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Abstract
Engineering metabolism to efficiently produce chemicals from multi-step pathways requires optimizing multi-gene expression programs to achieve enzyme balance. CRISPR-Cas transcriptional control systems are emerging as important tools for programming multi-gene expression, but poor predictability of guide RNA folding can disrupt expression control. Here, we correlate efficacy of modified guide RNAs (scRNAs) for CRISPR activation (CRISPRa) in E. coli with a computational kinetic parameter describing scRNA folding rate into the active structure (rS = 0.8). This parameter also enables forward design of scRNAs, allowing us to design a system of three synthetic CRISPRa promoters that can orthogonally activate (>35-fold) expression of chosen outputs. Through combinatorial activation tuning, we profile a three-dimensional design space expressing two different biosynthetic pathways, demonstrating variable production of pteridine and human milk oligosaccharide products. This RNA design approach aids combinatorial optimization of metabolic pathways and may accelerate routine design of effective multi-gene regulation programs in bacterial hosts.
Guide RNA folding affects functionality of CRISPR-Cas transcriptional control systems. Here, the authors report computational gRNA design together with creation of synthetic CRISPRa promoters for orthogonal expression control and demonstrate the application in pteridine and human milk oligosaccharide production in E. coli.
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1 University of Washington, Molecular Engineering & Sciences Institute and Center for Synthetic Biology, Seattle, USA (GRID:grid.34477.33) (ISNI:0000 0001 2298 6657); University of Washington, Department of Chemistry, Seattle, USA (GRID:grid.34477.33) (ISNI:0000 0001 2298 6657); University of Washington, Department of Chemical Engineering, Seattle, USA (GRID:grid.34477.33) (ISNI:0000 0001 2298 6657)
2 University of Washington, Molecular Engineering & Sciences Institute and Center for Synthetic Biology, Seattle, USA (GRID:grid.34477.33) (ISNI:0000 0001 2298 6657); University of Washington, Department of Chemical Engineering, Seattle, USA (GRID:grid.34477.33) (ISNI:0000 0001 2298 6657)
3 University of Washington, Molecular Engineering & Sciences Institute and Center for Synthetic Biology, Seattle, USA (GRID:grid.34477.33) (ISNI:0000 0001 2298 6657); University of Washington, Department of Bioengineering, Seattle, USA (GRID:grid.34477.33) (ISNI:0000 0001 2298 6657)
4 Lawrence Berkeley National Laboratory, Biological Systems and Engineering Division, Berkeley, USA (GRID:grid.184769.5) (ISNI:0000 0001 2231 4551); DOE Joint BioEnergy Institute, Biofuels and Bioproducts Division, Emeryville, USA (GRID:grid.451372.6) (ISNI:0000 0004 0407 8980); DOE Agile BioFoundry, Emeryville, USA (GRID:grid.451372.6)
5 University of Washington, Molecular Engineering & Sciences Institute and Center for Synthetic Biology, Seattle, USA (GRID:grid.34477.33) (ISNI:0000 0001 2298 6657); University of Washington, Department of Chemistry, Seattle, USA (GRID:grid.34477.33) (ISNI:0000 0001 2298 6657)