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A hierarchy of biomolecular proportional-integral-derivative feedback controllers for robust perfect adaptation and dynamic performance

Author

Listed:
  • Maurice Filo

    (ETH Zürich)

  • Sant Kumar

    (ETH Zürich)

  • Mustafa Khammash

    (ETH Zürich)

Abstract

Proportional-Integral-Derivative (PID) feedback controllers are the most widely used controllers in industry. Recently, the design of molecular PID-controllers has been identified as an important goal for synthetic biology and the field of cybergenetics. In this paper, we consider the realization of PID-controllers via biomolecular reactions. We propose an array of topologies offering a compromise between simplicity and high performance. We first demonstrate that different biomolecular PI-controllers exhibit different performance-enhancing capabilities. Next, we introduce several derivative controllers based on incoherent feedforward loops acting in a feedback configuration. Alternatively, we show that differentiators can be realized by placing molecular integrators in a negative feedback loop, which can be augmented by PI-components to yield PID-controllers. We demonstrate that PID-controllers can enhance stability and dynamic performance, and can also reduce stochastic noise. Finally, we provide an experimental demonstration using a hybrid setup where in silico PID-controllers regulate a genetic circuit in single yeast cells.

Suggested Citation

  • Maurice Filo & Sant Kumar & Mustafa Khammash, 2022. "A hierarchy of biomolecular proportional-integral-derivative feedback controllers for robust perfect adaptation and dynamic performance," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-29640-7
    DOI: 10.1038/s41467-022-29640-7
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    References listed on IDEAS

    as
    1. Sant Kumar & Marc Rullan & Mustafa Khammash, 2021. "Rapid prototyping and design of cybergenetic single-cell controllers," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    2. Saurabh Modi & Supravat Dey & Abhyudai Singh, 2021. "Noise suppression in stochastic genetic circuits using PID controllers," PLOS Computational Biology, Public Library of Science, vol. 17(7), pages 1-25, July.
    3. Andrew H. Ng & Taylor H. Nguyen & Mariana Gómez-Schiavon & Galen Dods & Robert A. Langan & Scott E. Boyken & Jennifer A. Samson & Lucas M. Waldburger & John E. Dueber & David Baker & Hana El-Samad, 2019. "Modular and tunable biological feedback control using a de novo protein switch," Nature, Nature, vol. 572(7768), pages 265-269, August.
    4. Andreas Milias-Argeitis & Marc Rullan & Stephanie K. Aoki & Peter Buchmann & Mustafa Khammash, 2016. "Automated optogenetic feedback control for precise and robust regulation of gene expression and cell growth," Nature Communications, Nature, vol. 7(1), pages 1-11, November.
    5. Hsin-Ho Huang & Yili Qian & Domitilla Del Vecchio, 2018. "A quasi-integral controller for adaptation of genetic modules to variable ribosome demand," Nature Communications, Nature, vol. 9(1), pages 1-12, December.
    6. Andreas K. Brödel & Alfonso Jaramillo & Mark Isalan, 2016. "Engineering orthogonal dual transcription factors for multi-input synthetic promoters," Nature Communications, Nature, vol. 7(1), pages 1-9, December.
    7. Deepak K. Agrawal & Ryan Marshall & Vincent Noireaux & Eduardo D Sontag, 2019. "In vitro implementation of robust gene regulation in a synthetic biomolecular integral controller," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
    8. Stephanie K. Aoki & Gabriele Lillacci & Ankit Gupta & Armin Baumschlager & David Schweingruber & Mustafa Khammash, 2019. "A universal biomolecular integral feedback controller for robust perfect adaptation," Nature, Nature, vol. 570(7762), pages 533-537, June.
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    Cited by:

    1. Andras Gyorgy, 2023. "Competition and evolutionary selection among core regulatory motifs in gene expression control," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    2. Stanislav Anastassov & Maurice Filo & Ching-Hsiang Chang & Mustafa Khammash, 2023. "A cybergenetic framework for engineering intein-mediated integral feedback control systems," Nature Communications, Nature, vol. 14(1), pages 1-16, December.

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