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A universal biomolecular integral feedback controller for robust perfect adaptation

Author

Listed:
  • Stephanie K. Aoki

    (Department of Biosystems Science and Engineering)

  • Gabriele Lillacci

    (Department of Biosystems Science and Engineering)

  • Ankit Gupta

    (Department of Biosystems Science and Engineering)

  • Armin Baumschlager

    (Department of Biosystems Science and Engineering)

  • David Schweingruber

    (Department of Biosystems Science and Engineering)

  • Mustafa Khammash

    (Department of Biosystems Science and Engineering)

Abstract

Homeostasis is a recurring theme in biology that ensures that regulated variables robustly—and in some systems, completely—adapt to environmental perturbations. This robust perfect adaptation feature is achieved in natural circuits by using integral control, a negative feedback strategy that performs mathematical integration to achieve structurally robust regulation1,2. Despite its benefits, the synthetic realization of integral feedback in living cells has remained elusive owing to the complexity of the required biological computations. Here we prove mathematically that there is a single fundamental biomolecular controller topology3 that realizes integral feedback and achieves robust perfect adaptation in arbitrary intracellular networks with noisy dynamics. This adaptation property is guaranteed both for the population-average and for the time-average of single cells. On the basis of this concept, we genetically engineer a synthetic integral feedback controller in living cells4 and demonstrate its tunability and adaptation properties. A growth-rate control application in Escherichia coli shows the intrinsic capacity of our integral controller to deliver robustness and highlights its potential use as a versatile controller for regulation of biological variables in uncertain networks. Our results provide conceptual and practical tools in the area of cybergenetics3,5, for engineering synthetic controllers that steer the dynamics of living systems3–9.

Suggested Citation

  • 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.
  • Handle: RePEc:nat:nature:v:570:y:2019:i:7762:d:10.1038_s41586-019-1321-1
    DOI: 10.1038/s41586-019-1321-1
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    Citations

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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. Shivang Hina-Nilesh Joshi & Chentao Yong & Andras Gyorgy, 2022. "Inducible plasmid copy number control for synthetic biology in commonly used E. coli strains," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    3. 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.
    4. Robyn P. Araujo & Lance A. Liotta, 2023. "Universal structures for adaptation in biochemical reaction networks," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    5. Lauren Gambill & August Staubus & Kim Wai Mo & Andrea Ameruoso & James Chappell, 2023. "A split ribozyme that links detection of a native RNA to orthogonal protein outputs," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    6. Kirill Sechkar & Harrison Steel & Giansimone Perrino & Guy-Bart Stan, 2024. "A coarse-grained bacterial cell model for resource-aware analysis and design of synthetic gene circuits," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    7. 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.
    8. Ankit Gupta & Mustafa Khammash, 2022. "Frequency spectra and the color of cellular noise," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    9. Zhou Fang & Ankit Gupta & Sant Kumar & Mustafa Khammash, 2024. "Advanced methods for gene network identification and noise decomposition from single-cell data," Nature Communications, Nature, vol. 15(1), pages 1-19, December.
    10. Luna Rizik & Loai Danial & Mouna Habib & Ron Weiss & Ramez Daniel, 2022. "Synthetic neuromorphic computing in living cells," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    11. Chelsea Y. Hu & Richard M. Murray, 2022. "Layered feedback control overcomes performance trade-off in synthetic biomolecular networks," Nature Communications, Nature, vol. 13(1), pages 1-13, December.

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