Modelling Campylobacter survival and spread through poultry processing: a population genomics approach.

Campylobacter is the most common cause of bacterial gastro-enteritis in the developed world. This organism is a common constituent of the gut micro-biota of birds and other animals and human infection is usually associated with the consumption of contaminated meat or poultry. Considerable effort has gone into investigating the root to human infection and there is substantial evidence that strains associated with chicken are a major source of disease. This is not thought to be because chicken types are more pathogenic but because chickens have high levels of contamination on the farm and this is maintained all the way through processing to retail. The mechanisms by which Campylobacter, an organism that is poorly adapted to survival outside of the host, spreads and potentially increases through poultry processing are poorly understood. Eliminating Campylobacter on the farm could tackle the problem but it requires expensive biosecurity interventions and there may other points through processing where interventions could be effective and practicable in the modern poultry industry. In this project we will use state-of-the-art means of determining the entire genetic code (genome) of Campylobacter strains from key stages through poultry processing and human disease. This genetic information will be used to examine how variation in the physical traits (phenotype), such as survival in a particular stage/niche, are determined by changes to the genes (genotype). Changes in the genetic structure of the population will be used to inform a mathematical model that simulates the passage of Campylobacter through processing based upon selection for certain genes, for example those required by the organism to survive outside of the chicken gut. By running model simulations with different parameters we will investigate (i) how the strains change through processing, (ii) the factors responsible for the survival and proliferation of disease associated lineages, and (iii) points in processing where Campylobacter can be most effectively pushed to extinction. This systems approach to understanding Campylobacter survival and spread will inform targeted interventions.

By identifying the genetic elements and associated phenotypes that enable some chicken-associated genotypes to survive poultry processing and infect humans, the aim of this proposal is to inform targeted interventions to reduce Campylobacter. A modelling approach based upon comparative functional genomics data will address fundamental questions about the genetic basis of genotypic variation from farm chickens to retail poultry. We will exploit recent advances in Illumina GA resequencing technologies, specifically high through-put isolate multiplexing, to sequence multiple genomes in individual and pooled samples to identify genomic differences associated with source. Data from association mapping will feed into the stochastic evolutionary genetics simulation model that incorporates many of the features involved in the generation and maintenance of sequence diversity at a population level including: initial number of genotypes, population size, mutation and recombination rate, growth rate, the fitness of particular genes and niche structure. Variables will be changed to reflect input from real systems enabling hypotheses based on the genome association studies to be tested. Specifically, fitness functions for particular genes will be derived from real data and selective sweeps acting on genes identified as important for survival will simulate the effect of various stages in poultry processing. Predictions from simulations will be tested in replicate experiments by tracking the changes in the genetic structure of Campylobacter populations in the same batch of chickens leaving the farm and at points through processing. Where the relative abundance of particular genes or alleles, identified by PCR, deviates from predictions in silico the model parameters will be adjusted (eg. allele fitness). Simulations will then be run using the validated model to identify points in processing were the Campylobacter population is vulnerable to targeted interventions.

(i) Business and Commerce BioCote Ltd. (www.biocote.com), the industrial partner named in this grant proposal, presents itself as the world's leading antimicrobial brand providing antimicrobial technology, technical and marketing support, and research to commercial organisations working in hygiene-critical environments. The results of commissioned studies and collaborations are presented in the scientific literature including the recent Biocote-Oxford University study in which the microbiological impact of antimicrobial treatment of poultry transportation crates was quantified. This has recently been accepted for publication in the Journal of Applied Microbiology and influenced this proposal. There are distinct commercial requirements for the system modelling approach in this proposal. Evidence for procedure/product claims including efficacy, effective period, and undesirable consequences has become increasingly important and can provide a competitive advantage. The commercial organisations affiliated to this study, including BioCote Ltd and its industry collaborators, will benefit through enhanced intervention development and also though differentiating themselves from similar products on a global scale. The list of commercial organisations associated with BioCote that potentially benefit from this study is restricted but there is highly significant interest from manufacturers of products and interventions for the poultry industry because of the inclusion of BioCote Ltd. Commercial benefit is difficult to quantify but given the scale and volume of the poultry processing industry, both in the UK and globally, there are considerable prospects of an increased market share for companies supplying the poultry industry who have adopted or can adopt interventions informed by this study's conclusions. Other commercial beneficiaries include organisations that supply infection control/decontamination aspects of poultry processing to whom antimicrobial technology is not applicable or relevant. Output data from simulations has the potential to dictate product development, formulation, composition and deployment and drive manufacturers towards more defined and efficacious products and strategies. (ii) Public health Campylobacter is the largest cause of bacterial gastroenteritis in the developed world and our recent research has shown the most significant source of human infection in the UK is chickens. While education and food preparation practices are important a major reduction in the human disease burden requires action to reduce Campylobacter in poultry. Interventions in the poultry industry abroad have resulted in dramatic decreases in human infection rates. For example, in Iceland flocks that tested positive before slaughter were frozen, together with on-farm measures, this led to a 10-fold reduction human disease. There is increasing pressure on UK poultry producers to tackle the problem of Campylobacter and government (FSA) targets are to be set for reduction in levels in raw chicken by 2015. Evidence based programmes are required to achieve this and are dependent upon high quality baseline data and analysis to inform the most effective targets for interventions such as improved on-farm biosecurity, improved hygiene, antimicrobial transport crates, chlorine washes at abattoirs, poultry freezing etc. Testing specific interventions to reduce Campylobacter at key stages through processing is relatively straight forward it is difficult develop effective strategies to break the transmission chain without investigating the system as a whole. This is where the modelling approach has its greatest advantage. When properly validated by detailed data from real systems our model will allow exhaustive testing of scenarios for reducing Campylobacter in the food chain and by informing interventions, translate to public health benefit.