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Restoring circadian gene profiles in clock networks using synthetic feedback control
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Foo, Mathias, Akman, Ozgur E. and Bates, Declan G. (2022) Restoring circadian gene profiles in clock networks using synthetic feedback control. npj Systems Biology and Applications, 8 . 7. doi:10.1038/s41540-022-00216-x ISSN 2056-7189.
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Official URL: https://doi.org/10.1038/s41540-022-00216-x
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.
Item Type: | Journal Article | ||||||||||||
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Subjects: | Q Science > QH Natural history T Technology > TA Engineering (General). Civil engineering (General) T Technology > TJ Mechanical engineering and machinery |
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||||||||
Library of Congress Subject Headings (LCSH): | Circadian rhythms, Automatic control , Systems biology, Synthetic biology | ||||||||||||
Journal or Publication Title: | npj Systems Biology and Applications | ||||||||||||
Publisher: | Nature Partner Journals | ||||||||||||
ISSN: | 2056-7189 | ||||||||||||
Official Date: | 15 February 2022 | ||||||||||||
Dates: |
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Volume: | 8 | ||||||||||||
Article Number: | 7 | ||||||||||||
DOI: | 10.1038/s41540-022-00216-x | ||||||||||||
Status: | Peer Reviewed | ||||||||||||
Publication Status: | Published | ||||||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||||||
Date of first compliant deposit: | 15 February 2022 | ||||||||||||
Date of first compliant Open Access: | 18 February 2022 | ||||||||||||
RIOXX Funder/Project Grant: |
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