Metabolic Network design of Synechocystis sp. PCC 6803 to obtain bioethanol under autotrophic conditions

Abstract

In this work, we propose a genomic scale metabolic network model of the genetically engineered Synechocystis sp. PCC 6803 within a bilevel programming framework to study ethanol photosynthetic production. The model is studied under carbon limiting conditions with restricted photon flux. Maximum biomass and ethanol theoretical productions are obtained using flux balance analysis for the decoupled case. Furthermore, we formulate a bilevel programming problem, reformulated into a mixed integer linear problem (MILP), to study the possibility of coupling cell growth with ethanol production. Models are formulated within an equation-oriented framework in GAMS. Numerical results provide useful insights on ethanol production by this strain within the context of genomic-scale cyanobacterial metabolism.