Scalable model development of carbon photosynthetic assimilation and partitioning in a green microalga during nitrogen starvation

Lipid accumulation in green microalgae is induced by stresses (e.g. nitrogen starvation) which compromise photosynthetic activity resulting in significantly lower biomass productivity than under nutrient replete conditions. While algae photosynthetic growth has been well characterized and modelled under nutrient replete conditions, the loss of photosynthetic activity during nitrogen starvation lacks specific studies to determine suitable parameterisation. The loss of photosynthetic activity of the lipid-accumulating microalgae Chlorella vulgaris NIES 227 was studied under varying light intensities during nitrogen starvation. Partition of assimilated carbon between the different macromolecules pools (carbohydrates, lipids, and proteins) was concomitantly monitored. The results showed that the decrease of photosynthetic activity correlated well to the increase of cell C:N ratio (R²=0.883,N=65) enabling to develop a model of microalgae growth and carbon partition under nitrogen starvation. Biomass dry-weight increase could be predicted with good accuracy (R²=0.940,N=66), as total lipid and carbohydrate production could also be predicted with fair accuracy (R²=0.841 and 0.618, respectively). The present study henceforth showed that modelling microalgae productivity based on photosynthetic activity inferred from local light intensity, as done in scalable models under nutrient replete conditions, may be extended to nitrogen starvation conditions and enabled the prediction of lipids and carbohydrates productivity. The model proposed should thus prove useful in optimizing photobioreactors design for the production of important energetic molecules based on light distribution knowledge.