Literature DB >> 19289068

Logarithmic sensing in Escherichia coli bacterial chemotaxis.

Yevgeniy V Kalinin1, Lili Jiang, Yuhai Tu, Mingming Wu.   

Abstract

We studied the response of swimming Escherichia coli (E. coli) bacteria in a comprehensive set of well-controlled chemical concentration gradients using a newly developed microfluidic device and cell tracking imaging technique. In parallel, we carried out a multi-scale theoretical modeling of bacterial chemotaxis taking into account the relevant internal signaling pathway dynamics, and predicted bacterial chemotactic responses at the cellular level. By measuring the E. coli cell density profiles across the microfluidic channel at various spatial gradients of ligand concentration grad[L] and the average ligand concentration [L] near the peak chemotactic response region, we demonstrated unambiguously in both experiments and model simulation that the mean chemotactic drift velocity of E. coli cells increased monotonically with grad [L]/[L] or approximately grad(log[L])--that is E. coli cells sense the spatial gradient of the logarithmic ligand concentration. The exact range of the log-sensing regime was determined. The agreements between the experiments and the multi-scale model simulation verify the validity of the theoretical model, and revealed that the key microscopic mechanism for logarithmic sensing in bacterial chemotaxis is the adaptation kinetics, in contrast to explanations based directly on ligand occupancy.

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Year:  2009        PMID: 19289068      PMCID: PMC2989150          DOI: 10.1016/j.bpj.2008.10.027

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  42 in total

Review 1.  Transmembrane signaling in bacterial chemoreceptors.

Authors:  J J Falke; G L Hazelbauer
Journal:  Trends Biochem Sci       Date:  2001-04       Impact factor: 13.807

2.  An ultrasensitive bacterial motor revealed by monitoring signaling proteins in single cells.

Authors:  P Cluzel; M Surette; S Leibler
Journal:  Science       Date:  2000-03-03       Impact factor: 47.728

Review 3.  How signals are heard during bacterial chemotaxis: protein-protein interactions in sensory signal propagation.

Authors:  A Bren; M Eisenbach
Journal:  J Bacteriol       Date:  2000-12       Impact factor: 3.490

4.  Receptor sensitivity in bacterial chemotaxis.

Authors:  Victor Sourjik; Howard C Berg
Journal:  Proc Natl Acad Sci U S A       Date:  2001-12-11       Impact factor: 11.205

5.  STOCHSIM: modelling of stochastic biomolecular processes.

Authors:  N Le Novère; T S Shimizu
Journal:  Bioinformatics       Date:  2001-06       Impact factor: 6.937

6.  Localization of components of the chemotaxis machinery of Escherichia coli using fluorescent protein fusions.

Authors:  V Sourjik; H C Berg
Journal:  Mol Microbiol       Date:  2000-08       Impact factor: 3.501

7.  A sensitive, versatile microfluidic assay for bacterial chemotaxis.

Authors:  Hanbin Mao; Paul S Cremer; Michael D Manson
Journal:  Proc Natl Acad Sci U S A       Date:  2003-04-18       Impact factor: 11.205

8.  Perfect and near-perfect adaptation in a model of bacterial chemotaxis.

Authors:  Bernardo A Mello; Yuhai Tu
Journal:  Biophys J       Date:  2003-05       Impact factor: 4.033

9.  Assessing neural stem cell motility using an agarose gel-based microfluidic device.

Authors:  Kevin Wong; Angel Ayuso-Sacido; Patrick Ahyow; Andrew Darling; John A Boockvar; Mingming Wu
Journal:  J Vis Exp       Date:  2008-02-11       Impact factor: 1.355

10.  Quantitative modeling of sensitivity in bacterial chemotaxis: the role of coupling among different chemoreceptor species.

Authors:  Bernardo A Mello; Yuhai Tu
Journal:  Proc Natl Acad Sci U S A       Date:  2003-06-25       Impact factor: 12.779

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  70 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

3.  Fold-change detection and scalar symmetry of sensory input fields.

Authors:  Oren Shoval; Lea Goentoro; Yuval Hart; Avi Mayo; Eduardo Sontag; Uri Alon
Journal:  Proc Natl Acad Sci U S A       Date:  2010-08-20       Impact factor: 11.205

Review 4.  Live from under the lens: exploring microbial motility with dynamic imaging and microfluidics.

Authors:  Kwangmin Son; Douglas R Brumley; Roman Stocker
Journal:  Nat Rev Microbiol       Date:  2015-12       Impact factor: 60.633

5.  Physical limits on bacterial navigation in dynamic environments.

Authors:  Andrew M Hein; Douglas R Brumley; Francesco Carrara; Roman Stocker; Simon A Levin
Journal:  J R Soc Interface       Date:  2016-01       Impact factor: 4.118

6.  The Aerotactic Response of Caulobacter crescentus.

Authors:  Michael Morse; Remy Colin; Laurence G Wilson; Jay X Tang
Journal:  Biophys J       Date:  2016-05-10       Impact factor: 4.033

7.  Directional persistence of chemotactic bacteria in a traveling concentration wave.

Authors:  J Saragosti; V Calvez; N Bournaveas; B Perthame; A Buguin; P Silberzan
Journal:  Proc Natl Acad Sci U S A       Date:  2011-09-14       Impact factor: 11.205

Review 8.  Microfluidics expanding the frontiers of microbial ecology.

Authors:  Roberto Rusconi; Melissa Garren; Roman Stocker
Journal:  Annu Rev Biophys       Date:  2014       Impact factor: 12.981

Review 9.  Quantitative modeling of bacterial chemotaxis: signal amplification and accurate adaptation.

Authors:  Yuhai Tu
Journal:  Annu Rev Biophys       Date:  2013-02-28       Impact factor: 12.981

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

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