(430b) Large-Scale Kinetic Model of Chlamydomonas Reinhardtii Metabolism Reveals Diffuse Control Over Growth Precursors

Algae are used for the industrial-scale production of chemicals spanning food supplements, pharmaceuticals, and biofuels because they are robust, photosynthetic, and can be cultivated on a large scale. Similar to other industrially-used microorganisms, it is desirable to develop an in silico model of algae metabolism that can be used to predict the effects of environmental and genomic perturbations and stress, which could be used to rationally identify approaches for engineering more productive strains. Dynamic metabolic models are of particular interest because they can inherently describe time-based perturbations, metabolic cycles, and complex enzyme and gene interactions. Herein we detail the development and validation of the first reported large-scale kinetic model of the Chlamydomonas reinhardtii metabolism, comprising four organeller compartments, 369 chemical reactions, and incorporating known inhibition kinetics for highly regulated control points (e.g. Calvin, TCA). After generating an ensemble of thousands of possible models for this system, which spanned known thermodynamic and biological limits, and screening these models for nitrogen-deprivation phenotypes observed experimentally, a model was identified that reproduced known nutrient exchange trends and observed shifts in growth precursors, energy stores, and intracellular metabolite contents under nutrient stress. A control study was then executed to identify enzymes expressions that exerted great pressure over growth-related fluxes and CO2 uptake; this study revealed that control over growth is wielded by a very diffuse set of reactions, many of which lie outside of the metabolic pathways typically included metabolic studies of photosynthetic organisms. It also suggested several genetic engineering targets for improved biomass accumulation.