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Engineering sensor-based antithetic integral controllers for enhanced dynamic performance and noise attenuation.

Maurice Filo1, Stephanie K Aoki1, Mucun Hou1

  • 1Department of Biosystems Science and Engineering, ETH Zürich, 4056 Basel, Switzerland.

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Summary
This summary is machine-generated.

We engineered a novel sensor-based antithetic integral feedback (sAIF) controller for robust cellular regulation. This synthetic biology tool enhances speed and reduces variability in biological systems.

Keywords:
chemical reaction networkscybergeneticsgenetic circuitshomeostasisintegral feedback controlinteinsnoiserobust perfect adaptation

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Area of Science:

  • Synthetic biology
  • Systems biology
  • Biochemical engineering

Background:

  • Cellular regulation is crucial for maintaining homeostasis against environmental changes.
  • Classical antithetic integral feedback controllers offer stability but can amplify noise.
  • Need for improved biological controllers with faster dynamics and reduced variability.

Purpose of the Study:

  • To develop and analyze a novel sensor-based antithetic integral feedback (sAIF) controller.
  • To embed proportional and integral actions into a minimal genetic architecture.
  • To enhance cellular regulation by improving speed and reducing noise.

Main Methods:

  • Development and analysis of the sAIF controller using control-theoretic and stochastic methods.
  • Minimal genetic architecture modification of the classical antithetic control motif.
  • Implementation of sAIF in E. coli using intein-mediated splicing.

Main Results:

  • The sAIF controller intrinsically incorporates proportional feedback, speeding up dynamic response.
  • Proportional action counteracts noise amplification, leading to reduced cellular variability.
  • Demonstrated robust perfect adaptation, strong disturbance rejection, and favorable noise properties in E. coli.

Conclusions:

  • The sAIF controller represents a generalizable design principle for high-performance biological controllers.
  • Findings have broad implications for synthetic biology, metabolic engineering, and cell-based therapies.
  • Established a new standard for engineering efficient and robust biological feedback systems.