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Euro Surveill. 2017 Nov;22(45). doi: 10.2807/1560-7917.ES.2017.22.45.17-00137.

Epidemiological information is key when interpreting whole genome sequence data - lessons learned from a large Legionella pneumophila outbreak in Warstein, Germany, 2013.

Author information

1
The ESCMID Study Group for Legionella infections (ESGLI).
2
These authors contributed equally to the work.
3
Institute of Medical Microbiology and Hygiene, Dresden University of Technology, Dresden, Germany.
4
Department for Periodontology and Restorative Dentistry, University Hospital Muenster, Muenster, Germany.
5
Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
6
Public Health Services, Ministry of Health, Jerusalem, Israel.

Abstract

IntroductionWhole genome sequencing (WGS) is increasingly used in Legionnaires' disease (LD) outbreak investigations, owing to its higher resolution than sequence-based typing, the gold standard typing method for Legionella pneumophila, in the analysis of endemic strains. Recently, a gene-by-gene typing approach based on 1,521 core genes called core genome multilocus sequence typing (cgMLST) was described that enables a robust and standardised typing of L. pneumophila. Methods: We applied this cgMLST scheme to isolates obtained during the largest outbreak of LD reported so far in Germany. In this outbreak, the epidemic clone ST345 had been isolated from patients and four different environmental sources. In total 42 clinical and environmental isolates were retrospectively typed. Results: Epidemiologically unrelated ST345 isolates were clearly distinguishable from the epidemic clone. Remarkably, epidemic isolates split up into two distinct clusters, ST345-A and ST345-B, each respectively containing a mix of clinical and epidemiologically-related environmental samples. Discussion/conclusion: The outbreak was therefore likely caused by both variants of the single sequence type, which pre-existed in the environmental reservoirs. The two clusters differed by 40 alleles located in two neighbouring genomic regions of ca 42 and 26 kb. Additional analysis supported horizontal gene transfer of the two regions as responsible for the difference between the variants. Both regions comprise virulence genes and have previously been reported to be involved in recombination events. This corroborates the notion that genomic outbreak investigations should always take epidemiological information into consideration when making inferences. Overall, cgMLST proved helpful in disentangling the complex genomic epidemiology of the outbreak.

KEYWORDS:

Legionella pneumophila; Legionnaires' disease; Outbreaks; Whole Genome Sequencing; cgMLST; multilocus sequence typing

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