Of the two natural metabolic pathways for making terpenoids, biotechnological utilization of the mevalonate (MVA) pathway has enabled commercial production of valuable compounds, while the more recently discovered but stoichiometrically more efficient methylerythritol phosphate (MEP) pathway is underdeveloped. We conducted a study on the overexpression of each enzyme in the MEP pathway in the unicellular cyanobacterium Synechocystis sp. PCC 6803, to identify potential targets for increasing flux towards terpenoid production, using isoprene as a reporter molecule. Results showed that the enzymes Ipi, Dxs and IspD had the biggest impact on isoprene production. By combining and creating operons out of those genes, isoprene production was increased 2-fold compared to the base strain. A genome-scale model was used to identify targets upstream of the MEP pathway that could redirect flux towards terpenoids. A total of ten reactions from the Calvin-Benson-Bassham cycle, lower glycolysis and co-factor synthesis pathways were probed for their effect on isoprene synthesis by co-expressing them with the MEP enzymes, resulting in a 60% increase in production from the best strain. Lastly, we studied two isoprene synthases with the highest reported catalytic rates. Only by expressing them together with Dxs and Ipi could we get stable strains that produced 2.8 mg/g isoprene per dry cell weight, a 40-fold improvement compared to the initial strain. 

Photoautotrophic production of fuels and chemicals by cyanobacteria typically gives lower volumetric productivities and titers than heterotrophic production. Cyanobacteria cultures become light limited above an optimal cell density, so that this substrate is not supplied to all cells sufficiently. Here, we investigate genetic strategies for a two-phase cultivation, where biofuel-producing Synechocystis cultures are limited to an optimal cell density through inducible CRISPR interference (CRISPRi) repression of cell growth. Fixed CO2 is diverted to ethanol or n-butanol. Among the most successful strategies was partial repression of citrate synthase gltA. Strong repression (>90%) of gitA at low culture densities increased carbon partitioning to n-butanol 5-fold relative to a nonrepression strain, but sacrificed volumetric productivity due to severe growth restriction. CO2 fixation continued for at least 3 days after growth was arrested. By targeting sgRNAs to different regions of the gitA gene, we could modulate GItA expression and carbon partitioning between growth and product to increase both specific and volumetric productivity. These growth arrest strategies can be useful for improving performance of other photoautotrophic processes.

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 how cyanobacteria could be engineered to reach competitive biofuel productivities.