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Feasibility and reliability of sequential logic with gene regulatory networks | JoVE Visualize

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Feasibility and reliability of sequential logic with gene regulatory networks

Morgan Madec¹, Elise Rosati¹, Christophe Lallement¹

¹Laboratory of Engineering Sciences, Computer Sciences and Imaging, UMR 7357 (University of Strasbourg / CNRS), Illkirch, France.

Plos One|March 30, 2021

View abstract on PubMed

Summary

Designing complex gene regulatory networks (GRNs) for biological computation is challenging. Stochasticity and response inhomogeneity in biological systems increase the risk of malfunctions in these synthetic GRNs.

Area of Science:

Synthetic Biology
Computational Biology
Systems Biology

Background:

Gene regulatory networks (GRNs) are foundational to biological processes.
Boolean logic gates (AND, OR, XOR) are well-established in GRN design.
Sophisticated functions like computation require state-dependent behaviors, akin to sequential circuits or state machines.

Purpose of the Study:

To assess the impact of biological particularities on the reliability of designed GRNs.
To evaluate the risks associated with stochasticity and response inhomogeneity in synthetic GRNs.
To explore potential solutions for enhancing the reliability of complex GRNs.

Main Methods:

Theoretical design of GRNs analogous to digital electronic circuits.
Numerical simulations to model GRN behavior under biological conditions.
Analysis of two specific use cases to identify failure points.

Main Results:

Designed GRNs, theoretically functional, exhibit high risks of malfunction.
Biological stochasticity significantly impacts GRN output reliability.
Inhomogeneous responses in regulatory mechanisms further compromise GRN performance.

Conclusions:

Standard GRN design principles face significant challenges due to inherent biological variability.
Synthetic GRNs require robust design strategies to overcome stochasticity and inhomogeneity.
Further research is needed to develop reliable solutions for complex biological circuit design.

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Feasibility And Reliability Of Sequential Logic With Gene Regulatory Networks