Biological analysis and mathematical modeling of glucose metabolism and the aspartate and pyruvate family amino acid biosyntheses in Escherichia coli K12

To elucidate the systems biology of the model organism, Escherichia coli, mathematical models to simulate carbon flow through the pathways of central metabolism, and pyruvate and aspartate family amino acid biosynthesis are developed. A "bottom-up" approach is elected to incorporate detailed enzyme kinetic and pathway-specific regulatory mechanisms from experimental data into the models. To achieve this goal, kMech and Cellerator packages in Mathematica(TM) are used to automatically convert models for enzyme mechanisms and regulation patterns into association-dissociation reactions, and then into differential equations. These equations are solved by Mathematica(TM) to simulate each model and to generate graphical outputs. In addition to simplifying the underlining mathematics of writing differential equations, this approach allows the examination of the biochemical behavior of metabolites and enzyme states in the pathway with great detail.; Models to simulate the behavior of more complex enzymes in an overall simulation of central metabolic and amino acid biosynthesis pathways also are described. A more flexible model in Cellerator, which generalizes the Monod, Wyman, Changeux (MWC) model for enzyme allosteric regulation is used to allow for multiple substrate, activator and inhibitor binding sites. This model expands the ability to simulate the behavior of allosteric enzymes and their feedback inhibition mechanisms and allows the generation of a more accurate simulation of allosteric effects in biosynthetic pathways. A random steady state model is used to describe catalysis by large enzyme complexes such as pyruvate dehydrogenase and alpha-ketoglutarate dehydrogenase in the TCA cycle. This model incorporates the rate of the overall cycles of reactions in the complex with the random nature of the structural organization of component enzymes.; To verify the simulations and models for enzyme mechanisms, the models' behavior is tested under conditions of metabolic and genetic perturbations, and the results are compared with experimental data from the literature. The overall effect of cellular growth on an alternative carbon source such as acetate on the central pathways of metabolism and how well this shift correlates with the simulations is also explored. In all cases, the simulations are consistent with experimental results and data in the literature.