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Modularity and predictability in cell signaling and decision making
Cells make decisions to differentiate, divide, or apoptose based on multiple signals of internal and external origin. These decisions are discrete outputs from dynamic networks comprised of signaling pathways. Yet the validity of this decomposition of regulatory proteins into distinct pathways is un...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The American Society for Cell Biology
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4230600/ https://www.ncbi.nlm.nih.gov/pubmed/25368418 http://dx.doi.org/10.1091/mbc.E14-02-0718 |
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author | Atay, Oguzhan Skotheim, Jan M. |
author_facet | Atay, Oguzhan Skotheim, Jan M. |
author_sort | Atay, Oguzhan |
collection | PubMed |
description | Cells make decisions to differentiate, divide, or apoptose based on multiple signals of internal and external origin. These decisions are discrete outputs from dynamic networks comprised of signaling pathways. Yet the validity of this decomposition of regulatory proteins into distinct pathways is unclear because many regulatory proteins are pleiotropic and interact through cross-talk with components of other pathways. In addition to the deterministic complexity of interconnected networks, there is stochastic complexity arising from the fluctuations in concentrations of regulatory molecules. Even within a genetically identical population of cells grown in the same environment, cell-to-cell variations in mRNA and protein concentrations can be as high as 50% in yeast and even higher in mammalian cells. Thus, if everything is connected and stochastic, what hope could we have for a quantitative understanding of cellular decisions? Here we discuss the implications of recent advances in genomics, single-cell, and single-cell genomics technology for network modularity and cellular decisions. On the basis of these recent advances, we argue that most gene expression stochasticity and pathway interconnectivity is nonfunctional and that cellular decisions are likely much more predictable than previously expected. |
format | Online Article Text |
id | pubmed-4230600 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | The American Society for Cell Biology |
record_format | MEDLINE/PubMed |
spelling | pubmed-42306002015-01-20 Modularity and predictability in cell signaling and decision making Atay, Oguzhan Skotheim, Jan M. Mol Biol Cell Perspectives Cells make decisions to differentiate, divide, or apoptose based on multiple signals of internal and external origin. These decisions are discrete outputs from dynamic networks comprised of signaling pathways. Yet the validity of this decomposition of regulatory proteins into distinct pathways is unclear because many regulatory proteins are pleiotropic and interact through cross-talk with components of other pathways. In addition to the deterministic complexity of interconnected networks, there is stochastic complexity arising from the fluctuations in concentrations of regulatory molecules. Even within a genetically identical population of cells grown in the same environment, cell-to-cell variations in mRNA and protein concentrations can be as high as 50% in yeast and even higher in mammalian cells. Thus, if everything is connected and stochastic, what hope could we have for a quantitative understanding of cellular decisions? Here we discuss the implications of recent advances in genomics, single-cell, and single-cell genomics technology for network modularity and cellular decisions. On the basis of these recent advances, we argue that most gene expression stochasticity and pathway interconnectivity is nonfunctional and that cellular decisions are likely much more predictable than previously expected. The American Society for Cell Biology 2014-11-05 /pmc/articles/PMC4230600/ /pubmed/25368418 http://dx.doi.org/10.1091/mbc.E14-02-0718 Text en © 2014 Atay and Skotheim. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0). “ASCB®,” “The American Society for Cell Biology®,” and “Molecular Biology of the Cell®” are registered trademarks of The American Society for Cell Biology. |
spellingShingle | Perspectives Atay, Oguzhan Skotheim, Jan M. Modularity and predictability in cell signaling and decision making |
title | Modularity and predictability in cell signaling and decision making |
title_full | Modularity and predictability in cell signaling and decision making |
title_fullStr | Modularity and predictability in cell signaling and decision making |
title_full_unstemmed | Modularity and predictability in cell signaling and decision making |
title_short | Modularity and predictability in cell signaling and decision making |
title_sort | modularity and predictability in cell signaling and decision making |
topic | Perspectives |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4230600/ https://www.ncbi.nlm.nih.gov/pubmed/25368418 http://dx.doi.org/10.1091/mbc.E14-02-0718 |
work_keys_str_mv | AT atayoguzhan modularityandpredictabilityincellsignalinganddecisionmaking AT skotheimjanm modularityandpredictabilityincellsignalinganddecisionmaking |