(404f) The Genome-Scale Model Biomass Constituting Equation Plays a Large Role in Predicting Biofuels Production | AIChE

(404f) The Genome-Scale Model Biomass Constituting Equation Plays a Large Role in Predicting Biofuels Production


Senger, R. S. - Presenter, Virginia Tech

Genome-scale models have made important contributions to biotechnology and biomedicine. When used with flux balance analysis for predictive purposes, maximizing the specific growth rate is the common objective function. To simulate cell growth, a biomass constituting equation is required and consists of several macromolecules (e.g., protein, DNA, RNA, lipids, etc.) as well as organic metabolites, energy, reducing power, and ionic species. Sensitivity analyses have been performed on different biomass constituting equations of several genome-scale models. In most cases, relatively low influence of the stoichiometric coefficients of biomass components on the resulting specific growth rate has been observed. Because of this, it is easy to interpret that the biomass constituting equation holds little significance to genome-scale modeling when compared to the catabolic pathways. Here, this assumption is shown to be false as the predicted production of biobutanol from Clostridium acetobutylicum ATCC 824 is shown to be a strong function of the biomass constituting equation. First, several existing biomass constituting equations (from closely-related organisms) were evaluated using an existing C. acetobutylicum model to determine the influence of the biomass constituting equation on the relationship between the specific growth rate of the organism and the predicted biobutanol production. Next, the specific proton influx/efflux rate showed to have a strong influence on this relationship, as did cellular maintenance requirements. The relative amounts of specific lipids in the biomass constituting equation showed to have little effect, demonstrating a need for solvent toxicity mechanisms to be built into genome-scale models. These findings have several implications. In particular, it is demonstrated that the biomass constituting equation should no longer exist as a static entity in a genome-scale model, and steps are presented on how to develop dynamic biomass equations. The concept of a global sensitivity analysis of the biomass constituting equation is presented here, and the implications of this approach are contrasted with the relative sensitivity analysis approaches that have been used to date.