Article Text
Abstract
Objectives Pseudomonas aeruginosa is a common nosocomial pathogen responsible for significant morbidity and mortality internationally. Patients may become colonised or infected with P. aeruginosa after exposure to contaminated sources within the hospital environment. The aim of this study was to determine whether whole-genome sequencing (WGS) can be used to determine the source in a cohort of burns patients at high risk of P. aeruginosa acquisition.
Study design An observational prospective cohort study.
Setting Burns care ward and critical care ward in the UK.
Participants Patients with >7% total burns by surface area were recruited into the study.
Methods All patients were screened for P. aeruginosa on admission and samples taken from their immediate environment, including water. Screening patients who subsequently developed a positive P. aeruginosa microbiology result were subject to enhanced environmental surveillance. All isolates of P. aeruginosa were genome sequenced. Sequence analysis looked at similarity and relatedness between isolates.
Results WGS for 141 P. aeruginosa isolates were obtained from patients, hospital water and the ward environment. Phylogenetic analysis revealed eight distinct clades, with a single clade representing the majority of environmental isolates in the burns unit. Isolates from three patients had identical genotypes compared with water isolates from the same room. There was clear clustering of water isolates by room and outlet, allowing the source of acquisitions to be unambiguously identified. Whole-genome shotgun sequencing of biofilm DNA extracted from a thermostatic mixer valve revealed this was the source of a P. aeruginosa subpopulation previously detected in water. In the remaining two cases there was no clear link to the hospital environment.
Conclusions This study reveals that WGS can be used for source tracking of P. aeruginosa in a hospital setting, and that acquisitions can be traced to a specific source within a hospital ward.
- BIOTECHNOLOGY & BIOINFORMATICS
- MICROBIOLOGY
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