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Synthetic BiologyiScience
Peer-reviewed journal article

Biomolecular mechanisms for signal differentiation

Emmanouil AlexisiD, Carolin C. M. SchulteiD, Luca CardelliiD, Antonis PapachristodoulouiD

Abstract

Cells can sense temporal changes of molecular signals, allowing them to predict environmental vari-ations and modulate their behaviour. This paper elucidates the underlying 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 behaviour. In particular, we describe and analyse three alternative biomolecular topologies that work as signal differentiators of high accuracy to arbitrary 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 found 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.

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Citations
20
FWCI
0.94
Field percentile
top 27%

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Emmanouil Alexis, José L. Avalos‬, Luca Cardelli+1 more·bioRxiv·Jan 29, 2024· 1 citations