Journal of Antimicrobial Chemotherapy · 2013 · 65 citations · 32 references
Life SciencesInfectious DiseasesMicrobiologyAntimicrobial ResistanceMedical MicrobiologyMolecular EpidemiologyAntibiotic ResistanceBacterial EpidemiologyBacterial InfectionsMolecular Epidemiology Of ResistanceMolecular TypingResistance GenesMethicillin-resistant Staphylococcus Aureus SurveillanceMolecular Typing Of IsolatesMolecular Typing Of PathogensMolecular Typing Of Resistant IsolatesMultilocus Sequence AnalysisResistance ClonesResistance Gene TypingResistance Mechanisms In Staphylococci
OBJECTIVES: The distribution of methicillin-resistant Staphylococcus aureus (MRSA) clones is dynamic and geographically unique. To understand the changing epidemiology of MRSA infections in China, we performed a prospective, multicity surveillance study with molecular typing and phenotypic analysis to determine the association of major prevalent clones with their antimicrobial resistance profiles. METHODS: A total of 517 S. aureus isolates collected between January 2009 and March 2012 from six cities in China were subjected to antibiogram analysis and molecular typing, including staphylococcal cassette chromosome mec typing, multilocus sequence typing, staphylococcal protein A gene typing and PFGE typing. RESULTS: Among the isolates collected, 309 were characterized as MRSA, with a prevalence of 59.8%. Three major clones were found to be prevalent in China: ST239-MRSA-III-t030, ST239-MRSA-III-t037 and ST5-MRSA-II-t002. These three clones were associated with two characteristic resistance profiles, namely, gentamicin/ciprofloxacin/rifampicin/levofloxacin for the first clone and gentamicin/ciprofloxacin/clindamycin/erythromycin/tetracycline/levofloxacin/trimethoprim/sulfamethoxazole for the latter two. Several geographically unique minor clones were also identified. CONCLUSIONS: The predominant MRSA clones in China were associated with characteristic antimicrobial resistance profiles. Antibiotics for treating patients with MRSA infections can be selected based on the strain typing data.
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