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Updated: Jun 3, 2025

In vivo Application of the REMOTE-control System for the Manipulation of Endogenous Gene Expression
Published on: March 29, 2019
Population-level amplification of gene regulation by programmable gene transfer
Hye-In Son1, Grayson S Hamrick1, Ashwini R Shende1
1Department of Biomedical Engineering, Duke University, Durham, NC, USA.
Researchers engineered bacteria for dynamic gene regulation using plasmid transfer. This approach amplifies single-cell signals across populations, expanding gene expression control in microbial communities.
Area of Science:
- Synthetic Biology
- Microbial Engineering
- Genetic Circuit Design
Background:
- Single-cell gene regulation often limits dynamic range and control.
- Population-level mechanisms, like immune responses, offer robust control strategies.
- Existing synthetic biology tools struggle with scalable, dynamic population-wide gene regulation.
Purpose of the Study:
- To develop a programmable system for dynamic, population-level gene regulation in bacteria.
- To leverage plasmid-mediated gene transfer for amplifying single-cell regulatory signals.
- To expand the dynamic range and orthogonality of gene expression in engineered microbial communities.
Main Methods:
- Utilized Cas9 endonuclease, F conjugation machinery, and antibiotic selection to control plasmid dynamics.
- Regulated plasmid loss rate, transfer rate, and fitness effects to modulate plasmid-carrying cell fraction.
- Implemented a plasmid-mediated gene transfer system for programmable population control.
Main Results:
- Demonstrated dynamic control and amplification of gene regulation in bacterial populations.
- Successfully modulated the fraction of plasmid-carrying cells, acting as an amplification factor.
- Achieved expanded dynamic range and orthogonal control of gene expression across cell populations.
Conclusions:
- The developed platform enables dynamic regulation of gene expression in engineered microbial communities.
- Plasmid-mediated gene transfer provides a versatile strategy for population-level synthetic biology applications.
- This approach enhances the scalability and robustness of engineered biological systems.
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