Epidemiological analysis of Legionnaires' disease in Scotland: a genomic study

Abstract

Legionella pneumophila is the main cause of a severe pneumonic illness known as Legionnaires' disease and is a global public health threat. Whole-genome sequencing (WGS) can be applied to trace environmental origins of L pneumophila infections, providing information to guide appropriate interventions. We aim to explore the evolutionary and epidemiological relationships in a 36-year Scottish L pneumophila reference isolate collection. We investigated the genomic epidemiology of Legionnaires' disease over 36 years in Scotland, comparing genome sequences for all clinical L pneumophila isolates (1984-2020) with a sequence dataset of 3211 local and globally representative isolates. We used a stratified clustering approach to capture epidemiological relationships by core genome Multi-locus Sequence Typing, followed by high-resolution phylogenetic analysis of clusters to measure diversity and evolutionary relatedness in context with epidemiological metadata. Clustering analysis showed that 111 (57·5 %) of 193 of L pneumophila infections in Scotland were caused by ten endemic lineages with a wide temporal and geographical distribution. Phylogenetic analysis of L pneumophila identified hospital-associated sublineages that had been detected in the hospital environment up to 19 years. Furthermore, 12 (30·0%) of 40 community-associated infections (excluding a single, large outbreak) that occurred over a 13 year period (from 2000 to 2013) were caused by a single widely distributed endemic clone (ST37), consistent with enhanced human pathogenicity. Finally, our analysis revealed clusters linked by national or international travel to distinct geographical regions, indicating several previously unrecognised travel links between closely related isolates (fewer than five single nucleotide polymorphisms) connected by geography. Our analysis reveals the existence of previously undetected endemic clones of L pneumophila that existed for many years in hospital, community, and travel-associated environments. In light of these findings, we propose that cluster and outbreak definitions should be reconsidered, and propose WGS-based surveillance as a critical public health tool for real-time identification and mitigation of clinically important endemic clones. Chief Scientist Office, Biotechnology and Biological Sciences Research Council (UK), Medical Research Council Precision Medicine Doctoral Training Programme, Wellcome Trust, and Medical Research Council (UK).