Literature DB >> 18299569

Relationship between cellular response and behavioral variability in bacterial chemotaxis.

Thierry Emonet1, Philippe Cluzel.   

Abstract

Over the last decades, bacterial chemotaxis in Escherichia coli has emerged as a canonical system for the study of signal transduction. A remarkable feature of this system is the coexistence of a robust adaptive behavior observed at the population level with a large fluctuating behavior in single cells [Korobkova E, Emonet T, Vilar JMG, Shimizu TS, Cluzel P (2004) Nature 428:574-578]. Using a unified stochastic model, we demonstrate that this coexistence is not fortuitous but a direct consequence of the architecture of this adaptive system. The methylation and demethylation cycles that regulate the activity of receptor-kinase complexes are ultrasensitive because they operate outside the region of first-order kinetics. As a result, the receptor-kinase that governs cellular behavior exhibits a sigmoidal activation curve. We propose that the steepness of this kinase activation curve simultaneously controls the behavioral variability in nonstimulated individual bacteria and the duration of the adaptive response to small stimuli. We predict that the fluctuating behavior and the chemotactic response of individual cells both peak within the transition region of this sigmoidal curve. Large-scale simulations of digital bacteria suggest that the chemotaxis network is tuned to simultaneously maximize both the random spread of cells in the absence of nutrients and the cellular response to gradients of attractant. This study highlights a fundamental relation from which the behavioral variability of nonstimulated cells is used to infer the timing of the cellular response to small stimuli.

Entities:  

Mesh:

Substances:

Year:  2008        PMID: 18299569      PMCID: PMC2265172          DOI: 10.1073/pnas.0705463105

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  42 in total

1.  Heightened sensitivity of a lattice of membrane receptors.

Authors:  T A Duke; D Bray
Journal:  Proc Natl Acad Sci U S A       Date:  1999-08-31       Impact factor: 11.205

2.  An allosteric model for heterogeneous receptor complexes: understanding bacterial chemotaxis responses to multiple stimuli.

Authors:  Bernardo A Mello; Yuhai Tu
Journal:  Proc Natl Acad Sci U S A       Date:  2005-11-17       Impact factor: 11.205

3.  Adaptational assistance in clusters of bacterial chemoreceptors.

Authors:  Mingshan Li; Gerald L Hazelbauer
Journal:  Mol Microbiol       Date:  2005-06       Impact factor: 3.501

4.  Physical limits to biochemical signaling.

Authors:  William Bialek; Sima Setayeshgar
Journal:  Proc Natl Acad Sci U S A       Date:  2005-07-08       Impact factor: 11.205

5.  Chemosensing in Escherichia coli: two regimes of two-state receptors.

Authors:  Juan E Keymer; Robert G Endres; Monica Skoge; Yigal Meir; Ned S Wingreen
Journal:  Proc Natl Acad Sci U S A       Date:  2006-01-30       Impact factor: 11.205

6.  Precise adaptation in bacterial chemotaxis through "assistance neighborhoods".

Authors:  Robert G Endres; Ned S Wingreen
Journal:  Proc Natl Acad Sci U S A       Date:  2006-08-21       Impact factor: 11.205

7.  Noise propagation in gene networks.

Authors:  Juan M Pedraza; Alexander van Oudenaarden
Journal:  Science       Date:  2005-03-25       Impact factor: 47.728

8.  Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise.

Authors:  John R S Newman; Sina Ghaemmaghami; Jan Ihmels; David K Breslow; Matthew Noble; Joseph L DeRisi; Jonathan S Weissman
Journal:  Nature       Date:  2006-05-14       Impact factor: 49.962

9.  Gene network shaping of inherent noise spectra.

Authors:  D W Austin; M S Allen; J M McCollum; R D Dar; J R Wilgus; G S Sayler; N F Samatova; C D Cox; M L Simpson
Journal:  Nature       Date:  2006-02-02       Impact factor: 49.962

10.  Optimal noise filtering in the chemotactic response of Escherichia coli.

Authors:  Burton W Andrews; Tau-Mu Yi; Pablo A Iglesias
Journal:  PLoS Comput Biol       Date:  2006-10-05       Impact factor: 4.475

View more
  53 in total

Review 1.  Responding to chemical gradients: bacterial chemotaxis.

Authors:  Victor Sourjik; Ned S Wingreen
Journal:  Curr Opin Cell Biol       Date:  2011-12-09       Impact factor: 8.382

2.  Stochastic coordination of multiple actuators reduces latency and improves chemotactic response in bacteria.

Authors:  Michael W Sneddon; William Pontius; Thierry Emonet
Journal:  Proc Natl Acad Sci U S A       Date:  2011-12-27       Impact factor: 11.205

Review 3.  Spatial organization in bacterial chemotaxis.

Authors:  Victor Sourjik; Judith P Armitage
Journal:  EMBO J       Date:  2010-08-18       Impact factor: 11.598

4.  Interdependence of behavioural variability and response to small stimuli in bacteria.

Authors:  Heungwon Park; William Pontius; Calin C Guet; John F Marko; Thierry Emonet; Philippe Cluzel
Journal:  Nature       Date:  2010-11-14       Impact factor: 49.962

Review 5.  Bacterial protein networks: properties and functions.

Authors:  Athanasios Typas; Victor Sourjik
Journal:  Nat Rev Microbiol       Date:  2015-08-10       Impact factor: 60.633

6.  Fine-tuning of chemotactic response in E. coli determined by high-throughput capillary assay.

Authors:  Heungwon Park; Calin C Guet; Thierry Emonet; Philippe Cluzel
Journal:  Curr Microbiol       Date:  2010-10-24       Impact factor: 2.188

7.  Bacterial strategies for chemotaxis response.

Authors:  Antonio Celani; Massimo Vergassola
Journal:  Proc Natl Acad Sci U S A       Date:  2010-01-04       Impact factor: 11.205

8.  Modeling the chemotactic response of Escherichia coli to time-varying stimuli.

Authors:  Yuhai Tu; Thomas S Shimizu; Howard C Berg
Journal:  Proc Natl Acad Sci U S A       Date:  2008-09-23       Impact factor: 11.205

9.  Reverse engineering of bacterial chemotaxis pathway via frequency domain analysis.

Authors:  Junjie Luo; Jun Wang; Ting Martin Ma; Zhirong Sun
Journal:  PLoS One       Date:  2010-03-09       Impact factor: 3.240

10.  Quantitative modeling of Escherichia coli chemotactic motion in environments varying in space and time.

Authors:  Lili Jiang; Qi Ouyang; Yuhai Tu
Journal:  PLoS Comput Biol       Date:  2010-04-08       Impact factor: 4.475

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.