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Article

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

1
Department of Animal Science, Food and Nutrition, Faculty of Agricultural, Food and Environmental Sciences, Università Cattolica del Sacro Cuore, 29122 Piacenza, Italy
2
Department for Sustainable Food Process, Faculty of Agricultural, Food and Environmental Sciences, Università Cattolica del Sacro Cuore, 29122 Piacenza, Italy
3
oloBion—OMICS LIFE LAB, 08028 Barcelona, Spain
*
Author to whom correspondence should be addressed.
Metabolites 2021, 11(8), 475; https://doi.org/10.3390/metabo11080475
Submission received: 29 June 2021 / Revised: 20 July 2021 / Accepted: 21 July 2021 / Published: 23 July 2021
(This article belongs to the Special Issue Multi-Omics Methods in Dairy Research)

Abstract

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 Aspergillus- and Penicillium-mycotoxins; (2) low levels of fumonisins and other Fusarium-mycotoxins; (3) high levels of Aspergillus-mycotoxins; (4) high levels of non-regulated Fusarium-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 Aspergillus 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.
Keywords: milk metabolomics; mass spectrometry; multivariate statistics; mycotoxins milk metabolomics; mass spectrometry; multivariate statistics; mycotoxins

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MDPI and ACS Style

Rocchetti, G.; Ghilardelli, F.; Bonini, P.; Lucini, L.; Masoero, F.; Gallo, A. Changes of Milk Metabolomic Profiles Resulting from a Mycotoxins-Contaminated Corn Silage Intake by Dairy Cows. Metabolites 2021, 11, 475. https://doi.org/10.3390/metabo11080475

AMA Style

Rocchetti G, Ghilardelli F, Bonini P, Lucini L, Masoero F, Gallo A. Changes of Milk Metabolomic Profiles Resulting from a Mycotoxins-Contaminated Corn Silage Intake by Dairy Cows. Metabolites. 2021; 11(8):475. https://doi.org/10.3390/metabo11080475

Chicago/Turabian Style

Rocchetti, Gabriele, Francesca Ghilardelli, Paolo Bonini, Luigi Lucini, Francesco Masoero, and Antonio Gallo. 2021. "Changes of Milk Metabolomic Profiles Resulting from a Mycotoxins-Contaminated Corn Silage Intake by Dairy Cows" Metabolites 11, no. 8: 475. https://doi.org/10.3390/metabo11080475

APA Style

Rocchetti, G., Ghilardelli, F., Bonini, P., Lucini, L., Masoero, F., & Gallo, A. (2021). Changes of Milk Metabolomic Profiles Resulting from a Mycotoxins-Contaminated Corn Silage Intake by Dairy Cows. Metabolites, 11(8), 475. https://doi.org/10.3390/metabo11080475

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