Literature DB >> 17179490

From fluctuations to phenotypes: the physiology of noise.

Michael S Samoilov1, Gavin Price, Adam P Arkin.   

Abstract

There are fundamental physical reasons why biochemical processes might be subject to noise and stochastic fluctuations. Indeed, it has long been understood that random molecular-scale mechanisms, such as those that drive genetic mutation, lie at the heart of population-scale evolutionary dynamics. What we can now appreciate is how stochastic fluctuations inherent in biochemical processes contribute to cellular and organismal phenotypes. Advancements in techniques for empirically measuring single cells and in corresponding theoretical methods have enabled the rigorous design and interpretation of experiments that provide incontrovertible proof that there are important endogenous sources of stochasticity that drive biological processes at the scale of individual organisms. Recently, some studies have progressed beyond merely ascertaining the presence of noise in biological systems; they trace its role in cellular physiology as it is passed through and processed by the biomolecular pathways-from the underlying origins of stochastic fluctuations in random biomolecular interactions to their ultimate manifestations in characteristic species phenotypes. These emerging results suggest new biological network design principles that account for a constructive role played by noise in defining the structure, function, and fitness of biological systems. They further show that stochastic mechanisms open novel classes of regulatory, signaling, and organizational choices that can serve as efficient and effective biological solutions to problems that are more complex, less robust, or otherwise suboptimal to deal with in the context of purely deterministic systems. Research in Drosophila melanogaster eye color-vision development and Bacillus subtilis competence induction has elegantly traced the role of noise in vital physiological processes from fluctuations to phenotypes, and is used here to highlight these developments.

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Year:  2006        PMID: 17179490     DOI: 10.1126/stke.3662006re17

Source DB:  PubMed          Journal:  Sci STKE        ISSN: 1525-8882


  38 in total

1.  Stochastic steady state gain in a gene expression process with mRNA degradation control.

Authors:  Hiroyuki Kuwahara; Russell Schwartz
Journal:  J R Soc Interface       Date:  2012-01-11       Impact factor: 4.118

2.  Stochastic variation: from single cells to superorganisms.

Authors:  Maria L Kilfoil; Paul Lasko; Ehab Abouheif
Journal:  HFSP J       Date:  2009-10-09

3.  Negative autoregulation linearizes the dose-response and suppresses the heterogeneity of gene expression.

Authors:  Dmitry Nevozhay; Rhys M Adams; Kevin F Murphy; Kresimir Josic; Gábor Balázsi
Journal:  Proc Natl Acad Sci U S A       Date:  2009-03-11       Impact factor: 11.205

Review 4.  Analytic approaches to stochastic gene expression in multicellular systems.

Authors:  Alistair Nicol Boettiger
Journal:  Biophys J       Date:  2013-12-17       Impact factor: 4.033

5.  Temperature control of fimbriation circuit switch in uropathogenic Escherichia coli: quantitative analysis via automated model abstraction.

Authors:  Hiroyuki Kuwahara; Chris J Myers; Michael S Samoilov
Journal:  PLoS Comput Biol       Date:  2010-03-26       Impact factor: 4.475

6.  HIV promoter integration site primarily modulates transcriptional burst size rather than frequency.

Authors:  Ron Skupsky; John C Burnett; Jonathan E Foley; David V Schaffer; Adam P Arkin
Journal:  PLoS Comput Biol       Date:  2010-09-30       Impact factor: 4.475

7.  Transcriptional infidelity promotes heritable phenotypic change in a bistable gene network.

Authors:  Alasdair J E Gordon; Jennifer A Halliday; Matthew D Blankschien; Philip A Burns; Fumio Yatagai; Christophe Herman
Journal:  PLoS Biol       Date:  2009-02-24       Impact factor: 8.029

8.  Predicting phenotypic diversity and the underlying quantitative molecular transitions.

Authors:  Claudiu A Giurumescu; Paul W Sternberg; Anand R Asthagiri
Journal:  PLoS Comput Biol       Date:  2009-04-10       Impact factor: 4.475

9.  Genomic analysis reveals a tight link between transcription factor dynamics and regulatory network architecture.

Authors:  Raja Jothi; S Balaji; Arthur Wuster; Joshua A Grochow; Jörg Gsponer; Teresa M Przytycka; L Aravind; M Madan Babu
Journal:  Mol Syst Biol       Date:  2009-08-18       Impact factor: 11.429

10.  On the spontaneous stochastic dynamics of a single gene: complexity of the molecular interplay at the promoter.

Authors:  Antoine Coulon; Olivier Gandrillon; Guillaume Beslon
Journal:  BMC Syst Biol       Date:  2010-01-08
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