Literature DB >> 17406083

Positive feedback, stochasticity and genetic competence.

Rajesh Karmakar1, Indrani Bose.   

Abstract

A single gene, regulating its own expression via a positive feedback loop, constitutes a common motif in gene regulatory networks and signalling cascades. Recent experiments on the development of competence in the bacterial population B. subtilis show that the autoregulatory genetic module by itself can give rise to two types of cellular states. The states correspond to the low and high expression states of the master regulator ComK. The high expression state is attained when the ComK protein level exceeds a threshold value leading to a full activation of the autostimulatory loop. Stochasticity in gene expression drives the transitions between the two stable states. In this paper, we explain the appearance of bimodal protein distributions in B. subtilis cell population in the framework of three possible scenarios. In two of the cases, bistability provides the basis for binary gene expression. In the third case, the system is monostable in a deterministic description and stochasticity in gene expression is solely responsible for the appearance of the two expression states.

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Year:  2007        PMID: 17406083     DOI: 10.1088/1478-3975/4/1/004

Source DB:  PubMed          Journal:  Phys Biol        ISSN: 1478-3967            Impact factor:   2.583


  25 in total

1.  Emergent bistability: effects of additive and multiplicative noise.

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3.  Purely stochastic binary decisions in cell signaling models without underlying deterministic bistabilities.

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4.  Molecular level stochastic model for competence cycles in Bacillus subtilis.

Authors:  Daniel Schultz; Eshel Ben Jacob; José N Onuchic; Peter G Wolynes
Journal:  Proc Natl Acad Sci U S A       Date:  2007-10-25       Impact factor: 11.205

5.  Kinetics of genetic switching into the state of bacterial competence.

Authors:  Madeleine Leisner; Jan-Timm Kuhr; Joachim O Rädler; Erwin Frey; Berenike Maier
Journal:  Biophys J       Date:  2009-02       Impact factor: 4.033

6.  Noise-induced regime shifts: A quantitative characterization.

Authors:  Sayantari Ghosh; Amit Kumar Pal; Indrani Bose
Journal:  Eur Phys J E Soft Matter       Date:  2013-10-28       Impact factor: 1.890

7.  Exponential sensitivity of noise-driven switching in genetic networks.

Authors:  Pankaj Mehta; Ranjan Mukhopadhyay; Ned S Wingreen
Journal:  Phys Biol       Date:  2008-06-16       Impact factor: 2.583

8.  Gene expression dynamics in randomly varying environments.

Authors:  Michael W Smiley; Stephen R Proulx
Journal:  J Math Biol       Date:  2009-09-16       Impact factor: 2.259

9.  Origins of binary gene expression in post-transcriptional regulation by microRNAs.

Authors:  I Bose; S Ghosh
Journal:  Eur Phys J E Soft Matter       Date:  2012-10-15       Impact factor: 1.890

10.  Type of noise defines global attractors in bistable molecular regulatory systems.

Authors:  Joanna Jaruszewicz; Pawel J Zuk; Tomasz Lipniacki
Journal:  J Theor Biol       Date:  2012-10-11       Impact factor: 2.691

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