microorganisms Article Comparative Analysis of Fecal Microbiota in Grasscutter (Thryonomys swinderianus) and Other Herbivorous Livestock in Ghana Kiyonori Kawasaki 1,† , Kenji Ohya 2,3,† , Tsutomu Omatsu 4, Yukie Katayama 4, Yasuhiro Takashima 2,3,5, Tsuyoshi Kinoshita 1, Justice Opare Odoi 3, Kotaro Sawai 2 , Hideto Fukushi 2,3, Hirohito Ogawa 6 , Miho Inoue-Murayama 7,8, Tetsuya Mizutani 4, Christopher Adenyo 9, Yoshiki Matsumoto 1,* and Boniface Kayang 10,* 1 Faculty of Agriculture, Kagawa University, Kagawa 761-0795, Japan; kkawasaki@ag.kagawa-u.ac.jp (K.K.); s17g602@stu.kagawa-u.ac.jp (T.K.) 2 Faculty of Applied Biological Sciences, Gifu University, Gifu 501-1112, Japan; kenji.ohya@kkd.biglobe.ne.jp (K.O.); atakashi@gifu-u.ac.jp (Y.T.); sawaik107@affrc.go.jp (K.S.); hfukushi@gifu-u.ac.jp (H.F.) 3 Graduate School of Veterinary Sciences, Gifu University, Gifu 501-1112, Japan; wentworthprince@yahoo.com 4 Faculty of Agriculture, Research and Education Center for Prevention of Global Infectious Diseases of Animals, Tokyo University of Agriculture and Technology, Tokyo 183-8538, Japan; tomatsu@cc.tuat.ac.jp (T.O.); katayam07@yahoo.co.jp (Y.K.); tmizutan@cc.tuat.ac.jp (T.M.) 5 Center for Highly Advanced Integration of Nano and Life Sciences, Gifu University (G-CHAIN), Gifu 501-1193, Japan 6 Dentistry and Pharmaceutical Sciences, Graduate School of Medicine, Okayama University, Okayama 700-0914, Japan; hogawa@okayama-u.ac.jp 7 Wildlife Research Center, Kyoto University, Kyoto 606-8203, Japan; mmurayama@wrc.kyoto-u.ac.jp 8 Wildlife Genome Collaborative Research Group, National Institute of Environmental Studies, Tsukuba 305-8506, Japan 9 Livestock and Poultry Research Centre, College of Basic and Applied Sciences, University of Ghana, Accra P.O. Box LG 38, Ghana; adenyo.chris@gmail.com 10 Department of Animal Science, College of Basic and Applied Sciences, University of Ghana, Accra P.O. Box LG 226, Ghana * Correspondence: myoshiki@ag.kagawa-u.ac.jp (Y.M.); bbkayang@hotmail.com (B.K.); Tel.: +81-87-891-3057 (Y.M.) † These authors contributed equally to this work. Received: 27 January 2020; Accepted: 13 February 2020; Published: 15 February 2020 Abstract: The grasscutter (also known as the greater cane rat; Thryonomys swinderianus) is a large rodent native to West Africa that is currently under domestication process for meat production. However, little is known about the physiology of this species. In the present study, aiming to provide information about gut microbiota of the grasscutter and better understand its physiology, we investigated the intestinal microbiota of grasscutters and compared it with that of other livestock (cattle, goat, rabbit, and sheep) using 16S rRNA metagenomics analysis. Similar to the other herbivorous animals, bacteria classified as Bacteroidales, Clostridiales, Ruminococcaceae, and Lachnospiraceae were abundant in the microbiome of grasscutters. However, Prevotella and Treponema bacteria, which have fiber fermentation ability, were especially abundant in grasscutters, where the relative abundance of these genera was higher than that in the other animals. The presence of these genera might confer grasscutters the ability to easily breakdown dietary fibers. Diets for grasscutters should be made from ingredients not consumed by humans to avoid competition for resources and the ability to digest fibers may allow the use of fiber-rich feed materials not used by humans. Our findings serve as reference and support future studies on changes in the gut microbiota of the grasscutter as domestication progresses in order to establish appropriate feeding methods and captivity conditions. Microorganisms 2020, 8, 265; doi:10.3390/microorganisms8020265 www.mdpi.com/journal/microorganisms Microorganisms 2020, 8, 265 2 of 11 Keywords: cattle; goat; grasscutter; rabbit; sheep; microbiome; Prevotella; Treponema 1. Introduction The human population has grown by 30% in recent decades in Ghana [1], where food supply balance has been unstable, particularly in the northern area, causing severe malnutrition [2]. In order to solve food problems, it is essential to secure not only grain but also animal protein sources [2]. In the northern area of Ghana, the hunting of wild animals is the main source of protein [3], which has a serious impact on ecosystems and raises concern about the risk of zoonotic infections. Therefore, it is urgent to secure a sustainable protein source to replace wild animals [4], but it is difficult to breed large livestock (e.g., bovine or swine) or fish in the northern area, where climatic conditions are harsh. Moreover, conventional livestock (e.g., cattle, pig, and chicken) consumes large amounts of grains and, thus, compete with humans for grain crops [5]. The domestication of animals that can be raised on feed that are not consumed by humans stands as an attractive alternative. Currently, there is an on-going project in northwestern Ghana aiming to enhance the domestication of a large rodent native to West Africa called grasscutter (Thryonomys swinderianus, also known as the greater cane rat), whose meat is a delicacy for people in West Africa [6]. As part of this project, we developed DNA markers to support the genetic management of the grasscutter in Ghana [7]. Still, there is limited information on grasscutter physiology. Growing evidence indicates a close relationship between nutrient utilization and gut microbiome communities in various animals [8–11]. For example, herbivorous small hindgut fermenters get short-chain fatty acids from the bacterial fermentation of fiber carbohydrates in the cecum and essential amino acids from microbial proteins through cecotrophy [12–15]. Since the grasscutter is a herbivorous small hindgut fermenter, microorganisms living in its cecum are expected to play an important role in its digestive physiology. Moreover, the carbohydrate fermentation ability of microbiota in captive animals with unnatural feeding habits is inferior to that of wild animals [9]. Therefore, assessing the microbiota of grasscutters may help to determine the appropriate feed materials and composition for promoting domestication of grasscutters. Moreover, gut microbiota of livestock is being profiled all over the world, and the interplay between health condition or growth performance of livestock and their gut microbiota is gradually becoming clearer. However, grasscutters are still in the process of being domesticated, and there is no data on their gut microbiota. Thus, in the present study, to form a better view of the grasscutter gut microbiome, we investigated the microbiota of grasscutters using 16S rRNA metagenomics analysis and compared it to that of conventional livestock animals. 2. Materials and Methods 2.1. Animals and Sample Collection This research was conducted with the approval of the Gifu University animal experiment committee (Approval number: 17070; approval date: 2017.7.3) and the College of Basic and Applied Sciences Directorate (approval number was not assigned). We collected feces from 5 grasscutters and 16 livestock animals (cattle, Bos indicus: Sanga; goat, Capra hircus: the West-African Dwarf; rabbit, Oryctolagus cuniculus: the New Zealand white × California White; and sheep, Ovis aries: the Nungua Black Head; n = 4 for each species) in September 2016, 2017, and 2018 in Ghana (Figure 1). Grasscutters were purchased at the Kantamanto bushmeat market in the city of Accra, Ghana. Animals traded at the bushmeat market are hunted and brought from a wide geographical area in the coastal zone of Ghana, so their exact location is unknown. The other samples were obtained from livestock reared at the Livestock and Poultry Research Centre, University of Ghana (5◦40′28” N, 0◦6′5” W; Greater Accra; 15 km north of Accra). Feces were stored on ice, and fecal DNA extraction was conducted within 1 h after sampling. Microorganisms 2019, 7, x FOR PEER REVIEW 3 of 12 the Livestock and Poultry Research Centre, University of Ghana (5°40′28” N, 0°6′5” W; Greater Accra; 15 km north of Accra). Feces were stored on ice, and fecal DNA extraction was conducted within 1 h after sampling. 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Ananlaylsyisiso fofF Feceacal lM Micicrroobbiioottaa bby 16S rRNA Meettaaggeennoommicicss SSeqequuenencicnign g DDNNAAw wasase xextrtaraccteteddf frroom ffeecceess ussiingg IISSOFFEECCAALL fofor rbbeaedasd bsebaetaintign (gN(iNppipopno GneGnee,n Teo,kTyook,y Joap, Jaanp) an) acaccocrodridnigngto toth tehem maannuufafacctuturreerr’’ss iinnssttrruuccttiioonnss.. TThhee VV33-V-V44 hhyypperevravraiaribalbe lreergeiognio onf obfabctaecrtiearl i1a6lS1 6rRSNrRAN A gegneensews wasasa mampplilfiifeidedu usisninggt htheeu unniivveerrssaall pprriimmeerrss 334411FF ((55′-′C-CCCTTAACCGGGGGGNNGGGGCWCWGCGACGA-G3′-)3 a′n) da n8d058R0 5R (5′(-5G′-GAACCTATACCHHVVGGGGGGTTAATTCCTTAAAATTCCCC--33′)) [[1166]].. TThhe ePPCCRR reraecatciotino nmmixtiuxtrue rwe aws acsomcopmospeods eodf 1o0f 1µ0Mµ M fofrowrwaradrdp rpirmimere,r,1 100µ µMMr reevveerrssee pprriimmeerr,, 22×× pprreemmixix EExx TTaaqq HHSS (T(Taakkaraar aBiBoi,o S,hSihgaig, aJa, pJaapn)a,n a)n, da ntdhet he exetxratrcatcetdedfe fceaclaDl DNNAAt etemmpplalattee.. TThhee fifirrsstt PPCCRR ccoonnddititioionnss wweerer:e i:niintiiatila dledneantuatruatriaotnio ant 9a4t 9°C4 ◦fCor f3o rm3inm, in, foflloollwowededb yby2 525c yccylcelseso of f9 944◦ °CCf foorr 3300 ss,, 5555 °◦CC ffoorr 3300 ss, ,7722 °◦CC fofor r303 0s,s a,nadn da fainfianl aelxetexntesniosnio sntespt eapt 7a2t °7C2 ◦C for 10 min. The second PCR conditions for index attachment were: initial denaturation at 98 °C for 30 for 10 min. The second PCR conditions for index attachment were: initial denaturation at 98 ◦C for s, followed by 8 cycles of 98 °C f◦or 30 s, 60 °C fo◦r 30 s, 72 °C for◦ 30 s, and a final extension step at 72 30 s, followed by 8 cycles of 98 C for 30 s, 60 C for 30 s, 72 C for 30 s, and a final extension step °C f◦or 5 min. The amplicons were purified using AMPure XP beads (Beckman Coulter, Brea, CA, atU7S2A)C. fPoarir5edm-einnd. Tsheqeuaemncpinligc oonfs awlle rleibpraurrieifis ewdauss ipnegrfAorMmPedu reonX Panb eIalldusm(iBneac kMmiSaenq Csoeuqulteenr,ceBrr ea, CA(Il,luUmSAin)a., PSaainr eDdi-eegnod, CsAeq, uUeSnAc)i nugsinogf aal lMliiSberqar Rieesagweanst kpiet rvf3o r(m60e0d cyocnleas;n IlIllulumminian)a acMcoiSrdeqingse tqou tehne cer (Ilmluamnuinfaac, tSuarenr’Ds iiengsotr,uCctAio,nUs.S AO)peursaitniognaal MtaixSoenqoRmeiacg uennitt k(iOt TvU3 )( 6i0d0enctyifcilceast;ioInll uamndin ap)hyalcocgoerndeintigc to thcelamssainfiucafaticotnu rwere’rsei npsetrrfuocrtmioends .uOsipnegr aQtiIoInMaEl tavx2o.0n o[1m7]i.c uThneit (dOatTaUba)sied efnorti fitacxaotinoonmainc dapsshigynlomgeennte tic cla(isdsiefinctaittyio 9n9%w)e rweapse Grfroeremngedenuessi n(1g3_Q8I IrMeleEavse2). 0a[tt1a7c]h. eTdh etod paitpaeblainsee fQorIItMaxEo fnoorm micicarossbiigonmmee annta(liydseins,t ity 99a%n)d walal seGqurenencegse noets ju(1d3g_e8d raesl cehaisme)eraat twacehre dexttoracptiepde alinnde uQseIIdM foEr sfuorbsmeqiucreonbt iaonmaleysains.a Nlyuscilse,oatindde all sesqeuqeunecnecsen doattjau rdegpeodrtaesdc ahriem aevrailwabelre ienx thraec DteDdBaJn ddautasbeadsefos rusnudbesre tqhuee anctcaenssailoyns insu. mNubecrle DotRidAe0s0e9q4u68e.n ce data reported are available in the DDBJ databases under the accession number DRA009468. 2.3. Statistical Analysis 2.3. Statistical Analysis Alpha diversity (Chao1 and Shannon indices) of fecal microbiota was calculated using QIIME v2.0A [lp17h]a adnidv esrtastiitsyti(cCalhlya oa1nalnydzeSdh uasninogn oinned-wicaeys )aonfaflyecsiasl omf ivcaroribainoctea (wAaNsOcValAcu).l aFtoerd βu-dsinvegrsQitIyIM, E v2u.0nw[1e7i]ghatned satnadti swtieciaglhlyteadn UalnyizFerdac udsiisntagnocense -bwetawyeaen aslaymsips loesf vwaerriea nccaelcu(AlaNteOd VuAsi)n.gF oQrIIβM-dE iv2e.r0s ity, unweighted and weighted UniFrac distances between samples were calculated using QIIME v2.0 [17], vis ualized by principal coordinate analysis (PCoA), and statistically analyzed using permutational multivariate analysis of variance (PERMANOVA). Figures of α and β diversity were generated using phyloseq [18]. The abundance of each bacterial genus in fecal microbiota was statistically analyzed using Welch’s t-test in the statistical analysis of metagenomic profiles (STAMP) software [19]. Microorganisms 2020, 8, 265 4 of 11 3. Results 3.1. Relative Abundance of Fecal Microbiota Sequencing resulted in the identification of 37,420 OTUs among 11,741,207 (lowest 296,955; highest 1,676,171) high quality sequences. This generated a list of the ten most abundant bacterial groups (classified at the lowest possible taxonomic level) in fecal samples from grasscutter and conventional livestock animals (Table 1). Although their relative abundance differed between samples, the major microbiota groups identified in fecal samples of the animals were Bacteroidales, Clostridiales, LachnosMpicirroaorcgeanaisem,sa 2n01d9, 7R, xu FmORin PoEEcRo RcEcVaIcEeWa e (Table 1). 6 of 12 At the genus level, the mean proportion of 22, 16, 24, and 19 genera were significantly different between graAsst cthuet tgeernauns dlevcealt, ttlhee, mgoeaants p, rsohpeoerptio, na nodf 2r2a, b16b,i 2ts4,, arensdp 1e9c gtievneelrya. wInerep sairgtnicifuiclaanrt,lyth deifafebruenntd ance of Prevotellbaetween grasscutter and cattle, goats, sheep, and rabbits, respectively. In particuPlar, the abundance was significantly higher in grasscutters than in the other animals ( < 0.05, Figure 2). of Prevotella was significantly higher in grasscutters than in the other animals (P < 0.05, Figure 2). (A) (B) Figure 2. Cont. Microorganisms 2020, 8, 265 5 of 11 Microorganisms 2019, 7, x FOR PEER REVIEW 7 of 12 (C) (D) Figure F2i.gCuroem 2.p Caroamtipvaeraatnivael yasneaslyosfest hoef tthaex otanxoomnoicmcico mcopmopsoitsiiotinono of ft htheem miiccrroobbiiaall ccoommmmuunnitiiteise sata tthteh e genus level ingfeencuals slaevmelp ilne sfefrcoalm sagmrapslessc ufrtotemr agnradssccounttvere natnido ncaolnlvievnetsitooncakl .liTvehsetomcke. aTnhpe rmopeaonr tpioronpoofrtrieopn roefs entative representative genera that differed significantly between groups are shown as bars on the left. The genera that differed significantly between groups are shown as bars on the left. The differences in mean differences in mean proportion of each genus, the 95% confidence intervals, and corrected P values, proportaios ncaolcfuelaatcehd bgye nstuasti,stthiceal9 a5n%alycsoisn ofifd meentcaegeinnotemrvica plsro, fainleds (cSoTrAreMcPte)d soPftwvaalrue,e asr,ea sshcoawlcnu olna ttehde rbigyhst.t atistical analysis of metagenomic profiles (STAMP) software, are shown on the right. (A) Grasscutter (Thryonomys swinderianus) versus cattle (Bos primigenius). (B) Grasscutter versus goat (Capra hircus). (C) Grasscutter versus sheep (Ovis aries). (D) Grasscutter versus rabbit (Oryctolagus cuniculus). Microorganisms 2020, 8, 265 6 of 11 Table 1. The ten most abundant microbial taxonomic groups (relative abundance, %) in fecal samples from ruminant and non-ruminant herbivorous livestock in Ghana. Non-ruminant Ruminant Grasscutter Rabbit Cattle Goat Sheep No. Taxonomy 1 (%) Taxonomy (%) Taxonomy (%) Taxonomy (%) Taxonomy (%) 1 Bacteroidales 11.59 Bacteroides 20.89 Ruminococcaceae 28.27 Ruminococcaceae 31.29 Ruminococcaceae 25.14 2 Ruminococcaceae 10.44 Clostridiales 16.62 Clostridiales 9.79 Clostridiales 11.12 Clostridiales 9.85 3 Clostridiales 9.79 Lachnospiraceae 10.41 Bacteroidales 7.64 Bacteroidales 7.75 Lysinibacillus 8.74 4 Ruminococcus 9.15 Ruminococcus 7.71 Oscillospira 4.69 Lachnospiraceae 4.97 Bacteroidales 7.21 5 Lachnospiraceae 6.71 Anaeroplasma 6.29 Lachnospiraceae 4.10 Bacillales 4.16 Lachnospiraceae 4.19 6 Prevotella 6.66 Akkermansia 5.32 5-7N15 3.17 Christensenellaceae 3.64 Rikenellaceae 3.41 7 Fibrobacter 3.56 Oscillospira 4.73 Clostridium 2.73 Lysinibacillus 3.50 Bacillales 3.20 8 RF16 3.24 Rikenellaceae 3.84 [Clostridium] 2.55 5-7N15 3.50 Ruminococcus 3.07 9 Treponema 2.35 Bacillus 3.00 Rikenellaceae 2.43 Akkermansia 3.01 5-7N15 2.75 10 S24-7 1.99 Ruminococcaceae 2.99 [Mogibacteriaceae] 2.40 Oscillospira 2.92 Christensenellaceae 2.49 Total 65.48 81.80 67.77 75.87 70.03 1 Microbial classification at the lowest possible taxonomic level and their relative abundance in the fecal microbiota of grasscutters (n = 5) and other livestock (n = 4). Microorganisms 2019, 7, x FOR PEER REVIEW 8 of 12 (a) Grasscutter (Thryonomys swinderianus) versus cattle (Bos primigenius). (b) Grasscutter versus goat Microo(rCgaanpirsam shi2r0c2u0s,)8. , (2c6)5 Grasscutter versus sheep (Ovis aries). (d) Grasscutter versus rabbit (Oryctolagus7 of 11 cuniculus). 3..2.. Anaallyssiiss ooff Miiccrroobbiiaall Diiveerrssiitty ffoorr bbeettweeeen Aniimaallss Wheen α--diiveerrssiitty ((Chao 1 iindeex:: rriicchneessss,, Shannon iindeex:: eeveenneessss)) wass ccomparreed among tthee aniimallss,, botth iindiiccess werre ssiigniiffiiccanttlly llowerr iin rrabbiittss tthan tthosse iin tthe ottherr aniimallss ((P < 0..05));; howeverr,, nnood idffieffrernecnecbee tbweteweneegnr agssrcaussttceurtstearnsd arnudm irnuamntinliavnets tolicvkeswtoacsko bwsearsv eodbsfeorrvaendy fαo-rd iavneyrs iαty- idnidverxs(iFtyig iunrdeex3) (.Figure 3). Chao1: ANOVA < 0.0001 Shannon: ANOVA < 0.0001 Figure 3.. Allphaa ddiviveerrssitiytyi ninddiciecses(C (hCahoa1oa1n adnSdh Sanhnanon)oonf) mofi cmroibciraolbcioaml cmomunmituiensiitniefse cinal fseacmalp sleasmfprolems gfrroamss cgurtatsesrcsu(tnte=rs5 ()na =n d5)o atnhder oltivhesr tloivckes(tnoc=k4 ()n. = 4). Reeggaarrddiinngg β--ddiivveerrssiittyy bbaasseedd oonn uunnweeiigghhtteedd aanndd weeiigghhtteedd UnniiFFrraacc ddiissttaannccee,, rruumiinnaannttss weerree cclloosseellyy cclluusstteerreedd iinn tthhee PPCooA pplloottss ooff tthhee fifirrsstt ttwoo aaxxeess ((aaxxeess 11 aanndd 22;; FFiigguurree 44)).. Grraassssccuutttteerrss ddaattaa weerree llooccaatteedd aawaayy ffrroom tthhoossee ooff rraabbbbiittss,, whhiicchh aarree aallssoo ssmaallll hhiinnddgguutt ffeerrmeenntteerrss.. IInn uunnweeiigghhtteedd UnniiFFrraacc ddiissttaannccee,, ggrarassssccuutttetersr sanadn drarbabbibtsi tws ewree rcelucsltuesrteedr ewditwhiinth tihne tshaemsea mraengrea ning ethien fitrhset afixrisst (aaxxiiss (1a)x oisf t1h)e oPfCtohAe PpCloot A(Fipgluorte (4Faig).u Creon4tAra)s.tiCnognlytr, ainst iwngeilgy,htiendw UenigiFhrtaecd dUisntaiFnrcaec, rdabisbtaitns caen, dr arbubmitisnaanntds r(nuomt ingarnastssc(untottegrsr)a swsceurtet ecrlso)sweleyr ecclluossteelryedcl uisnt etrheed ifnirstht eafixriss t(aaxxiiss (a1x) iso1f )tohfet hPeCPoCAo Aplpolto t(F(Figiguurere 44bB)).. PPeerrmuuttaattiioonnaall muullttiivvaarriiaattee aannaallyyssiiss ooff vvaarriiaannccee iinnddiiccaatteedd tthhaatt tthhee β--ddiivveerrssiittyy ooff ffeeccaall miiccrroobbiioottaa iinn ggrraassssccutttteerrss waass ssiiggnniiffiiccaannttllyy diiffffeerreenntt ffrroom tthhaatt iinn ootthheerr aanniimaallss ((PERMANOVA P < 00..0055;; FFiiggurree 44)).. Microorganisms 2020, 8, 265 8 of 11 Microorganisms 2019, 7, x FOR PEER REVIEW 9 of 12 PERMANOVA = 0.0001 PERMANOVA = 0.0001 (A) (B) Figure 4. Beta diversity of microbial communities in fecal samples from grasscutter and conventional Figure 4. Beta diversity of microbial communities in fecal samples from grasscutter and conventional livestock. (A) Unweighted and (B) weighted UniFrac distance principal coordinate analysis (PCoA) livestock. (a) Unweighted and (b) weighted UniFrac distance principal coordinate analysis (PCoA) plots of β-diversity measures of the microbiota communities in grasscutter (n = 5) and other livestock plots of β-diversity measures of the microbiota communities in grasscutter (n = 5) and other livestock (n = 4). (n = 4). 4. Discussion 4. Discussion In this study, aiming to establish an appropriate feeding method for domestication of the grasscutter, we inIvne stthigisa tsetduidtsyf, eacaiml minicgr otboi oetsataanbdlischo mapna raepdpirtowpirtihatteh ofseeedfrionmg omtheetrhhoedr bfiovro rdouoms leivsetisctaotcikonin oGfh athnea . gSrimasislcaur tttoert,h we eo tihnevresatnigimataelds, itths efercealal tmiviecraobbuiontdaa annced ocfomBapcaterreodi dita lwesit,hC tlhosotsreid firaolmes ,oRthuemr ihneorcboicvcoarcoeuaes , laivnedsLtoacckh nions piGrahcaenaae.— Swimhiiclhara retot hethme ajootrhbearc taerniiamgarolsu, ptshien hreerlbaitvivoere sa[b2u0–n2d3a]n—cwe aosfh iBgahcitnertohiedafelecsa,l Cmloicsrtoribdioiatlaeso, fRguramssincoucttoecrcsa.ceMaeo,r eaonvde rL, atwchonobsapctirearciaeagee—newrahiwche raeree stpheec iamllayjoarb ubancdtaenrita ingrtohuepfse cianl hmeircbriovboiroems [e2o0f–2g3r]a—sswcuatst ehrisg,hP rinev tohteel lfaecaanld mTircerpoobnieomtaa ,owf ghroassescleuvtteelrssw. Meroerheoigvheerr, tiwn og rbaascstceurtiate grsenthearan wtheorsee eisnpaenciyalolyth aebruanndimanatl .inS otmhee fsepceacl imesicorfoPbrioevmotee lolaf agnradssTcruepttoenresm, Pa rheavvoteelfilab earnfde rTmreepnotnaetmioan, wabhiloistye ; lPerveevlost ewllearsep hecigiehserm iank egraacsestciuc tatecrids tfhroamn tlhigonsoe cienl luanloys eot[h24e]r, aannidmTarle. pSoonmemea ssppeeccieiess oafr ePrfeovuontedllain atnhde Tinrteepsotnineme ao fhtaevrem fiitbees,r wfehrmereenthtaetyiopnl aaybialintyim; Pproevrtoatneltlar ospleeicniecse mllualkoes eacfeertmic eanctidat iforonm[1 l1i,g2n5o].ceTlhluelporsees [e2n4c]e, aonfdsu Tcrhepaodniesmtian cstpiveceimesi carroeb fiooumnedi ning rthases cinuttetestrisn,ein ocfl utderinmgitbeasc, twerhiaerteh atht ecayn pblareya aknd oimwnpodriteatnart yrofilbee irns , cmelalyulcoosne fefrergmraesnstcauttitoenrs [h1i1g,h2e5r].fi Tbehre dpigreessteinbicleit yotfh asuncthh aat odf iostthinecrthiveer bimvoicrreosb. iFormome tihne gvriaewsspcuotitnetros,f idnocmluedsitnigca tbioanct,earniao pthtiamt alcadnie tbfroeragkrdaoswscnu ttdeirestashryo uflidbebres,b amseady oncornefseoru rgcreasstshcautttaerres nhotigchoenrs ufmibeedr dbiygehsutimbialintsy, tshoatnh tahtatth oerf eoitshenro hceormbipveotrietiso. nF.roIfmth tehee xvpieewctpedoinhtig ohf adboimliteysttiocadtiiognes, tafinb oeprtiismcaoln dfiiremt feodr , ggrraassssccuutttteerrss cshououldldb ebefe dbaasefidb eorn-r ircehsoduiertceasn dth, atht uasr,en noot tc ocmonpseutme wedit hbyh uhmumanasn.s, so that there is no compCetoimtiopna.r Iinf gthteh eexαp-decivteedrs hitiyghof afbecilaitlym tioc rdoibgieostta faibmeor nisg ctohnefainrmimeadl,s g, oranslysctuhtatteorsf rcaobublidts bseh foewde ad faibleorw- rviachlu de.ieItn arnadb,b tihtsu,st,h neontu cmombepreotef OwTitUh shiunmgauntsm. icrobiota varies greatly [22,26–28]. Accordingly, in the preseCnotmstpuadryin, gm tohree αO-dTiUvesrwsiteyr eofo fbescearlv medicrinobtihoetag aumt omnigc rtohbei oanmime oalfso, othnelry ltihvaets otof crkabtbhiatns sihnotwhaetdo af ltohwe rvaablubiet.s I.nR raabbbbiittss, htahve entuhme bwera sohf- ObaTcUkst yinp eguotf mcoilcornobiciosteap vaarariteios ngrmeaetclhy a[n2i2s,m26–(C28S]M. A),ccwohrdicihngislya, isnp tehceia pl rgeassetrnoti snttuedstyin, aml omree cOhaTnUissm wtehraet oabllsoewrvsesdm inal tlhfoe ogdupt marticicrloebsitoomfleo wof iontthoetrh leivceesctuomck[ t1h2a,1n3 i,n29 t,h3a0t] . oSfi nthcee trhaebbgirtass. sRcaubttbeirtsi shaalvseo tahhe iwndagshu-tbfaecrkm teynptee ro, fo ncoelmonaiyc sseppeacrualtaitoent hmaetcthhaenyimsma y(CaSlsMo )h, awvheiachC iSsM a . sHpoewciaelv egr,ausntrloikinetreasbtibnitasl, gmraescshcaunttiesrms mtahyath aavleloawnos thsemrakliln dfooofdC SpMarptircelseesn ttion rfolodwen tisn, ttoh e tmheu cucesc-turamp [t1y2p,1e3o,2f9C,3S0M]. .STinhceem thuec ugsr-atsrsacputmteerc ihsa anlissom a ahlilnodwgsutth feerflmowenotefrf,o oonde pmaartyic slpesecthualattaer tehlaatr tgheeryt hmaanyt haolssoe htraavnes pa oCrSteMd.b Hyothweewvears,h u-nbalickke tryapbebiintst,o gtrhaesscceucuttmers[3 m0]a.yIt hiasvsue gagneosttheedr tkhiantdth oef wCSaMsh -pbraecskeCntS iMn rsoedalesntthse, trhaeb bmitu’scucesc-utrmapf otyrpmei corfo CbiSoMta. fTerhme emntuactuiosn-t[r3a0p– m32e].chInanoitshmer awlloorwdss ,trhaeb bfliotswm oifg hfotobde pabalretitcolesse ltehcatti vaerley lsatrogreerm thicarno bthiootsae, twrahnesrpeaosrtoetdh bery atnhiem waalsshd-obancokt thyapvee isnutoch thaeb icleitcyu.mTh [i3s0m]. Iigt ihst slueagdgetsoteadn tihnacrt etahsee winasthh-e baabcukn CdaSnMc eseoaflds othmei rnaabnbtist’pse cceiceus min ftohre mceiccraol bmioictrao fbeirommeentoaftrioanb b[3it0s–, 3w2h].i cInh omthayerb weothrdesr,e raasbobnitws mhyigthhet beev eanbnlee stso osfemlecictrivoebliyo tsatoinrer ambibcirtosbwioatsal, owhwerheeans ocothmepr aarninimg aitlss αd-od invoetr shiatyvew siuthchth aabt ioliftyo.t hTehrisa nmimigahlst . lead tIon athne icnacsreeaosfet hine ftehcea lambuicnrdoabnioctea oβf- ddiovmerisniatyn,tg srpasescciuestt ienr sthane dcercaablb mitsicwroebreiocmleaer olyf sreapbabritast,e dwfhriocmh mruamy ibnea nthtse irneathsoenP wCohAy tphleo et.vDenonmeesss toicfa mteidcrroabbiboittas ihna rvaebbniotsT wreapos nloemwa winhethne ciromgupta, ruinnlgik itesh αa-rdeisv(eLrespituys wspitph. )th[2a2t, 3o3f ,o3t4h].erG arnaismscaulstt. ers and rabbits are both small hindgut fermenters, but they were plotted separInat ethlye fcraosme eoaf cthheo tfheecrali nmtihceroPbCiootAa aβn-daliyvseirss.itNy,a tgurraaslsrcaubttbeirtsd aientds arraebcboitms pwoesreed colefafrolryb ss,ewpahrearteeads from ruminants in the PCoA plot. Domesticated rabbits have no Treponema in their gut, unlike hares (Lepus spp.) [22,33,34]. Grasscutters and rabbits are both small hindgut fermenters, but they were plotted separately from each other in the PCoA analysis. Natural rabbit diets are composed of forbs, Microorganisms 2020, 8, 265 9 of 11 grasscutters prefer the stem portions of grasses and other plants, which could explain the diversity difference between these species. The evident separation of grasscutters from the conventional livestock animals at both UniFrac analyses may be caused by differences in feeding habits and environment. This is supported by the observation that livestock fed with the same feed under the same husbandry conditions are plotted closely to each other. For example, ruminants and hindgut fermenters are plotted away from each other in microbiota β-diversity analyses, and ruminant living in the same environment are clustered together [35]. Therefore, the grasscutters used in this study were likely obtained from the same region. Besides, it is expected that the grasscutters microbial community structure changes, which affects how it relates to that in other livestock [20], as the domestication progresses. In captivity, the grasscutter has been fed mainly with elephant grass (Pennisetum purpureum) or cassava (Manihot esculenta) [36,37]. In addition, farmers in the northern area of Ghana are currently feeding grasscutters elephant grass, guinea grass (Megathyrsus maximus), or agricultural residues of maize from the surrounding area. In African countries, wild grasscutters cause damage to corn, wheat, and grass crops [38,39]. In other words, the feed currently given by farmers is be close to what wild individuals would eat. However, considering that weight gain is one of the most important parameters in meat production, the development of feed formulations (e.g., with low fiber content) for weight gain is expected. Such an artificial diet may affect the gut microbiota of the grasscutter. Indeed, in other animals, the fecal microbiota of wild and domesticated individuals within the same species are different, and their fecal microbiota is affected by feed differences [20]. Moreover, low-fiber diets or high-protein diets can alter the diversity of gut microbiota and may cause adverse effects, such as diarrhea and reduced fertility due to obesity [40,41]. Thus, in future studies, it is crucial to assess how much feed characteristics affect the gut microbiota of domesticated grasscutters. Grasscutters are in the process of domestication, and gut microbiota of non-wild grasscutters should be analyze in the future. The data from this study will be useful for future domestication of grasscutters, especially in terms of the relationship between feed and gut microbiota. The eventual changes in the gut microbiota of the grasscutter as domestication progresses warrant further research to support the establishment of appropriate feeding methods. Author Contributions: Conceptualization, K.K., Y.M., Y.T., K.O., M.I.-M., C.A. and B.K.; validation, K.K., Y.M., T.O., T.M., K.O. and B.K.; formal analysis, K.K., T.O., T.M. and K.O.; investigation and experiments, K.K., Y.T., J.O.O., K.S., H.O., H.F., C.A. and K.O.; resources, C.A. and B.K.; data curation, K.K., T.K., T.O., Y.K., T.M. and K.O.; writing—original draft preparation, K.K. and K.O.; writing—review and editing, Y.M. and B.K.; visualization, K.K., T.O. and Y.K.; supervision, Y.M., K.O. and B.K.; project administration, Y.M., K.O., M.I.-M. and B.K.; funding acquisition, Y.M., K.O., Y.T. and M.I.-M. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by JSPS KAKENHI, grant numbers JP26304039 (to K.O.) and JP16H05801 (M.I.-M.), and by JSPS Bilateral Programs to M.I.-M., Y.T. and K.O. This work was also supported by the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan, through the Joint Research Program of the Research Center for Zoonosis Control, Hokkaido University (to H.O., Y.T. and K.O.). Acknowledgments: J.O.O. received a scholarship from the Japanese government (MEXT). T.K. was a recipient of the Tobitate! (Leap for Tomorrow) Young Ambassador Program from the MEXT. Conflicts of Interest: The authors declare no conflicts of interest. References 1. United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects Volume I: Comprehensive Tables; United Nations: New York, NY, USA, 2019; pp. 22–33. 2. Saaka, M.; Larbi, A.; Hoeschle-Zeledon, I.; Appiah, B. 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