The rumen microbiome plays a crucial role in determining the metabolic and digestive efficiency of livestock. Despite its crucial role, the impact of the rumen microbiome on average daily gain (ADG) in Xuzhou cattle remains underexplored. Xuzhou cattle is a well-known breed in China, renowned for rapid growth and superior meat quality. We selected 10 individuals from the Xuzhou cattle population and categorized Xuzhou cattle into High-ADG and Low-ADG groups and analyzed their rumen microbiota. Through comprehensive metagenomic and metabolomic analyses, we characterized the microbial diversity and functional composition of the rumen microbiome, uncovering distinct taxonomic and functional alterations associated with ADG. Thirteen kingdoms, 224 phyla, and over 16,000 species were identified, and principal coordinates analysis (PCoA) indicated significant microbial differentiation between the two groups on phylum, genus, and species levels (P < 0.05). Notably, Lentisphaerae, along with several other genera and species, presented a higher abundance in High, suggesting a potential connection with enhanced growth performance. Further functional annotation revealed that the High group displayed enriched carbohydrate and amino acid metabolism pathways, with a greater abundance of carbohydrate-active enzymes (CAZymes), particularly those involved in the degradation of complex carbohydrates. The Low-ADG group exhibited reduced metabolic activity in these pathways. Metabolomic analysis revealed 10 significantly altered metabolites, including gamma-glutamyltyrosine and N-acetylaspartic acid, which were upregulated in the High-ADG group, indicating their potential role in growth promotion. Spearman's rank correlation analysis further uncovered significant interactions between key microbiomes and metabolites, which correlated with ADG. Random forest analysis identified Victivallales and Lentisphaerae as key taxa, with gamma-glutamyltyrosine and Asp-Phe emerging as predictive biomarkers for ADG.
Importance: This study identifies key microbiota (Victivallales and Lentisphaerae) and metabolites (gamma-glutamyltyrosine, Asp-Phe, N-acetylaspartic acid, Gly-Phe) that positively regulate average daily gain (ADG) in Xuzhou cattle through amino acid metabolism. This fundamental information is vital for the development of potential manipulation strategies to improve the daily gain level through precision feeding.
Keywords: Xuzhou cattle; daily weight gain; machine learning; metabolites; rumen microbiome.