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Inference of Antibiotic Resistance and Virulence among Diverse Group A Streptococcus Strains Using emm Sequencing and Multilocus Genotyping Methods
Authors:David Metzgar  Darcie Baynes  Christian J Hansen  Erin A McDonough  Daisy R Cabrera  Melody M Ellorin  Patrick J Blair  Kevin L Russell  Dennis J Faix
Institution:1. Department of Respiratory Diseases Research, Naval Health Research Center, San Diego, California, United States of America.; 2. Department of Defense Global Emerging Infections Surveillance and Response System (DoD-GEIS), Armed Forces Health Surveillance Center, Silver Spring, Maryland, United States of America.;St. Petersburg Pasteur Institute, Russian Federation
Abstract:

Background

Group A Streptococcus pyogenes (GAS) exhibits a high degree of clinically relevant phenotypic diversity. Strains vary widely in terms of antibiotic resistance (AbR), clinical severity, and transmission rate. Currently, strain identification is achieved by emm typing (direct sequencing of the genomic segment coding for the antigenic portion of the M protein) or by multilocus genotyping methods. Phenotype analysis, including critical AbR typing, is generally achieved by much slower and more laborious direct culture-based methods.

Methodology/Principal Findings

We compare genotype identification (by emm typing and PCR/ESI-MS) with directly measured phenotypes (AbR and outbreak associations) for 802 clinical isolates of GAS collected from symptomatic patients over a period of 6 years at 10 military facilities in the United States. All independent strain characterization methods are highly correlated. This shows that recombination, horizontal transfer, and other forms of reassortment are rare in GAS insofar as housekeeping genes, primary virulence and antibiotic resistance determinants, and the emm gene are concerned. Therefore, genotyping methods offer an efficient way to predict emm type and the associated AbR and virulence phenotypes.

Conclusions/Significance

The data presented here, combined with much historical data, suggest that emm typing assays and faster molecular methods that infer emm type from genomic signatures could be used to efficiently infer critical phenotypic characteristics based on robust genotype: phenotype correlations. This, in turn, would enable faster and better-targeted responses during identified outbreaks of constitutively resistant or particularly virulent emm types.
Keywords:
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