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Stochastic adaptation and fold-change detection: from single-cell to population behavior
BACKGROUND: In cell signaling terminology, adaptation refers to a system's capability of returning to its equilibrium upon a transient response. To achieve this, a network has to be both sensitive and precise. Namely, the system must display a significant output response upon stimulation, and l...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2011
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3049136/ https://www.ncbi.nlm.nih.gov/pubmed/21291524 http://dx.doi.org/10.1186/1752-0509-5-22 |
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author | Marquez-Lago, Tatiana T Leier, André |
author_facet | Marquez-Lago, Tatiana T Leier, André |
author_sort | Marquez-Lago, Tatiana T |
collection | PubMed |
description | BACKGROUND: In cell signaling terminology, adaptation refers to a system's capability of returning to its equilibrium upon a transient response. To achieve this, a network has to be both sensitive and precise. Namely, the system must display a significant output response upon stimulation, and later on return to pre-stimulation levels. If the system settles at the exact same equilibrium, adaptation is said to be 'perfect'. Examples of adaptation mechanisms include temperature regulation, calcium regulation and bacterial chemotaxis. RESULTS: We present models of the simplest adaptation architecture, a two-state protein system, in a stochastic setting. Furthermore, we consider differences between individual and collective adaptive behavior, and show how our system displays fold-change detection properties. Our analysis and simulations highlight why adaptation needs to be understood in terms of probability, and not in strict numbers of molecules. Most importantly, selection of appropriate parameters in this simple linear setting may yield populations of cells displaying adaptation, while single cells do not. CONCLUSIONS: Single cell behavior cannot be inferred from population measurements and, sometimes, collective behavior cannot be determined from the individuals. By consequence, adaptation can many times be considered a purely emergent property of the collective system. This is a clear example where biological ergodicity cannot be assumed, just as is also the case when cell replication rates are not homogeneous, or depend on the cell state. Our analysis shows, for the first time, how ergodicity cannot be taken for granted in simple linear examples either. The latter holds even when cells are considered isolated and devoid of replication capabilities (cell-cycle arrested). We also show how a simple linear adaptation scheme displays fold-change detection properties, and how rupture of ergodicity prevails in scenarios where transitions between protein states are mediated by other molecular species in the system, such as phosphatases and kinases. |
format | Text |
id | pubmed-3049136 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-30491362011-03-17 Stochastic adaptation and fold-change detection: from single-cell to population behavior Marquez-Lago, Tatiana T Leier, André BMC Syst Biol Research Article BACKGROUND: In cell signaling terminology, adaptation refers to a system's capability of returning to its equilibrium upon a transient response. To achieve this, a network has to be both sensitive and precise. Namely, the system must display a significant output response upon stimulation, and later on return to pre-stimulation levels. If the system settles at the exact same equilibrium, adaptation is said to be 'perfect'. Examples of adaptation mechanisms include temperature regulation, calcium regulation and bacterial chemotaxis. RESULTS: We present models of the simplest adaptation architecture, a two-state protein system, in a stochastic setting. Furthermore, we consider differences between individual and collective adaptive behavior, and show how our system displays fold-change detection properties. Our analysis and simulations highlight why adaptation needs to be understood in terms of probability, and not in strict numbers of molecules. Most importantly, selection of appropriate parameters in this simple linear setting may yield populations of cells displaying adaptation, while single cells do not. CONCLUSIONS: Single cell behavior cannot be inferred from population measurements and, sometimes, collective behavior cannot be determined from the individuals. By consequence, adaptation can many times be considered a purely emergent property of the collective system. This is a clear example where biological ergodicity cannot be assumed, just as is also the case when cell replication rates are not homogeneous, or depend on the cell state. Our analysis shows, for the first time, how ergodicity cannot be taken for granted in simple linear examples either. The latter holds even when cells are considered isolated and devoid of replication capabilities (cell-cycle arrested). We also show how a simple linear adaptation scheme displays fold-change detection properties, and how rupture of ergodicity prevails in scenarios where transitions between protein states are mediated by other molecular species in the system, such as phosphatases and kinases. BioMed Central 2011-02-03 /pmc/articles/PMC3049136/ /pubmed/21291524 http://dx.doi.org/10.1186/1752-0509-5-22 Text en Copyright ©2011 Marquez-Lago and Leier; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Marquez-Lago, Tatiana T Leier, André Stochastic adaptation and fold-change detection: from single-cell to population behavior |
title | Stochastic adaptation and fold-change detection: from single-cell to population behavior |
title_full | Stochastic adaptation and fold-change detection: from single-cell to population behavior |
title_fullStr | Stochastic adaptation and fold-change detection: from single-cell to population behavior |
title_full_unstemmed | Stochastic adaptation and fold-change detection: from single-cell to population behavior |
title_short | Stochastic adaptation and fold-change detection: from single-cell to population behavior |
title_sort | stochastic adaptation and fold-change detection: from single-cell to population behavior |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3049136/ https://www.ncbi.nlm.nih.gov/pubmed/21291524 http://dx.doi.org/10.1186/1752-0509-5-22 |
work_keys_str_mv | AT marquezlagotatianat stochasticadaptationandfoldchangedetectionfromsinglecelltopopulationbehavior AT leierandre stochasticadaptationandfoldchangedetectionfromsinglecelltopopulationbehavior |