DNA Microarray Profiling of a Diverse Collection of Nosocomial Methicillin-Resistant Staphylococcus aureus Isolates Assigns the Majority to the Correct Sequence Type and Staphylococcal Cassette Chromosome mec (SCCmec) Type and Results in the Subsequent Identification and Characterization of Novel SCCmec-SCCM1 Composite Islands

ABSTRACT One hundred seventy-five isolates representative of methicillin-resistant Staphylococcus aureus (MRSA) clones that predominated in Irish hospitals between 1971 and 2004 and that previously underwent multilocus sequence typing (MLST) and staphylococcal cassette chromosome mec (SCC mec ) typing were characterized by spa typing (175 isolates) and DNA microarray profiling (107 isolates). The isolates belonged to 26 sequence type (ST)-SCC mec types and subtypes and 35 spa types. The array assigned all isolates to the correct MLST clonal complex (CC), and 94% (100/107) were assigned an ST, with 98% (98/100) correlating with MLST. The array assigned all isolates to the correct SCC mec type, but subtyping of only some SCC mec elements was possible. Additional SCC mec/ SCC genes or DNA sequence variation not detected by SCC mec typing was detected by array profiling, including the SCC-fusidic acid resistance determinant Q6GD50/ fusC . Novel SCC mec /SCC composite islands (CIs) were detected among CC8 isolates and comprised SCC mec IIA-IIE, IVE, IVF, or IVg and a ccrAB4 -SCC element with 99% DNA sequence identity to SCC M1 from ST8/t024-MRSA, SCC mec VIII, and SCC-CI in Staphylococcus epidermidis. The array showed that the majority of isolates harbored one or more superantigen (94%; 100/107) and immune evasion cluster (91%; 97/107) genes. Apart from fusidic acid and trimethoprim resistance, the correlation between isolate antimicrobial resistance phenotype and the presence of specific resistance genes was ≥97%. Array profiling allowed high-throughput, accurate assignment of MRSA to CCs/STs and SCC mec types and provided further evidence of the diversity of SCC mec /SCC. In most cases, array profiling can accurately predict the resistance phenotype of an isolate.