Phylogenomics and gene association analysis support probiotic potential in a subset of Staphylococcus xylosus...

Mastitis is a major disease in dairy cattle, often caused by Staphylococcus aureus infection and increasingly complicated by antimicrobial resistance. As a result, bacterial strains able to effectively provide colonization resistance in the bovine mammary gland are being explored as potential probiotics to reduce reliance on antimicrobial treatments. Among these, some non-S. aureus staphylococci species have shown promise; however, their effects appear to be highly strain-dependent. In this study, a combination of machine learning approaches alongside standard genomic and phylogenetic analyses was used to compare and select putative probiotic Staphylococcus xylosus strains. The genomes of 82 S. xylosus and 16 closely related Staphylococcus isolates from milk samples obtained from the Canadian Bovine Mastitis Research Network were assembled and annotated. In addition to identifying orthologous gene families and reconstructing phylogenetic relationships, each genome was screened for virulence factors, antimicrobial resistance (AMR) genes and bacteriocins. Random forest modelling and association rule learning were then applied to identify combinations of genes associated with isolates from milk samples collected from quarters exhibiting low inflammation, assessed using somatic cell counts (SCC). This approach identified 63 genes that frequently co-occurred in isolates from low SCC samples (low SCC <25,000 cells ml^-1) but were largely absent in those from high SCC samples (≥200,000 cells ml^-1). These gene sets were used as biomarkers in conjunction with phylogenetic and clustering analyses to guide the selection of a subset of S. xylosus isolates with potential probiotic properties.