Abstract
Staphylococcus aureus is a major source of both hospital- and community-acquired infections worldwide. Advances in whole-genome sequencing (WGS) technologies have recently generated large volumes of S. aureus WGS data. The timely classification of S. aureus WGS data using genomic typing technologies has the potential to describe detailed genomic epidemiology at large and small scales. In this study, a multilevel genome typing (MGT) scheme, consisting of eight levels of multilocus sequence typing (MLST) schemes of increasing resolution, was developed for S. aureus and was used to analyze 50,481 publicly available genomes. The application of MGT to S. aureus epidemiology was shown in three case studies. First, the population structure of the globally disseminated MLST sequence type 8 (ST8) was described by MGT2 and compared with Spa typing. Second, MGT was used to characterize MLST ST8-USA300 isolates that colonized multiple body sites in the same patient. Finally, the MGT was used to describe the transmission of MLST ST239-SCCmec III throughout a single hospital. MGT STs were able to describe both isolates that had spread between wards and those that had colonized different reservoirs within a ward. S. aureus MGT describes S. aureus genomic epidemiology at multiple resolutions ranging from the global spread to local/individual scale using stable and standardized ST assignments. The S. aureus MGT database (https://mgtdb.unsw.edu.au/staphylococcus) is capable of tracking new and existing clones to facilitate the design of new strategies to reduce the global health burden of S. aureus infections. IMPORTANCE: Staphylococcus aureus causes both hospital- and community-acquired infections worldwide. Methicillin-resistant S. aureus is best known and has spread across the globe. Whole-genome sequencing (WGS) can type strains at the highest resolution. To enable best use of WGS data for surveillance of S. aureus, this study developed a multilevel genome typing (MGT) scheme that provides a publicly available, standardized, flexible, and easily communicated system to describe S. aureus strains. MGT has eight typing levels that provide progressively higher resolution. Each of these levels allows subtypes to be accurately identified and tracked. We show that MGT can be used to track well-known S. aureus strains at low resolution while simultaneously being able to track outbreaks in hospital settings at high resolution. The S. aureus MGT will facilitate the use of genomic data for surveillance without the need for bioinformatic expertise, improving efforts to control this important pathogen and prevent infections.