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Feasibility and reliability of sequential logic with gene regulatory networks

Gene regulatory networks exhibiting Boolean behaviour, e.g. AND, OR or XOR, have been routinely designed for years. However, achieving more sophisticated functions, such as control or computation, usually requires sequential circuits or so-called state machines. For such a circuit, outputs depend bo...

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Detalles Bibliográficos
Autores principales: Madec, Morgan, Rosati, Elise, Lallement, Christophe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8009411/
https://www.ncbi.nlm.nih.gov/pubmed/33784367
http://dx.doi.org/10.1371/journal.pone.0249234
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author Madec, Morgan
Rosati, Elise
Lallement, Christophe
author_facet Madec, Morgan
Rosati, Elise
Lallement, Christophe
author_sort Madec, Morgan
collection PubMed
description Gene regulatory networks exhibiting Boolean behaviour, e.g. AND, OR or XOR, have been routinely designed for years. However, achieving more sophisticated functions, such as control or computation, usually requires sequential circuits or so-called state machines. For such a circuit, outputs depend both on inputs and the current state of the system. Although it is still possible to design such circuits by analogy with digital electronics, some particularities of biology make the task trickier. The impact of two of them, namely the stochasticity of biological processes and the inhomogeneity in the response of regulation mechanisms, are assessed in this paper. Numerical simulations performed in two use cases point out high risks of malfunctions even for designed GRNs functional from a theoretical point of view. Several solutions to improve reliability of such systems are also discussed.
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spelling pubmed-80094112021-04-07 Feasibility and reliability of sequential logic with gene regulatory networks Madec, Morgan Rosati, Elise Lallement, Christophe PLoS One Research Article Gene regulatory networks exhibiting Boolean behaviour, e.g. AND, OR or XOR, have been routinely designed for years. However, achieving more sophisticated functions, such as control or computation, usually requires sequential circuits or so-called state machines. For such a circuit, outputs depend both on inputs and the current state of the system. Although it is still possible to design such circuits by analogy with digital electronics, some particularities of biology make the task trickier. The impact of two of them, namely the stochasticity of biological processes and the inhomogeneity in the response of regulation mechanisms, are assessed in this paper. Numerical simulations performed in two use cases point out high risks of malfunctions even for designed GRNs functional from a theoretical point of view. Several solutions to improve reliability of such systems are also discussed. Public Library of Science 2021-03-30 /pmc/articles/PMC8009411/ /pubmed/33784367 http://dx.doi.org/10.1371/journal.pone.0249234 Text en © 2021 Madec et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Madec, Morgan
Rosati, Elise
Lallement, Christophe
Feasibility and reliability of sequential logic with gene regulatory networks
title Feasibility and reliability of sequential logic with gene regulatory networks
title_full Feasibility and reliability of sequential logic with gene regulatory networks
title_fullStr Feasibility and reliability of sequential logic with gene regulatory networks
title_full_unstemmed Feasibility and reliability of sequential logic with gene regulatory networks
title_short Feasibility and reliability of sequential logic with gene regulatory networks
title_sort feasibility and reliability of sequential logic with gene regulatory networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8009411/
https://www.ncbi.nlm.nih.gov/pubmed/33784367
http://dx.doi.org/10.1371/journal.pone.0249234
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