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  Robust signal processing in living cells

Steuer, R., Waldherr, S., Sourjik, V., & Kollmann, M. (2012). Robust signal processing in living cells. PLoS Comput Biol, 7(11), e1002218. doi:10.1371/journal.pcbi.1002218.

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Steuer, R., Author
Waldherr, S., Author
Sourjik, V.1, Author           
Kollmann, M., Author
Affiliations:
1Center for Molecular Biology of University Heidelberg, DKFZ-ZMBH Alliance, Heidelberg, ou_persistent22              

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Free keywords: Bacterial Proteins/physiology Cell Communication/physiology Chemotaxis/physiology Escherichia coli/*physiology Escherichia coli Proteins Membrane Proteins/physiology Methyl-Accepting Chemotaxis Proteins *Models, Biological Signal Transduction/*physiology Systems Biology
 Abstract: 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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 Dates: 2012-01-05
 Publication Status: Issued
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 Identifiers: Other: 22215991
DOI: 10.1371/journal.pcbi.1002218
ISSN: 1553-7358 (Electronic)1553-734X (Linking)
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Title: PLoS Comput Biol
Source Genre: Journal
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Pages: - Volume / Issue: 7 (11) Sequence Number: - Start / End Page: e1002218 Identifier: -