Literature DB >> 11972055

Mechanisms of noise-resistance in genetic oscillators.

José M G Vilar1, Hao Yuan Kueh, Naama Barkai, Stanislas Leibler.   

Abstract

A wide range of organisms use circadian clocks to keep internal sense of daily time and regulate their behavior accordingly. Most of these clocks use intracellular genetic networks based on positive and negative regulatory elements. The integration of these "circuits" at the cellular level imposes strong constraints on their functioning and design. Here, we study a recently proposed model [Barkai, N. & Leibler, S. (2000) Nature (London), 403, 267-268] that incorporates just the essential elements found experimentally. We show that this type of oscillator is driven mainly by two elements: the concentration of a repressor protein and the dynamics of an activator protein forming an inactive complex with the repressor. Thus, the clock does not need to rely on mRNA dynamics to oscillate, which makes it especially resistant to fluctuations. Oscillations can be present even when the time average of the number of mRNA molecules goes below one. Under some conditions, this oscillator is not only resistant to but, paradoxically, also enhanced by the intrinsic biochemical noise.

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Year:  2002        PMID: 11972055      PMCID: PMC122889          DOI: 10.1073/pnas.092133899

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


  7 in total

1.  Circadian clocks limited by noise.

Authors:  N Barkai; S Leibler
Journal:  Nature       Date:  2000-01-20       Impact factor: 49.962

2.  Noise suppression by noise.

Authors:  J M Vilar; J M Rubí
Journal:  Phys Rev Lett       Date:  2001-02-05       Impact factor: 9.161

Review 3.  It's a noisy business! Genetic regulation at the nanomolar scale.

Authors:  H H McAdams; A Arkin
Journal:  Trends Genet       Date:  1999-02       Impact factor: 11.639

4.  Random signal fluctuations can reduce random fluctuations in regulated components of chemical regulatory networks.

Authors:  J Paulsson; M Ehrenberg
Journal:  Phys Rev Lett       Date:  2000-06-05       Impact factor: 9.161

Review 5.  Molecular bases for circadian clocks.

Authors:  J C Dunlap
Journal:  Cell       Date:  1999-01-22       Impact factor: 41.582

6.  A model for circadian rhythms in Drosophila incorporating the formation of a complex between the PER and TIM proteins.

Authors:  J C Leloup; A Goldbeter
Journal:  J Biol Rhythms       Date:  1998-02       Impact factor: 3.182

7.  Modeling circadian oscillations with interlocking positive and negative feedback loops.

Authors:  P Smolen; D A Baxter; J H Byrne
Journal:  J Neurosci       Date:  2001-09-01       Impact factor: 6.167

  7 in total
  122 in total

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Journal:  Biophys J       Date:  2003-01       Impact factor: 4.033

2.  Fast evaluation of fluctuations in biochemical networks with the linear noise approximation.

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Journal:  Genome Res       Date:  2003-11       Impact factor: 9.043

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Journal:  Genome Res       Date:  2003-11       Impact factor: 9.043

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Journal:  Biophys J       Date:  2004-07       Impact factor: 4.033

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Authors:  Jordi Garcia-Ojalvo; Michael B Elowitz; Steven H Strogatz
Journal:  Proc Natl Acad Sci U S A       Date:  2004-07-15       Impact factor: 11.205

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Journal:  Biophys J       Date:  2004-08       Impact factor: 4.033

7.  Fluorescence correlation spectroscopy with high-order and dual-color correlation to probe nonequilibrium steady states.

Authors:  Hong Qian; Elliot L Elson
Journal:  Proc Natl Acad Sci U S A       Date:  2004-02-17       Impact factor: 11.205

8.  A pathwise derivative approach to the computation of parameter sensitivities in discrete stochastic chemical systems.

Authors:  Patrick W Sheppard; Muruhan Rathinam; Mustafa Khammash
Journal:  J Chem Phys       Date:  2012-01-21       Impact factor: 3.488

9.  A data-integrated method for analyzing stochastic biochemical networks.

Authors:  Michael W Chevalier; Hana El-Samad
Journal:  J Chem Phys       Date:  2011-12-07       Impact factor: 3.488

Review 10.  Use of virtual cell in studies of cellular dynamics.

Authors:  Boris M Slepchenko; Leslie M Loew
Journal:  Int Rev Cell Mol Biol       Date:  2010       Impact factor: 6.813

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