Literature DB >> 18202292

Effects of molecular memory and bursting on fluctuations in gene expression.

Juan M Pedraza1, Johan Paulsson.   

Abstract

Many cellular components are present in such low numbers per cell that random births and deaths of individual molecules can cause substantial "noise" in concentrations. But biochemical events do not necessarily occur in single steps of individual molecules. Some processes are greatly randomized when synthesis or degradation occurs in large bursts of many molecules during a short time interval. Conversely, each birth or death of a macromolecule could involve several small steps, creating a memory between individual events. We present a generalized theory for stochastic gene expression, formulating the variance in protein abundance in terms of the randomness of the individual gene expression events. We show that common types of molecular mechanisms can produce gestation and senescence periods that reduce noise without requiring higher abundances, shorter lifetimes, or any concentration-dependent control loops. We also show that most single-cell experimental methods cannot distinguish between qualitatively different stochastic principles, although this in turn makes such methods better suited for identifying which components introduce fluctuations. Characterizing the random events that give rise to noise in concentrations instead requires dynamic measurements with single-molecule resolution.

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Year:  2008        PMID: 18202292     DOI: 10.1126/science.1144331

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  145 in total

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2.  Analytical distribution and tunability of noise in a model of promoter progress.

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Journal:  Biophys J       Date:  2012-03-20       Impact factor: 4.033

3.  Stochastic expression dynamics of a transcription factor revealed by single-molecule noise analysis.

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4.  The mean and noise of protein numbers in stochastic gene expression.

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Journal:  J Math Biol       Date:  2012-05-26       Impact factor: 2.259

5.  Memories of lost enhancers.

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Journal:  Genes Dev       Date:  2010-05-15       Impact factor: 11.361

Review 6.  Modeling the dynamic behavior of biochemical regulatory networks.

Authors:  John J Tyson; Teeraphan Laomettachit; Pavel Kraikivski
Journal:  J Theor Biol       Date:  2018-11-28       Impact factor: 2.691

7.  Non-genetic heterogeneity from stochastic partitioning at cell division.

Authors:  Dann Huh; Johan Paulsson
Journal:  Nat Genet       Date:  2010-12-26       Impact factor: 38.330

8.  Elongation dynamics shape bursty transcription and translation.

Authors:  Maciej Dobrzynski; Frank J Bruggeman
Journal:  Proc Natl Acad Sci U S A       Date:  2009-02-05       Impact factor: 11.205

Review 9.  Nature, nurture, or chance: stochastic gene expression and its consequences.

Authors:  Arjun Raj; Alexander van Oudenaarden
Journal:  Cell       Date:  2008-10-17       Impact factor: 41.582

10.  Engineering stochasticity in gene expression.

Authors:  Jeffrey J Tabor; Travis S Bayer; Zachary B Simpson; Matthew Levy; Andrew D Ellington
Journal:  Mol Biosyst       Date:  2008-05-01
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