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Biomolecular mechanisms for signal differentiation.

ABSTRACT: Cells can sense temporal changes of molecular signals, allowing them to predict environmental variations and modulate their behavior. This paper elucidates biomolecular mechanisms of time derivative computation, facilitating the design of reliable synthetic differentiator devices for a variety of applications, ultimately expanding our understanding of cell behavior. In particular, we describe and analyze three alternative biomolecular topologies that are able to work as signal differentiators to input signals around their nominal operation. We propose strategies to preserve their performance even in the presence of high-frequency input signal components which are detrimental to the performance of most differentiators. We find that the core of the proposed topologies appears in natural regulatory networks and we further discuss their biological relevance. The simple structure of our designs makes them promising tools for realizing derivative control action in synthetic biology.

SUBMITTER: Alexis E

PROVIDER: S-EPMC8649740 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Biomolecular mechanisms for signal differentiation.

Alexis Emmanouil E Schulte Carolin C M CCM Cardelli Luca L Papachristodoulou Antonis A

iScience 20211117 12

Cells can sense temporal changes of molecular signals, allowing them to predict environmental variations and modulate their behavior. This paper elucidates biomolecular mechanisms of time derivative computation, facilitating the design of reliable synthetic differentiator devices for a variety of applications, ultimately expanding our understanding of cell behavior. In particular, we describe and analyze three alternative biomolecular topologies that are able to work as signal differentiators to ...[more]

PMID: 34927021

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Dataset Information

Biomolecular mechanisms for signal differentiation.

Publications

Biomolecular mechanisms for signal differentiation.

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