DOI QR코드

DOI QR Code

Understanding the functionality of the rumen microbiota: searching for better opportunities for rumen microbial manipulation

  • Wenlingli Qi (Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Sciences, Zhejiang University) ;
  • Ming-Yuan Xue (Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Sciences, Zhejiang University) ;
  • Ming-Hui Jia (Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Sciences, Zhejiang University) ;
  • Shuxian Zhang (CAS Key Laboratory of Agro-Ecological Processes in Subtropical Region, Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, Institute of Subtropical Agriculture, Chinese Academy of Sciences) ;
  • Qiongxian Yan (CAS Key Laboratory of Agro-Ecological Processes in Subtropical Region, Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, Institute of Subtropical Agriculture, Chinese Academy of Sciences) ;
  • Hui-Zeng Sun (Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Sciences, Zhejiang University)
  • 투고 : 2023.08.17
  • 심사 : 2023.11.03
  • 발행 : 2024.02.01

초록

Rumen microbiota play a central role in the digestive process of ruminants. Their remarkable ability to break down complex plant fibers and proteins, converting them into essential organic compounds that provide animals with energy and nutrition. Research on rumen microbiota not only contributes to improving animal production performance and enhancing feed utilization efficiency but also holds the potential to reduce methane emissions and environmental impact. Nevertheless, studies on rumen microbiota face numerous challenges, including complexity, difficulties in cultivation, and obstacles in functional analysis. This review provides an overview of microbial species involved in the degradation of macromolecules, the fermentation processes, and methane production in the rumen, all based on cultivation methods. Additionally, the review introduces the applications, advantages, and limitations of emerging omics technologies such as metagenomics, meta-transcriptomics, metaproteomics, and metabolomics, in investigating the functionality of rumen microbiota. Finally, the article offers a forward-looking perspective on the new horizons and technologies in the field of rumen microbiota functional research. These emerging technologies, with continuous refinement and mutual complementation, have deepened our understanding of rumen microbiota functionality, thereby enabling effective manipulation of the rumen microbial community.

키워드

과제정보

This study was supported by the National Key R&D Program Project (2022YFD1301700).

참고문헌

  1. Langda S, Zhang C, Zhang K, et al. Diversity and composition of rumen bacteria, fungi, and protozoa in goats and sheep living in the same high-altitude pasture. Animals (Basel) 2020;10:186. https://doi.org/10.3390/ani10020186
  2. Cammack KM, Austin KJ, Lamberson WR, Conant GC, Cunningham HC. RUMINNAT NUTRITION SYMPOSIUM: Tiny but mighty: the role of the rumen microbes in livestock production. J Anim Sci 2018;96:752-70. https://doi.org/10.1093/jas/skx053
  3. Poulsen M, Schwab C, Borg Jensen B, et al. Methylotrophic methanogenic Thermoplasmata implicated in reduced methane emissions from bovine rumen. Nat Commun 2013;4:1428. https://doi.org/10.1038/ncomms2432
  4. Hess M, Sczyrba A, Egan R, et al. Metagenomic discovery of biomass-degrading genes and genomes from cow rumen. Science 2011;331:463-7. https://doi.org/10.1126/science.1200387
  5. Stewart RD, Auffret MD, Warr A, et al. Assembly of 913 microbial genomes from metagenomic sequencing of the cow rumen. Nat Commun 2018;9:870. https://doi.org/10.1038/s41467-018-03317-6
  6. Morais S, Mizrahi I. The road not taken: the rumen microbiome, functional groups, and community states. Trends Microbiol 2019;27:538-49. https://doi.org/10.1016/j.tim.2018.12.011
  7. Benson AK, Kelly SA, Legge R, et al. Individuality in gut microbiota composition is a complex polygenic trait shaped by multiple environmental and host genetic factors. Proc Natl Acad Sci USA 2010;107:18933-8. https://doi.org/10.1073/pnas.1007028107
  8. Taxis TM, Wolff S, Gregg SJ, et al. The players may change but the game remains: network analyses of ruminal microbiomes suggest taxonomic differences mask functional similarity. Nucleic Acids Res 2015;43:9600-12. https://doi.org/10.1093/nar/gkv973
  9. Boon E, Meehan CJ, Whidden C, Wong DHJ, Langille MGI, Beiko RG. Interactions in the microbiome: communities of organisms and communities of genes. FEMS Microbiol Rev 2020;38:90-118. https://doi.org/10.1111/1574-6976.12035
  10. Ransom-Jones E, Jones DL, McCarthy AJ, McDonald JE. The fibrobacteres: an important phylum of cellulose-degrading bacteria. Microb Ecol 2012;63:267-81. https://doi.org/10.1007/s00248-011-9998-1
  11. Morais S, Mizrahi I. Islands in the stream: from individual to communal fiber degradation in the rumen ecosystem. FEMS Microbiol Rev 2019;43:362-79. https://doi.org/10.1093/femsre/fuz007
  12. Stevenson DM, Weimer PJ. Dominance of Prevotella and low abundance of classical ruminal bacterial species in the bovine rumen revealed by relative quantification real-time PCR. Appl Microbiol Biotechnol 2007;75:165-74. https://doi.org/10.1007/s00253-006-0802-y
  13. Yeoman CJ, Fields CJ, Lepercq P, et al. In vivo competitions between fibrobacter succinogenes, ruminococcus flavefaciens, and ruminoccus albus in a gnotobiotic sheep model revealed by multi-omic analyses. Mbio 2021;12:10.1128/mbio.0353320. https://doi.org/10.1128/mbio.03533-20
  14. Hungate RE. Microorganisms in the rumen of cattle fed a constant ration. Can J Microbiol 1957;3:289-311. https://doi.org/10.1139/m57-034
  15. Rodriguez Hernaez J, Ceron Cucchi ME, Cravero S, et al. The first complete genomic structure of Butyrivibrio fibrisolvens and its chromid. Microb Genomics 2018;4:e000216. https://doi.org/10.1099/mgen.0.000216
  16. Weimer PJ. Degradation of cellulose and hemicellulose by ruminal microorganisms. Microorganisms 2022;10:2345. https://doi.org/10.3390/microorganisms10122345
  17. Paul SS, Deb SM, Punia BS, Singh D, Kumar R. Fibrolytic potential of anaerobic fungi (Piromyces sp.) isolated from wild cattle and blue bulls in pure culture and effect of their addition on in vitro fermentation of wheat straw and methane emission by rumen fluid of buffaloes. J Sci Food Agric 2010;90:1218-26. https://doi.org/10.1002/jsfa.3952
  18. Saye LMG, Navaratna TA, Chong JPJ, O'Malley MA, Theodorou MK, Reilly M. The anaerobic fungi: challenges and opportunities for industrial lignocellulosic biofuel production. Microorganisms 2021;9:694. https://doi.org/10.3390/microorganisms9040694
  19. Coen JA, Dehority BA. Degradation and utilization of hemicellulose from intact forages by pure cultures of rumen bacteria. Appl Microbiol 1970;20:362-8. https://doi.org/10.1128/am.20.3.362-368.1970
  20. Emerson EL, Weimer PJ. Fermentation of model hemicelluloses by Prevotella strains and Butyrivibrio fibrisolvens in pure culture and in ruminal enrichment cultures. Appl Microbiol Biotechnol 2017;101:4269-78. https://doi.org/10.1007/s00253-017-8150-7
  21. Patel S, Ambalam P. Role of rumen protozoa: metabolic and fibrolytic. Adv Biotechnol Microbiol 2018;10:555793. https://doi.org/10.19080/AIBM.2018.10.555793
  22. Anderson KL. Biochemical analysis of starch degradation by Ruminobacter amylophilus 70. Appl Environ Microbiol 1995;61:1488-91. https://doi.org/10.1128/aem.61.4.14881491.1995
  23. Cerqueira FM, Photenhauer AL, Pollet RM, Brown HA, Koropatkin NM. Starch digestion by gut bacteria: crowdsourcing for carbs. Trends Microbiol 2020;28:95-108. https://doi.org/10.1016/j.tim.2019.09.004
  24. Ze X, Ben David Y, Laverde-Gomez JA, et al. Unique organization of extracellular amylases into amylosomes in the resistant starch-utilizing human colonic firmicutes bacterium Ruminococcus bromii. Mbio 2015;6:e01058-01015. https://doi.org/10.1128/mBio.01058-15
  25. Hua D, Hendriks WH, Xiong B, Pellikaan WF. Starch and cellulose degradation in the rumen and applications of metagenomics on ruminal microorganisms. Animals-Basel 2022;12:3020. https://doi.org/10.3390/ani12213020
  26. McAllister TA, Cheng KJ, Rode LM, Forsberg CW. Digestion of barley, maize, and wheat by selected species of ruminal bacteria. Appl Environ Microbiol 1990;56:3146-53. https://doi.org/10.1128/aem.56.10.3146-3153.1990
  27. McAllister TA, Cheng KJ. Microbial strategies in the ruminal digestion of cereal grains. Anim Feed Sci Technol 1996;62:29-36. https://doi.org/10.1016/S0377-8401(96)01003-6
  28. Coleman GS. The metabolism of rumen ciliate protozoa. FEMS Microbiol Rev 1986;2:321-44. https://doi.org/10.1111/j.1574-6968.1986.tb01864.x
  29. McAllister TA, Dong Y, Yank LJ, et al. Cereal grain digestion by selected strains of ruminal fungi. Can J Microbiol 1993;39:367-76. https://doi.org/10.1139/m93-054
  30. Liu J, Wang JK, Zhu W, et al. Monitoring the rumen pectinolytic bacteria Treponema saccharophilum using real-time PCR. FEMS Microbiol Ecol 2014;87:576-85. https://doi.org/10.1111/1574-6941.12246
  31. Cai S, Li J, Hu FZ, et al. Cellulosilyticum ruminicola, a newly described rumen bacterium that possesses redundant fibrolytic-protein-encoding genes and degrades lignocellulose with multiple carbohydrate- borne fibrolytic enzymes. Appl Environ Microbiol 2010;76:3818-24. https://doi.org/10.1128/AEM.03124-09
  32. Marounek M, Duskova D. Metabolism of pectin in rumen bacteria Butyrivibrio fibrisolvens and Prevotella ruminicola. Lett Appl Microbiol 1999;29:429-33. https://doi.org/10.1046/j.1472-765X.1999.00671.x
  33. Tan P, Liu H, Zhao J, et al. Amino acids metabolism by rumen microorganisms: Nutrition and ecology strategies to reduce nitrogen emissions from the inside to the outside. Sci Total Environ 2021;800:149596. https://doi.org/10.1016/j.scitotenv.2021.149596
  34. Hartinger T, Gresner N, Sudekum KH. Does intra-ruminal nitrogen recycling waste valuable resources? A review of major players and their manipulation. J Anim Sci Biotechnol 2018;9:33. https://doi.org/10.1186/s40104-018-0249-x
  35. Belanche A, Doreau M, Edwards JE, Moorby JM, Pinloche E, Newbold CJ. Shifts in the rumen microbiota due to the type of carbohydrate and level of protein ingested by dairy cattle are associated with changes in rumen fermentation. J Nutr 2012;142:1684-92. https://doi.org/10.3945/jn.112.159574
  36. Cotta MA, Hespell RB. Proteolytic activity of the ruminal bacterium Butyrivibrio fibrisolvens. Appl Environ Microbiol 1986;52:51-8. https://doi.org/10.1128/aem.52.1.51-58.1986
  37. Wallace RJ, McKain N, Broderick GA, et al. Peptidases of the rumen bacterium, Prevotella ruminicola. Anaerobe 1997;3:35-42. https://doi.org/10.1006/anae.1996.0065
  38. Prins RA, van Rheenen DL, van't Klooster AT. Characterization of microbial proteolytic enzymes in the rumen. Antonie van Leeuwenhoek 1983;49:585-95. https://doi.org/10.1007/BF00399852
  39. Coleman GS. Hydrolysis of Fraction 1 leaf protein and casein by rumen entodiniomorphid protozoa. J Appl Bacteriol 1983;55:111-8. https://doi.org/10.1111/j.1365-2672.1983.tb02654.x
  40. Asao N, Ushida K, Kojima Y. Proteolytic activity of rumen fungi belonging to the genera Neocallimastix and Piromyces. Lett Appl Microbiol 1993;16:247-50. https://doi.org/10.1111/j.1472-765X.1993.tb01410.x
  41. Wallace RJ, McKain N. A survey of peptidase activity in rumen bacteria. J Gen Microbiol 1991;137:2259-64. https://doi.org/10.1099/00221287-137-9-2259
  42. Wallace RJ, McKain N, Newbold CJ. Metabolism of small peptides in rumen fluid. Accumulation of intermediates during hydrolysis of alanine oligomers, and comparison of peptidolytic activities of bacteria and protozoa. J Sci Food Agric 1990;50:191-9. https://doi.org/10.1002/jsfa.2740500207
  43. Hobson PN, Mann SO. The isolation of glycerol-fermenting and lipolytic bacteria from the rumen of the sheep. J Gen Microbiol 1961;25:227-40. https://doi.org/10.1099/0022128725-2-227
  44. Jarvis GN, Moore ERB. Lipid metabolism and the rumen microbial ecosystem. In: Timmis KN, editor. Handbook of hydrocarbon and lipid microbiology. Berlin, Heidelberg, Germany: Springer; 2010. pp. 2245-57. https://doi.org/10.1007/978-3-540-77587-4_163
  45. Wallace RJ, Brammall ML. The role of different species of bacteria in the hydrolysis of protein in the rumen. J Gen Microbiol 1985;131:821-32. https://doi.org/10.1099/00221287-131-4-821
  46. Lourenco M, Ramos-Morales E, Wallace RJ. The role of microbes in rumen lipolysis and biohydrogenation and their manipulation. Animal 2010;4:1008-23. https://doi.org/10.1017/S175173111000042X
  47. Jenkins TC, Wallace RJ, Moate PJ, Mosley EE. BOARD-INVITED REVIEW: Recent advances in biohydrogenation of unsaturated fatty acids within the rumen microbial ecosystem. J Anim Sci 2008;86:397-412. https://doi.org/10.2527/jas.2007-0588
  48. Nagaraja TG. Microbiology of the rumen. In: Millen DD, De Beni Arrigoni M, Lauritano Pacheco RD, editors. Rumenology. Cham: Springer International Publishing; 2016. pp. 39-61. https://doi.org/10.1007/978-3-319-30533-2_2
  49. Seshadri R, Leahy SC, Attwood GT, et al. Cultivation and sequencing of rumen microbiome members from the Hungate 1000 collection. Nat Biotechnol 2018;36:359-67. https://doi.org/10.1038/nbt.4110
  50. Song H, Lee SY. Production of succinic acid by bacterial fermentation. Enzyme Microb Technol 2006;39:352-61. https://doi.org/10.1016/j.enzmictec.2005.11.043
  51. Gylswyk van NO. Succiniclasticum ruminis gen. nov., sp. nov., a ruminal bacterium converting succinate to propionate as the sole energy-yielding mechanism. Int J Syst Evol Microbiol 1995;45:297-300. https://doi.org/10.1099/00207713-45-2-297
  52. Wei W, Zhen Y, Wang Y, Shahzad K, Wang M. Advances of rumen functional bacteria and the application of microencapsulation fermentation technology in ruminants: a review. Fermentation 2022;8:564. https://doi.org/10.3390/fermentation8100564
  53. Wallace RJ. Ruminal microbial metabolism of peptides and amino acids. J Nutr 1996;126:1326S-34S. https://doi.org/10.1093/jn/126.suppl_4.1326S
  54. Mizrahi I, Wallace RJ, Morais S. The rumen microbiome: balancing food security and environmental impacts. Nat Rev Microbiol 2021;19:553-66. https://doi.org/10.1038/s41579-021-00543-6
  55. Malik PK, Trivedi S, Mohapatra A, et al. Comparison of enteric methane yield and diversity of ruminal methanogens in cattle and buffaloes fed on the same diet. PLoS One 2021;16:e0256048. https://doi.org/10.1371/journal.pone.0256048
  56. Lan W, Yang C. Ruminal methane production: associated microorganisms and the potential of applying hydrogen-utilizing bacteria for mitigation. Sci Total Environ 2019;654:1270-83. https://doi.org/10.1016/j.scitotenv.2018.11.180
  57. Liu Y, Whitman WB. Metabolic, phylogenetic, and ecological diversity of the methanogenic archaea. Ann NY Acad Sci 2008;1125:171-89. https://doi.org/10.1196/annals.1419.019
  58. Liu J, Chen H, Zhu Q, et al. A novel pathway of direct methane production and emission by eukaryotes including plants, animals and fungi: an overview. Atmos Environ 2015;115:26-35. https://doi.org/10.1016/j.atmosenv.2015.05.019
  59. Watson M. New insights from 33,813 publicly available metagenome-assembled-genomes (MAGs) assembled from the rumen microbiome. bioRxiv 2021;2021.04. 02.438222. https://doi.org/10.1101/2021.04.02.438222
  60. Handelsman J, Rondon MR, Brady SF, Clardy J, Goodman RM. Molecular biological access to the chemistry of unknown soil microbes: a new frontier for natural products. Chem Biol 1998;5:R245-9. https://doi.org/10.1016/s1074-5521(98)90108-9
  61. Brulc JM, Antonopoulos DA, Berg Miller ME, et al. Gene-centric metagenomics of the fiber-adherent bovine rumen microbiome reveals forage specific glycoside hydrolases. Proc Natl Acad Sci USA 2009;106:1948-53. https://doi.org/10.1073/pnas.0806191105
  62. Pope PB, Mackenzie AK, Gregor I, et al. Metagenomics of the svalbard reindeer rumen microbiome reveals abundance of polysaccharide utilization loci. PLoS One 2012;7:e38571. https://doi.org/10.1371/journal.pone.0038571
  63. Dai X, Zhu Y, Luo Y, et al. Metagenomic insights into the fibrolytic microbiome in yak rumen. PLoS One 2012;7:e40430. https://doi.org/10.1371/journal.pone.0040430
  64. 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;96:6030-46. https://doi.org/10.3168/jds.20136766
  65. Denman SE, Martinez Fernandez G, Shinkai T, Mitsumori M, McSweeney CS. Metagenomic analysis of the rumen microbial community following inhibition of methane formation by a halogenated methane analog. Front Microbiol 2015;6:1087. https://doi.org/10.3389/fmicb.2015.01087
  66. Auffret MD, Dewhurst RJ, Duthie CA, et al. The rumen microbiome as a reservoir of antimicrobial resistance and pathogenicity genes is directly affected by diet in beef cattle. Microbiome 2017;5:159. https://doi.org/10.1186/s40168-017-0378-z
  67. Wallace RJ, Rooke JA, McKain N, et al. The rumen microbial metagenome associated with high methane production in cattle. BMC Genomics 2015;16:839. https://doi.org/10.1186/s12864-015-2032-0
  68. Auffret MD, Stewart R, Dewhurst RJ, et al. Identification, comparison, and validation of robust rumen microbial biomarkers for methane emissions using diverse bos taurus breeds and basal diets. Front Microbiol 2018;8:2642. https://doi.org/10.3389/fmicb.2017.02642
  69. Shi W, Moon CD, Leahy SC, et al. Methane yield phenotypes linked to differential gene expression in the sheep rumen microbiome. Genome Res 2014;24:1517-25. https://doi.org/10.1101/gr.168245.113
  70. Kamke J, Kittelmann S, Soni P, et al. Rumen metagenome and metatranscriptome analyses of low methane yield sheep reveals a Sharpea-enriched microbiome characterised by lactic acid formation and utilisation. Microbiome 2016;4:56. https://doi.org/10.1186/s40168-016-0201-2
  71. Shabat SKB, Sasson G, Doronfaigenboim A, et al. Specific microbiome-dependent mechanisms underlie the energy harvest efficiency of ruminants. ISME J 2016;10:2958-72. https://doi.org/10.1038/ismej.2016.62
  72. Li F, Hitch TCA, Chen Y, Creevey CJ, Guan LL. Comparative metagenomic and metatranscriptomic analyses reveal the breed effect on the rumen microbiome and its associations with feed efficiency in beef cattle. Microbiome 2019;7:6. https://doi.org/10.1186/s40168-019-0618-5
  73. Yang C, Chowdhury D, Zhang Z, et al. A review of computational tools for generating metagenome-assembled genomes from metagenomic sequencing data. Comput Struct Biotechnol J 2021;19:6301-14. https://doi.org/10.1016/j.csbj.2021.11.028
  74. Meijenfeldt von FAB, Arkhipova K, Cambuy DD, Coutinho FH, Dutilh BE. Robust taxonomic classification of uncharted microbial sequences and bins with CAT and BAT. Genome Biol 2019;20:217. https://doi.org/10.1186/s13059-019-1817-x
  75. Andrews SJ, Rothnagel JA. Emerging evidence for functional peptides encoded by short open reading frames. Nat Rev Genet 2014;15:193-204. https://doi.org/10.1038/nrg3520
  76. Xie F, Jin W, Si H, et al. An integrated gene catalog and over 10,000 metagenome-assembled genomes from the gastrointestinal microbiome of ruminants. Microbiome 2021;9:137. https://doi.org/10.1186/s40168-021-01078-x
  77. Jiang Q, Lin L, Xie F, et al. Metagenomic insights into the microbe-mediated B and K2 vitamin biosynthesis in the gastrointestinal microbiome of ruminants. Microbiome 2022;10:109. https://doi.org/10.1186/s40168-022-01298-9
  78. Lin L, Lai Z, Yang H, et al. Genome-centric investigation of bile acid metabolizing microbiota of dairy cows and associated diet-induced functional implications. ISME J 2023;17:17284. https://doi.org/10.1038/s41396-022-01333-5
  79. Chen LX, Anantharaman K, Shaiber A, Murat Eren A, Banfield JF. Accurate and complete genomes from metagenomes. Genome Res 2020;30:315-33. https://doi.org/10.1101/gr.258640.119
  80. Kim CY, Ma J, Lee I. HiFi metagenomic sequencing enables assembly of accurate and complete genomes from human gut microbiota. Nat Commun 2022;13:6367. https://doi.org/10.1038/s41467-022-34149-0
  81. Olson ND, Treangen TJ, Hill CM, et al. Metagenomic assembly through the lens of validation: recent advances in assessing and improving the quality of genomes assembled from metagenomes. Brief Bioinform 2019;20:1140-50. https://doi.org/10.1093/bib/bbx098
  82. Simon C, Daniel R. Metagenomic analyses: past and future trends. Appl Environ Microbiol 2011;77:1153-61. https://doi.org/10.1128/AEM.02345-10
  83. Aguiar-Pulido V, Huang W, Suarez-Ulloa V, Cickovski T, Mathee K, Narasimhan G. Metagenomics, metatranscriptomics, and metabolomics approaches for microbiome analysis. Evol Bioinform Online 2016;12s1:5-16. https://doi.org/10.4137/EBO.S36436
  84. Qi M, Wang P, O'Toole N, et al. Snapshot of the eukaryotic gene expression in muskoxen rumen-a metatranscriptomic approach. PLoS One 2011;6:e20521. https://doi.org/10.1371/journal.pone.0020521
  85. Dai X, Tian Y, Li J, et al. Metatranscriptomic analyses of plant cell wall polysaccharide degradation by microorganisms in the cow rumen. Appl Environ Microbiol 2015;81:1375-86. https://doi.org/10.1128/AEM.03682-14
  86. Shinkai T, Mitsumori M, Sofyan A, et al. Comprehensive detection of bacterial carbohydrate-active enzyme coding genes expressed in cow rumen. Anim Sci J 2016;87:136370. https://doi.org/10.1111/asj.12585
  87. Comtet-Marre S, Parisot N, Lepercq P, et al. Metatranscriptomics reveals the active bacterial and eukaryotic fibrolytic communities in the rumen of dairy cow fed a mixed diet. Front Microbiol 2017;8:67. https://doi.org/10.3389/fmicb.2017.00067
  88. 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;62:313-22. https://doi.org/10.1111/j.1574-6941.2007.00394.x
  89. Hart EH, Creevey CJ, Hitch T, Kingston-Smith AH. Metaproteomics of rumen microbiota indicates niche compartmentalisation and functional dominance in a limited number of metabolic pathways between abundant bacteria. Sci Rep 2018;8:10504. https://doi.org/10.1038/s41598-018-28827-7
  90. Sasson G, Morais S, Kokou F, et al. Metaproteome plasticity sheds light on the ecology of the rumen microbiome and its connection to host traits. ISME J 2022;16:2610-21. https://doi.org/10.1038/s41396-022-01295-8
  91. Schiebenhoefer H, Van Den Bossche T, Fuchs S, Renard BY, Muth T, Martens L. Challenges and promise at the interface of metaproteomics and genomics: an overview of recent progress in metaproteogenomic data analysis. Expert Rev Proteomics 2019;16:375-90. https://doi.org/10.1080/14789450.2019.1609944
  92. Toyoda A, Iio W, Mitsumori M, et al. Isolation and identification of cellulose-binding proteins from sheep rumen contents. Appl Environ Microbiol 2009;75:1667-73. https://doi.org/10.1128/aem.01838-08
  93. Snelling TJ, Wallace RJ. The rumen microbial metaproteome as revealed by SDS-PAGE. BMC Microbiol 2017;17:9. https://doi.org/10.1186/s12866-016-0917-y
  94. Andersen TO, Altshuler I, Vera-Ponce de Leon A, et al. Metabolic influence of core ciliates within the rumen microbiome. ISME J 2023;17:1128-40. https://doi.org/10.1038/s41396-023-01407-y
  95. Deusch S, Seifert J. Catching the tip of the iceberg - Evaluation of sample preparation protocols for metaproteomic studies of the rumen microbiota. Proteomics 2015;15:3590-5. https://doi.org/10.1002/pmic.201400556
  96. Deusch S, Camarinha-Silva A, Conrad J, Beifuss U. A structural and functional elucidation of the rumen microbiome influenced by various diets and microenvironments. Front Microbiol 2017;8:1605. https://doi.org/10.3389/fmicb.2017.01605
  97. Kueger S, Steinhauser D, Willmitzer L, Giavalisco P. High-resolution plant metabolomics: from mass spectral features to metabolites and from whole-cell analysis to subcellular metabolite distributions. Plant J 2012;70:39-50. https://doi.org/10.1111/j.1365-313X.2012.04902.x
  98. Yang Q, Zhang A, Miao J, et al. Metabolomics biotechnology, applications, and future trends: a systematic review. RSC Adv 2019;9:37245-57. https://doi.org/10.1039/C9RA06697G
  99. Artegoitia VM, Foote AP, Lewis RM, Freetly HC. Rumen fluid metabolomics analysis associated with feed efficiency on crossbred steers. Sci Rep 2017;7:2864. https://doi.org/10.1038/s41598-017-02856-0
  100. Saleem F, Ametaj BN, Bouatra S, et al. A metabolomics approach to uncover the effects of grain diets on rumen health in dairy cows. J Dairy Sci 2012;95:6606-23. https://doi.org/10.3168/jds.2012-5403
  101. Ametaj BN, Zebeli Q, Saleem F, et al. Metabolomics reveals unhealthy alterations in rumen metabolism with increased proportion of cereal grain in the diet of dairy cows. Metabolomics 2010;6:583-94. https://doi.org/10.1007/s11306-010-0227-6
  102. Saleem F, Bouatra S, Guo AC, et al. The bovine ruminal fluid metabolome. Metabolomics 2013;9:360-78. https://doi.org/10.1007/s11306-012-0458-9
  103. Saro C, Hohenester UM, Bernard M, et al. Effectiveness of interventions to modulate the rumen microbiota composition and function in pre-ruminant and ruminant lambs. Front Microbiol 2018;9:1273. https://doi.org/10.3389/fmicb.2018.01273
  104. Morgavi DP, Rathahao-Paris E, Popova M, Boccard J, Nielsen KF, Boudra H. Rumen microbial communities influence metabolic phenotypes in lambs. Front Microbiol 2015;6:1060. https://doi.org/10.3389/fmicb.2015.01060
  105. Solden LM, Hoyt DW, Collins WB, et al. New roles in hemi-cellulosic sugar fermentation for the uncultivated Bacteroidetes family BS11. ISME J 2017;11:691-703. https://doi.org/10.1038/ismej.2016.150
  106. Li Z, Wang X, Zhang Y, et al. Genomic insights into the phylogeny and biomass-degrading enzymes of rumen ciliates. ISME J 2022;16:2775-87. https://doi.org/10.1038/s41396-022-01306-8
  107. Anderson CL, Sullivan MB, Fernando SC. Dietary energy drives the dynamic response of bovine rumen viral communities. Microbiome 2017;5:155. https://doi.org/10.1186/s40168-017-0374-3
  108. Solden LM, Naas AE, Roux S, et al. Interspecies cross-feeding orchestrates carbon degradation in the rumen ecosystem. Nat Microbiol 2018;3:1274-84. https://doi.org/10.1038/s41564-018-0225-4
  109. Kadosh E, Snir-Alkalay I, Venkatachalam A, et al. The gut microbiome switches mutant p53 from tumour-suppressive to oncogenic. Nature 2020;586:133-8. https://doi.org/10.1038/s41586-020-2541-0
  110. Jing X, Gou H, Gong Y, et al. Raman-activated cell sorting and metagenomic sequencing revealing carbon-fixing bacteria in the ocean. Environ Microbiol 2018;20:2241-55. https://doi.org/10.1111/1462-2920.14268
  111. Santra A, Karim SA. Rumen manipulation to improve animal productivity. Asian-Australas J Anim Sci 2003;16:748-63. https://doi.org/10.5713/ajas.2003.748
  112. Weimer PJ. Redundancy, resilience, and host specificity of the ruminal microbiota: implications for engineering improved ruminal fermentations. Front Microbiol 2015;6:296. https://doi.org/10.3389/fmicb.2015.00296
  113. Li F, Li C, Chen Y, et al. Host genetics influence the rumen microbiota and heritable rumen microbial features associate with feed efficiency in cattle. Microbiome 2019;7:92. https://doi.org/10.1186/s40168-019-0699-1
  114. Malmuthuge N, Guan LL. Understanding host-microbial interactions in rumen: searching the best opportunity for microbiota manipulation. J Anim Sci Biotechnol 2017;8:8. https://doi.org/10.1186/s40104-016-0135-3