Exploiting the Nonlinear Structure of the Antithetic Integral Controller to Enhance Dynamic Performance

Filo, Maurice; Kumar, Sant; Anastassov, Stanislav; Khammash, Mustafa

doi:10.1109/cdc51059.2022.9993268

Cited by 8 publications

(13 citation statements)

References 19 publications

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“…While much of the literature on AIF control has fo-cused on reference-actuated systems, different actuation inputs are possible [8, 9, 23, 54, 55]. In particular, the antithetic integral ‘rein controller’ proposed in [9] consid-ers AIF control where both the reference species Z 1 and sensor species Z 2 affect the controlled species X .…”

Section: Resultsmentioning

confidence: 99%

Noise properties of adaptation-conferring biochemical control modules

Kell

Ripsman

Hilfinger

2023

Preprint

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A key goal of synthetic biology is to establish functional biochemical modules with network-independent properties. Antithetic integral feedback (AIF) is a recently developed control module in which two control species perfectly annihilate each other's biological activity. The AIF module confers robust perfect adaptation to the steady-state average level of a controlled cellular component when subjected to sustained perturbations. Recent work has suggested that such robustness comes at the unavoidable price of increased stochastic fluctuations around average levels. We present theoretical results that support and quantify this trade-off for the commonly analyzed AIF variant in the idealized limit with perfect annihilation. However, we also show that this trade-off is a singular limit of the control module. Even minute deviations from perfect adaptation allow systems to achieve effective noise suppression as long as cells can pay the corresponding energetic cost of the control module. We further show that an alternative configuration of the control module can achieve significant noise suppression even in the idealized limit with perfect adaptation, suggesting certain AIF configurations may exhibit preferable noise properties for synthetic biology applications.

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Section: Resultsmentioning

confidence: 99%

Noise properties of adaptation-conferring biochemical control modules

Kell

Ripsman

Hilfinger

2023

Preprint

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“…In the following section, we conduct this analysis for the sAIF topology. The analysis for the rAIF topology can be found in Appendix A.2, while that for the rAIF + P topology is available in [24,25].…”

Section: Biomolecular Proportional-integral Controllersmentioning

confidence: 99%

“…Since the introduction of the AIF controller, efforts have been directed towards enhancing its performance either by tuning and exploring the dynamic trade-offs [21][22][23], or by adding extra circuitry [24][25][26][27][28][29][30] including molecular buffering, which was inspired by [31], and realizations of Proportional-Integral (PI) and Proportional-Integral-Derivative (PID) controllers. The need for such advanced biomolecular controllers arises from the limitations of standalone integral controllers.…”

Section: Introductionmentioning

confidence: 99%

“…The need for such advanced biomolecular controllers arises from the limitations of standalone integral controllers. For example, previous works have highlighted that the standalone AIF controller can only shape the dynamic response up to a certain extent [24,25]. Moreover, it was found that the standalone AIF controller achieves RPA at the population level, but it comes at the expense of increased stochastic noise in the form of elevated cell-to-cell variability [26].…”

Section: Introductionmentioning

confidence: 99%

“…However, these limitations can be mitigated by appending proportional and derivative components to the controller. In fact, studies have shown that adding a proportional feedback component to the AIF controller can improve dynamic performance and reduce the noise introduced by the integrator [24][25][26].…”

Section: Introductionmentioning

confidence: 99%

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A Hidden Proportional Feedback Mechanism Underlies Enhanced Dynamic Performance and Noise Rejection in Sensor-Based Antithetic Integral Control

Filo

Hou

Khammash

2023

Preprint

Self Cite

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Efficient regulation of cellular processes is essential for both endogenous and synthetic biological processes. The design of biomolecular feedback controllers that achieve robust and timely regulation is the subject of considerable research at the interface between synthetic biology and control theory. Integral feedback controllers, known for their ability to confer the property of Robust Perfect Adaptation (RPA), are increasingly becoming common features in biological control design. Antithetic integral feedback (AIF) controllers, in particular, have enabled effective chemical reaction realizations of integral controllers that deliver RPA in both deterministic and stochastic settings. This paved the way to experimental implementations of integral controllers in bacterial and mammalian cells. While AIF controllers deliver favorable adaptation properties, they do not necessarily lead to good transient performance or noise reduction properties and may in some cases lead to increased overshoot or cell-to-cell variability. These limitations are commonly circumvented by augmenting new circuitry that realize proportional or derivative feedback mechanisms to enhance dynamic and noise rejection features without affecting the AIF controller's adaptation properties. In this paper, we report that a sensor-based variant of the basic AIF motif exhibits favorable transient dynamic properties and (as reported elsewhere) reduced noise variance. We show that these features are attributed to a "hidden" proportional feedback component that is inherent in the controller structure and that such mechanism is solely responsible for the controller's underlying enhanced dynamic performance and noise rejection properties. This sensor-based AIF controller hence offers a minimal biomolecular realization of Proportional-Integral (PI) control, whereby both integral and proportional feedback mechanisms are achieved through a single actuation reaction.

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A cybergenetic framework for engineering intein-mediated integral feedback control systems

et al. 2023

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The ability of biological systems to tightly regulate targeted variables, despite external and internal disturbances, is known as Robust Perfect Adaptation (RPA). Achieved frequently through biomolecular integral feedback controllers at the cellular level, RPA has important implications for biotechnology and its various applications. In this study, we identify inteins as a versatile class of genetic components suitable for implementing these controllers and present a systematic approach for their design. We develop a theoretical foundation for screening intein-based RPA-achieving controllers and a simplified approach for modeling them. We then genetically engineer and test intein-based controllers using commonly used transcription factors in mammalian cells and demonstrate their exceptional adaptation properties over a wide dynamic range. The small size, flexibility, and applicability of inteins across life forms allow us to create a diversity of genetic RPA-achieving integral feedback control systems that can be used in various applications, including metabolic engineering and cell-based therapy.

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Exploiting the Nonlinear Structure of the Antithetic Integral Controller to Enhance Dynamic Performance

Cited by 8 publications

References 19 publications

Noise properties of adaptation-conferring biochemical control modules

Noise properties of adaptation-conferring biochemical control modules

A Hidden Proportional Feedback Mechanism Underlies Enhanced Dynamic Performance and Noise Rejection in Sensor-Based Antithetic Integral Control

A cybergenetic framework for engineering intein-mediated integral feedback control systems

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