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Archaea (Vancouver, B.C.)2014; 2014; 483574; doi: 10.1155/2014/483574

Comparative analysis of the methanogen diversity in horse and pony by using mcrA gene and archaeal 16s rRNA gene clone libraries.

Abstract: Comparative analysis of methanogen compositions in the feces of horse and pony was carried out by constructing the α -subunit of methyl coenzyme-M reductase (mcrA) gene and 16S ribosomal RNA gene (16S rRNA) clone libraries. The mcrA clone library analysis indicated that Methanomicrobiales was predominant in both horse and pony. Furthermore, most of the clones of the 16S rRNA gene library showed that Methanomicrobiales was also predominant in horse and pony, but the LIBSHUFF analysis showed that the horse and pony libraries were significantly different (P < 0.05). Most of operational taxonomic units (OTUs) showed low similarity to the identified methanogens in both the mcrA and the 16S rRNA clone libraries. The results suggest that horse and pony harbor unidentified and novel methanogens in their hindgut. The methanogen population was higher in horse than in pony; however, the anaerobic fungal population was similar in horse and pony. The methanogen diversity was different between two breeds of Equus caballus.
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Publication Date: 2014-01-30 PubMed ID: 24678264PubMed Central: PMC3941164DOI: 10.1155/2014/483574Google Scholar: Lookup
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  • Comparative Study
  • Journal Article
  • Research Support
  • Non-U.S. Gov't

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

This research study investigates the variations in methanogen organisms (methane-producing microbes) found in the feces of horses and ponies, discovering differences in the distribution and diversity of these microbes and suggesting the presence of novel, unidentified methanogens within these animals’ hindguts.

Research Methodology

  • The research made use of the α -subunit of methyl coenzyme-M reductase (mcrA) gene and 16S ribosomal RNA gene (16S rRNA) clone libraries. These mechanisms are instrumental in studying microbial diversity within a sample, allowing researchers to identify and differentiate between various microbial species.
  • These clone libraries were constructed from the fecal samples of both horses and ponies. The mcrA gene is specific to methanogens and provides a reliable database for investigating methanogen diversity, whereas the 16S rRNA gene is a universal marker used for phylogenetic studies.
  • The clone libraries enabled the comparison of the methanogen diversity within the two subject groups, horses and ponies.

Research Findings

  • The mcrA clone library analysis revealed Methanomicrobiales as the dominant methanogen in both species, a finding which was mostly echoed in the 16S rRNA clone library analysis. Methanomicrobiales are a type of archaea that are known to produce methane, a potent greenhouse gas.
  • Even though Methanomicrobiales predominated in both groups, the LIBSHUFF analysis, a technique for determining significant differences between microbial communities, found that the two libraries from horse and pony were significantly different. This result suggests that there is variation in the methanogen communities between horses and ponies.
  • Most of the operational taxonomic units (OTUs)—groupings that share common genetic or physical characteristics—showed low resemblance to known methanogens. This suggests the existence of novel and unidentified methanogen species within the hindguts of these animals.
  • The study also found a higher population of methanogens in horses compared to ponies, even though the anaerobic fungal populations, which interact extensively with methanogens, remained similar in both species.
  • Overall, the research indicates differences in the diversity of methanogens between horse and pony, two breeds of Equus caballus.

Implications and Conclusions

  • The findings of this study could contribute to our understanding of methane production in animals, important given the significant contribution of livestock to greenhouse gas emissions.
  • The suggestion of novel and currently unidentified methanogens paves the way for future research in this area, which could lead to advancements in microbial ecology, methane mitigation strategies, and animal digestive health.

Cite This Article

APA
Lwin KO, Matsui H. (2014). Comparative analysis of the methanogen diversity in horse and pony by using mcrA gene and archaeal 16s rRNA gene clone libraries. Archaea, 2014, 483574. https://doi.org/10.1155/2014/483574

Publication

Archaea (Vancouver, B.C.)
ISSN: 1472-3654
NlmUniqueID: 101142614
Country: United States
Language: English
Volume: 2014
Pages: 483574
PII: 483574

Researcher Affiliations

Lwin, Khin-Ohnmar
  • Graduate School of Bioresources, Mie University, 1577 Kurimamachiya-Cho, Tsu, Mie 514-8507, Japan ; Livestock Breeding and Veterinary Department, Yangon Diagnostic Laboratory, Yangon 11121, Myanmar.
Matsui, Hiroki
  • Graduate School of Bioresources, Mie University, 1577 Kurimamachiya-Cho, Tsu, Mie 514-8507, Japan.

MeSH Terms

  • Animals
  • Archaea / classification
  • Archaea / isolation & purification
  • Archaea / metabolism
  • Biodiversity
  • Cluster Analysis
  • DNA, Archaeal / chemistry
  • DNA, Archaeal / genetics
  • DNA, Ribosomal / chemistry
  • DNA, Ribosomal / genetics
  • Horses
  • Methane / metabolism
  • Molecular Sequence Data
  • Oxidoreductases / genetics
  • Phylogeny
  • RNA, Ribosomal, 16S / genetics
  • Sequence Analysis, DNA

References

This article includes 44 references
  1. Stewart CS. Microorganisms in hindgut fermentors. In: Mackie I, White BA, Issacson RE, editors. GastroIntestInal Microbiology. Vol. 2. New York, NY, USA: Chapman and Hall; 1996. pp. 162–171.
  2. Daly K, Stewart CS, Flint HJ, Shirazi-Beechey SP. Bacterial diversity within the equine large intestine as revealed by molecular analysis of cloned 16S rRNA genes. FEMS Microbiology Ecology 2001;38(2-3):141–151.
  3. Moore BE, Dehority BA. Effects of diet and hindgut defaunation on diet digestibility and microbial concentrations in the cecum and colon of the horse.. J Anim Sci 1993 Dec;71(12):3350-8.
    pubmed: 8294287doi: 10.2527/1993.71123350xgoogle scholar: lookup
  4. Lin C, Stahl DA. Taxon-specific probes for the cellulolytic genus Fibrobacter reveal abundant and novel equine-associated populations.. Appl Environ Microbiol 1995 Apr;61(4):1348-51.
    pmc: PMC167390pubmed: 7538274doi: 10.1128/aem.61.4.1348-1351.1995google scholar: lookup
  5. Yamano H, Koike S, Kobayashi Y, Hata H. Phylogenetic analysis of hindgut microbiota in Hokkaido native horses compared to light horses. Animal Science Journal 2008;79(2):234–242.
  6. Hastie PM, Mitchell K, Murray JA. Semi-quantitative analysis of Ruminococcus flavefaciens, Fibrobacter succinogenes and Streptococcus bovis in the equine large intestine using real-time polymerase chain reaction.. Br J Nutr 2008 Sep;100(3):561-8.
    pubmed: 18377691doi: 10.1017/s0007114508968227google scholar: lookup
  7. Koike S, Shingu Y, Inaba H. Fecal bacteria in Hokkaido native horses as characterized by microscopic enumeration and competitive polymerase chain reaction assays. Journal of Equine Science 2000;11(2):45–50.
  8. Julliand V, de Vaux A, Millet L, Fonty G. Identification of Ruminococcus flavefaciens as the predominant cellulolytic bacterial species of the equine cecum.. Appl Environ Microbiol 1999 Aug;65(8):3738-41.
    pmc: PMC91562pubmed: 10427077doi: 10.1128/aem.65.8.3738-3741.1999google scholar: lookup
  9. Kobayashi Y, Koike S, Miyaji M, Hata H, Tanaka K. Hindgut microbes, fermentation and their seasonal variations in Hokkaido native horses compared to light horses. Ecological Research 2006;21(2):285–291.
  10. Lin C, Miller TL. Phylogenetic analysis of Methanobrevibacter isolated from feces of humans and other animals.. Arch Microbiol 1998 May;169(5):397-403.
    pubmed: 9560420doi: 10.1007/s002030050589google scholar: lookup
  11. Wright AD, Williams AJ, Winder B, Christophersen CT, Rodgers SL, Smith KD. Molecular diversity of rumen methanogens from sheep in Western Australia.. Appl Environ Microbiol 2004 Mar;70(3):1263-70.
    pmc: PMC368393pubmed: 15006742doi: 10.1128/aem.70.3.1263-1270.2004google scholar: lookup
  12. Shin EC, Choi BR, Lim WJ, Hong SY, An CL, Cho KM, Kim YK, An JM, Kang JM, Lee SS, Kim H, Yun HD. Phylogenetic analysis of archaea in three fractions of cow rumen based on the 16S rDNA sequence.. Anaerobe 2004 Dec;10(6):313-9.
    pubmed: 16701533doi: 10.1016/j.anaerobe.2004.08.002google scholar: lookup
  13. King EE, Smith RP, St-Pierre B, Wright AD. Differences in the rumen methanogen populations of lactating Jersey and Holstein dairy cows under the same diet regimen.. Appl Environ Microbiol 2011 Aug 15;77(16):5682-7.
    pmc: PMC3165256pubmed: 21705541doi: 10.1128/aem.05130-11google scholar: lookup
  14. Tan HY, Sieo CC, Lee CM, Abdullah N, Liang JB, Ho YW. Diversity of bovine rumen methanogens In vitro in the presence of condensed tannins, as determined by sequence analysis of 16S rRNA gene library.. J Microbiol 2011 Jun;49(3):492-8.
    pubmed: 21717338doi: 10.1007/s12275-011-0319-7google scholar: lookup
  15. Tajima K, Nagamine T, Matsui H, Nakamura M, Aminov RI. Phylogenetic analysis of archaeal 16S rRNA libraries from the rumen suggests the existence of a novel group of archaea not associated with known methanogens.. FEMS Microbiol Lett 2001 Jun 12;200(1):67-72.
    pubmed: 11410351doi: 10.1111/j.1574-6968.2001.tb10694.xgoogle scholar: lookup
  16. Yanagita K, Kamagata Y, Kawaharasaki M, Suzuki T, Nakamura Y, Minato H. Phylogenetic analysis of methanogens in sheep rumen ecosystem and detection of Methanomicrobium mobile By fluorescence in situ hybridization.. Biosci Biotechnol Biochem 2000 Aug;64(8):1737-42.
    pubmed: 10993166doi: 10.1271/bbb.64.1737google scholar: lookup
  17. Lwin KO, Kondo M, Ban-Tokuda T, Lapitan RM, Del-Barrio AN, Fujihara T, Matsui H. Ruminal fermentation and microbial ecology of buffaloes and cattle fed the same diet.. Anim Sci J 2012 Dec;83(12):767-76.
    pubmed: 23216542doi: 10.1111/j.1740-0929.2012.01031.xgoogle scholar: lookup
  18. Skillman LC, Toovey AF, Williams AJ, Wright AD. Development and validation of a real-time PCR method to quantify rumen protozoa and examination of variability between entodinium populations in sheep offered a hay-based diet.. Appl Environ Microbiol 2006 Jan;72(1):200-6.
    pmc: PMC1352179pubmed: 16391043doi: 10.1128/aem.72.1.200-206.2006google scholar: lookup
  19. Regensbogenova M, McEwan NR, Javorsky P, Kisidayova S, Michalowski T, Newbold CJ, Hackstein JH, Pristas P. A re-appraisal of the diversity of the methanogens associated with the rumen ciliates.. FEMS Microbiol Lett 2004 Sep 15;238(2):307-13.
    pubmed: 15358415doi: 10.1016/j.femsle.2004.07.049google scholar: lookup
  20. Tokura M, Chagan I, Ushida K, Kojima Y. Phylogenetic study of methanogens associated with rumen ciliates.. Curr Microbiol 1999 Sep;39(3):123-8.
    pubmed: 10441724doi: 10.1007/s002849900432google scholar: lookup
  21. Whitford MF, Teather RM, Forster RJ. Phylogenetic analysis of methanogens from the bovine rumen.. BMC Microbiol 2001;1:5.
    pmc: PMC32158pubmed: 11384509doi: 10.1186/1471-2180-1-5google scholar: lookup
  22. Sharp R, Ziemer CJ, Stern MD, Stahl DA. Taxon-specific associations between protozoal and methanogen populations in the rumen and a model rumen system. FEMS Microbiology Ecology 1998;26(1):71–78.
  23. Denman SE, Tomkins NW, McSweeney CS. Quantitation and diversity analysis of ruminal methanogenic populations in response to the antimethanogenic compound bromochloromethane.. FEMS Microbiol Ecol 2007 Dec;62(3):313-22.
    pubmed: 17949432doi: 10.1111/j.1574-6941.2007.00394.xgoogle scholar: lookup
  24. Ozutsumi Y, Tajima K, Takenaka A, Itabashi H. McrA gene and 16S rRNA gene in the phylogenetic analysis of methanogens in the rumen of faunated and unfaunated cattle.. Anim Sci J 2012 Nov;83(11):727-34.
    pubmed: 23126325doi: 10.1111/j.1740-0929.2012.01023.xgoogle scholar: lookup
  25. Paul K, Nonoh JO, Mikulski L, Brune A. "Methanoplasmatales," Thermoplasmatales-related archaea in termite guts and other environments, are the seventh order of methanogens.. Appl Environ Microbiol 2012 Dec;78(23):8245-53.
    pmc: PMC3497382pubmed: 23001661doi: 10.1128/aem.02193-12google scholar: lookup
  26. Dehority BA, Orpin CG. Development of, and natural fluctuations in, rumen microbial populations. In: Hobson PN, editor. The Rumen Microbial Ecosystem. London, UK: Elsevier Applied Science; 1988. pp. 151–183.
  27. Sato H, Nakajima J. Fecal ammonia, urea, volatile fatty acid and lactate levels in dairy cows and their pathophysiological significance during diarrhea. Animal Science Journal 2005;76(6):595–599.
  28. Lwin KO, Hayakawa M, Ban-Tokuda T, Matsui H. Real-time PCR assays for monitoring anaerobic fungal biomass and population size in the rumen.. Curr Microbiol 2011 Apr;62(4):1147-51.
    pubmed: 21153728doi: 10.1007/s00284-010-9843-7google scholar: lookup
  29. Denman SE, McSweeney CS. Development of a real-time PCR assay for monitoring anaerobic fungal and cellulolytic bacterial populations within the rumen.. FEMS Microbiol Ecol 2006 Dec;58(3):572-82.
    pubmed: 17117998doi: 10.1111/j.1574-6941.2006.00190.xgoogle scholar: lookup
  30. Wright AD, Pimm C. Improved strategy for presumptive identification of methanogens using 16S riboprinting.. J Microbiol Methods 2003 Nov;55(2):337-49.
    pubmed: 14529955doi: 10.1016/s0167-7012(03)00169-6google scholar: lookup
  31. Luton PE, Wayne JM, Sharp RJ, Riley PW. The mcrA gene as an alternative to 16S rRNA in the phylogenetic analysis of methanogen populations in landfill.. Microbiology (Reading) 2002 Nov;148(Pt 11):3521-3530.
    pubmed: 12427943doi: 10.1099/00221287-148-11-3521google scholar: lookup
  32. Matsui H, Ban-Tokuda T, Wakita M. Detection of fiber-digesting bacteria in the ceca of ostrich using specific primer sets.. Curr Microbiol 2010 Feb;60(2):112-6.
    pubmed: 19787401doi: 10.1007/s00284-009-9513-9google scholar: lookup
  33. Altschul SF, Madden TL, Schäffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.. Nucleic Acids Res 1997 Sep 1;25(17):3389-402.
    pmc: PMC146917pubmed: 9254694doi: 10.1093/nar/25.17.3389google scholar: lookup
  34. Cole JR, Chai B, Marsh TL, Farris RJ, Wang Q, Kulam SA, Chandra S, McGarrell DM, Schmidt TM, Garrity GM, Tiedje JM. The Ribosomal Database Project (RDP-II): previewing a new autoaligner that allows regular updates and the new prokaryotic taxonomy.. Nucleic Acids Res 2003 Jan 1;31(1):442-3.
    pmc: PMC165486pubmed: 12520046doi: 10.1093/nar/gkg039google scholar: lookup
  35. Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, Valentin F, Wallace IM, Wilm A, Lopez R, Thompson JD, Gibson TJ, Higgins DG. Clustal W and Clustal X version 2.0.. Bioinformatics 2007 Nov 1;23(21):2947-8.
    pubmed: 17846036doi: 10.1093/bioinformatics/btm404google scholar: lookup
  36. Saitou N, Nei M. The neighbor-joining method: a new method for reconstructing phylogenetic trees.. Mol Biol Evol 1987 Jul;4(4):406-25.
    pubmed: 3447015doi: 10.1093/oxfordjournals.molbev.a040454google scholar: lookup
  37. Schloss PD, Handelsman J. Introducing DOTUR, a computer program for defining operational taxonomic units and estimating species richness.. Appl Environ Microbiol 2005 Mar;71(3):1501-6.
    pmc: PMC1065144pubmed: 15746353doi: 10.1128/aem.71.3.1501-1506.2005google scholar: lookup
  38. Magurran AE. Ecological Diversity and Its Measurement. Princeton, NJ, USA: Princeton University Press; 1988.
  39. Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, Lesniewski RA, Oakley BB, Parks DH, Robinson CJ, Sahl JW, Stres B, Thallinger GG, Van Horn DJ, Weber CF. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities.. Appl Environ Microbiol 2009 Dec;75(23):7537-41.
    pmc: PMC2786419pubmed: 19801464doi: 10.1128/aem.01541-09google scholar: lookup
  40. Evans PN, Hinds LA, Sly LI, McSweeney CS, Morrison M, Wright AD. Community composition and density of methanogens in the foregut of the Tammar wallaby (Macropus eugenii).. Appl Environ Microbiol 2009 Apr;75(8):2598-602.
    pmc: PMC2675200pubmed: 19218421doi: 10.1128/aem.02436-08google scholar: lookup
  41. Miller TL, Wolin MJ. Methanogens in human and animal intestinal tracts. Systematic and Applied Microbiology 1986;7(2-3):223–229.
  42. Jensen BB. Methanogenesis in monogastric animals.. Environ Monit Assess 1996 Sep;42(1-2):99-112.
    pubmed: 24193495doi: 10.1007/bf00394044google scholar: lookup
  43. Morvan B, Bonnemoy F, Fonty G, Gouet P. Quantitative determination of H2-utilizing acetogenic and sulfate-reducing bacteria and methanogenic archaea from digestive tract of different mammals.. Curr Microbiol 1996 Mar;32(3):129-33.
    pubmed: 8704656doi: 10.1007/s002849900023google scholar: lookup
  44. Chaudhary PP, Sirohi SK, Saxena J. Diversity analysis of methanogens in rumen of Bubalus bubalis by 16S riboprinting and sequence analysis.. Gene 2012 Feb 1;493(1):13-7.
    pubmed: 22155312doi: 10.1016/j.gene.2011.11.041google scholar: lookup

Citations

This article has been cited 13 times.
  1. Zaitseva S, Dagurova O, Radnagurueva A, Kozlova A, Izotova A, Krylova A, Noskov S, Begmatov S, Patutina E, Barkhutova DD. Fecal Microbiota and Diet Composition of Buryatian Horses Grazing Warm- and Cold-Season Grass Pastures. Microorganisms 2023 Jul 30;11(8).
    doi: 10.3390/microorganisms11081947pubmed: 37630507google scholar: lookup
  2. Zhang Z, Huang B, Gao X, Shi X, Wang X, Wang T, Wang Y, Liu G, Wang C. Dynamic changes in fecal microbiota in donkey foals during weaning: From pre-weaning to post-weaning. Front Microbiol 2023;14:1105330.
    doi: 10.3389/fmicb.2023.1105330pubmed: 36778861google scholar: lookup
  3. Edwards JE, Shetty SA, van den Berg P, Burden F, van Doorn DA, Pellikaan WF, Dijkstra J, Smidt H. Multi-kingdom characterization of the core equine fecal microbiota based on multiple equine (sub)species. Anim Microbiome 2020 Feb 12;2(1):6.
    doi: 10.1186/s42523-020-0023-1pubmed: 33499982google scholar: lookup
  4. Mienaltowski MJ, Belt A, Henderson JD, Boyd TN, Marter N, Maga EA, DePeters EJ. Psyllium supplementation is associated with changes in the fecal microbiota of horses. BMC Res Notes 2020 Sep 29;13(1):459.
    doi: 10.1186/s13104-020-05305-wpubmed: 32993781google scholar: lookup
  5. Huang J, Li Y. Rumen methanogen and protozoal communities of Tibetan sheep and Gansu Alpine Finewool sheep grazing on the Qinghai-Tibetan Plateau, China. BMC Microbiol 2018 Dec 13;18(1):212.
    doi: 10.1186/s12866-018-1351-0pubmed: 30545295google scholar: lookup
  6. Peachey LE, Molena RA, Jenkins TP, Di Cesare A, Traversa D, Hodgkinson JE, Cantacessi C. The relationships between faecal egg counts and gut microbial composition in UK Thoroughbreds infected by cyathostomins. Int J Parasitol 2018 May;48(6):403-412.
    doi: 10.1016/j.ijpara.2017.11.003pubmed: 29432771google scholar: lookup
  7. Salgado-Flores A, Bockwoldt M, Hagen LH, Pope PB, Sundset MA. First insight into the faecal microbiota of the high Arctic muskoxen (Ovibos moschatus). Microb Genom 2016 Jul;2(7):e000066.
    doi: 10.1099/mgen.0.000066pubmed: 28348861google scholar: lookup
  8. Ziganshin AM, Ziganshina EE, Kleinsteuber S, Nikolausz M. Comparative Analysis of Methanogenic Communities in Different Laboratory-Scale Anaerobic Digesters. Archaea 2016;2016:3401272.
    doi: 10.1155/2016/3401272pubmed: 28074084google scholar: lookup
  9. St-Pierre B, Cersosimo LM, Ishaq SL, Wright AD. Toward the identification of methanogenic archaeal groups as targets of methane mitigation in livestock animalsr. Front Microbiol 2015;6:776.
    doi: 10.3389/fmicb.2015.00776pubmed: 26284054google scholar: lookup
  10. Alvarado A, Montañez-Hernández LE, Palacio-Molina SL, Oropeza-Navarro R, Luévanos-Escareño MP, Balagurusamy N. Microbial trophic interactions and mcrA gene expression in monitoring of anaerobic digesters. Front Microbiol 2014;5:597.
    doi: 10.3389/fmicb.2014.00597pubmed: 25429286google scholar: lookup
  11. Maier I, Kienzle E. A Meta-Analysis on Quantitative Sodium, Potassium and Chloride Metabolism in Horses and Ponies. Animals (Basel) 2025 Jan 13;15(2).
    doi: 10.3390/ani15020191pubmed: 39858191google scholar: lookup
  12. Protasov E, Nonoh JO, Kästle Silva JM, Mies US, Hervé V, Dietrich C, Lang K, Mikulski L, Platt K, Poehlein A, Köhler-Ramm T, Miambi E, Boga HI, Feldewert C, Ngugi DK, Plarre R, Sillam-Dussès D, Šobotník J, Daniel R, Brune A. Diversity and taxonomic revision of methanogens and other archaea in the intestinal tract of terrestrial arthropods. Front Microbiol 2023;14:1281628.
    doi: 10.3389/fmicb.2023.1281628pubmed: 38033561google scholar: lookup
  13. Volmer JG, McRae H, Morrison M. The evolving role of methanogenic archaea in mammalian microbiomes. Front Microbiol 2023;14:1268451.
    doi: 10.3389/fmicb.2023.1268451pubmed: 37727289google scholar: lookup
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