4.8 Article

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

Journal

MICROBIOME
Volume 10, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s40168-022-01228-9

Keywords

Dairy cattle; Feed efficiency; Metabolomics; Metagenomics; Metatranscriptomics; Rumen microbiome

Categories

Funding

  1. National Natural Science Foundation of China [31872380]
  2. Fundamental Research Funds for the Zhejiang University [2021XZZX027]
  3. China National Postdoctoral Program for Innovative Talents [BX2021252]
  4. China Postdoctoral Science Foundation [2020M681878]

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This study used metagenomics, metatranscriptomics, and metabolomics to uncover ruminal microbial features associated with feed efficiency in dairy cows. The results showed that high-efficiency animals had more and stronger microbial interactions in the rumen, with Selenomonas and members of the Succinivibrionaceae family playing key roles in carbohydrate metabolism. Analysis of ruminal metabolites identified six carbohydrates-derived metabolites as potential markers to differentiate efficient and inefficient microbiomes.
Background: As 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. Results: Comparison 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%. Conclusions: The 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.

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