( V5-tagged bacterial dihydrofolate reductase [DHFR] ) -expressing cells ( Fig 3B ) . Although a more potent inhibitory effect of V5-RyDEN expression was observed in HepG2 cells than in Huh7 . 5 cells ( Fig 3B ) , it was presumed that this difference occurred due to a higher susceptibility of Huh7 . 5 cells to DENV infection or a higher expression of V5-RyDEN in HepG2 cells ( Fig 3A ) . DENV inhibition by RyDEN expression was also observed in HEK293T cells ( S2 Fig ) . The ability of RyDEN to inhibit three other serotypes of DENV ( Singapore isolates [36] ) and another strain of DENV-2 ( New Guinea C [NGC] ) was also examined . Results showed that the replication of DENV-1 , -2 , -3 , and -4 were inhibited 12 . 3- , 72 . 7- , 20 . 0- , and 92 . 3-fold , respectively ( Fig 3C ) . Using an RNA interference experiment , we next investigated whether endogenous expression of RyDEN acts as a suppressor against DENV . To create RyDEN knockdown cells , lentiviral vectors expressing three different small hairpin RNA ( shRNA ) sequences against RyDEN mRNA ( sh1425 , sh3151 , and sh5890 ) or a non-targeting control shRNA ( shCtrl ) were constructed and used to transduce HeLa cells . Quantitative reverse transcription-PCR ( qRT-PCR ) analysis showed that the expression levels of endogenous RyDEN mRNA in shRNA1425- , sh3151- , and sh5890-expressing cells were 33 . 3 , 67 . 8 , and 99 . 2% , respectively , as compared with those of shCtrl-expressing cells ( Fig 3D ) . Following infection of the knockdown cell lines with DENV-2 at an MOI of 1 revealed that virus replication was significantly stimulated by RyDEN silencing , which was in accordance with the depletion efficiency of RyDEN mRNA in the three shRNA cell lines ( Fig 3E ) . This enhancement of DENV replication by the knockdown of endogenous RyDEN was also observed in HepG2 and Huh7 . 5 cells ( S3 Fig ) . In order to test the specificity and reproducibility of the shRNA experiment , we also created sh1425- and shCtrl-expressing cell lines using HepG2 cells . Then , sh1425-susceptible wild-type ( WT ) or sh1425-resistant mutant ( 1425R ) V5-RyDEN was expressed in the cell lines by the transduction of the lentiviral vector system ( Fig 3F ) . The created cells were challenged with DENV-2 . When compared to untransduced ( parental ) shRNA cells , both V5-RyDEN ( i . e . , WT and 1425R ) suppressed DENV replication at a similar levels in shCtrl cells , whereas , in sh1425 cells , a significant reduction of virus replication was observed only with 1425R RyDEN expression but not with WT RyDEN expression ( Fig 3G ) . Taken together , these data conclude that the expression of RyDEN confers resistance to DENV infection in human cells . Since RyDEN was first identified by a gain-of-function screen using a type I IFN-treated HeLa cell-derived cDNA library ( Fig 1 ) , we examined whether RyDEN was upregulated by IFN treatment in human cells . Immunoblotting analysis using a commercially available anti-RyDEN antibodies ( anti-C19orf66 rabbit IgG purchased from Abcam ) revealed that RyDEN expression was indeed enhanced in HeLa cells in response to the increasing concentration of IFN-α/ω ( Fig 4A ) . In addition to the type I IFN treatment , the expression of RyDEN was also upregulated by treatment with type II ( IFN-γ ) and type III ( IFN-λ ) IFNs ( Fig 4B ) . It is notable that the specificity of the anti-RyDEN antibody on treatment with IFNs was confirmed by knockdown of RyDEN mRNA in sh1425-expressing HepG2 cells ( Fig 4B ) . Quantitative analysis of RyDEN mRNA by qRT-PCR showed that upregulation of RyDEN expression by type I IFN treatment was also observed in all of the human cell lines tested; however , the induction level varied among cells ( S4 Fig ) . Next , we evaluated how RyDEN expression could contribute to IFN-mediated anti-DENV functions using the RyDEN knockdown cell line . As was observed in a previous report [15] , pretreatment with IFN-α/ω suppressed the replication of DENV-2 104-fold in control shRNA ( shCtrl ) -expressing HepG2 cells ( Fig 4C , white bars ) . However , in HeLa cells in which endogenous RyDEN had been depleted by sh1425 , type I IFN treatment inhibited DENV infection by only 29% ( Fig 4C , gray bars ) . Thus , these results indicate that RyDEN is an ISG that plays a critical role in the IFN-mediated anti-DENV response in human cells . In order to test the possibility that RyDEN may be a key component in the IFN signaling pathway , we compared gene expressions of a variety of ISGs between RyDEN and control protein-expressing cells . HepG2 cells were transfected with V5-tagged RyDEN or control BAP -expressing plasmid DNA , and 48 h after transfection , the level of mRNA expression of the ISGs ( LY6E , ISG15 , ISG54 , and RIG-I ) and IFN-β were measured by qRT-PCR analysis . The results showed that no significant activation in the mRNA expression of these genes was observed with the V5-RyDEN transfection , whereas the transfection of a stimulator of the interferon gene ( STING ) , an endoplasmic reticulum-associated adaptor molecule regulating the IFN production [38] , upregulated the ISGs and the IFN-β gene ( Fig 4D ) . Additionally , a parallel experiment using RyDEN knockdown ( sh1425 ) and control ( shCtrl ) HeLa cells revealed that gene expressions of ISG15 , ISG54 , RIG-I , and IFN-β upon treatment with IFN-α/ω were not reduced by the depletion of endogenous RyDEN ( Fig 4E ) . A recent study reported a unique regulation of ISG expression , in which some host RNA-binding proteins activated the translational process of ISG mRNA [39] . Hence , we also tested whether RyDEN was involved in the translational regulation of ISGs . An immunoblotting analysis against ISG15 , which has been reported to restrict DENV replication [30] , showed that a comparable level of ISG15 protein expression following type I IFN treatment was detected in RyDEN knockdown ( sh1425-expressing ) and control ( shCtrl-expressing ) HeLa cells ( Fig 4F ) . In summary , these results indicate that RyDEN is not a regulator of the IFN response . To gain insight into the process of DENV replication that is affected by RyDEN , we first assessed the efficiency of virus entry using previously reported entry assays [34 , 40] . V5-tagged RyDEN or control protein ( Renilla luciferase [RLuc] ) -expressing Huh7 . 5 cells were exposed to DENV-2 at an MOI of 5 at 37°C for 2 h , which allowed binding and internalization of virions , and then treated with a high-salt concentration alkaline solution on ice to remove uninternalized viruses , followed by additional washing with PBS . qRT-PCR analysis targeted against the DENV 3’UTR to measure the amount of internalized viruses showed that RyDEN expression did not influence the virus binding/entry process ( Fig 5A ) . To confirm the observation that the post-entry process is affected by RyDEN , an indirect assay , in which viral genomic RNA was transfected to cells to bypass the binding , entry , and uncoating steps of DENV replication , was performed [34 , 41] . Naked viral RNA was purified from a culture supernatant that contained infectious DENV-2 and was transfected to V5-RyDEN or control protein-expressing Huh7 . 5 cells . When infectious titers of DENV produced from transfected cells were analyzed by plaque assay 3 days after transfection , the production and subsequent replication of DENV was significantly inhibited by the expression RyDEN ( Fig 5B ) . Next , we examined the inhibitory effect of RyDEN on intracellular events in DENV replication using a reporter luciferase-expressing DENV-2 subgenomic RNA replicon system ( DENrepPAC2A-Rluc [42] ) . The transient transfection of V5-RyDEN-expressing plasmid DNA into A549 cells harboring the DENV replicon exhibited a significant and dose-dependent suppression of the luciferase activity as compared with the V5- BAP control-expressing plasmid transfection ( Fig 5C ) . As indicated in previous studies [42 , 43] , treatment with two antiviral components , small interference RNA ( siRNA ) against DENV-2 NS3 ( siNS3 , Fig 5C ) and mycophenolic acid ( MPA ) that has been demonstrated to prevent viral RNA replication ( S5 Fig ) , resulted in drastic reductions in the replicon signal . Although the inhibition of DENV replicon activity by a transfection of RyDEN was less effective when compared to the NS3 siRNA or MPA treatment , it was still comparable to the level of inhibition by type I IFN treatment ( S5 Fig ) . We further monitored the kinetics of DENV RNA accumulation in virus-infected cells . When total DENV RNA ( T ) was measured by qRT-PCR analysis using a random primer for RT , a slight and insignificant decrease in the amount of viral RNA was detected in RyDEN-expressing cells 6 h after infection ( 2 . 3 times lower than in control protein-expressing cells , Fig 5D ) . Nevertheless , further and significant reductions in the level of total viral RNA were observed 18 and 24 h after infection ( Fig 5D ) . When the level of negative-strand DENV RNA ( N ) as measured by qRT-PCR analysis using 3’UTR-specfic forward primer for RT was compared , a significant decrease in the amount of negative-strand RNA was also detected 18 and 24 h after infection in RyDEN-expressing cells ( Fig 5D ) . However , the kinetics of accumulating total and negative-strand DENV RNA in the V5-RyDEN-expressing cells appeared to be similar to those in control cells ( Fig 5D ) . Taken together , these data suggest that RyDEN somehow inhibits intracellular events of DENV replication independent of the entry , uncoating , assembly , or negative-strand RNA synthesis of a virus . In order to search for additional clues regarding the function of RyDEN , we attempted to identify the interacting partners of RyDEN using an affinity purification-mass spectrometry approach . For this purpose , HepG2 cell lines stably expressing RyDEN or control protein ( BAP ) were fused by lentiviral vector transduction with an N-terminal tandem affinity purification ( TAP ) tag that contained two IgG binding units [44] . TAP-fused RyDEN and its associated proteins were recovered from the extract of the HepG2 cell lines using IgG Sepharose beads under physiological conditions [44] . SDS-PAGE and subsequent silver staining analysis showed that TAP-RyDEN , but not the TAP-BAP , were specifically co-purified with a >70 kDa band ( Fig 6A ) . Mass spectrometry analysis then identified the >70 kDa band as a poly ( A ) -binding protein cytoplasmic 1 ( PABPC1 ) . Likewise , as we shall see below , mass spectrometry analysis revealed that the additional protein band with a molecular weight mass of around 150 kDa was the La motif-related protein 1 ( LARP1 ) . The >40-kDa protein band was confirmed to be TAP-RyDEN ( Fig 6A and S6 Fig ) . PABPC1 belongs to the evolutionally conserved PABP family of proteins that bind the 3’ poly ( A ) tail of the mRNA and have multiple roles in translation and mRNA stability [45] . PABPC1 is expressed widely in a variety of human tissues [46] and is reported to have multiple roles in cytoplasmic mRNA function [47 , 48] . Interestingly , a previous biochemical study by Polacek et al . demonstrated that PABP binds to the DENV 3’UTR RNA in vitro , despite the lack of a poly ( A ) tail in the viral genome , suggesting the modulatory activity of PABP in DENV mRNA translation [49] . LARP1 is one of the La-motif related proteins that is a superfamily of RNA-binding factor , which is conserved in eukaryotes [50] . This RNA-binding protein was first identified in Drosophila , and is reported to be involved in spermatogenesis , embryogenesis , and cell cycle progression [51–53] . In mammalian cells , it has been demonstrated that LARP1 regulates cell division , apoptosis , and cell migration [54] . It should be noted that LARP1 is found in a complex of certain poly ( A ) -binding proteins and also interacts with PABPC1 in Drosophila and human cells [53–55] . To examine the role of these cellular mRNA-binding proteins in DENV infection , HepG2 cells were subjected to gene silencing by siRNA against PABPC1 and LARP1 , resulting in 10 . 0- and 2 . 9-fold reductions in mRNA expression , respectively , as measured by qRT-PCR analysis ( Fig 6B and 6C ) . When siRNA-transfected cells were infected with DENV-2 at an MOI of 1 , we found that the level of virus replication was significantly decreased in both knockdown cells as compared with the replication in non-targeting control siRNA ( siCtrl , Fig 6D and 6E ) , implying that PABPC1 and LARP1 positively impact DENV replication . Note that , at least in the PABPC1 siRNA-transfected cells , severe growth defects , which might lead to limited DENV replication , was not likely to be caused by the depletion of PABPC1 ( S7 Fig ) . We sought to determine the RyDEN domain that is required for interaction with PABPC1 . To map the binding domain , a series of V5-tagged RyDEN containing N- and C-terminally truncated mutants was constructed ( Fig 7A ) and stably expressed in Huh7 . 5 cells . In this experiment , V5-tagged RLuc was used as a control protein to confirm the specificity of RyDEN-PABPC1 interaction . Co-immunoprecipitation using anti-V5 antibodies followed by immunoblotting using anti-PABPC1 antibodies confirmed that full-length ( WT ) RyDEN interacted with PABPC1 ( Fig 7B , middle panel , lane 2 ) . Importantly , interaction with PABPC1 was also detected with RyDEN-truncated mutants 1–250 , 51–291 , and 101–291 ( lanes 3–5 ) , whereas RyDEN mutant 151–291 was not co-precipitated with PABPC1 ( lane 6 ) . Therefore , this result indicates that the domain of interaction with PABPC1 is located in RyDEN’s middle region , which is between amino acid positions 102–150 . As described above , RyDEN was predicted to possesses a sequence resembling a bipartite NLS ( 121RRVPQRKEVSRCRKCRK137 , Fig 1F ) , which was called an NLS-like ( NLS-L ) sequence in this study . An IFA using V5-RyDEN-exppressing HepG2 cells and anti-V5 antibodies showed that a higher concentration of ectopically expressed RyDEN was found in cytoplasm ( Fig 7C ) . When intracellular distribution of RyDEN was analyzed by IFA using a newly generated anti-RyDEN rabbit serum , endogenous RyDEN that had been induced by type I IFN localized mainly in the cytoplasm of HepG2 cells ( Fig 7D ) . This cytoplasmic localization of RyDEN was observed in several other human cell lines as well ( S8 Fig ) . By contrast , a parallel IFA using V5-RyDEN truncation mutant ( Fig 7A ) -expressing cells revealed that the localization of RyDEN to the nucleus was only observed when the C-terminal domain encompassing the putative NES sequence was deleted ( V5-RyDEN 1–250 , Fig 7E ) . These data indicate that , in the presence of C-terminal NES , the NLS-L sequence may not function as an active NLS to accumulate RyDEN in the nucleus . Meanwhile , since the NLS-L sequence is located in the domain of RyDEN’s interaction with PABPC1 ( 102–150 , Fig 7A ) , we examined whether the NLS-L mutations influenced the binding of RyDEN to PABPC1 . To this end , we constructed a site-directed mutant of RyDEN , in which positively charged arginine ( R121 , R122 , R126 , R131 , R133 , and R136 ) and lysine ( K127 , K134 , and K137 ) residues in NLS-L were changed to alanine ( 121AAVPQAAEVSACAACAA137 , Fig 7A ) . Intriguingly , immunoprecipitation analysis using lysates of V5-tagged WT or NLS-L mutant RyDEN-expressing HepG2 cells revealed that the binding efficiency of RyDEN to PABPC1 was decreased by the mutation of NLS-L ( Fig 7F ) . More importantly , when the replication of DENV-2 in each cell line was compared , although some inhibition of virus replication was still observed in the NLS-L mutant-expressing cells , its inhibitory effect was 25 . 4-fold lower than that obtained in WT RyDEN-expressing cells ( Fig 7G ) . These results suggest that interaction with PABPC1 participates in RyDEN’s anti-DENV activity . The functional interaction of RyDEN with cellular mRNA-binding proteins PABPC1 and LARP1 ( Figs 6 and 7 ) prompted us to test whether RyDEN was recruited to DENV RNA during infection . To analyze the association of RyDEN with DENV RNA , RNA immunoprecipitation ( RIP ) assay was performed . HepG2 cells stably expressing V5-tagged protein were infected with DENV-2 at an MOI of 5 , and cell lysates were subjected to immunoprecipitation 6 h after infection . In this experiment , we needed to harvest infected cells at an early time point to recover sufficient amounts of DENV RNA because , at a later time point , the amount of viral RNA synthesis had been shown to be dramatically inhibited by the overexpression of V5-RyDEN ( Fig 5D ) . In fact , a significant reduction in the amount of DENV RNA was already detected in the input fraction of V5-RyDEN-expressing cells 6 h after infection ( Fig 8A ) . Note that a significant reduction of viral RNA was not observed in NLS-L mutant RyDEN-expressing cells ( a 27% reduction relative to V5-DHFR-expressing cells , Fig 8A ) . Cell lysates from V5-tagged WT RyDEN- , NLS-L mutant RyDEN- , and control DHFR-expressing cells were used for immunoprecipitation using anti-V5 antibodies , and the total RNA extracted from immunoprecipitates was detected by qRT-PCR analysis against the DENV-2 3’UTR . When the input fraction and the immunoprecipitates were subjected to an immunoblotting analysis , comparable levels of V5-tagged proteins were found to be pulled down by the immunoprecipitation ( Fig 8B ) . However , as anticipated , immunoprecipitation with V5-RyDEN significantly enriched DENV RNA as compared to the level of viral RNA detected in V5-DHFR immunoprecipitates ( Fig 8C ) . In contrast , immunoprecipitation with the NLS-L mutant of RyDEN , which was not able to impair DENV RNA synthesis 6 h after infection ( Fig 8A ) exhibited only slight enrichment of viral RNA ( not statistically significantly different from the V5-DHFR sample , Fig 8C ) . To further examine the association of RyDEN with DENV RNA , we performed an in vitro RNA-binding assay based on AlphaScreen technology ( PerkinElmer ) . For this experiment , recombinant proteins ( RyDEN and PABPC1 ) were obtained by the wheat germ cell-free protein production system , a eukaryotic cell-based in vitro translation method that allows the generation of properly folded high-quality proteins [56] , because the expression of RyDEN in E . coli was found to be toxic to the bacterial cells . N-terminal FLAG-tagged ( RyDEN WT , RyDEN NLS-L mutant , and control DHFR ) and glutathione S-transferase ( GST ) -tagged ( PABPC1 and control DHFR ) proteins were produced , affinity purified ( S9 Fig ) , and mixed with biotin-labeled DENV-2 3’UTR RNA ( 450 base ) , followed by incubation with streptavidin-coated donor beads , anti-FLAG antibodies , and protein A-conjugated acceptor beads . If FLAG-RyDEN interacts with biotinylated 3’UTR RNA , the reaction bridges the donor and acceptor beads by recognizing the biotin of RNA and FLAG-tagged proteins , respectively , which in turn enables the generation of singlet oxygen ( O2 ( 1Dg ) ) from donor beads upon the illumination and the chemical energy transfer to acceptor beads , resulting in a luminescent AlphaScreen signal ( Fig 8D ) [56] . As shown in Fig 8E , a reaction containing FLAG-RyDEN WT and unlabeled ( i . e . non-biotinylated ) DENV 3’UTR RNA ( Rxn 1 ) or FLAG-DHFR and biotinylated 3’UTR RNA ( Rxn 4 ) gave a negligible background signal in the AlphaScreen assay . When FLAG-RyDEN WT was incubated with biotinylated 3’UTR RNA ( Rxn 5 ) , a significantly increased luminescent signal was detected , while this was also observed in the incubation with biotinylated nonspecific control RNA ( Rxn 2 ) , indicating the RNA-binding property of RyDEN . However , the binding signal between WT RyDEN and biotinylated 3'UTR was significantly enhanced by the presence of GST-PABPC1 ( Rxn 6 ) . The specific interaction between RyDEN and DENV 3'UTR in this reaction was shown by a competition assay using unlabeled 3'UTR RNA as a competitor ( S10 Fig ) . In contrast , the addition of GST-PABPC1 did not change the luminescent signal of FLAG-RyDEN WT and the biotinylated control RNA incubation ( Rxn 3 ) . More importantly , even in the presence of GST-PABPC1 , the RyDEN NLS-L mutant ( Rxn 7 ) , which was shown to have reduced binding activity to PABPC1 ( Fig 7F ) , did not generate the higher interaction signals with biotinylated 3’UTR RNA that were observed in the incubation with RyDEN WT ( Rxn 6 ) . These data , therefore , demonstrate that RyDEN is an RNA-binding protein , and binding specificity to DENV RNA is provided through a complex formation with PABPC1 . The interaction of RyDEN with PABPC1 , an important molecule involved in cellular mRNA translation , led us to hypothesize that RyDEN might interfere with the translation process of DENV RNA . First , in order to investigate the effect of RyDEN expression on global cellular translation , puromycin labeling of newly synthesized proteins was performed using RyDEN-expressing cells [57] . HepG2 cells expressing V5-RyDEN or V5-DHFR were pulsed with puromycin , and cell lysates after the 40 min pulse were subjected to immunoblotting using anti-puromycin antibodies to compare the total protein synthesis of these two cell lines . As evident in control treatments in which cells had been treated with a protein synthesis inhibitor , cycloheximide , before puromycin pulse ( CHX , Fig 9A ) , proteins detected by immunoblotting indicated de novo synthesized proteins that incorporated puromycin during mRNA translation in cells [57] . When the level of puromycin-labeled proteins was compared , there was no obvious difference in the protein synthesis of V5-RyDEN and V5-DHFR-expressing cells ( Fig 9A ) , indicating that the global translation rate was not reduced by the expression of RyDEN . We next examined the ability of RyDEN to interfere with protein synthesis from DENV RNA by employing a DENV-2-based luciferase reporter construct , DENrepPAC2A-Rluc [42] . DENV reporter RNA was transcribed in vitro transcribed using linearized construct DNA in the presence of an m7GpppA cap analogue and transfected to V5-RyDEN- or V5-DHFR-expressing HepG2 cells . As shown in Fig 9B , the RNA transfection of WT DENV reporter replicon ( DENrepPAC2A-Rluc WT ) exhibited reduced luciferase activity in V5-RyDEN-expressing cells when compared to V5-DHFR-expressing control cells 4 and 8 h after transfection . Importantly , diminished luciferase activity in the RyDEN-expressing cells at the early time points were also observed by RNA transfection of a mutant DENV reporter construct , DENrepPAC2A-Rluc GVD , in which the GDD motif in the active site of the RNA-dependent RNA polymerase ( RdRp ) had been changed to GVD ( Fig 9B ) [58] . Since the GVD mutation in the NS5 RdRp is reported to abolish viral RNA replication [58] , the luciferase activity was considered to reflect the level of protein production from mRNA of the transfected construct . Although the inhibitory effect of RyDEN on the reporter protein production was relatively modest as compared to the inhibition levels observed in DENV replication ( Fig 1 ) and viral RNA accumulation ( Fig 5D ) , these data suggest that the expression of RyDEN is likely to be suppressive to the translation process of DENV RNA . Since RyDEN was found to be involved in establishing an antiviral state against DENV in human cells , we also investigated whether the expression of RyDEN influences the replication of other viruses . To this end , V5-RyDEN-expressing cells were further created using human cell lines including HeLa , Jurkat , and A549 cells by lentiviral vector-mediated transduction . Cell lines were then infected with several RNA ( hepatitis C virus [HCV , Flaviviridae] , West Nile virus Kunjin strain [WNVKUN , Flaviviridae] , Chikungunya virus [CHIKV , Togaviridae] , poliovirus [Picornaviridae] , human enterovirus 71 [EV71 , Picornaviridae] , and human immunodeficiency virus type-1 [HIV-1 , Retroviridae] ) and DNA ( herpes simplex virus 1 [HSV-1 , Herpesviridae] , HSV-2 , and human adenovirus type 3 [HAdV-3 , Adenoviridae] ) viruses . Measurements of the virus titer in the supernatants of infected cells indicated that significant inhibition by the overexpression of RyDEN was observed in HCV , WNVKUN , and CHIKV , but not in poliovirus , EV71 , or HIV-1 infections , as compared to that in control protein-expressing cells ( Fig 10A ) . A preliminary result showed that replication of the Sindbis virus , a Togaviridae family virus , was also suppressed in V5-RyDEN-expressing HeLa cells ( S11 Fig ) , suggesting that Flaviviridae and Togaviridae family members are broadly susceptible to RyDEN . Intriguingly , the replication of some DNA viruses , including HSV-1 and HAdV-3 , were negatively affected by V5-RyDEN expression , whereas it had no influence on HSV-2 infection ( Fig 10B ) .
In terms of morbidity and mortality , dengue has emerged as one of the most important arthropod-borne diseases in the world , with cases predominantly documented in tropical and sub-tropical urban centers . Currently , the development of new antiviral medications and vaccinations against DENV is an urgently needed . In this regard , understanding the host innate immune response that restricts DENV replication , such as the IFN response , will be important for the development of antiviral agents and effective vaccines . In this study , we present RyDEN ( C19orf66 ) as an ISG that limits all serotypes of DENV . Our findings suggest that RyDEN may target the translation of DENV RNA through interaction with other cellular RNA-binding proteins . Expression cloning of the cDNA library is a powerful approach to the functional and comprehensive analysis of cellular genes; such a gain-of-function screen has been applied to identify host factors involved in DENV replication [33 , 59] . In this study , a library of cDNA was generated from mRNA of type I IFN-treated HeLa cells and lentivirally expressed in Huh7 . 5 cells that exhibited massive cell death with DENV infection ( S1 Fig ) , which was expected to confer extensive resistance to DENV-induced cell death ( Fig 1A ) . Indeed , one round of a DENV-2 challenge resulted in more than 50 surviving cell clones on a 150-mm dish . An additional infection assay showed that 32 clones remained more or less resistant to DENV infection ( Fig 2 ) . Sequencing analysis of cDNA recovered from DENV-resistant Huh7 . 5 cells revealed that 19 cells harbored the RyDEN gene . Although some of the cells also contained all or parts of other genes or non-ORF sequences , the full ORF of RyDEN was isolated from all cells ( Fig 2 ) , indicating that RyDEN should be a major determinant of resistance to DENV in a cDNA library screening assay . Intriguingly , almost the same mutant ( amino acid position 304–702 ) of DNAJC14 , an Hsp40 family member that has been identified as an anti-flavivirus factor by a cDNA library screen [60] , was also recovered in this study ( Fig 2 , clone 31 ) , demonstrating the integrity of our screening . The previous report by Yi et al . showed that despite screening using cDNA from IFN-α-treated cells , DNAJC14 mRNA levels were not upregulated by interferon treatment , although the DNAJC14 mutant was again identified with a cDNA library of IFN-treated HeLa cells in our study . Thus , it still would be interesting to investigate how the DNAJC14 function is associated with the IFN-mediated antiviral response . In addition , the future investigation of other genes identified in our IFN cDNA library screen ( e . g . , IFN-α-inducible protein 27 , C19orf53 ) in flavivirus replication including DENV will provide fascinating insights into the interaction between virus and host . RyDEN is expressed from chromosome 19 as an eight-exon gene that encodes a 291 amino acid protein ( Fig 1E ) . A BLAST search analysis using RyDEN’s amino acid sequence did not show any overt similarities with other proteins in mammals; however , this protein was predicted to contain a zinc-ribbon domain in the central region and a coiled-coil motif in the C-terminal region ( Fig 1F ) . The zinc-ribbon motif , which is basically defined by CXXC ( H ) -15/17-CXXC , is a general architectural motif initially found in some eukaryotic transcription factors and RNA polymerase subunits that currently form largest group of zinc fingers [37] . Although the zinc ribbons seem to display limited sequence similarities , structural analysis revealed that a variety of cellular and viral proteins possess this motif as a binding domain for zinc [37] . Of interest is the fact that cyclic GMP-AMP synthase ( cGAS ) , a cytosolic DNA-recognition receptor for the induction of IFN responses , has recently been shown to contain zinc ribbon , which is likely to be required for DNA recognition [61] . Since zinc ribbon is found in many DNA- and RNA-binding proteins [37] , RyDEN may harbor nucleic acid-binding activity , as discussed below . Also , in amino acid sequence-based protein motif prediction programs , putative NLS ( referred to as NLS-L ) and NES sequences were found in the zinc-ribbon ( 121–137 ) and C-terminal domains ( 261–269 ) , respectively ( Fig 1F ) . Since IFA experiments showed that RyDEN was mainly dispersed throughout the cytoplasm ( Fig 7C and S8A Fig ) , at least in a normally dividing cell , the NLS-L sequence does not function to accumulate RyDEN in the nucleus . However , deletion of the C-terminal domain containing the putative NES sequence led to an exclusively nuclear location ( Fig 7E ) , suggesting that RyDEN is a potential nucleocytoplasmic shuttling protein , which is mostly retained in the cytoplasm . Note that no obvious changes in the subcellular localization of overexpressed RyDEN were observed with IFN treatment or DENV infection ( S8B Fig ) . In this study , RyDEN was shown to be an antiviral ISG . The overexpression of RyDEN in human cells suppressed all serotypes of DENV ( Fig 3C ) and , importantly , the endogenous expression of RyDEN was upregulated with the treatment of types I , II , and III IFNs ( Fig 4B ) . Although the level of artificially expressed RyDEN ( i . e . V5-RyDEN ) was 38 . 7±2 . 1 times higher than that of IFN-induced endogenous RyDEN in HepG2 cells as measured by qRT-PCR analysis , we believe that the expression level of IFN-induced RyDEN sufficiently participates in the inhibition of DENV replication in human cells . Supporting this , in the RyDEN knockdown cell line , the inhibitory effect of type I IFN against DENV-2 was reduced by more than 70% ( Fig 4C ) , indicating a major contribution of RyDEN to the IFN-mediated anti-DENV response . It should also be noted that even without IFN treatment , knockdown of the endogenous expression of RyDEN significantly enhanced DENV replication in several cell lines ( Fig 3E and S3 Fig ) , indicating that a steady-state level of RyDEN acts as a DENV inhibitor . In addition , expression levels of RyDEN as measured by qRT-PCR varied among different human cell lines ( S4 Fig ) , RyDEN expression may be one intracellular factor that determines the cellular tropism of DENV . One question to ponder is , how does RyDEN suppress the replication of DENV ? When the efficiency of virus entry was assessed by qRT-PCR , the level of viral RNA internalized in RyDEN-expressing cells was comparable to that in the control cells ( Fig 5A ) . In contrast , a significant decrease in the level of intracellular DENV RNA was observed in RyDEN-expressing cells 18–24 h after infection ( Fig 5D ) . RyDEN was , therefore , suggested to inhibit the post entry process during DENV replication . Consistent with this , the use of a cell line that harbored the RLuc reporter gene-carrying DENV subgenomic RNA replicon showed that the suppression of luciferase activity occurred with the transient expression of RyDEN ( Fig 5C ) at a level similar to IFN treatment ( S5 Fig ) . Importantly , transfection of a replication-defective mutant of the DENV reporter construct RNA ( DENrepPAC2A-Rluc GVD [58] ) showed that luciferase activity of the reporter construct RNA was diminished by the expression of RyDEN ( Fig 9B ) . Since RyDEN was not a mediator of the IFN response ( Fig 4 ) , these results suggest that RyDEN is a downstream effector molecule in the anti-DENV IFN response , which may target the translation process of viral RNA . Nevertheless , when compared to more pronounced effect on DENV titers ( Fig 1 ) and viral RNA levels ( Fig 5D ) , the inhibitory effect of RyDEN on the protein translation was modest ( Fig 9B ) . Therefore , we cannot rule out the possibility that RyDEN may also interfere with other step ( s ) of DENV replication such as RNA transcription or protein processing . Affinity purification-mass spectrometry analysis using TAP-tagged RyDEN then provided an important clue about RyDEN’s mechanism-of-action: RyDEN was likely to form a complex with the cellular RNA-binding protein PABPC1 ( Fig 6A ) . PABPC1 is one of the major PABP-family proteins in eukaryotes and is ubiquitously expressed in cytoplasm [45] . Although PABPC1 is reported to play multiple roles in the translation , deadenylation , and stability of mRNA through binding to a 3’ poly ( A ) tail , the typical function of this protein is to form the closed-loop structure of mRNA by interaction with eIF4G , a subunit of the 5’ cap-binding eIF4E complex , to initiate protein translation [47 , 48] . Of particular interest , a previous study by Polacek et al . has shown that PABP is able to bind the 3’UTR of DENV in vitro [49] . Although the DENV RNA genome lacks a terminal Poly ( A ) tail , Polacek et al . reported that A-rich stretches upstream of the stem-loop in the 3’UTR appeared to be involved in PABP binding [49] . In our study , the interaction domain of RyDEN with PABPC1 was mapped to the central region between amino acid positions 102–150 ( Fig 7A and 7B ) . Importantly , alanine substitution of positively charged arginine and lysine residues in the NLS-L sequence ( 121–137 ) of RyDEN resulted in decreased efficiency in the interaction with PABPC1 and reduced inhibitory activity against DENV replication ( Fig 7G ) . Additionally , the affinity purification-mass spectrometry analysis identified LARP1 as another interactor with RyDEN ( Fig 6A ) . LARP1 is also an RNA-binding protein that contains two RNA-binding motifs called the La motif and the RNA recognition motif [50] . While it has been documented that the La motif-related protein family is involved in a broad range of activities in cellular RNA , including tRNA processing and mRNA metabolism , LARPs are also reported to affect the translation process of mRNA [50] . In fact , it has been shown that LARP1 associates with PABPC1 and eIF4E in human cells and has a positive role at an early stage of translation initiation [54] . In our study , PABPC1 and LARP1 were found to be positive regulators of DENV , since the siRNA-mediated knockdown of these genes significantly reduced the level of virus replication in HepG2 cells ( Fig 6 ) . Given the fact that both PABPC1 and LARP1 have RNA-binding activity [45 , 50] , one could envisage that RyDEN may associate with DENV RNA through its interaction with these proteins during infection . As expected , our data of RIP assay showed that DENV RNA was significantly enriched by V5-tagged RyDEN ( Fig 8C ) . Moreover , AlphaScreen technology-based in vitro RNA-binding assay revealed that RyDEN possessed binding activity to DENV 3’UTR RNA , and the association of RyDEN with 3’UTR RNA was enhanced by the presence of PABPC1 ( Fig 8E ) . Therefore , based on our findings and the reported functions of PABPC1/LARP1 , the following possibility could be proposed regarding the mechanism of RyDEN-mediated antiviral activity in DENV-infected cells: RyDEN forms a complex with PABPC1 ( and LARP1 ) on DENV RNA , and then somehow interferes with the translation machinery of circularized viral RNA ( Fig 11 ) . This scenario would be consistent with the previous report by Diamond and Harris , in which IFN treatment was shown to inhibit the translation of DENV RNA rather than by preventing the association of DENV RNA with ribosomes [34] . In light of the data obtained by in vitro RNA-binding assay ( Fig 8E ) , one could envisage that RyDEN’s RNA-binding activity is RNA sequence-nonspecific , but that it gains specificity to positive-strand DENV RNA via interaction with PABPC1 that has been suggested to recognize A-rich stretches in the 3’UTR [49] . Intriguingly , Paip2 , a suppressor of PABPC1 , has been reported to be such a cellular inhibitor in the viral translation machineries [49 , 62] . The above-mentioned study of Polacek et al . also presented fascinating evidence that Paip2 is able to block the interaction of PABPC1 with DENV 3’UTR RNA in vitro [49] . Furthermore , a recent work has revealed that Paip2 , whose expression is stimulated by human cytomegalovirus ( HCMV ) infection , limits HCMV protein synthesis and replication [62] . It is noteworthy that a characteristic glutamic acid ( E ) -rich domain that has been characterized as a binding domain of Paip2 to PABPC1 [63] was also found in the C-terminal region of RyDEN ( Fig 1F ) . Although the C-terminal region surrounding the E-rich domain of RyDEN appeared not to be critical to its interaction with PABPC1 ( Fig 7B ) , RyDEN and Paip2 may have evolutionarily gained a similar regulatory function controlling PABPC1 activity . One concern would be that the translational suppression by RyDEN through interaction with PABPC1 might lead to a translation arrest of the host cell , which would result in the suppression of DENV replication . However , global cellular protein synthesis was not inhibited by the overexpression of RyDEN ( Fig 9A ) . It is therefore conceivable that there is specificity to RyDEN’s recognition of the viral RNA translation complex . In addition , RyDEN may stimulate the degradation of DENV RNA in cytoplasmic P-bodies or stress granules ( SGs ) in collaboration with PABPC1 and/or LARP1 , since the role of PABPC1 and LARP1 in eukaryotic mRNA decay as P-body and SG components has also been demonstrated [64 , 65] . These should be interesting topics to address in the future . Our study has also shown that multiple viruses are susceptible to the inhibitory action of RyDEN to a greater or lesser extent , including HCV , WNVKUN , and CHIKV , whereas the replication of other RNA viruses tested ( poliovirus , EV71 , and HIV-1 ) was not suppressed by RyDEN overexpression ( Fig 10A ) . Interestingly , some DNA virus replications ( HSV-1 and HAdV-3 ) were also affected by RyDEN ( Fig 10B ) . Our preliminary data showed that the replication of the Sindbis virus was impaired in V5-RyDEN-expressing cells ( S11 Fig ) , suggesting that RyDEN acts as a broad-ranging inhibitory factor , at least against the Flaviviridae and Togaviridae families . Given the proposed model of RyDEN’s inhibitory mode of action against DENV ( Fig 11 ) , viruses whose replication is influenced by RyDEN may utilize PABPC1/LARP1 in their replication , particularly in the viral protein translation process . It should be emphasized that PABPs are well-known targets of several viruses , and it has been demonstrated that enteroviruses and lentiviruses cleave PABP by their protease to shut off cellular translation; in contrast , an HSV-1 protein binds PABP to stimulate viral mRNA translation [66] . Therefore , we hypothesize that the antiviral activity of RyDEN depends on whether the virus requires PABPC1 ( and LARP1 ) function in its replication cycle . Indeed , PABPC1 is shown to promote HCV infection [67] , which was inhibited by RyDEN ( Fig 10A ) . In agreement with our data , a recent comprehensive study by Schoggins et al . using an overexpression screening of an ISG library has also reported the anti-HCV activity of RyDEN ( shown as FLJ11286 gene [24] ) . Thus , further understanding of the molecular detail of RyDEN will contribute to the development of broadly active antiviral inhibitors .
HEK293T ( human embryonic kidney , American Type Culture Collection [ATCC] CRL-11268 ) , Huh7 . 5 ( human hepatocellular carcinoma [68] , obtained from Apath , LLC ) , HepG2 ( human hepatoma , ATCC HB-8065 ) , and HeLa ( human cervical carcinoma , ATCC CCL-2 ) cells were cultured in DMEM supplemented with 10% fetal calf serum ( FCS , Life Technologies ) and antibiotics ( 100 units/ml penicillin and 100 μg/ml streptomycin ) . A549 ( human lung adenocarcinoma , ATCC CCL-185 ) and Vero ( green monkey kidney , ATCC CCL-81 ) cells were maintained in F-12K and Eagle's Minimum Essential Medium , respectively , which were supplemented with 10% FCS and antibiotics . BHK-21 ( baby hamster kidney , ATCC CCL-10 ) and Jurkat ( human lymphoblastoid T , ATCC TIB-152 ) cells were grown in RPMI 1640 supplemented with 10% FCS and antibiotics . C6/36 ( Aedes albopictus mosquito , ATCC CRL-1660 ) cells were maintained at 28°C in HEPES-modified RPMI 1640 containing 10% FCS and antibiotics . The four serotypes of DENV , which was isolated from isolated from patients recruited into the EDEN ( early dengue infection and outcome ) study in Singapore ( DENV-1: Singapore isolate S144; DENV-2: Singapore isolate EDEN2 3295; DENV-3: Singapore isolate EDEN 130/05; and DENV-4: Singapore isolate S8976 [36 , 41] ) , DENV-2 ( New Guinea C strain ) , CHIKV ( Ross strain ) , and WNVKUN were propagated in the C6/36 mosquito cells , and viral infectivity was titrated by plaque assays using BHK-21 cells as described previously [30] . HCV J6/JFH1-P47 ( genotype 2 ) was produced using Huh7 . 5 cells and the virus titer was determined as focus forming units ( FFU ) /ml by previously reported IFA [69] on Huh7 . 5 cells using mouse anti-HCV core monoclonal antibodies ( MA1-080 , Pierce ) . Poliovirus ( Sabin strain ) and human enterovirus 71 ( Singapore isolate ) were propagated in RD cells , and viral infectivity was titrated by plaque assays using RD cells . HIV-1 ( NL4-3 ) was produced by a transfection of HEK293T cells with pNL4-3 , and the virus titer of the culture supernatants collected was determined as previously described [35] . Production and titration of HSV-1/2 and HAdV-3 were carried out using Vero and A549 cells , respectively . Virus titer was calculated as plaque-forming units ( PFU ) /ml ( except for HCV and HIV-1 ) . A Gateway-compatible cDNA library was generated from mRNA isolated from HeLa cells that had been treated with 1 , 000 U/ml type I IFN ( a mixture of human interferon α and ω , Sigma ) for 24 h . Briefly , total RNA was extracted using the RNeasy Mini Kit ( Qiagen ) , and mRNA was then isolated using a PolyATtract mRNA Isolation System II ( Promega ) according to the manufacturer’s recommendations . The cDNA was synthesized using the CloneMiner cDNA Library Construction Kit ( Life Technologies ) from 3 μg of mRNA and fractionated with cDNA Size Fractionation Columns ( Life Technologies ) . After BP recombination reaction ( Life Technologies ) using 100 ng of cDNA and 300 ng of an entry vector , pDONR221 , the entry library containing approximately 2 . 5 x 107 clones , was amplified as a pool of transformants in One Shot TOP10 Electrocomp E . coli cells ( Life Technologies ) . The entry vector plasmid DNA was purified using the QIAGEN Plasmid Midi Kit ( Qiagen ) . To generate the lentiviral vector cDNA library , LR recombination reaction ( Life Technologies ) was performed using 300 ng of the entry cDNA library and 300 ng of an EcoRI-digested destination vector , pYK005C [35] . The resultant vector library was amplified as a pool of recombinants in One Shot TOP10 Electrocomp E . coli cells and purified using the QIAGEN Plasmid Maxi Kit ( Qiagen ) . A VSV-G-pseudotyped lentiviral vector expressing the IFN cDNA library was produced by the calcium phosphate-mediated transfection method using HEK293T cells as described previously [35] . Concentrated lentiviral vectors were titrated with HEK293T cells by evaluating the percentage of humanized Renilla green fluorescence protein positive cells 48 h after infection using a CyAn ADP flow cytometer ( Beckman Coulter ) . In a 150-mm dish , 1 x 107 of Huh7 . 5 cells were seeded 1 day before transduction and infected with 5 x 106 infectious dose of the IFN cDNA carrying lentiviral vectors for 24 h . After 48 h post-transduction , the cells were challenged with DENV-2 ( EDEN2 3295 ) at an MOI of 1 . The culture medium was changed every 2–3 days , and after 2 weeks , cell colonies that survived the DENV challenge were transferred to 48-well plates and expanded for further analysis . Genomic DNA was isolated from the resistant clones using the Wizard Genomic DNA Purification Kit ( Promega ) from cells that displayed low infectivity of DENV in immunofluorescence and plaque assay . The cDNA was then amplified by PCR using KOD-Plus 2 DNA polymerase ( Toyobo ) and primers ( 5’-CTT CCA TTT CAG GTG TCG TGA ACA CGC TAC CGG TCT CGA G-3’ and 5’-CAA ACG CAC ACC GGC CTT ATT CCA AGC GGC TTC GGC CAG-3’ ) flanking the Gateway cassette in the pYK005c lentiviral vector . cDNA was further amplified by nested PCR using primers ( 5’-ACC GGT CTC GAG AAT TAT CAA CAA-3’ and 5’-GCT GCA GAA TTA TCA ACC ACT TTG-3’ ) and cloned into the pCR-Blunt II-TOPO vector ( Life Technologies ) . The sequence of cDNA in the pCR-Blunt II-TOPO vector was analyzed by an automated DNA sequencer , and the data was compared with the DNA database at the National Center for Biotechnology Information using a BLAST search . To stain for DENV dsRNA in surviving clones , 3 x 104 of cells preseeded in Lab-Tek II 8-well chamber slides ( Thermo Scientific ) were infected with DENV-2 at an MOI of 5 . Two days after infection , cells were fixed with 4% PFA for 30 min , permeabilized with 0 . 1% Triton X-100 in PBS for 10 min , and blocked with 5% goat serum and 0 . 5% BSA in PBS for 30 min at room temperature . The cells were stained with anti-dsRNA mouse monoclonal antibody ( J2 , English & Scientific Consulting Bt . ) , followed by a secondary antibody , Alexa Fluor 488-conjugated goat anti-rabbit IgG ( Life Technologies ) . A slide was mounted with a ProLong Gold antifade reagent containing DAPI ( Life Technologies ) and observed under an Olympus IX81 fluorescence microscope . Images were captured with the CellSens Dimension software ( Olympus ) . Staining of V5-tagged proteins was performed using a primary antibody , anti-V5 mouse monoclonal ( Life Technologies ) , followed by Alexa Fluor 488-conjugated anti-mouse secondary antibody ( Life Technologies ) . To detect endogenous RyDEN , a rabbit serum was generated by Sigma using synthesized 4 peptides derived from RyDEN ( amino acid positions 1–19 , 51–69 , 186–205 , and 223–242 ) . Cells preseeded in 8-well chamber slides ( 3 x 104 of cells per well ) were incubated with 1 , 000 U/ml type I IFN for 24 h , fixed , permeabilized with 1% Triton X-100 , and blocked with Blocker Casein ( Thermo Scientific ) . Immunostaining was carried out by an incubation with anti-RyDEN rabbit serum ( 1:5 , 000 in blocking buffer ) and subsequent incubation with FITC-conjugated donkey anti-rabbit IgG ( Rockland ) . To create stable cell lines expressing V5-tagged proteins , the ORF of RyDEN and the control proteins ( DHFR and RLuc ) were amplified by PCR and cloned into pDONR221 through a Gateway BP reaction . The individual ORF was then transferred to a Gateway-compatible lentiviral vector , pYK-nV5-Bla , in which a V5 epitope tag sequence had been added to the upstream of the Gateway unit in pYK005C-Bla [70] by LR reaction . A VSV-G-pseudotyped lentiviral vector was produced as described above and used to transduce human cells , including Huh7 . 5 , HepG2 , HeLa , Jurkat , and A549 cells . Transduced cells were selected in the presence of 10 μg/ml of blasticidin ( InvivoGen ) . Expressions of V5-tagged proteins in the stable cell lines were confirmed by immunoblotting using anti-V5 antibodies as described below . To construct a lentiviral vector that expressed shRNA , synthesized oligonucleotides that contained shRNA sequences against RyDEN ORF ( sh1425: 5’-GAA CTA AGT AAC GAT CTG GAT-3’; sh3151: 5’-GAG AAG TTT CAT GGG AAG GTA-3’; sh5890: 5’- GAA GCC AAC CTA CGC ATG TTT-3’ ) were designed by using the RNAi Consortium web portal ( http://www . broadinstitute . org/rnai/public/ ) and inserted into AgeI-EcoRI sites of a lentiviral vector pLKO . 1 puro ( Addgene ) . VSV-G-pseudotyped lentiviral vector particles were produced by the transfection of lentiviral vector DNA encoding sh1425 , sh3151 , sh5890 , or non-targeting control shRNA ( SHC002 , Sigma ) and used to transduce HeLa cells . Transduced cells were selected over 2 weeks with 2 μg/ml of puromycin ( InvivoGen ) . The knockdown efficiency of RyDEN mRNA in each cell line was analyzed by qRT-PCR as described below . The shRNA-resistant RyDEN expression vector was constructed using pYK005C-Bla by replacing the sh1425-targeting sequence of 5’-GAG CTG AGC AAT GAC CTC GAC-3’ , which introduced seven silent mutations without changing the amino acid sequences of RyDEN . Total RNA was isolated from cells using the RNeasy Mini Kit ( Qiagen ) and was treated with DNase using the TURBO DNA-free Kit ( Ambion ) . cDNA was synthesized using High-Capacity cDNA Reverse Transcription Kit ( Applied Biosystems ) , and subjected to real-time qPCR using SsoAdvanced SYBR Green Supermix and CFX96 Real-Time PCR detection system ( Bio-Rad ) . The expression levels of target RNA were calculated by the comparative cycle threshold ( CT ) method and normalized with GAPDH mRNA levels . In some experiments for the detection of DENV-2 RNA , qRT-PCR was performed by High-Capacity cDNA Reverse Transcription Kit and SsoFast Probes Supermix ( Bio-Rad ) using previously described primers and fluorescent probe targeting 3’UTR of the DENV genome [71] . For qRT-PCR analysis of DENV-2 minus-strand RNA , cDNA synthesis was carried out using forward primer of 3'UTR instead of random primer as described in previous report [72] . Primer sequences for qRT-PCR analysis are listed in S1 Table . Protein samples were denatured in an SDS sample buffer , separated by 10% SDS-PAGE gel , and transferred to an Immobilon-P transfer membrane ( Millipore ) . The primary antibodies used were anti-V5 mouse monoclonal ( Life Technologies ) , anti-C19orf66 rabbit polyclonal ( Abcam ) , anti-PABPC1 mouse monoclonal ( 10E10 , Santa Cruz Biotechnology ) , anti-ISG15 rabbit polyclonal ( 2743 , Cell Signaling ) , and anti-actin mouse monoclonal ( AC40 , Sigma ) antibodies . Horseradish peroxidase ( HRP ) -conjugated anti-mouse or anti-rabbit IgG antibody ( Cell Signaling ) was used as a secondary antibody . For immunoprecipitation analysis , TrueBlot ULTRA anti-mouse IgG HRP ( Rockland ) was used as a secondary antibody . Proteins were detected using an ImageQuant LAS 4000 mini chemiluminescent image analyzer ( GE Healthcare ) . To analyze RyDEN expression , HeLa cells preseeded in a 12-well plate at 1 x 105/well density 1 day before treatment were incubated with 10 , 100 , or 1 , 000 units/ml of IFN-α/ω at 37°C . Twenty-four hours after treatment , cells were collected and subjected to immunoblotting using an anti-RyDEN antibody . In a parallel experiment , HepG2 cells expressing sh1425 and shCtrl were treated with 300 units/ml of IFN-α/ω , IFN-γ ( BioLegend ) , or IFN-λ1 ( PeproTech ) for 24 h before assessing RyDEN expression by immunoblotting . For DENV infection , shRNA-expressing HepG2 cells were treated with or without IFN-α/ω ( 300 units/ml ) for 24 h and then inoculated with DENV-2 at an MOI of 1 . The culture supernatant was collected 48 h after infection and subjected to plaque assay . For DENV infection , cells ( V5-tagged protein or shRNA-expressing ) preseeded in 6-well plate at 5 x 105/well density 1 day prior to infection were infected at an MOI of 0 . 1 , 1 , or 10 . After 1 h of incubation at 37°C , cells were washed once followed by replacement with growth medium without selection antibiotics . The culture supernatant was collected at indicated time points and subjected to a standard plaque assay . In a similar way , HCV , poliovirus , and EV71 infections were performed by exposing the viruses to V5-RyDEN or V5-DHFR-expressing Huh7 . 5 cells at an MOI of 2 ( HCV ) or 1 ( poliovirus and EV71 ) , and the culture supernatant was collected 4 days ( HCV ) or 1 day ( poliovirus and EV71 ) after infection . For WNVKUN , CHIKV , HSV-1 , and HSV-2 infections , V5-RyDEN or V5-DHFR-expressing HeLa cells were infected at an MOI of 1 ( for WNVKUN and CHIKV ) or an MOI of 0 . 1 ( for HSV-1 and HSV-2 ) , and the culture supernatant was collected 48 h ( for KUNV ) or 72 h ( for CHIKV , HSV-1 , and HSV-2 ) after infection . HIV-1 infection of V5-RyDEN or V5-DHFR-expressing Jurkat cells were carried out by exposing the virus ( MOI of 0 . 005 ) for 2 h , and the level of virus replication was measured with a p24Capsid concentration in a culture supernatant of infected cells [35] . For HAdV-3 infection , V5-RyDEN or V5-RLuc-expressing A549 cells were infected with a virus at an MOI of 1 , and the culture supernatant was collected at 24 h . Virus entry assay was performed as reported by Le Sommer et al . [40] . Huh7 . 5 cells stably expressing V5-RyDEN or V5-RLuc , which had been seeded in a 24-well plate at a density of 5 x 104/well 1 day before infection , were incubated with DENV-2 at an MOI of 5 at 37°C for 2 h . Uninternalized virus particles were removed by washing the cells twice with cold PBS , followed by a 3-min exposure to 1 M NaCl and 50 mM Na2CO3 , pH 9 . 5 . After washing with cold PBS three more times , total RNA was extracted and cell-associated DENV RNA was analyzed by qRT-PCR analysis . DENV-2 RNA was first extracted from the virus supernatant using QIAamp Viral RNA Mini Kit ( Qiagen ) . For transfecting the isolated viral RNA , Huh7 . 5 cells that expressed V5-RyDEN or V5-RLuc were preseeded in a 6-well plate at a density of 5 × 105/well 1 day before transfection and transfected with DENV-2 RNA equivalent to 6 . 7 × 107 PFU using Lipofectamine 2000 ( Life Technologies ) . After 3 days , the culture supernatant was collected to measure the infectious titer of extracellular virus via plaque assay . A stable A549 cell line expressing a self-replicating DENV replicon was generated by the transfection of in vitro transcribed and 5'-capped genomic RNA of the DENV-2 NGC strain , in which structural genes had been replaced with puromycin-resistant gene and Renilla luciferase gene ( DENrepPAC2A-Rluc ) , and subsequent selection with 5 μg/ml of puromycin as described previously [42] . Established cells were seeded in a 24-well plate at a density of 2 x 104 cells/well and , on the next day , transfected with 4–400 ng of V5-RyDEN or V5-BAP-expressing pcDNA3 . 1 by Lipofectamine 2000 . Forty-eight hours after transfection , cells were harvested and subjected to a luciferase assay using the Renilla Luciferase Glow Assay Kit ( Thermo Scientific ) , as described previously [70] . As an inhibition control experiment , RLuc replicon-expressing A549 cells were also transfected with 10 nM siRNA duplex against DENV NS3 [42] or a scrambled siRNA duplex using siLentFect ( Bio-Rad ) and analyzed by luciferase assay . To construct a mutant DENV reporter construct , DENrepPAC2A-Rluc GVD , aspartic acid ( D ) at position 663 of NS5 was changed to valine ( V ) [58 , 73] by QuikChange II XL Site-Directed Mutagenesis Kit ( Agilent ) using DENrepPAC2A-Rluc as a template plasmid DNA . RNA of DENrepPAC2A-Rluc WT and GVD were in vitro transcribed from XbaI-digested plasmid DNA using MEGAscript T7 Transcription Kit ( Life Technologies ) in the presence of m7GpppA cap analogue ( NEB ) and purified by RNeasy Mini Kit ( Qiagen ) . For reporter assay , V5-RyDEN and V5-DHFR-expressing HepG2 cells , which had been preseeded in 24-well plates at 1 x 105 cells/well density , were transfected with 500 ng of transcribed RNA using Lipofectamine 2000 , and 4 and 8 h after transfection , the cells were subjected to luciferase activity assay . V5-RyDEN or V5-BAP-expressing plasmid DNA was constructed using pcDNA3 . 1/nV5-DEST ( Life Technologies ) by a Gateway BP reaction . To construct the expression plasmid of STING , ORF of STING , which was fused with the N-terminal HA tag sequence , was generated by RT-PCR using mRNA from HeLa cells and cloned into the EcoRV site of pcDNA3 . 1 ( Life Technologies ) . Constructed plasmid DNA ( 500 ng ) was transfected to HepG2 cells ( preseeded in a 24-well plate at 5 x 104 cells/well density 1 day before transfection ) using jetPRIME ( Polyplus Transfection ) and incubated for 48 h . Total RNA was extracted using the RNeasy Mini Kit ( Qiagen ) and was subjected to RT-qPCR analysis using SsoAdvanced SYBR Green Supermix and primers listed in S1 Table . An ORF of RyDEN or BAP was cloned into a lentiviral vector , pYK005C-NTAP-Bla in which a TAP tag consisting of two IgG binding units , a tobacco etch virus ( TEV ) protease cleavage site , and a streptavidin-binding peptide [44] had been added upstream of the Gateway unit in pYK005C-Bla by LR reaction . A VSV-G-pseudotyped lentiviral vector produced using 293T cells was used to transduce HepG2 cells . The transduced cells were selected in the presence of 10 μg/ml of blasticidin . Expression of N-terminal TAP-tagged RyDEN and BAP proteins were confirmed by immunoblotting using nonspecific rabbit IgG ( primary antibody ) and HRP-conjugated anti-rabbit IgG as a secondary antibody . For affinity purification analysis , TAP-fused protein-expressing cells ( 90% confluence in a 100-mm culture dish ) were harvested from a total of 12 dishes , washed twice in PBS that contained 10 mM EDTA , and lysed in 7 . 8 ml of TAP lysis buffer ( 50 mM Tris-HCl , pH8 . 0 , 0 . 5 mM EDTA , 1 mM DTT , 150 mM NaCl , 0 . 2% NP-40 , protease inhibitors ) on ice for 40 min . Cell debris was removed by centrifugation for 10 min at 10 , 000 × g . The supernatants were incubated with 840 μl of IgG Sepharose 6 Fast Flow ( 50% slurry , GE Healthcare ) at 4°C for 2 h . Beads were washed three times with TAP washing buffer ( 50 mM Tris-HCl , pH 8 . 0 , 0 . 5 mM EDTA , 1 mM DTT , 300 mM NaCl , 1% NP-40 ) . Proteins were eluted in 1 . 24 ml of TAP elution buffer ( 50 mM Tris-HCl , pH 8 . 0 , 0 . 5 mM EDTA , 1 mM DTT , 150 mM NaCl , 0 . 2% NP-40 ) containing 60 U of TEV protease ( Life Technologies ) at 4°C overnight . The eluted protein sample was concentrated using trichloroacetic acid and separated by a 10% SDS-PAGE gel . Mass spectrometric identification of proteins was performed using MALDI TOF-TOF MS at Protein and Proteomics Centre , Department of Biological Sciences , National University of Singapore . To construct deletion mutants of RyDEN , cDNA covering amino acid positions 51–291 , 101–291 , 151–291 , and 1–250 were amplified by PCR . Site-directed mutagenesis of RyDEN for substitutions of arginine and lysine to alanine in NLS-L ( amino acid positions 121–137 ) was performed by the overlapping PCR technique using two complementary primers flanking both ends of the RyDEN ORF and two internal mutagenic 25-nucleotide primers . After the first round of PCR , the two mutated DNA fragments ( 5’ and 3’ parts ) were annealed , and a second round of PCR was carried out using the complementary primers . All PCR fragments were gel purified , cloned into pDONR221 , and , after confirmation of sequences , transferred to the Gateway unit of pYK005C-Bla . The VSV-G-pseudotyped lentiviral vectors were produced using HEK293T cells and were used to transduce Huh7 . 5 ( for the deletion mutant experiment ) or HepG2 ( for the NLS-L mutant experiment ) , followed by selection with blasticidin ( 10 μg/ml ) . Stable cell lines ( 90% confluence in a 100-mm culture dish ) that expressed V5-tagged RyDEN ( WT , deletion mutants , and NLS-L mutants ) , or control RLuc were lysed using 1 . 1 ml of TAP lysis buffer on ice for 40 min and cleared by centrifugation . Five-hundred microliters of cell lysate were then incubated with 3 μl of an anti-PABPC1 mouse monoclonal antibody ( 10E10 , Santa Cruz Biotechnology ) at 4°C for 2 h with rotation , followed by the addition of 30 μl of Protein A/G agarose beads ( Santa Cruz Biotechnology ) and another 2 h of incubation at 4°C . The bound complexes were washed five times with TAP elution buffer and eluted in SDS sample buffer for immunoblotting analysis . In the co-immunoprecipitation experiments , V5-RLuc was used as a control protein to avoid overlapping with IgG light chain of the anti-PABPC1 antibody ( used for pull-down ) on immunoblots . siRNA duplexes that target human PABPC1 ( siPABPC1: 5’-AGG CGA UGC UCU ACG AGA AdTdT-3’ ) and human LARP1 ( siLARP1: 5’-GAA UGG AGA UGA GGA UUG CdTdT-3’ ) and a negative control siRNA duplex ( siCtrl ) were purchased from SABio ( Singapore ) . HepG2 cells preseeded in a 24-well plate at a density of 1 x 105 cells/well 1 day before transfection were transfected with 50 nM siRNA duplex using jetPRIME and then inoculated with DENV-2 at an MOI of 1 48 h after transfection . Forty-eight hours after infection , the culture supernatant was collected and subjected to plaque assay to determine the viral infectious titer . At the same time , total RNA was extracted from infected cells and used for qRT-PCR to analyze the knockdown efficiency of PABPC1 and LARP1 mRNA using the primers listed in S1 Table . HepG2 cells that expressed V5- RyDEN ( WT and NLS mutants ) or V5-DHFR were seeded in a 6-well plate at a density of 5 x 105 cells/well 1 day before infection and exposed to 2 . 5 x 106 PFU of DENV-2 for 6 h . Cells were then washed with cold PBS three times and lysed with 300 μl of TAP lysis buffer on ice . After centrifugation at 10 , 000 x g for 10 min , the supernatant was incubated with 3 μl of an anti-V5 mouse monoclonal antibody in the presence of 100 ng/ml of tRNA ( Sigma ) at 4°C for 2 h with rotation , followed by the addition of 30 μl of protein A/G agarose beads ( 50% slurry in PBS , Pierce ) and another 2 h of incubation at 4°C . The immune complex was washed with 500 μl of TAP washing buffer 5 times and suspended with RNase-free PBS . One-fourth of the suspension was used for immunoblotting to detect V5-tagged proteins , and the rest was used for RNA analysis . DENV RNA was extracted from the suspension using TRIzol ( Life Technologies ) and subjected to qRT-PCR using DENV 3’UTR-specific primers and a fluorescent probe ( S1 Table ) . 3’UTR sequence of DENV-2 NGC ( nucleotide positions 10 , 271–10 , 724 ) was cloned into pEU vector containing SP6 promoter sequence ( CellFree Sciences , Japan ) . A DNA fragment covering the upstream SP6 promoter and the downstream 3’UTR sequences ( or DHFR sequence for nonspecific control RNA ) was amplified from the pEU-based construct by PCR , which was then used for in vitro transcription in 25 μl of reaction containing 10 mM NTP , 0 . 25 mM biotinylated UTP ( Roche Diagnostics ) , and 0 . 8 units/μl SP6 polymerase ( CellFree Sciences ) . Resulting transcripts were column purified , followed by ethanol precipitation to remove free biotinylated UTP . For production of recombinant proteins , a DNA fragment containing 5’ SP6 promoter , N-terminal tag ( consisting of GST and FLAG units , separated by TEV protease cleavage site [GST-TEV-FLAG] for FLAG-tagged proteins [RyDEN WT , RyDEN NLS-L mutant , and DHFR] , or GST unit and TEV protease site [GST-TEV] for GST-tagged proteins [PABPC1 and DHFR] ) , and the protein ORF sequences was amplified from plasmid DNA encoding RyDEN ( WT or NLS-L mutant ) , DHFR , or PABPC1 by previously described split-primer PCR method [74] and used as a template for in vitro transcription . In vitro RNA transcription and subsequent translation of proteins using wheat germ cell-free protein production system were performed in 96-well plate by the bilayer diffusion method using ENDEXT technology ( CellFree Sciences ) according to the manufacturer’s protocol . The synthesized proteins were captured with glutathione Sepharose 4B ( GE healthcare ) , and the beads were washed with PBS . Proteins were then eluted from beads using elution buffer ( 50 mM Tris-HCl , pH8 . 0 , 100 mM NaCl ) containing 0 . 4 U/μl TEV protease ( for FLAG-tagged proteins ) or 10 mM reduced glutathione ( for GST-tagged proteins ) . In vitro RNA binding assay was performed with 384-well OptiPlate by AlphaScreen technology ( PerkinElmer ) . Twenty nanomolar of FLAG-tagged proteins were mixed with 20 nM of GST-tagged proteins and 3 . 5 ng/μl biotinylated ( or non-biotinylated ) DENV 3’UTR RNA ( or control RNA ) in 15 μl of the binding mixture containing reaction buffer ( 100 mM Tris-HCl , pH7 . 5 , 100 mM NaCl , 1 mg/ml BSA , 0 . 01% Tween 20 ) at 16°C . After 1 h incubation , 10 μl of the detection mixture containing 0 . 2 μg/ml anti-FLAG mouse monoclonal antibody ( Wako ) , 0 . 1 μl of streptavidin-coated donor beads and 0 . 1 μl of protein A-conjugated acceptor beads ( PerkinElmer ) in reaction buffer was added to the binding mixture , followed by incubation at 16°C for 1 h . Luminescent signal was analyzed by an EnVision microplate luminometer ( PerkinElmer ) [56] . V5-RyDEN and V5-DHFR-expressing HepG2 cells preseeded in a 12-well plate at a density of 2 x 105 cells/well 1 day before assay were cultured with 10 or 20 μg/ml cycloheximide for 1 h . After the medium was changed , cells were further cultured in the presence of 10 μg/ml of puromycin ( Clontech ) . Cells were harvested 40 min after puromycin pulse , and the cell lysate was subjected to immunoblotting using anti-puromycin mouse monoclonal antibody ( 3RH11 , KeraFAST ) . All data are obtained by a representative set of at least three independent experiments , and the average values are shown with error bars indicating the standard deviation ( SD ) . Statistical significance was performed using JMP Pro software version 11 ( SAS Institute ) . P values below 0 . 05 ( P<0 . 05 , *; P<0 . 01 , **; P<0 . 001 , *** ) were considered significant . In this study , the following reference sequences were used to design oligonucleotides: DENV-2 NGC ( AF038403 . 1 ) ; C19orf66 ( NM_018381 ) ; PABPC1 ( NM_002568 . 3 ) ; LARP1 ( NM_015315 . 4 ) ; BAP ( M13345 . 1 ) ; DHFR ( J01609 . 1 ) ; ISG54 ( NM_001547 . 4 ) ; ISG15 ( NM_005101 . 3 ) ; LY6E ( NM_002346 . 2 ) ; RIG-I ( AF038963 . 1 ) ; IFN-β ( M25460 . 1 ) ; GAPDH ( NM_002046 . 5 ) . | Dengue is the most common arthropod-borne viral infection and is spreading to new areas every year . Its causative agent , dengue virus ( DENV ) , has immunologically distinct serotypes that increase the risk of life-threatening diseases such as dengue hemorrhagic fever . However , an effective medication for dengue has not yet been established . There is , therefore , an urgent need to develop new antivirals and vaccines against DENV . Here , we have characterized C19orf66 , named Repressor of yield of DENV ( RyDEN ) , as a cellular gene that inhibits the replication of all DENV serotypes . The expression of RyDEN was found to be upregulated by interferon ( IFN ) treatment and played a critical role in the IFN-mediated anti-DENV response . We also found that RyDEN was likely to block the protein translation of DENV RNA through its association with cellular mRNA-binding proteins and viral RNA . Intriguingly , replication of several other viruses , such as hepatitis C virus , Kunjin virus , and Chikungunya virus , was also limited by RyDEN expression . Thus , this study describes a novel mechanism of an IFN-inducible inhibitory factor for DENV and provides the basis for future development of broad-spectrum antivirals against infectious viral diseases , including dengue . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2016 | Characterization of RyDEN (C19orf66) as an Interferon-Stimulated Cellular Inhibitor against Dengue Virus Replication |
The stem-cell leukemia ( SCL , also known as TAL1 ) gene encodes a basic helix-loop-helix transcription factor that is essential for the initiation of primitive and definitive hematopoiesis , erythrocyte and megakarocyte differentiation , angiogenesis , and astrocyte development . Here we report that the zebrafish produces , through an alternative promoter site , a novel truncated scl ( tal1 ) isoform , scl-β , which manifests a temporal and spatial expression distinct from the previously described full-length scl-α . Functional analysis reveals that while scl-α and -β are redundant for the initiation of primitive hematopoiesis , these two isoforms exert distinct functions in the regulation of primitive erythroid differentiation and definitive hematopoietic stem cell specification . We further demonstrate that differences in the protein expression levels of scl-α and -β , by regulating their protein stability , are likely to give rise to their distinct functions . Our findings suggest that hematopoietic cells at different levels of hierarchy are likely governed by a gradient of the Scl protein established through temporal and spatial patterns of expression of the different isoforms .
On the basis of anatomic locations of development , time of initiation , and cell type produced , vertebrate hematopoiesis can be divided into primitive and definitive programs [1–3] . In mouse , the primitive , or first , wave of hematopoiesis initiates in the yolk sac at about embryonic day 7 . 5 and produces primarily nucleated embryonic erythrocytes and macrophages [4 , 5] . The definitive , or second , wave of hematopoiesis is believed to originate from the intra-embryonic aorta–gonads–mesonephros at approximately embryonic day 8 . 5 and give rise to all the mature blood cell types [6–8] . Similar to that of mammals , zebrafish hematopoiesis also consists of primitive and definitive programs , and produces differentiated cells analogous to most of the mature blood lineages found in mammals [9–11] . Zebrafish primitive erythropoiesis originates from the posterior lateral mesoderm ( PLM ) as a pair of bilateral stripes at approximately the five-somite stage [9 , 10 , 12] . These bilateral stripes extend anteriorly and posteriorly , and converge in the midline at the 20-somite stage to form the main structure of the intermediate cell mass ( ICM ) , where the erythroid progenitors further develop . On the other hand , primitive myelopoiesis is believed to arise from the rostral blood island of the anterior lateral mesoderm ( ALM ) region at around the ten-somite stage , and produces mainly macrophages [10 , 13] . Compared to the onset of primitive hematopoiesis , the onset of zebrafish definitive hematopoiesis is less well defined . Preliminary studies indicate that the earliest definitive hematopoietic stem and progenitor cells arise from the ventral wall of dorsal aorta ( DA ) at around 26 to 30 h postfertilization ( hpf ) and subsequently migrate to the kidney , the adult hematopoietic organ in zebrafish , by 5 d postfertilization ( dpf ) [10 , 14 , 15] . Stem-cell leukemia ( SCL , also known as TAL1 ) was originally identified as a proto-oncogene through the study of T cell acute lymphoblastic leukemia patients with a chromosomal translocation at the breakpoint of t ( 1;14 ) ( p32;q11 ) [16–18] . The importance of SCL in normal hematopoiesis and angiogenesis was revealed by gene targeting analysis in mouse embryonic stem cells . Mice lacking SCL function failed to form vitelline vessels in the yolk sac and died at embryonic day 8 . 5 of development because of the complete absence of primitive hematopoiesis [19–21] . SCL-null embryonic stem cells , when injected into blastocysts , failed to contribute to any hematopoietic lineage in mouse chimeras [22 , 23] . These results demonstrate that SCL is essential for the generation of primitive and definitive hematopoietic cells as well as for the formation of yolk sac vessels . In addition to its pivotal role in early hematopoiesis , SCL also exerts important biological functions in subsequent hematopoietic lineage specification . Enforced SCL expression in hematopoietic cell lines favors erythroid differentiation [24 , 25] , and ablation of SCL in adult mice impairs erythropoiesis and megakarypoiesis [26 , 27] . Despite its important functions , the molecular mechanisms of how SCL mediates these multiple functions remain obscure . Previous in vitro studies in human and mouse malignant hematopoietic cell lines have described several SCL isoforms involved in T cell leukemia development and differentiation of erythrocytes and megakaryocytes [28–33] . However , the existence and biological functions of these SCL isoforms in vivo have not been demonstrated . In this study , we report that the zebrafish produces , through an alternative promoter site within exon 2 , a novel scl ( tal1 ) isoform , scl-β , that encodes a truncated protein lacking the N-terminal 118 amino acids ( aa ) . Whole-mount in situ hybridization ( WISH ) demonstrated that scl-β exhibits temporal and spatial expression that overlaps but is clearly distinctive from that of the full-length scl-α: scl-β emerges first and expresses in the entire ALM and PLM and the ventral wall of DA , where the first definitive hematopoietic progenitors arise; scl-α expresses later in the posterior of the ALM and the PLM , possibly in a manner overlapping with scl-β , and is subsequently restricted to the ICM region . Loss-of-function analysis using an antisense morpholino oligonucleotide ( MO ) knockdown approach revealed that while scl-α and -β are redundant in the initiation of primitive hematopoiesis , these two isoforms appear to function at different stages of primitive erythroid cell differentiation . Analysis of definitive hematopoiesis of scl-α and -β MO-injected embryos ( morphants ) showed that the knockdown of Scl-β , but not Scl-α , protein expression resulted in the loss of c-myb ( cmyb ) and runx1 expression in the ventral wall of DA as well as rag1 expression in the thymus , demonstrating that scl-β but not scl-α is essential for definitive hematopoietic stem cell development . Interestingly , we found that scl-β and -α exhibited a remarkable difference in their protein expression levels both in vitro and in vivo , indicating that differences in the protein expression level of scl-α and -β isoforms likely confer their distinct functions in the regulation of hematopoietic cell development .
To investigate whether different scl isoforms exist in zebrafish , RNA samples were prepared from 18-somite-stage embryos and kidney , the adult hematopoietic organ in zebrafish [10] , and subjected to Northern blot analysis . The result showed that two transcripts , one 2 . 6 kilobases ( kb ) and the other 2 . 2 kb , were specifically hybridized to the probes corresponding to the coding sequence and the 3′ untranslated region ( UTR ) of the zebrafish scl cDNA ( data not shown ) , suggesting that the 2 . 6-kb and 2 . 2-kb transcripts may represent two different scl isoforms . To characterize the nature of these two transcripts , we carried out a rapid amplification of cDNA ends ( RACE ) experiment and obtained one 3′ RACE and two 5′ RACE products ( data not shown ) . DNA sequencing revealed that the larger 5′ RACE product was identical to the published full-length scl sequence [34 , 35] , whereas the smaller fragment was also identical except that it lacked the first 438 base pairs at the 5′ end of the full-length scl , indicating that the 2 . 6-kb transcript is the full-length scl and the 2 . 2-kb transcript represents a novel scl isoform . This was confirmed by Northern blot analysis , which showed that while both transcripts were hybridized to the scl 3′ UTR probe ( 3′-probe ) , only the larger 2 . 6-kb species was recognized by the scl 5′ 414-bp probe ( 5′-probe ) ( Figure 1A ) . We hereafter designate the 2 . 6-kb full-length and the 2 . 2-kb truncated forms as scl-α and scl-β , respectively . Time course analysis by Northern blot revealed that the expression of scl-β began at the one- to two-somite stage , peaking at around the 11- to 18-somite stage , and maintained a lower level in the adult kidney ( Figure 1A ) . On the other hand , the scl-α transcript was not detected until the four-somite stage , after which it rapidly increased its level to that of scl-β , subsequently becoming the dominant form in the adult kidney ( Figure 1A ) . Considering the fact that the scl-β transcript initiates within the exon 2 , where a potential TATA-box sequence can be found at position −31 of the predicted transcription initiation site ( Figure 1B ) , and expresses earlier than scl-α ( Figure 1A ) , we conclude that scl-β is generated from an alternative promoter site within exon 2 encoding a truncated Scl protein lacking the N-terminal 118 aa ( Figure S1 ) . WISH was performed to examine the temporal and spatial expression of scl-α and -β . As shown in Figure 2 , the 3′-probe , which recognized both scl-α and -β , exhibited a pattern identical to that of scl expression described previously [34 , 35] . It first emerged at around the two-somite stage as one pair of stripes in the PLM followed by the appearance of a second pair of stripes in the ALM at the four-somite stage ( Figure 2A and 2B ) . These two pairs of stripes , which represented the combination of both scl-α and -β transcripts ( referred to as scl-α/β stripes hereafter ) , extended anteriorly and posteriorly from the four-somite stage onwards ( Figure 2B and 2C ) . And by the 18-somite stage , the scl-α/β stripes were mainly localized in three regions: the ALM , the anterior of the PLM ( APLM ) , and ICM ( Figure 2D ) . In contrast to the 3′-probe-positive signals , the 5′-probe-positive signals , which represented only the full-length scl-α , appeared at the four- and six-somite stage as two pairs of stripes ( scl-α stripes ) in the PLM and ALM , respectively ( Figure 2H , and data not shown ) . By the 18-somite stage , the scl-α expression was restricted to the ICM ( Figure 2J ) , where primitive erythropoiesis actively occurs at this stage [10] , suggesting that scl-α is predominantly expressed in the erythroid lineage from the 18-somite stage onwards . This possibility was further supported by the lack of scl-α expression in the erythrocyte-deficient mon ( trim33 ) mutant embryos [36] ( Figure 2F and 2L ) . Notably by 26 hpf , only a weak signal of the 3′- but not the 5′-probe was detected in the ventral wall of DA ( Figure 2E and 2K ) , where the first definitive hematopoietic stem cells presumably emerge [10 , 14 , 15] , suggesting that scl-β is the main isoform expressed in the definitive hematopoietic stem cells . To test this possiblity , we carried out double staining analysis in which 26 hpf embryos were stained with anti-Scl-α ( Ab-Scl-N ) or anti-Scl-α/β ( Ab-Scl-C ) antibodies together with c-myb WISH . The transverse section through the trunk region of these embryos showed that Scl-β but not Scl-α protein was present in the ventral wall of DA in a manner partially overlapping with c-myb-positive cells ( Figure 2M–2R ) , indicating that the definitive hematopoietic stem cells predominantly express scl-β . Based on these observations , we conclude ( as illustrated in Figure 2S ) that scl-β appears first and expresses in the entire ALM and PLM regions; scl-α emerges later in the ALM and ICM , possibly in a manner overlapping with scl-β , and is subsequently restricted to the ICM by the 18-somite stage . Notably , only scl-β expresses in the ventral wall of DA where the first definitive hematopoietic stem cells arise . To determine the biological functions of scl-α and -β in hematopoiesis , two MOs , scl-α MO and scl-β MO ( Figure 1B ) , that specifically inhibited the protein syntheses of scl-α and -β , respectively , were injected into wild-type zebrafish embryos . Immunohistochemistry staining showed that scl-α MO and -β MO specifically abolished the Scl-α and -β protein expression as indicated by lack of anti-Scl-N staining in the ICM of scl-α morphants ( Figure 3N , n = 35/35 ) , and the selective loss of anti-Scl-C staining in the APLM ( where only scl-β was transcribed [Figure 2D] ) of scl-β morphants ( Figure 3S , n = 32/32 ) . Microscopic analysis of the 24-hpf embryos injected with either MO revealed no obvious abnormality in general morphology ( data not shown ) . Examination of the expression of gata1 ( Figure 3A , n = 46/46; 3B , n = 43/43; and 3C , n = 41/41 ) , βe1-globin ( hbbe1 ) ( Figure 3E , n = 49/49; 3F , n = 51/51; and 3G , n = 49/49 ) , and pu . 1 ( spi1 ) ( Figure 3I , n = 41/41; 3J , n = 41/43; and 3K , n = 45/45 ) by WISH confirmed that the initiation of primitive erythropoiesis and myelopoiesis were intact in the scl-α and -β morphants . We reasoned that the lack of phenotypes in both morphants was likely due to the functional redundancy of scl-α and -β . To test this possibility , we co-injected scl-α MO and scl-β MO to block both protein syntheses ( Figure 3P , n = 45/45; and 3T , n = 50/50 ) , and found that the expression of gata1 , βe1-globin , and pu . 1 were either absent or drastically reduced in the co-injected morphants ( Figure 3D , n = 42/42; 3H , 46/46; and 3L , n = 47/47 ) . This phenotype is very similar to that found in the scl-sp morphants , in which both Scl-α and -β protein expression were eliminated by scl-sp MO ( Figure 1B ) that interfered with the splicing between exon 2 and 3 of the scl gene [37 , 38] . Furthermore , injection of in vitro synthesized scl-α or -β mRNA was sufficient to rescue the expression of gata1 , βe1-globin , and pu . 1 in the scl-sp morphants ( data not shown ) . Taken together , we conclude from these results that scl-α and -β are functionally redundant in the initiation of primitive hematopoiesis . To address their functions in the late developmental stages of primitive erythropoiesis , we examined the scl-α and -β morphants beyond 30 hpf . Although primitive erythropoiesis initiated normally , o-dianisidine staining revealed that the red blood cells ( RBCs ) in the scl-β morphants were significantly reduced by 2 dpf ( data not shown ) and finally not detectable by 3 dpf ( Figure 4C ) . On the other hand , RBCs in the scl-α morphants were normal before 3 dpf ( Figure 4B ) but began to decrease by 4 dpf ( data not shown ) and were severely reduced by 5 dpf ( Figure 4E ) . These data indicate that the loss of either Scl-α or -β protein renders abnormal RBC differentiation at different developmental stages , eventually resulting in anemia . To provide an additional test of this possibility , circulating RBCs were collected from the scl-α and -β morphants , stained with May-Grunwald Giemsa , and compared to those from wild-type embryos . Based on the size of cell , shape of nucleus , and staining of cytoplasm , normal primitive RBCs from 30 hpf to 5 dpf can be classified into four main stages: stage I , basophilic erythroblast; stage II , polychromatophilic erythroblast; stage III , orthochromatophilic erythroblast; and stage IV , mature erythrocyte ( Figure 4G ) . In the 2-dpf wild-type embryos and 2-dpf scl-α morphants , more than 98% of the circulating RBCs were at stage II ( Figure 4H and 4I ) . However , 90% of the circulating RBCs arrested at stage I in the 2-dpf scl-β morphants ( Figure 4J ) . As expected , although the circulating RBCs developed normally before 3 dpf , 80% of them were blocked at stage II in the 4-dpf scl-α morphants ( Figure 4L ) , compared to the number of RBCs at stage III in the 4-dpf wild-type embryos ( Figure 4K ) . These phenotypes concurred with the virtual Northern blot result showing that circulating RBCs from 30-hpf wild-type embryos contain both scl-α and -β , whereas those from 2-dpf wild-type embryos express predominantly scl-α ( Figure 5 ) . Collectively , we conclude that scl-β plays a critical role in the differentiation of basophilic erythroblasts to polychromatophilic erythroblasts , whereas scl-α is pivotal for the transition from polychromatophilic erythroblasts to orthochromatophilic erythroblasts . We next explored the roles of the scl-β and -α isoforms in definitive hematopoiesis . In zebrafish , definitive hematopoietic stem cells originate from the ventral wall of DA at around 26 hpf to 30 hpf , and these cells are enriched in c-myb and runx1 expression [10 , 14 , 15] . We therefore first examined c-myb and runx1 expression in the 30-hpf scl-α and -β morphants . WISH revealed that expression of c-myb and runx1 in the ventral wall of DA was abolished in the scl-β morphants ( Figure 6C , n = 43/45; and 6F , n = 40/43 ) but not in the control embryos ( Figure 6A , n = 40/40; and 6D , n = 42/42 ) or scl-α morphants ( Figure 6B , n = 45/46; and 6E , n = 43/45 ) . As artery endothelial cells appeared to be retained in both scl-α and -β morphants , as indicated by two artery-specific markers deltaC ( dlc ) and grl ( hey2 ) ( Figure S2 ) , these data indicate that scl-β , but not -α , is essential for definitive hematopoietic stem cell development . This result is consistent with the finding that only scl-β is expressed in the ventral wall of DA ( Figure 2 ) . To further test whether scl-β is indeed required for the development of definitive hematopoietic stem cells , we investigated T cell development in both morphants by examining rag1 expression at 5 dpf . As expected , rag1 was detected in the thymus of control embryos and scl-α morphants ( Figure 6G , n = 30/30; and 6H , n = 42/45 ) but not scl-β morphants ( Figure 6I , n = 46/50 ) . Taken together , these data demonstrate that scl-β is essential for the development of definitive hematopoietic stem cells while scl-α is dispensable . To gain insight into the molecular basis underlying the distinct functions of scl-α and -β in hematopoietic cell development , we performed rescue experiments—by co-injecting in vitro synthesized scl-α or scl-β mRNA with scl-sp MO into wild-type embryos—to test whether the lack of the N-terminal 118 aa could lead to the differences in their biological functions . Examination of the expression of βe1-globin and c-myb by WISH showed that either isoform was sufficient to rescue both primitive and definitive hematopoietic defects in the scl-sp morphants ( Figure 7A , n = 35/35; 7B , n = 41/41; 7C , n = 44/44; 7D , n = 47/47; 7E , n = 36/36; 7F , n = 40/45; 7G , n = 41/45; and 7H , n = 42/46 ) . The data indicate that the N-terminal 118-aa segment is not essential for determination of the functions of these two Scl protein isoforms , consistent with previous findings showing that the basic helix-loop-helix domain of the murine SCL protein is sufficient for hematopoiesis [39] . As recent studies have suggested that different SCL protein expression levels are required at different levels of hematopoietic hierarchy [40 , 41] , these findings raise the possibility that the distinct functions of scl-α and -β are due to differences in their protein expression levels , resulting in establishment of a gradient of Scl protein at different stages of hematopoietic hierarchy . To test this hypothesis , we performed immunoblotting of protein extracts from 18-somite-stage wild-type embryos , in which the transcription levels of the scl-α and -β isoforms are similar ( the scl-β RNA is slightly higher ) ( Figure 1A ) . We found that the protein expression level of Scl-β was much lower than that of Scl-α in these embryos ( the Scl-β protein was hardly detectable at all by Western blot; Figure 7I ) . When COS7 cells were transiently transfected with construct expressing either the full-length scl-α or scl-β , the protein expression level of Scl-β was also much lower than that of Scl-α , while their RNA levels were comparable ( Figure 7J ) . These data strongly indicate that a post-transcriptional mechanism is involved in the regulation of Scl-β protein expression level . To test this , equal amounts of in vitro synthesized scl-α and -β mRNA were injected into one-cell-stage wild-type embryos , and protein levels were examined at different time points post-injection ( Figure 7K ) . As anticipated , real-time reverse transcriptase PCR analysis revealed that mRNAs of both isoforms behaved similarly in these injected embryos ( data not shown ) . Immunoblotting of whole embryo protein extracts showed that protein expression levels were comparable at 3 h post-injection , indicating that both isoforms are effectively translated . However , by 4 h post-injection , Scl-β protein level was greatly reduced , while Scl-α level increased ( Figure 7K ) , showing that the low protein expression level of Scl-β was likely due to the rapid degradation of its protein . Taken together , these data strongly indicate that differences in the protein expression levels of Scl-α and -β isoforms , via regulation of their protein stabilities , likely confer their distinct functions in the regulation of hematopoietic cell development .
It is believed that the complexity in morphology and behavior of higher organism is achieved not only by higher gene numbers , but also by multiple protein isoforms being encoded by a single gene locus and by the complexity of protein–protein interactions . The most well studied phenomenon that results in the generation of multiple protein isoforms from a single gene is alternative splicing of pre-mRNA [42] . However , other mechanisms such as use of an alternative promoter—a phenomenon that is as equally widespread in higher organisms as alternative pre-mRNA splicing [43 , 44]—are less appreciated . In this article , we described how zebrafish produce , through alternative promoter sites , two scl isoforms , the full-length scl-α and a novel truncated scl-β ( Figure 1 ) . We further showed that these two scl isoforms manifest distinct temporal and spatial expression ( Figure 2 ) and exert distinct functions in the regulation of primitive and definitive hematopoiesis ( Figures 3–6 ) . The identification of the alternative-promoter-generated scl-β isoform in zebrafish has not only revealed new insight into the roles of scl in the regulation of hematopoietic cell development , but also provided another example to highlight the importance of alternative promoter usage in generating protein and regulatory diversity . Previous studies have revealed that mammals contain several SCL isoforms generated by either alternative splicing , alternative promoters , or alternative translation initiation sites [28–33] . These mammalian SCL isoforms arise from alternative promoters in exon 1a and exon 1b , and encode identical proteins , the full-length SCL . In contrast , scl-β in zebrafish is generated through an alternative promoter site within the scl exon 2 , the equivalent of the mammalian SCL exon 4 , and encodes an N-terminal truncated protein ( Figures 1 and S1 ) . Thus , scl-β is clearly distinct from the previously described mammalian SCL isoforms . One intriguing question raised is whether the mechanism of generating different scl isoforms found in zebrafish is evolutionarily conserved in higher vertebrates , especially in mammals . Considering the facts that ( 1 ) the SCL locus is highly conserved in vertebrates [45] , ( 2 ) there are observations showing that the murine SCL exon 4 has promoter activity in the context of SCL 3′ stem cell enhancer [46] , and ( 3 ) a truncated SCL transcript initiated from exon 4 can be detected in some of the human T cell leukemia cell lines [28 , 29] , we speculate that a scl-β equivalent may exist in higher vertebrate species . Another interesting issue raised by this study is the regulation of scl-α and -β transcripts during hematopoiesis . Notably , scl-β first appears in hematopoietic stem and progenitor cells and soon diminishes in the differentiated primitive RBCs ( Figures 2 and 5 ) . In contrast , scl-α emerges later and is predominantly restricted to RBCs ( Figures 2 and 5 ) . Thus , it appears that an on–off switch , from scl-β to -α expression , must occur during primitive RBC development . Considering the facts that ( 1 ) the earliest definitive hematopoietic stem/progenitor cells located in the ventral wall of DA express only scl-β and ( 2 ) scl-α becomes the predominant isoform expressed in the adult kidney marrow , where definitive hematopoiesis takes place presumably from 5 dpf onwards in zebrafish development , it is conceivable to speculate that this on–off switch may also exist during definitive erythroid cell development . However , it is unclear at this moment whether this on–off switch takes place at the transcriptional level or the post-transcriptional level , or perhaps a combination of both . Nevertheless , we believe that the on–off switch of these scl isoforms must play a crucial role in normal hematopoietic cell development , at least for RBCs , and that the underlying molecular basis of this regulation warrants further studies . Our study has provided evidence indicating that differences in the protein expression levels of the scl-α and -β isoforms are likely to confer their distinct functions in regulating hematopoietic cell development ( Figure 7 ) . Although we cannot rule out the possibility that translational control may contribute to the regulation of their protein expression levels , the fact that the Scl-β protein was initially expressed at a level comparable to that of Scl-α but soon reduced dramatically upon injection of equal amounts of in vitro synthesized scl-α and -β mRNA ( Figure 7K ) strongly indicates that differences in the protein expression levels of the scl-α and -β isoforms are largely due to the rapid turnover of the Scl-β protein . However , the triggers causing the onset of rapid degradation of Scl-β protein in vivo are unclear . Given the differences in their N-terminal residues , one could speculate that , perhaps , the short half-life of the Scl-β protein is mediated through the N-end rule degradation , a common proteolytic pathway that is present in prokaryotes , fungi , plants , and animals [47] . Further biochemical analyses are required to clarify this issue . Finally , our data strongly suggest that the establishment of an appropriate Scl protein gradient at different levels of hematopoietic hierarchy—a low level in hematopoietic stem and progenitor cells and a high level in differentiated RBCs—is essential for hematopoietic cell development . The phenomenon of a lower Scl protein level in hematopoietic stem and progenitor cells correlating to the importance of hematopoietic cell development is intriguing . One possibility is that the specification of definitive stem and progenitor cells requires the low concentration of Scl protein , which occurs by preferential expression of scl-β during early hematopoiesis . However , the fact that injection of either scl-α or -β mRNA is sufficient to rescue the c-myb expression at 30 hpf in the ventral wall of DA in scl-sp morphants ( Figure 7 ) suggests that this may not be the case . A high Scl protein level , which is known to be required for the maturation of RBCs [40 , 41] , has the tendency to promote hematopoietic stem and progenitor cell differentiation into erythroid lineage , so a more likely explanation is that the low concentration of the Scl-β protein ensures the proper expansion of these cell pools by promoting their proliferation rather than their differentiation . In addition , the low concentration of Scl-β may also be crucial for maintaining an unbiased differentiation potential of hematopoietic stem and progenitor cells during ontogeny . Uncovering the molecular basis of scl-α- and -β-mediated actions will provide further insight into our understanding of the specification , proliferation , and differentiation of hematopoietic lineages .
Zebrafish were maintained at 27 to 28 °C as described in [48] . The clos5 and montg234 mutants were kindly provided by Didier Y . R . Stainier ( University of California San Francisco , United States ) and Artemis Pharmaceuticals ( Germany ) , respectively . The full-length scl-α and -β DNA were amplified by RT-PCR and cloned into pCS2+ vector . The scl-5′ and scl-3′ constructs contained the first 414 bp of the 5′ UTR of scl-α and the last 539 bp of the 3′ UTR of scl-α/β , respectively . They were amplified by PCR using two sets of specific primers ( scl-5′: 5′-acttcagtgcatctaaaacctcag-3′/5′-ttttatatccgcgctccctcctc-3′; scl-3′: 5′-tggaaattcaagcgggtaatgac-3′/5′-gggcttttcatataaaatttgtgag-3′ ) and subcloned into pGEM-T Easy and pGEM-T vector ( Promega , http://www . promega . com ) . Total RNA was extracted from wild-type embryos and subjected to 5′ and 3′ RACE using the SMART RACE cDNA Amplification Kit ( Clontech , http://www . clontech . com ) according to the manufacturer's instructions . For 5′ and 3′ RACE , two sets of primers ( scl-5′-P1: 5′-aagttgatgtacttcatggccag-3′; scl-5′-P2: 5′-atacatcccatactgttccgcatctccagc-3′; scl-3′-P1: 5′-gcggaacagtatgggatgtatcct-3′; scl-3′-P2: 5′-ctagtgcgggacgacctc-3′ ) were used . The RACE products were cloned into pGEM-T Easy vector ( Promega ) and subsequently sequenced . The T-Coffee method [49] was used for protein sequence alignment . Total RNA from different stages of embryos , adult kidney , and RBCs were prepared using the RNeasy Kit ( Qiagen , http://www . qiagen . com ) according to the manufacturer's instructions . mRNA was purified using the NucleoTrap mRNA mini kit ( Macherey-Nagel , http://www . macherey-nagel . com ) according to the manufacturer's instructions . Three micrograms of each embryonic mRNA and 30 μg of total kidney RNA were used for Northern blot analysis ( Figure 1A ) . For virtual Northern blot , total RNA from 30-hpf and 2-dpf embryos and RBCs were reverse transcribed into cDNA and then amplified by the SMART PCR cDNA synthesis kit ( Clontech ) . The amplified cDNAs were used as targets for hybridization with the DIG-labeled scl-5′ and scl-3′ probes . DIG labeling was carried out by PCR amplification with the DIG Probe Synthesis Kit ( Roche Applied Science , http://www . roche-applied-science . com ) according to the manufacturer's instructions . Northern blot and virtual Northern blot analyses were performed as previously described [50 , 51] . Fish embryos were stained for 15 min in the dark in o-dianisidine staining solution as previously described [12] . Generation of the DIG-labeled anti-sense RNA probes and whole-mount in situ hybridization were performed as described in [48] . For transverse cryosection , embryos were embedded in OCT solution ( Sakura , http://www . sakura . com ) after WISH and immunochemistry staining . Embedded embryos were sectioned at a thickness of 10 μm using a Leica ( http://www . leica . com ) microtome . The sections were mounted on glass slides and imaged using a Zeiss ( http://www . zeiss . com ) AxioPhot 2 imaging system . Anti-zebrafish Scl-α N-terminal ( aa 17 to 62 , referred to as Ab-Scl-N ) and Scl-α/β C-terminal ( aa 255 to 325 , referred to as Ab-Scl-C ) antisera were generated by immunizing rabbits with the GST-Scl-N and GST-Scl-C fusion proteins using standard protocol . Antibody purification and immunohistochemistry staining were carried out as previously described [52] . Anti-sense MOs ( Gene Tools ) were designed as follows: scl-α MO , 5′-gctcggatttcagtttttccatcat-3′; scl-β MO , 5′-gcggactcaactgcaccattcgagt-3′; scl-sp MO , 5′-agatttaaaatgctcttaccatcgt-3′ . Three nanograms of scl-α MO , 8 ng of scl-β MO , and 8 ng of scl-sp MO mixed with phenol red were separately injected into wild-type embryos at the one-cell stage . Similarly , 3 ng of scl-α MO and 8 ng of scl-β MO were used for the co-injection experiment . Wild-type embryos injected with a mixture of sterile water and phenol red were used as control . Fish embryos were anesthetized in calcium- and magnesium-free PBS ( pH 7 . 4 ) containing 0 . 02% tricaine ( Sigma-Aldrich , http://www . sigmaaldrich . com ) and 1% BSA ( Sigma-Aldrich ) . After tail clipping using surgical scissors , blood cells were collected by pipetting and cytospun onto slides by centrifugation at 450 rpm for 3 min using a Cytospin 4 ( Thermo Scientific , http://www . thermo . com ) . The slides were then air-dried and subjected to May-Grunwald Giemsa staining according to the standard protocol . In vitro transcription was carried out using the mMESSAGE mMACHINE sp6 kit ( Ambion , http://www . ambion . com ) according to the manufacturer's instructions . For rescue experiments , 200 pg of scl-α or -β RNA was co-injected with 8 ng of scl-sp MO into wild-type embryos at the one-cell stage . For protein stability analysis in fish embryos , 500 pg of in vitro synthesized scl-α or -β mRNA was injected into embryos at the one-cell stage , and protein extracts were prepared as described in [48] . Total RNA from both scl-α- and -β-injected embryos at 6 h post-injection were extracted and reverse transcribed using random hexamer as primer . The cDNAs were examined with real-time PCR using scl-specific primers ( scl-961F , 5′-ctagtgcgggacgacctc-3′; scl-1528R , 5′-ggaactaaactgtgccga-3′ ) , which can amplify both injected scl-α and -β mRNA . COS7 cells were maintained in DMEM ( Gibco , http://www . invitrogen . com/content . cfm ? pageid=11040 ) supplemented with 10% bovine calf serum ( Hyclone , http://www . hyclone . com ) . Transient transfection was carried out by SuperFect Reagent ( Qiagen ) according to the manufacturer's protocol . Real-time RT-PCR was performed to ensure that the transfection efficiency was similar using the same RT-PCR protocol for protein stability analysis in fish embryos . Cell extract preparation and Western blot were carried out as described previously [50] . | Hematopoiesis is the process that generates all the body's blood cells . In vertebrates , hematopoietic development occurs in two phases: a transitory embryonic , or primitive , wave produces only erythrocytes ( red blood cells ) and myeloid cells; an adult , or definitive , wave gives rise to at least three blood cell lineages , including erythrocytes and two types of immune cells—myeloid cells and lymphocytes . Previous studies have shown that the stem-cell leukemia ( SCL ) gene is essential for hematopoietic stem cell specification and erythrocyte maturation . Yet how SCL regulates these distinct processes is not fully understood . This study demonstrates that zebrafish produce a smaller isoform of scl , scl-β , that plays an overlapping role with the full-length scl-α in the initiation of primitive hematopoiesis , but possesses distinct functions in regulating primitive erythrocyte maturation and definitive hematopoietic stem cell development . We further show that the distinct functions of scl-α and -β are likely due to differences in their protein expression level through the regulation of protein stability . We postulate that hematopoietic cell development at different levels of hierarchy is governed by a gradient of the Scl protein created by temporal and spatial expression of different scl isoforms . | [
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] | 2007 | Distinct Functions for Different scl Isoforms in Zebrafish Primitive and Definitive Hematopoiesis |
Positive-strand RNA virus infections can induce the stress-related unfolded protein response ( UPR ) in host cells . This study found that enterovirus A71 ( EVA71 ) utilizes host UDP-glucose glycoprotein glucosyltransferase 1 ( UGGT1 ) , a key endoplasmic reticulum protein ( ER ) involved in UPR , to enhance viral replication and virulence . EVA71 forms replication complexes ( RCs ) on cellular membranes that contain a mix of host and viral proteins to facilitate viral replication , but the components and processes involved in the assembly and function of RCs are not fully understood . Using EVA71 as a model , this study found that host UGGT1 and viral 3D polymerase co-precipitate along with other factors on membranous replication complexes to enhance viral replication . Increased UGGT1 levels elevated viral growth rates , while viral pathogenicity was observed to be lower in heterozygous knockout mice ( Uggt1 +/- mice ) . These findings provide important insight on the role of UPR and host UGGT1 in regulating RNA virus replication and pathogenicity .
Positive-strand RNA viruses are capable of infecting a wide range of hosts , ranging from algae to humans . The mechanism underlying this broad range of pathogenicity spanning different hosts and tissue types involves the use of cellular membranes for viral genomic RNA replication , which provides a number of key benefits . Membrane structures allow buildup of a high local concentration of viral proteins , while also serving as a protective screen against protease cleavage . Membranes can further provide a structural scaffold that facilitates the correct spatial organization of viral replication complex ( RC ) components , and RCs can also be protected by the membrane against host infection sensors or other defense mechanisms [1 , 2] . Different positive-strand RNA viruses utilize different cellular membranes , resulting in a variety of morphological alterations; however , the sequences and functional domains of key viral proteins involved in membrane utilization are quite conserved among these viruses , suggesting that there are common strategies for the incorporation of cellular membranes into viral RCs [3 , 4] . Picornaviruses are a family of small positive-strand RNA viruses that include several notorious animal and human pathogens , such as rhinoviruses , Coxsackie viruses , foot and mouth disease virus , hepatitis A virus , and enterovirus A71 ( EVA71 ) . EVA71 typically causes hand , foot , and mouth disease ( HFMD ) , which is generally regarded as a mild childhood illness [5]; however , not along after its initial isolation in California during 1969 [6] , several deadly EVA71 epidemics occurred in the 1970s [7–9] , and the virus has recently been associated with severe neurological complications , such as brain stem encephalitis and acute flaccid paralysis , in Asian infants and young children [10] . Several large HFMD outbreaks in the Asia-Pacific region have also occurred in recent years , including Malaysia , 2007 [11]; Taiwan , 1998 [12]; Singapore , 2000 [13]; Japan , 1997 and 2000 [14]; Shandong , China , 2007 [15]; and Fuyang , China , 2008 [16 , 17] . EVA71 genomic RNA is about 7 , 400 nucleotides ( nt ) long , and upon viral entry into host cells , the RNA genome is directly translated into one polyprotein , which is then cleaved by virus-specific proteases into structural and replication proteins . About 10 mature proteins and several other intermediate products are generated during this process , and these elements go on to perform many independent functions in the viral life cycle [18 , 19] . One non-structural protein that plays a key role in EVA71 replication is the 3D viral polymerase , which is encoded in the P3 viral genome region and is cleaved by viral proteases from the 3CD precursor proteinase after translation [20–22] . The 3D polymerase is an RNA-dependent RNA polymerase ( RdRp ) responsible for plus-strand and minus-strand viral RNA synthesis in viral RCs [23 , 24] . The first step in this process involves uridylylation of the small viral protein , VPg , in which two uridine monophosphate ( UMP ) molecules bind to the hydroxyl group of a tyrosine residue near the N-terminus of VPg via a reaction catalyzed by the viral 3D polymerase [25] . The 3D polymerase can also facilitate viral RNA chain elongation in viral RCs [26–29] , and is known to interact with several host proteins , including Sam68 [30] . During picornavirus infection , viral RNA replication occurs on the cytoplasmic surfaces of single-membrane vesicles derived from the endoplasmic reticulum ( ER ) , and the membranes can serve to accelerate RC assembly during positive-strand genomic RNA replication [31] . Viral proteins 2BC and 3A are known to be involved in viral RC formation , and these proteins contain hydrophobic domains that allow them to interact extensively with cellular membranes [32 , 33] . Viral protein 3A also plays an important role in membrane reorganization through its interactions with cellular proteins such as GBF1 , Arf1 , and PI4KIIIβ [34–37] . Other non-structural viral proteins are known to interfere with cellular membrane metabolism , and even rearrange subcellular organelles . Many viral and host proteins and lipids are involved in the membrane remodeling process induced by RCs , and the underlying mechanisms are complex and not well understood; for example , the 3D viral polymerase does not have obvious membrane binding sequences or properties , and its presence in RCs is therefore quite puzzling . To enhance the current understanding of RC components and viral RNA replication following picornavirus infection , we used EVA71 as a model to evaluate interactions between the 3D viral polymerase and host proteins after virus infection . Proteins associated with 3D polymerase were immunoprecipitated with an anti-3D monoclonal antibody , and results showed that the host protein , UDP-glucose glycoprotein glucosyltransferase 1 ( UGGT1 ) , associates with 3D polymerase . UGGT1 , also known as HUGT1 , is a soluble ER protein that selectively reglucosylates unfolded glycoproteins , thus providing quality control for proteins transported out of the ER . Viral infections drive the accumulation of unfolded and misfolded proteins in the ER [38] , and to reduce the adverse effects of such accumulation , the host cell utilizes a stress-related defense mechanism known as the unfolded protein response ( UPR ) to decrease the load of newly synthesized proteins within the ER and eliminate incorrectly folded proteins [39–41] . Alternatively , proteins possessing non-native structures are recognized by UGGT1 , reglucosylated , and targeted for chaperone rebinding and ER retention [42] . UGGT1 can also add glucose molecules to the N-linked glycans of non-glucosylated substrates that fail quality control tests , thereby supporting additional rounds of chaperone binding and ER retention [42–46] . It has been shown that the disruption of protein folding in the ER induces UGGT1 expression [47] . Importantly , during EVA71 infection , we found that UGGT1 expression levels increase , and UGGT1 also redeploys from the ER to the cytoplasm , where it acts as a positive regulator of viral RNA synthesis . The 3A viral protein was also shown to increase UGGT1 and 3D polymerase levels in the membrane fraction . We further observed that the pathogenicity of EVA71 infection decreased in heterozygous Uggt1 knockout mice . These findings shed light on the molecular processes driven by host UGGT1 and viral 3D protein association , and provide important insight on the relationship between virus pathogenicity and viral-host interactions .
To better understand how the EVA71 3D polymerase associates with host proteins and other components of the viral replication machinery at RCs , we sought to identify novel host factors that associate with the 3D polymerase in RCs . Accordingly , an anti-3D monoclonal antibody was used to perform immunoprecipitation assays , in order to purify proteins associating with the 3D polymerase in infected cells . We immunoprecipitated mock-infected and EVA71-infected cell lysates with this anti-3D monoclonal antibody , and subsequently identified seven major protein bands that appeared in the EVA71-infected lysates , but not in the mock-infected lysates ( Fig 1A ) . We excised the protein bands that specifically associated with the 3D polymerase as shown in Fig 1A , digested the excisions with trypsin , and subjected them to matrix-assisted laser desorption/ionization time-of-flight mass spectrometry ( MALDI-TOF MS ) analysis . Table 1 presents these seven proteins and their accession numbers , as obtained from the US National Center for Biotechnology Information ( NCBI ) protein database ( Table 1 ) . The seven proteins included one viral protein , the EVA71 3CD polyprotein ( Fig 1A , band 5 ) , and six host proteins: UGGT1 , elongation factor 2 , interleukin enhancer binding factor 3 ( ILF3 ) , lamina-associated polypeptide 2 isoform alpha , T-complex protein 1 subunit theta , and eukaryotic translation initiation factor 3 . The identified peptide sequences accounted for 24% of the UGGT1 sequence ( Table 1 and S1 Fig ) . The ER protein , UGGT1 ( Fig 1A , band 1 ) , was selected for further investigation . We performed Western blot analysis to confirm that UGGT1 associated with the 3D polymerase following EVA71 infection . Co-IP experiments using EVA71-infected or mock-infected RD cell extracts were conducted , and the anti-3D antibody was able to immunoprecipitate UGGT1 ( Fig 1B , lanes 3 and 4 ) , while reciprocal co-IP experiments showed that the anti-UGGT1 antibody was also able to immunoprecipitate 3D polymerase in EVA71-infected cell lysates ( Fig 1B , lanes 7 and 8 ) . Viral capsid proteins were not observed in the UGGT1-viral protein complexes ( Fig 1B ) . These results provide evidence that UGGT1 interacts with the EVA71 viral 3D polymerase . Host cells can mobilize the UPR in an attempt to restrict viral infection , and UGGT1 is known to be a key UPR factor in the ER . To ascertain UGGT1 expression levels in EVA71-infected cells , we compared UGGT1 levels in mock-infected and infected cells . UGGT1 expression levels were found to increase upon viral infection ( Fig 1B and 1C , input lysate ) . It is known that the 3D viral polymerase associates with viral RNA , and to determine whether UGGT1 interaction with 3D polymerase was mediated by RNA , we examined the interaction between UGGT1 and viral genomic RNA . Treatment with RNase A prior to co-IP assays did not reduce UGGT1 interaction with the EVA71 3D polymerase , indicating that this interaction was not mediated by viral genomic RNA ( Fig 1C , lanes 5 and 6 ) . Host protein ILF3 is an RNA-binding protein that associates with the 3D viral polymerase ( Table 1 ) . Here , ILF3 served as a positive control for RNase A treatment . ILF3 association with the 3D viral polymerase was reduced after RNase A was applied prior to co-IP assays . Degradation of RNA was confirmed by RNA gel analysis ( Fig 1C ) . To clarify the components of the UGGT1-3D complex , we purified the membrane fraction of EVA71-infected cells , and performed an immunoprecipitation assay to identify other viral proteins involved . The results shown in Fig 1D indicate that the 3A viral protein was also present in the UGGT1-3D complex , and this provides evidence to support an indirect interaction dependent on other viral proteins between UGGT1 and the 3D polymerase . In addition , as the 3D viral polymerase is located in the nucleus and cytoplasm at different stages of viral replication , while UGGT1 is located predominantly in the ER , we therefore sought to examine how UGGT1 and the 3D polymerase colocalize intracellularly during EVA71 infection , using fluorescence confocal microscopy . In mock-infected cells , UGGT1 was predominantly localized in the cytoplasm ( Fig 1E , panel 4 ) , while in EVA71-infected cells , both the 3D polymerase and UGGT1 were localized in the cytoplasm at 6 h post-infection ( Fig 1E , panel 8 ) . Moreover , when an anti-dsRNA antibody was used to highlight the location of RCs in an immunofluorescence assay , staining results showed that UGGT1 associates with RCs in the cytoplasm ( Fig 1F ) . However , co-IP experiments conducted in uninfected cells co-expressing Flag-UGGT1 and HA-3D showed that anti-HA antibodies did not precipitate Flag-UGGT1 , nor did anti-Flag antibodies precipitate HA-3D . Anti-HA antibodies also did not co-immunoprecipitate endogenous UGGT1 from RD cells expressing HA-3D ( Fig 2 ) . These results show that UGGT1 can co-precipitate with EVA71 viral polymerases in RCs , and further indicate that viral infection is essential for UGGT1 co-purification with the EVA71 3D polymerase . Together , these findings confirm that upon viral infection , UGGT1 levels increase , and UGGT1 co-precipitates with 3D polymerase and other factors on membranous replication complexes . To ascertain the effect of UGGT1 on viral replication and propagation , we infected ( negative control ) NC or UGGT1 siRNA-transfected cells with a high titer of EVA71 ( MOI = 10 ) , and assessed 3D polymerase expression at 6 h post-infection by confocal microscopy . We first analyzed the effect of UGGT1 knockdown on siRNA-transfected cell viability . Cell viability was measured by a CellTiter-Glo Luminescent Cell Viability kit ( Promega ) , which quantitates the ATP generated in viable cells . The results presented in S2 Fig demonstrate that cell proliferation and viability were not significantly different between NC siRNA- and UGGT1 siRNA-transfected cells ( S2 Fig ) . In UGGT1 siRNA-treated cells , viral protein expression was significantly lower compared to NC siRNA-treated cells ( Fig 3A , panels 10 and 14 ) . These results suggest that UGGT1 plays a critical role in enhancing viral replication . To further evaluate the effects of UGGT1 on EVA71 replication rates , we treated RD cells with NC or UGGT1 siRNA , and then infected these cells with a high ( MOI = 10 ) or low ( MOI = 0 . 1 ) EVA71 titer . The plaque assay was used to detect viral yields at various timepoints post-infection . Viral replication rates were found to be lower in uggt1 knockdown cells as compared to NC siRNA-treated cells , regardless of MOI levels ( Fig 3B and 3C ) . These results support the hypothesis that UGGT1 is a positive regulator during EVA71 infection . We repeated this experiment in SF268 glioblastoma ( SF268 ) cells to determine whether the effects of UGGT1 on viral replication are specific to a given cell type . Results showed that viral replication rates were also lower in UGGT1 siRNA-treated SF268 cells , as compared to NC siRNA-treated cells ( S3A and S3B Fig ) . To avoid siRNA off-target effects , we used EVA71 to infect cells overexpressing UGGT1 , and subsequently measured virus yields at 4 , 6 , and 8 h post-infection . The results showed that viral replication increased when UGGT1 was overexpressed in infected cells ( Fig 3D , S3C and S3D Fig ) . We further evaluated the role of UGGT1 in enterovirus D68 ( EVD68 ) . EVD68 is classified in a different group as other more common enteroviruses , such as EVA71 and coxsackievirus A16 , but this does not mean it is less pathogenic: in a 2014 outbreak of EVD68 , a total of 1 , 152 people in United States were confirmed as having acute respiratory infections caused by EVD68 . It is important for emergency clinicians to recognize this viral illness , because it can lead to respiratory distress that requires hospitalization or , in some instances , intensive care [48] . After infecting NC or UGGT1 siRNA-treated cells with EVD68 , we evaluated viral replication rates , and observed that EVD68 viral titers were lower in UGGT1 siRNA-transfected cells as compared to NC siRNA-transfected cells ( S3E and S3F Fig ) . These results confirm that UGGT1 is a positive regulator of EVA71 and EVD68 replication , and suggest that it may be a commonly utilized host factor for viral replication in enteroviruses . To assess whether the enzymatic activity of UGGT1 is critical for viral replication , we generated UGGT1 variants lacking monoglucosylation activity ( UGGT1 ( mut ) ) . Previously , it was shown that UGGT1 enzymatic activity would be abolished after the elimination of monoglucosylation activity via mutation [47] . We overexpressed UGGT1 or UGGT1 ( mut ) in infected cells , and subsequent comparison of viral yields showed no significant difference ( S4 Fig ) , suggesting that UGGT1 enzymatic activity is not critical for viral replication . In light of this , we propose that UGGT1 may primarily act as a protein bridge to facilitate viral replication . To assess the role of UGGT1 in viral pathogenicity in vivo , we generated Uggt1 knockout mice from the KOMP-CSD ES cell resource [43] . The Uggt1 gene deletion destroys reglucosylation activity in cells and is embryonically lethal at day E13 in mice [45] . Homozygous Uggt1 knockout mice were embryonically lethal; however , heterozygous mice were viable , fertile , developed normally , and did not reveal any obvious phenotypic alterations up to adulthood ( Fig 4A ) . Heterozygous Uggt1 knockout mice expressed only 50–60% of UGGT1 as compared to their UGGT1 wild-type littermates ( Fig 4B ) . A mouse-adapted EVA71 strain with increased virulence in mice , MP4 , was generated after four serial passages of the parental EVA71 strain 4643 in mice [46] . To quantify EVA71 replication rates in wild-type or heterozygous Uggt1 knockout mice , the viral load in different mouse tissues on Day 3 after EVA71 infection was assessed . EVA71 was detected in the brain ( Fig 4C ) and muscle tissues ( Fig 4D ) , but the viral load in Uggt1 heterozygous knockout mice was significantly lower than that in wild-type mice . These results prompted us to investigate the virulence of EVA71 in Uggt1 heterozygous knockout mice . We challenged 10-day-old wild-type or heterozygous Uggt1 knockout mice with a 105 plaque-forming unit ( PFU ) /mouse dose of EVA71 strain MP4 . Wild-type mice displayed severe limb paralysis on Day 4 after infection , while heterozygous knockout mice only demonstrated mild limb paralysis ( Fig 4E ) . Infected wild-type mice began to die on Day 8 after infection , whereas heterozygous Uggt1 knockout mice began to die on Day 10; however , the 90% survival rate in infected heterozygous knockout mice was still significantly higher ( P < 0 . 001 ) than the 0% survival in wild-type mice ( Fig 4F ) . To further ascertain if UGGT1 plays a similarly important role in other virus families with regard to enhancing virulence and pathogenicity , we selected the Japanese Encephalitis Virus ( JEV ) from the family Flaviviridae to study the role of UGGT1 upon virus infection . First , we performed Western blot analysis to confirm the association between UGGT1 and the NS5 polymerase following JEV infection . Immunoprecipitation experiments using JEV-infected or mock-infected BHK-21 cell extracts were conducted , and the anti-UGGT1 antibody was able to immunoprecipitate NS5 polymerase only in JEV-infected cell lysate ( S5A Fig ) . To determine growth efficiency of the virus in mouse brains , an experiment was carried out in suckling mice by intracranial inoculation with 104 PFU/mouse of the T1P1 JEV strain . After 7 days post-infection , we collected suckling mice brain tissue , and performed a plaque assay to determine viral titers . The results indicated that UGGT1 was able to associate with JEV polymerase NS5 and enhance viral growth efficiency in suckling mice tissue ( S5B Fig ) . These results show that UGGT1 knockdown can reduce EVA71 and JEV virulence and improve disease outcome . The EVA71 life cycle comprises entry , viral mRNA translation , viral RNA synthesis , and virus assembly . To evaluate the biological significance of UGGT1 in EVA71 replication , we examined the effects of UGGT1 on EVA71 replication efficiency . NC and UGGT1 siRNA knockdown RD cells were transfected with EVA71-Luc replicon RNA , and cell firefly luciferase activity ( measured in relative light units , RLU ) was measured at 6 h post-transfection . In EVA71-Luc replicon RNA , the viral genome P1 region was replaced with a firefly luciferase reporter gene , and luciferase expression therefore reflected viral replication . In UGGT1 siRNA-treated cells , EVA71-Luc replicon luciferase activity was reduced to 55% of the activity in control cells ( Fig 5A ) . This could be due to loss of UGGT1 promotion of either viral mRNA translation or viral RNA replication . We therefore examined the effect of UGGT1 on EVA71 cap-independent translation first , using dicistronic and monocistronic IRES-mediated translation assays [49] . In the dicistronic translation assay , the first cistron ( Renilla luciferase , RLuc ) involved cap-dependent translation , while the second cistron ( Firefly luciferase , FLuc ) required EVA71 IRES-dependent translation . The ratio of FLuc expression to RLuc expression reflects IRES-mediated translation activity . We transfected RD cells with NC or UGGT1 siRNA , and a dicistronic reporter plasmid was then co-transfected . After 48 h post-transfection , cell lysates were collected and used to calculate the ratio of FLuc to RLuc . The results showed that dicistronic IRES activity in NC siRNA-treated cells was not significantly superior to the activity in UGGT1 siRNA-treated cells ( S6 Fig ) , and monocistronic IRES activity also showed no significant difference between NC and UGGT1 siRNA-treated cells ( Fig 5B ) . These results indicate that assisting viral mRNA translation is not the role played by UGGT1 in EVA71 infection . As UGGT1 can be co-purified with the 3D polymerase , we speculated that UGGT1 may facilitate EVA71 replication by enhancing viral RNA synthesis . To ascertain this , we first monitored viral RNA production in NC or UGGT1 siRNA-treated RD cells that were subsequently infected with EVA71 . Intracellular RNA was isolated at different intervals post-infection , and EVA71 viral RNA was measured using quantitative real-time reverse transcription polymerase chain reaction ( RT-PCR ) . Results showed that viral RNA production was 33% lower in UGGT1 siRNA-treated cells , as compared to NC siRNA-transfected cells ( Fig 5C ) . Viral RNA levels were further investigated in Uggt1 knockdown cells . EVA71 was used to infect cells , and viral RNA was extracted at various timepoints post-infection . Slot blot analysis , using specific RNA probes that recognize positive or negative sense EVA71 RNA , was used to monitor viral RNA synthesis . The results in Fig 5D show that levels of both positive and negative sense EVA71 RNA were lower in UGGT1 siRNA-treated cells than NC siRNA-treated cells; specifically , positive-strand RNA levels were reduced by 20% in UGGT1 siRNA-treated cells , while negative-strand RNA levels were reduced by 54% ( Fig 5D ) . These results suggest that UGGT1 likely acts to enhance viral RNA synthesis during EVA71 infection . UGGT1 is a key quality control factor and protein folding sensor of the ER . To determine the localization of UGGT1 in cells following EVA71 infection , we used an anti-calnexin ( CNX ) antibody to evaluate proteins located in the ER in an immunoprecipitation assay . CNX is a transmembrane protein on the ER . In the absence of infection , UGGT1 and CNX were shown to colocalize in the ER ( Fig 6A , panels 5 and 21 ) , but some UGGT1 began deploying out of the ER to colocalize with the 3D viral polymerase upon EVA71 infection ( Fig 6A , panels 20 and 22 ) , to the point where little UGGT1 remained in the ER with CNX . UGGT1 and CNX signals overlapped by more than 75% in mock-infected cells , but this overlap was reduced to less than 55% in EVA71-infected cells ( Fig 6B ) . We further performed subcellular fractionation to separate the cytosol and microsome fractions in mock- or EVA71-infected cell extracts . Microsomes are vesicle-like artifacts re-formed from pieces of the ER when cells are broken up in the laboratory , and can be separated from other cellular components by differential centrifugation . The cellular protein , calnexin , serves as a marker for the ER component in the microsome fraction . UGGT1 was predominantly located within the ER microsome in the mock cell lysates ( Fig 6C , lanes 3 and 5 ) ; however , during EVA71 infection , UGGT1 was found to deploy out of the ER microsome . The proportion of UGGT1 external to the ER rose from 11% to 37% upon viral infection ( Fig 6C , lane 3 and 4 ) . EVA71 infection induces the rearrangement of intracellular ER membranes into characteristic vesicles that assemble into viral RCs . According to Fig 1D and 1F , UGGT1 colocalizes at RCs in association with the 3D viral polymerase; however , the 3D polymerase does not possess obvious membrane-binding sequences or properties , and therefore it is unclear as to how it came to be present in RCs . In contrast , viral protein 3A contains hydrophobic domains and extensively interacts with the cellular membranes that form RCs , and thus can play an important role in membrane reorganization through its interactions with host cellular proteins . To investigate the effect of UGGT1 co-precipitation with the 3D polymerase upon RC formation , we transfected plasmids expressing viral protein 3A , 3AB , or 3D into cells , and performed the membrane protein fractionation assay . ER membranes in cells were modified by the expression of 3A and 3AB . Levels of UGGT1 and 3D polymerase in the membrane protein fraction of 3A and 3D co-expressing cells were higher than that from cells expressing 3D alone ( Fig 7A ) . This indicates that the presence of viral proteins 3A or 3AB can enhance levels of UGGT1 and the 3D viral polymerase in the membrane protein fraction . To observe the effect of viral protein 3A upon the enhancement of UGGT1 levels in the membrane protein fraction , we used only 3A- or 3AB-expressing cells in the fractionation assay . Results showed that expression of 3A or 3AB enhanced the amount of UGGT1 by 2 . 1- and 1 . 8-fold in the membrane protein fraction ( Fig 7B ) . To evaluate the effect of UGGT1 levels on the amount of 3D polymerase in the membrane protein fraction , we co-transfected 3A- or 3AB-expressing plasmids with pFLAG-3D into NC or UGGT1 siRNA-treated cells , and compared the amount of 3D polymerase in the membrane protein fractions . Fig 6C shows that the amount of 3D polymerase in Uggt1 knockdown cells decreased to just 90% ( 3A+3D ) or 30% ( 3AB+3D ) of levels in NC siRNA-treated cells ( Fig 7C ) . We further performed an experiment assessing 3D recruitment to cell membranes with UGGT1 knockdown in the absence of 3A or 3AB . It is well-documented in poliovirus experimental systems that 3D interacts with 3AB , and therefore it is important to ascertain whether UGGT1 directly recruits 3D , or if it merely facilitates 3D-3A interaction . In Fig 7D , the results indicated that the level of 3D recruitment to cell membranes was the same between NC siRNA- or UGGT1 siRNA-treated cells . These results show that UGGT1 can indirectly facilitate 3D-3A interactions ( Fig 7D ) , and demonstrate that although the 3A viral protein can act to enhance levels of UGGT1 and the 3D viral polymerase in membrane protein fractions , the presence of 3D is also partly dependent on UGGT1 . To the best of our understanding , UGGT1 is the first identified host protein that deploys from the ER to the cytosol following EVA71 infection , and our results indicate that UGGT1 acts to promote 3D viral polymerase levels in the viral protein 3A-associated membrane fraction , which in turn may enhance viral replication and increase viral titers .
Viral infection typically triggers an arms race between the virus and host cell . For example , host cells can induce UPR in the ER to restrict viral infection , but viruses can counter this by manipulating the UPR to facilitate viral propagation . In this study , we showed that expression of the key UPR factor , UGGT1 , not only increases upon viral infection , but UGGT1 interaction with the EVA71 3D polymerase also has positive effects on viral growth and pathogenicity as well . Immunoprecipitation assays and MALDI-TOF analysis results indicate that the 3D viral polymerase co-precipitates with UGGT1 during EVA71 infection ( Figs 1 and 2 ) , and this interaction promotes EVA71 replication ( Fig 3 ) . Furthermore , heterozygous uggt1 knockout mice demonstrated lower EVA71 pathogenicity than wild-type mice ( Fig 4 ) , and this may be due to reduction of positive- and negative-strand viral RNA synthesis in the absence of UGGT1 ( Fig 5 ) . We also noted that UGGT1 deploys from the ER to the cytosol upon EVA71 infection ( Fig 6 ) , where it enhances 3D polymerase levels in the membrane fraction involved in RC formation; this process is facilitated by viral protein 3A , which acts to enhance the amount of UGGT1 in the membrane fraction ( Fig 7 ) . Together , these results confirm that EVA71 can utilize the UPR host defense mechanism and the UPR factor UGGT1 to facilitate viral RNA synthesis and pathogenicity , via UGGT1 co-precipitation with the 3D viral polymerase at RCs . We used immunoprecipitation assays to identify seven proteins that co-precipitate with the 3D polymerase , and future research could include the evaluation of other 3D polymerase-interacting host proteins as to their involvement in EVA71 replication , particularly ILF3 ( Table 1 ) . ILF3 acts to facilitate double-stranded RNA-regulated gene expression at the post-transcriptional level [50 , 51] . In recent years , investigators have developed an increasing interest in ILF3 and its interaction with select viral proteins [52–54] . It is known that ILF3 interacts with the 3’ stem-loop structure of dengue RNA and serves as a positive regulator of dengue virus replication [55]; however , ILF3 is also known to inhibit influenza virus replication during the early phase of infection via direct interactions with viral nucleoproteins [56] . These findings suggest that ILF3 can play both positive and negative regulatory roles in different types of viral infections . There is currently no research on the role of ILF3 in the EVA71 life cycle , and therefore further investigation on the effects of ILF3 in this respect could have significant import . Incidentally , although other proteins known to associate with viral genome RNA were also identified in Table 1 , including elongation factor 2 and eukaryotic translation initiation factor 3 [57 , 58] , our results show that RNase A treatment did not reduce the co-precipitation between UGGT1 and the 3D viral polymerase ( Fig 1C ) , and indicate that viral genomic RNA does not mediate UGGT1-3D interaction . Further research showed that viral proteins 3C , 3AB , and 3A also co-purify with the 3D-UGGT1 complex , and may act to facilitate UGGT1 and 3D interaction . Previous studies have found that picornavirus RNA replication occurs on the cytoplasmic surfaces of double-membrane vesicles originating from the ER , Golgi , and lysosomes in infected cells [31 , 59–61] . Poliovirus-induced membrane vesicles have also been linked to intracellular vesicular traffic involving COPII-dependent vesicles [62] . A recent study showed that poliovirus enriches membranes with phosphatidylinositol-4 phosphate , and promotes RNA replication through the recruitment of relevant viral and cellular proteins [37] . Our findings were similar in that UGGT1 also distributes from the ER to the cytosol to co-localize with the 3D viral polymerase , and this may help to facilitate EVA71 RC formation . To our understanding , this is the first study to report on an ER protein deploying to the cytosol to co-localize with the 3D viral polymerase . However , further research is needed to determine the exact location of UGGT1 within the viral RC membrane structure , perhaps by using an electron microscope . This research could also include further examination of the effects of UGGT1 and 3D polymerase association on the membrane secretory pathway . In S5 Fig , we found that UGGT1 associated with JEV polymerase NS5 upon viral infection , and enhanced viral pathogenicity . However , the UGGT1 and NS5 interaction may be direct or indirect . In future , we will seek to perform additional experiments to detect other cellular or viral proteins involved in the UGGT1-NS5 complex . This research is expected to provide more information regarding the role of UGGT1 in flavivirus replication . Mice have two UGGT genes , Uggt1 and Uggt2 [47] , but only the Uggt1 gene product displays reglucosylation activity , and its deletion halts reglucosylation activity in cells [45] . However , the product of Uggt2 has no reglucosylation activity , and its function is unknown . When 80% of UGGT2 is replaced with the UGGT1 N-terminal substrate recognition domain , reglucosylation activity can be partly restored in vitro , demonstrating that the remaining 20% of the UGGT2 C-terminal region can serve as a functional glucosyltransferase [63] . To ascertain whether UGGT1 activity is required during viral replication , or whether UGGT1 merely acts as a protein bridge , we generated UGGT1 mutation variants lacking monoglucosylation activity , and subsequently performed UGGT1 overexpression experiments , with the results shown in S4 Fig . After comparing viral yields between cells in which UGGT1 or UGGT1 ( mut ) was overexpressed , we found that there was no significant difference , suggesting that the enzymatic activity of UGGT1 is not required to enhance viral growth . We therefore propose that UGGT1 may primarily serve as a protein bridge that facilitates viral replication . In summary , our results demonstrate that UGGT1 can co-precipitate with the 3D polymerase at EVA71 RCs to increase viral RNA replication . This is the first study to describe the deployment of an ER protein to the cytosol upon viral infection , and the interesting role of UGGT1 in EVA71 replication suggests that it may provide insight into the development of novel anti-EVA71 strategies . Investigators have already designed several small molecular drugs that target the 3D viral polymerase [64–67] , and thus it may be feasible to develop therapies that target either the interaction between 3D and UGGT1 , or between 3D and RCs . Ascertaining the functions of other cellular factors in positive-strand RNA virus replication could further facilitate the development of unique antiviral strategies , or perhaps allow the harnessing of these viral proteins for other applications .
All animal experiments were conducted in accordance with the policies and procedures set forth by the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . All procedures were approved by the Institutional Animal Care and Use Committee of Chang Gung University , Taiwan ( IACUC approval number CGU15-017 ) . Human embryonal rhabdomyosarcoma ( RD; from American Type Culture Collection: CRL-1620 ) and human glioblastoma ( SF268; provided by Dr . Jim-Tong Horng lab at Chang Gung University , Taiwan ) cells were maintained in Dulbecco's Modified Eagle Medium ( DMEM; Gibco , Grand Island , NY ) supplemented with 10% fetal bovine serum ( FBS; Gibco ) , and cultured at 37°C in a 5% CO2 atmosphere . Hamster kidney fibroblast ( BHK-21; from American Type Culture Collection: CCL-10 ) cells were maintained in RPMI 1640 Medium ( Gibco , Grand Island , NY ) supplemented with 2% fetal bovine serum ( FBS; Gibco ) , and cultured at 37°C in a 5% CO2 atmosphere . For transfection studies , subconfluent ( 70% ) monolayer cultures were transiently transfected or cotransfected with the respective plasmids , using Lipofectamine 2000 ( Invitrogen , Carlsbad , CA ) . Transfected cultures were incubated for a further 48 h before being used in pull-down or co-immunoprecipitation ( Co-IP ) assays . The pFLAG-UGGT1 plasmid was constructed by amplifying UGGT1 from RD cell total RNA by RT-PCR , using a UGGT1 primer ( 5′-ATAAGAATGCGGCCGCGGGCTGCAAGGGAGACGCGAG-3′ ) containing a NotI restriction enzyme cutting site , and another primer ( 5′-GCTCTAGATCATAATTCTTCACGTTTCT-3′ ) containing a XbaI restriction enzyme site . The derived UGGT1 sequence was then cloned into a p3xFLAG-Myc-CMV vector ( Sigma-Aldrich , Munich , Germany ) . Plasmid pHA-3D was constructed by amplifying the sequence encoding the 3D viral polymerase from the EVA71 full-length infectious cDNA clone via PCR , using an EVA71 primer ( 5′-CGGAATTCCGATGGGTGAGATCCAATGGAT-3′ ) containing a EcoRI restriction enzyme site and another primer ( 5′-ACCTCGAGATCACAATTCGAGCCAATTTC-3′ ) containing a XhoI restriction enzyme site . The derived sequence was then cloned into a pCMV-HA vector ( Clontech , Palo Alto , CA ) . A UGGT1 variant in which the amino acid residues critical to monoglucosylation activity , aa 1452–1457 , were deleted ( UGGT1 ( mut ) ) , was generated by two-step overlap PCR mutagenesis . Primers * ( 5’-CGAGTAATAACTTCTTTGTGGA-3’ ) and ( 5’-ATGAATCATGTTAAGATTTGAAAG-3’ ) were used to generate the 5’ fragment and primers ( 5’-CTTTCAAATCTTAACATGATTCAT-3’ ) and * ( 5’- GGAATTCCGGAGACAGATCA-3’ ) were used to generate the 3’ fragment . Primers designated by asterisks were then used to amplify the overlapping fragments for substitution , via Spe1 and EcoR1 sites , into the UGGT1 expression vector ( pFLAG-UGGT1 ) described above . The mutation was confirmed by DNA sequencing , and the resulting plasmid DNA was designated pFLAG-UGGT1 ( mut ) [47] . RD cells were infected with EVA71 ( strain 4643/TW/98 ) at a multiplicity of infection ( MOI ) of 10 and incubated for 6 h , prior to conducting immunoprecipitation or Co-IP assays . Infected cells were lysed in a buffer containing 50 mM Tris-HCl ( pH 7 . 4 ) , 150 mM sodium chloride ( NaCl ) , 1% Triton X-100 , and a protease inhibitor cocktail ( Roche , Mannheim , Germany ) . Cell lysates were precleared with mouse immunoglobulin G ( IgG ) agarose and incubated with a mouse anti-3D monoclonal antibody on ice for 2 h , after which 50 μL of protein G-Sepharose beads were added , and the mixtures were incubated at 4°C overnight . Proteins bound to the beads were eluted into a 1× sodium dodecyl sulfate ( SDS ) running buffer by heating at 95°C for 5 min . For RNase A treatment , 100 μL of RNase A in an RNase A working buffer ( 0 . 5 U ) was added before any antibodies , and the samples were incubated at 37°C for 25 min . Total degradation RNA was extracted using an RNeasy kit ( Qiagen , Chatsworth , CA ) , according to the manufacturer's recommendations , and gel analysis was conducted . For the JEV immunoprecipitation assay , BHK-21 cells were infected with JEV ( strain T1P1 ) and incubated for 24 h , prior to conducting the immunoprecipitation assay . Pull-down products containing eluted proteins were boiled , subjected to 8–16% sodium dodecyl sulfate polyacrylamide gel electrophoresis ( SDS-PAGE ) , and visualized by silver staining or Western blotting . Each protein band was excised , destained , reduced , alkylated , and digested with trypsin . To extract the polypeptides , gel particles were subjected twice to consecutive 20 mM sodium bicarbonate and 5% formic acid in 50% acetonitrile treatments . The supernatants were combined and lyophilized , and the dried polypeptides were recovered by adding 10 μL of 0 . 1% formic acid , followed by sonication for 1 min . The recovered polypeptides were further purified using a ZipTip C18 column ( Millipore , Billerica , MA ) , and eluted with acetonitrile to a final volume of 3 μL . Protein bands were excised and identified using in-gel trypsin digestion , then analyzed using a Bruker Ultraflex MALDI-TOF mass spectrometer ( Bremen , Germany ) . After removing the masses derived from the standards , trypsin , matrix proteins , and keratins , the monoisotopic mass lists for each protonated peptide were subjected to database searches , and mass lists were exported to the Biotool 2 . 0 software package to perform peptide mass fingerprinting , using the Mascot ( http://www . matrixscience . com ) algorithm scoring to identify proteins . RD cells were seeded on 20-mm coverslips to 60% confluency and infected with EVA71 ( strain 4643/TW/98 ) at an MOI of 10 . At various post-infection timepoints , cells were washed with phosphate-buffered saline ( PBS ) and fixed with 4% formaldehyde for 30 min at room temperature ( RT ) . Cells were then washed with PBS and permeabilized using 0 . 75% Triton X-100 for 5 min at RT , then washed again with PBS and incubated in blocking solution ( PBS containing 0 . 5% bovine serum albumin ) for 1 h at RT . Cells were then immunostained with an anti-double-strand RNA antibody , J2 ( diluted 1:200; Scicons , Szirák , Hungary ) ; an anti-3D antibody , clone 1 ( diluted 1:500; prepared in the lab from recombinant 3D protein ) ; an anti-UGGT1 antibody , K-16 ( diluted 1:200; Santa Cruz Biotechnology , Santa Cruz , CA ) ; and an anti-CNX ( calnexin ) antibody , H-70 ( diluted 1:400; Santa Cruz Biotechnology ) for 2 h at 37°C . After washing three times with PBS , cells were incubated with Alexa Fluor 568-conjugated donkey anti-goat IgG ( Invitrogen ) and Alexa Fluor 488 goat anti-mouse IgG ( Invitrogen ) for 1 h at RT . Cell nuclei were stained using Hoechst 33258 ( 1:500 dilution ) for 20 min , according to methods previously described [68] . The cells were then observed using a confocal laser-scanning microscope ( LSM 510 NLO; Zeiss , Jena , Germany ) . RD cells were cultured in six-well plates ( 2×105 cells/well ) for 24 h and then transfected with UGGT1 siRNA ( UGGT1-HSS183580; Invitrogen ) , using Lipofectamine 2000 according to the manufacturer’s protocol ( Invitrogen ) . The cell viability assay was performed using CellTiter-Glo Luminescent Cell Viability Assay ( Promega ) . For the viability assays , to quantitate ATP generated by metabolically active cells , negative control ( NC ) or UGGT1 siRNA transfected cells were plated in 96-well plates at 5 , 000 cells/well . Cells were lysed with CellTiter-Glo Luminescent Cell Viability Assay reagent ( Promega ) , and luminescence was read using the GloMax Explorer System according to the manufacturer's instructions . Following transfection with NC or UGGT1 siRNA for 2 days , RD cells were seeded onto 12-well plates and incubated for 24 h . Cells were then plated to six-well plates ( 6×105 cells/well ) and infected with EVA71 at an MOI of 1 . After 60 min absorption at 37°C , the cells were washed twice and supplemented with medium , then incubated at 37°C for the indicated time periods , after which intracellular RNA was extracted using an RNeasy kit ( Qiagen , Chatsworth , CA ) . Viral RNA was detected via quantitative real-time RT-PCR with a Roche RT-PCR kit and a Lightcycler LC480 apparatus . The oligonucleotide primers and the probe for detecting EVA71 RNA were designed by Verstrepen et al [69] . Each sample was assayed in triplicate , and experiments were independently performed three times . The obtained data were analyzed using Roche Lightcycler LC480 system software . EVA71 RNA yields were normalized to that of actin RNA . Slot blot analysis for detecting positive-strand and negative-strand viral RNA was performed as previously described [70] . Viral RNA was extracted and dissolved in a solution of formaldehyde and 20× SSC for 30 min at 60°C . The reaction was then loaded onto a nitrocellulose membrane in the slot blot manifold . After washing twice , the nitrocellulose membrane was removed , air dried , and UV crosslinked . Digoxigenin-labeled RNA probes of 100 ng , specific for the genome or anti-genome of EVA71 , were produced using a DIG Northern starter kit ( Roche ) . The hybridization and detection procedures were performed according to the manufacturer’s protocol . For EVA71-Luc replicon assays , RD cells were transfected with NC or UGGT1 siRNA . Three days after transfection , the EVA71-Luc replicon ( kindly provided by Dr . Craig E . Cameron ) was transfected into cells . After 6 h , cell lysates were collected , and luciferase expression levels were determined with the luciferase reporter assay ( Promega , Madison , WI ) according to the manufacturer’s instructions . For the dicistronic expression assay , RD cells were transfected with UGGT1 siRNA , and after 3 days , a dicistronic construct , pRHF-EVA71 , was cotransfected with UGGT1 siRNA to RD cells . After 2 days , cell lysates were prepared in a passive buffer ( Promega ) and examined for Renilla luciferase ( RLuc ) and Firefly luciferase ( FLuc ) activities with a Lumat LB 9507 bioluminometer ( EG&G Berthold , Wildbad , Germany ) , using dual-luciferase reporter assays ( Promega ) conducted in accordance with the manufacturer’s instructions . Pixel colocalization of different color channels in confocal images was analyzed using Image J software and the ColocalizeRGB and Area Calculator plugins . Cellular membrane fractions were collected using the Mem-PER Plus Membrane Protein Extraction Kit ( ThermoFisher Scientific , San Jose , CA ) , in accordance with the manufacturer’s instructions . Approximately 40 μg of membrane proteins were separated with 12% polyacrylamide gels for SDS-PAGE , and electroblotted onto polyvinylidene fluoride ( PVDF ) membranes ( BioRad , Richmond , CA ) . PVDF membranes were blocked for 2 h at RT in 5% milk-TBST ( 25 mM Tris-HCl , pH 7 . 5 , 150 mM NaCl , 0 . 05% Tween 20 ) , and then stained with anti-3D antibody ( diluted 1:10 , 000 ) , anti-3A antibody ( diluted 1:1 , 000 ) , anti-UGGT1 antibody ( diluted 1:500 ) , anti-VP2 antibody , MAB979 ( diluted 1:2 , 000; MILLIPORE ) , anti-CNX ( calnexin ) antibody ( diluted 1:1 , 000 ) , and an anti-HSP90 ( heat shock protein 90 ) antibody , ADI-SPS-771 ( diluted 1:1 , 000; Enzo Life Sciences , Farmingdale , NY ) for 2 h at 37°C . Afterwards , the membranes were washed for four times with TBST , and incubated at RT for 1 h with a peroxidase-conjugated secondary antibody ( diluted 1:1 , 000 ) , after which Amersham ECL Prime ( GE Healthcare , Waukesha , WI ) was used for chemiluminescence detection , and the signal was recorded on X-ray films . RD cells were mock infected or infected with EVA71 at an MOI of 10 . The cells were harvested at 6 h post-infection . EVA71-infected cells were washed with PBS on ice , scraped into PBS , and collected by centrifugation for 5 min at 1 , 500 × g . Cell pellets were resuspended in hypotonic solution ( 42 mM KCl , 10 mM MgCl2 , 10 mM HEPES , and pH adjusted to 7 . 4 ) and homogenized using a cell cracker ( 8 . 020-mm internal diameter , 8 . 010-mm bead diameter; HGM , Heidelberg , Germany ) . The homogenates were subjected to centrifugation for 10 min at 7 , 000 × g , after which mitochondrial-rich pellet was removed . The supernatant was collected and the concentration adjusted to 1 μg/μL using a hypotonic solution , then centrifuged for 45 min at 55 , 000 rpm at 4°C . The resulting supernatant was collected and designated as the cytosolic fraction . The pellet was resuspended in lysis buffer ( 10 mM HEPES , pH 7 . 9 , 1 . 5 mM MgCl2 , 10 mM KCl , 0 . 5 mM DTT , 1 mg/mL leupeptin , 2 mg/mL aprotonin , 1 mg/mL pepstatin A , 0 . 5 mM PMSF , 10 mM β-glycerophosphate , 1 mM sodium vanadate , and 0 . 1% Triton X-100 ) to derive the microsome-rich fraction . Following transfection with either NC or UGGT1 siRNA for 2 days , RD and SF268 cells were seeded to 12-well plates and incubated for 24 h . The cells were then infected with EVA71 ( strain 4643/TW/98 ) or EVD68 ( strain CGMH/TW/14 ) at an MOI of 10 or 0 . 1 . The viruses were allowed to adsorb for 1 h at 37°C . At various timepoints post-infection , cell lysates and supernatants of the cell culture medium were collected to determine viral titers , using plaque assays . At the final time point , cell lysates were collected to measure UGGT1 expression levels . For plaque assays , virus stocks were serially diluted in PBS and allowed to adsorb onto confluent cells for 1 h at 37°C . The inoculum was then removed , and cells were washed twice with PBS and then covered with 3 mL of an agar medium . After 4 days of incubation , plaques were counted , and virus concentration was calculated as PFU/mL . The mouse strain used in this study was created from an ES cell clone ( KOMP ID: CSD66441 , EPD0550_1_E05 clone ) obtained from the Knockout Mouse Project ( KOMP ) Repository supported by the US National Center for Research Resources-National Institutes of Health ( NCRR-NIH ) , and which was generated by the CSD consortium for KOMP ( https://www . komp . org/ ) . The ES cell clone was used to generate chimeric mice . Germline transmitted animals were bred at the Transgenic Mouse Model Core Facility of the National Core Facility Program for Biotechnology ( NCFPB ) , Academia Sinica , Taiwan . Animal care and handling were approved by the Institutional Animal Care and Use Committee of Chang Gung University . Uggt1 heterozygous knockout mice were housed under specific-pathogen-free conditions in individual ventilated cages . Institutional guidelines for animal care and use were strictly followed . Mice were intraperitoneally administered with 105 PFU/mouse of EVA71 strain MP4 [46] , and were then monitored daily for pathological signs , and sacrificed at various times post-inoculation . The severity of central nervous system ( CNS ) syndromes was scored from 0 to 4 using the following criteria for scoring CNS diseases: 4 = death , 3 = paralysis of both hind legs , 2 = paralysis of one hind leg , 1 = jerky movement , and 0 = normal movement . In the JEV-infected suckling mice model , 1-day-old WT or Uggt1 heterozygous knockout mice were injected with 104 PFU/mouse of JEV strain T1P1 , and on Day 7 after infection , JEV was extracted from brain tissues and quantitated . The tissues and organs of EVA71-infected mice and JEV-infected mice were harvested and stored at −80°C , and homogenized in DMEM on ice using a Precellys 24 ( Bertin Technologies , Montigny , France ) homogenizer . Viral titers in the supernatants of clarified homogenates were determined by a plaque assay as described above , and expressed as virus titers ( PFU/ml ) . | Positive-strand RNA viruses are adept at hijacking host cell machinery to promote viral propagation , including the formation of RCs containing viral and host proteins on intracellular membranes to facilitate virion assembly and avoid detection by host defense mechanisms . However , the processes by which RCs are assembled , as well as the host proteins involved , have not been fully elucidated as yet . Here , we show that the endoplasmic reticulum ( ER ) protein UGGT1 , a key regulator of the UPR host defense mechanism , co-precipitates with the 3D polymerase of EVA71 to facilitate RC formation , enhance viral RNA synthesis , and promote viral replication . Knockout of Uggt1 reduced viral pathogenicity in animal studies . These findings highlight the role to which viruses can hijack key host proteins to promote viral replication , and may serve as the basis for the development of novel anti-viral strategies . | [
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"immunoprecipitati... | 2017 | UGGT1 enhances enterovirus 71 pathogenicity by promoting viral RNA synthesis and viral replication |
Antioxidants produced by the parasite Schistosoma mansoni are believed to be involved in the maintenance of cellular redox balance , thus contributing to larval survival in their intermediate snail host , Biomphalaria glabrata . Here , we focused on specific antioxidant enzymes , including glutathione-S-transferases 26 and 28 ( GST26 and 28 ) , glutathione peroxidase ( GPx ) , peroxiredoxin 1 and 2 ( Prx1 and 2 ) and Cu/Zn superoxide dismutase ( SOD ) , known to be involved in cellular redox reactions , in an attempt to evaluate their endogenous antioxidant function in the early-developing primary sporocyst stage of S . mansoni . Previously we demonstrated a specific and consistent RNA interference ( RNAi ) -mediated knockdown of GST26 and 28 , Prx1 and 2 , and GPx transcripts , and an unexpected elevation of SOD transcripts in sporocysts treated with gene-specific double-stranded ( ds ) RNA . In the present followup study , in vitro transforming sporocysts were exposed to dsRNAs for GST26 and 28 , combined Prx1/2 , GPx , SOD or green-fluorescent protein ( GFP , control ) for 7 days in culture , followed by assessment of the effects of specific dsRNA treatments on protein levels using semi-quantitative Western blot analysis ( GST26 , Prx1/2 only ) , and larval susceptibility to exogenous oxidative stress in in vitro killing assays . Significant decreases ( 80% and 50% ) in immunoreactive GST26 and Prx1/2 , respectively , were observed in sporocysts treated with specific dsRNA , compared to control larvae treated with GFP dsRNA . Sporocysts cultured with dsRNAs for GST26 , GST28 , Prx1/2 and GPx , but not SOD dsRNA , were significantly increased in their susceptibility to H2O2 oxidative stress ( 60–80% mortalities at 48 hr ) compared to GFP dsRNA controls ( ∼18% mortality ) . H2O2-mediated killing was abrogated by bovine catalase , further supporting a protective role for endogenous sporocyst antioxidants . Finally , in vitro killing of S . mansoni sporocysts by hemocytes of susceptible NMRI B . glabrata snails was increased in larvae treated with Prx1/2 , GST26 and GST28 dsRNA , compared to those treated with GFP or SOD dsRNAs . Results of these experiments strongly support the hypothesis that endogenous expression and regulation of larval antioxidant enzymes serve a direct role in protection against external oxidative stress , including immune-mediated cytotoxic reactions . Moreover , these findings illustrate the efficacy of a RNAi-type approach in investigating gene function in larval schistosomes .
Miracidial penetration and entry into the molluscan intermediate host represent a critical transition period in which the previously free-living larval stage is now confronted with a potentially hostile environment as it attempts to establish a viable infection [1] , [2] . Miracidia of the human blood fluke Schistosoma mansoni shed their ciliated epidermal plates soon after entry into the host snail Biomphalaria spp . , transforming to primary or mother sporocysts . It is during this time of transition and early sporocyst development that larvae are especially vulnerable to oxidative stress generated from products of oxidized plasma hemoglobin [3] , or reactive oxygen or nitrogen species ( ROS and RNS , respectively ) resulting from hemocyte-mediated immune responses [4]–[7] . In such a potentially damaging environment , it is vital that parasites possess the capability of maintaining a redox equilibrium in order to counteract the effects of ROS/RNS generated both internally ( products of endogenous metabolic oxidative reactions ) and externally ( environmental insults ) [1] , [8] . Recent studies have shown that S . mansoni larvae possess numerous enzymes involved in ROS metabolism and detoxification of oxidative products [9]–[14] , and , like their adult stage counterparts [15]–[18] , appear to complement each other to maintain the redox balance in the parasite . Included among these enzymes are the following: ( i ) glutathione-S-transferases 26 and 28 ( GST26 and GST28 ) that function to neutralize potential membrane damage by the linked catalysis of glutathione ( GSH ) reduction with detoxification reactions involving thiol-conjugation to xenobiotics [19] , ( ii ) peroxiredoxin ( Prx1 and Prx2 ) that are involved in maintaining redox balance , by reducing hydrogen peroxide ( H2O2 ) using a thioredoxin as an electron donor [20] , ( iii ) superoxide dismutases ( SOD ) , metalloenzymes responsible for catalyzing the dismutation of the superoxide radical to hydrogen peroxide as a defense mechanism against oxygen toxicity [21] , and ( iv ) glutathione peroxidase ( GPx ) , an H2O2-metabolizing enzyme that protects membranes from damage by phospholipid peroxidation [20] , [22] . It is noteworthy that unlike most organisms , catalase , an enzyme responsible for H2O2 metabolism , is absent in S . mansoni [18] , [23] , [24] , but is functionally replaced by Prx and GPx [16] . Interestingly , for schistosome GPx , whose H2O2-reactivity is typically very low in adult worms [8] , exposure to the mammalian host environment induces enzyme activity and appears to be positively correlated to the parasite's resistance to oxidative stress [22] . In contrast to GPx , high levels of Prx activity are found in adult S . mansoni worms , and these enzymes are believed to be key components in maintaining redox balance , as well as are major contributors to antioxidant activity [16] . Previous findings have demonstrated that in vitro cultured S . mansoni sporocysts are highly sensitive to H2O2 toxicity [5] , and that sublethal exposure of sporocysts in vitro to ROS , in particular H2O2 , elicits an upregulation of genes encoding various antioxidant proteins [7] , [11] . These data support the hypothesis that the primary sporocyst is capable of interfering with , or deactivating ROS-mediated damage , through activity of an endogenous antioxidant system [1] . However , to date , a functional role of specific antioxidant enzymes within intact larvae in providing protection against external ROS insults has not been demonstrated . Recently Mourão et al . [25] demonstrated consistent transcript knockdown for various antioxidant/redox-active detoxicant mRNA species in S . mansoni sporocysts using RNA interference as originally described [26] . These included transcripts for GST26 and 28 , Prx1 and 2 , and GPx . As a followup to these findings , the present study was conducted to determine the functional consequences of these induced antioxidant gene changes , especially their relevance to S . mansoni sporocyst interactions with the intermediate snail host B . glabrata .
Research procedures involving mice used in the course of this study were reviewed and approved by the Institutional Animal Care and Use Committee ( IACUC ) at the University of Wisconsin-Madison under assurance no . A3368-01 . The NMRI strain of S . mansoni was used for all experiments . S . mansoni eggs were isolated from livers obtained from mice harboring 7-week old infections , and miracidia hatched in an artificial “pond water” supplemented with antibiotics ( 50 µg/mL streptomycin and 60 µg/mL penicillin ) [27] . Larvae were washed twice in ice-cold , sterile pond water by centrifugation , before being resuspended in Chernin's Balanced Saline Solution ( CBSS; [28] ) , containing glucose and trehalose ( 1 g/L each ) streptomycin and penicillin ( 50 µg/mL and 60 µg/mL , respectively ) . Miracidia were then counted and distributed into 48- or 96-well polystyrene tissue culture plates ( Costar , Corning Incorporated , NY ) , at concentrations of ∼500 , 1000 or 8000 miracidia/well for oxidative stress experiments , immunocytochemistry or Western blot analyses , respectively . Finally , double-stranded RNAs were synthesized from isolated sporocyst cDNA using T7 RiboMAX Express RNAi Kit ( Promega , Madison , WI ) , according to manufacturer protocol . Briefly , dsRNAs synthesis reactions were allowed to incubate for 16 hr at 37°C prior to DNAse treatment . DsRNA products were then extracted by phenol/chloroform and purified by precipitation with isopropanol . DsRNAs ( 50 nM final concentration ) for specific antioxidant genes or green-fluorescent protein ( GFP; specificity control dsRNA ) were added to cultures containing 100 µL of CBSS for the oxidative stress assays and immunocytochemistry and 400 µL for the Western blot experiments . Because of the sequence and functional similarities of Prx1 and 2 , dsRNAs for these transcripts were combined as a single treatment , designated hereafter as Prx1/2 . Larvae were incubated for 7 days as previously detailed [25] , after which time the functional consequences of dsRNA treatments were determined in functional assays described below . It should be noted that in a previous series of RNAi experiments conducted in parallel with the present study [25] , a consistent , significant knockdown of steady-state transcript levels for each of the antioxidant genes currently under study was well documented . The only exception was the Cu/Zn superoxide dismutase ( SOD ) gene , in which larval exposure to SOD dsRNA resulted in a consistent increase , not knockdown , of SOD transcripts . To assess the effects of antioxidant dsRNA on the expression of specific proteins in sporocysts , we analyzed protein extracts of dsRNA-exposed sporocysts by Western immunoblot analysis [29] incorporating specific antibodies to two antioxidant species; namely SmGST26 ( Cell Signaling Technology , Danvers , MA ) and SmPrx1/2 ( gift from Dr . D . Williams ) . Briefly , protein samples ( ∼8 µg ) and Precision Plus Dual Color Marker ( Bio-Rad , Bio-Rad Laboratories , Inc . , Hercules , CA ) were separated on 12 . 5% SDS-PAGE gels and transferred by semi-dry electroblotting ( Amersham Biosciences ) to nitrocellulose membranes ( Bio-Rad ) . After blocking overnight in TBS ( 2 . 42 g Tris base , 8 g NaCl , pH 7 . 6 ) containing 5% bovine serum albumin ( BSA ) , membranes were incubated in specific antibodies or a mouse anti-α tubulin antibody ( serving as loading control , 1∶1000 dilution; Upstate Biotechnology Inc . , Lake Placid , NY ) for 16 hr at 4°C with gentle rocking . Membranes were then washed for 30 min in TBS-Tween ( 0 . 1% ) , and incubated for 1 hr in TBS-BSA ( 5% ) containing either alkaline phosphatase ( AP ) -conjugated goat anti-rabbit IgG or AP-rabbit anti-mouse IgG at dilutions of 1∶104 and 1∶5000 , respectively ( Promega , Madison , WI ) . The colorimetric immunoreactivity was detected with the chromogen 5-bromo-4-chloro-3-indolyl phosphate ( BCIP ) and nitro-blue tetrazolium ( NBT ) diluted in AP buffer ( 0 . 1 M Tris , 0 . 1 M NaCl , 0 . 05 M MgCl2 , pH 9 . 5 ) . To quantify the observed immunoreactivity of each target protein in sporocysts treated with specific dsRNA and control GFP dsRNA , the intensities of reactive target bands were measured using Ultraviolet Transilluminator BioImaging Systems ( UVP , Inc . , Upland , CA ) and normalized to the αtubulin band with LabWorks Image Acquisition and Analysis Software ( version 4 . 6 ) in order to quantitatively evaluate the effects of antioxidant dsRNA treatment on specific protein levels . Three independent experimental replicates were performed and analyzed by Student's t-test , with significance set at P≤0 . 05 . In order to compare in situ GST26 and Prx protein levels in antioxidant dsRNA-treated parasites , we prepared whole , intact sporocysts for immunofluorescent observations . All washing steps , in eppendorf tubes , were performed by centrifugation at 1600 rpm for 2 min and repeated 5 times , or as otherwise mentioned . Following transformation and in vitro cultivation ( 24 hr ) , sporocysts were washed 3 times in CBSS , to remove detached ciliated plates , prior transfer to siliconized-tubes containing 2% paraformaldehyde and 1% Triton-X100/sPBS . Larvae were fixed overnight at 4°C under gentle agitation , then washed in snail phosphate-buffered saline ( sPBS; [30] ) and resuspended in blocking buffer ( 5% normal goat serum + 0 . 02% sodium azide in sPBS ) for 16 hr at 4°C . Rabbit-anti-GST26 or mouse anti-Prx1/2 primary antibodies , diluted at 1∶2000 , and 1∶200 , respectively , were then added to the larvae in fresh blocking buffer for 16 hr at 4°C under gentle agitation . This was followed by 5 washes , 10 min each , in sPBS , and resuspension in blocking buffer containing 4 µg/mL AlexaFluor 488-conjugated anti-rabbit/mouse antibody , 7 units/mL phalloidin-Alexa 546 and 10 µg/mL Hoechst 33258 dye ( Invitrogen ) . Tubes containing samples were incubated for 16 hr at 4°C under constant rotation , followed by washing in sPBS , resuspension in 40 µl of sPBS and mounting on coverslips . A Nikon Eclipse TE2000 ( Nikon Instrument Inc . , Melville , NY ) inverted epifluorescence microscope equipped with a Bio-Rad Radiance 2100 MP Rainbow Confocal/Multiphoton Imaging System ( W . M . Keck Laboratory for Biological Imaging , Instrumentation , UW-Medical School ) was used for specimen imaging and evaluation .
Previous work in our lab has established a consistent and specific pattern of altered antioxidant transcript expression in primary sporocysts after 7 days of double-stranded ( ds ) RNA exposure [25] . Specifically , statistically significant knockdown of S . mansoni GST26 , GST28 , GPx , and Prx1/Prx2 transcript levels , and an unexpected robust increase in those of SOD were observed in dsRNA-treated larval populations . To further explore the functional relevance of these enzymes in this parasite model , we conducted experiments to determine how antioxidant dsRNA exposure affected gene expression at the protein level ( for selected enzymes ) , and whether a functional association could be established between antioxidant gene knockdown and parasite survival in presence of stressors such as reactive oxygen species ( H2O2 ) or encapsulating hemocytes . To verify that specific dsRNA treatments had a predicted downregulating effect on sporocysts at the protein levels , Western blot analyses were performed on sporocysts treated with dsRNA for GST26 , Prx1/2 and GFP ( control ) using antibodies specifically against S . mansoni GST26 and Prx1/2 [20] . In all experiments a crossreactive anti-α tubulin antibody served as a loading control . As shown in Figure 1 , proteins extracted from GFP dsRNA-treated sporocysts ( specificity control ) presented two distinctive bands at ∼26 and 55 kDa , corresponding to GST26 and α tubulin , respectively . However , although larvae treated with GST26 dsRNA also exhibited the 55 kDa α tubulin protein , little immunoreactivity was observed at 26 kDa , suggesting an RNAi-induced GST26 protein knockdown ( Fig . 1A ) . Quantification of band intensities by scanning densitometry , using anti-α tubulin reactivity to normalize protein loads in both treatment samples , confirmed that GST26 protein levels were significantly reduced ( by ∼80% ) in GST26 dsRNA-treated sporocysts compared to the nonspecific GFP dsRNA control group ( Fig . 1C ) . Similarly , although not as dramatic , larval exposure to Prx1/2 dsRNA also exhibited a significant ∼50% decrease in protein level compared to the GFP control treatment by semi-quantitative Western blot analysis ( Figs . 1B and D ) . Consistent with Western blot analyses , in situ confocal observations of anti-GST26 localization in GST26 dsRNA-exposed and control GFP dsRNA-treated sporocysts revealed contrasting expressions of immunoreactivities . Anti-GST26 antibodies strongly reacted with endogeneous S . mansoni GST26 in sporocyst controls ( Fig . 2A ) , but was much reduced in those treated with GST26 dsRNA ( Fig . 2B ) , indicating a RNAi-mediated GST26 protein knockdown . Immunolocalization of anti-Prx1/2 , however , revealed little difference in observed staining intensities between the GFP and Prx dsRNA-treated groups ( Figs . 2C and 2D , respectively ) , except for a slight decrease in surface immunoreactivity in Prx-treated sporocysts . This also is consistent with the smaller knockdown effect of dsRNA exposure on Prx protein expression seen in immunoblot analysis ( Fig . 1B ) . In order to evaluate the effects of a potential loss of antioxidant activity in sporocysts due to dsRNA-induced antioxidant knockdown , we exposed groups of treated parasites to a range of hydrogen peroxide ( H2O2 ) concentrations . In these preliminary tests 50 µM H2O2 was determined to represent a sublethal dosage under our experimental conditions ( % larval death was not significantly different from control groups ) , whereas mortality rates significantly increased at 100 µM and higher H2O2 concentrations ( data not shown ) . As shown in Figure 3 , none of the dsRNA-treated sporocysts exhibited significant increases in H2O2-mediated mortality when compared to the GFP control treatments after 4 hr of exposure . However , at 24 and 48 hr sporocysts in all dsRNA-treatments , except the SOD dsRNA-exposed group , displayed significant increases in mortality with an average of 35% sporocyst death compared to 8% in control treatments after 24 hr , and 60 to 80% mortalities , compared to ∼18% in control treatments , at 48 hr post treatments ( FdsRNA = 28 . 21 , P≤0 . 0001; FTime = 84 . 71 , P≤0 . 0001 , N = 4 ) . In contrast to other antioxidant treatments , sporocysts exposed to SOD dsRNA exhibited a H2O2-mediated mortality rate similar to that of control treatments at all time points ( Fig . 3 ) . See Figure 3 legend for means comparisons using Bonferroni's post-test . To confirm that sporocyst death was specifically due to H2O2 as an exogeneous oxidative stressor , we exposed dsRNA-treated sporocysts to 50 µM H2O2 in presence or absence of bovine catalase or to catalase only ( no H2O2 control ) , and evaluated sporocysts mortality in all treatments after 48 hr . Overall ANOVA indicated a significant effect of dsRNA treatment and H2O2-exposure ( FdsRNA = 7 . 44 , P≤0 . 001; FOxid = 15 . 33 , P≤0 . 0001 , N = 6 ) . Within each treatment group , the percent mortalities for sporocysts exposed to GPx , GST26 , GST28 and Prx1/2 dsRNAs were very similar when incubated in H2O2+catalase or catalase only ( t values ranging from 0 . 23–1 . 74; all nonsignificant ) ( Fig . 4 ) . These results are in contrast to the effects of exposure to H2O2 alone ( positive killing control ) , in which mortality rates for sporocysts treated with the same antioxidant dsRNAs were significantly higher ( ranging from 50–75% ) when compared to 25% average sporocyst death in the catalase treatment groups ( see Fig . 4 for Bonferroni's post-test comparisons ) . As previously observed , SOD dsRNA-treated larvae , again showed no difference in mortality rates between the different treatments , nor when compared to the control GFP dsRNA group . Finally , in order to evaluate the effect of dsRNA antioxidant knockdown on snail hemocyte-sporocyst interactions in vitro , dsRNA-treated sporocysts were co-cultured with isolated hemocytes from the susceptible NMRI strain of Biomphalaria glabrata . After 24 hr of sporocyst-hemocytes incubation in an in vitro cell-mediated cytotoxicity assay [5] , we observed that dsRNA knockdown of GST26 ( t = 2 . 50 , P≤0 . 01 ) , GST28 ( P≤0 . 0461 ) and Prx1/2 ( t = 3 . 17 , P≤0 . 04 ) resulted in small , but statistically significant increases in larval death , averaging ∼20% compared to ∼8% mortality in the GFP dsRNA control group ( Fig . 5 ) . Note that sporocysts treated with GPx dsRNA also showed an increase in mean mortality rate , but was not statistically significant when compared to the GFP control parasites . As observed in previous experiments , sporocysts treated with SOD dsRNA exhibited no difference in mortality compared to the GFP-treated control sample .
Enzymes involved in cellular redox pathways , which include proteins with antioxidant activities , are believed to be essential components regulating B . glabrata/S . mansoni molecular interaction [1] , [2] . It is now well recognized that certain strains of B . glabrata snail immune cells or hemocytes produce substantial amounts of reactive oxygen [4] , [5] and nitrogen [6] species as a consequence of stimulation by known activators of ROS/RNS or when encountering S . mansoni sporocysts , and that sporocysts are exquisitely sensitive to ROS-mediated killing , especially to H2O2 . Moreover , in a series of followup studies , Bayne and co-workers have implicated a Cu/Zn-superoxide dismutase ( SOD1 ) as a key enzyme involved in oxidative killing activity by hemocytes of resistant ( R ) strains of B . glabrata snails . Their studies demonstrated that ( 1 ) SOD transcript expression and enzyme activity are higher in certain R vs . susceptible ( S ) snail hemocytes [32] and this correlates with greater H2O2 production in the R strain [33] , ( 2 ) B . glabrata SOD1 is comprised of 3 alleles , of which one ( B allele ) is significantly associated with R snails [34] , and ( 3 ) SOD1 B allelelic expression is higher in R hemocytes than those of the S strain [35] . Based on their findings it is suggested that snail strain differences in SOD hemocyte expression may be causally linked to the observed S and R strain phenotypes . Because SOD catalyzes the conversion of superoxide to cytotoxic H2O2 it is reasoned that upregulation of the SOD1 gene and its resultant heightening of SOD enzymatic activity in R hemocytes may represent a possible mechanism for the differential larval killing response by R vs . S snail hemocytes [2] . While snail hemocytes produce H2O2 as an anti-parasite effector molecule , evidence also strongly supports the presence of an active antioxidant system in early developing S . mansoni sporocysts [11]–[13] . Catalase gene homologues were not found in recent searches of the S . mansoni genomic and EST databases , and this is consistent with earlier findings [16] , [23] , [24] indicating that these parasites must possess alternative means for neutralizing H2O2 and other ROS . As clearly demonstrated in mammalian stages of S . mansoni , this is accomplished by a thiol-dependent redox system involving thioredoxin glutathione reductase ( TGR ) as the central enzyme driving redox reactions [36] . Similarly , early intramolluscan larval stages also express redox genes , including TGR , thioredoxin , Cu/Zn SOD , GPx , Prx and GST [7] , [11]–[13] , [37] , and in the case of GPx [7] and Prx1 and 2 [11] , sporocyst expression levels are dramatically increased in response to ROS exposure . In addition , Cu/Zn SOD , GST26 and 28 and Prx were recently identified in larval transformation proteins ( LTP ) released during in vitro transformation of miracidia to sporocysts , demonstrating not only the synthesis of these antioxidants by miracidia , but also their active release during larval infection [9] , [14] . Implied in these findings is the notion that antioxidant LTPs may be playing a potential protective role during early parasite development . This prospect of larval-protective antioxidants was given further credence by Vermeire and Yoshino [11] who demonstrated that Prx1/2 in LTP can function as scavengers of exogenous H2O2 suggesting the potential importance of excreted antioxidants as a sporocyst defense mechanisms . In this study , we provide the first evidence for a functional role of the endogenous antioxidants GPx , Prx and GSTs in the survival of S . mansoni sporocysts confronted with exogenous oxidative stress . By successfully knocking down antioxidant transcript/protein levels using an RNAi-type approach , we were able to characterize the impact of introduced molecular H2O2 and presumed ROS produced during hemocyte encapsulation reactions on survival of intact primary sporocysts of S . mansoni . In a previous companion study that was run in parallel with the current experiments [25] we showed that larval treatment with double-stranded RNA ( dsRNA ) for all of the antioxidants , except SOD , produced a consistent , significant and specific transcript knockdown in sporocysts . In the present study , consistent with the transcript knockdown seen earlier , we demonstrated a dsRNA-associated decrease in GST 26 and Prx1/2 protein levels using specific antibodies in a semi-quantitative Western blot assay . This protein knockdown effect was supported by immunocytochemistry ( ICC ) in the case of GST26 , but not as clearly for Prx . Importantly , the dsRNA-mediated decrease in GST26 and Prx protein content correlated well with significant increases in sporocyst mortality at 24 and 48 hr post-H2O2 exposure compared to the dsRNA control groups , implying a functional role for endogenous GST26 and Prx in the protection of primary sporocysts against external oxidative stress . Although lack of specific antibodies to the other antioxidants precluded a complete analysis of the other RNAi targeted genes used in this study , we continued to see a consistent correlation between dsRNA-induced decrease in transcript levels [25] and sporocyst survival patterns for larvae treated with GST28 and GPx dsRNA that were similar to those treated with GST26 and Prx1/2 dsRNAs . Indeed , compared to the untreated and GFP dsRNA controls , exposure of antioxidant dsRNA-treated sporocysts to a sublethal concentration of H2O2 in vitro resulted in dramatic decreases in parasite survival in all treatment groups except SOD , supporting the notion that GST28 and GPx , similar to Prx and GST26 , also are capable of enhancing sporocyst survival in an oxidative environment . These new findings are consistent with the extensive and ongoing work on the redox mechanism in the adult stage of S . mansoni , in which an active thiol-dependent redox maintenance system revolves around a thioredoxin glutathione reductase ( TGR; [36] ) , a single enzyme that combines the activities of two enzymes , thioredoxin reductase and glutathione reductase , present in mammals [17] . Schistosome TGR is responsible for maintaining the reduced and active states of both thioredoxin ( TR ) and glutathione ( GSH ) , allowing them to activate several Prxs and GPx , which in turn are capable of reducing H2O2 and other hydroperoxides [8] . Furthermore , in a more recent study , Sayed and coworkers [16] showed that Prx activity was essential to S . mansoni adult worm survival in vitro , further supporting the importance of maintaining a steady supply of this , and other antioxidant enzymes by S . mansoni adults . It appears that , like adult worms , early intramolluscan stages also must rely on robust endogenous system of antioxidant production that allows the parasite to overcome oxidative stress from both internal and external sources . In addition to the antioxidant protective role of S . mansoni sporocysts in the presence of exogeneously introduced oxidative stress , we observed a similar survival pattern in dsRNA antioxidant-treated sporocysts that have come in contact with hemocytes from the susceptible NMRI B . glabrata strain . Our rationale for incorporating susceptible snail hemocytes in these experiments was to test the hypothesis that reducing the antioxidant capacity of sporocysts would increase their vulnerability to sublethal levels of ROS normally produced by NMRI snail hemocytes in in vitro cell-mediated cytotoxicity ( CMC ) assays [5] , [38] . In this in vitro biologically-relevant context , we demonstrated a significant protective role of Prx and GSTs in sporocysts during hemocyte interactions . Co-culture of plasma-free hemocytes from susceptible NMRI snails with Prx , GST26 , and GST28 dsRNA-treated sporocysts induced an increase in sporocyst mortality ( to ∼20% ) within 24 h of initial contact , when compared to GFP dsRNA-treated control group ( 8% ) . GPx dsRNA-treated sporocysts also showed a comparable increase in hemocyte-mediated killing , but high variance in replicate values rendered the increase nonsignificant . Thus the protective role of GPx against hemocyte-mediated ROS attack still remains to be proven . Taken together , however , our overall results suggest that ROS production in susceptible snail hemocytes is capable of overpowering antioxidant-deficient parasites . Zelck and Janowsky [7] hypothesized that susceptible snails generate relatively small amount of ROS , which in turn may induce antioxidant production in schistosomes , effectively neutralizing snail-generated ROS . In this study , we have demonstrated that effectively reducing their antioxidant enzyme capacity , sporocyst survival , when confronted by a usually benign hemocyte challenge , is significantly reduced , thus supporting the critical importance of the endogenous antioxidant system in establishing viable larval infections within the susceptible snail host . Finally , a major exception to our present finding of enhanced larval susceptibility to oxidative stress by redox proteins was signal peptide ( SP ) Cu/Zn SOD [39] . In this case Cu/Zn SOD dsRNA treatment consistently had no effect on parasite survival whether in the presence of sublethal H2O2 or encapsulating hemocytes . These differing effects of SOD dsRNA exposure may have been predicted as treated S . mansoni sporocysts consistently displayed extreme elevations , rather than knockdown in transcript levels [25] , indicating a strong induction of SOD gene expression in these larval stages . At present , the signaling mechanisms involved in this response are not known although , as suggested by Zelck and Von Janowsky [7] and Vermeire and Yoshino [11] , sporocysts may be sensing ROS levels ( including H2O2 ) and responding by upregulating protective antioxidant proteins . It is speculated that larval treatement with SOD dsRNA may have caused an initial downregulation of SOD transcripts that then led to a compensatory triggering of SOD over-expression . However , as shown in other systems , small interfering dsRNA also can trigger activation of transcription [40] and , therefore , could also represent a likely mechanism [25] . Its unusual expression pattern not withstanding , results indicate that hyperexpression of the SOD gene in S . mansoni sporocysts appeared to have a “neutral” effect on dsRNA-treated larvae ( i . e . , an effect similar to control dsRNA treatment ) ( present study ) . This does not necessarily imply that SOD has no role to play in maintaining redox balance within sporocysts both internally or in response to exogenous ROS sources . However , the mechanisms by which this is accomplished are currently unknown and represent the subject of further followup investigations in our lab . | Species of the human blood fluke Schistosoma are estimated to infect approximately 200 million people worldwide , resulting in loss of health , vitality and productivity mainly among the world's poorest inhabitants . Since snail intermediate hosts represent an essential part of the flukes' life cycle , an understanding of the strategies used by the intramolluscan schistosome larvae to survive within this host may provide novel approaches for disrupting larval development and thus transmission to humans . Anti-oxidant enzymes produced by the parasite Schistosoma mansoni are believed to play a critical role in the maintenance of cellular redox balance , contributing to larval survival in their snail host , Biomphalaria glabrata . In this study , we have incorporated a RNA interference approach attempting to knock down specific anti-oxidant enzymes , including gluthatione-S-transferases 26 and 28 ( GST26 and 28 ) , gluthatione peroxidase ( GPx ) , peroxiredoxins 1 and 2 ( Prx1/2 ) and superoxide dismutase ( SOD ) , and to evaluate their endogenous anti-oxidant function in the sporocyst stage of S . mansoni . Results clearly demonstrated a significantly higher susceptibility of antioxidant double-stranded ( ds ) RNA-treated larvae to in vitro H2O2 treatment or hemocytic encapsulation compared to GFP dsRNA controls . Taken together , our findings support the hypothesis that endogenous expression and regulation of larval antioxidant enzymes serve a direct role in protection against external oxidative stress , including immune-mediated cytotoxic reactions . | [
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"cell",
"biology... | 2009 | Role of the Endogenous Antioxidant System in the Protection of Schistosoma mansoni Primary Sporocysts against Exogenous Oxidative Stress |
The cholinergic class of anthelmintic drugs is used for the control of parasitic nematodes . One of this class of drugs , tribendimidine ( a symmetrical diamidine derivative , of amidantel ) , was developed in China for use in humans in the mid-1980s . It has a broader-spectrum anthelmintic action against soil-transmitted helminthiasis than other cholinergic anthelmintics , and is effective against hookworm , pinworms , roundworms , and Strongyloides and flatworm of humans . Although molecular studies on C . elegans suggest that tribendimidine is a cholinergic agonist that is selective for the same nematode muscle nAChR as levamisole , no direct electrophysiological observations in nematode parasites have been made to test this hypothesis . Also the hypothesis that levamisole and tribendimine act on the same receptor , does not explain why tribendimidine is effective against some nematode parasites when levamisole is not . Here we examine the effects of tribendimidine on the electrophysiology and contraction of Ascaris suum body muscle and show that tribendimidine produces depolarization antagonized by the nicotinic antagonist mecamylamine , and that tribendimidine is an agonist of muscle nAChRs of parasitic nematodes . Further pharmacological characterization of the nAChRs activated by tribendimidine in our Ascaris muscle contraction assay shows that tribendimidine is not selective for the same receptor subtypes as levamisole , and that tribendimidine is more selective for the B-subtype than the L-subtype of nAChR . In addition , larval migration inhibition assays with levamisole-resistant Oesophagostomum dentatum isolates show that tribendimidine is as active on a levamisole-resistant isolate as on a levamisole-sensitive isolate , suggesting that the selectivity for levamisole and tribendimidine is not the same . It is concluded that tribendimidine can activate a different population of nematode parasite nAChRs than levamisole , and is more like bephenium . The different nAChR subtype selectivity of tribendimidine may explain why the spectrum of action of tribendimidine is different to that of other cholinergic anthelmintics like levamisole .
Limiting the debilitating effects of Soil-Transmitted Helminth ( STH ) infections in humans and animals is a challenge . Effective vaccines are not available , and sanitation and clean water are not universally available . de Silva et al . [1] estimated that: there are 1 . 24 billion people infected with A . lumbricoides; there are 811 million people infected with Trichuriasis; and 716 million people are infected with hookworm . There are only a limited number of anthelmintic drugs available for human treatment [2] . On the World Health Organization list of essential medicines , there are four anthelmintics for treatment of soil transmitted nematodes: the benzimidazoles , albendazole and mebendazole; and the nicotinic agonists , pyrantel and levamisole . This list needs to be expanded and one additional drug may be tribendimidine . Tribendimidine has a symmetrical diamidine structure ( Fig . 1A ) that was developed by the Chinese CDC in the mid-1980s and the China State FDA approved it for human use in 2004 [3] . It has a broad-spectrum of action when used in a single-dose against parasitic nematodes of humans: it is effective against hookworm , Ascaris , Strongyloides but not Trichuris [4 , 5] . It also has effects again flatworm [5] and a potential for single-dose Mass Drug Administration ( MDA ) . However , its mechanism of action in nematode parasites has not been fully characterized . Little was known of its mode of action until Hu et al . [6] published observations on C . elegans . These authors used null mutants and showed that for tribendimidine to immobilize C . elegans levamisole , L-nAChRs were required . These experiments are helpful but limited because of concerns that the levamisole receptor of C . elegans has different pharmacological properties to the muscle receptors of parasitic nematodes . The C . elegans L-nAChR is a single pharmacological receptor subtype which is not activated by nicotine . Nematode parasite levamisole nAChRs receptors are , however , activated by both nicotine and levamisole and they are a mixture of pharmacological subtypes of receptors . The C . elegans levamisole-nAChR is a pentameric receptor composed of UNC-38:UNC-29:UNC-63:LEV-1:LEV-8 subunits [7] . The parasitic nematode receptors include a number of subtypes composed of different combinations of UNC-38:UNC-29:UNC-63:ACR-8 subunits [8 , 9] . The parasitic nematode Ascaris suum has three separable subtypes known as the N- , L- and B-subtypes [10 , 11 , 12] . The N-subtype is selectively activated by nicotine and oxantel; the L-subtype is selectively activated by levamisole and antagonized competitively by paraherquamide; the B-subtype is selectively activated by bephenium and selectively antagonized by derquantel ( = 2-desoxyparaherquamide ) [10 , 11] . We hypothesized that tribendimidine is a potent muscle nAChR agonist in parasitic nematodes but that it may not be an L-subtype selective agonist like levamisole because it has a very different chemical structure to levamisole . The significance of determining the subtype selectivity for tribendimidine relates to whether or not tribendimidine could be active in worms that are resistant to other cholinergic anthelmintics like levamisole or pyrantel and if tribendimidine could be synergistic with levamisole [13] . Such information is important for managing resistance and knowing how to combine tribendimidine with other nicotinic anthelmintics Here we test the hypothesis that tribendimidine is a cholinergic anthelmintic using electrophysiological experiments . We examine its nicotinic receptor subtype selectivity to find that it is more selective for the B-subtype but not selective for the same L-subtype of receptors as levamisole . Tribendimidine may therefore be effective when levamisole is not , and tribendimidine may not show cross-resistance with levamisole .
Adult A . suum were obtained weekly from the JBS Swift pork packing plant at Marshalltown , Iowa and maintained in Locke’s solution at 32°C , changed daily and the worms were used within 3 days of collection for contraction experiments and within 5 days of collection for electrophysiology experiments . We prepared 1 cm muscle tissue flaps from the anterior 2–3 cm part of the worm that was then pinned onto a Sylgard™-lined double jacketed bath chamber maintained at 35°C by inner circulation of warm water . The preparation was continuously perfused , unless otherwise stated , with Ascaris Perienteric Fluid-Ringer ( APF-Ringer ) [composition ( mM ) : NaCl 23 , Na-acetate 110 , KCl 24 , CaCl2 6 , MgCl2 5 , glucose 11 , and HEPES 5; adjusted the pH to 7 . 6 with NaOH] . The rate of perfusion was 3 . 5–4 ml/min through a 20 gauge needle placed directly above the muscle bag recorded from . The experimental compounds were dissolved in APF-Ringer . A two-micropipette current-clamp technique was employed to examine the electrophysiological effects in the bag region of A . suum muscle ( Fig . 1B ) . We used 3M potassium acetate in the micropipettes with resistances of 20–30 MΩ . The recordings were obtained by impaling the bag region of A . suum muscle with 2 microelectrodes , one for current injection ( I ) and one for voltage recording ( V ) . All experiments were performed using an Axoclamp 2A amplifier , a 1320A Digidata interface and Clampex 9 software ( Molecular Devices , CA , USA ) displayed and analyzed on a PC based desktop computer . The current injecting electrode injected 500ms 40 nA hyperpolarizing step currents at 0 . 3 Hz , while the voltage recording electrode recorded the change in membrane potential in response to the injected currents . Cells with constant membrane potentials more negative than -20 mV for 20 min and a stable input conductance of < 3 . 5 μS were selected for the recordings . Two 1-cm body-flap preparations , one dorsal and one ventral , were made from each A . suum female from the region anterior to the genital pore . Each flap was monitored isometrically on a force transducer in an experimental bath at 37°C containing 10 ml of the APF-Ringer bubbled with nitrogen . After dissection , the preparations were allowed to equilibrate for 15 min under an initial tension of 2 . 0 g . The antagonist was then added to the preparation 15 min before the application of the first concentration of the agonist . The agonists were added cumulatively with 2–3 min intervals between applications and the responses were steady changes in tension in response to increasing tribendimidine concentrations . The responses for each concentration were measured as the gram force tension produced and also expressed as the % of the maximum contraction . Changes in isometric muscle tension responses were monitored using a PowerLab System ( AD Instruments Colorado Springs , CO ) that consists of the PowerLab hardware unit and Chart for Windows software . Sigmoid dose-response curves for each individual flap preparation at each concentration of antagonist were fitted using Prism 5 . 01 ( GraphPad Software , San Diego , CA , USA ) to estimate the constants by non-linear regression for each group of preparations receiving the same treatment . In preparations where desensitization was evident , the maximum response was used for fitting . The pEC50 was calculated as the negative logarithm of EC50 . The agonist concentration-response relationship at each concentration of antagonist were illustrated and described by the lines best fitted to the Hill equation ( constants: pEC50; slope , nH; and maximum response ) . The pA2 was obtained by fitting the equation: pEC50=−log ( [XB]N+10−pA2*N ) —log C . Where pEC50 is the same as before , XB is the concentration of the antagonist , N is the equivalent to the slope of the Schild plot , pA2 is the concentration of the antagonist producing a dose-ration of 2 and C is a constant ( -log C is the difference between [pA2 X N] and the agonist control curve pEC50 . The pA2 estimates for methyllycaconitine , paraherquamide and derquantel with tribendimidine were made were made using the Prism software . The estimation of the pA2 rather than pKB is appropriate because the value of N for the competitive model for each agonist-antagonist pair is sometime less than unity and the distribution of the data is log-normal [12] . Cluster analysis was conducted on the pA2 values obtained with the antagonists , methyllycaconitine , paraherquamide and derquantel for the agonist tribendimidine and those that had previously be determined using the same methods for bephenium , thenium , pyrantel , levamisole , oxantel , methyridine and nicotine [12] . We used Minitab 13 . 2 ( State College , PA ) for the cluster analysis ( average , squared Euclidian , standardized variable ) to determine the similarity . Fuller details of the contraction assay , use of pA2 and methods are available [12] Levamisole-sensitive and levamisole-resistant O . dentatum were originally supplied by the Royal Veterinary and Agricultural School , Frederiksberg , Copenhagen and then reproduced at yearly intervals by passage in pigs at Iowa State University , Ames , Iowa . The L3 isolates were maintained between passages in tap water refrigerated at 11°C . The levamisole-resistant isolates were maintained under selection pressure by collecting eggs for L3 preparation following treatment with a therapeutic dose of 8 mg/Kg levamisole . The pigs were infected and following collection of the parasites killed humanely: all animal procedures complied with and were governed by Institutional Animal Care and Use Committee ( IACUC ) regulations under U . S . Federal laws and policies which required formal written prior approval by the IACUC committee of the procedures as well as veterinary supervision of the animals . 1 , 500–3 , 000 L3s were ex-sheathed by 5–10 min incubation in 1 . 5% sodium hypochlorite solution . The larvae were then washed 3 times in migration buffer ( composition: 0 . 85% NaCl , 5 mM Tris-HCl , pH to 7 . 0 with 1 M NaOH ) with the help of centrifugation ( 5 min at 500 g ) . 150 larvae were collected with a pipette and placed in each of the drug concentrations to be tested for 2 h at 37°C . After incubation , L3 larvae were re-suspended in fresh test solutions . The migration apparatus was made of two tightly fitting plastic tubes ( ∼ 10 mm length ) secured to a 20 μm nylon filter placed in each test solution of a 24-well plate . The re-suspended larvae were added to the top of each filter , allowed to migrate through the filters and into the wells during 2 h incubation at 37°C . At the end of the incubation period , the number of larvae remaining within each of the filter tubes was counted and the number of larvae entering into the 24 well plates was counted . We then calculated the percentage of larvae not migrating for each of the concentrations . The relationship between the concentrations of levamisole and the percentage of inhibited larvae was then examined by fitting the Hill equation to describe the sigmoidal dose-response curves . The relationship between the concentrations of tribendimidine is the percentage inhibited larvae was examined in the same way . Tribendimidine was a gift of Prof S . H . Xiao , National Institute of Parasitic Diseases , Shanghai , and Peoples Republic of China . Derquantel and paraherquamide , a gift of Pfizer Animal Health ( now Zoetis ) were dissolved in DMSO and used at a maximum concentration of 0 . 1% . All other drugs were obtained from Sigma-Aldrich , St . Louis , MO . Tribendimidine was initially dissolved in DMSO and diluted in APF to the concentrations shown in results . The maximum concentration of DMSO used was 0 . 1% , a concentration that was tested and found to have no effect . The maximum soluble concentration of tribendimidine that was used was 30 μM .
Tribendimidine ( Fig . 1A ) is a derivative of amidantel which is a cholinergic anthelmintic . Molecular studies in C . elegans [6] suggests that tribendimidine acts selectively as an agonist , like levamisole , on nematode muscle nicotinic receptor ion-channels . To test the hypothesis that tribendimidine is a cholinergic agonist on parasite muscle , we used a two-micropipette current-clamp technique ( Fig . 1B ) to record from A . suum somatic muscle during microperfusion of the acetylcholine and tribendimidine . We observed that tribendimidine produced a concentration-dependent and reversible depolarization associated with an increase in membrane conductance like acetylcholine ( Fig . 1C ) and other cholinergic anthelmintics in A . suum [14] . Tribendimidine is more potent than acetylcholine and this is also illustrated in Fig . 1C which shows a recording of the effects of acetylcholine ( 1 μM ) and tribendimidine ( 0 . 1 , 1 and 10 μM ) from the same muscle cell: the depolarization effect ( 10 . 7 mV ) of 3 μM acetylcholine was less than the depolarizing effect ( 14 . 3 mV ) of 1 μM tribendimidine . To determine the concentration-response characteristics of tribendimidine , ten-second applications of tribendimidine were used at different concentrations at , and greater than 0 . 03 μM ( Fig . 2A ) . The concentration-depolarization response plot had an EC50 of 0 . 83 μM ( log EC50 = -6 . 08 ± 0 . 67; n = 36 , Fig . 2B ) . Mecamylamine is a potent nicotinic antagonist on Ascaris muscle acetylcholine receptors , which at a concentration of 3 μM also non-competitively antagonized the effects of tribendimidine on membrane potential ( Fig . 2A & B ) . These observations are consistent with tribendimidine acting as a potent cholinergic anthelmintic agonist on Ascaris muscle . The nicotinic cholinergic receptors on A . suum muscle have been separated into three different subtypes based on their pharmacology in muscle contraction experiments and characterized by their single channel conductance in patch-clamp experiments [11 , 12] . The different types appear to be due to different arrangements of the subunits of the nicotinic receptor [8 , 9] . We used the Ascaris muscle strip preparation ( Fig . 3A ) along with the competitive antagonists derquantel , paraherquamide and methyllycaconitine to examine the subtype selectivity of tribendimidine [12] . The principle of the technique is to measure the pA2s ( antagonist potencies ) of the three antagonists against tribendimidine using the competitive antagonism model and to compare the pA2 values against the pA2 obtained for other cholinergic anthelmintics . We used cluster analysis to pharmacologically group the selectivity of tribendimidine . Fig . 3A shows a representative tribendimidine cumulative-concentration contraction-response experiment for an Ascaris muscle strip and Fig . 3B shows the plot of means ± s . e . ( n ≥ 4 ) for the tribendimidine responses . Tribendimidine had a potent effect on contraction and the EC50 for tribendimidine contraction was 0 . 2 μM . We tested the effects of different concentrations of derquantel ( Fig . 4A ) paraherquamide ( Fig . 4B ) and methyllycaconitine ( Fig . 4C ) on the tribendimidine responses . Each concentration-response was fitted with the modified Hill Equation restrained to be parallel to yield estimates of the pA2s of the antagonists with tribendimidine as the agonist . The pA2 for derquantel was 6 . 42±0 . 15 ( 377 nM ) ; the pA2 for paraherquamide was 7 . 21±0 . 13 ( 62 nM ) ; and the pA2 for methyllycaconitine was 6 . 61±0 . 09 ( 219 nM ) . Cluster analysis of these values was used to compare these pA2 values with the cholinergic anthelmintic agonists , bephenium , thenium , levamisole , pyrantel , oxantel , methyridine and nicotine [12] . Fig . 5 shows that tribendimidine is most similar to and clusters with bephenium ( B-subtype ) and not with levamisole ( L-subtype ) or nicotine ( N-subtype ) , suggesting that it has similarities to bephenium and has a different subtype selectivity to levamisole , and nicotine . We tested the effects of levamisole and tribendimidine on larval motility using the larval migration inhibition assay with Oesophagostomum dentatum L3 larvae ( Fig . 6 ) on levamisole-sensitive and levamisole-resistant isolates [14] . Levamisole ( Fig . 6A ) was more potent ( p< 0 . 001 , F-test ) at inhibiting the migration of SENS ( levamisole-sensitive larvae ) than the migration of LEVR ( levamisole-resistant ) larvae . We tested the effects of tribendimidine to the limits of its solubility ( ∼30 μM ) , Fig . 6B , and found that tribendimidine was more potent on the levamisole-resistant isolate ( LEVR ) than on the levamisole-sensitive ( SENS ) isolate and that the difference was significant ( p < 0 . 001 , F-test ) . The bigger effect of tribendimidine on the LEVR than the SENS isolate suggests that these two drugs do not activate the same nAChR receptor subtypes .
Hu et al . , [6] have described how , in C . elegans , null-mutants of 11 genes ( including the subunit genes: unc-63; unc-38 , unc-29 , lev-1 and lev-8 ) produce both levamisole-resistance and tribendimidine-resistance . Their observations suggest that tribendimine activates levamisole ( L-type ) receptors like levamisole and pyrantel . When we compare these observations on levamisole and tribendimidine in C . elegans with our observations on parasitic nematodes , there is a difference: the C . elegans observations suggest that tribendimidine acts selectively and exclusively on its L-type nAChRs; but our observations with parasitic nematode suggest that tribendimidine activates nAChRs that levamisole does not . The levamisole receptor of C . elegans is made of an obligatory pentameric arrangement of UNC-63 , UNC-38 , LEV-8 , LEV-1 and UNC-29; omission of one of these subunits will cause levamisole and tribendimidine resistance [6] and prevent expression in Xenopus oocytes [6 , 7] . Thus loss of one subunit in C . elegans will lead to resistance of both levamisole and tribendimidine because only one type of receptor is present . In the parasitic nematodes A . suum and O . dentatum [11 , 15] there are heterogeneous muscle nAChRs subtypes . Although receptor subtypes present in A . suum muscle strips may not all be the same as those present in O . dentatum larvae , particularly since A . suum is Clade III and O . dentatum is Clade V suggesting that these nematode parasites are very well separated evolutionarily and molecularly , there is evidence of the presence of an L-subtype in both species [8 , 11 , 15] and other subtypes . The receptor pool subtypes of muscle nAChR can be produced by different combinations of the receptor subunits [8 , 9 , 16] . In Ascaris , we can separate three pharmacological subtypes: the N-subtype which is more sensitive to nicotine; the B-subtype which is more sensitive to bephenium; and the L-subtype which is more sensitive to levamisole . In adult Oesophagostomum there is also evidence of the L-subtype of nAChR [8 , 15] but the other subtypes have not yet been separated pharmacologically Our cluster analysis of the Ascaris resulted shows that tribendimidine is more pharmacologically similar to bephenium than levamisole and is more selective for the B-subtype of nAChR subtype than levamisole ( Fig . 5 ) . The different selectivity of tribendimidine for the B-subtypes and of levamisole for the L-subtypes may explain differences in the effects of levamisole and tribendimidine on levamisole-sensitive and levamisole-resistant larvae in the larval migration studies . The levamisole-sensitive larvae ( SENS ) appear to have more L-subtype receptors present than the other subtypes because levamisole is more potent than tribendimine . With the levamisole-resistant isolate ( LEVR ) , a loss of L-subtype receptors could lead to a reduction in the levamisole sensitivity and an apparent increase in the other nAChR receptor subtypes . We have observed that tribendimidine will produce depolarization ( EC50 = 0 . 8 μM ) of Ascaris muscle and contraction of Ascaris muscle strips in a concentration-dependent manner ( EC50 = 0 . 2 μM ) with B-subtype selectivity . A different subtype selectivity for tribendimidine and levamisole on nAChR receptors subtypes has also been observed for O . dentatum expressed receptors [8] supporting the notion that tribendimidine has the potential to be effective against nematode parasites that are not sensitive to levamisole . Tribendimidine then , has an interesting and promising pharmacology and has potential for single-dose MDA with its broad-spectrum . Its future use as an effective broad-spectrum anthelmintic against soil-transmitted helminths and flatworm [5] , could be compromised because of its metabolism to p- ( 1-dimethylamino ethylimino ) aniline and terephthalaldehyde [17 , 18 , 19] which are dimethylamino anilines that are potential carcinogens and mutagens [20 , 21]; but these metabolites are completely broken down and eliminated within 24 h reducing the chances of carcinogenic effects . Although tribendimidine appears safe and has broad-spectrum , a large-scale clinical study is advocated to further verify safety [5] . The contraction and electrophysiological effects of tribendimidine demonstrate a nicotinic agonist action on nAChRs present on Ascaris muscle . Tribendimidine has a selective effect on the B-subtype of nAChRs rather than the L-subtype of nAChR as in C . elegans . The observations highlight the need to examine anthelmintic modes of action in parasitic nematodes as well as C . elegans because of their possible differences . Finally our observations suggest that tribendimidine may be useful for soil-transmitted nematodes that are not susceptible to levamisole . | Nematode parasites are a plague on the human condition in many developing countries with limited health care and sanitation . The morbidity produced by these parasites limits human health , development and prosperity . Nematode parasites also adversely affect animal welfare and production . Vaccines are not effective , so anthelmintic drugs are necessary for prophylaxis and treatment . Most anthelmintics belong to one of three classes: the macrocyclic lactones ( ivermectin , moxidectin ) ; the nicotinic anthelmintics ( levamisole , pyrantel , derquantel ) or; the benzimidazoles ( albendazole , mebendazole ) . With the limited number of drugs available , there is real concern about the development of resistance . Tribendimidine was developed in China in the mid-1980s as a broad spectrum anthelmintic against soil-transmitted nematodes . Its mode of action has been investigated molecularly in C . elegans and on expressed nAChRs but , its mode of action has not been investigated directly in parasitic nematodes . Here we describe its effects on muscle contraction and electrophysiology in the pig nematode parasite , A . suum , which is very similar or the same as the human parasite , A . lumbricoides . Here we show that tribendimidine is a B-subtype selective nicotinic anthelmintic agonist that activates muscle nAChRs that are pharmacologically different from other cholinergic anthelmintics . It is concluded that tribendimidine could be effective against nematode parasites resistant to another cholinergic anthelmintic . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [] | 2015 | Tribendimidine: Mode of Action and nAChR Subtype Selectivity in Ascaris and Oesophagostomum |
Acute resistance to low dose M . tuberculosis ( Mtb ) infection is not dependent on Toll-like receptor ( TLR ) 2 . However , whether TLR2 contributes to resistance in chronic Mtb infection has remained uncertain . Here we report that , following low dose aerosol infection with Mtb , mice lacking TLR2 ( TLR2KO ) , in comparison with wild type ( WT ) mice , exhibit enhanced cellular infiltration and inflammation in the lungs , and fail to stably control bacterial burden during chronic infection . IFNγ and IL-17 was expressed at equivalent levels in the two groups; however , the characteristic accumulation of Foxp3+ T regulatory cells ( Tregs ) in pulmonary granulomas was significantly reduced in TLR2KO mice . Nonetheless , this reduction in Tregs was independent of whether Tregs expressed TLR2 or not . To directly link the reduced number of Tregs to the increased inflammation present in the TLR2KO mice , we used a macrophage adoptive transfer model . At seven weeks post-Mtb infection , TLR2KO mice , which were adoptively transferred with WT macrophages , displayed enhanced accumulation of Tregs in the lungs and a concomitant reduction in inflammation in contrast with control mice that received TLR2KO macrophages . However , the pulmonary bacterial burden between the two groups remained similar indicating that TLR2's role in modulating immunopathology is functionally distinct from its role in restricting Mtb growth in chronic infection . Together , these findings unequivocally demonstrate that TLR2 contributes to host resistance against chronic Mtb infection and reveal a novel role for TLR2 in mediating the recruitment of Foxp3+ Tregs to the lungs to control inflammation .
Mtb expresses a large diversity of TLR2 ligands , including several types of lipoproteins and glycolipids , and also a trehalose dimycolate [1]–[3] . Interaction of these ligands with TLR2 expressed on macrophages and dendritic cells has multiple downstream effects . Several studies have reported that Mtb-derived TLR2 ligands produce a pro-inflammatory response [4]–[6] , and consistent with these findings , mice deficient in TLR2 have diminished IL-17 response [7] . TLR2 signaling also induces direct antimicrobial activity in Mtb-infected human macrophages [8] by vitamin D3-dependent up-regulation of anti-microbial peptides [9] . Additionally , TLR2 signaling leads to suppressive effects on the functions of antigen-presenting cells ( APCs ) . For example , TLR2 signaling in APCs induces IL-10 secretion [10] and prolonged signaling inhibits MHC class II expression [11] , [12] , antigen processing [3] , [13] , and IFNγ responsiveness [14] . Despite the extensive remodeling of macrophage functions following TLR2 signaling , TLR2-deficient mice are able to resist acute Mtb infection [15]–[17] and develop an appropriate secondary immune response [18] following a low dose aerosol infection . However , TLR2-deficient mice infected with a high dose of Mtb are more susceptible than WT to chronic infection and display an exaggerated immune inflammatory response , characterized by pneumonitis and enhanced cellular infiltration [15] , [17] . These findings implicate a potential role for TLR2 in controlling inflammation during chronic infection . Risk of developing tuberculosis has been shown to be associated with polymorphisms within the TLR2 gene , particularly within the TIR domain [19]–[21] . Analysis of a polymorphic guanine-thymine ( GT ) repeat located upstream of the TLR2 translational start site correlated shorter GT repeats with development of tuberculosis ( TB ) and lower TLR2 expression [22] . In addition , a TLR1 transmembrane domain polymorphism was shown to regulate the innate immune response to triacylated lipopeptides as well as extracts of mycobacteria [23] . Although the mechanism behind how these polymorphisms affect the immune response to Mtb is unclear , these correlations suggest an important role for TLR2 in host defense against Mtb . The aim of this study was to identify the mechanism by which TLR2 signals control inflammation and contribute to host resistance against Mtb . Here , we report that TLR2 functions in protection against chronic Mtb infection by keeping bacterial replication in check and limiting inflammation through recruitment of Foxp3+ Tregs to the lungs .
We first evaluated the role of TLR2 in host resistance against chronic Mtb infection . WT and TLR2KO mice were aerosol-infected with approximately 100 CFU of Mtb and disease progression was monitored for 15 weeks . As shown in Figure 1A , TLR2KO mice exhibited a significantly increased bacterial burden at weeks 7 and 10 , and , by week 12 , there was more than a log increase in bacterial burden in the TLR2KO mice as compared with WT . Beginning at 10 weeks following infection , the TLR2KO mice also began to succumb to infection . The WT mice , as expected , were able to control infection and maintain a steady bacterial load . A repeat experiment using a similar infectious dose of Mtb ( around 150 CFU ) demonstrated consistent findings ( Fig . 1B ) . Previous studies have indicated that the magnitude of the immune response leading to control of Mtb infection can be dependent on infectious dose [24] . To ensure that the reduced resistance of TLR2KO mice was not dependent on Mtb inoculum size , disease progression in response to a very low inoculum was also followed . During aerosol infection with a low dose of Mtb ( approximately 10 CFU ) , TLR2KO mice again demonstrated a log increase in pulmonary bacterial burden , although increased morbidity was not observed until around 18 weeks post-infection , at which point the difference in bacterial burden between WT and TLR2KO mice was around 2 logs ( Fig . 1C ) . Consistent with the differences observed in bacterial loads , acid-fast staining of infected lung tissue demonstrated increased bacilli within lung macrophages in the TLR2KO mice ( S1A ) . The absence of TLR2 did not affect Mtb dissemination and replication outside of the lung since differences were not observed in the spleen ( S1B ) . The development of pulmonary pathology in H&E stained sections of infected TLR2KO and WT mice was next characterized ( Figure 1 , D–I ) . The murine granulomatous lesion is a collection of peripheral lymphocytic aggregates with B cell follicles juxtaposing areas with macrophages and other inflammatory cells types . These lesions lack the heterogeneity exhibited by human granulomas; although the granulomatous reaction is progressive , necrosis is not exhibited until an exorbitant bacillary load is achieved , and caseous necrosis and cavitation do not occur in C57BL/6 mice [25] . At 4 weeks post-infection , tissue architecture was similar between both groups , with distinct areas of granulomatous cellular infiltration ( arrows ) surrounded by unaffected lung areas apparent in WT and TLR2KO ( Figure 1 , D and E ) . As infection progressed , the granuloma architecture in the TLR2KO began to deviate from what is normally observed in WT mice . At 7 weeks post-infection , WT mice developed typical compact granulomatous lesions ( arrow ) containing macrophages and lymphocytic infiltrates ( Figure 1F ) . In comparison , lungs of the TLR2KO mice exhibited increased inflammation with disrupted granuloma architecture ( Figure 1G ) . Similarly , during the chronic stage at 12 weeks post-infection , the characteristic granulomatous structure of macrophages and densely compact lymphocytes was apparent in the WT lungs ( Figure 1H ) while extensive cellular infiltration and markedly reduced alveolar spaces were observed in TLR2KO lungs ( Figure 1 I ) . The TLR2KO lungs displayed poorly formed granulomas , with loosely aggregated lymphocytes dispersed amongst macrophages ( Figure 1 I ) . Overall , the TLR2KO mice exhibited an early inflammatory response to Mtb similar to WT . However , as the infection progressed towards the chronic stage , the granuloma architecture in the WT lungs stabilized , while the TLR2KO lungs became consolidated with infiltrates which disrupted the granuloma morphology and progressively spread to comprise a majority of the lungs . These data confirm and extend the findings reported by Drennan and colleagues [17] that Mtb infection of TLR2KO mice leads to an exaggerated inflammatory response in the lungs . Flow cytometric analysis of the cell surface markers CD11c , CD11b , and Gr-1 demonstrated significant increases in the numbers of CD11c−CD11b+ recruited macrophages , CD11c+CD11b+ myeloid DCs , CD11c+CD11b− alveolar macrophages , and Gr-1hiCD11b+ neutrophils infiltrating the lungs at a late stage of infection ( 10 and 13 weeks ) ( Figure S2B ) . Differences in NK1 . 1+ NK cells and CD19+ B cells were not observed ( data not shown ) . Overall , these observations of increased recruitment of inflammatory cells to the lungs in the absence of TLR2 are consistent with the severe inflammatory lung pathology in TLR2KO mice during late stages of infection . The enhanced inflammatory response in the lungs of Mtb infected TLR2KO mice led to the hypothesis that a regulatory T cell population may be lacking in the absence of TLR2 . Natural Foxp3-expressing regulatory T cells ( natTregs ) are present in Mtb granulomas [26] . Therefore , the presence of natTregs in the lungs based on expression of Foxp3 was investigated . Lungs were harvested at the indicated time points post-infection , and flow cytometric analysis was performed to determine the percentage of Foxp3+ cells out of the CD4+ T cell population ( Figure S3 ) . The percentage of CD4+ cells expressing Foxp3 in the lungs was similar between WT and TLR2KO mice prior to Mtb infection . However , following infection , the TLR2KO mice displayed decreased frequencies of Foxp3+ Tregs in the lungs compared to WT ( Figure 2A ) . While the percentage of Foxp3+ cells was lower in TLR2KO lungs than WT lungs , Tregs in both groups had equivalent expression of glucocorticoid-induced TNF receptor-related protein ( GITR ) and cytotoxic T-lymphocyte antigen-4 ( CTLA-4 ) , indicating a true natTreg phenotype of the Foxp3+ cells present in TLR2KO lungs ( data not shown ) . Of note , it was also observed that both groups displayed decreased percentages of Foxp3+ cells out of the CD4+ population in the lungs compared to their naïve counterparts , although to a greater extent in the TLR2KO . This decrease is probably reflective of a greater expansion of CD4+ effector T cells compared to CD4+ Tregs following Mtb infection . Enumeration of cell infiltrates showed that total cell numbers , and CD4+ and CD8+ T cell numbers in TLR2KO mice were similar to WT at 7 weeks following infection ( Figure S2A ) , a time when the percentage of Treg cells was lower in TLR2KO . This supports that the decreased percentage of Tregs in TLR2KO mice is not merely due to the greater expansion of T effector cells . However , total cell numbers and T cell numbers continually increased over time in TLR2KO mice , while they stabilized in WT mice ( Figure S2A ) . Therefore , we further investigated differences in Foxp3+ cells in the WT and TLR2KO by immunohistochemical staining of lung sections for the presence and localization of Foxp3-expressing cells . At 4 weeks post-infection , there were few Foxp3-expressing cells present in the granulomatous lesions of either WT or TLR2KO mice , although more were apparent in WT . At this time point , Foxp3+ cells were present in perivascular and peribronchiolar regions in both groups ( Figure S4 , Panels G and H ) . By 12 weeks post-infection , examination of WT ( Figure 2C ) and TLR2KO lung lesions ( Figure 2F ) by immunochemistry showed accumulation of high numbers of Foxp3+ cells in lesions of WT mice ( Figure 2D ) . In contrast , very few Foxp3+ cells were observed in the affected areas of the lungs of TLR2KO mice at this time point ( Figure 2G ) . Individual Foxp3+ cells or small clusters of Foxp3+ cells were dispersed randomly in TLR2KO lungs ( Figure 2H ) , although they were not aggregated to the same extent as in WT ( Figure 2E ) . Together , these findings show that TLR2 signals are necessary for the accumulation of regulatory T cells in the lungs during Mtb infection . Other studies using murine models of Mtb infection have demonstrated that depletion of CD4+CD25+Foxp3+ natTregs or the complete absence of this population results in increased frequencies of IFNγ-producing CD4+ effector T cells [27] , [28] . Given the importance of IFNγ in the protective immune response against Mtb , the possibility that decreased frequencies of Foxp3+ Tregs in the lungs of TLR2KO mice may correlate to enhanced Th1 responses was investigated . ELISPOT assay was performed with cells isolated from the lungs during chronic stages of infection and re-stimulated with Mtb-pulsed bone marrow-derived DCs serving as APCs . As shown in Figure 3A , there were no differences in the numbers of Mtb-specific IFNγ secreting cells in the lungs of WT and TLR2KO mice . Further , the decreased accumulation of Foxp3+ Tregs did not correlate to enhanced IL-17 gene expression , as there were no significant differences in IL-17 gene expression between WT and TLR2KO lungs ( Figure 3B ) . Overall , these results indicate that the decreased accumulation of Foxp3+ Tregs in the lungs of TLR2KO mice is not associated with enhanced Mtb-induced Type I T cell responses . It has been reported that TLR2 signaling on natTregs promotes their expansion and survival [29]–[31] . Therefore , the decreased number of Foxp3+CD4+ cells observed in the lungs of TLR2KO mice could result from decreased expansion of this population in peripheral lymphoid organs . To address this , the levels of Foxp3+ Tregs in the spleens were monitored following Mtb infection . Consistent with a previous report [32] , decreased Foxp3+CD4+ cells were observed in the spleens of naïve TLR2KO mice as compared to WT levels . However , during Mtb infection this difference was no longer observed ( Figure 2B ) , suggesting that differences in peripheral expansion of Foxp3+ Tregs between WT and TLR2KO mice do not account for the decreased frequencies of these cells in the lungs in the absence of TLR2 . Given the possibility that TLR2 signals are important for natTreg survival , we determined if reconstitution of TLR2KO mice with WT Tregs would allow for Treg accumulation in TLR2KO lungs . CD4+CD25+ Tregs from naïve WT mice were transferred to both TLR2KO and WT mice one day prior to and 4 weeks post-Mtb infection . TLR2KO and WT mice that did not receive Tregs were infected at the same time as controls . Flow cytometric analysis of Foxp3+CD4+ cells at 6 and 10 weeks post-infection indicated that the transfer of WT Tregs did not increase the frequency of this population in the lungs of TLR2KO mice , which were significantly lower than WT controls at 6 weeks ( Figure 4A ) . Consistent with this , total pulmonary cell numbers at 10 weeks were significantly increased in both recipient and non-recipient TLR2KO as opposed to WT controls ( Figure 4B ) . Also , the transfer of Foxp3+Tregs did not affect bacterial burden in the lungs . Total CFU in the lungs was increased by 1 log in the TLR2KO groups at both 6 and 10 weeks , although this increase was only significant at 6 weeks within the non-recipient group ( Figure 4C ) . Together , these data demonstrate that the transfer of WT Foxp3+ Tregs failed to restore Treg numbers to WT levels in the lungs of TLR2KO hosts . To definitively address whether the absence of TLR2 on natTregs is responsible for their decreased accumulation in the lungs of Mtb-infected TLR2KO mice , an adoptive transfer model using T cell-deficient Rag2−/− mice was used ( described in Figure S5A ) . Conventional naïve CD4+CD25− T cells ( which will be referred to as Tconv ) and CD4+CD25+ T cells ( Treg ) were purified from WT ( CD45 . 1+ ) and TLR2KO ( CD45 . 2+ ) mice . By flow cytometry , greater than 99% of sorted CD25+ cells reacted with anti-Foxp3 antibody ( data not shown ) . Rag2−/− mice were reconstituted one day prior to Mtb infection with combinations of 2×106 Tconv cells and 2×105 Treg cells . Group I received WT Tconv ( CD45 . 1 ) and TLR2KO Treg ( CD45 . 2 ) , and Group II received TLR2KO Tconv ( CD45 . 2 ) and WT Treg ( CD45 . 1 ) . These combinations allowed for investigation of the effects of TLR2 signaling on Tconv and Treg populations separately , on an otherwise WT background for myeloid and stromal cells . At 4 and 9 weeks post-infection , Treg accumulation and bacterial burden was analyzed . Single cell suspensions were prepared from the lungs and spleens derived from the two groups of mice at the indicated time points after Mtb challenge and stained with antibodies against CD4 , CD45 . 1 , CD45 . 2 and Foxp3 for flow cytometric analysis . Lymphocytes were gated on , followed by gating on CD4+ cells . For Group 1 , the frequencies of Treg and Tconv were determined by gating on CD45 . 2 and CD45 . 1 populations , respectively , within the CD4+ gate , and are presented as percentage out of CD4+ T cells . Similarly , for Group II , the frequencies of Treg and Tconv were determined by gating on CD45 . 1 and CD45 . 2 populations , respectively , within the CD4+ gate . The dot plot analysis for lung and spleen is presented in Supplementary Figure 5B and 5C , respectively . Equivalent numbers of CD4+ cells were recruited to the lungs in the two groups of mice at both 4 and 9 weeks post-infection ( Figure 5A ) . Similarly , analysis of the Treg and Tconv populations out of the CD4+ cells showed that both groups had similar frequencies of these populations in the lungs ( Figure 5A ) . Therefore , accumulation of Tregs in Group I mice that received TLR2KO CD4+CD25+ T cells was similar to that of Group II mice that had received WT CD4+CD25+ T cells . Analysis in the spleens showed a similar result as in the lungs , with no differences observed in CD4+ cell numbers or in the frequencies of Tregs between the two groups ( Figure 5B ) . Immunohistochemistry for Foxp3+ cells also demonstrated that Foxp3+ Tregs could be detected in the lungs in both groups ( Figure 5C ) . Consistent with the equivalent Treg/Tconv frequencies observed , Mtb growth kinetics in the lungs were comparable in both groups of mice ( Figure 5D ) . Further flow cytometric analysis of the CD45 . 1 and CD45 . 2 populations in the lungs and spleen ( Figure S5D–G ) of the two groups of mice demonstrated that , in both groups , Foxp3 expression was retained at a similar level and was limited to the congenic marker of the original CD4+CD25+ injected population . These findings confirm that the Tregs which accumulated in the lungs of Group I originated from the TLR2KO CD4+CD25+ T cells injected and were not due to conversion of the injected WT CD4+CD25− population . It is important to note that the immunoregulatory functions of B cells [33] are lacking in the reconstituted Rag2−/− mice . Nonetheless , the findings from this experiment demonstrate that TLR2 signaling on CD4+Foxp3+ Tregs is not necessary for their expansion and subsequent recruitment into Mtb-infected lungs . Since TLR2 signaling on Tregs themselves does not affect their accumulation into Mtb-infected lungs , we considered that TLR2 signals on pulmonary myeloid cells may play a role in Treg recruitment to granulomatous areas . To directly address this potential role of TLR2 on myeloid cells , we investigated whether providing TLR2-expressing WT myeloid cells to a TLR2KO host would restore normal accumulation of Foxp3+ Tregs in the lung and protect from inflammatory pathology . Macrophages purified from WT or TLR2KO mice were adoptively transferred directly into the lungs by intra-tracheal instillation one day prior to Mtb infection . At seven weeks post-infection , lungs from the TLR2KO mice adoptively transferred with WT macrophages ( WT→TLR2KO mice ) or TLR2KO macrophages ( TLR2KO→TLR2KO mice ) were harvested and evaluated for Treg accumulation , cellular infiltration , granulomatous inflammation , and bacterial burden . Flow cytometric analysis of single cell suspensions of lungs showed a significantly higher percentage of Foxp3+ Tregs in the WT→TLR2KO mice than the TLR2KO→TLR2KO mice ( Figure 6A ) while the percentage of CD4+ T cells was similar in the two groups ( Figure 6B ) . Immunohistochemical staining of lung sections demonstrated high levels of Foxp3+ cell accumulation in the granulomatous lesions of WT→TLR2KO mice ( Figure 7A ) , while very few Foxp3+ cells were observed in the affected areas of the lungs of TLR2KO→TLR2KO mice ( Figure 7D ) . In the latter group , the sparsely recruited Foxp3+ cells were mainly observed in perivascular and peribronchiolar regions ( Figure 7D ) . No background was observed in serial sections stained with isotype control ( Figure 7B and E ) . Consistent with higher Foxp3+ Treg cell accumulation , WT→TLR2KO mice exhibited significantly less cellular infiltration than the TLR2KO→TLR2KO mice ( Figure 6C ) . Histopathological evaluation of lung tissue revealed that the characteristic granulomatous structure with compact aggregation of cells observed in WT mice was restored in the WT →TLR2KO mice ( Figure 7C ) , while lung tissue from the TLR2KO→TLR2KO mice exhibited loosely aggregated lymphocytes and increased inflammation ( Figure 7F ) with a significantly greater area of lung involvement as expected in a TLR2KO host ( Figure 6D ) . While WT→TLR2KO mice exhibited improved Treg accumulation and decreased inflammatory pathology , the bacterial burden in the lungs ( Figure 6E ) and spleen ( Figure 6F ) was similar in both groups , indicating that the role of TLR2 in controlling bacterial burden may be distinct from its role in controlling inflammation . Overall , these findings indicate that TLR2 signaling from macrophages promotes Treg recruitment to the lungs and decreases inflammatory pathology during Mtb infection .
In this study , we conclusively demonstrate that Mtb infection in the absence of TLR2 results in poorly formed granulomas , progressive pulmonary pathology , and increased lung bacterial burden during chronic infection . Our data also indicate that Treg dysfunction may , in part , underlie the immune pathogenesis observed in the lungs of TLR2KO mice . Moreover , we have demonstrated that transfer of WT macrophages significantly enhanced the accumulation of Foxp3+ Tregs within pulmonary granulomatous lesions in TLR2KO mice and concomitantly alleviated pulmonary inflammation . This clearly establishes a causal role for Tregs in controlling the immunopathology of TB . Finally , our data that bacterial burden in the lungs of TLR2KO mice was not affected by the transfer of WT macrophages suggests that the immunoregulatory function of TLR2 can be uncoupled from its antibacterial function . TLR2 ligation activates a multitude of MAPK signaling pathways [34]; it is likely that these distinct pathways regulate the dual functions of TLR2 in chronic infection . The finding that Tregs expand independently of direct TLR2 signals was surprising given the evidence that TLR2 ligation on Foxp3+ Tregs enhances their proliferation and survival [29]–[31] . These prior reports , however , investigated the effects of TLR2 signaling on Tregs through direct ligation by synthetic TLR2 ligands , not in the context of TLR2 signaling that may occur during an infection . Our study demonstrates that , during Mtb infection , TLR2 signaling on Tregs does not significantly contribute to the expansion and recruitment of Tregs to sites of infection . Instead , TLR2 activation on myeloid cells is necessary to induce the accumulation of Tregs in the lungs . The precise mechanism by which myeloid cells contribute to Treg accumulation remains to be determined , but it is likely dependent on the initiation of an appropriate chemokine axis in the microenvironment of the granuloma . For example , Tregs express the chemokine receptor CCR4 and are highly chemotactic towards its ligands , macrophage-derived chemokine ( MDC/CCL22 ) and thymus and activation regulated chemokine ( TARC/CCL17 ) [35] , [36] . While the secretion of CCL22 and CCL17 has been implicated in Treg recruitment to the tumor microenvironment in several studies [37]–[41] , the role of these chemokines in the recruitment of Tregs to inflammatory sites during Mtb infection has yet to be addressed . It has also been shown that a subset of Foxp3+ Tregs expressing the Th1 transcription factor T-bet as well as the chemokine receptor driven by T-bet , CXCR3 , accumulate at sites of Th1-mediated inflammation [42] . Therefore , a deficiency in any of the IFNγ-inducible CXCR3 ligands may affect Treg recruitment to Mtb granulomas . It is also possible that activation of TLR2 on macrophages may be important for supporting Treg proliferation and maintenance in the lung following recruitment . Future experiments using specific antibodies and gene-deficient mice are necessary to analyze these various possibilities . Mycobacterial lipids , including TLR2 ligands such as LpqH , are released from Mtb-infected macrophages via exocytosis [43] , [44] . Also , Mtb releases membrane vesicles within macrophages that stimulate cytokine and chemokine release in a TLR2-dependent fashion [45] . Therefore , it is conceivable that during chronic infection , Mtb-derived TLR2 ligands are released into the granuloma microenvironment where they can interact with macrophages and perhaps dendritic cells to initiate the chemokine axis required to direct Tregs towards areas of granulomatous inflammation in the lungs and , subsequently , into the granuloma . Our findings indicate that Tregs are necessary to control granulomatous inflammation and maintain a stable granuloma . However , other studies found that natTregs undergo expansion in the blood and at disease sites , and their removal from circulation improved cytokine production from T cells [46]–[48] . Also , Tregs were shown to delay Th1 cell activation in the murine model [49] . Together , these data suggest that the temporal removal of Tregs may be beneficial to the host in enhancing a protective immune response , but , because of the persistent nature of Mtb , it is critical that sufficient numbers of Tregs are recruited to the lungs to mitigate immunopathology . This idea is supported by studies in non-human primates which found that higher frequencies of Tregs correlated to the development of latent TB over active TB disease [50] and that Tregs and Teffector cells acted together to control inflammation without enhancing Mtb replication [51] . The current findings that TLR2 is required for controlling chronic Mtb infection support and extend a previous study [17] . However , these results contradict studies by Holscher and colleagues who reported that TLR2/4 double- and TLR2/4/9 triple-deficient mice are able to efficiently control low dose aerosol infection with Mtb [52] , [53] . Reasons for these variable outcomes to Mtb infection are not clear , but they could be related to different experimental conditions , dose of infection , Mtb strain , or perhaps to differences in commensal microbiota . A recent study by Iwasaki and colleagues [54] showed that gut microbiota , critical for maintaining immune homeostasis in the gut mucosa [55] , [56] , can also influence immunity to infection at a distant site , such as the respiratory mucosa . The authors demonstrated that the commensal microbiota were required for optimal activation of the adaptive immune response against influenza virus infection by providing signal 1 for the expression of mRNA for pro–IL-1β and pro–IL-18 at steady state . This requirement for intact commensal bacteria to generate an appropriate adaptive immune response was found to be restricted to pathogens that are dependent on inflammasomes for immune cell priming , and not to all respiratory pathogens . For example , T cell and B cell responses to Legionella pneumophila were not affected in antibiotic-treated animals . Given that NLP3 inflammasome activation is linked to exacerbated pathology in the lungs of Mtb-infected mice [57] , it is possible that microbiota may differentially influence the outcome of Mtb infection in mice bred at different facilities . Our finding that the transfer of WT macrophages restores Treg accumulation and results in improved control of inflammation in TLR2KO mice reduces the likelihood that our observations were influenced by differences in the microbiota of WT and TLR2KO mice that were bred at different sites . Nevertheless , it does not rule out the possibility that differences in microbiota could be a contributing factor to the discrepant results seen between our studies and those of Holcher and colleagues [52] . Depending on the composition of the microbiota , the steady state expression of pro-IL-1β and IL-18 may vary , thus necessitating differences in the requirement of regulatory components to control pulmonary inflammation during Mtb infection . This is an area rich for future investigations . There are several possible pathways that may be activated by Tregs to prevent immunopathology and associated tissue damage . There is now accumulating evidence to indicate that beyond its anti-microbial function , IFNγ also limits immunopathology in Mtb-infected hosts . IFNγ down-modulates IL-17 production and the subsequent accumulation of pathogenic neutrophils [57] . IFNγ signalingalso dampens the production of the pro-inflammatory cytokines , IL-1α and IL-1β , from myeloid cells [58] , via NOS2-mediated inhibition of assembly and activation of the NLRP3 inflammasome [59] . Conspicuous B cell aggregates with characteristic germinal center features are present in the lungs of Mtb-infected mice [60] and emerging evidence indicates a regulatory role for these cells during Mtb infection . Mtb-infected mice deficient in B cells display an exaggerated immunopathology associated with enhanced neutrophil recruitment to the lungs [33] . The enhanced inflammation observed in the TLR2KO mice in our study , however , was not associated with alterations in IFNγ-secreting cells , IL-17 gene expression , or B cell numbers during chronic infection . Despite this , the increased mononuclear cell infiltration suggests that Tregs may function to restrain the influx of monocytes and neutrophils to the lung . Although neutrophils provide protection during acute infection [61] , their presence in the lung in chronic infection is associated with pathology ( [62] and reviewed in [63] ) . Thus , by controlling neutrophil recruitment , Tregs may limit inflammation and pulmonary pathology . Also , it is possible that by regulating cellular recruitment , Tregs serve to limit the availability of intracellular niches for Mtb to replicate . Indeed , inhibition of recruitment of new macrophages to the granuloma reduces Mtb numbers in the lung [64] , [65] . Although we have delineated that TLR2 controls Mtb growth and inflammation via distinct mechanisms , it is possible that an interplay could exist between the two mechanisms . Future studies will address whether the increased bacterial burden observed in TLR2KO hosts is due to the absence of TLR2-mediated antimicrobial activity within the granuloma or as a consequence of the enhanced inflammation . In sum , our study supports that the TLR2/Treg axis is one of several regulatory circuits that are activated during chronic Mtb infection to safeguard the host against exaggerated inflammation and damage induced by the persistence of Mtb in the lungs .
All animal experiments described in this study conform with the UMDNJ Newark IACUC Guidelines , NIH and USDA policies on the care and use of animals in research and teaching , and the policies of the Guide for the Care and the Use of Laboratory Animals . Animal protocols used in this study were approved by the UMDNJ Institutional Animal Care and Use Committee . ( Assurance number A3158-01 ) . Every effort to eliminate animal pain and distress through the use of anesthesia , analgesics or tranquilizers was made . C57Bl/6 mice and B6-Ly5 . 2 congenic mice were purchased from The Jackson Laboratory ( Bar Harbor , ME ) . Rag-2-deficient ( Rag2−/− ) mice were purchased from Taconic Farms , Inc . TLR2-deficient ( TLR2KO ) mice were developed by S . Akira and colleagues [66] . TLR2KO mice were bred and maintained under pathogen-free conditions at the transgenic animal facility at the UMDNJ-NJMS . M . tuberculosis-infected mice were housed in the BSL3 facility at the Public Health Research Institute at UMDNJ-NJMS . Animal protocols used in this study were approved by the UMDNJ Institutional Animal Care and Use Committee . The virulent Erdman strain ( Trudeau Institute , Saranac Lake , NY ) of M . tuberculosis was used for all infections . Bacterial stocks were generated by initial passage in C57Bl/6 mice . Bacterial colonies obtained from lung homogenates were grown in 7H9 media until mid-log phase , and the culture was stored in aliquots at −80°C . The stock titer was determined by plating 10-fold serial dilutions on Middlebrook 7H11 selective medium ( Difco ) . Female mice ( age 6–8 weeks ) were infected via the respiratory route using a closed-air aerosolization system from In-TOX Products or the Inhalation exposure System from Glas-Col . Mice were exposed for 20 minutes to nebulized bacteria at a density optimized to deliver a standard low dose of around 100 CFU ( unless otherwise indicated ) . For all infections , the actual infection dose was determined by plating total lung homogenates from a minimum of 2 mice on Middlebrook 7H11 plates at 24 hours after aerosol exposure . Lungs and spleens were harvested at indicated time points post infection . The right superior lobe of the lung was used for determining bacterial burden . The right lower lobe was reserved for histological studies . The right middle lobe was reserved for protein determination . The postcaval lobe was reserved for tissue gene expression . The remaining lung tissue was cut into small pieces and digested with 2 mg/ml collagenase D ( Roche ) for 30 minutes at 37°C . The digestion was stopped by adding 10 mM EDTA . The digested tissue was forced through a 40 µm cell strainer ( BD Falcon ) to obtain single cell suspensions . Spleen tissues were processed similarly , but without collagenase digestion . Red blood cells were lysed using ACK lysing buffer ( Quality Biological , Inc ) . The number of viable cells obtained per tissue was determined by trypan blue dye exclusion . Lung tissue was homogenized in PBS containing 0 . 05% Tween-80 . Total CFU per lung was determined by plating 10-fold serial dilutions on Middlebrook 7H11 plates . CFU were counted after 21 days of incubation at 37°C . Lung tissue was fixed in 4% paraformaldehyde in PBS for four days , followed by paraffin embedding . For histopathological analysis , five to seven micrometer sections were cut and stained using a standard H&E protocol . For visualization of acid-fast bacilli , tissue sections were stained using the Ziehl-Neelsen method . For immunohistochemical detection of Foxp3+ cells , tissue samples were de-paraffinized with xylene and rehydrated with ethanol gradations and water . The samples were subjected to heat-induced antigen retrieval by microwave warming using 10 mM citrate buffer ( pH 6 . 0 ) . Endogenous peroxidase activity was blocked using 0 . 3% hydrogen peroxide and then subsequently blocked with 1× PowerBlock ( BioGenex ) . PBS containing 0 . 05% Tween-20 was used to wash tissues in between steps . For each sample , serial sections were incubated with the primary anti-mouse/rat Foxp3 antibody ( clone FJK-16s; eBioscience ) at a 1∶250 dilution or with isotype control ( BioLegend ) at the same concentration . Sections were subsequently incubated with biotinylated secondary antibody ( 1∶100 Vector Laboratories ) . Streptavidin horseradish peroxidase ( BioGenex ) was used to label the secondary antibody for immunodetection by DAB chromogen ( BioGenex ) . After counterstaining with Mayer's hematoxylin ( BioGenex ) , the samples were dehydrated with ethanol gradations , dipped in xylene , and mounted using Permount ( Fisher Scientific ) . For quantitation of involved lung area , photomicrographs of H&E stained lung sections were captured using a 5× objective lens . A 546 point grid overlay was superimposed onto each image using Image-Pro Discovery Software , and the numbers of points hitting areas of granulomatous infiltration were counted . The percentage of affected lung tissue was calculated as number of involved points/total points per section ×100 . Single cell suspensions were stained at saturating conditions using specific monoclonal antibodies . All mAbs were directly conjugated to one of the following fluorochromes: Alexa Fluor 488 , FITC , PE , PerCpCy5 . 5 , PE-Cy7 , APC , or Alexa Fluor700 . Isotype controls were included for each . The following mAbs were used in the studies: CD4 ( clone RM4–5 ) , CD8 ( clone 53-6 . 7 ) , Foxp3 ( clone FJK-16s ) , CD11c ( clone HL3 ) , CD11b ( clone M1/70 ) , Gr-1 ( Ly-6G and Ly-6C; clone RB6-8C5 ) , CD45 . 1 ( clone A20 ) , CD45 . 2 ( clone 104 ) . Abs to Foxp3 , CD45 . 1 , and CD45 . 2 was purchased from eBioscience . The remaining Abs were purchased from BD Biosciences . For surface staining , cells were re-suspended in FACS buffer ( 1× PBS +2% fetal calf serum and 0 . 09% sodium azide ) containing a cocktail of mAbs against proteins of interest . For Foxp3 staining , surface staining was performed , followed by fixation , permeabilization , and intracellular staining of Foxp3 according to the manufacturer's protocol ( Ebioscience ) . Following surface or intracytoplasmic staining , samples were fixed in 4% paraformaldehyde for 30 minutes and then acquired on a FACSCalibur or LSRII ( BD Biosciences ) . Analysis was performed using FlowJo software ( Tree Star , Inc . ) . Gating was based on isotype controls . ELISPOT assay to detect the frequency of Mtb-specific IFNγ producing cells was performed as described previously [67] . 96-well MultiScreen HTS filter plates ( Millipore ) were coated with 8 µg/ml anti-IFNγ antibody ( clone R4-6A2 , BD Biosciences ) . Single cell suspensions from lungs were seeded at 0 . 25×105 , 0 . 5×105 , and 1×105 cells per well . Cells were restimulated with Mtb-infected bone marrow-derived dendritic cells ( 3 MOI , overnight ) at a ratio of 1∶2 , or uninfected BMDCs as a control . The cultures were supplemented with IL-2 at 20 U/ml . The cells were co-cultured for 40 hr at 37°C . The plates were subsequently washed with PBS containing 0 . 05% Tween-20 and treated sequentially with biotinylated secondary antibody ( Clone XMG1 . 2 , BD Biosciences ) , ELISPOT streptavidin-HRP ( BD Biosciences ) , and the HRP substrate 3-amino-9-ethyl-carbazole ( Sigma ) . Spot-forming units were enumerated using an ELISPOT plate reader ( Cellular Technology ) . Bone marrow-derived dendritic cells ( BMDCs ) were prepared as described previously [68] . Briefly , bone marrow cells were flushed from the femurs and tibiae of mice with PBS containing penicillin and streptomycin ( 100 U/ml each ) . Red blood cell lysis was performed using ACK lysing buffer . 2×106 bone marrow cells were seeded into 10 cm Petri dishes in 10 ml RPMI-1640 media ( Mediatech , Inc . ) containing 10% defined FBS ( HyClone Laboratories , Logan , UT ) and supplemented with penicillin ( 100 U/ml ) , streptomycin ( 100 µg/ml ) , glutamine ( 2 mM ) , β-ME ( 50 µM ) , and 10% conditioned medium from murine GM-CSF-secreting X63 cells . On Day 3 , an additional 10-ml complete medium containing GM-CSF was added to the cultures . On Day 6 , the cultures were fed by changing fifty percent of the culture medium . Non-adherent cells were harvested on day 8 . The MACS Regulatory T cell isolation kit ( Miltenyi Biotec ) was used to separate CD4+CD25− and CD4+CD25+ lymphocytes from spleens and peripheral lymph nodes ( axillary and inguinal ) of naïve WT congenic B6-Ly5 . 2 mice ( CD45 . 1+ ) and TLR2KO mice ( CD45 . 2+ ) . For adoptive transfer , a mixture of 2×106 CD4+CD25− ( naïve conventional T cells ) and 2×105 CD4+CD25+ ( natural regulatory T cells ) in PBS were transferred into Rag2−/− mice via retro-orbital injection . Group I received WT CD4+CD25− and TLR2KO CD4+CD25+ cells , and group II received TLR2KO CD4+CD25− and WT CD4+CD25+ cells . One day after transfer , recipient mice were infected with a low dose aerosol of Mtb . At 4 and 9 weeks post-infection , recipient mice were euthanized and lungs and spleens were used for analysis . Lung lobes were homogenized in 1 ml of TRIzol reagent in lysing matrix D tubes ( MP Biomedicals ) using a FastPrep homogenizer ( MP Biomedicals ) . Samples were immediately stored at −80°C following lysis in TRIzol . Total RNA was extracted via the manufacturer's TRIzol/chloroform method and purified using RNeasy columns ( Qiagen ) . Total RNA was reverse transcribed using Superscript II RT ( Invitrogen ) . Real-time PCR was performed using the Mx3000P system ( Stratagene ) . TaqMan gene expression assay ( Applied Biosystems ) for IL-17A and β-actin were used to determine relative IL-17 expression . Relative gene expression was determined by the ΔΔCt calculationt , where ΔCt = Ct ( gene of interest ) – Ct ( normalizer = β-actin ) and the ΔΔCt = ΔCt ( sample ) – ΔCt ( calibrator ) . Total RNA from uninfected lungs was used as calibrator . Baseline gene expression from uninfected WT and TLR2KO was equivalent . Peritoneal exudate macrophages ( PEM ) were prepared and adoptively transferred as described previously [69] . Briefly , PEM from WT and TLR2KO mice ( 5 mice/group ) were elicited by intra-peritoneal injection of 2 mls of sterile thioglycollate broth 5 days before peritoneal lavage . PEM from each group of mice were pooled and TLR2KO mice received 2 . 5×106 WT or TLR2KO macrophages via the intra-tracheal route . One day after transfer , recipient mice were infected with a low dose aerosol of Mtb . | Tuberculosis ( TB ) is an important cause of mortality in many parts of the world . Infection with Mycobacterium tuberculosis ( Mtb ) , the causative agent of TB , is usually acquired via inhalation of airborne droplets containing the bacteria . Following inhalation , Mtb interacts with specialized receptors , called Toll-like receptors ( TLRs ) , on phagocytic cells present in the lung . In this study , we examine the contribution of TLR2 in activating the body's natural defenses against Mtb . Wild type mice infected with Mtb by the aerosol route are able to control bacterial replication in the lung and maintain it at a steady level during chronic infection . However , in genetically modified mice that do not express TLR2 ( TLR2KO ) , Mtb infection leads to increased inflammation in the lung and inability to control Mtb growth . Here , we identify that the increased inflammation present in the lungs of Mtb-infected TLR2KO mice is due to the diminished ability of a type of regulatory cell ( Foxp3+ Tregs ) to accumulate in the lungs . The ability to recruit Tregs to the lungs is restored in TLR2KO mice if they are adoptively transferred with macrophages from wild type mice . In summary , we demonstrate that TLR2 functions in protection against chronic Mtb infection by controlling Treg accumulation in the lung to limit inflammation and tissue damage . | [
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] | 2013 | Host Defense and Recruitment of Foxp3+ T Regulatory Cells to the Lungs in Chronic Mycobacterium tuberculosis Infection Requires Toll-like Receptor 2 |
Better knowledge of the epidemiological characteristics of snakebites could help to take measures to improve their management . The incidence and mortality of snakebites in the Americas are most often estimated from medical and scientific literature , which generally lack precision and representativeness . Authors used the notifications of snakebites treated in health centers collected by the Ministries of Health of the American countries to estimate their incidence and mortality . Data were obtained from official reports available on-line at government sites , including those of the Ministry of Health in each country and was sustained by recent literature obtained from PubMed . The average annual incidence is about 57 , 500 snake bites ( 6 . 2 per 100 , 000 population ) and mortality is close to 370 deaths ( 0 . 04 per 100 , 000 population ) , that is , between one third and half of the previous estimates . The incidence of snakebites is influenced by the abundance of snakes , which is related to ( i ) climate and altitude , ( ii ) specific preferences of the snake for environments suitable for their development , and ( iii ) human population density . Recent literature allowed to notice that the severity of the bites depends mainly on ( i ) the snake responsible for the bite ( species and size ) and ( ii ) accessibility of health care , including availability of antivenoms . The main limitation of this study could be the reliability and accuracy of the notifications by national health services . However , the data seemed consistent considering the similarity of the incidences on each side of national boundaries while the sources are distinct . However , snakebite incidence could be underestimated due to the use of traditional medicine by the patients who escaped the reporting of cases . However , gathered data corresponded to the actual use of the health facilities , and therefore to the actual demand for antivenoms , which should make it possible to improve their management .
Snakebite is an important public health issue in the Americas , particularly in inter-tropical America [1; 2] . A better understanding of the epidemiological burden of snakebite , i . e . incidence , geographical distribution , population at risk , bite circumstances and severity , would improve their management [3] and should be used to urge World Health Organization ( WHO ) to include definitely snakebites in the list of neglected tropical diseases ( NTD ) and to convince international agencies and foundations of funding . It would also help the antivenom manufacturers to produce the necessary quantity , and the Health Authorities to supply the health centers according to the declared incidence and the geographical distribution of the envenomations . However , most data available for the Americas are fragmentary and poorly representative , mainly because they come from the literature , making them incomplete and biased . This is particularly true in Central and South American countries . In recent years , international workshop dedicated to the improvement of antivenoms pointed out that “renewed efforts were required on national and regional basis to improve the epidemiological surveillance system in order to gather a more precise picture of the impact of this health problem” [4] and recommended “to improve the information systems on the epidemiology of snakebite envenomations in the region , that is essential for the design of effective distribution policies and training programs” [5] . As a consequence , most Latin American countries introduced mandatory notification of snakebites during the 2000s . The bites by opistoglyphic ( rear fanged ) snakes and those of the families lacking fangs delivering venom ( Boidae , Aniilidae in particular ) being weakly toxic [6] , represent a low demand for health services , although the incidence is far from trivial [7] . The snakes belonging to the Scolecophidia suborder ( Typhlopidae and Leptotyphlopidae ) are definitely non-toxic and unable to bite . As a consequence , two snake families share responsibility for snake envenomations in the Americas: the Viperidae ( including half a dozen genera , the most frequent being Crotalus , Bothrops and Agkistrodon ) and the Elapidae of which Micrurus is the main genus [8] . The bites of the latter represent less than 1% of the envenomations [9–13] . The symptoms caused by viper bite are mainly hemorrhagic and cytotoxic , the latter sometimes resulting in limb amputation or permanent disability [14; 15] . Some species of Crotalus may also produce neurotoxic symptoms similar to envenomation by Elapidae [16] , and sometimes associated with acute renal failure [17] . Unlike the neurotoxins of rattlesnake venoms that act on presynaptic receptors ( β-neurotoxins ) , the α-neurotoxins of Elapidae venoms bind to postsynaptic cholinergic receptors [13] . In both cases , paralysis of the cranial nerves can occur , inducing in some cases a potentially fatal respiratory arrest in the absence of specific ( antivenom ) and/or symptomatic treatment ( artificial ventilation ) . The aim of this work was to assess the epidemiological burden of snakebite , including the incidence , mortality , population at risk and main explanatory characteristics of their frequency and severity: season , environment , altitude , density of human population , management , etc . , in order to provide recent and useful data to improve the management of snakebites in the Americas .
A bibliographic search was performed by querying MedLine ( PubMed last access 06/11/2016 ) using the keywords "America AND snake * AND [envenom * OR antiven *]" . From a total of 4 , 514 references , 187 concerned the epidemiology and/or management of snakebites in the Americas . Furthermore , websites regarding i ) the epidemiology of snakebites ( using the words “health surveillance” , “surveillance bulletin” , “epidemiology surveillance” , “snakebite envenomation” , “snakebite death” ) , ii ) population demography ( using the words “population demography” ) and iii ) administrative and environmental geography ( using the word “map” ) were identified using the Google search engine for each of the countries of America and using the official language of each country ( English , Spanish , Portuguese , French and Dutch ) . Access to these websites was made between September 2010 and December 2016 . The list of the websites and the last access date to each are mentioned in Table 1 . However , a few websites were closed during this period and sometimes replaced by new ones , the use of which was often restricted by a password . All the data were transferred and analyzed using Excel software . The trend curves and R2 , the coefficient of determination that is the square of the coefficient of correlation indicates the extent to which the dependent variable is predictable , were calculated through Excel . The comparisons were made using parametric tests ( t-test , χ2 and Pearson correlation ) or non-parametric ( Mann-Whitney ) , depending on the distribution of studied variables and number of cases/groups . The significance level was equal to 0 . 05 and the means were expressed using a 95% IC . Statistical analyzes were performed using the BiostatTGV online software ( http://marne . u707 . jussieu . fr/biostatgv/ ) . Topographic , physical and political maps were taken from the World Atlas of Wikimedia ( https://commons . wikimedia . org/wiki/Atlas_of_the_world ) and drawn on the basis of the data obtained in this study .
Information is available online since 2007 . According to Ministry of Health records , there was an average of 700 envenomations ( 1 . 63 per 100 , 000 inhabitants ) and 5 deaths per year ( 0 . 012 per 100 , 000 inhabitants ) during the 2007–2014 period . There was a steady decrease in annual incidence ( Fig 1A ) . The incidence showed a decreasing gradient from north to south ( Fig 2 ) , which corresponded to the climatic trend between the Chaco province which climate is subtropical , and the Patagonia province more rigorous on the one hand , and the Andean climate of eastern Argentina , on the other hand . Two provinces presented a higher incidence than the others: Santiago del Estero in the north with a low population density ( 7 inhabitants per km2 ) and Misiones in the north-east with a higher density ( 35 inhabitants per km2 ) but predominantly agricultural . The seasonal distribution of envenomation showed a summer incidence five to six times higher than the winter one ( Fig 1B ) . These results corroborated those by Dolab et al . [18] obtained from a questionnaire survey conducted at health facilities . These authors have shown the strong geographical heterogeneity of the incidence which can reach 150 envenimations per 100 000 inhabitants in certain places . They confirmed the low case fatality rate ( 0 . 04% according to the survey ) . Bothrops were responsible for 96 . 6% of the bites , Crotalus 2 . 8% and Micrurus 0 . 6% . Population at risk consisted of young men bitten during agricultural activities . Most envenomations ( 90% ) were treated within the first four hours by an antivenom . No information on snakebites has been obtained for Belize . However , on the basis of existing data from neighboring countries showing similar environments , the annual number of bites can be estimated at 35 ( 10 per 100 , 000 population ) and deaths at 1 every 2 to 4 years ( 0 , 1 per 100 000 inhabitants ) . The information is available online from 1996 but the notification was interrupted between 2001 and 2009 . It returned to availability from 2010 . The presentation of the data has been standardized , in particular as regards the classification of age groups . By 2015 , the information has been supplemented by the addition of the gender of the patients . However , mortality from envenomation is still not provided . In their study on snakebites in Bolivia , Chippaux and Postigo [19] reported a national incidence of 8 bites per 100 , 000 population per year with a case fatality rate of 0 . 42 per 100 , 000 population . They extrapolated mortality from household survey data , which lacks precision and reliability but was consistent with the mortality observed in neighboring countries . Updating data available up to 2015 confirmed the impact over this period with over 900 annual bites ( 9 . 1 per 100 , 000 population ) . The number of deaths is still not reported but has been estimated at around 40 per year [19] . The main results of these authors , in particular the geographical distribution and the distribution by age group , were confirmed by the notifications during the years 2010–2015 . The annual incidence increased significantly between 2010 and 2015 ( Fig 3A ) . The distribution of the specific incidence showed a steady growth according to age ( Fig 3B ) . The sex ratio ( M/F ) was 1 . 81 . The geographical distribution was very heterogeneous . The incidence is very low ( less than 1 snakebites per 100 , 000 inhabitants ) in the high mountain region , notably the Altiplano ( departments of Potossi , Oruro and most of that of La Paz where altitude exceeds 3 , 500 m asl ) . The lowland or steppe departments , such as the Chaco region ( Departments of Tajira , Santa Cruz , Chuquisaca , Cochabamba and Beni ) have an incidence of between 5 and 50 per 100 , 000 inhabitants . Finally , the incidence exceeds 50 bites per 100 , 000 inhabitants in the Department of Pando in the Bolivian Amazon [19] . The seasonal distribution ( Fig 3C ) showed a clear difference between the Chaco province ( medium-altitude steppe ) where the incidence is highest in the dry season , and Amazonia ( low-lying primary forest ) where bites occur mainly during the season rains . Finally , if the relationship between population density and incidence was not shown , Chippaux and Postigo [19] observed a significant inverse correlation ( P < 1 . 6·10−4 ) between incidence and altitude . The notification of snakebites is performed for a long time in Brazil but the results are online only since 2001 . According to Chippaux [20] from the data reported by the health facilities and available online on the site of SINAN which is the main Database on causes of morbidity and mortality available online since 2001 [21] , the average number of snakebites was about 27 , 200 per year ( 15 per 100 , 000 population ) with more than 115 deaths ( 0 . 06 100 , 000 inhabitants ) during the period 2001–2012 . The geographical distribution showed a clear predominance in northern Brazil , especially in the Amazon ( Fig 4 ) . The seasonal distribution of bites was more pronounced in the summer , particularly in the southern regions ( Fig 5 ) . The incidence by age group varied greatly from region to region . It was higher among young people in the Amazon and in people over the age of 40 on the inland plateau [20] . Bothrops species were responsible for most of the bites everywhere in Brazil . Bites by Crotalus durissus are more frequent in the eastern and central savannas . The bites by Lachesis sp . are mostly observed in the Amazonian region . Those by Micrurus sp . are rare . Finally , there was a strong inverse correlation between incidence and population density [20] . The population at risk was made up of male farmers . Risk factors were more or less directly related to the agriculture and rural housing of the victims [22; 23] . Bochner and Struchiner [24] showed that these characteristics have been constant since the first epidemiological studies carried out by Vital Brazil in the early 20th century . Incidence and mortality increased discreetly and seemed to follow demographic trends [20] . Snakebites appeared to be very rare in Canada because of a climate unfavorable to the establishment of snake populations , and a highly mechanized agricultural activity . The presence of Sistrurus catenatus is attested in southern Ontario , the most populated region of the State , and Crotalus oreganus occurs in British Columbia . Crotalus horridus disappeared from Oregon since 1941 and from Quebec more recently [25] . Rumors of his return to southeastern Canada , including Quebec , have not been validated by the Recovery Commission for the Ontario Rattlesnake [26] . According to Dubinsky [27] , there were about sixty snakebites reported in Ontario each year . There would have been 2 deaths between 1900 and 1960 [28] and since the 60s none has been reported in the literature . There were no figures for British Columbia and snakebites are considered very rare . In total , it can be assumed that snakebites are fewer than 100 annually and no death was reported in Canada since a long time . Snakebites are distributed in the two southern states ( Ontario and British Columbia ) close to the border of United States of America where rattlesnakes are still encountered . However , some snakebites recorded could be illegitimate bites inflicted when manipulating a snake in the field or in captivity . There are neither Bothrops , nor Crotalus , nor Micrurus in Chile . Snakebites by opistoglyphic snakes were reported but not considered as public health issue [29] . Notifications have been available online since 2009 . The number of reported snakebites was approximately 4 , 150 per year ( 8 . 5 per 100 , 000 population ) , resulting in about 35 deaths ( 0 . 08 per 100 , 000 population ) between 2009 and 2014 . The incidence of snakebites increased significantly during the period ( Fig 6A ) without clear explanation . Maybe , the case report system–or political situation–improved enough to obtain more reliable data . The geographical distribution was heterogeneous . Incidence was relatively high in the whole of the country , especially in the Amazonian departments in the south ( Fig 7 ) and much lower in central Colombia , both mountainous and urban . There was no correlation between population density and incidence . The seasonal distribution was constant throughout the year ( Fig 6B ) . The notification has been available online since 2005 with some shortcomings—or delays in data capture—after 2012 . From 2005 to 2012 , an average of nearly 700 snakebites ( 15 per 100 , 000 inhabitants ) and 7 deaths ( 0 . 15 per 100 , 000 inhabitants ) were reported . The incidence of snakebites was significantly higher in the eastern provinces . In the center of the country , it was lower , especially in the province of San José , which is the most densely populated and mountainous ( Fig 8 ) . Annual snakebites ranged 500–1 , 000 without any particular trend [30] . The sex ratio was 1 . 7 ( M/F ) and increased in adult male whereas it decreased in women over 15 years ( Fig 9A ) . The seasonal incidence was relatively stable during the year , however , with marked variability in the rainy season from May to November when the majority of snakebites occurred ( Fig 9B ) . These results were in agreement with those from the literature . The highest mortality is observed in the provinces of Puntarenas in the south and Limon in the east , linked to the abundance of Bothrops asper [31; 32] . Based on the notification of cases and environmental information , Hansson et al . [33] were able to model high risk zones of bites by Bothrops asper , and to recommend a targeted supply of antivenoms . Access to full epidemiological data for years prior to 2013 was limited [34] . From 2013 , the weekly notification was available online but showed many shortcomings . According to González-Andrade and Chippaux [34] , there were nearly 1 , 500 snakebites ( 9 . 8 per 100 , 000 inhabitants ) resulting in about 10 deaths ( 0 . 06 per 100 , 000 inhabitants ) each year . The highest incidence occurred in the Amazonian provinces ( Oriente province ) , with 37% of the envenomations and an average annual incidence of 100 envenomations per 100 , 000 inhabitants ( Fig 10 ) . The majority of snakebites ( 58% ) were in the coastal region ( Costa province ) with an average incidence of 12 bites per 100 , 000 inhabitants . In highland provinces in the center of the country ( Sierra province ) , incidence was about 5 bites per 100 , 000 population ( 5% of the snakebites ) . During the rainy season , from January to April , the incidence of snake bites is twice as high as in the dry season . The incidence of snakebites is twice as high after the age of 10 and remains stable from teenagers to elderly . The very young children below 5 are ten times less involved than adults . Although notification of snakebites has been mandatory since 2010 , data are not accessible . On the other hand , they are subject to periodic reports put online . We used that of 2013 which compiled the data from 2010 to 2012 . About 300 annual snakebites ( 5 per 100 , 000 inhabitants ) were irregularly distributed during the year . Based on the results of neighboring states , the annual number of deaths can be estimated at 3 ( 0 . 05 per 100 , 000 inhabitants ) . The six months of the rainy season ( May to October ) accounted for nearly 65% of the envenomations ( Fig 11A ) . The population at risk was mainly composed of young men . Patients aged 10 to 30 constituted 51% of the bites , while this age group represented less than 40% of the population . In addition , the sex ratio ( M/F ) was 1 . 5 . During this period , no death was reported . The geographic distribution of incidence was heterogeneous , i . e . lower on the coast and in the center of the country ( Fig 12 ) , a probable consequence of the local population density , which is the highest of the Americas ( Fig 11B ) . There was no recent data concerning this small French department . According to the literature , mostly from surveys dating back to the 1980s , the annual incidence of envenomation exceeded 25 cases per 100 , 000 inhabitants with relatively high mortality [35–37] . Data were available online since 2001 with some gaps , notably in 2005 . With almost 900 snakebites on average each year ( 2001–2010 ) , the distribution of the incidence was very heterogeneous ( Fig 13 ) . Mortality was not documented . It was estimated on the basis of neighboring country mortality at about 10 deaths per year ( 0 . 06 per 100 , 000 population ) . There was no notification of snakebites in Guyana . However , a study of cases of envenomation treated at the Georgetown Public Hospital Corporation ( GPHC ) in 2014 provided an estimate of the burden of envenomation for Guyana as a whole . However , data for the Amazon region , which is sparsely populated but with high snakebite risk , was highly under-estimated , partly because it was likely that few patients visit the health facilities and , on the other hand because the evacuation possibilities on Georgetown are almost nonexistent . According to Bux [38] , there would be more than 200 snakebites each year in Guyana , an incidence greater than 25 bites per 100 , 000 inhabitants . The number of deaths was not specified , but Langston [39] mentioned a high number of deaths . The press reported 3 deaths in Georgetown between 2011 and 2014 , which was probably underestimated since it did not take into account deaths in provincial health facilities . More than 80 snakebites were treated each year at the Georgetown Reference Hospital during the 2010–2012 period . However , the geographical distribution was biased due to the lack of reliable data for the South ( Amazonian region ) of the country ( Fig 14 ) . The age-specific incidence calculated on the basis of hospital data showed a constant increase of snakebite incidence until the age of 30–40 years and then a steady decline up to 60 years . Notification of snakebites has been mandatory since 2009 but online display was interrupted at the end of 2013 . A little more than 650 snakebites occurred annually on average ( 10 per 100 , 000 inhabitants ) . The number of deaths was not reported but was estimated at 7 per year ( 0 . 08 per 100 , 000 population ) based on observations in neighboring countries . Snakebites were mostly distributed to the north and east of the country ( Fig 15 ) , regions with the lowest altitude . The number of snakebites is relatively stable throughout the year with a slight increase in incidence during the rainy season from May to October . Notification of snakebites was not mandatory in Martinique and records were not available online . According to the literature [40;41;42] , about 15 envenomations are treated in hospital every year ( about 5 per 100 , 000 inhabitants ) . The average number of deaths was 4 every 20 years ( 0 . 05 per 100 , 000 population ) during the 1990–2010 period . Only one venomous species ( Bothrops lanceolatus ) is present on the island [8] . The geographical distribution of the bites covered the whole of the island , but mainly involved small agricultural communes ( Fig 16 ) . However , no obvious link was observed between snakebite incidence and agricultural work in the two main types of plantations of Martinique ( bananas and sugarcane ) . Venomous animal attacks was reported since 1996 but snakebites were separated and available online only since 2003 . The annual number of bites averaged 4 , 000 ( 3 . 3 per 100 , 000 inhabitants ) with steady growth between 2003 and 2015 ( Fig 17A ) . The number of deaths was below fifty per year ( 0 . 035 per 100 , 000 inhabitants ) . As showed by Frayre-Torres et al . [43] , the mortality rate decreased from 0 . 25 per 100 , 000 population in the 1970s to 0 . 05 during the 2000s . The lowering continued after the 2010 and is now less than 0 . 04 per 100 000 ( Fig 17B ) . In addition , mortality was higher in the South than in the North of Mexico and increased significantly after the age of 40 , whereas it appeared to be stable before . Case fatality rate was higher among males than females ( P <0 . 028 ) . The geographical distribution was relatively homogeneous ( Fig 18 ) with a decreasing trend from the north , where the mean incidence was close to 2 per 100 , 000 inhabitants , towards the center ( average incidence 7 per 100 , 000 inhabitants ) and the South ( incidence greater than 9 bites per 100 , 000 inhabitants ) . The sex ratio ( M/F ) was 1 . 97 . The seasonal distribution showed a marked summer increase in snakebites ( Fig 18 ) . Notification of snakebites is not available online . The epidemiological data were based on the work by Hansson et al . [44] the source of whom was the Ministry of Health . According to these authors , there were about 650 snakebites each year ( 56 per 100 , 000 inhabitants ) and 7 deaths ( 0 . 6 per 100 , 000 inhabitants ) . The geographical distribution was very heterogeneous , with a higher incidence in the south of the country , largely dependent on altitude , land use and health supply [44] . Notification of snakebites in Panama was not available online . According to the Ministry of Health , the average annual incidence could be 1 , 900 snake bites ( 55 bites per 100 , 000 inhabitants ) . Valderrama et al . [45] mentioned about fifteen deaths per year ( 0 . 5 deaths per 100 , 000 inhabitants ) . The incidence was highest in the provinces of Darién , Coclé , Los Santos ( three provinces in the center of the country ) and Veraguas in the east , although in the latter the data were much underestimated . The work by Barahona de Mosca ( 2003 , quoted by Valderrama et al . [45] ) showed that people aged 20 to 44 were the most affected ( 44% ) , followed by teenagers aged 10–19 ( 23% ) , and children 0–9 ( 18% ) . In all age groups , males were most often bitten . Highest incidence occurred during the rainy season ( from May to November ) . Notification of snakebites has been mandatory since 2008 but was only truly functional from 2009 . Nearly 250 snakebites were reported annually ( 3 . 5 per 100 , 000 population ) during the period 2004–2015 . Snakebites decreased regularly between 2009 and 2013 , and then increased dramatically in 2014 and 2015 . However , the general trend of incidence is decreasing ( R2 = 0 . 7319 ) suggesting that the annual variations are random and risk is reducing . The average number of deaths was 5 per year ( 0 . 08 per 100 , 000 inhabitants ) . The seasonal incidence is relatively constant throughout the year with a slight increase during the rainy season ( December to April ) . The incidence was higher in northern and eastern Paraguay ( Fig 19 ) . Notification of snakebites has been available online since 2000 . On average , 2 , 150 snakebites occurred per year in Peru ( 7 . 2 per 100 , 000 population ) , resulting in about 10 deaths ( 0 . 043 per 100 , 000 population ) during the years 2000–2015 . The increase in incidence was significant . However , after a steady increase until 2011 , the incidence tends to stabilize or even to decrease slightly in recent years ( R2 = 0 . 739 ) . The highest incidence was observed in the Amazon region , while the incidence in the coastal region and the south of the country was low ( Fig 20 ) . The seasonal incidence is constant for most of the year with a net decrease in the middle of the dry season ( mainly from June to September ) . There was no information about Saint Lucia . However , the epidemiological situation should be comparable to that of Martinique , which corresponded to about ten bites per year ( 6 per 100 , 000 inhabitants ) and one death every 5 to 10 years ( 0 . 1 per 100 , 000 inhabitants ) . Bothrops caribbaeus , a species close to B . lanceolatus , is endemic to the island [8; 46] . Notification of snakebites was not mandatory in Suriname and no information on envenomation has been found . Based on the situation in French Guiana , the annual number of snakebites can be estimated at 135 ( 25 per 100 , 000 inhabitants ) and the number of deaths at 5 deaths ( 0 . 9 per 100 , 000 inhabitants ) . Notification was not mandatory in the island of Trinidad for which there was no information on snakebites . Based on the data collected in coastal Venezuela and Guyana , it can be expected 130 snakebites ( 10 per 100 000 inhabitants ) and 1 to 2 deaths ( 0 . 1 per 100 000 inhabitants ) each year . Four poisonous species occur in Trinidad: Micrurus lemniscatus and M . circinalis , both Elapids , and Bothrops atrox and Lachesis muta that are vipers . M . circinalis and M . fulvius are present in some Bocas islands . There is no Elapidae or Viperidae in Tobago [8] . The notification of snakebites in the US was old but hardly available online . Several sources were used and the data were regularly reported in the literature [47–56] . These data were based on notifications from separate systems but were consistent and highly convergent . Between the late 1950s and early 2000s , incidence decreased by half ( 3 . 6 versus 1 . 7 per 100 , 000 population ) as a result of both the reduction in the number of bites ( 6 , 680 in 1959 versus 4 , 735 in 2005 ) and the increase in population ( 185 million versus 285 million ) . The reduction in incidence concerned most of the States , particularly in the southern and eastern US ( Fig 21 ) . However , using the National Electronic Injury Surveillance System , Langley et al . [56] estimated the number of snakebites ( including from non-venomous snakes ) to be close to 9 , 200 on average per year over the period 2001–2010 . The number of bites for which the species was identified as venomous would be more than 2 , 800 per year . Furthermore , Morgan et al . [57] reported 97 health deaths from 1979 to 1998 , i . e . 4 . 85 on average per year ( 0 . 002 per 100 , 000 population ) . The population at risk was predominantly composed of people whose age is between 10 and 50 years . However , the age-specific incidence showed a peak in teenagers ( incidence higher than 5 bites per 100 , 000 young people aged 10–14 years ) and then a steady decrease in adults to about 2 bites per 100 , 000 Subjects over 65 years of age . The sex ratio ( M/F ) was 2 . 7 . Most bites occurred from late spring to fall [53] . However , the information provided by the various databases did not detail whether the bites were accidental or illegitimate , the latter probably more frequent in USA , and not seasonal . Notification of snakebites was mandatory but data were not available online . However , the Ministry of Health published a summary report on snakebites between 1986 and 2001 and a second on the cases of 2010 and 2011 . Despite the lack of information between 2002 and 2009 , the incidence was likely to be stable . There are nearly 80 snakebites annually ( 2 . 4 per 100 , 000 population ) and 2 deaths ( 0 . 033 per 100 , 000 population ) . The geographical distribution showed a very high incidence in the eastern part of the country , high in the west and low in the south , especially in the Montevideo region ( Fig 22 ) . The age-specific incidence was the highest in young subjects between 15 and 30 years of age . The sex ratio was highly imbalanced in favor of man ( M/F = 4 . 9 ) . The seasonal incidence showed a marked increase in the spring-summer period ( October to April ) with a peak in March ( average cases twice higher than those of other summer months ) . The reporting of snakebite incidence and mortality has been mandatory since 1995 and has been available online since 1996 and 1995 respectively [58] . From 1995–96 to 2012 , the average number of snakebites and deaths was 5 , 700 ( 20 per 100 , 000 population ) and 32 ( 0 . 1 per 100 , 000 population ) a year , respectively . Incidence increased from 1996 to 2006 ( R2 = 0 . 7194 ) and then drastically decreased until 2011 ( R2 = 0 . 9576 , the last available year . The overall trend is slightly decreasing from 1996 to 2011 ( R2 = 0 . 1507 ) . A possible explanation could be deterioration in the collection of data after 2010 but it is not excluded that changes in economical activities induced a lower snakebite risk . The geographical distribution was relatively homogeneous ( Fig 23 ) . There is a correlation between the mean incidence of snake bites and population density ( R2 = 0 . 6568 ) . Interestingly , the incidence was likely to be underestimated–compared to data from other countries–in some states of the Amazon region , which could be due to either low performances of case reporting system or peculiar treatment seeking behavior by patients , both linked to poor health care offer . Mortality was relatively constant over time [59] . However , the relative risk of death as a function of age was roughly constant from childhood to adulthood up to 40 years ( between 0 . 05 and 0 . 09 per 100 , 000 subjects of each age group ) and rose in older people to exceed 0 . 5 per 100 , 000 population above 60 years of age .
Every year , near 60 , 000 snakebites ( 6 per 100 , 000 inhabitants ) are managed by the health services of the Americas . Despite the lack of mortality data in a few countries , most of which are small and poorly populous , the total number of deaths can be estimated at 370 per year ( 0 . 04 per 100 , 000 inhabitants ) , based on the data from the neighboring countries and risk factors described below . The previous epidemiological estimates , based mainly on medical and scientific literature , mentioned greater numbers of snakebites: about 115 , 000 [84 , 110–140 , 981] with 2 , 000 deaths [652–3 , 466] in the study by Kasturiratne et al . [2] and even 150 , 000 snakebites of which 5 , 000 deaths in Chippaux's one [1] . The number of bites did not decreased in the last twenty years ( see below ) , in contrary of deaths . These figures were therefore overestimated , which can be explained by the highly biased epidemiological source of information . Indeed , most authors who publish epidemiological or clinical studies on snakebites report facts upon regions with high incidence—or severity—of envenomation that are often poorly representative [60] . Nevertheless , the general incidence is much lower than in Asia or Africa [1; 2; 61] , excluding for particular regions such as the Amazon . However , mortality remains moderate , except in enclosed or poorly equipped areas . Most of the data collected in this study comes from the Ministries of Health of the concerned countries . Until now , epidemiological surveys were needed to obtain information that was most often limited geographically according to the constraints and choices of the investigators . Sometimes methodological biases , particularly in site selection , led to approximations or significant errors in the estimation of the incidence or severity of envenomations [62] . For the past decade , mandatory reporting of snakebites resulted in better epidemiological data in most countries of the Americas . Mandatory reporting of cases allows covering a country as a whole rather than a few sites chosen by the investigators , leading to poorly representative figures . However , data gaps and limitations are still observed resulting from a poor surveillance system . On the one hand , it is expected that over time the data collection will improve and on the other hand the standardization of the questionnaires will make it possible to have more robust , reliable and complete information . For example , useful , often missing data , particularly severity , treatment ( brand and dose of antivenom ) and clinical outcomes ( mortality , sequelae ) need to be collected , which is not currently the case in most situations . However , in some countries ( Brazil , United States ) , these data are available , showing that such a goal is feasible . It is rarely stated whether the notification of snakebites included asymptomatic bites , which is probably the case in most countries . Asymptomatic snakebites may result either from a bite by a non-venomous snake or a venomous one that did not inject venom ( dry bite ) . According to the countries and authors , asymptomatic snakebites represent between 10 and 40% , about one third of which are dry bites [7; 63; 64] . As a consequence , the comparison with the recent literature has been very useful for , a ) confirming ( or supplementing ) the data from other sources and , b ) providing additional information , in particular on the clinical severity of envenomations , details on circumstances of the bite or implementation of the treatment . It was emphasized that the notification was not very precise and reliable , at least variable from one country to another . However , the reporting system improves over the time and , of course , provides a minimal—conservative—incidence of snakebites seen by healthcare institutions from which it can be inferred treatment needs , especially antivenoms . The increase in incidence observed in some countries ( Bolivia , Brazil , Colombia , Mexico , Peru , Venezuela ) can be attributed to an improvement in data collection , particularly in the early years of its implementation . The stabilization or reversal of the upward trend confirms this . However , environmental ( e . g . reduction of snake population ) or demographic ( population migration to urban centers with low snakebite risk ( see below ) ) causes should not be underestimated . It is notable , for example , that the incidence is often similar on both sides of a border between two neighbor countries—despite likely differences in data collection efficiency - , reflecting a constant figure regarding both risk and population reaction to the snakebite . Actually , administrative policies are different on each side of the border , but populations are often the same on the both sides… It is known , for example , that many patients prefer to use alternative medicine rather than a modern treatment provided by health center . This occurrence is poorly addressed in Latin America , but it probably plays a significant role in underestimating the incidence and possibly severity ( mortality ) of envenomations . However , some inconsistencies can be explained either by different environmental conditions affecting the risk factors mentioned below , or by significant differences in the quality of the notifications . The report still suffers from inadequacies , resulting in underestimations of snakebite incidence and mortality in some regions of Latin America [44] . The geographical distribution of the incidence was heterogeneous: it was higher in the intertropical region and in developing countries . The incidence depends mainly on environmental and anthropic factors that are detailed below . The number of deaths appeared to be more difficult to determine due to the lack of notification in several countries . However , these countries are generally sparsely populated regions , which limit the impact on the total result . We proposed here a reasonable estimate for each of these countries at the risk of a trivial error . Basically , the incidence results from the encounter between a man and a snake . It is therefore legitimate to consider the activities and the presence of the first as well as the behaviors of the latter . It is difficult to explain what affects snakebite incidence because of the complexity of possible causes and their interactions , such as the biology of animal populations composed of many species or the demographics of human populations that are dependent on many social , economic , environmental factors . The coefficient of determination R2 indicates the proportion of the variance in the dependent variable that is predictable from the independent variable , i . e . it gives some information about the goodness of fit of a model . The closer R2 is to 1 , the better the data match the model , but this does not mean the model is relevant . Incidence tends to grow mechanically as a function of demography although there is a partial offset related to a decrease due to anthropization of the environment which reduces snake populations and/or snake-man contacts . In addition , the proximity of human populations to the natural environment explains a greater frequency of encounters with snakes . As a consequence , snakebites occur usually in rural areas during agricultural activities , especially in developing countries where farming is an important and weakly mechanized economic activity . Population density was sometimes inversely correlated with the incidence of bites , as in Brazil [20] , suggesting that a high human presence limited the development of snake populations . However , other reasons may locally explain the inverse correlation , e . g . when the human population remains large while snakes do not encounter favorable conditions for their development . For instance , the altitude and roughness of the climate appeared to have a negative impact on snake populations as shown in Bolivia or El Salvador , and Canada or Argentina , respectively . Isolated areas are the most affected , mainly due to lack of good roads linking urban centers and activities of the population performed in precarious conditions ( forestry , subsistence agriculture and hunting , among others ) . These occurrences increase both the likelihood of encounters with snakes and the difficulty of receiving timely medical help . As a consequence , scarcity of health centers is a factor that indirectly influences the incidence of snakebites and directly ( and significantly ) affects the clinical outcomes of envenomations [33; 44; 65] . The abundance of snakes , especially species that inhabit cultivated or settled areas and sometimes even reproduce there , varies according to climatic ( heat and humidity ) and environmental ( vegetation and landscape ) factors that determine food supply , both qualitative and quantitative , and camouflage opportunities [66] . While some species established in natural environments , such as the Amazon rainforest , e . g . Bothriopsis taeniata , are absent or rare in anthropogenic areas , others come near to human settlements and may even grow there [67] , at least to some extent . Some species of Crotalus , e . g . C . viridis or C . oreganus in the USA [68; 69] , or Bothrops , as Bothrops asper in Costa Rica [36] , are attracted to anthropogenic areas where they find their food . Ecological niche modeling ( ENM ) allows , using appropriate algorithms , to predict the geographic distribution of a species from climatic and environmental data . Yañez-Arenas et al . [70] used the ENM to assess the potential distributions of several species of rattlesnakes in Veracruz and to associate them with a prediction of abundance estimated by the distance from the niche centroid ( DNC ) . These authors found a significant inverse relationship between the snakebites and DNCs of two common vipers ( Crotalus simus and Bothrops asper ) , partially explaining the variation in the incidence of snakebites . Moreover , the DNCs of the two vipers , combined with the marginalization of human populations , accounted for 3/4 of the variation in incidence . Thus , several factors , environmental , socio-economic and sanitary , contribute to explain the incidence of snakebites . Populations at risk were very similar in most countries . While children and teenagers constituted an important part of the population , sometimes the majority in developing countries , they were not the mostly bitten . Population at risk was predominantly composed of young men between the ages of 15 and 45 , living in rural areas and bitten during agricultural activities . This may explain why bites occur most often during hot ( summer ) and wet ( rainy season ) periods , usually at harvest time . The severity of the envenomation , in particular mortality , is related to the species , but also the size , of the snake responsible for the bite , which determine the composition of the venom and the quantity injected respectively [14; 15; 71] . This explains why some snakebites are asymptomatic , when the snake is not venomous , or when it does not inject its venom [6; 7; 63; 64] . It is more difficult to explain some of the factors identified by Jorge et al . [71] as the season or time of day . This may be due to a particular distribution of species within stands , depending on time and space according to their ecological tropisms . Age of the patient appeared to be a risk factor , especially at both ends of life , in children and elderly persons–a priori more vulnerable [72] . However , as we have seen above , children are not the most exposed . In addition , the mortality and incidence of complications–most notably the sequelae–depend on the management of snakebites , i . e . the health care system as a whole ( number and distribution of health facilities , equipment , access to antivenoms and adequacy of therapeutic protocols , skill of health personnel , etc . ) . For example , the significant decline in mortality in many countries–particularly in Costa Rica [30–32] , Ecuador [34] , Mexico [43] and Venezuela [59] while the number of snakebites in these countries remained stable or even increased–can be attributed to better management of snakebites , notably through the improvement of primary health care and access to medical services , including availability of antivenoms . However , other factors may also affect the mortality and severity of envenomations , such as the availability of health centers and treatment , which may be very irregular , particularly in remote areas where activities of the indigenous population are often very close to nature . The delay in treatment may thus compromise the clinical course of envenomation . Nevertheless , the treatment seeking behavior is complex and many patients , particularly in remote areas , still use traditional medicine . The latter should be associated with modern medicine in order to define relevant recommendations that do not put them into competition but optimize the therapeutic approaches to avoid complications and disabling sequelae as is still often the case . This study summarized the burden and epidemiological characteristics of snakebites in the American continent . The incidence and severity of envenomation appeared to be lower than previously assessed , although many risk factors have been already known and studied . This work showed the importance of mandatory reporting of snakebites to improve their management , provided that health authorities endorse , analyze and exploit the data . It therefore seems necessary to continue this effort , improve the case reporting system and take the measures that can be inferred from the obtained analysis of the available information . | A better knowledge of snakebites incidence and mortality might improve their management . However , they are difficult to estimate , in particular because most of them are based on extrapolations from scientific and medical publications that are not representative of the epidemiological situation . This study , based on data available on-line at government sites in the Americas—reflecting notifications from health services—sustained by recent publications to provide useful information on snakebites treated in health centers of American countries . On average , nearly 60 , 000 snake bites are managed every year in health facilities in the Americas and approximately 370 deaths are reported officially . The development of snake populations results from environmental conditions favorable to their feeding and camouflage . Moreover , the activities of human—notably agricultural—explain encounters with the snakes . The literature underlines that the severity of the envenomation depend on the species responsible for the bite and quality of the management of the patient . Without excluding an underestimation of snakebite incidence , due to the frequent use of traditional medicine , this study should enable health authorities to better analyze the epidemiological situation of snakebites , including their frequency , distribution and severity , in order to improve the management of the envenomation . | [
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"s... | 2017 | Incidence and mortality due to snakebite in the Americas |
Covalent modification of proteins by ubiquitin or ubiquitin chains is one of the most prevalent post-translational modifications in eukaryotes . Different types of ubiquitin chains are assumed to selectively signal respectively modified proteins for different fates . In support of this hypothesis , structural studies have shown that the eight possible ubiquitin dimers adopt different conformations . However , at least in some cases , these structures cannot sufficiently explain the molecular basis of the selective signaling mechanisms . This indicates that the available structures represent only a few distinct conformations within the entire conformational space adopted by a ubiquitin dimer . Here , molecular simulations on different levels of resolution can complement the structural information . We have combined exhaustive coarse grained and atomistic simulations of all eight possible ubiquitin dimers with a suitable dimensionality reduction technique and a new method to characterize protein-protein interfaces and the conformational landscape of protein conjugates . We found that ubiquitin dimers exhibit characteristic linkage type-dependent properties in solution , such as interface stability and the character of contacts between the subunits , which can be directly correlated with experimentally observed linkage-specific properties .
Ubiquitylation is a selective process mediated by a complex enzymatic cascade and involved in the regulation of many cellular processes [1] . Usually , ubiquitin ( Ub ) is covalently attached to substrate proteins via isopeptide bond formation between its C-terminal carboxylate group and the ϵ-amino group of a substrate’s lysine residue . Since Ub itself contains seven lysine residues and each of these as well as the N-terminal α-amino group can be ubiquitylated , substrate proteins can either be mono-ubiquitylated or modified by an in principle sheer unlimited number of different types of Ub polymers ( Ub chains ) [2] . Homotypic Ub chains , i . e . within one chain Ub moieties are linked via the same lysine residue or via the N-terminal methionine , are the best understood chain types with respect to structure and function [3] . For example , in a simplified view , K48-linked Ub chains target proteins to the 26S proteasome for degradation , while K63-linked chains signal modified proteins for non-proteolytic fates . The “Ub code” , i . e . the relation between the linkage type and the fate of the modified protein , is presumably mediated by different conformations of differently linked Ub chains [4] . The latter are in turn recognized by proteins harboring Ub binding domains ( UBDs ) that show either relative or absolute selectivity for different linkage types and determine the eventual cellular signal [5] . Due to their functional and physiological relevance , Ub chains and , in particular , Ub dimers have been a popular object for structural analysis by X-ray crystallography [6–9] and NMR spectroscopy [10–16] . The data clearly indicate that Ub dimers adopt different stable conformations that vary in their extent of inter-domain contacts . However , the structures available represent a subset of the entire conformation space that can be occupied by individual Ub dimers . The hydrophobic patch , as an example , that was reported to serve as an interaction hot spot for K48-linked chains , is apparently not accessible in various structures that were determined for this linkage type [17] . Consequently , additional efforts are required to elucidate the entire conformational ensemble of Ub dimers and , thus , the Ub code [18] . Molecular dynamics ( MD ) simulation is ideally suited to complement experimental data and to provide novel insights into properties of Ub dimers , like the nature and thermodynamic stability of distinct conformations in solution . Although Ub was in the focus of several computational studies , the full conformational space of Ub dimers has not been described by MD simulations so far [19–21] . Due to the computational cost of atomistic sampling , the equilibrium between different conformations is hardly accessible by standard atomistic MD techniques for a system of that size . A common method to overcome time and size limitations of atomistic MD simulations is coarse graining ( CG ) [22–25] . By uniting several atoms into one bead , the number of degrees of freedom can be drastically reduced ( Fig 1A ) . Additional speedup is gained from softer potentials which allow larger time-steps and faster effective kinetics . On the downside , reduction of resolution inevitably limits the capability of a CG model to correctly reproduce all properties of a system . Therefore , in the present study , we pursued a dual-scale approach that takes advantage of CG and atomistic levels of resolution to simulate all 8 natively linked Ub dimers [26 , 27] . Thus , we managed to sample the conformational phase space of each dimer on the timescale of 120 μs . We introduce a new method to characterize and compare conformational free-energy landscapes of protein conjugates . This enabled us to systematically connect simulations on different resolution levels and to provide a quantitative measure for the similarity of differently linked Ub dimers ( diUbs ) . We obtained a reliable atomistic description of their respective conformational characteristic which is in good accordance to known experimental data and can serve as an explanation for linkage-specific biological function .
Key to the identification of conformational states is finding suitable collective variables ( CVs ) that capture the characteristic features of a system . Since the number of CVs is often very large , dimensionality reduction techniques are applied that allow the data to be projected into a two or three dimensional representation for visualization and further interpretation [28] . For the characterization and comparison of diUbs , we identified a high-dimensional ( 144D ) set of CVs that describe the multi-domain structure by internal coordinates between the two Ub moieties and projected these data to a 2D representation to obtain estimates of the free-energy landscape . In the following , we present a more detailed analysis of the conformational space visited by the diUb , with the aim to better understand the differences and similarities between the linkages , identify linkage-dependent surface properties of the chains , and relate them to experimental data .
By the use of dual-scale MD simulations and a detailed mathematical analysis of the thus obtained conformational ensembles , we obtained insights into the properties of differently linked Ub dimers in solution . Residue-wise minimum distances turned out to be suitable CVs to represent the conformational space of diUb , in particular with a sketch-map projection into a 2D free energy landscape . We showed that this allows an intuitive examination of the conformational space , as well as qualitative and quantitative assessment of the ( dis ) similarities of different linkage types . In the present case , we were able to validate data that were obtained from a CG force field with atomistic simulations and compare all native diUb types . This newly developed approach for diUb should be more generally applicable to other problems where domains perform complex movements relative to each other . For diUb , we found that the character of inter-domain contacts depends strongly on the linkage position . Thus , the surface of Ub , which is accessible for contacts with interaction partners , is altered by ubiquitylation , particularly on the proximal monomer . However , some diUb show very similar behaviour , e . g . K6 and K11 or K29 and K33 , which is in agreement with experimental results and confirms the redundant character of the ubiquitin code [15] . Coverage of distal residues is comparable for all linkage types . We therefore conclude that the most distal Ub in a Ub chain makes the least contribution to specificity . Hence , the proximal Ub , which is ubiquitylated itself , holds the major information about the actual function of the respective chain type . This provides a hint why sometimes a certain minimum Ub chain length is required for recognition by UBDs [38] . It may also indicate that deubiquitylating enzymes , which perform distal trimming of Ub chains [39] , have to bind to at least two of the very last subunits of a chain to obtain linkage type specificity . In the future , it will be highly interesting to study the behavior of Ub moieties , which are in the interior of a longer chain and consequently should display a mixture of unspecific distal and specific proximal properties . This will extend our knowledge about relevant patterns underlying the Ub code . Work provided here opens up a whole realm of possible applications to questions related to protein-protein interactions inside as well as outside of the Ub signaling system .
All simulations were performed with the GROMACS simulation package v5 [40] . Temperature and pressure were kept at 300 K and 1 bar using the velocity rescaling thermostat and the Parrinello-Rahman barostat , respectively . The Verlet cut-off scheme was applied . The LINKS algorithm was used to constrain all bonds . The default md ( leap-frog ) integrator was used . All open initial conformations of diUb were constructed from two Ub units ( PDB-ID: 1UBQ ) by placing the Ub moieties next to each other so that the C-terminal distal carboxyl group and the proximal lysine side chain were closer than 0 . 3 nm . For each linkage type , a second conformation was generated . For this , the relative orientation between the distal and proximal Ub was altered . For all simulations , diUb was placed in a 10×10×10 nm dodecahedron box to avoid interactions between periodic copies . All structures were relaxed by energy minimization before and after solvation . Solvated systems were equilibrated in three short runs of 200 ps: ( 1 ) under constant temperature ( NVT ) with a position restrained backbone; ( 2 ) under constant temperature and pressure ( NPT ) with a position restrained backbone; ( 3 ) NPT without any position restrains . For atomistic MD simulations , the GROMOS96 54a7 force field [41] with the SPC/E water model was used . The integration time step was 2 fs with a cut-off for short range van der Waals interactions of 1 . 4 nm . Electrostatics were treated with the Particle Mesh Ewald scheme with a 1 . 4 nm cut-off . Coarse grained diUb structures , which were used for atomistic simulations , were back-mapped with BACKWARD [32] . The force field had to be complemented to enable the simulation of covalently linked dimers via an isopeptide bond . The respective parameters were chosen in analogy to the regular peptide bond of the force field . The MARTINI force field v2 . 2 [42 , 43] was used as basis for all CG simulations . The MARTINI non polarizable coarse grained water was used as solvent . A 10 fs time step could be used due to the soft elastic network potentials . The cut-off distance for short range van der Waals interactions was set to 1 . 1 nm and electrostatics were treated by the reaction field method with a cut-off distance of 1 . 1 nm and a dielectric constant of 15 . For nonbonded interactions a modified MARTINI parameter set where all protein-water interactions are increased by 0 . 35 kJ mol was used ( kindly provided by D . H . de Jong , University of Muenster , personal communication ) . Structure and topology input files for CG simulations were created with the martinize script , v2 . 4 available at the MARTINI project website . For construction of topologies of diUb , this script was modified and functionality for a formation of an isopeptide bond was added . All coarse grained simulations were performed using the ELNEDIN force field [44] for bonded interactions . The MARTINI ff was adapted to describe the structural and dynamic properties of diUb as accurate as possible . This was achieved in three steps . Firstly , by parametrization of an isopeptide linker , which is not available in MARTINI . Secondly , by determination of a favorable secondary structure in solution for assignment of the strength of non-bonded backbone interactions . For further details please see S1 Text . Finally , a supportive network was derived to reproduce the intrinsic dynamic properties of Ub correctly . The Iteratively-refined Distance-based Elastic Network ( IDEN ) method [45] was used to obtain a supportive network . This approach requires an ensemble of reference conformations which was composed from atomistically simulated structures and already used for secondary structure determination . Best results were achieved using a maximum bond distance of 1 . 0 nm and an initial force constant of 800 kJ mol . Pseudobonds were excluded by a variance threshold of 0 . 015 nm and explicitly included by a covariance threshold of 0 . 7 nm . Refinement against distance variance differences was achieved using 50 ns long reference simulations with a scaling factor of 4000 over 30 iteration steps . Pseudobonds with a final force constant of 1 kJ mol or lower were removed from the topology to prevent cut-off errors and thus terminations in subsequent simulations . Sketch-map v3 . 0 was used . RMD values were computed every 100 ps and 10 ps from CG and atomistic simulations , respectively . Based on the high-dimensional distance distribution of CG data , the sigmoid function parameters σ = 5 . 9 , A = 12 , B = 4 , a = 2 , b = 4 were chosen . Landmarks ( N = 2000 ) were selected from CG simulations only ( S1 Fig ) . This selection was done randomly in combination with the minmax option with γ = 0 . 1 . For further details please see the Results section and S1 Text . | Post-translational modification of proteins by covalent attachment of ubiquitin is a key cellular process , regulating for example the fate and recycling of proteins . We present a new method to combine multiscale simulation with advanced analysis methods to characterize the states of ubiquitin-ubiquitin conjugates . We found that the linkage position affects the conformational space of ubiquitin dimers , determining the number and stability of relevant states , the character of subunit contacts and the nature of the surface exposed to possible binding partners . | [
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"anal... | 2018 | Towards a molecular basis of ubiquitin signaling: A dual-scale simulation study of ubiquitin dimers |
Trachomatous trichiasis ( TT ) will continue to develop among those people who have had repeated infections after active trachoma is controlled . Detecting and treating affected individuals will remain necessary for years; a long “tail” of incident cases is anticipated . As the prevalence of TT declines , there will be fewer cases available for training trachoma graders ( TG ) , necessitating alternative methods . Prospective , diagnostic accuracy study assessing sensitivity and specificity of 3D and 2D photography as a tool for training TG to detect TT . Individuals with TT in Ethiopia were examined , and 2D and 3D clinical images taken . Images were independently graded by four graders for presence or absence of trichiasis and compared to field grading . We recruited 153 participants . Clinical assessments and images were available for 306 eyes . Trichiasis was identified in 204 eyes by field grading . Image grading was performed on a selection of 262 eyes ( 131 with trichiasis ) . Most eyes with trichiasis had minor trichiasis ( 94/131 ) . Pooled sensitivity was 88 . 3% ( 3D ) and 98 . 0% ( 2D ) ; pooled specificity was 59 . 8% ( 3D ) and 26 . 8% ( 2D ) . 3D photo grading was 33 . 0% more specific than the 2D photo grading ( p = 0 . 0002 ) . The overall Kappa scores were 0 . 48 ( 3D ) and 0 . 25 ( 2D ) . We trained 26 novice TG in Ethiopia using 3D images . They were tested on a 3D images set and had 71 . 4% agreement ( kappa 0 . 46 ) , relative to an expert . They were then tested examining 50 people , and had 86 . 8% agreement ( kappa 0 . 75 ) . We also tested 27 experienced TG on the same cases ( 86 . 4% agreement , kappa 0 . 75 ) . There was no difference in performance between groups ( p = 0 . 76 ) . All participants preferred 3D over 2D images for training . The slightly higher sensitivity of 2D photos comes at considerable cost in specificity . Training with 3D images enabled novice TG to identify cases as well as experienced TG . 3D were preferred to conventional 2D photos for training . Standardized 3D images of TT could be a useful tool for training TG , in settings where there are now few TT cases .
Trachoma remains the commonest infectious cause of blindness worldwide . [1] The World Health Organization ( WHO ) Alliance for the Global Elimination of Trachoma ( GET2020 ) aims to eliminate the disease as a public health problem by the year 2020 . [2] The two key clinical parameters used to guide programme decisions and the assessment of elimination are the prevalence of trachomatous inflammation—follicular ( TF ) conjunctivitis in children and trachomatous trichiasis ( TT ) in adults . These clinical signs form part of the WHO Simplified Trachoma Grading System , which was designed for field grading by non-specialists , and is widely used in surveys to measure the disease prevalence . [3] The Global Trachoma Mapping Project ( GTMP ) , which mapped nearly all accessible suspected trachoma endemic districts , developed a protocol to train trachoma graders to reliably recognize these signs . [4 , 5] This built on earlier training protocols used by trachoma programmes in Ethiopia , Nigeria and South Sudan . [6–8] As countries approach the elimination targets and need to demonstrate sustained achievement , a similar methodology is being applied , through Tropical Data , with additional surveys following the cessation of intervention programmes . Tropical Data is a WHO led survey methodology and data management platform developed partly out GTMP , after GTMP was completed in 2015 . The GTMP/Tropical Data trachoma prevalence survey training for graders is conducted over five days , the first two of which are an intensive classroom- and field-based “grader qualifying workshop” . [9] In order to qualify as a grader , candidates need to pass ( kappa ≥0 . 7 ) a photograph-based inter-grader agreement ( IGA ) test comprising 50 images showing the presence or absence of TF . Subsequently , they need to pass a field IGA test ( kappa ≥0 . 7 against a grader trainer ) on 50 children of whom at least 5 have TF . Tropical Data has also developed a TT-only survey training manual , which includes an Objective Structured Clinical Examination ( OSCE ) using photographic images ( 2D or 3D ) to assess trainees’ skills in TT grading , as the number and availability of people with trichiasis is too low to assess via an IGA assessment . [10] In 1990 West and Taylor proposed that using still images was a valid and reliable tool for grading trachoma . [11] This was used to assess the appearance of the tarsal conjunctiva , but not TT . Since then , there have been a number of studies comparing field grading to photographic assessment . [12–14] The Kappa-values in these studies ranged from 0 . 44 to 0 . 75 . However , none of these studies have compared the field and photograph grading of TT . A recent trial comparing two alternative trichiasis surgery procedures used two dimensional ( 2D ) clinical images to assess the presence of TT following surgery . [15] In this study the photographic grading result was highly concordant with the field grading . However , TT was slightly “over-called” from these images compared to the field-grading; this was thought to be due to the two-dimensional nature of the images , which can give the impression that lashes overlying the globe are touching when there is actually a small gap . Three-dimensional ( 3D ) images may be able to reduce this limitation of 2D images by providing an additional perspective on whether the eyelashes close to the eye are actually touching the globe . There have been no previous reports of the use of 3D photography to assess trichiasis . In this study we investigated whether this might be a useful tool in the training and assessment of graders within a trachoma control programme , especially during the anticipated long “tail” of incident TT , following the control of active disease . We initially compared the masked grading of 2D and 3D images to the “live” field grading of the same eyes , for the presence of TT with lashes touching the eye . We then trained a cohort of trichiasis graders using 3D photography and compared their performance with experienced trichiasis graders . Our objectives were to firstly investigate the relative diagnostic accuracy of 2D and 3D images , compared to “live” grading . Secondly , to evaluate the utility of using 3D images within training programmes for teaching the novice trainees how to detect TT and compare their performance in “live” grading by experienced graders .
This study was approved by the Ethiopian National Health Research Ethics Review Committee , the London School of Hygiene & Tropical Medicine Ethics Committee and Emory University Institutional Review Board . It conformed to the tenets of the Declaration of Helsinki . Written informed consent in Amharic was obtained before enrolment of participants . If a participant was unable to read and write , the information sheet and consent form were read to them and their consent recorded by thumbprint in the presence of an independent witness . The study took place in Amhara Region , Ethiopia . It was conducted in two parts: ( 1 ) comparison of field to photographic grading; ( 2 ) evaluation of 3D images within a training programme . Only adults were recruited into the study . In this prospective study , consecutive adults with upper lid TT in one or both eyes were recruited through community-based screening conducted at community health centres in three districts of West Gojam Zone . TT was defined as one or more lashes touching the globe . Both eyes were examined by a single experienced field grader ( EH ) using 2 . 5x binocular loupes with a torch and graded using the Detailed WHO FPC Grading System . [16] Eyelids were graded for the presence or absence of TT and the number of lashes touching were counted . Standardised 2D and 3D images were taken using a Nikon D90 digital SLR camera with Loreo 3D macro lens and Nikon SB-R200 flash units . Images were taken in primary gaze and up-gaze . We found substantial dermatoblepharochalasis was common and frequently obscured the view of the lid margin and lashes . Therefore , the skin of the upper eyelid was supported with a swab shaft to prevent it resting heavily on the lashes . Care was taken to ensure that this did not cause external rotation of the lid margin that might affect whether or not lashes touched the globe . The Loreo 3D system works by transposing two images within the beam-splitter into a parallel format output . This results in a pair of “split images” ( Fig 1 ) . This image pair can then be viewed using a low-cost parallel format 3D-image viewer which incorporates two prismatic lenses , allowing someone with stereoscopic vision to fuse the images and view the image in 3D . The resulting image size on the retina is similar to that obtained when viewing a patient with 2 . 5x loupes . Comparisons were made between the field grading ( EH ) for the same eye and the image grading by four independent graders with experience in trachoma field grading . For the image set that was used in this comparison , poor quality images ( out of focus , movement artefact , over/under exposed ) were excluded . In addition , we randomly excluded images of eyes with TT until we were left with an approximately equal number of images with and without TT . The orders of the both 3D and 2D image sets were randomised and all images were relabelled . The 3D images were viewed on a MacBook Pro 15” with Retina Display computer ( Apple ) using Loreo 3D Pixi-Viewer glasses under standardised conditions: monitor set to full brightness in a darkened room and no changes made to the display settings . For the 2D assessment , the left-hand image of the two “split images” was used without the 3D glasses . Grading of all the 2D and 3D images was done separately . Each eye was evaluated using the primary gaze and up-gaze images . Graders were asked to specify whether they thought there were any lashes touching the globe . For the counting of lashes , the highest number of lashes touching the eye seen in either primary or up-gaze was recorded as the result . In February 2018 , 26 health professionals ( 17 Health Officers , and 9 BSc Clinical Nurses ) , hereafter referred to as Trichiasis Graders ( TG ) , with no prior training or experience of TT case identification were recruited from 17 districts of West Gojam Zone , Amhara Region , and were enrolled on a four-day training programme for TT case identification using 3D images . The mean age of the TGs was 26 years ( Range 21–40 years ) , 18 were male and 8 were female . The training was based on the Amhara Region Integrated Eye Care Worker ( IECW ) training manual and incorporated all the components of IECW training except for trichiasis case identification training using live subjects . This training included prevention of blindness and primary eye care , anatomy of the eye , common eye conditions , trachoma , TT case mobilisation , eyelid examination techniques using magnifying loupes . Trainees were initially shown clinical images of trachoma in 2D , including TT , projected onto a large screen . Then they were trained in the identification of trichiasis using a series of 3D pictures . The trainees were shown how to view 3D images printed on paper using the Loreo Pixi-Viewer 3D glasses ( Fig 2a ) . Once they were confident with obtaining a 3D view , they were shown a series of 3D images of eyes with and without trichiasis over one day of intensive training . They were taught how to grade whether trichiasis was present or not and to count the number of eyelashes touching the eye if trichiasis was present . On the final training day , all trainees were tested in an intergrader assessment ( IGA ) using a set of 3D colour printed images of 50 eyes with and without trichiasis ( Fig 2b ) . This set of images had been selected from those used in Part 1 . We only included images for which all four experienced graders agreed with the field grading on the presence or absence of trichiasis . The image set contained 28 eyes without trichiasis and 22 cases with trichiasis . For each eye two 3D pictures were printed on one page showing primary position and up-gaze ( Fig 1 ) . The trainees were asked to grade the eye for the presence or absence of trichiasis , and then to count the number of lashes touching the eye if TT was thought to be present . They were allowed 30 seconds per image ( 1 minute per eye ) , equating to a test of 50 minutes in duration . Images with only evidence of epilation , but without lashes currently touching , were graded as having “no trichiasis” . Immediately after the IGA the trichiasis graders were asked to complete an evaluation form on the 3D training . The evaluation form included questions on the ease of using 3D glasses , subjective comparison of 2D and 3D images , future application of 3D image-based trichiasis graders training , and suggestions for improvements . After the completion of the 3D training and IGA , the trichiasis graders were then taken to the field to assess 50 patients ( one eye per patient ) with and without trichiasis , using 2 . 5x magnifying loupes and a torch . In this “live” clinical assessment test they were allowed 90 seconds per patient . There were 23 people ( eyes ) with trichiasis and 27 people ( eyes ) without trichiasis . The trichiasis graders were asked to record presence or absence of trichiasis , and to count the number of lashes touching the eye , if trichiasis is present . Their results were compared to the grading given by an expert trachoma grader ( EH ) on the same day . Immediately after the trainee test , a separate group of 27 experienced IECWs ( 8 Health Officers , and 19 BSc Clinical Nurses ) , with a mean age of 28 years ( range 24–36 years ) , from 17 districts of Wet Gojam Zone , Amhara Region , examined and graded the same group of 50 patients using the same procedure . This was done to compare the grading quality of trichiasis graders trained using 3D images to the grading quality of experienced IECWs , most of whom had previously been involved in trachoma impact assessment surveys . At the end of the exercise , all subjects were re-graded by the expert trachoma grader . Data were double-entered into an Access database ( Microsoft ) and transferred to Stata 14 ( StataCorp ) for analysis . For the first part of the study we calculated for each grader the sensitivities , specificities , positive predictive values ( PPV ) , negative predictive values ( NPV ) , overall percentage agreement and Kappa scores relative to the field grading ( EH ) . Estimated values for sensitivity and specificity were obtained using logistic regression with a random effect included for the rater , the mean kappa score was estimated by taking the mean of the Fisher Z-transformed kappa scores , then back-transforming . P-values comparing sensitivities and specificities for 2D versus 3D images were calculated using the Z-test . For the second part , we compared the results of the novice TG image grading and live clinical assessments to the grading of the same patients by the expert grader ( EH ) . Similarly , we compared the results of the experienced ICEWs to those of the expert grader . We plotted Hierarchical Summary Receiver Operating Characteristic ( HSROC ) curves for the relationship between the reference field grading ( EH ) and the trainees’ grading of the 3D images .
We recruited , examined and photographed the eye of 153 people for this study . Their mean age was 50 . 9 years SD 14 . 0 , range 18–80 ) and 96 ( 62 . 8% ) were female . We selected 260 good quality eye images for masked grading , of which 131/260 ( 50 . 4% ) eyes had trichiasis and 129/260 ( 49 . 6% ) did not have lashes touching the globe at the time of examination . Among eyes with current TT , the mean number of lashes touching the globe was 5 . 16 ( SD 6 . 28 , median 3 , range 1–40 ) . The distribution of the total number of lashes touching the eyes with trichiasis is shown in Fig 3 . The sensitivity and specificity , PPV and NPV for the 3D image grading compared to the field grading are presented in Table 1 . The pooled estimates of sensitivity and specificity were 88 . 3% ( 95% CI 84 . 4–91 . 4% ) and 59 . 8% ( 95% CI 46 . 2–72 . 1% ) , respectively . The corresponding results for the 2D photos are also presented in Table 1 . Their pooled sensitivity and specificity were 98 . 0% ( 95% CI 91 . 4–99 . 6% ) and 26 . 8% ( 95% CI 17 . 2–39 . 2% ) , respectively . There was a statistically significant difference in both the sensitivity and specificity between 2D and 3D images for each grader ( Table 1 ) . Overall , the sensitivity was slightly higher ( 9 . 7% , p = 0 . 0004 ) for the 2D images and specificity substantially higher for 3D images ( 33 . 0% , p = 0 . 0002 ) . This suggests that although 2D grading was slightly more sensitive , this was at the expense of reduced specificity . There was also slightly better overall agreement between the grading of 3D images ( 73 . 9% ) and the field grading , compared to the 2D image ( 62 . 8% ) grading . One grader ( Grader 3 ) tended to over-grade TT , resulting in a lower specificity for both 2D and 3D photos . When there were discordant results between field grading and 2D or 3D photo grading , this was mainly due to false positives , i . e . lashes that were not found to be touching on field grading but were overlying the globe and therefore appeared to be touching in the images . The four graders reported fewer false positives from the 3D images . Furthermore , the false positives from 3D image grading were mainly for minor trichiasis ( median 1 lash touching , IQR 0 . 75–2 , using mean of graders ) , compared to 2D image grades , where the distribution was over a wider range ( median 3 lashes touching , IQR 2–4 . 5 ) , Fig 4A . The false negatives ( cases of TT identified by field grading , but graded as not having TT by 2D or 3D images ) tended to milder trichiasis , with only 1 or 2 lashes touching on field grading , Fig 4B . The pooled overall agreement for the intergrader assessment comparing the trainees’ 3D image grading to the expert field grading was 71 . 4% ( SD 9 . 2% , range 52–88% ) . The pooled sensitivity and specificity were 87 . 7% ( CI 82 . 4–91 . 6 ) and 62 . 8% ( CI 52 . 1–72 . 4 ) , respectively , shown in the HSROC plot ( Fig 5 ) . The mean kappa score was 0 . 46 ( CI 0 . 39–0 . 52 ) . The individual kappa scores for each trainee are given in Table 2 . In the “live” clinical assessment test of the trainees , the pooled overall agreement was 86 . 8% ( SD 5 . 3% , range 74–94% ) , compared to the results of an expert trachoma grader . Their pooled sensitivity was 86 . 7% ( 95%CI: 83 . 4–89 . 4 ) and pooled specificity was 89 . 0% ( 84 . 9–92 . 1 ) , shown in the HSROC plot ( Fig 6 ) . The mean kappa score was 0 . 75 ( CI 0 . 71–0 . 79 ) . The individual kappa scores for each trainee are given in Table 2 . In the “live” clinical assessment test of the experienced IECWs , the pooled overall agreement was 86 . 4% ( SD 5 . 9% , range 72–96% ) , compared to the results of an expert trachoma grader . Their pooled sensitivity was 91 . 9% ( 95%CI: 89 . 3–93 . 9 ) and pooled specificity was 83 . 2% ( 78 . 3–87 . 1 ) , shown in the HSROC plot ( Fig 7 ) . Their pooled kappa score was 0 . 75 ( CI 0 . 70–0 . 79 ) . The individual kappa scores for each IECW are given in Table 3 . There was no evidence of a difference between the trainees and the experienced IECWs in the odds of overall correctly diagnosing the presence or absence of TT ( OR = 0 . 96 , 95%CI 0 . 74–1 . 24 , p = 0 . 76 ) . However , there was some evidence that the two groups had slightly different sensitivity and specificity . The experienced IECWs had slightly higher sensitivity ( OR = 1 . 74 , 95%CI 1 . 21–2 . 49 , p = 0 . 003 ) for detecting TT than the trainees . Conversely , the IECWs had a slightly lower specificity ( OR = 0 . 62 , 95%CI 0 . 39–0 . 98 , p = 0 . 041 ) than the trainees . The number of trichiasis cases and the number of eyelashes touching the cornea did not change between the first grading by the trachoma expert and the final grading at the end of testing . The 3D glasses were found to be either “very easy” or “easy” to use by 80 . 8% of trainees and viewing the 3D images was considered to be either “very realistic” or “realistic” by 84 . 6% of the trainees ( Table 4 ) . All 26 ( 100% ) trainee participants found the 3D images were more useful than 2D images for training and thought that they should be included in future training . The most commonly reported reasons for 3D image preference included being able to see trichiasis more clearly than with 2D images ( 52% of responses ) and being easy to use ( 26% of responses ) . Conversely , negative feedback for 3D images centred around taking time to get used to viewing them ( 62 . 1% ) , with the second most frequently reported negative feature was being difficult or unable to use ( 17 . 2% ) . When asked for suggestions for improvement with the 3D training , the most commonly suggested improvement was to allow for more time for 3D training ( 22 . 6% ) , whilst no improvement was suggested in 41 . 9% of responses . The full results are given in Table 4 .
It is currently estimated that there are about 3 . 2 million people with TT in need of surgery . [17] Reliably identifying people with TT is key for both finding all individuals needing corrective trichiasis surgery , as well as measuring programme impact and ultimately the validation of elimination of trachoma as a public health problem by WHO . In many settings the numbers of individuals with untreated TT are already very low or anticipated to become very low in the near future . Therefore , it is increasingly impractical to gather sufficient numbers of TT cases together at one time to perform a “live” interobserver assessment exercise . Reliable alternative methods to train and assess TT graders are needed . In this study we first investigated the relative utility of 2D and 3D images of the same eyes to determine whether or not eyelashes were touching the eye . Using field grading as the “gold standard” , the sensitivity of 3D photography was high ( 88% ) and its specificity was relatively good ( 60% ) . Although the sensitivity of 2D image grading was higher ( 98% ) than for 3D , this was at a considerable cost to specificity ( 27% ) . There was a tendency for the graders to “overcall” TT from 2D images; this was significantly reduced by using 3D images . In 2D images downward projecting eyelashes from the upper eyelid may appear to be touching the eye when in fact they are not . We found that 3D images help to overcome this to a certain extent by providing a stereoscopic view of the eyelashes , so that it is easier to tell if they are touching the eye or projecting over it without touching . The kappa scores and percent agreement were higher for 3D images , providing some evidence that these are moderately better than 2D images for determining whether or not lashes are touching the eye . There is little published data comparing photographic grading with field grading for TT . Most studies have focused on grading active trachoma . [11–14] Moreover , there is little published on the reliability of TT grading from an operational setting . We recently reported use of 2D eyelid images to assess for signs of TT; this was done to independently evaluate potential observer bias when assessing the outcome of two different surgical interventions in a randomised controlled trial . [15] Although there was good agreement between the field and image grading ( % agreement , 86 . 6%; Kappa , 0 . 60; Sensitivity , 83 . 8%; Specificity , 87 . 2% , PPV , 58%; NPV , 96 . 2% ) , we found 2D image grades tended to slightly “overcall” TT , which is consistent with the present study , and led us to explore the potential value of 3D photography for this . There have been no previous studies assessing 3D photography for TT . An analysis of the number of lashes thought to be touching in TT “false positive” eyes from 3D images found the large majority had only 1 or 2 lashes , when the field grading indicated none . The “false positive” eyes from the 2D images had a higher median value . Again , this is likely due to the greater difficulty of assessing the relative position of lashes in a two-dimensional image . The “false negatives” tended to be eyes with only 1 or 2 lashes touching . Three of the four graders had similar results . However , Grader 3 tended to “overcall” trichiasis for both image sets , leading to a lower specificity . This accounts for the wide confidence interval for pooled specificity . Despite this , the specificity and percent agreement for Grader 3 were higher for the 3D images , suggesting that this provides more reliable differentiation than 2D images . Training with 3D images was well received by the candidates . They gave positive feedback , and it prepared them well for grading patients . The performance of the new trainees who had been taught on 3D images and the experienced IECWs were very comparable . The trainees performed better in the “live” grading exercise than on the 3D assessment . This suggests that the 3D test may in fact be more difficult than the field grading itself . Furthermore , candidates received their results with feedback following the 3D test , which may have influenced how they performed on the field grading test ( i . e . candidates performing poorly may have been motivated to prepare better for the field grading or improved their skills as a result of the exercise ) . The results of the 3D test do not predict performance in the field grading . Tropical Data uses a cut-off of 0 . 7 or greater as the kappa score for the IGA test for TF , for both the slide test as well as on real patients . [9 , 10] There is currently no formal assessment of TT grading in the prevalence survey training manual , although the OSCE methodology used in the TT-only training manual will be incorporated into the upcoming revised prevalence survey training manual . If we were to use the same benchmark , only 1/26 candidates would “pass” the 3D IGA test ( and none of the four experts ) . We therefore do not recommend that the results of the 3D IGA test should be used for TG to progress to field grading . However , the TG performed much better with the real patients , when 19/26 TG would have passed this benchmark . We therefore propose that training candidates using 3D photography is a useful , more realistic tool than 2D photography alone . There are a number of limitations to our study . In this study the field grading was considered to be the “gold standard” , which assumes that all cases of trichiasis and no trichiasis were correctly diagnosed . It is possible , although relatively unlikely , that the field grading may have been incorrect in some cases , which would affect the results . This field grader ( EH ) has more than 10 years field grading experience and has previously been shown to have a very strong agreement in grading validation studies with senior graders . [15] For the 2D photograph in this study , we chose to use the left-hand image of the split 3D image , rather than the higher resolution 2D macro image which was available . It was felt that although the macro image was of a higher resolution and much higher magnification , it was less realistic compared to what would be encountered in real life and therefore of less value for training and assessment purposes . This study set out to assess a new form of imaging for training and assessing graders rather than for remote image grading . Using 3D viewing glasses can take a few minutes of practice and requires binocular single vision . The 2D image used was not taken using the same set-up as previous studies using a dedicated 2D macro lens which gives much greater magnification . The results for 2D grading may be better when using a more magnified image; however , as discussed above , this is less realistic when compared to examining in the community . There is a limitation to using Kappa scores as its use depends partly on the proportion of the population on which it is difficult to agree , with lower Kappa scores when there is a higher number of difficult cases . [18] We did not directly compare novice TG trained using conventional 3D images to a separate group of novice TG trained using 2D images as we had previously shown that 3D images provide similar sensitivity and substantially better specificity for the detection of trichiasis . Stereopsis is required to view images in 3D and to examine patients in 3D . It is estimated that 5% have no stereopsis and 32% have moderate to poor stereopsis . [19] We did not formally assess the participants’ stereopsis as this is not usually done as part of the selection process of trachoma graders . It is possible that some trainees might have been unable to for a 3D view , however , that would have also likely been the case for their live examinations . It may be appropriate for programmes to evaluate stereopsis before training . In the real-life grading the examiner is able to move around the patient to assess for any lashes touching the eye from different angles . In particular , asking the patient to look up and looking from the side can be helpful . In an attempt to emulate this , we did pilot taking photographs from the side . However , the limitation we found was the depth of field was such that only a small length of the upper lid lashes was in focus at the same time really limiting its value . In conclusion , we think that using standardised 3D images of TT can be a useful tool in training trachoma graders to identify TT , with a specificity performance that is better than that of 2D image grading , and leads to live examination results that are comparable to those of experienced graders . | Trachomatous trichiasis ( TT ) is the in-turning of eyelashes , which leads to sight loss . Control programmes are training health workers to recognise and refer TT for surgery . Currently , training uses a mix of 2D images and examination of live patients . With the decline in TT prevalence , there will be too few TT patients available for this training . Here we explored the possibility of using 3D images of eyes with TT to train and test new trachoma graders . We found that experienced graders were more accurate using 3D than 2D photos , compared to “live grading” . We found that novice trachoma graders could be successfully trained using 3D images , without seeing live patients; and were as reliable as experienced graders when tested in “live grading” on a mixture of people with and without TT . Therefore , we think that 3D photos offer an alternative training tool for programmes , particularly when there are too few people with TT to engage in training activities . | [
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"negle... | 2019 | 3D images as a field grader training tool for trachomatous trichiasis: A diagnostic accuracy study in Ethiopia |
In many species , sex-related differences in crossover ( CO ) rates have been described at chromosomal and regional levels . In this study , we determined the CO distribution along the entire Arabidopsis thaliana Chromosome 4 ( 18 Mb ) in male and female meiosis , using high density genetic maps built on large backcross populations ( 44 markers , >1 , 300 plants ) . We observed dramatic differences between male and female map lengths that were calculated as 88 cM and 52 cM , respectively . This difference is remarkably parallel to that between the total synaptonemal complex lengths measured in male and female meiocytes by immunolabeling of ZYP1 ( a component of the synaptonemal complex ) . Moreover , CO landscapes were clearly different: in particular , at both ends of the map , male CO rates were higher ( up to 4-fold the mean value ) , whereas female CO rates were equal or even below the chromosomal average . This unique material gave us the opportunity to perform a detailed analysis of CO interference on Chromosome 4 in male and female meiosis . The number of COs per chromosome and the distances between them clearly departs from randomness . Strikingly , the interference level ( measured by coincidence ) varied significantly along the chromosome in male meiosis and was correlated to the physical distance between COs . The significance of this finding on the relevance of current CO interference models is discussed .
One prominent feature of the eukaryotic life cycle is the segregation of homologous chromosomes to two different cells during the first , also known as reductional , meiotic division . The proper completion of this segregation relies on the formation of stable physical connections between homologous chromosomes . In most eukaryotic species , these connections are mediated by crossovers ( COs ) . These are sites where large ( megabase scale ) segments of homologous ( nonsister ) chromatids are exchanged . Consequently , COs are essential to the ploidy reduction process , as well as to play a role in the creation of allelic combinations . CO number and distribution along chromosomes differ between male and female meiosis in many plant and animal taxa ( for review see [1] ) . This widespread phenomenon is called heterochiasmy . Both the direction and magnitude of these differences are highly variable . For example , depending on the species , CO number may be higher in female ( F ) meiosis ( most eutherian mammals ) , or male ( M ) meiosis ( some metatherian mammals ) , or there may be no significant difference between sexes ( goat , dog , barley ) . This difference may be small or moderate , but sometimes it is huge ( e . g . , teleostean fishes ) . Even closely related species can exhibit different M/F CO ratios . In the Brassicaceae , for example , this ratio reaches 1 . 2 in Sinapis alba [2] , whereas in Brassica oleracea it is inversed ( 0 . 6 ) [3] , and there is no significant difference in Brassica napus ( 0 . 98 ) [4] . Therefore , the nature of evolutionary forces driving heterochiasmy is a puzzling issue . In addition , the underlying molecular and cellular mechanisms are currently unknown . Yet sex-related differences in CO number per chromosome are paralleled by sex-related differences in the length of synaptonemal complex ( SC ) in human [5] and mouse [6] . The SC is a proteic structure scaffolded along synapsed homologous chromosomes at pachytene stage [7] . COs can be localized along chromosomes by analyzing genetic recombination data . They can also be visualized cytologically either as chiasma , or as immunolabeled MLH1 foci that mark most CO sites [8] , or as late recombination nodules [9] , which are electron-dense structures located on SCs [9–11] . COs originate from programmed double-strand breaks ( DSBs ) that occur early in prophase of the first meiotic division [12] . Only a part of these DSBs give rise to COs; the remaining DSBs are repaired as “noncrossovers” ( NCOs ) , without exchange of large DNA segments between homologous chromosomes . Numerous studies showed that CO formation is tightly controlled at both chromosomal and local scales [13 , 14] . Indeed , COs are not uniformly distributed and inter-CO distances are not random . The former feature is well illustrated by numerous datasets in mammals [15–17] and higher plants [11 , 18] . Several studies have tried to correlate CO rates along chromosomes with various sequence features , such as gene or transposable element density , GC nucleotides % , CpG ratio , simple repeats , etc . However , even if some weak correlations were found , it seems that none holds true in all species [15 , 16 , 19–21] , suggesting that other constraints act on CO distribution . One of these constraints is CO interference . This phenomenon was originally described as a lower frequency of double-COs in disjoint chromosomal segments than expected if they occur independently of each other [22] . The existence of interference has been confirmed in most species tested [10] . As a consequence of interference , COs tend to be more evenly spaced than expected if CO positions were random [23] . In addition , in many species , which have a limited number of COs per chromosome , interference tends to increase physical distances between adjacent COs . This is well illustrated by recombination nodules or MLH1 foci maps produced in various species [5 , 17 , 24–26] . The mechanisms of interference setup are still poorly understood . Several models of meiotic CO interference have been proposed over years ( see [14] for a comprehensive review ) . The two main contenders are currently the “counting” model [27] and the mechanical stress model [28] . The basic postulate of the counting model is that the CO designation process among recombination precursors occurs in such a way that any two adjacent COs are separated by a fixed number of NCOs . Alternatively , the mechanical stress model hypothesizes that COs originate from a mechanical stress imposed on the chromosome . CO designation would promote a stress relief that would ( i ) inhibit CO designation among nearby recombination intermediates and ( ii ) attenuate in a distance-dependent manner . Neither of these two models is presently strongly supported by experimental data . In a previous study , we produced a high resolution map ( at around the 210-kb scale ) of meiotic crossovers on Arabidopsis thaliana Chromosome 4 [18] . We showed that CO rates vary greatly along the chromosome from 0 to 20 cM/Mb , and that COs displayed interference . However , CO rates on this map were sex-averaged because we used the selfed progeny of F1 hybrids for the mapping population . Given that the existence of heterochiasmy in A . thaliana had been previously suggested by several studies [29–32] , we decided to investigate the relative contributions of male and female meiosis in the distribution of COs on Chromosome 4 . We observed dramatic differences between male and female genetic maps . Strikingly , we found a good correlation between the sex-ratio of mean CO number per Chromosome 4 on one hand and the sex-ratio of total SC length on the other hand . Moreover , we were able to detect significant variations in interference strength along Chromosome 4 . Stunningly , it turned out that interference strength covaries with the physical distance between COs . These results could have important upshots on the reliability of current interference models .
A . thaliana “Columbia” ( Col ) and “Landsberg erecta” ( Ler ) accessions were crossed to obtain F1 hybrids . Col plants were then crossed with an F1 hybrid used either as the male ( Col × ( Col × Ler ) ) or as the female ( ( Col × Ler ) × Col ) parent . Seeds from these crosses were sowed in vitro , and then seedlings were grown in short-day conditions at 21 °C . After 2 wk , 1 , 476 whole seedlings of each population were collected and their DNA was extracted as described previously [33] . In a previous experiment , F2 plants from a Col × Ler cross were genotyped with a set of 70 SNP markers spanning A . thaliana Chromosome 4 [18] . In the present study , 46 SNPs out of these 70 and two additional SNPs were chosen so that the mean sex-averaged genetic distance between adjacent markers was 1 . 9 cM . SNPs are listed in Table S1 . Genotyping was performed using SNPlex technology ( Applied Biosystems , http://www . appliedbiosystems . com ) following the supplier protocols . After quality scoring of genotyping data , four markers were dismissed from the whole dataset . In some cases it was not possible to assess the genotype of remaining markers in some plants so these were also removed from the dataset . The resulting populations comprised 1 , 305 and 1 , 419 plants for female and male meiosis , respectively . The genetic size of intervals was computed as the ratio between the number of recombined chromosomes and the number of analyzed meioses , which in the case of a backcross progeny is equal to the number of analyzed plants . CO rates , physical and genetic sizes are listed in Table S2 . In order to calculate single-interval , sex-averaged CO rates in the pool of M and F populations , the sex-specific CO rates were weighted according to the respective population size . All pair-wise comparisons between CO rates were performed using a chi-square homogeneity test . For multiple testing , p-values were subsequently corrected using the false discovery rate procedure [34] . Predicted Poisson distributions of CO number per chromosome were calculated using the following formula: where S ( k ) is the number of chromosomes harboring exactly k CO , e is the neperian logarithm base , m is the observed mean number of CO per chromosome , and N is the total number of chromosomes . Whole comparisons between observed and Poisson distributions were performed using a chi-square goodness-of-fit test . For both M and F datasets , the genetic “width” of inter-CO distance classes was chosen to be 17 . 5 cM ( ± 5% ) in order to: ( i ) provide distance classes spanning the whole chromosome genetic length , ( ii ) ensure a common denominator in both M and F maps , and ( iii ) prevent small class sizes , in order to maintain moderate sampling variances , thus allowing conclusive statistical testing . The continuous probability distribution function of inter-CO distances on chromosomes with exactly a independent COs is: , where L is the genetic size of the chromosome and d is the distance between successive COs . The derivation of this formula is as follows: a independent CO points are randomly placed on a chromosome of length L . Then a CO point is added at one end to bring the chromosome to the shape of a ring . a + 1 points are thus randomly and independently positioned on the circle of perimeter L . The statistics of distances between successive COs is the same for all pairs; to compute this for the first pair , we need to find the distribution of the smallest of a random variables , representing the positions of COs along the interval , which are uniformly distributed in [0 , L] ( the remaining point is by definition at position zero ) . The probability that this smallest value , which is the distance between the last and the first CO , is greater or equal to X is ( 1 − X/L ) a . The minus derivative of this cumulated distribution then gives the desired probability distribution . The following formula , which is easily deduced from the formula above , allows convenient calculation of discrete distributions of inter-CO distances on finite-size chromosomes with exactly two independent COs: , where n is the number of classes , k is the rank of the class ( increasing with distance ) , N is the population size , and S ( k ) is the size of the kth′ class . Whole comparisons between observed and calculated distributions were performed using a chi-square goodness-of-fit test . For both M and F datasets , the genetic size of intervals used for coincidence analyses was chosen to be the same as the genetic “width” of distance classes used for inter-CO distance comparisons , for the same reasons ( see above ) . Given two intervals , the coefficient of coincidence between them is calculated as follows: where C is the coincidence and rij is the chance of i CO across the first interval and j CO across the second interval . In most cases i and j values are either 0 or 1; 2 COs were rarely found in one of the intervals and were considered as no CO , while 3 COs were considered as 1 only , accordingly to what would have been observed if the intervals would have not contained internal markers . The standard deviation of coincidence was calculated according to [35] . We have developed a procedure which computes the p-value for the hypothesis H0 that two coefficients of coincidence cu and cv estimated from quadruplets or triplets of markers are in fact generated from the same theoretical coincidence value cth . Under that hypothesis , H0 , cu , and cv are actually not expected to differ from each other . A small p-value for the difference between cu and cv then indicates that H0 is unlikely to be true given the genotype data of the mapping population . Let a quadruplet have markers A , B , C , and D , assumed to be in the order in which they appear on the chromosome . If the quadruplet is instead a triplet , this formalism can be applied by setting B = C . In a first phase , we compute cth by the maximum likelihood method . Consider the first quadruplet: the probability ( likelihood ) that N gametes lead to a measured coincidence value of cu is where nnn , nrn , nnr , nrr are the number of gametes that are respectively recombinant between ( i ) neither A and B nor C and D , ( ii ) A and B but not C and D , ( iii ) C and D but not A and B , ( iv ) both A and B and C and D . N is the total number of gametes with valid data at the four markers , namely nnn+ nrn+ nnr+ nrr . The dependence on cth is through the probabilities: where rAB and rCD are recombination fractions between A and B and B and C , respectively . Next , we consider the two quadruplets of interest . L ( cv ) is calculated as for L ( cu ) . The joint likelihood of both observations is the product L ( cu ) × L ( cv ) , and we numerically determine the cth which maximizes this joint likelihood . The result is a cth lying somewhere between cu and cv . In a second phase , we compute a p-value for the hypothesis H0 given cth . We do this by determining the probability that | cu − cv | is at least as large as measured from the experimental data . But if cu and cv are estimated using shared gametes , the recombination events in the four intervals are a priori correlated . Thus , when measuring cu and cv we need to use independent sets of gametes by using half ( N/2 ) of the gametes for cu and the other half for cv . So that the value | cu − cv | is not dependent on the data order , | cu − cv | is computed for 105 random order combinations and the median value taken . The p-value is obtained by simulating interference events within H0 given cth: we generate N/2 realizations of gametes for each quadruplet; for each realization , we choose among the four possibilities of recombinants or not in each interval according to the probabilities prr , prn , pnr , pnn . For this set of N gametes , we extract the two associated coincidence coefficients cu′ and cv′ . Repeating this 105 times , we get a probability distribution for | cu′ − cv′ |; the desired p-value is then the frequency with which | cu′ − cv′ | is larger than the experimental value . Cytological observations were carried out on Col × Ler F1 plants . The anti-ASY1 polyclonal antibody has been described elsewhere [36] . It was used at a dilution of 1:500 . The anti-ZYP1 polyclonal antibody was described by [37] . It was used at a dilution of 1:500 . Preparation of prophase stage spreads for immunocytology was performed according to [36] with the modifications described in [38] . All observations were made using a Leica ( http://www . leica . com ) DM RXA2 microscope; photographs were taken using a CoolSNAP HQ ( Roper , http://www . roperscientific . com ) camera driven by Open LAB 4 . 0 . 4 software; all images were further processed with Open LAB 4 . 0 . 4 or AdobePhotoshop 7 . 0 ( http://www . adobe . com ) . SC length measurement was performed using Optimas ( Bioscan Incorporated , http://www . bioscan . com ) software .
We first compared CO rates in the F2 population previously described to those in pooled M and F populations , in each of the same 43 intervals spanning Chromosome 4 ( Figure 1A ) . As expected , the “averaged” ( see Materials and Methods ) CO rates observed in the pool of the M and F backcross progenies ( corresponding respectively to male and female meiosis ) were not significantly different from those observed in the F2 progeny ( resulting half from male meiosis , half from female meiosis ) generated from the same parental accessions ( lowest p-value is 0 . 35; Figure 1A ) . This implies that there is no significant variation in meiotic recombination over time for a given genetic background , thus enabling direct comparisons of data . At first glance , the difference between male and female recombination rates is obvious when comparing total genetic size of both maps ( Figure 1B ) . The M map is 87 . 9 cM long and the F map is 52 . 3 cM long . This indicates that a Chromosome 4 bivalent experiences on average 1 . 76 CO in male meiosis , but only 1 . 05 CO in female meiosis ( M/F ratio 1 . 68 ) . This M/F difference is highly significant ( χ2 p-value < 0 . 001 ) Next , we compared recombination rates in male and female meiosis interval-by-interval ( Figure 1C ) . For a majority of intervals ( 36/43 ) the M/F ratio was above 1 , with the most notable differences in the last telomeric third of the long arm . However , only the distal interval on the short arm and the five distal intervals on the long arm were highly significantly different in male and female ( mean M/F ratio for these six intervals is 6 . 1 , χ2 p-value < 0 . 05 ) . The remaining central intervals were not significantly different in male and female , when compared one-by-one . However , if these were grouped and considered as a single interval , there was still a significant difference between male and female ( M/F ratio 1 . 37 , χ2 p-value < 0 . 001 ) . In summary , male and female meiotic CO landscapes along Chromosome 4 are strikingly different . The difference is high close to the telomere on the long arm and to the nucleolar organizer region on the short arm and modest in the median region of the chromosome ( see Figure 1B and 1C ) . Meiotic chromosomes at pachytene stage were immunolabeled with antibodies against ZYP1 . This protein is a major component of the central element of the SC , which ties homologous chromosomes together . We used ASY1 immunolabeling to visualize the axial element , which is a proteinaceous axis formed along pairs of sister chromatids [39] ( Figure 2 ) . At pachytene stage , ZYP1 labeling extends continuously along the entire SC , hence allowing total SC length measurement . We found that SC length in male meiocytes is 166 ± 24 μm ( n = 22 ) compared to only 98 ± 20 μm ( n = 25 ) in female . Our estimate of male SC length is in good agreement with that obtained in a previous study ( 147 ± 28 μm; n = 19 ) using electron microscopy [40] . The value we obtained for the M/F ratio of total SC lengths is very close to that for the M/F ratio of mean CO numbers per chromosome ( 1 . 70 versus 1 . 76 ) . This suggests that sex-related differences in CO number and total SC length are correlated . We next looked at the distribution of CO number per Chromosome 4 in the M and F populations ( Figure 3 ) . According to the hypothesis that CO placements are random and independent events , the distribution of CO number per chromosome should fit a Poisson distribution . Thus , we calculated the Poisson distributions expected for the observed average number of COs per Chromosome 4 and compared these to the observed ones ( see Figure 3A and 3B ) . In the F population , about half of chromosomes had no CO or only one CO , while very few had two COs or more ( Figure 3B ) . This distribution is highly significantly different ( p-value < 0 . 001 ) from the theoretical Poisson distribution , in which the “0 CO” group was the main class ( 59% ) and multiple CO classes accounted for 10% . Hence , in female meiosis almost all bivalents experienced only the “obligate CO” required for the proper segregation of homologous chromosomes at anaphase I . In the M population , only one third of chromosomes had no CO and about half had one CO ( Figure 3A ) . Consequently , chromosomes with multiple COs were more frequent than in the F population . Conversely , in the corresponding Poisson distribution “0 CO” and “1 CO” chromosomes were represented at 42% and 36% , respectively . Observed and expected distributions were clearly different from each other ( p-value < 0 . 001 ) . As a consequence of interference , inter-CO distances are less variable and greater ( when CO number is limited ) than expected under the assumption that COs are distributed randomly and independently . Positions of double-COs ( on chromosomes with exactly two COs ) were represented in two-dimensional plots in Figure 4 . x and y axis coordinates correspond to the positions of the first and second CO on the genetic map , respectively . Under the assumption of no interference , points should be uniformly distributed over the triangle . For both M and F double-CO populations , the observed points were clearly heterogeneously distributed: they were underrepresented next to the diagonal line , which corresponds to low inter-CO distances . In order to test this deviation from independence between COs , inter-CO distances on chromosomes with two COs only ( see Materials and Methods ) were grouped into size classes , and the observed distributions were compared to the “random” ( no CO interference ) distributions ( Figure 5 ) . For both M and F datasets , the genetic length ( 17 . 5 cM ± 5% ) of the intervals was chosen to optimize the number of double-COs per interval , in order to avoid high sampling variance and thus allow statistically significant differences to be detected . In the F population , we found opposing observed and expected distributions: for the expected distribution the minor class was 35–52 . 5 cM and the major class 0–17 . 5 cM , whereas in the observed distribution the majority of inter-CO distances were long , and short distances were the minority ( Figure 5A ) . This difference was highly significant ( p-value < 0 . 001 ) . The observed M distribution was rather symmetrical , with the mode between 35 and 53 cM . It was strikingly different from the theoretical distribution , in which the class size decreased with increasing genetic length ( p-value < 0 . 001; Figure 5B ) . For both M and F distributions the mean observed inter-CO distance , respectively 51% and 63% of the total map size , exceeded the expected one , which is exactly one third of the total map size . Therefore , in male and female meiosis , widely spaced COs were overrepresented , whereas closely spaced COs were underrepresented . This difference between expected and observed distributions of distances between COs is fully consistent with interference . Besides altered inter-CO distances , another expected consequence of interference is a lowered chance of finding close double-COs than expected from randomness . More precisely speaking , given two intervals , double-COs ( one CO in each interval ) will occur at a lower frequency than two independent COs ( one CO in the first or in the second interval , both being not exclusive ) . This departure is called coincidence and can be calculated as follows: where rij is the chance of i CO across the first interval and j CO across the second interval . The value of C is 1 if there is no interference and 0 if interference is absolute ( meaning that double-COs are completely absent ) . Coincidence is widely used as a measure of interference from genetic data . Moreover , most mathematical models of CO interference assume a covariation between coincidence at a given genetic distance and the level of interference ( see for example [27] , reviewed in [14] ) . Hence , plotting coincidence for pairs of adjacent intervals ( three-point coincidence: C3; [27] ) all along a chromosome gives access to local variations of interference level , provided that the genetic size of intervals remains constant . We thus performed all coincidence analyses on every possible pairs of 17 . 5 cM ( ± 5% ) adjacent intervals ( 30 and 21 pairs fit these requirements in M and F datasets , respectively ) . This means that we “moved” a 2 × 17 . 5-cM window along the genetic map . The interference level measured by C3 was clearly variable across Chromosome 4 for both maps . In male meiosis , starting from the short-arm end , interference strength was high until ∼30 cM ( C3 < 0 . 1 ) , then it decreased from ∼30 cM to ∼45 cM ( C3 ∼0 . 3 ) , to reach a minimum at ∼52 cM ( C3 ∼0 . 75 ) , and finally increased again from ∼65 cM to the end of the map ( C3 ∼0 . 3; Figure 6A ) . Most of these variations in C3 were found to be significant ( see Figure 6 , Table 1 , and Materials and Methods ) . We can thus conclude that local interference level varied significantly along Chromosome 4 in male meiosis . In the F plot , all observed C3 values are very low ( ≤0 . 1 ) . We could not observe any significant variation in coincidence among the few points of the plot ( Figure 6 and Table 1 ) . Given the very small number of double-COs , it seems likely that many more plants would be needed to detect any possible coincidence variation . Another way of analyzing interference is to plot coincidence between one fixed interval and a series of increasingly distant intervals ( four-point coincidence: C4; [27] ) . This means that we fixed a 17 . 5 cM ( ± 5% ) window and moved a second 17 . 5 cM ( ± 5% ) window all along the chromosome . This method provides a global description of interference depending on genetic distance ( see Materials and Methods ) . For each M and F population , two different C4 plots were made , using either the terminal interval of the short arm ( Figures 7A and 8A ) or the telomeric interval of the long arm as the fixed interval ( Figures 7B and 8B ) . For the M population , regardless of whether the fixed interval was located at the end of the long or short arm , plots had globally the same shape . This kind of shape has been consistently observed in various species ( for review see [41] ) , showing that interference decreases with genetic distance . Nevertheless , C4 values from the short-arm end were systematically lower ( from 0 . 05 to 1 . 11 ) than those from the long-arm end ( from 0 . 3 to 1 . 23 ) . This confirms that the strength of interference is weaker at the distal region of the long arm than on the short arm . In both plots , coincidence increased up to 1 at ∼45–50 cM , peaked above 1 at ∼55–60 cM , and then decreased toward 1 . The shape of the C4 plots was determined by two factors: ( i ) the genetic distance between intervals and ( ii ) fluctuations of interference strength as described above . The occurrence of a peak of coincidence above 1 means that at some genetic distances , double-COs are more frequent than expected if COs were randomly placed: this corresponds to what is called negative interference . At short distances from the terminal short-arm interval ( which includes the centromere ) coincidence was very low . Interestingly , this shows that the presence of the centromere did not block interference . Regarding the F population ( Figure 8 ) , because the F map was very short ( 52 . 4 cM ) and double-COs were rare , C4 plots were less informative . From both ends , coincidence increased up to ∼0 . 4 at ∼35 cM . Strikingly , C never reached 1 , showing that in female meiosis interference acted across the whole chromosome . Given that significant variations of interference level along Chromosome 4 were detected in male meiosis , we addressed the issue of possible correlations between interference level and physical distance . We thus calculated the physical size of the pairs of intervals considered for the C3 coincidence analysis described above , which have all the same genetic size ( 2 × 17 . 5 cM ) . The coincidence values were next plotted against these sizes ( see Figure 9A ) . We could clearly observe two scatters of points . The smallest one contains all pairs of intervals encompassing the heterochromatic knob located on the small arm and the centromere , while the largest scatter comprises all the pairs of intervals located on the long arm only . For the large scatter , we could note a striking positive correlation between the C3 coincidence and the physical size ( r2 = 0 . 91 ± 0 . 04 ) . The small scatter was shifted by about 4 . 5 Mb relative to the large scatter . This is a direct consequence of the presence of a large CO-free region , which does not contribute to the genetic size of the considered pairs of intervals , but hugely increases their physical size . Indeed , when subtracting the cumulated size of the knob and the centromere ( 4 . 7 Mb ) from the size of the pairs of intervals encompassing these chromosome parts and making a new plot ( see Figure 9B ) , the two scatters of Figure 9A grouped into a single scatter that showed this time a chromosome-wide tight correlation between C3 coincidence and physical size ( r2 = 0 . 93 ± 0 . 04 ) . It means that interference level—measured by coincidence analysis on adjacent intervals of constant genetic size—decreases as the physical size increases . In other words , for a given genetic size ( i . e . , a given CO frequency ) , a greater physical size enhances the opportunity for double-COs to occur .
In this study , we compared male and female meiotic CO distributions along A . thaliana Chromosome 4 . We depicted strong sex-related differences in CO distribution ( heterochiasmy ) and unequivocal variations in CO interference level along the male chromosome . One major finding in this study was that the genetic sizes of male and female maps were strikingly different ( M map 88 cM , F map 52 cM ) . This means that Chromosome 4 harbors an average of 1 . 8 CO in male meiosis , but only 1 in female meiosis . Noticeably , the size of our male map was very close to that previously reported for the Col accession [42] ( 87 . 9 versus 83 . 6 cM ) . Moreover , we described a marked difference in total SC length between sexes . Remarkably , this difference was very close to the M/F CO ratio observed for Chromosome 4 . By using a high density of markers , as well as a large-sized population , we could describe the sex-specific fine scale distribution of COs for the first time in A . thaliana . Thus , we could detect highly significant variations of M/F CO ratio along the chromosome . We observed large differences ( up to 18 . 7-fold ) at both ends of the genetic map and less pronounced—though significant—differences on the median part of the chromosome ( from 5 Mb to 13 Mb , see Figure 1C ) . In this median region both curves presented the same overall pattern of “peaks” and “valleys , ” even if the local male CO rate was higher than the female CO rate for most intervals ( 30/37 ) . In summary , we detected heterochiasmy , not only at the whole chromosome level , but also at a regional scale . Heterochiasmy in A . thaliana has been suggested by several previous studies . Indeed , chiasma counts showed that COs are more frequent in male meiosis ( 9 . 7 ) than in female ( 8 . 5 ) [32] , but the result of this count , carried out on only ten meiocytes , was not highly significant and did not provide any precise information about CO location . In two other studies , a comparison of male and female recombination rates on all five A . thaliana chromosomes was performed [29 , 31] , but in each case only a few markers were scored , covering only part of the genome . Nevertheless , these results also suggested that recombination is higher in male than female meiosis and that there are variations in the M/F CO ratio along chromosomes . At the whole genome scale , heterochiasmy is widespread ( reviewed in [1] ) , but this observation remains largely unexplained from an evolutionary point of view . Nevertheless , SC length was shown to differ significantly between male and female meiocytes in human [5] and mouse [6] , paralleling variations in MLH1 foci number . Similar results were reported in other species , such as zebrafish [43 , 44] , Dendrocoelum lacteum [45] , and others ( reviewed in [46] ) . This statement can now be extended to higher plants , since we obtained comparable results in A . thaliana . Such correlated variations in SC length and CO number were also reported among chromosomes in one sex only , among individuals in the same species , and even among meiocytes in a single organism [5 , 17 , 47–50] . However , based on current knowledge it is difficult to claim that SC length determines CO number , if the reverse is true , or even if another unidentified factor determines both . Besides global differences , there is also compelling evidence that the distribution of COs along chromosomes is contrasted in both sexes . Similarly to what we observe in A . thaliana , enhancement of the M/F ratio close to telomeres was reported in other Brassicaceae species [2 , 3] . In vertebrates , such a conservation in heterochiasmy patterns along chromosomes was also observed: in mouse , human , and several teleostean fishes , the M/F ratio decreases around the centromeres and tends to increase close to the telomeres [15 , 16 , 43 , 51] . At the present time , the molecular and cellular bases of regional heterochiasmy remain elusive . And , generally speaking , the mechanisms ruling CO distribution along chromosomes are also poorly characterized . Data from various model organisms show that CO distribution results from the integration of several levels of control [14]: ( i ) the density of meiotic DSBs initiating recombination between homologous chromosomes varies along chromosomes; ( ii ) the propensity of a DSB to be repaired as a CO or a NCO probably varies; ( iii ) interference shapes the final CO distribution; ( iv ) only a part ( variable among species ) of COs are sensitive to interference ( type I CO ) , the remaining are insensitive ( type II CO ) . Each of these layers of control could act on observed heterochiasmy patterns along chromosomes . The DSB distribution , CO/NCO ratio , interference strength/interference strength variations , and the proportion of type II COs could vary between male and female meiosis , even if no experimental data presently support these hypotheses . Other factors were also suggested to effect differences between CO distributions in male and female meiosis . Several studies suggested that in human , parental imprinting in a few regions could explain at least part of local heterochiasmy [52 , 53] . Additionally , it was proposed that synapsis initiation sites colocalize with COs [54] . For example , in human , synapsis initiation occurs in sub-telomeric regions in male [55] whereas it is rather interstitial in female ( reviewed in [56] ) , which seems compatible with the observed pattern of heterochiasmy . Due to the availability of whole genome sequences , correlations between CO rates along chromosomes and various genomic features could be examined [15 , 16 , 19–21] , but all the resulting correlations were weak . This could be explained by the fact that only sex-averaged recombination rates were used in these studies . A priori , there is no evidence that genomic features correlated to CO rates have the same weight in male and female meiosis . Thus , when possible , correlation analyses should be done separately on data from both sexes . Presumably , this could disclose previously unidentified relationships or reinforce existing ones and reveal differences in correlations between sexes . Altogether , it is likely that multiple constraints act synergistically to shape CO distribution along male and female chromosomes in meiosis , some of which remain to be elucidated . In this paper , we have presented the first detailed study on the effect of interference on CO distribution along a whole chromosome in male and female meiosis of A . thaliana . Both CO number per chromosome and inter-CO distances clearly show that COs are not independent of each other . Interestingly , we unequivocally show that the centromere is not a barrier to interference , in accordance with previous reports [18 , 57–59] . The coincidence plots also clearly show the existence of negative interference at some genetic distance ( 55–60 cM ) , which corresponds to a greater chance of another CO than expected from random . This phenomenon has been repeatedly observed from various genetic datasets ( see , for instance , [58] ) and is also predicted by various models of CO interference [27 , 28] . Furthermore , we provide unambiguous evidence that interference strength varies significantly along A . thaliana Chromosome 4 in male meiosis . It has recently been shown that in most eukaryotes , a part of meiotic COs arising from a distinct pathway are not sensitive to interference [60] . Such COs account for about 15% of the total in A . thaliana [37 , 61] . Thus , the observed variation of interference level , measured on the whole population of COs , can be explained by two nonexclusive hypotheses: ( i ) the interference level between interfering COs is actually variable , or ( ii ) this interference level is constant , but the relative proportions of the two kinds of COs are variable along chromosome , so that locally , a high density of noninterfering COs leads to a decrease of the interference level that is measured on the whole population of COs . In female meiosis , observed variations are not significant because double-COs are rare , hence sampling variance is high , causing an increase in p-values from statistical testing . Such variations in interference strength along chromosomes were previously suggested from analysis of human pedigree data [62] . Moreover , the level of interference was reported to vary among chromosomes in humans in several studies [17 , 62–64] . Sex-linked variations of interference have also been reported along human Chromosome 21 [64] . Even fluctuations of interference level among human individuals have been described [17 , 26] . The molecular bases of these variations are currently poorly documented . Our results provide clear evidence that across a chromosome segment displaying a given CO frequency , a greater physical size enhances the opportunity for double-COs to occur . In other words , interference level between COs separated by a fixed genetic distance is a function of physical distance . Interestingly , cytogenetic data collected in humans demonstrate a negative correlation among chromosomes between SC length and the global ( chromosomal ) level of interference [17] . At the present time , the molecular bases of these variations are totally unknown . The mechanisms of interference itself are still elusive . Several models have been proposed , but no experimental data directly support them . One of the most widely used is the “counting” model . Its basic postulate is that a fixed number of NCOs occurs between any two adjacent COs . As a consequence , interference strength is supposed to be constant at the chromosome scale [27 , 65] . Our data and those cited above strongly argue against such constancy and also call into question the concept of an unchanging “count” itself . Moreover , a recent study in yeast showed that CO number is maintained at the expense of NCOs when the DSB number is reduced , without affecting interference [66] . Other models propose that an interference signal results either from the progressive polymerization of a hypothetical structure along the chromosome [67] , or from a mechanical stress imposed on the chromosome axis [28] . Our data are compatible with these two models , in which the interference level is not explicitly intended to be constant and an interference signal propagates along the chromosomes . However , as data in the field of meiotic recombination continue to accumulate exponentially , it is likely that new CO interference models supported by experimental evidences will emerge in the near future . Our study provides the first detailed analysis of heterochiasmy and CO interference at the whole chromosome scale in a plant species . It provides the basis for future investigations on the determinism of CO distribution at the whole genome scale in A . thaliana and other species . | Meiotic crossovers between homologous chromosomes ensure their proper segregation to generate ultimately gametes . They also create new allelic combinations which contribute to the diversity of traits among individuals . In all eukaryotes , the number and the localization of crossovers along chromosomes are not random . In addition , crossovers are not independent of each other: the occurrence of a crossover lowers the probability that another crossover arises in its vicinity . The mechanism of this phenomenon , called “crossover interference , ” is one of the most challenging puzzles that geneticists have been faced with in the last century . In this paper , we precisely described the distribution of crossovers along Chromosome 4 of the model plant species Arabidopsis thaliana , separately in male and female meiosis . Interestingly , we observed that crossovers are 1 . 7 more numerous in male than in female meiosis , and this increase is especially marked at the ends of the chromosome . Moreover , our results provide the first evidence that the level of interference along a chromosome is not a constant and is correlated with the physical distance between crossovers . These results shed new light on the determinism of crossover localization and could have important outcomes on the relevance of current models of crossover interference . | [
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] | 2007 | Sex-Specific Crossover Distributions and Variations in Interference Level along Arabidopsis thaliana Chromosome 4 |
The continued spread of highly pathogenic H5N1 influenza viruses among poultry and wild birds , together with the emergence of drug-resistant variants and the possibility of human-to-human transmission , has spurred attempts to develop an effective vaccine . Inactivated subvirion or whole-virion H5N1 vaccines have shown promising immunogenicity in clinical trials , but their ability to elicit protective immunity in unprimed human populations remains unknown . A cold-adapted , live attenuated vaccine with the hemagglutinin ( HA ) and neuraminidase ( NA ) genes of an H5N1 virus A/VN/1203/2004 ( clade 1 ) was protective against the pulmonary replication of homologous and heterologous wild-type H5N1 viruses in mice and ferrets . In this study , we used reverse genetics to produce a cold-adapted , live attenuated H5N1 vaccine ( AH/AAca ) that contains HA and NA genes from a recent H5N1 isolate , A/Anhui/2/05 virus ( AH/05 ) ( clade 2 . 3 ) , and the backbone of the cold-adapted influenza H2N2 A/AnnArbor/6/60 virus ( AAca ) . AH/AAca was attenuated in chickens , mice , and monkeys , and it induced robust neutralizing antibody responses as well as HA-specific CD4+ T cell immune responses in rhesus macaques immunized twice intranasally . Importantly , the vaccinated macaques were fully protected from challenge with either the homologous AH/05 virus or a heterologous H5N1 virus , A/bar-headed goose/Qinghai/3/05 ( BHG/05; clade 2 . 2 ) . These results demonstrate for the first time that a cold-adapted H5N1 vaccine can elicit protective immunity against highly pathogenic H5N1 virus infection in a nonhuman primate model and provide a compelling argument for further testing of double immunization with live attenuated H5N1 vaccines in human trials .
In 1996 , a highly pathogenic H5N1 avian influenza virus was detected in geese in China [1] . A year later , a reassortant H5N1 virus caused disease outbreaks in poultry in Hong Kong [2] and was transmitted to humans , infecting 18 people , six of whom died [3] , [4] . Beginning in late 2003 , outbreaks of H5N1 influenza A virus infection appeared among poultry , and wild birds in numerous countries in Asia and subsequently were reported in Europe and Africa ( Office International des Epizooties [OIE]; http://www . oie . int ) . Despite substantial efforts to control the infection in poultry , H5N1 viruses have continued to evolve and spread , producing human infections in 14 countries , with 236 of the 372 confirmed cases proving fatal ( World Health Organization [WHO]; http://www . who . int ) . The emergence of H5N1 viruses resistant to adamantanes and oseltamivir [5] , [6] , [7] has raised serious concerns over the ability of current antiviral agents to prevent global influenza outbreaks . Thus , the development of an effective vaccine has assumed the highest priority in preparedness for an H5N1 influenza pandemic . H5N1 inactivated vaccines can induce functional and cross-reactive antibodies that protect ferrets or nonhuman primates from H5N1 infection [8] , and have been shown to be safe and tolerable in human trials [9] , [10] , [11] . With the addition of adjuvants , such vaccines induce antibody titers that are known to provide protection against seasonal influenza in humans [11] , however , the antibody level considered to be protective was based on findings in humans who had likely been exposed to the seasonal human virus and thus were “preimmunized” . Because the vast majority of humans have not been exposed to highly pathogenic H5N1 viruses , it is still unknown whether the level of antibody known to be protective against seasonal human influenza virus infection would also be effective against H5N1 viruses . Additionally , while humoral immunity is effectively induced by the inactivated vaccines , the cellular immune response is not [12] . This deficit has raised concern because of indications that the cellular immune response may play a significant role in protection against H5N1 infection [12] . The cold-adapted ( ca ) influenza virus A/Ann Arbor/6/60 ( AA ) ( H2N2 ) has been developed as a live attenuated vaccine seed virus that exhibits cold-adaptation , temperature-sensitive ( ts ) , and attenuation ( att ) phenotypes which are specified by mutations in the internal genes . Reassortant H1N1 and H3N2 human influenza A viruses with the six internal gene segments of the AAca virus have been repeatedly demonstrated to bear these phenotypes and extensive evaluation in humans has proven them to be attenuated and safe as live virus vaccines ( reviewed in [13]–[15] ) . In previous studies , live attenuated H5N1 vaccines generated by reverse genetics and comprising internal genes of the AAca virus and the HA and NA genes derived from earlier H5N1 influenza viruses were proved to be safe in mice and ferrets , and to protect these animals from death against different H5N1 viruses challenges [16] , [17] . In this study , we produced three live attenuated , ca H5N1 viruses , using reverse genetics , that contain the HA and NA genes of H5N1 viruses isolated at different times and from different species in China . After in vitro and in vivo analyses , one of the cold-adapted virus that contains the HA and NA genes from a recent H5N1 virus , A/Anhui/2/2005 ( AH/05 ) ( clade 2 . 3 ) , was selected for immunogenicity and efficacy testing in mice and nonhuman primates .
We constructed three H5N1 reassortant virus by reverse genetics [18] , [19] , [20] , using the published sequences of the low pathogenic A/Ann Arbor/6/60 ca virus ( AAca ) [21] to generate all of the genes encoding the internal proteins . The HA and NA genes were from the highly pathogenic H5N1 influenza viruses , including A/goose/Guangdong/1/1996 ( GS/GD/96 ) ( clade 0 ) , A/chicken/Shanxi/2/2006 ( CK/SX/06 ) , a virus isolated from chickens in northern Chine in 2006 , and A/Anhui/2/2005 ( AH/05 ) ( clade 2 . 3 ) , which was isolated from a human in China ( WHO; http://www . who . int ) . The multiple basic amino acids at the HA cleavage site , a major virulence motif for H5N1 influenza viruses , were replaced with those found at the HA cleavage site of a nonpathogenic avian influenza virus , as previously described [16] , [22] . The cold-adapted ( ca ) and temperature-sensitive ( ts ) phenotypes of the resultant viruses GSGD/AAca , CKSX/AAca , and AH/AAca , attributable to the internal genes of AAca , were also confirmed as described previously ( data not shown ) . The ca reassortant viruses did not cause disease or death in chickens upon intranasal or intravenous administration , while all of the three wild-type H5N1 viruses are lethal to chickens ( Table 1 ) . We evaluated the replication of GSGD/AAca , CKSX/AAca , and AH/AAca , in mammals , using the BALB/c mouse . Groups of 6-week-old female BALB/c mice were inoculated intranasally with 106 EID50 ( dose required to infect 50% of eggs ) of the reassortant viruses or their wild-type H5N1 viruses . Three mice in each group were killed on day 3 postinoculation ( p . i . ) and their organs were collected for virus titration . As previously reported [1] , the replication of the wild-type GS/GD/96 virus was not detected in any organs on day 3 p . i . ; however , the ca virus GSGD/AAca was detected in the nasal turbinate of the inoculated mice at this timepoint ( Table 2 ) . The wild-type CK/SX/06 virus replicated in the nasal turbinate and lung , while the replication of the reassortant ca virus CKSX/AAca was not detected in any organs ( Table 2 ) . The wild-type AH/05 replicated systemically with high virus titers in all of the organs examined . The replication of AH/AAca , by contrast , was restricted to the respiratory system . Even in lung , the AH/AAca titer was significantly lower than that for AH/05 ( Table 2 ) . The reassortant viruses , as well as the wild-type GS/GD/96 and CK/SX/06 viruses did not kill any mice at the highest inoculation dose , whereas the AH/05 virus killed mice at a very low dosage ( MLD50 = 1 . 5 log10EID50 ) ( Table 2 ) . We then evaluated the immunogenicity of the three reassortant ca H5N1 viruses in mice . Four weeks after the first intranasal immunization of GSGD/AAca , hemagglutinin inhibition ( HI ) antibody against the homologous virus GS/GD/96 was not detected , but the neutralization ( NT ) antibody titers was 320 . After the second vaccination , the HI and NT antibodies increased sharply to titers of 80 and 1067 , respectively ( Table 3 ) . HI and NT antibodies in the CKSX/AAca-inoculated mice were not detected even after the second vaccination ( Table 3 ) . However , both HA and NT antibodies were detected in mice after one vaccination of the AH/AAca virus , and the mean titers increased sharply after the second vaccination ( Table 3 ) . These results indicate that the AH/AAca virus induced a better immune response than the other two ca reassortant viruses . Therefore , we selected the AH/AAca virus for further vaccine efficacy investigations in mice and monkeys . We first evaluated the protective efficacy of the AH/AAca vaccine in mice . By 4 weeks after the first intranasal immunization of 106 EID50 of AH/AAca , the mean±s . d . titers of HI and NT antibodies against the homologous AH/05 virus had increased significantly over the pretest values ( P<0 . 01 ) ( Figure 1A and 1B ) . They also rose sharply after the second vaccination ( P<0 . 01 [HI] , P<0 . 05 [NT] ) ( Figure 1A and 1B ) . Antibodies to the heterologous A/bar-headed goose/Qinghai/3/05 ( BHG/05 ) ( clade 2 . 2 ) virus were either undetectable ( HI ) or increased ( NT ) after the first vaccination , rising to 80±23 ( HI , P<0 . 01 ) and 533±184 ( NT , P<0 . 05 ) after the second immunization ( Figure 1A and 1B ) . Four weeks after vaccination , we challenged the mice intranasally with a lethal dose ( 102 LD50 ) of two different H5N1 viruses , AH/05 and BHG/05 , whose genetic and antigenic properties are different from those of the AH/05 virus . Three mice were killed on day 3 postchallenge , and their organs were collected for virus titration; the remaining seven mice in each group were observed for 2 weeks . As shown in Figure 1C–1E , mice were completely protected from homologous AH/05 virus challenge in both the single- and two-vaccination groups . Virus was not detected in any of the organs tested , and the mice remained healthy over the 2 weeks of observation ( no weight loss ) . By contrast , the virus replicated systemically and was detected in all of the test organs in unvaccinated mice , with death occurring between 6 and 10 days postchallenge . In mice challenged with BHG/05 , virus was detected at low titers ( <2 log10 EID50 g−1 ) in the nasal turbinates of animals that had received a single dose of vaccine , but was undetectable in the organs from mice that were vaccinated twice ( Figure 1F ) . All of the vaccinated mice remained healthy during the 2-week observation period , whereas the virus replicated systemically and killed all of the mice within 10 days postchallenge in the unvaccinated group ( Figure 1G and 1H ) . To assess the immunogenicity of the AH/AAca reassortant virus in a rhesus macaque ( Macaca mulatta ) model , we inoculated 2- to 3-year-old female animals ( n = 8 , Vaccinated 1–8 , V1–V8 ) intranasally with 107 EID50 of the AH/AAca virus in a 1-ml volume , twice , at a 4-week interval . A control group ( n = 8 , Control 1–8 , C1–C8 ) received the same volume of phosphate-buffered saline ( PBS ) . Serum was collected from each animal at 4 weeks after the first vaccination ( week postvaccination dose , wpd1 ) and at 2 weeks after the second vaccination ( wpd2 ) . Peripheral blood mononuclear cells ( PBMCs ) of the monkeys were isolated at different times for detection of a T-cell immune response using an H5-HA specific IFN-γ ELISPOT assay . Intranasal inoculation of the AH/AAca virus was not associated with any adverse events ( not shown ) . As shown in Figure 2A , each of the vaccinated macaques had a detectable antibody response by ELISA ( enzyme-linked immunosorbent assay ) at 2 weeks after the first inoculation , with the titer ranging from 120–780 ( median , 760 ) , and the titers increased sharply at 4 weeks after the first inoculation , with titers ranging from 1520 to 12780 ( median , 7640 ) . HI and NT antibodies were not detectable from the animals at 2 weeks after the first inoculation ( data not shown ) . Five of these animals developed HI antibodies to the AH/05 virus ( titers , range of 10–80 , median , 40 ) , and all had NT antibodies to this virus ( range of titers , 40–640 , median 240 ) ( Figure 2B and 2D ) at 4 weeks after the first inoculation . Antibody levels in the vaccinated animals increased significantly after the second vaccination ( Figure 2 ) . Eight animals had detectable HI antibody to AH/05 ( range of titers , 40–640; median , 160 ) at 2 weeks after the second vaccination , while NT and ELISA antibody titers reached 320–2560 and 25 , 118–199 , 526 , respectively , at this interval ( Figure 2A , 2B , and 2D ) . Overall , the HI and NT antibody titers against the heterologous virus BHG/05 ( Figure 2C and 2E ) were 2- to 4-fold lower than those against the AH/05 virus . T cell responses to the HA protein were not detected at 4 weeks after the first immunization . However , the HA-specific T cell responses could be detected at 2 weeks after the second immunization in all vaccinated macaques ( Figure 3 ) . Interestingly , 11 of the 13 T cell HA-specific peptides identified in samples from eight macaques represented CD4+ T cells ( Table 4 ) , suggesting this T cell subset may have played a role in the generation of antibodies against H5N1 epitopes . The HI and NT antibodies and the T cell response of the control animals at all time points before challenge are the same as the pretested values . Three weeks after the second vaccination , animals in each group were challenged with an intratracheal inoculation of 106 EID50 of AH/05 virus ( n = 4 ) or BHG/05 virus ( n = 4 ) in a 3-ml volume . Three days later , two animals from each group were euthanized , and different parts of the respiratory system were collected for virus titration and histologic and immunohistochemical studies . The remaining animals were observed and euthanized on day 15 postchallenge . The control animals showed disease symptoms after challenge . All eight control animals became anorexic on day 1 postchallenge , and completely lost their appetites for two days . Four were euthanized on day 3 postchallenge , while the remaining four animals gradually recovered on days 4 and 5 postchallenge . Four control animals challenged with AH/05 and three challenged with BHG/05 developed fever within the first 2 days postchallenge ( Figure 4A and 4B ) . By contrast , the vaccinated animals remained healthy during the 15 days of observation post-challenge with either the AH/05 or BHG/05 virus . The appetites and body temperatures of the vaccinated animals were unchanged during this period ( Figure 4A and 4B ) . In the vaccinated animals , the HI and NT antibody titers measured at 2 weeks postchallenge were approximately the same as those recorded at 2 weeks after the second vaccination ( Figure 2B–2E ) . HA-specific T cell responses increased on week 1 after challenge , and the peak response was detected at 2 weeks postchallenge ( Figure 3 ) . While in the control animals , although the titers of antibodies measured by ELISA reached 400–800 , the HI and NT antibody , and the HA-specific T cell responses were not detected at 2 weeks after challenge ( data not shown ) . Lung tissue from four vaccinated macaques euthanized on day 3 postchallenge with either BHG/05 or AH/05 lacked macroscopic lesions , had only mild-to-moderate bronchopneumonia with prominent peribronchiolar lymph follicles apparent on microscopic observation , and were free of detectable viral antigen ( Figure 5A , 5B , 5E , 5F , and 5I ) . A spectrum of macroscopic lesions—including congestion , exudation , and consolidation—were observed in the lung lobes of two unvaccinated control animals challenged with the BHG/05 virus ( C3 and C4 ) and one challenged with the AH/05 virus ( C1 ) . Only prominent swelling of the lymph nodes and tonsil were seen in another control animal ( C2 ) challenged with the AH/05 virus . Moderate-to-severe bronchopneumonia with prominent viral antigen expression was a characteristic finding in the nonvaccinated animals ( Figure 5C , 5D , 5G , 5H , and 5I; also Table 5 ) . Virus was not isolated from any of the organs tested in the four vaccinated animals challenged with either the AH/05 or BHG/05 virus ( Figure 6A and 6B ) , but was found at high titers in the trachea , bronchus , lung , lymph nodes , and tonsil of the four unvaccinated animals on day 3 postchallenge ( Figure 6A and 6B ) . Among the eight macaques euthanized on day 15 postchallenge , virus was isolated from tonsil of the two control animals challenged with AH/05 virus ( C5 and C6 ) at titers of 5 . 3 and 5 . 7 log10EID50/g , respectively ( Figure 6C ) , but not from either of the two vaccinated animals . Virus was recovered at a low titer from the nasal swab of a single macaque ( C8 ) on day 4 postchallenge and of another ( C6 ) on day 6 postchallenge ( Figure 6D ) .
We generated a reassortant H5N1 cold-adapted virus , AH/AAca , using reverse genetics in Vero cells , and evaluated its immunogenecity and efficacy as a live attenuated vaccine . The virus retained both the ca and ts phenotypes of the AAca virus , and was attenuated in chickens , mice and monkeys . After a single immunizing dose , the vaccine induced strong HI and NT antibody responses to H5 influenza virus in mice and protected them from homologous and heterologous H5N1 virus challenges . Most importantly , after two immunizations , the vaccine induced both humoral and T cell immune response in nonhuman primates and completely protected these animals from challenge with either homologous or heterologous H5N1 virus . Our results warrant human testing of the AH/AAca virus as a candidate live attenuated pandemic vaccine for use against H5N1 influenza virus . The H5N1 viruses are divided into ten distinct phylogenetic clades ( 0–9 ) based on their HA genes . Those associated with human infection are all from either clade 1 , representing viruses isolated mainly from patients in Thailand and Vietnam , or clade 2 , in which the viruses have been further divided into different subclades [23] . The clade 2 . 1 viruses are circulating only in Indonesia , while the clade 2 . 2 and 2 . 3 viruses continue to infect poultry and humans in multiple countries , posing severe threats to public health [23] . The H5N1 pandemic vaccines evaluated to date are all based on clade 1 [9]–[11] , [17] or calde 0 viruses [16] , [17] , and their efficacy against clade 2 viruses is quite limited [17] . The AH/AAca vaccine we described provides complete protection against challenge with viruses from both clades 2 . 2 and 2 . 3; moreover , the monkey antisera induced by AH/AAca cross reacted well with clade 1 virus as in an HI test ( data not shown ) . The H5N1 viruses , AH/05 and BHG/05 , replicate in multiple organs in mice after intranasal inoculation ( Table 2 ) , however , our preliminary studies indicate that these viruses could not replicate in monkeys after intranasal inoculation , but they replicate efficiently in the respiratory system and caused severe pneumonia upon intratracheal inoculation , as has been seen with human patients [24] . This is why we challenged the monkeys with intratracheal inoculation instead of the intranasal inoculation . Despite introduction of the challenge virus into the trachea , a preferred site of replication for H5N1 viruses , the intranasal immunization of the AH/AAca vaccine provided complete protection to animals , further demonstrating the efficacy of this live vaccine . In a previous study , Suguitan et al [17] found differences in the immunogenicity of three H5N1 live attenuated viruses . The vaccine that contains the HA and NA genes from a clade 1 virus ( A/VN/1203/2004 ) was poorly immunogenic in mice , and was not able to prevent the replication of the challenge viruses in lungs and turbinates of mice ( even two doses of the vaccine were not able to prevent the replication of the challenge virus in ferrets ) . That vaccine was also poorly immunogenic in humans ( personal communication from Dr . Subbarao ) . We also generated different H5N1 live attenuated viruses with the surface genes derived from different viruses that had been isolated in China . We found that these reassortants possessed diverse replicative abilities and induced varied antibody responses in mice; only the AH/AAca vaccine proved highly immunogenic in both mice and monkeys . These results suggest that the immunogenicity of H5N1 live attenuated vaccine largely depends on the HA and NA genes , emphasizing the need for careful selection of donor viruses when preparing vaccines for a likely H5N1 influenza pandemic . Although the precise responses that must be induced to protect against H5N1 infection in humans are unknown , animal studies indicate a central role for the cellular immune response [12] . Thus , in the face of a pandemic , a vaccine that elicits cellular immunity could be valuable in reducing the severity of disease and mortality , if not in providing complete protection from infection [25] . Moreover , a vaccine that induces a cellular immune response could increase the likelihood of generating broadly cross-reactive responses that may be effective against multiple virus strains . Ruat et al [8] reported that inoculation of two doses of inactivated vaccine ( containing 30 µg of HA ) with adjuvants in monkeys could induce functional antibody and protect the animals from a homologous H5N1 virus challenge , but that vaccine did not induce any detecable cellular immune response . In the present study , the HI antibody titers induced by two doses of the AH/AAca vaccine in monkeys were higher than those achieved with two doses of the inactivated vaccine in the study of Ruat et al [8] . Two doses of AH/AAca vaccine also induced strong T cell responses , which may play an important role in the sterile protection of monkeys after H5N1 influenza virus challenge . Whether cold-adapted , live attenuated H5N1 vaccines would be sufficiently immunogenic to merit their widespread use during a pandemic remains unclear , the use of live influenza H5N1 vaccines before a pandemic would be difficult to justify , as this strategy would introduce a new HA gene into human populations . Nonetheless , considering the efficacy shown by our vaccine in nonhuman primates , we suggest that it has strong potential as an effective H5N1 virus countermeasure , warranting further evaluation in humans .
The H5N1 virus AH/05 was isolated from the tracheal secretion of a patient with lethal outcome from Anhui province in China in 2005 [26] , [27] , the BHG/05 virus and the GS/GD/96 viruses were isolated from a bar-headed goose and a goose , respectively , as described previously [1] , [28] , and the CK/SX/06 virus was isolated from a chicken in northern China in 2006 . Virus stocks were propagated in specific-pathogen free chicken embryos or MDCK cells . The PB2 , PB1 , PA , NP , M and NS genes of the AAca virus were synthesized ( Jinsite Biotechnology , www . jinsite . com . cn ) and inserted into the viral RNA-mRNA bidirectional expression plasmid pBD as described previously [29] . The HA and NA genes of the AH/05 virus were amplified by RT-PCR and inserted into pBD; the region that encodes basic amino acids at the HA cleavage site of the plasmid was modifed to encode the amino acid sequence corresponding to the sequence in the avirulent virus HA as described previously [16] , [22] . AH/AAca virus was generated by reverse genetics [18] , [19] , [20] . Virus stock was propagated in specific pathogen-free chicken eggs . The ca and ts phenotype and the replication of AH/AAca in chickens were tested as previously described [30] . Serum antibody against H5N1 influenza virus was detected by IgG ELISA essentially as described by DiNapoli et al [31] using 400 ng of AH/AAca virus , which was grown in eggs and purified by ultracentrifugation though a 30% sucrose cushion , to coat the 96-well Immulon 1B plates ( Dynex Technologies , Inc . , www . dynextechnologies . com ) . The pretest ELISA values ( range 20–80 ) are the background; which have been subtracted from the experimental values of the monkeys . Sera were treated with Vibrio cholerae ( Denka-Seiken , www . denka-seiken . co . jp ) receptor-destroying enzyme before being tested for the presence of HI antibody with 0 . 5% ( V/V ) chicken erythrocytes . The antigens used were homologous wild-type H5N1 virus or BHG/05 virus . The NT antibody titers were tested in MDCK cells with heat-inactivated sera collected from mice or animals . HI and NT antibody titers were transformed into log10 titers for the calculation of mean±s . d . values . The frequencies of PBMC-derived T lymphocytes that released IFN-γ upon restimulation with H5 HA-derived peptide pools were determined by an ELISPOT assay , using a Mabtech kit according to the manufacturer's instructions . Briefly , thawed PBMC samples , isolated by Lymphoprep density gradient centrifugation ( Axis-Shield , www . axis-shield . com ) , were incubated without peptides at 37°C in 5% CO2 for 4 h . After washing , they were incubated for 20 h at a concentration of 20 µg/ml with peptides ( 18-mer overlapped by 10 amino acids; Sigma , www . sigmaaldrich . com ) generated from a human H5N1 isolate ( A/Anhui/01/05 ) . PHA mitogen was used as a positive control . Cells ( 200 , 000 per well ) were added to each well of the ELISPOT plates ( Millipore , www . millipore . com ) , which had been coated with antiprimate IFN-γ antibody ( Mabtech clone G2 . 4 ) , and incubated at 4°C overnight . The wells were next washed six times with PBS to remove cells and were then treated with a biotinylated antiprimate IFN-γ monoclonal antibody ( Mabtech clone 7-B6-1 ) in PBS containing 0 . 5% BSA for 2 h at room temperature . After another three washes with PBS , an avidin-alkaline phosphatase complex was added , followed by incubation for 1 h at room temperature . The wells were then washed , incubated with BCIP substrate ( BioRad , www . bio-rad . com ) for 15 min at room temperature , rinsed with distilled water to halt spot development , dried and read with an automated ELISPOT reader ( AID , www . elispot . com ) . The number of spot-forming cells ( SFCs ) from each well was determined for each animal after subtraction of counts from cells cultured without peptide . A response was considered positive if SFCs exceeded 20 per 106 PBMCs . The average response for negative peptides and mock controls was 3 SFC/million PBMC . The H5 HA response of each animal was taken the sum of the IFN-γ positive responses from all HA pools after subtraction of background counts . To confirm the presence of peptide induced IFN- γ responses and their relationship to CD4+ or CD8+ T lymphocytes , we tested individual peptides from the first ELISPOT using a two-dimensional matrix system in a second ELISPOT assay , using thawed PBMC samples depleted of CD8+ T lymphocytes . Cell depletion was carried out with nonhuman primate CD8+-specific microbeads according to the manufacturer's instructions ( Miltenyi Biotec , www . miltenyibiotec . com ) . CD8+ lymphocytes in the PBMC samples were removed by labeling the cells with specific microbeads in buffer containing PBS pH7 . 2 , 0 . 5% BSA and 2 mM EDTA and then applying a magnetic field . Undepleted PBMCs were used as positive controls . Six-week-old female specific-pathogen-free BALB/c mice were used in this study . The wild-type and reassortant viruses were both tested for their replicative capacity , and the dose required to kill 50% of the mice ( MLD50 ) was determined as described previously [1] . For the immunogenicity study , groups of 5 mice were anesthetized with CO2 before they were inoculated intranasally once or twice ( 4 weeks apart ) with 106 EID50 of the GSGD/AAca , CKSX/AAca or AH/AAca virus . Sera were collected at 4 weeks after the first vaccination or second vaccination for the HI and NT antibody detection using the homologous wild-type H5N1 virus as antigen . For the vaccine study , 80 6-week-old female specific-pathogen-free BALB/c mice were anesthetized with CO2 before they were inoculated intranasally once or twice ( 4 weeks apart ) with 106 EID50 of the AH/AAca in a 50 µl volume or with PBS as control . Serum samples were collected from six mice in each group at 4 weeks after the first and second immunizations and were examined for HI and NT antibody using the homologous AH/05 virus and heterologous BHG/05 virus as antigens . Four weeks after vaccination , the mice were challenged with 100 MLD50 of the AH/05 ( 103 . 5EID50 ) or BHG/05 ( 103 . 6EID50 ) virus intranasally; three mice from each group were killed on day 3 postchallenge , and their organs collected for virus titration . The remaining seven mice were observed for 15 days for body weight change and death . Sixteen female rhesus macaques ( Macaca mulatta ) 2 or 3 years of age were divided into two groups of eight animals each; one group ( V1–V8 ) was inoculated intranasally twice ( 4 weeks apart ) with 107 EID50 of the AH/AAca virus in a 1-ml volume , while the other ( C1–C8 ) received the same volume of PBS as a control . Serum samples were collected from each animal at 2 and 4 weeks after the first immunization and 2 weeks after the second immunization . Three weeks after the second immunization , the animals in each group were challenged by intratracheal inoculation of 106 EID50 of AH/05 virus ( n = 4 ) or BHG/05 ( n = 4 ) virus in a 3 ml volume . Three days later , two animals from each subgroup were euthanized , and different parts of their respiratory system were collected for virus titration and histologic and immunohistochemical examinations; the remaining animals were observed and euthanized on day 15 postchallenge . Nasal swabs were collected from all of the animals on days 2 , 4 and 6 postchallenge for virus isolation in eggs . Tissues fixed in 10% phosphate-buffered formalin were dehydrated , embedded in paraffin , cut into 5-µm thick sections , and stained with standard hematoxylin-and-eosin . Immunohistochemistry was performed with antibodies to an H5 virus ( A/Vietnam/1203/04 ) using the Dako Envision system ( Dako , www . dako . com ) . Studies with highly pathogenic H5N1 avian influenza viruses inoculated into mice and macaques were conducted in a biosecurity level 3+ laboratory approved by the Chinese Ministry of Agriculture . All animal studies were approved by the Review Board of Harbin Veterinary Research Institute , Chinese Academy of Agricultural Sciences . Virus titers in mice , antibody titers of mice and monkeys were compared with a two-sided t-test . | H5N1 influenza viruses have caused human infections with more than 60% fatality in 14 countries and may yet be the source of the next pandemic . Therefore , the development of effective vaccines against these viruses is the highest priority for H5N1 pandemic preparedness . A high dosage or adjuvants improve the immunogenicity of H5N1 inactivated vaccines; however , limited production capacity for conventional inactivated influenza virus vaccines could severely hinder the ability to control the spread of H5N1 influenza through vaccination . Here , we generated and tested the efficacy of a cold-adapted , live attenuated H5N1 vaccine in mice and nonhuman primates . We found that the vaccine provided complete protection in these animals against homologous and heterologous H5N1 virus challenge . Since live vaccines require less processing than inactivated vaccines and do not require adjuvants , our study represents a major advance in vaccine development for H5N1 pandemic influenza . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"virology/vaccines"
] | 2009 | Immunogenicity and Protective Efficacy of a Live Attenuated H5N1 Vaccine in Nonhuman Primates |
Mathematical models are increasingly being used to evaluate strategies aiming to achieve the control or elimination of parasitic diseases . Recently , owing to growing realization that process-oriented models are useful for ecological forecasts only if the biological processes are well defined , attention has focused on data assimilation as a means to improve the predictive performance of these models . We report on the development of an analytical framework to quantify the relative values of various longitudinal infection surveillance data collected in field sites undergoing mass drug administrations ( MDAs ) for calibrating three lymphatic filariasis ( LF ) models ( EPIFIL , LYMFASIM , and TRANSFIL ) , and for improving their predictions of the required durations of drug interventions to achieve parasite elimination in endemic populations . The relative information contribution of site-specific data collected at the time points proposed by the WHO monitoring framework was evaluated using model-data updating procedures , and via calculations of the Shannon information index and weighted variances from the probability distributions of the estimated timelines to parasite extinction made by each model . Results show that data-informed models provided more precise forecasts of elimination timelines in each site compared to model-only simulations . Data streams that included year 5 post-MDA microfilariae ( mf ) survey data , however , reduced each model’s uncertainty most compared to data streams containing only baseline and/or post-MDA 3 or longer-term mf survey data irrespective of MDA coverage , suggesting that data up to this monitoring point may be optimal for informing the present LF models . We show that the improvements observed in the predictive performance of the best data-informed models may be a function of temporal changes in inter-parameter interactions . Such best data-informed models may also produce more accurate predictions of the durations of drug interventions required to achieve parasite elimination . Knowledge of relative information contributions of model only versus data-informed models is valuable for improving the usefulness of LF model predictions in management decision making , learning system dynamics , and for supporting the design of parasite monitoring programmes . The present results further pinpoint the crucial need for longitudinal infection surveillance data for enhancing the precision and accuracy of model predictions of the intervention durations required to achieve parasite elimination in an endemic location .
Mathematical models of parasite transmission , via their capacity for producing dynamical forecasts or predictions of the likely future states of an infection system , offer an important tool for guiding the development and evaluation of strategies aiming to control or eliminate infectious diseases [1–7] . The power of these numerical simulation tools is based uniquely on their ability to appropriately incorporate the underlying nonlinear and multivariate processes of pathogen transmission in order to facilitate plausible predictions outside the range of conditions at which these processes are either directly observed or quantified [8–11] . The value of these tools for guiding policy and management decisions by providing comparative predictions of the outcomes of various strategies for achieving the control or elimination of the major Neglected Tropical Diseases ( NTDs ) has been highlighted in a series of recent publications [8 , 11 , 12] , demonstrating the crucial role these quantitative tools are beginning to play in advancing policy options for these diseases . While these developments underscore the utility of transmission models for supporting policy development in parasite control , a growing realization is that these models can be useful for this purpose only if the biological processes are well defined and demographic and environmental stochasticity are either well-characterized or unimportant for meeting the goal of the policy modelling exercise [9–11 , 13–16] . This is because the realized predictability of any model for a system depends on the initial conditions , parameterizations and process equations that are utilized in its simulation such that model outcomes are strongly sensitive to the choice of values used for these variables [17] . Any misspecification of these system attributes will lead to failure in accurately forecasting the future behaviour of a system , with predictions of actual future states becoming highly uncertain even when the exact representation of the underlying deterministic process is well established but precise specification of initial conditions or forcing and/or parameter values is difficult to achieve [17 , 18] . This problem becomes even more intractable when theoretical models depend on parameter estimates taken from other studies [5 , 17 , 19] . Both these challenges , viz . sensitivity to forcing conditions and use of parameter estimates from settings that are different from the dynamical environment in which a model will be used for simulation , imply that strong limits will be imposed on the realized predictability of any given model for an application [9 , 10 , 20] . As we have shown recently , if such uncertainties are ignored , the ability of parasite transmission models to form the scientific basis for management decisions can be severely undermined , especially when predictions are required over long time frames and across heterogeneous geographic locations [4 , 5 , 7] . These inherent difficulties with using an idealized model for producing predictions to guide management have led to consideration of data-driven modelling procedures that allow the use of information contained within observations to improve specification and hence the predictive performance of process-based models [9 , 10 , 14 , 21–23] . Such approaches , termed model-data fusion or data assimilation methods , act by combining models with various data streams ( including observations made at different spatial or temporal scales ) in a statistically rigorous way to inform initial conditions , constrain model parameters and system states , and quantify model errors . The result is the discovery of models that can more adequately capture the prevailing system dynamics in a site , an outcome which in turn has been shown to result in the making of significantly improved predictions for management decision making [9 , 10 , 14 , 24] . Initially used in geophysics and weather forecasting , these methods are also beginning to be applied in ecological modelling , including more recently in the case of infectious disease modelling [9 , 10] . In the latter case , the approach has shown that it can reliably constrain a disease transmission model during simulation to yield results that approximate epidemiological reality as closely as possible , and as a consequence improve the accuracy of forecasts of the response of a pathogen system exposed to various control efforts [4–7 , 21 , 25–27] . More recently , attention has also focused on the notion that a model essentially represents a conditional proposition , i . e . that running a model in a predictive mode presupposes that the driving forces of the system will remain within the bounds of the model conceptualization or specification [28] . If these driving forces were to change , then it follows that even a model well-calibrated to a given historical dataset will fail . New developments in longitudinal data assimilation can mitigate this problem of potential time variation of parameters via the recursive adjustment of the model by assimilation of data obtained through time [22 , 29 , 30] . Apart from allowing assessment of whether stasis bias may occur in model predictions , such sequential model calibration with time-varying data can also be useful for quantifying the utility of the next measurement in maximizing the information gained from all measurements together [31] . Carrying out such longitudinal model-data analysis has thus the potential for providing information to improve the efficiency and cost-effectiveness of data monitoring campaigns [24 , 31–33] , along with facilitating more reliable model forecasts . A key question , however , is evaluating which longitudinal data streams provide the most information to improve model performance [33] . Indeed , it is possible that from a modelling perspective using more data may not always lead to a better-constrained model [34] . This suggests that addressing this question is not only relevant to model developers , who need observational data to improve , constrain , and test models , but also for disease managers working on the design of disease surveillance plans . At a more philosophical level , we contend that these questions have implications for how current longitudinal monitoring data from parasite control programmes can best be exploited both scientifically and in management [31] . Specifically , we suggest that these surveillance data need to be analysed using models in a manner that allows the extraction of maximal information about the monitored dynamical systems so that this can be used to better guide both the collection of such data as well as the provision of more precise estimates of the system state for use in making state-dependent decisions [2 , 35–37] . Currently , parasite control programmes use infection monitoring data largely from sentinel sites primarily to determine if an often arbitrarily set target is met [3] . Little consideration is given to whether these data could also be used to learn about the underlying transmission dynamics of the parasitic system , or how such learning can be effectively used by management to make better decisions regarding the interventions required in a setting to meet stated goals [2 , 4] . Here , we develop an analytical framework to investigate the value of using longitudinal LF infection data for improving predictions of the durations of drug interventions required for achieving LF elimination by coupling data collected during mass drug interventions ( MDAs ) carried out in three example field sites to three existing state-of-the-art lymphatic filariasis ( LF ) models [4 , 6 , 21 , 38–43] . To be managerially relevant to current WHO-specified LF intervention surveillance efforts , we evaluated the usefulness of infection data collected in these sites at the time points proposed by the WHO monitoring framework in carrying out the present assessment [44] . This was specifically performed by ranking these different infection surveillance data streams according to the incremental information gain that each stream provided for reducing the prediction uncertainty of each model .
Longitudinal pre- and post-infection and MDA data from representative sites located in each of the three major regions endemic for LF ( Africa , India , and Papua New Guinea ( PNG ) ) were assembled from the published literature for use in constraining the LF models employed in this study . The three sites ( Kirare , Tanzania , Alagramam , India , and Peneng , PNG ) were selected on the basis that each represents the average endemic transmission conditions ( average level of infection , transmitting mosquito genus ) of each of these three major extant LF regions , while providing details on the required model inputs and data for conducting this study . These data inputs encompassed information on the annual biting rate ( ABR ) and dominant mosquito genus , as well as MDA intervention details , including the relevant drug regimen , time and population coverage of MDA , and times and results of the conducted microfilaria ( mf ) prevalence surveys ( Table 1 ) . Note each site also provided these infection and MDA data at the time points pertinent to the existing WHO guidelines for conducting LF monitoring surveys during a MDA programme [44] , which additionally , as pointed out above , allowed the assessment of the value of such infection data both for supporting effective model calibration and for producing more reliable intervention forecasts . The three existing LF models employed for this study included EPIFIL , a deterministic Monte Carlo population-based model , and LYMFASIM and TRANSFIL , which are both stochastic , individual-based models . All three models simulate LF transmission in a population by accounting for key biological and intervention processes such as impacts of vector density , the life cycle of the parasite , age-dependent exposure , density-dependent transmission processes , infection aggregation , and the effects of drug treatments as well as vector control [4 , 21 , 38–40 , 42 , 43 , 49] . Although the three models structurally follow a basic coupled immigration-death model formulation , they differ in implementation ( e . g . from individual to population-based ) , the total number of parameters included , and the way biological and intervention processes are mathematically incorporated and parameterized . The three models have been compared in recent work [8 , 12] , with full details of the implementation and simulation procedures for each individual model also described [6 , 8 , 12 , 21 , 39 , 42 , 43 , 49 , 50] . Individual model parameters and fitting procedures specific to this work are given in detail in S1 Supplementary Information . We used longitudinal data assimilation methods to sequentially calibrate the three LF models with the investigated surveillance data such that parameter estimates and model predictions reflect not only the information contained in the baseline but also follow-up data points . The available mf prevalence data from each site were arranged into four different temporal data streams to imitate the current WHO guidelines regarding the time points for conducting monitoring surveys during an MDA programme . This protocol proposes that infection data be collected in sentinel sites before the first round of MDA to establish baseline conditions , no sooner than 6 months following the third round of MDA , and no sooner than 6 months following the fifth MDA to assess whether transmission has been interrupted ( defined as reduction of mf prevalence to below 1% in a population ) [44 , 51] . Thus , the four data streams considered for investigating the value of information gained from each survey were respectively: scenario 1—baseline mf prevalence data only , scenario 2—baseline and post-MDA 3 mf prevalence data , scenario 3—baseline , post-MDA 3 , and post-MDA 5 mf prevalence data , and scenario 4—baseline and post-MDA 5 mf prevalence data . In addition to these four data streams , a fifth model-only scenario ( scenario 0 ) was also considered where no site-specific data was introduced . In this case , simulations of interventions were performed using only model-specific parameter and ABR priors estimated for each region . The first step for all models during the data assimilation exercises reported here was to initially simulate the baseline infection conditions in each site using a large number of samples ( 100 , 000 for EPIFIL and TRANSFIL , and 10 , 000–30 , 000 for LYMFASIM ) randomly selected from the parameter priors deployed by each model . The number of parameters which were left free to be fitted to these data by each model range from 3 ( LYMFASIM and TRANSFIL ) to 21 ( EPIFIL ) . The ABR , a key transmission parameter in all three models , was also left as a free parameter whose distribution was influenced by the observed ABR ( Table 1 ) and/or by fits to previous region-specific datasets ( see S1 Supplementary Information for model-specific implementations ) . The subsequent steps used to incorporate longitudinal infection data into the model calibration procedure varied among the models , but in all cases the goodness-of-fit of the model outputs for the site-specific mf prevalence data was assessed using the chi-square metric ( α = 0 . 05 ) [52] . EPIFIL used a sequential model updating procedure to iteratively modify the parameters with the introduction of each subsequent follow up data point through time [6] . This process uses parameter estimates from model fits to previous data as priors for the simulation of the next data which are successively updated with the introduction of each new observation , thus providing a flexible framework by which to constrain a model using newly available data . Fig 1 summarizes the iterative algorithm used for conducting this sequential model-data assimilation exercise [6] . LYMFASIM and TRANSFIL , by contrast , included all the data in each investigated stream together for selecting the best-fitting models for each time series–i . e . model selection for each data series was based on using all relevant observations simultaneously in the fitting process [30 , 53 , 54] . Although a limitation of this batch estimation approach is that the posterior probability of each model is fixed for the whole simulation period , unlike the case in sequential data assimilation where a restricted set of parameters is exposed to each observation ( as a result of parameter constraining by data used in the previous time step ) –which thereby yields models that give better predictions for different portions of the underlying temporal process—here we use both methods to include and assess the impact that this implementation difference may have on the results presented below . For all models , the final updated parameter estimates from each data stream were used to simulate the impact of observed MDA rounds and for predicting the impact of continued MDA to estimate how many years were required to achieve 1% mf prevalence . Interventions were modelled by using the updated parameter vectors or models selected from each scenario for simulating the impact of the reported as well as hypothetical future MDA rounds on the number of years required to reduce the observed baseline LF prevalence in each site to below the WHO transmission threshold of 1% mf prevalence [44] . When simulating these interventions , the observed MDA times , regimens , and coverages followed in each site were used ( Table 1 ) , while MDA was assumed to target all residents aged 5 years and above . For making mf prevalence forecasts beyond the observations made in each site , MDA simulations were extended for a total of 50 annual rounds in each site at an assumed coverage of 65% . While the drug-induced mf kill rate and the duration of adult worm sterilization were fixed among the models ( Table 1 ) , the worm kill rate was left as a free parameter to be estimated from post-intervention data to account for the uncertainty in this drug efficacy parameter [4 , 7 , 21] . The number of years of MDA required to achieve the threshold of 1% mf prevalence was calculated from model forecasts of changes in mf prevalence due to MDA for each model-data fusion scenario . The predictions from each model regarding timelines to achieve 1% mf for each fitting scenario were used to determine the information gained from each data stream compared to the information attributable to the model itself [14 , 33 , 55] . The relative information gained from a particular data stream was calculated as Id = Hm—Hmd where H measures the entropy or uncertainty associated with a random variable , Hm denotes predictions from the model-only scenario ( scenario 0 ) which essentially represents the impact of prior knowledge of the system , and Hmd signifies predictions from each of the four model-data scenarios ( i . e . scenarios 1–4 ) . The values of Id for each data scenario or stream were compared in a site to infer which survey data are most useful for reducing model uncertainty . The Shannon information index was used to measure entropy , H , as follows: H=−∑i=1mp ( xi ) log2p ( xi ) , where p ( xi ) is the discrete probability density function ( PDF ) of the number of years of MDA predicted by each fitted model to reach 1% mf , and is estimated from a histogram of the respective model predictions for m bins ( of equal width in the range between the minimum and maximum values of the PDFs ) [14 , 56] . To statistically compare two entropy values , a permutation test using the differential Shannon entropy ( DSE ) was performed [57] . DSE is defined as |H1—H2| where H1 was calculated from the distribution of timelines to achieve 1% mf for a given scenario , y1 , and H2 was calculated from the distribution of timelines to achieve 1% mf for a different scenario , y2 . The list of elements in y1 and y2 were combined into a single list of size y1 + y2 and the list was permuted 20 , 000 times . DSE was then recalculated each time by calculating a new H1 from the first y1 elements and a new H2 from the last y2 elements from each permutation , from which p-values may be quantified as the proportion of all recalculated DSEs that were greater than the original DSE . Model predictions of the mean and variance in timelines to LF elimination were weighted according to the frequencies by which predictions occurred in a group of simulations . In general , if D1 , D2 , … , Dn are data points ( model predictions in the present case ) that occur in an ensemble of simulations with different weights or frequencies W1 , W2 , … , Wn , then the weighted mean , Wmean , = ∑i=1nWi*Di∑i=1nWi , while the weighted variance , Wvariance , = ∑i=1nWi* ( Di−Wmean ) 2 ( n′−1 ) *∑i=1nWin′ Here , n is the number of data points and n′ is the number of non-zero weights . In this study , the weighted variance of the distributions of predicted timelines to achieve 1% mf prevalence was calculated to provide a measure of the precision of model predictions in addition to the entropy measure , H . A similar weighting scheme was also used to pool the timeline predictions of all three models . Here , predictions made by each of the three models for each data scenario were weighted as above , and a composite weighted 95% percentile interval for the pooled predictions was calculated for each data stream . This was done by first computing the weighted percentiles for the combined model simulations from which the pooled 2 . 5th and 97 . 5th percentile values were quantified . The Matlab function , wprctile , was used to carry out this calculation . The extent by which parameter constraints are achieved through the coupling of models with data was evaluated to determine if improvements in such constraints by the use of additional data may lead to reduced model prediction uncertainty [33] . Parameter constraint was calculated as the ratio of the mean standard deviation of all fitted parameter distributions to the mean standard deviation of all prior parameter distributions . A ratio of less than one indicates the fitted parameter space is more constrained than the prior parameter space [33] . This assessment was carried out using the EPIFIL model only . In addition , pairwise parameter correlations were also evaluated to assess whether the sign , magnitude , and significance of these correlations changed by scenario to determine if using additional data might alter these interactions to better constrain a model . For this assessment , Spearman’s correlation coefficients and p-values testing the hypothesis of no correlation against the alternative of correlation were calculated , and the exercise was run using the estimated parameters from the EPIFIL model . EPIFIL was used to conduct a sensitivity analysis investigating whether the trend in relative information gained by coupling the model with longitudinal data was dependent on the interventions simulated . The same series of simulations ( for three LF endemic sites and five fitting scenarios ) were completed with the extended MDA coverage beyond the observations given in Table 1 set here at 80% instead of 65% to represent an optimal control strategy . As before , the timelines to reach 1% mf prevalence in each fitting scenario were calculated and used to determine which data stream provided the model with the greatest gain of information . The results were compared to the original series of simulations to assess whether the trends are robust to changes in the intervention coverages simulated . EPIFIL was also used to perform another sensitivity analysis expanding the number of data streams to investigate if the WHO monitoring scheme is adequate for informing the making of reliable model-based predictions of timelines for achieving LF elimination . To perform this sensitivity analysis , pre- and post-MDA data from Villupuram district , India that provide extended data points ( viz . scenario 1–4 as previously defined , plus scenario 5—baseline , post-MDA 3 , post-MDA 5 , and post-MDA 7 mf prevalence data , and scenario 6—baseline , post-MDA 3 , post-MDA 5 , post-MDA 7 , and post-MDA 9 mf prevalence ) were assembled from the published literature [47 , 58] . The timelines to reach 1% mf prevalence and the entropy for each of these additional scenarios were calculated to determine whether additional data streams over those recommended by WHO are required for achieving more reliable model constraints , which among these data might be considered as compulsory , and which might be optional for supporting predictions of elimination . Differences in predicted medians , weighted variances and entropy values between data scenarios , models and sites were statistically evaluated using Kruskall-Wallis tests for equal medians , F-tests for equality of variance , and DSE permutation tests , respectively . P-values for assessing significance for all pairwise tests were obtained using the Benjamini-Hochberg procedure for controlling the false discovery rate , i . e . for protecting against the likelihood of obtaining false positive results when carrying out multiple testing [59] .
Here , our goal was twofold . First , to determine if data are required to improve the predictability of intervention forecasts by the present LF models in comparison with the use of theoretical models only , and second , to evaluate the benefit of using different longitudinal streams of mf survey data for calibrating the three models in order to determine which data stream was most informative for reducing the uncertainty in model predictions in a site . Table 2 summarises the key results from our investigation of these questions: these are the number of accepted best-fitting models for each data stream or scenario in the three study sites ( Table 1 ) , the predicted median and range ( 2 . 5th-97 . 5th percentiles ) in years to achieve the mf threshold of 1% mf prevalence , the weighted variance and entropy values based on these predictions , and the relative information gained ( in terms of reduced prediction uncertainty ) by the use of longitudinal data for constraining the projections of each of the three LF models investigated . Even though the number of selected best-fit models based on the chi-square criterion ( see Methods ) differed for each site and model , these results indicate unequivocally that models constrained by data provided significantly more precise intervention predictions compared to model-only predictions ( Table 2 ) . Note that this was also irrespective of the two types of longitudinal data assimilation procedures ( sequential vs . simultaneous ) used by the different models in this study . Thus , for all models and sites , model-only predictions made in the absence of data ( scenario 0 ) showed the highest prediction uncertainty , highlighting the need for data to improve the predictive performance of the present models . The relative information gained by using each data stream in comparison to model-only predictions further support this finding , with the best gains in reducing model prediction uncertainty provided by those data constraining scenarios that gave the lowest weighted variance and entropy values; as much as 92% to 96% reductions in prediction variance were achieved by these scenarios in comparison to model-only predictions between the three models ( Table 2 ) . The results also show , however , that data streams including post-MDA 5 mf survey data ( scenarios 3 and 4 ) reduced model uncertainty ( based on both the variance and entropy measures ) most compared to data streams containing only baseline and/or post-MDA 3 mf survey data ( scenarios 1 and 2 ) ( Table 2 ) . Although there were differences between the three models ( due to implementation differences either in how the models are run ( Monte Carlo deterministic vs . individual-based ) or in relation to how the present data were assimilated ( see above ) ) , overall , scenario 3 , which includes baseline , post-MDA 3 , and post-MDA 5 data , was shown to most often reduce model uncertainty the greatest . Additionally , there was no statistical difference between the performances of scenarios 3 and 4 in those cases where scenario 4 resulted in the greatest gain of information ( Table 2 ) . It is also noticeable that the best constraining data stream for each combination of site and model also produced as expected the lowest range in predictions of the numbers of years of annual MDA required to achieve the 1% mf prevalence in each site , with the widest ranges estimated for model-only predictions ( scenario 0 ) and the shorter data streams ( scenario 1 ) . In general , this constriction in predictions also led to lower estimates of the median times to achieve LF elimination , although this varied between models and sites ( Table 2 ) . The change in the distributions of predicted timelines to LF elimination without and with model constraining by the different longitudinal data streams is illustrated in Fig 2 for the Kirare site ( see S2 Supplementary Information for results obtained for the other two study villages investigated here ) . The results illustrate that both the location and length of the tail of the prediction distributions can change as models are constrained with increasing lengths of longitudinal data , with inclusion of post-MDA 5 mf survey data consistently producing a narrower or sharper range of predictions compared to when this survey point is excluded . Fig 3 compares the uncertainty in predictions of timelines to achieve elimination made by each of the three models without ( scenario 0 ) and via their constraining by the data streams providing the lowest prediction entropy for each of the models per site . Note that variations in scenario 0 predictions among the three models directly reflect the different model structures , parameterizations , and the presence ( or absence ) of stochastic elements . The boxplots in the figure , however , show that for all three sites and models , calibration of each model by data greatly reduces the uncertainty in predictions of the years of annual MDA required to eliminate LF compared to model-only predictions , with the data streams producing the lowest entropy for simulations in each site significantly improving the precision of these predictions ( Table 2 ) . This gain in precision , and thus the information gained using these data streams , is , as expected , greater for the stochastic LYMFASIM and TRANSFIL models compared to the deterministic EPIFIL model . Note also that even though the ranges in predictions of the annual MDA years required to eliminate LF by the data streams providing the lowest prediction entropy differed statistically between the three models , the values overlapped markedly ( e . g . for Kirare the ranges are 10–18 , 9–14 , 9–15 for EPIFIL , LYMFASIM and TRANSFIL respectively ) , suggesting the occurrence of a similar constraining of predictive behaviour among the three models . To investigate this potential for a differential model effect , we further pooled the predictions from all three models for all the data scenarios and evaluated the value of each investigated data stream for improving their combined predictive ability . The weighted 95% percentile intervals from the pooled predictions were used for carrying out this assessment . The results are depicted in Fig 4 and indicate that , as for the individual model predictions , uncertainty in the collective predictions by the three LF models for the required number of years to eliminate LF using annual MDA in each site may be reduced by model calibration to data , with the longitudinal mf prevalence data collected during the later monitoring periods ( scenarios 3 and 4 ) contributing most to improving the multi-model predictions for each site . We attempted to investigate if model uncertainty in predictions by the use of longitudinal data was a direct function of parameter constraining by the addition of data . Given the similarity in outcomes of each model , we remark on the results from the fits of the technically easier to run EPIFIL model to evaluate this possibility here . The assessment of the parameter space constraint achieved through the inclusion of data was made by determining if the fitted parameter distributions for the model became reduced in comparison with priors as data streams were added to the system [33] . The exercise showed that the size of the estimated parameter distributions reduced with addition of data , with even scenario 1 data producing reductions for Kirare and Peneng ( Fig 5 ) . In the case of Alagramam , however , there was very little , if any , constraint in the fitted parameter space compared to the prior parameter space . This result , together with the fact that even using all the data in Kirare and Peneng produced up to only between 2 . 5 to 5% reductions in fitted parameter distributions when compared to the priors , indicate that the observed model prediction uncertainty in this study may be due to other complex factors connected with model parameterization . Table 3 provides the results of an analysis of pairwise parameter correlations of the selected best-fitting models for data scenario 1 compared to those selected by the data stream that gave the best reduction in EPIFIL prediction uncertainty for Alagramam ( scenario 3 ) . These results show that while the parameter space was not being constrained with the addition of more data , the pattern of parameter correlations changed in a complex manner between the two constraining data sets . For example , although the number of significantly correlated parameters did not differ , the magnitude and direction of parameter correlations were shown to change between the two data scenarios ( Table 3 ) . The corresponding results for Kirare and Peneng are shown in S3 Supplementary Information , and indicate that a broadly similar pattern of changes in parameter associations also occurred as a result of model calibration to the sequential data measured from those sites . This suggests that this outcome may constitute a general phenomenon at least with regards to the sequential constraining of EPIFIL using longitudinal mf prevalence data . An intriguing finding ( from all three data settings ) is that the most sensitive parameters in this regard , i . e . with respect to altered strengths in pairwise parameter correlations , may be those representing the relationship of various components of host immunity with different transmission processes , including with adult worm mortality , rates of production and survival of mf , larval development rates in the mosquito vector and infection aggregation ( Table 3 ) . This suggests that , as more constraining data are added , changes in the multidimensional parameter relationships related to host immunity could contribute to the sequential reductions in the LF model predictive uncertainty observed in this study . The LF elimination timeline predictions used above were based on modelling the impacts of annual MDA given the reported coverages in each site followed by an assumed standard coverage for making longer term predictions ( see Methods ) . This raises the question as to whether the differences detected in the case of the best constraining data stream between the present study sites and between models ( Table 2 ) could be a function of the simulated MDA coverages in each site . To investigate this possibility , we used EPIFIL to model the outcome of changing the assumed MDA coverage in each site on the corresponding entropy and information gain trends in elimination predictions made from the models calibrated to each of the site-specific data scenarios/streams investigated here . The results of increasing the assumed coverage of MDA to 80% for each site are shown in Fig 6 and indicate that the choice of MDA coverage in this study are unlikely to have significantly influenced the conclusion made above that the best performing data streams for reducing model uncertainty for predicting LF elimination pertains to data scenarios 3 and 4 . However , while the model-predicted timelines to achieve the 1% mf prevalence threshold using the observed MDA coverage followed by 80% MDA coverage showed that the data stream which most reduced uncertainty did not change from the impact of using the observed MDA coverage followed by 65% MDA coverage modelled for Kirare and Peneng ( Table 2 , Fig 6 ) , this was not the case for Alagramam , where data from scenario 3 with a 80% coverage resulted in the greatest reduction in entropy compared to the original results using 65% coverage which indicated that scenario 4 data performed best ( Table 2 , Fig 6 ) . Notably , though , the entropy values of predictions using the data scenario 3 and 4 constraints were not statistically different for this site ( p-value < 0 . 05 ) ( Fig 6 ) . EPIFIL was also used to expand the number of calibration scenarios using a dataset with longer term post-MDA data from Villupuram district , India . This dataset contained two addition data streams: scenario 5 which included baseline , post-MDA 3 , post-MDA 5 , and post-MDA 7 mf data , and scenario 6 , which included baseline , post-MDA 3 , post-MDA 5 , post-MDA 7 , and post-MDA 9 mf data . Scenario 6 thus contained the most post-MDA data and was demonstrated to be the most effective for reducing model uncertainty , but this effect was not statistically significantly different from the reductions produced by assimilating data contained in scenarios 3 and 5 ( Table 4 ) . The inclusion of more data than are considered in scenario 3 therefore did not result in any significant additional reduction in model uncertainty . EPIFIL was used to evaluate the accuracy of the data-driven predictions of the timelines required to meet the goal of LF elimination based on breaching the WHO-set target of 1% mf prevalence . This analysis was performed by using the longitudinal pre and post-infection and MDA data reported for the Nigerian site , Dokan Tofa , where elimination was achieved according to WHO recommended criteria after seven rounds of MDA ( Table 5 ) . The data from this site comprised information on the ABR and dominant mosquito genus , as well as details of the MDA intervention carried out , including the relevant drug regimen applied , time and population coverage of MDA , and outcomes from the mf prevalence surveys conducted at baseline and at multiple time points during MDA [60] . The results of model predictions of the timelines to reach below 1% mf prevalence as a result of sequential fitting to the mf prevalence data from this site pertaining to scenarios 0–4 ( as defined above ) are shown in Table 6 . Note that in the post MDA 3 , 5 and 7 surveys , as no LF positive individuals were detected among the sample populations , we used a one-sided 95% Clopper-Pearson interval to determine the expected upper one-sided 95% confidence limits for these sequentially observed zero infection values using the “Rule of Three” approximation after K empty samples formula [61] . The results show that model constraining by scenario 2 , which includes baseline and post-MDA 3 data , and scenario 3 , which includes baseline , post-MDA 3 , and post-MDA 5 data , resulted in both the least entropy values and the shortest predicted times , i . e . , from as low as 2 to as high as 7 years , required for achieving LF elimination in this site ( Table 6 ) . The data in Table 5 show that the first instance the calculated one-sided upper 95% confidence limit in this setting fell below 1% mf prevalence also occurred post MDA 7 ( i . e after 7 years of MDA ) . This is a significant result , and indicates that apart from being able to reduce prediction uncertainty , the best data-constrained models are also able to more accurately predict the maximal time ( 7 years ) by which LF elimination occurred in this site .
Our major goal in this study was to compare the reliability of forecasts of timelines required for achieving parasite elimination made by generic LF models versus models constrained by sequential mf prevalence surveillance data obtained from field sites undergoing MDA . A secondary aim was to evaluate the relative value of data obtained at each of the sampling time points proposed by the WHO for monitoring the effects of LF interventions in informing these model predictions . This assessment allowed us to investigate the role of these data for learning system dynamics and measure their value for guiding the design of surveillance programmes in order to support better predictions of the outcomes of applied interventions . Fundamentally , however , this work addresses the question of how best to use predictive parasite transmission models for guiding management decision making , i . e . whether this should be based on the use of ideal models which incorporate generalized parameter values or on models with parameters informed by local data [10] . If we find that data-informed models can reduce prediction uncertainty significantly compared to the use of theoretical models unconstrained by data , then it is clear that to be useful for management decision making we require the application of model-data assimilation frameworks that can effectively incorporate information from appropriate data into models for producing reliable intervention projections . Antithetically , such a finding implies that using unconstrained ideal models in these circumstances will provide only approximate predictions characterized by a degree of uncertainty that might be too large to be useful for reliable decision making [14 , 33 , 62] . Here , we have used three state-of-the-art LF models calibrated to longitudinal human mf prevalence data obtained from three representative LF study sites to carry out a systematic analysis of these questions in parasite intervention modelling ( see also Walker et al [63] for a recent study highlighting the importance of using longitudinal sentinel site data for improving the prediction performances of the closely-related onchocerciasis models ) . Further , by iteratively testing the reduction in the uncertainty of the projections of timelines required to achieve LF elimination in a site made by the models matching each observed data point , we have also quantified the relative values of temporal data streams , including assessing optimal record lengths , for informing the current LF models . Our results provide important insights as to how best to use process models for understanding and generating predictions of parasite dynamics . They also highlight how site-specific longitudinal surveillance data coupled with models can be useful for providing information about system dynamics and hence for improving predictions of relevance to management decision-making . The first result of major importance from our work is that models informed by data can significantly reduce predictive uncertainty and hence improve performance of the present LF models for guiding policy and management decision-making . Our results show that these improvements in predictive precision were consistent between the three models and across all three of our study sites , and can be very substantive with up to as much as 92% to 96% reductions in prediction variance obtained by the best data-constrained models in a site compared to the use of model-only predictions ( Table 2 ) . The practical policy implications of this finding can also be gleaned from appraising the actual numerical ranges in the predictions made by each individual model for each of the modelling scenarios investigated here . In the case of EPIFIL , the best data-informed model ( scenario 3 in Peneng ) gave an elimination prediction range of 7–12 years , while the corresponding model-only predictions for this site indicated a need for between 6–29 years of annual MDA ( Table 2 ) . These gains in information from using data to inform model parameters and hence predictions were even larger for the two stochastic models investigated here , viz . LYMFASIM and TRANSFIL , where ranges as wide as 7–28 years predicted by model-only scenarios were reduced to 9–14 years for the best data-informed models in the case of LYMFASIM for Kirare village , and from as broad as 8–48 years to 7–22 years respectively in the case of TRANSFIL for Peneng ( Table 2 ) . These results unequivocally indicate that if parasite transmission models are used unconstrained by data , i . e . based on general parameter values uninformed by local data , it would lead to the making of predictions that would be marked by uncertainties that are likely to be far too large to be meaningful for practical policy making . If managers are risk averse , this outcome will also mean their need to plan interventions for substantially much longer than necessary , with major implications for the ultimate cost of the programme . Note also that although statistically significant changes in the median years of MDA required to achieve LF elimination were observed for the best data-informed models for all the three LF model types in each site , these were relatively small compared to the large reductions seen in each model’s predictive uncertainly ( Table 2 , Fig 3 ) . This result highlights that the major gains from constraining the present models by data lies in improving their predictive certainty rather than in advancing their average behaviour . However , our preliminary analysis of model predictive accuracy suggests that the best data-constrained models may also be able to generate more accurate predictions of the impact of control ( Table 6 ) , indicating that , apart from simply reducing predictive uncertainty , such models could additionally have improved capability for producing more reliable predictions of the outcomes of interventions carried out in a setting . The iterative testing of the reduction in forecast uncertainty using mf surveillance data measured at time points proposed by the WHO ( to support assessment of whether the threshold of 1% mf prevalence has been reached before implementation units can move to post-treatment surveillance [44] ) has provided further insights into the relative value of these data for improving the predictive performance of each of the present LF models . Our critical finding here is that parameter uncertainty in all three LF models was similarly reduced by the assimilation of a few additional longitudinal data records ( Table 2 ) . In particular , we show that data streams comprising baseline + post-MDA 3 + post-MDA 5 ( scenario 3 ) and those comprising baseline + post-MDA 5 data ( scenario 4 ) best reduced parameter-based uncertainty in model projections of the impact of MDAs carried out in each study site irrespective of the models used . Although preliminary , a potential key finding is that the use of longer-term data additional to the data measured at the WHO proposed monitoring time points did not lead to a significant further reduction in parameter uncertainty ( Table 4 ) . Also , the finding that the WHO data scenarios 3 and 4 were adequate for constraining the present LF models appears not to be an artefact of variations in the MDA coverages observed between the three study sites ( Fig 6 ) . These results suggest that up to 5 years of post-MDA mf prevalence data are sufficient to constrain model predictions of the impact of LF interventions at a time scale that can go up to as high as 7 to 22 years depending on the site and model , and that precision may not improve any further if more new data are added ( Table 2 , Table 4 ) . Given that the WHO post-MDA LF infection monitoring protocol was developed for the purpose solely focussed on supporting the meeting of set targets ( e . g . the 1% mf prevalence threshold ) and not on a priori hypotheses regarding how surveillance data could be used also to understand the evolution and hence prediction of the dynamical parasitic system in response to management action , our results are entirely fortuitous with respect to the value of the current LF monitoring data for learning about the LF system and its extinction dynamics in different settings [31] . They do , nonetheless , hint at the value that coupling models to data may offer to inform general theory for guiding the collection and use of monitoring data in parasite surveillance programmes in a manner that could help extract maximal information about the underlying parasite system of interest . Our assessment of whether the incremental increase in model predictive performance observed as a result of assimilating longitudinal data may be due to parameter constraining by the addition of data has shed intriguing new light on the impact that qualitative changes in dynamical system behaviour may have on parameter estimates and structure , and hence on the nature of the future projections of system change we can make from models . Our major finding in this regard is that even though the parameter space itself may not be overly constrained by the best data stream ( scenario 3 in this case for Alagramam village ) , the magnitude and direction of parameter correlations , particularly those representing the relationship of different components of host immunity with various transmission processes , changed markedly between the shorter ( scenario 1 ) and seemingly optimal data streams ( scenario 3 ) . This qualitative change in system behaviour induced by alteration in parameter interactions in response to perturbations has been shown to represent a characteristic feature of complex adaptive ecological systems , particularly when these systems approach a critical boundary [64–66] . This underscores yet another important reason to incorporate parameter information from data for generating sound system forecasts [67] . The finding that additional data beyond 5 years post-MDA did not appear to significantly improve model predictive performance in this regard suggests that pronounced change in LF parameter interactions in response to MDA interventions may occur generally around this time point for this parasitic disease , and that once in this parameter regime further change appears to be unlikely . This is an interesting finding , which not only indicates that coupling models to at least 5 years post-MDA will allow detection of the boundaries delimiting the primary LF parameter regions with different qualitative behaviour , but also that the current WHO monitoring protocol might be sufficient to allow this discovery of system change . Although our principal focus in this study was in investigating the value of longitudinal data for informing the predictive performance of the current LF models , the results presented here have also underscored the existence of significant spatial heterogeneity in the dynamics of parasite extinction between the present sites ( Table 2 , Fig 3 ) . In line with our previous findings , this observed conditional dependency of systems dynamics on local transmission conditions means that timelines or durations of interventions required to break LF transmission ( as depicted in Table 2 ) will also vary from site to site even under similar control conditions [3–5 , 21] . As we indicated before , this outcome implies that we vitally require the application of models to detailed spatio-temporal infection surveillance data , such as that exemplified by the data collected by countries in sentinel sites as part of their WHO-directed monitoring and evaluation activities , if we are to use the present models to make more reliable intervention predictions to drive policy and management decisions ( particularly with respect to the durations of interventions required , need for switching to more intensified or new MDA regimens , and need for enhanced supplementary vector control ) in a given endemic setting [64] . As we have previously pointed out , the development of such spatially adaptive intervention plans will require the development and use of spatially-explicit data assimilation modelling platforms that can couple geostatistical interpolation of model inputs ( eg . ABR and/or sentinel site mf/antigen prevalence data ) with discovery of localized models from such data in order to produce the required regional or national intervention forecasts [5] . The estimated parameter and prediction uncertainties presented here are clearly dependent on the model-data fusion methodology and its implementation , and the cost function used to discover the appropriate models for a data stream [20] . While we have attempted to evaluate differences in individual model structures , their computer implementation , and the data assimilation procedures followed ( e . g . sequential vs . simultaneous data assimilation ) , via comparing the collective predictions of the three models versus the predictions provided by each model singly , and show that these factors are unlikely to play a major role in influencing the current results , we indicate that future work must address these issues adequately to improve the initial methods we have employed in this work . Currently , we are examining the development of sequential Bayesian-based multi-model ensemble approaches that will allow better integration of each model’s behaviour as well as better calculation of each model’s transient parameter space at each time a new observation becomes available [30] . This work also involves the development of a method to fuse information from several indicators of infection ( e . g . mf , antigenemia , antibody responses [21] ) together to achieve a more robust constraining of the present models . As different types of data can act as mutual constraints on a model , we also expect that such multi-indicator model-data fusion methods will additionally address the problem of equifinality , which is known to complicate the parameterization of complex dynamical models [24 , 68] . Of course , the ultimate test of the results reported here , viz . that LF models constrained by coupling to year 5 post-MDA data can provide the best predictions of timelines for meeting the 1% mf prevalence threshold in a site , is by carrying out the direct validation of our results against independent observations ( as demonstrated by the preliminary validation study carried out here using the Dokan Tofa data ( Tables 5 and 6 ) ) . We expect that data useful for performing these studies at scale may be available at the sentinel site level in the countries carrying out the current WHO-led monitoring programme . The present results indicate that access to such data , and to post-treatment surveillance data which are beginning to be assembled by many countries , is now a major need if the present LF models are to provide maximal information about parasite system responses to management and thus generate better predictions of system states for use in policy making and in judging management effectiveness in different spatio-temporal settings [24 , 31] . Given that previous modelling work has indicated that if the globally fixed WHO-proposed 1% mf prevalence threshold is insufficient to break LF transmission in every setting ( and thus conversely leading to significant infection recrudescence [21] ) , the modelling of such spatio-temporal surveillance data will additionally allow testing if meeting this recommended threshold will indeed result in successfully achieving the interruption of LF transmission everywhere . | Although parasite transmission models offer powerful tools for predicting the impacts of interventions , there is growing realization that these models can be useful for this purpose only if their governing biological processes are well defined . Recently , model-data assimilation has been applied to address this problem and improve the performance of process-oriented models for ecological forecasting . Here , we developed an analytical framework that allowed the sequential coupling of the three existing lymphatic filariasis ( LF ) models with longitudinal infection monitoring data collected in field sites undergoing mass drug administrations ( MDAs ) to examine the relative value of such data for parameterizing these models and for improving their predictions of the required durations of drug interventions to break parasite transmission . We found that data-informed models provided more precise and reliable forecasts of elimination timelines in the study sites compared to model-only predictions , and that data collected up to 5 years post-MDA reduced each model’s predictive uncertainty most . We also found that this improved performance may be intriguingly related to temporal changes in system dynamics . Our results underscore the significance of sequential model-data fusion for enhancing the understanding of LF transmission dynamics , design of surveillance , and generation of reliable model predictions for management decision making . | [
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"co... | 2018 | Quantifying the value of surveillance data for improving model predictions of lymphatic filariasis elimination |
While the role of drug resistance mutations in HIV protease has been studied comprehensively , mutations in its substrate , Gag , have not been extensively cataloged . Using deep sequencing , we analyzed a unique collection of longitudinal viral samples from 93 patients who have been treated with therapies containing protease inhibitors ( PIs ) . Due to the high sequence coverage within each sample , the frequencies of mutations at individual positions were calculated with high precision . We used this information to characterize the variability in the Gag polyprotein and its effects on PI-therapy outcomes . To examine covariation of mutations between two different sites using deep sequencing data , we developed an approach to estimate the tight bounds on the two-site bivariate probabilities in each viral sample , and the mutual information between pairs of positions based on all the bounds . Utilizing the new methodology we found that mutations in the matrix and p6 proteins contribute to continued therapy failure and have a major role in the network of strongly correlated mutations in the Gag polyprotein , as well as between Gag and protease . Although covariation is not direct evidence of structural propensities , we found the strongest correlations between residues on capsid and matrix of the same Gag protein were often due to structural proximity . This suggests that some of the strongest inter-protein Gag correlations are the result of structural proximity . Moreover , the strong covariation between residues in matrix and capsid at the N-terminus with p1 and p6 at the C-terminus is consistent with residue-residue contacts between these proteins at some point in the viral life cycle .
Despite great advances in the treatment of HIV/AIDS , the rapid evolution of resistance against protease inhibitors ( PIs ) contributes significantly to the persistence of highly active retroviral ( ART ) failure . Resistance mutations in the viral protease ( PR ) have been extensively studied [1–5] , but mutations in its substrate , Gag , have been less well-studied and drug resistant mutations not as well cataloged . Protease inhibitor-mediated mutations in gag function as compensatory mutations for protease function and can directly promote resistance to PIs [6–14] . Investigation of resistance mutations in protease has led to advancements in protease inhibitor development . A better understanding of the association among inhibitor resistance mutations in Gag and their contribution to PI failure could be useful for the design of maturation inhibitors and clinical treatment strategies , and for building structural models . During the past decade , advancements in DNA sequencing technologies have allowed for the study of the viral populations within an individual , and importantly these advancements allow for the quantification of low and infrequent HIV drug resistant mutations , which are difficult to detect using traditional Sanger sequencing [15–17] . Moreover , it has been reported that viral mutations that occur with frequencies less than 10% are systematically under-measured with conventional sequencing techniques [18 , 19] . Importantly , deep-sequencing technologies can reliably detect sequence variants with frequencies of 1% or less when template tagging such as PrimerID is utilized [20 , 21] . The sequencing depth afforded by deep-sequencing comes with a cost , as the templates being sequenced , typically 75–200bp in size , are often smaller than the region of interest , thus disrupting linkage analysis . Even when paired-end read methodology is used , it is nearly impossible to determine if two mutations far apart in a sequence occur simultaneously . These limitations have forced most studies to focus on analyzing the frequencies of single residue substitutions . Little progress has been made in identifying pairs or higher order patterns of residue substitutions in HIV samples from patients using deep-sequencing technologies . Additionally , due to the cost of deep-sequencing large regions of a target genome , comprehensive , simultaneous deep sequencing of viral samples from patients is not attempted on a regular basis . An open question in better understanding protease inhibitor resistance is the role of gag mutations , both cleavage and non-cleavage site mutations , in contributing to resistance . To this end , we have relied on next generation sequencing of a 2 kb region encompassing the entire gag gene and the protease portion of the pol gene from 93 HIV positive patients undergoing ART which included a protease inhibitor . This patient population is unique in that all patients were followed after the first failure through the second treatment , of which approximately one-half of the patients failed treatment and the remaining patients controlled their virus [22] . Given our sequential patient sample collection , viral sample amplification methodology , and the precise sequence coverage from deep-sequencing , we calculated single-site residue frequency variation in gag and protease from the viral population from each patient sample . These studies allowed examination of the patterns of single amino acid substitutions in Gag and their correlations with repeated PI-therapy failure . Importantly , the comprehensive viral sample collection and sequencing methodology allowed us to investigate two central aspects of protease inhibitor resistance in protease and gag: single-site variation and two-site covariation . Conventional analysis methods of two-site covariation , often conducted on multiple sequence alignments of full DNA sequences , are difficult to apply to our type of data set due to the limited read lengths provided by current deep-sequencing methodology and the presence of multiple viral species in each sample . To overcome this challenge , we have developed a statistical framework to estimate the probabilities of observing double mutants from the observed single-site marginal probabilities in each sample . This advantage over other methods allows for the aggregation of the probabilities from all samples into a single probability to which conventional covariation analyses can be applied . This then allowed us to utilize mutual information ( MI ) to calculate the pair correlations between pairs of positions in gag . The strongest of such correlations were identified and their implications for gag structural propensities are discussed . The same statistical framework can be applied to other systems that have been sequenced with next-generation sequencing technologies .
A sequential collection of peripheral blood viral samples from patients undergoing ART , containing a protease inhibitor ( PI ) and combinations of nucleoside and non-nucleoside reverse transcriptase inhibitors ( NRTIs and NNRTIs ) , provides a unique opportunity to evaluate mutational changes in the Gag polyprotein and protease over time as a function of protease inhibitor treatment . For patients from which samples were obtained , all ARTs contained a single PI , but included combinations of nucleoside and non-nucleoside reverse transcriptase inhibitors ( NRTIs and NNRTIs ) . There are only two relevant PI therapies for each patient: the first of which all patients failed prior to sequencing ( treatment with various regimens had failed to maintain long-term suppression of viral replication below the limit of detection ( 50–400 copies/mL , depending on the time of testing ) ) , and a second therapy , in which a different prescribed PI was provided and patients were successfully treated and suppressed virus or continued to fail treatment . Of 93 patients entering treatment , 80 patients had definitive second therapy outcomes , defined as success ( 28 patients , viral levels below 100 copies/mL ) or failure ( 52 patients treatment with various regimens had failed to maintain long-term suppression of viral replication below the limit of detection ( 100–400 copies/mL , depending on the time of testing ) ) . For the purpose of sequencing , samples were considered for inclusion into the studies with >1000 copies/mL . If possible , additional samples were obtained from patients who failed the second therapy . The remaining 13 patients had varying levels of viral load slightly below 1000 copies/mL and samples were excluded given inadequate viral amounts for sequencing studies . Current next generation sequencing technologies require a large amount of starting material that greatly exceeds the amount of viral RNA present in a typical clinical sample . Reverse transcription and amplification of the viral material by PCR could introduce bias based on stochastic resampling , leading to a final product pool that is not representative of the initial sample . To reduce the effect of resampling , we attempted to maximize cDNA production and usage by adopting a 1-step RT-PCR approach . This single round of PCR used 40 cycles and was sufficient to generate hundreds of nanograms of product for >95% of RNA samples . In contrast , some other studies [21 , 23] have relied on a nested PCR approach , which may contribute to resampling bias and increases the total number of PCR cycles . To evaluate possible biases resulting from our RT-PCR procedure , we compared SNP frequencies in technical replicates , finding a high level of concordance . Specifically , for three clinical samples , we obtained multiple aliquots that were processed independently throughout the entire process of preparation and sequencing . These samples spanned a range of clinically relevant viral loads , from 2 , 000 copies/mL to 30 , 000 copies/mL . In each case , the paired replicates showed SNP frequencies that were well correlated even when ignoring SNPs that occur with <10% or >90% frequency in paired samples , R>0 . 95 for each pair ( Fig 1 ) . The difference between replicates appeared smallest for the sample with greatest viral load , indicating that a higher number of template molecules can reduce stochastic effects , as might be expected . Aside from the RT-PCR process , the high level of sequencing coverage afforded by the use of the Illumina HiSeq 1000 could also be a factor in the strong correlation between replicates . The consensus among many studies using next generation sequencing is that discrimination of true variants from background variation becomes difficult at frequencies below 1% [16] . Additionally , recent work comparing sequencing with different primer tagging procedures shows that standard sequencing analysis , like has been conducted in this study , cannot distinguish true mutations from artificial mutations present at frequencies less than 1% [15] . However , at frequencies above 1% , standard sequencing analysis has a similar accuracy to that of primer tagged sequences . To ensure that mutations were likely to be biologically relevant we required that mutations occur with frequencies >1% ( i . e . , related to exposure to protease inhibitors ) and occur in ≥5 different patient samples . Mutations in protease that occur under protease inhibitor ( PI ) treatment have been documented extensively [1 , 3–7 , 24–26] . The mutational patterns in prior reports serve as a comparison standard to which we can compare the mutational patterns identified in protease using deep sequencing . Across all treatment samples , regardless of treatment , 50 drug-associated protease mutations at 33 different positions were identified . In each patient sample , these mutations tend to be either dominant or almost absent . Due to this bimodal nature of the mutations at each position within a sample , a mutation was labeled as present if the proportion of the mutation is greater than 1% , and as absent if the proportion of the mutation is less than 1% . By this categorization , we are able to compare the protease mutation pattern in each sample with patterns seen in bulk sequencing and reported in the Stanford HIV Drug Resistance Database [24 , 27] ( shown in S1 Fig ) . Overall , the protease mutational patterns in our samples resemble patterns from the Stanford HIV Drug Resistance Database exposed to a single PI . This is consistent with the notion that our samples were obtained from patients treated with a minimum of 1 PI and a maximum of two PIs . In contrast , the Stanford Database also included sequences from more protease inhibitor experienced patients . The protease site-specific frequencies identified are shown in S2 Fig . The majority of Gag mutations that have been associated with protease inhibitor resistance are confined to mutations within or near the 5 cleavage sites ( CSs ) separating the Gag proteins [6] . Currently , there are less than 65 mutations at 40 Gag positions reported that are PI- or maturation inhibitor-associated or found to covary with protease mutations [6] . Of the 65 PI-associated mutations , only 10 have been shown to directly contribute to PI-resistance; the remaining mutations have been observed only under PI-treatment , but are otherwise of unknown viral utility . Together , these mutations only represent residue variation of roughly 8% of gag , and half are located at cleavage sites , which include the 10 resistance mutations contributing to PI-resistance . Nevertheless , it has been noted using conventional sequencing that many polymorphisms exist in Gag [28] . Utilizing deep sequencing , we found that residue variation in gag was abundant; shown in Table 1 , we observe 329 residue changes at 192 positions throughout gag . In Fig 2 , the observed variation in the deep sequencing data ( top ) is shown above with the variation present in 2378 drug-naive gag sequences from the Los Alamos HIV sequence database ( bottom ) ( http://www . hiv . lanl . gov/ ) . Positions in gag that have similar mutation frequencies between the two datasets are shown in light gray and with reported mutations linked to PI-exposure in red [6] . Mutations were identified within and just outside cleavage sites , but many mutations occurred outside the cleavage sites . We identified considerably more mutations from our deep sequencing data as compared with LANL data in the following regions of gag: in matrix both near the matrix/capsid ( MA/CA ) cleavage site and scattered throughout the central portion of MA; in p2 and nucleocapsid ( NC ) on either side of the p2/NC cleavage site; and throughout the first half of p6 . Our studies identified mutation positions currently associated with PI-resistance [6] , as well as mutation variants associated with PI-exposure in cleavage sites . Cleavage site mutations that are associated with PI-resistance in the CA/p2 cleavage site , residues A360 and L363 , and the NC/p1 cleavage site residue Q430 , were not seen . In four of the five cleavage sites , defined as the region of 10 residues centered on the proteolytic site , mutations were identified that are not currently PI-associated ( S1 Table ) . However , many of these mutations are variants of PI-associated mutations ( S2 Table ) , and therefore could well be PI-associated . Of the observed cleavage site mutations that are known to be associated with PI resistance , excluding those in the highly variable p2/NC cleavage site , most occurred at relatively low frequency within each sample . However , NC/p1 and p1/p6 cleavage site mutations which we observe at low frequency have been shown to almost always appear in the presence of protease mutations that decrease inhibitor binding , such as D30 , V82 , I84 , and M90 mutants [6] . HIV CA , and other selected domains of Gag , are necessary for assembly and are under pressure to maintain their functionality [6 , 29 , 30] . Regions of viral gag that are highly conserved , i . e . , with low residue variability after drug treatment , are of interest given that these regions may be targets for future inhibitors . We examined the frequencies of mutated residues within the gag genes . The CA region demonstrated a mutated residue frequency accounting for 20% of its length , thus making it much more conserved than other Gag proteins ( Table 1 ) . A recent report has evaluated the viral fitness effects of single amino acid substitutions in CA [29] . Rihn et al . found that ~5% of all possible amino acid CA substitutions resulted in viruses that replicate in vivo . Moreover , engineered viruses were identified that contained “fit but rare” mutants that were <0 . 3% of or never found in 1000 HIV B patient sequences selected from the Los Alamos HIV database . The authors concluded that there exists some unknown selection pressure that selects against these particular high fitness mutations in individuals . However , an alternative possibility is that these high fitness mutants are present in viral populations from patients , but were too rare to be detected reliably in the authors’ reference sequences , which were obtained by conventional sequencing . To evaluate this possibility , we have examined whether 11 high fitness mutations presented in Rihn et al . ( Table 9 of [29] ) , I2L , I6T , N21S , S33C , I91T , R100S , S149C , E187V , A204G , A209T , and A209V , were present in our dataset . Of these mutants , 9 were completely absent in the dataset . The remaining two mutants , N21S and I91T , occur infrequently . Thus , 9 of 11 fit but rare mutations identified by Rihn et al . were absent in both our dataset [29] and the Los Alamos HIV database . Next , we evaluated the differences in mutation variation in gag-protease between the viral samples obtained from patients that failed or were successful on ART . At the 599 gag-protease positions , 140 individual mutations are observed above 1% frequency in 5 or more patients who failed subsequent ART ( which constitutes 10% or more of patients who failed therapy ) . From these 140 mutations , we identified 11 mutations that are significantly associated with repeated therapy failure when adjusted for multiple hypothesis testing: MA N124S , NC/p1 cleavage site K436R , p6 E460A and F465S , and PR L10I , R41K , M46I , I54V , I62V , I72V , V82A . The number of patients from each group in which these mutations were observed is shown in Fig 3 . All of the protease mutations , except R41K , are associated with PI-resistance , including the NC/p1 cleavage site mutation K436R . The protease mutations M46I , I54V , and V82A have been shown to have a major impact on PI susceptibility , while L10I , R41K , I62V , I72V are accessory or polymorphic mutations [1 , 4 , 5 , 27] . The MA N124S mutation and two p6 E460A , F465S mutations have not been characterized as to their role in fitness or drug resistance , although N124 is proximal to the MA/CA cleavage site and could possibly function to enhance cleavage . Of the 22 mutations identified in Fig 3 , which represents those with largest frequency differences between the viral sequences identified in failed and successfully treated patients , almost 90% of the total occur in MA , p1/p6 , and protease . This finding closely parallels the observation shown in Fig 2 , in which the majority of inhibitor-mediated mutational variation occurs in MA and p6 . Identifying pairs of correlated mutations from deep sequencing data is not as straightforward as when given conventional multiple sequence alignments . This problem arises given the short reads from deep sequencing templates , which results in loss of direct sequence linkage between distal genes , such as between gag and protease , and the presence of many viruses ( distinct gag and protease combinations ) in a population . Thus , determining the joint probabilities for observing changes in pairs of distal mutations cannot be readily determined . Furthermore , it is not clear how to aggregate these joint probabilities from the many sequencing reads obtained from a viral population . To provide an estimate of distal mutation variant frequency , we have designed a procedure with two main steps: In the first step , for any pair of residue positions , say one in gag and one in protease , we calculate bounds on the joint probability of observing a double mutant at that pair of residue positions from the marginal mutation probabilities obtained from each sample . We then estimate the joint probability from those bounds and then aggregate these joint probability estimates from each viral sample into a single estimate for the probability to observe that pair of mutations across all samples . In the second step , using these joint probabilities , we assess the correlation implicit in the joint probabilities involving two positions in the viral genome using mutual information ( MI ) . We briefly explain the procedure below , for a more detailed description , see Materials and Methods . For any pair of positions , we know with high-precision how likely each mutation is to occur independently of other mutations due to the extremely deep sequence coverage in each sample . These single-site probabilities constrain the possible values of the joint probability of the mutations occurring simultaneously . Within each viral sample , we find that the bounds on the double mutant probability are often very narrow because of the bimodal nature of the mutations , which are either dominant or almost absent at a typical position within a sample . Using estimates for the double mutant probability from each sample based on the bounding procedure described in Materials and Methods , we average the probabilities over all patient viral samples to get an estimate for the double mutant probability in the patient population . Although the number of samples is limited , because we are averaging probabilities and not a single binary count from each sample , this procedure produces a probability table for the joint probabilities for the status of two mutants that differs from how a table of counts is directly constructed from a multiple sequence alignment . As a result , given tight bounds , the joint probability estimates are much more precise than those calculated from table counts . In our study , for each pair of positions , we construct a 2×2 probability table representing the probabilities of observing both wildtype residues , a single amino acid substitution at the first position , a single amino acid substitution at the second position , and amino acid substitutions at both positions . Utilizing this methodology we can identify co-evolving pairs of mutations by searching for pairs of mutants with average double mutant probabilities that differ greatly from independence . We quantify this deviation by the mutual information ( MI ) ; pairs with the largest mutual information have the strongest covariation . The details of this procedure are explained in Materials and Methods . It is crucial for our method to be validated on a dataset where correlations between two positions are known . A simple test dataset can be constructed from the deep sequencing pileup from each sample in which pairs of PR residues are close enough in sequence to be on the same set of 100bp paired end reads . Doing so provides us with a test dataset which mirrors the structure of our true dataset , but the bivariate marginal distributions are known . From the known bivariate marginals , we can compute the univariate marginal distributions from which we then estimate bounds on the bivariate marginals via our bounding procedure . We have calculated bivariate counts from the deep sequencing pileup for 24 pairs of PR residues which have previously been shown to be correlated using conventional sequencing [3 , 4] where we had sufficient pileup ( >10 , 000 overlapping reads ) . The estimated bounds ( shown in S5 Fig ) are typically very narrow , and the lower bound is often a very conservative estimate of the double mutant probability in each sample for all pairs examined . The mutual information ( MI ) computed for each pair using the bounding procedure is in good agreement with the MI computed using the known bivariate marginal probabilities , as shown in Fig 4 . In practice , extracting the pileup can be computationally expensive for large regions of interest where the coverage is very high , and for systems with short reads , this method only allows for covariation analysis for residues that are relatively close together . Using our bounding procedure provides a computationally fast method to estimate bivariate marginals from single-site frequency counts for all pairs of interest , not just those within 200–300bp . Protease mutation covariation in PI resistant viruses has been extensively studied and reported by Shafer and others [3–5] . Findings in these publications potentially serve as a benchmark that can be used to estimate how well we are able to recover information about correlated mutations from protease and gag deep sequencing data using the bounding procedure . Using a multiple sequence alignment ( MSA ) of 4919 treated protease sequences from the Stanford HIV Database ( HIVDB , [24] ) ; we computed the MI for all 4851 ( 99 choose 2 ) pairs of positions . Among the 1594 pairs with positive , nonzero MI extracted from the MSA , 1275 pairs are common to our deep sequencing dataset; we chose these 1275 PR-PR positively correlated pairs to assess our bounding procedure . From these 1275 pairs , the 127 ( top 10% ) pairs with the highest MI when calculated using the MSA were selected as the putative true positives to which we compared our procedure . These 127 pairs closely resemble the pairs of positions [4 , 5] and corresponding pairs of mutations [3] identified as highly correlated in previous work [3–5] . Fig 5 shows the recovery of the 127 pairs with highest MI from the Stanford Database in our dataset . In the most strongly correlated pairs , we recover several well-studied strongly correlated pairs of protease mutations , such as D30-N88 , I54-V82 , and E35-M36 . The 20 most strongly correlated pairs are shown in Table 2 . We observe an 8-fold enrichment within the top 1% of deep sequencing pairs with highest MI ( Fig 5 , insert ) , and 5-fold enrichment within the top 5% of deep sequencing pairs with highest MI ( S3 Table ) . The recovery is uniformly higher if the least conservative bound on the double mutant probability is used , and a comparison is shown in S3 Fig . But it is evident that below the pairs with the largest MI values , which are consistent between the two databases , there are many pairs identified in the deep sequencing dataset as correlated that are not identified in the Stanford HIVDB . These differences are not likely due to sample size effects in the relatively small number of patient samples in this study because the univariate marginals and the bivariate marginal estimates are calculated with high precision in each sample due to the extremely high coverage afforded by deep sequencing and the very narrow bounds imposed on the bivariate probabilities by the univariate probabilities . We believe this discrepancy is due to real differences between the two sets of data , specifically that joint probabilities are systematically under-estimated using conventional sequencing technologies . It has been shown that variants with frequencies less than 35% are difficult to detect with conventional Sanger sequencing , and protease and gag mutations with frequencies less than 10% often go undetected using standard genotyping analysis [18 , 19] . Yet with deep sequencing , even without template tagging , we are able to reliably detect variants with frequencies as low as 1% in each patient sample . For example , we observe positions L24-T74 to be strongly correlated in the deep-sequencing dataset ( 5th highest PR-PR pair by MI ) , but this pair is not found to be correlated using the HIVDB MSA . We have confidence this correlation exists because individual mutations L24I and T74S/P/A have strong associations with PIs [4 , 26] . The double mutant probability for this pair is estimated between 2 . 18–2 . 19% in the deep sequencing dataset but is 0 . 91% in the HIVDB . With reliable detection of low frequency mutants , deep sequencing allows us to more accurately identify correlations between pairs of residues that are difficult to detect with conventional sequencing . As additional evidence that we observe meaningful correlations derived from the deep sequencing using our bounding procedure to constrain the bivariate probabilities , we note that many of the apparent false positive pairs of mutations in protease identified in our analysis may be biologically important because these pairs contain at least one variant associated with PI-exposure . For example , mutations at pairs of positions such as D30-E35 , E35-V84 , and M36-N88 have been shown individually to directly reduce drug susceptibility . D30 and V84 are located in the protease active site and thus these pairs of positions suggest we observe compensatory-active site pairs previously under sampled due to the limitations of conventional sequencing techniques . Moreover , in the top 5% of pairs with highest MI from deep sequencing , 34 of the 58 pairs identified as putative false positives involve at least one known resistance mutation . The fact that many of the putative false positives detected via our procedure are combinations of PI-associated residues suggests that the true recovery of strongly covarying pairs of protease positions using our bounding procedure is likely significantly higher than the apparent recovery rate shown in Fig 5 . We turn now to a consideration of correlations within the Gag polyprotein and between Gag and protease . Tables 3 and 4 show the strongest 20 positively correlated pairs for Gag-PR and Gag-Gag; the top 1% positively correlated pairs with highest MI values for each region are displayed in S4 and S5 Tables respectively . For the Gag-PR pairs shown in Table 3 , the NC/p1 cleavage site residue A431 is well represented and strongly correlated with protease residues associated with major PI-resistance V82 , M46 , L10 , and L93 . Association between A431V and protease mutations V82A and M46L has been demonstrated using in vitro mutagenesis experiments [31] and regression analysis [14] , but the correlations between A431 and both L10 and L93 have not been previously reported . Additionally , mutations at the p1/p6 CS , P453 and L449 , are strongly correlated with PI-associated protease positions M36 and I84 respectively . L449-I84 has been previously observed [14] , but P453-M36 is not mentioned in the literature . It has been recently reported that mutations in the p1/p6 cleavage site are correlated with PR resistance mutations D30N and N88D [32] , and while we observe no pairs in the top 1% that involve these PR mutations , within the top 5% , R452/P453-D30 and R452/P453-N88 are present . There is no previous evidence of mutations at the CA/p2 CS that are associated with PR mutations in the literature , and while we find positions in 4 of the 5 Gag CSs that are strongly correlated with positions in PR , we also find no evidence that positions at the CA/p2 CS are strongly correlated with positions in PR . Outside of the CSs we find that the overwhelming majority of Gag positions strongly correlated with mutations in protease are located within the first 200 residues ( MA/CA ) or the last 60 residues ( p1/p6 ) of Gag . Although some positions in PR only appear correlated with positions in specific Gag proteins , such as A118/V128-I66 and T456/L486-L24 , the majority of positions in PR shown in Tables 3 , S4 ( E35 , N37 , R41 , and L93 ) are correlated with residues on opposite sides of the Gag polyprotein . For Gag-Gag pairs , many intra- and inter-protein pairs are represented . The majority of the pairs in Table 3 that involve cleavage site residues appear in the NC/p2 cleavage site , which has been shown to be PI-sensitive and highly variable in bulk sequencing . Additionally , 20% of the 70 pairs shown in Table 3 involve the p1 residue G443 , which is located near the gag-pol frameshift-regulating region and is flanked by several positions associated with PI-exposure mutations , K436 , I437 , and L449 [33] . Although there is little analysis of covariation of non-CS Gag mutations currently in the literature , residues R76 , Y79 , and T81 have been described as co-evolving under drug pressure [34] . These residues are all located on an alpha helix in the folded MA protein and it is theorized that mutations in this alpha helix allow greater flexibility in the secondary structure , which may enhance MA/CA cleavage site accessibility to the protease . We also observe strong correlations between residues in this region of MA as pairs Y79-T81 and V82-T84 are highly correlated ( Tables 4 , S5 ) . Additionally , MA residue L75 is highly correlated with several residues in other Gag proteins . While Gag is not the primary target of protease inhibitors , we observe the correlations as measured by mutual information within Gag proteins are of similar magnitudes as in protease ( Tables 2 , 3 , 4 ) . The most strongly correlated pair of positions identified is between two CA residues , which as can be observed from their crystal structures are in close proximity ( PDB 3MGE , 2M8L , 3P05 , 3MGE ) . This is also observed for several other strongly correlated pairs of residues on the same Gag protein ( see Materials and Methods for a full list of PDB IDs ) . Table 5 shows the heavy atom-atom distances between wild type residues for the strongest 20 intra-Gag protein and-protease correlations for which structures exist in the PDB file ( atom-atom distances for all intra-protein pairs from Tables 2 , 3 , 4 are listed in S6 Table ) . We observe 11 of these 20 positions to be within 8Å within the mature protease and Gag proteins . It is apparent that ranking pairs of residues by MI provides major enrichment for detecting structural proximity over random sampling; for example , measuring the distance between 20 randomly chosen pairs from the CA pentamer dimer will yield 11 pairs in close proximity with probability less than 10-14 . All available multimerizations of these proteins were examined for structural contacts: MA ( monomer , trimer ) , CA ( monomer , dimer , pentamer , hexamer ) , NC ( monomer ) , PR ( dimer ) ; see Materials and Methods for more details . We find that the pair of positions with the largest mutual information identified in this study , Gag M228-G248 , is within 6Å in all CA structures . The second most-strongly correlated pair , Gag V159-T280 , is close in some CA dimer structures ( <7Å ) in the NMR structure . These residues may be functionally important in the multimerization of CA as they are on α-helices that play integral roles in dimerization and the formation of the hexameric CA lattice [35] . We also examined the distribution of inter-protein correlations among Gag proteins and protease and we observe that more than 300 residues separate some of the strongest Gag inter-protein correlations in sequence , shown in Fig 6 . There are no complete crystallographic or NMR structures containing two or more of the large Gag proteins . However , models have been constructed to simulate the structural propensities of a mutated Gag intermediate comprised of MA , CA , p2 , and NC , all of which involve the MA domain folding over the CA domain , and it is theorized these structures occur due to entropic effects disfavoring straight conformations of the polyprotein [36] . We observed strong MA-CA correlations that are consistent with these models , and moreover , we find many strong correlations between the MA/CA proteins and residues in p1/p6 . One explanation for these very long-range Gag correlations could be transient structural contacts between the p1/p6 proteins and the MA/CA fold in the immature Gag polyprotein at some point in the viral life cycle . A possible model for the full polyprotein is a distorted circular structure; with a fold near either side of p2 , the C-terminus proteins could interact directly with the MA/CA hairpin structure previously theorized [36] . However , further analysis is needed to distinguish correlations arising from direct spatial proximity from those that are due to networks of indirect effects [37] .
To the best of our knowledge , no previous study has attempted to use multiple deep sequencing samples from PI resistant patients as a population from which to infer correlated mutation pairs . Typically , this type of analysis has been done by examining the one- and two-site amino acid frequency counts at each position in multiple sequence alignments . Previous to this study , there was no direct method to extract two-site frequency counts from viral deep sequencing data of gag and pol given the absence of sequence linkage due to the short sequencing reads . In order to identify strongly correlated residues through the entire 2 kb region of gag and pol we sequenced , we developed a procedure that estimates the bivariate joint probabilities from the observed single-site frequencies . This is made possible by the high precision with which the single-site frequencies are calculated in each sample due to high coverage , and by the bimodal nature of the single-site frequencies in each sample , which yield tight bounds on the bivariate probabilities . Although we considered the simplest such procedure , which involves estimating bounds on the four pair probabilities ( M , M ) , ( M , W ) , ( W , M ) , and ( W , W ) , where W denotes the consensus amino acid and M denotes any amino acid substitution , similar to [4 , 38] , this procedure can be expanded to consider pairs of all individual amino acid substitutions instead of grouping all substitutions together . Recent advances in sequencing and library construction may allow the two-site frequencies to be observed directly from longer sequencing reads [21 , 39] , but until this methodology becomes more widely available , our procedure provides a way to extract meaningful two-site frequencies from short , non-physically linked reads . However , our procedure is reliant on the ability to distinguish the population within individuals from the entire population consisting of all the individual samples . This particular concern is often absent in the analysis of collections of sequences obtained from traditional sequencing where typically only one sequence is sampled from one individual , and the only analysis to be done is to examine the patterns of sequence variation across individuals . The use of deep sequencing expands upon this by allowing the variation within individuals to be studied . When there is considerable variation within , it becomes difficult to untangle the variation across patients from that present within individuals . As discussed previously , the frequency of mutations within each sample is typically limited to a bimodal present-or-absent pattern , which allows for analysis of covariation across samples . The covariation analysis performed in this study relies on the frequency counts measured from the viral sequence population within each patient . The viral population within each patient has descended from founder viruses and the population at the time of sampling may have some background correlation due to phylogenetic similarity . Covariation analysis can be confounded by such phylogenetic effects [40–44] , and a large literature has developed to account for such biases [44 , 45] . Although we have not accounted for this bias in our analyses , there are a number of factors that would argue against the covariation uncovered in our analyses being the result of simple inheritance from founder viruses . Firstly , strong selection pressure can create the environment for convergent evolution in which covariation dominates over phylogenetic effects [42 , 46 , 47]; indeed , drug resistance selection from reverse transcriptase ( RT ) inhibitors has been reported to generate a higher evolution rate in RT , thus fixing mutations , as compared to viral genes not under not under drug selection , such as envelope [48] . Secondly , in our covariation analysis , we have considered the potential influence of phylogeny across samples , evaluated the effects on MI , and found the effects to be minimal ( see Materials and Methods ) . In the patient samples used in this study , the protease and gag population diversity within an individual sample is typically limited . As a result the bounds on the bivariate probabilities are very tight and therefore we are able to aggregate the joint probabilities from the individual samples to extract meaningful information about population covariation . The fact that we examine a portion of the HIV genome which is relatively conserved , when compared , for example , to HIV env gene proteins [49] under immune selective pressure , influences the effectiveness of our analysis . Proteins or protein families evolving very rapidly under genetic drift and other forms of natural variation may not necessarily satisfy these conditions . Nevertheless , the procedure we have developed for identifying covariation from deep sequencing data with short reads used on single site mutation frequencies and bounds on joint marginals serves as a good starting point upon which future studies may expand datasets containing many deep sequenced samples . As inhibitor potency increases , mutation pathways which confer resistance become more complex and involve more amino acid substitutions to compensate for major resistance mutations . Very few PI-associated mutations and even fewer resistance mutations have been previously identified outside of the protease and Gag cleavage sites [6] . By examining the patterns of amino acid substitutions in HIV Gag , we find evidence for new patterns of resistance . Mutations in the MA , and p6 proteins are much more prevalent in PI-experienced individuals who have failed therapy versus individuals who had successful therapy . All patients failed the initial ART , which include PIs , and thus most patients were found to have major PI-resistance mutations in protease . Gag mutations are likely accessory mutations , but the mechanisms by which most Gag mutations compensate for major resistance mutations are not known [50 , 51] . Recently Breuer et al . has proposed that PI-mediated cleavage and non-cleavage site mutations function to enhance the catalytic efficacy of PI-resistance proteases [52] . Mutations identified in this study that contribute to repeated therapy failure may “prime” the viral populations for major resistance mutations in subsequent therapies by enhancing catalytic efficacy of PI-resistant proteases , pre-compensating for resistance mutations with high fitness costs . The majority of the Gag-protease correlations we observe have not been previously studied and these findings serve as a basis for future research into the resistance mechanisms in these regions . We observe positions in MA , CA , p1 , and p6 which are strongly correlated with positions in protease at which major resistance mutations occur . This suggests that residues outside of the cleavage sites can influence protease function , and furthermore , resistance mechanisms in HIV are mediated not just by a few major resistance mutations , but a larger network of residues spanning the Gag polyprotein . It has been shown that the cleavage of Gag proteins is highly dependent on the sequence of the entire cleavage site and possibly proximal residues as well [52 , 53] . Similarly , correlated networks of amino acid mutations across Gag proteins likely contribute more strongly to the development of resistance than single amino acid substitutions . Recent studies have examined covariation among Gag residues in drug naïve patients as the result of immune-pressures [54–58] , but in the context of PI-exposure , very little has been published concerning the covariation of Gag residues with other Gag residues . Despite lacking directly accessible two-site frequencies , we are able to identify several strong signals of covariation in Gag . The magnitudes of the correlations we observe among positions in the Gag polyprotein are as large as those observed in protease . Although covariation is not direct evidence of structural propensities , this information can be useful for solving the structure of the Gag polyprotein at low resolution . We identify strong covariation between residues in MA , CA , p1 , and p6 proteins , which suggests that p1 and p6 may be proximal to MA and CA regions of the Gag polyprotein at some point in the viral life cycle . The Gag polyprotein is believed to multimerize via first dimerizing in the CA domain [35]; the model suggested by the pattern of MI values is consistent with this thinking as it leaves CA exposed . There exist several methods , some based on mutual information , which have been developed to extract direct structural contacts ( typically <8Å ) from multiple sequence alignments [37 , 59–63]; it is possible to adapt these methods to detect direct structural propensities using covariation extracted from deep sequencing . In fact , due to the limited number of publicly available , full length Gag sequences , the bivariate probabilities estimated here may be better suited to parameterize these models than two-site frequency counts extracted from an MSA . When information about correlated mutations is combined with lower resolution structural information from experiments to determine structural contacts , like small angle X-ray scattering ( SAXS ) or hydrogen-deuterium exchange , more consistent models can be constructed for the structural ensembles that represent the Gag polyprotein which are needed for the interpretation of functional studies .
The serum/plasma patient specimens were obtained from the U . S . Military HIV Natural History Study ( IDCRP-000-03 ) as part of the Infectious Disease Clinical Research Program ( IDCRP ) . All samples received by The Scripps Research Institute from the U . S . Military HIV Natural History Study were de-identified and anonymous . The Office of the Protection of Research Subjects at the Scripps Research Institute has reviewed and approved the research project described in this manuscript . A copy of the approval letter is provided in the supplementary material ( S1 Text ) . Plasma samples were obtained from 93 patients who had been treated with therapies that included protease inhibitors . For the samples sequenced in this study , all therapies were protease inhibitor ( PI ) based with a single PI ( some with ritonavir ( RTV ) boosting ) , but included combinations of nucleoside and non-nucleoside reverse transcriptase inhibitors ( NRTIs and NNRTIs ) . Therapies prior to sequencing were NRTI and NNRTI-based with no PIs . Although some patients were sequenced only once and others several times , there are only two relevant PI therapies for each patient: the first of which all patients failed prior to sequencing , and a second therapy on which patients were successfully treated or continued to fail treatment . Patients with multiple sequencing points after initial failure did not receive additional new therapies . Samples were obtained when therapy failed to adequately suppress viral replication ( >1 , 000 copies/mL ) , allowing multiple samples to be taken for some patients . Following extraction of viral RNA from these patient samples , 40 cycles of one-step RT-PCR was used to generate two 1 kilobase amplicons that spanned HIV Gag and protease . Primer design was based on conserved regions of the HIV-1 genome and follows the procedure in [22] . A liquid handling robot ( Biomek NX , Beckman Coulter , Brea , CA , USA ) was used to pool the two regions of amplified cDNA . Then , the pooled and amplified cDNA was prepared for sequencing using the NEBNext DNA Library Prep Master Mix Set ( NEB , Ipswich , MA , USA ) . Specifically , the two amplicons were pooled in equimolar amounts , then 1ug of this mixture was fragmented to an average size of 275bp via mechanical shearing ( S2 instrument , Covaris , Woburn , MA , USA ) . The samples were ligated to 1 of 48 sequencing adapters , each containing a unique 6bp index for downstream demultiplexing . ( These adapters were custom made by ordering oligos from IDT . The sequences of the oligos are the same or similar to Illumina’s Trueseq indexes . ) The fragments were size selected using Ampure beads ( Beckman Coulter ) , and subsequently amplified using six cycles of PCR . After validating the libraries using the Bioanalyzer ( Agilent , Santa Clara , CA , USA ) and Qubit system ( Life Technologies ) , the libraries were loaded onto the cBot ( Illumina , San Diego , CA , USA ) , clonally amplified , and sequenced using 4 lanes on the Hiseq 2000 ( Illumina ) to yield an average of 4 . 3 million of 100bp paired end reads per sample . After sequencing , reads were mapped to the Gag-Pol region of the HIV-1 HXB2 consensus sequence using Burrows-Wheeler Aligner ( BWA , version 0 . 5 . 9-r16 ) . The average mapping success rate to the HXB2 reference was 89 . 85% , with minimum , first quartile , and third quartile values of 54 . 72% , 86 . 99% , and 95 . 82% , respectively . Mapping results were corrected using indel recalibration and base quality score recalibration with Genome Analysis Toolkit ( GATK , version 2 . 6-4-g3e5ff60 ) . Reads with low recalibrated quality scores ( MAPQ<30 ) were discarded . Single-site variants were called using VarScan ( version 2 . 3 ) . Samples with low coverage over either gag or protease were excluded from analysis . The average coverage over all positions in each sample is 202141 overlapping reads , with first and third quartile values of 152188 reads and 245360 reads , respectively , with the distribution of coverages skewed toward very deep coverage . The highest average coverage observed was 671075 reads , and the lowest average coverage was 26161 reads . Variation in the deep sequencing data was compared to protease sequence variation in the Stanford HIV Database and Gag/Gag-Pol sequence variation in the Los Alamos National Laboratory HIV Sequence Database . For protease sequences , the 4/29/2013 downloadable protease dataset was downloaded from http://hivdb . stanford . edu/pages/geno-rx-datasets . html [24] . Non-ambiguous , complete subtype B sequences were separated into two sets of 4919 sequences exposed to treatment involving protease inhibitors and 12764 drug-naive sequences . Each entry in the downloadable dataset contains at least a nucleotide sequence or a list of amino acid substitutions . Entries with available nucleotide data were translated using IUPAC standard protein codes and , if any ambiguities existed in the translated sequence or nucleotide data was unavailable for that sequence , corresponding protein sequence data was used to fill in any ambiguities in the translated sequence . Gag sequences were downloaded using the following settings through the standard search interface from http://www . hiv . lanl . gov/content/sequence/HIV/mainpage . html: virus: HIV-1; subtype: B; culture method: any; Only drug naïve sequences: checked; genomic region: Gag ( searching with amino acid index 790–2292 results in identical results ) . The resulting 2378 Gag amino acid sequences were downloaded using squeeze gap handling and aligned to a HXB2 reference sequence . All but one sequence ( which was discarded ) had gaps and ambiguous amino acids at less than 10% of their length . Uncultured drug-naive gag sequences were also used; although the variation in the uncultured sequences is not identical to that in all naïve sequences ( S4 Fig ) , due to the size of the uncultured set ( <350 sequences ) , the full naïve set was used . To access the differences in variation between patients who failed therapy and patients who were successfully treated , we used the two sample proportion test . Patients were partitioned into two groups based on therapy: success and failure of sizes Ns and Nf respectively . In each patient , mutations present at or above 1% are considered detectable . For a given mutant at a single position , the proportion of patients with that mutation detectable is calculated in each group , Ps and Pf . While the distribution of Ps and Pf are not necessarily normal , the distribution of ( Pf-Ps ) is normally distributed . The pooled proportion Pp Pp=Ps×Ns+Pf×NfNs+Nf and the standard error SE=Pp ( 1-Pp ) ( 1Ns+1Nf ) are computed . From these quantities , a z-score and p-value can be computed assuming a normal distribution using Z = ( Pf-Ps ) /SE . A p-value is computed for each mutation at all 599 positions for which the mutation is detectable in at least 5 patients who failed therapy . Statistically significant mutants were identified after correcting for multiple hypothesis testing using the Holm-Bonferroni method with family wise error rates of 0 . 1 and 0 . 01 ( denoted with * and ** in Fig 3 , respectively ) . To assess the covariation amongst gag and protease mutations between a set of deep sequenced samples , we have constructed a protocol which estimates the joint probability of observing a double mutant and we use the mutual information ( MI ) to quantify how this probability deviates from a null model . For a particular pair of positions and given N samples , the probabilities of observing a mutation at position 1 and a mutation at position 2 individually in sample i are pX and pY , where 1≤i≤N . For each sample i , we then construct a 2×2 table of the joint probabilities of observing a double mutation ( XY ) , only one mutation ( X0 , 0Y ) , and no mutations ( 00 ) . These joint probabilities are constrained by the row marginal probabilities pX , 1-pX , and the column marginal probabilities pY , 1-pY such that only one joint probability is free . Take this to be the double mutation probability pXY , which is bounded such that: max ( 0 , pX+pY-1 ) ≤pXY≤min ( pX , pY ) Moreover , the bounds are exact given that for any number q between the upper and lower bounds , there exists a valid 2×2 table of probabilities with pXY equal to q . Note that if pX and pY are close to either 0 or 1 , then the bounds become very tight . This property is particularly useful in our analysis of the gag and protease deep sequencing data . The bounds on pXY are computed for each sample i , and are then averaged yielding a single upper and lower bound for the average double mutation probability . Using the average single site probabilities pX and pY , we construct a full 2×2 probability table for each of the averaged bounds: pXYlowerpX0lowerp0Ylowerp00lowerpXYupperpX0upperp0Yupperp00upper We also construct an estimate of the joint probabilities assuming X and Y mutate independently , such that pXY0pX00p0Y0p000=pXpYpX ( 1-pY ) ( 1-pX ) pY ( 1-pX ) ( 1-pY ) The deviation of the average 2×2 probability tables from this independent table represents the covariation of X and Y . For assessing positive covariation , the most conservative estimate of pXY is given by max ( 0 , pXYlower ) , whereas the least conservative estimate of pXY is given by pXYupper . For assessing negative covariation the most conservative estimate of pXY is given by min ( 0 , pXYupper ) , whereas the least conservative estimate of pXY is given by pXYlower . The mutual information is defined as MI=∑a∈{X , 0} , b∈{Y , 0}pablog ( pab/pab0 ) It is easily shown that MI = 0 when pXY=pXY0 , and increases as pXY moves away from pXY0 in either direction . Given our bounding procedure , the most positively correlated pairs of mutations are those with the largest MI . Using the deep sequencing data , this procedure is conducted for all pairs of mutations for which the frequencies of the mutations are above 1% in 5 or more samples . It is important to understand the relationship between the proposed procedure for deep sequenced data and those for MSA data consisting of binary counts from single sequences . Each sequence in a MSA provides a single count for a particular single mutant for each position ( double mutant for each pair of positions ) . The counts from all sequences are averaged to get one- and two-site frequency counts , which approximate the univariate and bivariate marginal probabilities when the number of sequences is very large . In contrast , each patient sample in the deep sequenced data essentially provides a MSA of several million sequences . When aggregated , we calculate the mean univariate and bivariate probabilities from each sample , not counts . Therefore , although our dataset contains many fewer samples than sequences in a MSA , a sample in the deep sequenced data provides considerably more information than a single sequence in a MSA . The permutation procedure used to generate p-values for the Jaccard similarity coefficient for MSA data in [3] , if the number of permutations tends to infinity , is equivalent to computing Fisher's exact test ( See S8 Table ) . This procedure determines how likely the observed data could arise from chance and is not a direct measure of the correlation between two mutations . For instance , with this procedure it is possible to know a pair of mutations is weakly correlated with high confidence . Moreover , for MSA data , ranking the strength of correlation by mutual information for a 2×2 table of probabilities is equivalent to ranking by the log likelihood ratio statistic ( LR ) for testing independence in a 2×2 table of counts , because LR = -N×MI . But , as the total sample size tends to infinity , ranking based on LR is asymptotically equivalent to ranking based on Fisher’s exact test of independence [64] . Therefore , the proposed procedure for deep sequencing data differs from previous analyses of MSA data [3] mainly in the necessary step of constructing lower and upper probability tables and , to a lesser extent , in the use of mutual information for ranking correlations in probability tables without depending on the total sample size . Alternative analyses to determine correlations were attempted without estimating joint probabilities , such as using Kendall's tau . In this analysis method , for each mutant in a pair of residues , a vector of single-site frequencies is constructed from the frequencies in each sample . Kendall's tau-b for each such pair is calculated with an accompanying z-score from which a p-value can be calculated . However , Kendall's tau is not appropriate for this type of data because Kendall's tau typically requires the underlying population to be bivariate normal; the frequencies we observe are not normally distributed . Furthermore , Kendall's tau is extremely sensitive to data located at the maximum or minimum of the possible spectrum of values , and the fact that many mutations are either mostly absent or dominant in a single sample produce unreliable results with Kendall's tau . We recognize that the Mutual Information ( MI ) does not account for correlations which arise from phylogenetic relationships among the population of interest . In this specific study , where there is the population within each patient and the combined population of all patients , any phylogenetic correction to MI will only reduce phylogenetic influence in the combined population . Alongside of the uncorrected MI , we have computed MIp [65] . Prior analysis of many methods developed to account for phylogeny , not limited to MI based statistics , has found MIp to be the leading choice for large datasets [66] . We find that the two statistics , MI and MIp , give similar rankings of the most correlated pairs of PR-PR residues as shown in S6 Fig . Shown in S7 Fig is the recovery of positively correlated PR-PR pairs identified in [3] using MIp and the recovery is similar to that using MI shown in Fig 5 . Although we lack the sequence linkage to apply other simple corrections for phylogenetic effects , such as sequence reweighting [55 , 57 , 59] , MI of weighted and unweighted HIV sequences has been shown to be similar [55] . Because results between MI and MIp were found to be similar , we used the uncorrected MI throughout the study . For pairs of residues in MA , CA , NC , and PR , the smallest all-atom distances were calculated by scanning through PDB files for all possible multimerizations of each protein: MA ( monomer PDB 2H3F* , trimer PDB 1HIW ) , CA ( monomer PDB 3MGE , dimer PDB 2M8L* , pentamer PDB 3P05 , hexamer PDB 3MGE ) , NC ( monomer PDB 2EXF* ) , PR ( dimer PDB 1ODW ) . For a single pair , the distance between all combinations of heavy atoms ( backbone and sidechain ) was computed for each combination of chains ( for multimers ) for each conformation . The minimum distance ( Rij ) is listed in Table 5 , S6 Table , as well as the pair of chains , atoms , and the PDB structure from which the distance is derived . Pairs with smallest Rij when on different chains are denoted with the chain combination; otherwise , the chain combination is listed as '-' . For structures derived from NMR data ( denoted with * above ) , the smallest atom-atom distance was calculated for each model , and the smallest distance from all models is reported in Table 5 . The distribution of model distances for each PDB derived from NMR is listed in S7 Table . | Understanding the structure of HIV proteins and the function of drug-resistant mutations of these proteins is critical for the development of effective HIV treatments . Selected gag mutations have been shown to provide compensatory functions for protease resistance mutations and may directly contribute to the development of drug resistance . To determine associations between protease inhibitor mutations and gag , we utilized deep sequencing of HIV gag and protease from a collection of viral isolates from patients treated with highly active retroviral protease inhibitors . Deep sequencing allows for accurate measurement of mutation frequencies at each position , allowing estimation , using a novel method we developed , of the covariation between any two residues on gag . Using this information , we characterize the variation within gag and protease and identify the most strongly correlated pairs of inter- and intra-protein residues . Our results suggest that matrix and p1/p6 mutations form the core of a network of strongly correlated gag mutations and contribute to recurrent treatment failure . Extracting gag residue covariation information from the deep sequencing of patient viral samples may provide insight into structural aspects of the Gag polyprotein as well new areas for small molecule targeting to disrupt Gag function . | [
"Abstract",
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] | [] | 2015 | Deep Sequencing of Protease Inhibitor Resistant HIV Patient Isolates Reveals Patterns of Correlated Mutations in Gag and Protease |
Wnt Planar Cell Polarity ( PCP ) signaling is a universal regulator of polarity in epithelial cells , but it regulates axon outgrowth in neurons , suggesting the existence of axonal modulators of Wnt-PCP activity . The Amyloid precursor proteins ( APPs ) are intensely investigated because of their link to Alzheimer's disease ( AD ) . APP's in vivo function in the brain and the mechanisms underlying it remain unclear and controversial . Drosophila possesses a single APP homologue called APP Like , or APPL . APPL is expressed in all neurons throughout development , but has no established function in neuronal development . We therefore investigated the role of Drosophila APPL during brain development . We find that APPL is involved in the development of the Mushroom Body αβ neurons and , in particular , is required cell-autonomously for the β-axons and non-cell autonomously for the α-axons growth . Moreover , we find that APPL is a modulator of the Wnt-PCP pathway required for axonal outgrowth , but not cell polarity . Molecularly , both human APP and fly APPL form complexes with PCP receptors , thus suggesting that APPs are part of the membrane protein complex upstream of PCP signaling . Moreover , we show that APPL regulates PCP pathway activation by modulating the phosphorylation of the Wnt adaptor protein Dishevelled ( Dsh ) by Abelson kinase ( Abl ) . Taken together our data suggest that APPL is the first example of a modulator of the Wnt-PCP pathway specifically required for axon outgrowth .
The Wnt Planar Cell Polarity ( PCP ) pathway is a highly conserved regulator of cellular orientation within the plane of an epithelium [1] , [2] . Genetic and molecular studies in Drosophila indicate Disheveled ( Dsh ) , a cytoplasmic transducer of Wnt signaling; Frizzled ( Fz ) , a seven-transmembrane receptor for Wnt ligands; and Van Gogh ( Vang ) , a four-pass transmembrane protein , as core Wnt-PCP proteins . Intriguingly , the Wnt-PCP pathway regulates axon outgrowth rather than neuronal polarity during brain development of both vertebrates and Drosophila [3]–[5] . The Amyloid Precursor Protein ( APP ) is a member of a highly conserved family of type I transmembrane proteins that includes APP , APLP1 , and APLP2 [6] in mammals and APP-Like , or APPL , in Drosophila melanogaster [7] . APP proteins show not only structural but also functional conservation , as exemplified by the ability of human APP to rescue behavioral phenotypes of APPL null flies [8] . APP is the subject of intense research because of genetic and biochemical links to Alzheimer's disease ( AD ) , whereby the proteolytic processing of APP generates the Amyloid Beta peptide whose accumulation in the brain is widely thought to induce neurodegeneration [9]–[12] . Despite these efforts , the normal physiological function of APP in vivo in the nervous system remains elusive and highly controversial . This is due to the lack of a consensus over the neuronal phenotypes in null mutant animals and the mechanism of APP action in vivo . APP knock-out mice are viable and show developmental neuronal deficits , namely cortical migration and agenesis of the corpus callosum , at variable penetrance depending on genetic background [13]–[15] . In contrast , another in vivo report , based mainly on gain of function and RNA interference experiments , suggests that APP may be required for developmental axonal degeneration [16] , although it is unclear whether APP knock-out mice show these phenotypes . Finally , initial findings proposed an axonal transport function for APP [17] but later studies strongly questioned the presence of these defects in APP knock-out mice [18] . Mechanistically , there is also disagreement on whether APP acts cell autonomously or non autonomously . For example , an extensive network of molecular interactions has been described for the intracellular domain of APP [19] , yet a knock-in of APP lacking the intracellular domain appears to rescue physiological and learning deficits reported in APP knock-out mice , suggesting that the intracellular domain is dispensable [20] . Because current models based on Amyloid toxicity do not provide a complete explanation for the onset of neuronal dysfunction in AD , it has long been argued that greater attention needs to shift towards understanding the normal physiological function of APP in order to assess its potential contribution to AD pathology [21] , [22] . Therefore , a mechanistic understanding of the in vivo physiological function of APP proteins is of paramount importance . To elucidate the function and mechanism of action of APP proteins in vivo , we first investigated Drosophila APPL , the APP homologue in the fruit fly , as a model system . We show that APPL is a novel neuronal-specific modulator of the PCP pathway required for the robustness of axonal outgrowth during the development of the Mushroom Bodies ( MB ) , a Drosophila center for learning and memory . APPL carries out this function through facilitating the PCP-specific phosphorylation of the Wnt adaptor protein Dishevelled ( Dsh/Dvl ) by the Abelson kinase ( Abl ) . Furthermore , we show that APPL is part of the membrane complex formed by Wnt-PCP core proteins . Finally , biochemical and cell biological analyses show that human APP immunoprecipitates mammalian PCP proteins and that APP proteins are necessary for Dvl phosphorylation in response to the PCP ligand Wnt5a . Therefore , the APP proteins represent a novel and conserved family of neuronal modulators of Wnt-PCP signaling required for the robustness of brain wiring during development .
Drosophila APPL is a neuronal-specific protein expressed in most , if not all , neurons throughout development and adult life . In particular , APPL is highly expressed in the developing Drosophila MB , especially the so-called αβ neurons ( Figure 1A–D ) . Flies null for Appl ( henceforth Appl−/− ) are viable , fertile , and reported to show no gross structural defects in the brain [8] . While a requirement for APPL in learning and memory specifically in adult flies has been shown [23] , the function of its pan-neuronal expression throughout development remains unknown , as does the in vivo mechanism of its action ( s ) . We began addressing the function of APPL in neuronal development by carefully examining the development of the Drosophila MB in Appl−/− mutant flies . The MB derives from two groups of four neuroblasts , one in each hemisphere , that sequentially generate three subsets of neurons: the γ- , α′β′ and αβ neurons , where APPL is highly expressed . Each αβ neuron projects an axon that branches into a dorsal “α branch” and a medial “β branch . ” The fascicles generated by each of these branches are referred to as the α lobe and β lobe . The α and β lobes can be easily visualized using the anti-FascilinII ( FasII ) antibody . The lobes were present and morphologically normal in 97 adult control animals ( Figure 1E ) examined . In contrast , 26% of Appl−/− brains examined ( n = 101 ) showed axonal defects ( Figure S1 ) . Specifically , 14% of the brains show α-lobe loss ( Figure 1F ) , whereas 12% of the brains show β-lobe loss ( Figure 1G ) . These defects are developmental in origin as they can be observed during αβ lobe formation at 48 h of pupal development ( Figure 1H–J ) . To ascertain whether APPL acts cell autonomously to regulate MB axonal outgrowth , we generated GFP-marked single Appl−/− cell clones using the MARCM technique [24] . While none of the control clones showed any defects ( Figure 2A ) , 10% of the mutant clones showed lack of β-lobe growth ( Figures 2B and S2A ) , similar to the penetrance observed in null mutant brains . However , none of the mutant clones showed loss of α-lobe growth . Taken together , these data indicate that APPL is required for normal MB axonal outgrowth and that it is required cell-autonomously for the growth of the β-lobe and non-cell autonomously for the growth of α lobe . To verify the specificity of the Appl−/− phenotype , we rescued the defects by restoring APPL expression in αβ neurons . Expression of full-length membrane-bound APPL , but not a secreted form or a form lacking the intracellular domain ( ApplΔC ) , strongly suppresses the β-lobe loss phenotype ( Figures 2C–H and S2B ) . These results indicate that APPL is required as a full-length , membrane-tethered protein and that the intracellular signaling downstream of APPL is necessary for normal β-lobe outgrowth . Interestingly , secreted APPL strongly reduces the loss of the α lobe ( Figure S2C and S2D ) , confirming that APPL acts non-autonomously in α-lobe outgrowth . All together , the results suggest that APPL is a robustness factor for an unknown axon growth signal whereby Appl−/− αβ neurons are at a phenotypic threshold that causes them to fail to grow in approximately 26% of the cases . To unravel the mechanism by which APPL supports MB axon outgrowth , we chose to focus on the cell-autonomous function of APPL in the β lobe . A previous study using APPL gain of function indicates that APPL overexpression induces axonal outgrowth that is dependent on Abl kinase activity [25] . We asked whether Abl kinase also acts downstream of APPL during MB β-lobe growth . First , we tested if APPL genetically interacts with Abl . To this end we analyzed the adult MB morphology of Appl−/−; Abl−/+ flies . Loss of one copy of Abelson causes a dramatic increase ( up to 51% ) in complete ( 41% ) or partial ( 10% ) β-lobe loss , compared to Appl−/− alone ( Figure 3A , 3B and 3E , 3F ) . As controls we analyzed the siblings heterozygous for both Appl and Abl ( Appl−/+; Abl−/+ ) and observed no phenotypes ( Figure 3F ) . Similarly to Appl−/− mutants alone , the phenotypes arise at early developmental stages ( Figure S3A ) . To further confirm that Abl is the downstream mediator of APPL signaling during β-lobe growth , we tested if overexpression of Abl specifically in MB αβ neurons rescues the Appl null phenotype . We find that wild-type Abl , but not a Kinase Dead ( Abl-KD ) form of Abl , rescues the Appl null phenotype ( Figure 3C–F ) to the same extent as MB αβ expression of APPL itself ( Figure S2B ) . Taken together these data indicate that Abl is the effector of APPL required for the β-lobe growth . Next , we further characterized the downstream pathway involved . It has been recently shown that Abl phosphorylates Disheveled ( Dsh ) , a core intracellular component of the Wnt pathway , on the Tyrosine 473 . This modification is required for the efficient activation of the PCP signaling pathway in epithelial cells [26] . Interestingly , in the nervous system the Wnt-PCP pathway is required for robust axonal outgrowth both in Drosophila [27] and mouse [28] , [29] . More recently , several PCP pathway components , like the Wnt receptor Frizzled ( Fz ) , Flamingo ( Fmi ) , Strabismus ( Stbm or Vang ) , and Dsh , have been shown to play a role in the correct targeting and bifurcation of MB axons [4] , [30] , [31] . Indeed , we observe that flies harboring a PCP-specific mutation in Dsh ( dsh1 ) [32] show the same MB developmental defects observed in Appl−/− flies ( Figure 4A ) . Together , these observations prompted us to speculate that APPL acts to facilitate Wnt-PCP pathway activation during MB development by mediating Dsh phosphorylation by Abl . To verify this hypothesis we tested if the phosphorylation of Dsh on Y473 is required for MB development . We analyzed dsh1 flies harboring one of two genomic rescue constructs: a wild-type construct ( dsh-DshGFP-wt ) or a Tyrosine 473 phospho-mutant construct ( dsh-DshGFP-Y473F ) . Whereas the restoration of wild-type Dsh fully rescues the dsh1 MB phenotype ( Figures 4B and S4A ) , DshY473F completely fails to do so ( Figures 4C and S4A ) . To exclude that DshY473F failure to rescue the phenotype is due to a perturbation in the expression pattern resulting from the point mutation , we performed anti-GFP staining on adult brains of both transgenic lines . As shown in Figure 4D and 4E , both wild type and mutant Dsh are expressed in the MB lobes . These results clearly indicate that Abl phosphorylation of Dsh on Tyrosine 473 and the subsequent activation of Wnt-PCP signaling are required for the β-lobe growth . Collectively , the data suggest the exciting possibility that APPL may be a neuronal-specific component of the Wnt-PCP pathway . To address this issue , we first asked if APPL interacts genetically with core members of the Wnt-PCP pathway like the classical Wnt-PCP receptor Fz and the canonical Wnt-PCP protein Van Gogh/Strabismus ( Vang/Stbm ) . We first analyzed the β-lobe of Appl−/−; Fz−/+ flies . Reduction of Fz in the APPL null background increases the frequency of the β lobe loss up to 21% , whereas no phenotype is observed in control siblings ( Figures 5B , E and S5A ) . This interaction is specific to the MB because expression of a dominant negative form of Fz ( Fz-DN ) in Appl−/− αβ neurons yields similar results ( Figures 5C , 5E and S5A ) . In both experiments described , the increase in β-lobe loss is relatively mild compared to the dramatic increase in β-lobe loss due to APPL-Abl epistasis for example , suggesting that APPL and Fz may act together for Wnt-PCP activation . To clarify this , we tested if inhibition of Fz alone is sufficient to induce the β phenotype . Overexpression of Fz-DN in αβ neurons of wild-type flies did not cause any morphological defects ( Figure S5A and S5B ) . These data were further confirmed by the analysis of Fz mutant αβ clones of different sizes . None of the analyzed MB clones showed morphologically aberrant axons ( Figure S5C ) . To rule out compensation by Fz2 , we examined Fz2 expression in the brain and found that it is not detectable in MB ( unpublished data ) . Furthermore , MARCM clones null for Fz2 alone or Fz and Fz2 together show no aberrant morphology ( Figure S5D and S5E ) . Therefore , APPL function is a critical determinant of the role of PCP in the outgrowth of MB β axons . To further ascertain the interaction with the Wnt-PCP pathway , we analyzed if APPL interacts with the Wnt-PCP four-pass transmembrane protein Vang/Stbm . Reduction of Van Gogh in the Appl null background ( Appl−/−;vang−/+ ) increases the frequency of the β-lobe loss phenotype to 33% ( Figures 5D , E and S5A ) , whereas no phenotype is observed in control siblings . APPL is also expressed in the developing fly retina ( Figure S5F ) , where the PCP pathway regulates the polarity of photoreceptor cells . However , we did not observe defects in photoreceptor polarity ( Figure S5G–I ) , suggesting that the role of APPL in Wnt-PCP signaling is specific to axonal outgrowth . Together , the data above identify APPL as the first neuronal-specific modulator of the Wnt-PCP pathway's role in axonal outgrowth . Next , we analyzed if the expression pattern of Vang and APPL overlaps during MB development . For this purpose , we used a line that expresses a YFP tagged form of Vang under the control of the Actin promoter . As shown in Figure 5F , during the development of the β lobe both APPL and Vang are expressed at a high level in the growing axons . Interestingly , in adult stage , APPL expression is reduced in the rest of the brain and enriched in the αβ neurons while Vang levels are strongly reduced in these axons ( Figure 5G ) . Moreover , in the developing fly retina , APPL and Vang do not colocalize and are found in juxtaposed domains ( Figure S5L ) . Taken together these results suggest that both APPL and Vang are present in developing αβ axons where their genetic interaction is required for the correct development of the β axons . On the contrary , the two proteins are expressed in different compartments in the fly retina where APPL function is not required for PCP activity . Finally , to confirm that PCP signaling is indeed positively modulated by APPL and that the activation of the signaling is required for the β-lobe growth , we performed rescue experiments with Dsh . As shown in Figure 5F , overexpression of Dsh in the Appl−/− background strongly reduces ( 7% ) the β-lobe loss but does not fully rescue the phenotype . This result indicates that the phosphorylation of Dsh by Abelson is the limiting step in the activation of PCP signaling; increasing the amount of Dsh present in the neurons improves the phenotype , but probably the endogenous Abelson is not sufficient to phosphorylate the whole pool of Dsh . To overcome this problem we decided to enhance the activation of PCP signaling by overexpressing Wnt5 in the Appl−/− background . Interestingly , overexpression of Wnt5 significantly rescues the β-lobe loss ( Figure 5H ) , indicating that the PCP signaling activation is required for the development of the β lobe and is reduced in absence of APPL . The previously described results raise two important questions . First , is the interaction between APPL and the Wnt-PCP pathway conserved in mammalian APP proteins ? Second , if so , do the genetic interactions observed in Drosophila reflect a biochemical association of APPL/APP with the Wnt-PCP receptors ? To address these issues , we first investigated if mouse APP proteins mediate the phosphorylation of mouse Disheveled ( Dvl ) in response to the Wnt-PCP ligand Wnt5a . To this end , we analyzed Dvl phosphorylation in response to Wnt5a treatment in wild-type versus APP/APLP2 double knock-out mouse embryonic fibroblast ( dKO MEFs ) . In WT MEFs , Dvl2 phosphorylation increases dramatically upon treatment with Wnt5a . In contrast , Dvl2 in dKO MEFs completely fails to respond to Wnt5a treatment ( Figure 6A ) . The effect on the activation of Dvl2 is a direct consequence of APP loss because upon reintroduction of APP cDNA Dvl2 phosphorylation is restored ( Figure 6A ) . Next , we tested if APPL and APP interacts with core Wnt-PCP receptor proteins . In particular , we performed co-immunoprecipitation ( Co-IP ) analyses of tagged proteins expressed in HEK-293T cells . As shown in Figures 6B and S6B , APPL immunoprecipitates Vang when the two proteins are co-expressed in the same cells . Drosophila APPL immunoprecipitates human Van Gogh 2 ( Vangl2 ) ( Figures 6C and S6C ) . Importantly , this multiprotein complex can only be detected when the proteins are expressed in the same cells , but not when lysates from separately expressing cells are mixed ( Figure S6E ) . This observation also accounts for the absence of rescue observed when a form of APPL lacking the C terminal is expressed in the Appl−/− animals ( Figure 2H ) . Similarly , the membrane tethered C-terminus of human APP ( APP-C99 ) immunoprecipitates Vangl2 ( Figures 6D and S6D ) . Moreover , we tested if APPL also immunoprecipitates other PCP receptors like Fz . As shown in Figures 6E and S6F , APPL immunoprecipitates Fz , suggesting that the core PCP proteins and APPL might form a multiprotein complex on the membrane , responsible for the efficient activation of the pathway . Similarly , the membrane-tethered C-terminus of human APP ( APP-C99 ) immunoprecipitates human Fzd5 ( Figure 6F ) .
AD is a neurodegenerative disorder characterized by progressive loss of neurons in specific regions of the brain that correlates with progressive impairment of higher cognitive functions . A growing body of evidence identifies the APP and its metabolite the Aβ peptide as main players in the pathogenesis of AD . In particular , the accumulation of Aβ peptides in the brain seems to be the trigger of the pathological cascade that eventually results in neuronal loss and degeneration [33] . Despite efforts to characterize the molecular mechanisms underlying Aβ's toxic function , it is still not clear what triggers the accumulation of the peptide and how this is correlated with the pathogenesis of the disease and the dementia . In fact , most of the work done to unveil the pathogenesis of the disease has focused on the analysis of Aβ-peptide and the search for its receptors and downstream effectors . Even though the numerous in vitro studies performed in cell culture identified several molecules that interact with Aβ peptide , the in vivo biological relevance of these interactions remains to be clarified . The amyloid cascade hypothesis has also dominated the search for AD treatments , but the promising molecular candidates developed to modulate the Aβ peptide and reached clinical trials failed [34] , [35] . Finally , over the last few years many studies indicated that there is no linear correlation between the accumulation of the peptide and the cognitive decline , leading to a revision of the amyloidogenic hypothesis . Taken together , these observations suggest that the accumulation of the peptide is not the only cause of the pathology and that other factors are involved . Interestingly , under physiological conditions APP is mainly found in its uncleaved or α-cleaved form , suggesting that the shift towards amyloidogenic processing not only increases the production of Aβ peptide but also depletes the pool of APP that undergoes non-amyloidogenic processing , with hitherto unknown consequences . It is therefore of paramount importance to understand the physiological role of APP and how perturbing this role could contribute to the pathogenesis of the disease . An important contribution to the study of the function of a protein comes from the analysis of the knock-out ( KO ) animals . In the case of APP , several KO models have been generated and analyzed in detail both from the morphological and behavioral point of view [13] , [36]–[38] . Despite these efforts , the normal physiological function of APP in vivo in the nervous system remains largely elusive and highly controversial . This is due to the lack of consensus over the neuronal phenotypes in null mutant animals and the mechanism of action in vivo . The data collected by different labs confirmed the involvement of APPs in development and function of the nervous system , but these studies do not provide an in-depth analysis of the development of the brain during the pre-natal stages or the molecular mechanism underlying APPs' putative functions . We therefore took advantage of Drosophila melanogaster to further analyze the consequence of loss of APP Like ( APPL ) during brain development . In the present study we demonstrate that APPL is involved in brain development of Drosophila melanogaster , particularly in the Mushroom Body ( MB ) neurons . We show that APPL is required for the development of αβ neurons . In Appl−/− flies , MB neurons fail to project the α lobe in 14% of the cases and the β-lobe in 12% of the cases ( Figure 1 ) . Further analysis of the phenotype reveals that APPL is required cell-autonomously for the development of the β lobe and non-cell autonomously for the development of the α lobe . In fact , single cell Appl−/− clones display only β-lobe loss and no α loss . The re-introduction of a full-length , membrane-tethered form of APPL , but not a soluble form , rescues β-lobe loss ( Figure 2 ) . This is of particular interest because it confirms that , similar to mammalian APPs , the physiological role of APPL is mediated both by its full-length form , required in the neurons to achieve the correct β-lobe pattern , and by its soluble form ( sAPPL ) that regulates the extension of the α lobe . Moreover , the rescue data indicate that , at least in this context , the function of sAPPL is mediated not by homo-dimerization with the full-length form but by some other receptor , hitherto unknown . Further experiments are required to clarify the sAPPL non-cell autonomous effect , but we hypothesize that it might be involved in modulating signaling mediated by the cells that surround the MB axons . Taken together , the analysis of the Appl−/− animals confirmed the important role of APPs during brain development but reinforced the idea that the phenotypes are present with incomplete penetrance and might be subtle . It would therefore be of interest to analyze the phenotype of the KO mice in greater detail and , in particular , to better characterize the APP's downstream pathway leading to these defects . Moreover , the results described clearly support a model of APPL as a novel , neuronal-specific positive modulator of the Wnt-PCP pathway ( Figure 4 ) . The PCP pathway was initially described because of its role in tissue polarity establishment and , in particular , of its regulation of cell orientation in plane of an epithelium . Among the different processes regulated by PCP signaling , we are interested in axon growth and guidance . It has been described that mice null for Fzd3/Ceslr3−/− genes show severe defects in several major axon tracts like thalamocortical , corticothalamic , and nigrostriatal tracts , defects of the anterior commissure , and similarly to APP KO mice , the variable loss of the corpus callosum [5] , [39] . The molecular mechanism underlying the function of PCP-signaling in regulating tissue polarity has been broadly studied . The current model suggests that , upon polarized expression of the different core proteins , Dsh is recruited to the membrane via Fz and leads to the activation of a cascade of small GTPases finally resulting in cytoskeleton rearrangements . In the case of regulation of axon growth and guidance , it is less clear how the signaling is regulated and transmitted to the cytoskeleton . A recent publication suggested that during axon growth the transmembrane PCP receptor-like Vang and Fzd are localized at the growth cone area on the tip of the fillopodia , thus suggesting that in this context the asymmetric localization is not needed [28] . Furthermore , Dsh needs to relocalize from the cytoplasm to the membrane to ensure the proper activation of PCP signaling , and this is dependent on its phosphorylation status . Singh and colleagues showed that Abelson is one kinase responsible for this modification , but the receptor upstream of the kinase was not identified [26] . Based on the evidence we generated , we propose that APPL is a novel regulator of Wnt-PCP pathway involved in axon growth and guidance ( Figure 7 ) . This is of interest because while the PCP core proteins are ubiquitously expressed , APPL is restricted to the nervous system , suggesting that it could be the first described tissue-specific modulator of the pathway . Mechanistically , we propose that APPL-Abl complex modulates Dsh via dual protein-protein interactions . First , Abl might have an intrinsic affinity for its substrate Dsh [26] . Secondly , this interaction is strengthened or stabilized by the inclusion of APPL in a PCP receptor complex . This dual affinity complex leads to increased PCP signaling efficiency at the developing growth cone . Both biochemical and physiological data show that this function is highly conserved in mammalian APP , suggesting that it may play a similar role in the mammalian brain . The canonical-Wnt signaling pathway has already been connected to AD pathogenesis because of its link to the tau-kinase GSK-3β . Interestingly , no clear link between the Wnt-PCP pathway and this neurodegenerative disorder has been made . Previous reports [27] , [28] show that , in flies and mice , Jun N-terminal Kinase ( JNK ) is the final effector of PCP in axon outgrowth and JNK was shown to be required for the effect of APP overexpression in the fly [25] , [40] . Interestingly , JNK signaling has also been linked to the neuronal loss observed in AD [41] . It is therefore worth investigating whether the physiological function of APP as a neuronal PCP modulator explains the JNK-AD connection .
Drosophila stocks used include Appld w* , Appld , FRT19A w* , elavC155 , hsFLP , w*;UAS-mCD8::GFP . , UAS-lacZ/CyO;tubP-GAL80 , FRT2A/TM6 , Tb , Hu , hsFlp , UAS-CD8-GFP;;FRT2A , tubGal80/TM3;OK107 , hsFlp , UAS-CD8-GFP; FRT2A , tubGal80/TM3;OK107 , Flp122; sp/CyO;Fz p21 , ri , FRT2A/TM2 , fz2C1ri , FRT2A/TM3 , Sb , yw , hsflip;Fz1H51Fz2C1riFRT2A/TM2 , UAS-Fz-DN/CyO;P247Gal4/TM6c , UAS-Abl-KD/CyO;P247Gal . Abl4 kar1 red1 e1/TM6B , Tb1 , w*;UAS-Abl/CyO;P247 , w; fz [KD]/TM3 , Sb , Vangstbm-6 , w;201Y , UAS-GFP , FRT19A;ry50 , FRT19A , tub-Gal80 , hsFLP/FM7;UAS-CD8-GFP/CyO;OK107 , UAS-Appl/CyO;P247Gal4 , UAS-sAppl/Cyo;P247Gal4 , w1 , dsh:1 , dsh>Dsh-GFP ( J7 ) /TM6 . dshV26 , dsh>Dsh-GFP; dsh>Dsh-GFP Y473F , and Act-stbm-EYFP/TM3 . APPL ( FBgn0000108 ) , fz ( FBgn0001085 ) , fz2 ( FBgn0016797 ) , Fzd5 ( NP_003459 . 2 ) , dsh ( FBgn0000499 ) , dvl1 ( AAB65242 . 1 ) , dvl2 ( AAB65243 . 1 ) , Vang ( FBgn0015838 ) , Vagl2 ( NP_065068 . 1 ) , and Abl ( FBgn0000017 ) . Larval , pupal , or adult brains were dissected in phosphate buffered saline ( PBS ) and fixed in 3 . 7% formaldehyde in PBT ( PBS+ Triton ×100 0 . 1% ) for 15 min . The samples were subsequently rinsed three times in PBT and blocked in PAX-DG for 1 h . Following these steps , the brains were incubated with the primary antibody diluted in PAX-DG overnight at 4°C . This incubation was followed by three washes with PBT and a subsequent incubation with the appropriate fluorescent secondary antibodies for 2 h at RT . After three rinses in PBT , the brains were put in 50% Glycerol diluted in PBS and then mounted in Vectashield ( Vector Labs ) mounting medium . The following antibodies were used: rabbit anti-GFP ( Invitrogen , 1∶1 , 000 ) , mouse anti-FasII ( Hybridoma Bank , 1∶50 ) , rabbit anti-APP-C-term ( kind gift of Bart de Strooper lab , 1∶5 , 000 ) , and anti-Phalloidin TRITC ( 1∶1 , 000 ) . The mounted brains were imaged either on a LEICA DM 6000 CS microscope coupled to a LEICA CTR 6500 confocal system or on a Nikon A1-R confocal ( Nikon ) mounted on a Nikon Ti-2000 inverted microscope ( Nikon ) and equipped with 405 , 488 , 561 , and 639 nm lasers from Melles Griot . The pictures were then processed using ImageJ and Adobe Photoshop . Crosses were set up at 25°C and transferred every day . We transferred 0 to 24 pupae in a fresh vial , and they were heath shocked for 45′ at 37°C and shifted back at 25°C until eclosion . The morphology of the MB clones was analyzed in flies 0–7 d old . WT MEFs , APP/APLP2 double KO MEFs , APP/APLP2 double KO+hAPP , and HEK-293T cells were propagated in DMEM , 10% FCS , 2 mM L-glutamine , 50 units/ml penicillin , 50 units/ml streptomycin . MEFs ( 200 , 000 cells per well ) were seeded in 24-well plates for biochemical analyses . MEFs were treated 2 d after seeding with rmWnt5a ( R&D Systems ) for 2 h . Cells were harvested for immunoblotting by direct lysis in 1× Laemmli buffer followed by boiling at 95°C for 5 min . Control stimulations were done with 0 . 1% BSA in PBS . Protein from total cell lysates/samples was resolved in 10% polyacrylamide gels ( SDS-PAGE ) under denaturing conditions and then transferred to nitrocellulose membranes . The blots were probed using polyclonal anti-FLAG M2 ( F1804 , Sigma-Aldrich 1∶1 , 000 ) , monoclonal anti-Myc ( M4439 , Sigma-Aldrich 1∶1 , 000 ) , anti-Dvl1 ( sc-8025 , Santa Cruz Biotechnologies , 1∶1 , 000 ) , anti-Dvl2 ( #3224 , Cell Signaling Technologies , 1∶1 , 000 ) , anti-V5 ( R960-25 , Invitrogen , 1∶1 , 000 ) , anti-HA ( HA . 11 , MMS-101R , Covance , 1∶2 , 000 ) , and anti-beta-actin ( sc-1615 , Santa Cruz Biotechnology , 1∶2 , 000 ) . Bands were visualized using anti-IgG HRP-conjugated secondary antibodies , and the ECL Western Blotting Detection System ( GE Healthcare , UK ) . For the Co-IP of Drosophila proteins , pCDNA3-APPL-FLAG and pCDNA3-Vang-Myc were transiently transfected in HEK293T cells ( 4 . 5×106 cells per 10 cm dish ) using Fugene HD ( Roche ) . After 3 d , cells were collected in Lysis Buffer ( 150 mM NaCl , 50 mM Tris/HCl pH 7 . 5 , 10% glycerol , 0 . 4% Nonidet P-40 ) and cleared with Dynabeads M-270 epoxy ( Invitrogen ) for 45′ at 4°C . After the clearing , lysates ( half volume ) were incubated with anti-FLAG covalently conjugated to Dynabeads M-270 ( pre-saturated with BSA ) for 1 h at 4°C . Beads were then washed , and bound proteins were resuspended in 6× Laemmli and subjected to SDS-PAGE followed by Western blot analysis . For the Co-IP of Drosophila and human proteins , HEK293 cells grown at 50% confluency on 10-cm plates were transfected with 6 µg of each plasmid . After 2 d , cells were lysed for 15 min in 1 ml of lysis buffer ( [0 mM Tris buffer pH 7 . 4 , 150 mM NaCl , 1 mM EDTA , 0 . 5% NP40 supplemented with 1 mM DTT and protease inhibitor cocktail ( Roche , cat . no . 11836145001 ) ] . Lysates were centrifuged at 13 , 200× g for 20 min at 4°C , supernatants were collected , and 0 . 4 ml of the supernatant was incubated with 1 µg of indicated immunoprecipitating antibody for 1 h at 4°C . Immunoprecipitates were collected on Protein G sepharose beads by overnight rotation , washed four times with lysis buffer , resuspended in 2× Laemmli sample buffer , and subjected to SDS-PAGE followed by Western blot analysis . The antibodies used for immunoprecipitation include FLAG M2 ( F1804 Sigma-Aldrich ) , anti-HA ( ab9110; Abcam ) , anti-Myc ( M4439 , Sigma-Aldrich ) , and anti-V5 ( R960-25 , Invitrogen ) . | Wnt Planar Cell Polarity ( PCP ) signaling is a universal regulator of polarity in epithelial cells , but in neurons it regulates axon outgrowth , suggesting the existence of axonal modulators of Wnt-PCP activity . The Amyloid Precursor Proteins ( APPs ) are intensely investigated because of their link to Alzheimer's disease ( AD ) . APP's in vivo function in the brain and the mechanisms underlying it remain unclear and controversial . In the present work we investigate the role of the Drosophila neuron-specific APP homologue , called APPL , during brain development . We find that APPL is required for the development of αβ neurons in the mushroom body , a structure critical for learning and memory . We find that APPL is a modulator of the Wnt-PCP pathway required for axonal outgrowth , but not for cell polarity . Molecularly , both human APP and fly APPL are found in membrane complexes with PCP receptors . Moreover , we show that APPL regulates PCP pathway activation through its downstream effector Abelson kinase ( Abl ) , which modulates the phosphorylation of the Wnt adaptor protein Dishevelled ( Dsh ) and the subsequent activation of Wnt-PCP signaling . Taken together our data suggest that APPL is the first example of a neuron-specific modulator of the Wnt-PCP pathway . | [
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] | 2013 | The Drosophila Homologue of the Amyloid Precursor Protein Is a Conserved Modulator of Wnt PCP Signaling |
The increasing knowledge on the functional relevance of endogenous small RNAs ( esRNAs ) as riboregulators has stimulated the identification and characterization of these molecules in numerous eukaryotes . In the basal fungus Mucor circinelloides , an emerging opportunistic human pathogen , esRNAs that regulate the expression of many protein coding genes have been described . These esRNAs share common machinery for their biogenesis consisting of an RNase III endonuclease Dicer , a single Argonaute protein and two RNA-dependent RNA polymerases . We show in this study that , besides participating in this canonical dicer-dependent RNA interference ( RNAi ) pathway , the rdrp genes are involved in a novel dicer-independent degradation process of endogenous mRNAs . The analysis of esRNAs accumulated in wild type and silencing mutants demonstrates that this new rdrp-dependent dicer-independent regulatory pathway , which does not produce sRNA molecules of discrete sizes , controls the expression of target genes promoting the specific degradation of mRNAs by a previously unknown RNase . This pathway mainly regulates conserved genes involved in metabolism and cellular processes and signaling , such as those required for heme biosynthesis , and controls responses to specific environmental signals . Searching the Mucor genome for candidate RNases to participate in this pathway , and functional analysis of the corresponding knockout mutants , identified a new protein , R3B2 . This RNase III-like protein presents unique domain architecture , it is specifically found in basal fungi and , besides its relevant role in the rdrp-dependent dicer-independent pathway , it is also involved in the canonical dicer-dependent RNAi pathway , highlighting its crucial role in the biogenesis and function of regulatory esRNAs . The involvement of RdRPs in RNA degradation could represent the first evolutionary step towards the development of an RNAi mechanism and constitutes a genetic link between mRNA degradation and post-transcriptional gene silencing .
Since the discovery of RNAi in Caenorhabditis elegans [1] , our knowledge on the crucial role of endogenous small RNA ( esRNA ) as riboregulators has increased dramatically . Multiple classes of esRNAs , including microRNAs ( miRNAs ) and small interfering RNAs ( siRNAs ) , have been identified both in metazoans and lower eukaryotic organisms [2–5] . Biogenesis of most of those esRNAs shares a minimal common machinery consisting in an RNase III endonuclease Dicer that processes double-stranded RNA ( dsRNA ) precursors into small RNA ( sRNA ) molecules , and an Argonaute endonuclease that binds sRNAs and uses them as a guide to identify and cleave complementary target mRNA . Additionally , some RNAi-competent organisms , including plants , nematodes and fungi , require RNA-dependent RNA polymerases to generate dsRNA from single-stranded RNA inducers or to amplify siRNA signals . Besides this canonical pathway , different non-canonical alternatives in which Dicer proteins do not participate have been described to be responsible for the biogenesis of specific esRNAs , not only the well-known Piwi-interacting RNAs ( piRNAs ) but also miRNAs and miRNA-like ( milRNA ) molecules [6–8] . In these cases , the catalytic activity of Argonaute family proteins and the trimming activity of specific exonucleases are required for the production of mature esRNAs . However , the majority of the non-canonical miRNA molecules are poorly conserved and low in abundance , which shed doubts on their functionality . In filamentous fungi , different classes of regulatory esRNAs produced by canonical and non-canonical pathways have been described , although information on their functional roles is very scarce [3 , 9] . The basal fungus Mucor circinelloides , an emerging opportunistic human pathogen of the order mucorales [10] , is a great model to investigate the functional roles of esRNAs , as shown by the finding of esRNAs derived from exons , named ex-siRNAs , that regulate the expression of the protein coding genes from which they derive [11] . Depending on the proteins of the RNAi machinery required for their biogenesis , these ex-siRNAs can be classified into four different classes , all of which are dicer-dependent , since they require one of the M . circinelloides Dicer-like ( Dcl ) proteins for their biogenesis . The main class of the dicer-dependent ex-siRNAs ( class II ) requires Dcl-2 [12] and RdRP-1 [13] , an RNA-dependent RNA polymerase essential for activation of silencing with single stranded RNA molecules by producing antisense RNA transcripts . Only a small group of dcl-2-dependent ex-siRNAs ( class I ) does not require RdRP-1 for their biogenesis , but most of them require RdRP-2 [13] , which is involved in the amplification process that produce secondary siRNAs . These two classes are specifically bound to Ago-1 , one of the three M . circinelloides Argonaute proteins [14] and are accumulated at a reduced extent in the ago-1- mutants , suggesting that they require Ago-1 for their biogenesis/stability . Class III corresponds to ex-siRNAs that can be generated by either Dcl-1 or Dcl-2 and require both RdRP-1 and RdRP-2 , and class IV is a tiny group of ex-siRNAs that depends on dcl-1 [15] but not on dcl-2 [11] . Classes III and IV are not found among Ago-1-bound ex-siRNAs , which suggests that either they do not act through a canonical pathway or they are bound to a different Ago protein [14] . The role of the dicer-dependent ex-siRNAs in the regulation of endogenous genes has been confirmed experimentally , since the reduction of specific ex-siRNAs in mutants affected in the RNAi machinery is associated with an increase in mRNA accumulation of the corresponding target protein coding genes [11 , 14] . In fact , RNA-seq analysis of M . circinelloides RNAi mutants identified hundreds of genes that showed differential mRNA expression compared to the wild type strain [16] . Detailed analysis of the differentially expressed genes allowed the identification of candidates that may be responsible for the phenotypes shown by mutants affected in the RNAi machinery , such as defects in vegetative growth , hyphal morphology and sporulation efficiency , or even differential response to nutritional stress [16 , 17] . Most of these phenotypes are related to developmental responses to endogenous and environmental signals , suggesting that the RNAi machinery modulates the expression of genes involved in these responses . This is supported by the ability of M . circinelloides to adapt to the environment through a new epigenetic mechanism based on an RNAi-mediated pathway [18] , pointing out the relevance of the RNAi mechanism in the control of phenotypic plasticity . Previous analyses of M . circinelloides esRNAs were exclusively focused on those produced through dicer-dependent pathways , since only esRNAs that showed a significant reduction in normalized reads in any of the dcl- mutants compared to wild type were considered [11 , 14] . On the other hand , comparisons of the phenotypes shown by the different RNAi mutants revealed that several phenotypes were shared by the rdrp-1- and rdrp-2- mutants but not the dcl- mutants [16] . We analyze here the complete esRNA content of the wild type , dcl- and rdrp- strains and identify a new rdrp-dependent dicer-independent esRNA class derived from exons . Analysis of these sRNAs shows that they are produced by a degradation pathway in which the RdRP-1 and/or RdRP-2 proteins mark specific transcripts to be degraded by a previously unknown RNase . Search of the Mucor genome for candidate RNases involved in this rdrp-dependent dicer-independent RNA degradation pathway and functional analysis of the corresponding genes identified a new protein , named R3B2 . This RNase III-like protein presents a unique domain architecture and it is also implicated in the canonical dicer-dependent RNAi pathway , highlighting the crucial role of the R3B2 protein in the biogenesis and function of regulatory esRNAs . Phenotypic analysis of the r3b2- mutant and its comparison with other silencing mutants suggests that the rdrp-dependent dicer-independent degradation pathway regulates cellular responses to specific environmental signals .
We have previously demonstrated the existence of different classes of endogenous siRNAs ( esRNAs ) in M . circinelloides produced with the involvement of a Dicer activity [11] . The ago-1 , rdrp-1 and , at a minor extent , rdrp-2 genes are also required , in different combinations , for the production of those esRNAs [11 , 14] . Many of these esRNAs derive from exons ( ex-siRNAs ) and regulate the expression of the protein coding genes from which they are produced [11 , 14] . Deep sequencing of short RNAs ( 18–25nt ) in the M . circinelloides wild type , dicer- and rdrp- strains identified , besides the mentioned dicer-dependent esRNAs , new loci that produced esRNAs by a dicer-independent but rdrp-1- and/or rdrp-2-dependent mechanism . In these analyses , loci were defined by reads that mapped to the genome in close proximity ( ≤ 200 bp ) to each other ( as previously described in [11] ) . The rdrp-dependent dicer-independent sRNA loci were identified as those that showed at least a fourfold decrease in normalized sRNA reads in rdrp-1- or rdrp-2- mutants compared to wild type , with no significant change between wild-type and any of the dicer- mutants . We identified a total of 1523 rdrp-dependent loci , among which 611 were dicer-independent , and they were grouped based on the annotation of the locus as intergenic , transposon or exonic loci ( Table 1 and S1 Fig ) . Whereas none or a small number of transposon and intergenic loci were rdrp-dependent dicer-independent , as many as 531 exonic loci corresponded to this category . These loci produced sRNAs that showed a very strong strand bias , almost all of them being exclusively sense to the mRNAs ( Fig 1A , S1 Table and S2 Fig ) , but they did not show enrichment for a specific size ( Fig 1B ) . This suggests these sRNAs are not produced by a canonical RNA silencing mechanism , since the majority of the known M . circinelloides ex-siRNAs are dicer-dependent and derive from exons producing a mixed sense and antisense ex-siRNAs mainly 23–24 nt long [11] . Most loci of the rdrp-dependent dicer-independent class required rdrp-1 or both rdrp-1 and rdrp-2 genes for production of esRNAs ( S1 Table and S1 Fig ) . Thus , despite the prominent role of the rdrp-2 gene in transgene-induced silencing , rdrp-1 seems to play a more relevant role in the production of endogenous sRNAs , both in a dicer-dependent [11] and in a dicer-independent pathway ( Table 1 ) . Accumulation of sRNAs from some of those rdrp-dependent dicer-independent loci was analyzed by Northern blot hybridization to validate the sequencing data . However , contrary to the dicer-dependent classes of esRNAs [11 , 14] , we could not detect any sRNAs similar to those in the dicer-independent classes , neither with sense-specific or antisense-specific riboprobes ( Figs 1C and S3 ) . These sRNAs were either not detectable or the probes detected a smear between 15–2000-nt but not discrete bands with sizes between 20–25nt . Thus , we concluded that reads from these loci are most likely small degradation products of mRNAs . According to this , these rdrp-dependent dicer-independent sRNA molecules showed a random spread of size distribution ( Fig 1B ) , different from the dicer-dependent classes that produced predominantly 23–24 nt sRNAs [11] . We analyzed the nucleotide distribution in each position of the rdrp-dependent dicer-independent sRNA degradation products and found a very strong bias for uracil in the penultimate position for all sizes of sRNAs ( 18–24 nt; Figs 1D and S4 ) . This bias for uracil in the penultimate position , whereas it is under-represented in the rest of the sRNAs , suggests that the generation of this class of sRNAs is not random . In fact , if we extend the sequence upstream and downstream of the sRNAs , an over-representation of uracil can be detected 2 nt upstream of the sRNA for any size analyzed ( S5 Fig ) , suggesting that an RNase may exist in M . circinelloides that preferentially cleaves mRNAs two nucleotides downstream of any uracil . This cleavage preference would produce fragments of various sizes resulting in the smears observed in the Northern blot analyses ( Figs 1C and S3 ) . However , when the distance between two uracils is 18–24 nucleotides , the cleavage products would be present in the sRNA library , as the libraries were generated from any 18–24-mer RNA molecules that can be ligated to adapters . Besides the preference for uracil in the penultimate position , sequence logos also showed a biased purine/pyrimidine distribution for all sizes of sRNA degradation products , which showed A/G enrichment throughout their whole sequence . This bias is not specific to Mucor rdrp-dependent sRNAs , since it is has been also found in canonical ex-siRNAs [11] and the small RNA datasets of seven different plant species [19] . It has been suggested that the distorted purine pyrimidine ratio in cellular sRNA populations implies that cells selectively accumulates purine rich strands and eliminates the pyrimidine rich strands , although the molecular mechanism for this active strand selection is not known [19] . In agreement with the non-canonical nature of the rdrp-dependent dicer-independent sRNAs , they do not show the strong bias for uracil at the 5’ end shown by the canonical ex-siRNAs bound by M . circinelloides Ago-1 [11 , 14] . In fact , only eleven out of 531 sRNAs of the rdrp-dependent dicer-independent class were detected among those specifically bound to M . circinelloides Ago-1 ( S1 Table , [14] ) , suggesting that this sRNA class does not act through the canonical RNAi pathway . According to the nature of the rdrp-dependent dicer-independent RNA class , which was identified through sequencing small RNAs but corresponds to non-random degradation products of mRNAs that can have any size and are generated by a rdrp-dependent mechanism , we named those RNA molecules as rdrp-dependent degraded RNA ( rdRNA ) . Although the above results indicate that the rdrp-dependent dicer-independent rdRNAs are not "classical sRNAs" ( i . e . they are not 20–24-mer RNA molecules generated by dicer ) , the sequencing data suggested that they are not non-specific degradation products , since accumulation of these rdRNAs was significantly reduced in the rdrp- mutants relative to the wild type and dicer- strains ( S1 Table ) . This fact raised the possibility that this new pathway could also regulate the level of mRNAs . Therefore , we analyzed mRNA accumulation during the exponential growth from representative loci in the wild type , rdrp- and dicer- mutants by Northern blot analysis of RNA samples isolated from cultures grown 24 hours in liquid MMC medium . Three different rdRNA-producing exons ( P1 to P3 ) were selected based on their different numbers of normalized sRNA reads in the wild type strain , thus representing the variability found in the sRNA transcriptomic analysis ( Fig 2C ) . The accumulation of all tested mRNAs increased two fold , as an average , in the rdrp- mutant strains compared to the wild type and dicer- mutants when growing exponentially ( Fig 2A and 2B , lanes 1–4 ) . This demonstrated a clear trend of the reverse relationship between mRNAs and small RNAs accumulation of the selected reporter genes , the increase in mRNA levels being associated with the reduction in the normalized reads in the rdrp- mutants relative to the wild type and dicer- mutant strains ( Fig 2C ) . A linear correlation between sRNA decrease and mRNA increase is not expected , given the different methods used for detection of mRNAs and sRNAs . sRNA read numbers are affected by the length of the mRNA , uracil content and distribution and the ligation bias [20] , since only degradation fragments with a distance between two uracil of 18–24 nt would be able to be included in the sRNA libraries . However , if transcript accumulation of different genes is regulated by the same mechanism , it is expected that alteration of this mechanism by mutation provokes a similar effect in all those genes . The same results were obtained at stationary growth conditions , when cultures were grown for 48 hours in liquid MMC medium ( S6A and S6B Fig , lanes 1–4 ) . These results confirm the existence of a degradation pathway in M . circinelloides that regulates mRNA levels and requires RdRP-1 and/or RdRP-2 proteins but not Dcl-1 and Dcl-2 . To identify the processes regulated by this new pathway , we performed an Eukaryotic Orthologous Group ( KOG ) enrichment analysis of the rdRNA-producing exons , according to the whole-genome annotation of M . circinelloides , whose version 2 . 0 is now available ( http://genome . jgi-psf . org/Mucci2/Mucci2 . home . html ) ( Figs 3 and 4 , S1 Table ) . Although most of the KOG classes were similarly represented both among genes regulated by the non-canonical pathway and the total genome ( Fig 3 ) , we observed a significant enrichment in the regulated genes for those involved in coenzyme transport and metabolism , cytoskeleton , inorganic ion transport and metabolism , intracellular trafficking and secretion , and secondary metabolites biosynthesis , transport and catabolism . The most highly enriched class was the coenzyme transport and metabolism category , with 21 genes that account for 3 . 95% of the total number of regulated genes , compared to the 0 . 87% of these genes in the total genome ( Fig 3 ) . Twelve out of 21 genes of this class participate in heme B biosynthesis pathway or metabolism ( Fig 4A ) . Besides haemoglobin and myoglobin , hemes are also found in a number of other biological relevant hemoproteins , such as catalase , which is an essential enzyme for protecting the cell from oxidative damage . Also the gene coding for gamma-glutamylcysteine synthetase ( now glutamate cysteine-ligase , ID87510 ) , which controls the first and rate-limiting step in the biosynthesis of the cellular antioxidant glutathione , is included in this class , accumulating a significantly lesser amount of rdRNAs in the rdrp- mutants relative to the wild type ( Fig 4A ) . The differential expression of those genes in the rdrp- mutants could be responsible for the specific phenotypic alterations shown by those strains . In fact , the rdrp-1- and , at a lesser extent , rdrp-2- mutants are more resistant to oxidative stress than the wild type strain , as indicated by their ability to germinate in the presence of different concentrations of hydrogen peroxide ( Fig 4B ) . It is also worth noting the significant reduction in non-annotated genes among those regulated by the non-canonical pathway , with only 5 . 65% of non-annotated genes compared to 22 . 57% in the total genome ( S1 Table ) . In fact , almost 60% of the rdRNA-producing loci correspond to conserved genes involved in metabolism and cellular processes and signaling ( S7A Fig and S1 Table ) , which is significantly different to the functional annotation of genes regulated by the canonical dicer-dependent ex-siRNAs ( S7B Fig , [11] ) . Thus , the canonical and non-canonical RNA pathways seem to regulate different groups of genes . The proposed pathway for the production of the rdRNAs involves the participation of an RNase that degrades target mRNAs . To identify the implicated RNase , we attempted to knock out four genes for putative RNAses: 80729 , 136157 , 110239 , and 77996 . Those proteins were identified by performing an in silico analysis of the M . circinelloides genome ( v2 . 0 ) looking for annotated proteins containing RNase domains . Twenty-four proteins annotated under the endoribonuclease activity GO term ( GO 0004521 ) were identified . A careful analysis of those proteins allowed us to select several candidates to be investigated for their participation in the non-canonical silencing pathway . Briefly , we selected putative RNases without precise information on their molecular role or those with functional annotation that could be related with the non-canonical pathway ( S3 Table ) , discarding proteins with well-described ribonuclease activities , such as Dcl-1 , Dcl-2 , RNase P , RNase T2 , RNase A , RNase H and others . Thus , the four putative RNases mentioned above were investigated . Because protein 80729 contains an RNaseIII domain ( r3 ) , and two dsRNA binding domain ( b2 ) , we named the corresponding gene r3b2 . The selected genes and their adjacent sequences were amplified and knockout vectors were designed to disrupt each candidate gene by gene replacement ( see description of plasmids and generation of knockout mutants in S1 Supporting Information ) . The knockout vectors contained the pyrG gene as selectable marker flanked by adjacent sequences of the different RNase genes to allow homologous recombination . Disruption fragments were used to transform the MU402 strain , which is auxotrophic for uracil and leucine , and transformants that correctly integrated the knockout fragment were identified by PCR analysis ( S1 Supporting Information ) . After several vegetative cycles on selective media to increase the proportion of transformed nuclei , homokaryotic transformants were isolated and confirmed by Southern blot analysis ( S1 Supporting Information ) . Two out of three homokaryotic transformants obtained with the r3b2 disruption fragment were confirmed to contain a pyrG insertion of 3 . 4 kb replacing the r3b2 gene ( S8 Fig ) . One of them was named MU412 and was used as null mutant for this gene . Two out of four homokaryotic transformants obtained with the 136157 disruption fragment were confirmed as replacement mutants and were named MU450 and MU451 ( S9 Fig ) . However , it was impossible to obtain homokaryotic knockout mutants for genes 110239 and 77996 , as transformants containing the mutant alleles maintained wild type nuclei even after more than ten vegetative cycles on selective media ( S10 Fig and S1 Supporting Information ) . This suggests that those genes may play essential roles for the viability of M . circinelloides . To investigate the role of the candidate RNases in the non-canonical RNA degradation pathway we first analyzed the accumulation of mRNA of representative loci regulated by this pathway ( P1 to P3 , see above ) in the MU412 mutant ( r3b2- ) and in the null mutants for gene 136157 , MU450 and MU451 . All tested mRNAs up-regulated in the rdrp-1- and/or rdrp-2- mutants compared to the wild-type strain and dicer- mutant were also up-regulated in the r3b2- mutant , in samples isolated during both exponential ( Fig 2A , lane5 ) and stationary growth ( S6A Fig , lane 5 ) . In fact , the increase in mRNA accumulation of the target genes in the r3b2- mutant relative to the wild type strain was roughly two-fold , similarly to the rdrp-1- and rdrp-2- mutants ( Figs 2B and S6B ) , suggesting that the r3b2 gene encodes an RNase required for the degradation of specific mRNAs by the rdrp-dependent , dicer-independent non-canonical pathway . In contrast , mRNA accumulation of target genes in the MU450 and MU451 mutants , which are deficient in the putative RNase protein 136157 , was similar to the wild type and dicer- mutant ( S6C Fig ) , indicating that this RNase does not participate in the non-canonical RNA degradation pathway . Lack of homokaryotic null mutants for genes 110239 and 77996 precluded the analysis on their participation in the rdrp-dependent , dicer-independent pathway . The presumed role of the RNase III R3B2 in the generation of rdRNAs by the rdrp-dependent , dicer-independent non-canonical pathway was confirmed by deep sequencing of the sRNA content ( 18–25 nt ) in the r3b2- mutant and its comparison with the wild type strain ( accession number SRR1576768 ) . Almost 1 , 560 exonic loci were identified that showed a significant reduction in normalized sRNA reads in the r3b2- mutant relative to the wild type ( S5 Table ) . Those loci were selected as those showing at least a fourfold decrease in normalized reads in the r3b2- mutant compared to wild type , and a normalized abundance count of more than 50 in the wild type . All but one of the 531 rdRNA-producing loci were found among those significantly down-regulated in the r3b2- mutant , as shown in Tables 2 and S6 . In fact , the log2 fold change values in the r3b2- mutant relative to the wild type strain were even more significant than those of the rdrp- strains for most of the rdrp-dependent dicer-independent exonic loci , pointing to the relevant role of R3B2 in the biogenesis of rdRNAs . The lower rdRNA levels in the r3b2- mutant can be also seen in genes involved in heme biosynthesis , which show at least a 38-fold reduction in rdRNA accumulation relative to the wild type strain ( S11 Fig ) . These results demonstrate the participation of the R3B2 protein in the biogenesis of the rdrp-dependent dicer-independent rdRNAs , strongly suggesting that it is indeed the RNase involved in the degradation process of specific mRNAs by the non-canonical silencing pathway . Different types of dicer-dependent ex-siRNAs were previously identified and classified based on the components of the silencing machinery required for their biogenesis [11] . Most of those classes were also found among the exonic sRNAs significantly down-regulated in the r3b2- mutant ( Tables 2 and S7 ) . The majority of ex-siRNAs of the dicer-dependent classes II , III and IV showed at least a four-fold reduction in the r3b2- mutant relative to the wild type , whereas only three out of nine loci of class I were significantly reduced in the mutant strain . These results indicate that R3B2 , besides its role in the non-canonical pathway , also participates in the production of the majority of canonical dicer-dependent ex-siRNAs , although its contribution varies among the different ex-siRNA classes . Particularly interesting is the large decrease in ex-siRNAs of class III in the r3b2- mutant . Class III ex-siRNAs can be produced both by Dcl-1 and Dcl-2 , since their reduction is only seen in the double dcl-1-/dcl-2- mutant , and its biogenesis requires the participation of both RdRP-1 and RdRP-2 proteins [11] . The structural characteristic of this ex-siRNA class and its lack of binding to Ago-1 indicated that class III ex-siRNAs are not bona fide ex-siRNAs and it had been proposed that they could be produced by degradation of specific mRNAs by unknown RNases [11 , 14] . The structural and functional similarities between class III of dicer-dependent ex-siRNAs and the rdrp-dependent dicer-independent rdRNAs and the large decrease of both classes in the r3b2- mutant might suggest that they can be produced by the same RNase , the R3B2 protein . In fact , comparing the reduction of the class III ex-siRNA levels in the double dcl-1-/dcl-2- mutant ( average log2 fold change from wild type -3 . 21 [11] ) with their reduction in the r3b2- mutant ( -6 . 92; Table 2 ) suggests that R3B2 plays the more prominent role in the production of this class of ex-siRNAs ( see Discussion ) . To confirm the participation of the r3b2 gene in the dicer-dependent canonical pathway , we analyzed the capacity of the r3b2- mutant to activate the silencing mechanism by exogenous sequences . For that , we transformed the r3b2- mutant and the wild type strain with two different self-replicative silencing vectors containing sequences of the carB gene ( phytoene dehydrogenase ) expressed from the strong promoter of the gpd1 gene ( glycerol-3-phosphate dehydrogenase ) as silencing reporter , since carB function is required for the production of colored carotenoids . Plasmid pMAT1279 contains a sense carB transgene ( s-transgene ) [13] , whereas plasmid pMAT1253 expresses a carB hairpin RNA ( hpRNA ) [12] . Both plasmids were able to efficiently activate silencing of the endogenous carB gene in the wild type strain , giving rise to a high proportion of transformants that remained albino in the light , because of the absence of the carB function ( Table 3 ) . However , the frequency of albino transformants was severely reduced in the r3b2- mutant , in which only a few colonies with albino patches were obtained . These results indicated that r3b2 is required for efficient transgene-induced silencing regardless the nature of the silencing trigger , since sense and inverted repeat transgenes showed a similar reduction in the efficiency of silencing compared to the wild type strain . As expected , null mutants for the candidate RNase 136157 ( MU450 and MU451 strain ) , which does not participate in the non-canonical silencing pathway ( S6C Fig ) , showed silencing frequencies similar to the wild type strain ( Table 3 ) , indicating that this putative RNase does not play any role in the canonical silencing pathway either . The R3B2 protein ( ID 80729 ) is annotated in the M . circinelloides genome ( v2 . 0 ) as containing an amino-terminal RNase III catalytic domain-like of the SCOP ( Structural Classification of Proteins ) superfamily SSF 69065 , and two C-terminal dsRNA-binding domains ( Fig 5A ) . Comparison of the RNase III catalytic domain-like of R3B2 with the Ribonuclease III family signature ( Prosite PS00517 ) identified several substitutions in conserved amino acids ( Fig 5B ) . In fact , the invariant glutamic acid in the signature is changed to asparagine in R3B2 and the aspartic acid residue that is essential for catalysis in vitro [21] is substituted by glutamic acid . To confirm that the R3B2 function in RNA silencing relies on its RNase III domain-like , we performed directed mutagenesis to change several residues of the domain and analyzed the ability of the mutant allele to complement the lack of R3B2 function in the r3b2- null mutant . The R3B2 residues H49 , G55 and E56 , which correspond to the highly conserved E38 , G44 and D45 residues of the E . coli RNase III [21] , were simultaneously changed to alanine ( Fig 5B ) ( S1 Supporting Information ) . This r3b2 mutant allele ( r3b2* ) was cloned in a M . circinelloides vector that expresses a carB hairpin RNA ( hpRNA ) under the control of the gpd1 promoter , giving rise to plasmid pMAT772 ( S1 Supporting Information ) . As a control , plasmid pMAT771 , which contains a wild type r3b2 allele and the hairpin carB transgene , was also constructed . Those plasmids were used to transform the wild type and null r3b2- mutant strains and the ability of the transformants to silence the expression of the endogenous carB gene was analyzed . Transformation of the r3b2- mutant with the control plasmid pMAT771 should simultaneously complement the null r3b2- mutation and induce silencing of the carB gene . In fact , the silencing frequency in the r3b2- mutant when transformed with this complementing plasmid was similar to the wild type strain ( Table 3 ) , demonstrating that the r3b2 wild type allele is perfectly able to complement lack of R3B2 function in the r3b2- mutant strain . The reduction observed in the efficiency of pMAT771 to induce silencing relative to other silencing vectors is probably due to the large size of this plasmid . This could result in a low plasmid copy number in the transformants , which has been demonstrated to negatively affect silencing efficiency [22] . A similar silencing frequency was obtained when the silencing vector containing the r3b2* mutant allele ( plasmid pMAT772 ) was used to induce silencing in the wild type strain . However , this plasmid was barely able to activate silencing in the r3b2- mutant , indicating that substitutions of conserved residues in the RNase III domain-like of R3B2 greatly abolish the activity of this protein in the canonical transgene-induced RNA silencing pathway . To confirm the requirement of an intact RNase III-like domain for the R3B2 function in the non-canonical RNA degradation pathway we constructed stable strains containing the wild type and r3b2* mutant alleles integrated at the carRP locus . Integration at the carRP locus can be easily detected due to the color change provoked by the disruption of the carRP gene , which encode a bifunctional enzyme with phytoene synthase and lycopene cyclase activities [23] . For the integrative complementation analysis , disruption fragments containing the wild type and mutant r3b2* alleles flanked by sequences of the carRP locus were constructed ( plasmids pMAT787 and pMAT788 , S1 Supporting Information ) ( S12A Fig ) . Those fragments were used to transform the null r3b2- mutant strains and transformants that remain albino in the light were selected , since integration at the carRP locus provokes the disruption of the carRP gene and avoids accumulation of colored carotenoids . Several homokaryotic transformants harboring the wild type r3b2 or mutant r3b2* alleles integrated at the carRP locus were obtained ( S12B Fig ) , and they were used to analyze mRNA accumulation of genes regulated by the rdrp-dependent dicer-independent pathway . The r3b2 wild type allele integrated at the carRP locus efficiently complements the effect of the r3b2- mutation on mRNA accumulation of target genes , since all tested genes up-regulated in the r3b2- , rdrp-1- and rdrp-2- mutants recovered their wild type expression levels in the complemented strain ( Fig 6A and 6B , lane 5 ) . However , the r3b2- transformants harboring the r3b2* mutant allele integrated at the carRP locus showed an increased mRNA accumulation of the target genes similar to the recipient strain ( Fig 6A and 6B , lanes 6 and 7 ) , demonstrating that the r3b2* mutant allele was unable to complement the r3b2- mutation . Together , those results indicate that the RNase-like domain of R3B2 is required for the correct function of this protein both in the canonical dicer-dependent RNAi pathway and in the rdrp-dependent dicer-independent RNA degradation pathway . Confirming the participation of R3B2 in both , the canonical and non-canonical RNA pathways , the null r3b2- mutant presented phenotypes associated to alterations in cellular processes controlled by those pathways ( Fig 7 ) . The dcl-2- , ago-1- and rdrp-2- mutants , which participate in the canonical dicer-dependent ex-siRNA pathway , are affected in cellular processes connected with nutrient sensing of the cells , such as production of vegetative spores and autolysis induced by nutrient starvation [12 , 14 , 16] . Those processes are also affected in the r3b2- mutant , which presents intermediate phenotypes both , for the autolysis of aged mycelia provoked by nutritional stress , which initiates at earlier state than the wild type strain ( Fig 7A ) and for the production of vegetative spores , which is significantly reduced relative to the wild type ( Fig 7B ) . Even more relevant is the corroboration of the R3B2 participation in the rdrp-dependent dicer-independent RNA degradation pathway . Besides their better response to oxidative stress ( Fig 4 ) , the rdrp- mutants showed defects in sexual interaction and production of zygospores [16] . These phenotypes had been observed only in rdrp-1- and rdrp-2- mutants but not in dcl- or ago-1- mutants , suggesting that a non-canonical dicer-independent RNA pathway had to be involved . The r3b2- mutant is also affected in the production of zygospores ( Fig 7C ) and showed an increased resistance to oxidative stress relative to the wild type ( Fig 7D ) , confirming its participation in the rdrp-dependent dicer-independent RNA degradation pathway and suggesting a role for this pathway in the response to specific environmental signals . The domain architecture of R3B2 is unusual , since prokaryotic and fungal class 1 RNase IIIs contain only one dsRNA binding domain , besides the RNase III catalytic motif , whereas classes 2 and 3 of eukaryotic RNase III are larger proteins with several structural domains , as occurs in Drosha and Dicer [24] . In fact , no proteins with the same domain architecture as R3B2 could be identified in the Conserved Domain Architecture Retrieval Tool ( CDART ) [25] . To investigate the presence of proteins similar to R3B2 in the fungal kingdom , the fungal and oomycete genomics resource FungiDB ( http://fungidb . org/fungidb/ ) [26] was used . Sixty four organisms from 14 fungal classes are included in this data base , which allows searching for genes using different criteria . Searching for proteins similar to R3B2 identified nine proteins of this database with an expected value lower than one , all of them belonging to the order mucorales ( S13 Fig ) . No other proteins were identified when using less stringent conditions , indicating that , within the fungal kingdom , the R3B2 protein family seems to be specific of the order mucorales . Most of the proteins identified contain RNase III-like and/or dsRNA binding domains , although the majority of them are smaller than R3B2 . The phylogenetic relationship among the R3B2 protein family shows several M . circinelloides paralogous proteins highly similar to R3B2 ( Fig 5C ) . It is not known if those proteins are expressed and if their structure has been correctly annotated . However , it could be possible that one or several of them might play accessory roles in RNA silencing pathways , since they contain similar residues at the catalytic sites of their RNase III-like domains as R3B2 ( Fig 5D ) . In fact , most of the proteins of the R3B2 family contain acidic residues at the catalytic positions , although three out of four M . circinelloides R3B2 paralogs have a positively charged lysine residue in one of these positions , raising doubts about their functionality . Moreover , none of the R3B2 paralogs have been annotated as containing RNase III domains in the Mucor genome , suggesting that their differences with the consensus sequence for this domain is too high to allow their detection as putative RNase III . We also investigated the presence of proteins similar to R3B2 among sequences included at the National Center for Biotechnology Information Server ( NCBI ) . No proteins , except those present in the publicly available M . circinelloides f . circinelloides1006PhL ( ID HMPREF1544_02076 ) and Rhizopus delemar RA 99–880 ( ID RO3G_09768 ) genomes were identified ( S13 Fig ) . Strikingly , the RNase III-like domain of R3B2 showed a limited similarity ( best e-value 0 . 15 ) with the RNase III domain of different bacteria of the order Burkholderiales , although the domain of these bacterial proteins contains all the conserved residues of the RNase III signature . These data could suggest a horizontal transfer event between Burkholderia and an ancestor of the order mucorales and the generation of a fusion protein , with subsequent duplications and diversifications in different mucoralean lineages .
Several RdRP proteins have been involved in the production of endogenous siRNAs in plants and nematodes [4 , 27] . In those organisms , RdRPs show functional diversification in distinct endogenous silencing pathways as they are linked to the action of specific Dicer enzymes and/or Argonaute proteins . Also in M . circinelloides the two RdRP proteins described are functionally different . The RdRP-1 protein is involved in activation of silencing by sense transgenes and produces antisense RNAs corresponding to transgene transcripts [13] . It is also required for the production of the largest class of dicer-dependent ex-siRNAs [11] . RdRP-2 is involved in the amplification process that produces secondary siRNAs [13] and it has a role in the production of several classes of dicer-dependent ex-siRNAs [11] . We have shown here that , besides playing an essential role in this endogenous silencing pathway , the RdRP enzymes are also involved in a novel mechanism that control degradation of specific mRNAs . By deep sequencing , more than 500 loci corresponding to exons were observed to produce short RNAs in an rdrp-dependent but dicer-independent manner . However , no discrete RNA species could be detected by northern blot , suggesting that they may be degradation products of mRNAs . Sequence analysis of these short RNA molecules and their flanking genomic regions indicated that this degradation was not random and suggested the existence of a M . circinelloides RNase that preferentially cleaves mRNAs two nucleotides downstream of any uracil . Different RNase-based mechanisms have been involved in the control of mRNA stability but an RdRP enzyme was not demonstrated to participate in any of those mechanisms [28] . Our results indicate that RdRP-1 and/or RdRP-2 proteins have a functional role in the degradation of specific mRNAs , since the levels of these mRNAs were significantly increased in rdrp- mutants . Thus , reduction of the mRNA degradation rate in the rdrp- mutants would be associated with a low accumulation of degradation products ( rdRNAs ) , leading to the identification of the corresponding loci as rdrp-dependent . Confirming the non-canonical nature of this rdrp-dependent dicer-independent rdRNAs , only a minority of them were found associated with Ago-1 , the M . circinelloides Argonaute protein involved in exogenous and endogenous RNAi canonical pathways [14] . Although two other ago genes have been identified in Mucor , their genomic sequences and expression patterns do not suggest a role for their protein products in the degradation pathway described in this study [14] . We have analyzed the biological functions of genes regulated by this novel degradation pathway ( S1 Table ) . Although the large number of affected genes makes it difficult to precisely understand the processes regulated by this degradation pathway , it can be emphasized that many of those genes code for metabolic enzymes or proteins involved in regular cellular functions , such as mRNA processing , translation or signaling . Particularly interesting is the regulation of genes involved in heme biosynthesis or metabolism ( Fig 4 ) . Heme B , the most abundant heme , is synthetized by eight enzymatic steps , some of which occur in the cytoplasm and some in the mitochondrion [29] ( S14A Fig ) . Five out of eight proteins involved in heme biosynthesis are regulated by the rdrp-dependent dicer-independent degradation pathway ( S14B Fig ) , suggesting a role for this pathway in the regulation of heme-containing protein ( s ) . Curiously , a M . circinelloides protein ( ID 95051 ) highly similar to the ferrochetalase enzyme , which is required to bind iron to protoporphyrin IX , is regulated by dicer-dependent ex-siRNAs of class III ( S7 Table ) , which share some characteristics with the rdRNAs ( see below ) . In addition to that , the uroporphyrinogen III methyltransferase , which controls the first of the three steps leading to the formation of siroheme from uroporphyrinogen III , is also regulated by this pathway ( S14 Fig ) . Siroheme is a heme-like prosthetic group for sulfite and nitrite reductases that is required for methionine and cysteine synthesis [29] . Finally , two proteins highly similar to methemoglobin reductases , which are involved in heme metabolism by reducing the iron in the heme group from the ferric state ( methemoglobin ) to the ferrous state of the normal hemoglobin , are also regulated by the rdrp-dependent dicer-independent degradation pathway ( S14 Fig ) . Impairment of the degradation pathway in the rdrp- mutants would result in an increased accumulation of the mRNAs corresponding to the mentioned genes and thus , an up-regulation of heme biosynthesis and , consequently , an increase of intracellular heme levels . In fungi , hemes are found in a number of biological relevant proteins , i . e . peroxidases , cytochrome , flavohemoglobins and others [29] . Many of these proteins are involved in the response to different environmental stresses , such as low oxygen conditions [30] . Interestingly , one of the most relevant fungal hemoproteins is catalase , which is essential for protecting the cell from oxidative damage [31] . The M . circinelloides glutamate cysteine ligase-like protein 87510 is also regulated by the rdrp-dependent dicer-independent degradation pathway ( Fig 4 ) . This enzyme , also named gamma-glutamylcysteine synthetase , catalyzes the first and rate-limiting step in the production of cellular antioxidant glutathione , which plays key roles in the response to several stress situations in fungi , including oxidative stress [32] . Several other genes regulated by the rdrp-dependent dicer-independent pathway also encode antioxidant proteins , such as thioredoxin ( ID 87683 ) , glutaredoxin ( ID 37397 ) and peroxiredoxin ( ID 25842 and ID 51186 ) . Up-regulation of these genes in the rdrp- and r3b2- mutants , together with the increase in heme biosynthesis , could explain the better response to oxidative stress shown by these strains relative to the wild type , manifested by their increased ability to germinate in presence of hydrogen peroxide ( Figs 4B and 7D ) . Detailed analysis of each of the above genes would be required to assess their specific roles in the responses of M . circinelloides to oxidative stress and other environmental signals . On the other hand , the high number of genes regulated by the rdrp-dependent dicer-independent pathway containing domains involved in transcriptional regulation or signal transduction , makes difficult to ascertain the gene ( s ) responsible ( s ) for the sexual behavior of the rdrp-1- , rdrp-2- and r3b2- mutants . However , it is worth noting that one of the genes regulated by this pathway codes for a protein ( ID 43858 ) highly similar to the mating factor M secretion protein Mam1 of Schizosaccharomyces pombe ( 1 . 3E-125 ) , which is responsible for the secretion of the mating pheromone [33] . It is tempting to speculate that modulation of M . circinelloides protein expression in mutants affected in the rdrp-dependent dicer-independent pathway could be responsible , at least in part , of the defects shown by those mutants in their sexual behavior . We have identified the RNase III-like protein R3B2 as the RNase involved in the rdrp-dependent dicer-independent RNA degradation pathway . More than 1 , 500 exonic loci were identified that produced sRNAs in a R3B2-dependent manner ( S5 Table ) . These loci included all but one rdrp-dependent dicer-independent loci , revealing the participation of this RNase in the degradation pathway ( S6 Table ) . Surprisingly , also a significant number of dicer-dependent ex-siRNA loci , mainly those belonging to the class III ex-siRNAs , were found to be dependent on R3B2 for their biogenesis ( S7 Table ) . Class III ex-siRNAs share several structural and functional features with the rdrp-dependent dicer-independent rdRNAs [11 , 14] . They have the same polarity as mRNA and a random spread of size distribution , as well as a very strong preference for uracil in the penultimate position , and they do not specifically bind to Ago-1 , as occurs with the rdRNAs . This allowed us to propose that class III ex-siRNAs are not produced by a canonical RNAi pathway [11] . The difference with the rdrp-dependent dicer-independent rdRNAs relies in the participation of Dcl-1 or Dcl-2 in the biogenesis of class III ex-siRNAs . Thus , it can be suggested that the activity of RdRP-1 and/or RdRP-2 on target transcripts , presumably aberrant transcripts lacking normal processing signals such as a 5′ cap or a polyA tail , generates discrete dsRNA stretches that could be directly recognized by the RNase III-like R3B2 , targeting those transcripts for degradation ( rdRNAs ) or could be firstly processed by either Dcl-1 or Dcl-2 and after the initial cleavage the single stranded portions of mRNAs would be degraded by R3B2 ( class III ex-siRNAs ) ( Fig 8 ) . R3B2 contains a catalytic RNase III domain and two dsRBDs , which differ from typical class 1 RNase IIIs in terms of the number of dsRBDs . Only a single protein from Arabidopsis thaliana , the RNase III-like protein 2 ( AtRTL2 , At3g20420 ) display this unusual domain organization , although its catalytic domain contains a canonical RNase III signature motif [34] . Class 1 RNase IIIs are normally involved in the processing of ribosomal RNA precursors and some mRNAs . However , AtRTL2 has no effect on rRNA maturation in vivo , which suggests that it may function differently to RNase IIIs of class 1 [35] . In fact , this protein cleaves dsRNAs in vitro giving rise to cleavage products of longer size than other class 1 RNases , and it is involved in the production of small RNAs derived from transgenes in vivo . This raised the possibility that AtRTL2 may interact with other A . thaliana Dicer enzymes to positively affect the Dicer activity in siRNA generation [35] . Although the sequence similarity between AtRTL2 and M . circinelloides R3B2 is low , their similar and unique domain organization supports that R3B2 also has functions distinct from those of other class 1 RNase IIIs in vivo . Results shown here indicate that the RNase III domain-like of R3B2 is required for efficient R3B2 function in RNA silencing , although it lacks a canonical RNase III signature motif . The biochemical requirements for RNA cleavage by R3B2 are unknown , but the presence of two dsRBD , which might be utilized for protein–protein interactions [36] , suggests that it may interact with other members of the RNAi machinery ( e . g . RdRP or Dicer proteins ) to degrade target transcripts or positively affect siRNA production . Most genes regulated by the rdrp-dependent dicer-independent pathway seem to be highly expressed , as denoted by the high number of sequences derived from those genes that are included in the EST repertoire sequenced from M . circinelloides ( http://genome . jgi-psf . org/Mucci2/Mucci2 . home . html ) . For instance , all but one of genes involved in heme biosynthesis and metabolism shown in Fig 4 are present in the Mucor EST collection , whereas the global percentage of genes with ESTs in the Mucor genome is only 33% . It is tempting to speculate that this RdRP-dependent degradation process is a control mechanism for genes with high levels of expression , since elevated transcription increases the production of aberrant RNAs [37 , 38] . All eukaryotic cells , including fungi , contain general and specialized mRNA decay pathways that target aberrant transcripts for degradation . Besides these quality control systems , the correct RNA turnover of mRNAs , carried out by defined degradation mechanisms , can play an important role in setting the basal level of mRNA expression and how that level is modulated by environmental stimuli [39] . Although numerous components of the RNA degradation mechanisms have already been identified , no RdRP enzyme has been demonstrated to be involved in any of those mechanisms . However , several evidences suggest that proteins involved in proper mRNA turnover or RNA quality-control systems compete with the RNAi machinery for aberrant transcripts [40–42] . In all the reported cases , the efficiency of transgene-induced gene silencing increased in mutants affected in the mRNA degradation pathways , suggesting that degradation of aberrant transcripts limits their entry into the RNAi pathway and providing insights into the interplay between mRNA degradation and post-transcriptional gene silencing . Here , we have shown a genetic link , the rdrp genes , between these two processes . The RdRP proteins bound to aberrant transcripts may be able to either make a short complementary strand that signals the RNase R3B2 for preferential degradation or synthesize long dsRNA molecules that trigger the RNAi mechanism . How the RdRP enzymes discriminate what RNAs are directed to the canonical silencing pathway or to the degradation pathway is not known yet . However , it is worth noting that the results obtained in this work agree with the enhanced activation of the RNAi-induced epimutation pathway observed in the rdrp-1- mutants [18] . It has been shown that spontaneous resistance to an antifungal drug via an epigenetic RNAi-mediated pathway that silences the drug target gene is highly increased in the rdrp-1- mutants , suggesting that in these mutants the RNA degradation pathway has been abolished and mRNAs are primarily directed to the canonical RNAi silencing pathway . The involvement of RdRPs in RNA degradation could represent the first step in the evolution of the RNAi mechanism . RNAi is a complex process and it is unlikely that the entire process developed at once . The RdRP could be the first player that somehow marked mRNAs for degradation . Later on , Dicer may have appeared and cleaved the RdRP products . Finally , Argonaute proteins evolved to acquire the siRNAs produced by Dicer and use them for further RNA degradation . It is tempting to speculate that in M . circinelloides , and probably other members of the mucoralean basal lineage of the fungal kingdom , all of these mechanisms are still simultaneously operating .
The leucine auxotroph R7B , derived from the ( - ) mating type M . circinelloides f . lusitanicus CBS 277 . 49 ( syn . Mucor racemosus ATCC 1216b ) , was used as the wild type strain . Strain MU402 [15] is a uracil and leucine auxotroph derived from R7B used as recipient strain to knock out the candidate RNase genes . Strains MU411 ( dcl-1-/dcl-2- ) [12] , MU413 ( ago-1- ) [14] , MU419 ( rdrp-1- ) and MU420 ( rdrp-2- ) [13] were all derived from MU402 . The M . circinelloides f . lusitanicus strain of the ( + ) mating type NRRL3631 was used in sexual interaction analysis . Cultures were grown at 26°C in minimal YNB medium , complete YPG medium or in MMC medium as described previously [15] . Media were supplemented with uridine ( 200 μg/ml ) or leucine ( 20 μg/ml ) when required . The pH was adjusted to 4 . 5 and 3 . 2 for mycelial and colonial growth , respectively . Transformation was carried out as described previously [43] . For increasing the proportion of transformed nuclei , transformants were grown in selective medium for several vegetative cycles , since primary transformants are heterokaryons due to the presence of several nuclei in the protoplasts . Illumination conditions were as previously described [44] . Competent cells of E . coli DH5α strain were used for cloning experiments . A complete description of plasmids used in this work for cloning and functional analysis of the candidate RNase genes can be found in S1 Supporting Information . Genomic DNA from M . circinelloides mycelia was extracted as previously described [15] . Recombinant DNA manipulations were performed as reported [45] . To identify transformants that correctly integrate the knockout vectors designed to disrupt the candidate RNase genes , a rapid protocol for isolating DNA to be used in PCR amplifications was utilized [15] . Total RNA was isolated using Trizol reagent following the supplier’s recommendation ( Invitrogen ) . Southern blot and Northern blot hybridizations were carried out under stringent conditions [15] . DNA probes were labeled with [α-32P]dCTP using Ready-To-Go Labeling Beads ( GE Healthcare Life Science ) . For Northern blot experiments , P1 , P2 and P3 probes were directly amplified from genomic DNA using specific primers ( S2 Table ) . For Southern blot hybridizations , specific probes that discriminate between the wild type and disrupted alleles of each candidate RNase gene were obtained as follows . The r3b2 probe ( S8 Fig , probe a ) corresponds to a 720 bp SacI fragment isolated from plasmid pMAT1294 , which contains the r3b2 gene and adjacent sequences ( S1 Supporting Information ) . The 136157 probes b and c ( S9 Fig ) , correspond to a 1 . 1 kb HincII and 0 . 6 kb NcoI/SacI fragments isolated from plasmid pMAT767 , respectively . The 110239 specific probe ( S10 Fig , probe d ) corresponds to a 0 . 8 kb fragment of its downstream region amplified by the primer pair F6/R5 ( S4 Table ) . The 77996 probe ( S10 Fig , probe e ) corresponds to a 1 . 0 kb fragment of its downstream region amplified by the primer pair F9-pyrG/R8 ( S4 Table ) . The carRP probe ( S12 Fig , probe f ) used to identify homologous integration of r3b2 alleles into the carRP locus was amplified with primers carRP-F1 and carRP-R2 ( S4 Table ) . Signal intensities were estimated from autoradiograms using a Shimadzu CS-9000 densitometer and the ImageJ application , an open source image analysis program ( rsbweb . nih . gov/ij/ ) . EcoTaq Plus ( Ecogen , Spain ) or PfuUltra Hotstart DNA Polymerase ( Stratagene ) were used in PCR experiments . A PCR-based strategy was used for cloning the selected genes encoding proteins with an RNase domain and for the generation of knock-out vectors to disrupt each gene . A precise description of the constructs and the procedures used can be found in S1 Supporting Information . Vegetative sporulation and lysis measurements were carried out as previously described [14] . Autolysis of aged mycelia was estimated by image analysis of the plates using ImageJ ( rsbweb . nih . gov/ij/ ) . Quantification of sexual mating and zygospores formation was carried out as described [16] . Briefly , spores of the ( - ) and ( + ) mating types were co-inoculated in the middle of agar YPD plates , approximately 2 cm apart , and incubated at room temperature under dark conditions during 20 days . The formation of zygospores in the contact zone gives rise to a dark line that was sliced in portions of 1 cm2 and fixed in 10% formaldehyde during 10 hours . After fixation , samples were frozen and sliced using a cryotome to produce sections of 30 μm . Zygospores from twelve sections were counted by optical microscopy ( bright field 10X ) for each interaction . For endogenous sRNA analysis , small RNA samples were extracted from mycelia grown 48 h on YPG plates using the miRVana kit ( Ambion ) , following the instructions of the supplier . cDNA libraries of small RNAs were generated and sequenced as described previously [11] . For isolation of sRNAs bound to the Ago-1 protein , small RNA samples were extracted from Ago-1-containing fractions and used to construct the cDNA library as previously described [11] . Equivalent fractions from the ago-1- mutant were used for isolation of sRNAs as a negative control . Sequencing of the Ago-1 bound cDNA libraries were carried out as described [14] . For detection of endogenous sRNAs in Northern blot experiments , membranes were hybridized as described [22] with sense and antisense-specific riboprobes prepared by in vitro transcription ( MAXIscript transcription kit; Ambion ) of linearized plasmids containing specific sequences for each locus ( S2 Table ) . Computational sequence analysis was carried out using European Bioinformatics Institute Server software ( EMBL Outstation , Hinxton , U . K . ) , the National Center for Biotechnology Information Server ( NCBI , Bethesda , MD , USA ) and the Methodes et Algorithmes pour la Bio-informatique LIRMM ( MABL ) server ( Montpellier , France ) . For the analysis of endogenous sRNAs , raw reads were processed and normalized as previously described [11 , 14] . sRNAs were mapped to annotated exons , transposons and intergenic regions of the M . circinelloides genome ( http://genome . jgi-psf . org/Mucci1/Mucci1 . home . html ) ( v 1 . 0 ) using PatMaN [46] . sRNA loci were said to be down-regulated in a given sample if the normalized locus abundance showed at least a fourfold decrease in comparison to the wild type sample ( log2 fold change ≤ -2 ) . This arbitrary fourfold difference was used as a cut-off to increase the stringency of the analysis . sRNAs were said to be bound to Ago-1 if the normalized abundance in the Ago-1 fractions purified from the wild type strain showed at least a fourfold increase relative to the ago-1- sample ( log2 fold change ≥ 2 ) . To increase the stringency of the analysis and avoid lowly expressed regions , any loci with a normalized abundance count of less than 50 in the wild type were excluded from the analysis . The accession numbers of the sRNAs cloned in the wild type and rdrp-1- and rdrp-2- mutants are GSM469403 , GSM469406 and GSM469407 , respectively; all accessions are under GEO accession GSE18958 . The raw reads of M . circinelloides Ago-1-bound small RNAs in wild type and ago-1- mutant are deposited in the Sequence Read Archive ( SRA ) database under the accession number SRR835448 . The raw reads of M . circinelloides small RNAs in the r3b2- mutant have been deposited in the SRA database under the accession number SRR1576768 . | Most eukaryotic organisms produce different classes of endogenous small RNA ( esRNA ) molecules that suppress gene expression through RNA interference ( RNAi ) pathways . These pathways , which may differ among organisms , are normally involved in genome defense , heterochromatin formation and regulation of genes involved in multiple cellular functions . In the basal fungus Mucor circinelloides , an opportunistic human pathogen , we previously demonstrated that biogenesis of a large group of esRNA molecules requires a basic RNAi machinery consisting of a Dicer-like protein , an Argonaute nuclease and two RNA-dependent RNA polymerases . This canonical dicer-dependent pathway regulates different cellular processes , such as vegetative sporulation . Besides those esRNAs generated by this canonical RNAi pathway , we have identified a new rdrp-dependent dicer-independent esRNA class . These esRNAs are produced by a degradation pathway in which the RdRP proteins signal specific transcripts that will be degraded by a newly identified RNase . This RNase , named R3B2 , presents unique domain architecture , can only be found in basal fungi and it is also involved in the canonical dicer-dependent RNAi pathway . Our results expand the role of RdRPs in gene silencing and reveal the involvement of these proteins in a new RNA degradation process that could represent the first step in the evolution of RNAi . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2015 | A Non-canonical RNA Silencing Pathway Promotes mRNA Degradation in Basal Fungi |
Biological processes in living cells are often carried out by gene networks in which signals and reactions are integrated through network hubs . Despite their functional importance , it remains unclear to what extent network hubs are evolvable and how alterations impact long-term evolution . We investigated these issues using heat shock protein 90 ( Hsp90 ) , a central hub of proteostasis networks . When native Hsp90 in Saccharomyces cerevisiae cells was replaced by the ortholog from hypersaline-tolerant Yarrowia lipolytica that diverged from S . cerevisiae about 270 million years ago , the cells exhibited improved growth in hypersaline environments but compromised growth in others , indicating functional divergence in Hsp90 between the two yeasts . Laboratory evolution shows that evolved Y . lipolytica-HSP90–carrying S . cerevisiae cells exhibit a wider range of phenotypic variation than cells carrying native Hsp90 . Identified beneficial mutations are involved in multiple pathways and are often pleiotropic . Our results show that cells adapt to a heterologous Hsp90 by modifying different subnetworks , facilitating the evolution of phenotypic diversity inaccessible to wild-type cells .
Biological functions are often considered the collective output of genes interacting coordinately in a network [1–4] . Although most genes in a network only have a few links , some “hub” genes are highly connected to network components and play a vital role in maintaining intra-network connectivity [2] . As a consequence , hub genes usually possess pleiotropic functions and have a profound influence on cell fitness [5 , 6] . Phenotypic variation was enhanced in yeast cells in which hub genes were disrupted , revealing a role for hub genes in network robustness against genetic or environmental perturbations [7] . Comparative genomics has shown that some hub genes can diverge significantly at the sequence level . However , little is known about to what extent the function of hub genes can change over long-term evolution or how changes in hub genes influence the evolutionary trajectory of an entire network . The molecular chaperone heat shock protein 90 ( Hsp90 ) represents a well-documented network hub . Hsp90 is present in bacteria , fungi , plants , and animals [8] and is essential for cell viability in all studied eukaryotic species [9–13] . Large-scale studies in S . cerevisiae indicate that Hsp90 is one of the central hubs in both physical and genetic interaction networks [14 , 15] . More than 10% of the whole yeast and human proteomes have been shown to be clients of Hsp90 [16] . Moreover , the yeast Hsp90-dependent proteome is enriched with other hubs and essential genes [17] . In general , Hsp90 acts at a late stage of protein folding . It assists partially folded clients to reach structural maturation [16] , or it stabilizes the components of multi-subunit protein complexes and facilitates their assembly [18–20] . Hsp90 has a high degree of specificity for client recognition , which is attributed to its sophisticated co-chaperone system [21 , 22] . Interestingly , it has been found that the activity or stability of some Hsp90 client proteins can become Hsp90 independent after introducing mutations [23 , 24] , suggesting that the link between Hsp90 and its clients may be changed over time . Apart from these physiological functions , Hsp90 has been suggested to buffer genetic and nongenetic variations to ensure developmental stability in fungi , plants , and animals [25–28] . Organisms exhibit constant phenotypes under normal conditions , even if they host genetic or nongenetic variations . However , when Hsp90 activity is compromised or titrated by extreme environmental stresses , heterogeneous phenotypes are revealed in a population . This increased phenotypic diversity is hypothesized to help the population survive or adapt during drastic environmental changes [29] . To understand the implications of hub evolution , we replaced the Hsp90-coding gene of S . cerevisiae with orthologs from other yeast species and examined their functions . S . cerevisiae cells carrying Y . lipolytica-Hsp90 ( Ylip-Hsp90 ) exhibited decreased fitness in most tested conditions but improved growth in high-salt medium , suggesting that the function of Ylip-Hsp90 has differentiated from its S . cerevisiae ortholog . We further evolved the Ylip-Hsp90–hosting strain to study how cells respond to a changed network hub . The evolved clones adopted various evolutionary trajectories , but none involved changing the heterologous Hsp90 per se . Furthermore , fitness measurements in different stress environments showed that these clones had evolved diverged phenotypes that differed from each other and also deviated from wild-type S . cerevisiae cells .
Hsp90 is an essential hub protein that interacts with 10%–20% of the whole yeast proteome , and changes to Hsp90 are probably constrained by the function of its client proteins or even the network structure [16] . To investigate whether Hsp90 protein function has changed during evolution , we replaced the endogenous Hsp90 gene in S . cerevisiae with the plasmids carrying its orthologs from Naumovozyma castellii ( Ncas ) , Kluyveromyces lactis ( Klac ) , and Y . lipolytica ( Ylip ) , which diverged from the common ancestor of S . cerevisiae ( Scer ) at different times [30 , 31] ( Fig 1A ) . Our previous data showed that the original promoters of the orthologs from distant species often do not function properly in S . cerevisiae cells . Therefore , we placed the coding sequences of Scer-HSC82 ( one of the genes encoding Hsp90 in S . cerevisiae ) and its orthologous genes under a strong tetracycline operator 7 repeats ( TetO7 ) promoter , which enabled us to study changes in protein function and to also control expression levels . We then examined these Hsp90-ortholog replacement strains ( denominated as Ncas-HSP90 , Klac-HSP90 , and Ylip-HSP90 ) under different growth conditions . To examine how orthologous Hsp90 proteins influence the physiology of hosting S . cerevisiae strains , we measured the fitness of replacement strains under 17 different growth conditions using spot assays ( see Materials and methods ) . For most test conditions , Ncas-Hsp90 and Klac-Hsp90 hosting strains exhibited similar fitness as Scer-Hsc82–carrying cells ( Fig 1 , S1 Fig and S1 Table ) , indicating that the function of Hsp90 is not drastically different among N . castellii , K . lactis , and S . cerevisiae . In contrast , the Ylip-Hsp90 hosting strain exhibited lower fitness than Scer-Hsc82 cells under most conditions; similar fitness to Scer-Hsc82 cells in media containing 150 mM MgCl2 , 1 . 8 M sorbitol , or 0 . 5 M NaCl; and higher fitness under two hypersaline conditions ( media containing 1 M NaCl or 0 . 2 M LiCl , see Fig 1B , S1 Fig and S1 Table ) . The phenotypic differences between Ylip-Hsp90– and Scer-Hsc82–carrying cells might be due to differences in the expression level , activity , or/and specificity of these two orthologs . No significant difference was observed when the protein levels of Ylip-Hsp90 and Scer-Hsc82 were measured using western blots ( S2A Fig ) . To test whether the activity of Ylip-Hsp90 is different than that of Scer-Hsc82 , we performed a v-src kinase assay . Hsp90 is required for the activation of v-src and , therefore , by measuring the level of v-src–dependent tyrosine phosphorylation , the activity of Hsp90 can be estimated [32] . In the kinase assay , we observed similar levels of v-src–dependent tyrosine phosphorylation in Ylip-Hsp90– and Scer-Hsc82–carrying cells ( S2B Fig ) , suggesting that the main difference between Ylip-Hsp90 and Scer-Hsc82 is the interaction specificity instead of the activity . Y . lipolytica cells are often isolated from hypersaline environments and exhibit high tolerance to NaCl and LiCl ( S2C Fig ) [33 , 34] . Previous research in S . cerevisiae suggested that Hsp90 plays a crucial role in salt stress tolerance by regulating the activity of its client , calcineurin [35] . Hsp90 is essential for activation of calcineurin . However , overexpression of Hsp90 also led to salt hypersensitivity because calcineurin was sequestered by Hsp90 . The increased salt resistance in Ylip-Hsp90 hosting cells suggests that the interaction between Ylip-Hsp90 and calcineurin may have been changed or Ylip-Hsp90 can facilitate the activity of other proteins involved in hypersaline growth . The altered growth pattern of Ylip-Hsp90 hosting cells reveals that the function of Hsp90 has significantly diverged between Y . lipolytica and S . cerevisiae . Moreover , our findings indicate that even a central network hub like Hsp90 can change significantly over the course of long-term evolution . Alteration of a network hub often has a strong impact on cell fitness [5 , 6] . Cells may be selected to quickly restore the original functions of the hub , or the network may be rewired to accommodate or compensate for the altered hub . In the latter scenario , it may also open the possibility for cells to evolve novel phenotypes . To explore the possible evolutionary trajectories of an altered Hsp90 network , we evolved 12 independent haploid lines carrying Ylip-HSP90 and 12 control lines carrying Scer-HSC82 that were all derived from the same parental S . cerevisiae clone . These cell lines were grown in regular rich medium ( Yeast extract-Peptone-Dextrose [YPD] ) at 28°C so that their major selective pressure is to restore the general growth defects caused by Ylip-HSP90 . In each evolving culture , two isogenic strains carrying either the green or red fluorescent protein marker ( Fig 2A ) were mixed at an approximate initial ratio of 1:1 . By monitoring the proportions of the two fluorescence-labeled populations at different time points , we could estimate when the first beneficial mutation was fixed in each culture ( S3 Fig ) . In the Ylip-HSP90 lines , more than half of the cultures fixed the first beneficial mutation within 450 generations ( Fig 2B ) . It took another 200 generations for the Scer-HSC82 lines to reach similar proportions of fixation . This outcome is consistent with the assumption that Ylip-HSP90 hosting cells were initially under high selective pressure to resolve the incompatibility between the heterologous Ylip-Hsp90 and its interactive network in the S . cerevisiae background . In contrast , the Scer-HSC82 lines only experienced very low or no selective pressure , because the evolution experiments were conducted under a normal growth condition . After evolving for around 2 , 200 generations , three Ylip-HSP90 ( evo1 , evo2 , and evo12 ) lines and one Scer-HSC82 ( con6 ) line were lost because of contamination . We further analyzed the remaining evolved cultures . The fitness of evolved Ylip-HSP90 populations in YPD at 28°C improved by 16%–24% compared with their ancestor ( Fig 2C ) . The degree of improvement was significantly higher than that observed in the evolved Scer-HSC82 populations , suggesting that the adaptive phenotype is likely to be Ylip-HSP90 specific . When the fitness of evolved Scer-HSC82 clones was compared with their ancestor , no significant difference was observed in four evolved lines ( S2 Table ) , suggesting that both genetic drift and beneficial mutations contributed to the evolved phenotypes of Scer-HSC82 populations . To characterize the evolved phenotype , we isolated three single colonies from each evolved culture and measured their fitness . The colonies with the highest fitness from each population were chosen to represent the lineage for further examination ( denominated E3 to E11 for evolved Ylip-HSP90 clones and C1 to C12 for evolved Scer-HSC82 clones ) . It was previously reported that S . cerevisiae cells often converge to a diploid state during laboratory evolution [36] . We examined the genome content of evolved clones using flow cytometry and found that all of the evolved Scer-HSC82 clones had become diploid or triploid ( S4A Fig ) . In contrast , most of the evolved Ylip-HSP90 clones remained haploid , except for E10 , which had become diploid . To ensure that the ploidy expansion observed in individual clones is representative of the whole population , we also examined the evolved cultures using flow cytometry and observed the same results . Because all the cultures were evolved under the same selective regime , the difference in ploidy observed in evolved cultures further implicates functional divergence between Ylip-Hsp90 and Scer-Hsc82 . To further test the effect of Hsp90 on ploidy expansion or maintenance , we generated diploid strains by mating haploid cells and compared their fitness with haploid strains . Haploid Ylip-HSP90–carrying cells exhibited higher fitness than diploid Ylip-HSP90–carrying cells ( S4B Fig ) . This result provides the possible reason why most Ylip-HSP90 lines remained haploid after evolution . Because the evolved clones restored the fitness of Ylip-HSP90 cells in rich media , we wondered whether they would become sensitive to hypersaline stress like Scer-HSC82 cells . When evolved Ylip-HSP90 clones were tested on 0 . 2 M LiCl-containing plates , they displayed similar or higher fitness compared with ancestral Ylip-HSP90 strains ( Fig 3A ) , indicating that the Y . lipolytica-specific hypersaline-resistant phenotype had been stably maintained in the Hsp90 network of the evolved cells . The function of Ylip-Hsp90 might be enhanced if its expression level is increased or the protein is mutated in the evolved clones . We measured protein levels of Ylip-HSP90 using western blots . All evolved clones presented similar levels of the Hsp90 protein compared to the ancestral Ylip-HSP90 strains ( S4C Fig ) . We also sequenced the Ylip-HSP90 gene of all evolved clones and found no mutation in any of them . Together , these data indicate that the evolved cells had not improved their fitness by modifying the Ylip-HSP90 gene . The observed fitness improvement in evolved Ylip-HSP90 clones might be specific to the heterologous Hsp90 or simply be due to mutations that enhance general cell proliferation ( e . g . , loss of the costly genes or gain of glucose uptake genes ) . To differentiate between these two possibilities , we replaced the Ylip-HSP90 gene of the evolved and ancestral clones with Scer-HSC82 and measured their fitness in YPD at 28°C . The extent of fitness improvements was drastically diminished when Ylip-Hsp90 was replaced ( Fig 3B and S2 Table ) , indicating that the beneficial effects of evolved mutations are dependent on Ylip-Hsp90 . Because Hsp90 is an important molecular chaperone involved in maintaining protein homeostasis , we suspected that the reduced fitness of ancestral Ylip-HSP90 cells in normal conditions might reflect disturbed internal proteostasis caused by the compromised Hsp90 network . We used an Hsp104 aggregation assay to investigate this possibility [37] . Hsp104 is a disaggregase that localizes to protein aggregates upon heat stress and helps with the disaggregation and refolding process . Ancestral and evolved cells containing fluorescent Hsp104-BFP fusion protein were first grown at 25°C and then shifted to 37°C for high-temperature adaptation . By monitoring the fraction of cells containing Hsp104-BFP foci during heat treatment , we could assess how well protein homeostasis is maintained . Ancestral Ylip-HSP90 cells contained more Hsp104-BFP foci than Scer-HSC82 cells before and during heat treatment , suggesting that Ylip-HSP90 cells indeed have a high endogenous proteome burden even before heat treatment ( Fig 3C and S5A Fig ) . Interestingly , even though all evolved Ylip-HSP90 clones had improved their fitness to the wild-type level , not all of them could restore their ability to efficiently clear protein aggregates . E11 cells exhibited a disaggregation pattern similar to ancestral Ylip-HSP90 cells . In contrast , E7 cells had lower levels of Hsp104-BFP foci at initial and later time points compared with Scer-HSC82 cells ( Fig 3C , S5A and S5B Fig ) . Our results suggest that different evolved lines probably took different paths to fix the compromised Hsp90 network . In addition to attenuated protein homeostasis , ancestral Ylip-HSP90 cells also exhibited an elongated cell morphology that has previously been observed in cells lacking sufficient Hsp90 activity to stabilize its client proteins [28] . When we examined the cell morphology of evolved Ylip-HSP90 clones , we found that only E3 , E4 , and E9 cells recovered from the elongated cell morphology . E5 and E11 evolved to an even more elongated form , whereas the remaining clones were not significantly different than their ancestor ( Fig 3D and S5C Fig ) . These results reinforce that different adaptive paths had been taken by the individual evolved lines . Both the Hsp104 aggregation assay and our cell morphology measurements suggested that the phenotypes of evolved Ylip-HSP90 lines are diverged from each other and from their ancestor and Scer-HSC82 cells . To obtain a more complete picture of the evolved phenotypes , we subjected the evolved clones to two growth media and nine different stress conditions that challenge different aspects of protein homeostasis and then measured their fitness ( see Materials and methods ) . Our results revealed a broad spectrum of adaptive phenotypes in the evolved clones ( Fig 4A and S2 Table ) so that , even if some strains shared similar fitness levels for one or two conditions , their fitness levels differed under other conditions . Moreover , for many of the conditions we tested , the evolved clones exhibited higher fitness than Scer-HSC82 cells ( S2 Table and Fig 4A ) . We also tested whether the observed fitness was correlated with the protein abundance of Hsp90 in evolved Ylip-HSP90 clones . No significant correlation was observed in any tested condition ( S3 Table ) . To obtain a more general overview of the evolved features in different clones , we performed hierarchical clustering and principal component analysis ( PCA ) according to their fitness measurements under the 11 tested conditions ( Fig 4B and 4C , S6A Fig and S4 Table ) . Hierarchical clustering revealed that clones E4 and E9 were more similar to Scer-HSC82 cells than other evolved clones . The first principal component ( explaining 33 . 8% of the variance ) of our PCA showed that most clones evolved toward the Scer-HSC82 phenotype ( S6A Fig ) . Nonetheless , they were not closely clustered . Phenotypic divergence between the evolved clones was further revealed by the second and third principal components ( explaining 28 . 4% and 14 . 2% of the variance , respectively ) . These results suggest that Ylip-HSP90 lines have evolved diverged phenotypes that both differ from each other and from ancestor and Scer-HSC82 cells . The observed phenotypic variation in the evolved Ylip-HSP90 clones suggests that after the heterologous Hsp90 was introduced , different Hsp90-related functions in individual evolving lines were modified to regain fitness . Under this hypothesis , high phenotypic variation should not occur in the evolved Scer-HSC82 clones ( i . e . , the control lines ) , because the network hub has not changed . We performed two types of analysis to address this issue . We first measured the fitness of evolved Scer-HSC82 clones under the same 11 growth conditions ( S6B Fig ) and calculated the variance of fitness improvements among evolved Ylip-HSP90 and Scer-HSC82 clones in individual conditions . We then compared the variance between evolved Ylip-HSP90 and Scer-HSC82 groups . The data show that the evolved Ylip-HSP90 clones exhibited greater variance than the evolved Scer-HSC82 group ( p-value = 0 . 039 , one-tailed Student t test ) , indicating that responses of evolved Ylip-HSP90 clones to different stress conditions were more varied than evolved Scer-HSC82 clones ( S6C Fig ) . In the second analysis , we calculated the Pearson correlation distances between fitness levels under different conditions ( see Materials and methods , S5 Table ) to quantify the variation in distribution patterns of individual fitness between each pair of conditions . If individual clones show similar ranking patterns for fitness between two conditions , Pearson correlation distances will be small . In contrast , large Pearson correlation distances indicate that individual evolved clones behave very differently in two conditions . Overall , pairwise comparisons revealed that the evolved Scer-HSC82 clones behaved similarly under different stress conditions , except for the complete supplement mixture ( CSM ) and azetidine-2-carboxylate ( AZC ) media ( Fig 4D and S5 Table ) . The stress condition–based phenotypic distance of evolved Scer-HSC82 clones is significantly smaller than that of evolved Ylip-HSP90 clones ( S6D Fig ) , supporting our hypothesis that high phenotypic variation only occurred in evolved Ylip-HSP90 clones . To explore the genetic basis of the evolved phenotypes , we sequenced the genomes of the evolved Ylip-HSP90 clones . On average , each evolved clone hosted eight protein-sequence-changing mutations ( seven nonsynonymous and one insertion/deletion ) and 14 total mutations ( S7 Fig ) . The calculated mutation rate ( 5 . 45 × 10−10 per bp per generation ) is comparable with the estimated spontaneous mutation rates from previous studies [38 , 39] . Only a small group of genes were recurrently mutated in multiple evolved clones ( i . e . , BRE5 in three clones and BUD2 , FMP30 , SIR3 , and HXK2 in two clones , S6 Table ) . We investigated the BRE5 gene further in the reconstitution experiments . In evolved clones , we found that large-scale copy number variation only occurred in mitochondrial genomes and ribosomal DNA , and that small-scale copy number variation was also rare outside subtelomeric regions ( S7 Table ) . When the gene functions of all identified protein-sequence-changing mutations were analyzed further ( Table 1 and S8 Table ) , we found that most of them could be categorized into several Hsp90-related functions [14 , 40] , including protein synthesis , folding and modification , intracellular trafficking , ribosome biogenesis , cellular conjugation , chromatin organization , and signaling , as well as mitochondrial physiology ( Fig 5 ) . Many of these genes have known interactions with Hsp90 or belong to the Hsp90-dependent proteome [17 , 41] , raising the possibility that evolved yeasts might adapt by modifying different Hsp90 subnetworks . Not all the mutations in the evolved clones are likely to contribute equally to the adaptive phenotypes . We performed segregant analysis to map the mutations with strong effects in three evolved clones ( E4 , E5 and E7 ) . These clones were selected because E4 and E5 clones showed opposite trends in cell morphology , and E7 has the largest improvement in protein homeostasis ( Fig 3 ) . The evolved Ylip-HSP90 clones were backcrossed to the ancestral Ylip-HSP90 strain and their F1 spores ( from 40–45 four-viable spore tetrads ) were analyzed . In all three evolved clones , our genetic analysis indicated that multiple loci were involved in the evolved phenotypes ( S9 Table ) . The F1 progeny with phenotypes similar to evolved or ancestral clones were grouped into good and bad spore pools , respectively ( see Materials and methods ) . Genomic DNA was isolated from both pools and then subjected to Illumina sequencing . Based on our computational simulation , two criteria were used to select the mutations with strong effects: ( 1 ) the mutation frequency in the good spore pool is greater than 70% or ( 2 ) the difference in mutation frequencies between good and bad spore pools is greater than 45% . Nine mutations—sec9-E310K and tap42-F72S from E4; izh3-S115* ( * indicating a premature stop codon ) , bud4-P981fs ( fs indicating a frameshift mutation ) , bre5-L433F , and mdm12-F148S from E5; and siz1-P401L , pbp1-N318fs , and nop53-E289_N290insE ( ins indicating an insertion ) from E7 ( S10 Table ) —were identified and used for reconstitution experiments to confirm their effects . Our phenotypic assays had revealed that independent Ylip-HSP90 lines evolved diverse phenotypes ( Fig 4 ) . To understand how the evolved mutations contribute to the broad spectrum of phenotypes , we used the clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 ( CRISPR/Cas9 ) system to reintroduce these mutations into the ancestral Ylip-HSP90 strain and examined the fitness of these mutants under different stress conditions ( Fig 6A , S8 Fig and S11 Table ) . Four major conclusions can be drawn from the phenotypic assays . First , individual mutations usually had dominant effects under at least one stress condition ( e . g . , in clone E7 , the siz1 , pbp1 , and nop53 mutants exhibited strongest effects under conditions of 37°C , macbecin II treatment , and doxycycline treatment , respectively ) , confirming that these mutations really contribute to the evolved phenotypes . Second , several mutations exhibited positive effects under one stress condition but negative effects under others ( e . g . , in clone E7 , pbp1 mutants had a positive effect under macbecin II treatment but a negative effect under the MG132 stress condition ) , indicating that antagonistic pleiotropy is common among the evolved mutations . Third , in a few stress conditions ( e . g . , for clone E5 in medium containing macbecin II ) , the sum of individual effects exceeded the effect observed in the evolved clone , suggesting the existence of negative epistasis between mutations . Fourth , for some other conditions ( e . g . , clone E4 in medium containing MG132 ) , the sum of all individual effects was still far below the effect observed in evolved clones . This outcome can be explained if there is positive epistasis between mutations . Alternatively , some mutations with weak individual effects but that are strongly epistatic to other mutations might have been missed by our mapping exercise . We selected one mutation from the E4 clone , cbk1-L461F , that exhibited a mutation frequency slightly lower than our segregant analysis criteria to test these possibilities . The cbk1-L461F single mutation did not result in any significant effects under any tested stress condition ( Fig 6A ) . However , when cbk1-L461F was combined with sec9-E310K or tap42-F72S and tested in all conditions , it displayed positive epistatic effects with sec9-E310K and tap42-F72S in medium containing brefeldin A ( BFA ) and MG132 , respectively ( Fig 6B and S11 Table ) . In addition to its fitness improvement , our Hsp104 aggregation assay showed that the E7 clone has a strong aggregate clearance phenotype ( Fig 3C ) . This allowed us to characterize the contribution of individual mutations to protein homeostasis . We found that all three single mutations ( siz1 , pbp1 , and nop53 ) reduced the formation of Hsp104 foci at 37°C , but pbp1-N318fs had the strongest effect ( Fig 6C ) . When all three mutations were combined in a single clone , the further enhanced aggregate clearance phenotype was observed at the 3-hour time point . These results reveal a specific role of pbp1-N318fs in maintaining protein homeostasis under heat stress conditions .
The Hsp90 network performs many crucial functions in eukaryotic cells and probably represents a robust system resilient to genetic perturbations [16 , 40] . Nevertheless , the ability of Ylip-Hsp90 to enhance hypersaline tolerance in S . cerevisiae cells and the compromised fitness of such cells under other stress conditions indicate that even a central hub like Hsp90 can change its functions or partners during evolution . This seeming discrepancy may be explained by a computational simulation study of complex signaling circuits that showed phenotypic robustness and variability are positively correlated [42] . Because a broad range of genotypes usually supports a robust phenotype , a greater diversity of phenotypes is accessible from among the genotypic neighborhood . This model implies that a robust system like the Hsp90 network can still be genetically adjusted to facilitate adaptation to novel environments . If the Hsp90 network is continually modified in a specific direction ( e . g . , to tolerate hypersaline stress ) , it may eventually lead to alterations in a network hub such as Ylip-Hsp90 . Evolvability represents an organism’s capacity to generate selectable phenotypic traits during evolution [43] , so the level of evolvability may influence the likelihood of an organism surviving in or adapting to a new habitat . In developmental biology , large phenotypic changes or innovations are often associated with changes in the transcriptional network hubs [44–46] . Despite strong evidence supporting a link between network hubs and evolvability , it is difficult to study directly the effect of changed network hubs on evolutionary trajectories using natural populations . Our laboratory evolution experiments provide an alternative approach to address this issue . In the current study , we replaced the Hsp90-coding gene of S . cerevisiae with the ortholog from a distant species . Nonetheless , a similar evolutionary process may occur in nature under the following conditions: ( 1 ) a hybrid progeny carries incompatible gene pairs that compromise the function of a network hub . Genetic incompatibility has been observed to exist between closely related species and cause defects in different important cellular functions [47] . Although these types of hybrids have lower fitness and are likely to be eliminated in most cases , they may also create the chance for the organism to evolve new phenotypes , especially in the hybrid zone where hybrids are constantly generated . ( 2 ) Mutations occur in critical domains of a hub gene . Mutagenesis experiments in Hsp90 have shown that even a single amino acid change can alter the activity or interacting partners of the protein completely [48] . Such mutations will often result in the low fitness of the cell , as in the hybrid case . However , they may lead to the evolution of new phenotypes if compensatory mutations that restore fitness occur and are subsequently fixed by selection [49] . ( 3 ) A multifunctional gene is obtained through horizontal gene transfer ( HGT ) . In recent years , HGT has been shown to occur frequently , even in eukaryotes [50 , 51] . A foreign multifunctional protein may disturb the original cellular network and open a new evolutionary path . Network structures contribute to phenotypic robustness against genetic or environmental perturbations [52] . When network hubs are compromised , pre-existing cryptic genetic or nongenetic variation may be exposed that facilitates short-term population adaptation [7] . Our study reveals a different role played by network hubs in long-term evolution in a population without much genetic variation . S . cerevisiae cells immediately gained hypersaline tolerance like Y . lipolytica cells solely by replacing a single hub gene , HSP90 , with the corresponding ortholog . This is similar to a previous observation that bacteria dramatically increased the growth rate at lower temperatures with the introduction of psychrophilic chaperonins [53] . Moreover , the novel Hsp90 allowed individual clonal populations to evolve diverse phenotypes unobserved in cells hosting native Scer-Hsc82 . These novel phenotypes may enable evolved cells to explore niches inaccessible to Scer-Hsc82–hosting cells and , in the long term , may broaden opportunities for population diversification and speciation . Previous laboratory evolution experiments in bacteria showed that when essential ribosomal genes or translation factors were replaced by their orthologs from other bacteria or the ancestral sequence , expression levels of the introduced orthologous genes were often amplified to compensate for the incompatibility [54–56] . In our evolved clones , protein levels of Ylip-Hsp90 were not changed , suggesting that the cells were able to quickly gain other mutations to ameliorate the growth defect in the conditions under which they evolved . One major function of network hubs is to coordinate different subnetworks ( or pathways ) so that the cell can quickly respond to environmental changes . However , when a hub is compromised or altered ( such as in the Ylip-Hsp90–hosting cells ) , any mutation that can improve cell fitness under the existing growth conditions will be selected , even if it has costs in other conditions or distorts the balance between different subnetworks . The evolved Ylip-HSP90 clones restored only some of the functions of Hsp90 despite that all clones had similar or higher fitness in rich medium compared to Scer-HSC82 cells ( Figs 3C , 3D and 4 ) . By sequencing the evolved clones and reconstituting mutations , we confirmed that individual subnetworks of Hsp90 had been modified in different evolved lineages . As expected , some of the evolved mutations showed strong antagonistic pleiotropy , exhibiting improved cell fitness in rich medium but growth defects under other stress conditions . Because cells are constantly challenged by environmental fluctuations , it is likely that another layer of compensatory mutations can be selected to resolve the fitness conflict of pleiotropic mutations under different conditions [57] . These compensatory mutations may not exhibit adaptive effects by themselves but will be epistatic to the previous pleiotropic mutations . This hypothesis is indirectly supported by our reconstitution experiments , which showed that intergenic epistasis is common among the evolved mutations . After obtaining compensatory mutations , modified subnetworks are likely to stay in the lineage and to have a long-term influence on evolutionary paths . The fact that no mutations occurred in the Ylip-HSP90 gene indicates a strong constraint on the hub , probably due to pleiotropic effects . Therefore , evolved cells resolved the fitness conflict through modifying the functions or structures of some subnetworks . Similar processes have been observed in the evolution of transcription networks . Although different species may share the same transcription factors , the downstream targets of the orthologs could have been rewired greatly [58 , 59] . Previous studies of digital organisms have suggested that deleterious mutations might act as stepping stones for the evolution of complex phenotypes inaccessible to the wild type [60 , 61] . Our study provides direct evidence that diverse phenotypes can evolve when an essential network hub is altered . Robust networks are often connected to a larger phenotypic space [42] . An initial adaptation to a changed or compromised network hub allows a cell to reshape its network structures in different directions , which further broadens its evolutionary potential ( Fig 7 ) .
All the S . cerevisiae strains were derived from R1158 ( JYL1821 ) containing the tTA transactivator with the CMV promoter that allows us to down-regulate the expression level of the TetO7 promoter–containing gene by adding doxycycline [62] . In S . cerevisiae , the essential function of Hsp90 is performed by two highly similar and functionally redundant genes , HSC82 and HSP82 ( protein identity and similarity are 0 . 969 and 0 . 987 , respectively ) [9] . We first generated the HSP90 plasmid shuffling strain ( JYL1827 ) in which both HSC82 and HSP82 were deleted , and the essential Hsp90 functions were performed by an HSC82-containing plasmid ( pRS416-Scer-HSC82 ) . The coding regions of HSC82 and its orthologs were PCR amplified from the genomic DNA or cDNA of S . cerevisiae , N . castellii , K . lactis , or Y . lipolytica and cloned into a plasmid ( pRS413-pTetO7 ) containing the kanR-TetO7-TATACYC1 cassette from RP188 [63] . These ortholog-containing plasmids were then transformed into the shuffling strain to replace pRS416-Scer-HSC82 . The ortholog-replacement strains were checked using PCR to confirm the loss of pRS416-Scer-HSC82 and are denominated as JYL5001 ( Scer-HSC82 ) , JYL1831 ( Ncas-HSP90 ) , JYL1833 ( Klac-HSP90 ) , and JYL1835 ( Ylip-HSP90 ) . In our experiments , the orthologs of Hsp90 were all carried by the plasmid so they could be easily shuffled to check whether the observed effects are ortholog specific . For the evolution experiment , JYL5001 and JYL1835 were transformed with HindIII-linearized GFP ( pGS62 ) and DsRED ( pGS64 ) integration plasmid DNA [64] to generate green and red fluorescent protein-labeled ancestral strains . We mixed the two colored subpopulations of Ylip-HSP90 or Scer-HSC82 cells in an approximate ratio of 1:1 to establish starting cultures and then divided them into 12 evolving and 12 control lines . These cell lines were grown in YPD medium at 28°C through a daily 1 , 000-fold dilution ( about 10 generations ) with an effective population size of 4 . 69 × 105 cells on the first 140 days and 2 . 79 × 106 cells after day 140 . The effective population size was estimated using the formula , Ne = N0 × g , in which N0 is the initial population size and g is the number of generations during a single cycle of growth [65] . We tracked the proportion of the green and red subpopulations in each lineage using the BD LSR II system ( Becton Dickinson , Franklin Lakes , NJ ) . Fixation of the evolved culture is defined when either the green or red subpopulation reaches a population frequency of 95% . For the fitness spot assay on plates , around 103 cells were taken from overnight cell cultures growing in YPD at 28°C and spotted onto the plates following 10-fold serial dilutions . Plates were then incubated at specified temperatures until individual colonies became visible . Colony size and cell density were used to estimate the cell fitness and survival rate for each condition . For the fitness assay in liquid , overnight cell cultures growing in YPD at 28°C were inoculated into 120 μL fresh medium in 96-well tissue culture plates at an initial concentration of 0 . 1 OD595 , and cell densities ( OD595 ) were measured every 10 minutes using Infinite 200 series plate readers ( Tecan , Mannedorf , Switzerland ) with a shaking cycle ( 1 minute shaking and 3 minutes standing ) until the culture reached diauxic shift . Growth rates ( OD595/hour ) of the sample were calculated using the 10-point sliding window , and the maximal growth rate was used to represent the fitness value . Fitness improvement compared with ancestors was calculated as ( Fx/Fa−1 ) × 100% , where Fx is the fitness value of evolved or reconstituted clones and Fa is the fitness value of the ancestral strain . In order to uncover the functional differentiation between Hsp90 orthologs , the ortholog-replacement strains were examined under YPD at 28°C and 16 other conditions , including 0 . 015% or 0 . 03% H2O2 , 150 mM MgCl2 , 50 μM CH3COOH , 0 . 3 μM tunicamycin ( cat . no . T7765 , Sigma-Aldrich , St . Louis , MO ) , 5 mM guanidine hydrochloride ( GuHCl ) , pH 5 or pH 9 , 1 μg/mL doxycycline ( cat . no . D9891 , Sigma-Aldrich ) , 0 . 5 or 1 M NaCl , 0 . 2 M LiCl , 16°C , 34°C , or 37°C , and 1 . 8 M sorbitol . Chemicals were added into YPD to prepare media for specific conditions . Liquid fitness assays were used in all measurements . To characterize the evolved phenotypes , we measured the fitness of evolved clones under nine different stress conditions: AZC ( cat . no . A0760 , Sigma-Aldrich ) , a proline analog that can be incorporated into newly synthesized proteins and cause failure in folding or structural instability [66 , 67]; cycloheximide ( CYH , cat . no . C7698 , Sigma-Aldrich ) , which inhibits the 80S ribosome from translating mRNA into proteins [68]; BFA ( cat . no . B6542 , Sigma-Aldrich ) , which blocks protein trafficking and affects the central vacuolar secretory pathway , resulting in ER/Golgi membrane mixing [69] and an unfolded protein response [70]; high temperature ( 37°C ) and ethanol ( EtOH ) , which induce protein misfolding and change the membrane protein composition [71]; doxycycline , which reduces the expression level of Hsp90 orthologs; GuHCl , which inhibits the disaggregase activity of Hsp104 and reduces cell thermotolerance [72]; MG132 ( cat . no . C2211 , Sigma-Aldrich ) , a compound that inhibits protein degradation by blocking proteasome activity [73]; and macbecin II ( MacII , cat . no . NSC 330500 , NIH , Bethesda , MD ) , which is a compound that inhibits the ATPase activity of Hsp90 . CSM at 28°C was a suboptimal condition . Apart from CSM , as well as MG132 that was added to synthetic medium ( 0 . 17% yeast nitrogen base without ammonium sulfate supplemented with 0 . 1% proline , amino acids , 2% glucose , and 0 . 003% SDS ) [74] , all these chemicals were added into YPD medium . Liquid fitness assays were used in all measurements . We constructed pRS413-pTetO7-TAP-Scer-HSC82 and pRS413-pTetO7-TAP-Ylip-HSP90 plasmids , in which a tandem affinity purification ( TAP ) tag was fused to the N-terminus of the Hsp90 protein . These plasmids were then transformed into corresponding ancestral or evolved clones . Cell pellets were collected by centrifugation , washed once with ddH2O , and lysed using the NaOH-lysis method [75] . The anti-TAP-tag antibody ( cat . no . CAB1001 , Thermo Fisher Scientific , Waltham , MA ) was used to detect TAP-Scer-Hsc82 or TAP-Ylip-Hsp90 proteins , and the anti-G6PDH antibody ( cat . no . A9521 , Sigma-Aldrich ) was used to detect the G6PDH protein as the internal control . Ancestral Scer-HSC82 and Ylip-HSP90 strains were first transformed with the plasmid Y316v-srcv5 containing v-src with a C-terminal V5 tag under a galactose-regulated promoter [76] . Cells were then maintained on 2% glucose CSM-Ura plates to prevent the expression of v-src . Before the experiment , cells were grown to log phase in 2% glucose CSM-Ura liquid cultures , transferred to 2% raffinose CSM-Ura , and then grown to about 5 × 106 cells/mL . Cells were pelleted , resuspended in 2% galactose CSM-Ura , and grown for 6 hours to induce the expression of v-src . The whole experiment was carried out at 28°C . Cell pellets were collected by centrifugation , washed once with water , and lysed with the NaOH-lysis method . Total protein extracts were mixed with the sample buffer ( 50 mM Tris , pH 6 . 8 , 2% SDS , 10% glycerol , 0 . 004% bromophenol blue , and 2% 2-Mercaptoethanol ) and boiled at 100°C for 5 minutes . The anti-phospho-tyrosine antibody 4G10 ( cat . no . 05–321 , Merck Millipore , Burlington , MA ) was used to detect phosphorylated tyrosine residues , and the anti-V5-Tag antibody ( cat . no . MCA1360 , BioRad , Hercules , CA ) was used to detect the v-src protein . Flow cytometry was used to determine the DNA content of ancestral and evolved cells . Total 5 × 106 log-phase cells were harvested , resuspended in ice-cold fixation buffer ( 40% ethanol , 0 . 1 M sorbitol , and 5 mM EDTA ) , and then kept at −20°C overnight . The fixed cells were then washed twice with 1 mL ddH2O and then washed with 1 mL PBS + 0 . 5% Triton X-100 . After washing , the cells were treated with 0 . 5 mL 50 mM Tris-Cl ( pH 8 . 0 ) with 150 μg/mL RNase A and incubated at 37°C for 16–18 hours . SYTOX Green nucleic acid stain ( Invitrogen , Carlsbad , CA ) and 38 mM sodium citrate were mixed in a 1:800 ratio , and 300 μL of the mixture was added into the cell solution . The stained cells were diluted into 1 mL 0 . 1 M EDTA and sonicated for at least 3 minutes prior to flow cytometry . A total of 10 , 000 cells were scored for DNA content using the BD FACScan system ( Becton Dickinson ) . The E10 clone was excluded from further examination because of its altered ploidy . A blue fluorescence protein ( BFP ) cassette was amplified from the pFA6a-link-yomTagBFP2-Kan plasmid and integrated into the genome to generate an Hsp104-BFP fusion protein in all tested strains [77] . Log-phase cells growing in YPD at 25°C were transferred to a 37°C water bath and cells were collected at 0 , 1 , 2 , and 3 hours after the temperature shift . The samples were resuspended in 200 μL PBS and transferred to a Glass Bottom ViewPlate-96F ( PerkinElmer , Waltham , MA ) that was precoated with concanavalin A ( cat . no . C2010 , Sigma-Aldrich ) . Images of Hsp104-BFP foci were acquired using an ImageXpress Micro XL system ( Molecular Devices , San Jose , CA ) and analyzed using a custom-built module under MetaXpress High-Content Image Acquisition and Analysis Software ( Molecular Devices ) . Log-phase cells were harvested and washed twice with PBS , and cell walls were stained with either 25 μg/mL NHS-Rhodamine ( E3 , E5 , E7 , E8 , E9 , green Ylip-HSP90 , and Scer-HSC82 ancestors ) or NHS-Fluorescein ( E4 , E6 , E11 , and red Ylip-HSP90 and Scer-HSC82 ancestors ) ( Pierce , Rockford , IL ) for 8 minutes in the PBS buffer with 0 . 1 M NaHCO3 and 5 mM EDTA . Cells were then washed twice with PBS and sonicated for 3 minutes before 2 × 104 cells were transferred to a Glass Bottom ViewPlate-96F for image acquisition . We used Calmorph to calculate the ratio of the long versus short axes of yeast cells ( http://scmd . gi . k . u-tokyo . ac . jp/datamine/calmorph/ ) [78] . For hierarchical clustering , we divided individual fitness values by the mean of all fitness values for the same stress condition to normalize fitness data to a similar scale between conditions . We applied a hierarchical clustering method in R ( v3 . 4 . 0 ) [79] to group the evolved Ylip-Hsp90-hosting clones according to their fitness similarity between different conditions . The strain and condition dendrograms were constructed with the hclust function and the heatmap was drawn with the heatmap . 2 function in the gplots R package [80] . For PCA , fitness values were used directly , i . e . , without normalization , and the prcomp function in R was used to conduct the analysis . We used the growth rates of all evolved Scer-HSC82 and Ylip-HSP90 clones to conduct pairwise Pearson correlations between each condition . The Pearson correlation distance ( d = 1 − Pearson’s correlation coefficient ) is used to represent the phenotypic distance between each pair of conditions . A large d means the fitness distributions of evolved clones have very different patterns in two conditions . We used the fviz_dist function of the factoextra package in R to draw the heatmap [81] . Yeast genomic DNA was isolated using the previously described phenol/chloroform method with one more run of 200 μL of PCIA resuspension and 95% ethanol precipitation to remove the residual RNase A [82] . Isolated genomic DNA was fragmented using a Covaris microTUBE M220 Focused-ultrasonicator ( Covaris , Worburn , MA ) and DNA libraries were prepared using a TruSeq DNA PCR-Free HT Library Prep Kit ( Illumina , San Diego , CA ) . Ancestral and each evolved Ylip-HSP90 clone was sequenced to an average depth of 100-fold coverage with a rapid-mode Illumina HiSeq 2500 system ( 250 bp paired-end reads ) and the spore pools were sequenced to an average depth of 200-fold coverage with the NextSeq 500 system ( 150 bp paired-end reads ) . For single nucleotide polymorphism ( SNP ) analysis , raw reads were mapped , and SNPs with coverage greater than 20-fold and a frequency higher than 35 ( for the segregant analysis , the allele frequency threshold was lowered to 10 to include more low-frequency evolved mutations ) were called using CLC bio software ( CLC bio , Aarhus , Denmark ) . Evolved mutations were manually identified by comparing the mutation lists between evolved and ancestral Ylip-HSP90 clones , and poor-quality SNPs were excluded after manual checking using the Integrative Genome Viewer [83] . Two kinds of mutations were further excluded from our evolved mutation list ( S4 Table ) : double-called SNPs due to overlap between two open reading frames , and SNPs ( grx3-A196V , hop1-K510fs , isu1-I100V , and rsf2-C966G ) shared by multiple evolved clones that were likely to be pre-existing SNPs in the ancestral population . For copy number variation ( CNV ) analysis , raw reads were mapped via BWA-MEM and CNVs were analyzed via the SAMtools program [84] . The copy number of each gene was calculated by normalizing gene coverage by the median of whole genome coverage derived from the SAMtools bedcov module . Genes with copy number variation greater than 0 . 8 compared with the ancestral strain were selected and the fold-change is provided in S7 Table . E4 , E5 , and E7 clones were backcrossed to the ancestral strain and the diploids were sporulated . Tetrads were dissected and only spores from four-viable spore tetrads were used . The fitness of F1 haploid progeny was examined under the following conditions: YPD at 28°C , YPD at 37°C , and YPD + GuHCl at 28°C . The latter two conditions were included because they had a better resolution to separate the ancestral and evolved phenotypes . F1 haploid progenies with fitness similar to the evolved or ancestral clones were assigned into good or bad spore pools , respectively . A maximum of one good and one bad spore was selected from a single tetrad . If all four progeny from a single tetrad had fitness that deviated from the evolved and ancestral strains , then none were selected . Individual E7 spores behaved similarly under the high temperature and GuHCl conditions ( r = 0 . 851 , Pearson correlation ) . When cells behaved differently under two conditions , we used the more prominent phenotype of the evolved clone to select the spores ( i . e . , fitness at 37°C for E4 and fitness in GuHCl-containing medium for E5 ) . We picked 5–20 spores for each pool and employed Illumina sequencing to examine the mutant allele frequency ( S9 Table ) . The two frequency thresholds used to select the mutations with strong effects were determined based on computational simulations following the previous method [85] . The 90% , 95% , and 99% percentiles of 10 , 000 times of simulations with the coverage of 200 and pool size N = 5 , 9 , 10 , 18 , and 21 were listed in S10 Table . We selected the threshold frequency that approximated to N = 9 as the general criteria for all three analyzed evolved clones . The genes containing protein sequence mutations from all evolved Ylip-HSP90 clones were subjected to Gene Ontology ( GO ) analysis using Yeast GO-Slim Process embedded in Saccharomyces Genome Database ( SGD: https://www . yeastgenome . org/ ) . GO categories with only one gene were excluded . Enrichment scores ( Table 1 and S8 Table ) were calculated by dividing the proportion of mutated genes classified into the indicated category by the proportion of those in the genome background . Significance of enrichment was analyzed using hypergeometric test ( phyper module ) in R [79] , and p-values were adjusted using the Benjamini Hochberg method [86] . We excluded genes with uncharacterized function or dubious open reading frames , including YLR345W , YEL034C-A , YMR102C , YLR419W , YOL166C , and Q0182 . To understand the functional relationship between the mutated genes and Hsp90 , we constructed the functional network between them . The genetic and physical interactions of Hsp90 were first constructed using STRING’s website ( https://string-db . org/ ) , and then each interacting pair was confirmed using the information from the SGD ( https://www . yeastgenome . org/ ) . We manually incorporated the up- and down-regulated protein-level data from a proteomics analysis [17] to make the regulatory network more complete . Gene functional groups shown in Fig 5 were derived from enriched GO categories and gene-specific description in SGD . The interaction network was constructed with both S . cerevisiae Hsp90 coding genes and all genes that contain protein-sequence-changing mutations in evolved Ylip-HSP90 clones using the cytoscape software [87] . Evolved mutations were reconstituted in the ancestral shuffling strain carrying the pRS415-pTetO7-Ylip-HSP90 plasmid ( S12 Table ) . The CRISPR-Cas9 system was modified from previous methods [88 , 89] . The guide RNA expression plasmid pRS426-gRNA-AB was modified from pRS426-gRNA . CAN1 . Y [88] , with BamHI and EcoRI cutting sites added to both sides of the gRNA sequence . pRS426-gRNA-AB was linearized by BamHI and EcoRI digestion . Guide RNA was amplified by two-fragment fusion PCR using four primers: IgRNAAB-F , target gene gRNA-R , target gene gRNA-F , and IgRNAAB-R ( S12 Table ) . Donor DNA sequences were around 300–600 bp in length and were PCR amplified from the evolved clones . The original plasmid carrying the high-specificity Cas9 nuclease , eSpCas9 ( 1 . 1 ) [90] , was obtained from Addgene ( plasmid number 71814 , Cambridge , MA ) and the Cas9 nuclease was further subcloned into the yeast pRS414 vector in our lab . MDM12 and BRE5 mutations were constructed using the wild-type Cas9 nuclease from Dr . George Church’s group [88] . CRISPR-Cas9-reconstituted clones were screened by PCR with either Donor F or R primer and an allele-specific primer that has the mutation site at the last position of the 3′ end and a mismatched nucleotide at the third last position to decrease the tendency of nonspecific annealing [91] . Fitness data were obtained by measuring at least three independent CRISPR-reconstituted clones . | Biological processes in living cells are often carried out by gene networks . Hubs are highly connected network components important for integrating signal inputs and generating responsive functional outputs . Heat shock protein 90 ( Hsp90 ) , a versatile hub in the protein homeostasis network , is a molecular chaperone essential for cell viability in all tested eukaryotic cells . In yeast , about a quarter of the expressed proteins are profoundly influenced when Hsp90 activity is reduced . Despite its pivotal role , we found that the function of Hsp90 has diverged between two yeast species , Yarrowia lipolytica and Saccharomyces cerevisiae , which split about 270 million years ago . To understand the impacts and adaptive strategies in cells with an altered network hub , we conducted laboratory evolution experiments using a S . cerevisiae strain in which native Hsp90 is replaced by its counterpart in Y . lipolytica . We observed different fitness gain or loss under various stress conditions in individual evolved clones , suggesting that cells adapted via different evolutionary paths . Genome sequencing and mutation reconstitution experiments show that beneficial mutations occurred in multiple Hsp90-related pathways that interact with each other . Our results show that a perturbed network allows cells to evolve a broader range of phenotypic diversity unavailable to wild-type cells . | [
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"... | 2018 | Heterologous Hsp90 promotes phenotypic diversity through network evolution |
The relationship between poor sanitation and the parasitic infection schistosomiasis is well-known , but still rarely investigated directly and quantitatively . In a Brazilian village we correlated the spatial concentration of human fecal contamination of its main river and the prevalence of schistosomiasis . We validated three bacterial markers of contamination in this population by high throughput sequencing of the 16S rRNA gene and qPCR of feces from local residents . The qPCR of genetic markers from the 16S rRNA gene of Bacteroides-Prevotella group , Bacteroides HF8 cluster , and Lachnospiraceae Lachno2 cluster as well as sequencing was performed on georeferenced samples of river water . Ninety-six percent of residents were examined for schistosomiasis . Sequence of 16S rRNA DNA from stool samples validated the relative human specificity of the HF8 and Lachno 2 fecal indicators compared to animals . The concentration of fecal contamination increased markedly along the river as it passed an increasing proportion of the population on its way downstream as did the sequence reads from bacterial families associated with human feces . Lachnospiraceae provided the most robust signal of human fecal contamination . The prevalence of schistosomiasis likewise increased downstream . Using a linear regression model , a significant correlation was demonstrated between the prevalence of S . mansoni infection and local concentration of human fecal contamination based on the Lachnospiraceae Lachno2 cluster ( r2 0 . 53 ) as compared to the correlation with the general fecal marker E . coli ( r2 0 . 28 ) . Fecal contamination in rivers has a downstream cumulative effect . The transmission of schistosomiasis correlates with very local factors probably resulting from the distribution of human fecal contamination , the limited movement of snails , and the frequency of water contact near the home . In endemic regions , the combined use of human associated bacterial markers and GIS analysis can quantitatively identify areas with risk for schistosomiasis as well as assess the efficacy of sanitation and environmental interventions for prevention .
The culture of common fecal organisms such as coliforms and enterococci from surface waters has historically been used as a proxy for the risk of infection with viral , bacterial , and parasitic pathogens [1] . It forms the standard for the United States Environmental Protection Agency's criteria for water quality [2] . Despite the well-studied association between fecal contamination of water and acute enteric and skin diseases [2] , [3] , a correlation between these bacterial proxies and specific disease causing organisms has been difficult to demonstrate in the absence of a point-source such as sewage outflows [4] . Known limitations that could explain this weak association include the short survival of some fecal indicator organisms in water [5] , their presence in environmental sources including soils and sediments [6] , [7] , contributions from non-human sources , and low sensitivity of detection methods for some pathogens [6] , [7] . The short incubation and shedding periods of these infections may also cause the pathogenic organism to no longer be present in sampled water by the time an investigation is undertaken . Molecular methods have been developed to address some of these weaknesses . Most current approaches involve PCR amplification of bacterial rDNA taken directly from specific hosts or sources of fecal contamination without prior culture . Fecal anaerobic bacteria are some of the most promising alternative indicators to Escherichia coli and enterococci . They are more abundant than coliforms , they do not multiply in the water column , and some sub-species or strains are more specific for host sources [8]–[12] . One of the most commonly employed and reliable indicators for human fecal pollution are human Bacteroides originally described as the HF8 cluster [13] , [14] . A concern remains as to the distribution of these markers originally developed in the US and other developed countries and whether they can be associated with disease risk in other parts of the world [15] . In contrast to most waterborne bacterial and viral infections , schistosomiasis is a chronic parasitic infection that results from skin contact with water as opposed to ingestion . It is a global disease that is transmitted in 78 countries with 240 million people infected [16] . In Brazil , where it is the second most common cause of morbidity and death due to parasitic infection [17] , Schistosoma mansoni is the only human species transmitted . Its transmission in common with other waterborne diseases is dependent on human fecal contamination of fresh water . Thus , in Brazil at a national scale the distribution of schistosomiasis maps to areas with the poorest level of sanitation [18] . The parasite is able to establish a long-term infection ( 5–40 years ) that produces hundreds to thousands of eggs per day , most of which will be eliminated in the feces [19] . An obligate step in transmission is development in a host snail , so that there can be no direct temporal connection between fecal contamination and human infection . Snails movements , however , are extremely restricted geographically [20] and in this way past contamination and infection events are registered locally in chronic human infections . Given the complex life cycle of this parasite and its long-term survival in a community , bacterial indicators that track human sources of fecal contamination in water may contribute much to our understanding of the transmission dynamics of the parasite . Since snail infection with S . mansoni is dependent on human fecal contamination of surface waters , the probability of snail infection and differences in the spatial distribution of human schistosomiasis is likely to correlate with differences in the concentration and distribution of this contamination . We tested this in one small community in Northeastern Brazil .
The Committee on Ethics in Research of the Oswaldo Cruz Foundation of Salvador , Bahia , the Brazilian National Committee on Ethics in Research , and the Institutional Review Board for Human Investigation of University Hospitals Case Medical Centre , Cleveland , Ohio approved the study design . Study participants provided written informed consent . Animal owners provided permission to collect the stool samples of their animals . The village of Jenipapo in the state of Bahia , Brazil was selected for study because of its high prevalence of S . mansoni infection , the geographic distribution of its human population around surface waters , and its relative isolation from other settlements . The village is split north and south by the Jiquiriçá River and a two-lane highway . The Brejões River descends from the north , borders part of the village on the west , and enters the Jiquiriçá River at approximately the village midpoint ( Fig . 1a ) . Within Jenipapo , the Jiquiriçá River measures 5–10 meters across and less than 1 m deep , with areas of bare rock as well as thick aquatic vegetation . The Brejões is narrower and shallower , but still perennial . Most houses are located within 20 meters of these rivers . Topographically , the region is a narrow river valley with approximately equal elevations on both sides . Commercial activity is primarily devoted to raising livestock along with planting cassava , beans , and bananas . Demographic data and prevalence of schistosomiasis was obtained from interviews and a fecal survey of all residents of the village in 2009 . The description of the community has been published previously [21] , [22] . The location of each home and human water contact sites in the community was registered with a hand-held Trimble/Nomad GPS unit ( Model 65220-11 ) . The course of the river within the village was surveyed by walking along one bank . Data were imported into ESRI ArcGIS 10 . 0 ( Redlands , CA ) for mapping and analyses . Kernel density estimation was used to assess and display the spatial density of the human population , schistosome infection , and river use for sewage disposal . The Moran's I statistic was calculated using the Spatial Autocorrelation Tool in ArcGIS to assess spatial clustering . The collection and processing of human fecal samples of the residents of Jenipapo was described previously [22] . Briefly , all inhabitants of the community >1 year of age were asked to enroll in the study , and in addition to answering a questionnaire , they provided a stool on 3 different days . A single slide was prepared by the Kato-Katz method [23] . Microscopists trained for parasitological studies read one slide per sample , and from this the number of eggs per gram of stool ( epg ) in each sample was determined . Participants with one or more egg-positive stools were treated with praziquantel at dosages recommended by Brazilian Ministry of Health . One ml of each sample was placed in culture media ( 3M Petrifilm E . coli/Coliform Count Plate , 3M , Saint Paul , MN ) for 24 h at 37°C and counted for colony forming units ( CFUs ) of total coliforms and E . coli . Six different qPCR assays were used in extracted DNA of all collected water samples for identification and quantification of fecal bacteria indicative of human or ruminant sources ( Table 1 ) . All qPCR assays were amplified in 25 µl reactions using 12 . 5 µl TaqMan Master mix , 1 . 0 µl 25 µM primer mixtures , 1 . 0 µl 2 µM probe mixtures , 5 . 5 µl water and 5 . 0 µl of DNA . Assays were carried out as previously described in the referenced literature in Table 1 . All assays were run in duplicate . Deep sequencing using the Illumina MiSeq platform was carried out at the Josephine Bay Paul Center of the Marine Biological Laboratory . A comprehensive microbial community profile was generated for five river samples , ten human fecal samples , and all collected animal fecal samples . The V6 hypervariable regions of the 16S rRNA gene were amplified in each of the samples using previously described primers and protocols [25] . Sequences were trimmed , controlled for low quality and contaminated reads , and then aligned . Nearly 27 million bacterial sequence reads were generated ( ∼1 million reads per sample ) . The sequence data were further processed and stored in the Visualization and Analysis of Microbial Population Structures ( VAMPS ) database ( http://vamps . mbl . edu ) [26] . Taxonomic assignments were made for all sequences using Global Alignment for Sequence Taxonomy ( GAST ) [27] . Further analysis of sequence data is reported in [28] and sequence data is available in the National Center for Biotechnology Information ( NCBI ) Short Read Archive under the accession number SRP041262 . To assess the proportion of bacterial community members that are potentially amplified by the human-indicative fecal indicator assays , a BLAST search was performed against the Illumina sequence data sets with the HF8 and Lachno2 primers [29] . Since the primers for the human-indicative assays are in regions of the 16S rRNA gene different from or only encompasses a larger region that the V6 sequences , the HF8 and Lachno2 primers were BLASTed against the complete reference sequences dataset that corresponded to the shorter V6 sequences . The V6 sequencing reads , each a proxy for a bacterial community member , were then binned within the HF8 cluster or Lachno2 cluster if their corresponding reference sequences contained both the forward and reverse primers and the probe sequences for the assays . To examine the association between proximity to fecally contaminated water and schistosomiasis , a linear regression model was created with SPSS version 19 and ArcGIS 10 . 1 . For the model , we made the following simplifying assumptions: 1 ) infection occurs at the common water contact sites , 2 ) probability of infection depends only on proximity of place of residence to a water contact site , 3 ) distribution of snails along the river is homogeneous , and 4 ) prevalence of snail infection is proportional to degree of human fecal contamination in water . In order to associate spatial distribution and the prevalence of S . mansoni , the residential area of Jenipapo was mapped as a grid of 200 m2 blocks . The density of human population and density of number of cases of schistosomiasis per block was calculated using the point density tool in ArcGIS . The prevalence of schistosomiasis within each block was obtained by calculating the ratio of these two values using the Map Algebra tool . All houses within a 200 m2 block along the river were assigned the mean prevalence for that block . This spatial prevalence for each household then comprised the dependent variable in the linear regression . The independent variable was the risk of exposure to fecal contamination . To assign a value for fecal exposure for each household , spatial interpolation of two fecal marker DNA concentrations measured from the eight-water sample sites was performed using Inverse Distance Weighting ( IDW ) . The village was divided into a two-dimensional grid of cells whose values were a function of their distance from a water contact site and the concentration of a fecal contamination marker at that site . A power of 2 was determined to be the best value for the weighting exponent by distance with a cell size of 20 m . Since human fecal contamination of water is necessary for transmission of S . mansoni , we hypothesized that a human-indicative fecal marker ( Lachno2 ) would be a better predictor of schistosome infection than a general fecal marker , i . e . E . coli . Consequently , E . coli and Lachno2 estimated concentrations at each resident's location were extracted from the IDW generated surface to obtain an E . coli-IDW and Lachno2-IDW value for each home . Water samples were not taken from the Brejões River , thus , the section of the community bordering the Brejões was not included in the analysis . The relationship of fecal contamination to prevalence of schistosomiasis was then assessed by standard linear regression . The model significance was determined by bootstrapping with 1000 resamples at the household level .
In 2009 , Jenipapo consisted of 128 houses with 482 residents . Twenty-three residents had no house assigned , hence were not included in the analysis ( Table 2 ) . More than 98% of residents had tap water and an indoor flush toilet . There was access to adequate sanitation for 201 ( 43 . 8% ) via home septic tanks , while sewage drained directly into the river for the remaining 258 ( 56 . 2% ) . Schistosomiasis was found in 209 individuals ( 45 . 5% ) by examination of 3 stools collected on different days [22] . The geometric mean of intensity ( 57 epg ) indicates that infections are generally light and comparable to other studies in Brazil [30] . Ten percent of the infections were heavy ( >400 epg ) . The Jiquiriçá River flows from west to east , and its course measures 1542 meters from the upstream sampling site to the downstream site . There is one formal bridge across the river at the point where the Brejões River enters the Jiquiriçá . Human water contact sites were primarily used to cross the river as well as for bathing , washing clothes , or fishing ( Fig . 1a ) . The majority of houses are located on the south bank . Kernel density estimation shows clustering of human population density at both ends of the village along the south side of the Jiquiriçá River , but the greatest density clustered along the Brejões ( Fig . 1b ) . The distribution of houses with sewage draining directly into the river ( Fig . 1c ) , however , were not clustered based on Moran's I statistic , which fell within the 95% confidence interval of the null hypothesis ( random spatial distribution ) as indicated by a low z-score ( Moran's index = −0 . 013 , p = 0 . 847 , z = −0 . 19 ) . In contrast , for the prevalence of schistosomiasis , kernel density estimation shows clusters located along the Brejões River and for people living along the most downstream segment of the village ( Fig . 1d ) . The positive Moran's index with a high z-score and low p value indicated that the distribution of schistosomiasis was not random ( Moran's index = 0 . 042 , p = 0 . 006 , z = 2 . 74 ) . The 16S rRNA sequencing reads of extracted DNA from fecal samples of ten humans and all collected animal fecal samples were normalized against their maximum number of reads and queried for the human-indicative Bacteroides HF8 and Lachno2 clusters . Overall , humans had considerably lower amounts of Bacteroides in relation to Lachnospiraceae or more specifically , Blautia ( one genera within Lachnospiraceae from which the Lachno2 assay was designed ) . Despite the low amount of overall Bacteroides in humans , the HF8 sequence represented 28% of all Bacteroides sequences . Overall , the proportion of sequence reads matching the HF8 cluster in humans was 10-fold higher than for pigs and dogs , and 100-fold higher than for horses and cows . The Lachno2 cluster showed even higher specificity with the proportion of reads in humans ∼100-fold higher than three animal sources , but ∼10-fold higher than for horses ( Table 3 ) . Using qPCR , the concentration of the Bacteroides-Prevotella group was at its lowest ( <2 . 7×105 copies/100 ml ) from site S1 , located upstream of the first house of the village , through site S3 ( Fig . 2 ) . There was a steep increase at S4 to 4 . 8×105 copies/100 ml . The highest concentration was found at S5 ( 5 . 4×105 copies/100 ml ) , where the Brejões River joins the Jiquiriçá . Its concentration then decreased gradually and by S8 , located downstream of the last house , the concentration of this general fecal marker had returned to a value similar to S1 ( 2 . 7×105 ) . The human-indicative markers ( HF8 and Lachno2 ) followed a similar distribution , however , concentrations increased one site further downstream compared to the Bacteroides-Prevotella group marker . The HF8 marker was undetectable until site S5 , at which point it also reached its peak ( 0 . 9×104 copies/100 ml ) , followed by a gradual decline . Lachno2 was detectable in minimal quantities at sites S1 to S4 ( maximum concentration 684 copies/100 ml ) , and also had a marked increase by site S5 . The peak Lachno2 concentration was at site S7 ( 1 . 6×104 copies/100 ml ) , which is the last site downstream in Jenipapo that humans utilize to cross the river , and declined by S8 . The ruminant-indicative marker was undetectable until S5 and remained in low concentrations without significant variation between sites thereafter . The E . coli marker showed a smaller degree of increase after S5 . By contrast , the source of drinking water located 4 . 8 km north of the village had no copies of the HF8 human-indicative marker; other assays were not performed on this sample . Colony counts for coliforms , and less so for E . coli , also increased as the river moved down stream and declined sharply past the last house in the village ( Fig . 3 ) . Sequence data from the microbial communities found in river water was used to compare the relative abundance of >20 bacterial families . Consistent with the qPCR results , the proportion of Prevotellaceae and Lachnospiraceae increased significantly in the downstream portion of the village ( Fig . 4 ) . Ruminococcaceae and Enterobacteriaceae , two other families associated with fecal communities , also increased . These combined fecal families increased their representation from ∼3% to ∼9% of all bacterial community between upstream to downstream sites . Families associated with sewage- contaminated water - Moraxellaceae and Aeromonadaceae , specifically Acinetobacter spp . and Aeromonas spp . [31]–[34] - also increased at sites six and seven . Comamonadaceae , a bacteria common to the environment and freshwater [35] , was the most abundant family on average , accounting for over 40% of the microbial community populations at each sampling site . Bacteroidaceae , which includes the genera Bacteroides , were in low abundance and are not represented in Figure 4 . The 200 m2 schistosomiasis prevalence grid for Jenipapo produced 7 blocks ( Fig . 5 ) . Each house was assigned a value for exposure to fecal contamination based on proximity to a water sample site and the fecal marker concentration at site . The relationship of risk for infection with S . mansoni to the concentration and proximity to fecal contamination was modeled and tested statistically using the data from Jenipapo . Linear regression of prevalence of schistosome infection against fecal contamination yielded an r2 of 0 . 28 for the E . coli-IDW value ( two-tailed p<0 . 001 , 95% CI 0 . 22–0 . 35 ) and 0 . 53 for the Lachno2-IDW value ( two-tailed p<0 . 001 , 95% CI 0 . 48–0 . 58 ) . These results can be interpreted as local concentration of human fecal contamination explaining over 50% of the variance in risk for schistosomiasis .
Although the village of Jenipapo is small , it is typical of many villages of Latin America . It also shares a pattern of development common with larger communities and even the great metropolises of Brazil . The village grew up along the two rivers that meet at its center , and most homes border these rivers in part to have access to a ready form of sewage removal . The community's drinking water supply is 4 . 8 km away where a dammed stream forms a small reservoir . Jenipapo's geometry is a simple , mostly linear distribution of residences and water contact sites , and this made it ideal for studying the dynamics of fecal contamination and its relationship to acquisition of schistosomiasis . Putting the degree of fecal contamination of the Jiquiriçá River within Jenipapo in context , the geometric mean CFUs for E . coli ( 113 CFU/100 ml ) was at the upper limit of the EPA's 2012 Recreational Water Quality Criteria value of 100 CFU/100 ml [2] . This level of contamination was estimated to result in 32 gastrointestinal illnesses per 1000 primary recreational contacts . We were further able to identify human waste as the major contributor to this contamination . We validated both the HF8 and Lachno2 genetic markers as human-indicative by directly assaying the resident population . Interestingly , both human-indicative markers were identified from humans in the US , but were also significantly associated with humans in Brazil . The frequency of members of the Prevotella complex were higher in this rural Brazilian population than in communities in countries like the US and Italy where fat and protein form more of the diet than cereals , with Bacteroides a minor component of the human samples . In all human communities , including hunter gatherers , the Lachnospriaceae group , however , is more similarly represented [36] . In comparison with other human indicative markers , Lachno2 showed a high signal in the water sample and all human feces , but near absence in cows , the other major animal contributing to fecal contamination of the river . These markers indicated that human waste was the major contributor of fecal contamination in this section of river . Overall , human-indicative fecal indicators contribute important quantitative information on water quality that could be used for surveillance to gauge specific sanitation interventions . The nearest community to Jenipapo is 8 km upstream with a population of 353 and similar level of sanitation , and there are few intervening houses , but many areas of pasture . Twelve km further upstream there is a town of 12000 . Despite nearby populations , quantitative tracking of human fecal contamination in this study suggests a predominance of local effects . The qPCR markers for human and other fecal contamination , as well as coliform colony counts , are very low at the entrance to the village and significantly increase as the river continues downstream . Inflow for the village has significant levels of the Bacteroides-Prevotella group , but is very low for human fecal contamination indicating that most influence from communities upstream has dissipated . We presume this is not the result of the HF8 marker being sensitive to environmental degradation , since experimentally the duration of signals from Bacteroides ranges from days to several weeks [37] . In addition , the other marker of human fecal contamination ( Lachno2 ) shows a similar pattern . Within Jenipapo , the entry of sewage is not clustered to one area of the community , and we noted the concentration of contamination is cumulative as the river moves downstream through the village . The analysis of bacterial communities was based on number of sequence reads and is consistent with the qPCR genetic marker data . The study is limited in the relatively small number of samples taken , sampling only ∼50 m beyond the community's houses and a lack of household water samples . Also the human and animal samples were handled differently , but the distribution of bacterial families is consistent with other studies of the human gut biome [38] . A major strength of the study is the use of markers highly informative for the presence of human feces . Traditional indicators , such as E . coli culture and PCR , are able to demonstrate some of the same distribution pattern as HF8 and Lachno2 , but the better model fit using Lachno2 demonstrates that higher tier assessments like qPCR for human indicative markers may provide better linkages between disease and human sources . Human fecal contamination of water and the presence of snails are prerequisites for transmission of schistosomiasis . Snails are known to have a limited range of movement [39] . Proximity to water bodies where there are infected snails is a known risk factor for schistosomiasis [40] , [41] . However , all inhabitants in Jenipapo are essentially equidistant from the river , and finding and determining which snails are infected can be laborious . In this study we show that , in a village with high prevalence of schistosomiasis , the risk of acquiring the infection is driven not only by proximity to surface water but also by its degree of human fecal contamination . The model explained a large amount of variation without including data on snail populations . We also observed that parasite populations were genetically more similar among infected members of the same household compared to parasite populations of all infected individuals in the village [21] , which further supports the local , household level of acquisition . The variation not explained by our model was likely due to violations of our simplifying assumptions . Snails are not likely to be evenly distributed , and infection risk is influenced by more than distance to a contact site ( age , type of activity , etc . ) . Some infection occurs outside of contact sites or not at the nearest contact site . Although the human population disperses widely over this area , the local opportunities for exposure near the home may dominate the infection risk profile . Since awareness of schistosomiasis has been raised in the community and well before the analysis of fecal contamination , we have heard reports that teenage boys now prefer to enter the river upstream of the village . This may be a wise precaution , although the better solution will be to remove the contamination from the river rather than remove the boys and girls . | People tend to live close to natural water bodies , and often these water bodies are used as waste disposal in many regions of the world . The consequences of this are often studied with regard to bacterial and viral infections , but rarely for parasitic infections . In this study the authors examined a rural community settled along a river in Brazil , and found that the concentration of fecal bacteria in water accumulates as the river runs downstream . Molecular methods were able to show that most of these fecal bacteria were of human origin rather than from local livestock or other domestic animals . To assess the impact of fecal contamination of surface waters , the authors investigated its association with schistosomiasis , a parasitic infection transmitted by snails exposed to water contaminated by human feces . Similar to the distribution of fecal contamination , the proportion of people with schistosomiasis was higher in areas located downstream . A model combining concentration of human fecal bacteria in water and Geographic Information Systems ( GIS ) analysis of schistosomiasis prevalence showed that areas of increased concentration of human feces correlated with areas in the village at higher risk for schistosomiasis . This research provides insight into the dynamics of fecal contamination of rivers and its spatial impact on a human parasitic disease . | [
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"nature-society",
"interacti... | 2014 | Sources and Distribution of Surface Water Fecal Contamination and Prevalence of Schistosomiasis in a Brazilian Village |
The outcome of malaria infection is determined , in part , by the balance of pro-inflammatory and regulatory immune responses . Failure to develop an effective pro-inflammatory response can lead to unrestricted parasite replication , whilst failure to regulate this response leads to the development of severe immunopathology . IL-10 and TGF-β are known to be important components of the regulatory response , but the cellular source of these cytokines is still unknown . Here we have examined the role of natural and adaptive regulatory T cells in the control of malaria infection and find that classical CD4+CD25hi ( and Foxp3+ ) regulatory T cells do not significantly influence the outcome of infections with the lethal ( 17XL ) strain of Plasmodium yoelii ( PyL ) . In contrast , we find that adaptive IL-10-producing , CD4+ T cells ( which are CD25− , Foxp3− , and CD127− and do not produce Th1 , Th2 , or Th17 associated cytokines ) that are generated during both PyL and non-lethal P . yoelii 17X ( PyNL ) infections are able to down-regulate pro-inflammatory responses and impede parasite clearance . In summary , we have identified a population of induced Foxp3− regulatory ( Tr1 ) T cells , characterised by production of IL-10 and down regulation of IL-7Rα , that modulates the inflammatory response to malaria .
The erythrocytic stage of malaria infection is characterised by the development of strong pro-inflammatory immune responses which , although required to control parasite replication and promote clearance of infected erythrocytes , must be tightly regulated to prevent the immune-mediated pathology which is integral to the development of the severe complications of infection in humans and in a number of well-characterised animal models [1]–[3] . Previous studies have highlighted important roles for IL-10 and TGF-β in regulating the pro-inflammatory response during malaria infection [4]–[11] . Thus , although IL-10−/− and TGF-β-depleted mice are able to control parasite replication during P . chabaudi AS infection as effectively as WT mice , unlike WT mice they develop severe TNF-mediated pathologies which are typically fatal [4] , [9]–[11] . Similarly , IL-10 can prevent the onset of cerebral malaria in P . berghei ANKA-infected mice [8] . However , the exact role of IL-10 and TGF-β appears to vary between infections with different malaria species and strains , depending on the timing of cytokine production in relation to disease progression . Thus , production of TGF-β and IL-10 during the first few days of a lethal P . yoelii 17XL ( PyL ) infection is associated with inhibition of pro-inflammatory responses , rapidly escalating parasitaemia and death [5] , [7] . In contrast , mice infected with the non-lethal variant ( P . yoelii 17X; PyNL ) produce no or only low levels of TGF-β and IL-10 during early acute infection and eventually control their parasitaemia [5] . Blockade of IL-10R signalling in combination with anti-TGF-β treatment restores the type-1 immune response during lethal P . yoelii infection , and a proportion of infected animals are able to control their infections and survive [5] . Moreover , splenocytes from susceptible BALB/c mice , but not resistant DBA/2 mice , infected with PyNL produce IL-10 and TGF-beta during the early acute stage of infection , which is associated with an increase in the proportion of splenic CD25+ CD4 T cells [12] . Taken together , these studies demonstrate a causal role for immunoregulatory cytokines in suppressing parasite clearance mechanisms . In accordance with these findings , a study by Hisaeda and colleagues indicated that differential activation of natural regulatory T cells ( nTreg ) may account for the differing virulence of P . yoelii strains , since depletion of CD4+CD25hi T cells ( with anti-CD25 antibody ) prior to infection converted PyL from a rapidly lethal infection into a resolving infection but had no effect on the course of PyNL infection [13] . Although first identified as cells that limit autoimmune pro-inflammatory responses [14] , nTreg ( defined by expression of CD4 , the transcription factor Foxp3 and high levels of CD25 ) have since been shown to regulate the immune response in a number infections including Leishmania spp infections , Mycobacterium tuberculosis and helminth infections [15]–[18] , mediating their effects either via direct cell contact or by release of cytokines . However , it is now becoming apparent that both adaptive ( Foxp3− ) regulatory T cell populations and classical T-bet expressing Th1 cells also play crucial immunoregulatory roles during infection and mediate their effects through secretion of IL-10 [19]–[21] . In this study we have examined the generation and function of both nTreg and adaptive IL-10-secreting T cells during malaria infection . We observe equivalent expansion of natural Foxp3+ regulatory T cells during both lethal and non-lethal P . yoelii infections but , using either anti-CD25 treatment or adoptive transfer of purified CD25hi/Foxp3+ nTreg or CD25−/Foxp3− non-Treg T cell populations , we find no role for nTreg during PyL infection . Conversely , we demonstrate that populations of adaptive regulatory CD4+ T cells , that are CD25− , Foxp3− and CD127− , and which do not make IFN-γ , IL-4 or IL-17 , develop during both PyL and PyNL infections . These cells inhibit parasite clearance but , importantly , also prevent the development of pathology via production of IL-10 . These data are consistent with the notion that whilst endogenous populations of nTreg may be sufficient to prevent immune-mediated pathology during chronic infections which induce rather modest inflammatory responses , such as avirulent leishmania , tuberculosis or helminth infections , rapid induction of distinct populations of adaptive/Th1 CD4+ T cells producing IL-10 may be required to counter the powerful inflammatory signals provided by virulent , rapidly replicating pathogens .
In accordance with previous observations [5] , [22] , infection of C57BL/6 mice with 104 P . yoelii 17XL ( PyL ) parasites was associated with a rapid onset of fulminant parasitaemia ( approaching 100% by day 7 pi ) that was universally fatal ( Figure 1A , B ) . In contrast , infection with 104 P . yoelii 17X ( NL ) ( PyNL ) parasites led to a more gradual increase in parasitaemia with peak parasitaemia of approx . 30% on day 14 pi , before the infection eventually resolved . Significant differences in malaria-induced anaemia were also evident between lethal and non-lethal infections , with more rapid onset and increased severity of anaemia occurring in PyL-infected mice compared with PyNL-infected mice ( Figure 1C ) . We have previously reported that simultaneous neutralisation of TGF-β and blockade of IL-10 signalling allows a proportion of PyL-infected mice to resolve their infections and survive [5] , suggesting that active immune regulation/immune suppression occurs during PyL infection that inhibits optimal parasite control . In agreement with these observations , Kobayashi et al [7] have reported that IL-10 is produced very early during PyL ( but not during PyNL ) infection and Perry et al [23] have reported a switch from IL-12 ( at day 3 pi ) to IL-10 ( at day 17 pi ) production by splenic dendritic cells during the course of a non-lethal Py infection . These data are consistent with the hypothesis that protective pro-inflammatory responses develop during the acute phase of PyNL infection that limit parasite numbers , whereas an early anti-inflammatory cytokine response during the acute phase of PyL infection inhibits the development of protective immune responses . As CD4+CD25+ regulatory T cells ( nTreg ) have been reported to regulate immunity in a number of auto-immune and infectious diseases [14]–[18] and can exert their regulatory role through secretion of IL-10 and/or TGF-β we investigated , using intracellular staining for Foxp3 as well as transgenic Foxp3-GFP reporter mice [24] , whether nTreg activation is correlated with the virulence of PyL infection . CD4+ splenic lymphocytes from uninfected ( control ) mice , or from PyL- or PyNL- infected mice , were analysed for intracellular Foxp3 expression ( Figure 2A ) and the numbers of CD4+Foxp3+ cells , the expression levels of Foxp3 and the ratios of CD4+Foxp3+ ( nTReg ) to CD4+Foxp3− ( non-regulatory T cells ) were assessed over the first 7 days pi ( Figure 2B–D ) . In accordance with previous observations [25] a significant increase in the numbers of splenic CD4+Foxp3+ nTreg was observed during the first 5 days of PyL infection ( Figure 2B ) and this was accompanied by increased levels ( MFI ) of Foxp3 expression ( Figure 2C ) and a transient increase ( on day 3pi ) in the nTreg/non-Treg ratio ( Figure 2D ) . However , almost identical changes in nTreg numbers and Foxp3 expression levels were observed in mice infected with PyNL , and there were no significant differences in any nTreg parameter between PyL-infected and PyNL-infected mice at any time up to 7 days pi , after which the PyL-infected mice succumbed to their infections . Similar results were obtained with Foxp3-GFP reporter mice [24] . Importantly , the course of PyL and PyNL infections were equivalent in Foxp3-GFP mice and C57BL/6 mice ( data not shown ) . A representative plot showing Foxp3-GFP expression in infected and uninfected mice is shown in Figure 2E . Numbers of CD4+GFP+ cells were significantly increased in the spleen on 5 day pi ( Figure 2F ) and on day 7 pi ( data not shown ) but did not differ significantly between PyL-infected and PyNL-infected mice . Finally , no significant differences were observed in expression of Foxp3 mRNA in CD4+ T cells purified from spleens of PyL and PyNL-infected mice on days 1 , 3 , 5 and 7 pi ( data not shown ) . The similarity of the nTreg response during PyL and PyNL infections suggested that , in our hands , suppression of effector cell responses by nTreg was unlikely to explain the highly virulent nature of PyL infections . However , to formally test the role of nTreg , mice were treated with a cocktail of anti-CD25 antibodies ( previously shown to give optimal depletion of CD4+CD25hiFoxp3+cells; 25 ) 3 days prior to infection with PyL ( Figure 3 ) . As previously reported [25] , the 7D4 ( IgM , anti-CD25 ) antibody substantially reduced the proportion of splenic CD25+ CD4 cells within 3 days ( i . e day of infection ) but CD25+ cells recovered to normal levels by day 4 pi ( results not shown ) and 7D4 treatment had no significant effect on the frequency of CD4+Foxp3+ve cells ( results not shown ) . In contrast , PC61 ( IgG anti-CD25 ) given in combination with 7D4 induced an approximately 50% reduction in the frequency of both CD25+ and Foxp3+ cells that was sustained throughout the 7 day infection period [25] . Nonetheless , neither 7D4 treatment nor combined 7D4+PC61 treatment significantly altered the course of parasitaemia , anaemia or survival of PyL infection in C57BL/6 mice ( Figure 3A–C ) . As these observations contradict those of a similar published study [13] we considered whether some effect of natural T reg might be being masked by the rapidly ascending parasitaemia and early mortality associated with infection with 104 PyL parasites . We therefore repeated the anti-CD25 antibody treatment in C57BL/6 mice infected with either a 10 fold lower dose of PyL parasites ( 103 PyL ) or with 104 PyNL parasites . However , anti-CD25 antibody treatment did not alter the outcome of either of these infections ( Figures S1 and S2 ) suggesting that natural T reg cells do not markedly influence P . yoelii infections in C57/BL6 mice . It has been reported that regulatory T cell responses are more effective at limiting pro-inflammatory responses in BALB/c mice than in C57BL/6 mice [26] . Therefore , to determine whether mouse strain influences the outcome of anti-CD25 treatment during PyL infection , we repeated the CD25-depletion experiments in BALB/c mice and compared our depletion strategies ( single dose of 7D4 or 7D4+PC61 given 3 days prior to infection ) with a strategy previously shown to affect PyL infection [13] , namely repeated injections of 7D4 antibody on days −3 , −1 and 5 relative to PyL infection . Repeated administration of 7D4 did not increase either the duration of CD25+ T cell depletion or the extent of depletion of CD4+Foxp3+ve cells compared to the other treatment regimes ( Figure S3 ) . Consistent with this , repeated administration of 7D4 did not alter the course of PyL infection compared with single 7D4 administration or combined 7D4 and PC61 administration ( Figure S3 ) , and none of our CD25-depletion regimes had any effect on PyL infection in BALB/c mice ( Figure S3 ) . It is becoming increasingly evident that anti-CD25 antibody treatment is not a specific or robust strategy to examine the importance of natural regulatory T cells during inflammatory episodes [25] , [27]–[29] . CD25 expression is not limited to nTreg [24] . Moreover , depending on the precise protocol used , a variable but significant proportion of Foxp3+ cells escape depletion by anti-CD25 antibody . We therefore compared the outcome of PyL infection in RAG−/− mice reconstituted or not with purified naïve CD4+CD25− ( putative effector ) T cells or a 10∶1 ratio of effector ( CD4+CD25− ) to nTreg ( CD4+CD25+ ) cells . Furthermore , as nTreg can down-regulate NK cell responses [30] , and as NK cells have previously been reported to play a protective role during malaria infection [31]–[33] , we adoptively transferred CD4+CD25+ ( nTreg ) cells in the absence of CD4+CD25− ( effector ) cells , to determine whether nTreg modulate innate immune responses during malaria infection . The proportion of Foxp3+ cells fell from 10–15% in unsorted CD4+ T cells to 1–2% in the CD25−CD4+ population , whereas CD25+ cells were highly enriched for Foxp3+ cells ( 70–80%; Figure 3D ) . In accordance with our previous studies [22] , we found that control ( unreconstituted ) RAG−/− mice succumbed to PyL infection with the same kinetics as WT mice ( compare Figure 3E , F with Figure 1 ) . Furthermore , the course of infection was virtually indistinguishable in RAG−/− mice reconstituted with CD4+CD25− , CD4+CD25+ or a 10∶1 ratio of CD4+CD25−/CD4+CD25+ T cells ( Figure 3E , F ) . Thus , using two independent models of nTreg depletion , we have found no significant role for natural CD4+CD25+Foxp3+ regulatory T cells in suppression of anti-parasitic immunity during PyL infection in either C57BL/6 or BALB/c mice . Having found no evidence that nTreg influence the outcome of PyL infection we next investigated the possibility that IL-10 producing CD4+ T cells ( “adaptive” Treg or Tr1 cells ) might be induced during PyL and/or PyNL infection that regulate parasite killing and/or pathology . Expression of IL-10 mRNA was determined by real time PCR in purified splenic CD4+ T cells obtained on days 1 , 3 , 5 and 7 post-infection from wild type ( WT ) C57/BL6 mice and plasma levels of IL-10 were determined by ELISA on days 1 , 3 , 5 and 7 pi from WT and RAG−/− mice . We find that CD4+ T cells are a significant source of IL-10 by day 5 of both PyL and PyNL infections , since IL-10 mRNA is significantly upregulated in splenic CD4+ cells on days 5 and 7 post-infection compared with cells from uninfected mice ( Figure 4A ) . Furthermore , CD4+ T cells ( and potentially B cells ) may be the major source of IL-10 during infection since plasma IL-10 does not increase above baseline levels in RAG−/− mice ( Figure 4B , C ) except on day 3 pi of PyL infection . To more accurately determine the cellular source of IL-10 during P . yoelii infection , splenocytes from IL-10-GFP reporter mice [21] were examined for expression of GFP and various cell surface markers on selected days after PyL or PyNL infection ( Figure 5A–C ) . In both infections , from day 5 onwards , the vast majority of the IL-10+ cells were CD4+ lymphocytes . At no point during either PyL or PyNL infection did we observe significant IL-10 production by myeloid ( CD11b+ ) , lymphoid dendritic cells ( CD11c+ ) or macrophages ( F4-80+ ) ( results not shown ) . IL-10 production by CD19+ B cells was observed , on day 7 post-infection , only during PyL but not PyNL infection ( results not shown ) . Moreover , IL-10 producing non-CD4+ T cells produced only low quantities of IL-10 , whereas CD4+ T cells were heterogeneous in their ability to produce IL-10 ( Figure 5A ) . Since it is not possible to stain for intranuclear Foxp3 without quenching the fluorescence of GFP , IL-10/GFP+ CD4+ T cells were analysed for expression of CD25 , CD62L and CD127 and separately analysed for CD25 and Foxp3 ( Figure 5B , C ) . On day 5 post-infection , IL-10+ CD4+ T cells showed very variable expression of CD25 with approx . 60% being CD25− , indicating that they are not a typical nTreg population . As we have previously observed transient upregulation of CD25 on CD4+Foxp3− T cells at this time ( Figure 5B and [22] ) , we considered it likely that at 5 days post-infection the majority of IL-10+ cells were Foxp3− . In confirmation of this , by day 7 post-infection , IL-10+ CD4+ T cells were almost exclusively CD25− indicating that , since the majority of Foxp3+ cells maintain CD25 expression during P . yoelii infection ( Figure 5B ) , CD25−Foxp3− CD4+ T cells are the primary source of IL-10 during both PyL and PyNL infection . Interestingly the frequencies and numbers of IL-10+ CD4+TCR-β+ cells were equivalent in PyL and PyNL infected mice on day 7 post-infection ( Figure 5D ) . IL-10+ cells were heterogeneous in terms of expression of CD62L suggesting that they comprise of a mixed population of cells in terms of memory/activation status , and despite being Foxp3− , the majority of IL-10+ CD4+ cells were CD127− , suggesting that down-regulation of IL-7Rα may be a useful marker for differentiating adaptive Treg from other antigen-experienced T cells ( Figure 5C ) . We have shown that CD4+ T cells are the primary source of IL-10 during malaria infection , and that these cells do not express CD25 , suggesting that they may not be conventional nTreg cells . Since IL-10 can be produced by various effector CD4+ T cell subsets ( including Th1 , Th2 and Th17 cells ) , as well as specialised regulatory populations such as Tr1 [19 , 20 34–36] , we examined the expression of Th1 , Th2 and Th17 lineage-associated cytokines in IL-10-producing ( GFP+ ) and IL-10-GFP− CD4+ T cells purified from IL-10-GFP reporter mice on day 7 of infection . As seen previously ( Figure 5 ) , GFP expression was similar in CD4+ T cells isolated from PyL and PyNL infected mice ( Figure 6A ) . As expected , IL-10 mRNA was expressed at much higher levels in GFP+ than in GFP− cells but cells isolated from PyL and PyNL infected animals expressed similar levels of IL-10 mRNA ( Figure 6B ) . Importantly , Foxp3 mRNA was not upregulated in IL-10-GFP+ cells isolated during either PyL or PyNL infection , confirming that the IL-10-producing CD4+ T cells that develop during P . yoelii infection are neither natural nor induced Foxp3+ regulatory T cells . Moreover , GFP+ cells did not express significant amounts of mRNA for IFN-γ , IL-4 or IL-17 , thus distinguishing them from classical Th1 , Th2 and Th17 cells . Although IL-10-GFP+ cells expressed IL-13 mRNA , levels were comparable to those seen in GFP− cells indicating that IL-10 producing cells did not preferentially co-produce IL-13 . Thus , the IL-10-producing CD4+ T cells induced during P . yoelii infection fit the definition [35] of adaptive , Tr1 , regulatory T cells . To determine whether IL-10 production from T cells is functionally important during Py infection , we first compared the course of PyL and PyNL infection in IL-10−/− and WT mice ( Figure 7 ) . PyNL infection was significantly attenuated - with significant reductions in parasitaemia and anaemia in IL-10−/− mice compared with WT mice ( Figure 7A–D ) , although the IL-10−/− mice did lose significantly more weight than age-matched WT mice ( Figure 7C ) . Furthermore , approx 30% ( 6/21 mice ) of IL-10−/− ( but not WT ) mice infected with 104 PyL pRBC were able to control their infections and survived ( Figure 7E–H ) , with parasitaemia declining from a peak of approx 45% on day 6pi . Moreover , IL-10−/− ( but , again , not WT ) mice given a low dose PyL infection ( 103 pRBC ) were fully able to control parasitaemia and 100% of the mice survived ( Figure 7I–L ) . Taken together , these data indicate that IL-10 suppresses immune effector mechanisms which would otherwise be able to control low dose PyL infections . Since this IL-10 emanates principally from CD4+ T cells ( Figure 5 ) we hypothesised that IL-10-deficient CD4+ T cells may promote more effective parasite control than WT CD4+ T cells . To test this , purified naïve WT or IL-10−/− CD4+ T cells were adoptively transferred into RAG−/− mice which were then infected with PyNL or PyL parasites . PyNL-infected RAG−/− mice that had received IL-10−/− CD4+ T cells developed significantly lower parasite burdens than those which had received WT CD4+ T cells ( Figure 8A ) . Although both groups developed similar levels of anaemia , mice that received IL-10−/− T cells lost significantly more weight and succumbed to infection more rapidly than mice that received WT CD4+ T cells ( Figure 8B–D ) . Exacerbation of disease despite improved parasite control in mice receiving IL-10−/− CD4+ T cells was associated with more extensive proliferation of the adoptively transferred T cells ( IL-10−/− T cells comprised >30% of total splenic leucocytes compared with <10% for transferred WT cells ) , higher concentrations of circulating IFN-γ and lower plasma concentrations of IL-10 ( data not shown ) . These data are consistent with the conclusion that recipients of IL-10−/− CD4+ T cells died of immunopathology whilst recipients of WT CD4+ T cells eventually died because they were unable to fully resolve their infections . By contrast , RAG−/− mice that had received IL-10−/− CD4+ T cells were somewhat better able to control infections with 103 ( 8E–H ) or 104 ( 8I–L ) PyL infections than were mice receiving WT CD4+ T cells; a proportion of mice receiving IL-10−/− T cells were able to control their infections , although failure to fully eliminate parasites eventually led to death from anaemia . Thus , IL-10 derived from CD4+ T cells significantly modulates the outcome of both PyL and PyNL infection . It has previously been shown that IL-10−/− mice succumb to normally avirulent P . chabaudi chabaudi infections despite comparable - or more effective - control of malaria parasitaemia compared to WT mice [9] . The increased susceptibility of IL-10−/− mice is due to elevated plasma concentrations of IFN-γ and TNF-α [10] and survival of IL-10−/− mice following malaria infection can be enhanced by treatment with anti-TNF-α [10] . Whilst there was no marked difference in mortality between P . yoelii-infected IL-10−/− and WT mice , IL-10−/− mice ( and RAG−/− mice reconstituted with IL-10−/− T cells ) lost significantly more weight than mice reconstituted with WT T cells during PyNL infection , indicative of more severe morbidity ( Figure 7C , 8C ) . Histopathological examination of infected animals did not reveal any liver or lung damage 3 days post-infection ( data not shown ) but revealed significantly more hepatic cellular changes including periportal inflammation , necrosis and bridging necrosis in IL-10−/− mice than in WT mice on days 7 and 14 post-infection ( Figure 9A ) and this was significantly more severe in PyL-infected than PyNL-infected animals on day 7 post-infection . We also found that by day 25 of PyNL infection , RAG−/− recipients of IL-10−/− CD4+ T cells had developed significantly more severe hepatic periportal inflammation and necrosis ( including bridging necrosis ) than RAG−/− recipients of WT CD4+ T cells ( Figure 9B ) . Thus , T cell derived IL-10 , although negatively regulating parasite killing , is protective during malaria infection by preventing the onset of immunopathology .
It is well established , in a variety of infections , that regulatory cytokines both ameliorate immunopathology and delay pathogen clearance [5] , [8] , [9]–[11] , [37]–[42] . Manipulation of these cytokines by vaccination or immunotherapy , to simultaneously enhance pathogen clearance and limit the associated pathology , requires a better understanding of their cellular sources and mechanisms of induction . Important roles have been demonstrated for both IL-10 [6]–[11] and TGF-β [4] , [5] in modulating the outcome of murine malaria infections , and observational data strongly suggests that they play a similar role in human infections [43]–[45] . Recently , endogenous or natural , CD25hi , Foxp3+ CD4+ T cells ( nTreg ) have been implicated as major regulators of malarial pathology [13] , [46] but their mechanisms of action remain undefined . Attempting to elucidate the role of nTreg in murine Plasmodium yoelii infections , we were surprised to find no role for these cells in regulating the outcome of either high dose ( 104 ) or lower dose ( 103 ) lethal ( Py17XL; PyL ) or non-lethal ( Py17X; PyNL ) infection in either C57BL/6 or BALB/c mice . In contrast , we find that adaptive , IL-10-producing CD4+ Tr1 cells ( CD25− , Foxp3− , CD127− , IFN-γ− , IL-4− and IL-17− ) , are generated during both PyL and PyNL infections and are associated with down-regulation of pro-inflammatory responses , moderation of both morbidity and mortality and failure to clear parasites . Crucially , we were able to demonstrate a causal relationship between these various observations by showing that IL-10−/− CD4+ T cells adoptively transferred into RAG−/− mice provided more effective parasite control than did WT CD4+ T cells , but at the cost of more severe pathology . We conclude that induced Foxp3− regulatory T cells , characterised by down-regulation of CD127/IL-7Rα , modulate the inflammatory response to Plasmodium yoelii malaria by production of IL-10 . Although it has been observed in humans [47] , [48] and mice [48] that CD127 is down-regulated on endogenous ( Foxp3+ ) regulatory T cells , our data demonstrate – for the first time - that CD127 is also down-regulated on adaptive ( Foxp3− ) Tr1 cells . The lack of any effect of anti-CD25 antibody treatment on the course of PyL infection in our experiments contradicts the published data [13] , [46] . Despite numerous attempts , using three different depletion protocols - including a protocol identical to that previously reported to ameliorate PyL infection [13] , in both C57BL/6 and BALB/c mice we were unable to reproduce the published observations . Anti-CD25 treatment failed to ameliorate PyL infection initiated by a 10 fold lower dose of parasites , discounting the possibility that the virulence of high dose PyL infection masks regulatory activity of nTreg that would otherwise be evident during a less virulent infection . Furthermore , adoptive transfer of CD25+ and/or CD25− CD4+ T cells into RAG−/− mice also failed to reveal any role for CD25+ Foxp3+ cells in this infection . The discrepancy between our findings and those of other labs is reminiscent of the disparate results obtained for P . berghei ANKA infection which report that depletion of CD25+ regulatory cells either facilitates parasite control and prevents the onset of the cerebral pathology infection in C57BL/6 mice [49] , or enhances effector T cell responses and increases the severity of brain pathology in normally resistant BALB/c mice [50] or has no effect on cerebral pathology [51] . One explanation for these inconsistent results may be differences in prior exposure to pathogens or commensal organisms between mice in different laboratories . Components of the normal intestinal flora of conventionally housed animals are essential for development of intestinal nTreg [52] and nTreg development is facilitated by the presence of covert infections such as Helicobacter hepaticus [53] . Depletion of nTreg by anti-CD25 treatment in such mice may lead to more profound alteration in the effector / regulatory cell balance than in mice ( such as those used in our studies ) raised in low-infection environments . Although , we could show no role for nTreg in acute PyL and PyNL infection , we have shown that the adaptive IL-10-producing regulatory T cells that develop during P . yoelii infection hinder parasite control but simultaneously limit disease severity . In contrast to recent studies describing a role for IL-10 producing Th1 cells in Toxoplasma gondii [20] and Leishmania spp [19] , [54] , [55] infections , the adaptive IL-10 producing Tregs we describe do not co-express IFN-γ or other effector cytokines and better fit the definition of Tr1 cells . Nevertheless in several virulent protozoal infections ( PyL , Toxoplasma gondii , Leishmania major SD and L . donovani ) , adaptive IL-10-producing CD4+ T cells are required to regulate the fulminant Th1-effector responses that are induced whereas classical ( Foxp3+ ) Treg appear to be sufficient to regulate the effector response to a less virulent ( healing ) strain of L . major [15] . Given that naïve CD4+ T cells can develop into adaptive Treg after interaction with IL-10-producing dendritic cells expressing low levels of co-stimulatory molecules [56]–[59] , it is possible that the induction of Treg during P . yoelii infection is linked to the modulation of macrophage and dendritic cell function that occurs in response to prolonged toll-like receptor signalling [60] . Alternatively , parasite-induced TGF-β [40] , [60] , IL-6 [44] and/or IL-27 may synergise to promote production of IL-10 by Th1 , Th2 , Th17 and Tr1 cells [34] , [36] , [61] , [62] . We have not yet definitively identified the mechanism by which IL-10 suppresses parasite clearance but given our recent findings that control of the acute phase of P . yoelii parasitaemia is critically dependent on macrophages [22] , it is likely that T cell-derived IL-10 acts directly on macrophages to inhibit their anti-parasitic mechanisms . It is also possible that , as in mycobacterial infections , adaptive Treg induce an autocrine signalling loop in which macrophages both secrete and respond to IL-10 with consequent down regulation of effector function and pathology via a STAT-3 –dependent pathway [63]–[66] . In summary , we have demonstrated that adaptive , but not natural , regulatory T cells control parasite numbers during PyL and PyNL infections whilst also limiting the onset of immunopathology . These cells are characterised by lack of expression of CD25 and Foxp3 , down-regulation of CD127 and production of IL-10 but not IFN-γ , IL-4 or IL-17 . Taken together with our data highlighting the importance of macrophages in the control of malaria infection [22] , these findings identify an important pathway of adaptive , T cell- mediated control of innate immune responses . Further studies are required to identify the pathways leading to induction of this important regulatory cell population .
C57BL/6 , Foxp3-GFP ( F2: 129/C57BL/6; from A . Rudensky , University of Washington , 24 ) , C57BL/6 RAG-1−/− , C57BL/6 IL-10−/− and BALB/c mice were bred in-house or purchased from Harlan and maintained under barrier conditions at LSHTM . IL-10-GFP reporter mice [21] were maintained under barrier conditions at the National Institutes of Health . Cryopreserved Plasmodium yoelii 17X ( non lethal; PyNL ) and P . yoelii 17XL ( lethal; PyL ) parasites were passaged once through mice before being used in experimental animals . Unless stated otherwise , male or female mice , 7–9 weeks of age , were infected intraveneously with 1 × 103 or 1 × 104 parasitised red blood cells ( pRBC ) . Parasitaemia was determined daily by examination of Giemsa-stained thin smears of tail blood for the first seven days of infection and every second day thereafter . On every second day , mice were weighed and RBCs were counted using an automated haemoanalyser ( Beckman Coulter ) . Plasma was stored ( at −20°C ) for cytokine quantification . On selected days post-infection , mice were sacrificed and spleens were removed . Single spleen cell suspensions were prepared by homogenisation through a 70 µm cell strainer ( BD Biosciences ) and live cells enumerated by trypan blue exclusion . CD4+ T cells were positively selected using anti-mouse CD4-conjugated midiMACS beads ( Miltenyi Biotec ) according to the manufacturer's instructions and the purity of eluted cells was checked by flow cytometry . In some experiments , the CD4+ cells were labelled with anti-mouse CD4 ( GK1 . 5: Rat IgG2b: E-bioscience ) and anti-mouse CD25 ( PC61: Rat IgG1: E-bioscience ) fluorochrome-labelled antibodies and sorted , using a BD FACSVantage SE , into CD4+CD25+ and CD4+CD25− populations . In separate experiments CD4+ T cells , isolated from IL-10-GFP reporter mice [21] on day 7 of infection , were labelled with anti-mouse CD4 ( GK1 . 5: Rat IgG2b: E-bioscience ) and IL-10 producing ( GFP+ ) and non-IL-10 producing ( GFP− ) CD4+ T cells were purified by flow cytometric cell sorting . IL-10 , Foxp3 , IFN-γ , IL-4 , IL-13 and IL-17A mRNA were quantified by Taqman ( ABI , Warrington , UK ) . RNA was extracted ( RNAeasy ) and DNAse1 treated prior to cDNA synthesis . cDNA expression for each sample was standardised using the housekeeping gene GAPDH . Cycling conditions were: initialisation 2 min at 50°C and 10 min at 95°C followed by 40 cycles of 15 sec at 95°C and 1 min at 60°C . Primer sequences: IL-10 Forward ATGCTGCCTGCTCTTACTGACTG Reverse CCCAAGTAACCCTTAAAGTCCTGC , Foxp3 Forward CACCTATGCCACCCTTATCC , Reverse CGAACATGCGAGTAAACCAA IFN-γ Forward AGA GCC AGA TTA TCT CTT TCT ACC TCA G Reverse CCT TTT TCG CCT TGC TGT TG IL-4 Forward ACG AGG TCA CAG GAG AAG GGA Reverse AGC CCT ACA GAC GAG CTC ACT C IL-13 Forward CCTCTGACCCTTAAGGAGCTTAT Reverse CGTTGCACAGGGGAGTCT IL-17A Forward TGTGAAGGTCAACCTCAAAGTC Reverse AGGGATATCTATCAGGGTCTTCATT Rat anti-mouse IL-10 ( JES5-2A5; Rat IgG1; Mabtech , Sweden ) or rat anti-mouse interferon ( IFN ) -γ ( AN-18; Rat IgG1; eBioscience ) antibodies were used as capture antibodies , diluted in 0 . 5 M Tris-HCl , pH 8 . 9 buffer . Biotinylated rat anti-mouse IL-10 MAb ( JES5-16E3; Rat IgG2b; Mabtech ) or rat anti-mouse IFN-γ MAb ( R4-6A2; Rat IgG1; Mabtech ) were used as detecting antibodies and were visualised using streptavidin-alkaline phosphatase ( eBioscience ) and p-nitrophenyl phosphate ( Sigma Aldrich , UK ) . Absorbance was read at 405 nm using a MRX TC II microplate reader ( Dynex Technologies Ltd , . UK ) For flow cytometric analysis , cells were surface stained with anti-mouse CD4 ( RM4-5; Rat IgG2a; BD Biosciences ) , anti-mouse CD25 ( PC61; Rat IgG1; eBioscience ) , anti-mouse CD69 ( H1 . 2F3; Armenian Hamster IgG; eBioscience ) , anti-mouse CD62L ( MEL-14; Rat IgG2a; eBioscience ) or anti-mouse CD127 ( A7R34; Rat IgG2a; eBioscience ) . Intracellular Foxp3 staining using anti-mouse Foxp3 ( FJK-16s; Rat IgG2a; eBioscience ) was performed by permeabilising cells with 0 . 1% Saponin/PBS . Cells were concurrently incubated with anti-mouse CD16/32 ( Fc block ) when staining with all conjugated antibodies . Flow cytometric acquisition was performed using a FACSCalibur ( BD Immunocytometry Systems , USA ) and all analysis was performed using Flowjo software ( Treestar Inc . , OR , USA ) Liver and lung tissues were fixed in 10% Formalin-saline . Fixed tissues were paraffin embedded and stained with haematoxylin and eosin . Slides were microscopically examined at 20X magnification . Statistical significance was determined using Student's T test , unless otherwise stated , with P<0 . 05 taken as indicating a significant difference . | Much of the pathology of malaria infection is due to an excessive inflammatory response to the parasite . The regulatory cytokine IL-10 is known to control inflammation during malaria infections and thus protect against immunopathology , but , in so doing , it reduces the effectiveness of other immune mechanisms which remove the parasites . In order to try to dissociate these two effects of IL-10 , to allow simultaneous control of infection and avoidance of pathology , we need a better understanding of the processes leading to IL-10 production , the timing of its production , and the cells that produce it . In this study we have found that the major source of IL-10 during malaria ( Plasmodium yoelii ) infection is adaptive regulatory CD4+ T cells . This population is distinct from natural regulatory T cells and classical effector T cells . IL-10 derived from these adaptive CD4+ T cells prevents hepatic immunopathology but also suppresses the effector T cell response , preventing parasite clearance . Further work is now required to determine how these two key cell types ( anti-parasitic effector T cells and IL-10-producing regulatory T cells ) are induced , so that vaccines can be designed that will induce optimal numbers of each cell type at appropriate stages of the infection . | [
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"immunology/immunomodulation",
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] | 2008 | IL-10 from CD4+CD25−Foxp3−CD127− Adaptive Regulatory T Cells Modulates Parasite Clearance and Pathology during Malaria Infection |
HIV-1 persists in infected individuals in a stable pool of resting CD4+ T cells as a latent but replication-competent provirus . This latent reservoir is the major barrier to the eradication of HIV-1 . Clinical trials are currently underway investigating the effects of latency-disrupting compounds on the persistence of the latent reservoir in infected individuals . To accurately assess the effects of such compounds , accurate assays to measure the frequency of latently infected cells are essential . The development of a simpler assay for the latent reservoir has been identified as a major AIDS research priority . We report here the development and validation of a rapid viral outgrowth assay that quantifies the frequency of cells that can release replication-competent virus following cellular activation . This new assay utilizes bead and column-based purification of resting CD4+ T cells from the peripheral blood of HIV-1 infected patients rather than cell sorting to obtain comparable resting CD4+ T cell purity . This new assay also utilizes the MOLT-4/CCR5 cell line for viral expansion , producing statistically comparable measurements of the frequency of latent HIV-1 infection . Finally , this new assay employs a novel quantitative RT-PCR specific for polyadenylated HIV-1 RNA for virus detection , which we demonstrate is a more sensitive and cost-effective method to detect HIV-1 replication than expensive commercial ELISA detection methods . The reductions in both labor and cost make this assay suitable for quantifying the frequency of latently infected cells in clinical trials of HIV-1 eradication strategies .
Highly active antiretroviral therapy ( HAART ) has significantly reduced the morbidity and mortality associated with HIV-1 infection . However , while HAART can reduce plasma viral load to below the clinical limit of detection ( 50 copies HIV-1 RNA/mL ) in adherent patients [1]–[3] , this treatment is not curative . Even in individuals on prolonged suppressive HAART , HIV-1 persists as a latent but replication-competent provirus integrated in the genomes of a small percentage of resting memory CD4+ T cells [3]–[8] . These latently infected cells are extremely long lived as a consequence of the biology of memory T cells , with an estimated half-life of 44 months [9] , [10] . The extreme stability of this HIV-1 reservoir precludes eradication with HAART alone and suggests that , without disruption of this reservoir , infected individuals must remain on HAART for the remainder of their lives [9] , [10] . Recent studies have identified small molecules capable of reactivating HIV-1 gene expression [11]–[17] . While resting CD4+ T cells harboring a latent HIV-1 provirus are not susceptible to viral cytopathic effects or immune clearance , pharmacological reactivation of latent proviruses could lead to depletion of this latent reservoir . Recent in vitro work suggests that reactivation paired with a T cell vaccination strategy could be used to eradicate the latent reservoir of HIV-1 in resting CD4+ T cells [18] . Several clinical trials are investigating the ability of small molecule reactivators to perturb the latent state of the provirus and reduce the size of the latent reservoir [19] , [20] . Assessing strategies to perturb or eliminate the latent reservoir requires assays that can accurately quantitate the size of the latent reservoir and that can be scaled for use in large clinical trials . The reservoir was originally identified using a viral outgrowth assay carried out on highly purified resting CD4+ T cells isolated from patient peripheral blood mononuclear cells ( PBMC ) [6] , [7] , [9] , [21] . These resting cells do not actively produce virus without stimulation [4] . Limiting dilutions of the resting CD4+T cells are activated with the mitogen phytohemagglutinin ( PHA ) in the presence of irradiated allogeneic PBMC . This activation reverses latency and reinitiates the production of infectious HIV-1 from the subset of resting CD4+ T cells harboring replication-competent proviruses . The viruses that are produced are expanded in PHA-stimulated CD4+ lymphoblasts from uninfected donors , which are added to the culture at two time points . After two weeks , viral outgrowth is assessed by an ELISA assay for HIV-1 p24 antigen in the culture supernatant . The frequency of latent infection , expressed as infectious units per million ( IUPM ) resting CD4+ T cells , is determined using Poisson statistics . Typically , patients on long term HAART exhibit IUPM values between 0 . 1 and 1 [6] , [7] , [9] . While this viral outgrowth assay is widely recognized as the definitive assay for determining the minimum frequency of CD4+ T cells harboring replication-competent proviruses , it is time-consuming , labor-intensive , and expensive , requiring two weeks of cell culture and PBMC from at least three uninfected blood donors per assay . In its current form , this assay is not suitable for use in large clinical trials evaluating the efficacy of eradication strategies , and the identification of simpler assays for the latent reservoir has been identified as an AIDS research priority [22] . A recent study compared 11 different approaches for measuring persistent HIV-1 in patients on HAART [23] . Infected cell frequencies measured by PCR-based methods were generally at least two orders of magnitude higher than and poorly correlated with IUPM values . This likely reflects the presence of large numbers of defective proviruses that are detected by PCR-based assays . The results raise doubts about whether PCR-based assays can be used to assess the frequency of cells harboring replication-competent proviruses . Therefore we developed a rapid and simple viral outgrowth assay that can nevertheless detect and provide at least a minimal estimate of the frequency of cells that must be eliminated to cure HIV-1 infection .
A rapid and simple viral outgrowth assay was developed and evaluated using samples from 20 patients with HIV-1 infection . The baseline characteristics of the patient cohort enrolled in this study are summarized in Table 1 . Seventeen patients were recruited on the basis of prolonged suppression of viremia to <50 copies of HIV-1 RNA/mL on HAART , with a duration of suppression from 12 to 156 months . We intentionally enrolled three additional patients who were viremic at the time of blood draw with viral loads of 5 , 392 , 452 , 059 , and 31 , 238 copies/mL . Of the three viremic patients , one patient had not yet started HAART and two were known to be non-adherent . The average age of the cohort ( ± SD ) was 50 . 8 . ±10 . 8 years , and the cohort was overwhelmingly comprised of black males . The CD4 nadir of the cohort ranged from 6 to 755 cells/µL , and 8 patients had a history of an AIDS diagnosis . The original viral outgrowth assay used to define the latent reservoir was performed on resting CD4+ T cells purified from PBMC in a multistep process that included fluorescence activated cell sorting ( FACS ) and required a BSL-3 sorting facility . Resting CD4+ T cells were differentiated from activated CD4+ T cells by the absence of cell surface markers CD69 , CD25 , and HLA-DR . To simplify the purification of resting CD4+ T cells , we devised a two-step bead depletion purification procedure . Initially , CD4+ T cells were purified from PBMC by negative selection as described in Materials and Methods . Subsequent bead depletion of cells expressing CD69 , CD25 , or HLA-DR yielded a highly purified , unmanipulated population of resting CD4+ T cells . The purity of these cells was routinely assessed by staining with antibodies to CD4 and HLA-DR . Representative examples are shown in Figure 1 and Figure S1 . Typical purities were 96–97% with less than 0 . 1% contamination with activated ( HLA-DR+ ) CD4+ T cells . As is discussed below , IUPM values obtained with these purified resting CD4+ T cells were in the same range as observed with sorted cells . The standard viral outgrowth assay requires a minimum of 3 separate blood samples from healthy donors in addition to a blood sample from the test patient ( Figure 2 ) . CD4+ T lymphoblasts from two of these samples are added to cultures at days 2 and 7 to expand virus released from patient cells in which latency has been reversed by T cell activation . These donor lymphoblasts are prepared by PHA stimulation of donor PBMC for 2 days followed by depletion of CD8+ T cells . Eliminating the need for donor lymphoblasts in virus expansion would significantly simplify the assay . We hypothesized that a single addition of a cell line expressing high levels of CD4 and the co-receptors CCR5 and CXCR4 would allow for efficient expansion of viruses released from latently infected cells . We chose the MOLT-4/CCR5 cell line [24] . This cell line was derived from MOLT-4 cells [25] , which express high levels of CD4 and CXCR4 , and has been engineered to stably express CCR5 . It is thus capable of supporting replication of both X4-tropic and R5-tropic variants of HIV-1 . To verify that the MOLT-4/CCR5 cells are an acceptable alternative for donor-derived CD4+ T lymphoblasts , we compared IUPM values obtained using the standard viral outgrowth assay with donor derived lymphoblasts to IUPM values obtained using a simplified assay in which a single addition of MOLT-4/CCR5 cells was used in place of donor lymphoblasts . All 3 viremic patients ( V1 , V2 , V3 ) and 14 of the 17 patients on suppressive HAART ( S1–S14 ) were included in this comparison . Resting CD4+ T cells obtained from each patient using the bead depletion method described above were split and tested using the standard assay and the simplified MOLT-4/CCR5 assay as outlined in Figure 2 . The p24 ELISA at day 14 was used as an assay endpoint . Replication-competent HIV-1 was isolated from purified resting CD4+ T lymphocytes in all 3 of the viremic patients and 10 of the 14 patients on HAART by both assays ( Figure 3A , Table S1 ) . In 3 of the 14 patients on HAART , replication-competent HIV-1 was isolated in only one of the two viral outgrowth assays ( Figure 3A , Table S1 , Patients S4 , S7 , and S14 ) . No replication-competent HIV-1 was recovered from purified resting CD4+ T lymphocytes by either viral outgrowth assay in 2 of the 14 patients on HAART ( Figure 3A , Table S1 , Patients S8 and S13 ) . These results are expected because splitting the sample reduces the input number of resting CD4+ T cells . The frequency of latently infected resting CD4+ T lymphocytes was markedly higher in the viremic patients compared to patients on HAART ( Figure 3A , Table S1 ) , consistent with our previous results [10] . No significant difference was observed between the frequency of latently infected resting CD4+ T lymphocytes measured in the standard viral outgrowth assay versus the MOLT-4/CCR5 viral outgrowth assay ( Figure 3B , Wilcoxon rank sum test , p = 0 . 9032 ) . Furthermore , the frequency of latently infected cells as measured by the MOLT-4/CCR5 viral outgrowth assay correlates highly with that of the standard viral outgrowth assay ( Figure 3C , Pearson's correlation coefficient , r = 0 . 9381 , p<0 . 0001 ) . When only patients on suppressive HAART were considered , the correlation remained highly significant ( r = 0 . 7602 , p = 0 . 0016 ) . To shorten the time required to measure latently infected cells by the viral outgrowth assay , we explored the use of RT-PCR as an alternative to the p24 ELISA to detect virus production . Twenty-nine replicate wells were set up with 200 , 000 patient resting CD4+ T cells/well from a patient on suppressive HAART ( S15 ) . The cells were activated with PHA and irradiated feeders and then cultured with MOLT-4/CCR5 cells over 14 days using the protocol developed for the viral outgrowth assay . Culture supernatants were assayed for released virus at multiple time points during the 14 day culture using both the p24 antigen ELISA and a novel RT-PCR assay . This assay detects polyadenylated HIV RNAs without interference from proviral or plasmid DNA , and when applied to virion-containing supernatants , detects mainly genomic viral RNA , allowing accurate quantitation of virus release [26] . For both assays , positive wells showed an exponential increase in the amount of virus in the supernatant ( Figures 4A and 4B ) . Among the wells positive for outgrowth , there was complete concordance between HIV-1 p24 antigen ELISA and HIV-1 specific RT-PCR at 14 days . All of the wells that were positive for outgrowth by RT-PCR eventually tested positive by p24 ELISA ( Figure 4C ) . Under conditions where a majority of the positive wells are predicted to contain a single latently infected cell , HIV-1 specific RT-PCR detected viral outgrowth significantly earlier than HIV-1 p24 antigen ELISA ( Figure 4D , Wilcoxon rank sum test , p = 0 . 0020 ) , with the average days ( ± S . D . ) of detection being 6 . 1±2 . 1 and 9 . 6±2 . 7 days , respectively . These results indicate that HIV-1 specific RT-PCR accurately detects viral outgrowth in a shorter time frame . Given that HIV-1 specific RT-PCR accurately detected HIV-1 outgrowth from the latent reservoir significantly earlier than the HIV-1 p24 antigen ELISA , we sought to determine whether HIV-1 specific RT-PCR could be used to detect positive wells more rapidly in the MOLT-4/CCR5 viral outgrowth assay . As shown in Figure 4B , nearly all wells that eventually became positive by p24 ELISA were positive by RT-PCR on day 7 . Therefore , supernatants from viral outgrowth cultures from patients S8–S14 and V1–V3 were tested at day 7 using the HIV-1 specific RT-PCR assay . For comparison , an HIV-1 p24 antigen ELISA was also performed on culture supernatants from these viral outgrowth cultures on day 7 . The frequencies of latently infected cells obtained using both assays on day 7 of the viral outgrowth assay were compared to the frequencies determined on day 14 using the HIV-1 p24 antigen ELISA ( Figure 5A ) . The frequencies determined with HIV-1 p24 antigen ELISA on day 7 were significantly lower than the frequencies determined with the same assay on day 14 ( Figure 5A , Wilcoxon rank sum test , p = 0 . 0010 ) . However , the frequencies determined with HIV-1 specific RT-PCR on day 7 and with HIV-1 p24 antigen ELISA on day 14 were not significantly different ( Figure 5A , Wilcoxon rank sum test , p = 0 . 9219 ) . These results suggest that the use of a sensitive assay for free virus on day 7 on the culture may effectively substitute for an ELISA assay on day 14 . We next sought to evaluate the agreement between the day 7 and day 14 endpoint assays . A total of 74 wells from patients S8–S14 and V1–V3 were positive for HIV-1 outgrowth by either HIV-1 specific RT-PCR or HIV-1 p24 antigen ELISA . Outgrowth was detectable on day 7 using HIV-1 p24 antigen ELISA in only 60% of the positive wells . However , outgrowth was detectable in 81% of the positive wells on day 7 using HIV-1 specific RT-PCR . The correlation of the frequency of latently infected resting CD4+ T cells calculated at day 7 and day 14 was evaluated using Pearson's correlation coefficient . The correlation between the frequency of latent infection calculated at day 14 using HIV-1 p24 antigen ELISA and the frequency determined on day 7 was markedly higher when the HIV-1 specific RT-PCR assay was used rather than the HIV-1 p24 antigen ELISA ( Figure 5C versus Figure 5B , r = 0 . 9698 versus r = 0 . 9133 ) . When only patients on suppressive HAART were considered , the frequency determined at day 7 using the RT-PCR assay was positively correlated with the frequency determined at day 14 by HIV-1 p24 antigen ELISA ( r = 0 . 8516 , p = 0 . 0001 ) while the frequency determined at day 7 using the HIV-1 p24 antigen ELISA no longer correlated with the frequency determined at day 14 by ELISA ( r = 0 . 4448 , p = 0 . 1110 ) . Two additional patients on suppressive HAART ( S16 , S17 ) were included in a final comparison of the rapid MOLT-4/CCR5 viral outgrowth assay and the standard viral outgrowth assay . A statistically significant positive correlation was seen when the frequency of latently infected resting CD4+ T cells determined using the rapid MOLT-4/CCR5 viral outgrowth assay was compared to the frequency determined using the standard viral outgrowth assay ( Figure 5D , r = 0 . 9591 , p<0 . 0001 ) . When only patients on suppressive HAART were considered , a statistically significant positive correlation was still observed ( r = 0 . 7522 , p = 0 . 0194 ) .
Latent HIV-1 infection of resting CD4+ T cells remains the major barrier to HIV-1 eradication . A number of small molecules have been identified that are capable of reactivating transcription of otherwise silent HIV-1 proviruses [11]–[15] , [17] . Some of these compounds have already entered clinical trials [19] , and drug discovery efforts to find additional compounds that can perturb or eliminate latent HIV-1 continue . Concurrently , immunological approaches are being investigated and have shown promise [18] . However , a key hurdle facing HIV-1 eradication efforts has , until recently , been largely ignored: the development of a reliable and simple assay to measure the size of the HIV-1 latent reservoir . Such an assay is absolutely required for evaluating the effectiveness of an eradication strategy . PCR based assays are being used to quantify proviruses in T cell subsets and the level of residual viremia in HIV-1 infected patients [19] , [27]–[31] . A recent study has compared results of various PCR based assays with those obtained with the viral outgrowth assay using a set of samples from two well characterized cohorts of patients on HAART [23] . Because current PCR assays detect both replication-competent and defective proviruses , the correlation between infected cell frequencies measured by PCR and viral outgrowth was not strong , with the exception of an assay measuring integrated HIV-1 DNA in PBMC [23] . The measurement of integrated HIV-1 DNA by Alu PCR [30] is of particular interest because the stable reservoir for HIV-1 consists of resting CD4+ T cells harboring integrated HIV-1 DNA [4] , [5] . It is likely that this and other PCR based assays will play an important complementary role to viral outgrowth assays . Prior to the present study , the standard viral outgrowth assay was the only assay available to directly quantify the frequency of resting CD4+ T cells harboring latent but replication-competent viral genomes . The development of a rapid isolation procedure to obtain unperturbed resting CD4+ T cells was an essential first step towards creating a viral outgrowth assay suitable for widespread use in eradication studies and clinical trials . The latent reservoir was originally defined using viral outgrowth assays performed on highly purified populations of resting CD4+ T cells obtained through a combination of magnetic bead depletion and cell sorting . Thus , the assay required a BSL-3 cell sorting facility . While feasible for small-scale studies , this approach cannot be utilized for large-scale studies in which numerous measurements of the size of the latent reservoir must be taken across many patients . As we have demonstrated here , our isolation procedure yields a highly purified resting CD4+ T cell population . Moreover , the frequencies of latently infected cells measured in these populations are very similar to those obtained with the sorting method [4]–[6] . The standard viral outgrowth assay relies on a minimum of 3 separate blood samples from healthy donors . PBMC from two of the subsequent donations are added to the cultures to propagate the HIV-1 released following the reversal of latency . These healthy donor cells may also provide subsequent allogeneic stimulation to the patient cells in culture . We sought to replace these healthy donor cells with a cell line that supports infection by both X4-tropic and R5-tropic HIV-1 . Furthermore , we believed that a cell line would provide greater uniformity to the viral outgrowth assay , since every viral isolate growing out of a patient's latent reservoir would propagate in identical culture conditions . As we have clearly demonstrated , the MOLT-4/CCR5 cell line performs robustly in place of mitogen stimulated CD8-depleted healthy donor PBMC in the viral outgrowth assay . This modification significantly simplifies the assay and allows the assay to be more easily scaled for large studies or clinical trials . Other cell lines that support replication of both X4 and R5 isolates could potentially be used as target cells in this assay . Of note , our rapid assay in its current form still requires a single blood donation from a healthy donor for the generation of irradiated PBMC used in the initial mitogen stimulation . It is possible that the replacement of mitogen stimulation with co-stimulation via anti-CD3 and anti-CD28 monoclonal antibodies could alleviate the need for any healthy blood donors . Interestingly , the success of MOLT-4/CCR5 cells in propagating reactivated HIV-1 suggests that the allogeneic stimulation provided by the healthy donor CD4+ T lymphoblasts was not required . As MOLT-4/CCR5 cells do not express MHC class II [32] , [33] , no allogeneic stimulation of patient CD4+ T cells should occur . The lack of allogeneic stimulation was noted in the early characterization of the MOLT-4 cell line [34]–[36] . Thus , we can infer from our study that the initial mitogen stimulation alone is generally sufficient for reactivation of latent HIV-1 and viral outgrowth . However , we cannot conclude that this initial mitogen stimulation is sufficient for reactivation of all latent proviruses . Studies are ongoing to determine whether any replication-competent proviruses remain non-induced after a single round of mitogen stimulation . If this is the case , any measurement of the size of the latent reservoir that relies upon reactivation of latent proviruses through a single round of T cell stimulation may in fact be underestimating the size of the reservoir . The strategic use of both culture and PCR based assays may allow us to bracket the true size of the latent reservoir . The standard viral outgrowth assay requires 14 days to complete . This 14 day period includes two additions of CD4+ T lymphoblasts from healthy donor PBMC as well as multiple media changes . The length of time required for the standard viral outgrowth assay is a function of the endpoint assay used to measure viral outgrowth: the HIV-1 p24 antigen ELISA . With the goal of reducing the length time required for detecting viral outgrowth , we adapted a recently developed HIV-1 specific RT-PCR assay for use as an endpoint assay . On average , viral outgrowth from the latent reservoir under conditions resembling the MOLT-4/CCR5 viral outgrowth assay was detectable by the HIV-1 specific RT-PCR assay after 6 . 1±2 . 1 days ( ± S . D ) versus 9 . 6±2 . 7 days ( ± S . D ) for HIV-1 p24 antigen ELISA . This result indicated that utilizing a more sensitive endpoint assay for viral outgrowth could indeed reduce the length of time required to complete the MOLT-4/CCR5 viral outgrowth assay . The data presented here demonstrate that no significant difference exists between the frequency of latent infection of resting CD4+ T cells as measured at day 7 using HIV-1 specific RT-PCR and at day 14 as measured by HIV-1 p24 antigen ELISA . The utilization of an RT-PCR based measurement for HIV-1 outgrowth not only allows more sensitive detection of viral replication , but will allow more high-throughput measurement of HIV-1 replication . Of note , extremely high sequence conservation has been observed at the primer and probe binding sites , especially amongst subtype B isolates [26] . The degree of conservation is actually higher than is observed in the regions of gag that are amplified in many other PCR assays [26] . It remains possible that in rare patients , sequence variation in these conserved regions could interfere with PCR detection . In these rare cases , negative results in the PCR assay may be due to primer mismatch rather than low frequency of latent infection . Given the greater sensitivity of the HIV-1 specific RT-PCR assay , it is possible that small amounts of replication-defective virus released after mitogen stimulation of resting CD4+ T cells might be detected , resulting in a false positive readout of viral outgrowth . Our data suggest that the release of replication-defective virus is not widely detected by the RT-PCR assay at day 7 . In rare cases ( patient S13 ) , we observed weak positive signals by RT-PCR at day 7 in wells that remained negative by p24 ELISA at day 14 . These data could represent viruses that have low fitness and a slower replication rate than needed to expand to beyond the limit of detection for HIV-1 p24 antigen ELISA on day 14 . It is possible that such viruses could be detected by HIV-1 p24 antigen ELISA with a longer culture period . As shown in Figure 4C , only 11 out of 29 wells containing an input of 200 , 000 resting CD4+ T cells from patient S15 were positive for viral outgrowth . The frequency of latent HIV-1 infection measured in the resting CD4+ T cells of patient S15 ( 3 . 25 IUPM ) suggests that each of the 29 replicate wells likely contained dozens of integrated , defective proviruses . However , only 11 wells were positive for when tested by RT-PCR . Furthermore , of the wells that were positive for viral outgrowth , detection by HIV-1 specific RT-PCR was not possible until day 6 . 1±2 . 1 days ( ± S . D ) , and these wells remained positive for the duration of the outgrowth time course , with an exponentially increasing amount of virus . These data suggest that our HIV-1 specific RT-PCR requires a level of viral replication achieved after a nearly one week and is not sensitive enough to detect replication defective viruses that do not expand further . The MOLT4/CCR5 viral outgrowth assay does require a single large blood sample of 150–200 mL . This is due to the low frequency of replication-competent proviruses harbored within resting CD4+ T cells . Given this fundamental aspect of the biology of HIV-1 latency , it is unlikely that any version of a viral outgrowth assay can be performed without a large input of resting CD4+ T cells . However , because no alternative assay exists that specifically measures latent , replication-competent proviruses in resting CD4+ T cells , viral outgrowth assays will likely continue to play an important role in evaluating HIV-1 eradication strategies . The MOLT-4/CCR5 utilizing viral outgrowth assay presented here is the most rapid and scalable assay available for measuring the size of the HIV-1 latent reservoir . As such , we believe that this assay will be an indispensable tool in evaluating the success of strategies to perturb or eradicate the HIV-1 latent reservoir .
Twenty HIV-1 infected patients were enrolled in this study; 19 were recruited from the Moore Clinic at The Johns Hopkins Hospital and 1 patient was recruited from the SCOPE cohort at the University of California San Francisco . All study participants provided written informed consent for participation . This study was approved by the Johns Hopkins Institutional Review Board . Seventeen of the 20 patients were recruited on the basis of prolonged continuous suppression of plasma HIV-1 viremia on HAART to below the limit of detection of standard clinical assays ( <50 copies HIV-1 RNA/mL ) . Three of the 20 patients were recruited on the basis of detectable plasma HIV-1 viremia; two patients were reported non-adherent to their HAART regimens and one patient had not yet initiated therapy . Peripheral blood mononuclear cells ( PBMC ) were isolated using density gradient centrifugation . CD4+ T lymphocytes were enriched by negative depletion ( CD4+ T cell Isolation Kit , Miltenyi Biotec ) . Resting CD4+ T lymphocytes were further enriched through negative depletion of cells expressing CD69 , CD25 , or HLA-DR ( CD69 MicroBead Kit II , Miltenyi Biotec; CD25 MicroBeads , Miltenyi Biotec; Anti-HLA-DR MicroBeads , Miltenyi Biotec ) . Resting CD4+ T cells purified using the above described two-step bead depletion procedure were stained with CD4-PE and HLA-DR-APC ( BD Biosciences ) . The purity of these cells was analyzed by flow cytometry using a FACS Canto II ( BD Biosciences ) and FlowJo software ( Treestar ) . For each patient , both a standard viral outgrowth assay and a MOLT-4/CCR5 viral outgrowth assay were performed using freshly purified resting CD4+ T lymphocytes obtained from a single blood draw as described above . Briefly , five-fold serial dilutions of resting CD4+ T lymphocytes from HIV-1 infected patients were stimulated by co-culture with a 10-fold excess of γ-irradiated allogeneic PBMC from uninfected donors and the mitogen PHA ( Remel ) in RPMI containing 10% fetal bovine serum , 100 U/mL IL-2 ( Novartis ) and 1% T-cell growth factor ( produced in house , as described previously [21] ) . These conditions are sufficient to activate 100% of the resting CD4+ T lymphocytes , as previously demonstrated by CFSE dilution and expression of cell surface activation markers [6] , [37] . T cell activation reverses HIV-1 latency in at least a fraction of the latently infected cells . After one day of stimulation , the mitogen containing media is removed and either MOLT-4/CCR5 cells or health donor CD4+ lymphoblasts are added in fresh media to propagate replication-competent HIV-1 in the culture wells . The standard viral outgrowth assay utilizes two additions of CD4+ lymphoblasts from uninfected donors as target cells for HIV-1 outgrowth on days 2 and 9 . The MOLT-4/CCR5 viral outgrowth assay utilizes a single addition of MOLT-4/CCR5 cells on day 2 . The ratio of target cells added is the same for both assays [21] , with 1×107 target cells added to wells containing 1×106 patient resting CD4+ T cells and 2 . 5×106 target cells added to all other wells . Five days after initial mitogen stimulation of input resting CD4+ T lymphocytes , the culture media was changed and the cells in each well were split . Supernatants from each well were tested for HIV-1 RNA and/or HIV-1 p24 protein at various time points by RT-PCR and ELISA ( Alliance HIV-1 p24 antigen ELISA Kit , Perkin Elmer ) , respectively . The frequency of latently infected cells among the input resting CD4+ T lymphocytes was calculated by a maximum likelihood method , as described previously and is expressed as infectious units per million cells ( IUPM ) [21] . The 95% confidence intervals for individual IUPM determinations are ±0 . 7 log IUPM , or 5 fold [21] . With a sample size of 25 , this assay can detect with 80% power a 0 . 2 log reduction in the reservoir assuming a type 1 error of 0 . 05 . After reversal of latency and subsequent release of HIV-1 , virion-associated HIV-1 RNA was isolated from 60 µL of culture supernatant using the ZR-96 Viral RNA Kit ( Zymo Research ) , a 96-well column based RNA isolation kit . cDNA was synthesized from the isolated HIV-1 RNA using the SuperScript III First-Strand Synthesis System ( Invitrogen ) with oligo-dT primers . Isolated cDNA was assayed for HIV-1 by RT-PCR as described previously [26] using an Applied Biosystems 7300 Real Time PCR System ( Applied Biosystems ) and TaqMan Universal PCR Mastermix ( Applied Biosystems ) . RNA copy number was determined using a standard curve generated with the DNA plasmid pVQA , described previously [26] . RNA copy numbers below 10 copies or above 106 copies were extrapolated based on the standard curve generated . Infected cells frequencies in limiting dilution assays were calculated as described by Myers et al . [38] . Where appropriate , results were expressed as mean ± standard deviation . A Wilcoxon rank sum test ( paired comparison ) was used for statistical analysis . All statistical analyses were performed with MedCalc software , v12 . 4 . 0 . 0 . A p value of <0 . 05 was considered significant . | The eradication of HIV-1 from infected individuals is stymied by the persistence of the virus in a stable reservoir of latently infected CD4+ T cells . Latently infected cells can be found in all HIV-1 infected individuals at a very low frequency and allow the virus to persist despite antiretroviral therapy for the lifetime of an infected patient . Current efforts are focused on identifying small molecules or immune strategies to eliminate these latently infected cells . To assess the efficacy of these elimination strategies in HIV-1 infected patients , we must be able to measure the size of the latent reservoir . While an assay developed previously in our lab can measure the size of this latent reservoir , it is too laborious and costly to be utilized in large-scale HIV-1 eradication trials . We have developed a rapid assay to measure the size of the HIV-1 latent reservoir more amenable to these eradication trials . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
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"and",
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] | [
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] | 2013 | Rapid Quantification of the Latent Reservoir for HIV-1 Using a Viral Outgrowth Assay |
A major goal of systems neuroscience is to decipher the structure-function relationship in neural networks . Here we study network functionality in light of the common-neighbor-rule ( CNR ) in which a pair of neurons is more likely to be connected the more common neighbors it shares . Focusing on the fully-mapped neural network of C . elegans worms , we establish that the CNR is an emerging property in this connectome . Moreover , sets of common neighbors form homogenous structures that appear in defined layers of the network . Simulations of signal propagation reveal their potential functional roles: signal amplification and short-term memory at the sensory/inter-neuron layer , and synchronized activity at the motoneuron layer supporting coordinated movement . A coarse-grained view of the neural network based on homogenous connected sets alone reveals a simple modular network architecture that is intuitive to understand . These findings provide a novel framework for analyzing larger , more complex , connectomes once these become available .
Systems neuroscience is reaching the stage where large connectomes are being mapped and ambitious collaborative projects are established to decipher the fundamental questions relating structure and function [1–4] . To name few are the current attempts to construct a large-scale computer simulation of the human brain [5–7] , the development of various methods for obtaining whole-brain functional dynamics and connectivity maps [8 , 9] , and others [10–12] . These massive efforts will yield gigantic networks composed of millions of inter-connected neurons . This poses a genuine challenge: how to analyze these perplexing connectomes such that functional principles can be extracted based on connectivity data alone . Various approaches and theories had been developed to understand the structure–function relationship in neural networks [13–18] . Analyses of network properties , such as clustering coefficient and characteristic path length , revealed that neural networks are organized in a small-world topology , where the path length between any pair of nodes is relatively short [13 , 14] . In addition , neural networks , like many other biological networks , show a power law degree distribution in which the majority of the neurons are connected to relatively few partners , while a small fraction of the neurons are connected to exceptionally high number of other neurons [14] . A different approach to analyzing networks was to focus on the recurring building blocks embedded in networks [19–23] . These studies revealed that defined small building blocks , termed network motifs , are significantly overrepresented in biological networks , including the neural network of the round worm C . elegans [19 , 22–27] . Focusing on these small motifs allowed deciphering their potential functional roles in the network [20–23 , 25 , 28–30] . In addition , linear systems analyses have been used to predict functional sub-circuits purely based on network topology [26 , 31 , 32] . Recently , an intriguing observation was made in the rat somatosensory cortex . Using multiple electrode recordings , Perin and colleagues [33] showed that the wiring in layer 5 pyramidal cells obeys the common neighbor rule ( CNR ) . According to this rule , the more common neighbors a pair of neurons shares , the more likely for this pair to be connected ( A neuron X is considered a neighbor of neuron Y if X shares a chemical synapse or a gap junction with Y . A neuron is considered a common neighbor to a pair of neurons X , Y if it is connected directly to both X and Y , either via a chemical synapse or a gap junction ) . A similar principle was also observed in the rat visual cortex as simultaneous electrophysiological recordings from adjacent layer 2/3 pyramidal cells showed that connected pairs of neurons are more likely to share a common input [34 , 35] . Conversely , unconnected pairs share very little common inputs . Such an organization is thought to generate relatively independent subnetworks that are embedded within the larger-scale network architecture [33–36] . Here we aimed to elucidate whether the CNR is indeed an organizing principle in neural networks , and if so , to elucidate the functional roles that common neighbor sets of neurons may confer the network . To carry such analyses on the network-wide level , we focused on the sole fully-mapped neural network that is currently available–the C . elegans neural network . The connectome of C . elegans hermaphrodites consists of 302 neurons for which a complete wiring diagram is available , including number of synapses , spatial anatomical position , and the nature of these connections ( chemical synapses or electrical gap junctions ) [26 , 37–39] . Importantly , these data provide the unique opportunity for studying such structure-function relationships at the network-wide level , rather than focusing on specific cell types of selected brain areas only . We show that the CNR is indeed an emerging property in the neural network of C . elegans . Moreover , sets of common neighbors form homogenous structures that appear in defined layers of the network confer valuable functional roles . Focusing on these sub-circuits reveals a simple functional architecture of the network that is intuitive to understand , and establishes a novel framework for studying functionality in , yet to come , bigger and more complex neural networks .
We begin by asking whether the CNR is found in the C . elegans neural network . To address this , we analyzed the available connectome of hermaphroditic C . elegans worms [26 , 37] . We find that the CNR is a striking feature in the C . elegans neural network where the fraction of connected pairs of neurons increase the more common neurons this pair of neurons shares ( Fig 1A and 1B ) . In fact , this relationship grows linearly ( R2 = 0 . 96 ) similarly to the relationship observed in the rat cortex [33] . The CNR observed in the C . elegans neural network could have arisen solely due to the degree distribution of the network . For example , the C . elegans neural network shows characteristics of a small-world network with a heavy tail degree distribution that follows a power law [14 , 26 , 38] . The CNR could have arisen merely because such networks contain hub neurons that connect many others . To test this , we generated random networks based on the known network topology but randomly shuffled the edges while preserving the in- and out- degree of each node constant [19] ( S1 Text ) . While such random networks show CNR properties , the emergence of the rule in the genuine C . elegans neural network is significantly more prominent ( p<10–10 , z-test; Fig 1B ) . Finally , we analyzed whether random networks with no degree distribution constraints also obey the CNR . For this , we generated Erdős–Rényi random networks ( S1 Text ) and found that the CNR does not emerge in such networks ( p<10–10 , z-test; Fig 1B ) . In neural networks , neurons are linked via physical connections in the form of chemical synapses or gap junctions . In particular , adjacent neurons are more likely to be connected than distant neurons since such a wiring strategy minimizes wiring costs [40–43] . Indeed , our analyses show a higher tendency to form connections between adjacent neurons ( S1 Fig ) . Such distance-dependent connectivity may lead to local clusters in which neurons are more likely to be connected and share multiple common neighbors . To test if the CNR could have emerged solely due to this local clustering , we analyzed the number of common neighbors to a pair of neurons as a function of their inter-somatic distance . We find no correlation between these two parameters ( Fig 1C , r = -0 . 13 , p ≈ 1; One tailed student's t-test for Pearson correlation coefficient ) , thus excluding the possibility that physical proximity between neurons underlies the emergence of the CNR . In fact , we find that geometrically distant neurons can equally share multiple neighbors and that this feature depends on their degree ( Fig 1C , notice the two peaks at short and long inter-somatic distances are due to the major head and tail hub neurons ) . Together , these results demonstrate that the CNR is significantly overrepresented in the genuine neural network of C . elegans . Moreover , this rule cannot be explained by the networks’ degree distribution or by the spatial position of the neurons . This suggests that the CNR could evolve in the neural network probably as it confers functional roles . We next studied the structure of individual sets of common neighbors , where a set is a pair of neurons , X and Y , together with their common neighbors Z1 , Z2 , …Zn . A set can be connected or unconnected depending on the existence of a synapse between X and Y . Each set can be decomposed into n triads , such that each triad contains X , Y , and a single Z ( n being the number of Z's; Fig 2A; S2A Fig ) . Theoretically , each set of common neighbors can be made of a mixture of the different triad types ( for example , any of the triads 1–15 shown in Fig 2A for connected sets ) , resulting in a heterogeneous set structure . In such heterogeneous sets , the prospect to assign the entire set with a concrete functional role becomes virtually impossible since each triad type potentially carries distinct functional tasks . Surprisingly , however , we observed that most of the sets are not heterogeneous as randomly expected ( examples of typical sets are shown in Fig 2B and S2 Table ) . To understand the tendency of a pair to become connected the more common neighbors it shares ( the CNR ) we continued by focusing on connected sets only ( data concerning unconnected sets is shown in S2 Fig ) . Importantly , we focused on sets containing at least five common neighbors to minimize false positive homogenous sets formed by chance due to the small number of common neighbors . To provide a quantitative measure for sets’ homogeneity we performed a statistical hyper-geometric test that takes into account the relative abundance of the triad type in all sets ( S1 Text ) . Moreover , to extract the most significant homogeneous sets of common neighbors we introduced a second criterion on top of that defined by the hyper-geometric test: only sets of which at least half of their triads are of the same type are considered homogeneous . When filtering using these two very strict criteria , we find 231 ( out of the 1 , 150 in total , ~20% ) significantly homogeneous connected sets ( hyper-geometric test p-value threshold is set to 0 . 05; S1 Text ) . The significance of sets’ homogeneity is further underscored when performing the same statistical analyses on randomly shuffled sets ( p<10–50 when comparing C . elegans homogeneity to the homogeneity calculated for randomly shuffled sets , Fig 2C , S1 Text ) . Strikingly , these homogeneous connected common neighbor sets make a significant portion of the neural network comprising ~70% of the total synapses of the network . Of note , the vast majority of the homogeneous sets are not due to the bilateral symmetry of the neural network ( we consider bilateral symmetric neurons only pairs of neurons of the form XXXR , XXXL; S3 Fig ) . We next asked whether these homogenous connected sets of common neighbors are predominantly made of specific triad types . We find that only specific triad types are significantly overrepresented in homogenous sets ( Fig 2D ) . In particular , sets homogenous with triads #10 , #1 , #2 , #11 , #14 and #13 make the top list among all sets that appear in the network significantly more than randomly expected , ( triad #10 being the most significant and the others follow in descending order; p<10–10 for all; z-test after Bonferroni correction ) . Interestingly , sets #1 , #2 and #5 are made of triads forming a feed-forward loop ( FFL ) , a known network motif in the C . elegans neural network [19 , 22 , 23 , 25] . Moreover , a topological generalization of the FFL circuit shows that these FFLs are embedded in larger clusters of multi FFLs [24] . These generalized FFLs resemble the homogenous connected sets of common neighbors that we observe in the network . One of the generalized FFL overrepresented in the C . elegans neural network is the multi-input FFL which corresponds to the homogenous common neighbor set made up primarily of triad #5 . Indeed , and in agreement with Kashtan et al [24] , our analyses show that this homogenous set is significantly overrepresented in the network ( p<0 . 0001; z-test; after Bonferroni correction; Fig 2D ) . In addition , we find that the other FFLs are significantly overrepresented: multi-output and multi-inter FFLs which correspond to sets homogenous with triads #1 and #2 , respectively ( p<10–10; z-test; after Bonferroni correction; Fig 2D ) . FFLs as well as their generalized multi-FFL forms had been previously studied emphasizing their potential functional roles in information processing in biological networks [19 , 24 , 29 , 30 , 44–46] . We find new homogenous set structures that appear significantly more than randomly expected and which had not been hitherto described in the context of neural networks . Among those , sets of type #10 and #13 are the most enriched with homogeneous sets ( both in terms of the total number of sets , and in the difference from the shuffled sets; Fig 2D ) . The interesting feature in these two sets is the bidirectional connection between X and Y neurons . In triad #10 , the X and Y neurons synapse one another and both are presynaptic to their mutual Z neurons , a structure termed mutually regulating ( X and Y mutually regulate the Z neurons ) . In contrast , in triad #13 , the bi-directionally connected X and Y neurons are post-synaptic to their mutual Z neurons , a structure termed mutually regulated ( X and Y are mutually regulated by the Z neurons; Fig 2A ) . We proceeded by analyzing whether these sets appear in defined areas of the network . The rationale is that a circuit location can often hint of its potential functional role . For this , we defined four functional layers in the network and assigned each neuron to one of these layers based on its known function: sensory , inter , pre-motor , and motor neuron layers ( for a complete list of neurons and their corresponding layers see S1 Table ) . Specifically , for each homogeneous connected common neighbor set , we analyzed whether the X and Y neurons are located on the same layer or on different layers of the network ( Fig 3A and 3B ) . Interestingly , we found that X and Y neurons tend in general to reside on different layers , with the exception of the homogenous sets consisted of triads #10 and #13 , the mutually regulating and mutually regulated sets , respectively ( Fig 3B ) . In these two sets , the X and Y neurons are predominantly confined to the same layer . Moreover , in the mutually regulating sets ( set type #10 ) both X and Y appear significantly more in the sensory layer than would be randomly expected ( p = 0 . 009 , hypergeometric test; after Bonferroni correction; Fig 3C and S4 Fig ) . In the mutually regulated sets ( set type #13 ) , X and Y appear almost exclusively in the motor neuron layer ( p<10–10 , hypergeometric test; after Bonferroni correction; Fig 3C and S4 Fig ) . Analysis of the type of the bidirectional synapse between X and Y reveals that in mutually regulating sets the bidirectional connection is enriched with chemical synapses , while in mutually regulated sets the bidirectional connection is made primarily of gap junctions ( Fig 3D ) . Similarly , set #15 , a fully bidirectional connected set ( Fig 2A ) , that is significantly enriched with pre-motor and motor neurons ( Fig 3C ) , is also made primarily of gap junctions ( Fig 3D ) . To emphasize the enrichment of gap junctions in sets #13 and #15 we analyzed the network considering chemical synapses only . In such a network these sets are no longer overrepresented ( p>0 . 05 , S5 Fig ) . Overrepresented generalized FFLs , on the other hand , such as homogenous sets #1 and #2 , show a different pattern of layer distribution where X and Y are distributed across all layers of the network ( Fig 3B and 3C ) . Taken together , we find homogenous sets of neurons , consisted of specific types of synapses , to appear in defined areas of the network . These observations may hint to possible functional roles of these sets in the neural network . To assign a functional role to such sets , we continue with the most significant homogeneous connected sets ( Hypergeometric p-value threshold is set to 10–5 , S2 Table ) . Here we provide two intriguing examples where linking the type of a homogenous set together with its network position and synaptic connections can disclose its potential functional roles in the network:
In this study we analyzed the connectome of the hermaphrodite C . elegans nematode and established that the CNR is an emerging property in this neural network . Strikingly , we find that specific sets of common neighbors are largely anatomically homogenous . Moreover , these sets are located in defined layers of the network indicating their potential functional roles in the neural network . In fact , a coarse-grained view [51] of the neural network using the most abundant and the significantly overrepresented common neighbor sets reveals a simple network organization that is intuitive to understand ( Fig 4 ) . Specialized homogeneous sets appear in defined areas of the neural network , serving as functional building blocks that carry different processing tasks . For example , mutually regulating homogeneous sets support signal integration and amplification at the sensory/inter-neuron layers , while mutually regulated homogeneous sets synchronize multiple inputs from the common upstream neurons to support coordinated activity of the motor system ( Fig 4A ) . Other sets , predominantly made of generalized forms of FFLs , are found throughout the network across different layers ( Fig 4B ) . For example , set #1 is significantly overrepresented as a homogenous set in the network ( S2 Table ) . In this set X and Y form a unidirectional chemical synapse , Y being mostly in the sensory layer , while X is either on the sensory- or inter- neuron layer ( Figs 2A , 3 and S6 Fig ) . Of the most homogenous sets of this type is the pair of neurons AVHR-ADLR; ADLR being a sensory neuron and AVHR an interneuron ( S1 and S2 Tables ) . The unidirectional chemical synapse from the AVHR interneuron to the upstream sensory neuron ADLR is an interesting feature that may provide a top-down feedback signal to modulate activity in a context dependent manner [52–56] . The coarse grain view suggests that the network can be partitioned and better understood based on these homogenous common neighbor sets . Such a partition contributes to a modular view of the network , and Indeed , biological networks are thought to evolve modular structures [16 , 33 , 36 , 38 , 45 , 57–61] . This modularity confers neural networks with robust learning capabilities [62] , and rapid dynamic adjustments to constantly changing environments [24 , 45] . Our analyses revealed specific sets of common neighbors that are significantly overrepresented in the network: the mutually regulating and the mutually regulated sets . While these structures were previously studied in the context of developmental transcription programs [27 , 44 , 63] , their significant emergence in neural networks was overlooked . This is possibly due to the different approach by which we analyzed the C . elegans neural network: ( a ) We considered the full wiring diagram currently available as opposed to previous analyses that considered neural connections with five synapses or more only; ( b ) The network we analyzed included gap junctions while previous analyses considered the network formed by chemical synapses only [24] . While providing unprecedented full connectome data , there are several limitations to the C . elegans wiring diagram . For example , it lacks important information regarding the directionality of gap junctions . In the absence of such data we considered all gap junctions as bidirectional , an obvious oversimplification of the genuine architecture . Similarly , the type and the nature of the chemical synapses are also largely unknown ( for example , are the synapses excitatory or inhibitory; are they axo-dendritic , axo-axonic , dendro-dendritic , or dendro-axonic ) . In addition , the wiring diagram of the hermaphrodite C . elegans worm is reconstructed based on few animals only . In the lack of a greater number of reconstructed animals , one cannot be certain how wiring varies from animal to animal . Current efforts focus on reanalyzing the original EM data ( WormWiring . org ) [37] , and to providing a map of the neurotransmitters expressed in each neuron [64] . These efforts will refine the connectome , so it will be interesting to apply our approaches once such data become available . Despite these obvious limitations , our comprehensive network approach focusing on the most significant homogenous sets , allows extracting meaningful circuits and assign them with potential functional roles . Interestingly , social networks show similar connectivity patterns . In these networks , people interact and make connections preferentially with individuals that share similar backgrounds and interests ( known as homophily [65] ) , and often add new friends if there is a common acquaintance ( known as triadic closure [66] ) . Simulating social networks evolution with similar constrains yield networks characterized by the CNR [67] . In that respect , Facebook is a classic example for such a social network . We analyzed the available Facebook friendship connectivity and established that , indeed , the CNR is an emerging property in the Facebook social network: that is , the more common friends shared by two individuals , the more likely for these individuals to be friends as well ( S9 Fig ) . While the emergence of the CNR in social networks might be intuitive to understand , the benefit of such a design in neural networks is not trivially apparent . In the rat cortex the observed CNR is thought to be an organizing principle that clusters neurons into elementary building blocks of cortical computations and memory [33 , 36] . Our study provides several novel insights to this phenomenon: we established that the CNR is indeed an emerging organizing principle in the C . elegans neural network , and that sets of common neighbor neurons can be viewed as building blocks found in defined layers of the network exerting valuable functional roles ( e . g . , signal amplification , synchronization , and robust information processing ) . These novel findings may explain the emergence of the CNR in mammalian neural networks as well . For example , signal amplification and robust information processing are essential for efficient cortical computations . Thus , it will be fascinating to study these cortical building blocks in light of the observed CNR once such connectomes become available . Importantly , we did not consider cell types a priori when analyzing the network to establish the CNR and the homogenous sets . Only subsequent analyses revealed the interesting principle of how information may flow through homogenous sets and across layers . In addition , homogenous sets are not found only between cells of different types , but many are between cells of the same type ( For example set #10 appears more at the sensory neurons layer , while set #13 almost exclusively found at the motor neurons layer ) . Thus , applying these approaches to any new connectome may reveal hidden layers in what initially may seem as a homogenous layout made of the same types of neurons . Finally , once connectome data of higher brain systems become available , the generality of our findings regarding network topology can be tested . Importantly , our approach can be used to extract the specific types of homogenous sets enriched in any connectome data , providing a novel platform to studying structure-function relationships in complex biological networks .
All code files generated in this study are available on github: http://AzulEye . github . io/HomogeneousSetsFinder . The files include the code for generating all the figures in the manuscript as well as the random networks . In addition , we provide a generic pipeline that extracts homogeneous sets from any network using its adjacency matrix as an input . This is to be used with any future available connectomes or other biological networks such as transcriptional networks . | How can we understand the function of gigantic complex networks ( e . g . the brain ) based on connectivity data alone ? We use the available full connectome of a nematode and apply new approaches to find that the neural network is made of structurally homogeneous neural circuits . These sets of neurons also appear in defined regions of the network where they may provide valuable functional roles such as signal integration and synchronization . Moreover , if we redraw the network considering these homogeneous sets alone , we reveal a simplified network layout that is intuitive to understand . As connectome data of higher brain systems are soon to be released our novel approaches can be immediately applied to studying these complex systems . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
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] | [
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"... | 2016 | The C. elegans Connectome Consists of Homogenous Circuits with Defined Functional Roles |
Leptospirosis is a widespread zoonotic infection that primarily affects residents of tropical regions , but causes infections in animals and humans in temperate regions as well . The agents of leptospirosis comprise several members of the genus Leptospira , which also includes non-pathogenic , saprophytic species . Leptospirosis can vary in severity from a mild , non-specific illness to severe disease that includes multi-organ failure and widespread endothelial damage and hemorrhage . To begin to investigate how pathogenic leptospires affect endothelial cells , we compared the responses of two endothelial cell lines to infection by pathogenic versus non-pathogenic leptospires . Microarray analyses suggested that pathogenic L . interrogans and non-pathogenic L . biflexa triggered changes in expression of genes whose products are involved in cellular architecture and interactions with the matrix , but that the changes were in opposite directions , with infection by L . biflexa primarily predicted to increase or maintain cell layer integrity , while L . interrogans lead primarily to changes predicted to disrupt cell layer integrity . Neither bacterial strain caused necrosis or apoptosis of the cells even after prolonged incubation . The pathogenic L . interrogans , however , did result in significant disruption of endothelial cell layers as assessed by microscopy and the ability of the bacteria to cross the cell layers . This disruption of endothelial layer integrity was abrogated by addition of the endothelial protective drug lisinopril at physiologically relevant concentrations . These results suggest that , through adhesion of L . interrogans to endothelial cells , the bacteria may disrupt endothelial barrier function , promoting dissemination of the bacteria and contributing to severe disease manifestations . In addition , supplementing antibiotic therapy with lisinopril or derivatives with endothelial protective activities may decrease the severity of leptospirosis .
Leptospirosis is a geographically widespread zoonosis that has emerged as a significant public health problem in urban slums , particularly in the tropics . The infection is caused by species of spirochetes belonging to the genus Leptospira . There are more than 200 serovars of Leptospira distributed among both pathogenic and non-pathogenic species [1] . The pathogenicity of different strains can vary considerably depending on the host species and age , and on the infecting serovar [2] . The spirochete's mode of entry is through mucous membranes and cuts or abrasions on the skin [1] . Upon entry , the organisms travel through the bloodstream to multiple sites , and may cause liver and kidney damage , meningitis , and a variety of other inflammatory conditions . If the host survives the acute infection , leptospires can persist in the proximal renal tubules for weeks to months , protected from antibodies and causing little to no inflammation . The bacteria are then shed in the urine , and animal urine contamination of water is the primary source of human exposure . Although little is known about how Leptospira species establish infection in their hosts , adhesion to the host cell surface and extracellular matrix ( ECM ) by pathogens is often the first critical step in the initiation of infection . Several groups have investigated the adhesion of Leptospira interrogans to endothelial , fibroblast , kidney epithelial , and monocyte-macrophage cell lines cultured in vitro [3]–[9] . It is likely that pathogenic leptospires can attach to several different types of mammalian receptors to establish the infection . In fact , infectious strains of Leptospira have been shown to adhere to ECM components including collagen type IV , fibronectin and laminin , and also to the plasma protein fibrinogen [4] , [10]–[12] . Adhesion to several ECM components is mediated at least in part by the LigA and LigB proteins [11] and a group of additional related proteins that were identified through homology to a laminin binding protein [10] , [12] . Several studies have shown that the adhesion of pathogens to mammalian cells will provoke multiple changes in the physiology and/or gene expression of the host . The host-pathogen interactions that define a disease are clearly complex . Microarrays are a powerful tool to explore those host-pathogen interactions by analyzing the transcriptional profiles of host cells or pathogens . Although it has been documented that temperature and osmolarity alter leptospiral gene expression [13] , [14] , no previously published research has focused on the mammalian cell responses to the bacteria . To understand how human endothelial cells alter gene expression in response to incubation with different strains of Leptospira , human gene arrays were probed with cDNA derived from the RNA purified from infected cells and uninfected controls . In this study , we discuss how global analysis of gene expression allows us to gain insights into host specific responses to infection with pathogenic Leptospira .
The human microvascular endothelial cell line of dermal origin ( HMEC-1 ) [15] was obtained from Dr . Ades ( Centers for Disease Control and Prevention , Atlanta , Georgia ) and cultured in endothelial basal medium ( Clonetics , San Diego , CA ) supplemented with 15% heat-inactivated fetal bovine serum ( Hyclone , Logan , UT ) , 1 µg/ml hydrocortisone ( Sigma-Aldrich , St . Louis , MO ) and 10 ng/ml epidermal growth factor ( Sigma-Aldrich ) . The immortalized human macrovascular endothelial cell line EA . hy926 [16] was kindly provided by Dr . C . -J . Edgell ( University of North Carolina , Chapel Hill , NC ) and grown in Dulbecco's modified Eagle medium with high glucose supplemented with 10% heat-inactivated fetal bovine serum ( Gibco , Grand Island , NY ) and HAT Media Supplement ( Sigma-Aldrich ) . Both cell lines were cultured in the medium recommended by the supplier in a humidified atmosphere of 5% CO2 and both cell media were supplemented with 1 U/mL penicillin , 1 µg/mL streptomycin , and 2 mM L-glutamine for routine propagation . Cells to be used for experimental infection with Leptospira strains were cultured without the antibiotics . The roles of proteoglycans in the endothelial cell response to L . interrogans were tested based on previously published protocols [17] . Briefly , chondroitin sulfate B was shown to bind L . interrogans and to competitively inhibit L . interrogans to mammalian cells , so it was tested for the ability to inhibit the endothelial cell responses to the bacteria described below . In addition , inhibition of proteoglycan synthesis by β-xyloside , which also decreases L . interrogans attachment to mammalian cells , was tested for any effect . Controls included chondroitin sulfate A , to which L . interrogans does not bind , and the sugar analog α-galactoside , which does not affect proteoglycan synthesis . The reference strain Leptospira biflexa serovar Patoc was obtained from the American Type Culture Collection ( ATCC 23582 , Manassas , VA ) , and is a non-pathogenic species . L . interrogans serovar Canicola ( pathogenic , strain ATCC 23606 and strain 11203-32 ) were obtained from the ATCC and Dr . Richard Zuerner ( USDA , Ames , IA ) , respectively . L . interrogans serovar Copenhageni ( pathogenic , strain designated Fiocruz L1-130 ) was provided by Dr . David Haake ( UCLA , Los Angeles , CA ) . Bacterial strains were maintained in ambient air at 30°C . Bacteria utilized for this study were at low passage from the suppliers ( ≤passage 6 ) and cultured in EMJH medium [1] supplemented with 100 µg/ml of 5-fluorouracil and 1% rabbit serum ( Sigma-Aldrich ) . For some experiments , the bacteria were radiolabeled by addition of 35S cysteine plus methionine to the medium as described previously [17] . The bacteria were enumerated using a Petroff-Hausser counting chamber and dark field microscopy . Mammalian cells were plated in T-225 tissue culture flasks ( BD Falcon , Bedford , MA ) and grown up to 90% or higher confluence . When cells reached desired confluence , the monolayer was washed with PBS and the cells were lifted off the plastic culture flask with 5mM EDTA in PBS . This was done to allow access of the bacteria to endothelial cell surface receptors that are normally involved in attachment to the substratum , i . e . receptors that the bacteria may encounter when penetrating the vasculature . In addition , this approach minimizes degradation of mRNA that occurs during harvesting of adherent cells . After lifting , cells were spun for 10 minutes at 1 , 000 rpm , resuspended in the cell culture medium without antibiotics , and enumerated using a hemocytometer counting chamber . 2×107 cells per sample were incubated in suspension with either L . biflexa serovar Patoc or L . interrogans serovar Canicola , or without any bacteria , for 1 h and 3 h at room temperature in the cell medium without antibiotics . The MOI ( multiplicity of infection ) used was 10 bacteria per mammalian cell . After incubation , cells were washed with phosphate buffered saline ( PBS ) and harvested for RNA isolation . The RNA was purified using RNeasy kit ( Qiagen , Valencia , CA ) with DNase digestion according to manufacturer's manual . The quality of RNA was checked using a Bioanalyzer ( Agilent , Santa Clara , CA ) . Human HEEBO ( Human Exonic Evidence Based Oligonucleotide ) Arrays , consisting of 44 , 544 70mer probes representing 30 , 718 known genes , were purchased from Microarrays Inc . ( Nashville , TN ) . 5 to 20 µg of total RNA from uninfected control and infected samples was used to generate cDNA labeled with aminoallyl ( aa ) -dUTP through a reverse transcription reaction using anchored oligo ( dT ) primers . The purified aa-dUTP-labeled cDNAs were coupled in 10 µl 0 . 1 M NaHCO3 with either Cy3 or Cy5 NHS-ester dye . Cy-dye labeled cDNA was purified using a Cyscribe GFX column ( Amersham Biosciences , Piscataway , NJ ) . The two differently labeled cDNAs were mixed and hybridized using Pronto Microarray Hybridization Kit in a hybridization chamber ( Corning , Corning , NY ) , with the same array slide for 38 to 42 hr according to manufacturer's instruction . After a series of washes using the buffers provided in the kit , slides were spun dry and scanned under two laser channels in a Scanarray 4000 scanner ( Packard Bioscience , Meriden , CT ) . Images were overlaid and analyzed using Imagene ( BioDiscovery , El Segundo , CA ) . Raw gene expression was imported from Imagene to GeneSifter ( GeneSifter . Net , VizX Labs , Seattle , WA ) for analysis . Data from 3 biological replicate experiments were normalized using Lowess normalization and by the median of the raw intensities for all spots in each sample for each array . The ratio of two fluorescence intensities of each spot reflected the ratio of each gene expressed in the infected and uninfected samples . Genes were considered to be induced or repressed when the ratio of infected/uninfected was at least 1 . 5 fold ( increased or decreased ) , and the P value was <0 . 05 by the Student's two-tailed t test . For analysis involving more than one time point and/or condition , the one way ANOVA test was performed . Microarray data are deposited in GEO archive under the accession numbers GSE23172 and GSE23173 . EA . hy926 cells were seeded in tissue culture treated glass slides ( BD Falcon ) and grown at 37°C as described above . After cells reached 100% confluence , the monolayer was washed three times with PBS and medium without antibiotics was added . Four compartments of each slide were inoculated with 1×107 bacteria ( MOI = 10 ) of either L . biflexa serovar Patoc or L . interrogans serovar Canicola . The remaining four wells were left uninfected to serve as negative controls . In some cases , parallel experiments were performed using cells plated on coverslips in 24 well culture dishes , which allowed centrifugation to facilitate bacterial-endothelial cell contact . At the end of the incubation ( 1 h , 3 h and 24 h ) the slides were washed three times with PBS and fixed with 3% ( wt/vol ) paraformaldehyde in PBS at room temperature for 30 min . Cells were permeabilized with 0 . 1% Triton X-100 in PBS , washed three more times with PBS , and blocked overnight at 4°C with HEPES buffered saline ( HBS ) and 1% bovine serum albumin ( BSA ) . On the next day the slides were washed again with PBS and incubated with fresh blocking solution for 1h at room temperature . After blocking , the layers were probed with either rabbit anti-L . interrogans ( a gift from Dr . Richard Zuerner , USDA , AMES , IA ) diluted 1∶5000 or anti-L . biflexa antiserum ( Biogenesis , Inc . , Brentwood , NH ) diluted 1∶1000 , followed by anti-rabbit IgG-TRITC conjugate ( 1∶1000 ) plus phalloidin-FITC ( 200 U/mL ) to stain filamentous actin . After repeated washing in PBS , chambers were removed from the slides and Prolong Anti-Fade ( Invitrogen , Carlsbad , CA ) was used to mount coverslips . Two different microscopes at two different institutions were used throughout the course of this work . At institution one , images were captured using a Zeiss Axioplan microscope with a digital charge-coupled device camera ( Hamamatsu , Hamamatsu City , Japan ) and co-localization of the fluorescent labels was done using Volocity software ( Improvision Inc . , Lexington , MA ) . At the second institution a Zeiss Axioimager Z1 with an Axiocam HrC camera and a Nuance Multi-Spectral Imaging System ( software CRI Inc , Woburn , MA , v . 2 . 6 . 0 ) was used . The endothelial cell lines EA . hy926 and HMEC were plated in 3 . 0 µm ( 2×106 pores/cm2 ) polyester transwell inserts ( Corning ) and cultured as described above . After reaching 100% confluence , as assessed by lack of penetration of the fluorescent dye FITC-dextran 40 , 000 ( and loss of penetration of the L . biflexa serovar Patoc ) , the monolayer was washed with PBS and cell medium without antibiotics was added to the inserts and wells . Inserts without cells were used as controls for these experiments . Bacteria were added to an MOI of 50 to allow reliable enumeration of bacteria crossing the cell layers or membranes without cells at early time points , and 10 µL from the insert and from the well were taken after 1 h , 3 h , 6 h , 24 h , 27 h , 48 h and 72 h . In addition to the non-pathogenic strain Patoc and the pathogenic Canicola , Leptospira interrogans serovar Copenhageni was also used to analyze the migration of leptospires through the cell monolayer . Motile leptospires were counted by dark-field microscopy using a Petroff-Hausser chamber . Data are shown for the time points through which the bacteria were motile; after 72 hr there was a progressive decrease in L . biflexa motility . To determine whether the bacteria were affecting the viability of the endothelial cells , four methods were used . First , adherent and EDTA-lifted endothelial cells infected at an MOI of 10 were washed , then incubated with the vital dye CellTracker Green ( CT-CMFDA , 10 µM ) plus DAPI ( 0 . 02 µg/ml ) ( Molecular Probes , now part of Invitrogen , Eugene , OR ) for 1 hour at 37°C under 5% CO2 . The samples were mounted and viewed using the Zeiss Axioplan microscope described above , and live cells ( bright green cytoplasm ) and dead cells ( bright blue nuclei ) were enumerated in at least three fields per sample in at least three independent experiments . Second , the cells were stained using the Vybrant Apoptosis Assay Kit 2 ( Molecular Probes ) , which stains for annexin V and membrane permeability . Third , the APO-BrdU TUNEL kit , also from Molecular Probes , was used . A second TUNEL-based kit , Alert DNA Fragmentation kit ( Clontech Laboratories , Inc . , Mountain View , CA ) was also used . For methods two and three , the cells were also assessed using fluorescence microscopy . Finally , cells were harvested , and DNA was purified and analyzed for fragmentation ( an assessment of apoptosis ) using conventional agarose gel electrophoresis .
We identified statistically significant and reproducible changes in endothelial cell gene expression after incubation with each bacterial strain as compared to the uninfected controls and to each other . The data were analyzed using Webgestalt [18] to identify mammalian cell genes whose products comprise functional pathways in which multiple components showed alterations in gene expression ( Table 1 ) . Four pathways that show internally consistent changes in gene expression are the KEGG focal adhesion , regulation of actin cytoskeleton , leukocyte transendothelial migration , and ECM-receptor interaction pathways . They are considered together because a number of genes encode proteins whose functions participate in aspects of cell biology common to these pathways . Actin microfilaments are one of the three major components of the cellular cytoskeleton . The cytoskeleton participates in maintaining adhesion to and communicating with the extracellular matrix , cell migration , division , and signaling . β-Actin ( ACTB ) mRNA was decreased in response to L . interrogans but increased in response to L . biflexa , both as compared to the uninfected control cells ( Table 2 ) . Guanine nucleotide-binding protein alpha-13 subunit ( GNA13 ) mediates the activation of the small GTPase RhoA [19] which when activated controls the assembly of focal adhesions and actin in the formation of stress fibers [20] . Although RhoA was not differentially regulated in response to the bacteria , Rho GTPase activating protein 5 ( RhoGAP5 ) was differentially expressed following the same pattern as GNA13 , in which both genes were downregulated in response to the pathogenic leptospires in comparison to the uninfected controls , and upregulated in response to the non-pathogen . The effect of decreased GNA13 may be to decrease stimulation of Rho , while decreasing the GAP would decrease inactivation of Rho with concomitant decreased cell spreading on the extracellular matrix . The changes in expression of several additional genes are consistent with changes in cellular architecture as a result of leptospiral infection of these endothelial cells . For example , decreases in the mRNAs for radixin ( RDX , a protein that links the actin cytoskeleton to the plasma ) , caveolins 1 and 2 ( CAV1 and CAV2 , which couple integrins to the Ras-ERK pathway , titin , the ECM component laminin β1 , and integrin subunits αv and β3 ( Table 2 ) , were seen in cells infected with L . interrogans Canicola as compared to the uninfected controls . In contrast , the L . biflexa Patoc caused increases in mRNA levels for the same genes in infected cells vs . uninfected controls ( Table 2 ) . Together , all of these gene expression patterns are consistent with the hypothesis that one effect of L . interrogans serovar Canicola is to promote actin remodeling and detachment of the cells from the ECM . A fundamental stage in the pathogenesis of Leptospira infections is the ability of the bacteria to cross mucous membranes and underlying epithelial barriers , as well as endothelial cell barriers , and disseminate to different organs . Although Leptospira species are extracellular bacteria apparently devoid of actin modifying exotoxins [21]–[23] , and devoid of the specialized secretion systems utilized by many bacterial pathogens to deliver toxins that disrupt the host cell cytoskeleton ( as reviewed in [24]–[28] ) , pathogenic leptospires might be indirectly targeting the cytoskeleton via cell surface attachment mechanisms that co-opt the host cell signaling to achieve the same result . Decreased cellular adhesion to the ECM and rearrangement of the cytoskeleton may facilitate the migration of Leptospira through endothelial barriers as it disseminates from the site of inoculation . To further explore the possibility that actin rearrangements are triggered by Leptospira infection at the functional level , endothelial cells plated in chamber slides were infected at an MOI of 10 for 1 hour and 3 hours . As shown in Figure 1 , the bacteria were clearly more adherent to the cells than to the extracellular space , and the pathogenic bacteria caused dramatically more significant alterations in cellular morphology and integrity of the cell layer than did the non-pathogenic bacteria . The earliest change noted was a reduction in cortical actin ( so the cell edges are less defined ) and appearance of gaps in confluent cell layers , followed by loss of stress fibers and rounding of the cells . The images shown in Figure 1 are from cell layers that were just below confluence prior to infection , to allow better visualization of changes in individual cells . For example , while the cortical actin has largely disappeared in cells infected with L . interrogans Canicola by 1 hour post-infection , and stress fibers have disappeared and cell rounding is evident by 3 hours , the cells are largely unaffected at the same time points after infection with L . biflexa Patoc ( Figure 1 ) . L . biflexa does adhere to mammalian cells in culture less efficiently than does L . interrogans ( as shown and reviewed in [17] ) , but even when bacterial contact with the cells was facilitated by centrifugation , the L . biflexa caused little disruption to cellular morphology and cell layer integrity ( data not shown ) . Although these and subsequent experiments were performed using adherent cells , the morphologic changes are consistent with changes in mRNA levels seen using lifted cells in the microarray experiments . Despite the alterations in cellular architecture and monolayer integrity , no decrease in endothelial cell viability was found by any of several criteria ( see Materials and Methods ) , even after infection times extended as long as 48 hours ( Figure 2 ) . The disruptions in the layers did , however , result in the ability of the pathogenic strain to cross the monolayers more efficiently than did the non-pathogenic bacteria ( Figure 3 ) . After a brief period in which the endothelial layer did prevent significant transmigration of the bacteria , the layer rapidly became essentially irrelevant as a barrier to the penetration of the pathogenic bacteria , as the bacterial counts in the lower chamber were unaffected by whether or not cells had been plated on the membrane . Because Leptospira interrogans has been shown to bind to proteoglycans on the mammalian cell surface [17] , we tested a proteoglycan synthesis inhibitor , β-xyloside , for the ability to decrease damage to endothelial cell layers caused by L . interrogans Canicola . β-xyloside inhibits transfer of glycosaminoglycan chains to protein cores; a control sugar analog , α-galactoside , was tested in parallel . As shown in Figure 4 , inhibition of proteoglycan synthesis did not fully prevent the damage to the endothelial cell layers caused by L . interrogans . The inhibition of glycosaminoglycan chain attachment does not significantly affect the formation of holes in the cell layer caused by L . interrogans Canicola as assessed visually and by measurement of L . interrogans penetration of the cell layers ( data not shown ) . β-xyloside does cause a reduction of L . interrogans Canicola and Copenhageni attachment to these cells ( [17] and data not shown ) , but does not abolish bacterial attachment , consistent with the hypothesis that additional non-proteoglycan molecules serve as substrates for L . interrogans attachment to cells . Direct bacterial attachment to the cells does appear to be required for the damage to the endothelial cell layers , as supernatants harvested from infected cell layers ( infection times of 1–24 hr ) and sterilized by centrifugation and filtration through 0 . 1 µm filters did not affect endothelial cell layer integrity ( data not shown ) . Therefore , non-proteoglycan cell surface receptors are likely to be those primarily involved in the responses of the endothelial cells to L . interrogans attachment , and efforts to identify both the host cell and the bacterial cell molecules involved in these interactions are underway . As noted in the publication reporting the sequence of two L . biflexa Patoc strains [29] , there are a number of proteins predicted in the published L . interrogans genomes that are not present in the L . biflexa Patoc genome , including some that are postulated to have potential adhesin activities . These include proteins containing leucine-rich repeats , which are involved in many protein-protein interactions [29] . As stated in the publication of the L . biflexa genome , it is intriguing that a Treponema denticola leucine-rich repeat protein , LrrA , has been identified as an adhesion/tissue penetration factor [29] , [30] . It is also possible that additional components of the surfaces of L . interrogans and L . biflexa might have different effects on host cells [31]–[33] . At this point , however , the determinants critical to the effects of L . interrogans-host cell interaction reported here remain to be identified , and neither bacterial adhesins nor host substrates can necessarily be predicted solely on the basis of the primary amino acid sequences . Several drugs currently in use in humans have been reported to have endothelial barrier protective function; all are in use as anti-hypertensive therapeutics , and some for other therapeutic purposes as well . We therefore tested four different drugs with different mechanisms of action for the ability to prevent the damage to endothelial layers in culture caused by L . interrogans . Lisinopril binds to and competitively inhibits angiotensin 1 binding to angiotensin converting enzyme ( ACE ) , which is expressed by endothelial cells , while telmisartan competitively inhibits angiotensin 2 binding to its receptor AT1 . Dopamine is an antagonist of VEGF/VEGFR2-mediated cell layer permeability in treatment of human umbilical vein endothelial cells ( HUVECs ) in vitro at 10µM , as well as VEGF-mediated angiogenesis in vivo and proliferation of HUVECs at 1 µM in vitro [34] , [35] . Furosemide is an anion transport blocker and is used as a diuretic but has anti-hypertensive activity as a consequence , and was used as a control not expected to preserve endothelial layer integrity . While telmisartan , furosemide , and dopamine did not protect the endothelial layers from the damage due to L . interrogans Copenhageni infection , lisinopril did at 100 nM , 1 µM and 10 µM ( Figure 5 , representing 3 independent experiments , and data not shown ) . There are several possible explanations for this , including: 1 ) lisinopril inhibits L . interrogans attachment to the cells , and 2 ) that attachment is unaffected but the interaction of the bacteria triggers activation of a signaling cascade or release of a mediator whose action or activation is inhibited by lisinopril . We therefore investigated the possibility that lisinopril might prevent endothelial damage by blocking L . interrogans Copenhageni attachment to the cells , but no inhibition of adhesion of 35S-labeled bacteria [17] was seen even at a concentration of lisinopril 10 fold over the concentration used for these experiments ( Figure 5 ) . Although it was tempting to speculate that cell-surface-localized ACE could serve as a receptor for L . interrogans , as the enzyme is expressed by endothelial cells and proximal tubule epithelial cells [36] , and is therefore open to possible competition by the lisinopril , this is not consistent with our results to date . However , ACE2 is not inhibitable by lisinopril , but is a receptor for the SARS virus [37] , so there is precedent for ACE proteins serving as receptors for pathogens . It is also possible that the effect of lisinopril in our system is not related to ACE inhibition , but is instead due to additional effects of lisinopril , such as inhibition of isoprenoid synthesis , which is required for the post-translational modification of Rho GTPases , which in turn regulate the actin cytoskeleton [38] . In turn , this may lead to increased NO synthesis , which is protective of endothelial function in the face of a variety of insults . Given that doxycycline also has endothelial protective effects [39] , and that doxycycline is effective in treating leptospirosis [40] , our results may also provide a starting point for investigation into possible combinatorial therapeutic approaches to reduction of endothelial damage and consequent organ damage in human populations during leptospirosis outbreaks . Should this combinatorial approach prove useful in animal models , consideration as a focused approach to the treatment of human leptospirosis is warranted . The 1 µM dose shown in Figure 5 is at the high end of the physiologically relevant dosing range for humans , but administration of an antihypertensive to a patient with clinical manifestations of leptospirosis would be contraindicated , as further depression of blood pressure levels would be potentially lethal . However , in outbreak situations , this agent could potentially help to reduce endothelial damage if administered to affected populations as soon as an outbreak situation is recognized , prior to exposure of the majority of the population to pathogenic Leptospira species . In addition , protective effects of lisinopril were maintained even at a dose of 100 nM , which is well within the range routinely used in humans ( Figure 6 ) . It will also be interesting to investigate the possibility that , on a population basis , patients on lisinopril fare better than patients not on this therapy during leptospirosis outbreaks . Reorganization of the actin cytoskeleton , as indicated by our microarray studies and by phalloidin staining of F actin , is essential to the pathogenesis of diverse bacterial infections , and pathogens use many different strategies to provoke changes in the cellular cytoskeleton in order to facilitate invasion of tissues , invasion of host cells , or evasion of phagocytosis ( as reviewed in [24] , [41] , [42] ) . A different spirochete , Treponema denticola , produces the protein Msp , which disrupts the actin cytoskeleton in neutrophils and fibroblasts , preventing phagocytosis of the bacterium and inhibiting the cellular migration required to respond to and repair the damage caused by the pathogen and the host response at the site of infection [43] , [44] . These activities are likely to facilitate invasion and colonization of periodontal tissues by T . denticola . Previous work by another laboratory demonstrated that L . interrogans Copenhageni crosses MDCK canine kidney epithelial cell layers in culture more rapidly than does L . biflexa Patoc [45] , but without significant disruption to the cell layers or the actin cytoskeleton . Consistent with these results , in experiments not shown here we also observed no significant damage to NRK ( normal rat kidney ) 293 ( human kidney ) or HEp-2 ( human laryngeal ) epithelial cell layers infected with L . interrogans Canicola or L . interrogans Copenhageni . The calculations of the proportions of bacteria crossing the cell layers differed between the two studies , but our protocol accounted for the replication of the L . interrogans Canicola and Copenhageni in the co-cultures , while the L . biflexa Patoc did not replicate ( data not shown ) . Thus the endothelial cells tested here respond very differently to the bacteria than did the MDCK epithelial cells , and our results are the first to suggest a mechanism: disruption of actin dynamics by bacterial attachment to the cell surface . Thus , while L . interrogans has not been shown to secrete a toxin that modifies actin , the bacteria are able to manipulate the actin cytoskeleton indirectly . Even the pore forming toxin activity reported for Leptospira [46] , [47] does not appear to have as large an effect , as the endothelial cells here were viable throughout the experiments . The leptospires may be able to establish disseminated infection in part due to the binding of the bacteria to one or more mammalian cell surface receptors that in turn , regulate the dynamics of the actin cytoskeleton in the mammalian cell . Deciphering the role of , and mechanisms behind , actin rearrangement in response to pathogenic Leptospira will provide insights into the mechanisms that leptospires uses to disseminate to different organs of the host to cause infection and disease , and provides a possible avenue for therapeutic intervention in conjunction with antimicrobial therapy . | Leptospirosis is a widespread zoonotic infection that primarily affects residents of tropical regions , but is seen occasionally in temperate regions as well . Leptospirosis can vary in severity from a mild , non-specific illness to severe disease that includes multi-organ failure and widespread endothelial damage and hemorrhage . To investigate how pathogenic leptospires affect endothelial cells , we compared the responses of two endothelial cell lines to infection by pathogenic versus non-pathogenic leptospires . Our analyses suggested that pathogenic L . interrogans and non-pathogenic L . biflexa caused changes in expression of genes whose products are involved in cellular architecture and interactions with the matrix , but that the changes were in opposite directions , with infection by L . biflexa primarily maintaining cell layer integrity , while L . interrogans disrupted cell layers . In fact , L . interrogans caused significant disruption of endothelial cell layers , but this damage could be abrogated by the endothelial protective drug lisinopril . Our results suggest that L . interrogans binds to endothelial cells and disrupts endothelial barrier function , which may promote dissemination of the bacteria and contribute to severe disease manifestations . This disruption may be slowed by endothelial-protective drugs to decrease damage in leptospirosis . | [
"Abstract",
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"diseases/bacterial",
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] | 2010 | Responses of Human Endothelial Cells to Pathogenic and Non-Pathogenic Leptospira Species |
Pure populations of quiescent yeast can be obtained from stationary phase cultures that have ceased proliferation after exhausting glucose and other carbon sources from their environment . They are uniformly arrested in the G1 phase of the cell cycle , and display very high thermo-tolerance and longevity . We find that G1 arrest is initiated before all the glucose has been scavenged from the media . Maintaining G1 arrest requires transcriptional repression of the G1 cyclin , CLN3 , by Xbp1 . Xbp1 is induced as glucose is depleted and it is among the most abundant transcripts in quiescent cells . Xbp1 binds and represses CLN3 transcription and in the absence of Xbp1 , or with extra copies of CLN3 , cells undergo ectopic divisions and produce very small cells . The Rad53-mediated replication stress checkpoint reinforces the arrest and becomes essential when Cln3 is overproduced . The XBP1 transcript also undergoes metabolic oscillations under glucose limitation and we identified many additional transcripts that oscillate out of phase with XBP1 and have Xbp1 binding sites in their promoters . Further global analysis revealed that Xbp1 represses 15% of all yeast genes as they enter the quiescent state and over 500 of these transcripts contain Xbp1 binding sites in their promoters . Xbp1-repressed transcripts are highly enriched for genes involved in the regulation of cell growth , cell division and metabolism . Failure to repress some or all of these targets leads xbp1 cells to enter a permanent arrest or senescence with a shortened lifespan .
Budding yeast that are grown in rich glucose-containing media and are allowed to naturally exhaust their carbon source undergo a series of changes that enable a significant fraction of the cells , primarily daughter cells , to enter a protective quiescent ( Q ) state [1] . As yeast cells transition to quiescence , they shift to respiration [2] and stockpile their glucose in the form of glycogen and trehalose [3] , [4] . These Q cells are significantly denser than their nonquiescent ( nonQ ) siblings , which enables us to purify them by density sedimentation [1] . The ability to purify Q cells offers a unique opportunity to study this transition . An important characteristic of all quiescent cells is that they arrest their cell cycle in G1 . This requires the G1 to S transition to be stably halted by a mechanism that can be readily reversed when conditions permit . In cycling cells , progression through G1 into the next S phase involves two consecutive waves of G1 cyclin ( Cln ) expression . CLN3 is transcribed at the M/G1 border [5] and Cln3 associated with the cyclin-dependent kinase ( Cdk ) activates the transcription of the CLN1 and CLN2 cyclins and other genes that trigger budding and DNA replication [6]–[8] . If the fidelity or timing of S phase is disrupted , there are checkpoint proteins , including Rad53 and Rad9 , which monitor incomplete or damaged DNA and delay cell division to allow for reparations [9] . Cln3/Cdk activity is rate limiting for the G1 to S transition during exponential growth . Excess Cln3 results in shorter G1 phases and smaller cells , while loss of Cln3 function prolongs G1 and results in larger cells [10] , [11] . Previous studies have shown that the G1 cyclin Cln3 , ectopically expressed during stationary phase from the UBI4 promoter , prevents G1 arrest and causes loss of viability [12] . Tetraploid cells also die in stationary phase and this inviability can be completely rescued by deletion of all four CLN3 genes [13] . These deleterious effects indicate that Cln3/Cdk must be tightly controlled during stationary phase and that its deregulation antagonizes entry into the Q state . In this work , we demonstrate that G1 arrest is initiated before the diauxic shift ( DS ) , which is when all the glucose has been scavenged from the media . CLN3 is a critical target of repression for G1 arrest and for the transition to quiescence . Rad53 checkpoint activity reinforces this arrest in wild type cells and becomes essential when Cln3 is overproduced . Xbp1 is also important for maintaining G1 arrest . Xbp1 is a repressor of CLN3 transcription [14] , [15] . It is related to the Swi4/Mbp1 family of transcription factors , which are the DNA binding components of the yeast complexes paralogous to E2F/Dp1 in higher cells [7] , [8] . As glucose is exhausted from the media , the XBP1 transcript is induced and it is among the most abundant transcripts in Q cells . Xbp1 binds and represses hundreds of genes , including CLN3 during the post-DS phase of growth . In the absence of Xbp1 , cells undergo extra post-DS cell divisions and produce very small cells . These phenotypes are Cln3-dependent . xbp1 mutant Q cells are also defective in the maintenance of and recovery from the Q state . xbp1 Q cells maintain viability , but lose the ability to re-enter the cell cycle . Using Next Generation Sequencing [16] , we have identified over 800 transcripts that are repressed three-fold or more by an Xbp1-dependent mechanism and 520 of these contain Xbp1 binding sites in their promoters . Xbp1 binds directly to all seven of the promoters we tested , in vivo , but only in post-DS cells . These findings indicate that Xbp1 is a global regulator specifically during the transition to quiescence . Xbp1's other targets include many genes involved in cell division , with a particular enrichment of genes required for cytokinesis . Many genes whose products localize to sites of polarized cell growth and are involved in cell wall remodeling are targeted by Xbp1 . In addition , many metabolic and transport pathways are repressed by Xbp1 .
Yeast cells spend most of their time in a non-dividing state triggered by nutrient depletion from their environment . Under the conditions we employ ( see Methods ) , yeast undergo a highly reproducible transition from the logarithmic ( log ) phase of growth to stationary phase in response to carbon limitation . Figure 1 shows the average of four growth curves in which we monitored cell density , cell number and DNA content as prototrophic W303 cells grew from log phase to stationary phase in rich medium . The turbidity of the culture increases over this time course to an optical density ( OD600 ) of about 24 , but the cell number only doubles once after the DS , which occurs between the 12 and 14 hour time points . We have monitored the DNA content of these cells to determine what fraction of cells are in G1 , S and G2/M over this time course . Interestingly , the 12 to 14 hour interval shows the sharpest increase in the percentage of cells in G1 . This indicates that the signal to slow proliferation is occurring at or before the DS and cells respond by extending or arresting in G1 . Figure 1D shows the DNA of wild type cells in log phase ( 8 hours ) , immediately after the DS , and one hour later . During log phase , the G1 ( 1N ) and G2/M ( 2N ) cells form two spots or peaks of high density by flow cytometry . The cells in S phase , with intermediate DNA content , are scattered between them and make up about 20% of the cells in the population . At the DS , the percentage of cells in G1 is already double that of log phase cells . This indicates that cells begin to slow the G1 to S transition before the diauxic shift . Also at the DS , we see a drop in the number of cells that are in early S phase ( Figure 1D , ) which is an indication that the initiation of new DNA synthesis ceases at this time . One hour after the DS , less than 3% of the cells are in S phase , and this pattern persists for at least 34 hours . We conclude that the signal to stop proliferation is received before the cells have scavenged all the glucose from the media and they respond by extending G1 . The halt to DNA replication is correlated with and could be triggered by the DS . To determine how G1 arrest is accomplished , we have assessed the role of several key regulators of the G1 to S transition . Cln3/Cdk activity is rate limiting for the G1 to S transition during exponential growth . To investigate the effects of over-producing Cln3 on Q cell formation , we generated a prototrophic strain carrying five copies of the wild type CLN3 gene ( 5XCLN3 ) . This strategy maintains all the regulatory features of the wild type CLN3 gene , while it increases the Cln3 expression level . We first verified that the 5XCLN3 construct produces about five-fold higher levels of CLN3 mRNA than wild type as cells grow from log to stationary phase ( Figure 2A ) . To assess the impact of excess Cln3 on the transition to quiescence , we compared Q cell yield in 5XCLN3 cells to cln3 mutant and wild type cells . 5XCLN3 consistently reduces Q cell yield by half , and cln3 mutants increase Q cell production by at least 30% . This confirms that Cln3 activity is above wild type levels in the 5XCLN3 strain and that this excess Cln3 inhibits Q cell formation . It also suggests that cells enter the Q state from G1 and the longer they stay in G1 the more likely they are to achieve a successful transition into this state . The CLN3 transcript level is high in rapidly cycling cells then it drops abruptly as cells enter stationary phase ( Figure 2A ) . This is not unexpected , because the CLN3 promoter is cell cycle regulated [5] , and it is activated by Azf1 in the presence of glucose [17] , [18] . In addition , CLN3 is a target of the Xbp1 repressor , which is highly induced by glucose limitation [14] . Xbp1 is a transcriptional repressor that is not expressed during the log phase of growth , but it is induced by many forms of stress , including DNA damage and glucose limitation [14] , [19] . When Xbp1 is ectopically produced in log phase cells , it binds to and represses the CLN3 , CLN1 and CLB2 cyclin promoters [15] . Xbp1 overproducers also grow slowly and prolong the G1 phase of the cell cycle [14] , [20] . This led us to ask if Xbp1 could be important for repressing CLN3 and halting cell division during the transition from log phase to quiescence . xbp1 and wild type cells are identical in size during logarithmic growth , however xbp1 cells are much smaller than wild type cells when grown to stationary phase ( Figure 2B ) . This could be explained if xbp1 mutants continue proliferating under growth limiting conditions and the physical growth of the resulting cells is impaired . Figure 2C shows that this is the case . xbp1 cultures attain a higher cell number at stationary phase than do wild type cells , indicating that they undergo extra cell divisions . This can also be seen as a slower accumulation in G1 ( Figure 2D ) . The xbp1 mutant reaches 80% G1 eight hours after wild type cells . If CLN3 is a critical target of Xbp1 , we expected that the ectopic cell divisions , the small cell size , and the G1 arrest delay of xbp1 mutants would depend on the presence of Cln3 . We have assayed these phenotypes in the xbp1cln3 double mutant . As predicted , xbp1cln3 cells are the same large size as cln3 cells ( Figure 2B ) , and they undergo fewer cell divisions , as do cln3 cells ( Figure 2C . ) xbp1cln3 cells also display the same rate of accumulation in G1 that is seen in wild type cells ( Figure 2D ) . This shows that these hyper-proliferative phenotypes of xbp1 are Cln3-dependent . We also expected that 5XCLN3 would share these xbp1 phenotypes . Figure 2B shows that 5XCLN3 cells are the same small size as xbp1 cells during post-diauxic growth , they undergo extra cell divisions like xbp1 ( Figure 2C ) , and 5XCLN3 delays G1 arrest ( Figure 2E . ) During logarithmic growth , accelerating the transition from G1 to S causes a sub-optimal S phase and such cells cannot survive without eliciting the replication stress checkpoint [21]–[23] . The fact that excess Cln3 only delays G1 arrest led us to wonder if the replication stress checkpoint also plays a role in restraining cell cycle progression under these conditions . To test this , we combined rad53-21 , which lacks checkpoint activity [24] with 5XCLN3 . These cells were grown from log phase into stationary phase and assayed for their ability to G1 arrest . Like 5XCLN3 , rad53-21 alone has a modest G1 arrest defect . However , Rad53 is critically important for G1 arrest and Q cell formation when Cln3 is in excess . rad53-21 5XCLN3 cells divide more slowly and undergo the DS six hours later than wild type cells . They very gradually accumulate in G1 , reaching 50% G1 about 30 hours later than wild type ( Figure 2E ) . These cells also lose viability rapidly as they enter stationary phase ( Figure 2F . ) After seven days of growth 80% of the rad53-21 5XCLN3 cells were dead based on vital dye staining . rad53-21 5XCLN3 cells are also completely defective in Q cell formation . These results indicate that the excess Cln3 produced by the 5XCLN3 loci is toxic to nutrient-limited cells that do not have Rad53 checkpoint function . It is worth noting that this experiment was carried out at a constant pH in rich medium . Therefore , this loss of viability cannot be due to acidification , as it is in unbuffered , minimal media [25] . Reactive oxygen species ( ROS ) and DNA fragmentation has been associated with DNA damage and replication stress in yeast and metazoan cells [26] , [27] . During log phase , 8% of the rad53-21 5XCLN3 cells were ROS positive ( data not shown . ) By day five , 43% of these cells contained ROS and 31% showed DNA fragmentation , as detected by TUNEL staining ( Figure 2G ) . ROS was also detectable in 5XCLN3 and rad53-21 single mutants , but they showed no detectable TUNEL positive cells and high viability over this time course , which indicates that they were able to tolerate this level of ROS accumulation . However , the rad53-21 cells contained four times more ROS than wild type cells by day five ( Figure 2G ) . This indicates that wild type cells also rely on Rad53 checkpoint activity during the transition to quiescence . Rad53 is activated in response to both replicative stress and DNA damage . To see if DNA damage is involved , we combined 5XCLN3 with rad9 , which is a DNA damage-specific checkpoint protein [28]–[30] . 5XCLN3 showed no toxicity in the absence of Rad9 ( Figure 2F ) . We conclude that cells utilize the replicative stress checkpoint to reinforce cell cycle arrest during the transition to quiescence . Cells that fail to down-regulate CLN3 during this transition depend on this checkpoint for their survival . Checkpoint failure leads to apoptotic cell death . Repression of CLN3 is important for the G1 arrest that is initiated by glucose limitation , and our data are consistent with Xbp1 playing a role in that process . However , when we combine xbp1 with rad53-21 , there is no additive effect . The xbp1 rad53-21 is no more defective in G1 arrest then rad53-21 alone ( Figure 2D ) . This suggests that Xbp1 may not repress CLN3 under these conditions . To directly assess the role of Xbp1 in CLN3 repression , we used chromatin immunoprecipitation and RNA Next Generation sequencing . Figure 3A ( lanes 1 and 2 ) show that Xbp1 binding to the CLN3 promoter is undetectable in log phase cells , but it is clearly bound in cells harvested after 24 hours of growth . This can be explained by the fact that Xbp1 is induced by glucose limitation . Figure 3B shows the dramatic induction of XBP1 mRNA that begins before the diauxic shift ( 14 hours ) and continues for 48 hours . It is also present at very high levels in Q cells purified from a seven day old culture . In fact , XBP1 ranks within the top 100 most abundant transcripts in Q cells . Figure 3C shows CLN3 mRNA levels over this same time course in wild type and xbp1 cells . The initial pre-DS drop in CLN3 mRNA still occurs , but we see a two to three-fold de-repression of CLN3 from 14 to 48 hours in the absence of Xbp1 . It then drops to a very low level in Q cells , and that drop is also Xbp1-independent . This pattern suggests that there may be three distinct mechanisms for establishing and maintaining CLN3 repression and that Xbp1 plays a role in maintaining CLN3 repression during post-diauxic growth . The fact that the pre-DS drop in CLN3 levels still occurs in xbp1 cells indicates that the initial signaling to slow proliferation is intact . Figure 2C and D also show that cell number and the fraction of xbp1 cells in G1 is very similar to wild type for the first 18 hours . Direct comparison of the FACS profiles of wild type ( Figure 1D ) and xbp1 cells ( Figure 3D ) shows that xbp1 cells halt S phase as well as wild type at the 14 hour time point , but by 20 hours a new S phase population has emerged ( Figure 3D . ) This S phase re-entry is also Cln3-dependent ( data not shown . ) In contrast , S phase cells are present at the DS and throughout this time course in the 5XCLN3 population ( Figure 3E . ) It is possible that either the timing or the extent of replication driven by 5XCLN3 makes these cells more dependent upon the Rad53 replication stress checkpoint for viability . The high level of induction of XBP1 suggests that it may be a major regulator during post-diauxic growth and in Q cells . Two other key properties of Q cells are their ability to rapidly reverse their arrest upon re-feeding , and their longevity during prolonged intervals of arrest . Xbp1 Q cells are defective in both of these processes . Figure 4A shows the recovery cycle of wild type and xbp1 Q cells upon re-feeding . Wild type Q cells have a 90 minute delay , followed by a highly synchronous cell cycle as monitored by budding . xbp1 Q cells initiate budding 30 minutes later and only about half the cells participate . The very small xbp1 Q cells show no indication of budding at the 150 minute time point ( Figure 4D . ) These small cells initiate budding two hours after wild type Q cells begin to bud . Q cell longevity is also compromised by xbp1 . Figure 4B shows that xbp1 Q cells , suspended in water , retain wild type viability for at least 8 weeks , as assayed by vital dye exclusion . Q cells do not acidify the water over this time course , indicating that they are in a fundamentally different state than stationary phase cultures [25] . However , xbp1 Q cells lose the ability to form colonies more rapidly than wild type Q cells , indicating that they cannot maintain a reversible quiescent state ( Figure 4C ) . After six weeks , 75% of xbp1 Q cells are viable , but only one-third of those can re-enter the cell cycle and form a colony . Interestingly , all of the viable cln3 Q cells can return to the cell cycle at this time point . This irreversible non-dividing state or senescence exhibited by xbp1 Q cells can be delayed , but it is not suppressed by deleting CLN3 . This indicates that the premature senescence of xbp1 is not a Cln3-dependent phenotype . We conclude that Xbp1 also targets genes that influence the recovery and longevity of Q cells . To see if Xbp1 performs a broader repressive function during the transition to quiescence , we looked for transcripts that are repressed when XBP1 is induced . XBP1 mRNA undergoes dramatic oscillations in cells that are synchronized to undergo metabolic and cell cycle oscillations by glucose limitation [31] . Xbp1's known targets ( CLN3 , CYS3 , CLN1 and CLB2 ) also display metabolic oscillations , and peak out of phase with Xbp1 . Using microarray and motif search tools [32]–[34] , we identified ten transcripts that undergo metabolic oscillations out of phase with Xbp1 and that contain Xbp1 binding sites in their promoters . We verified that PIS1 , DOG2 , and CDC10 are bound in vivo by Xbp1 after the DS , just like CLN3 ( Figure 3A ) . We then identified 100 transcripts whose profiles in the metabolic oscillation data set were most closely correlated with the average profile of CLN3 , DOG2 and PIS1 ( Supplementary Figure S1 ) [35] . Among those 100 genes , 54 contained Xbp1 binding sites ( CTCGAG/A [14] ) within 800 base pairs of their translational start sites . Three of these genes encode transcription factors ( RCS1/AFT1 , RFX1 and NRG2 ) , which we also verified to be in vivo binding sites for Xbp1 by chromatin immunoprecipitation ( Figure 3A ) . To show that the repression of these transcripts is Xbp1-mediated and to identify other targets , we used our Next-Generation RNA sequencing [16] data to compare transcript levels of genes from wild type and xbp1 cells as they transit from log phase to stationary phase . CLN3 ( Figure 3C ) , and all 54 of the transcripts we identified as having Xbp1 binding sites , were derepressed in one or more of the post-DS time points in the xbp1 mutant . We then identified over 800 transcripts ( Supplementary Table S1 ) that are repressed by Xbp1 , three-fold or more , in at least one of the post-DS time points . More than half ( 520 ) of these genes contained Xbp1 binding sites within the 800 base pairs upstream of their coding sequences . Figure 5A shows the consensus Xbp1 binding site derived from these 520 derepressed transcripts . We will refer to these 520 genes as direct targets of Xbp1 . Figure 5B shows a dot plot comparison of all transcript levels in xbp1 and wild type cells . Direct Xbp1 targets ( red dots ) are not significantly affected by the absence of Xbp1 during log phase ( 8 hours ) . A few transcripts begin to rise in the xbp1 cells at the DS ( 14 hours ) , and this trend continues throughout the time course and in purified Q cells . Very few direct targets are down-regulated . This is consistent with our previous findings that Xbp1 functions as a repressor [14] , [15] , and expands its role as a global repressor specifically during post diauxic growth and quiescence . Xbp1 expression is induced at 14 hours and remains high across this time course ( Figure 3B ) , but both the levels and the timing of transcription of its targets vary widely . Figure 6 shows the transcript levels of the direct and indirect targets of Xbp1 that are elevated three-fold or greater during post-diauxic growth . Forty of these transcripts are elevated at least sixteen-fold . However , most reach their peak during a specific interval , which varies for each target gene . We speculate that this variation is due to differences in activation . If Xbp1 serves solely as a repressor , the expression of each one of its target genes would still depend on the expression and stability of its activator ( s ) . To look more closely at all Xbp1-mediated repression , we identified transcripts that are derepressed three-fold or greater at each time point ( Table 1 ) . Significant derepression is observed after 18 hours . The majority of these Xbp1-repressed transcripts are involved in biological regulation ( p value 10–9 ) . One third are localized to the cell periphery , but only nine are classified as cell wall proteins . 23 are localized to sites of polarized cell growth [36] . Several of these genes are involved in bud site selection or are components of the Cdc42-mediated cell polarization pathway . Components of the septin ring , which separates mother from daughter [37] , the cohesion complex , which holds sister chromatids together , and components that facilitate chromosome segregation [38] are repressed by Xbp1 at 18 hours . Two cyclins ( CLN3 and CLN1 ) that drive the G1 to S transition [6] and are known Xbp1 targets [14] , [15] are elevated at this time point . Regulators of transcription are also affected . Among these are transcription factors that promote the G1 to S transition ( SWI6 [39] ) , the S to G2/M transition ( NDD1 [40] , and others that induce alternative cell fates: filamentation ( MSS11 and MGA1 [41] ) , and meiosis ( IME1 [42] ) . Hence , Xbp1 promotes quiescence by repressing multiple targets involved in mitotic growth and by preventing cells from adopting other developmental fates . After 24 hours of growth , 65 known genes are derepressed in the absence of Xbp1 . At this time point , cell wall proteins are highly enriched . These include most of the daughter-specific genes [43] . Six gluconases and the chitinase Cts1 , which are responsible for degrading the cell wall and chitin ring between mother and daughter to achieve cell separation [44] are targeted . In addition , cell division and specifically cytokinesis targets are highly enriched . Three late cycle cyclins ( CLB4 , CLB2 [45] and PCL9 [46] ) are also targeted . By 48 hours , nearly 10% of all genes ( 515 ) are derepressed in the absence of Xbp1 . At this time point almost half of the known targeted genes are involved in metabolism and the other large class is involved in cell wall biogenesis . 45 cell cycle genes and 25 transcription regulators are also derepressed at this time point . Only one-third of these derepressed genes are also derepressed in Q cells . Xbp1 affects a more diverse group of genes in purified Q cells . Metabolic genes are the largest class . In addition , 42 genes involved in transmembrane transport , including five glucose transporters are repressed by Xbp1 in Q cells . We also analyzed direct and indirect targets separately . What is striking is that direct and indirect targets are largely in the same pathways . At 18 and 24 hours , mitosis , cell cycle , cell division and cytokinesis are significantly enriched classes in both direct and indirect targets ( Supplementary Table S2 ) . At 48 hours , both direct and indirect targets are highly enriched for genes involved in metabolism and cell wall organization . The dot plots of Figure 5 show that Xbp1 primarily serves as a repressor of transcription . Transcripts whose levels are under-represented by three-fold or more in the xbp1 mutant are rare until the 48 hour time point and in Q cells . However , at these two time points almost 500 transcripts fit this criterion . Unlike the derepressed transcripts , of which 60% are associated with Xbp1 binding sites , only one fifth of the down-regulated genes are near an Xbp1 binding site , which is about what is expected by chance . This is consistent with Xbp1 playing an indirect role at these promoters . To our surprise , there are only 14 transcripts that are under-represented both at 48 hours and in Q cells . At 48 hours , the under-represented transcripts are nearly all involved in ribosome biogenesis ( 90/257 , p value 10–45 ) and nitrogen metabolism ( 156/257 p value 10–18 ) . In Q cells , they are highly enriched for ribosomal proteins ( 47/129 , p value 10–42 ) and genes involved in monosaccharide catabolism ( 16/129 p value 10–12 ) . The ribosome biogenesis and ribosomal protein transcripts are tightly and coordinately regulated in response to nutrient conditions [47] . It is unclear how Xbp1 influences the expression of these genes . The striking lack of overlap between the transcripts that are under-represented in xbp1 cells at 48 hours versus purified Q cells suggests that these are fundamentally different states .
In rich glucose-containing medium , yeast cells cease growth and division after about 48 hours due to carbon limitation . The resulting culture is a heterogeneous population of live and dead cells . Most of the daughter cells enter a quiescent state and can be purified due to their increased density [1] . Q cells develop unique characteristics including high thermo-tolerance [1] and high levels of glucose stored in the form of trehalose and glycogen [4] . The transition to quiescence does not occur when cells are abruptly deprived of glucose ( Li et al , submitted ) , so there must be some cellular response to its waning supply that signals cells to stop proliferating , stockpile the remaining glucose and enter a quiescent state . We are investigating the events that differentiate Q cells from nonQ cells and promote their longevity [48] . We find that G1 arrest is an early event in the transition to quiescence . There is a three-fold increase in the fraction of cells in G1 that occurs before glucose is depleted from the medium . At this point , referred to as the diauxic shift ( DS ) , initiation of DNA synthesis is dramatically reduced and most of the cell division that occurs thereafter can be accounted for by the completion of cell cycles that were previously initiated . We have identified several key regulators that are important for achieving this arrest . We find that excess Cln3 activity , expressed from five integrated copies of the wild type CLN3 gene , interferes with Q cell formation , and cells lacking Cln3 produce more Q cells . Cells transitioning to quiescence with excess Cln3 accumulate in G1 more slowly than wild type cells , but they eventually arrest and remain viable due to the activation of the checkpoint kinase Rad53 . Rad53 is an effector of the DNA damage and replication stress checkpoints [49] . Rad9 , which is specific to the DNA damage checkpoint [29] , [30] , is not required for the survival of 5XCLN3 cells , so we conclude that replicative stress , not DNA damage , triggers the checkpoint during the transition to quiescence . We detect delayed G1 arrest and increased ROS accumulation as nutrients become limiting , even in wild type cells carrying rad53-21 . This suggests that replication stress occurs and this checkpoint pathway plays a role in restricting cell cycle progression during the wild type transition to quiescence . With excess Cln3 , checkpoint function becomes essential and cells lacking it fail to arrest in G1 and undergo apoptosis . Related effects have been observed with excess cyclin E , and other activated oncogenes in higher cells [50] , [51] and in yeast [26] , [27] , [52] . Our data indicate that CLN3 repression is mechanistically different before and after the DS , and that only its post-DS repression is Xbp1-dependent . The initial drop in CLN3 levels and the halt to S phase that we observe at the DS are Xbp1-independent . Only after the DS , the CLN3 promoter is bound and repressed by Xbp1 . Cells lacking Xbp1 resume DNA replication and continue to divide after the DS , and this results in a significant population of very small cells . These phenotypes are Cln3-dependent . These data are consistent with Xbp1 playing a role in maintaining repression of CLN3 and G1 arrest as cells transition from growth to quiescence . However , unlike 5XCLN3 , xbp1 mutants are not dependent on the Rad53 replication stress checkpoint for viability . We suspect that either the timing or the extent of derepression of CLN3 by xbp1 could explain the Rad53-independence of these cells . A third possibility is that Rad53 acts in the same pathway and upstream of Xbp1 to restrict cell cycle progression . Rad53 has been shown to increase the level of Xbp1 in response to DNA damage [19] . These possibilities are under investigation . Xbp1 mutant Q cells remain viable , but they are profoundly delayed in cell cycle re-entry upon re-feeding . They are also short-lived as Q cells , entering an irreversible , senescent state more rapidly than wild type . We have not identified the genes responsible for these phenotypes because our data show that Xbp1 plays a global and continuous repressive role in cells as they transition from a dividing to a non-dividing quiescent state . We have identified 520 targets of Xbp1-mediated repression that contain Xbp1 binding sites in their promoters . All seven that we tested are direct in vivo binding sites for Xbp1 . Binding is only detected after the DS , which explains why these targets were not identified in previous studies . None of the Xbp1 targets identified by genome-wide location analysis [53] are among the 520 targets we have identified , and only 5 of the 41 transcripts reported to be affected by an xbp1 deletion [54] are among the 822 transcripts that we find are derepressed after the DS . These differences emphasize the need to determine when a transcription factor is active and use those conditions to search for its targets . The consensus binding site we have derived from the 520 targets agrees with that which we initially identified by site selection [14] and that reported by [55] . XBP1 mRNA oscillates dramatically in cells that are undergoing yeast metabolic and cell cycle ( YMC ) oscillations [31] , and we identified many Xbp1 targets by looking for its binding site in transcripts that oscillate out of phase with XBP1 . YMC oscillations are achieved by growing the cells to maximum density , starving them for glucose , then restoring a limited amount of glucose , which is immediately imported and cannot be detected in the media [31] , [56] . These conditions resemble the DS and they evoke the expression of genes that are induced by glucose starvation and stress , including XBP1 . Cell division stops and storage carbohydrates accumulate . This is the quiescence-like phase of the YMC [4] . In the subsequent phase , XBP1 is turned off , and it's targets peak . Then , DNA replication takes place and cells divide . The striking parallels between the events associated with the transitions in and out of quiescence , and those associated with the YMC suggest that YMC oscillations may be the result of switching on and off the signal to arrest in G1 and enter quiescence . It also seems likely that the oscillation of XBP1 expression is responsible for the subsequent YMC oscillations of its many targets . One such verified target , CLN3 , and many other cell cycle regulated transcripts have been shown to have different peak time or multiple peaks in the synchronized cell cycles induced by the YMC protocol [57] , [58] compared to that of other cell cycle synchronization studies [59]–[61] . Our finding that a global repressor of CLN3 and 800 other transcripts is also oscillating during the YMC time course may explain some of those altered peak times . Xbp1 negatively regulates the mRNA levels of 15% of yeast genes during post-diauxic growth . When Xbp1 was ectopically expressed during logarithmic growth , only a small number of Xbp1 targets were identified [14] . This suggests that Xbp1 may be more active in the post-diauxic state , either due to modification of Xbp1 or to the presence of co-factors that increase its activity or the accessibility of its targets . Among its many targets , Xbp1 represses the transcription of key activators of mitosis , meiosis , and filamentation . Repressing these genes may promote the quiescent state by reinforcing G1 arrest and by preventing cells from adopting alternative fates that are also triggered by nutrient limitation . Xbp1 also plays a major but complex role in the metabolic shifts that take place as cells shift from glycolysis to respiration to quiescence . Its many structural and regulatory targets involved in cell wall remodeling and cell division indicate that preventing growth is an active and continuous process in quiescent cells . Even basal expression of these genes may be deleterious to the stability of the quiescent state and/or to the orderly recovery from it . It is striking that transcripts derepressed by xbp1 early in the transition to quiescence are largely cell cycle and growth regulators . At 18 hours , even the gene products associated with the cell periphery are largely sensors and regulators , rather then structural proteins . This is true of both direct and indirect targets . One possible explanation is that xbp1 mutant cells continue to divide during this interval . About 20% of Xbp1 targets are cell cycle regulated at the transcript level ( data not shown ) . These transcripts are not made when cells stop dividing , so anything that promotes ectopic cell division would increase the transcription of these genes . However , only one-third of the 600 most cell cycle regulated transcripts [62] are elevated in the absence of Xbp1 and no particular class is enriched . If their elevated levels were due to continued cell divisions , all 600 would be elevated . We conclude that repression of these transcripts is an active Xbp1-mediated process , and the fact that half of them contain Xbp1 binding sites in their promoters is consistent with that conclusion . By 48 hours , hundreds of transcripts involved in metabolism and cell wall organization are affected . Again this is true of direct and indirect targets . At this point cell division has ceased , and transcriptional activators that promote cell division are likely to be inactive . Without these activators , loss of Xbp1-mediated repression may be of little consequence . However , house-keeping and metabolic genes may be constitutively active and require sustained repression in order to conserve resources . Our data indicate that Xbp1 provides the repression of these genes , perhaps through its recruitment of the histone deacetylase , Rpd3 [19] . We also looked for transcripts that were under-represented in the xbp1 mutant . These were prominent only in the last two time points and they do not show any enrichment for Xbp1 binding sites . This supports the view that Xbp1 functions primarily , if not solely , as a repressor . We expect that the reduced levels of these transcripts are an indirect effect of the many perturbations that arise in xbp1 cells where 15% of genes are expressed at a time when they should be off . XBP1 mRNA is among the top 1% highest level transcripts in Q cells . Xbp1 has also been shown to be translationally up-regulated in response to both glucose and amino acid starvation [63] . These observations are consistent with Xbp1 serving as a global repressor of transcription as cells respond to nutrient depletion and transition to a non-dividing quiescent state . The longevity and recovery defects we observe for xbp1 mutant Q cells demonstrate the importance of this repression . Xbp1 shares homology within its DNA binding domain with four other S . cerevisiae transcription factors that specify cell fate . Swi4 and Mbp1 associate with Swi6 and serve as activators of mitotic growth [64] . Sok2 and Phd1 play opposing roles in pseudohyphal development [65]–[67] . Xbp1 plays a minor role in sporulation [15] and pseudohyphal development [68] , and this work shows that it is an important global repressor during the transition to quiescence . This family of transcription factors is found only in fungi , and may be important targets for anti-fungal drugs . One of the Candida family members , Efg1 , is critical for biofilm formation , which renders these pathogens drug-resistant [69] . We note that many Xbp1 targets are also known to affect virulence in bacterial and fungal pathogens . These include PMT1 , 2 , and 4 [70] , ECM33 [71] , SMI1 and FKS1 [72] . Understanding Xbp1's regulation and its role in defining the quiescent state may provide important insights with both medical and basic research implications .
The yeast strains were all derived from W303 . The auxotrophic markers were corrected in all strains . The strains carrying five copies of CLN3 were generated by integrating additional copies of CLN3 at four different marker loci using the integrating vectors , pRS303-306 [73] . The wild type controls for these studies contain the same empty vectors integrated at the same locations . To generate the W303 prototroph , BY6500 , the auxotrophic mutations were replaced with the wild-type sequence by homologous gene replacement and verified by PCR and sequencing . The checkpoint deficient rad53-21 mutant ( Allen et al . , 1994 ) was crossed into the W303 background above to generate BY6741 and subsequently crossed with the 5XCLN3 strain to generate BY6698 . CLN3 , XBP1 and RAD9 were deleted with KanMX as described [74] . Reproducible growth curves were obtained by patching cells from fresh plates onto YEP plus 2% glycerol and growing them overnight to eliminate petites . This patch was used to inoculate 5 ml YEPD , then a further 1/50 dilution was made and grown overnight . This culture was used to inoculate 25 ml YEPD in a 250 ml flask to an optical density ( OD600 ) of 0 . 02 and allowed to grow at 30°C , shaking at 200 RPM . The diauxic shift was defined as the point at which no glucose was detected in the media , which was determined with glucose detection strips ( GLU 300 , Precision labs , Inc . West Chester , OH ) . Quiescent ( Q ) cells were purified from YEPD cultures that were seven days old using a 25 ml percoll density gradient [1] with minor modifications [48] . Q cell yield is calculated as the percentage of OD600 units loaded that sediment to the bottom nine ml of the gradient . Cell size and cell count was measured on a Z2 Beckman Coulter Counter . All time course data was collected in duplicate or triplicate , averaged and error bars are shown . Cell viability was monitored using the FungaLight Yeast Viability Kit ( Molecular Probes ) according to the manufacturer's protocol and the percentage of live cells was plotted over time . Reproductive capacity was assayed as the ability to resume cell division and produce colonies . Serial dilutions were plated on YEPD plates in duplicate and the percentage of colony forming units ( CFU ) was plotted , using the CFU from the freshly harvested Q cell sample as 100% . The FungaLight and CFU viability data are averages from at least two independent experiments . Calcofluor staining of bud scars: Approximately 107 cells were collected and mixed with Calcofluor white M2R ( Fluorescent brightener 28; Sigma ) at a final concentration of 100 µg/ml . Cells were incubated at room temperature for 15 min in the dark then were washed twice with H2O . The stained cells were examined with a Nikon Eclipse E600 microscope with a Nikon Plan Apochromat 60XA/1 . 40 oil immersion objective and a UV-2E/C DAPI filter ( excitation at 330–380 nm ) . Photomicrographs of cells were taken on a Photometrics Cascade 512B camera and analyzed with MetaMorph version 6 . 3r2 software ( Molecular Devices , Sunnyvale , CA ) . TUNEL Assay: Cells were fixed with 4% paraformaldehyde at room temperature for 15 min , spun down at 5000 rpm for 5 min and washed once with 0 . 1 M potassium phosphate 1 . 2 M sorbitol buffer pH 7 . 5 . Stationary phase cells were first resuspended in 100–200 µl fresh pretreatment buffer ( 1 M Sorbitol , 25 mM EDTA , 50 mM DTT , pH 8 ) , and then pelleted in a microfuge at 2000 rpm for 3 min at room temperature . These cells were resuspended in 1 M sorbitol and pelleted as before . Cell walls were digested with 50 µg/ml Zymolyase 100T in 1 M Sorbitol buffer ( pH 5 . 8 ) for 10–45 min at 30°C . Cells were pelleted at 2000 rpm for 3 min , gently washed and resuspended in 15 µl potassium phosphate/sorbitol buffer , transferred to 0 . 1% polylysine-coated wells of an eight well microscope slide and allowed to settle for 20 min at room temperature . The slide was washed twice with phosphate-buffered saline ( PBS ) . Each well was incubated with 40 µl fresh permeabilization solution ( 0 . 1% Triton X-100 in a 0 . 1% sodium citrate solution ) for 2 min on ice , then rinsed with PBS buffer . 15 µl TUNEL reaction mixture ( In Situ Cell Death Detection Kit , AP , Roche ) was added to each well , slides were covered and incubated for 60 min at 37°C , then rinsed twice with PBS . Cells were observed under the microscope with an FITC filter ( excitation at 460–500 nm ) . 100–200 cells per sample were evaluated . For flow cytometry , cells were fixed in 70% ethanol for two hours or overnight , washed once with water , then resuspended in . 5 ml 50 mM Tris-HCl ( pH 8 . 0 ) containing 0 . 2 mg/ml RNAse A and incubated at 37°C for four hours . These cells were spun down , resuspended in . 5 ml 50 mM Tris-HCl ( pH 7 . 5 ) containing 2 mg/ml Proteinase K , and incubated at 50°C for one hour . They were then spun down again and resuspended in . 5 ml 50 mM Tris-HCl ( pH 7 . 5 ) and stored at 4°C . Before analysis , they were sonicated , pelleted , and resuspended in . 5 ml I . 0 µM Sytox Green ( Invitrogen ) . Percent of cells in G1 , S or G2/M phase of the cell cycle were quantified with FlowJo V9 . For ROS assays , approximately 1×106 cells were pelleted , gently washed with PBS , then resuspended in 1 mL PBS . 2 . 5 µL of a 10 mM carboxy-H2DCFDA ( Invitrogen ) stock solution was added and the cells were incubated for 30 minutes at 37°C . Cells were washed twice with PBS , resuspended in 1 mL 50 mM Tris-HCl pH 7 . 5 . Cultures were then sonicated and 30 , 000 cells per sample were collected on a Fluorescence Activated Cell Sorter FACScan cytometer ( BD Biosciences , San Jose , CA ) and analyzed using Cell Quest software . FACS parameters were set at excitation and emission settings of 495 nm and 529 nm ( filter FL-1 ) , respectively . Average from two experiments is reported . To generate enough cells for RNA measurements during growth from log phase to stationary phase , 5 OD600 of cells were collected every 10 minutes , washed with RNA buffer ( 50 mM Tris•HCl pH 7 . 4 , 100 mM NaCl , 10 mM EDTA ) and frozen for later RNA purification . The levels of CLN3 and ACT1 mRNA were monitored by an S1 nuclease protection assay as previously described [61] . CLN3 and ACT1 transcript levels were measured in each sample of wild type and 5XCLN3 cells . The ACT1 , though not invariant , was not affected by excess CLN3 so it could be used to normalize the RNA levels between the two strains . Next-Generation RNA sequencing was carried out with RNA prepared as above from log phase cells , purified Q cells , and cells grown in YEPD to log phase ( 8 hours ) the DS ( 14 hours ) , then 18 , 24 and 48 hours . mRNA expression levels following polyA selection were assayed using the HiSeq 2000 next generation sequencing system from Illumina [16] , with RNA libraries prepared according to the manufacturer's instructions . FASTQ sequence output files were generated , demultiplexed by the Illumina CASAVA software package and filtered to remove sequences with low read quality . Nucleotide fragments were paired-end sequenced . The W303 reference genome in FASTA format and gene annotations in GFF were obtained from the Wellcome Trust Sanger Institute's SGRP group . Sequences from each read were mapped to the Saccharomyces cerevisiae W303 reference genome using the Tophat application , a fast splice junction mapper for RNA-Seq reads [75] . Representation of RNA from annotated genes were assessed using HTSeq , a Python package developed by Simon Anders at EMBL Heidelberg , with quantitative expression calculated proportional to the number of reads per length of the modeled exon ( MRPKBME ) . Finally , differential gene representation between treatments were assessed using the R/Bioconductor package DESeq [76] . These data for differentially expressed genes are provided as Supplementary Table S3 . The demultiplexed FASTQ files have been submitted to the National Center for Biotechnology Information Sequence Read Archive and are available there as accession SRA098245 . Cells carrying Xbp1 tagged with a Tandem Affinity Purification ( TAP ) tag [77] or a non-tagged Xbp1 were collected from log phase cultures and cultures that had been growing for 24 hours into stationary phase . Proteins were cross linked to DNA as described [78] and IgG agarose beads ( Sigma A2909 ) were used to pull down in vivo binding sites . PCR primers used to amplify potential targets as well as an unregulated DNA ( IRV ) are provided as Supplementary Table S4 . | Complex organisms depend on populations of non-dividing quiescent cells for their controlled growth , development and tissue renewal . These quiescent cells are maintained in a resting state , and divide only when stimulated to do so . Unscheduled exit or failure to enter this quiescent state results in uncontrolled proliferation and cancer . Yeast cells also enter a stable , protected and reversible quiescent state . As with higher cells , they exit the cell cycle from G1 , reduce growth , conserve and recycle cellular contents . These similarities , and the fact that the mechanisms that start and stop the cell cycle are fundamentally conserved lead us to think that understanding how yeast enter , maintain and reverse quiescence could give important leads into the same processes in complex organisms . We show that yeast cells maintain G1 arrest by expressing a transcription factor that represses conserved activators ( cyclins ) and hundreds of other genes that are important for cell division and cell growth . Failure to repress some or all of these targets leads to extra cell divisions , prevents reversible arrest and shortens life span . Many Xbp1 targets are conserved cell cycle regulators and may also be actively repressed in the quiescent cells of more complex organisms . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2013 | Xbp1 Directs Global Repression of Budding Yeast Transcription during the Transition to Quiescence and Is Important for the Longevity and Reversibility of the Quiescent State |
Lariat RNAs formed as by-products of splicing are quickly degraded by the RNA debranching enzyme 1 ( DBR1 ) , leading to their turnover . Null dbr1 mutants in both animals and plants are embryo lethal , but the mechanism underlying the lethality remains unclear . Here we characterized a weak mutant allele of DBR1 in Arabidopsis , dbr1-2 , and showed that a global increase in lariat RNAs was unexpectedly accompanied by a genome-wide reduction in miRNA accumulation . The dbr1-2 mutation had no effects on expression of miRNA biogenesis genes or primary miRNAs ( pri-miRNAs ) , but the association of pri-miRNAs with the DCL1/HYL1 dicing complex was impaired . Lariat RNAs were associated with the DCL1/HYL1 dicing complex in vivo and competitively inhibited the binding of HYL1 with pri-miRNA . Consistent with the impacts of lariat RNAs on miRNA biogenesis , over-expression of lariat RNAs reduced miRNA accumulation . Lariat RNAs localized in nuclear bodies , and partially co-localize with HYL1 , and both DCL1 and HYL1 were mis-localized in dbr1-2 . Together with our findings that nearly four hundred lariat RNAs exist in wild type plants and that these lariat RNAs also associate with the DCL1/HYL1 dicing complex in vivo , we thus propose that lariat RNAs , as decoys , inhibit miRNA processing , suggesting a hitherto unknown layer of regulation in miRNA biogenesis .
In higher eukaryotes , splicing of mRNA precursors ( pre-mRNA ) , a critical step for gene expression , comprises two catalytic steps [1] . In the first step , the 5’ splice site is cleaved and concurrently the 5’ end of the intron is joined to the branch nucleotide by forming a phosphodiester bond . This results in the production of a 5’ exon and a 3’exon-containing lariat precursor . In the second step , the lariat precursor is cleaved at the 3’ splice site and the two exons are ligated to produce the mRNA . The excised intronic lariat RNA is linearized for degradation by an RNA debranching enzyme ( DBR1 ) [2] . DBR1 was originally identified from budding yeast ( Saccharomyces cerevisiae ) in a study aimed at identifying host cellular factors involved in transposition of the Ty1 retrotransposon [3] . The dbr1Δ mutant of S . cerevisiae has reduced Ty1 transposition frequency and also shows increased accumulation of lariat RNAs . DBR1 is not essential for cell viability in S . cerevisiae . However , the dbr1Δ mutant in fission yeast ( Saccharomyces pombe ) exhibits severe growth defects [2] . Moreover , both the dbr1 mutant in Arabidopsis [4] and mice [5] are embryo lethal . DBR1 is a single copy gene in eukaryotes [6] , and homologues of DBR1 isolated from plants or animals can complement the S . pombe dbr1 mutant [7] , indicating that DBR1 function is conserved . MicroRNAs ( miRNAs ) are a class of 21-24nt small RNAs generated from endogenous stem-loop transcripts . miRNA biogenesis begins with the processing of primary miRNAs ( pri-miRNAs ) , which contain a hairpin structure that is cleaved twice by the dicing complex , which is mainly composed of the nuclear RNase III enzyme Dicer-Like 1 ( DCL1 ) [8] and an RNA binding protein HYL1 [9] , yielding mature miRNAs . DCL1 and HYL1 , together with pri-miRNAs , are co-localized in nuclear dicing bodies [10 , 11] , and HYL1 facilitates the binding of DCL1 to enhance the efficiency and accuracy of miRNA processing [12 , 13] . Previous findings showed that DBR1 is required for mirtron miRNA biogenesis in animals [14 , 15] , where it is independent of cleavage by the microprocessor . The existence of mirtron miRNAs in embryos might contribute the embryo lethality of the null dbr1 mutant in animals [14] . However , no mirtron miRNA has been functionally validated in plants [16] . In addition , earlier studies showed that DBR1 is required for intronic snoRNAs biogenesis in yeast [17 , 18] , but plant snoRNAs are originated from either an intronic or a non-intronic context [19 , 20] , indicating that the involvement of DBR1 in snoRNA biogenesis is not sufficient to explain the important role of DBR1 during embryo development . Here , we report that lariat RNAs inhibit global miRNA biogenesis in Arabidopsis , possibly explaining the detrimental effects of lariat over-accumulation . We provide evidence that the over-accumulation of lariat RNAs caused genome-wide reduction of miRNAs in Arabidopsis , and show that lariat RNAs associated with the DCL1/HYL1 dicing complex to compete with pri-miRNAs . Moreover , we demonstrated that hundreds of lariat RNAs exist in wild type plants , suggesting that these lariat RNAs might be biologically relevant . Given the observations of lariat RNAs in embryonic stem cells [21] and evidence for lariat RNAs acting as decoys of RNA binding proteins [22] , we thus propose that lariat RNAs function as decoys of the dicing complex to maintain a proper processing of pri-miRNAs .
In an ethyl methanesulfonate mutagenesis screen aimed at isolating mutants compromised in miRNA biogenesis using dcl1-14 as a parental line [23] , we isolated a mutant with pleiotropic developmental phenotypes , which included curly and serrated leaves , increased branching , short stature , and reduced fertility ( Fig 1A ) . Whole genome sequencing identified a G-to-A mutation in the coding region of DBR1 , which encodes an RNA debranching enzyme ( DBR1 ) ( S1A and S1B Fig ) . This mutation caused the conversion of a glycine , located within the LRL motif required for substrate binding ( S1A and S1B Fig ) [24] , a region highly conserved in DBR1 in S . pombe , animals , and plants , to an arginine ( S1A and S1B Fig ) . When DBR1 genomic fragments driven by the native promoter and fused to GFP , RFP , or Flag , respectively , were introduced into this mutant , the phenotypes were completely rescued ( Fig 1A ) . We identified a T-DNA insertion allele in DBR1 only in a heterozygous state and crossed it to the homozygous mutant isolated from our genetic screen . Approximately half ( 83/178 ) of the F1 plants exhibited mutant phenotypes ( S1C Fig ) . Therefore , the mutant is an allele of DBR1 . Both a previously isolated loss-of-function allele of DBR1 [4] ( here renamed dbr1-1 ) and the T-DNA insertion line ( here named dbr1-3 ) are embryo lethal . The abundance of DBR1 was unaffected in our weak mutant allele ( here named dbr1-2 ) ( S1D Fig ) . Considering that the dbr1-2 mutant resembles mutants that are defective in miRNA accumulation , we examined miRNA accumulation in dbr1-2 by northern blot analysis . Compared to those in Col-0 , the levels of tested miRNAs were reduced in dbr1-2 ( Fig 1B ) . pDBR1::DBR1-RFP ( Compl ) fully restored the levels of these miRNAs ( Fig 1B ) . To determine whether DBR1 is required for global miRNA accumulation , we compared mature miRNA levels in dbr1-2 and Col-0 by small RNA deep sequencing analysis . Results from two replicates confirmed a genome-wide reduction of miRNA levels in dbr1-2 ( Fig 1C and S1 Table ) . Compared to many canonical miRNAs reduced in hyl1 [25 , 26] , our northern blot assay ( Fig 1B ) and deep sequencing analysis ( S1 Table ) showed that most HYL1-dependent miRNAs from 32 canonical miRNA families , such as miR156 , miR159 , and miR160 , were also obviously reduced in dbr1-2 ( S1 Table ) , indicating that DBR1 and HYL1 have overlapping functions in miRNA biogenesis . Due to the potential feedback regulation between lariat RNA debranching and pre-mRNA splicing , we wondered whether the effects of DBR1 on miRNA biogenesis was dependent on the possible function of DBR1 on splicing . Moreover , recent studies showed that many MIR genes contain introns and those MIR genes with introns usually stimulate biogenesis of miRNAs originating from such intron-containing precursors [27 , 28] . By analyzing the genomic structure of 54 MIR genes with reduced miRNAs in dbr1-2 , we showed that only 8 MIR genes contain introns ( S1 Table ) , and that among more than 15 intronic miRNAs in Arabidopsis , only 4 intronic miRNAs were reduced in dbr1-2 ( S1 Table ) , suggesting that the involvement of DBR1 in miRNA biogenesis might be unrelated to the possible function of DBR1 in pre-mRNA splicing , and thus that the effects of DBR1 on miRNA biogenesis are independent of the properties of MIR genes . We thus concluded that DBR1 is required for miRNA accumulation in plants . To exclude the possibility that the reduced miRNA levels observed in dbr1-2 were due to altered expression of the miRNA pathway components , we performed quantitative RT-PCR ( qRT-PCR ) to determine transcript levels of genes that have been shown to act in miRNA biogenesis [8 , 9 , 29 , 30] . As shown in S2A Fig , the expression levels of these genes were comparable to those in Col-0; Western blot analysis further confirmed that the protein levels of those key components in the miRNA pathway in dbr1-2 were comparable to those in Col-0 ( S2B Fig ) . These results indicate that the dbr1-2 mutation had no effects on the expression of the miRNA pathway components . The reduced miRNA accumulation in dbr1-2 could be caused by reduced pri-miRNA levels . To test whether it was the case , we examined the levels of pri-miRNAs in Col-0 and dbr1-2 plants . qRT-PCR analyses showed that the levels of the nine pri-miRNAs tested were increased by 2- to 4-fold in dbr1-2 ( Fig 2A ) , a fold-change similar to that found in hyl1 ( Fig 2A ) . The observation of increased levels of pri-miRNA prompted us to examine whether DBR1 plays a role in the transcription of miRNA genes ( MIR ) . Pol II is responsible for MIR transcription in animals and plants [31–33] . Therefore , we first examined Pol II occupancy at promoters of MIR genes by chromatin immunoprecipitation ( ChIP ) , using an antibody against the second largest subunit of Pol II ( NRPB2 ) . Compared to the no antibody control ( S2C Fig ) , Pol II occupancy at MIR was comparable to that in dbr1-2 ( S2D Fig ) . To further exclude the possibility that the over-accumulation of pri-miRNAs in dbr1-2 was due to increased transcription of MIR , we examined the effect of dbr1-2 on the expression of a GUS reporter gene driven by either the MIR172a promoter ( MIR172a::GUS ) or the MIR390b promoter ( MIR390b::GUS ) . The transgenic lines MIR172a::GUS and MIR390b::GUS were separately crossed with dbr1-2 and progeny plants homozygous for both transgene and dbr1-2 were analyzed . Both GUS activity ( S2E Fig ) and the levels of GUS transcripts ( S2F Fig ) in dbr1-2 were comparable to those in Col-0 , while the levels of pri-miR172a and pri-miR390b were increased in the dbr1-2 lines ( S2F Fig ) . Taken together , these results indicate that DBR1 is not required for MIR transcription . That pri-miRNAs over-accumulated and the levels of mature miRNAs were reduced in dbr1-2 suggested that miRNA processing might be impaired . We then investigated whether the association of pri-miRNAs with the dicing complex was compromised in dbr1-2 using RNA immunoprecipitation ( RIP ) experiments . We performed RIP assays , using DCL1 antibody , with Col-0 and dbr1-2 inflorescences , and using HYL1 antibody with Col-0 , dbr1-2 , and hyl1-2 seedlings . Pri-miRNAs were detected by qRT-PCR from immunoprecipitated RNAs . The amounts of the pri-miRNAs bound by both DCL1 ( Fig 2B ) and HYL1 ( Fig 2C ) were significantly reduced in the dbr1-2 background . To determine whether DBR1 is required for genome-wide pri-miRNA binding with the dicing complex , we compared the levels of DCL1- or HYL1-immunoprecipitated miRNA precursors ( pri-miRNA ) from Col-0 and dbr1-2 by RNA sequencing analysis . We found that most reads were predominantly mapped to the whole region of MIR genes . However because the boundaries of most pri-miRNAs are not clear , it was not feasible to calculate the abundance of pri-miRNAs , and thus we only counted reads uniquely mapped to pre-miRNA regions . We found that pre-miRNAs were overall enriched in both DCL1- and HYL1-immunoprecipitated samples in Col-0 ( Fig 2D and S2 Table ) . Furthermore , enrichment of most pre-miRNAs with detectable RIP-seq abundances ( more than 5 RPKM in either the dbr1-2 or Col-0 libraries ) , in both DCL1- and HYL1-immunoprecipitated samples , were reduced in dbr1-2 ( Fig 2D and S2 Table ) . These results indicate that the association of pri-miRNAs with the dicing complex was disrupted in dbr1-2 , which leads to reduced miRNA processing . Because DBR1 strongly binds to lariat RNAs [34] , we hypothesized that DBR1 might directly act in the binding of pri-miRNAs with the dicing complex . To test this hypothesis , we performed a RIP assay using DBR1 antibodies , but found that DBR1 was not associated with pri-miRNA in vivo ( S3A Fig ) . However , DBR1 is obviously associated with lariat RNAs ( S3A Fig ) , which is consistent with previous studies [34] . In addition , a Co-IP assay showed no association between DBR1 and the miRNA biogenesis machinery ( S3B Fig ) . These results therefore make it unlikely that DBR1 itself is a component of the dicing complex during miRNA processing . Loss-of-function of DBR1 causes global accumulation of lariat RNAs in yeast [2] . To investigate the relationship between the accumulation of lariat RNAs and miRNA biogenesis , we tested genome-wide how many lariat RNAs accumulate in dbr1-2 . As RNase R specifically degrades linear RNAs , while keeping the loop portion of a lariat RNA intact [35] , our strategy was to globally compare total RNAs in dbr1-2 and Col-0 , with or without RNase R-treatments . Therefore , we performed RNA-seq after constructing libraries of ribosomal RNA ( rRNA ) -depleted RNAs , with or without RNase R-treatments ( S3C Fig ) . By selecting uniquely mapped intronic reads , 1560 intronic RNAs were identified as potential lariat RNAs in dbr1-2 ( Fig 3A and S3 Table ) . After RNase R treatment , most of them ( 1534 ) were still detectable ( Fig 3A and S3 Table ) , indicating that these lariat RNAs exist as stable circular forms . Unexpectedly , approximately 23% ( 360/1534 ) of these lariat RNAs also exhibited significant expression ( > = 5 RPKM ) in wild type plants ( S3 Table ) , suggesting that these lariat RNAs naturally escaped debranching , a phenomenon recently shown in human cells [21] . To validate lariat RNAs , we performed RT-PCR using sets of divergent primers ( Fig 3B ) . As shown in Fig 3C and 3D , most tested lariat RNAs obviously over-accumulated in dbr1-2 . Some lariat RNAs , such as lariat24a , lariat28 , lariat35 , and lariat41 , were easily detected in Col-0 ( Fig 3C ) , further confirming that these lariat RNAs naturally escaped the debranching activity of DBR1 . Further qRT-PCR analyses of RNase R-untreated samples confirmed the results of RT-PCR ( Fig 3D ) . To test whether the lariat RNAs were circular , we performed RT-PCR using RNase R-treated RNAs as templates , and showed that all tested lariat RNAs were circular ( Fig 3C ) . To determine whether RNase R treatments were complete , we performed qRT-PCR analyses using both RNase R-untreated and RNase R-treated samples , and showed that lariat RNAs were stably detectable in both samples , while the corresponding linear mRNAs were almost eliminated by RNase R treatments ( Fig 3E ) . Sanger sequencing further confirmed that lariat RNAs are circular ( S3D Fig ) . Taken together , these results suggest that both lariat RNAs over-accumulated in dbr1-2 , and lariat RNAs naturally present in wild type plants , might play certain roles in biological processes . To investigate whether lariat RNAs accumulated in dbr1-2 were correlated with reduced binding of the dicing complex to pri-miRNAs , we first investigated whether these lariat RNAs were associated with the DCL1/HYL1 complex in vivo . Lariat RNAs were present in both DCL1- and HYL1-immunoprecipitates in dbr1-2 ( Fig 4A and 4B ) . Notably , compared to that of negative control , UBQ5 , and other lariat RNAs hardly detected in Col-0 ( lariat7 , lariat31 , lariat36 ) , several tested lariat RNAs naturally present in Col-0 , such as lariat24a , lariat28 , lariat32 , and lariat40 , were also bound by both DCL1 and HYL1 ( Fig 4A and 4B ) , indicating that lariat RNAs that naturally escaped debranching could be bound by the DCL1/HYL1 dicing complex . Due to the observations that lariat RNAs are circular and that most circular RNAs accumulated in dbr1-2 could be lariat-derived , we then investigated whether the association of the DCL1/HYL1 complex with lariat RNAs affected binding of the DCL1/HYL1 complex to pri-miRNAs . We performed RNA electrophoretic mobility shift assays ( R-EMSA ) with Col-0 and dbr1-2 , to compare the binding capacity of recombinant HYL1 ( S4A Fig ) with biotin-labeled pri-miR167b in the presence or absence of lariat RNAs . Consistent with a previous study [36] , HYL1 specifically bound pri-miR167b as indicated by the arrow ( S4B Fig ) , while other unrelated recombinant proteins MBP and GST ( S4A Fig ) did not bind pri-miR167b ( S4B Fig ) . Notably , DBR1 recombinant protein showed no binding with pri-miR167b ( S4B Fig ) , further supporting that DBR1 itself is not directly required for the binding of pri-miRNA with the dicing complex . To investigate whether lariat RNAs regulate HYL1 binding with pri-miRNA , we performed competition assays . Notably , due to the limitations of synthesizing lariat RNA in vitro in our conditions , and because lariat RNAs should be the most abundant population of circular RNAs in dbr1 mutants , we used RNase R-digested RNAs ( R ( + ) -RNA ) to perform the competition assays . Increasing amounts ( 0 . 3 to 1 . 2 μg ) of cold R ( + ) -RNA were added to the binding reaction mixture containing HYL1 and labeled pri-miR167b . As shown in Fig 4C and 4D , the signal corresponding to the HYL1-pri-miR167b complex was decreased proportionally to the amount of cold circular RNA added from dbr1-2 . Unexpectedly , the addition of cold circular RNA from Col-0 in the binding reaction also produced moderate competition effects ( Fig 4C and 4D ) , while linear single-stranded RNA of GAPDH had minor competition effects on HYL1 binding ( S4C Fig ) . Considering that the function of DBR1 is highly conserved in eukaryotes , we speculated that lariat RNAs from other species might play similar roles in binding the dicing complex . To test this idea , we examined the effects of circular RNAs from a fission yeast dbr1Δ strain on the binding capacity of HYL1 with pri-miR167b . Compared to the binding in the control ( S4D Fig ) , circular RNAs from the yeast dbr1 mutant greatly attenuated the binding of HYL1 ( S4D and S4E Fig ) . Taken together , these results suggest that circular RNAs , most likely lariat RNAs , could play a regulatory role in binding of the dicing complex to pri-miRNAs . Since it seems that lariat RNAs compete for HYL1/DCL1 binding to pri-miRNAs , thus reducing their processing and then the accumulation of miRNAs , we hypothesized that any method that changed lariat RNAs levels would have an impact on miRNA accumulation . To test this , we generated over-expression ( OE ) lines of lariat RNA and assessed miRNA accumulation . Although how some lariat RNAs escape debranching in wild type plants remains unknown , we hypothesized that over-expressing the corresponding genomic DNA should lead to increased levels of intron-derived lariat RNAs . Here , we selected lariat41 , which is detectable in wild type plants ( Fig 3C and S3 Table ) , to investigate whether over-expression of lariat RNA would affect miRNA accumulation . We generated more than 10 independent transgenic plants over-expressing the genomic DNA of At5g37720 ( lariat41-OE ) or the CDS of At5g37720 ( local41-OE ) ( Fig 5A ) . Only lariat41-OE transgenic plants exhibited pleiotropic phenotypes ( Fig 5B ) , which were reminiscent of mutants deficient in miRNA accumulation . Both RT-PCR and western blot analysis showed comparable mRNA and protein levels of At5g37720 in local41-OE and lariat41-OE plants ( Fig 5C ) . As expected , lariat41 was significantly increased in lariat41-OE lines but not in local41-OE lines ( Fig 5C ) , while lariat28 , an unrelated lariat RNA , was equal among the three genotypes ( Fig 5D ) . Importantly , we showed that levels of miR159 and miR167 were reduced in lariat41-OE but not in local41-OE plants ( Fig 5E ) , indicating that increased lariat41 levels were anti-correlated with accumulation of miRNAs . To further support this anti-correlation , we transiently expressed lariat42 in tobacco leaves ( S5 Fig ) with a split YFP separated by lariat42-originated intron sequences ( S5A Fig ) . The YFP signal was detected , indicating that the lariat42-originated intron was properly spliced ( S5B Fig ) . RT-PCR analysis showed that lariat42 accumulated in the infiltrated leaves but not in control leaves ( S5C Fig ) . Northern blot analysis showed that miR167 was reduced in leaves over-expressing lariat42 ( lariat42-OE ) . Taken together , these results indicate that lariat RNA accumulation is negatively correlated with miRNA levels . Pre-mRNA splicing occurs in the nucleus and lariat RNAs are byproducts of splicing , so we reasoned that DBR1 might localize in the nucleus . Transient expression of DBR1-RFP in tobacco as well as transgenic Arabidopsis plants expressing DBR1-GFP showed that DBR1 was distributed in both the nucleus and cytoplasm ( Fig 6A ) , which is consistent with the finding that DBR1 is a nucleocytoplasmic shuttling protein in humans [37] . The DBR1-2 mutant protein did not affect the distribution of DBR1 ( S6A Fig ) . Because processing of pri-miRNAs occurs in the nucleus , we hypothesized that nuclear lariat RNAs might be co-localized with components of the DCL1/HYL1 complex . To test this idea , we modified the MS2 system [38] to visualize endogenous lariat RNAs in plants ( Fig 6B and S6B Fig ) . Six copies of the binding site for the RNA-binding MS2 coat proteins ( MS2-CP ) were inserted into the lariat24a- or lariat41-generating intronic regions of At5g63530 ( Fig 6B ) and At5g37720 ( S6B Fig ) , respectively . Expression of MS2-CP fused to GFP carrying an NLS signal ( MS2-CP-GFP ) enables the visualization of lariat24a and lariat41 tagged with MS2-binding sites . We co-transformed tobacco with different combinations of plasmids harboring MS2-CP-GFP , HYL1-RFP or lariat24a-MS2 and lariat41-MS2 under the control of the 35S promoter . To differentiate the subcellular localization of lariat RNA and the mRNA of the corresponding gene , we co-transformed a plasmid harboring the full length genomic DNA fused to 6X MS2 at the end of the last exon of the lariat24a corresponding gene , under control of the 35S promoter . As a positive control for dicing bodies , we co-transformed a plasmid harboring pri-miR163-MS2 under control of the 35S promoter . We analyzed the subcellular localization of MS2-CP-GFP by fluorescence microscopy . MS2-CP-GFP uniformly accumulated in one big dot in the nucleus ( Fig 6C ) , while HYL1-RFP accumulated in small dots in addition to the big dot in the nucleus in some nuclei ( Fig 6C ) . Notably , in many nuclei HYL1-RFP was also distributed more evenly without any dots ( S6C Fig ) , a localization consistent with a previous study [39] . As expected , when the plasmid of pri-miR163-MS2 was introduced , we observed small bodies surrounding the big dot in some nuclei ( Fig 6C ) , and these nuclear bodies were partially co-localized with HYL1-nuclear bodies ( Fig 6C ) , consistent with previous localization studies [10 , 11] . Intriguingly , lariat24a and lariat41 also accumulated in small nuclear bodies surrounding the big dot in some nuclei ( Fig 6C and S6D and S6E Fig ) , and similar to pri-miR163 , both lariat24a and lariat41 partially co-localized with HYL1-nuclear bodies ( Fig 6C and S6D and S6E Fig ) . As a negative control , we showed that the mRNA of the lariat24a corresponding gene was uniformly distributed in all examined nuclei ( S6C Fig ) . Collectively , our data indicate that lariat RNAs are partially recruited into nuclear bodies . Several mutants deficient in miRNA biogenesis exhibit abnormal patterns of dicing bodies [40–42] , which might reflect a deficiency in the function of the dicing complex . To examine whether DBR1 affects localization of the dicing complex , we examined the effects of dbr1-2 on the sub-nuclear localization of DCL1 and HYL1 . Progeny homozygous for both transgenes ( DCL1-YFP and YFP-HYL1 ) and dbr1-2 were obtained . In Col-0 , more than 85% of 1168 root cells harbored three or fewer dicing bodies in the nucleus and less than 10% of root cells harbored more than three dicing bodies ( Fig 7A ) . In contrast , dbr1-2 had significantly more DCL1-containing nuclear bodies ( Fig 7A ) ; more than 40% of 1027 root cells contained four or more dicing bodies ( Fig 7A ) . A similar observation was made for HYL1-containing dicing bodies ( Fig 7B ) . Taken together , these results suggest that DBR1 is required for the proper sub-nuclear localization of the dicing complex . To further dissect the genetic relationship between lariat RNA debranching and pri-miRNA processing , we crossed dbr1-2 to hyl1-2 . The double mutant was morphologically similar to hyl1-2 ( Fig 7C ) , and expression levels of pri-miRNAs ( Fig 7D ) in hyl1-2 dbr1-2 were comparable to that in hyl1-2 , suggesting that DBR1 and HYL1 act in miRNA biogenesis in the same genetic pathway . Taken together , these observations indicate the debranching process of lariat RNAs is tightly coupled with pri-miRNA processing , and thus that non-debranched lariat RNAs are conveniently accessible for the dicing complex to balance the binding of pri-miRNAs .
Although a few plant miRNAs originate from intronic regions , it is becoming increasingly apparent that miRNA biogenesis has to be coordinately regulated by pre-mRNA splicing , since many mutants of genes involved in splicing exhibit defects in miRNA biogenesis [29 , 43–45] . However , the mechanism by which pre-mRNA splicing affects miRNA biogenesis remains largely unexplored . Here we demonstrated that lariat RNAs , as so-called by-products of pre-mRNA splicing , play a negative role in regulation of miRNA homeostasis . Lariat RNAs act as a molecular sponge to sequester the dicing complex , and thus maintain a steady level of mature miRNAs . Therefore , our data provide new insights into how by-products of pre-mRNA splicing , other than the previously thought spliceosome itself , play a role in miRNA biogenesis . Our results suggest that the debranching process of lariat RNAs contributes to the proper processing of pri-miRNA by balancing the binding of pri-miRNA to the DCL1/HYL1 complex . As we proposed , in wild type plants ( Fig 8 , upper panel ) , DBR1 is able to degrade most lariat RNAs , but some lariat RNAs naturally escape debranching , as also shown in human embryonic stem cells [21] . In Arabidopsis , we showed that these non-debranched lariat-derived circular RNAs act as a molecular sponge of the dicing complex , in which lariats play a potential competitive role to avoid excessive pri-miRNA processing by attracting the DCL1/HYL1 complex . In contrast , in dbr1-2 ( Fig 8 , lower panel ) , the over-accumulation of lariat RNAs disrupts the binding of the DCL1/HYL1 complex to pri-miRNA , and thus causes less miRNA production . In conclusion , our results uncover a new layer of miRNA biogenesis regulation by other RNA molecules , and establish the link between the splicing process and the generation of small RNAs that had not been conceived previously . It is well known that pri-miRNA binding to the dicing complex is an important step in miRNA biogenesis , but how the dicing complex differentiates pri-miRNAs from other structurally related RNAs is unclear . A previous study in plants showed that SINE RNAs , potentially with loop structures , compete with pri-miRNAs for HYL1 binding [46] , and a study in human cells showed that the microprocessor recognizes the basal UG and apical UGU motifs of pri-miRNAs [47] . Interestingly , lariat RNAs contain the GU/UG motif from the 5’ splicing site next to the branch point , indicating that the GU/UG motif might be wrongly recognized by the DCL1/HYL1 complex in plants . In addition , recent studies in animals showed that DGCR8 binds other RNAs besides pri-miRNAs [48] , and that Dicer globally binds to many loop RNAs [49] , which thus sequesters Dicer to reduce miRNA accumulation [49] , suggesting that binding of the miRNA biogenesis machinery could be regulated . Indeed , together with the findings that lariat RNA acts as sources for both mirtron miRNA biogenesis in animals [14 , 15] and siRNA biogenesis in yeast [50] , our finding that lariat RNA inhibits global miRNA processing in plants implicates a widespread involvement of lariat RNA in small RNA biogenesis . In species such as yeast , which lack miRNAs , lariat RNAs are further processed into siRNA for gene silencing [50] . In contrast , in eukaryotes such as Drosophila and Arabidopsis , which are enriched in miRNAs , lariat RNA might have switched its role from siRNA biogenesis to miRNA biogenesis . Elucidation of additional genetic modifiers of lariat RNA binding and processing should provide more insights into how lariat RNA acts in small RNA biogenesis .
Arabidopsis thaliana Columbia ( Col-0 ) is wild type . Seeds of dbr1-3 ( SALK_047099 ) , hyl1-2 ( SALK_064863 ) , and MIR390b::GUS ( CS66477 ) were obtained from the Arabidopsis Biological Resources Center ( ABRC , www . arabidopsis . org ) . 35S::DCL1-YFP seeds were generated in our laboratory . pHYL1::YFP-HYL1 seeds were obtained from Yuda Fang’s lab . Wild-type and dbr1 fission yeast strains were purchased from Bioneer ( http://pombe . bioneer . co . kr ) . Anti-DCL1 ( Agrisera , #AS122102 ) , anti-HYL1 ( Agrisera , #AS06136 ) , anti-SE ( Agrisera , #AS09532 ) , anti-Hsc70 ( Stressgen , SPA-018 ) , anti-GFP ( Covance , #MMS-118R ) , and anti-FLAG ( Sigma , #F7425 ) antibodies were purchased . Anti-DBR1 , anti-NRPB2 , and anti-AGO1 antibodies were generated by our laboratory . For construction of the DBR1-GFP , DBR1-RFP , DBR1-Flag , 35S::DBR1-RFP , and 35S::DBR1-YFP plasmids containing the endogenous promoter , DBR1 was amplified from Col-0 genomic DNA with the primer pair DBR1F1/R1 , cloned into pENTR-D/TOPO , and then transferred into the plant expression destination vector pMDC107 to construct DBR1-GFP , into pMDC163 ( GUS was replaced by mRFP ) to construct DBR1-RFP , into pEarleyGate302 to construct DBR1-Flag , into pEarleyGate101 ( HA-GFP was replaced by mRFP ) to construct 35S::DBR1-RFP , and into pB7YWG2 to construct 35S::DBR1-YFP . To construct 35S::DBR1-Flag , the DBR1 CDS was obtained using the primer pair DBR1F2/R2 and cloned into the plant expression vector pCambia1306 . To construct 35S::DBR1-2-YFP , the CDS sequences of DBR1 was amplified from dbr1-2 with primer pairs DBR1F2/R2 and cloned into pCambia2302 . To construct DBR1-GST , the CDS sequences of DBR1 was amplified with primer pairs DBR1F3/R2 and cloned into pGEX2TK . To construct DCL1-YFP , HYL1-RFP , and HYL1-Flag , the CDS sequences of DCL1 and HYL1 , respectively , were obtained using the primer pairs DCL1F1/R1 and HYL1F1/R1 , cloned into pENTR-D/TOPO , and then transferred into the plant expression destination vectors pEarleyGate101 , pEarleyGate101 ( YFP-HA was replaced by mRFP ) , and pEarleyGate202 , respectively . To construct SE-Flag , the CDS sequence of SE was obtained using the primer pair SEF1/R1 , and cloned into the plant expression vector pCambia1306 . To construct lariat41-OE , the full length genomic region of At5g37720 was amplified using primer pair lariat41F2/R2 and ligated to pENTR1A , and transferred into pB7YWG2 . To construct local41-OE , the full length coding region of At5g37720 was amplified from Col-0 cDNA using primer pair lariat41F2/R2 and ligated to pENTR1A , and transferred into pB7YWG2 . To construct lariat42-OE , the intron sequences of At5g43100 were amplified using primer pair lariat42F2/R2 and inserted between nYFP and cYFP , and transferred into pB7WG2 . To transfer lariat24a and lariat41 into the MS2 system , we first constructed lariat24a-pENTR-D/TOPO and lariat41-pENTR1A by introducing full length genomic fragments of At5g63530 and At5g37720 into pENTR-D/TOPO and pENTR1A using the primer pairs gL24F/R and gL41F/R , respectively , and then the 6XMS2 loops were amplified with primers 6XMS2Loops_F1/R1 and 6XMS2Loops_F2/R2 from 35S::GW-6XMS2 , then ligated into lariat24a-pENTR-D/TOPO by XmnI and lariat41-pENTR1A by SacI , respectively , then transferred into the plant expression vector pB7WG2 . To construct the mRNA control of At5g63530 into the MS2 system ( local24-MS2 ) , the plasmid of lariat24a-pENTR-D/TOPO were introduced into 35S::GW-6XMS2 by LR reaction . To construct pri-miR163 into the MS2 system , we first constructed pri-miR163-pENTR-D/TOPO by introducing full length genomic fragments of MIR163 into pENTR-D/TOPO with the primer pair miR163-MS2-F/R , and then transferred into the plant expression vector 35S::GW-6XMS2 . Primer sequences are listed in S4 Table . Illumina sequencing of small RNA libraries from inflorescences was performed by Genergy ( Shanghai , China ) , and small RNA libraries were constructed according to Illumina's instructions using a TruSeq Small RNA Library Preparation kit . The small RNA sequencing profiles were analyzed as described [51] . Briefly , the sequencing reads were filtered to remove reads with more than 5 nucleotides with sequencing scores smaller than 20 . Adaptor sequences were removed to extract small RNAs . Redundant sequences were eliminated , and unique small RNAs were counted . Unique small RNAs were mapped back to the A . thaliana reference genome using SOAP2 [52]; mature miRNAs and pre-miRNAs ( downloaded from miRBase , http://www . mirbase . org/ , v19 ) were found using BLASTN . Then , custom programs were used to calculate the normalized abundance ( RPTM , Reads Per Ten Million sequencing tags ) of mature miRNAs . miRNAs with at least 100 RPTM in either Col-0 or dbr1-2 were used to calculate log2 fold changes of their RPTM values . Deep sequencing datasets were deposited in the SRA database of National Center for Biotechnology Information with accession No . SRP062035 . Total RNA was extracted using Trizol reagent from inflorescences . 5 μg small RNAs enriched by PEG8000 were separated by denaturing 15% ( w/v ) PAGE and transferred to a nylon membrane . 5’_biotin_labeled-oligo nucleotide sequences complementary to miRNA were synthesized as probes . Hybridization was performed using hybridization buffer ( Ambion ) , and signals were detected using chemiluminescent nucleic acid detection module . U6 was used as a loading control . The probes are listed in S4 Table . R-EMSA was performed according to [36] with modifications . Biotin-labeled pri-miR167b was synthesized by in vitro transcription . Using an RNA EMSA Kit ( Thermo Scientific ) , electrophoresis mobility shift assay experiments were performed in a 20 μl reaction system containing binding buffer , 5% ( v/v ) glycerol , 2 μg tRNA , 2 nM of biotin-labeled pri-miR67b transcripts , and purified MBP-HYL1_D1D2 ( only two DsRBD domains ) . For the competition assay , total RNA treated by RNase R was added to the reaction at different concentrations . The reaction was incubated for 30 min , electrophoresed on a 6 . 5% ( w/v ) native PAGE gel , and transferred to a nylon membrane , then detected using a chemiluminescent nucleic acid detection module . Chromatin from inflorescences of Col-0 and dbr1-2 was immunoprecipitated with anti-DCL1 and anti-HYL1 antibodies . For the DBR1 RIP assay , chromatin from inflorescences of Col-0 was immunoprecipitated with anti-DBR1 antibodies . RNA recovered from the immunoprecipitates was used for cDNA synthesis with Oligo dT . The primer sets used for PCR are listed in the S4 Table . For RIP-seq analysis , recovered RNAs were used for library preparation with Illumina TruSeq Stranded Total RNA HT Sample Prep Kit ( P/N15031048 ) , and then subjected to deep sequencing with Illumina HiSeq 2000 at Genergy ( Shanghai , China ) . The RIP-seq libraries were aligned to the genome with Cufflinks 2 [53] . The "bedtools genomecov" command of bedtools [51] was used to calculate genome coverage of RIP-seq libraries . Then , a custom program was used to calculate the RPKMs ( Reads Per Kilo basepairs and per Million sequencing tags ) of pre-miRNAs in miRBase ( v21 ) , using the genome coverage of RIP-seq libraries . Deep sequencing datasets were deposited in the SRA database of National Center for Biotechnology Information with accession No . SRP063916 . ChIP was performed similar to RIP , the difference is that DNA not RNA is recovered . Pol II occupancy at miRNA loci was determined by ChIP using anti-RPB2 antibody and 2-week-old seedlings from Col-0 and dbr1-2 , respectively . Immunoprecipitated DNA was quantified by qPCR relative to total input DNA . The results shown were consistent in three biological replicates . The primer sets used for the PCR are listed in S4 Table . Three week-old seedlings from transgenic plants in Col-0 and dbr1-2 backgrounds was fixed in 90% acetone for 2–3 h and then stained for 12 h in 50 mM sodium phosphate buffer , pH 7 . 0 , containing 0 . 2% Triton X-100 , 5 mM potassium ferrocyanide , 5mM potassium ferricyanide , and 1 mM X-Gluc , then washed in 70% ethanol three times . Images were taken with a Leica DFC295 stereoscope . Total RNA isolated from Col-0 and dbr1-2 was first treated with a Ribo Zero kit ( Epicenter ) to obtain a ribosomal RNA-depleted RNA ( ribo- RNA ) . Then ribo- RNA was incubated with or without RNase R ( Epicentre ) and then subjected to phenol:chloroform purification . Purified RNAs were further used for library preparation with Illumina TruSeq Stranded Total RNA Sample Prep Kit , and then subjected to deep sequencing with Illumina HiSeq 2000 at Genergy ( Shanghai , China ) . Stranded RNA-seq reads were mapped to the Arabidopsis genome annotation ( TAIR 10 ) with Cufflinks 2 [53] . CuffDiff in Cufflinks 2 was used to find deregulated genes . Genes with at least 5 RPKM in either dbr1-2 or Col-0 and q-values smaller than 0 . 05 were designated deregulated genes . The "bedtools genomecov" command of bedtools [53] was used to calculate the genome coverage of RNA-seq libraries . Then , a custom program was used to calculate the RPKMs ( Reads Per Kilo basepairs and per Million sequencing tags ) of introns of annotated genes in TAIR10 , using the genome coverage of RNA-seq libraries . Introns that had at least 5 RPKM in dbr1-2 profiles and had multiple test corrected P-values of smaller than 0 . 05 , calculated with edgeR [54] , were designated as enriched introns . Deep sequencing datasets were deposited in the SRA database of National Center for Biotechnology Information with accession No . SRP062035 . Lariat RNAs across the branch site were detected by RT-PCR as described [35] . Total RNA with or without RNase R-treatment were used as templates . cDNA synthesis was carried out using SuperScript III ( Invitrogen ) with random hexamers . The reaction mixtures were incubated at 30°C for 10 min , at 42°C for 120 min , at 50°C for 30 min , at 60°C for 30 min , and at 99°C for 5 min . We then used divergent primer sets to detect lariat RNAs by PCR or qPCR . Primer sequences used are listed in S4 Table . The corresponding plasmids of DBR1-pGEX2TK and HYL1 ( D1D2 ) -pMAL were introduced into the expression host BL21-CodonPlus ( DE3 ) . Cells was grown to an OD600 of 0 . 4–0 . 6 , and expression of GST or MBP fused proteins were induced by addition of 0 . 1 mM IPTG and incubation at 16°C for overnight . Cells carrying the pGEX2TK or pMAL empty vectors were also grown and induced as controls . Cell pellets were resuspended in lysis buffer and purified according to the recommended protocols of Glutathione Sepharose4B resin ( for GST ) or the amylose resin ( for MBP ) , respectively . 35S::DCL1-YFP with 35S::DBR1-Flag , 35S::HYL1-Flag , and 35S::SE-Flag , respectively , were co-expressed in N . benthamiana . Leaves were ground in liquid nitrogen and homogenized in lysis buffer ( 50 mM Tris_HCl ( pH 8 . 0 ) , 150 mM NaCl , 0 . 2% Nonidet P-40 , 2 mM DTT , 5% glycerol , proteinase inhibitor ) and centrifuged for 15 min at 13200 rpm . The lysate was incubated with GFP-Trap agarose beads ( Chromotek ) for 2 h . The immune complexes were then washed with lysis buffer . Proteins retained on the beads were resolved on SDS-PAGE . Anti-GFP and anti-Flag antibodies were used to detect DCL1 , and DBR1 , HYL1 or SE , respectively , by using western blot analysis . The data reported in this paper have been deposited in the SRA database of National Center for Biotechnology Information with accession No . SRP062035 for small RNA seq and RNA-seq , and accession No . SRP063916 for RIP-seq . | It is known that lariat RNAs formed during pre-mRNA splicing are debranched by DBR1 ( RNA debranching enzyme 1 ) . Loss of function of DBR1 causes embryo lethality in both animals and plants . In animals , some debranched lariat RNAs could be further processed into mirtron miRNAs , a class of nonconventional miRNAs that bypass the microprocessor for their biogenesis . However , no mirtron has been functionally validated in plants , and how the accumulation of lariat RNA in dbr1 results in embryo lethality remains unclear . Here , we show that DBR1 is necessary for the regulation of genome-wide miRNA biogenesis in plants . By investigating the correlation between lariat RNA accumulation and miRNA processing , we showed that the DBR1-mediated lariat RNA debranching process provides a safeguard role for the binding of the dicing complex with miRNA precursors . As both the DBR1-mediated lariat RNA debranching process and miRNA biogenesis are common features in higher eukaryotes , the finding that lariat RNAs sequester the dicing complex in plants may have a broad implications for the non-coding RNA field . | [
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"biolog... | 2016 | Intron Lariat RNA Inhibits MicroRNA Biogenesis by Sequestering the Dicing Complex in Arabidopsis |
Antiviral responses must rapidly defend against infection while minimizing inflammatory damage , but the mechanisms that regulate the magnitude of response within an infected cell are not well understood . miRNAs are small non-coding RNAs that suppress protein levels by binding target sequences on their cognate mRNA . Here , we identify miR-144 as a negative regulator of the host antiviral response . Ectopic expression of miR-144 resulted in increased replication of three RNA viruses in primary mouse lung epithelial cells: influenza virus , EMCV , and VSV . We identified the transcriptional network regulated by miR-144 and demonstrate that miR-144 post-transcriptionally suppresses TRAF6 levels . In vivo ablation of miR-144 reduced influenza virus replication in the lung and disease severity . These data suggest that miR-144 reduces the antiviral response by attenuating the TRAF6-IRF7 pathway to alter the cellular antiviral transcriptional landscape .
Viruses co-opt host cellular processes in order to replicate , and pathogenicity often correlates with growth rate . The best-characterized antiviral program is regulated by type I interferons , which restricts multiple aspects of the viral life cycle ( reviewed in [1–3] ) . An antiviral response program expressed at a level appropriate to the pathogenicity of the virus can effectively control infection . In contrast , an inadequate response will fail to restrain viral replication while an exaggerated inflammatory response can itself cause damage to the host . Ensuring rapid yet measured antiviral responses at mucosal surfaces , which require a threshold that permits containment of pathogenic insults yet tolerates benign foreign stimuli , is particularly important . In the case of influenza infection , progeny virions can be produced within 6 hours , necessitating a rapid response to quell the infection without triggering excessive inflammation that would compromise airway function . MicroRNAs ( miRNAs ) are post-transcriptional regulators that are excellent candidates for finely tuning immune responses . These small ( 20–25 nucleotide ) non-coding RNAs bind to target mRNAs by base-pairing to effect mRNA degradation or translational repression [4] . While the effect of miRNAs on individual target mRNA levels can often be modest , miRNAs are predicted to affect multiple targets in a biological pathway . This functional coherence in target genes can result in larger effects of a miRNA on biological processes than suggested by studies of individual miRNA-target interactions [5] . miRNA cooperativity in regulating levels of multiple targets in a pathway can also extend to cooperative interactions between multiple miRNAs in binding the same target , which can result in additive effects on biological processes [5 , 6] . The ability of miRNAs to shape host-virus interactions is a recently emerging concept ( reviewed in [7] , [8 , 9] ) . For example , miR-122 directly interacts with the hepatitis C ( HCV ) viral genome to stimulate translation and accelerate growth [10 , 11] . miRNAs that can target host mRNAs to modulate antiviral responses following influenza infection have recently been identified [9] . However , the mechanisms by which host miRNAs shape antiviral resistance by controlling innate immune signaling pathways are poorly understood . Here , we demonstrate that miR-144 attenuates a module of antiviral interferon-induced genes controlled by TRAF6 and IRF7 .
C57BL/6 mice ( Jackson Laboratories ) , IRF7null mice ( C57BL/6 background , provided by T . Taniguchi , University of Tokyo , Tokyo , Japan ) , and miR-144/miR-451null mice were housed in a specific pathogen-free barrier facility . miR-144/miR-451null mice [12] were backcrossed 5 times onto the C57BL/6 background ( verified to be >95% C57BL/6 ) , and wild type littermates used for infection experiments . 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 and all efforts were made to minimize suffering and mice were euthanized by CO2 inhalation . All animal work was reviewed and approved by the Institutional Animal Care and Use Committee at the Center for Infectious Disease Research ( protocol #AA-10 ) following guidelines established by the Institute of Laboratory Animal Resources and approved by the Governing Board of the U . S . National Research Council . Perfused lungs from C57BL/6 mice were digested using a dispase-agarose protocol [13] and cells isolated using CD45+ microbeads and autoMACS separation or sorting using a FACSAria . Live ( 7AAD- ) cells were sorted from lungs as follows: CD45+Sca-1± ( hematopoietic and bronchoalveolar stem cells ) , CD45-Sca1-T1a+ ( type I epithelial ) , CD45-Sca1-T1a- FITC ( autofluorescence ) + ( type II epithelial ) , CD45-Sca1-T1a-FITC- ( contains club cells ) . The sorted type II epithelial cells were predominantly pro-SPC+ ( Millipore ) and the club cells were predominantly Mucin+ ( NeoMarkers ) , which identifies goblet cells in addition to club cells; by intracellular staining and immunofluorescence microscopy . To specifically exclude RBCs , enzymatically dissociated perfused lungs were treated with ACK lysis buffer , stained for Ter119 , and Ter119-CD45+ ( hematopoietic ) cells and Ter119-CD45-T1alpha+ ( type I lung epithelial ) cells isolated using a FACSAria . Antibodies were obtained from e-Biosciences ( T1alpha , Ter119 ) or BD ( CD45 , Sca1 ) . miRNA profiling was performed on lungs infected with PR8 influenza virus for 72 h using 384-well microfluidic miRNA arrays ( ThermoFisher ) and miRNA expression measured relative to sno202 or U6 . RNA was isolated using Trizol ( Invitrogen ) and cDNA synthesized from DNase-treated RNA using random primers or miR-specific primers and analyzed by qRT-PCR using gene- or miRNA-specific Applied Biossytems TaqMan primers and probes ( ThermoFisher ) . Expression was normalized to EF-1 for mRNA and sno202 or U6 for miRNA . Influenza A/Puerto Rico/8/34 was provided by P . Thomas ( St . Jude’s , Memphis , TN ) , and VSV and EMCV obtained from ATCC . Wild-type mice were anesthetized using ketamine/xylazine and challenged with 105 PFU of PR8 influenza virus ( for 12 h and 24 h time points ) or 700 PFU ( for 3–12 day time points ) in 30 μL intranasally , divided between 2 nostrils . Weight-loss was measured daily as a correlate of morbidity . Lungs were lavaged using 1 mL of Hank’s buffered saline , the left lung lobe reserved for histopathological analysis , and the right lung lobes mechanically homogenized in 1 mLTrizol and RNA isolated for quantification of viral M gene by qRT-PCR as described for in vitro infections . 100 uL of cell-free lavage fluid was mixed with 1 mL Trizol for quantification of viral M gene . IRF7null mice were challenged with 105 PFU PR8 influenza virus for 24 h prior to lung lavage for viral load determination and lung RNA isolation for gene expression analysis as for WT animals . Formalin-fixed cells were permeabilized using 0 . 2% saponin , stained with anti-influenza NP ( ViroStat or Argene ) antisera followed by fluorescently conjugated secondary antibodies , and fluorescence measured using a FACSCalibur . Infected lungs were enzymatically dissociated using Liberase Blendzyme III ( Roche ) and analyzed using a FACSCalibur . All cell lineage-specific antibodies used in S3 Fig were from BD except for PDCA-1 ( Miltenyi ) . Five-micrometer sections from neutral buffered formalin-fixed left lung lobes were stained with hematoxylin and eosin and examined by a board-certified veterinary pathologist who was blinded to genotype and infection time point . Lung architecture was assessed to be normal in uninfected miR-144/miR-451null mice . Histopathological severity was assessed on a four-point scale and the extent of the section affected in the most severe manner was scored on a 4 point scale . Histology scores were calculated by multiplying each severity metric by the extent of section affected in the most severe manner , with a maximum severity score of 16 for each histopathological feature . Pneumonia = interstitial pneumonia/alveolitis x extent of the most severe changes; Bronchial necrosis = necrotizing bronchiolitis x extent of the most severe changes; Acute inflammation = necrosuppurative bronchiolitis + perivascular neutrophils; Chronic inflammation = bronchial hyperplasia + alveolar hyperplasia + perivascular mononuclear cells + lymphoid aggregates . TC-1 C57BL/6 mouse lung epithelial cells , 293T , and Vero cells ( ATCC ) were used where indicated . LET1 cells were generated by murine stem cell virus ( MSCV ) -SV40 large T antigen transduction of primary mouse lung epithelial type I cells trans-differentiated from type II epithelial cells and used after a minimal number of passages ( BEI Resources ) [14] . Cells were infected with influenza virus at a multiplicity of infection ( MOI ) of 5 for 1 h in OptiMEM without trypsin , the inoculum removed by washing , and cells cultured in OptiMEM for 18–24 h . Where indicated , cells were incubated with 10 uM Tpl2 kinase inhibitor ( Calbiochem ) or equivalent concentration of DMSO vehicle for 30 min prior to infection and throughout infection . RNA , protein , and cell supernatants were collected after 18–24 h . Viral RNA was quantified by RT-PCR using primers specific for influenza virus M gene ( Forward 5' CAT GGA ATG GCT AAA GAC AAG ACC , Reverse 5' CCA TTA AGG GCA TTT TGG ACA , Probe FAM- 5' TTT GTG TTC ACG CTC ACC GTG CCC A–TAMRA ) and normalized to the level of mouse EF-1 RNA obtained from equivalent volumes of supernatants . To permit comparison between experiments , viral load at 24 h was normalized to initial viral load at 1 h , where indicated . Influenza virus plaque assays were performed by plating serial dilutions of 24 h cell supernatants or BAL fluid on MDCK cells in duplicate , overlaying with agarose , and enumerating crystal violet-stained plaques . Cells were infected with EMCV ( MOI = 0 . 001 ) , VSV ( MOI = 0 . 1 ) or MCMV ( MOI = 10 ) in complete DMEM for 1 h , cells washed thoroughly to remove inoculum , and incubated for 24 h . EMCV and VSV plaque assays were performed similarly using Vero cells and a methyl cellulose overlay . To adjust for differences in rate of viral replication and cytotoxicity between these 4 viruses , different inoculums were selected to support multiple rounds of infection and replication over 24 h while allowing reproducible quantification of initial infection of the cell monolayer at 1 h . Formalin-fixed cells were permeabilized using 0 . 2% saponin , stained with anti-influenza NP ( ViroStat or Argene ) antisera followed by fluorescently conjugated secondary antibodies , and fluorescence measured using a FACSCalibur . Western blots were performed on cell lysates by serially incubating membranes with TRAF6 ( sc7221 , Santa Cruz ) or β-actin-HRP ( ab20271 , Abcam ) antibodies , anti-rabbit-HRP secondary antibody , followed by enhanced chemiluminescent detection and exposure to film for various times . Films from non-saturated exposures were quantified by densitometry using Photoshop ( Adobe ) , background subtracted ( using pixels contained in an adjacent area of identical size ) , and TRAF6 pixels/area divided by β-actin pixels/area to give normalized quantification of TRAF6 protein . Constructs expressing both murine mmu-miR-144-3p and mmu-miR-451a were cloned with 145 bp upstream of pre-miR-144 and 330 bp downstream from the end of pre-miR-451 . miR-451 alone was expressed with flanking sequences 100 bp upstream and 198 bp downstream . miR-144 was cloned with 145 bp upstream of pre-miR-144 and 198 bp downstream of the end of pre-miR-451; the activity of miR-451 included in this construct was ablated using site-directed mutagenesis of 7 bp of the mature miR-451 . These sequences were cloned into retroviral MSCV-GFP or lentiviral pLenti6 ( ±GFP ) vectors . Packaged virus was transduced into the indicated cells , and stably selected using 4 μg/mL puromycin ( TC-1 cells ) or 2 μg/mL puromycin ( LET1 cells ) . Influenza virus replication phenotypes were confirmed in cells generated by at least 3 independent transductions . LET1 cells were transduced with TRAF6 shRNA lentivirus ( sc-36718V , Santa Cruz ) or control scrambled shRNA lentivirus ( sc-108080V , Santa Cruz ) and stably selected using puromycin . Luciferase constructs were generated by cloning murine Irf7 ( complete coding sequence +3’-UTR; NM_016850 , 1–1830 nt ) , Trim30 3’-UTR , or Traf6 3’-UTR ( BC060705 , 1966–5368 nt; Open Biosystems ) 3’ of firefly luciferase . Wild type and mutant miR-144 target sequences in the Traf6 3’-UTR were generated by annealing complementary 45-mer oligos containing the sequences shown in the figure flanked by restriction sites , and cloning directly into the luciferase vector . 293T cells were transfected with pLenti6-miRNA constructs or empty vector along with the UTR-luciferase vector , which gave equivalent results to TC-1 transfections . Cell lysates were collected after 2 d and luciferase luminescence was normalized against a Renilla luciferase control present on the same plasmid ( Stop and Glo , Promega ) . Total RNA was isolated using Trizol from TC-1 cells expressing either MSCV empty vector or MSCV-miR-144+451 and infected with PR8 influenza virus for 24 h . Labeled RNA was hybridized to Affymetrix GeneChip Mouse Exon ST 1 . 0 arrays , probe-set intensities RMA normalized , and differential expression analysis performed using the Bioconductor package limma . Total RNA from LET1 cells was hybridized to Agilent SurePrint G3 Mouse GE 8x60K microarrays . Microarray analysis was performed on 3–5 samples from independent experiments , as indicated in figure legends . Annotated genes with fold changes >2 between conditions were retained for further analysis . Promoter sequences ( 1 kB upstream of the TSS ) were scanned for transcription factor binding-site motifs ( TRANSFAC 7 . 0 ) using FIMO ( MEME suite ) with a p-value cut-off of 0 . 0001 . GOMiner was used for GO enrichment determination . miRWalk was used to predict potential miR-144 targets using multiple algorithms ( TargetScan , RNA22 , PITA , PICTAR4 , PICTAR5 , RNAHybrid , miRWalk , miRDB , miRanda , and DIANAmT ) . miRWalk , TargetScan , and RNA22 predicted the miR-144 target sequences in Traf6 . The InnateDB curated protein interaction database was used and network visualization was performed using InnateDB and Cytoscape ( www . cytoscape . org ) . Expression data is available at GEO ( Accession # GSE31957 ( TC-1 ) and GSE50742 ( LET1 ) ) . P-values were determined using an unpaired two-tailed Student’s t-test , assuming equal variances .
We used the well-characterized murine influenza A virus infection model to investigate how microRNAs may regulate lung epithelial cell responses to respiratory infection and began by globally profiling expression of miRNAs in the influenza virus-infected lung ( S1 Table ) . miR-451 was the most abundant miRNA with an available knockout mouse , which enabled us to functionally test the contribution of this miRNA to host response to influenza virus infection . miR-451 is adjacent to miR-144 on mouse chromosome 11 and both miRNAs are co-expressed in erythroid cells as one transcript that is processed into two mature miRNAs . miR-144 and miR-451 bind to unique sequences in target genes to play non-redundant roles in erythroid lineage differentiation [12 , 15 , 16] but are not well-characterized in the lung . We used FACS analysis to determine which specific lung cell populations express each of these miRNAs ( Fig 1A ) . miR-144 ( mmu-miR-144-3p ) expression was much higher in type I lung epithelial cells than in CD45+ hematopoietic cells , whereas miR-451 ( mmu-miR-451a ) was expressed in both hematopoietic and epithelial cells ( Fig 1A ) . Since these miRNAs have been best characterized in cells of the erythroid lineage , we specifically excluded red blood cells from the sorted epithelial cell populations and measured no hemoglobin Hbb2 expression above the detection limit , excluding the possibility that the miR-144 measured in Ter119- T1α+ type I epithelial cells was due contamination by erythroid ( Ter119+ ) cells ( S2 Table ) . We evaluated the effect of miR-144 and miR-451 on viral replication since they are expressed within the natural host cells for influenza [17–19] . miR-144/451-deficient mice exhibit mild anemia due to dysregulated erythroid development and a 2-fold splenic enlargement due to erythroid hyperplasia , but possess an otherwise normal hematopoietic compartment [12 , 15 , 16] ) and normal lung architecture . miR-144/451-deficient mice had decreased viral load in the lung and in bronchoalveolar lavage ( BAL ) fluid over the first 3 days of infection ( Fig 1B ) , exhibited a delayed onset of weight loss , an established correlate of morbidity and viral load , and recovered their starting weights sooner than wild-type littermates ( Fig 1C ) . Flu-induced lesions were similar in character but decreased in severity and extent in miR-144/451-deficient mice . miR-144/451-deficient mice showed reduced interstitial pneumonia and bronchial epithelial necrosis at day 3 , which are characteristics of acute inflammation , and a trend of increased bronchiolar and alveolar epithelial hyperplasia at day 7 , which are characteristics of chronic inflammation ( S1 and S2 Figs ) . Alveolar-capillary barrier integrity following infection was equivalent between mice , as indicated by equivalent BAL protein content at early and late time points ( S2 Fig ) . miR-144/451-deficient mice showed increased cellularity in the BAL within the first day of infection and reduced numbers of recruited inflammatory cells at days 3 and 12 ( S2 and S3 Figs ) . These data suggest that miR-144/miR-451 affects influenza virus replication in epithelial cells , as the largest difference in viral load was observed within the first 12 hours of infection , prior to substantial inflammatory cell recruitment . We have previously observed that lung type I alveolar epithelial cells are rapidly infected in this experimental intranasal infection model , with faster kinetics than the descending infection that occurs during natural infection [20] . We observed a significantly lower viral load in type I epithelial cells isolated from miR-144/451-deficient mice relative to wild-type cells following in vitro influenza virus infection ( Fig 2A ) . Obtaining a mechanistic understanding of this in vivo phenotype required relevant in vitro models for studying influenza virus infection that would permit experimental modulation of miRNA expression . Influenza virus can infect and replicate in multiple types of respiratory epithelial cells; we focused on type I epithelial cells as these are infected by clinically-relevant H1N1 and H3N2 viruses [17 , 18 , 21] and offered more tractable models than were available for type II epithelial cells , another replicative niche for influenza virus . The expression of miR-144 and miR-451 in three tractable cell culture models is significantly lower than in freshly isolated lung epithelial cells ( S4 Fig ) . Therefore , to develop a model that matches the expression of miR-144/miR-451 in vivo , we generated lines of TC-1 and LET1 [14] cells stably over-expressing miR-144 , miR-451 , miR-155 ( as a negative control ) , or vector alone ( S4 Fig ) . Ectopic expression of miR-144 significantly increased levels of viral genomes and protein ( Fig 2B–2E ) . This increased permissiveness for viral replication was not a generalized response to miRNA expression , since expression of miR-451 or miR-155 did not affect viral replication ( Fig 2B and 2C ) . miR-144 expression significantly increased infectious virion production in cells infected with the negative-sense single-stranded RNA viruses influenza and vesicular stomatitis virus ( VSV ) and the positive-sense ssRNA encephalomyocarditis virus ( EMCV ) , indicating that the effect of miR-144 is not restricted to influenza virus infection ( Fig 2E ) . To elucidate the mechanism whereby miR-144 increases influenza virus replication within lung epithelial cells , we compared the transcriptional profiles of influenza-infected wild-type and miR-144 over-expressing cells . Expression of miR-144 significantly decreased the expression of 48 genes and increased the expression of 9 genes by >2 fold in TC-1 cells ( Fig 3A ) and similarly impacted the transcriptional profile of LET1 cells ( S5 Fig ) . A dominant feature of the array data was the suppressed expression of genes associated with antiviral and immune interferon responses in cells over-expressing miR-144 ( enriched gene ontology ( GO ) functional categories: defense response to virus and immune response ( p<0 . 05 ) ) . A heat map with genes grouped by functional annotations shows two dominant functional modules: antiviral and immune ( Fig 3A ) . We validated the differential expression of several characterized and putative antiviral effectors ( Rsad2 , Ifi203 , Mpa2l , Oas2 , and Trim30 ) and the transcription factor Irf7 by qRT-PCR . In contrast , miR-144 expression did not decrease levels of Irf3 , Irf1 , or Irak1 , showing specificity in the transcriptional regulation of a unique subset of antiviral genes ( Fig 3B and GSE50742 and GSE31957 ) . The suppressive effect of miR-144 on the expression of this group of antiviral genes was confirmed in LET1 lung epithelial cells ectopically expressing miR-144 ( S5A and S5B Fig ) and we measured increased expression of this gene module in miR-144null primary type I epithelial cells ( Fig 3C ) . We hypothesized a central role for IRF7 in the regulation of the miR-144-regulated transcriptional network because it was the only transcription factor that was differentially expressed and computational predictions identified IRF7 binding motifs within the cis-regulatory elements of the majority of miR-144-regulated genes ( Fig 3A ) . It has been demonstrated previously that IRF7 plays a dominant role in regulating type I and type III IFN-dependent antiviral responses to influenza virus at epithelial surfaces [22–25] . Human IRF7 deficiency results in lower interferon production and impaired control of influenza virus replication [26] and IRF7-null mice are more susceptible to viral infections [22 , 27] , with increased morbidity and mortality following infection with influenza virus [27] . We observed a 10-fold increase in lung viral load in IRF7-null mice relative to wild type mice after 24 hours ( Fig 4A ) , supporting a role for IRF7-regulated transcriptional programs in the early control of influenza virus infection and concordant with the increased susceptibility of these mice to other viral infections [22 , 28 , 29] . To identify which of the miR-144-regulated genes are controlled both directly and indirectly by IRF7 , we compared gene expression in the lungs of influenza virus-infected IRF7-null and wild type mice . As expected , we observed that the absence of IRF7 significantly reduced the expression of type I and III interferons ( Ifnα2 , Ifnα4 , Ifnα14 , Ifnλ3 , Ifnβ1 ) , as well as miR-144-regulated genes in Fig 3 with predicted antiviral functions ( Oas2 , Ifi203 , Mpa2l , Trim30 , Rsad2 ) ( Fig 4B ) . These data suggest that IRF7 is necessary for normal expression of the network of genes that is regulated by miR-144 . We tested whether Irf7 mRNA is a direct target of miR-144 in a luciferase assay , despite its lack of a computationally predicted miR-144 target sequence . Ectopic expression of miR-144 did not alter expression of a full-length Irf7-luciferase construct; thus decreased Irf7 mRNA levels in miR-144-expressing cells do not result from a direct interaction between Irf7 and miR-144 ( Fig 4C ) . To establish a potential mechanism for miR-144 inhibiting Irf7 expression , we used Cytoscape to examine the InnateDB protein-protein interaction database [30] for proteins known to interact directly with IRF7 or with its nearest network neighbors . Computational analysis to identify miR-144 binding sites in the coding and non-coding sequences of the genes that belonged to this expanded network suggested only three candidates where we could hypothesize plausible mechanisms connecting them to our observed viral infection phenotype: Tpl2/Map3k8 , Trim30 , and Traf6 , which each have at least one predicted canonical target sequences in their 3’-UTRs . TPL2/MAP3K8 is a MAP kinase that can regulate NF-κB and ERK signaling and IFN production [31–33] . We excluded this as a mechanism underlying the observed miR-144 phenotype since ectopic expression miR-144 did not alter Tpl2/Map3K8 expression and chemical inhibition of the kinase did not recapitulate the effect of miR-144 overexpression on viral load ( S6A and S6B Fig and GSE50742 ) . TRIM30 is an interferon-induced member of the TRIM family of proteins that can negatively regulate TLR and NLR signaling pathways [34 , 35] . Data did not support Trim30 being a direct target of miR-144 since expression of the 3’-UTR of Trim30 , which contains the predicted miR-144-target sequence , in a luciferase construct was not modulated by miR-144 expression ( Fig 4C ) . TRAF6 is an E3 ubiquitin ligase that is critical for type I interferon responses to viral infection [36] . TRAF6 physically associates with IRF7 [37 , 38] and activates its transcriptional activity by mediating K63-linked ubiquitination which permits its subsequent phosphorylation by various kinases [37 , 39] . This crucial interaction between TRAF6 and IRF7 is supported by the observation that when IRF7 is mutated so that it cannot be ubiquitinated by TRAF6 , it fails to mediate transcriptional responses [40] . We fused the complete 3’-UTR of Traf6 to firefly luciferase ( Fig 4D ) and measured a significant decrease in luminescence only in the presence of miR-144 ( Fig 4E ) , to an extent in concordance with published studies for other miRNA-dependent effects [41 , 42] . This indicates that miR-144 can post-transcriptionally regulate Traf6 expression . Traf6 is predicted to contain two miR-144 target sequences in its 3’-UTR . We generated luciferase constructs containing individual intact or mutated miR-144 target sites ( Fig 4D ) . Mutation of 7 nucleotides in the predicted miR-144 target sequence in site 2 completely abrogated the suppressive effect of miR-144 on expression of the reporter construct , while mutating the same nucleotides in site 1 had no effect ( Fig 4E ) . We observed a significantly reduced level of Traf6 mRNA and protein in cells expressing miR-144 ( Figs 4F and 4G , S5C and S5D ) and higher TRAF6 mRNA in miR-144-deficient cells ( Fig 3C ) . TRAF6 has also been shown to be regulated by miR-146a [43 , 44]; however , miR-144 expression did not alter miR-146a expression in cells ( S6C Fig ) , and therefore we have no data to suggest that miR-144 regulates TRAF6 via miR-146a . Together , while miR-144 may interact with other target mRNAs to contribute to this antiviral phenotype , these luciferase data and quantification of TRAF6 mRNA and protein abundance indicate that miR-144 can negatively regulate TRAF6 levels . As TRAF6-dependent K63-ubiquitination of IRF7 is necessary for its transcriptional activity [40] , our data support a model whereby miR-144 modulates the expression of a network of IRF7-regulated genes by targeting the 3’-UTR of Traf6 mRNA . We hypothesized that cells expressing shRNAs specific for Traf6 should have a similarly impaired antiviral capacity as cells expressing miR-144 if reduced steady state TRAF6 levels are mechanistically linked to impaired IRF7-dependent transcription . To test this hypothesis , we generated immortalized lung type I epithelial cells with TRAF6 protein levels reduced by miR-144 or specific shRNAs , along with control cells expressing miR-451 or a non-functional shRNA ( Fig 5A ) . Reduced TRAF6 levels were associated with reduced IRF7 protein and mRNA levels ( Fig 5A and 5B ) , which is expected as IRF7 positively feedbacks on its own transcription to amplify the IRF7-dependent transcriptional program [22] . These decreased levels of IRF7 have functional consequences for the IRF7 network . For example , expression of Ifi203 , Rsad2 , Trim30 , Oas2 , and Mpa2l is impaired when TRAF6 levels are suppressed by specific shRNA ( Fig 5B ) or miR-144 ( Figs 3B and S5B ) . The role of TRAF6 as the proximal component in the TRAF6-IRF7-IFN antiviral network is further supported by the observation that decreased TRAF6 levels brought about by two independent approaches ( overexpressed miR-144 or anti-TRAF6 shRNA ) are associated with significantly increased viral replication ( Fig 2 and Fig 5C and 5D , respectively ) . We observe concordant decreased expression of a module of antiviral genes in cells over-expressing miR-144 , TRAF6 shRNAs , and IRF7-deficient cells ( Fig 5E , blue ) , and reciprocal expression in miR-144-deficient cells ( Fig 5E red ) . These data support the network model depicted in Fig 5F , where miR-144 suppresses expression of the TRAF6-IRF7-IFN-regulated gene expression network to diminish the antiviral capacity of influenza virus-infected cells .
We have demonstrated microRNA attenuation of the host antiviral response using a miRNA knockout mouse and in vitro models . Reciprocal data obtained from gain- and loss-of-function studies shows that miR-144 modulates an antiviral transcriptional network within lung epithelial cells . The predominant effect of miR-144 deficiency was to decrease viral load rather than modulate inflammatory responses within the virus-infected lung , and better control of very early viral replication within epithelial cells significantly decreased morbidity . We employed primary lung epithelial cells and cell lines since they are a relevant replicative niche for influenza virus , and ectopically expressed miR-144 at physiological levels as a strategy to identify biologically relevant targets of miR-144 . miR-144 also increased virion production following infection with VSV , a negative-sense single-stranded RNA viruses , and EMCV , a positive-sense ssRNA encephalomyocarditis virus , indicating that the effect of miR-144 is not restricted to influenza virus . Recent studies have identified miRNAs with proviral effects in influenza virus-infected cells , resulting in increased viral replication [45 , 46] , while other miRNAs impair viral replication [47] . mRNAs targeted by miRNAs in influenza-infected cells encode a range of proteins relevant to the immune response to infection , including viral sensors [46] , cytokines [48 , 49] , and interferon [50] . Global proteomics studies have shown that miRNAs modestly decrease protein levels of many targets . Therefore , while decreasing TRAF6 levels by a similar extent through expression of miR-144 or TRAF6 shRNAs was sufficient to impair the antiviral capacity of epithelial cells , it is probable that miR-144 also regulates other target genes to mediate this cellular phenotype . One caveat of our study is that it utilized transcriptional profiling of miR-144 overexpressing cells to identify potential miR-144 target genes , which will not identify miRNA-mRNA interactions that impact protein translation . It is also relevant to consider potential interplay between miRNAs regulating the same pathway: miR-146a also targets TRAF6 and is induced following infection [43 , 44 , 51] and therefore could play a more prominent role in negatively regulating TRAF6-dependent antiviral responses at later stages of infection . Negative regulation of multiple genes in a signaling pathway or of a single gene by multiple miRNAs could explain how modest effects on individual targets can result in robust phenotypes . The relevance of miRNAs in regulating viral replication has been questioned by data from Dicer-deficient 293T cells that lack nearly all miRNAs , which showed normal replication by a large number of clinically-relevant viruses , including influenza A virus [52] . Aguado et al . employed a rapid vector-mediated miRNA ablation system and showed that cellular miRNAs predominantly regulate cytokine rather than antiviral effector genes in 293T and human foreskin fibroblast cells during acute viral infection [53] . In contrast , we observe a significant impact of the loss of the miR-144/451 locus on lung viral load rather than cytokines ( Fig 1 ) . We measure expression levels of miR-144 that is four orders of magnitude higher in primary normal human bronchial epithelial cells , the host cell targeted by influenza A virus , compared with the 293T kidney cell line ( S4 Fig ) . Therefore , the impact we observe of miR-144 on influenza virus replication in lung epithelial cells could not be modeled by the in vitro system employed in those two studies . We interpret these data as additional support for the emerging appreciation of the contextual nature of miRNA-target interactions . Mice deficient in miR-144 showed improved control of influenza virus replication , leading us to speculate that constitutive expression of this negative regulatory mechanism must not be deleterious and could be advantageous in some contexts . Appropriate regulation of epithelial responses during viral infection is critical to sufficiently activate effector functions that limit viral replication while minimizing tissue damage [54] . Seo et al demonstrated that miRNAs negatively regulate many interferon-stimulated genes in uninfected cells , particularly those associated with cell death and proliferation , in order to maintain homeostasis [55] . Low basal IFN-α expression has been suggested to set an activation threshold by priming cells to respond more rapidly and robustly to viral infection , in part by regulating IRF7 levels [23] . Negative regulation of TRAF6 levels by miR-144 provides an additional layer of post-transcriptional control of IRF7 . miRNAs can exert cell type-specific roles based on restriction of miRNA expression to specific cell types or differing relative abundance of mRNA target sequences . Plasmacytoid dendritic cells are specialized rapid and robust producers of type I interferons . miR-144 is not detected in plasmacytoid dendritic cells [48 , 56] suggesting that our observations of the effect of miR-144 in lung epithelial cells do not extend to regulation of basal IRF7-dependent antiviral gene expression in plasmacytoid dendritic cells . Cell lineage-specific expression of negative regulators in mucosal tissues , such as the lung , provides a potential mechanism for setting a higher threshold of immune activation than that required at sterile sites . Constitutive expression of a different microRNA was shown to contribute to the establishment of mucosal tolerance within the neonatal intestine [57] , lending support to a model where basal miRNA expression at mucosal surfaces counterbalances immune transcriptional activation from environmental insults with post-transcriptional repression . | Antiviral responses must be regulated to rapidly defend against infection while minimizing inflammatory damage . However , the mechanisms for establishing the magnitude of response within an infected cell are incompletely understood . miRNAs are small non-coding RNAs that negatively regulate protein levels by binding complementary sequences on their target mRNA . In this study , we show that microRNA-144 impairs the ability of host cells to control the replication of three viruses: influenza virus , EMCV , and VSV . We identify a mechanism underlying the effect of this microRNA on antiviral responses . microRNA-144 suppresses TRAF6 levels and impairs the gene expression program regulated by the transcription factor IRF7 . The resulting dysregulated expression of antiviral genes correlates with enhanced viral replication . Our findings in isolated lung epithelial cells were consistent with the effects observed in influenza virus-infected mice lacking miR-144 . Together , these data support a role for miRNAs in tuning transcriptional programs during early responses to viral infection . | [
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"i... | 2017 | miR-144 attenuates the host response to influenza virus by targeting the TRAF6-IRF7 signaling axis |
Proper organ patterning depends on a tight coordination between cell proliferation and differentiation . The patterning of Drosophila retina occurs both very fast and with high precision . This process is driven by the dynamic changes in signaling activity of the conserved Hedgehog ( Hh ) pathway , which coordinates cell fate determination , cell cycle and tissue morphogenesis . Here we show that during Drosophila retinogenesis , the retinal determination gene dachshund ( dac ) is not only a target of the Hh signaling pathway , but is also a modulator of its activity . Using developmental genetics techniques , we demonstrate that dac enhances Hh signaling by promoting the accumulation of the Gli transcription factor Cubitus interruptus ( Ci ) parallel to or downstream of fused . In the absence of dac , all Hh-mediated events associated to the morphogenetic furrow are delayed . One of the consequences is that , posterior to the furrow , dac- cells cannot activate a Roadkill-Cullin3 negative feedback loop that attenuates Hh signaling and which is necessary for retinal cells to continue normal differentiation . Therefore , dac is part of an essential positive feedback loop in the Hh pathway , guaranteeing the speed and the accuracy of Drosophila retinogenesis .
Temporal and spatial coordination between cell proliferation and differentiation is essential for proper organ patterning . A way to ensure this coordination is through the use of regulatory signaling pathways that control both processes . Among those is the Hedgehog ( Hh ) signaling pathway that regulates organ growth and patterning in embryos and tissue homeostasis in adults , both in vertebrates and invertebrates [1–4] . Not surprisingly , mutations in components of the Hh signaling pathway cause a number of human disorders , including congenital abnormalities and cancer [2–4] . One of the processes in which Hh signaling plays an essential role is the patterning of the retina in vertebrates and invertebrates [5–7] . In Drosophila , Hh is responsible for organizing a moving signaling wave that patterns the primordium of the fly eye during the last larval stage ( L3 ) . The processes under Hh signaling control have been extensively studied and summarized in what follows . The front of the differentiation wave is marked by a straight indentation of the eye epithelium , called morphogenetic furrow ( MF ) , that runs across the dorsoventral axis of the eye primordium , or “eye imaginal disc” [8–10] . hh , initially expressed along the posterior margin of the eye disc [11] and later by the differentiating photoreceptors ( PRs ) , activates the expression of the BMP2 decapentaplegic ( dpp ) within the MF [12] . Hh instructs undifferentiated proliferating progenitor cells to synchronously undergo mitosis ( First Mitotic Wave , FMW ) and then stop temporarily their cell cycle in G1 phase through Dpp , which acts long range [13–16] . At a shorter range , Hh initiates the expression of the proneural gene atonal ( ato ) [17–23] and stabilizes the G1 state by activating the expression of the p21/p27 Cdk inhibitor homologue dacapo ( dap ) [24–27] . In addition , together with Dpp , Hh induces coordinated cell shape changes responsible for MF formation [18 , 19 , 23 , 28–31] by promoting the apical constriction , apical-basal contraction and basal nuclei migration of cells ( Fig 1A ) . These cellular changes are mediated , at least in part , through the contraction of the acto-myosin cytoskeleton [32 , 33] . Immediately behind the MF , Ato expression is restricted to evenly spaced cells , which become the ommatidial founder photoreceptors ( PR8s ) . Then , PR8s induce neuronal differentiation of the adjacent precursor cells . Precursor cells that did not start their differentiation program immediately after the MF suffer one last round of mitosis , the Second Mitotic Wave ( SMW ) [10] . Therefore , Hh secreted by differentiating PR cells drives the anterior propagation of the MF and its associated differentiation wave , while regulating the SMW locally [25 , 34–36] . Thus , the MF coincides spatially with the onset of differentiation . Interestingly , the MF state is transient: while anterior precursor cells are recruited to enter the MF state , the newly differentiating PRs and cells at the SMW exit this “furrowed” state . The coordinated action of Hh has been shown to rely on dynamic changes of its signaling activity . In flies , Hh signaling regulates the post-translational proteolytic processing of the Gli-family transcription factor Cubitus interruptus ( Ci ) . Hh binding to the receptor Patched ( Ptc ) relieves the inhibition exerted by unbound Ptc on the transducer Smoothened ( Smo ) , and thus promotes the activation of the Fused ( Fu ) kinase [1–3] . In turn , activated Fu promotes the conversion of the full-length form of Ci ( CiFL ) to Ci activator ( CiA ) form [37] . As a result , CiFL is no longer phosphorylated by Protein Kinase A ( PKA ) [38–40] and other kinases . Otherwise , CiFL phosphorylation leads to the generation of the Ci repressor form ( CiR ) through partial CiFL degradation by the F-box-containing protein E3 ubiquitin ligase complex ( SCFSlim-Cullin1 ) . The relative amount of both CiR and CiA determines the transcriptional status of Hh-target genes , such as ptc , dpp and engrailed ( en ) [41–44] . In the developing Drosophila eye , while low levels of Hh signaling promotes cell shape changes associated with MF formation and concomitant dpp expression , high levels are required for the re-entry of the precursor cells in the cell cycle at the SMW and for the activation of roadkill ( rdx ) expression [45–48] . Rdx targets CiFL to full degradation through the recruitment of the Cullin3 ( Cul3 ) -based E3 ligase complex [45 , 46] . Thus , posterior to the MF , high levels of Hh signaling attenuate its own activity by Rdx:Cul3 complex , allowing retinogenesis to occur properly [45 , 46] . Therefore , mutations that affect MF progression could be additional components of the machinery that regulates Hh signaling intensity and dynamics . Mutations in the retinal determination gene dachshund ( dac ) affect MF movement , without blocking differentiation [49] . dac expression depends on Hh signaling itself [25 , 50] . It localizes to all nuclei straddling the CiFL-expressing domain , from the progenitor domain to the SMW , where differentiating PR cells start expressing hh ( Fig 1B and 1C–1C´´ ) . Therefore , high Dac levels coincide with the major neuronal differentiation and morphogenetic processes controlled by Hh signaling . Altogether , these results indicate that dac exhibits the traits required for being a candidate modulator of Hh signaling intensity . Here , we show that indeed dac potentiates Hh signaling in the MF by promoting CiFL accumulation and CiA activity downstream or in parallel of Fu . Our observations argue that this mechanism is absolutely required to promote proper retinogenesis by controlling the timing of MF formation , accurate specification of the founder PR cell and to trigger the Rdx-dependent negative feedback , which turns Hh signaling off posterior to the MF . Thus , Hh signaling potentiation by Dac allows the fast building up of signaling that is required for the swift processes associated with the moving retinal differentiation wave in Drosophila .
To investigate a role of dac as a candidate modulator of Hh signaling , we reexamined the consequence of removing dac on MF-associated processes . Consistent with previous observations [49] , all GFP-marked dac- clones larger than 6 cells straddling this region showed a delay in MF formation ( Fig 1D , S1A and S1A´ Fig; n = 53 ) . Accordingly , the onset of PR differentiation , detected by labeling with an antibody against the neuronal marker Elav , was also retarded in these clones ( Fig 1E and 1E´ , S1D and S1D´ Fig ) . This retardation was associated with a delay in the onset of ato expression and with an aberrant spacing of Ato-positive PR8 cells ( Fig 1 , compare 1G and 1G´ with 1F ) . These defects were not specific of any ommatidial cell type: in dac- clones posterior to the MF , we detected expression of the hh-Z enhancer trap , which marks PR2-5 cells ( Fig 1H and 1H´ ) , of the PR3/4 marker Spalt ( Sal ) ( Fig 1I ) and of the PR7 marker Prospero ( Pros ) ( Fig 1J ) . However , the density of ommatidia ( Fig 1E and 1E´ , 1H and 1H´ , S1D and S1D´ Fig ) and the proper number of cell types per ommatidium were affected by the loss of dac function . For instance , some ommatidia only contained one Sal-expressing cell instead of two ( yellow arrow in Fig 1I ) . Concomitant with the delayed MF and differentiation onset , the SMW was also retarded and became asynchronous . Posterior to the SMW , dac- clones showed persistent reentry into the cell cycle , as detected by elevated expression of the G2/M CyclinB ( CycB ) ( S2A and S2A´ Fig ) , increased number of cycling cells ( S2B and S2B´ , S2C and S2C´ Fig ) , as well as maintenance of the expression of the G1/S cyclin CyclinE ( CycE ) and loss of dap ( S2D and S2D´ and S2E Fig ) . Taken together , we conclude that dac is required for three essential roles played by Hh signaling: MF movement , regulation of the cell cycle and proper retinogenesis . Downregulating the function of the Hh-signal transducer smo ( smo3 clones ) also caused a delay in MF movement ( seen by E-Cadherin ( E-Cad ) higher signal intensity ) and affected apical constriction of cells within the MF ( S1B and S1B´ Fig ) . In addition , the density of ommatidia was reduced in smo- clones ( S1E and S1E´ Fig ) . Thus , smo- and dac-mutant clones shared similar phenotypes ( Fig 1D , 1E and 1E´ and S2A and S2B´ , S2D and S2E´ Fig ) . In agreement with dac and smo being part of the same signaling pathway , dac synergized with smo in MF formation and PRs differentiation . All smo , dac double-mutant cells failed to undergo the cell shape changes associated with the MF ( S1C and S1C´ Fig , n = 33 discs ) and to differentiate PRs ( S1F and S1F´ Fig , n = 20 discs ) . As dac was expressed in cells that accumulated CiFL at high levels in the MF and at low levels posterior to the MF where Ci promotes the transcription of the rdxZ reporter ( Fig 1B–1C´´ and 2A–2B´´´ ) , we next analyzed if dac affected Hh signaling . Strikingly , 67% of discs containing GFP-marked dac- clones straddling the MF showed reduced CiFL levels ( Fig 2C–2F; n = 24 discs ) and lower transcription of dpp , monitored by the transcriptional reporter dppZ ( Fig 2G–2J; 64% of discs , n = 14 ) . In addition , all dac- clones failed to trigger high levels of a lacZ enhancer trap insertion in the rdx gene ( rdxZ ) posterior to the MF ( Fig 2K–2N; n = 9 discs ) . All these results indicate that dac is required for a full activation of the Hh signaling pathway . To determine if Dac is sufficient to potentiate Hh signaling , we analyzed the effect of overexpressing dac on Hh signaling activity in the wing imaginal disc , where endogenous Dac protein is expressed only in a few restricted patches [49] . In this tissue , Hh produced in the posterior ( P ) compartment signals to the anterior ( A ) compartment ( Fig 3A ) . Thus , cells along the AP boundary compartment receive maximal Hh signaling , leading to the activation of rdx expression and consequently signaling attenuation through Rdx:Cul3-mediated CiFL degradation [45 , 46] . At these signaling levels , immediately adjacent to the P compartment , ptc expression is induced [41–44] . Next to this domain and further away from the AP boundary dpp is expressed [41–44] . Therefore , if dac potentiates Hh signaling , we expected that its expression along the AP boundary should enhance signaling levels and allow dpp transcription . Although overexpressing dac ( HA::dac ) along the AP boundary compartment using a ptc-Gal4 driver ( Fig 3A ) promoted CiFL accumulation ( Fig 3 , compare 3C–3C´´ with 3B–3B´´ and 3D´ with 3D ) and increased expression of dppZ ( Fig 3 , compare 3G and 3G´ with 3E , 3F and 3F´ and 3H´ with 3H ) , these effects were relatively modest . Overactivation of Hh signaling would also be expected to potentiate rdx transcription , which would limit CiFL accumulation and Hh signaling activity . In agreement with this , overexpressing HA::dac in the dorsal compartment using the apterous-Gal4 ( ap-Gal4 ) driver ( Fig 3A ) upregulated rdxZ expression in 85% of discs analyzed ( n = 20 ) and drastically extended the CiFL-expression domain in the dorsal wing disc cells closed to the AP boundary in 82% of cases ( n = 17 ) ( Fig 3 , compare 3J–J´´ with 3I and 3I´ and 3K´ with 3K ) . Taken together , we conclude that dac is necessary and sufficient to potentiate Hh signaling activity by promoting CiFL accumulation and the activation of Hh target genes . The Hh pathway has built-in a negative feedback that serves to attenuate signaling following maximal activation . This feedback rests on the activation of rdx by high signal levels . Once expressed , Rdx drives a Cul3-dependent CiFL degradation posterior to the MF thus allowing the exit from the furrow state [45 , 46] . We therefore tested if the loss of dac function induces the persistence of Hh signaling posterior to the MF . Indeed , some dac- clones located in internal region of the disc primordium showed ectopic expression of CiFL ( Fig 4B and 4B´ ) and of the Hh-target genes Ptc ( Fig 4D and 4D´ ) and dppZ ( Fig 4F–4H ) . Strikingly , all these clones dropped basally ( Fig 4A , 4C and 4E ) . As sustained exposure to Hh signaling promotes MyOII-dependent cell ingression and groove formation [32 , 33] , we analyzed the shape of dac- clones posterior to the MF using the apical marker E-Cad . We confirmed that the disappearance of dac- cells from the apical surface ( Fig 5A ) did not result from a loss of cell polarity , as dac- cells maintained E-Cad expression apically ( Fig 5B ) . However , cross section through the eye disc showed that dac- clones ingressed within the epithelium , forming grooves ( Fig 5C and 5C´ ) . In addition , these clones accumulated activated MyOII , detected by phospho-Myosin Light Chain ( pMLC ) antibody at the apical surface of ingressed clones ( Fig 5D , 5E and 5E´ ) . These drastic changes in cell shape were associated with the presence of PR nuclei , expressing Elav and hhZ that were still localized close to the apical cell surface but appeared on basal focal planes compared to control GFP-positive neighboring nuclei ( Fig 5F and 5F´ to 5I and 5I´ ) . dac- clones spanning the disc margin that delayed MF progression and PRs differentiation also contained higher Ptc levels ( S3A and S3A´´ Fig ) . However , those in which MF initiation and retinogenesis were compromised [49] showed reduced Ptc expression ( S3B and S3B´ Fig ) . Thus , dac is required for the swift dynamic changes in Hh signaling associated to the passing MF . In its absence , Hh target genes activation and Hh-regulated processes suffer a general delay . Interestingly , one of the consequences is that Hh signaling persists for longer , as its attenuation mediated by rdx is also delayed . To understand how dac promotes CiFL accumulation , we analyzed the requirement for dac to transduce Hh signaling in cells expressing constitutive active forms of Hh pathway components . We first expressed in clones a form of ci insensitive to phosphorylation by PKA ( cipka+ ) . Consistent with previous observations , cipka+ clones promoted precocious differentiation anterior to the MF , where cells express dac endogenously [20 , 51–56] . All cipka+ clones accumulated CiFL ( Fig 6A and 6A´; n = 7 discs ) , while 89% displayed an enrichment of F-actin , reminiscent to the apical cell constriction in the MF ( Fig 6C and 6C´; n = 27 discs ) and 62% formed ectopic PRs ( Fig 6E and 6E´; n = 8 discs ) . However , posterior to the MF , where CiFL degradation is independent of PKA [57] , Cipka+ accumulation was reduced when compared to clones located in the MF and anterior to the MF ( Fig 6A and 6A´ ) . Thus , Cipka+ may suffer degradation in this domain . Removing dac function did not affect the ability of clones expressing ectopic cipka+ to accumulate CiFL ( Fig 6B and 6B´; 100% of discs , n = 10 ) , F-actin ( Fig 6D and 6D´; 95% of discs , n = 22 ) or differentiate ectopic PRs ( Fig 6F and 6F´; 22% of discs , n = 12 ) anterior to the MF . Therefore , dac acts upstream of CiFL . We next investigated if dac was required for the activity of the upstream Ci regulator Fused ( Fu ) . Overexpressing a constitutive active form of fu ( fuEE+ ) anterior to the MF also triggered CiFL accumulation in 93% of discs with clones ( Fig 6G and 6G´ , n = 27 discs ) , an enrichment of F-actin or E-Cad , reminiscent to the apical cell constriction in the MF in 85% of cases ( Fig 6I and 6I´; n = 13 discs ) , and ectopic PR differentiation in 11% of discs with clones ( Fig 6K and 6K´; n = 27 discs ) . In contrast , when these clones were also mutant for dac , the accumulation of CiFL ( Fig 6H and 6H´; 36% of discs , n = 11 ) and of F-actin ( Fig 6J and 6J´; 41% of discs , n = 27 ) was severely reduced . In addition , these clones were no longer able to differentiate ectopic PRs ( Fig 6L and 6L´ , n = 6 ) . Further , overexpressing fuEE+ did not rescue the MF delay of dac-mutant tissue ( Fig 6H and 6H´ and 6J and 6J´ ) ) . Thus , dac potentiates Hh signaling by promoting CiFL accumulation downstream of , or parallel to fu . dac encodes a nuclear protein , which has been shown to bind double-stranded nucleic acids [58] and to activate transcription of a reporter gene in yeast [59] . We therefore tested , using a genome-wide ChIP-seq approach , the possibility that Dac regulated the expression of some of the components along the Hh signaling pathway ( see Materials and Methods ) . We analyzed specifically ChIP peaks in distal regions ( i . e . excluding those falling in 5’UTRs and 1kb upstream of transcription start sites ) . Within the ChIP peaks , we identified a set of 352 distal regions in which we found significantly enriched an A-rich motif . This motif is similar to the DNA binding motif identified previously for the human DACH by protein structure , in-silico and ChIP-seq analyses ( S4 Fig , [60] ) . This fact indicated that the set of 352 ChIP peaks were likely directly bound by Dac . However , among the nearby genes ( S4 Fig ) , we could not identify any of the major components of the Hh signaling pathway ( including hh itself plus smo , PKA , CKI , ci , cullin1 , Slimb , skp-1 , and cul3 ) . This result suggested that the effect of dac on the activity of the Hh pathway was unlikely to be mediated by the transcriptional regulation of these signaling components . To test experimentally this point , we generated dac- clones and asked whether dac loss affected the expression of the hhZ and ciZ enhancer traps , which serve as transcriptional reporters . Although dac mutant clones located in internal region of the eye primordium appeared to contain reduced hhZ expression ( Fig 1H and 1H´ ) , this effect likely resulted from a reduction in the number of PR cells per ommatidia in dac- mutant tissue , as PR hhZ levels were not different than in wild type cells . Similarly , in clones straddling the MF , the absence of dac function delayed hhZ expression , but appeared normally as PR cells gained ELAV signal ( S5A and S5A´´´ Fig ) . In addition , dac was neither necessary nor sufficient to control ci transcription , as ciZ expression was not affected in dac mutant in the eye discs ( S5B and S5C´ Fig ) or in wing discs overexpressing dac using the ptc-Gal4 driver ( S5 Fig , compare S5H to S5J with S5D to S5F and S5K with S5G ) . We conclude that dac does not promote CiFL accumulation downstream of , or parallel to fu by affecting hh or ci expression and , most likely , neither affecting the transcription of other major pathway components .
Our observations demonstrate that dac is required to strengthen Hh signaling . First , the absence of dac function recapitulates phenotypically a reduction of Hh signaling . Removing smo or dac function delays MF progression ( Figs 1 and 2 , S1 Fig , [23 , 28–31 , 49] ) and the re-entry in S-phase in the SMW ( S2 Fig; [25] ) . In addition , loss of dac ( Fig 1 ) or smo [23 , 29 , 31] results in reduced ato expression ahead of the MF and affects the restriction of ato , first in proneural clusters and then in single PR8 posterior to the MF . Furthermore , neither loss of dac ( Fig 1 ) , nor smo [31 , 35] affects ommatidial cell fate . The cause of the reduced number of ommatidia and variable number of cells per ommatidium in dac mutant clones ( Fig 1 ) is not totally clear . It could result from the effects in ato expression , including its abnormal spacing posterior to the MF and the singling of the ommatidial founder PR8 [62–67]; it could also arise from alterations in cell cycle control , as we detect persistent cell cycling posterior to the MF , which may affect cell recruitment into the ommatidium [25 , 36]; or from a combination of both . Second , smo and dac synergize to promote MF progression and PR differentiation ( S1 Fig ) . Accordingly , removing one copy of hh enhances the dac mutant eye phenotype and fully suppresses PRs differentiation of dac mutant clones located in internal regions of the disc primordium [49] . Third , dac mutant clones show reduced levels of CiFL and lower expression of the Hh target gene dpp in the MF and rdx posterior to the MF ( Fig 2 ) . In addition , ptc expression , another Hh target , is reduced in marginal dac mutant clones that fail to differentiate photoreceptor cells ( S3 Fig ) . Conversely , expressing dac ectopically in the wing disc is sufficient to enhance CiFL accumulation and rdx expression , and to induce dpp in the domain immediately adjacent to the compartment boundary ( Fig 3 ) . Our observations argue that dac potentiates Hh signaling by promoting CiFL accumulation downstream of , or in parallel to Fu . First , loss of dac reduces CiFL levels in the MF ( Fig 2 ) , while expressing dac ectopically in the wing disc has the opposite effect ( Fig 3 ) . Second , an activated form of Fu ( FuEE+ ) , which inhibits Ci processing ( into CiR ) and promotes CiFL/CiA accumulation [68] , requires dac function for this accumulation of CiFL and to induce MF-like features and precocious PR differentiation anterior to the MF . In contrast , removing dac function has no major effect on the ability of a PKA-insensitive form of Ci ( Cipka+ ) to trigger features associated to ectopic Hh signaling in this domain ( Fig 6 ) . The precise molecular mechanism by which Dac affects this step along the Hh signaling pathway is unknown at the moment . dac encodes a nuclear protein , which has been shown to bind double-stranded nucleic acids [58] and to activate transcription of a reporter gene in yeast [59] . Our functional and ChIP-seq experiments indicate that hh and ci are not direct transcriptional targets of Dac . In addition , the ChIP-seq data suggest that neither are any of the major pathway components of the Hh pathway ( S4 Fig ) –although without further studies this possibility cannot be ruled out completely . This would shift the control of the Hh signaling activity to other Dac targets , which would exert this control directly or indirectly . Another , not mutually exclusive possibility is that Dac collaborates with CiA in enhancing the expression of CiA-dependent target genes , such as rdx or ptc ( Figs 2 and 3 ) . Although we have previously shown that Dac inhibits the transcriptional ability of the Homothorax/Yorkie ( Hth/Yki ) complex [69] , Dac may act as an activator or repressor depending on the cellular context [70] . Therefore , Dac may contribute to the transcriptional activity of CiA promoting the expression of target genes responsible for proneural fate acquisition and differentiation . In agreement with this hypothesis , using the bioinformatic tool Clover [71] , with standard parameters , we also found , besides the Dac motif , the Gli/Ci consensus binding motif significantly enriched ( p<0 . 001 ) in the distal Dac-ChIP-peaks ( S4 Fig ) , suggesting that Dac might indeed collaborate with CiA to enhancer expression of its targets . In addition , we cannot exclude other mechanisms of Dac action independent of its role in transcriptional regulation . In fact , although it was not reported in Drosophila tissues , the human Dac homologue DACH1 presents both nuclear and cytoplasmic localization in different tissues [72–75] . Moreover , DACH1 localization shifts from the nucleus in normal tissue to the cytoplasm in ovarian cancer [72] . Dac/DACH1 might be involved in the control of Hh signaling pathway in a subcellular localization manner . Further studies are required to elucidate the mechanism by which Dac affects CiFL accumulation and consequently potentiates Hh signaling . In the developing eye , dac lies downstream of eye absent ( eya ) and the dpp signaling pathway [50 , 76–78] where it regulates multiple events that together coordinate cell proliferation and differentiation in time and space . We demonstrate here that dac potentiates Hh signaling . This together with dac’s role in the transition from proliferating progenitor cells to committed precursor cells together with Dpp signal [69] can account for the pleiotropic and essential roles played by dac ( Fig 7 ) . Retinogenesis starts with the formation of the MF and the triggering of two major Hh targets: dpp and ato . The weakening of Hh signaling together with the reduced dpp transcription can account for MF delay , as both signals are required for this morphogenetic event [18 , 19 , 23 , 28–31] . Right at the MF and immediately posterior to it , the cell cycle is tightly regulated . We observe that the expression of the p21/p27 Cdk inhibitor dap is lost in dac- cells ( S2E Fig ) and that this is accompanied by persistent cycling beyond the SMW ( S2A and S2C´ Fig ) . This cell cycle misregulation , together with the aberrant restriction of ato expression , is the likely cause of the abnormal retinogenesis in dac-mutant tissues that includes ommatidia with variable number of cells . Posterior to the MF , high Hh signaling levels activates the expression of Rdx , which , together with Cul3 , targets CiFL to full proteasomal degradation . In doing so , Hh signal becomes attenuated , and this attenuation allows cells to exit the furrowed state . In fact , dac-mutant clones posterior to the MF often remain as apically constricted inpouchings of the disc epithelium with high levels of P-MyOII , accumulated CiFL and expression of CiA target genes ( Figs 4 and 5 ) . This report , together with our previous study [69] , places dac as an essential regulator of retinal development , controlling the transitions from proliferating progenitor cells to committed precursor cells first [69] and then from precursors to differentiating retinal cells ( this work ) . The dac expression profile spans the regions of the eye disc where it exerts its functions: the increasing Dac expression in precursor cells approaching the MF ensures that cells transit from proliferation to G1 arrest , while peak levels in the MF secure proper retinogenesis by potentiating Hh signaling here . High dac expression in the MF in addition to its downregulation in differentiating photoreceptors could both contribute to turn off Hh signaling in this domain . This could be achieved , at least in part , by inducing the activation of a negative feedback via rdx expression and by limiting CiFL accumulation downstream or in parallel to Fu , respectively . Whether this function is also carried out by the vertebrate dac homologues , the DACH1 and DACH2 genes , awaits further investigation .
Fly stocks used were dac3 , smo3 , hhP30 ( hhZ ) , rdx03477 ( rdxZ ) , P{dpp-lacZ . Exel . 2}3 ( dpp-Z ) , ciZ [79] , UAS-HA:dacF [80] , UAS-mCD8GFP , UAS-mCherry ( TRIP #35787 ) , UAS-fuEE [81–83] , UAS-Cipka [82] , ptc-Gal4 [84] , ap-Gal4 [85] . Mutant clones for dac3 marked by the absence of GFP were generated through mitotic recombination [86] . The MARCM technique [87] was used to induce clones marked by the presence of GFP , mutant for dac3 or smo3 or smo3 and dac3 or expressing UAS-fuEE or UAS-cipka or mutant for dac3 and expressing UAS-fuEE or UAS-cipka . Larvae were heat-shocked for 1 hour at 37°C between 48 and 72h after egg laying . Gain of function experiments using UAS-HA:dacF were performed using the ptc-Gal4 or ap-Gal4 driver that drives expression in the AP boundary compartment or dorsal region of the wing disc , respectively . Crosses carrying UAS-HA:dacF and the corresponding controls were raised at 18°C , while others were raised at 25°C . Imaginal discs were dissected and fixed according to standard protocols . Primary antibodies used were mouse anti-Dac ( 1:100; mAbdac2 . 3 , DSHB ) ; mouse anti-CycB ( 1:25; F2F4 , DSHB ) ; mouse anti-β-Galactosidase ( 1:200; Z378B , Promega ) , rabbit anti-β-Galactosidase ( 1:1000; 55976 , Cappel ) ; rat anti-E-Cad ( 1:50; DCAD2 , DSHB ) ; guinea pig anti-CycE ( 1:1000; gift from T . Orr-Weaver , Whitehead Institute , Cambridge , USA ) ; rabbit anti-Ato ( 1:5000; [22] ) ; rabbit anti-pMLC ( 1:10; 36715 , Cell Signaling ) , which reveals pMyOII; rat anti-Elav ( 1:1000; 7E8A10 , DSHB ) ; mouse anti-Elav ( 1:100; 9F8A9 , DSHB ) ; guinea pig anti-Sens ( 1:1000; [88] ) ; guinea pig anti-Pros ( 1:25; [89] ) ; rabbit anti-Sal ( 1:200; [90] ) ; rabbit anti-PH3 ( 1:200; 9701 , Cell Signaling ) ; mouse anti-Ptc ( 1:100; Drosophila Ptc ( Apa1 ) , DSHB ) ; rat anti-Ci ( 1:10; 2A1 , DSHB ) . Rhodamine-conjugated ( Sigma ) and C660–conjugated Phalloidin ( Biotium ) were used at a concentration of 0 . 3 μM and 5U/ml , respectively . DAPI was used at a concentration of 1ng/ml . Fluorescently labeled secondary antibodies were from Jackson Immunoresearch , ( 1:200 ) . Imaging was carried out on Leica SP2 or SP5 confocal microscopy set ups . Plot profiles of fluorescent intensity were obtained using an NIH ImageJ program [91] . Fluorescent intensities were normalized to the maximum intensity for each channel . Anti-mouse-HRP ( Sigma ) was used for immunoperoxidase staining . Digoxigen labelled dap RNA probe ( Roche ) was produced from the cDNA clone LP07247 ( BDGP ) . For BrdU incorporation assay , eye-antennal discs were dissected and incubated in 10μM BrdU in PBS for 30min . BrdU was detected with an anti-BrdU antibody ( 1:400; Roche ) after treatment with DNase . Wandering 3rd instar larvae ( Dac:GFP , Bloomington stock 42269 ) were dissected in cold PBS and imaginal discs were fixed with formaldehyde for 25 minutes . Chromatin was fragmented by sonication till it reached an average size of 500 bp . 20 μl of protein A/G magnetic beads ( Merck , Millipore ) was added to pre-clean the samples . The anti-GFP Ab ( ab290 , Abcam ) was added to a fixed chromatin aliquot and incubated at 4°C overnight . Immunocomplexes were recovered by adding protein A/G magnetic beads to the sample and incubating for 3 hours at 4°C . Beads were resuspended in elution buffer , RNase was added to the immunoprecipitated chromatin and incubated for 30 minutes at 37°C . ChIP libraries were prepared with the Truseq DNA library prep kit ( Illumina ) and the samples were sequenced on a HiSeq 2000 ( Illumina ) . The reads were cleaned using fastq-mcf and mapped with bowtie2 to the Drosophila melanogaster genome ( Flybase version 5 ) . Dac-ChIP peaks ( minus input ) were called using macs2 ( dac-ChIP-vs-ChIP_Input_peaks . bed ) . From this bed file all regions lying in a 5’UTR or 1kb upstream of a TSS were removed using bedtools intersectBed , to retain only distal Dac-ChIP-peaks ( dac-ChIP-vs-ChIP_Input_peaks_not-in-5UTR_not-in-1kb-up . bed ) . The distal Dac-ChIP-peaks were loaded into i-cistarget [92] , a motif enrichment tool , to obtain a final table ( S4 Fig ) of potential Dac targets . Access to the whole dataset can be found in the GEO database with the accession number GSE82151 ( http://www . ncbi . nlm . nih . gov/geo/query/acc . cgi ? acc=GSE82151 ) , used as reference for all subsequent manuscripts referring to these data . | Molecules of the Hedgehog ( Hh ) family are involved in the control of many developmental processes in both vertebrates and invertebrates . One of these processes is the formation of the retina in the fruitfly Drosophila . Here , Hh orchestrates a differentiation wave that allows the fast and precise differentiation of the fly retina , by controlling cell cycle , fate and morphogenesis . In this work we identify the gene dachshund ( dac ) as necessary to potentiate Hh signaling . In its absence , all Hh-dependent processes are delayed and retinal differentiation is severely impaired . Using genetic analysis , we find that dac , a nuclear factor that can bind DNA , is required for the stabilization of the nuclear transducer of the Hh signal , the Gli transcription factor Ci . dac expression is activated by Hh signaling and therefore is a key element in a positive feedback loop within the Hh signaling pathway that ensures a fast and robust differentiation of the retina . The vertebrate dac homologues , the DACH1 and 2 genes , are also important developmental regulators and cancer genes and a potential link between DACH genes and the Hh pathway in vertebrates awaits investigation . | [
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"mela... | 2016 | dachshund Potentiates Hedgehog Signaling during Drosophila Retinogenesis |
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