Robust signal processing in living cells.

Cellular signaling networks have evolved an astonishing ability to function reliably and with high fidelity in uncertain environments. A crucial prerequisite for the high precision exhibited by many signaling circuits is their ability to keep the concentrations of active signaling compounds within t...

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Main Authors: Ralf Steuer, Steffen Waldherr, Victor Sourjik, Markus Kollmann
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2011-11-01
Series:PLoS Computational Biology
Online Access:http://europepmc.org/articles/PMC3219616?pdf=render
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spelling doaj-c208dc05a3d8490ba31d4eabc646c10c2020-11-25T01:32:25ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582011-11-01711e100221810.1371/journal.pcbi.1002218Robust signal processing in living cells.Ralf SteuerSteffen WaldherrVictor SourjikMarkus KollmannCellular signaling networks have evolved an astonishing ability to function reliably and with high fidelity in uncertain environments. A crucial prerequisite for the high precision exhibited by many signaling circuits is their ability to keep the concentrations of active signaling compounds within tightly defined bounds, despite strong stochastic fluctuations in copy numbers and other detrimental influences. Based on a simple mathematical formalism, we identify topological organizing principles that facilitate such robust control of intracellular concentrations in the face of multifarious perturbations. Our framework allows us to judge whether a multiple-input-multiple-output reaction network is robust against large perturbations of network parameters and enables the predictive design of perfectly robust synthetic network architectures. Utilizing the Escherichia coli chemotaxis pathway as a hallmark example, we provide experimental evidence that our framework indeed allows us to unravel the topological organization of robust signaling. We demonstrate that the specific organization of the pathway allows the system to maintain global concentration robustness of the diffusible response regulator CheY with respect to several dominant perturbations. Our framework provides a counterpoint to the hypothesis that cellular function relies on an extensive machinery to fine-tune or control intracellular parameters. Rather, we suggest that for a large class of perturbations, there exists an appropriate topology that renders the network output invariant to the respective perturbations.http://europepmc.org/articles/PMC3219616?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Ralf Steuer
Steffen Waldherr
Victor Sourjik
Markus Kollmann
spellingShingle Ralf Steuer
Steffen Waldherr
Victor Sourjik
Markus Kollmann
Robust signal processing in living cells.
PLoS Computational Biology
author_facet Ralf Steuer
Steffen Waldherr
Victor Sourjik
Markus Kollmann
author_sort Ralf Steuer
title Robust signal processing in living cells.
title_short Robust signal processing in living cells.
title_full Robust signal processing in living cells.
title_fullStr Robust signal processing in living cells.
title_full_unstemmed Robust signal processing in living cells.
title_sort robust signal processing in living cells.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2011-11-01
description Cellular signaling networks have evolved an astonishing ability to function reliably and with high fidelity in uncertain environments. A crucial prerequisite for the high precision exhibited by many signaling circuits is their ability to keep the concentrations of active signaling compounds within tightly defined bounds, despite strong stochastic fluctuations in copy numbers and other detrimental influences. Based on a simple mathematical formalism, we identify topological organizing principles that facilitate such robust control of intracellular concentrations in the face of multifarious perturbations. Our framework allows us to judge whether a multiple-input-multiple-output reaction network is robust against large perturbations of network parameters and enables the predictive design of perfectly robust synthetic network architectures. Utilizing the Escherichia coli chemotaxis pathway as a hallmark example, we provide experimental evidence that our framework indeed allows us to unravel the topological organization of robust signaling. We demonstrate that the specific organization of the pathway allows the system to maintain global concentration robustness of the diffusible response regulator CheY with respect to several dominant perturbations. Our framework provides a counterpoint to the hypothesis that cellular function relies on an extensive machinery to fine-tune or control intracellular parameters. Rather, we suggest that for a large class of perturbations, there exists an appropriate topology that renders the network output invariant to the respective perturbations.
url http://europepmc.org/articles/PMC3219616?pdf=render
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