Constraint-based genome-scale metabolic modeling of Clostridium acetobutylicum behavior in an immobilized column

In this study a step-wise optimization procedure was developed to predict solvent production using continuous ABE fermentation with immobilized cells. The modeling approach presented here utilizes previously published constraint-based metabolic model for Clostridium acetobutylicum without direct flux constraints. A recently developed flux ratio constraint method was adopted for the model. An experimental data set consisting of 25 experiments using different sugar mixtures as substrates and differing dilution rates was simulated successfully with the modeling approach. Converted to end product concentrations the mean absolute error for acetone was 0.31 g/l, for butanol 0.49 g/l, and for ethanol 0.17 g/l. The modeling approach was validated with another data set from similar experimental setup. The model errors for the validation data set was 0.24 g/l, 0.60 g/l, and 0.17 g/l for acetone, butanol, and ethanol, respectively.