A universal biomolecular integral feedback controller for robust perfect adaptation

Stephanie K. Aoki, Gabriele Lillacci, Ankit Gupta, Armin Baumschlager, David Schweingruber and Mustafa Khammash ()
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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

Nature, 2019, vol. 570, issue 7762, 533-537

Abstract: 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.

Date: 2019
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DOI: 10.1038/s41586-019-1321-1

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