Robust network topologies for generating switch-like cellular responses.

Signaling networks that convert graded stimuli into binary, all-or-none cellular responses are critical in processes ranging from cell-cycle control to lineage commitment. To exhaustively enumerate topologies that exhibit this switch-like behavior, we simulated all possible two- and three-component...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Najaf A Shah, Casim A Sarkar
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2011
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/0206fdad440e40a9b0106ddad8d126a4
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:0206fdad440e40a9b0106ddad8d126a4
record_format	dspace
spelling	oai:doaj.org-article:0206fdad440e40a9b0106ddad8d126a42021-11-18T05:50:28ZRobust network topologies for generating switch-like cellular responses.1553-734X1553-735810.1371/journal.pcbi.1002085https://doaj.org/article/0206fdad440e40a9b0106ddad8d126a42011-06-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21731481/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Signaling networks that convert graded stimuli into binary, all-or-none cellular responses are critical in processes ranging from cell-cycle control to lineage commitment. To exhaustively enumerate topologies that exhibit this switch-like behavior, we simulated all possible two- and three-component networks on random parameter sets, and assessed the resulting response profiles for both steepness (ultrasensitivity) and extent of memory (bistability). Simulations were used to study purely enzymatic networks, purely transcriptional networks, and hybrid enzymatic/transcriptional networks, and the topologies in each class were rank ordered by parametric robustness (i.e., the percentage of applied parameter sets exhibiting ultrasensitivity or bistability). Results reveal that the distribution of network robustness is highly skewed, with the most robust topologies clustering into a small number of motifs. Hybrid networks are the most robust in generating ultrasensitivity (up to 28%) and bistability (up to 18%); strikingly, a purely transcriptional framework is the most fragile in generating either ultrasensitive (up to 3%) or bistable (up to 1%) responses. The disparity in robustness among the network classes is due in part to zero-order ultrasensitivity, an enzyme-specific phenomenon, which repeatedly emerges as a particularly robust mechanism for generating nonlinearity and can act as a building block for switch-like responses. We also highlight experimentally studied examples of topologies enabling switching behavior, in both native and synthetic systems, that rank highly in our simulations. This unbiased approach for identifying topologies capable of a given response may be useful in discovering new natural motifs and in designing robust synthetic gene networks.Najaf A ShahCasim A SarkarPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 7, Iss 6, p e1002085 (2011)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Najaf A Shah Casim A Sarkar Robust network topologies for generating switch-like cellular responses.
description	Signaling networks that convert graded stimuli into binary, all-or-none cellular responses are critical in processes ranging from cell-cycle control to lineage commitment. To exhaustively enumerate topologies that exhibit this switch-like behavior, we simulated all possible two- and three-component networks on random parameter sets, and assessed the resulting response profiles for both steepness (ultrasensitivity) and extent of memory (bistability). Simulations were used to study purely enzymatic networks, purely transcriptional networks, and hybrid enzymatic/transcriptional networks, and the topologies in each class were rank ordered by parametric robustness (i.e., the percentage of applied parameter sets exhibiting ultrasensitivity or bistability). Results reveal that the distribution of network robustness is highly skewed, with the most robust topologies clustering into a small number of motifs. Hybrid networks are the most robust in generating ultrasensitivity (up to 28%) and bistability (up to 18%); strikingly, a purely transcriptional framework is the most fragile in generating either ultrasensitive (up to 3%) or bistable (up to 1%) responses. The disparity in robustness among the network classes is due in part to zero-order ultrasensitivity, an enzyme-specific phenomenon, which repeatedly emerges as a particularly robust mechanism for generating nonlinearity and can act as a building block for switch-like responses. We also highlight experimentally studied examples of topologies enabling switching behavior, in both native and synthetic systems, that rank highly in our simulations. This unbiased approach for identifying topologies capable of a given response may be useful in discovering new natural motifs and in designing robust synthetic gene networks.
format	article
author	Najaf A Shah Casim A Sarkar
author_facet	Najaf A Shah Casim A Sarkar
author_sort	Najaf A Shah
title	Robust network topologies for generating switch-like cellular responses.
title_short	Robust network topologies for generating switch-like cellular responses.
title_full	Robust network topologies for generating switch-like cellular responses.
title_fullStr	Robust network topologies for generating switch-like cellular responses.
title_full_unstemmed	Robust network topologies for generating switch-like cellular responses.
title_sort	robust network topologies for generating switch-like cellular responses.
publisher	Public Library of Science (PLoS)
publishDate	2011
url	https://doaj.org/article/0206fdad440e40a9b0106ddad8d126a4
work_keys_str_mv	AT najafashah robustnetworktopologiesforgeneratingswitchlikecellularresponses AT casimasarkar robustnetworktopologiesforgeneratingswitchlikecellularresponses
_version_	1718424769060143104

Robust network topologies for generating switch-like cellular responses.

Ejemplares similares