Fei Xie1, Wei Jin1, Huazhe Si2, Yuan Yuan3, Ye Tao4, Junhua Liu1, Xiaoxu Wang5, Chengjian Yang6, Qiushuang Li7, Xiaoting Yan3, Limei Lin1, Qian Jiang1, Lei Zhang1, Changzheng Guo1, Chris Greening8, Rasmus Heller9, Le Luo Guan10, Phillip B Pope11, Zhiliang Tan7, Weiyun Zhu1, Min Wang12, Qiang Qiu13, Zhipeng Li14,15, Shengyong Mao16. 1. Laboratory of Gastrointestinal Microbiology, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China. 2. College of Animal Science and Technology, Jilin Agricultural University, Changchun, China. 3. School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, China. 4. Shanghai BIOZERON Biotechnology Company Ltd, Shanghai, China. 5. Department of Special Economic Animal Nutrition and Feed Science, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun, China. 6. Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning, China. 7. CAS Key Laboratory for Agro-Ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, China. 8. Biomedicine Discovery Institute, Department of Microbiology, Monash University, Clayton, Australia. 9. Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark. 10. Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Canada. 11. Faculty of Biosciences, Norwegian University of Life Sciences, Aas, Norway. 12. CAS Key Laboratory for Agro-Ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, China. mwang@isa.ac.cn. 13. School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, China. qiuqiang@lzu.edu.cn. 14. College of Animal Science and Technology, Jilin Agricultural University, Changchun, China. lizhipeng01@caas.cn. 15. Department of Special Economic Animal Nutrition and Feed Science, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun, China. lizhipeng01@caas.cn. 16. Laboratory of Gastrointestinal Microbiology, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China. maoshengyong@njau.edu.cn.
Abstract
BACKGROUND: Gastrointestinal tract (GIT) microbiomes in ruminants play major roles in host health and thus animal production. However, we lack an integrated understanding of microbial community structure and function as prior studies. are predominantly biased towards the rumen. Therefore, to acquire a microbiota inventory of the discrete GIT compartments, In this study, we used shotgun metagenomics to profile the microbiota of 370 samples that represent 10 GIT regions of seven ruminant species. RESULTS: Our analyses reconstructed a GIT microbial reference catalog with > 154 million nonredundant genes and identified 8745 uncultured candidate species from over 10,000 metagenome-assembled genomes. The integrated gene catalog across the GIT regions demonstrates spatial associations between the microbiome and physiological adaptations, and 8745 newly characterized genomes substantially expand the genomic landscape of ruminant microbiota, particularly those from the lower gut. This substantially expands the previously known set of endogenous microbial diversity and the taxonomic classification rate of the GIT microbiome. These candidate species encode hundreds of enzymes and novel biosynthetic gene clusters that improve our understanding concerning methane production and feed efficiency in ruminants. Overall, this study expands the characterization of the ruminant GIT microbiota at unprecedented spatial resolution and offers clues for improving ruminant livestock production in the future. CONCLUSIONS: Having access to a comprehensive gene catalog and collections of microbial genomes provides the ability to perform efficiently genome-based analysis to achieve a detailed classification of GIT microbial ecosystem composition. Our study will bring unprecedented power in future association studies to investigate the impact of the GIT microbiota in ruminant health and production. Video abstract.
BACKGROUND: Gastrointestinal tract (GIT) microbiomes in ruminants play major roles in host health and thus animal production. However, we lack an integrated understanding of microbial community structure and function as prior studies. are predominantly biased towards the rumen. Therefore, to acquire a microbiota inventory of the discrete GIT compartments, In this study, we used shotgun metagenomics to profile the microbiota of 370 samples that represent 10 GIT regions of seven ruminant species. RESULTS: Our analyses reconstructed a GIT microbial reference catalog with > 154 million nonredundant genes and identified 8745 uncultured candidate species from over 10,000 metagenome-assembled genomes. The integrated gene catalog across the GIT regions demonstrates spatial associations between the microbiome and physiological adaptations, and 8745 newly characterized genomes substantially expand the genomic landscape of ruminant microbiota, particularly those from the lower gut. This substantially expands the previously known set of endogenous microbial diversity and the taxonomic classification rate of the GIT microbiome. These candidate species encode hundreds of enzymes and novel biosynthetic gene clusters that improve our understanding concerning methane production and feed efficiency in ruminants. Overall, this study expands the characterization of the ruminant GIT microbiota at unprecedented spatial resolution and offers clues for improving ruminant livestock production in the future. CONCLUSIONS: Having access to a comprehensive gene catalog and collections of microbial genomes provides the ability to perform efficiently genome-based analysis to achieve a detailed classification of GIT microbial ecosystem composition. Our study will bring unprecedented power in future association studies to investigate the impact of the GIT microbiota in ruminant health and production. Video abstract.
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Authors: Robert D Stewart; Marc D Auffret; Amanda Warr; Alan W Walker; Rainer Roehe; Mick Watson Journal: Nat Biotechnol Date: 2019-08-02 Impact factor: 54.908
Authors: Oliver Schwengers; Lukas Jelonek; Marius Alfred Dieckmann; Sebastian Beyvers; Jochen Blom; Alexander Goesmann Journal: Microb Genom Date: 2021-11