Genome analysis of Campylobacter jejuni strains isolated from a waterborne outbreak

Abstract

BackgroundWaterborne Campylobacter jejuni outbreaks are common in the Nordic countries, and PFGE (pulsed field gel electrophoresis) remains the genotyping method of choice in outbreak investigations. However, PFGE cannot assess the clonal relationship between isolates, leading to difficulties in molecular epidemiological investigations. Here, we explored the applicability of whole genome sequencing to outbreak investigation by re-analysing three C. jejuni strains (one isolated from water and two from patients) from an earlier resolved Finnish waterborne outbreak from the year 2000.ResultsOne of the patient strains had the same PFGE profile, as well as an identical overall gene synteny and three polymorphisms in comparison with the water strain. However, the other patient isolate, which showed only minor differences in the PFGE pattern relative to the water strain, harboured several polymorphisms as well as rearrangements in the integrated element CJIE2. We reconstructed the genealogy of these strains with ClonalFrame including in the analysis four C. jejuni isolated from chicken in 2012 having the same PFGE profile and sequence type as the outbreak strains. The three outbreak strains exhibited a paraphyletic relationship, implying that the drinking water from 2000 was probably contaminated with at least two different, but related, C. jejuni strains.ConclusionsOur results emphasize the capability of whole genome sequencing to unambiguously resolve the clonal relationship between isolates of C. jejuni in an outbreak situation and evaluate the diversity of the C. jejuni population.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-768) contains supplementary material, which is available to authorized users.

Whole-Genome Sequencing in Epidemiology of Campylobacter jejuni Infections

“…With this approach, the authors were able to identify temporally associated clusters of strains from cases demonstrating no apparent epidemiological links but showing similar levels of genetic diversity, as observed for same-patient isolates (differences of 3 to 14 loci among 1,478 to 1,586 shared loci) (25). As observed in point-source outbreaks (7,15,17), the loci that recurrently showed variations between same-patient isolates and epidemiologically linked isolates were homopolymeric tracts in contingency genes. Similar results were reported by Kovanen et al, who also used a hierarchical wgMLST approach to investigate the genomic relationships of apparently sporadic cases collected during a seasonal peak in Finland (8).…”

“…A similar number of genomic differences (3 SNVs) was observed between one human isolate and the assumed source isolate in a waterborne outbreak (7). Further studies have confirmed the initial findings of Revez and colleagues (7,15). Zhang et al identified up to seven allele differences between clonal isolates collected from three waterborne outbreaks, using a reference-based gene-by-gene approach (defined as ad hoc analysis) with the program Genome Profiler (https:// sourceforge.net/projects/genomeprofiler) (17).…”

“…Revez et al, analyzing a milk-borne outbreak, observed up to 3 SNVs and phase variations in 12 loci between the milk-and patient-derived isolates, using a PubMLST-hosted whole-genome multilocus sequence typing (wgMLST) schema featuring 1,738 loci (15). A similar number of genomic differences (3 SNVs) was observed between one human isolate and the assumed source isolate in a waterborne outbreak (7). Further studies have confirmed the initial findings of Revez and colleagues (7,15).…”

“…For example, the number of observed genomic differences between the assumed source isolate and a second human outbreak isolate analyzed by Revez et al. exceeded what might be expected to accumulate over the course of the outbreak, being similar (69 SNVs) to what was observed between the water isolate and a chicken strain obtained 12 years later (7). In addition, an Australian study that investigated a foodborne outbreak by extrapolating SNVs using Snippy 3.0 (https://github.com/tseemann/snippy) reported the circulation of at least two different strains among patients, one showing SNVs in the range of 3 to 8 and the second up to 30 (20).…”

“…Due to their intrinsic genetic instability, variations observed in these genomic regions cannot be used to infer epidemiological relationships between isolates. Therefore, to ensure that the genetic signals used for tracing and source attribution of isolates are independent of genomic changes introduced by the host, such homopolymeric tracts should be excluded from genome comparisons in the context of public health investigations (7,8,15,16).…”