Biomolecular mechanisms for signal differentiation

Alexis, Emmanouil; Schulte, Carolin C. M.; Cardelli, Luca; Papachristodoulou, Antonis

doi:10.1101/2021.04.29.441952

Cited by 4 publications

(16 citation statements)

References 51 publications

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“…As shown in [19], for any non-negative constant input U ∗ , we obtain a positive locally exponentially stable steady state .…”

Section: Introductionsupporting

confidence: 62%

“…(6c) As shown in [19], for any non-negative constant input U * , we obtain a positive locally exponentially stable steady state (X * , Z * 1 , Z * 2 ). Through (Jacobian) linearization of system (6), we have for the local dynamics of BioSD-III:…”

Section: Two Important Biomolecular Motifsmentioning

confidence: 71%

“…As also shown in [19], the structural complexity of the differentiator module can be reduced by removing the reaction C D1 +C D3 k 1 C D1 +C D1 +C D3 in CRN (5) while the input/output behaviour remains the same. This results in ODE model (6) without the term +k 1 C D1 C D3 in Equation (6a).…”

Section: Two Important Biomolecular Motifsmentioning

confidence: 98%

“…The behaviour of the controller can be further improved by modifying appropriately the error quantity on which the proportional action acts. To this end, we consider an with the different types of biomolecular interactions adopted from our previous work [19]. (B) Antithetic integral controller regulating a target species which is part of an arbitrary biological process -"cloud" network (CRN (3)).…”

Section: A Key Points On Pid Controlmentioning

confidence: 99%

“…To see this, the CRN for BioSD-III consists of the reactions: where k in , b , k 2 , k 1 , η ∈ ℝ + . Note also that the rate of the degradation process with respect to C D 1 considered in [19] is assumed to be zero here.…”

Section: Introductionmentioning

confidence: 99%

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On the Design of a PID Bio-controller with Set Point Weighting and Filtered Derivative Action

Alexis

Cardelli²,

Papachristodoulou³

2022

Preprint

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Effective and robust regulation of biomolecular processes is crucial for designing reliable synthetic bio-devices functioning in uncertain and constantly changing biological environments. Proportional-Integral-Derivative (PID) controllers are undeniably the most common way of implementing feedback control in modern technological applications. Here, we introduce a highly tunable PID bio-controller with set point weighting and filtered derivative action presented as a chemical reaction network with mass action kinetics. To demonstrate its effectiveness, we apply our PID scheme on a simple biological process of two mutually activated species, one of which is assumed to be the output of interest. To highlight its performance advantages we compare it to PI regulation using numerical simulations in both the deterministic and stochastic setting.

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“…As shown in [19], for any non-negative constant input U ∗ , we obtain a positive locally exponentially stable steady state .…”

Section: Introductionsupporting

confidence: 62%

Section: Two Important Biomolecular Motifsmentioning

confidence: 71%

Section: Two Important Biomolecular Motifsmentioning

confidence: 98%

Section: A Key Points On Pid Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

On the Design of a PID Bio-controller with Set Point Weighting and Filtered Derivative Action

Alexis

Cardelli²,

Papachristodoulou³

2022

Preprint

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A Hierarchy of Biomolecular Proportional-Integral-Derivative Feedback Controllers for Robust Perfect Adaptation and Dynamic Performance

Filo

Khammash

2021

Preprint

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Proportional-Integral-Derivative (PID) feedback controllers have been the most widely used controllers in the industry for almost a century. This is mainly due to their simplicity and intuitive operation. Recently, motivated by their success in various engineering disciplines, PID controllers found their way into molecular biology. In this paper, we consider the mathematical realization of (nonlinear) PID controllers via biomolecular interactions in both the deterministic and stochastic settings. We propose several simple biomolecular PID control architectures that take into consideration the biological implementation aspect. We verify the underlying PID control structures by performing a linear perturbation analysis and examine their effects on the (deterministic and stochastic) performance and stability. In fact, we demonstrate that different proportional controllers exhibit different capabilities of enhancing the dynamics and reducing variance (cell-to-cell variability). Furthermore, we propose a simple derivative controller that is mathematically realized by cascading the antithetic integral controller with an incoherent feedforward loop without adding any additional species. We demonstrate that the derivative component is capable of enhancing the transient dynamics at the cost of boosting the variance, which agrees with the well known vulnerability of the derivative controller to noise. We also show that this can be mitigated by carefully designing the inhibition pathway of the incoherent feedforward loop. Throughout the paper, the stochastic analysis is carried out based on a tailored moment-closure technique and is also backed up by simulations.

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Regulation strategies for two-output biomolecular networks

Alexis

Schulte

Cardelli

et al. 2022

Preprint

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Feedback control theory allows the development of self-regulating systems with desired performance which are predictable and insensitive to disturbances. Feedback regulatory topologies are used by many natural systems and have been of key importance in the design of reliable synthetic bio-devices operating in complex biological environments. Here, we study control schemes for biomolecular processes with two outputs of interest, expanding previous traditional concepts describing one-output systems. This is a step forward in building bio-devices capable of sophisticated functions. Regulation of such processes may unlock new design possibilities but it can be challenging due to coupling interactions while potential disturbances applied on one of the outputs may affect both. We therefore propose architectures for robustly manipulating the ratio and linear combinations of the outputs as well as each of the output independently. To demonstrate their characteristics, we apply these architectures to a simple process of two mutually activated biomolecular species. We also highlight the potential for experimental implementation by exploring synthetic realizations both in vivo and in vitro.

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Biomolecular mechanisms for signal differentiation

Cited by 4 publications

References 51 publications

On the Design of a PID Bio-controller with Set Point Weighting and Filtered Derivative Action

On the Design of a PID Bio-controller with Set Point Weighting and Filtered Derivative Action

A Hierarchy of Biomolecular Proportional-Integral-Derivative Feedback Controllers for Robust Perfect Adaptation and Dynamic Performance

Regulation strategies for two-output biomolecular networks

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