SCC <i>mec</i> Finder, a Web-Based Tool for Typing of Staphylococcal Cassette Chromosome <i>mec</i> in Staphylococcus aureus Using Whole-Genome Sequence Data

Typing of methicillin-resistant <i>Staphylococcus aureus</i> (MRSA) is important in infection control and surveillance. The current nomenclature of MRSA includes the genetic background of the <i>S. aureus</i> strain determined by multilocus sequence typing (MLST) or equivalent methods like <i>spa</i> typing and typing of the mobile genetic element staphylococcal cassette chromosome <i>mec</i> (SCC<i>mec</i>), which carries the <i>mecA</i> or <i>mecC</i> gene. Whereas MLST and <i>spa</i> typing are relatively simple, typing of SCC<i>mec</i> is less trivial because of its heterogeneity. Whole-genome sequencing (WGS) provides the essential data for typing of the genetic background and SCC<i>mec</i>, but so far, no bioinformatic tools for SCC<i>mec</i> typing have been available. Here, we report the development and evaluation of SCC<i>mec</i>Finder for characterization of the SCC<i>mec</i> element from <i>S. aureus</i> WGS data. SCC<i>mec</i>Finder is able to identify all SCC<i>mec</i> element types, designated I to XIII, with subtyping of SCC<i>mec</i> types IV (2B) and V (5C2). SCC<i>mec</i> elements are characterized by two different gene prediction approaches to achieve correct annotation, a Basic Local Alignment Search Tool (BLAST)-based approach and a <i>k</i>-mer-based approach. Evaluation of SCC<i>mec</i>Finder by using a diverse collection of clinical isolates (<i>n</i> = 93) showed a high typeability level of 96.7%, which increased to 98.9% upon modification of the default settings. In conclusion, SCC<i>mec</i>Finder can be an alternative to more laborious SCC<i>mec</i> typing methods and is freely available at https://cge.cbs.dtu.dk/services/SCCmecFinder. <b>IMPORTANCE</b> SCC<i>mec</i> in MRSA is acknowledged to be of importance not only because it contains the <i>mecA</i> or <i>mecC</i> gene but also for staphylococcal adaptation to different environments, e.g., in hospitals, the community, and livestock. Typing of SCC<i>mec</i> by PCR techniques has, because of its heterogeneity, been challenging, and whole-genome sequencing has only partially solved this since no good bioinformatic tools have been available. In this article, we describe the development of a new bioinformatic tool, SCC<i>mec</i>Finder, that includes most of the needs for infection control professionals and researchers regarding the interpretation of SCC<i>mec</i> elements. The software detects all of the SCC<i>mec</i> elements accepted by the International Working Group on the Classification of Staphylococcal Cassette Chromosome Elements, and users will be prompted if diverging and potential new elements are uploaded. Furthermore, SCC<i>mec</i>Finder will be curated and updated as new elements are found and it is easy to use and freely accessible.