F2F Poster 21st Lancefield International Symposium for Streptococci and Streptococcal Diseases 2022

Applying whole genome sequencing to investigating clusters of Streptococcus pyogenes: experiences from England (#311)

Juliana Coelho 1 , Isabelle Poterill 1 , Sarah Lock 2 , Theresa Lamagni 1 , Max Courtney 2 , Sania Siddiq 2 , Rachael Hornigold 2 , Emma Blackmore 2 , Smruti Sinmyee 2 , Emily Phipps 2 , Lynsey Emmett 3 , Emma White 3 , Lucianne Lambourne 3 , Bruno Pichon 1
  1. UKHSA, London, United Kingdom
  2. UKHSA, South East, United Kingdom
  3. UKHSA, East of England, United Kingdom

 Background: Streptococcus pyogenes infection may have serious outcomes for patients, investigation and management of cases and clusters is key to limiting onward transmission. The Reference Laboratory in England routinely performs emm typing of isolates from invasive disease, and non-invasive isolates linked to cluster investigations. Where isolates are the same type, and further discrimination is needed, WGS is also performed.

Two clusters with iGAS emm 4 were identified in South East (SE) England in 2021. The first (emm 4.0, n=3) had clear links to local district nursing service; the second involved emm 4.19 cases (n=3 in 2021 and 1 in 2020) and was in a neighbouring area. WGS was performed on 57 isolates, including the outbreak cases and emm 4 control samples from across the UK.

Results: SNP variation of 0-385 (median 154) was observed amongst the sequences; 8 clusters of 0-5 SNPs were detected, including the 3 emm 4.0 cases in SE cluster 1, supporting the hypothesis of transmission and facilitating ongoing work with district nursing to review infection prevention and control measures. Variation of 0-49 SNPs was observed with SE cluster 2 emm 4.19, the two 2021 cases were 5 SNP apart. WGS data availability allowed investigation of additional cases in different regions; 3 further emm 4.0 in the SE were 66-72 SNPs apart, and were excluded from the cluster investigation, and 2 emm 4.0 cases in a neighbouring region were 0-SNPs apart, leading to additional investigations.

Conclusion: WGS analysis is paramount in supporting cluster investigation and informs interventions by ruling cases in or out of suspected clusters.