Literature DB >> 15111419

Tracking operator state fluctuations in gene expression in single cells.

B Banerjee1, S Balasubramanian, G Ananthakrishna, T V Ramakrishnan, G V Shivashankar.   

Abstract

We report the results of operator state fluctuations in gene expression for the entire bacterial growth cycle, using single-cell analysis and synthetic unregulated and negative-feedback transcription regulatory gene circuits. In the unregulated circuit, during the cell cycle, we observe a crossover from log-normal-to-normal distribution of expressed proteins and an unusual linear dependence of their standard deviation on the mean gene expression levels. With negative-feedback circuits we find the existence of bimodality as the cell cycle progresses. We suggest that such long-tail and bimodal distributions may be used as selection mechanisms in developmental switches and for assigning cell identity.

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Year:  2004        PMID: 15111419      PMCID: PMC1304171          DOI: 10.1016/S0006-3495(04)74354-4

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


  22 in total

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Journal:  Trends Genet       Date:  1992-12       Impact factor: 11.639

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6.  GFP tagging of budding yeast chromosomes reveals that protein-protein interactions can mediate sister chromatid cohesion.

Authors:  A F Straight; A S Belmont; C C Robinett; A W Murray
Journal:  Curr Biol       Date:  1996-12-01       Impact factor: 10.834

7.  Stochastic mechanisms in gene expression.

Authors:  H H McAdams; A Arkin
Journal:  Proc Natl Acad Sci U S A       Date:  1997-02-04       Impact factor: 11.205

Review 8.  Evolution of cell lineage.

Authors:  P W Sternberg; M A Félix
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9.  Negative autoregulation speeds the response times of transcription networks.

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Review 10.  Engineered gene circuits.

Authors:  Jeff Hasty; David McMillen; J J Collins
Journal:  Nature       Date:  2002-11-14       Impact factor: 49.962

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  12 in total

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2.  Noisy signal amplification in ultrasensitive signal transduction.

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3.  Stochastic simulations of the origins and implications of long-tailed distributions in gene expression.

Authors:  Sandeep Krishna; Bidisha Banerjee; T V Ramakrishnan; G V Shivashankar
Journal:  Proc Natl Acad Sci U S A       Date:  2005-03-16       Impact factor: 11.205

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6.  Cell-to-cell heterogeneity in growth rate and gene expression in Methylobacterium extorquens AM1.

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7.  Stochastic receptor expression allows sensitive bacteria to evade phage attack. Part II: theoretical analyses.

Authors:  E Chapman-McQuiston; X L Wu
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8.  Stochastic receptor expression allows sensitive bacteria to evade phage attack. Part I: experiments.

Authors:  E Chapman-McQuiston; X L Wu
Journal:  Biophys J       Date:  2008-02-29       Impact factor: 4.033

9.  Monitoring the single-cell stress response of the diatom Thalassiosira pseudonana by quantitative real-time reverse transcription-PCR.

Authors:  Xu Shi; Weimin Gao; Shih-hui Chao; Weiwen Zhang; Deirdre R Meldrum
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10.  Population heterogeneity in Methylobacterium extorquens AM1.

Authors:  Tim J Strovas; Mary E Lidstrom
Journal:  Microbiology (Reading)       Date:  2009-04-21       Impact factor: 2.777

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