Oral Samples as non-invasive proxies for assessing the composition of the rumen microbial community
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Microbial community analysis was carried out on ruminal digesta obtained directly via rumen fistula and buccal fluid, regurgitated digesta (bolus) and faeces of dairy cattle to assess if non-invasive samples could be used as proxies for ruminal digesta. Samples were collected from five cows receiving grass silage based diets containing no additional lipid or four different lipid supplements in a 5 x 5 Latin square design. Extracted DNA was analysed by qPCR and by sequencing 16S and 18S rRNA genes or the fungal ITS1 amplicons. Faeces contained few protozoa, and bacterial, fungal and archaeal communities were substantially different to ruminal digesta. Buccal and bolus samples gave much more similar profiles to ruminal digesta, although fewer archaea were detected in buccal and bolus samples. Bolus samples overall were most similar to ruminal samples. The differences between both buccal and bolus samples and ruminal digesta were consistent across all treatments. It can be concluded that either proxy sample type could be used as a predictor of the rumen microbial community, thereby enabling more convenient large-scale animal sampling for phenotyping and possible use in future animal breeding programs aimed at selecting cattle with a lower environmental footprint.
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Feces and samples from the intestines cannot be used as proxies of rumen function on a microbiome biomarker level.
“Notwithstanding, it is highlighted that feces and samples from the intestines cannot be used as proxies of rumen function on a microbiome biomarker level (Tapio et al., 2016).”
From Addressing global ruminant agricultural challenges through understanding the rumen microbiome: past, present, and future (2018) · cites this paper as Tapio et al., 2016
The oral microbiome of ruminants reflects the microbial diversity seen in the rumen.
“Recently it was suggested that the oral microbiome of ruminants reflects the microbial diversity seen in the rumen (Tapio et al., 2016), raising the possibility that buccal swabbing may be used as a proxy for rumen samples.”
From Addressing global ruminant agricultural challenges through understanding the rumen microbiome: past, present, and future (2018) · cites this paper as Tapio et al., 2016
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Cites
R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,706 · see citing works
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482 · see citing works
Basic local alignment search tool
Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990) · Journal of Molecular Biology · doi:10.1006/jmbi.1990.9999 · Cited by 98,669 · see citing works
QIIME allows analysis of high-throughput community sequencing data
Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., Fierer, N., Peña, A. G., Goodrich, J. K., Gordon, J. I., et al. (2010) · Nature Methods · doi:10.1038/nmeth.f.303 · Cited by 34,887 · see citing works
The SILVA ribosomal RNA gene database project: improved data processing and web-based tools
Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., Peplies, J., & Glöckner, F. O. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1219 · Cited by 33,055 · see citing works
Search and clustering orders of magnitude faster than BLAST
Edgar, R. C. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq461 · Cited by 20,617 · see citing works
The igraph software package for complex network research
Csárdi, G., & Nepusz, T. (2006) · Medical Entomology and Zoology · Cited by 10,078 · see citing works
Hubert, L., & Arabie, P. (1985) · Journal of Classification · doi:10.1007/bf01908075 · Cited by 8,219 · see citing works
The Ribosomal Database Project: improved alignments and new tools for rRNA analysis
Cole, J., Wang, Q., Cardenas, E., Fish, J., Chai, B., Farris, R. J., Kulam-Syed-Mohideen, A., Mcgarrell, D., Marsh, T., Garrity, G., et al. (2008) · Nucleic Acids Res. · doi:10.1093/nar/gkn879 · Cited by 4,940 · see citing works
Finding community structure in networks using the eigenvectors of matrices
Newman, M. E. J. (2006) · Physical Review E · doi:10.1103/physreve.74.036104 · Cited by 4,799 · see citing works
Inferring Correlation Networks from Genomic Survey Data
Friedman, J., & Alm, E. J. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002687 · Cited by 2,688 · see citing works
Hobson, P. N., & Stewart, C. S. (1997) · Springer eBooks · doi:10.1007/978-94-009-1453-7 · Cited by 2,145 · see citing works
Improved extraction of PCR-quality community DNA from digesta and fecal samples
Yu, Z., & Morrison, M. D. (2004) · BioTechniques · doi:10.2144/04365st04 · Cited by 1,668 · see citing works
Metagenomic discovery of biomass-degrading genes and genomes from cow rumen
Hess, M., Sczyrba, A., Egan, R., Kim, T.-W., Chokhawala, H., Schroth, G., Luo, S., Clark, D. S., Chen, F., Zhang, T., et al. (2011) · Science · doi:10.1126/science.1200387 · Cited by 1,319 · see citing works
obitools : a unix ‐inspired software package for DNA metabarcoding
Boyer, F., Mercier, C., Bonin, A., Bras, Y. L., Taberlet, P., & Coissac, É. (2015) · Molecular Ecology Resources · doi:10.1111/1755-0998.12428 · Cited by 1,140 · see citing works
Self-citationTowards the human intestinal microbiota phylogenetic core
Tap, J., Mondot, S., Levenez, F., Pelletier, E., Caron, C., Furet, J., Ugarte, E., Muñoz‐Tamayo, R., Paslier, D. L. E., Nalin, R., et al. (2009) · Environmental Microbiology · doi:10.1111/j.1462-2920.2009.01982.x · Cited by 927 · see citing works
Ramirez-Farias, C., Slezak, K., Fuller, Z., Duncan, A., Holtrop, G., & Louis, P. (2008) · British Journal of Nutrition · doi:10.1017/s0007114508019880 · Cited by 822 · see citing works
ecoPrimers: inference of new DNA barcode markers from whole genome sequence analysis
Riaz, T., Shehzad, W., Viari, A., Pompanon, F., Taberlet, P., & Coissac, É. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr732 · Cited by 777 · see citing works
Self-citationBrulc, J. M., Antonopoulos, D. A., Miller, M. E. B., Wilson, M. K., Yannarell, A. C., Dinsdale, E. A., Edwards, R. E., Frank, E. D., Emerson, J., Wacklin, P., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0806191105 · Cited by 757 · see citing works
Microbial ecosystem and methanogenesis in ruminants
Morgavi, D. P., Forano, E., Martin, C., & Newbold, C. J. (2010) · animal · doi:10.1017/s1751731110000546 · Cited by 694 · see citing works
Diet-Dependent Shifts in the Bacterial Population of the Rumen Revealed with Real-Time PCR
Tajima, K., Aminov, R. I., Nagamine, T., Matsui, H., Nakamura, M., & Benno, Y. (2001) · Applied and Environmental Microbiology · doi:10.1128/aem.67.6.2766-2774.2001 · Cited by 681 · see citing works
Williams, A. G., & Coleman, G. S. (1991) · Cited by 675 · see citing works
Rumen Microbiome Composition Determined Using Two Nutritional Models of Subacute Ruminal Acidosis
Khafipour, E., Li, S., Plaizier, J. C., & Krause, D. O. (2009) · Applied and Environmental Microbiology · doi:10.1128/aem.00739-09 · Cited by 518 · see citing works
Maeda, H. A., Fujimoto, C., Haruki, Y., Maeda, T., Kokeguchi, S., Petelin, M., Arai, H., Tanimoto, I., Nishimura, F., & Takashiba, S. (2003) · FEMS Immunology & Medical Microbiology · doi:10.1016/s0928-8244(03)00224-4 · Cited by 502 · see citing works
Cattle selected for lower residual feed intake have reduced daily methane production1,2
Hegarty, R. S., Goopy, J. P., Herd, R. M., & McCorkell, B. (2007) · Journal of Animal Science · doi:10.2527/jas.2006-236 · Cited by 449 · see citing works
Development of an Assay to Quantify Rumen Ciliate Protozoal Biomass in Cows Using Real-Time PCR
Sylvester, J. T., Karnati, S. K. R., Yu, Z., Morrison, M., & Firkins, J. L. (2004) · Journal of Nutrition · doi:10.1093/jn/134.12.3378 · Cited by 386 · see citing works
Kittelmann, S., Seedorf, H., Walters, W. A., Clemente, J. C., Knight, R. D., Gordon, J. I., & Janssen, P. H. (2013) · PLoS ONE · doi:10.1371/journal.pone.0047879 · Cited by 384 · see citing works
Gruninger, R. J., Puniya, A. K., Callaghan, T. M., Edwards, J. E., Youssef, N. H., Dagar, S. S., Fliegerova, K. O., Griffith, G. W., Forster, R. J., Tsang, A., et al. (2014) · FEMS Microbiology Ecology · doi:10.1111/1574-6941.12383 · Cited by 364 · see citing works
Comparison of Techniques for Measurement of Rumen pH in Lactating Dairy Cows
Duffield, T. F., Plaizier, J. C. B., Fairfield, A. M., et al. (2004) · Journal of Dairy Science · doi:10.3168/jds.s0022-0302(04)73142-2 · Cited by 351 · see citing works
Zhou, M., Hernandez‐Sanabria, E., & Guan, L. L. (2009) · Applied and Environmental Microbiology · doi:10.1128/aem.02815-08 · Cited by 343 · see citing works
Henderson, G., Cox, F., Kittelmann, S., Miri, V. H., Zethof, M., Noel, S. J., Waghorn, G. C., & Janssen, P. H. (2013) · PLoS ONE · doi:10.1371/journal.pone.0074787 · Cited by 328 · see citing works
Carberry, C. A., Kenny, D. A., Han, S., McCabe, M. S., & Waters, S. M. (2012) · Applied and Environmental Microbiology · doi:10.1128/aem.07759-11 · Cited by 311 · see citing works
Plant bioactives for ruminant health and productivity
Rochfort, S. J., Parker, A. J., & Dunshea, F. R. (2007) · Phytochemistry · doi:10.1016/j.phytochem.2007.08.017 · Cited by 292 · see citing works
Shen, J., Chai, Z., Li-min, S. O. N. G., Liu, J., & Wu, Y. (2012) · Journal of Dairy Science · doi:10.3168/jds.2012-5499 · Cited by 282 · see citing works
Characterizing the microbiota across the gastrointestinal tract of a Brazilian Nelore steer
de Oliveira, M. N. V., Jewell, K. A., Freitas, F. S., Benjamin, L. A., Tótola, M. R., Borges, A. C., Moraes, C. A., & Suen, G. (2013) · Veterinary Microbiology · doi:10.1016/j.vetmic.2013.02.013 · Cited by 184 · see citing works
Seedorf, H., Kittelmann, S., Henderson, G., & Janssen, P. H. (2014) · PeerJ · doi:10.7717/peerj.494 · Cited by 168 · see citing works
Hook, S. E., Northwood, K. S., Wright, A.-D. G., & McBride, B. W. (2008) · Applied and Environmental Microbiology · doi:10.1128/aem.01672-08 · Cited by 158 · see citing works
Ríus, A. G., Kittelmann, S., Macdonald, K. A., Waghorn, G. C., Janssen, P. H., & Sikkema, E. (2012) · Journal of Dairy Science · doi:10.3168/jds.2012-5392 · Cited by 141 · see citing works
Large Particle Breakdown by Cattle Eating Ryegrass and Alfalfa
McLeod, M. N., & Minson, D. J. (1988) · Journal of Animal Science · doi:10.2527/jas1988.664992x · Cited by 123 · see citing works
Lodge-Ivey, S. L., Browne-Silva, J., & Horvath, M. B. (2009) · Journal of Animal Science · doi:10.2527/jas.2008-1472 · Cited by 120 · see citing works
Frey, J. C., Pell, A. N., Berthiaume, R., Lapierre, H., Lee, S., Ha, J. K., Mendell, J. E., & Angert, E. R. (2009) · Journal of Applied Microbiology · doi:10.1111/j.1365-2672.2009.04602.x · Cited by 111 · see citing works
Treatment options for the eradication of intestinal protozoa
Farthing, M. J. G. (2006) · Nature Clinical Practice Gastroenterology & Hepatology · doi:10.1038/ncpgasthep0557 · Cited by 107 · see citing works
Odongo, N. E., Or-Rashid, M. M., Kebreab, E., France, J., & McBride, B. W. (2007) · Journal of Dairy Science · doi:10.3168/jds.2006-541 · Cited by 101 · see citing works
Wallace, R. J., Rooke, J. A., Duthie, C.-A., Hyslop, J. J., Ross, D. W., McKain, N., de Souza, S. M., Snelling, T. J., Waterhouse, A., & Roehe, R. (2014) · Scientific Reports · doi:10.1038/srep05892 · Cited by 100 · see citing works
Self-citationKittelmann, S., Kirk, M. R., Jonker, A., McCulloch, A., & Janssen, P. H. (2015) · Applied and Environmental Microbiology · doi:10.1128/aem.02385-15 · Cited by 82 · see citing works
Nitrogen and Phosphorus Nutrition of Cattle
Hristov, A. N., & Pfeffer, E. (2005) · Cited by 80 · see citing works
Koetschan, C., Kittelmann, S., Lu, J., Al-Halbouni, D., Jarvis, G. N., Müller, T., Wolf, M., & Janssen, P. H. (2014) · PLoS ONE · doi:10.1371/journal.pone.0091928 · Cited by 80 · see citing works
Fuller, Z., Louis, P., Mihajlovski, A., Rungapamestry, V., Ratcliffe, B., & Duncan, A. J. (2007) · British Journal Of Nutrition · doi:10.1017/s0007114507709091 · Cited by 70 · see citing works
Effect of rumination on reduction of particle size of rumen digesta by cattle
Kennedy, P. (1985) · Australian Journal of Agricultural Research · doi:10.1071/ar9850819 · Cited by 69 · see citing works
McAllister, T. A., Meale, S. J., Valle, E., Guan, L., Zhou, M., Kelly, W. J., Henderson, G., Attwood, G. T., & Janssen, P. H. (2015) · Journal of Animal Science · doi:10.2527/jas.2014-8329 · Cited by 66 · see citing works
Romero‐Pérez, G. A., Ominski, K., McAllister, T. A., & Krause, D. O. (2010) · Applied and Environmental Microbiology · doi:10.1128/aem.01289-09 · Cited by 59 · see citing works
Franzolin, R., St‐Pierre, B., Northwood, K. S., & Wright, A. G. (2012) · Microbial Ecology · doi:10.1007/s00248-012-0007-0 · Cited by 48 · see citing works
Archaeol – a biomarker for foregut fermentation in modern and ancient herbivorous mammals?
Gill, F., Dewhurst, R. J., Dungait, J. A. J., et al. (2010) · Organic Geochemistry · doi:10.1016/j.orggeochem.2010.02.001 · Cited by 44 · see citing works
Spatial and temporal variations of the bacterial community in the bovine digestive tract
Michelland, R. J., Monteils, V., Zened, A., Combes, S., Cauquil, L., Gidenne, T. N., Hamelin, J., & Fortun‐Lamothe, L. (2009) · Journal of Applied Microbiology · doi:10.1111/j.1365-2672.2009.04346.x · Cited by 42 · see citing works
Simons, K. W. (2010) · PubMed · Cited by 37 · see citing works
Assessment of archaeol as a molecular proxy for methane production in cattle
McCartney, C. A., Bull, I. D., Yan, T., & Dewhurst, R. J. (2012) · Journal of Dairy Science · doi:10.3168/jds.2012-6042 · Cited by 33 · see citing works
Genetic and environmental variation in methane emissions of sheep at pasture1
Robinson, D. L., Goopy, J. P., Hegarty, R. S., et al. (2014) · Journal of Animal Science · doi:10.2527/jas.2014-8042 · Cited by 31 · see citing works
Chemical markers for rumen methanogens and methanogenesis
McCartney, C. A., Bull, I. D., & Dewhurst, R. J. (2013) · animal · doi:10.1017/s1751731113000694 · Cited by 23 · see citing works
Khejornsart, P., & Wanapat, M. (2010) · Journal of Animal and Veterinary Advances · doi:10.3923/javaa.2010.3062.3069 · Cited by 18 · see citing works
Use of genomics and transcriptomics to identify strategies to lower ruminal methanogenesis
McAllister, T. A. (2014) · 2014 ADSA-ASAS-CSAS Joint Annual Meeting · Cited by 10 · see citing works
Interactions between cattle and the environment: a general introduction.
Pfeffer, E., & Hristov, A. N. (2005) · CABI Publishing eBooks · doi:10.1079/9780851990132.0001 · Cited by 6 · see citing works
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Research works printed but not linked: 2
- [20]European Union. Council Directive 86/609/EEC on the approximation of laws, regulations and administrative provisions of the Member States regarding the protection of animals used for experimental and other scientific purposes. Off J L 358, 1–28 (1986). 20397315
- [47]Roehe R, Rooke JA, McKain N, Duthie C-A, Hyslop JJ, Ross DW et al Sire and breed effects on bovine methane emissions and feed efficiency correlate with the ruminal metagenome, indicating that microbial gene abundance can be used as a trait to breed more efficient livestock. BMC Genomics (in press)
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Huws, S. A., Creevey, C. J., Oyama, L. B., Mizrahi, I., Denman, S. E., Popova, M., Muñoz-Tamayo, R., Forano, E., Waters, S. M., Hess, M., et al. (2018) · Frontiers in Microbiology · doi:10.3389/fmicb.2018.02161 · Cited by 487 · see citing works
Self-citationHost immune selection of rumen bacteria through salivary secretory IgA
Fouhse, J. M., Smiegielski, L., Tuplin, M., Guan, L. L., & Willing, B. P. (2017) · Frontiers in Microbiology · doi:10.3389/fmicb.2017.00848 · Cited by 37 · see citing works
- Authors
- Tapio, I., Shingfield, K. J., McKain, N., Bonin, A., Fischer, D., Bayat, A. R., Vilkki, J., Taberlet, P., Snelling, T. J., & Wallace, R. J.
- Affiliations
- Natural Resources Institute Finland (FI)
- University of Aberdeen (GB)
- Centre National de la Recherche Scientifique (FR)
- Corresponding author
- Wallace, R. John
- ORCID
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2016-03-17
- Volume
- 11
- Issue
- 3
- Pages
- e0151220
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC4795602
- OpenAlex
- W2299486820
- Cited by
- 125
- References
- 61
- Citations by year
- 2026: 9 · 2025: 10 · 2024: 8 · 2023: 10 · 2022: 12 · 2021: 18 · 2020: 27 · 2019: 9 · 2018: 9 · 2017: 10 · 2016: 3
- FWCI
- 21.15
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Aberdeen University Research Archive (Aberdeen University) (submittedVersion)
- Jukuri (Natural Resources Institute Finland (Luke)) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Jukuri (Natural Resources Institute Finland (Luke)) (submittedVersion)
- Funders
- European Commission (289319)
- Topics
- Life Sciences › Agricultural and Biological Sciences › Agronomy and Crop Science › Ruminant Nutrition and Digestive Physiology
- Physical Sciences › Engineering › Building and Construction › Anaerobic Digestion and Biogas Production
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Keywords
- rumen microbiota, non-invasive sampling, feces, rumen contents, dairy cattle, rumen protozoa, rumen archaea, rumen fungi, rumen bacteria, lipid supplementation, 16S rRNA, 18S rRNA, ITS1, animal breeding
- MeSH terms
- Animals, Animal Nutritional Physiological Phenomena, Archaea, Bacteria, Cattle, Diet, Feces, Female, Fungi, Poaceae, Mouth, RNA, Ribosomal, 16S, RNA, Ribosomal, 18S, Rumen, Silage, Dietary Supplements, Alveolata
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