Chemotactic response and adaptation dynamics in Escherichia coli.
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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2010-05-01
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| Series: | PLoS Computational Biology |
| Online Access: | http://europepmc.org/articles/PMC2873904?pdf=render |
| _version_ | 1830138918359531520 |
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| author | Diana Clausznitzer Olga Oleksiuk Linda Løvdok Victor Sourjik Robert G Endres |
| author_facet | Diana Clausznitzer Olga Oleksiuk Linda Løvdok Victor Sourjik Robert G Endres |
| author_sort | Diana Clausznitzer |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-17T08:34:27Z |
| format | Article |
| id | doaj.art-ba2bc1e54d83485bb33191bc26b21371 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-17T08:34:27Z |
| publishDate | 2010-05-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-ba2bc1e54d83485bb33191bc26b213712022-12-21T21:56:31ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582010-05-0165e100078410.1371/journal.pcbi.1000784Chemotactic response and adaptation dynamics in Escherichia coli.Diana ClausznitzerOlga OleksiukLinda LøvdokVictor SourjikRobert G EndresAdaptation 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.http://europepmc.org/articles/PMC2873904?pdf=render |
| spellingShingle | Diana Clausznitzer Olga Oleksiuk Linda Løvdok Victor Sourjik Robert G Endres Chemotactic response and adaptation dynamics in Escherichia coli. PLoS Computational Biology |
| title | Chemotactic response and adaptation dynamics in Escherichia coli. |
| title_full | Chemotactic response and adaptation dynamics in Escherichia coli. |
| title_fullStr | Chemotactic response and adaptation dynamics in Escherichia coli. |
| title_full_unstemmed | Chemotactic response and adaptation dynamics in Escherichia coli. |
| title_short | Chemotactic response and adaptation dynamics in Escherichia coli. |
| title_sort | chemotactic response and adaptation dynamics in escherichia coli |
| url | http://europepmc.org/articles/PMC2873904?pdf=render |
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