4.4 Article

Using nontargeted LC-MS metabolomics to identify the Association of Biomarkers in pig feces with feed efficiency

期刊

PORCINE HEALTH MANAGEMENT
卷 7, 期 1, 页码 -

出版社

BMC
DOI: 10.1186/s40813-021-00219-w

关键词

Feed efficiency; Pig; LC-MS; WGCNA

资金

  1. National Natural Science Foundation of China [31972540]
  2. National High-quality lean-type Pig Breeding United Research Program of China
  3. Guangdong YangFan Innovative and Entrepreneurial Research Team Program [2016YT03H062]
  4. Key-Area Research and Development Program of Guangdong Province [2018B020203002]

向作者/读者索取更多资源

This study explored the relationship between pig feed efficiency and fecal metabolites, identifying nine metabolites related to residual feed intake (RFI). These metabolites are involved in multiple metabolic pathways, including lipid metabolism, vitamin D, and glucose metabolism, providing new insights for evaluating commercial pig feed efficiency and developing new feed additives.
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.

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