Rumen metagenome and metatranscriptome analyses of low methane yield sheep reveals a Sharpea-enriched microbiome characterised by lactic acid formation and utilisation

Microbiome

Volumn 4, Issue , 2016, Pages

  Kamke, Janine ^a   Kittelmann, Sandra ^a   Soni, Priya ^a   Li, Yang ^a   Tavendale, Michael ^a   Ganesh, Siva ^a   Janssen, Peter H ^a   Shi, Weibing ^b,c   Froula, Jeff ^b,c   Rubin, Edward M ^b,c   Attwood, Graeme T ^a  

^a AGRESEARCH GRASSLANDS   (New Zealand)

^b DOE JOINT GENOME INSTITUTE   (United States)

^c LAWRENCE BERKELEY NATIONAL LABORATORY   (United States)

Author keywords

Bacteria; Lactate production; Lactate utilisation; Metagenomics; Metatranscriptomics; Methane; Sheep rumen

Indexed keywords

ACETIC ACID; ACETYL COENZYME A ACETYLTRANSFERASE; BUTYRIC ACID; LACTATE DEHYDROGENASE; LACTIC ACID; METHANE; PROPIONIC ACID; RNA 16S; BUTYRIC ACID DERIVATIVE; FATTY ACID; HEXOSE; PROPIONIC ACID DERIVATIVE;

AMINO ACID SYNTHESIS; ARTICLE; ERYSIPELOTRICHACEAE; FATTY ACID METABOLISM; GAS EVOLUTION; GENE CLUSTER; GENE EXPRESSION; GENE MAPPING; GENE SEQUENCE; GENETIC TRANSCRIPTION; LACHNOSPIRACEAE; MEGASPHAERA; METAGENOME; MICROBIAL COMMUNITY; NONHUMAN; PHENOTYPE; PREVOTELLACEAE; PRIORITY JOURNAL; RUMEN MICROORGANISM; RUMINOCOCCACEAE; SEQUENCE HOMOLOGY; SHEEP; ANIMAL; BACTERIUM; CLASSIFICATION; DNA SEQUENCE; FERMENTATION; GENETICS; GREENHOUSE EFFECT; HIGH THROUGHPUT SEQUENCING; LACTOBACILLACEAE; METABOLISM; MICROBIOLOGY; MICROFLORA; NUCLEOTIDE SEQUENCE; PHYSIOLOGY; RUMEN;

ANIMALS; BACTERIA; BASE SEQUENCE; BUTYRATES; FATTY ACIDS; FERMENTATION; GLOBAL WARMING; HEXOSES; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; LACTIC ACID; LACTOBACILLACEAE; METAGENOME; METHANE; MICROBIOTA; PROPIONATES; RNA, RIBOSOMAL, 16S; RUMEN; SEQUENCE ANALYSIS, DNA; SHEEP;

EID: 84995791150     PISSN: None     EISSN: 20492618     Source Type: Journal    
DOI: 10.1186/s40168-016-0201-2     Document Type: Article

References (50)

1. Parry ML, Canziani O, Palutikof JP. Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change, 2007. 2007. Climate Change 2007.
2. Yusuf RO, Noor ZZ, Abba AH, Hassan MAA, Din MFM. Renewable and sustainable energy reviews. Renewable and sustainable energy reviews. Elsevier. 2012;16:5059-70.
3. Goopy JP, Donaldson A, Hegarty R, Vercoe PE, Haynes F, Barnett M, Oddy VH. Low-methane yield sheep have smaller rumens and shorter rumen retention time. Br J Nutr. 2013;111:578-85.
4. Herd RM, Arthur PF, Donoghue KA, Bird SH, Bird-Gardiner T, Hegarty RS. Measures of methane production and their phenotypic relationships with dry matter intake, growth, and body composition traits in beef cattle. J Anim Sci. 2014;92:5267-74.
5. Pinares-Patiño CS, Hickey SM, Young EA, Dodds KG, MacLean S, Molano G, Sandoval E, Kjestrup H, Harland R, Hunt C, Pickering NK, McEwan JC. Heritability estimates of methane emissions from sheep. Animal. 2013;7:316-21.
6. Robinson DL, Goopy JP, Hegarty RS, Oddy VH, Thompson AN, Toovey AF, Macleay CA, Briegal JR, Woodgate RT, Donaldson AJ, Vercoe PE. Genetic and environmental variation in methane emissions of sheep at pasture. J Anim Sci. 2014;92:4349-63.
7. Benchaar C, Pomar C, Chiquette J. Evaluation of dietary strategies to reduce methane production in ruminants: a modelling approach. Canadian J Animal Sci. 2001;81:563-74.
8. Smuts M, Meissner HH, Cronjé PB. Retention time of digesta in the rumen: its repeatability and relationship with wool production of Merino rams. J Anim Sci. 1994;73:206-10.
9. Shi W, Moon CD, Leahy SC, Kang D, Froula J, Kittelmann S, Fan C, Deutsch S, Gagic D, Seedorf H, Kelly WJ, Atua R, Sang C, Soni P, Li D, Pinares-Patiño CS, McEwan JC, Janssen PH, Chen F, Visel A, Wang Z, Attwood GT, Rubin EM. Methane yield phenotypes linked to differential gene expression in the sheep rumen microbiome. Genome Res. 2014;24:1517-25.
10. Hook SE, Wright A-DG, McBride BW. Methanogens: methane producers of the rumen and mitigation strategies. Archaea. 2010;2010:1-11.
11. Hungate RE, Smith W, Bauchop T, Yu I, Rabinowitz JC. Formate as an intermediate in the bovine rumen fermentation. J Bacteriol. 1970;102:389-97.
12. Hobson PN, Stewart CS. The rumen microbial ecosystem. London: Chapman and Hall; 1997.
13. Janssen PH. Influence of hydrogen on rumen methane formation and fermentation balances through microbial growth kinetics and fermentation thermodynamics. Anim Feed Sci Technol. 2010;160:1-22.
14. Kittelmann S, Pinares-Patiño CS, Seedorf H, Kirk MR, Ganesh S, McEwan JC, Janssen PH. Two different bacterial community types are linked with the low-methane emission trait in sheep. PLoS One. 2014;9:e103171.
15. Hungate RE. Symposium: selected topics in microbial ecology. I. Microbial ecology of the rumen. Bacteriol Rev. 1960;24:353-64.
16. Reichardt N, Duncan SH, Young P, Belenguer A, Leitch CM, Scott KP, Flint HJ, Louis P. Phylogenetic distribution of three pathways for propionate production within the human gut microbiota. ISME J. 2014;8:1323-35.
17. Counotte GHM, Prins RA, Janssen RHAM, deBie MJA. Role of Megasphaera elsdenii in the fermentation of DL-[2-13C]lactate in the rumen of dairy cattle. Appl Environ Microbiol. 1981;42:649-55.
18. Wallace RJ, Rooke JA, McKain N, Duthie C-A, Hyslop JJ, Ross DW, Waterhouse A, Watson M, Roehe R. The rumen microbial metagenome associated with high methane production in cattle. BMC Genomics. 2015;16:839.
19. Roehe R, Dewhurst RJ, Duthie C-A, Rooke JA, McKain N, Ross DW, Hyslop JJ, Waterhouse A, Freeman TC, Watson M, Wallace RJ. Bovine host genetic variation influences rumen microbial methane production with best selection criterion for low methane emitting and efficiently feed converting hosts based on metagenomic gene abundance. PLoS Genet. 2016;12:e1005846.
20. Ross EM, Moate PJ, Marett L, Cocks BG, Hayes BJ. Investigating the effect of two methane-mitigating diets on the rumen microbiome using massively parallel sequencing. J Dairy Sci. 2013;96:1-17.
21. Ross EM, Moate PJ, Marett LC, Cocks BG, Hayes BJ. Metagenomic predictions: from microbiome to complex health and environmental phenotypes in humans and cattle. PLoS One. 2013;8:e73056. doi:10.1371/journal.pone. 0073056.
22. Morita H, Shiratori C, Murakami M, Takami H, Toh H, Kato Y, Nakajima F, Takagi M, Akita H, Masaoka T, Hattori M. Sharpea azabuensis gen. nov., sp. nov., a Gram-positive, strictly anaerobic bacterium isolated from the faeces of thoroughbred horses. Int J Syst Evol Microbiol. 2008;58:2682-6.
23. Bain W. Rumen differences between sheep identified as being low or high methane emitters. 10th World Congress on Genetics Applied to Livestock. 2014.
24. Dien BS, Jung H-JG, Vogel KP, Casler MD, Lamb JFS, Iten L, Mitchell RB, Sarath G. Chemical composition and response to dilute-acid pretreatment and enzymatic saccharification of alfalfa, reed canarygrass, and switchgrass. Biomass Bioenergy. 2006;30:880-91.
25. Neves AR, Pool WA, Solopova A, Kok J, Santos H, Kuipers OP. Towards enhanced galactose utilization by Lactococcus lactis. Appl Environ Microbiol. 2010; 76:7048-60.
26. Zeng L, Martino NC, Burne RA. Two gene clusters coordinate galactose and lactose metabolism in Streptococcus gordonii. Appl Environ Microbiol. 2012; 78:5597-605.
27. Bourquin LD, Fahey GC. Ruminal digestion and glycosyl linkage patterns of cell wall components from leaf and stem fractions of alfalfa, orchardgrass, and wheat straw. J Anim Sci. 1994;72:1362-74.
28. Herrmann KM, Weaver LM. The shikimate pathway. Annu Rev Plant Physiol Plant Mol Biol. 1999;50:473-503.
29. Light SH, Anderson WF. The diversity of allosteric controls at the gateway to aromatic amino acid biosynthesis. Protein Sci. 2013;22:395-404.
30. Munack S, Roderer K, ökvist M, Kamarauskaite J, Sasso S, van Eerde A, Kast P, Krengel U. Remote control by inter-enzyme allostery: a novel paradigm for regulation of the shikimate pathway. J Mol Biol. 2016;428:1237-55.
31. Tribe DE, Camakaris H, Pittard J. Constitutive and repressible enzymes of the common pathway of aromatic biosynthesis in Escherichia coli K-12:regulation of enzyme synthesis at different growth rates. J Bacteriol. 1976;127:1085-97.
32. Counotte GHM, Prins RA. Regulation of lactate metabolism in the rumen. Vet Res Commun. 1981;5:101-15.
33. Hungate RE. Chapter II-the rumen bacteria. In: The rumen and its microbes. New York: Academic; 1966. p. 8-90.
34. Salvetti E, Felis GE, Dellaglio F, Castioni A, Torriani S, Lawson PA. Reclassification of Lactobacillus catenaformis (Eggerth 1935) Moore and Holdeman 1970 and Lactobacillus vitulinus Sharpe et al. 1973 as Eggerthia catenaformis gen. nov., comb. nov. and Kandleria vitulina gen. nov., comb. nov., respectively. Int J Syst Evol Microbiol. 2011;61:2520-4.
35. Mackie RI, Gilchrist FMC. Changes in lactate-producing and lactate-utilizing bacteria in relation to pH in the rumen of sheep during stepwise adaptation to a high-concentrate diet. Appl Environ Microbiol. 1979;38:422-30.
36. Klieve AV, Hennessy D, Ouwerkerk D, Forster RJ, Mackie RI, Attwood GT. Establishing populations of Megasphaera elsdenii YE 34 and Butyrivibrio fibrisolvens YE 44 in the rumen of cattle fed high grain diets. J Appl Microbiol. 2002;95:621-30.
37. Shabat SKB, Sasson G, Doron-Faigenboim A, Durman T, Yaacoby S, Berg Miller ME, White BA, Shterzer N, Mizrahi I. Specific microbiome-dependent mechanisms underlie the energy harvest efficiency of ruminants. The ISME Journal. 2016;1-15. doi:10.1038/ismej.2016.62.
38. Prabhu R, Altman E, Eiteman MA. Lactate and acrylate metabolism by Megasphaera elsdenii under batch and steady-state conditions. Appl Environ Microbiol. 2012;78:8564-70.
39. Flatt WP, Warner RG, Loosli JK. Influence of purified materials on the development of the ruminant stomach. J Dairy Sci. 1958;41:1593-600.
40. Sander EG, Warner RG, Harrison HN, Loosli JK. The stimulatory effect of sodium butyrate and sodium propionate on the development of rumen mucosa in the young calf. J Dairy Sci. 1959;42:1600-5.
41. Dijkstra J, Boer H, Van Bruchem J, Bruining M, Tamminga S. Absorption of volatile fatty acids from the rumen of lactating dairy cows as influenced by volatile fatty acid concentration, pH and rumen liquid volume. Br J Nutr. 2007;69:385-96.
42. Pinares-Patiño CS, Ebrahimi SH, McEwan JC, Clark H, Luo D. Is rumen retention time implicated in sheep differences in methane emission? Proceedings New Zealand Soc Animal Prod. 2011;71:219-22.
43. Pinares-Patiño CS, McEwan JC, Dodds KG, Cárdenas EA, Hegarty RS, Koolaard JP, Clark H. Repeatability of methane emissions from sheep. Anim Feed Sci Technol. 2011;166:210-8.
44. Subramanian A, Kuehn H, Gould J, Tamayo P, Mesirov JP. GSEA-P: a desktop application for gene set enrichment analysis. Bioinformatics. 2007;23:3251-3.
45. Team RC. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2013.
46. Chung D, Chun H, Keles S. Spls: sparse partial least squares (SPLS) regression and classification. 2012. R package.
47. Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32:1792-7.
48. Ludwig W, Strunk O, Westram R, Richter L, Meier H, Yadhukumar, Buchner A, Lai T, Steppi S, Jobb G, Foèrster W, Brettske I, Gerber S, Ginhart AW, Gross O,Grumann S, Hermann S, Jost R, Koènig A, Liss T, Luèûmann R, May M, Nonhoff B, Reichel B, Strehlow R, Stamatakis A, Stuckmann N, Vilbig A, Lenke M, Ludwig T, Bode A, Schleifer K-H. ARB: a software environment for sequence data. Nucleic Acids Res. 2003;32:1363-71.
49. Stamatakis A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics. 2014;30:1312-3.
50. Nordberg H, Cantor M, Dusheyko S, Hua S, Poliakov A, Shabalov I, Smirnova T, Grigoriev IV, Dubchal I. The genome portal of the Department of Energy Joint Genome Institute: 2014 updates. Nucleic Acids Res. 2014;42:D26-31.