Risk assessment prediction from genome sequences: Promises and dreams

Abstract

The application of bacterial genomics opens new avenues of research on foodborne pathogens. Foodborne pathogens must be able to colonize their hosts and survive transmission from host to host. Different groups of genes are involved in the processes of survival, colonization, and virulence, and such genes are potential targets for risk assessment and intervention strategies. Filtering from genome sequences the genes relevant to these processes is a major challenge, and although many tools are already available for analyses, this type of data mining is just beginning. For the simplest application, gene comparison, it is important to know how gene function, for instance in virulence, is being defined and tested. In other genomic applications, reserachers look for specific properties or characteristics of (virulence) genes to identify novel gene candidates. Each approach has pitfalls, and gene candidates must be tested in the lab to confirm their function. Models for colonization and virulence are available for most although not all pathogens. Models for survival and stress responses are needed to increase the utilization of genomic approaches to risk assessment. Here, I discuss how genome sequences are likely to help in microbial risk assessment of foodborne pathogens and how dreams may become promises.