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Impact of Pasture-Based Diets on the Untargeted Metabolomics Profile of Sarda Sheep Milk

In this work, untargeted metabolomics was used to shed light on the impact of different pasture-based diets on the chemical profile of Sarda sheep milk. The study considered 11 dairy sheep farms located in Sardinia, and milk samples were collected in 4 different periods, namely January, March, May,...

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Autores principales: Rocchetti, Gabriele, Becchi, Pier Paolo, Salis, Lorenzo, Lucini, Luigi, Cabiddu, Andrea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9818515/
https://www.ncbi.nlm.nih.gov/pubmed/36613358
http://dx.doi.org/10.3390/foods12010143
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author Rocchetti, Gabriele
Becchi, Pier Paolo
Salis, Lorenzo
Lucini, Luigi
Cabiddu, Andrea
author_facet Rocchetti, Gabriele
Becchi, Pier Paolo
Salis, Lorenzo
Lucini, Luigi
Cabiddu, Andrea
author_sort Rocchetti, Gabriele
collection PubMed
description In this work, untargeted metabolomics was used to shed light on the impact of different pasture-based diets on the chemical profile of Sarda sheep milk. The study considered 11 dairy sheep farms located in Sardinia, and milk samples were collected in 4 different periods, namely January, March, May, and July 2019, when all sheep had 58, 98, 138, and 178 days in milk, respectively. The animal diet composition was based on the intake of grazed herbage in natural pasture, hay, and concentrate. Overall, the combination of two comprehensive databases on food, namely the Milk Composition Database and Phenol-Explorer, allowed the putative identification of 406 metabolites, with a significant (p < 0.01) enrichment of several metabolite classes, namely amino acids and peptides, monosaccharides, fatty acids, phenylacetic acids, benzoic acids, cinnamic acids, and flavonoids. The multivariate statistical approach based on supervised orthogonal projections to latent structures (OPLS-DA) allowed us to predict the chemical profile of sheep milk samples as a function of the high vs no fresh herbage intake, while the prediction model was not significant when considering both hay and concentrate intake. Among the discriminant markers of the herbage intake, we found five phenolic metabolites (such as hippuric and coumaric acids), together with lutein and cresol (belonging to carotenoids and their metabolites). Additionally, a high discriminant power was outlined for lipid derivatives followed by sugars, amino acids, and peptides. Finally, a pathway analysis revealed that the herbage intake affected mainly five biochemical pathways in milk, namely galactose metabolism, phenylalanine metabolism, alpha-linolenic acid metabolism, linoleic acid metabolism, and aromatic amino acids involved in protein synthesis (namely tyrosine, phenylalanine, and tryptophan).
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spelling pubmed-98185152023-01-07 Impact of Pasture-Based Diets on the Untargeted Metabolomics Profile of Sarda Sheep Milk Rocchetti, Gabriele Becchi, Pier Paolo Salis, Lorenzo Lucini, Luigi Cabiddu, Andrea Foods Article In this work, untargeted metabolomics was used to shed light on the impact of different pasture-based diets on the chemical profile of Sarda sheep milk. The study considered 11 dairy sheep farms located in Sardinia, and milk samples were collected in 4 different periods, namely January, March, May, and July 2019, when all sheep had 58, 98, 138, and 178 days in milk, respectively. The animal diet composition was based on the intake of grazed herbage in natural pasture, hay, and concentrate. Overall, the combination of two comprehensive databases on food, namely the Milk Composition Database and Phenol-Explorer, allowed the putative identification of 406 metabolites, with a significant (p < 0.01) enrichment of several metabolite classes, namely amino acids and peptides, monosaccharides, fatty acids, phenylacetic acids, benzoic acids, cinnamic acids, and flavonoids. The multivariate statistical approach based on supervised orthogonal projections to latent structures (OPLS-DA) allowed us to predict the chemical profile of sheep milk samples as a function of the high vs no fresh herbage intake, while the prediction model was not significant when considering both hay and concentrate intake. Among the discriminant markers of the herbage intake, we found five phenolic metabolites (such as hippuric and coumaric acids), together with lutein and cresol (belonging to carotenoids and their metabolites). Additionally, a high discriminant power was outlined for lipid derivatives followed by sugars, amino acids, and peptides. Finally, a pathway analysis revealed that the herbage intake affected mainly five biochemical pathways in milk, namely galactose metabolism, phenylalanine metabolism, alpha-linolenic acid metabolism, linoleic acid metabolism, and aromatic amino acids involved in protein synthesis (namely tyrosine, phenylalanine, and tryptophan). MDPI 2022-12-27 /pmc/articles/PMC9818515/ /pubmed/36613358 http://dx.doi.org/10.3390/foods12010143 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Rocchetti, Gabriele
Becchi, Pier Paolo
Salis, Lorenzo
Lucini, Luigi
Cabiddu, Andrea
Impact of Pasture-Based Diets on the Untargeted Metabolomics Profile of Sarda Sheep Milk
title Impact of Pasture-Based Diets on the Untargeted Metabolomics Profile of Sarda Sheep Milk
title_full Impact of Pasture-Based Diets on the Untargeted Metabolomics Profile of Sarda Sheep Milk
title_fullStr Impact of Pasture-Based Diets on the Untargeted Metabolomics Profile of Sarda Sheep Milk
title_full_unstemmed Impact of Pasture-Based Diets on the Untargeted Metabolomics Profile of Sarda Sheep Milk
title_short Impact of Pasture-Based Diets on the Untargeted Metabolomics Profile of Sarda Sheep Milk
title_sort impact of pasture-based diets on the untargeted metabolomics profile of sarda sheep milk
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9818515/
https://www.ncbi.nlm.nih.gov/pubmed/36613358
http://dx.doi.org/10.3390/foods12010143
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