Dynamic analysis of stochastic transcription cycles.

In individual mammalian cells the expression of some genes such as prolactin is highly variable over time and has been suggested to occur in stochastic pulses. To investigate the origins of this behavior and to understand its functional relevance, we quantitatively analyzed this variability using ne...

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Main Authors: Claire V Harper, Bärbel Finkenstädt, Dan J Woodcock, Sönke Friedrichsen, Sabrina Semprini, Louise Ashall, David G Spiller, John J Mullins, David A Rand, Julian R E Davis, Michael R H White
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2011-04-01
Series:PLoS Biology
Online Access:https://journals.plos.org/plosbiology/article/file?id=10.1371/journal.pbio.1000607&type=printable
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author Claire V Harper
Bärbel Finkenstädt
Dan J Woodcock
Sönke Friedrichsen
Sabrina Semprini
Louise Ashall
David G Spiller
John J Mullins
David A Rand
Julian R E Davis
Michael R H White
author_facet Claire V Harper
Bärbel Finkenstädt
Dan J Woodcock
Sönke Friedrichsen
Sabrina Semprini
Louise Ashall
David G Spiller
John J Mullins
David A Rand
Julian R E Davis
Michael R H White
author_sort Claire V Harper
collection DOAJ
description In individual mammalian cells the expression of some genes such as prolactin is highly variable over time and has been suggested to occur in stochastic pulses. To investigate the origins of this behavior and to understand its functional relevance, we quantitatively analyzed this variability using new mathematical tools that allowed us to reconstruct dynamic transcription rates of different reporter genes controlled by identical promoters in the same living cell. Quantitative microscopic analysis of two reporter genes, firefly luciferase and destabilized EGFP, was used to analyze the dynamics of prolactin promoter-directed gene expression in living individual clonal and primary pituitary cells over periods of up to 25 h. We quantified the time-dependence and cyclicity of the transcription pulses and estimated the length and variation of active and inactive transcription phases. We showed an average cycle period of approximately 11 h and demonstrated that while the measured time distribution of active phases agreed with commonly accepted models of transcription, the inactive phases were differently distributed and showed strong memory, with a refractory period of transcriptional inactivation close to 3 h. Cycles in transcription occurred at two distinct prolactin-promoter controlled reporter genes in the same individual clonal or primary cells. However, the timing of the cycles was independent and out-of-phase. For the first time, we have analyzed transcription dynamics from two equivalent loci in real-time in single cells. In unstimulated conditions, cells showed independent transcription dynamics at each locus. A key result from these analyses was the evidence for a minimum refractory period in the inactive-phase of transcription. The response to acute signals and the result of manipulation of histone acetylation was consistent with the hypothesis that this refractory period corresponded to a phase of chromatin remodeling which significantly increased the cyclicity. Stochastically timed bursts of transcription in an apparently random subset of cells in a tissue may thus produce an overall coordinated but heterogeneous phenotype capable of acute responses to stimuli.
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spelling doaj-art-188cf6c3240644bba2dec08fe24b29a32025-08-20T02:34:06ZengPublic Library of Science (PLoS)PLoS Biology1544-91731545-78852011-04-0194e100060710.1371/journal.pbio.1000607Dynamic analysis of stochastic transcription cycles.Claire V HarperBärbel FinkenstädtDan J WoodcockSönke FriedrichsenSabrina SempriniLouise AshallDavid G SpillerJohn J MullinsDavid A RandJulian R E DavisMichael R H WhiteIn individual mammalian cells the expression of some genes such as prolactin is highly variable over time and has been suggested to occur in stochastic pulses. To investigate the origins of this behavior and to understand its functional relevance, we quantitatively analyzed this variability using new mathematical tools that allowed us to reconstruct dynamic transcription rates of different reporter genes controlled by identical promoters in the same living cell. Quantitative microscopic analysis of two reporter genes, firefly luciferase and destabilized EGFP, was used to analyze the dynamics of prolactin promoter-directed gene expression in living individual clonal and primary pituitary cells over periods of up to 25 h. We quantified the time-dependence and cyclicity of the transcription pulses and estimated the length and variation of active and inactive transcription phases. We showed an average cycle period of approximately 11 h and demonstrated that while the measured time distribution of active phases agreed with commonly accepted models of transcription, the inactive phases were differently distributed and showed strong memory, with a refractory period of transcriptional inactivation close to 3 h. Cycles in transcription occurred at two distinct prolactin-promoter controlled reporter genes in the same individual clonal or primary cells. However, the timing of the cycles was independent and out-of-phase. For the first time, we have analyzed transcription dynamics from two equivalent loci in real-time in single cells. In unstimulated conditions, cells showed independent transcription dynamics at each locus. A key result from these analyses was the evidence for a minimum refractory period in the inactive-phase of transcription. The response to acute signals and the result of manipulation of histone acetylation was consistent with the hypothesis that this refractory period corresponded to a phase of chromatin remodeling which significantly increased the cyclicity. Stochastically timed bursts of transcription in an apparently random subset of cells in a tissue may thus produce an overall coordinated but heterogeneous phenotype capable of acute responses to stimuli.https://journals.plos.org/plosbiology/article/file?id=10.1371/journal.pbio.1000607&type=printable
spellingShingle Claire V Harper
Bärbel Finkenstädt
Dan J Woodcock
Sönke Friedrichsen
Sabrina Semprini
Louise Ashall
David G Spiller
John J Mullins
David A Rand
Julian R E Davis
Michael R H White
Dynamic analysis of stochastic transcription cycles.
PLoS Biology
title Dynamic analysis of stochastic transcription cycles.
title_full Dynamic analysis of stochastic transcription cycles.
title_fullStr Dynamic analysis of stochastic transcription cycles.
title_full_unstemmed Dynamic analysis of stochastic transcription cycles.
title_short Dynamic analysis of stochastic transcription cycles.
title_sort dynamic analysis of stochastic transcription cycles
url https://journals.plos.org/plosbiology/article/file?id=10.1371/journal.pbio.1000607&type=printable
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