Literature DB >> 27665109

Gene expression noise is affected differentially by feedback in burst frequency and burst size.

Pavol Bokes1, Abhyudai Singh2.   

Abstract

Inside individual cells, expression of genes is stochastic across organisms ranging from bacterial to human cells. A ubiquitous feature of stochastic expression is burst-like synthesis of gene products, which drives considerable intercellular variability in protein levels across an isogenic cell population. One common mechanism by which cells control such stochasticity is negative feedback regulation, where a protein inhibits its own synthesis. For a single gene that is expressed in bursts, negative feedback can affect the burst frequency or the burst size. In order to compare these feedback types, we study a piecewise deterministic model for gene expression of a self-regulating gene. Mathematically tractable steady-state protein distributions are derived and used to compare the noise suppression abilities of the two feedbacks. Results show that in the low noise regime, both feedbacks are similar in term of their noise buffering abilities. Intriguingly, feedback in burst size outperforms the feedback in burst frequency in the high noise regime. Finally, we discuss various regulatory strategies by which cells implement feedback to control burst sizes of expressed proteins at the level of single cells.

Entities:  

Keywords:  Asymptotic approximation of integrals; Negative feedback; Stochastic gene expression

Mesh:

Year:  2016        PMID: 27665109     DOI: 10.1007/s00285-016-1059-4

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  58 in total

1.  Stochasticity in transcriptional regulation: origins, consequences, and mathematical representations.

Authors:  T B Kepler; T C Elston
Journal:  Biophys J       Date:  2001-12       Impact factor: 4.033

2.  Bimodal gene expression in noncooperative regulatory systems.

Authors:  Anna Ochab-Marcinek; Marcin Tabaka
Journal:  Proc Natl Acad Sci U S A       Date:  2010-12-06       Impact factor: 11.205

3.  Regulated degradation is a mechanism for suppressing stochastic fluctuations in gene regulatory networks.

Authors:  Hana El-Samad; Mustafa Khammash
Journal:  Biophys J       Date:  2006-02-24       Impact factor: 4.033

4.  Negative feedback regulation among SR splicing factors encoded by Rbp1 and Rbp1-like in Drosophila.

Authors:  Supriya Kumar; A Javier Lopez
Journal:  EMBO J       Date:  2005-06-16       Impact factor: 11.598

5.  Transient changes in intercellular protein variability identify sources of noise in gene expression.

Authors:  Abhyudai Singh
Journal:  Biophys J       Date:  2014-11-04       Impact factor: 4.033

6.  Transcriptional bursting diversifies the behaviour of a toggle switch: hybrid simulation of stochastic gene expression.

Authors:  Pavol Bokes; John R King; Andrew T A Wood; Matthew Loose
Journal:  Bull Math Biol       Date:  2013-01-25       Impact factor: 1.758

7.  Evolution of gene auto-regulation in the presence of noise.

Authors:  A Singh; J P Hespanha
Journal:  IET Syst Biol       Date:  2009-09       Impact factor: 1.615

8.  Protein copy number distributions for a self-regulating gene in the presence of decoy binding sites.

Authors:  Pavol Bokes; Abhyudai Singh
Journal:  PLoS One       Date:  2015-03-26       Impact factor: 3.240

9.  Hybrid stochastic simplifications for multiscale gene networks.

Authors:  Alina Crudu; Arnaud Debussche; Ovidiu Radulescu
Journal:  BMC Syst Biol       Date:  2009-09-07

10.  The magnitude and colour of noise in genetic negative feedback systems.

Authors:  Margaritis Voliotis; Clive G Bowsher
Journal:  Nucleic Acids Res       Date:  2012-05-11       Impact factor: 16.971

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  5 in total

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5.  Efficient analysis of stochastic gene dynamics in the non-adiabatic regime using piecewise deterministic Markov processes.

Authors:  Yen Ting Lin; Nicolas E Buchler
Journal:  J R Soc Interface       Date:  2018-01       Impact factor: 4.118

  5 in total

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