Genome-Scale Metabolic Model Accurately Predicts Fermentation of Glucose by Chromochloris zofingiensis

Algae have the potential to be sources of renewable fuels and chemicals. One particular strain, Chromochloris zofingiensis, is of interest due to the co-production of triacylglycerols (TAGs) and astaxanthin, a valuable nutraceutical. To aid in future engineering efforts, we have developed the first genome-scale metabolic model on C. zofingiensis, iChr1925. This model includes 1925 genes, 3481 metabolic reactions and 2778 metabolites. The model was used to predict flux distributions for three different growth conditions: autotrophic, mixotrophic and heterotrophic growth. The model predicted production of fermentation products for growth on glucose due to overflow metabolism and we confirmed this via metabolomics analysis of the spent medium. The metabolic network robustness of Chromochloris zofingiensis was also evaluated by conducting an in silico gene essentiality analysis. This work lays a foundation for future endeavors in the metabolic engineering of this unique organism.