Metabolomic Analysis of Multiple Biological Specimens (Feces, Serum, and Urine) by (1)H-NMR Spectroscopy from Dairy Cows with Clinical Mastitis

SIMPLE SUMMARY: Dairy cows are commonly affected by mastitis, which causes huge economic losses to the dairy industry worldwide. This work aimed to study this disease by comparing multiple biological specimens (feces, serum, and urine) from individuals with or without clinical mastitis. Integrated analysis of metabolome changes across several key biofluids could facilitate knowledge discovery and reliable identification of potential biomarkers, which could in turn be used to shed light on the early diagnosis of dairy cow mastitis in its subclinical form. To the best of our knowledge, this is the first work dedicated to providing quantitative information on the multi-matrix metabolome of dairy cows with/without clinical mastitis by untargeted (1)H-NMR. Several pathways related to energy metabolism and amino acid metabolism have been highlighted to explain the mechanisms of the changes in the dairy cow metabolome related to clinical mastitis. Our findings are the first to provide an integrated view and better understanding of the metabolic mechanism of clinical mastitis, useful for the development of regulated strategies to improve the metabolic status of mastitic dairy cows. ABSTRACT: Due to huge economic losses to the dairy industry worldwide, mastitis can be considered as one of the most common diseases in dairy cows. This work aimed to study this disease by comparing multiple biological specimens (feces, serum, and urine) from individuals with or without clinical mastitis. This was performed by a single analytical platform, namely (1)H-NMR, through a multi-matrix strategy. Thanks to the high reproducibility of (1)H-NMR, we could characterize 120 molecules across dairy cow feces, serum, and urine. Among them, 23 molecules were in common across the three biofluids. By integrating the results of multi-matrix metabolomics, several pathways pertaining to energy metabolism and amino acid metabolism appeared to be affected by clinical mastitis. The present work wished to deepen the understanding of dairy cow mastitis in its clinical form. Simultaneous analysis of metabolome changes across several key biofluids could facilitate knowledge discovery and the reliable identification of potential biomarkers, which could be, in turn, used to shed light on the early diagnosis of dairy cow mastitis in its subclinical form.