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Adaptation with transcriptional regulation
Biochemical adaptation is one of the basic functions that are widely implemented in biological systems for a variety of purposes such as signal sensing, stress response and homeostasis. The adaptation time scales span from milliseconds to days, involving different regulatory machineries in different...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5324054/ https://www.ncbi.nlm.nih.gov/pubmed/28233824 http://dx.doi.org/10.1038/srep42648 |
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author | Shi, Wenjia Ma, Wenzhe Xiong, Liyang Zhang, Mingyue Tang, Chao |
author_facet | Shi, Wenjia Ma, Wenzhe Xiong, Liyang Zhang, Mingyue Tang, Chao |
author_sort | Shi, Wenjia |
collection | PubMed |
description | Biochemical adaptation is one of the basic functions that are widely implemented in biological systems for a variety of purposes such as signal sensing, stress response and homeostasis. The adaptation time scales span from milliseconds to days, involving different regulatory machineries in different processes. The adaptive networks with enzymatic regulation (ERNs) have been investigated in detail. But it remains unclear if and how other forms of regulation will impact the network topology and other features of the function. Here, we systematically studied three-node transcriptional regulatory networks (TRNs), with three different types of gene regulation logics. We found that the topologies of adaptive gene regulatory networks can still be grouped into two general classes: negative feedback loop (NFBL) and incoherent feed-forward loop (IFFL), but with some distinct topological features comparing to the enzymatic networks. Specifically, an auto-activation loop on the buffer node is necessary for the NFBL class. For IFFL class, the control node can be either a proportional node or an inversely-proportional node. Furthermore, the tunability of adaptive behavior differs between TRNs and ERNs. Our findings highlight the role of regulation forms in network topology, implementation and dynamics. |
format | Online Article Text |
id | pubmed-5324054 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-53240542017-03-01 Adaptation with transcriptional regulation Shi, Wenjia Ma, Wenzhe Xiong, Liyang Zhang, Mingyue Tang, Chao Sci Rep Article Biochemical adaptation is one of the basic functions that are widely implemented in biological systems for a variety of purposes such as signal sensing, stress response and homeostasis. The adaptation time scales span from milliseconds to days, involving different regulatory machineries in different processes. The adaptive networks with enzymatic regulation (ERNs) have been investigated in detail. But it remains unclear if and how other forms of regulation will impact the network topology and other features of the function. Here, we systematically studied three-node transcriptional regulatory networks (TRNs), with three different types of gene regulation logics. We found that the topologies of adaptive gene regulatory networks can still be grouped into two general classes: negative feedback loop (NFBL) and incoherent feed-forward loop (IFFL), but with some distinct topological features comparing to the enzymatic networks. Specifically, an auto-activation loop on the buffer node is necessary for the NFBL class. For IFFL class, the control node can be either a proportional node or an inversely-proportional node. Furthermore, the tunability of adaptive behavior differs between TRNs and ERNs. Our findings highlight the role of regulation forms in network topology, implementation and dynamics. Nature Publishing Group 2017-02-24 /pmc/articles/PMC5324054/ /pubmed/28233824 http://dx.doi.org/10.1038/srep42648 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Shi, Wenjia Ma, Wenzhe Xiong, Liyang Zhang, Mingyue Tang, Chao Adaptation with transcriptional regulation |
title | Adaptation with transcriptional regulation |
title_full | Adaptation with transcriptional regulation |
title_fullStr | Adaptation with transcriptional regulation |
title_full_unstemmed | Adaptation with transcriptional regulation |
title_short | Adaptation with transcriptional regulation |
title_sort | adaptation with transcriptional regulation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5324054/ https://www.ncbi.nlm.nih.gov/pubmed/28233824 http://dx.doi.org/10.1038/srep42648 |
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