Tracing isolates from domestic human Campylobacter jejuni infections to chicken slaughter batches and swimming water using whole-genome multilocus sequence typing

Abstract

Campylobacter jejuni is the leading cause of bacterial gastroenteritis and chicken is considered a major reservoir and source of human campylobacteriosis. In this study, we investigated temporally related Finnish human (n=95), chicken (n=83) and swimming water (n=20) C. jejuni isolates collected during the seasonal peak in 2012 using multilocus sequence typing (MLST) and whole-genome MLST (wgMLST). Our objective was to trace domestic human C. jejuni infections to C. jejuni isolates from chicken slaughter batches and swimming water. At MLST level, 79% of the sequence types (STs) of the human isolates overlapped with chicken STs suggesting chicken as an important reservoir. Four STs, the ST-45, ST-230, ST-267 and ST-677, covered 75% of the human and 64% of the chicken isolates. In addition, 50% of the swimming water isolates comprised ST-45, ST-230 and ST-677. Further wgMLST analysis of the isolates within STs, accounting their temporal relationship, revealed that 22 of the human isolates (24%) were traceable back to C. jejuni positive chicken slaughter batches. None of the human isolates were traced back to swimming water, which was rather sporadically sampled. The highly discriminatory wgMLST, together with the patient background information and temporal relationship data with possible sources, offers a new, accurate approach to trace back the origin of domestic campylobacteriosis. Our results suggest that potentially a substantial proportion of campylobacteriosis cases during the seasonal peak most probably are due to other sources than chicken meat consumption. These findings warrant further wgMLST-based studies to reassess the role of other reservoirs in the Campylobacter epidemiology both in Finland and elsewhere.

Whole-Genome Sequencing in Epidemiology of Campylobacter jejuni Infections

“…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).…”

“…This approach allowed the authors to identify subclusters of isolates (which varied in only a few loci) obtained from cases spread over a large geographical area, despite lacking an apparent epidemiological link (8). In their subsequent study, Kovanen and colleagues attempted to identify the possible sources of these predicted diffuse outbreaks, again applying a hierarchical wgMLST approach for each ST group and using the reference-based gene-by-gene method implemented in the Genome Profiler software (16,17). Thereafter, the authors manually screened for allele differences using a 5-SNV cutoff value, while excluding indels in homopolymeric tracts, to define clusters of genetically indistinguishable isolates (16).…”

“…In their subsequent study, Kovanen and colleagues attempted to identify the possible sources of these predicted diffuse outbreaks, again applying a hierarchical wgMLST approach for each ST group and using the reference-based gene-by-gene method implemented in the Genome Profiler software (16,17). Thereafter, the authors manually screened for allele differences using a 5-SNV cutoff value, while excluding indels in homopolymeric tracts, to define clusters of genetically indistinguishable isolates (16). When accounting for temporal clustering, the authors were able to link up to 24% of the human cases to specific chicken slaughter batches (16).…”

“…Thereafter, the authors manually screened for allele differences using a 5-SNV cutoff value, while excluding indels in homopolymeric tracts, to define clusters of genetically indistinguishable isolates (16). When accounting for temporal clustering, the authors were able to link up to 24% of the human cases to specific chicken slaughter batches (16). To identify the possible existence of a diffuse outbreak, Fernandes et al applied the method introduced by Cody and colleagues (25) to compare C. jejuni isolates collected through a surveillance program with a reference population of nonrelated isolates from the same lineage (ST-21) (27).…”

“…The common belief is that the gene-by-gene method is more suitable for this task than an SNV-calling approach, since the gene-by-gene approach is efficient, easy to automate, computationally less intensive, and less likely to be affected by multi-SNV import resulting from allelic replacement due to homologous gene transfer (24). Although a consensus regarding the analytical (experimental and bioinformatic) pipeline to use in the gene-by-gene approach and the interpretation criteria are still under evaluation, it seems clear that hierarchical wgMLST methodology (8,16,25), in which a first-level genomic clustering based on a core set of loci is followed by an ad hoc analysis with an increased number of loci for added discriminatory power, will be the basic approach for these types of investigations.…”