title: Construction of robust dynamic genome-scale metabolic model structures of Saccharomyces cerevisiae through iterative re-parameterization.
abstract: Dynamic flux balance analysis (dFBA) has been widely employed in metabolic engineering to predict the effect of genetic modifications and environmental conditions in the cell׳s metabolism during dynamic cultures. However, the importance of the model parameters used in these methodologies has not been properly addressed. Here, we present a novel and simple procedure to identify dFBA parameters that are relevant for model calibration. The procedure uses metaheuristic optimization and pre/post-regression diagnostics, fixing iteratively the model parameters that do not have a significant role. We evaluated this protocol in a Saccharomyces cerevisiae dFBA framework calibrated for aerobic fed-batch and anaerobic batch cultivations. The model structures achieved have only significant, sensitive and uncorrelated parameters and are able to calibrate different experimental data. We show that consumption, suboptimal growth and production rates are more useful for calibrating dynamic S. cerevisiae metabolic models than Boolean gene expression rules, biomass requirements and ATP maintenance.
authors.affiliation: Department of Chemical and Bioprocess Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Avenida Vicuña Mackenna 4860, Santiago, Chile. Electronic address: bjsanche@uc.cl.
authors.forename: Benjamín J
authors.initials: BJ
authors.lastname: Sánchez
authors.affiliation: Department of Chemical and Bioprocess Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Avenida Vicuña Mackenna 4860, Santiago, Chile. Electronic address: perez@ing.puc.cl.
authors.forename: José R
authors.initials: JR
authors.lastname: Pérez-Correa
authors.affiliation: Department of Chemical and Bioprocess Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Avenida Vicuña Mackenna 4860, Santiago, Chile. Electronic address: agosin@ing.puc.cl.
authors.forename: Eduardo
authors.initials: E
authors.lastname: Agosin
mesh_terms: D000465:Algorithms; D001688:Biological Products / Q000378:metabolism*; D003198:Computer Simulation; D064688:Metabolic Flux Analysis / Q000379:methods*; D008954:Models, Biological; D020543:Proteome / Q000378:metabolism*; D012441:Saccharomyces cerevisiae / Q000378:metabolism*; D029701:Saccharomyces cerevisiae Proteins / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology
chemical_list: D001688:Biological Products; D020543:Proteome; D029701:Saccharomyces cerevisiae Proteins
keywords: Dynamic flux balance analysis; Genome-scale metabolic models; Metaheuristic optimization; Parameter estimation; Sensitivity analysis; Yeast