Multiple distinct outbreaks of Panton-Valentine leucocidin-positive community-associated meticillin-resistant Staphylococcus aureus in Ireland investigated by whole-genome sequencing

Abstract

Background Panton–Valentine leucocidin (PVL)-positive community-associated meticillin-resistant Staphylococcus aureus (CA-MRSA) is increasingly associated with infection outbreaks. Aim To investigate multiple suspected PVL-positive CA-MRSA outbreaks using whole-genome sequencing (WGS). Methods Forty-six suspected outbreak-associated isolates from 36 individuals at three separate Irish hospitals (H1–H3) and from separate incidents involving separate families associated with H2 were investigated by whole-genome multi-locus sequence typing (wgMLST). Findings Two clusters (CH1 and CH2) consisting of 8/10 and 6/6 PVL-positive t008 ST8-MRSA-IVa isolates from H1 and H2, respectively, were identified. Within each cluster, neighbouring isolates were separated by ≤5 allelic differences; however, ≥73 allelic differences were identified between the clusters, indicating two independent outbreaks. Isolates from the H3 maternity unit formed two clusters (CH3–SCI and CH3–SCII) composed of four PVL-negative t4667 ST5-MRSA-V and 14 PVL-positive t002 ST5-MRSA-IVc isolates, respectively. Within clusters, neighbouring isolates were separated by ≤24 allelic differences, whereas both clusters were separated by 1822 allelic differences, indicating two distinct H3 outbreaks. Eight PVL-positive t127 ST1-MRSA-V+fus and three PVL-negative t267 ST97-MRSA-V+fus isolates from two distinct H2-associated families FC1 (N = 4) and FC2 (N = 7) formed three separate clusters (FC1 (t127), FC2 (t127) and FC2 (t267)). Neighbouring isolates within clusters were closely related and exhibited ≤7 allelic differences. Intrafamilial transmission was apparent, but the detection of ≥48 allelic differences between clusters indicated no interfamilial transmission. Conclusion The frequent importation of PVL-positive CA-MRSA into healthcare settings, transmission and association with outbreaks is a serious ongoing concern. WGS is a highly discriminatory, informative method for deciphering such outbreaks conclusively.