Generation and Comparative Analyses of Genome-scale Metabolic Models for the Genus Shewanella using the Model SEED

Faculty Mentor(s)

Dr. Aaron Best, Hope College
Dr. Matthew DeJongh, Hope College

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The genus Shewanella consists of aquatic microorganisms that are distributed worldwide. Their features include respiratory and metabolic diversity as well as the ability to thrive in extreme environments. The study of Shewanella’s versatile metabolism can provide insights into the species’ capacity for biotechnology such as bioremediation and microbial fuel cells. The Model SEED (http://seed-viewer.theseed.org/models), a web-based resource for microbial genome analysis, was used to generate genome-scale metabolic models for sequenced Shewanella genomes. The draft metabolic model for S. oneidensis was curated, focusing on areas of metabolism that have not been well-curated in previous modeling efforts (e.g., anaerobic respiratory systems, lipopolysaccharide biosynthesis). The goals of this work are to 1) expand the coverage of metabolic diversity in databases used for metabolic modeling, 2) design and refine software tools to facilitate manual curation of metabolic models and 3) generate a complete S. oneidensis metabolic model that can be used with computational tools and high throughput experimental approaches to advance our understanding of the metabolic strategies and physiology of the genus Shewanella.

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