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

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) CHMOmut. Diverse genetic combinations yielded significant improvements: optimizing LfSDR1M50 expression showed a 17-fold increase to 39.2 U g cell dry weight (CDW)-1. In vivo activity of Syn. YqjM was improved 16-fold to 58.7 U g CDW - 1 and, for Syn. CHMOmut, a 1.5-fold increase to 7.3 U g CDW - 1 was achieved by tailored genetic design. Thus, this strategy offers a pathway to optimize cyanobacteria as expression hosts, paving the way for broader applications in other cyanobacteria strains and larger libraries.