(640c) Computations-Driven Optimization of Alkane Production in Synechocystis Sp. PCC 6803

The prospect of using cyanobacteria as photo-catalysts in the production of hydrocarbons through atmospheric CO₂ sequestration is enticing and has led to considerable successes within the past decade. Unicellular cyanobacterium Synechocystis sp. PCC 6803 has shown tremendous metabolic capabilities and potential for use as biological chassis for biofuel production. Its natural transformation properties provide an opportunity to develop genetic tools and metabolic principles that can be applicable to other cyanobacteria for a number of production goals. To this aim we have chosen higher alkanes (i.e., pentadecane and heptadecane) as important biofuel candidate molecules, which are the main constituents of diesel and jet fuel. Major precursors for these alkanes are used along Calvin-Benson cycle and other central metabolic pathways for the production of biomass precursors, which further complicates the engineering of this microbial host for higher yields. Here, we demonstrate an integrated metabolic engineering effort by combining computationally driven predictions and metabolic flux analysis techniques to address this challenge. The OptForce procedure was used for suggesting and prioritizing genetic interventions to overproduce alkanes in Synechocystis sp. PCC 6803. We find upregulation of FABG and upregulation of FABG combined with upregulation of PGM could result 60% and 65% of the theoretical maximum yield for alkanes, respectively. In accordance with the OptForce interventions, we are now experimentally testing these strain designs. Therefore this work would highlight the benefit of using computational strain design and flux analysis tools in the design of recombinant strains of Synechocystis sp. PCC 6803 to produce enhanced level of alkanes.