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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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Detalles Bibliográficos
Autores principales: Steuer, Ralf, Waldherr, Steffen, Sourjik, Victor, Kollmann, Markus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3219616/
https://www.ncbi.nlm.nih.gov/pubmed/22215991
http://dx.doi.org/10.1371/journal.pcbi.1002218
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author Steuer, Ralf
Waldherr, Steffen
Sourjik, Victor
Kollmann, Markus
author_facet Steuer, Ralf
Waldherr, Steffen
Sourjik, Victor
Kollmann, Markus
author_sort Steuer, Ralf
collection PubMed
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.
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spelling pubmed-32196162012-01-03 Robust Signal Processing in Living Cells Steuer, Ralf Waldherr, Steffen Sourjik, Victor Kollmann, Markus PLoS Comput Biol Research Article 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. Public Library of Science 2011-11-17 /pmc/articles/PMC3219616/ /pubmed/22215991 http://dx.doi.org/10.1371/journal.pcbi.1002218 Text en Steuer et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Steuer, Ralf
Waldherr, Steffen
Sourjik, Victor
Kollmann, Markus
Robust Signal Processing in Living Cells
title 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_short Robust Signal Processing in Living Cells
title_sort robust signal processing in living cells
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3219616/
https://www.ncbi.nlm.nih.gov/pubmed/22215991
http://dx.doi.org/10.1371/journal.pcbi.1002218
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