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Engineering an Optogenetic CRISPRi Platform for Improved Chemical Production.
Peiling Wu1, Yufen Chen1, Mingyu Liu1
1State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network School of Life Sciences, Xiamen University, Xiamen, Fujian 361102, China.
ACS Synthetic Biology
|December 28, 2020
Summary
We developed an optogenetic-CRISPR interference (opto-CRISPRi) system to control microbial chemical production. This dynamic control enhanced muconic acid synthesis in bacteria by 130%.
Area of Science:
- Synthetic Biology
- Metabolic Engineering
- Microbial Biotechnology
Background:
- Microbial chemical synthesis requires redirecting metabolic flux toward desired products.
- Dynamic control strategies offer solutions to optimize metabolic pathways.
- Optogenetics provides spatial and temporal control over cellular processes.
Purpose of the Study:
- To develop and apply an optogenetic-CRISPR interference (opto-CRISPRi) system for dynamic metabolic control in bacteria.
- To enhance heterologous muconic acid synthesis by redirecting metabolic flux.
- To demonstrate the utility of light-inducible systems for microbial chemical production.
Main Methods:
- Utilized a blue light-sensitive protein (EL222) to regulate a dCpf1-mediated CRISPR interference system.
- Applied the opto-CRISPRi system to control gene expression in *Escherichia coli*.
- Dynamically suppressed central metabolism and competing pathways to favor muconic acid production.
Main Results:
- The opto-CRISPRi system successfully regulated metabolic flux in response to optical signals.
- Muconic acid production was increased by 130% through dynamic pathway suppression.
- Demonstrated effective redirection of metabolic resources toward target chemical synthesis.
Conclusions:
- The opto-CRISPRi platform offers an effective method for dynamic control of microbial chemical synthesis.
- This technology has broad applicability for enhancing the production of various chemicals in microbial systems.
- Optogenetic control provides a powerful tool for optimizing metabolic engineering strategies.

