Construction of robust dynamic genome-scale metabolic model structures of Saccharomyces cerevisiae through iterative re-parameterization.

摘要: Dynamic flux balance analysis (dFBA) has been widely employed in metabolic engineering to predict the effect of genetic modifications and environmental conditions cell׳s metabolism during dynamic cultures. However, importance model parameters used these methodologies not properly addressed. Here, we present a novel simple procedure identify dFBA that are relevant for calibration. The uses metaheuristic optimization pre/post-regression diagnostics, fixing iteratively do have significant role. We evaluated this protocol Saccharomyces cerevisiae framework calibrated aerobic fed-batch anaerobic batch cultivations. structures achieved only significant, sensitive uncorrelated able calibrate different experimental data. show consumption, suboptimal growth production rates more useful calibrating S. models than Boolean gene expression rules, biomass requirements ATP maintenance.