Guide RNA structure design enables combinatorial CRISPRa programs for biosynthetic profiling

Jason Fontana; David Sparkman-Yager; Ian Faulkner; Ryan Cardiff; Cholpisit Kiattisewee; Aria Walls; Tommy G Primo; Patrick C Kinnunen; Hector Garcia Martin; Jesse G Zalatan; James M Carothers

doi:10.1038/s41467-024-50528-1

Guide RNA structure design enables combinatorial CRISPRa programs for biosynthetic profiling

Nat Commun. 2024 Jul 27;15(1):6341. doi: 10.1038/s41467-024-50528-1.

Authors

Jason Fontana^#^{1

2

3}, David Sparkman-Yager^#^{1

3}, Ian Faulkner^#^{1

3}, Ryan Cardiff^{1

2

3}, Cholpisit Kiattisewee^{1

2

3}, Aria Walls^{1

3}, Tommy G Primo^{1

4}, Patrick C Kinnunen^{5

6

7}, Hector Garcia Martin^{5

6

7}, Jesse G Zalatan^{8

9}, James M Carothers^{10

11}

Affiliations

¹ Molecular Engineering & Sciences Institute and Center for Synthetic Biology, University of Washington, Seattle, WA, USA.
² Department of Chemistry, University of Washington, Seattle, WA, USA.
³ Department of Chemical Engineering, University of Washington, Seattle, WA, USA.
⁴ Department of Bioengineering, University of Washington, Seattle, WA, USA.
⁵ Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
⁶ Biofuels and Bioproducts Division, DOE Joint BioEnergy Institute, Emeryville, CA, USA.
⁷ DOE Agile BioFoundry, Emeryville, CA, USA.
⁸ Molecular Engineering & Sciences Institute and Center for Synthetic Biology, University of Washington, Seattle, WA, USA. zalatan@uw.edu.
⁹ Department of Chemistry, University of Washington, Seattle, WA, USA. zalatan@uw.edu.
¹⁰ Molecular Engineering & Sciences Institute and Center for Synthetic Biology, University of Washington, Seattle, WA, USA. jcaroth@uw.edu.
¹¹ Department of Chemical Engineering, University of Washington, Seattle, WA, USA. jcaroth@uw.edu.

^# Contributed equally.

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 (r_S = 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.

MeSH terms

Biosynthetic Pathways / genetics
CRISPR-Cas Systems*
Escherichia coli* / genetics
Escherichia coli* / metabolism
Gene Expression Regulation, Bacterial
Humans
Metabolic Engineering / methods
Promoter Regions, Genetic
RNA Folding
RNA, Guide, CRISPR-Cas Systems* / genetics
RNA, Guide, CRISPR-Cas Systems* / metabolism

Substances

RNA, Guide, CRISPR-Cas Systems

Abstract

MeSH terms

Substances

Grants and funding