Genomic Resolution of Outbreak-Associated Legionella pneumophila Serogroup 1 Isolates from New York State

Abstract

ABSTRACT A total of 30 Legionella pneumophila serogroup 1 isolates representing 10 separate legionellosis laboratory investigations (“outbreaks”) that occurred in New York State between 2004 and 2012 were selected for evaluation of whole-genome sequencing (WGS) approaches for molecular subtyping of this organism. Clinical and environmental isolates were available for each outbreak and were initially examined by pulsed-field gel electrophoresis (PFGE). Sequence-based typing alleles were extracted from WGS data yielding complete sequence types (ST) for isolates representing 8 out of the 10 outbreaks evaluated in this study. Isolates from separate outbreaks sharing the same ST also contained the fewest differences in core genome single nucleotide polymorphisms (SNPs) and the greatest proportion of identical allele sequences in a whole-genome multilocus sequence typing (wgMLST) scheme. Both core SNP and wgMLST analyses distinguished isolates from separate outbreaks, including those from two outbreaks sharing indistinguishable PFGE profiles. Isolates from a hospital-associated outbreak spanning multiple years shared indistinguishable PFGE profiles but displayed differences in their genome sequences, suggesting the presence of multiple environmental sources. Finally, the rtx gene demonstrated differences in the repeat region sequence among ST1 isolates from different outbreaks, suggesting that variation in this gene may be useful for targeted molecular subtyping approaches for L. pneumophila . This study demonstrates the utility of various genome sequence analysis approaches for L. pneumophila for environmental source attribution studies while furthering the understanding of Legionella ecology. IMPORTANCE We demonstrate that whole-genome sequencing helps to improve resolution of Legionella pneumophila isolated during laboratory investigations of legionellosis compared to traditional subtyping methods. These data can be important in confirming the environmental sources of legionellosis outbreaks. Moreover, we evaluated various methods to analyze genome sequence data to help resolve outbreak-related isolates.