Abstract
Despite being a clonal pathogen, Staphylococcus aureus continues to acquire virulence and antibiotic-resistant genes located on mobile genetic elements such as genomic islands, prophages, pathogenicity islands, and the staphylococcal chromosomal cassette mec (SCCmec) by horizontal gene transfer from other staphylococci. The potential virulence of a S. aureus strain is often determined by comparing its pulsed-field gel electrophoresis (PFGE) or multilocus sequence typing profiles to that of known epidemic or virulent clones and by PCR of the toxin genes. Whole-genome mapping (formerly optical mapping), which is a high-resolution ordered restriction mapping of a bacterial genome, is a relatively new genomic tool that allows comparative analysis across entire bacterial genomes to identify regions of genomic similarities and dissimilarities, including small and large insertions and deletions. We explored whether whole-genome maps (WGMs) of methicillin-resistant S. aureus (MRSA) could be used to predict the presence of methicillin resistance, SCCmec type, and Panton-Valentine leukocidin (PVL)-producing genes on an S. aureus genome. We determined the WGMs of 47 diverse clinical isolates of S. aureus, including well-characterized reference MRSA strains, and annotated the signature restriction pattern in SCCmec types, arginine catabolic mobile element (ACME), and PVL-carrying prophage, PhiSa2 or PhiSa2-like regions on the genome. WGMs of these isolates accurately characterized them as MRSA or methicillin-sensitive S. aureus based on the presence or absence of the SCCmec motif, ACME and the unique signature pattern for the prophage insertion that harbored the PVL genes. Susceptibility to methicillin resistance and the presence of mecA, SCCmec types, and PVL genes were confirmed by PCR. A WGM clustering approach was further able to discriminate isolates within the same PFGE clonal group. These results showed that WGMs could be used not only to genotype S. aureus but also to identify genetic motifs in MRSA that may predict virulence.