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      SCC mecFinder, a Web-Based Tool for Typing of Staphylococcal Cassette Chromosome mec in Staphylococcus aureus Using Whole-Genome Sequence Data

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          Abstract

          SCC mec in MRSA is acknowledged to be of importance not only because it contains the mecA or mecC gene but also for staphylococcal adaptation to different environments, e.g., in hospitals, the community, and livestock. Typing of SCC mec 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 mecFinder, that includes most of the needs for infection control professionals and researchers regarding the interpretation of SCC mec elements. The software detects all of the SCC mec 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 mecFinder will be curated and updated as new elements are found and it is easy to use and freely accessible.

          ABSTRACT

          Typing of methicillin-resistant Staphylococcus aureus (MRSA) is important in infection control and surveillance. The current nomenclature of MRSA includes the genetic background of the S. aureus strain determined by multilocus sequence typing (MLST) or equivalent methods like spa typing and typing of the mobile genetic element staphylococcal cassette chromosome mec (SCC mec), which carries the mecA or mecC gene. Whereas MLST and spa typing are relatively simple, typing of SCC mec is less trivial because of its heterogeneity. Whole-genome sequencing (WGS) provides the essential data for typing of the genetic background and SCC mec, but so far, no bioinformatic tools for SCC mec typing have been available. Here, we report the development and evaluation of SCC mecFinder for characterization of the SCC mec element from S. aureus WGS data. SCC mecFinder is able to identify all SCC mec element types, designated I to XIII, with subtyping of SCC mec types IV (2B) and V (5C2). SCC mec elements are characterized by two different gene prediction approaches to achieve correct annotation, a Basic Local Alignment Search Tool (BLAST)-based approach and a k-mer-based approach. Evaluation of SCC mecFinder by using a diverse collection of clinical isolates ( n = 93) showed a high typeability level of 96.7%, which increased to 98.9% upon modification of the default settings. In conclusion, SCC mecFinder can be an alternative to more laborious SCC mec typing methods and is freely available at https://cge.cbs.dtu.dk/services/SCCmecFinder.

          IMPORTANCE SCC mec in MRSA is acknowledged to be of importance not only because it contains the mecA or mecC gene but also for staphylococcal adaptation to different environments, e.g., in hospitals, the community, and livestock. Typing of SCC mec 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 mecFinder, that includes most of the needs for infection control professionals and researchers regarding the interpretation of SCC mec elements. The software detects all of the SCC mec 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 mecFinder will be curated and updated as new elements are found and it is easy to use and freely accessible.

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          The evolutionary history of methicillin-resistant Staphylococcus aureus (MRSA).

          Methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of hospital-acquired infections that are becoming increasingly difficult to combat because of emerging resistance to all current antibiotic classes. The evolutionary origins of MRSA are poorly understood, no rational nomenclature exists, and there is no consensus on the number of major MRSA clones or the relatedness of clones described from different countries. We resolve all of these issues and provide a more thorough and precise analysis of the evolution of MRSA clones than has previously been possible. Using multilocus sequence typing and an algorithm, BURST, we analyzed an international collection of 912 MRSA and methicillin-susceptible S. aureus (MSSA) isolates. We identified 11 major MRSA clones within five groups of related genotypes. The putative ancestral genotype of each group and the most parsimonious patterns of descent of isolates from each ancestor were inferred by using BURST, which, together with analysis of the methicillin resistance genes, established the likely evolutionary origins of each major MRSA clone, the genotype of the original MRSA clone and its MSSA progenitor, and the extent of acquisition and horizontal movement of the methicillin resistance genes. Major MRSA clones have arisen repeatedly from successful epidemic MSSA strains, and isolates with decreased susceptibility to vancomycin, the antibiotic of last resort, are arising from some of these major MRSA clones, highlighting a depressing progression of increasing drug resistance within a small number of ecologically successful S. aureus genotypes.
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            A Field Guide to Pandemic, Epidemic and Sporadic Clones of Methicillin-Resistant Staphylococcus aureus

            In recent years, methicillin-resistant Staphylococcus aureus (MRSA) have become a truly global challenge. In addition to the long-known healthcare-associated clones, novel strains have also emerged outside of the hospital settings, in the community as well as in livestock. The emergence and spread of virulent clones expressing Panton-Valentine leukocidin (PVL) is an additional cause for concern. In order to provide an overview of pandemic, epidemic and sporadic strains, more than 3,000 clinical and veterinary isolates of MRSA mainly from Germany, the United Kingdom, Ireland, France, Malta, Abu Dhabi, Hong Kong, Australia, Trinidad & Tobago as well as some reference strains from the United States have been genotyped by DNA microarray analysis. This technique allowed the assignment of the MRSA isolates to 34 distinct lineages which can be clearly defined based on non-mobile genes. The results were in accordance with data from multilocus sequence typing. More than 100 different strains were distinguished based on affiliation to these lineages, SCCmec type and the presence or absence of PVL. These strains are described here mainly with regard to clinically relevant antimicrobial resistance- and virulence-associated markers, but also in relation to epidemiology and geographic distribution. The findings of the study show a high level of biodiversity among MRSA, especially among strains harbouring SCCmec IV and V elements. The data also indicate a high rate of genetic recombination in MRSA involving SCC elements, bacteriophages or other mobile genetic elements and large-scale chromosomal replacements.
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              Classification of staphylococcal cassette chromosome mec (SCCmec): guidelines for reporting novel SCCmec elements.

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                Author and article information

                Contributors
                Role: Editor
                Journal
                mSphere
                mSphere
                msph
                msph
                mSphere
                mSphere
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2379-5042
                14 February 2018
                Jan-Feb 2018
                : 3
                : 1
                : e00612-17
                Affiliations
                [a ]Department of Bacteria, Parasites and Fungi, Statens Serum Institut, Copenhagen, Denmark
                [b ]Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Kgs Lyngby, Denmark
                [c ]Center for Biological Sequence Analysis, Department of Bioinformatics, Technical University of Denmark, Kgs Lyngby, Denmark
                U.S. Centers for Disease Control and Prevention
                Author notes
                Address correspondence to Anders Rhod Larsen, arl@ 123456ssi.dk .
                [*]

                Present address: Hülya Kaya, Statens Serum Institut, Copenhagen, Denmark.

                Citation Kaya H, Hasman H, Larsen J, Stegger M, Johannesen TB, Allesøe RL, Lemvigh CK, Aarestrup FM, Lund O, Larsen AR. 2018. SCC mecFinder, a web-based tool for typing of staphylococcal cassette chromosome mec in Staphylococcus aureus using whole-genome sequence data. mSphere 3:e00612-17. https://doi.org/10.1128/mSphere.00612-17.

                Author information
                https://orcid.org/0000-0003-0582-0457
                Article
                mSphere00612-17
                10.1128/mSphere.00612-17
                5812897
                29468193
                01995eed-9133-4f0a-a25b-183472bb6e20
                Copyright © 2018 Kaya et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 21 December 2017
                : 27 December 2017
                Page count
                supplementary-material: 4, Figures: 2, Tables: 4, Equations: 0, References: 13, Pages: 9, Words: 5215
                Funding
                Funded by: Danish Council for Strategic Research;
                Award ID: 09-067103
                Award Recipient : Award Recipient : Award Recipient :
                Funded by: EC | Horizon 2020 Framework Programme (H2020), https://doi.org/10.13039/100010661;
                Award Recipient :
                Categories
                Resource Report
                Clinical Science and Epidemiology
                Custom metadata
                January/February 2018

                mrsa,sccmec,bioinformatics,meca,mecc,typing
                mrsa, sccmec, bioinformatics, meca, mecc, typing

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