Transmission dynamics and molecular characterization of methicillin-resistant S. epidermidis among men who have sex with men in Guangzhou, China.

Methicillin-resistant Staphylococcus epidermidis (MRSE) is a major opportunistic pathogen associated with high morbidity and mortality. However, its transmission dynamics and molecular characteristics in high-risk populations such as men who have sex with men (MSM) remain poorly understood. A community-based cross-sectional study was performed to recruit 510 MSM, providing nasal swabs for MRSE analysis. All MRSE isolates were characterized using antimicrobial susceptibility testing, whole-genome sequencing, and phylogenetic analysis, so as to reveal genomic diversity and transmission clusters. Among 510 MSM participants, the nasal colonization rates of S. epidermidis and MRSE were 82.75% and 44.12%, respectively. Genomic analyses of 190 MRSE isolates identified 20.53% as homologous, forming 12 transmission clusters and 40 transmission routes. In addition, homologous isolates exhibited distinct resistance and virulence profiles (tet(K), ANT(4')-Ib, esaA, esaB, icaA, icaB, icaC, icaR, essA, essB, essC, and esxA; all P < 0.05) and genotypes (ST130, ST20, ST35, and ST57; all P < 0.05). The final Random Forest model achieved an accuracy of 81.58% in predicting homologous transmission risk. These findings highlight the high carriage risk and complex dynamics of MRSE transmission in this high-risk population, emphasizing the need for targeted surveillance and infection control strategies.IMPORTANCEThis study uncovers high nasal methicillin-resistant Staphylococcus epidermidis (MRSE) colonization (44.12%) and complex transmission dynamics among men who have sex with men (MSM), a key reservoir for multidrug-resistant S. epidermidis. Whole-genome analysis identified 12 transmission clusters and 40 transmission routes, with homologous isolates enriched in tet(K) and ANT(4')-Ib resistance genes but lacking biofilm-associated ica genes. A Random Forest model achieved a classification accuracy of 81.58% for predicting transmission risk. These findings highlight MSM as critical hubs for community MRSE spread and provide actionable targets for surveillance, guiding effective infection control strategies to curb antimicrobial resistance.