Literature DB >> 21943414

Landscape, flux, correlation, resonance, coherence, stability, and key network wirings of stochastic circadian oscillation.

Chunhe Li1, Erkang Wang, Jin Wang.   

Abstract

Circadian rhythms with a period of ~24 h, are natural timing machines. They are broadly distributed in living organisms, such as Neurospora, Drosophila, and mammals. The underlying natures of the rhythmic behavior have been explored by experimental and theoretical approaches. However, the global and physical natures of the oscillation under fluctuations are still not very clear. We developed a landscape and flux framework to explore the global stability and robustness of a circadian oscillation system. The potential landscape of the network is uncovered and has a global Mexican-hat shape. The height of the Mexican-hat provides a quantitative measure to evaluate the robustness and coherence of the oscillation. We found that in nonequilibrium dynamic systems, not only the potential landscape but also the probability flux are important to the dynamics of the system under intrinsic noise. Landscape attracts the systems down to the oscillation ring while flux drives the coherent oscillation on the ring. We also investigated the phase coherence and the entropy production rate of the system at different fluctuations and found that dissipations are less and the coherence is higher for larger number of molecules. We also found that the power spectrum of autocorrelation functions show resonance peak at the frequency of coherent oscillations. The peak is less prominent for smaller number of molecules and less barrier height and therefore can be used as another measure of stability of oscillations. As a consequence of nonzero probability flux, we show that the three-point correlations from the time traces show irreversibility, providing a possible way to explore the flux from the observations. Furthermore, we explored the escape time from the oscillation ring to outside at different molecular number. We found that when barrier height is higher, escape time is longer and phase coherence of oscillation is higher. Finally, we performed the global sensitivity analysis of the underlying parameters to find the key network wirings responsible for the stability of the oscillation system.
Copyright © 2011 Biophysical Society. Published by Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21943414      PMCID: PMC3177066          DOI: 10.1016/j.bpj.2011.08.012

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


  25 in total

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Journal:  Proc Natl Acad Sci U S A       Date:  2010-04-14       Impact factor: 11.205

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Review 9.  Modeling network dynamics: the lac operon, a case study.

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  8 in total

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Journal:  Biophys J       Date:  2012-03-06       Impact factor: 4.033

2.  Eddy current and coupled landscapes for nonadiabatic and nonequilibrium complex system dynamics.

Authors:  Kun Zhang; Masaki Sasai; Jin Wang
Journal:  Proc Natl Acad Sci U S A       Date:  2013-08-26       Impact factor: 11.205

3.  Landscape and flux reveal a new global view and physical quantification of mammalian cell cycle.

Authors:  Chunhe Li; Jin Wang
Journal:  Proc Natl Acad Sci U S A       Date:  2014-09-16       Impact factor: 11.205

4.  On the dephasing of genetic oscillators.

Authors:  Davit A Potoyan; Peter G Wolynes
Journal:  Proc Natl Acad Sci U S A       Date:  2014-01-27       Impact factor: 11.205

5.  Discrete and continuous models of probability flux of switching dynamics: Uncovering stochastic oscillations in a toggle-switch system.

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Journal:  J Chem Phys       Date:  2019-11-14       Impact factor: 3.488

6.  Quantifying the flux as the driving force for nonequilibrium dynamics and thermodynamics in non-Michaelis-Menten enzyme kinetics.

Authors:  Qiong Liu; Jin Wang
Journal:  Proc Natl Acad Sci U S A       Date:  2019-12-26       Impact factor: 11.205

7.  Role of ATP Hydrolysis in Cyanobacterial Circadian Oscillator.

Authors:  Sumita Das; Tomoki P Terada; Masaki Sasai
Journal:  Sci Rep       Date:  2017-12-12       Impact factor: 4.379

8.  Nonequilibrium Enhances Adaptation Efficiency of Stochastic Biochemical Systems.

Authors:  Chen Jia; Minping Qian
Journal:  PLoS One       Date:  2016-05-19       Impact factor: 3.240

  8 in total

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