研究旨在评估血清代谢物在肉牛进入饲养场前预测饲料效率的潜力。通过液相色谱-质谱检测到大量特征，在负离子和正离子模式下分别检测到3598和4210个m/z特征。网络分析（WGCNA）识别出与饲料效率相关联的代谢物模块，途径富集分析（Mummichog）显示视黄醇代谢途径与饲料效率有关。这些发现表明存在一种与饲料效率相关的血清代谢组学特征，并为可持续的营养管理提供了识别高效饲料动物的可能性。
摘要：
Background Ruminants play a great role in sustainable livestock since they transform pastures, silage, and crop residues into high-quality human food (i.e. milk and beef). Animals with better ability to convert food into animal protein, measured as a trait called feed efficiency (FE), also produce less manure and greenhouse gas per kilogram of produced meat. Thus, the identification of high feed efficiency cattle is important for sustainable nutritional management. Our aim was to evaluate the potential of serum metabolites to identify FE of beef cattle before they enter the feedlot. Results A total of 3598 and 4210 m/z features was detected in negative and positive ionization modes via liquid chromatography-mass spectrometry. A single feature was different between high and low FE groups. Network analysis (WGCNA) yielded the detection of 19 and 20 network modules of highly correlated features in negative and positive mode respectively, and 1 module of each acquisition mode was associated with RFI (r = 0.55, P < 0.05). Pathway enrichment analysis (Mummichog) yielded the Retinol metabolism pathway associated with feed efficiency in beef cattle in our conditions. Conclusion Altogether, these findings demonstrate the existence of a serum-based metabolomic signature associated with feed efficiency in beef cattle before they enter the feedlot. We are now working to validate the use of metabolites for identification of feed efficient animals for sustainable nutritional management. Electronic supplementary material The online version of this article (10.1186/s12864-018-5406-2) contains supplementary material, which is available to authorized users.
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