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Network design principle for robust oscillatory behaviors with respect to biological noise

Oscillatory behaviors, which are ubiquitous in transcriptional regulatory networks, are often subject to inevitable biological noise. Thus, a natural question is how transcriptional regulatory networks can robustly achieve accurate oscillation in the presence of biological noise. Here, we search all...

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Autores principales: Qiao, Lingxia, Zhang, Zhi-Bo, Zhao, Wei, Wei, Ping, Zhang, Lei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9489215/
https://www.ncbi.nlm.nih.gov/pubmed/36125857
http://dx.doi.org/10.7554/eLife.76188
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author Qiao, Lingxia
Zhang, Zhi-Bo
Zhao, Wei
Wei, Ping
Zhang, Lei
author_facet Qiao, Lingxia
Zhang, Zhi-Bo
Zhao, Wei
Wei, Ping
Zhang, Lei
author_sort Qiao, Lingxia
collection PubMed
description Oscillatory behaviors, which are ubiquitous in transcriptional regulatory networks, are often subject to inevitable biological noise. Thus, a natural question is how transcriptional regulatory networks can robustly achieve accurate oscillation in the presence of biological noise. Here, we search all two- and three-node transcriptional regulatory network topologies for those robustly capable of accurate oscillation against the parameter variability (extrinsic noise) or stochasticity of chemical reactions (intrinsic noise). We find that, no matter what source of the noise is applied, the topologies containing the repressilator with positive autoregulation show higher robustness of accurate oscillation than those containing the activator-inhibitor oscillator, and additional positive autoregulation enhances the robustness against noise. Nevertheless, the attenuation of different sources of noise is governed by distinct mechanisms: the parameter variability is buffered by the long period, while the stochasticity of chemical reactions is filtered by the high amplitude. Furthermore, we analyze the noise of a synthetic human nuclear factor κB (NF-κB) signaling network by varying three different topologies and verify that the addition of a repressilator to the activator-inhibitor oscillator, which leads to the emergence of high-robustness motif—the repressilator with positive autoregulation—improves the oscillation accuracy in comparison to the topology with only an activator-inhibitor oscillator. These design principles may be applicable to other oscillatory circuits.
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spelling pubmed-94892152022-09-21 Network design principle for robust oscillatory behaviors with respect to biological noise Qiao, Lingxia Zhang, Zhi-Bo Zhao, Wei Wei, Ping Zhang, Lei eLife Computational and Systems Biology Oscillatory behaviors, which are ubiquitous in transcriptional regulatory networks, are often subject to inevitable biological noise. Thus, a natural question is how transcriptional regulatory networks can robustly achieve accurate oscillation in the presence of biological noise. Here, we search all two- and three-node transcriptional regulatory network topologies for those robustly capable of accurate oscillation against the parameter variability (extrinsic noise) or stochasticity of chemical reactions (intrinsic noise). We find that, no matter what source of the noise is applied, the topologies containing the repressilator with positive autoregulation show higher robustness of accurate oscillation than those containing the activator-inhibitor oscillator, and additional positive autoregulation enhances the robustness against noise. Nevertheless, the attenuation of different sources of noise is governed by distinct mechanisms: the parameter variability is buffered by the long period, while the stochasticity of chemical reactions is filtered by the high amplitude. Furthermore, we analyze the noise of a synthetic human nuclear factor κB (NF-κB) signaling network by varying three different topologies and verify that the addition of a repressilator to the activator-inhibitor oscillator, which leads to the emergence of high-robustness motif—the repressilator with positive autoregulation—improves the oscillation accuracy in comparison to the topology with only an activator-inhibitor oscillator. These design principles may be applicable to other oscillatory circuits. eLife Sciences Publications, Ltd 2022-09-20 /pmc/articles/PMC9489215/ /pubmed/36125857 http://dx.doi.org/10.7554/eLife.76188 Text en © 2022, Qiao, Zhang, Zhao et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Computational and Systems Biology
Qiao, Lingxia
Zhang, Zhi-Bo
Zhao, Wei
Wei, Ping
Zhang, Lei
Network design principle for robust oscillatory behaviors with respect to biological noise
title Network design principle for robust oscillatory behaviors with respect to biological noise
title_full Network design principle for robust oscillatory behaviors with respect to biological noise
title_fullStr Network design principle for robust oscillatory behaviors with respect to biological noise
title_full_unstemmed Network design principle for robust oscillatory behaviors with respect to biological noise
title_short Network design principle for robust oscillatory behaviors with respect to biological noise
title_sort network design principle for robust oscillatory behaviors with respect to biological noise
topic Computational and Systems Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9489215/
https://www.ncbi.nlm.nih.gov/pubmed/36125857
http://dx.doi.org/10.7554/eLife.76188
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