Noise-processing by signaling networks

Abstract Signaling networks mediate environmental information to the cell nucleus. To perform this task effectively they must be able to integrate multiple stimuli and distinguish persistent signals from transient environmental fluctuations. However, the ways in which signaling networks process envi...

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Autores principales:	Styliani Kontogeorgaki, Rubén J. Sánchez-García, Rob M. Ewing, Konstantinos C. Zygalakis, Ben D. MacArthur
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/1575396668054f3e924a7fe85fe7ea65
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spelling	oai:doaj.org-article:1575396668054f3e924a7fe85fe7ea652021-12-02T11:52:34ZNoise-processing by signaling networks10.1038/s41598-017-00659-x2045-2322https://doaj.org/article/1575396668054f3e924a7fe85fe7ea652017-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-00659-xhttps://doaj.org/toc/2045-2322Abstract Signaling networks mediate environmental information to the cell nucleus. To perform this task effectively they must be able to integrate multiple stimuli and distinguish persistent signals from transient environmental fluctuations. However, the ways in which signaling networks process environmental noise are not well understood. Here we outline a mathematical framework that relates a network’s structure to its capacity to process noise, and use this framework to dissect the noise-processing ability of signaling networks. We find that complex networks that are dense in directed paths are poor noise processors, while those that are sparse and strongly directional process noise well. These results suggest that while cross-talk between signaling pathways may increase the ability of signaling networks to integrate multiple stimuli, too much cross-talk may compromise the ability of the network to distinguish signal from noise. To illustrate these general results we consider the structure of the signalling network that maintains pluripotency in mouse embryonic stem cells, and find an incoherent feedforward loop structure involving Stat3, Tfcp2l1, Esrrb, Klf2 and Klf4 is particularly important for noise-processing. Taken together these results suggest that noise-processing is an important function of signaling networks and they may be structured in part to optimize this task.Styliani KontogeorgakiRubén J. Sánchez-GarcíaRob M. EwingKonstantinos C. ZygalakisBen D. MacArthurNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-9 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Styliani Kontogeorgaki Rubén J. Sánchez-García Rob M. Ewing Konstantinos C. Zygalakis Ben D. MacArthur Noise-processing by signaling networks
description	Abstract Signaling networks mediate environmental information to the cell nucleus. To perform this task effectively they must be able to integrate multiple stimuli and distinguish persistent signals from transient environmental fluctuations. However, the ways in which signaling networks process environmental noise are not well understood. Here we outline a mathematical framework that relates a network’s structure to its capacity to process noise, and use this framework to dissect the noise-processing ability of signaling networks. We find that complex networks that are dense in directed paths are poor noise processors, while those that are sparse and strongly directional process noise well. These results suggest that while cross-talk between signaling pathways may increase the ability of signaling networks to integrate multiple stimuli, too much cross-talk may compromise the ability of the network to distinguish signal from noise. To illustrate these general results we consider the structure of the signalling network that maintains pluripotency in mouse embryonic stem cells, and find an incoherent feedforward loop structure involving Stat3, Tfcp2l1, Esrrb, Klf2 and Klf4 is particularly important for noise-processing. Taken together these results suggest that noise-processing is an important function of signaling networks and they may be structured in part to optimize this task.
format	article
author	Styliani Kontogeorgaki Rubén J. Sánchez-García Rob M. Ewing Konstantinos C. Zygalakis Ben D. MacArthur
author_facet	Styliani Kontogeorgaki Rubén J. Sánchez-García Rob M. Ewing Konstantinos C. Zygalakis Ben D. MacArthur
author_sort	Styliani Kontogeorgaki
title	Noise-processing by signaling networks
title_short	Noise-processing by signaling networks
title_full	Noise-processing by signaling networks
title_fullStr	Noise-processing by signaling networks
title_full_unstemmed	Noise-processing by signaling networks
title_sort	noise-processing by signaling networks
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/1575396668054f3e924a7fe85fe7ea65
work_keys_str_mv	AT stylianikontogeorgaki noiseprocessingbysignalingnetworks AT rubenjsanchezgarcia noiseprocessingbysignalingnetworks AT robmewing noiseprocessingbysignalingnetworks AT konstantinosczygalakis noiseprocessingbysignalingnetworks AT bendmacarthur noiseprocessingbysignalingnetworks
_version_	1718394967352672256

Noise-processing by signaling networks

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