(254b) Analysis of a Genome-Scale Metabolic Model of Chromochloris Zofingiensis

Metabolic modelling serves as a tool to distil meaningful information from genomic data sets and generate informed strategies for engineering an organism of interest. The metabolic modelling of algae has received significantly less attention than the modelling of heterotrophic bacteria and yeast. However, autotrophic algae have tremendous potential to use as cell factories in the production of valuable chemicals from sunlight and carbon dioxide. An automated tool for the rapid annotation of photosynthetic systems (RAPS) has been developed [Metcalf et.al. 2020 manuscript in preparation] and used to create a genome scale metabolic model of Chromochloris zofingiensis, an emerging model organism that is of interest for its lipid and astaxanthin producing capabilities. Astaxanthin is a naturally occurring pigment with powerful antioxidant properties that can be sold as a high value nutraceutical compound for an estimated $7000/kg.

Our model was used to conduct a flux balance analysis for autotrophic and two different mixotrophic growth conditions, each eliciting a varied metabolic response. Detailed experimental data on biomass composition was used to generate a different biomass objective function for each set of growth conditions. Results from this work illustrate the significant differences in biomass composition that arise in this alga when grown on varying carbon sources. These differences in biomass composition result in correspondingly different flux distributions predicted in the metabolic reaction network. These results highlight the importance of measuring biomass composition experimentally when conducting computational studies of cellular metabolism.