Literature DB >> 17339063

Co-expression of signaling proteins improves robustness of the bacterial chemotaxis pathway.

Linda Løvdok1, Markus Kollmann, Victor Sourjik.   

Abstract

Biological systems are exposed to various perturbations that affect performance of the cellular networks, with stochastic variation in protein levels, or gene expression noise, being one of the major sources of intracellular perturbations. We recently used Escherichia coli chemotaxis as a model to analyze robustness against such noise and demonstrated theoretically and experimentally that a steady-state output of the pathway is robust against concerted variation in the levels of all chemotaxis proteins. However, our model predicted that the pathway topology does not confer much robustness against an uncorrelated variation in the protein levels. To test whether additional robustness features might be missing from our model, we compare here its predictions with an experimentally determined chemotactic performance under varying levels of individual proteins. Our data show that the pathway is indeed even more robust than predicted to two types of perturbations-the variation in the levels of the adaptation enzymes and a correlated expression of CheY and CheZ. Although the design features that are responsible for this higher robustness still remain to be understood, our results stress the importance of a robust design of both native and synthetic signaling networks.

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Year:  2007        PMID: 17339063     DOI: 10.1016/j.jbiotec.2007.01.024

Source DB:  PubMed          Journal:  J Biotechnol        ISSN: 0168-1656            Impact factor:   3.307


  18 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.  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

3.  Environment determines evolutionary trajectory in a constrained phenotypic space.

Authors:  David T Fraebel; Harry Mickalide; Diane Schnitkey; Jason Merritt; Thomas E Kuhlman; Seppe Kuehn
Journal:  Elife       Date:  2017-03-27       Impact factor: 8.140

4.  An agent-based model of signal transduction in bacterial chemotaxis.

Authors:  Jameson Miller; Miles Parker; Robert B Bourret; Morgan C Giddings
Journal:  PLoS One       Date:  2010-05-13       Impact factor: 3.240

5.  A "trimer of dimers"-based model for the chemotactic signal transduction network in bacterial chemotaxis.

Authors:  Xiangrong Xin; Hans G Othmer
Journal:  Bull Math Biol       Date:  2012-08-04       Impact factor: 1.758

6.  Role of translational coupling in robustness of bacterial chemotaxis pathway.

Authors:  Linda Løvdok; Kajetan Bentele; Nikita Vladimirov; Anette Müller; Ferencz S Pop; Dirk Lebiedz; Markus Kollmann; Victor Sourjik
Journal:  PLoS Biol       Date:  2009-08-18       Impact factor: 8.029

Review 7.  Behavioral Variability and Phenotypic Diversity in Bacterial Chemotaxis.

Authors:  Adam James Waite; Nicholas W Frankel; Thierry Emonet
Journal:  Annu Rev Biophys       Date:  2018-04-04       Impact factor: 12.981

8.  Independence and interdependence of Dif and Frz chemosensory pathways in Myxococcus xanthus chemotaxis.

Authors:  Qian Xu; Wesley P Black; C Linn Cadieux; Zhaomin Yang
Journal:  Mol Microbiol       Date:  2008-06-28       Impact factor: 3.501

9.  Effects of receptor modification and temperature on dynamics of sensory complexes in Escherichia coli chemotaxis.

Authors:  Sonja Schulmeister; Karin Grosse; Victor Sourjik
Journal:  BMC Microbiol       Date:  2011-10-06       Impact factor: 3.605

10.  Deciphering chemotaxis pathways using cross species comparisons.

Authors:  Rebecca Hamer; Pao-Yang Chen; Judith P Armitage; Gesine Reinert; Charlotte M Deane
Journal:  BMC Syst Biol       Date:  2010-01-11
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