Restoring circadian gene profiles in clock networks using synthetic feedback control

Mathias Foo, Ozgur E. Akman, Declan G. Bates

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Abstract

The circadian system—an organism’s built-in biological clock—is responsible for orchestrating biological processes to adapt to diurnal and seasonal variations. Perturbations to the circadian system (e.g., pathogen attack, sudden environmental change) often result in pathophysiological responses (e.g., jetlag in humans, stunted growth in plants, etc.) In view of this, synthetic biologists are progressively adapting the idea of employing synthetic feedback control circuits to alleviate the effects of perturbations on circadian systems. To facilitate the design of such controllers, suitable models are required. Here, we extend our recently developed model for the plant circadian clock—termed the extended S-System model—to model circadian systems across different kingdoms of life. We then use this modeling strategy to develop a design framework, based on an antithetic integral feedback (AIF) controller, to restore a gene’s circadian profile when it is subject to loss-of-function due to external perturbations. The use of the AIF controller is motivated by its recent successful experimental implementation. Our findings provide circadian biologists with a systematic and general modeling and design approach for implementing synthetic feedback control of circadian systems.

Original languageEnglish
Article number7
Number of pages11
Journalnpj Systems Biology and Applications
Volume8
Issue number1
DOIs
Publication statusPublished - 15 Feb 2022

Bibliographical note

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

Funder

M.F. gratefully acknowledges the financial support of The Royal Society via research grant RGS/R2/180195. D.G.B. gratefully acknowledges the financial support of the EPSRC and BBSRC via research grants BB/M017982/1 to WISB and from the School of Engineering of the University of Warwick. O.E.A. wishes to acknowledge the financial support of the EPSRC (research grant EP/N017846/1). The authors would also like to thank Dr. Hafiz Ahmed from Nuclear Futures Institute, Bangor University for useful discussions on dynamical modeling.

Keywords

  • control theory
  • Synthetic biology

ASJC Scopus subject areas

  • Modelling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Drug Discovery
  • Computer Science Applications
  • Applied Mathematics

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