Unlocking the potential of cyanobacteria: a high-throughput strategy for enhancing biocatalytic performance through genetic optimization

Cyanobacteria show promise as hosts for whole-cell biocatalysis. Their photoautotrophic metabolism can be leveraged for a sustainable production process. Despite advancements, performance still lags behind heterotrophic hosts. A key challenge is the limited ability to overexpress recombinant enzymes, which also hinders their biocatalytic efficiency. To address this, we generated large-scale expression libraries and developed a high-throughput method combining fluorescence-activated cell sorting (FACS) and deep sequencing in Synechocystis sp. PCC 6803 (Syn. 6803) to screen and optimize its genetic background. We apply this approach to enhance expression and biocatalyst performance for three enzymes: the ketoreductase LfSDR1M50, enoate reductase YqjM, and Baeyer-Villiger monooxygenase (BVMO) CHMO