Role of tcaA, a potential target as a ceftobiprole resistance breaker in MRSA ß-lactam resistance.

ABSTRACT

OBJECTIVES: Using a random forest algorithm, we previously found that teicoplanin-associated gene A (tcaA) might play a role in resistance of methicillin-resistant Staphylococcus aureus (MRSA) to ß-lactams, which we have investigated further here. METHODS: Representative MRSA strains of prevalent clones were selected to identify the role of tcaA in the MRSA response to ß-lactams. tcaA genes were deleted by homologous recombination in the selected MRSA strains, and antibiotic susceptibility tests were applied to evaluate the effect of tcaA on the minimum inhibitory concentrations (MICs) of glycopeptides and ß-lactams. Scanning electron microscopy, RNA sequencing, and quantitative reverse transcription-polymerase chain reaction were performed to explore the mechanism of tcaA in MRSA resistance to ß-lactams. RESULTS: The MIC of penicillin plus clavulanate decreased from 3 mg/L to 0.064 mg/L and that of oxacillin decreased from 16 to 0.5 mg/L when tcaA was knocked out in the LAC strain. Compared with wild-type MRSA isolates, when tcaA was deleted, all selected strains were more susceptible to ß-lactams. Susceptibility to ceftobiprole was restored in the ceftobiprole-resistant strain when tcaA was deleted. tcaA knockout caused "log-like" abnormal division of MRSA, and tcaA deficiency mediated low expression of mecA, ponA, and murA2. CONCLUSIONS: Machine learning is a reliable tool for identifying drug resistance-related genes. tcaA may be involved in S. aureus cell division and may affect mecA, ponA, and murA2 expression. Furthermore, tcaA is a potential resistance breaker target for ß-lactams, including ceftobiprole, in MRSA.