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Using nontargeted LC-MS metabolomics to identify the Association of Biomarkers in pig feces with feed efficiency
BACKGROUND: Improving feed efficiency is economically and environmentally beneficial in the pig industry. A deeper understanding of feed efficiency is essential on many levels for its highly complex nature. The aim of this project is to explore the relationship between fecal metabolites and feed eff...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8170940/ https://www.ncbi.nlm.nih.gov/pubmed/34078468 http://dx.doi.org/10.1186/s40813-021-00219-w |
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author | Wu, Jie Ye, Yong Quan, Jianping Ding, Rongrong Wang, Xingwang Zhuang, Zhanwei Zhou, Shenping Geng, Qian Xu, Cineng Hong, Linjun Xu, Zheng Zheng, Enqin Cai, Gengyuan Wu, Zhenfang Yang, Jie |
author_facet | Wu, Jie Ye, Yong Quan, Jianping Ding, Rongrong Wang, Xingwang Zhuang, Zhanwei Zhou, Shenping Geng, Qian Xu, Cineng Hong, Linjun Xu, Zheng Zheng, Enqin Cai, Gengyuan Wu, Zhenfang Yang, Jie |
author_sort | Wu, Jie |
collection | PubMed |
description | BACKGROUND: Improving feed efficiency is economically and environmentally beneficial in the pig industry. A deeper understanding of feed efficiency is essential on many levels for its highly complex nature. The aim of this project is to explore the relationship between fecal metabolites and feed efficiency-related traits, thereby identifying metabolites that may assist in the screening of the feed efficiency of pigs. RESULTS: We performed fecal metabolomics analysis on 50 individuals selected from 225 Duroc x (Landrace x Yorkshire) (DLY) commercial pigs, 25 with an extremely high feed efficiency and 25 with an extremely low feed efficiency. A total of 6749 and 5644 m/z features were detected in positive and negative ionization modes by liquid chromatography-mass spectrometry (LC/MS). Regrettably, the PCA could not classify the the samples accurately. To improve the classification, OPLS-DA was introduced. However, the predictive ability of the OPLS-DA model did not perform well. Then, through weighted coexpression network analysis (WGCNA), we found that one module in each positive and negative mode was related to residual feed intake (RFI), and six and three metabolites were further identified. The nine metabolites were found to be involved in multiple metabolic pathways, including lipid metabolism (primary bile acid synthesis, linoleic acid metabolism), vitamin D, glucose metabolism, and others. Then, Lasso regression analysis was used to evaluate the importance of nine metabolites obtained by the annotation process. CONCLUSIONS: Altogether, this study provides new insights for the subsequent evaluation of commercial pig feed efficiency through small molecule metabolites, but also provide a reference for the development of new feed additives. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40813-021-00219-w. |
format | Online Article Text |
id | pubmed-8170940 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-81709402021-06-03 Using nontargeted LC-MS metabolomics to identify the Association of Biomarkers in pig feces with feed efficiency Wu, Jie Ye, Yong Quan, Jianping Ding, Rongrong Wang, Xingwang Zhuang, Zhanwei Zhou, Shenping Geng, Qian Xu, Cineng Hong, Linjun Xu, Zheng Zheng, Enqin Cai, Gengyuan Wu, Zhenfang Yang, Jie Porcine Health Manag Research BACKGROUND: Improving feed efficiency is economically and environmentally beneficial in the pig industry. A deeper understanding of feed efficiency is essential on many levels for its highly complex nature. The aim of this project is to explore the relationship between fecal metabolites and feed efficiency-related traits, thereby identifying metabolites that may assist in the screening of the feed efficiency of pigs. RESULTS: We performed fecal metabolomics analysis on 50 individuals selected from 225 Duroc x (Landrace x Yorkshire) (DLY) commercial pigs, 25 with an extremely high feed efficiency and 25 with an extremely low feed efficiency. A total of 6749 and 5644 m/z features were detected in positive and negative ionization modes by liquid chromatography-mass spectrometry (LC/MS). Regrettably, the PCA could not classify the the samples accurately. To improve the classification, OPLS-DA was introduced. However, the predictive ability of the OPLS-DA model did not perform well. Then, through weighted coexpression network analysis (WGCNA), we found that one module in each positive and negative mode was related to residual feed intake (RFI), and six and three metabolites were further identified. The nine metabolites were found to be involved in multiple metabolic pathways, including lipid metabolism (primary bile acid synthesis, linoleic acid metabolism), vitamin D, glucose metabolism, and others. Then, Lasso regression analysis was used to evaluate the importance of nine metabolites obtained by the annotation process. CONCLUSIONS: Altogether, this study provides new insights for the subsequent evaluation of commercial pig feed efficiency through small molecule metabolites, but also provide a reference for the development of new feed additives. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40813-021-00219-w. BioMed Central 2021-06-02 /pmc/articles/PMC8170940/ /pubmed/34078468 http://dx.doi.org/10.1186/s40813-021-00219-w Text en © The Author(s) 2021 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 Wu, Jie Ye, Yong Quan, Jianping Ding, Rongrong Wang, Xingwang Zhuang, Zhanwei Zhou, Shenping Geng, Qian Xu, Cineng Hong, Linjun Xu, Zheng Zheng, Enqin Cai, Gengyuan Wu, Zhenfang Yang, Jie Using nontargeted LC-MS metabolomics to identify the Association of Biomarkers in pig feces with feed efficiency |
title | Using nontargeted LC-MS metabolomics to identify the Association of Biomarkers in pig feces with feed efficiency |
title_full | Using nontargeted LC-MS metabolomics to identify the Association of Biomarkers in pig feces with feed efficiency |
title_fullStr | Using nontargeted LC-MS metabolomics to identify the Association of Biomarkers in pig feces with feed efficiency |
title_full_unstemmed | Using nontargeted LC-MS metabolomics to identify the Association of Biomarkers in pig feces with feed efficiency |
title_short | Using nontargeted LC-MS metabolomics to identify the Association of Biomarkers in pig feces with feed efficiency |
title_sort | using nontargeted lc-ms metabolomics to identify the association of biomarkers in pig feces with feed efficiency |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8170940/ https://www.ncbi.nlm.nih.gov/pubmed/34078468 http://dx.doi.org/10.1186/s40813-021-00219-w |
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