Computational metabolic engineering strategies for growth-coupled biofuel production by Synechocystis

Metabolic Engineering Communications
Kiyan Shabestary, Elton P Hudson

Abstract

Chemical and fuel production by photosynthetic cyanobacteria is a promising technology but to date has not reached competitive rates and titers. Genome-scale metabolic modeling can reveal limitations in cyanobacteria metabolism and guide genetic engineering strategies to increase chemical production. Here, we used constraint-based modeling and optimization algorithms on a genome-scale model of Synechocystis PCC6803 to find ways to improve productivity of fermentative, fatty-acid, and terpene-derived fuels. OptGene and MOMA were used to find heuristics for knockout strategies that could increase biofuel productivity. OptKnock was used to find a set of knockouts that led to coupling between biofuel and growth. Our results show that high productivity of fermentation or reversed beta-oxidation derived alcohols such as 1-butanol requires elimination of NADH sinks, while terpenes and fatty-acid based fuels require creating imbalances in intracellular ATP and NADPH production and consumption. The FBA-predicted productivities of these fuels are at least 10-fold higher than those reported so far in the literature. We also discuss the physiological and practical feasibility of implementing these knockouts. This work gives insight into ho...Continue Reading

Citations

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Methods Mentioned

BETA
gene knockouts
RNA-Seq
gene knockout

Software Mentioned

OptFlux
FBA
OptKnock
OptForce
CASOP
OptForce Algebraic Modeling System GAMS
ButFER
COBRA
MATLAB
Tomlab

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