Screening and dynamic change study of microbial and metabolite markers for calf diarrhea based on multi-omics and machine learning.

Neonatal calf diarrhea is a leading cause of calf mortality and substantial economic loss in the livestock industry, yet the dynamic microbial and metabolic signatures accompanying disease onset remain poorly defined. Here, we integrated 16S rRNA high-throughput sequencing, untargeted metabolomics, and machine learning approaches to longitudinally profile fecal samples from neonatal calves at 0, 5, 10, 15, and 20 days of age. Diarrheic calves exhibited significantly reduced gut microbial α-diversity, as indicated by lower Chao1 richness and Shannon index compared with healthy counterparts. At the genus level, IMPORTANCE: Neonatal calf diarrhea causes substantial early-life mortality and economic losses, yet the dynamic microbiota-metabolite alterations and early-warning biomarkers during disease onset remain poorly defined. Here, we longitudinally profiled fecal microbiota and metabolites in calves from birth to day 20 and integrated machine learning approaches to systematically characterize diarrhea-associated signatures. Diarrheic calves showed reduced α-diversity, and