The Generation of Promoter-Mediated Transcriptional Noise in Bacteria
Publication Date
July 11, 2008
Journal
PLOS Computational Biology
Authors
Namiko Mitarai, Ian B. Dodd, Michael T. Crooks & Kim Sneppen
Volume
4
Issue
7
Pages
e1000109
DOI
https://dx.plos.org/10.1371/journal.pcbi.1000109
Publisher URL
http://journals.plos.org/ploscompbiol/article?id=10.1371%2Fjournal.pcbi.1000109
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/18617999
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2442219
Europe PMC
http://europepmc.org/abstract/MED/18617999
Web of Science
000260039300019
Scopus
48249138167
Mendeley
http://www.mendeley.com/research/generation-promotermediated-transcriptional-noise-bacteria
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CiteULike | Further Information

Mendeley | Further Information

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Scopus | Further Information

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  • {"files"=>["https://ndownloader.figshare.com/files/457041"], "description"=>"<div><p>Noise in the expression of a gene produces fluctuations in the concentration of the gene product. These fluctuations can interfere with optimal function or can be exploited to generate beneficial diversity between cells; gene expression noise is therefore expected to be subject to evolutionary pressure. Shifts between modes of high and low rates of transcription initiation at a promoter appear to contribute to this noise both in eukaryotes and prokaryotes. However, models invoked for eukaryotic promoter noise such as stable activation scaffolds or persistent nucleosome alterations seem unlikely to apply to prokaryotic promoters. We consider the relative importance of the steps required for transcription initiation. The 3-step transcription initiation model of McClure is extended into a mathematical model that can be used to predict consequences of additional promoter properties. We show in principle that the transcriptional bursting observed at an <em>E. coli</em> promoter by Golding et al. (2005) can be explained by stimulation of initiation by the negative supercoiling behind a transcribing RNA polymerase (RNAP) or by the formation of moribund or dead-end RNAP-promoter complexes. Both mechanisms are tunable by the alteration of promoter kinetics and therefore allow the optimization of promoter mediated noise.</p></div>", "links"=>[], "tags"=>["promoter-mediated", "transcriptional"], "article_id"=>150029, "categories"=>["Biochemistry", "Biophysics", "Biological Sciences"], "users"=>["Namiko Mitarai", "Ian B. Dodd", "Michael T. Crooks", "Kim Sneppen"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000109", "stats"=>{"downloads"=>17, "page_views"=>17, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/The_Generation_of_Promoter_Mediated_Transcriptional_Noise_in_Bacteria/150029", "title"=>"The Generation of Promoter-Mediated Transcriptional Noise in Bacteria", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2008-07-11 00:00:29"}
  • {"files"=>["https://ndownloader.figshare.com/files/927156"], "description"=>"<p>(A–D) show the results from the recruitment model with the probability of recruitment <i>q</i> = 0.545. The average firing rate is 1/20 [1/min]. <i>k<sub>b</sub></i> = <i>k<sub>u</sub></i> = 60 [1/min], <i>E</i> = 1/2.9 [1/min], <i>O</i> = 1/18.3 [1/min], <i>l</i> = 35 [bp], <i>v</i> = 25 [bp/sec]. (A) Accumulated number of mRNAs, showing on periods and off-periods. Transcriptional bursting can be seen around 62 [min] to 70 [min], where 5 firings occur in rapid succession. See <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000109#s4\" target=\"_blank\">Materials and Methods</a> for the choice of parameters and definitions of <i>t<sub>on</sub></i> and <i>t<sub>off</sub></i>. (B) The distribution of the durations between firing, <i>P</i>(<i>Δt</i>). The solid line shows Equation 3. (C) The distribution of the number of firings per on-period, <i>P</i>(<i>Δn</i>). The filled circles show experimental data from Golding <i>et al </i><a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000109#pcbi.1000109-Golding1\" target=\"_blank\">[10]</a>, and the open circles are <i>Δn</i> from the recruitment model. (D) The distribution of the “on-times” <i>t<sub>on</sub></i> (open circles) and the “off-times” (open boxes) <i>t<sub>off</sub></i>. The experimental data from Golding <i>et al.</i> for the on-time (filled circles) and off-time (filled boxes) are also shown. (E) The distribution of intervals between initiations for the dead-end complex model (<a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000109#pcbi-1000109-g002\" target=\"_blank\">Figure 2B</a>). The probability of productive elongation is <i>Q</i> = 0.545, and the rate of removal of dead-end complexes is <i>d</i> = 1/<i>τ<sub>dead</sub></i> = 1/(20 [min]). The average firing rate is 1/22 [1/min]. <i>k<sub>b</sub></i> = <i>k<sub>u</sub></i> = 60[1/min], <i>E</i> = 1/1.5[1/min], <i>O</i> = 1/0.7 [1/min], <i>l</i> = 35 [bp], <i>v</i> = 25 [bp/sec]. This parameter choice corresponds to a Class 2 promoter in the on periods, which gives a round curve for short timescales (around 3 [min]). The solid line shows <i>Q</i>Δ<i>t</i> exp[−Δ<i>t</i>/<i>τ</i>]/<i>τ</i><sup>2</sup>+(1−<i>Q</i>) exp[−Δ<i>t</i>/(<i>τ<sub>dead</sub></i>/<i>Q</i>)]/(<i>τ<sub>dead</sub></i>/<i>Q</i>) with <i>τ</i> = <i>τ<sub>O</sub></i> = <i>τ<sub>E</sub></i>.</p>", "links"=>[], "tags"=>["bursting", "supercoiling", "assisted", "recruitment", "dead-end"], "article_id"=>597602, "categories"=>["Biochemistry", "Biophysics", "Computational Biology"], "users"=>["Namiko Mitarai", "Ian B. Dodd", "Michael T. Crooks", "Kim Sneppen"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000109.g003", "stats"=>{"downloads"=>3, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Transcriptional_bursting_from_three_step_model_with_supercoiling_assisted_recruitment_and_the_dead_end_complex_model_/597602", "title"=>"Transcriptional bursting from three step model with supercoiling assisted recruitment and the dead-end complex model.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-07-11 02:06:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/926927"], "description"=>"<p>(A) First an RNAP forms a closed complex at the promoter with some on (<i>k<sub>b</sub></i>) and off rates (<i>k<sub>u</sub></i>), and subsequently forms an open complex with rate <i>O</i>. This process is a directed non-equilibrium transition. Finally, the open complex escapes the promoter into productive transcription with the one way rate <i>E</i>. (B–C) The distribution of intervals between transcription events for the standard 3-step model. For binding and unbinding rates of the closed complex we use <i>k<sub>b</sub></i> = <i>k<sub>u</sub></i> = 60 [1/min]. The average total strength is <i>F</i> = 1/(20 [min]), whereas <i>l</i> = 35 [bp] and <i>v</i> = 25 [bp/sec]. (B) Class I: Probability distribution for time between transcripts Δ<i>t</i> for a promoter with a single rate limiting step. Here, it is isomerisation with <i>O</i> = 1/(9.7 [min]). The escape rate from the open complex is <i>E</i> = 1/(0.19[min]). Red dots: stochastic simulation results. Solid line: predicted distribution, (1/<i>τ</i>)exp[−Δ<i>t</i>/<i>τ</i>] with <i>τ</i> = 19.4 [min]. (C) Class II; Δ<i>t</i> probability distribution for a promoter with two rate limiting steps because the isomerisation and escape rates are similar (<i>O</i> = 1/(4.9[min]), <i>E</i> = 1/(9.7 [min])). Solid line shows the predicted distribution, (1/<i>τ</i>)<sup>2</sup> Δ<i>t</i> exp[−Δ<i>t</i>/<i>τ</i>] with <i>τ</i> = 9.7 [min].</p>", "links"=>[], "tags"=>["hawley-mcclure", "3-step", "transcription"], "article_id"=>597373, "categories"=>["Biochemistry", "Biophysics", "Computational Biology"], "users"=>["Namiko Mitarai", "Ian B. Dodd", "Michael T. Crooks", "Kim Sneppen"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000109.g001", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_Hawley_McClure_3_step_model_of_transcription_initiation_/597373", "title"=>"The Hawley-McClure 3-step model of transcription initiation.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-07-11 02:02:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/927322"], "description"=>"<p>Here, the duration Δ for a RNAP to transcribe one mRNA after it has been fired from the promoter is added, because in Golding's experiment the mRNA is already visible when it is being made.</p>", "links"=>[], "tags"=>["biochemistry/transcription and translation", "biophysics/theory and simulation", "biophysics/transcription and translation", "computational biology/transcriptional regulation"], "article_id"=>597774, "categories"=>["Biochemistry", "Biophysics", "Computational Biology"], "users"=>["Namiko Mitarai", "Ian B. Dodd", "Michael T. Crooks", "Kim Sneppen"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000109.t001", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Relations_between_model_parameters_and_the_average_n__t_on_and_t_off_/597774", "title"=>"Relations between model parameters and the average 〈Δ<i>n</i>〉, 〈<i>t<sub>on</sub></i>〉, and 〈<i>t<sub>off</sub></i>〉.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2008-07-11 02:09:34"}
  • {"files"=>["https://ndownloader.figshare.com/files/927271"], "description"=>"<p>(A) Fano factor in the recruitment model for 〈<i>N</i>〉 = <i>F</i>/<i>γ</i> = 10. The horizontal axis shows the aspect ratio <i>α = O</i>′<i>/E</i>, and the vertical axis shows the recruitment probability <i>q</i>. The fluctuations are larger for smaller <i>α</i>, where the formation of the closed complex is the rate-limiting step. (B) Fano factor for the dead-end model, with , for 〈<i>N</i>〉 = 10 and <i>α</i> = 1. The horizontal axis is <i>β</i> = (<i>τ<sub>O</sub></i>+<i>τ<sub>E</sub></i>)/<i>τ<sub>dead</sub></i>, the ratio of the average time required for successful firing to the average time taken to remove a dead-end complex, and the vertical axis is the probability of successful firing, <i>Q</i>. Small <i>β</i> and large <i>Q</i> gives large fluctuations, which enables bust like firing through successive normal firings (from large <i>Q</i>) and long silent periods until the dead-end complex is removed (from small <i>β</i>). The detailed calculations are given in <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000109#pcbi.1000109.s001\" target=\"_blank\">Text S1</a>.</p>", "links"=>[], "tags"=>["dependence", "fano"], "article_id"=>597724, "categories"=>["Biochemistry", "Biophysics", "Computational Biology"], "users"=>["Namiko Mitarai", "Ian B. Dodd", "Michael T. Crooks", "Kim Sneppen"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000109.g004", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Parameter_dependence_of_Fano_factor_/597724", "title"=>"Parameter dependence of Fano factor.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-07-11 02:08:44"}
  • {"files"=>["https://ndownloader.figshare.com/files/927047"], "description"=>"<p>We propose (A) supercoiling assisted open complex formation, and (B) possible stalling of an RNAP into a “moribund” complex. The yellow background indicates the state where most of the time is spent in the off period. (A) An elongating RNAP might recruit a subsequent RNAP into an open complex with probability <i>q</i>, thus by-passing the time needed to recruit an RNAP and form open complex. In the limit of large <i>k<sub>b</sub></i>, the firing rate is given by with . (B) Two alternative open complexes, of which one is productive and the other is a dead end complex that is removed with rate <i>d</i>. In this case <i>Q</i> denotes the probability that a closed complex enters into the productive open complex. In the limit of large <i>k<sub>b</sub></i>, the firing rate is given by with . The detailed calculations and equations for limiting <i>k<sub>b</sub></i> are given in <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000109#pcbi.1000109.s001\" target=\"_blank\">Text S1</a>. Both the dead-end and the recruitment model can be simulated on-line using the java applet on <a href=\"http://www.cmol.nbi.dk/models/transcription/RNAPInitiation.html\" target=\"_blank\">http://www.cmol.nbi.dk/models/transcription/RNAPInitiation.html</a>.</p>", "links"=>[], "tags"=>["mechanisms", "bunched"], "article_id"=>597505, "categories"=>["Biochemistry", "Biophysics", "Computational Biology"], "users"=>["Namiko Mitarai", "Ian B. Dodd", "Michael T. Crooks", "Kim Sneppen"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000109.g002", "stats"=>{"downloads"=>5, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Revisiting_mechanisms_for_bunched_firing_/597505", "title"=>"Revisiting mechanisms for bunched firing.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-07-11 02:05:05"}

PMC Usage Stats | Further Information

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  • {"unique-ip"=>"4", "full-text"=>"4", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}

Relative Metric

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