Systems Biology Approach to Discovery of Phenotype-Specific Metabolic Processes for Engineering Bacterial Bio-Hydrogen

Biological hydrogen is one of the most promising alternative energy and fuel resource today. Due to the ability of several naturally occurring microorganisms to generate hydrogen using different metabolic processes, engineered biohydrogen production is considered a feasible and sustainable technology. To improve upon current technological applications, biological and metabolic engineering approaches are underway to optimize metabolic processes involved in hydrogen production. In order to successfully modify metabolic pathways, full understanding of metabolic networks involved in expression of microbial traits in hydrogen producing organisms is necessary. In this paper, we demonstrate the application of two computational systems biology approaches to identify phenotype-related metabolic components related to hydrogen-producing bacteria. The first method utilizes prior knowledge to discover clusters of phenotype-related proteins in individual phenotypeexpressing microorganisms. When applied to bacterial functional relationship data, key enzymes, such as [FeFe]-hydrogenase, [NiFe]-hydrogenase, and glutamate synthase, were identified. In the second method, our efficient graph search algorithm, called PRP-Finder, is used to identify key genes and metabolic pathways that are likely related to biohydrogen production. In addition, predictions on a potential interplay, or cross-talk, between metabolic pathways can be predicted using this approach. Information obtained from both methodologies provides valuable insights into metabolic networks and system controls involved in expression of microbial traits essential for advancing engineering approaches that result in more efficient biohydrogen production.