On Integrating the Droop Model with the Flux Balance Analysis Method to Predict Metabolic Shifts in Microalgae Growth

Identifying the mechanism for and predicting the metabolic shift between lipid accumulation and cell growth is a key research issue for microalgal biodiesel production. In this research, we propose a novel way to integrate a metabolic network model with a semi-empirical model called “Droop model” to predict the lipid accumulation and cell growth simultaneously. At each time instant of mass balance model integration, the Droop model is used to predict the cell growth rate and the nutrient consumption. Then, the Flux Balance Analysis (FBA) model is used to predict the rate of lipid accumulation, which is biochemically consistent with the predicted growth rate. In order to test the validity of the proposed approach, experiments are conducted for growing microalgae specie C. reinhardtii in a batch photo-bioreactor. Parameters of the Droop model are estimated from the experimental data and model predictions for the lipid contents are verified with the measured data. Parameter sensitivity analysis is conducted to investigate how the various parameters affect the cell growth and lipid accumulation. Finally, changes in the intracellular flux distribution are analyzed and predicted over the course of microalgae growth and nitrogen starvation with the integrated model.