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<p>The long term goal of this project is to use new systems biology methods to generate computational metabolic models of numerous foodborne pathogens such as Listeria, Salmonella, and E. coli. These computational models will be used to make growth predictions, identify new control targets, and to shed new understanding about the evolutionary diversity of these groups of foodborne pathogens. We plan to conduct computational and "wet-lab" experiments with these pathogenic strains to validate computational predictions and to lead to new discovery. </p><p>The specific goals of this proposal are:</p><ol><li> Examination of the evolutionary diversity of Listeria spp. through genome-scale metabolic modeling</li><li> Evaluation of growth and metabolic variations of Salmonella spp. strains related to host-specificity using computational metabolic models</li><li> Determination of the metabolic capabilities and new control targets for the European foodborne outbreak strain of E. coli O104:H4 </li></ol></p>
Systems biology is an approach to connect all of the information known about an organism together using computational approaches to guide experimental design and lead to new understandings about biological organisms such as humans, bacteria, and viruses. These approaches lead to the development of new treatment methods for human disease and ways to make foods safer. This research combines computational modeling with experimental approaches to study foodborne pathogens to address human disease and food safety.