Metabolic modelling and simulation of the light and dark metabolism of Chlamydomonas reinhardtii

Summary A metabolic network model of the green microalga Chlamydomonas reinhardtii was used to characterize photoautotrophic and heterotrophic (i.e. growth on stored compounds) growth under light and dark, respectively. The metabolic network comprised 2514 reactions distributed among nine intracellular compartments and the extracellular space. The metabolic network included all the key biochemical pathways for synthesis and metabolism of starch and triacylglycerols ( TAG s). Under light and nitrogen limitation, the model simulated the accumulation of the energy‐rich compounds ( TAG s and starch) in the cell. In the dark, the model could simulate cell growth and maintenance on stored compounds. The model‐predicted consumption rates of storage compounds (starch or TAG s) to enable growth in the dark, were found to be greater than the rates of synthesis under light. This implied utilization of the storage compounds for cell maintenance in the dark. Under constant illumination, the simulations of cell growth and intracellular starch content agreed closely with independent experimental data. In other simulations, compared with the case without photorespiration, light uptake rate increased 1.04‐fold when the ratio of the rates of oxygenation and carboxylation (Rubisco) was 0.1. Although extensive experimental work exists on culture and physiology of microalgae, it does not allow quantitative predictions of the influence of dark metabolism on the productivity of metabolites to be made. This limitation is overcome using the present model. A metabolic network model of Chlamydomonas reinhardtii is shown to simulate growth and synthesis of energy‐rich compounds (triacylglycerols and starch) under light. The same model also simulates dark growth and maintenance through consumption of the stored energy‐rich compounds.