Collaborative Research: Predictive Modeling of Maize Metabolism

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This project will develop and test predictive mathematical models of the chemical reactions (metabolism) by which maize (corn) transforms the sugars produced during photosynthesis into compounds such as starch that are stored in the seeds. The goal is to understand starch metabolism better and provide the means for enhancing food production. This study will reveal fundamental principles of metabolic function and dynamics, and provide interdisciplinary training (in mathematical modeling, genetic engineering and metabolic biochemistry) to students engaged in this project.Starchy endosperm (SE) is the major site of carbohydrate and protein storage in cereals, but atypical constraints complicate detailed resolution of the system. These include a steady state carbon dioxide level of essentially zero, coincident with energy-expensive breakdown and re-synthesis of building blocks prior to storage polymer formation. A major question in SE metabolism is how ATP is generated to support starch and protein synthesis, and how the photo-assimilate is divided between catabolic and anabolic pathways. This project will expand upon existing flux models to account for bio-energetic parameters, and probe the system by directed genetic modifications that impair specific metabolic nodes. Metabolite levels and flux maps will be compared between SE from unaltered and mutant lines. These data will be applied to refine the mathematical models and test hypotheses of how the system diverts chemical resources for storage compound accumulation.