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The overarching goal of the proposed project is to construct genome-scale models of the metabolism and evolution of Shewanella species, which are widely distributed in soil and water, and are often associated with the spoilage of meat and milk products. The integrated modeling will facilitate the development of new genetic markers for the more accurate detection of Shewanella contaminations, and it will provide insights into the prevention of food spoilage. Additionally, Shewanella species have significant applications in biogeochemical cycling in the coastal environment. Its potential associations with marine animals can also influence the quality and quantity of ecologically and economically important agricultural species. Furthermore, the computational tools developed from this project can be applied to study other species of significant environmental influences.
Shewanella is a diverse group of microorganisms that widely occur in soil and water, and are often associated with the spoilage of meat and milk products. It is not clear how this group evolves and what leads to the emergence of pathogenicity. Using computational modeling, in this project we will simulate the evolution and metabolic diversity of Shewanella. Through this project, we expect to develop new methods for the detection and prevention of Shewanella contaminants in meat and agricultural products.