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Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
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Updated: Feb 18, 2026

Reliably Engineering and Controlling Stable Optogenetic Gene Circuits in Mammalian Cells
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Balancing a genetic toggle switch by real-time feedback control and periodic forcing.

Jean-Baptiste Lugagne1,2, Sebastián Sosa Carrillo2,3, Melanie Kirch1,2

  • 1Laboratoire Matière et Systèmes Complexes, UMR 7057 CNRS & Université Paris Diderot, 10 rue Alice Domon et Léonie Duquet, 75013, Paris, France.

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Researchers demonstrate real-time remote control of cellular processes using cybergenetics. A novel dual periodic forcing method maintains genetic toggle switches in an undecided state, enabling complex cell decision-making control.

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Area of Science:

  • Synthetic biology
  • Systems biology
  • Control theory

Background:

  • Cybergenetics aims for real-time remote control of cellular processes.
  • Current methods are limited to controlling few genetic circuits.
  • Multistable gene regulatory networks are crucial for cell differentiation and decision-making.

Purpose of the Study:

  • Investigate the control of multistable gene regulatory networks.
  • Demonstrate dynamic maintenance of a bistable genetic toggle switch near its unstable equilibrium.
  • Develop a method for simultaneously controlling multiple cells.

Main Methods:

  • Utilized an in silico feedback control loop.
  • Applied dual periodic forcing to a bistable genetic toggle switch model.
  • Simulated control of genetic networks at single-cell and population levels.

Main Results:

  • Successfully maintained a bistable genetic toggle switch near its unstable equilibrium for extended periods.
  • Showed that dual periodic forcing can simultaneously control many cells.
  • Validated the feasibility of cybernetic control for complex biological systems.

Conclusions:

  • Dual periodic forcing is a viable method for cybernetic control of gene regulatory networks.
  • This approach enables dynamic maintenance of cellular states for biotechnological applications.
  • Paves the way for controlling complex cell decision-making at multiple scales.