Genomic sequence investigation Streptococcus pyogenes clusters in England (2010–2015). (January 2019)

• Record Type: Journal Article
• Authors: Coelho, J.M.; Kapatai, G.; Jironkin, A.; Al-Shahib, A.; Daniel, R.; Dhami, C.; Laranjeira, A.M.; Chambers, T.; Phillips, S.; Tewolde, R.; Underwood, A.; Chalker, V.J.
• Is Part Of: Clinical microbiology and infection. Volume 25:Number 1(2019)
• Page Start: 96
• Page End: 101
• Publication Date: 2019-01
• Subjects: Clusters -- England -- Genomic sequence -- Investigation -- Streptococcus pyogenes; Medical microbiology -- Periodicals; Diagnostic microbiology -- Periodicals; Communicable diseases -- Periodicals; Infection -- Periodicals; 616.01
• DOI: 10.1016/j.cmi.2018.04.011
• Languages: English
• ISSNs: 1198-743X

Abstract

Abstract: Objectives: To analyse genomic sequence data of referred Streptococcus pyogenes isolates and those pertaining to selected elderly/nursing care or maternity clusters from 2010 to 2015 to ascertain genomic differences between epidemiologically related isolates and unrelated isolates from outbreaks of disease. Methods: The genomic sequences of 134 S. pyogenes isolates from 21 clusters of infection in elderly care or maternity settings from 2010 to 2015 were analysed using bioinformatics to ascertain genomic phylogeny, single nucleotide polymorphism (SNP) differences and statistical outliers from epidemiologically defined outbreaks. Analysis was undertaken within clusters and compared with sporadic isolates from geographically distinct outbreaks of S. pyogenes infection. Results: Genomic sequence analysis of 21 outbreaks of S. pyogenes infection ranged in size from a single patient (with colonized healthcare worker link) to 18 patient cases of group A streptococcus (GAS) infection in a single setting. Seventeen healthcare workers were identified in 8 of 21 outbreaks with the associated outbreak strain, with multiple staff in 2 of 21 outbreaks. Genomic sequences from epidemiologically linked isolates from patients, staff and healthcare environmental settings were highly conserved, differing by 0–1 SNP in some cases and mirrored geographical data. Four of 21 outbreaks had environmental contamination with the outbreak strain, indistinguishable or of limited SNP difference to the patient isolates. Genomic SNP analysis enabled exclusion of ten isolates from epidemiological outbreaks. Conclusions: Genomic discrimination can be applied to assist outbreak investigation. It enabled confirmation or exclusion of GAS cases from epidemiologically defined outbreaks. Colonization of healthcare workers and environmental contamination with the outbreak strain was demonstrated for several outbreaks.