Investigating locally relevant risk factors for Campylobacter infection in Australia: protocol for a case-control study and genomic analysis.
ABSTRACT: INTRODUCTION:The CampySource project aims to identify risk factors for human Campylobacter infection in Australia. We will investigate locally relevant risk factors and those significant in international studies in a case-control study. Case isolates and contemporaneous isolates from food and animal sources will be sequenced to conduct source attribution modelling, and findings will be combined with the case-control study in a source-assigned analysis. METHODS AND ANALYSIS:The case-control study will include 1200 participants (600 cases and 600 controls) across three regions in Australia. Cases will be recruited from campylobacteriosis notifications to health departments. Only those with a pure and viable Campylobacter isolate will be eligible for selection to allow for whole genome sequencing of isolates. Controls will be recruited from notified cases of influenza, frequency matched by sex, age group and geographical area of residence. All participants will be interviewed by trained telephone interviewers using a piloted questionnaire.We will collect Campylobacter isolates from retail meats and companion animals (specifically dogs), and all food, animal and human isolates will undergo whole genome sequencing. We will use sequence data to estimate the proportion of human infections that can be attributed to animal and food reservoirs (source attribution modelling), and to identify spatial clusters and temporal trends. Source-assigned analysis of the case-control study data will also be conducted where cases are grouped according to attributed sources. ETHICS AND DISSEMINATION:Human and animal ethics have been approved. Genomic data will be published in online archives accompanied by basic metadata. We anticipate several publications to come from this study.
Project description:Campylobacter infection is the most commonly notified bacterial enteritis in Germany. We performed a large combined case-control and source attribution study (Nov 2011-Feb 2014) to identify risk factors for sporadic intestinal Campylobacter infections and to determine the relative importance of various animal sources for human infections in Germany. We conducted multivariable logistic regression analysis to identify risk factors. Source attribution analysis was performed using the asymmetric island model based on MLST data of human and animal/food isolates. As animal sources we considered chicken, pig, pet dog or cat, cattle, and poultry other than chicken. Consumption of chicken meat and eating out were the most important risk factors for Campylobacter infections. Additional risk factors were preparation of poultry meat in the household; preparation of uncooked food and raw meat at the same time; contact with poultry animals; and the use of gastric acid inhibitors. The mean probability of human C. jejuni isolates to originate from chickens was highest (74%), whereas pigs were a negligible source for C. jejuni infections. Human C. coli isolates were likely to originate from chickens (56%) or from pigs (32%). Efforts need to be intensified along the food chain to reduce Campylobacter load, especially on chicken meat.
Project description: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.
Project description:Campylobacter infection is a leading cause of bacterial gastroenteritis worldwide, and most clinical cases appear as isolated, sporadic infections for which the source is rarely apparent. From July 2005 to December 2007 we conducted a prospective case-case study of sporadic, domestically-acquired Campylobacter enteritis in rural versus urban areas and a prevalence study of Campylobacter in animal and environmental sources in the Eastern Townships, Quebec. Isolates were typed using Multilocus Sequence Typing (MLST) to reinforce the case-case findings and to assign a source probability estimate for each human isolate. The risk of human campylobacteriosis was 1.89-fold higher in rural than urban areas. Unconditional multivariate logistic regression analysis identified two independent risk factors associated with human Campylobacter infections acquired in rural area: occupational exposure to animals (OR = 10.6, 95% CI: 1.2-91, p = 0.032), and household water coming from a private well (OR = 8.3, 95% CI: 3.4-20.4, p<0.0001). A total of 851 C. jejuni isolates (178 human, 257 chicken, 87 bovine, 266 water, 63 wild bird) were typed using MLST. Among human isolates, the incidence rates of clonal complexes (CC) CC-21, CC-45, and CC-61 were higher in rural than urban areas. MLST-based source attribution analysis indicated that 64.5% of human C. jejuni isolates were attributable to chicken, followed by cattle (25.8%), water (7.4%), and wild birds (2.3%). Chicken was the attributable source for the majority of cases, independent of residential area, sex and age. The increased incidence in rural compared to urban areas was associated with occupational exposure to animals, particularly cattle among those aged 15-34 years, and with consumption of private well water. Both bovine and water exposure appeared to contribute to the seasonal variation in campylobacteriosis. These results provide a basis for developing public education and preventive programs targeting the risk factors identified.
Project description:Genetic attribution of bacterial genotypes has become a major tool in the investigation of the epidemiology of campylobacteriosis and has implicated retail chicken meat as the major source of human infection in several countries. To investigate the robustness of this approach to the provenance of the reference data sets used, a collection of 742 Campylobacter jejuni and 261 Campylobacter coli isolates obtained from United Kingdom-sourced chicken meat was established and typed by multilocus sequence typing. Comparative analyses of the data with those from other isolates sourced from a variety of host animals and countries were undertaken by genetic attribution, genealogical, and population genetic approaches. The genotypes from the United Kingdom data set were highly diverse, yet structured into sequence types, clonal complexes, and genealogical groups very similar to those seen in chicken isolates from the Netherlands, the United States, and Senegal, but more distinct from isolates obtained from ruminant, swine, and wild bird sources. Assignment analyses consistently grouped isolates from different host animal sources regardless of geographical source; these associations were more robust than geographic associations across isolates from three continents. We conclude that, notwithstanding the high diversity of these pathogens, there is a strong signal of association of multilocus genotypes with particular hosts, which is greater than the geographic signal. These findings are consistent with local and international transmission of host-associated lineages among food animal species and provide a foundation for further improvements in genetic attribution.
Project description:Zoonotic diseases are a major cause of morbidity, and productivity losses in both human and animal populations. Identifying the source of food-borne zoonoses (e.g. an animal reservoir or food product) is crucial for the identification and prioritisation of food safety interventions. For many zoonotic diseases it is difficult to attribute human cases to sources of infection because there is little epidemiological information on the cases. However, microbial strain typing allows zoonotic pathogens to be categorised, and the relative frequencies of the strain types among the sources and in human cases allows inference on the likely source of each infection. We introduce sourceR, an R package for quantitative source attribution, aimed at food-borne diseases. It implements a Bayesian model using strain-typed surveillance data from both human cases and source samples, capable of identifying important sources of infection. The model measures the force of infection from each source, allowing for varying survivability, pathogenicity and virulence of pathogen strains, and varying abilities of the sources to act as vehicles of infection. A Bayesian non-parametric (Dirichlet process) approach is used to cluster pathogen strain types by epidemiological behaviour, avoiding model overfitting and allowing detection of strain types associated with potentially high "virulence". sourceR is demonstrated using Campylobacter jejuni isolate data collected in New Zealand between 2005 and 2008. Chicken from a particular poultry supplier was identified as the major source of campylobacteriosis, which is qualitatively similar to results of previous studies using the same dataset. Additionally, the software identifies a cluster of 9 multilocus sequence types with abnormally high 'virulence' in humans. sourceR enables straightforward attribution of cases of zoonotic infection to putative sources of infection. As sourceR develops, we intend it to become an important and flexible resource for food-borne disease attribution studies.
Project description:Zoonotic Salmonella causes millions of human salmonellosis infections worldwide each year. Information about the source of the bacteria guides risk managers on control and preventive strategies. Source attribution is the effort to quantify the number of sporadic human cases of a specific illness to specific sources and animal reservoirs. Source attribution methods for Salmonella have so far been based on traditional wet-lab typing methods. With the change to whole genome sequencing there is a need to develop new methods for source attribution based on sequencing data. Four European datasets collected in Denmark (DK), Germany (DE), the United Kingdom (UK) and France (FR) are presented in this descriptor. The datasets contain sequenced samples of Salmonella Typhimurium and its monophasic variants isolated from human, food, animal and the environment. The objective of the datasets was either to attribute the human salmonellosis cases to animal reservoirs or to investigate contamination of the environment by attributing the environmental isolates to different animal reservoirs.
Project description:A framework of general factors for infectious disease emergence was made operational for Campylobacter utilising explanatory variables including time series and risk factor data. These variables were generated using a combination of empirical epidemiology, case-case and case-control studies, time series analysis, and microbial sub-typing (source attribution, diversity, genetic distance) to unravel the changing/emerging aetiology of human campylobacteriosis. The study focused on Scotland between 1990-2012 where there was a 75% increase in reported cases that included >300% increase in the elderly and 50% decrease in young children. During this period there were three phases 1990-2000 a 75% rise and a 20% fall to 2006, followed by a 19% resurgence. The rise coincided with expansions in the poultry industry, consumption of chicken, and a shift from rural to urban cases. The post-2000 fall occurred across all groups apart from the elderly and coincided with a drop of the prevalence of Campylobacter in chicken and a higher proportion of rural cases. The increase in the elderly was associated with uptake of proton pump inhibitors. During the resurgence the increase was predominantly in adults and the elderly, again there was increasing use of PPIs and high prevalences in chicken and ruminants. Cases associated with foreign travel during the study also increased from 9% to a peak of 16% in 2006 before falling to an estimated 10% in 2011, predominantly in adults and older children. During all three periods source attribution, genetic distance, and diversity measurements placed human isolates most similar to those in chickens. A combination of emergence factors generic for infectious diseases were responsible for the Campylobacter epidemic. It was possible to use these to obtain a putative explanation for the changes in human disease and the potential to make an informed view of how incidence rates may change in the future.
Project description:The reservoir and source of human campylobacteriosis is primarily considered to be poultry, but also other such as ruminants, pets and environmental sources are related with infection burden. Multilocus sequence typing is often used for Campylobacter epidemiological studies to determine potential sources of human infections. The collection of 420 Campylobacter jejuni isolates with assigned MLST genotype from poultry (n = 139), cattle (n = 48) and wild birds (n = 101) were used in source attribution analysis. Asymmetric island model with accurate and congruent self-attribution results, was used to determine potential sources of human C. jejuni infections (n = 132) in Baltic States. Source attribution analysis revealed that poultry (88.3%) is the main source of C. jejuni human infections followed by cattle and wild bird with 9.4% and 2.3%, respectively. Our findings demonstrated that clinical cases of C. jejuni infections in Baltic countries are mainly linked to poultry, but also to cattle and wild bird sources.
Project description:Campylobacteriosis has increased markedly in Luxembourg during recent years. We sought to determine which Campylobacter genotypes infect humans, where they may originate from, and how they may infect humans. Multilocus sequence typing was performed on 1153 Campylobacter jejuni and 136 C. coli human strains to be attributed to three putative animal reservoirs (poultry, ruminants, pigs) and to environmental water using the asymmetric island model. A nationwide case-control study (2010-2013) for domestic campylobacteriosis was also conducted, including 367 C. jejuni and 48 C. coli cases, and 624 controls. Risk factors were investigated by Campylobacter species, and for strains attributed to different sources using a combined case-control and source attribution analysis. 282 sequence types (STs) were identified: ST-21, ST-48, ST-572, ST-50 and ST-257 were prevailing. Most cases were attributed to poultry (61.2%) and ruminants (33.3%). Consuming chicken outside the home was the dominant risk factor for both Campylobacter species. Newly identified risk factors included contact with garden soil for either species, and consuming beef specifically for C. coli. Poultry-associated campylobacteriosis was linked to poultry consumption in wintertime, and ruminant-associated campylobacteriosis to tap-water provider type. Besides confirming chicken as campylobacteriosis primary source, additional evidence was found for other reservoirs and transmission routes.
Project description:The partitioning of pathogenic strains isolated in environmental or human cases to their sources is challenging. The pathogens usually colonize multiple animal hosts, including livestock, which contaminate the food-production chain and the environment (e.g. soil and water), posing an additional public-health burden and major challenges in the identification of the source. Genomic data opens up new opportunities for the development of statistical models aiming to indicate the likely source of pathogen contamination. Here, we propose a computationally fast and efficient multinomial logistic regression source-attribution classifier to predict the animal source of bacterial isolates based on 'source-enriched' loci extracted from the accessory-genome profiles of a pangenomic dataset. Depending on the accuracy of the model's self-attribution step, the modeller selects the number of candidate accessory genes that best fit the model for calculating the likelihood of (source) category membership. The Accessory genes-Based Source Attribution (AB_SA) method was applied to a dataset of strains of Salmonella enterica Typhimurium and its monophasic variant (S. enterica 1,4,,12:i:-). The model was trained on 69 strains with known animal-source categories (i.e. poultry, ruminant and pig). The AB_SA method helped to identify 8 genes as predictors among the 2802 accessory genes. The self-attribution accuracy was 80?%. The AB_SA model was then able to classify 25 of the 29 S. enterica Typhimurium and S. enterica 1,4,,12:i:- isolates collected from the environment (considered to be of unknown source) into a specific category (i.e. animal source), with more than 85?% of probability. The AB_SA method herein described provides a user-friendly and valuable tool for performing source-attribution studies in only a few steps. AB_SA is written in R and freely available at https://github.com/lguillier/AB_SA.