An integrated gene catalog and over 10,000 metagenome-assembled genomes from the gastrointestinal microbiome of ruminants
Fei Xie,
Wei Jin,
Huazhe Si,
Yuan Yuan,
Ye Tao,
Junhua Liu,
Xiaoxu Wang,
Chengjian Yang,
Qiushuang Li,
Xiaoting Yan,
Limei Lin,
Qian Jiang,
Lei Zhang,
Changzheng Guo,
Chris Greening,
Rasmus Heller,
Le Luo Guan,
Phillip B. Pope,
Zhiliang Tan,
Weiyun Zhu,
Min Wang,
Qiang Qiu,
Zhipeng Li,
Shengyong Mao
Affiliations
Fei Xie
Laboratory of Gastrointestinal Microbiology, College of Animal Science and Technology, Nanjing Agricultural University
Wei Jin
Laboratory of Gastrointestinal Microbiology, College of Animal Science and Technology, Nanjing Agricultural University
Huazhe Si
College of Animal Science and Technology, Jilin Agricultural University
Yuan Yuan
School of Ecology and Environment, Northwestern Polytechnical University
Ye Tao
Shanghai BIOZERON Biotechnology Company Ltd
Junhua Liu
Laboratory of Gastrointestinal Microbiology, College of Animal Science and Technology, Nanjing Agricultural University
Xiaoxu Wang
Department of Special Economic Animal Nutrition and Feed Science, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences
Chengjian Yang
Buffalo Research Institute, Chinese Academy of Agricultural Sciences
Qiushuang Li
CAS Key Laboratory for Agro-Ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences
Xiaoting Yan
School of Ecology and Environment, Northwestern Polytechnical University
Limei Lin
Laboratory of Gastrointestinal Microbiology, College of Animal Science and Technology, Nanjing Agricultural University
Qian Jiang
Laboratory of Gastrointestinal Microbiology, College of Animal Science and Technology, Nanjing Agricultural University
Lei Zhang
Laboratory of Gastrointestinal Microbiology, College of Animal Science and Technology, Nanjing Agricultural University
Changzheng Guo
Laboratory of Gastrointestinal Microbiology, College of Animal Science and Technology, Nanjing Agricultural University
Chris Greening
Biomedicine Discovery Institute, Department of Microbiology, Monash University
Rasmus Heller
Section for Computational and RNA Biology, Department of Biology, University of Copenhagen
Le Luo Guan
Department of Agricultural, Food and Nutritional Science, University of Alberta
Phillip B. Pope
Faculty of Biosciences, Norwegian University of Life Sciences
Zhiliang Tan
CAS Key Laboratory for Agro-Ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences
Weiyun Zhu
Laboratory of Gastrointestinal Microbiology, College of Animal Science and Technology, Nanjing Agricultural University
Min Wang
CAS Key Laboratory for Agro-Ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences
Qiang Qiu
School of Ecology and Environment, Northwestern Polytechnical University
Zhipeng Li
College of Animal Science and Technology, Jilin Agricultural University
Shengyong Mao
Laboratory of Gastrointestinal Microbiology, College of Animal Science and Technology, Nanjing Agricultural University
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
