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Emergence of Switch-Like Behavior in a Large Family of Simple Biochemical Networks

Bistability plays a central role in the gene regulatory networks (GRNs) controlling many essential biological functions, including cellular differentiation and cell cycle control. However, establishing the network topologies that can exhibit bistability remains a challenge, in part due to the exceed...

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Autores principales: Siegal-Gaskins, Dan, Mejia-Guerra, Maria Katherine, Smith, Gregory D., Grotewold, Erich
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3093349/
https://www.ncbi.nlm.nih.gov/pubmed/21589886
http://dx.doi.org/10.1371/journal.pcbi.1002039
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author Siegal-Gaskins, Dan
Mejia-Guerra, Maria Katherine
Smith, Gregory D.
Grotewold, Erich
author_facet Siegal-Gaskins, Dan
Mejia-Guerra, Maria Katherine
Smith, Gregory D.
Grotewold, Erich
author_sort Siegal-Gaskins, Dan
collection PubMed
description Bistability plays a central role in the gene regulatory networks (GRNs) controlling many essential biological functions, including cellular differentiation and cell cycle control. However, establishing the network topologies that can exhibit bistability remains a challenge, in part due to the exceedingly large variety of GRNs that exist for even a small number of components. We begin to address this problem by employing chemical reaction network theory in a comprehensive in silico survey to determine the capacity for bistability of more than 40,000 simple networks that can be formed by two transcription factor-coding genes and their associated proteins (assuming only the most elementary biochemical processes). We find that there exist reaction rate constants leading to bistability in ∼90% of these GRN models, including several circuits that do not contain any of the TF cooperativity commonly associated with bistable systems, and the majority of which could only be identified as bistable through an original subnetwork-based analysis. A topological sorting of the two-gene family of networks based on the presence or absence of biochemical reactions reveals eleven minimal bistable networks (i.e., bistable networks that do not contain within them a smaller bistable subnetwork). The large number of previously unknown bistable network topologies suggests that the capacity for switch-like behavior in GRNs arises with relative ease and is not easily lost through network evolution. To highlight the relevance of the systematic application of CRNT to bistable network identification in real biological systems, we integrated publicly available protein-protein interaction, protein-DNA interaction, and gene expression data from Saccharomyces cerevisiae, and identified several GRNs predicted to behave in a bistable fashion.
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spelling pubmed-30933492011-05-17 Emergence of Switch-Like Behavior in a Large Family of Simple Biochemical Networks Siegal-Gaskins, Dan Mejia-Guerra, Maria Katherine Smith, Gregory D. Grotewold, Erich PLoS Comput Biol Research Article Bistability plays a central role in the gene regulatory networks (GRNs) controlling many essential biological functions, including cellular differentiation and cell cycle control. However, establishing the network topologies that can exhibit bistability remains a challenge, in part due to the exceedingly large variety of GRNs that exist for even a small number of components. We begin to address this problem by employing chemical reaction network theory in a comprehensive in silico survey to determine the capacity for bistability of more than 40,000 simple networks that can be formed by two transcription factor-coding genes and their associated proteins (assuming only the most elementary biochemical processes). We find that there exist reaction rate constants leading to bistability in ∼90% of these GRN models, including several circuits that do not contain any of the TF cooperativity commonly associated with bistable systems, and the majority of which could only be identified as bistable through an original subnetwork-based analysis. A topological sorting of the two-gene family of networks based on the presence or absence of biochemical reactions reveals eleven minimal bistable networks (i.e., bistable networks that do not contain within them a smaller bistable subnetwork). The large number of previously unknown bistable network topologies suggests that the capacity for switch-like behavior in GRNs arises with relative ease and is not easily lost through network evolution. To highlight the relevance of the systematic application of CRNT to bistable network identification in real biological systems, we integrated publicly available protein-protein interaction, protein-DNA interaction, and gene expression data from Saccharomyces cerevisiae, and identified several GRNs predicted to behave in a bistable fashion. Public Library of Science 2011-05-12 /pmc/articles/PMC3093349/ /pubmed/21589886 http://dx.doi.org/10.1371/journal.pcbi.1002039 Text en Siegal-Gaskins 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Siegal-Gaskins, Dan
Mejia-Guerra, Maria Katherine
Smith, Gregory D.
Grotewold, Erich
Emergence of Switch-Like Behavior in a Large Family of Simple Biochemical Networks
title Emergence of Switch-Like Behavior in a Large Family of Simple Biochemical Networks
title_full Emergence of Switch-Like Behavior in a Large Family of Simple Biochemical Networks
title_fullStr Emergence of Switch-Like Behavior in a Large Family of Simple Biochemical Networks
title_full_unstemmed Emergence of Switch-Like Behavior in a Large Family of Simple Biochemical Networks
title_short Emergence of Switch-Like Behavior in a Large Family of Simple Biochemical Networks
title_sort emergence of switch-like behavior in a large family of simple biochemical networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3093349/
https://www.ncbi.nlm.nih.gov/pubmed/21589886
http://dx.doi.org/10.1371/journal.pcbi.1002039
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