Literature DB >> 35035514

Escherichia coli chemotaxis is information limited.

H H Mattingly1,2, K Kamino1,2, B B Machta3,4, T Emonet1,2,3.   

Abstract

Organisms acquire and use information from their environment to guide their behaviour. However, it is unclear whether this information quantitatively limits their behavioural performance. Here, we relate information to the ability of Escherichia coli to navigate up chemical gradients, the behaviour known as chemotaxis. First, we derive a theoretical limit on the speed with which cells climb gradients, given the rate at which they acquire information. Next, we measure cells' gradient-climbing speeds and the rate of information acquisition by their chemotaxis signaling pathway. We find that E. coli make behavioural decisions with much less than the one bit required to determine whether they are swimming up-gradient. Some of this information is irrelevant to gradient climbing, and some is lost in communication to behaviour. Despite these limitations, E. coli climb gradients at speeds within a factor of two of the theoretical bound. Thus, information can limit the performance of an organism, and sensory-motor pathways may have evolved to efficiently use information acquired from the environment.

Entities:  

Year:  2021        PMID: 35035514      PMCID: PMC8758097          DOI: 10.1038/s41567-021-01380-3

Source DB:  PubMed          Journal:  Nat Phys        ISSN: 1745-2473            Impact factor:   19.684


  68 in total

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5.  Behavior of information flow near criticality.

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Journal:  Phys Rev E       Date:  2021-01       Impact factor: 2.529

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7.  A modular gradient-sensing network for chemotaxis in Escherichia coli revealed by responses to time-varying stimuli.

Authors:  Thomas S Shimizu; Yuhai Tu; Howard C Berg
Journal:  Mol Syst Biol       Date:  2010-06-22       Impact factor: 11.429

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Journal:  Nat Phys       Date:  2012-03-25       Impact factor: 20.034

9.  Feedback between motion and sensation provides nonlinear boost in run-and-tumble navigation.

Authors:  Junjiajia Long; Steven W Zucker; Thierry Emonet
Journal:  PLoS Comput Biol       Date:  2017-03-06       Impact factor: 4.475

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Authors:  Gabriele Micali; Robert G Endres
Journal:  Sci Rep       Date:  2019-11-15       Impact factor: 4.379

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  4 in total

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  4 in total

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