Development of a Serum Microbiome-Metabolomics Integrated Index for Predicting Subclinical Mastitis Outcomes in Dairy Cows in Oyo and Kwara States, North Central and South West Nigeria

Subclinical mastitis is the most prevalent production disease in dairy cattle globally and imposes the greatest economic burden through milk quality loss, yet predictive serum-based tools integrating the microbial and metabolic dimensions of host systemic response have not been developed for Nigerian dairy settings. This doctoral study developed and validated a serum microbiome-metabolomics integrated index for predicting subclinical mastitis clinical outcomes in Friesian-Zebu crossbred cows at commercial dairy farms in Oyo and Kwara States. A prospective cohort of one hundred and eighty cows was monitored from calving through sixteen weeks with fortnightly California Mastitis Test scoring and milk somatic cell counts as reference standards. At weeks two, four, and eight postpartum, serum was collected for untargeted metabolomics by liquid chromatography-mass spectrometry and cell-free microbial DNA detection by shotgun metagenomics sequencing. Cows that developed subclinical mastitis showed a distinct pre-disease serum metabolomic signature characterised by elevations in lipopolysaccharide-binding protein, lysophospholipids, and succinate, and reductions in hippurate and indole derivatives, detectable seven to ten days before elevated somatic cell count confirmation. Serum microbial DNA analysis identified translocation signatures from gut Gram-negative bacteria in pre-mastitis cows, suggesting gut barrier compromise as an upstream contributor. A combined index integrating five metabolites and two microbial DNA signatures predicted subclinical mastitis development with 87% sensitivity and 91% specificity at week four. This doctoral study provides the first microbiome-metabolomics integrated predictive framework for subclinical mastitis in Nigeria and advances early-warning precision management for dairy herds. Keywords: subclinical mastitis, serum metabolomics, metagenomics, prediction index, dairy cows.