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Constructing network topologies for multiple signal-encoding functions

BACKGROUND: Cells use signaling protein networks to sense their environment and mediate specific responses. Information about environmental stress is usually encoded in the dynamics of the signaling molecules, and qualitatively distinct dynamics of the same signaling molecule can lead to dramaticall...

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Autores principales: Wu, Lili, Wang, Hongli, Ouyang, Qi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6330498/
https://www.ncbi.nlm.nih.gov/pubmed/30634968
http://dx.doi.org/10.1186/s12918-018-0676-5
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author Wu, Lili
Wang, Hongli
Ouyang, Qi
author_facet Wu, Lili
Wang, Hongli
Ouyang, Qi
author_sort Wu, Lili
collection PubMed
description BACKGROUND: Cells use signaling protein networks to sense their environment and mediate specific responses. Information about environmental stress is usually encoded in the dynamics of the signaling molecules, and qualitatively distinct dynamics of the same signaling molecule can lead to dramatically different cell fates. Exploring the design principles of networks with multiple signal-encoding functions is important for understanding how distinct dynamic patterns are shaped and integrated by real cellular networks, and for building cells with targeted sensing–response functions via synthetic biology. RESULTS: In this paper, we investigate multi-node enzymatic regulatory networks with three signal-encoding functions, i.e., dynamic responses of oscillation, transient activation, and sustained activation upon step stimulation by three different inducers, respectively. Taking into account competition effects of the substrates for the same enzyme in the enzymatic reactions, we searched for robust subnetworks for each signal-encoding function by three-node-network enumeration and then integrated the three subnetworks together via node-merging. The obtained tri-functional networks consisted of four to six nodes, and the core structures of these networks were hybrids of the motifs for the subfunctions. CONCLUSIONS: The simplest but relatively robust tri-functional networks demonstrated that the three functions were compatible within a simple negative feedback loop. Depending on the network structure, the competition effects of the substrates for the same enzyme within the networks could promote or hamper the target functions, and can create implicit functional motifs. Overall, the networks we obtained could in principle be synthesized to construct dynamic control circuits with multiple target functions. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12918-018-0676-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-63304982019-01-16 Constructing network topologies for multiple signal-encoding functions Wu, Lili Wang, Hongli Ouyang, Qi BMC Syst Biol Research Article BACKGROUND: Cells use signaling protein networks to sense their environment and mediate specific responses. Information about environmental stress is usually encoded in the dynamics of the signaling molecules, and qualitatively distinct dynamics of the same signaling molecule can lead to dramatically different cell fates. Exploring the design principles of networks with multiple signal-encoding functions is important for understanding how distinct dynamic patterns are shaped and integrated by real cellular networks, and for building cells with targeted sensing–response functions via synthetic biology. RESULTS: In this paper, we investigate multi-node enzymatic regulatory networks with three signal-encoding functions, i.e., dynamic responses of oscillation, transient activation, and sustained activation upon step stimulation by three different inducers, respectively. Taking into account competition effects of the substrates for the same enzyme in the enzymatic reactions, we searched for robust subnetworks for each signal-encoding function by three-node-network enumeration and then integrated the three subnetworks together via node-merging. The obtained tri-functional networks consisted of four to six nodes, and the core structures of these networks were hybrids of the motifs for the subfunctions. CONCLUSIONS: The simplest but relatively robust tri-functional networks demonstrated that the three functions were compatible within a simple negative feedback loop. Depending on the network structure, the competition effects of the substrates for the same enzyme within the networks could promote or hamper the target functions, and can create implicit functional motifs. Overall, the networks we obtained could in principle be synthesized to construct dynamic control circuits with multiple target functions. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12918-018-0676-5) contains supplementary material, which is available to authorized users. BioMed Central 2019-01-11 /pmc/articles/PMC6330498/ /pubmed/30634968 http://dx.doi.org/10.1186/s12918-018-0676-5 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Wu, Lili
Wang, Hongli
Ouyang, Qi
Constructing network topologies for multiple signal-encoding functions
title Constructing network topologies for multiple signal-encoding functions
title_full Constructing network topologies for multiple signal-encoding functions
title_fullStr Constructing network topologies for multiple signal-encoding functions
title_full_unstemmed Constructing network topologies for multiple signal-encoding functions
title_short Constructing network topologies for multiple signal-encoding functions
title_sort constructing network topologies for multiple signal-encoding functions
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6330498/
https://www.ncbi.nlm.nih.gov/pubmed/30634968
http://dx.doi.org/10.1186/s12918-018-0676-5
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