Submitted 12 December 2018Accepted 18 March 2019Published 30 April 2019

Corresponding authorsYanhong Xiaoxiaoyh767nenueducnJiang Feng fengjnenueducn

Academic editorXavier Harrison

Additional Information andDeclarations can be found onpage 14

DOI 107717peerj6844

Copyright2019 Xiao et al

Distributed underCreative Commons CC-BY 40

OPEN ACCESS

Captivity causes taxonomic andfunctional convergence of gut microbialcommunities in batsYanhong Xiao1 Guohong Xiao1 Heng Liu1 Xin Zhao1 Congnan Sun1Xiao Tan1 Keping Sun1 Sen Liu2 and Jiang Feng13

1 Jilin Provincial Key Laboratory of Animal Resource Conservation and Utilization Northeast NormalUniversity Changchun Jilin China

2 Institute of Resources amp Environment Henan Polytechnic University Jiaozuo Henan China3College of Life Science Jilin Agricultural University Changchun Jilin ChinaThese authors contributed equally to this work

ABSTRACTBackground Diet plays a crucial role in sculpting microbial communities Similardiets appear to drive convergence of gut microbial communities between host speciesCaptivity usually provides an identical diet and environment to different animal speciesthat normally have similar diets Whether different speciesrsquo microbial gut communitiescan be homogenized by a uniform diet in captivity remains unclearMethods In this study we compared gut microbial communities of three insectivorousbat species (Rhinolophus ferrumequinumVespertilio sinensis andHipposideros armiger)in captivity and in the wild using 16S rDNA sequencing In captivity R ferrumequinumand V sinensis were fed yellow mealworms while H armiger was fed giant mealwormsto rule out the impact of an identical environment on the speciesrsquo gut microbialcommunitiesResults We found that the microbial communities of the bat species we studiedclustered by species in the wild while the microbial communities of R ferrumequinumand V sinensis in captivity clustered together All microbial functions found in captiveV sinensis were shared by R ferrumequinum Moreover the relative abundances of allmetabolism related KEGG pathways did not significantly differ between captive R fer-rumequinum and V sinensis however the relative abundance of lsquolsquoGlycan BiosynthesisandMetabolismrsquorsquo differed significantly between wild R ferrumequinum and V sinensisConclusion Our results suggest that consuming identical diets while in captivity tendsto homogenize the gut microbial communities among bat species This study furtherhighlights the importance of diet in shaping animal gut microbiotas

Subjects Ecology Microbiology ZoologyKeywords Diet Microbiome Convergence Bat

INTRODUCTIONTrillions of microorganisms reside in animal guts and these microorganisms constitutethe animalrsquos gut microbiota which is important for animal health (Flint et al 2012)Ley et al (2008a) found that animals who were closely related taxonomically had moresimilar gut microbial compositions Phylogenetic congruence of microflora communities

How to cite this article Xiao Y Xiao G Liu H Zhao X Sun C Tan X Sun K Liu S Feng J 2019 Captivity causes taxonomic and func-tional convergence of gut microbial communities in bats PeerJ 7e6844 httpdoiorg107717peerj6844

and their hosts was also observed among bat families (Ingala et al 2018 Phillips etal 2012) These studies indicated that host evolutionary history strongly impacts gutmicrobiome compositions Although gut microbial communities are host-specific theycan be influenced by the hostrsquos diet developing immune system chemical exposures andinitial colonizers (Donaldson Lee amp Mazmanian 2015) Diet has been suggested to have thegreatest impact on microbiota assembly (Donaldson Lee amp Mazmanian 2015) Diet shapesthe gut microbial community by providing substrates that differentially support or enhancethe growth of specific microbes (De Filippo et al 2010 Scott et al 2013Wang et al 2013)Taxonomic compositions of the gut microbial communities of different host species withsimilar diets appeared to converge in some studies (Carrillo-Araujo et al 2015 Delsuc etal 2014 Muegge et al 2011) Ley et al (2008a) also found that animals with similar diets(ie herbivores carnivores omnivores) had more similar gut microbiome compositions

Wild animals in captivity are usually housed under uniform conditions that includeidentical diets and environments (Hale et al 2018) This represents a rapid and dramaticdietary and environmental change to the animals The gut microbiome has been reportedto rapidly respond to an altered diet (David et al 2013) However whether differentspeciesrsquo gut microbiomes will respond similarly to the uniform conditions of captivityremains uncertain A study comparing the gut microbial diversity in two woodrat speciesin the wild and in captivity found that the microbial communities in these species did notconverge (Kohl Skopec amp Dearing 2014) Principal coordinate analysis results showed thatthe microbial signatures of the captive woodrats still clustered by species (Kohl Skopec ampDearing 2014) Woodrats are herbivores which represents only one mammalian dietarytype Carnivores represent another important dietary type of which insectivores arethought to represent the ancestral condition for placental mammals (OrsquoLeary et al 2013)However whether the taxonomic compositions of different insectivorous speciesrsquomicrobialgut communities tend to converge under identical dietary and environmental conditionsremains unclear In addition the two wood rat species that Kohl Skopec amp Dearing (2014)studied were closely related Given the phylogenetic distance among the hosts in the presentstudy it is unclear whether a homogenous dietenvironment or the hostrsquos evolutionaryhistory more strongly impacts the microbiome community composition

Bats (order Chiroptera) are the second largest mammalian group (Wilson amp Reeder2005) Most bats are insectivores which is also thought to be the ancestral condition forbats (Dawson amp Krishtalka 1984) To determine whether dietenvironment or evolutionarymore strongly impacts the microbiome we sampled feces (guano) from three bat speciesfrom three families (Rhinolophidae Vespertilionidae and Hipposideridae) the greaterhorseshoe bat (Rhinolophus ferrumequinum) the Asian parti-colored bat (Vespertiliosinensis) and the great Himalayan leaf-nosed bat (Hipposideros armiger) in the wild andin captivity We then compared the bacterial communities in both the wild and captivesamples between these three species We captured bats in the wild brought them back tothe laboratory and housed them in identical environments but provided different foodRhinolophus ferrumequinum and V sinensis were fed the same food (yellow mealworms)whileH armiger were provided giant mealworms thus forming a comparison to eliminatethe impact of environment on the gut microbiome Given that diet strongly influences

Xiao et al (2019) PeerJ DOI 107717peerj6844 220

Table 1 Summary of samples included in this study

Sampletype

Species Number Sex Age Weight(g meanplusmn SD)

Forearm length(mm meanplusmn SD)

Site

Wild R ferrumequinum 8 3M+5F Adults 1844plusmn 141 6055plusmn 092 JilinV sinensis 7 F Adults 2189plusmn 360 4944plusmn 212 HeilongjiangH armiger 8 M 1 Juvenile+ 7 Adults 6703plusmn 901 9582plusmn 258 Guizhou

Captive R ferrumequinum 10 1M+9F 6 Juveniles+ 4 Adults 2584plusmn 539 6083plusmn 135 JilinLiaoningShannxi

V sinensis 10 F Adults 2133plusmn 383 5087plusmn 121 HeilongjiangH armiger 10 8M+ 2F Adults 6912plusmn 808 9564plusmn 338 Shannxi

microbiome composition and similar diets appear to drive convergence of gut microbialcommunities between host species (Delsuc et al 2014 Muegge et al 2011) we predictedthat the gut microbiome compositions of captive R ferrumequinum and V sinensis underidentical environmental and dietary conditions would converge with each other but woulddiffer from captive H armiger In addition taxonomy and function are decoupled inmicrobial ecosystems (Graham et al 2016 Inkpen et al 2017 Louca Parfrey amp Doebeli2016) Microbial functions may converge despite the microbial communityrsquos taxonomiccompositions varying among host species (Phillips et al 2017) Thus microbial functionswere also predicted and compared among different bats species both in the wild and incaptivity to investigate whether the gut microbiome function converges in the captive bats

MATERIAL AND METHODSField sampling of batsAll three bat species are insectivores Rhinolophus ferrumequinum feeds preferentially onlepidopterans particularly the noctuid species which constitute approximately 41 of thebatrsquos diet (Jones 1990) The bats also eat coleopterans which constitute approximately 33of their diet of which dung beetles and cockchafers are often consumed (Jones 1990) Thedietary composition ofV sinensismainly comprises Lepidoptera (mean relative percentage328) Diptera (275) and Coleoptera (226) but the proportion of each order variesseasonally (Fukui amp Agetsuma 2010) H armigerrsquos diet mainly comprises 3159ndash3721Coleoptera and 1538ndash2287 Lepidoptera (Han amp He 2012)

Eight greater horseshoe bats seven Asian parti-colored bats and eight great leaf- nosedbats were collected from Jilin Heilongjiang and Guizhou China respectively during thesummer of 2018 Bats were collected from one group of each species Fecal samples werecollected from these bats in the field During the summer of 2017 we collected 10 greaterhorseshoe bats from three groups of which three bats were from Jilin one from Liaoningand six from Shannxi China Ten Asian parti-colored bats in one group and 10 great leaf-nosed bats in one group were collected fromHeilongjiang and Shannxi China respectivelyduring the summer of 2017 These bats were returned to the laboratory and different batspecies were housed in separate cages for 4ndash6 months before collecting their fecal samplesDetails on the bats collected are shown in Table 1

Xiao et al (2019) PeerJ DOI 107717peerj6844 320

Collection of fecal samplesFecal samples were used because dietary signals in the microbiome are more easily detectedin fecal samples than in intestinal samples (Ingala et al 2018) Bats were captured in thefield using mist nets placed at cave entrances immediately recovered from the nets andplaced in separate clean holding bags to await processing We recorded each batrsquos sex ageweight forearm length and reproductive condition (Table 1 and Data S1) Feces werecollected directly from the bottom of the holding bags and placed in sterile tubes usingsterile forceps then stored in dry ice before transport to the laboratory The bags werechecked frequently to ensure the samplesrsquofreshness In the laboratory the greater horseshoebats and the Asian parti-colored bats were fed yellow mealworms (Tenebrio molitor) whilethe great leaf-nosed bats were fed giant mealworms (Zophobas morio) for comparisonWe kept the bats for 4ndash6 months and collected their fecal pellets less than 15 min afterdefecationin the laboratory Each batrsquos sex age weight forearm length and reproductivecondition was recorded (Table 1 and Data S1) then the bats were placed in separate cleancages which were placed on sterile brown paper Feces were collected from the brownpaper and placed in sterile tubes then temporarily stored in liquid nitrogen The brownpaper was checked frequently to ensure the fecesrsquo freshness All samples were stored inminus80 C until DNA extraction

Sampling was conducted with permission from the local forestry department TheNational Animal Research Authority of Northeast Normal University China (approvalnumber NENU-20080416) and the Forestry Bureau of Jilin Province China (approvalnumber [2006]178) approved all study protocols

DNA extractionFifty-three fecal samples were used including 23 from the wild bats and 30 from thecaptive bats DNA was extracted from all fecal samples using the EZNA RcopyStool DNAKit (Omega Bio-Tek Inc Norcross GA USA) per the manufacturerrsquos instructions andstored at minus20 C for further analysis Extracted DNA was measured using a NanoDropNC2000 spectrophotometer (Thermo Fisher Scientific Waltham MA USA) and agarosegel electrophoresis to estimate DNA quantity and quality respectively

16S rDNA amplicon pyrosequencingThe V3-V4 region of the bacterial 16S rRNA genes were amplified via PCR using theforward primer 338F (5prime-ACTCCTACGGGAGGCAGCA-3prime) and the reverse primer806R (5prime-GGACTACHVGGGTWTCTAAT-3prime) (Dennis et al 2013) Sample-specific 7-bp barcodes were incorporated into the primers for multiplex sequencing The PCRcomponents contained 5 microl of Q5 reaction buffer (5times) 5 microl of Q5 High-Fidelity GCbuffer (5times) 2 microl of dNTPs (25 mM) 1 microl of each forward and reverse primer (10 microM)025 microl of Q5 High-Fidelity DNA polymerase (5 Umicrol) 2 microl of DNA template and 875microl of ddH2O The PCR conditions consisted of initial denaturation at 98 C for 2 minfollowed by 25 denaturation cycles at 98 C for 15 s annealing at 55 C for 30 s extensionat 72 C for 30 s and a final extension at 72 C for 5 min PCR products were purifiedwith Agencourt AMPure Beads (Beckman Coulter Indianapolis IN USA) and quantified

Xiao et al (2019) PeerJ DOI 107717peerj6844 420

using the PicoGreen dsDNA Assay Kit (Invitrogen Carlsbad CA USA) The individualPCR products were then pooled in equal amount and sequenced using the paired-end2times300 bp method on the Illumina MiSeq platform with MiSeq Reagent Kit v3 at ShanghaiPersonal Biotechnology Co Ltd (Shanghai China) All raw sequences were deposited intothe NCBI Sequence Read Archive under accession numbers SRR8238420ndashSRR8238472

Sequence analysisSequencing data were processed using the Quantitative Insights Into Microbial Ecology(QIIME v180) (Caporaso et al 2010) Briefly raw sequences with unique barcodes wereassigned to respective samples Sequences shorter than 150 bp having average Phredscores of lt20 containing ambiguous bases or sequences containing more than 8-bpmononucleotide repeats were regarded as low-quality sequences and removed (Chen ampJiang 2014 Gill et al 2006) Paired-end reads were assembled using FLASH (Magoč ampSalzberg 2011) Assembled sequences were trimmed of barcodes and sequencing primersAfter chimera detection the remaining trimmed and assembled sequences were clusteredinto operational taxonomic units (OTUs) at 97 sequence identity using UCLUST (Edgar2010) A representative sequence was selected from each OTU using default parametersRepresentative sequences were aligned to the Greengenes Database (DeSantis et al 2006)using the best hit (Altschul et al 1997) to classify the taxonomy which was conductedusing BLAST An OTU table was then generated to record each OTUrsquos abundance persample and the OTUrsquos taxonomy OTUs containing less than 0001 of the total sequencesacross all samples were discarded To minimize the differences in sequencing depth acrosssamples an averaged rounded rarefied OTU table was generated by averaging 100 evenlyresampled OTU subsets under 90 of the minimum sequencing depth for further analysis

Bioinformatics and statistical analysisSequence data were mainly analyzed using QIIME v180 and R v320 Beta diversity wasanalyzed to investigate the microbial communitiesrsquo structural variation across samplesusing UniFrac distance metrics (Lozupone amp Knight 2005 Lozupone et al 2007) andvisualized via principal coordinate analysis (PCoA) and nonmetric multidimensionalscaling (NMDS) (Ramette 2007) UniFrac is the only distance metric that considers thephylogenetic relationships between microorganisms and UniFrac-based beta diversity hasbecome a standard analytic method in microbiome studies Therefore we also chose theUniFrac distance to characterize the community structure in our study Differences in theUniFrac distances for pairwise comparisons among groupswere determined using Studentrsquost -test and the Monte Carlo permutation test with 1000 permutations then visualizedusing box-and-whiskers plots For UniFrac distance-based pairwise comparisons amonggroups we used a very conservative Bonferroni post-hoc correction method to performthe multiple corrections and evaluate the significance of the comparison Permutationalmultivariate analysis of variance (PERMANOVA) (McArdle amp Anderson 2001) and analysisof similarities (ANOSIM) (Clarke 1993 Warton Wright amp Wang 2012) were conductedusing the R package lsquolsquoveganrsquorsquo (v16-9) (Oksanen et al 2005) to assess the significanceof the differentiation of the microbiota structures among groups A Venn diagram was

Xiao et al (2019) PeerJ DOI 107717peerj6844 520

generated to visualize the shared and unique OTUs among groups using the R packagelsquolsquoVennDiagramrsquorsquo (v24-6) (Chen amp Boutros 2011) based on the occurrence of OTUs acrossgroups regardless of their relative abundance (Zaura et al 2009) Microbial functionswere predicted using Phylogenetic Investigation of communities by Reconstruction ofUnobserved States (PICRUSt v100) (Langille et al 2013) in the Kyoto Encyclopediaof Genes and Genomes (KEGG) database (Kanehisa et al 2004) based on high-qualitysequences The relative abundances of predicted functions in each sample were calculatedbased on the abundance matrix obtained via PICRUSt and significant differences ineach functionrsquos relative abundances among different species were tested using analysisof variance (ANOVA) or the KruskalndashWallis test (Wallis 1952) Results were consideredsignificant at p lt 005

RESULTSSequencing resultsA total of 768990 and 1466150 16S rDNA sequences were obtained from themicrobiomesof the 23 wild and 30 captive bats respectively and the average sequence numbers persample were 33434 and 48872 respectively Rarefaction analysis demonstrated that thesequencing depth was sufficient for each sample (Fig S1) A total of 3504 and 7057 OTUswere recovered at the similarity clustering threshold of 97

Shared microbial species were increased in captive batsVenn diagramswere plotted to visualize the shared and uniqueOTUs (roughly equivalent tobacterial species) among three species of wild and captive bats The captive bats we sampledshared more OTUs than did the wild bats (Fig 1) A total of 2022 OTUs (approximately29 of the total OTUs) were shared by the three species in captivity but only 228 OTUs(approximately 7 of the total OTUs) were shared by the wild bats Approximately 71 ofthe OTUs from captive V sinensis and R ferrumequinum were shared but only 18 wereshared by these two species in the wild The proportions of OTUs shared by V sinensisand H armiger were approximately 39 and 12 in captivity and the wild respectivelyMinimal difference was noted between the proportions of shared OTUs in the captive andwild R ferrumequinum and H armiger of which the proportions were nearly 36 and29 respectively

Microbial compositions converged in captive bats fed the same foodA NMDS based on unweighted beta diversity values indicated that the gut microbialcommunities in the wild bat were clustered strongly by bat species (Fig 2A) Howeverthe gut microbial community clustering was altered in the captive bats (Fig 2B) In thecaptive bats the gut microbial communities of the bats fed the same food (ie V sinensisand R ferrumequinum fed yellow mealworms) clustered together while the gut microbialcommunities of H armiger fed giant mealworms clustered alone A PCoA based onunweighted UniFrac distances also demonstrated similar clustering results using NMDSbased on unweighted UniFrac distances In the wild bats PC1 PC2 and PC3 accounted fornearly 42 of the variation and samples were separated roughly by bat species (Fig S2A)

Xiao et al (2019) PeerJ DOI 107717peerj6844 620

Figure 1 Venn diagram of shared and unique OTUs in the fecal bacterial communities of three batspecies (A) Wild batsrsquo fecal samples (B) Captive batsrsquo fecal samples WFVs WFRf and WFHa representfecal samples from V sinensis R ferrumequinum and H armiger collected from the wild respectively FVsFRf and FHa represent fecal samples from captive V sinensis R ferrumequinum and H armiger respec-tively

Full-size DOI 107717peerj6844fig-1

In the captive bats PC1 PC2 and PC3 accounted for 48 of the variation in microbialcomposition (Fig S2B)

Analyzing the differences in the UniFrac distances for pairwise comparisons amonggroups revealed that the differences between each pair group were significant in the wildsamples (Fig S3A Table 2) while the differences betweenV sinensis and R ferrumequinumwere not significant in the captive samples (p = 0381 and 0085) (Fig S3B Table 2)However the differences between H armiger and the other two species were all significantin the captive samples (Fig S3B Table 2) Statistical analyses of the significance of thedifferentiation in the microbiota structure among the groups also yielded similar resultsThe differences among groups were significant both for the wild and the captive bats(all ple 0001 Table 3) However PERMANOVA and ANOSIM analyses cannot assessthe significance of the differentiation between pairwise groups when more than twogroups are analyzed Thus we did not find that the differences between V sinensis andR ferrumequinum were not significant in the captive samples based on the PERMANOVAand ANOSIM analysis results

Convergence of microbial function in captive bats fed the same foodFinally we predicted the microbial functions of wild and captive bats using PICRUStwhich yielded 5971 and 4771 KEGG pathways respectively Venn diagrams showed thatin total 5495 KEGG pathways were shared among the wild bat samples and 3964 wereshared among the captive bat samples (Fig 3) Unlike the wild bats one hundred percentof the microbial functions in captive H armiger were shared by the other two species andall microbial functions in captive V sinensis were shared by R ferrumequinum Thus interms of presenceabsence the microbial functions appeared converged in the captive bats

Xiao et al (2019) PeerJ DOI 107717peerj6844 720

Figure 2 Wild and captive batsrsquo fecal bacterial communities clustered using nonmetric multidimen-sional scaling analysis of the unweighted UniFrac distance matrixWild (A) and captive (B) batsrsquo fe-cal bacterial communities clustered using nonmetric multidimensional scaling analysis Each point cor-responds to a fecal sample colored according to bat species with different symbols corresponding to hostfamily (red circle Hipposideridae green square Vespertilionidae blue triangle Rhinolophidae)

Full-size DOI 107717peerj6844fig-2

Xiao et al (2019) PeerJ DOI 107717peerj6844 820

Table 2 Results of Studentrsquos t -test and theMonte Carlo permutation test of differences in the UniFracdistances for pairwise comparisons among groups

Group 1 Group 2 t statistic p-valuea

Wild All within Group All between Group minus17881 0000

WFVs vs WFVs WFVs vs WFRf minus16090 0000

WFVs vs WFVs WFVs vs WFHa minus22230 0000

WFRf vs WFRf WFVs vs WFRf minus8363 0000

WFRf vs WFRf WFRf vs WFHa minus7793 0000

WFHa vs WFHa WFVs vs WFHa minus12663 0000

WFHa vs WFHa WFRf vs WFHa minus8920 0000

Captive All within Group All between Group minus19425 0000

FVs vs FVs FVs vs FRf minus2499 0381FVs vs FVs FVs vs FHa minus15337 0000

FRf vs FRf FVs vs FRf minus3014 0085FRf vs FRf FHa vs FRf minus15644 0000

FHa vs FHa FVs vs FHa minus48674 0000

FHa vs FHa FHa vs FRf minus58733 0000

Notesap-value was corrected by Bonferroni method

p-value le 0001

Table 3 Statistical analyses accessing significance of differentiation of microbiota structure amonggroups

Results of PERMANOVA analysis

Df Sums of Sqs F Model r2 p-value

Wild 2 2139 4565 0313 0001

Captive 2 2656 8320 0381 0001

Results of ANOSIM analysis

R statistic p-value Number ofpermutationos

Wild 0873 0001 999Captive 0803 0001 999

Notesp-value le 0001

Moreover in terms of the relative abundance of functions we found that the relativeabundances of all metabolism-related KEGG pathways did not significantly differ betweencaptive R ferrumequinum and V sinensis while the relative abundance of lsquolsquoGlycanBiosynthesis andMetabolismrsquorsquo differed significantly between thewildR ferrumequinum andV sinensis (Fig 4) In addition except lsquolsquoGlycan Biosynthesis and Metabolismrsquorsquo lsquolsquoEnzymeFamiliesrsquorsquo and lsquolsquoBiosynthesis of Other Secondary Metabolitesrsquorsquo no significant differenceswere found in the relative abundances of any other metabolic pathways among the threebat species in the wild (Fig 4A) while the relative abundances of all metabolism-relatedKEGG pathways except lsquolsquoMetabolism of Cofactors and Vitaminsrsquorsquo lsquolsquoLipid Metabolismrsquorsquoand lsquolsquoCarbohydrate Metabolismrsquorsquo differed significantly between captiveH armiger and the

Xiao et al (2019) PeerJ DOI 107717peerj6844 920

Figure 3 Venn diagram of shared and unique microbial functions in three bats species (A) Wild bats(B) Captive bats WFVs WFRf WFHa FVs FRf and FHa are defined in the legend of Fig 1

Full-size DOI 107717peerj6844fig-3

other two bat species (Fig 4B) This result indicated that the microbial functions convergein the captive bats fed the same food in terms of the relative abundance of functions

DISCUSSIONIn this study we investigated the influence of identical diets under laboratory conditionson the gut microbial communities of three insectivorous bat species Feces are sampled asa proxy for the gut microbiome in many studies of wild mammal microbiomes (Hale et al2018 Kohl Skopec amp Dearing 2014 Phillips et al 2017 Sommer et al 2016) Moreovermore signals from the hostrsquos diet are retained in fecal samples than in intestinal samples(Ingala et al 2018) Thus in our study we compared the microbial communities fromfecal samples of three captive bat species as well as the fecal microbial communities of theirconspecific bats in the wild The microbiome compositions of the bats in our study weremainly composed of Proteobacteria and Firmicutes which occupied more than 80 of themicrobiome (Figs S4 and S5) This was consistent with previous work on bat microbiomes(Carrillo-Araujo et al 2015 Ingala et al 2018 Phillips et al 2017 Phillips et al 2012)

Comparing the microbial communities of fecal samples from three bat species inthe wild revealed that the microbial signatures of R ferrumequinum V sinensis andH armiger in the wild cluster by species when measured by principal coordinate analysisMicroflora communities of wildlife species are shaped by complex processes includinghost phylogeny dietary strategy and reproductive conditions (Phillips et al 2012) ThoughR ferrumequinum V sinensis and H armiger are all insectivores wild bat diets are variedspecies-specific and belong to different bat families Thus taxonomic compositions of gutmicrobial communities differ among bat species in the wild Our result was consistent withthe study of Phillips et al (2017)

Xiao et al (2019) PeerJ DOI 107717peerj6844 1020

Figure 4 The relative abundance of microbial functions related to metabolism predicted by PICRUSt(A)Wild bats (B) Captive bats WFVs WFRf WFHa FVs FRf and FHa are defined in the legend of Fig 1Different letters in each KEGG pathway indicate significant differences (plt 005) in the relative abun-dances of this function in different bats species

Full-size DOI 107717peerj6844fig-4

Xiao et al (2019) PeerJ DOI 107717peerj6844 1120

Comparing the microbial communities in fecal samples from three captive batsspecies showed that the microbial compositions of two bat species (R ferrumequinumand V sinensis) fed the same food converged markedly while they differed from thoseof H armiger fed different food This result highlighted the importance of diet on gutmicrobial communities Diet shapes the gut microbiota by providing substrates thatdifferentially support or enhance specific microbial growth (De Filippo et al 2010 Scottet al 2013 Wang et al 2013) The gut microbiota can in turn enable their host to adaptto new dietary niches (Ley et al 2008a) In this study captive bats were fed mealwormswhich is a novel and high-quality diet for the previously wild bats Long-term dietary intakeinfluences the structure and activity of gut microbiota (Duncan et al 2007 Ley et al 2006Muegge et al 2011 Walker et al 2010 Wu et al 2011) After 4ndash6 monthsrsquo feeding in thelaboratory the batsrsquo gut microbiotas should have adapted to the new diet Feeding the batsthe same food means that same substrates are provided to the gut microbiota thus the gutmicrobial signatures of captive R ferrumequinum and V sinensis should cluster togetherSimilar results were obtained in a study comparing the gut microbiotas of captive colobinemonkeys This study found that the gut microbial communities were more similar in thecolobine species who consumed the same diet (Hale et al 2018) In contrast captive Harmiger were fed a different diet (giant mealworms) than were R ferrumequinum and Vsinensis and the gutmicrobial communities of captiveH armiger did not converge with theother two bat species This result eliminated the impact of environment on the gutmicrobialcommunities because the three bat species were housed in identical environments in thelaboratory Further this suggested that identical diets contribute to microbial communityconvergence in various bat species However fecal samples usually include bacteria that areingested with the food (eg the commensal bacteria in the mealworms) and distinguishingthese bacteria from the host-derived bacteria in the fecal microbiome is difficult Thusthe gut microbiota in this study did not specifically refer to the host-derived bacteria Themicrobial community compositions between species fed uniform diets may have convergeddue to changes in the compositions of the host-associated gut microbiome or a much largershared component of the fecal microbiome based on a completely shared diet comprisingmealworms and their commensal bacteria or both Our results highlight the need forfuture studies to address this issue for example incorporating dietary classifications viametabarcoding and classifying the microbiomes of the invertebrate prey In additionour results differed from those obtained by Kohl Skopec amp Dearing (2014) whose resultssuggested thatmicrobial communities of various woodrat species clustered by species ratherthan converged together after being exposed to similar diets The bat species in our studywere insectivores while the woodrat species in the work of Kohl Skopec amp Dearing (2014)were herbivores Herbivorous digestive systems contain multiple enzymes originatingfrom different microbial species needed to process (hemi)celluloses lignin-derivatives andinsoluble starches thus supporting a highly diverse ecosystem (Karasov Martiacutenezdel Rio ampCaviedes-Vidal 2011) Moreover bacterial diversity increases as the host diet diverges fromcarnivorous to omnivorous to herbivorous in mammalian guts (Ley et al 2008b) Thuswe hypothesize that the higher bacterial diversity in herbivorous mammals allows themto retain more species-specific microbial communities in captivity than do mammals that

Xiao et al (2019) PeerJ DOI 107717peerj6844 1220

eat animal-based diets In addition more unique bacteria make it difficult for microbialcommunities of different herbivorous species to cluster together although they have similardiets Kohl et alrsquos (2014) indicating that 64 and 51 of OTUs were retained in the twocaptive woodrat species studied may support our hypothesis Another possible explanationfor the differences between the bats in this study and the woodrats in Kohl et alrsquos study(2014) may be that the difference between the diets of captive bats and those in natureis larger than that of the woodrats In xenarthrans (anteaters sloths and armadillos)especially myrmecophagous mammals (ie mammals that eat termites and ants) the effectof captivity on their gut microbiomes is especially noticeable in animals whose diets differmarkedly in captivity and in nature (Superina 2011)

The divergence or convergence of microbial community compositions differs fromthe divergence or convergence of their microbial functions Different combinations ofmicrobial lineages may achieve comparable community functions meaning that microbialcommunities may differ in taxonomic composition but be similar in function (Phillips etal 2017) In terms of their presenceabsence the unique microbial functions of the batswe studied were lost when the bats were taken from the wild into captivity especiallyin H armiger and V sinensis This may be due to the lack of a different environmentor similar nutrient compositions in the mealworm larvae (Rumpold amp Schluumlter 2013)provided as food in the laboratory However in terms of the function frequency wefound that the relative abundances of most metabolic functions were similar although themicrobial community compositions differed among the three bat species in the wild Thisfinding was similar to that of Phillips et al (2017) and supports the hypothesis of functionalredundancy in the gut ecosystem which is defined as functions conferred by multiplebacteria that can be shared across both related and unrelated bacterial species (Moya ampFerrer 2016) That is although themicrobial composition varies differentmicrobiotasmayperform similar functions (Peacuterez-Cobas et al 2013) Comparing the relative abundances ofmetabolic functions among the three bat species in captivity the relative abundances ofmostmetabolic functions were similar between R ferrumequinum and V sinensis but differedin H armiger Combining the result that the microbial compositions of R ferrumequinumand V sinensis converged together but diverged from H armiger we inferred that thedifferent foods led to metabolic tuning of microbial functions and the identical diets whichin captivity led to the convergence of bothmicrobial compositions andmicrobial functions

Unexpectedly the number of OTUs found in the batsrsquo fecal samples was increased inthe captive bats compared with those in the wild In other words the gut microbiota wasmore diverse in the captive bats than in the wild bats This was surprising because thenumber of OTUs in the gut microbiome was expected to have been greatly decreased dueto the single-food-source diet and captive conditions This observation also contradictedthe findings of previous studies on the influence of captivity on the animal microbialcommunities which found that bringing animals into captivity resulted in a loss ofmicrobial diversity (Redford et al 2012 Kohl Skopec amp Dearing 2014 Kueneman et al2016) Several points may explain this First the bat species may have been exposed toeach otherrsquos microbes due to their being in captivity in the same laboratory thus theoverall community became more diverse because microbes were shared among species

Xiao et al (2019) PeerJ DOI 107717peerj6844 1320

Second the bacteria ingested with the mealworms may have increased the diversity of thecaptive batsrsquo gut microbial communities Although the microbial diversity was increasedin the captive bats the microbial function types were decreased in our study indicatingthat selection by host diet primarily acts on metagenomic functions Further research isrequired to investigate the possible reasons for this

CONCLUSIONSComparing the results from PCoA and NMDS analyses between wild and captive batssuggests that the identical diets that were provided in captivity contributed to the taxonomyconvergence of the gut microbial communities of R ferrumequinum and V sinensis Inaddition in terms of functional level the identical diets while in captivity yielded moresimilar relative abundances of metabolic functions in the gut microbiomes of captive Rferrumequinum and V sinensis than in the wild bats indicating that the identical diet whilein captivity contributed to the convergence of the gut microbial community functionsFinally the gut microbial diversity was surprisingly higher in the captive bats than in thewild bats However understanding why this phenomenon occurred requires further studyThis study highlights the dietrsquos crucial role in shaping captive bat gut microbiotas

ACKNOWLEDGEMENTSWe are grateful to Lixin Gong Biye Shi Zhongwei Yin and Chuantao Song for theirgreat contributions to samples collection Sequencing service was provided by PersonalBiotechnology Co Ltd Shanghai China We thank Traci Raley MS ELS from LiwenBianji Edanz Editing China for editing a draft of this manuscript

ADDITIONAL INFORMATION AND DECLARATIONS

FundingThis work was supported by the National Natural Science Foundation of China (Grant No31700319 31870354) Fundamental Research Funds for the Central Universities (GrantNo 2412017QD026) and Project funded by China Postdoctoral Science Foundation (GrantNo 2018M631852) The funders had no role in study design data collection and analysisdecision to publish or preparation of the manuscript

Grant DisclosuresThe following grant information was disclosed by the authorsNational Natural Science Foundation of China 31700319 31870354Fundamental Research Funds for the Central Universities 2412017QD026China Postdoctoral Science Foundation 2018M631852

Competing InterestsThe authors declare there are no competing interests

Xiao et al (2019) PeerJ DOI 107717peerj6844 1420

Author Contributionsbull Yanhong Xiao conceived and designed the experiments performed the experimentsanalyzed the data prepared figures andor tables authored or reviewed drafts of thepaper approved the final draftbull Guohong Xiao performed the experiments prepared figures andor tables approved thefinal draftbull Heng Liu Xin Zhao Congnan Sun and Xiao Tan performed the experiments approvedthe final draftbull Keping Sun authored or reviewed drafts of the paper approved the final draftbull Sen Liu performed the experiments approved the final draftbull Jiang Feng conceived and designed the experiments contributed reagentsmaterials-analysis tools authored or reviewed drafts of the paper approved the final draft

Animal EthicsThe following information was supplied relating to ethical approvals (ie approving bodyand any reference numbers)

All research carried out in this study was approved by the National Animal ResearchAuthority of Northeast Normal University China (NENU-20080416)

Field Study PermissionsThe following information was supplied relating to field study approvals (ie approvingbody and any reference numbers)

Sampling was conducted with the permission of the Forestry Bureau of Jilin Province ofChina

DNA DepositionThe following information was supplied regarding the deposition of DNA sequences

All raw sequences were deposited in the NCBI Sequence Read Archive under accessionnumber SRR8238420ndashSRR8238472

Data AvailabilityThe following information was supplied regarding data availability

All raw sequences are available in Files S9ndashS109

Supplemental InformationSupplemental information for this article can be found online at httpdxdoiorg107717peerj6844supplemental-information

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