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  Chemotactic response and adaptation dynamics in Escherichia coli

Clausznitzer, D., Oleksiuk, O., Lovdok, L., Sourjik, V., & Endres, R. G. (2010). Chemotactic response and adaptation dynamics in Escherichia coli. PLoS Comput Biol, 6(5), e1000784. doi:10.1371/journal.pcbi.1000784.

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Clausznitzer, D., Author
Oleksiuk, O., Author
Lovdok, L., Author
Sourjik, V.1, Author           
Endres, R. G., Author
Affiliations:
1Zentrum für Molekulare Biologie der Universität Heidelberg, DKFZ-ZMBH Alliance, Heidelberg, ou_persistent22              

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Free keywords: Adaptation, Physiological/*physiology Chemotaxis/*physiology Chi-Square Distribution DNA Methylation Dose-Response Relationship, Drug Escherichia coli/*physiology *Models, Biological Phosphorylation Signal Transduction Systems Biology/*methods Thermodynamics
 Abstract: Adaptation of the chemotaxis sensory pathway of the bacterium Escherichia coli is integral for detecting chemicals over a wide range of background concentrations, ultimately allowing cells to swim towards sources of attractant and away from repellents. Its biochemical mechanism based on methylation and demethylation of chemoreceptors has long been known. Despite the importance of adaptation for cell memory and behavior, the dynamics of adaptation are difficult to reconcile with current models of precise adaptation. Here, we follow time courses of signaling in response to concentration step changes of attractant using in vivo fluorescence resonance energy transfer measurements. Specifically, we use a condensed representation of adaptation time courses for efficient evaluation of different adaptation models. To quantitatively explain the data, we finally develop a dynamic model for signaling and adaptation based on the attractant flow in the experiment, signaling by cooperative receptor complexes, and multiple layers of feedback regulation for adaptation. We experimentally confirm the predicted effects of changing the enzyme-expression level and bypassing the negative feedback for demethylation. Our data analysis suggests significant imprecision in adaptation for large additions. Furthermore, our model predicts highly regulated, ultrafast adaptation in response to removal of attractant, which may be useful for fast reorientation of the cell and noise reduction in adaptation.

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 Dates: 2010-05-27
 Publication Status: Issued
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 Identifiers: Other: 20502674
DOI: 10.1371/journal.pcbi.1000784
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: 6 (5) Sequence Number: - Start / End Page: e1000784 Identifier: -