Genomic Science Program
U.S. Department of Energy | Office of Science | Biological and Environmental Research Program

A Systems Approach for Predicting Metabolic Fluxes in Auxenochlorella protothecoides

Authors:

Nanette R. Boyle1* (nboyle@mines.edu), Jacob Tamburro1, Mark Vigliotti1, Jeffrey L. Moseley2, Sabeeha S. Merchant2

Institutions:

1Colorado School of Mines; 2University of California–Berkeley

Goals

Auxenochlorella protothecoides, a Trebouxiophyte oleaginous alga, is a reference for discovery and a platform for photosynthesis-driven synthetic biology and sustainable bioproduction. The project will expand transformation markers, regulatory sequences, and reporter genes; improve transformation efficiency; and develop ribonucleoprotein-mediated gene-editing methods for genome modification. Systems analyses and metabolic modeling approaches will inform genome modifications for rational improvement of photosynthetic carbon fixation and strain engineering to produce cyclopropane fatty acids. Regulatory factors and signaling pathways responsible for activating fatty acid and triacylglycerol biosynthesis will be identified, and the team will manipulate them to increase lipid productivity. Nonphotochemical quenching and a regulatory circuit for maintaining photosynthesis under copper limitation, both of which are absent in A. protothecoides, will be introduced to improve photosynthetic resilience, and the performance of engineered strains will be modeled.

Abstract

One approach to inform the design of production strains is the use of metabolic models to identify novel gene targets and reduce the potential solution space to maximize productivity. Using a high-quality genome sequence and highly accurate annotations, researchers have generated a complete metabolic network of A. protothecoides. To have representative biomass formation equations for a variety of growth conditions, the team has measured the macromolecule content and composition of A. protothecoides in autotrophic, mixotrophic, and heterotrophic growth regimes. This data, coupled with experimentally determined uptake and excretion rates, was used to constrain the model. Researchers simulated growth in the different growth regimes and performed a gene knockout analysis to determine gene essentiality and the impact of knockouts on fatty acid production. The complete genome scale model and the simulation results will be presented.

Funding Information

This work was supported by the DOE Office of Science, BER program, grant no. DE-SC0023027.