Multi-omics characterization of blood metabolites and cervical microbiota associated with estrus in simmental cattle.

Abstract

Accurate estrus detection is critical for optimizing reproductive efficiency in beef cattle. This study characterized blood metabolites and cervical microbiota associated with estrus in Simmental cattle using an integrated multi-omics approach. Twelve multiparous cows were assigned to estrus (n = 6) or nonestrus (n = 6) groups based on behavioral, hormonal, and ultrasonographic criteria. Serum samples were analyzed via ELISA and UPLC-MS/MS, while cervical microbiota were profiled using 16S rRNA and ITS sequencing. Serum biochemical analysis revealed elevated levels of total protein, albumin, glucose, and insulin-like growth factor-1 during estrus (p < 0.01). Untargeted metabolomics identified 258 differentially abundant metabolites enriched in amino acid and lipid metabolism pathways. Cervical microbiota analysis showed that Firmicutes and Bacteroidetes were the dominant bacterial phyla, with Bacteroidetes increasing by 13.36% during estrus. Fungal Ascomycota dominated the estrus group (78.38% vs. 67.20%), accompanied by reduced alpha diversity (p < 0.05). LEfSe analysis identified 22 bacterial and 16 fungal biomarkers associated with estrus. Correlation analysis revealed that E2 was positively correlated with Bacteroidota (r = 0.604) and fungal genera Bacteroides (r = 0.703), while progesterone showed negative correlations. This study reveals a complex microbiota-metabolite-host network specific to estrus in Simmental cattle, providing potential biomarkers for estrus detection.