(untitled) (Journal of Bangladesh Academy of Sciences, 2025)
With rising antibiotic resistance, the discovery of novel antimicrobial compounds has become increasingly crucial. In silico genome mining is widely used to predict secondary metabolite production prior to laboratory testing. In this study, 505 Staphylococcus aureus genomes from the NCBI database were analyzed using antiSMASH 7.0, which identified a class I lanthipeptide gene cluster in 206 strains. Although antiSMASH annotated this gene cluster as hyicin 3682 and the RefSeq genome database classified it as a ‘gallidermin- or nisin-family lantibiotic’, the prepeptide sequence encoded by the cluster is identical to that of the S. aureus bacteriocin (Bsa) lantibiotic. Moreover, other genes within the cluster share the same number and orientation as the Bsa loci found in community-acquired S. aureus strains. Variations in prepeptide sequences and gene numbers revealed four distinct Bsa variants. Overall, this analysis supports the presence of lantibiotic gene clusters in pathogenic strains and highlights the potential of genome mining to reduce time, cost, and labor in antimicrobial discovery. J. Bangladesh Acad. Sci. 49(2); 179-188: December 2025