%0 Journal Article
%T Expanding a dynamic flux balance model of yeast fermentation to genome-scale
%A Felipe A Vargas
%A Francisco Pizarro
%A J Ricardo P¨Śrez-Correa
%A Eduardo Agosin
%J BMC Systems Biology
%D 2011
%I BioMed Central
%R 10.1186/1752-0509-5-75
%X Appropriate equations for maintenance, biomass composition, anaerobic metabolism and nutrient uptake are key to improve model performance, especially for predicting glycerol and ethanol synthesis. Prediction profiles of synthesis and consumption of the main metabolites involved in alcoholic fermentation closely agreed with experimental data obtained from numerous lab and industrial fermentations under different environmental conditions. Finally, fermentation simulations of genetically engineered yeasts closely reproduced previously reported experimental results regarding final concentrations of the main fermentation products such as ethanol and glycerol.A useful tool to describe, understand and predict metabolite production in batch yeast cultures was developed. The resulting model, if used wisely, could help to search for new metabolic engineering strategies to manage ethanol content in batch fermentations.Management of ethanol yields is emerging as one of the most relevant challenges for biotechnology, including both ethanol maximization (i.e. bioethanol and distilled beverages industries) and reduction/minimization (i.e. wine, bakery and commodities industries). Significant advances have been made in modeling ethanol fermentations [1-5], although steady-state, gene-modification strategies have resulted in varying degrees of success (for review see [6-8]) mainly due to growth impairment. In turn, dynamic models are able to describe and predict batch fermentations' time-courses better, since different metabolic stages are considered.A widely used modeling approach to predict cell behavior beyond calibration data is Flux Balance Analysis (FBA), which represents cell biochemical networks as a set of underdetermined constrained mass-balances. In this framework, linear programming is applied to generate a flux distribution that optimizes a given objective function, subject to flux balance equations and constraints. Objective functions commonly used are maximization of
%U http://www.biomedcentral.com/1752-0509/5/75