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Related Experiment Video

Updated: Nov 18, 2025

Reliably Engineering and Controlling Stable Optogenetic Gene Circuits in Mammalian Cells
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Real-Time Optogenetics System for Controlling Gene Expression Using a Model-Based Design.

Guy Soffer1,2, James M Perry2,3, Steve C C Shih1,2,3

  • 1Department of Electrical and Computer Engineering, Concordia University, 1455 de Maisonneuve Blvd West, Montréal, Québec H3G1M8, Canada.

Analytical Chemistry
|February 5, 2021
PubMed
Summary
This summary is machine-generated.

Researchers developed a real-time optogenetics platform for precise gene expression control in E. coli. This model-based system enables closed-loop regulation, offering a digital alternative to chemical methods for biological engineering.

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Area of Science:

  • Synthetic Biology
  • Genetic Engineering
  • Biotechnology

Background:

  • Precise control of gene expression is crucial for optimizing engineered biological systems.
  • Optogenetics offers dynamic control over gene expression, interfacing digital software with microbial cultures.
  • Conventional chemical methods for gene expression control can be less convenient and precise.

Purpose of the Study:

  • To construct a real-time optogenetics platform for closed-loop control of the CcaR-CcaS system in Escherichia coli.
  • To implement a model-based design approach for achieving dynamic gene expression regulation.
  • To demonstrate a digital, optogenetic alternative to chemical induction methods.

Main Methods:

  • Developed a nonlinear model of the CcaR-CcaS two-plasmid system.
  • Tuned the model using open-loop experimentation to match experimental behavior.
  • Applied the model in silico to guide the construction of a closed-loop optogenetic control system.
  • Utilized image processing to monitor optical density and fluorescence during closed-loop control.

Main Results:

  • Successfully constructed and implemented a real-time optogenetic platform for closed-loop control.
  • Demonstrated a model-based design strategy for engineering biological systems.
  • Achieved periodic induction and repression of the CcaR-CcaS system in E. coli.
  • Validated the platform's ability to record key biological metrics like optical density and fluorescence.

Conclusions:

  • The developed optogenetics platform provides facile, real-time, closed-loop control over gene expression.
  • The model-based design approach is effective for tuning and implementing optogenetic control systems.
  • This methodology can be extended to model and control other biological systems requiring dynamic gene expression regulation.