Integrated meta-omics reveals new ruminal microbial features associated with feed efficiency in dairy cattle

Microbiome

Yifan Zhong¹  Xiao-Jiao Ma¹  Yun-Yi Xie¹  Ming-Yuan Xue²  Hui-Zeng Sun²  Jian-Xin Liu² 

[1] Institute of Dairy Science, College of Animal Sciences, Zhejiang University, 310058, Hangzhou, China;Ministry of Education Key Laboratory of Molecular Animal Nutrition, Zhejiang University, 310058, Hangzhou, China;Institute of Dairy Science, College of Animal Sciences, Zhejiang University, 310058, Hangzhou, China;Ministry of Education Key Laboratory of Molecular Animal Nutrition, Zhejiang University, 310058, Hangzhou, China;Ministry of Education Innovation Team of Development and Function of Animal Digestive System, Zhejiang University, 310058, Hangzhou, China;

关键词: Dairy cattle;    Feed efficiency;    Metabolomics;    Metagenomics;    Metatranscriptomics;    Rumen microbiome;   

DOI  :  10.1186/s40168-022-01228-9

来源: Springer

【 摘 要 】

BackgroundAs the global population continues to grow, competition for resources between humans and livestock has been intensifying. Increasing milk protein production and improving feed efficiency are becoming increasingly important to meet the demand for high-quality dairy protein. In a previous study, we found that milk protein yield in dairy cows was associated with the rumen microbiome. The objective of this study was to elucidate the potential microbial features that underpins feed efficiency in dairy cows using metagenomics, metatranscriptomics, and metabolomics.ResultsComparison of metagenomic and metatranscriptomic data revealed that the latter was a better approach to uncover the associations between rumen microbial functions and host performance. Co-occurrence network analysis of the rumen microbiome revealed differential microbial interaction patterns between the animals with different feed efficiency, with high-efficiency animals having more and stronger associations than low-efficiency animals. In the rumen of high-efficiency animals, Selenomonas and members of the Succinivibrionaceae family positively interacted with each other, functioning as keystone members due to their essential ecological functions and active carbohydrate metabolic functions. At the metabolic level, analysis using random forest machine learning suggested that six ruminal metabolites (all derived from carbohydrates) could be used as metabolic markers that can potentially differentiate efficient and inefficient microbiomes, with an accuracy of prediction of 95.06%.ConclusionsThe results of the current study provided new insights into the new ruminal microbial features associated with feed efficiency in dairy cows, which may improve the ability to select animals for better performance in the dairy industry. The fundamental knowledge will also inform future interventions to improve feed efficiency in dairy cows.2fNfKsiaKwf1Ab-9aEYLYCVideo Abstract.

【 授权许可】

CC BY