Combinatorial assembly platform enabling engineering of genetically stable metabolic pathways in cyanobacteria

Abstract

Cyanobacteria are simple, efficient, genetically-tractable photosynthetic microorganisms which in principle represent ideal biocatalysts for CO ₂ capture and conversion. However, 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 sp. PCC 6803, and assembling a sparse combinatorial library of millions of metabolic pathway-encoding construct variants. Genetic instability was observed for some variants, which is expected when variants cause metabolic burden. Surprisingly however, in a single combinatorial round without iterative optimisation, 80% of variants chosen at random and cultured photoautotrophically over many generations accumulated the target terpenoid lycopene from atmospheric CO ₂, apparently overcoming genetic instability. This 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 CO ₂, avoiding fossil carbon or competition with food production.

Graphical Abstract

Graphical Abstract

Combinatorial assembly of libraries of metabolic pathway-encoding constructs from synthetic parts with suitable properties, followed by a small amount of screening, is a rapid, simple and effective strategy to obtain productive and genetically stable pathway designs for the cyanobacterium Synechocystis sp. PCC 6803.