Multi-omics analysis provides insight into the genetic basis of proline-derived milk microbiota in buffalo

Abstract

Understanding the intricate relationship between genetics, metabolites, and microbiota is paramount for unraveling the complexities that define buffalo milk composition. In this study, we employed a multi-omics approach to dissect the genetic and metabolic determinants of buffalo milk traits. Metabolomics analysis of 100 buffalo milk samples revealed a rich profile of 446 metabolites, with a particular emphasis on those associated with amino acid biosynthesis. Metabolite-based Genome-Wide Association Studies (mGWAS) uncovered 13 significant genetic variants, with a pronounced focus on l-Proline. Notably, single nucleotide polymorphisms (SNPs) within the ATG16L1 gene implicated its role in proline production. Concurrently, an in-depth exploration of milk microbiota dynamics highlighted marked differences between buffaloes with high and low proline groups. High proline abundance correlated with increased microbial diversity, dominated by Firmicutes and Proteobacteria. Distinct genera, such as Acinetobacter and Corynebacterium, characterized low and high proline groups, respectively. Functional changes in milk microbiota, especially in amino acid biosynthesis pathways, underscored proline's pivotal role in shaping microbial functions. Correlations between milk microbiota abundance and proline levels emphasized the intricate relationship between host physiology and microbial composition. These findings not only advance our understanding of the genetic basis of metabolic traits in buffalo milk but also present potential biomarkers for targeted breeding strategies. This integrated approach provides a nuanced perspective on milk composition, offering implications for dairy quality and nutritional enhancement.