Microbial community compositions in the gastrointestinal tract of Chinese Mongolian sheep using Illumina MiSeq sequencing revealed high microbial diversity
Open accessAbstract
Chinese Mongolian sheep are an important ruminant raised for wool and meat production. However, little is known about the microbiota of the gastrointestinal tract (GIT) of Chinese Mongolian sheep. To increase our understanding of the microbial community composition in the GIT of Chinese Mongolian sheep, microbiota of five sheep is investigate for the first time using the Illumina MiSeq platform. High microbial diversity was obtained from the GIT, and the microbiota exhibited a higher biodiversity in the stomach and large intestine than in the small intestine. Firmicutes (44.62%), Bacteroidetes (38.49%), and Proteobacteria (4.11%) were the three most abundant phyla present in the GIT of the sheep. The present study also revealed the core genera of Prevotella, Bacteroides, Ruminococcus, Oscillospira, Treponema, and Desulfovibrio in the GIT. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States indicated that the metabolic pathway related to carbohydrate metabolism was the richest in the sheep GIT. In addition, a series of metabolic pathways related to plant secondary metabolism was most abundant in the stomach and large intestine than in the small intestine. Overall, the present study provides insight into the microbial community composition in GIT of the Chinese Mongolian sheep which is highly diverse and needs to be studied further to exploit the complex interactions with the host.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Prevotella, Bacteroides, Ruminococcus, Treponema, and Desulfovibrio genera were detected in all segments of the GI tract of ruminant animals, while Fibrobacter was only present in the foregut.
“Prevotella, Bacteroides, Ruminococcus, Treponema, and Desulfovibrio genera were detected in all segments of the GI tract of ruminant animals, while Fibrobacter was only present in the foregut (Zeng et al., 2017).”
From Addressing global ruminant agricultural challenges through understanding the rumen microbiome: past, present, and future (2018) · cites this paper as Zeng et al., 2017
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
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
phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data
McMurdie, P. J., & Holmes, S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061217 · Cited by 21,013 · see citing works
Schloss, P. D., Westcott, S. L., Ryabin, T., Hall, J. R., Hartmann, M., Hollister, E. B., Lesniewski, R. A., Oakley, B. B., Parks, D. H., Robinson, C. J., et al. (2009) · Applied and Environmental Microbiology · doi:10.1128/aem.01541-09 · Cited by 20,966 · see citing works
A global reference for human genetic variation
The 1000 Genomes Project Consortium, authors, C., Auton, A., Abecasis, G. R., Steering committee, Altshuler, D. M., Durbin, R. M., Abecasis, G. R., Bentley, D. R., Chakravarti, A., et al. (2015) · Nature · doi:10.1038/nature15393 · Cited by 18,247 · see citing works
Self-citationUCHIME improves sensitivity and speed of chimera detection
Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C., & Knight, R. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr381 · Cited by 15,114 · see citing works
Structure, function and diversity of the healthy human microbiome
The Human Microbiome Project Consortium (2012) · Nature · doi:10.1038/nature11234 · Cited by 11,726 · see citing works
Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample
Caporaso, J. G., Lauber, C. L., Walters, W. A., Berg-Lyons, D., Lozupone, C., Turnbaugh, P. J., Fierer, N., & Knight, R. D. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1000080107 · Cited by 9,633 · see citing works
Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences
Langille, M. G. I., Zaneveld, J., Caporaso, J. G., McDonald, D., Knights, D., Reyes, J. A., Clemente, J. C., Burkepile, D. E., Vega Thurber, R. L., Knight, R., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2676 · Cited by 9,116 · see citing works
Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms
Caporaso, J. G., Lauber, C. L., Walters, W. A., Berg-Lyons, D., Huntley, J., Fierer, N., Owens, S. M., Betley, J., Fraser, L., Bauer, M., et al. (2012) · The ISME Journal · doi:10.1038/ismej.2012.8 · Cited by 8,839 · see citing works
A core gut microbiome in obese and lean twins
Turnbaugh, P. J., Hamady, M., Yatsunenko, T., Cantarel, B. L., Duncan, A., Ley, R. E., Sogin, M. L., Jones, W. J., Roe, B. A., Affourtit, J. P., et al. (2009) · Nature · doi:10.1038/nature07540 · Cited by 7,823 · see citing works
Enterotypes of the human gut microbiome
MetaHIT Consortium (additional members), Arumugam, M., Raes, J., Pelletier, E., Le Paslier, D., Yamada, T., Mende, D. R., Fernandes, G. R., Tap, J., Bruls, T., et al. (2011) · Nature · doi:10.1038/nature09944 · Cited by 7,548 · see citing works
Turnbaugh, P. J., Ley, R. E., Hamady, M., Fraser-Liggett, C. M., Knight, R., & Gordon, J. I. (2007) · Nature · doi:10.1038/nature06244 · Cited by 6,091 · see citing works
Population-level analysis of gut microbiome variation
Falony, G., Joossens, M., Vieira-Silva, S., Wang, J., Darzi, Y., Faust, K., Kurilshikov, A., Bonder, M. J., Valles-Colomer, M., Vandeputte, D., et al. (2016) · Science · doi:10.1126/science.aad3503 · Cited by 2,400 · 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
McDonald, D. T., Clemente, J. C., Kuczynski, J., Rideout, J. R., Stombaugh, J., Wendel, D., Wilke, A., Huse, S. M., Hufnagle, J., Meyer, F., et al. (2012) · GigaScience · doi:10.1186/2047-217x-1-7 · Cited by 901 · see citing works
Xu, J., & Gordon, J. I. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1734063100 · Cited by 856 · see citing works
Dirichlet Multinomial Mixtures: Generative Models for Microbial Metagenomics
Holmes, I. H., Harris, K. J., & Quince, C. (2012) · PLoS ONE · doi:10.1371/journal.pone.0030126 · Cited by 834 · see citing works
Zoetendal, E. G., Raes, J., van den Bogert, B., Arumugam, M., Booijink, C. C. G. M., Troost, F. J., Bork, P., Wels, M., de Vos, W. M., & Kleerebezem, M. (2012) · The ISME Journal · doi:10.1038/ismej.2011.212 · Cited by 722 · see citing works
Donia, M. S., Cimermancic, P., Schulze, C. J., Wieland Brown, L. C., Martin, J., Mitreva, M., Clardy, J., Linington, R. G., & Fischbach, M. A. (2014) · Cell · doi:10.1016/j.cell.2014.08.032 · Cited by 705 · see citing works
The sheep genome illuminates biology of the rumen and lipid metabolism
Jiang, Y., Xie, M., Chen, W., Talbot, R., Maddox, J. F., Faraut, T., Wu, C., Muzny, D. M., Li, Y., Zhang, W., et al. (2014) · Science · doi:10.1126/science.1252806 · Cited by 514 · see citing works
Self-citationKoren, O., Knights, D., Gonzalez, A., Waldron, L., Segata, N., Knight, R., Huttenhower, C., & Ley, R. E. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002863 · Cited by 508 · see citing works
Bacterial Community Mapping of the Mouse Gastrointestinal Tract
Gu, S., Chen, D., Zhang, J., Lv, X., Wang, K., Duan, L.-P., Nie, Y., & Wu, X. (2013) · PLoS ONE · doi:10.1371/journal.pone.0074957 · Cited by 439 · 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
Characterization of the rumen microbiota of pre-ruminant calves using metagenomic tools.
Li, R. W., Connor, E., Li, C.-J., Baldwin, R., & Sparks, M. E. (2012) · Environmental Microbiology · doi:10.1111/j.1462-2920.2011.02543.x · Cited by 353 · see citing works
Rumen microbial (meta)genomics and its application to ruminant production
Morgavi, D., Kelly, W. J., Janssen, P. H., & Attwood, G. T. (2012) · animal · doi:10.1017/s1751731112000419 · Cited by 278 · see citing works
Callaway, T. R., Dowd, S. E., Edrington, T. S., Anderson, R. C., Krueger, N., Bauer, N., Kononoff, P. J., & Nisbet, D. J. (2010) · Journal of Animal Science · doi:10.2527/jas.2010-2900 · Cited by 275 · see citing works
The host selects mucosal and luminal associations of coevolved gut microorganisms: a novel concept
den Abbeele, P. V., de Wiele, T. V., Verstraete, W., & Possemiers, S. (2011) · FEMS Microbiology Reviews · doi:10.1111/j.1574-6976.2011.00270.x · Cited by 263 · see citing works
Extensive Strain-Level Copy-Number Variation across Human Gut Microbiome Species
Greenblum, S. I., Carr, R., & Borenstein, E. (2015) · Cell · doi:10.1016/j.cell.2014.12.038 · Cited by 236 · see citing works
Role of the enteric microbiota in intestinal homeostasis and inflammation
Koboziev, I., Webb, C. R., Furr, K. L., & Grisham, M. B. (2013) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2013.11.008 · Cited by 229 · see citing works
A unified initiative to harness Earth's microbiomes
Alivisatos, A. P., Blaser, M. J., Brodie, E., Chun, M., Dangl, J. L., Donohue, T. J., Dorrestein, P. C., Gilbert, J. A., Green, J. L., Jansson, J. K., et al. (2015) · Science · doi:10.1126/science.aac8480 · Cited by 218 · see citing works
Avguštin, G., WALLACE, R. J., & Flint, H. J. (1997) · International Journal of Systematic Bacteriology · doi:10.1099/00207713-47-2-284 · Cited by 213 · see citing works
Thoetkiattikul, H., Mhuantong, W., Laothanachareon, T., Tangphatsornruang, S., Pattarajinda, V., Eurwilaichitr, L., & Champreda, V. (2013) · Current Microbiology · doi:10.1007/s00284-013-0336-3 · Cited by 209 · see citing works
Comparative analyses of foregut and hindgut bacterial communities in hoatzins and cows
Godoy‐Vitorino, F., Goldfarb, K. C., Karaöz, U., Leal, S. J., García-Amado, M. A., Hugenholtz, P., Tringe, S. G., Brodie, E., & Domínguez-Bello, M. G. (2011) · The ISME Journal · doi:10.1038/ismej.2011.131 · Cited by 207 · 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
Evans, N. J., Brown, J. M., Murray, R. D., Getty, B., Birtles, R. J., Hart, C. A., & Carter, S. D. (2010) · Applied and Environmental Microbiology · doi:10.1128/aem.00993-10 · Cited by 182 · see citing works
Fuentes, S., van Nood, E., Tims, S., Jong, I. H., ter Braak, C. J. F., Keller, J. J., Zoetendal, E. G., & de Vos, W. M. (2014) · The ISME Journal · doi:10.1038/ismej.2014.13 · Cited by 174 · see citing works
Spence, C., Wells, W. G., & Smith, C. J. (2006) · Journal of Bacteriology · doi:10.1128/jb.00125-06 · Cited by 147 · see citing works
Liu, J., Bian, G., Zhu, W., & Mao, S. (2015) · Frontiers in Microbiology · doi:10.3389/fmicb.2015.00167 · Cited by 128 · see citing works
Vazquez, I. V., Pérez-Rangel, M., Tapia, A., Buitrón, G., Molina–Guerrero, C. E., Hernández, G., & Amaya-Delgado, L. (2015) · Fuel · doi:10.1016/j.fuel.2015.06.052 · Cited by 117 · see citing works
Ultrasonography of the Gastrointestinal Tract in Cattle
Braun, U. (2009) · Veterinary Clinics of North America Food Animal Practice · doi:10.1016/j.cvfa.2009.07.004 · Cited by 111 · see citing works
Rumen Bacterial Diversity of 80 to 110-Day-Old Goats Using 16S rRNA Sequencing
Han, X., Yang, Y., Yan, H., Wang, X., Qu, L., & Chen, Y. (2015) · PLoS ONE · doi:10.1371/journal.pone.0117811 · Cited by 108 · see citing works
Analysis of human and animal fecal microbiota for microbial source tracking
Lee, J. E., Lee, S., Sung, J., & Ko, G. (2010) · The ISME Journal · doi:10.1038/ismej.2010.120 · Cited by 103 · see citing works
Wu, S., Baldwin, R. L., Li, W., Li, C., Connor, E. E., & Li, R. W. (2012) · Metagenomics · doi:10.4303/mg/235571 · Cited by 103 · see citing works
Cunha, I. S., Barreto, C. C., Costa, O. Y. A., et al. (2011) · Anaerobe · doi:10.1016/j.anaerobe.2011.04.018 · Cited by 100 · see citing works
Osborne, J. M., & Dehority, B. A. (1989) · Applied and Environmental Microbiology · doi:10.1128/aem.55.9.2247-2250.1989 · Cited by 95 · see citing works
Nyonyo, T., Shinkai, T., & Mitsumori, M. (2014) · FEMS Microbiology Ecology · doi:10.1111/1574-6941.12318 · Cited by 90 · see citing works
Bekele, A. Z., Koike, S., & Kobayashi, Y. (2010) · FEMS Microbiology Letters · doi:10.1111/j.1574-6968.2010.02191.x · Cited by 86 · see citing works
Evaluation of the RDP Classifier Accuracy Using 16S rRNA Gene Variable Regions
Vilo, C., & Dong, Q. (2012) · Metagenomics · doi:10.4303/mg/235551 · Cited by 83 · see citing works
Li, M., Zhou, M., Adamowicz, E. M., Basarab, J. A., & Guan, L. L. (2011) · Veterinary Microbiology · doi:10.1016/j.vetmic.2011.08.007 · Cited by 78 · see citing works
Investigation of the koala (Phascolarctos cinereus) hindgut microbiome via 16S pyrosequencing
Barker, C. J., Gillett, A. K., Polkinghorne, A., & Timms, P. (2013) · Veterinary Microbiology · doi:10.1016/j.vetmic.2013.08.025 · Cited by 74 · see citing works
Recent advances in modeling nutrient utilization in ruminants1
Kebreab, E., Dijkstra, J., Bannink, A., & France, J. (2008) · Journal of Animal Science · doi:10.2527/jas.2008-1313 · Cited by 65 · see citing works
Insight into the bacterial gut microbiome of the North American moose (Alces alces)
Ishaq, S. L., & Wright, A. G. (2012) · BMC Microbiology · doi:10.1186/1471-2180-12-212 · Cited by 62 · see citing works
Peng, S., Yin, J., Liu, X., et al. (2015) · Journal of Applied Genetics · doi:10.1007/s13353-014-0258-1 · Cited by 55 · see citing works
The fate of carbohydrates in the small and large intestines of the ruminant
Armstrong, D. G., & Smithard, R. (1979) · Proceedings of The Nutrition Society · doi:10.1079/pns19790050 · Cited by 55 · see citing works
Sanad, Y. M., Closs, G., Kumar, A., et al. (2012) · Foodborne Pathogens and Disease · doi:10.1089/fpd.2012.1293 · Cited by 43 · see citing works
Zeng, Y., Zeng, D., Zhang, Y., Ni, X., Tang, Y., Zhu, H., Wang, H., Yin, Z., Pan, K., & Jing, B. (2015) · World Journal of Microbiology and Biotechnology · doi:10.1007/s11274-015-1860-z · Cited by 42 · see citing works
Self-citationJiao, J., Wang, P., He, Z., Tang, S., Zhou, C., Han, X., Wang, M., Wu, D., Kang, J., & Tan, Z. (2013) · Journal of the Science of Food and Agriculture · doi:10.1002/jsfa.6485 · Cited by 40 · see citing works
Growth Characteristics of the Lactic Streptococcus Bacteriophage
Graham, D. M., & Potter, N. N. (1953) · Applied Microbiology · doi:10.1128/am.1.3.138-142.1953 · Cited by 7 · see citing works
Organelle isolation and partial characterization from giant cells ofAspergillus niger
Davis, B., & Smith, J. E. (1977) · FEMS Microbiology Letters · doi:10.1111/j.1574-6968.1977.tb00578.x · Cited by 3 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
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
The primary biological network of Bifidobacterium in the gut
Luo, J., Li, Y., Xie, J., Gao, L., Liu, L., Ou, S., Chen, L., & Peng, X. (2018) · FEMS Microbiology Letters · doi:10.1093/femsle/fny057 · Cited by 36 · see citing works
Self-citation
- Authors
- Zeng, Y., Zeng, D., Ni, X., Zhu, H., Jian, P., Zhou, Y., Xu, S., Lin, Y., Li, Y., Yin, Z., Pan, K., & Jing, B.
- Affiliations
- Sichuan Agricultural University (CN)
- Corresponding author
- Ni, Xueqin
- ORCID
- Venue
- AMB Express
- Published
- 2017-04-04
- Volume
- 7
- Issue
- 1
- Pages
- 75-75
- ISSN
- 2191-0855 (ISSN-L)
- PMC
- PMC5380569
- OpenAlex
- W2605036151
- Cited by
- 72
- References
- 59
- Citations by year
- 2026: 4 · 2025: 8 · 2024: 7 · 2023: 8 · 2022: 13 · 2021: 13 · 2020: 6 · 2019: 5 · 2018: 7 · 2017: 1
- FWCI
- 9.04
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- AMB Express (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Natural Science Foundation of China (31672318)
- Topics
- Life Sciences › Agricultural and Biological Sciences › Agronomy and Crop Science › Ruminant Nutrition and Digestive Physiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Life Sciences › Agricultural and Biological Sciences › Animal Science and Zoology › Animal Nutrition and Physiology
- Keywords
- gut microbiota, gut microbiota diversity, Firmicutes, Bacteroidetes, Prevotella, Bacteroides, Ruminococcus, carbohydrate metabolism, plant secondary metabolism, core genera
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
