Campylobacter is the most frequent cause of foodborne illness in the UK, with an estimated half a million annual cases in the UK alone, most of which are due to the consumption of contaminated poultry products. One strategy to reduce the number of cases is to reduce the levels of endemic Campylobacter in poultry by developing new treatment options, such as antimicrobials, that can control Campylobacter before it enters the food chain. New knowledge-led approaches are needed to achieve this goal. Scientists at the Institute of Food Research, which is strategically funded by BBSRC, have combined experimental and mathematical modelling approaches to identify the key genes and metabolic pathways needed for growth and survival of Campylobacter. Antimicrobial compounds that target these indispensible pathways could play a role in helping to ensure our food is safe, while lowering the chance of antimicrobial resistance, and reducing Campylobacter’s £500million annual cost to the UK economy.
The multidisciplinary team of researchers first constructed a model of the metabolism of a reference strain of Campylobacter jejuni. The model they developed describes the network of reactions that Campylobacter uses to fuel its growth and development, and drive all of the other processes essential to its survival. By combining previously published work they pieced together over 500 metabolic reactions, controlled by almost 400 genes, to produce the first metabolic model of how Campylobacter works, based on current knowledge. Computer simulations were then run on the model to find out the most critical pathways and genes. It is these pathways, and the genes needed for operating them, that are most important to Campylobacter, and so these would be the best targets for any new antibiotics. Alongside this computational approach, Campylobacter genes were inactivated at random in a high-throughput screening procedure, which allowed the identification of those genes essential for Campylobacter growth.
While these methods have been used independently, the power of this project is in the combination of the two methods. It has allowed the identification of one particular pathway in Campylobacter that is essential in both approaches. Known as the shikimate pathway, it is used by bacteria, as well as plants and fungi, to produce essential amino acids. The shikimate pathway is absent in mammals, which is a big advantage for the design of novel antimicrobial compounds as they are less likely to induce side-effects. In other bacteria this pathway has been used for generating vaccine strains, validating the approach taken to identify essential genes. This new analysis indicates that in the case of Campylobacter, this pathway represents the most significant chink in its armour, and a re-evaluation and further analysis of the genes could hold the key to controlling Campylobacter’s spread.
Lead author Dr Aline Metris said “I thoroughly enjoyed this work because whilst implementing a new modelling technique, I also learned a lot about Campylobacter metabolism as a significant part of the work consisted of exchanging information with biologists. I was thrilled to be able to show that the integration of information from these experts into a model can contribute to our microbiological understanding. Indeed, the development of experimental methods to study microbiology at the genome scale has lead to a data deluge. It is now essential to develop computational methods to make sense of the data and to understand how phenotypic traits can emerge from genomic information.”
Dr Arnoud van Vliet, who leads IFR’s Campylobacter research, concluded “This study is an excellent example of the power of the combination of experimental science with mathematical modelling, as advocated by BBSRC and exemplified by the work at IFR. On their own, each approach would have given multiple targets requiring time-consuming investigations, but when used jointly, the future research can be much more directed. We have good hope that the work in our study can be extended towards a future decrease in Campylobacter infections”.
Reference: In vivo and in silico determination of essential genes of Campylobacter jejuni, BMC Genomics 12:535 doi: 10.1186/1471-2164-12-535