Literature DB >> 22365828

Cellular noise regulons underlie fluctuations in Saccharomyces cerevisiae.

Jacob Stewart-Ornstein1, Jonathan S Weissman, Hana El-Samad.   

Abstract

Stochasticity is a hallmark of cellular processes, and different classes of genes show large differences in their cell-to-cell variability (noise). To decipher the sources and consequences of this noise, we systematically measured pairwise correlations between large numbers of genes, including those with high variability. We find that there is substantial pathway variability shared across similarly regulated genes. This induces quantitative correlations in the expression of functionally related genes such as those involved in the Msn2/4 stress response pathway, amino-acid biosynthesis, and mitochondrial maintenance. Bioinformatic analyses and genetic perturbations suggest that fluctuations in PKA and Tor signaling contribute to pathway-specific variability. Our results argue that a limited number of well-delineated "noise regulons" operate across a yeast cell and that such coordinated fluctuations enable a stochastic but coherent induction of functionally related genes. Finally, we show that pathway noise is a quantitative tool for exploring pathway features and regulatory relationships in un-stimulated systems. Copyright Â
© 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22365828      PMCID: PMC3327736          DOI: 10.1016/j.molcel.2011.11.035

Source DB:  PubMed          Journal:  Mol Cell        ISSN: 1097-2765            Impact factor:   17.970


  42 in total

1.  Acute glucose starvation activates the nuclear localization signal of a stress-specific yeast transcription factor.

Authors:  Wolfram Görner; Erich Durchschlag; Julia Wolf; Elizabeth L Brown; Gustav Ammerer; Helmut Ruis; Christoph Schüller
Journal:  EMBO J       Date:  2002-01-15       Impact factor: 11.598

2.  Regulation of noise in the expression of a single gene.

Authors:  Ertugrul M Ozbudak; Mukund Thattai; Iren Kurtser; Alan D Grossman; Alexander van Oudenaarden
Journal:  Nat Genet       Date:  2002-04-22       Impact factor: 38.330

3.  Contributions of low molecule number and chromosomal positioning to stochastic gene expression.

Authors:  Attila Becskei; Benjamin B Kaufmann; Alexander van Oudenaarden
Journal:  Nat Genet       Date:  2005-08-07       Impact factor: 38.330

4.  Regulation of thermotolerance by stress-induced transcription factors in Saccharomyces cerevisiae.

Authors:  Noritaka Yamamoto; Yuka Maeda; Aya Ikeda; Hiroshi Sakurai
Journal:  Eukaryot Cell       Date:  2008-03-21

5.  Noncooperative interactions between transcription factors and clustered DNA binding sites enable graded transcriptional responses to environmental inputs.

Authors:  Luca Giorgetti; Trevor Siggers; Guido Tiana; Greta Caprara; Samuele Notarbartolo; Teresa Corona; Manolis Pasparakis; Paolo Milani; Martha L Bulyk; Gioacchino Natoli
Journal:  Mol Cell       Date:  2010-02-12       Impact factor: 17.970

6.  Non-genetic individuality: chance in the single cell.

Authors:  J L Spudich; D E Koshland
Journal:  Nature       Date:  1976-08-05       Impact factor: 49.962

7.  A general lack of compensation for gene dosage in yeast.

Authors:  Michael Springer; Jonathan S Weissman; Marc W Kirschner
Journal:  Mol Syst Biol       Date:  2010-05-11       Impact factor: 11.429

8.  Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization.

Authors:  P T Spellman; G Sherlock; M Q Zhang; V R Iyer; K Anders; M B Eisen; P O Brown; D Botstein; B Futcher
Journal:  Mol Biol Cell       Date:  1998-12       Impact factor: 4.138

9.  Control of stochastic gene expression by host factors at the HIV promoter.

Authors:  John C Burnett; Kathryn Miller-Jensen; Priya S Shah; Adam P Arkin; David V Schaffer
Journal:  PLoS Pathog       Date:  2009-01-09       Impact factor: 6.823

10.  Construction, verification and experimental use of two epitope-tagged collections of budding yeast strains.

Authors:  Russell Howson; Won-Ki Huh; Sina Ghaemmaghami; James V Falvo; Kiowa Bower; Archana Belle; Noah Dephoure; Dennis D Wykoff; Jonathan S Weissman; Erin K O'Shea
Journal:  Comp Funct Genomics       Date:  2005
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  73 in total

1.  Single-cell protein dynamics reproduce universal fluctuations in cell populations.

Authors:  Naama Brenner; Erez Braun; Anna Yoney; Lee Susman; James Rotella; Hanna Salman
Journal:  Eur Phys J E Soft Matter       Date:  2015-09-28       Impact factor: 1.890

Review 2.  Using variability in gene expression as a tool for studying gene regulation.

Authors:  Olivia Padovan-Merhar; Arjun Raj
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2013-08-29

Review 3.  Models of signalling networks - what cell biologists can gain from them and give to them.

Authors:  Kevin A Janes; Douglas A Lauffenburger
Journal:  J Cell Sci       Date:  2013-05-01       Impact factor: 5.285

4.  Noise and low-level dynamics can coordinate multicomponent bet hedging mechanisms.

Authors:  Javier Garcia-Bernardo; Mary J Dunlop
Journal:  Biophys J       Date:  2015-01-06       Impact factor: 4.033

5.  Modeling stochastic noise in gene regulatory systems.

Authors:  Arwen Meister; Chao Du; Ye Henry Li; Wing Hung Wong
Journal:  Quant Biol       Date:  2014-03

6.  Parameterizing cell-to-cell regulatory heterogeneities via stochastic transcriptional profiles.

Authors:  Sameer S Bajikar; Christiane Fuchs; Andreas Roller; Fabian J Theis; Kevin A Janes
Journal:  Proc Natl Acad Sci U S A       Date:  2014-01-21       Impact factor: 11.205

7.  Msn2 coordinates a stoichiometric gene expression program.

Authors:  Jacob Stewart-Ornstein; Christopher Nelson; Joe DeRisi; Jonathan S Weissman; Hana El-Samad
Journal:  Curr Biol       Date:  2013-11-07       Impact factor: 10.834

Review 8.  Single cell protein analysis for systems biology.

Authors:  Ezra Levy; Nikolai Slavov
Journal:  Essays Biochem       Date:  2018-10-26       Impact factor: 8.000

9.  Genome-wide consequences of deleting any single gene.

Authors:  Xinchen Teng; Margaret Dayhoff-Brannigan; Wen-Chih Cheng; Catherine E Gilbert; Cierra N Sing; Nicola L Diny; Sarah J Wheelan; Maitreya J Dunham; Jef D Boeke; Fernando J Pineda; J Marie Hardwick
Journal:  Mol Cell       Date:  2013-11-07       Impact factor: 17.970

Review 10.  Analysis of omics data with genome-scale models of metabolism.

Authors:  Daniel R Hyduke; Nathan E Lewis; Bernhard Ø Palsson
Journal:  Mol Biosyst       Date:  2012-12-18
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