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Rumen Metagenomics

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Abstract

The rumen microbiome plays a critical role in normal physiology and nutrition of ruminants. Alterations in the rumen microbiome have important physiological and pathological implications. The advent of next-generation sequencing technologies and rapid development of computational tools and reference databases provide powerful tools in rumen microbiome studies. Rumen metagenomics enables studies on the collective genetic structure and functional composition of the rumen microbial community in a culture-independent manner and can be simply divided into functional metagenomics and sequencing-based computational metagenomics. Recent progresses in mining the rumen microbial community for novel enzymes, such as fibrolytic enzymes, or other biomolecules for industry and biotechnology applications using functional screening are discussed. Rapid advances in computational metagenomic tools and methods are summarized. Metagenomics has provided novel insights into the structure and function of the rumen microbiome. Recent efforts suggest that the core rumen microbiome consists of 8 phyla and 15 families, which likely contribute to the basic function of the rumen. Systematic investigations of the rumen microbiome, including its viral (virome) and plasmid (plasmidome) fractions, have revealed previously unrecognized biodiversity in the rumen. Resistance and resilience of the rumen microbial community in response to perturbation is also discussed. Moreover, the need for mechanistic models and applications of general ecological theories and principles in rumen metagenomic studies is emphasized.

Keywords

  • Rumen
  • Microbiome
  • Microbiota, metagenomics
  • 16S rRNA gene
  • Functional screening
  • Ruminant
  • Microbial
  • Ecosystem
  • Resilience
  • Next-generation sequencing
  • Assembly

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Fig. 16.1

References

  • Afiahayati, Sato K, Sakakibara Y (2013) An extended genovo metagenomic assembler by incorporating paired-end information. Peer J 1:e196

    Google Scholar 

  • Ander C, Schulz-Trieglaff OB, Stoye J et al (2013) MetaBEETL: high-throughput analysis of heterogeneous microbial populations from shotgun DNA sequences. BMC Bioinfo 14(Suppl 5) :S2

    Google Scholar 

  • Berg Miller ME, Yeoman CJ, Chia N et al (2012) Phage-bacteria relationships and CRISPR elements revealed by a metagenomic survey of the rumen microbiome. Environ Microbiol 14:207–227

    CAS  PubMed  Google Scholar 

  • Bhatt VD, Dande SS, Patil NV et al (2013) Molecular analysis of the bacterial microbiome in the forestomach fluid from the dromedary camel (Camelus dromedarius). Mol Biol Rep 40:3363–3371

    CAS  PubMed  Google Scholar 

  • Brady A, Salzberg SL (2009) Phymm and PhymmBL: metagenomic phylogenetic classification with interpolated Markov models. Nat Methods 6:673–676

    CAS  PubMed Central  PubMed  Google Scholar 

  • Brown Kav A, Sasson G, Jami E et al (2012) Insights into the bovine rumen plasmidome. Proc Natl Acad Sci U S A 109:5452–5457

    PubMed  Google Scholar 

  • Brown Kav A, Benhar I, Mizrahi I (2013) A method for purifying high quality and high yield plasmid DNA for metagenomic and deep sequencing approaches. J Microbiol Methods 95:272–279

    CAS  PubMed  Google Scholar 

  • Brulc JM, Antonopoulos DA, Miller ME, Wilson MK, Yannarell AC et al (2009) Gene-centric metagenomics of the fiber-adherent bovine rumen microbiome reveals forage specific glycoside hydrolases. Proc Natl Acad Sci U S A 106:1948–1953

    CAS  PubMed Central  PubMed  Google Scholar 

  • Cai Y, Sun Y (2011) ESPRIT-tree: hierarchical clustering analysis of millions of 16S rRNA pyrosequences in quasilinear computational time. Nucleic Acids Res 39:e95

    CAS  PubMed Central  PubMed  Google Scholar 

  • Castro-Carrera T, Toral PG, Frutos P et al (2014) Rumen bacterial community evaluated by 454 pyrosequencing and terminal restriction fragment length polymorphism analyses in dairy sheep fed marine algae. J Dairy Sci 97:1661–1669

    CAS  PubMed  Google Scholar 

  • Chaisson MJ, Brinza D, Pevzner PA (2009) De novo fragment assembly with short mate-paired reads: does the read length matter? Genet Res 19:336–346

    CAS  Google Scholar 

  • Chakravorty S, Helb D, Burday M et al (2007) A detailed analysis of 16S ribosomal RNA gene segments for the diagnosis of pathogenic bacteria. J Microbiol Methods 69:330–339

    CAS  PubMed Central  PubMed  Google Scholar 

  • Chaucheyras-Durand F, Masseglia S, Fonty G et al (2010) Influence of the composition of the cellulolytic flora on the development of hydrogenotrophic microorganisms hydrogen utilization and methane production in the rumens of gnotobiotically reared lambs. Appl Environ Microbiol 76:7931–7937

    CAS  PubMed Central  PubMed  Google Scholar 

  • Cheema TA, Jirajaroenrat K, Sirinarumitr T (2012) Isolation of a gene encoding a cellulolytic enzyme from swamp buffalo rumen metagenomes and its cloning and expression in Escherichia coli. Anim Biotechnol 23:261–277

    CAS  PubMed  Google Scholar 

  • Chen Y, Murrell JC (2010) When metagenomics meets stable-isotope probing: progress and perspectives. Trends Microbiol 18:157–163

    CAS  PubMed  Google Scholar 

  • Chen W, Zhang CK, Cheng Y et al (2013) A comparison of methods for clustering 16S rRNA sequences into OTUs. PLoS One 8:e70837

    CAS  PubMed Central  PubMed  Google Scholar 

  • Cheng F, Sheng J, Cai T et al (2012a) A protease-insensitive feruloyl esterase from China Holstein cow rumen metagenomic library: expression characterization and utilization in ferulic acid release from wheat straw. J Agric Food Chem 60:2546–2553

    CAS  PubMed  Google Scholar 

  • Cheng F, Sheng J, Dong R, Men Y, Gan L, Shen L (2012b) Novel xylanase from a holstein cattle rumen metagenomic library and its application in xylooligosaccharide and ferulic Acid production from wheat straw. J Agric Food Chem 60:12516–12524

    CAS  PubMed  Google Scholar 

  • Cole JR, Wang Q, Cardenas E, Fish J, Chai B, Farris RJ, Kulam-Syed-Mohideen AS, McGarrell DM, Marsh T, Garrity GM, Tiedje JM (2009) The ribosomal database project: improved alignments and new tools for rRNA analysis. Nucleic Acids Res 37:D141–D145

    CAS  PubMed Central  PubMed  Google Scholar 

  • Cox MP, Peterson DA, Biggs PJ (2010) SolexaQA: at-a-glance quality assessment of Illumina second-generation sequencing data. BMC Bioinf 11:485

    Google Scholar 

  • Dai X, Zhu Y, Luo Y, Song L, Liu D, Liu L, Chen F, Wang M, Li J, Zeng X, Dong Z, Hu S, Li L, Xu J, Huang L, Dong X (2012) Metagenomic insights into the fibrolytic microbiome in yak rumen. PLoS One 7:e40430

    CAS  PubMed Central  PubMed  Google Scholar 

  • Dalby PA (2011) Strategy and success for the directed evolution of enzymes. Curr Opin Struct Biol 21:473–480

    CAS  PubMed  Google Scholar 

  • De Eaton HL, Lorme M, Chaney RL, Craig AM (2011) Ovine ruminal microbes are capable of biotransforming hexahydro-135-trinitro-135-triazine (RDX). Microb Ecol 62:274–286

    CAS  PubMed  Google Scholar 

  • De Lorme M, Craig M (2009) Biotransformation of 246-trinitrotoluene by pure culture ruminal bacteria. Curr Microbiol 58:81–86

    CAS  PubMed  Google Scholar 

  • de Menezes AB, Lewis E, O’Donovan M, O’Neill BF, Clipson N, Doyle EM (2011) Microbiome analysis of dairy cows fed pasture or total mixed ration diets. FEMS Microbiol Ecol 78:256–265

    PubMed  Google Scholar 

  • de Oliveira MN, Jewell KA, Freitas FS, Benjamin LA, Totola MR, Borges AC, Moraes CA, Suen G (2013) Characterizing the microbiota across the gastrointestinal tract of a Brazilian Nelore steer. Vet Microbiol 164:307–314

    PubMed  Google Scholar 

  • DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, Huber T, Dalevi D, Hu P, Andersen GL (2006) Greengenes a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol 72:5069–5072

    CAS  PubMed Central  PubMed  Google Scholar 

  • Diaz NN, Krause L, Goesmann A, Niehaus K, Nattkemper TW (2009) TACOA: taxonomic classification of environmental genomic fragments using a kernelized nearest neighbor approach. BMC Bioinf 10:56

    Google Scholar 

  • Edgar RC (2010) Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26:2460–2461

    CAS  PubMed  Google Scholar 

  • Edgar RC (2013) UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat Methods 10:996–998

    CAS  PubMed  Google Scholar 

  • Edwards JE, McEwan NR, Travis AJ, Wallace RJ (2004) 16S rDNA library-based analysis of ruminal bacterial diversity. Antonie Van Leeuwenhoek 86:263–281

    CAS  Google Scholar 

  • Ekkers DM, Cretoiu MS, Kielak AM, Elsas JD (2012) The great screen anomaly–a new frontier in product discovery through functional metagenomics. Appl Microbiol Biotechnol 93:1005–1020

    CAS  PubMed Central  PubMed  Google Scholar 

  • El Allali A, Rose JR (2013) MGC: a metagenomic gene caller. BMC bioinformatics 14(Suppl 9):S6

    PubMed Central  PubMed  Google Scholar 

  • Ellison MJ, Conant GC, Cockrum RR, Austin KJ, Truong H, Becchi M, Lamberson WR, Cammack KM (2014) Diet alters both the structure and taxonomy of the ovine gut microbial ecosystem. DNA Res 21(5):115–125

    Google Scholar 

  • El-Metwally S, Hamza T, Zakaria M, Helmy M (2013) Next-generation sequence assembly: four stages of data processing and computational challenges. PLoS Comput Biol 9:e1003345

    PubMed Central  PubMed  Google Scholar 

  • Faust K, Raes J (2012) Microbial interactions: from networks to models. Nat Rev Microbiol 10:538–550

    CAS  PubMed  Google Scholar 

  • Faust K, Sathirapongsasuti JF, Izard J, Segata N, Gevers D, Raes J, Huttenhower C (2012) Microbial co-occurrence relationships in the human microbiome. PLoS Comput Biol 8:e1002606

    CAS  PubMed Central  PubMed  Google Scholar 

  • Ferrer M, Golyshina OV, Chernikova TN, Khachane AN, Reyes-Duarte D, Santos VA, Strompl C, Elborough K, Jarvis G, Neef A, Yakimov MM, Timmis KN, Golyshin PN (2005) Novel hydrolase diversity retrieved from a metagenome library of bovine rumen microflora. Environ Microbiol 7:1996–2010

    CAS  PubMed  Google Scholar 

  • Ferrer M, Beloqui A, Vieites JM, Guazzaroni ME, Berger I, Aharoni A (2009) Interplay of metagenomics and in vitro compartmentalization. J Microbial Biotechnol 2:31–39

    CAS  Google Scholar 

  • Ferrer M, Ghazi A, Beloqui A, Vieites JM, Lopez-Cortes N, Marin-Navarro J, Nechitaylo TY, Guazzaroni ME, Polaina J, Waliczek A, Chernikova TN, Reva ON, Golyshina OV, Golyshin PN (2012) Functional metagenomics unveils a multifunctional glycosyl hydrolase from the family 43 catalysing the breakdown of plant polymers in the calf rumen. PLoS One 7:e38134

    CAS  PubMed Central  PubMed  Google Scholar 

  • Fonty G, Gouet P, Nebout JM (1989) Development of the cellulolytic microflora in the rumen of lambs transferred into sterile isolators a few days after birth. Can J Microbiol 35:416–422

    CAS  PubMed  Google Scholar 

  • Fonty G, Joblin K, Chavarot M, Roux R, Naylor G, Michallon F (2007) Establishment and development of ruminal hydrogenotrophs in methanogen-free lambs. Appl Environ Microbiol 73:6391–6403

    CAS  PubMed Central  PubMed  Google Scholar 

  • Fu L, Niu B, Zhu Z, Wu S, Li W (2012) CD-HIT: accelerated for clustering the next-generation sequencing data. Bioinformatics 28:3150–3152

    CAS  PubMed Central  PubMed  Google Scholar 

  • Gagen EJ, Mosoni P, Denman SE, Al Jassim R, McSweeney CS, Forano E (2012) Methanogen colonisation does not significantly alter acetogen diversity in lambs isolated 17 h after birth and raised aseptically. Microb Ecol 64:628–640

    CAS  PubMed  Google Scholar 

  • Galbraith EA, Antonopoulos DA, White BA (2004) Suppressive subtractive hybridization as a tool for identifying genetic diversity in an environmental metagenome: the rumen as a model. Environ Microbiol 6:928–937

    CAS  PubMed  Google Scholar 

  • Gerlach W, Junemann S, Tille F, Goesmann A, Stoye J (2009) WebCARMA: a web application for the functional and taxonomic classification of unassembled metagenomic reads. BMC Bioinf 10:430

    Google Scholar 

  • Ghosh TS, Monzoorul Haque M, Mande SS (2010) DiScRIBinATE: a rapid method for accurate taxonomic classification of metagenomic sequences. BMC Bioinf 11(Suppl 7):S14

    Google Scholar 

  • Gong X, Gruninger RJ, Qi M, Paterson L, Forster RJ, Teather RM, McAllister TA (2012) Cloning and identification of novel hydrolase genes from a dairy cow rumen metagenomic library and characterization of a cellulase gene. BMC Res Notes 5:566

    CAS  PubMed Central  PubMed  Google Scholar 

  • Gruninger RJ, Gong X, Forster RJ, McAllister TA (2014) Biochemical and kinetic characterization of the multifunctional beta-glucosidase/beta-xylosidase/alpha-arabinosidase Bgxa1. Appl Microbiol Biotechnol 98(7):3003–3012

    Google Scholar 

  • Haft DH, Selengut JD, White O (2003) The TIGRFAMs database of protein families. Nucleic Acids Res 31:371–373

    CAS  PubMed Central  PubMed  Google Scholar 

  • Hamady M, Lozupone C, Knight R (2010) Fast UniFrac: facilitating high-throughput phylogenetic analyses of microbial communities including analysis of pyrosequencing and PhyloChip data. ISME J 4:17–27

    CAS  PubMed Central  PubMed  Google Scholar 

  • Hao X, Jiang R, Chen T (2011) Clustering 16S rRNA for OTU prediction: a method of unsupervised Bayesian clustering. Bioinformatics 27:611–618

    CAS  PubMed Central  PubMed  Google Scholar 

  • Hayete B, Bienkowska JR (2005) Gotrees: predicting go associations from protein domain composition using decision trees. Pac Symp Biocomput 10:127–138

    Google Scholar 

  • Hess M, Sczyrba A, Egan R, Kim TW, Chokhawala H, Schroth G, Luo S, Clark DS, Chen F, Zhang T, Mackie RI, Pennacchio LA, Tringe SG, Visel A, Woyke T, Wang Z, Rubin EM (2011) Metagenomic discovery of biomass-degrading genes and genomes from cow rumen. Science 331:463–467

    CAS  PubMed  Google Scholar 

  • Hoff KJ, Lingner T, Meinicke P, Tech M (2009) Orphelia: predicting genes in metagenomic sequencing reads. Nucleic Acids Res 37:W101–W105

    CAS  PubMed Central  PubMed  Google Scholar 

  • Huang Y, Li W, Perkins D, Li RW (2012) Comparison of de novo short read assemblers on simulated metagenomic data (chapter 5). In: Li RW (ed) Metagenomics and its applications in agriculture biomedicine and environmental studies. Nova Science, New York

    Google Scholar 

  • Huo W, Zhu W, Mao S (2014) Impact of subacute ruminal acidosis on the diversity of liquid and solid-associated bacteria in the rumen of goats. World J Microbiol Biotechnol 30:669–680

    CAS  PubMed  Google Scholar 

  • Huson DH, Auch AF, Qi J, Schuster SC (2007) MEGAN analysis of metagenomic data. Genome Res 17:377–386

    CAS  PubMed Central  PubMed  Google Scholar 

  • Jacobsen UP, Nielsen HB, Hildebrand F, Raes J, Sicheritz-Ponten T, Kouskoumvekaki I, Panagiotou G (2013) The chemical interactome space between the human host and the genetically defined gut metabotypes. ISME J 7:730–742

    CAS  PubMed Central  PubMed  Google Scholar 

  • Jagtap P, McGowan T, Bandhakavi S, Tu ZJ, Seymour S, Griffin TJ, Rudney JD (2012) Deep metaproteomic analysis of human salivary supernatant. Proteomics 12:992–1001

    CAS  PubMed Central  PubMed  Google Scholar 

  • Jami E, Mizrahi I (2012) Composition and similarity of bovine rumen microbiota across individual animals. PLoS One 7:e33306

    CAS  PubMed Central  PubMed  Google Scholar 

  • Jami E, Israel A, Kotser A, Mizrahi I (2013) Exploring the bovine rumen bacterial community from birth to adulthood. ISME J 7:1069–1079

    PubMed Central  PubMed  Google Scholar 

  • Jami E, White BA, Mizrahi I (2014) Potential role of the bovine rumen microbiome in modulating milk composition and feed efficiency. PLoS One 9:e85423

    PubMed Central  PubMed  Google Scholar 

  • Jenkins TC, Wallace RJ, Moate PJ, Mosley EE (2008) Board-invited review: recent advances in biohydrogenation of unsaturated fatty acids within the rumen microbial ecosystem. J Anim Sci 86:397–412

    CAS  PubMed  Google Scholar 

  • Kanehisa M (2002) The KEGG database. Novartis Found Symp 247:91–101; discussion 101–103 119–128 244–152

    Google Scholar 

  • Kelley DR, Liu B, Delcher AL, Pop M, Salzberg SL (2012) Gene prediction with Glimmer for metagenomic sequences augmented by classification and clustering. Nucleic Acids Res 40:e9

    CAS  PubMed Central  PubMed  Google Scholar 

  • Kim M, Morrison M, Yu Z (2011) Status of the phylogenetic diversity census of ruminal microbiomes. FEMS Microbiol Ecol 76:49–63

    CAS  PubMed  Google Scholar 

  • Kim MK, Kang TH, Kim J, Kim H, Yun HD (2012a) Cloning and identification of a new group esterase (Est5S) from noncultured rumen bacterium. J Microbiol Biotechnol 22:1044–1053

    CAS  PubMed  Google Scholar 

  • Kim OS, Cho YJ, Lee K, Yoon SH, Kim M, Na H, Park SC, Jeon YS, Lee JH, Yi H, Won S, Chun J (2012b) Introducing EzTaxon-e: a prokaryotic 16S rRNA gene sequence database with phylotypes that represent uncultured species. Int J Syst Evol Microbiol 62:716–721

    CAS  PubMed  Google Scholar 

  • Kim M, Lee KH, Yoon SW, Kim BS, Chun J, Yi H (2013) Analytical tools and databases for metagenomics in the next-generation sequencing era. Genomics Inform 11:102–113

    PubMed Central  PubMed  Google Scholar 

  • Kingston-Smith AH, Davies TE, Rees Stevens P, Mur LA (2013) Comparative metabolite fingerprinting of the rumen system during colonisation of three forage grass (Lolium perenne L) varieties. PLoS One 8:e82801

    PubMed Central  PubMed  Google Scholar 

  • Kittelmann S, Seedorf H, Walters WA, Clemente JC, Knight R, Gordon JI, Janssen PH (2013) Simultaneous amplicon sequencing to explore co-occurrence patterns of bacterial archaeal and eukaryotic microorganisms in rumen microbial communities. PLoS One 8:e47879

    CAS  PubMed Central  PubMed  Google Scholar 

  • Ko KC, Han Y, Cheong DE, Choi JH, Song JJ (2013) Strategy for screening metagenomic resources for exocellulase activity using a robotic high-throughput screening system. J Microbiol Methods 94:311–316

    CAS  PubMed  Google Scholar 

  • Koenig JE, Spor A, Scalfone N, Fricker AD, Stombaugh J, Knight R, Angenent LT, Ley RE (2011) Succession of microbial consortia in the developing infant gut microbiome. Proc Natl Acad Sci U S A 108(Suppl 1):4578–4585

    CAS  PubMed Central  PubMed  Google Scholar 

  • Laserson J, Jojic V, Koller D (2011) Genovo: de novo assembly for metagenomes. J Comput Biol 18:429–443

    CAS  PubMed  Google Scholar 

  • Lee YJ, Jenkins TC (2011) Biohydrogenation of linolenic acid to stearic acid by the rumen microbial population yields multiple intermediate conjugated diene isomers. J Nutr 141:1445–1450

    CAS  PubMed  Google Scholar 

  • Lee CC, Kibblewhite RE, Wagschal K, Li R, Orts WJ (2012a) Isolation of alpha-glucuronidase enzyme from a rumen metagenomic library. Protein J 31:206–211

    CAS  PubMed  Google Scholar 

  • Lee HJ, Jung JY, Oh YK, Lee SS, Madsen EL, Jeon CO (2012b) Comparative survey of rumen microbial communities and metabolites across one caprine and three bovine groups using bar-coded pyrosequencing and (1)H nuclear magnetic resonance spectroscopy. Appl Environ Microbiol 78:5983–5993

    CAS  PubMed Central  PubMed  Google Scholar 

  • Lee JH, Yi H, Jeon YS, Won S, Chun J (2012c) TBC: a clustering algorithm based on prokaryotic taxonomy. J Microbiol 50:181–185

    PubMed  Google Scholar 

  • Li W, Godzik A (2006) Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22:1658–1659

    CAS  PubMed  Google Scholar 

  • Li RW, Sparks ME, Connor EE (2012a) Dynamics of the rumen microbiota. In: Li RW (ed) Metagenomics and its applications in agriculture biomedicine and environmental studies. Nova Science, New York

    Google Scholar 

  • Li RW, Connor EE, Li C, Baldwin Vi RL, Sparks ME (2012b) Characterization of the rumen microbiota of pre-ruminant calves using metagenomic tools. Environ Microbiol 14:129–139

    PubMed  Google Scholar 

  • Li RW, Wu S, Baldwin RLVI, Li W, Li C (2012c) Perturbation dynamics of the rumen microbiota in response to exogenous butyrate. PLoS One 7:e29392

    CAS  PubMed Central  PubMed  Google Scholar 

  • Li RW, Wu S, Li W, Navarro K, Couch RD, Hill D, Urban JF Jr (2012d) Alterations in the porcine colon microbiota induced by the gastrointestinal nematode Trichuris suis. Infect Immun 80:2150–2157

    CAS  PubMed Central  PubMed  Google Scholar 

  • Li RW, Giarrizzo JG, WU S, Li W, Duringer JM, Craig AM (2014) Metagenomic insights into the RDX-degrading potential of the ovine rumen microbiome. PLoS One 9(11), e110505

    PubMed Central  PubMed  Google Scholar 

  • Liberles DA, Teufel AI, Liu L, Stadler T (2013) On the need for mechanistic models in computational genomics and metagenomics. Genome Biol Evol 5:2008–2018

    PubMed Central  PubMed  Google Scholar 

  • Lim S, Seo J, Choi H, Yoon D, Nam J, Kim H, Cho S, Chang J (2013) Metagenome analysis of protein domain colection within cellulase genes of goat rumen microbes. Asian-Aust J Anim Sci 26(8):1144–1151

    Google Scholar 

  • Lim YW, Schmieder R, Haynes M, Willner D, Furlan M, Youle M, Abbott K, Edwards R, Evangelista J, Conrad D, Rohwer F (2013) Metagenomics and metatranscriptomics: windows on CF-associated viral and microbial communities. J Cyst Fibros 12(2):154–164

    Google Scholar 

  • Liu B, Pop M (2011) MetaPath: identifying differentially abundant metabolic pathways in metagenomic datasets. BMC Proc 5(Suppl 2):S9

    PubMed Central  PubMed  Google Scholar 

  • Lozupone C, Knight R (2005) UniFrac: a new phylogenetic method for comparing microbial communities. Appl Environ Microbiol 71:8228–8235

    CAS  PubMed Central  PubMed  Google Scholar 

  • Luo C, Rodriguez RL, Konstantinidis KT (2013) A user’s guide to quantitative and comparative analysis of metagenomic datasets. Methods Enzymol 531:525–547

    CAS  PubMed  Google Scholar 

  • MacDonald NJ, Parks DH, Beiko RG (2012) Rapid identification of high-confidence taxonomic assignments for metagenomic data. Nucleic Acids Res 40:e111

    CAS  PubMed Central  PubMed  Google Scholar 

  • Malmuthuge N, Griebel PJ, Guan le L (2014) Taxonomic identification of commensal bacteria associated with the mucosa and digesta throughout the gastrointestinal tracts of preweaned calves. Appl Environ Microbiol 80:2021–2028

    PubMed Central  PubMed  Google Scholar 

  • Mao S, Huo W, Zhu W (2013) Use of pyrosequencing to characterize the microbiota in the ileum of goats fed with increasing proportion of dietary grain. Curr Microbiol 67:341–350

    CAS  PubMed  Google Scholar 

  • McHardy AC, Martín HG, Tsirigos A, Hugenholtz P, Rigoutsos I (2007) Accurate phylogenetic classification of variable-length DNA fragments. Nat Methods 4:63–72

    CAS  PubMed  Google Scholar 

  • Mende DR, Waller AS, Sunagawa S, Jarvelin AI, Chan MM, Arumugam M, Raes J, Bork P (2012) Assessment of metagenomic assembly using simulated next generation sequencing data. PLoS One 7:e31386

    CAS  PubMed Central  PubMed  Google Scholar 

  • Meyer F, Overbeek R, Rodriguez A (2009) FIGfams: yet another set of protein families. Nucleic Acids Res 37:6643–6654

    CAS  PubMed Central  PubMed  Google Scholar 

  • Michinaka A, Fujii T (2012) Efficient and direct identification of fructose fermenting and non-fermenting bacteria from calf gut microbiota using stable isotope probing and modified t-RFLP. J Gen Appl Microbiol 58:297–307

    CAS  PubMed  Google Scholar 

  • Miller JR, Koren S, Sutton G (2010) Assembly algorithms for next-generation sequencing data. Genomics 95:315–327

    CAS  PubMed Central  PubMed  Google Scholar 

  • Mizrahi I (2012) The rumen plasmidome: a genetic communication hub for the rumen microbiome. Mob Genet Elements 2:152–153

    PubMed Central  PubMed  Google Scholar 

  • Morgavi DP, Kelly WJ, Janssen PH, Attwood GT (2013) Rumen microbial (meta)genomics and its application to ruminant production. Animal 7(Suppl 1):184–201

    Google Scholar 

  • Morvan B, Dore J, Rieu-Lesme F, Foucat L, Fonty G, Gouet P (1994) Establishment of hydrogen-utilizing bacteria in the rumen of the newborn lamb. FEMS Microbiol Lett 117:249–256

    CAS  PubMed  Google Scholar 

  • Namiki T, Hachiya T, Tanaka H, Sakakibara Y (2012) MetaVelvet: an extension of Velvet assembler to de novo metagenome assembly from short sequence reads. Nucleic Acids Res 40:e155

    CAS  PubMed Central  PubMed  Google Scholar 

  • Nguyen NH, Maruset L, Uengwetwanit T, Mhuantong W, Harnpicharnchai P, Champreda V, Tanapongpipat S, Jirajaroenrat K, Rakshit SK, Eurwilaichitr L, Pongpattanakitshote S (2012) Identification and characterization of a cellulase-encoding gene from the buffalo rumen metagenomic library. Biosci Biotechnol Biochem 76:1075–1084

    CAS  PubMed  Google Scholar 

  • Noguchi H, Park J, Takagi T (2006) MetaGene: prokaryotic gene finding from environmental genome shotgun sequences. Nucleic Acids Res 34:5623–5630

    CAS  PubMed Central  PubMed  Google Scholar 

  • Noguchi H, Taniguchi T, Itoh T (2008) MetaGeneAnnotator: detecting species-specific patterns of ribosomal binding site for precise gene prediction in anonymous prokaryotic and phage genomes. DNA Res 15:387–396

    CAS  PubMed Central  PubMed  Google Scholar 

  • Nossa CW, Oberdorf WE, Yang L, Aas JA, Paster BJ, Desantis TZ, Brodie EL, Malamud D, Poles MA, Pei Z (2010) Design of 16S rRNA gene primers for 454 pyrosequencing of the human foregut microbiome. World J Gastroenterol 16:4135–4144

    CAS  PubMed Central  PubMed  Google Scholar 

  • Omoniyi LA, Jewell KA, Isah OA, Neumann AP, Onwuka CF, Onagbesan OM, Suen G (2014) An analysis of the ruminal bacterial microbiota in West African Dwarf sheep fed grass- and tree-based diets. J Appl Microbiol 116(5):1094–1105

    Google Scholar 

  • Peng Y, Leung HC, Yiu SM, Chin FY (2011) Meta-IDBA: a de Novo assembler for metagenomic data. Bioinformatics 27:i94–i101

    CAS  PubMed Central  PubMed  Google Scholar 

  • Peng Y, Leung HC, Yiu SM, Chin FY (2012) IDBA-UD: a de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth. Bioinformatics 28:1420–1428

    CAS  PubMed  Google Scholar 

  • Petri RM, Schwaiger T, Penner GB, Beauchemin KA, Forster RJ, McKinnon JJ, McAllister TA (2013a) Changes in the rumen epimural bacterial diversity of beef cattle as affected by diet and induced ruminal acidosis. Appl Environ Microbiol 79:3744–3755

    CAS  PubMed Central  PubMed  Google Scholar 

  • Petri RM, Schwaiger T, Penner GB, Beauchemin KA, Forster RJ, McKinnon JJ, McAllister TA (2013b) Characterization of the core rumen microbiome in cattle during transition from forage to concentrate as well as during and after an acidotic challenge. PLoS One 8:e83424

    PubMed Central  PubMed  Google Scholar 

  • Pinloche E, McEwan N, Marden JP, Bayourthe C, Auclair E, Newbold CJ (2013) The effects of a probiotic yeast on the bacterial diversity and population structure in the rumen of cattle. PLoS One 8:e67824

    CAS  PubMed Central  PubMed  Google Scholar 

  • Pitta DW, Kumar S, Veiccharelli B, Parmar N, Reddy B, Joshi CG (2014) Bacterial diversity associated with feeding dry forage at different dietary concentrations in the rumen contents of Mehshana buffalo (Bubalus bubalis) using 16S pyrotags. Anaerobe 25:31–41

    CAS  PubMed  Google Scholar 

  • Pop M (2009) Genome assembly reborn: recent computational challenges. Brief Bioinform 10:354–366

    CAS  PubMed Central  PubMed  Google Scholar 

  • Pop M, Salzberg SL (2008) Bioinformatics challenges of new sequencing technology. Trends Genet 24:142–149

    CAS  PubMed Central  PubMed  Google Scholar 

  • Pope PB, Mackenzie AK, Gregor I, Smith W, Sundset MA, McHardy AC, Morrison M, Eijsink VG (2012) Metagenomics of the Svalbard reindeer rumen microbiome reveals abundance of polysaccharide utilization loci. PLoS One 7:e38571

    CAS  PubMed Central  PubMed  Google Scholar 

  • Powell S, Forslund K, Szklarczyk D, Trachana K, Roth A, Huerta-Cepas J, Gabaldon T, Rattei T, Creevey C, Kuhn M, Jensen LJ, von Mering C, Bork P (2014) eggNOG v40: nested orthology inference across 3686 organisms. Nucleic Acids Res 42:D231–D239

    CAS  PubMed Central  PubMed  Google Scholar 

  • Punta M, Coggill PC, Eberhardt RY, Mistry J, Tate J, Boursnell C, Pang N, Forslund K, Ceric G, Clements J, Heger A, Holm L, Sonnhammer EL, Eddy SR, Bateman A, Finn RD (2012) The Pfam protein families database. Nucleic Acids Res 40:D290–D301

    CAS  PubMed Central  PubMed  Google Scholar 

  • Qi M, Wang P, O’Toole N, Barboza PS, Ungerfeld E, Leigh MB, Selinger LB, Butler G, Tsang A, McAllister TA, Forster RJ (2011) Snapshot of the eukaryotic gene expression in muskoxen rumen – a metatranscriptomic approach. PLoS One 6(5), e20521

    CAS  PubMed Central  PubMed  Google Scholar 

  • Qin J, Li Y, Cai Z, Li S, Zhu J, Zhang F, Liang S, Zhang W, Guan Y, Shen D, Peng Y, Zhang D, Jie Z, Wu W, Qin Y, Xue W, Li J, Han L, Lu D, Wu P, Dai Y, Sun X, Li Z, Tang A, Zhong S, Li X, Chen W, Xu R, Wang M, Feng Q, Gong M, Yu J, Zhang Y, Zhang M, Hansen T, Sanchez G, Raes J, Falony G, Okuda S, Almeida M, LeChatelier E, Renault P, Pons N, Batto JM, Zhang Z, Chen H, Yang R, Zheng W, Li S, Yang H, Wang J, Ehrlich SD, Nielsen R, Pedersen O, Kristiansen K, Wang J (2012) A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature 490:55–60

    CAS  PubMed  Google Scholar 

  • Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glockner FO (2013) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res 41:D590–D596

    CAS  PubMed Central  PubMed  Google Scholar 

  • Quigley JD 3rd, Schwab CG, Hylton WE (1985) Development of rumen function in calves: nature of protein reaching the abomasum. J Dairy Sci 68:694–702

    CAS  PubMed  Google Scholar 

  • Quince C, Lanzen A, Davenport RJ, Turnbaugh PJ (2011) Removing noise from pyrosequenced amplicons. BMC Bioinf 12:38

    Google Scholar 

  • Rashamuse KJ, Visser DF, Hennessy F, Kemp J, der Merwe MP R-v, Badenhorst J, Ronneburg T, Francis-Pope R, Brady D (2013) Characterisation of two bifunctional cellulase-xylanase enzymes isolated from a bovine rumen metagenome library. Curr Microbiol 66:145–151

    CAS  PubMed  Google Scholar 

  • Reichardt N, Barclay AR, Weaver LT, Morrison DJ (2011) Use of stable isotopes to measure the metabolic activity of the human intestinal microbiota. Appl Environ Microbiol 77:8009–8014

    CAS  PubMed Central  PubMed  Google Scholar 

  • Rho M, Tang H, Ye Y (2010) FragGeneScan: predicting genes in short and error-prone reads. Nucleic Acids Res 38:e191

    PubMed Central  PubMed  Google Scholar 

  • Robinson CJ, Bohannan BJ, Young VB (2010) From structure to function: the ecology of host-associated microbial communities. Microbiol Mol Biol Rev 74:453–476

    CAS  PubMed Central  PubMed  Google Scholar 

  • Ross EM, Petrovski S, Moate PJ, Hayes BJ (2013) Metagenomics of rumen bacteriophage from thirteen lactating dairy cattle. BMC Microbiol 13:242

    PubMed Central  PubMed  Google Scholar 

  • Sandri M, Manfrin C, Pallavicini A, Stefanon B (2014) Microbial biodiversity of the liquid fraction of rumen content from lactating cows. Animal 8(4):572–579

    Google Scholar 

  • 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 (2009) Introducing mothur: open-source platform-independent community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 75:7537–7541

    CAS  PubMed Central  PubMed  Google Scholar 

  • Schmieder R, Edwards R (2011) Fast identification and removal of sequence contamination from genomic and metagenomic datasets. PLoS One 6:e17288

    CAS  PubMed Central  PubMed  Google Scholar 

  • Schomburg I, Chang A, Ebeling C, Gremse M, Heldt C, Huhn G, Schomburg D (2004) BRENDA the enzyme database: updates and major new developments. Nucleic Acids Res 32:D431–D433

    CAS  PubMed Central  PubMed  Google Scholar 

  • Segata N, Waldron L, Ballarini A, Narasimhan V, Jousson O, Huttenhower C (2012) Metagenomic microbial community profiling using unique clade-specific marker genes. Nat Methods 9:811–814

    CAS  PubMed Central  PubMed  Google Scholar 

  • Sharma VK, Kumar N, Prakash T, Taylor TD (2010) MetaBioME: a database to explore commercially useful enzymes in metagenomic datasets. Nucleic Acids Res 38:D468–D472

    CAS  PubMed Central  PubMed  Google Scholar 

  • Simon C, Daniel R (2009) Achievements and new knowledge unraveled by metagenomic approaches. Appl Microbiol Biotechnol 85:265–276

    CAS  PubMed Central  PubMed  Google Scholar 

  • Simpson JT, Wong K, Jackman SD, Schein JE, Jones SJ, Birol I (2009) ABySS: a parallel assembler for short read sequence data. Genome Res 19:1117–1123

    CAS  PubMed Central  PubMed  Google Scholar 

  • Singh KM, Ahir VB, Tripathi AK, Ramani UV, Sajnani M, Koringa PG, Jakhesara S, Pandya PR, Rank DN, Murty DS, Kothari RK, Joshi CG (2012a) Metagenomic analysis of Surti buffalo (Bubalus bubalis) rumen: a preliminary study. Mol Biol Rep 39:4841–4848

    CAS  PubMed  Google Scholar 

  • Singh KM, Jakhesara SJ, Koringa PG, Rank DN, Joshi CG (2012b) Metagenomic analysis of virulence-associated and antibiotic resistance genes of microbes in rumen of Indian buffalo (Bubalus bubalis). Gene 507:146–151

    CAS  PubMed  Google Scholar 

  • Soergel DA, Dey N, Knight R, Brenner SE (2012) Selection of primers for optimal taxonomic classification of environmental 16S rRNA gene sequences. ISME J 6:1440–1444

    CAS  PubMed Central  PubMed  Google Scholar 

  • Sparks ME, Huang Y, Baldwin RL VI, Li W, Connor EE, Li C, Sonstegard TS, Schroeder SG, Bequette BJ, Li RW (2012) Detection of functional shifts in the rumen microbiota in response to propionate intake in cattle. In: Li RW (ed) Metagenomics and its applications in agriculture biomedicine and environmental studies. Nova Science, New York

    Google Scholar 

  • Sun Y, Cai Y, Liu L, Yu F, Farrell ML, McKendree W, Farmerie W (2009) ESPRIT: estimating species richness using large collections of 16S rRNA pyrosequences. Nucleic Acids Res 37:e76

    PubMed Central  PubMed  Google Scholar 

  • Tang S, Antonov I, Borodovsky M (2013) MetaGeneTack: ab initio detection of frameshifts in metagenomic sequences. Bioinformatics 29:114–116

    CAS  PubMed Central  PubMed  Google Scholar 

  • Tatusov RL, Galperin MY, Natale DA, Koonin EV (2000) The COG database: a tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Res 28:33–36

    CAS  PubMed Central  PubMed  Google Scholar 

  • Thoetkiattikul H, Mhuantong W, Laothanachareon T, Tangphatsornruang S, Pattarajinda V, Eurwilaichitr L, Champreda V (2013) Comparative analysis of microbial profiles in cow rumen fed with different dietary fiber by tagged 16S rRNA gene pyrosequencing. Curr Microbiol 67:130–137

    CAS  PubMed  Google Scholar 

  • Trimble WL, Keegan KP, D’Souza M, Wilke A, Wilkening J, Gilbert J, Meyer F (2012) Short-read reading-frame predictors are not created equal: sequence error causes loss of signal. BMC Bioinf 13:183

    Google Scholar 

  • Uhlik O, Leewis MC, Strejcek M, Musilova L, Mackova M, Leigh MB, Macek T (2013) Stable isotope probing in the metagenomics era: a bridge towards improved bioremediation. Biotechnol Adv 31:154–165

    CAS  PubMed Central  PubMed  Google Scholar 

  • Vazquez-Castellanos JF, Garcia-Lopez R, Perez-Brocal V, Pignatelli M, Moya A (2014) Comparison of different assembly and annotation tools on analysis of simulated viral metagenomic communities in the gut. BMC Genomics 15:37

    PubMed Central  PubMed  Google Scholar 

  • Vey G, Moreno-Hagelsieb G (2012) Metagenomic annotation networks: construction and applications. PLoS One 7:e41283

    CAS  PubMed Central  PubMed  Google Scholar 

  • Vilo C, Dong Q (2012) Evaluation of the RDP classifier accuracy using 16S rRNA gene variable regions. Metagenomics 1:e235551 doi: 10.4303/mg/235551

  • Wallace RJ (2008) Gut microbiology – broad genetic diversity yet specific metabolic niches. Animal 2:661–668

    CAS  Google Scholar 

  • Wang Q, Garrity GM, Tiedje JM, Cole JR (2007) Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 73:5261–5267

    CAS  PubMed Central  PubMed  Google Scholar 

  • Wang L, Hatem A, Catalyurek UV, Morrison M, Yu Z (2013) Metagenomic insights into the carbohydrate-active enzymes carried by the microorganisms adhering to solid digesta in the rumen of cows. PLoS One 8:e78507

    CAS  PubMed Central  PubMed  Google Scholar 

  • Warner D, Dijkstra J, Hendriks WH, Pellikaan WF (2013) Passage kinetics of 13C-labeled corn silage components through the gastrointestinal tract of dairy cows. J Dairy Sci 96:5844–5858

    CAS  PubMed  Google Scholar 

  • Weber M, Teeling H, Huang S, Waldmann J, Kassabgy M, Fuchs BM, Klindworth A, Klockow C, Wichels A, Gerdts G, Amann R, Glockner FO (2011) Practical application of self-organizing maps to interrelate biodiversity and functional data in NGS-based metagenomics. ISME J 5:918–928

    CAS  PubMed Central  PubMed  Google Scholar 

  • White JR, Nagarajan N, Pop M (2009) Statistical methods for detecting differentially abundant features in clinical metagenomic samples. PLoS Comput Biol 5:e1000352

    PubMed Central  PubMed  Google Scholar 

  • Wilke A, Glass EM, Bartels D, Bischof J, Braithwaite D, D’Souza M, Gerlach W, Harrison T, Keegan K, Matthews H, Kottmann R, Paczian T, Tang W, Trimble WL, Yilmaz P, Wilkening J, Desai N, Meyer F (2013) A metagenomics portal for a democratized sequencing world. Methods Enzymol 531:487–523

    CAS  PubMed  Google Scholar 

  • Wilmes P, Bond PL (2006) Metaproteomics: studying functional gene expression in microbial ecosystems. Trends Microbiol 14:92–97

    CAS  PubMed  Google Scholar 

  • Wu S, Baldwin RL VI, Li W, Li C, Connor EE, Li RW (2012a) The bacterial community composition of the bovine rumen detected using pyrosequencing of 16S rRNA genes. Metagenomics 1:e235571

    Google Scholar 

  • Wu S, Li RW, Li W, Beshah E, Dawson HD, Urban JF Jr (2012b) Worm burden-dependent disruption of the porcine colon microbiota by Trichuris suis infection. PLoS One 7:e35470

    CAS  PubMed Central  PubMed  Google Scholar 

  • Xia LC, Steele JA, Cram JA, Cardon ZG, Simmons SL, Vallino JJ, Fuhrman JA, Sun F (2011) Extended local similarity analysis (eLSA) of microbial community and other time series data with replicates. BMC Syst Biol 5(Suppl 2):S15

    PubMed Central  PubMed  Google Scholar 

  • Zerbino DR, Birney E (2008) Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res 18:821–829

    CAS  PubMed Central  PubMed  Google Scholar 

  • Zhang W, Chen J, Yang Y, Tang Y, Shang J, Shen B (2011) A practical comparison of de novo genome assembly software tools for next-generation sequencing technologies. PLoS One 6:e17915

    CAS  PubMed Central  PubMed  Google Scholar 

  • Zhang P, Gu J, He J, Gao W, Zhang W, Lindsay S, Meldrum DR (2012) Next-generation and future DNA sequencing technologies and metagenomics. In: Li RW (ed) Metagenomics and its applications in agriculture biomedicine and environmental studies. Nova Science, New York

    Google Scholar 

  • Zhao G, Bu D, Liu C, Li J, Yang J, Liu Z, Zhao Y, Chen R (2012) CloudLCA: finding the lowest common ancestor in metagenome analysis using cloud computing. Protein Cell 3:148–152

    CAS  PubMed  Google Scholar 

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Li, R.W. (2015). Rumen Metagenomics. In: Puniya, A., Singh, R., Kamra, D. (eds) Rumen Microbiology: From Evolution to Revolution. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2401-3_16

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