1887

Abstract

The faecal microbiota of muskoxen (n=3) pasturing on Ryøya (69° 33′ N 18° 43′ E), Norway, in late September was characterized using high-throughput sequencing of partial 16S rRNA gene regions. A total of 16 209 high-quality sequence reads from bacterial domains and 19 462 from archaea were generated. Preliminary taxonomic classifications of 806 bacterial operational taxonomic units (OTUs) resulted in 53.7–59.3 % of the total sequences being without designations beyond the family level. Firmicutes (70.7–81.1 % of the total sequences) and Bacteroidetes (16.8–25.3 %) constituted the two major bacterial phyla, with uncharacterized members within the family Ruminococcaceae (28.9–40.9 %) as the major phylotype. Multiple-library comparisons between muskoxen and other ruminants indicated a higher similarity for muskoxen faeces and reindeer caecum (P>0.05) and some samples from cattle faeces. The archaeal sequences clustered into 37 OTUs, with dominating phylotypes affiliated to the methane-producing genus Methanobrevibacter (80–92 % of the total sequences). UniFrac analysis demonstrated heterogeneity between muskoxen archaeal libraries and those from reindeer and roe deer (P=1.0e-02, Bonferroni corrected), but not with foregut fermenters. The high proportion of cellulose-degrading Ruminococcus-affiliated bacteria agrees with the ingestion of a highly fibrous diet. Further experiments are required to elucidate the role played by these novel bacteria in the digestion of this fibrous Artic diet eaten by muskoxen.

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2016-04-29
2019-11-15
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References

  1. Barboza P. S., Peltier T. C., Forster R. J.. 2006; Ruminal fermentation and fill change with season in an arctic grazer: responses to hyperphagia and hypophagia in muskoxen (Ovibos moschatus). Physiol Biochem Zool79:497–513 [CrossRef][PubMed]
    [Google Scholar]
  2. Ben David Y., Dassa B., Borovok I., Lamed R., Koropatkin N. M., Martens E. C., White B. A., Bernalier-Donadille A., Duncan S. H. et al. 2015; Ruminococcal cellulosome systems from rumen to human. Environ Microbiol17:3407–3426 [CrossRef][PubMed]
    [Google Scholar]
  3. Blaxter K. L., Clapperton J. L.. 1965; Prediction of the amount of methane produced by ruminants. Br J Nutr19:511–522 [CrossRef][PubMed]
    [Google Scholar]
  4. Blix A. S., Ness J., Lian H.. 2011; Experiences from 40 years of muskox (Ovibos moschatus) farming in Norway. Rangifer31:1–6 [CrossRef]
    [Google Scholar]
  5. Bodas R., Prieto N., García-González R., Andrés S., Giráldez F. J., López S.. 2012; Manipulation of rumen fermentation and methane production with plant secondary metabolites. Anim Feed Sci Tech176:78–93
    [Google Scholar]
  6. Campos P. F., Willerslev E., Sher A., Orlando L., Axelsson E., Tikhonov A., Aaris-Sørensen K., Greenwood A. D., Kahlke R. D. et al. 2010; Ancient DNA analyses exclude humans as the driving force behind late Pleistocene muskox (Ovibos moschatus) population dynamics. Proc Natl Acad Sci U S A107:5675–5680 [CrossRef][PubMed]
    [Google Scholar]
  7. Caporaso J. G., Kuczynski J., Stombaugh J., Bittinger K., Bushman F. D., Costello E. K., Fierer N., Peña A. G., Goodrich J. K. et al. 2010; QIIME allows analysis of high-throughput community sequencing data. Nat Methods7:335–336 [CrossRef][PubMed]
    [Google Scholar]
  8. Caporaso J. G., Bittinger K., Bushman F. D., DeSantis T. Z., Andersen G. L., Knight R.. 2010a; PyNAST: a flexible tool for aligning sequences to a template alignment. Bioinformatics26:266–267 [CrossRef]
    [Google Scholar]
  9. Cersosimo L. M., Lachance H., St-Pierre B., van Hoven W., Wright A. D.. 2015; Examination of the rumen bacteria and methanogenic archaea of wild impalas (Aepyceros melampus melampus) from Pongola, South Africa. Microb Ecol69:577–585 [CrossRef][PubMed]
    [Google Scholar]
  10. Chao A.. 1984; Nonparametric estimation of the number of classes in a population. Scand J Statist11:265–270
    [Google Scholar]
  11. Cole J. R., Chai B., Marsh T. L., Farris R. J., Wang Q., Kulam S. A., Chandra S., McGarrell D. M., Schmidt T. M. et al. 2003; The Ribosomal Database Project (RDP-II): previewing a new autoaligner that allows regular updates and the new prokaryotic taxonomy. Nucleic Acids Res31:442–443 [CrossRef][PubMed]
    [Google Scholar]
  12. de Oliveira M. N., Jewell K. A., Freitas F. S., Benjamin L. A., Tótola M. R., Borges A. C., Moraes C. A., Suen G.. 2013; Characterizing the microbiota across the gastrointestinal tract of a Brazilian Nelore steer. Vet Microbiol164:307–314 [CrossRef][PubMed]
    [Google Scholar]
  13. Dowd S. E., Callaway T. R., Wolcott R. D., Sun Y., McKeehan T., Hagevoort R. G., Edrington T. S.. 2008; Evaluation of the bacterial diversity in the feces of cattle using 16S rDNA bacterial tag-encoded FLX amplicon pyrosequencing (bTEFAP). BMC Microbiol8:125–132 [CrossRef][PubMed]
    [Google Scholar]
  14. Dridi B., Fardeau M. L., Ollivier B., Raoult D., Drancourt M.. 2012; Methanomassiliicoccus luminyensis gen. nov., sp. nov., a methanogenic archaeon isolated from human faeces. Int J Syst Evol Microbiol62:1902–1907 [CrossRef][PubMed]
    [Google Scholar]
  15. Durso L. M., Harhay G. P., Smith T. P., Bono J. L., Desantis T. Z., Harhay D. M., Andersen G. L., Keen J. E., Laegreid W. W., Clawson M. L.. 2010; Animal-to-animal variation in fecal microbial diversity among beef cattle. Appl Environ Microbiol76:4858–4862 [CrossRef][PubMed]
    [Google Scholar]
  16. Edgar R. C.. 2010; Search and clustering orders of magnitude faster than BLAST. Bioinformatics26:2460–2461 [CrossRef]
    [Google Scholar]
  17. Edgar R. C., Haas B. J., Clemente J. C., Quince C., Knight R.. 2011; UCHIME improves sensitivity and speed of chimera detection. Bioinformatics27:2194–2200 [CrossRef][PubMed]
    [Google Scholar]
  18. Fernando S. C., Purvis H. T., Najar F. Z., Sukharnikov L. O., Krehbiel C. R., Nagaraja T. G., Roe B. A., Desilva U.. 2010; Rumen microbial population dynamics during adaptation to a high-grain diet. Appl Environ Microbiol76:7482–7490 [CrossRef][PubMed]
    [Google Scholar]
  19. Forchhammer M. C.. 1995; Sex, age, and seasonal variation in the foraging dynamics of muskoxen, Ovibos moschatus, in Greenland. Can J Zool73:1344–1361 [CrossRef]
    [Google Scholar]
  20. Gantner S., Andersson A. F., Alonso-Sáez L., Bertilsson S.. 2011; Novel primers for 16S rRNA-based archaeal community analyses in environmental samples. J Microbiol Methods84:12–18 [CrossRef][PubMed]
    [Google Scholar]
  21. Good I. J.. 1953; The population frequencies of species and the estimation of populations parameters. Biometrika40:237–264 [CrossRef]
    [Google Scholar]
  22. Gorlas A., Robert C., Gimenez G., Drancourt M., Raoult D.. 2012; Complete genome sequence of Methanomassiliicoccus luminyensis, the largest genome of a human-associated Archaea species. J Bacteriol194:4745 [CrossRef][PubMed]
    [Google Scholar]
  23. Gradel C. M., Dehority B. A.. 1972; Fermentation of isolated pectin and pectin from intact forages by pure cultures of rumen bacteria. Appl Microbiol23:332–340[PubMed]
    [Google Scholar]
  24. Hamady M., Walker J. J., Harris J. K., Gold N. J., Knight R.. 2008; Error-correcting barcoded primers for pyrosequencing hundreds of samples in multiplex. Nat Methods5:235–237 [CrossRef][PubMed]
    [Google Scholar]
  25. Huang X. D., Tan H. Y., Long R., Liang J. B., Wright A. D. G.. 2012; Comparison of methanogen diversity of yak (Bos grunniens) and cattle (Bos taurus) from the Qinghai-Tibetan plateau, China. BMC Microbiol12:237 [CrossRef][PubMed]
    [Google Scholar]
  26. Iino T., Tamaki H., Tamazawa S., Ueno Y., Ohkuma M., Suzuki K., Igarashi Y., Haruta S.. 2013; Candidatus Methanogranum caenicola: a novel methanogen from the anaerobic digested sludge, and proposal of Methanomassiliicoccaceae fam. nov. and Methanomassiliicoccales ord. nov., for a methanogenic lineage of the class Thermoplasmata. Microbes Environ28:244–250 [CrossRef][PubMed]
    [Google Scholar]
  27. Ishaq S. L., Wright A. D.. 2014; High-throughput DNA sequencing of the ruminal bacteria from moose (Alces alces) in Vermont, Alaska, and Norway. Microb Ecol68:185–195 [CrossRef][PubMed]
    [Google Scholar]
  28. Johnson D. E., Ward G. M.. 1996; Estimates of animal methane emissions. Environ Monit Assess42:133–141 [CrossRef][PubMed]
    [Google Scholar]
  29. Kittelmann S., Seedorf H., Walters W. A., Clemente J. C., Knight R., Gordon J. I., Janssen P. H.. 2013; Simultaneous amplicon sequencing to explore co-occurrence patterns of bacterial, archaeal and eukaryotic microorganisms in rumen microbial communities. PLoS One8:e47879 [CrossRef][PubMed]
    [Google Scholar]
  30. Klein-Jöbstl D., Schornsteiner E., Mann E., Wagner M., Drillich M., Schmitz-Esser S.. 2014; Pyrosequencing reveals diverse fecal microbiota in Simmental calves during early development. Front Microbiol5:622 [CrossRef][PubMed]
    [Google Scholar]
  31. Lee H. J., Jung J. Y., Oh Y. K., Lee S. S., Madsen E. L., Jeon C. O.. 2012; Comparative survey of rumen microbial communities and metabolites across one caprine and three bovine groups, using bar-coded pyrosequencing and ¹H nuclear magnetic resonance spectroscopy. Appl Environ Microbiol78:5983–5993 [CrossRef][PubMed]
    [Google Scholar]
  32. Li Z., Zhang Z., Xu C., Zhao J., Liu H., Fan Z., Yang F., Wright A. D., Li G.. 2014; Bacteria and methanogens differ along the gastrointestinal tract of Chinese roe deer (Capreolus pygargus). PLoS One9:e114513 [CrossRef][PubMed]
    [Google Scholar]
  33. Liu C., Zhu Z. P., Liu Y. F., Guo T. J., Dong H. M.. 2012; Diversity and abundance of the rumen and fecal methanogens in Altay sheep native to Xinjiang and the influence of diversity on methane emissions. Arch Microbiol194:353–361 [CrossRef][PubMed]
    [Google Scholar]
  34. Lozupone C., Knight R.. 2005; UniFrac: a new phylogenetic method for comparing microbial communities. Appl Environ Microbiol71:8228–8235 [CrossRef][PubMed]
    [Google Scholar]
  35. Luo Y. H., Wright A. D., Li Y. L., Li H., Yang Q. H., Luo L. J., Yang M. X.. 2013); Diversity of methanogens in the hindgut of captive white rhinoceroses, Ceratotherium simum. BMC Microbiol 13:207
    [Google Scholar]
  36. Lwin K. O., Matsui H.. 2014; Comparative analysis of the methanogen diversity in horse and pony by using mcrA gene and archaeal 16s rRNA gene clone libraries. Archaea2014: [CrossRef][PubMed]
    [Google Scholar]
  37. Murray R. M., Bryant A. M., Leng R. A.. 1976; Rates of production of methane in the rumen and large intestine of sheep. Br J Nutr36:1–14 [CrossRef][PubMed]
    [Google Scholar]
  38. Osborne J. M., Dehority B. A.. 1989; Synergism in degradation and utilization of intact forage cellulose, hemicellulose, and pectin by three pure cultures of ruminal bacteria. Appl Environ Microbiol55:2247–2250[PubMed]
    [Google Scholar]
  39. Paul K., Nonoh J., Mikulski L., Brune A.. 2012; Methanoplasmatales, Thermoplasmatales-related Archaea in termite guts and other environment, are the seventh order of methanogens. Appl Environ Microbiol78:8245–8253
    [Google Scholar]
  40. Pope P. B., Mackenzie A. K., GregorGregor I., Smith W., Sundset M. A., McHardy A. C., Morrison M., Eijsink V. G.. 2012; Metagenomics of the Svalbard reindeer rumen microbiome reveals abundance of polysaccharide utilization loci. PLoS One7:e38571 [CrossRef][PubMed]
    [Google Scholar]
  41. Qi M., Wang P., O'Toole N., Barboza P. S., Ungerfeld E., Leigh M. B., Selinger L. B., Butler G., Tsang A. et al. 2011; Snapshot of the eukaryotic gene expression in muskoxen rumen – a metatranscriptomic approach. PLoS One6:e20521 [CrossRef][PubMed]
    [Google Scholar]
  42. R Development Core Team 2008; R: A Language and Environment for Statistical Computing Vienna: R Foundation for Statistical Computing;
    [Google Scholar]
  43. Rincón M. T., McCrae S. I., Kirby J., Scott K. P., Harry F. J.. 2001; EndB, a multidomain family 44 cellulase from Ruminococcus flavefaciens 17, binds to cellulose via a novel cellulose-binding module and to another R. flavefaciens protein via a dockerin domain. Appl Environ Microbiol67:4426–4431 [CrossRef][PubMed]
    [Google Scholar]
  44. Shannon C. E.. 1948; A Mathematical Theory of Communication. Bell Syst. Tech. J27:379–423
    [Google Scholar]
  45. Shannon P., Markiel A., Ozier O., Baliga N. S., Wang J. T., Ramage D., Amin N., Schwikowski B., Ideker T.. 2003; Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res13:2498–2504 [CrossRef][PubMed]
    [Google Scholar]
  46. Staaland H., Thing H.. 1991; Distribution of nutrients and minerals in the alimentary tract of muskoxen, Ovibos moschatus. Comp Biochem Physiol98:543–549 [CrossRef]
    [Google Scholar]
  47. Staaland H., Adamczewski J. Z., Gunn A.. 1997; A Comparison of digestive Tract Morphology in muskoxen and caribou from Victoria Island, Northwest Territories, Canada. Rangifer17:17–19 [CrossRef]
    [Google Scholar]
  48. Steelman S. M., Chowdhary B. P., Dowd S., Suchodolski J., Janečka J. E.. 2012; Pyrosequencing of 16S rRNA genes in fecal samples reveals high diversity of hindgut microflora in horses and potential links to chronic laminitis. BMC Vet Res8:231 [CrossRef][PubMed]
    [Google Scholar]
  49. Sundset M. A., Edwards J. E., Cheng Y. F., Senosiain R. S., Fraile M. N., Northwood K. S., Praesteng K. E., Glad T., Mathiesen S. D., Wright A. D. G.. 2009; Molecular diversity of the Rumen Microbiome of Norwegian reindeer on natural summer pasture. Microb Ecol57:335–348 [CrossRef][PubMed]
    [Google Scholar]
  50. Sundset M. A., Edwards J. E., Cheng Y. F., Senosiain R. S., Fraile M. N., Northwood K. S., Praesteng K. E., Glad T., Mathiesen S. D., Wright A.-D. G.. 2009b; Rumen microbial diversity in Svalbard reindeer, with particular emphasis on methanogenic archaea. FEMS Microbiol Ecol70:553–562 [CrossRef]
    [Google Scholar]
  51. Thing H., Klein D. R., Jingfors K., Holt S.. 1987; Ecology of muskoxen in Jameson Land, northeast Greenland. Holarctic Ecology10:95–103 [CrossRef]
    [Google Scholar]
  52. Turnbull K. L., Smith R. P., St-Pierre B., Wright A. D.. 2012; Molecular diversity of methanogens in fecal samples from Bactrian camels (Camelus bactrianus) at two zoos. Res Vet Sci93:246–249 [CrossRef][PubMed]
    [Google Scholar]
  53. Wallace R. J., Rooke J. A., McKain N., Duthie C. A., Hyslop J. J., Ross D. W., Waterhouse A., Watson M., Roehe R.. 2015; The rumen microbial metagenome associated with high methane production in cattle. BMC Genomics16:839 [CrossRef][PubMed]
    [Google Scholar]
  54. White R. G., Lawler J. P.. 2002; Can methane suppression during digestion of woody and leafy browse compensate for energy costs of detoxification of plant secondary compounds? A test with muskoxen fed willows and birch. Comp Biochem Physiol A Mol Integr Physiol133:849–859 [CrossRef][PubMed]
    [Google Scholar]
  55. Yu Z., Morrison M.. 2004; Improved extraction of PCR-quality community DNA from digesta and fecal samples. Biotechniques36:808–812[PubMed]
    [Google Scholar]
  56. Salgado-Flores, A., Bockwoldt, M., Hagen, L. H., Pope, P. B. & Sundset, M. A. Sequence Read Archive SRP049372. (2016)
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