Combinatorial metabolic engineering platform enabling stable overproduction of lycopene from carbon dioxide by cyanobacteria

Abstract

Cyanobacteria are simple, efficient, genetically-tractable photosynthetic microorganisms representing ideal biocatalysts for CO2 capture and conversion, in principle. In practice, genetic instability and low productivity are key, linked problems in engineered cyanobacteria. We took a massively parallel approach, generating and characterising libraries of synthetic promoters and RBSs for the cyanobacterium Synechocystis, and assembling a sparse combinatorial library of millions of metabolic pathway-encoding construct variants. Laboratory evolution suppressed variants causing metabolic burden in Synechocystis, leading to expected genetic instability. Surprisingly however, in a single combinatorial round without iterative optimisation, 80% of variants chosen at random overproduced the valuable terpenoid lycopene from atmospheric CO2 over many generations, apparently overcoming the trade-off between stability and productivity. This first large-scale parallel metabolic engineering of cyanobacteria provides a new platform for development of genetically stable cyanobacterial biocatalysts for sustainable light-driven production of valuable products directly from CO2, avoiding fossil carbon or competition with food production.