Changes in the milk and fecal microbiota in Holstein cows with subclinical intramammary infection

Understanding the relationship between microbial community alterations and disease can provide valuable insights for improving diagnostics, prevention, and treatment strategies. This study used 16S rRNA amplicon sequencing to investigate and compare microbial diversity in the milk and feces of Holstein cows with subclinical mastitis caused by Streptococcus agalactiae and Prototheca spp. with that of healthy cows. A bacteriological screening identified 50 Holstein cows reared in a commercial dairy farm and classified into 3 experimental groups: (1) animals negative at the bacteriological examination with no history of subclinical mastitis (HLTH; n = 16), (2) animals positive at the bacteriological examination for either Streptococcus agalactiae (STRP; n = 22) or Prototheca spp. (PRTH; n = 12). The milk microbiota showed significant pathogen-specific alterations, with increased Firmicutes in STRP cows (55.6%) and Cyanobacteria in PRTH cows (17.3%), compared with healthy cows (39.2% and 0.7%, respectively). Alpha diversity (observed amplicon sequence variants, Shannon, and evenness indices) was significantly lower in infected cows, confirming a microbial imbalance. Beta diversity analysis (PERMANOVA) revealed significant differences in microbial composition between healthy and infected cows, but no significant differences in fecal microbiota composition. Differential abundance analysis identified Streptococcus (log2fold change [FC] = 7.3) as the most enriched taxon in STRP cows and Cyanobacteria (log2FC = 8.9) as the most enriched in PRTH cows in milk matrix, while Macrococcus caseolyticus was significantly reduced in both infected groups (log2FC = −4.5). These findings suggest that subclinical mastitis leads to significant shifts in the milk microbiota but does not alter the fecal microbiome, supporting a localized rather than systemic microbial response. This study provides novel insights into the microbial dynamics of subclinical mastitis and potential biomarkers for disease monitoring