Changes of Milk Metabolomic Profiles Resulting from a Mycotoxins-Contaminated Corn Silage Intake by Dairy Cows

• Main Authors: Gabriele Rocchetti, Francesca Ghilardelli, Paolo Bonini, Luigi Lucini, Francesco Masoero, Antonio Gallo
• Format: Article
• Language: English
• Published: MDPI AG 2021-07-01
• Series: Metabolites
• Subjects: milk metabolomics; mass spectrometry; multivariate statistics; mycotoxins
• Online Access: https://www.mdpi.com/2218-1989/11/8/475

In this study, an untargeted metabolomics approach based on ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS) was used for investigating changes in chemical profiles of cow milk considering diets based on mycotoxins-contaminated corn silages. For this purpose, 45 milk samples were classified into five clusters according to the corn silage contamination profile, namely (1) low levels of <i>Aspergillus</i>- and <i>Penicillium</i>-mycotoxins; (2) low levels of fumonisins and other <i>Fusarium</i>-mycotoxins; (3) high levels of <i>Aspergillus</i>-mycotoxins; (4) high levels of non-regulated <i>Fusarium</i>-mycotoxins; (5) high levels of fumonisins and their metabolites, and subsequently analyzed by UHPLC-HRMS followed by a multivariate statistical analysis (both unsupervised and supervised statistical approaches). Overall, the milk metabolomic profile highlighted potential correlations between the quality of contaminated corn silages (as part of the total mixed ration) and milk composition. Metabolomics allowed to identify 628 significant milk metabolites as affected by the five levels of corn silage contamination considered, with amino acids and peptides showing the highest metabolite set enrichment (134 compounds). Additionally, 78 metabolites were selected as the best discriminant of the prediction model built, possessing a variable importance in projection score >1.2. The average Log Fold-Change variations of the discriminant metabolites provided evidence that sphingolipids, together with purine and pyrimidine-derived metabolites were the most affected chemical classes. Also, metabolomics revealed a significant accumulation of oxidized glutathione in milk samples belonging to the silage cluster contaminated by emerging <i>Aspergillus</i> toxins, likely involved in the oxidative imbalance. These preliminary findings provide new insights into the potential role of milk metabolomics to provide chemical indicators of mycotoxins-contaminated corn silage feeding systems.