470265 Constructing Predictive Kinetic Models of Metabolism for Guiding Strain Design
In addition, we reconstructed a second-generation genome scale metabolic model (iCth446) for C. thermocellum by correcting cofactor dependencies, restoring elemental and charge balances and updating GAM and NGAM values to improve phenotype predictions. The iCth446 model was next used as a scaffold to develop k-ctherm118, a core kinetic model of C. thermocellum metabolism . k-ctherm118 parameterization was carried out by simultaneously imposing fermentation data in lactate, malate, acetate and hydrogen production pathways for 19 measured metabolites spanning a library of 22 distinct single and multiple gene knock-out mutants. k-ctherm118 pointed at a systemic effect of limiting nitrogen resulting in increased yields for lactate, pyruvate and amino acids and an increase in ammonia and sugar phosphates concentrations (~1.5 fold) due to down-regulation of fermentation pathways under ethanol stress. The changes in the concentrations for fourteen out of eighteen metabolites in a ∆ldh mutant compared to wild-type were correctly predicted by k-ctherm118. These results quantitatively demonstrate that the developed kinetic models can reliably be used to predict genetically perturbed phenotypes under different growth conditions with a higher accuracy than any other earlier modeling effort.
 Khodayari, A., Maranas, C. k-ecoli457: A genome-scale Escherichia coli kinetic metabolic model satisfying flux data for multiple mutant strains. submitted.
 Dash, S., Khodayari, A., Lynd, L., Maranas, C. Characterization of Clostridium thermocellum strains with disrupted fermentation end-product pathways. in preparation.