Community outbreaks of group A Streptococcus revealed by genome sequencing

• Published in: Scientific reports Vol. 7; no. 1; pp. 8554 - 9
• Main Authors: Turner, Claire E., Bedford, Luke, Brown, Nicholas M., Judge, Kim, Török, M. Estée, Parkhill, Julian, Peacock, Sharon J.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 17.08.2017; Nature Publishing Group; Nature Portfolio
• Subjects: 45; 45/22; 45/23; 631/326/107; 631/326/325/2482; Community-Acquired Infections - epidemiology; Community-Acquired Infections - microbiology; Disease Outbreaks; Disease transmission; Genome, Bacterial - genetics; Genomes; Genomics; Genotype; Genotypes; Health risks; Host-Pathogen Interactions; Humanities and Social Sciences; Humans; Molecular Epidemiology - methods; Molecular Typing; multidisciplinary; Outbreaks; Phylogeny; Polymorphism, Single Nucleotide; Public health; Retrospective Studies; Science; Science (multidisciplinary); Single-nucleotide polymorphism; Streptococcal Infections - epidemiology; Streptococcal Infections - microbiology; Streptococcus; Streptococcus infections; Streptococcus pyogenes - classification; Streptococcus pyogenes - genetics; Streptococcus pyogenes - physiology; United Kingdom - epidemiology; Whole Genome Sequencing - methods; United Kingdom
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-017-08914-x

The frequent occurrence of disease outbreaks in humans caused by group A Streptococcus (GAS) is an on-going public health threat. Conventional bacterial typing methods lack the discriminatory power to confidently confirm or refute outbreaks in hospital and community settings. Microbial whole genome sequencing (WGS) provides a potential solution to this, but, there has been limited population-based surveillance with accompanying sequence data. We performed retrospective genomic surveillance of 93 clinical GAS isolates from individuals in a defined geographic region. Detailed clinical information was obtained for closely related clusters of isolates. Genomic sequence data was contextualised through comparison with international data. We identified 18 different emm genotypes within our bacterial population, and revealed both highly diverse and closely related isolates. This high level of diversity was maintained even in the context of international sequence data. We also identified two emm 1 clusters, and one emm 3 cluster, of closely-related isolates that differed only by 1 to 4 single nucleotide polymorphisms. Analysis of clinical information identified no healthcare associated contact between patients, indicating cryptic community transmission. Our findings suggest that genomic surveillance of GAS would increase detection of transmission and highlight opportunities for intervention.