Metris et al. BMC Genomics 2011, 12:535 http://www.biomedcentral.com/1471-2164/12/535 R E S E A R C H A R T I C L E Open Access In vivo and in silico determination of essential genes of Campylobacter jejuni Aline Metris*, Mark Reuter, Duncan JH Gaskin, Jozsef Baranyi and Arnoud HM van Vliet Abstract Background: In the United Kingdom, the thermophilic Campylobacter species C. jejuni and C. coli are the most frequent causes of food-borne gastroenteritis in humans. While campylobacteriosis is usually a relatively mild infection, it has a significant public health and economic impact, and possible complications include reactive arthritis and the autoimmune diseases Guillain-Barré syndrome. The rapid developments in “omics” technologies have resulted in the availability of diverse datasets allowing predictions of metabolism and physiology of pathogenic micro-organisms. When combined, these datasets may allow for the identification of potential weaknesses that can be used for development of new antimicrobials to reduce or eliminate C. jejuni and C. coli from the food chain. Results: A metabolic model of C. jejuni was constructed using the annotation of the NCTC 11168 genome sequence, a published model of the related bacterium Helicobacter pylori, and extensive literature mining. Using this model, we have used in silico Flux Balance Analysis (FBA) to determine key metabolic routes that are essential for generating energy and biomass, thus creating a list of genes potentially essential for growth under laboratory conditions. To complement this in silico approach, candidate essential genes have been determined using a whole genome transposon mutagenesis method. FBA and transposon mutagenesis (both this study and a published study) predict a similar number of essential genes (around 200). The analysis of the intersection between the three approaches highlights the shikimate pathway where genes are predicted to be essential by one or more method, and tend to be network hubs, based on a previously published Campylobacter protein-protein interaction network, and could therefore be targets for novel antimicrobial therapy. Conclusions: We have constructed the first curated metabolic model for the food-borne pathogen Campylobacter jejuni and have presented the resulting metabolic insights. We have shown that the combination of in silico and in vivo approaches could point to non-redundant, indispensable genes associated with the well characterised shikimate pathway, and also genes of unknown function specific to C. jejuni, which are all potential novel Campylobacter intervention targets. Background The rise of antibiotic resistance in pathogenic bacteria is a growing concern in the developed world necessitating knowledge-led approaches to identify new interventions and prevention strategies [1]. One of the common sources of pathogenic bacteria is food, with the food- borne zoonotic pathogens Salmonella, Escherichia coli and Campylobacter being prime examples. Although it can be contended whether the use of antibiotics in the food industry contributes to antimicrobial resistance, it * Correspondence: aline.metris@ifr.ac.uk Institute of Food Research, Norwich Research Park, Colney Lane, Norwich NR4 7UA, UK is clear that food-borne pathogens also increasingly acquire resistance to antimicrobial interventions. Multi- drug resistance in Salmonella is well documented [2,3]. For Listeria, antibiotic resistance has also been reported for strains isolated from food [4]. In Campylobacter, resistance to ampicillin, erythromycin, tetracycline, and ciprofloxacin have all been reported [5-7]. In Europe, Campylobacter was the most frequent cause of food-borne illness in 2007, with over 200,000 laboratory-confirmed cases [8] although the total num- ber of cases is thought to be approximately eightfold higher. Infection by Campylobacter is thought to be lar- gely due to the consumption of contaminated poultry © 2011 Metris et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.