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Integrated meta-omics reveals new ruminal microbial features associated with feed efficiency in dairy cattle
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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8849036/ https://www.ncbi.nlm.nih.gov/pubmed/35172905 http://dx.doi.org/10.1186/s40168-022-01228-9 |
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author | Xue, Ming-Yuan Xie, Yun-Yi Zhong, Yifan Ma, Xiao-Jiao Sun, Hui-Zeng Liu, Jian-Xin |
author_facet | Xue, Ming-Yuan Xie, Yun-Yi Zhong, Yifan Ma, Xiao-Jiao Sun, Hui-Zeng Liu, Jian-Xin |
author_sort | Xue, Ming-Yuan |
collection | PubMed |
description | 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40168-022-01228-9. |
format | Online Article Text |
id | pubmed-8849036 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-88490362022-02-22 Integrated meta-omics reveals new ruminal microbial features associated with feed efficiency in dairy cattle Xue, Ming-Yuan Xie, Yun-Yi Zhong, Yifan Ma, Xiao-Jiao Sun, Hui-Zeng Liu, Jian-Xin Microbiome Research 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40168-022-01228-9. BioMed Central 2022-02-16 /pmc/articles/PMC8849036/ /pubmed/35172905 http://dx.doi.org/10.1186/s40168-022-01228-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Xue, Ming-Yuan Xie, Yun-Yi Zhong, Yifan Ma, Xiao-Jiao Sun, Hui-Zeng Liu, Jian-Xin Integrated meta-omics reveals new ruminal microbial features associated with feed efficiency in dairy cattle |
title | Integrated meta-omics reveals new ruminal microbial features associated with feed efficiency in dairy cattle |
title_full | Integrated meta-omics reveals new ruminal microbial features associated with feed efficiency in dairy cattle |
title_fullStr | Integrated meta-omics reveals new ruminal microbial features associated with feed efficiency in dairy cattle |
title_full_unstemmed | Integrated meta-omics reveals new ruminal microbial features associated with feed efficiency in dairy cattle |
title_short | Integrated meta-omics reveals new ruminal microbial features associated with feed efficiency in dairy cattle |
title_sort | integrated meta-omics reveals new ruminal microbial features associated with feed efficiency in dairy cattle |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8849036/ https://www.ncbi.nlm.nih.gov/pubmed/35172905 http://dx.doi.org/10.1186/s40168-022-01228-9 |
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