(118f) Coupling Hydrodynamics and Flux Balance Analysis to Describe Microalgal Metabolism in Heterogeneous Photobioreactors

Blue-green algae, cyanobacteria, have emerged as promising platforms for production of biofuel and other economically valuable products. The main appealing trait of cyanobacterial biorefineries is their ability to harvest sunlight energy for CO₂ fixation. Thereby, they can be built near power plants to achieve both CO₂ mitigation and biosynthesis of desirable products. However, algal cultivations are often limited by uneven illuminations in photobioreactors because light intensity is attenuated as it passes through the culture. Hence, in large-volume algal bioreactors, cyanobacteria perform photoautotrophic growth in “light zone” (near the reactor surface), while use energy-storage compounds (such as glycogen) to conduct heterotrophic metabolism in the “dark zone” away from the light source. Thereby, cyanobacterial metabolism in photo-bioreactors is highly dynamic and strongly influenced by light intensity, mixing rates, and reactor geometry. To generate a better understanding of cyanobacterial metabolism in heterogeneous photobioreactors, we coupled genome-scale flux balance analysis (FBA, Synechocystis 6803 as a model strain) and photobioreactor hydrodynamics to describe temporal and spatial performances of cyanobacteria in photobioreactors.

Our model has proposed following three cell metabolic modes: 1) photoautotrophic condition under which the light and nutrients support cyanobacteria growth, and glycogen is accumulated as the carbon storage; 2) dark condition under which cyanobacteria degrade glycogen to maintain cell growth; and 3) resting condition under which cell metabolism stops. The model that couples FBA, kinetic model, and hydrodynamics model is under construction in the following approach. First, the light distribution is heterogeneous and dependent on both biomass concentration and light path length. Second, the cell motions through space and time are simulated using cosine functions, with their frequencies following a normal distribution. Third, a static optimization approach is used to divide the batch time and spaces into small intervals, in which we assume a homogenous and pseudo-steady state condition so that FBA models can be applied to resolve intracellular flux distributions in cells. Fourth, FBA can be integrated with the kinetic models by linking the biomass growth, N/P usage, and CO₂ gas-liquid transport.

Our integrated model can predict performance of flat-plate or column photobioreactors under different irradiation strategies and nutrient conditions, and thus reveal the influence of bioreactor scale-up on algal growth and product synthesis. Besides, our model also captures actual metabolic fluxes in the large photo-bioreactor environments: 1) metabolic fluxes in individual cells are highly oscillated; 2) overall fluxes in the central metabolism decreases during cultivation due to light attenuation; 3) the oxidative pentose pathway is active for NADPH production when cyanobacteria move to a dark zone; 4) biosynthesis (production rate and titer) can be significantly improved only if additional organic carbon source is available in the culture medium. Thereby, photo-mixotrophic biorefinery is a promising industrial strategy to achieve both high productivity biosynthesis and CO₂ mitigations.