In vivo and in silico determination of essential genes of Campylobacter jejuni

<p>Abstract</p> <p>Background</p> <p>In the United Kingdom, the thermophilic <it>Campylobacter </it>species <it>C. jejuni </it>and <it>C. coli </it>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 <it>C. jejuni </it>and <it>C. coli </it>from the food chain.</p> <p>Results</p> <p>A metabolic model of <it>C. jejuni </it>was constructed using the annotation of the NCTC 11168 genome sequence, a published model of the related bacterium <it>Helicobacter pylori</it>, and extensive literature mining. Using this model, we have used <it>in silico </it>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 <it>in silico </it>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 <it>Campylobacter </it>protein-protein interaction network, and could therefore be targets for novel antimicrobial therapy.</p> <p>Conclusions</p> <p>We have constructed the first curated metabolic model for the food-borne pathogen <it>Campylobacter jejuni </it>and have presented the resulting metabolic insights. We have shown that the combination of <it>in silico </it>and <it>in vivo </it>approaches could point to non-redundant, indispensable genes associated with the well characterised shikimate pathway, and also genes of unknown function specific to <it>C. jejuni</it>, which are all potential novel <it>Campylobacter </it>intervention targets.</p

A dynamic network analysis of the physiological state of foodborne pathogens: application to Escherichia coli during osmotic stress and comparison with Salmonella Typhimurium

International audienceTo characterise the physiological state of cells during adaptation to osmotic stress, we decompose the dynamic regulatory network of E. coli into subgraphs. We then compare the results of E. coli and Salmonella. Beside the sigma factor associated with stress, the response involves global regulators that modify nucleoid conformation which has been shown to be different in the two bacteria. In Salmonella, some genes involved in osmotic stress are also linked to virulence regulation. We conclude that decomposition of regulatory networks into subgraphs as a function of environmental conditions may be a useful representation of the physiological state of bacteria