Work

Molecular epidemiology of a nationwide Pseudomonas aeruginosa outbreak in Norway reveals multiple distinct clusters, including high-risk clone ST244

Year: 2025

Type: article

Abstract: BACKGROUND: A nationwide collection of Pseudomonas aeruginosa bacteraemia isolates was assembled during a wild-type P. aeruginosa ST3875 outbreak affecting approximately 400 patients across 40 hospitals in Norway in 2021-2022. AIM: To investigate the molecular epidemiology of P. aeruginosa in Norway through a multi-centre retrospective study. METHODS: All available isolates collected over 18 months were retrieved from 20 microbiology laboratories, and underwent whole-genome sequencing at five university hospitals. Metadata, including demographics, sampling dates and locations, were collated. Phylogenetic and comparative genomic analyses were performed to identify sequence types (STs), clusters, resistance determinants, and virulence factors. FINDINGS: This study included 376 unique patients with P. aeruginosa bacteraemia from 33 hospitals (69% male; median age 76 years), representing >90% of the national catchment area. Incidence varied regionally (5.1-16.3 per 100,000). The ST was resolved for 362 isolates, revealing 164 distinct types. Global high-risk and epidemic clones (e.g. ST233, ST244, ST277, ST298, ST308) comprised 30% of the collection. None of the isolates carried carbapenemases or extended-spectrum β-lactamases. Aside from the ST3875 outbreak clone (N=56), nine unrecognized phylogenetic clusters (two to 20 cases each) spanning multiple hospitals and regions were identified, including a widespread ST244 cluster harbouring a novel genomic island with putative virulence determinants, indicating a selective advantage for dissemination. CONCLUSIONS: This comprehensive genomic surveillance study uncovered multiple unexpected clusters of P. aeruginosa bacteraemia isolates in Norway, along with widespread presence of susceptible epidemic clones. Routine multi-level surveillance integrating sequencing with epidemiological data could enable earlier recognition of emerging high-risk clones and outbreaks, thereby strengthening infection prevention efforts.

Source: Journal of Hospital Infection

DOI: 10.1016/j.jhin.2025.11.004