Genome-Wide Identification of Host-Segregating Epidemiological Markers for Source Attribution in Campylobacter jejuni

Abstract

Campylobacter is among the most common worldwide causes of bacterial gastroenteritis. This organism is part of the commensal microbiota of numerous host species, including livestock, and these animals constitute potential sources of human infection. Molecular typing approaches, especially multilocus sequence typing (MLST), have been used to attribute the source of human campylobacteriosis by quantifying the relative abundance of alleles at seven MLST loci among isolates from animal reservoirs and human infection, implicating chicken as a major infection source. The increasing availability of bacterial genomes provides data on allelic variation at loci across the genome, providing the potential to improve the discriminatory power of data for source attribution. Here we present a source attribution approach based on the identification of novel epidemiological markers among a reference pan-genome list of 1,810 genes identified by gene-by-gene comparison of 884 genomes of Campylobacter jejuni isolates from animal reservoirs, the environment, and clinical cases. Fifteen loci involved in metabolic activities, protein modification, signal transduction, and stress response or coding for hypothetical proteins were selected as host-segregating markers and used to attribute the source of 42 French and 281 United Kingdom clinical C. jejuni isolates. Consistent with previous studies of British campylobacteriosis, analyses performed using STRUCTURE software attributed 56.8% of British clinical cases to chicken, emphasizing the importance of this host reservoir as an infection source in the United Kingdom. However, among French clinical isolates, approximately equal proportions of isolates were attributed to chicken and ruminant reservoirs, suggesting possible differences in the relative importance of animal host reservoirs and indicating a benefit for further national-scale attribution modeling to account for differences in production, behavior, and food consumption.IMPORTANCE Accurately quantifying the relative contribution of different host reservoirs to human Campylobacter infection is an ongoing challenge. This study, based on the development of a novel source attribution approach, provides the first results of source attribution in Campylobacter jejuni in France. A systematic analysis using gene-by-gene comparison of 884 genomes of C. jejuni isolates, with a pan-genome list of genes, identified 15 novel epidemiological markers for source attribution. The different proportions of French and United Kingdom clinical isolates attributed to each host reservoir illustrate a potential role for local/national variations in C. jejuni transmission dynamics.

Keywords: Campylobacter; food-borne diseases; gene-by-gene approach; genomics; source attribution.

FIG 1

Genetic structure of 411 C. jejuni isolates from chicken and ruminants in different countries. A phylogenetic tree was constructed from 1,810 genes found in four reference strains of C. jejuni (NCTC11168, 81-176, 81116, and M1) through an approximation of the maximum likelihood algorithm using FastTree2, and visualized using MEGA6. The bar represents the number of substitutions per site. The color of the circle indicates the original host of the isolates, and the kind of circle indicates the country of origin. Isolates from chicken are shown in yellow and those from ruminants in blue. Worldwide isolates are represented by empty (white) circles, and French isolates are represented by filled-in circles. Numeric labels correspond to clonal complexes (CC) or sequence type (ST) of chicken and cattle isolates.

FIG 2

Correct host assignment accuracy in self-attribution tests of 1,810 core, soft-core, or accessory genes in C. jejuni isolates from chicken (yellow) and ruminants (blue). Twenty self-attribution tests were performed on random subsets of isolates using STRUCTURE software. Alleles at all loci in isolates of known host origin were assigned to the host training data set, and the probability of correct host population attribution was recorded. The average ± standard deviation (error bar) values of the rates of correct host assignment in self-attribution were calculated for each population. A Student t test was performed to assess statistical significance. Values were considered significantly different when P < 0.01 and are indicated by an asterisk.

FIG 3

Host-segregating power of each locus within the core, soft-core, and accessory genomes of C. jejuni. Each circle represents the rate of correct host assignment of one locus in self-attribution tests on chicken and ruminant isolates. Self-attribution tests were performed using the allelic diversity of chicken or ruminant isolates within their core, soft-core, or accessory genomes separately and STRUCTURE software. Alleles at all loci in isolates of known host origin were assigned to the host training data set, and the probability of correct host population attribution was recorded to determine the host-segregating power of each locus. Solid red circles represent the 15 candidates for host-segregating markers, and MLST loci are colored in blue.

FIG 4

Assignment to source of British and French human clinical C. jejuni isolates and those from French pets using STRUCTURE software. Each vertical bar represents one isolate, and the color of the bar shows the estimated probability that this isolate originates from each of the potential sources. Attribution source populations are chickens (yellow), ruminants (blue), and environment/wild bird isolates (green). Isolates were ordered by assigned host.