Literature DB >> 12829377

Free RNA polymerase and modeling global transcription in Escherichia coli.

H Bremer1, P Dennis, M Ehrenberg.   

Abstract

Growth rate-dependent changes in the cytoplasmic concentration of free functional RNA polymerase, [R(f)], affect the activity of all bacterial genes. Since [R(f)] is not accessible to direct experimental quantitation, it can only be found indirectly from an evaluation of promoter activity data. Here, a theory has been derived to calculate [R(f)] from the concentrations of total RNA polymerase and promoters in a model system with known Michaelis-Menten constants for the polymerase-promoter interactions. The theory takes transcript lengths and elongation rates into account and predicts how [R(f)] changes with varying gene dosages. From experimental data on total concentrations of RNA polymerase and kinetic properties of different classes of promoters, the theory was developed into a mathematical model that reproduces the global transcriptional control in Escherichia coli growing at different rates. The model allows an estimation of the concentrations of free and DNA-bound RNA polymerase, as well as the partitioning of RNA polymerase into mRNA and stable RNA synthesizing fractions. According to this model, [R(f)] is about 0.4 and 1.2 microM at growth rates corresponding to 1.0 and 2.5 doublings/h, respectively. The model accurately reflects a number of further experimental observations and suggests that the free RNA polymerase concentration increases with increasing growth rate.

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Year:  2003        PMID: 12829377     DOI: 10.1016/s0300-9084(03)00105-6

Source DB:  PubMed          Journal:  Biochimie        ISSN: 0300-9084            Impact factor:   4.079


  31 in total

Review 1.  Control of rRNA synthesis in Escherichia coli: a systems biology approach.

Authors:  Patrick P Dennis; Mans Ehrenberg; Hans Bremer
Journal:  Microbiol Mol Biol Rev       Date:  2004-12       Impact factor: 11.056

2.  Model-driven designs of an oscillating gene network.

Authors:  Lisa M Tuttle; Howard Salis; Jonathan Tomshine; Yiannis N Kaznessis
Journal:  Biophys J       Date:  2005-09-23       Impact factor: 4.033

3.  Diffusion of transcription factors can drastically enhance the noise in gene expression.

Authors:  Jeroen S van Zon; Marco J Morelli; Sorin Tănase-Nicola; Pieter Rein ten Wolde
Journal:  Biophys J       Date:  2006-09-29       Impact factor: 4.033

4.  Elongation dynamics shape bursty transcription and translation.

Authors:  Maciej Dobrzynski; Frank J Bruggeman
Journal:  Proc Natl Acad Sci U S A       Date:  2009-02-05       Impact factor: 11.205

5.  A superresolution census of RNA polymerase.

Authors:  Stefan Klumpp
Journal:  Biophys J       Date:  2013-12-17       Impact factor: 4.033

6.  Partitioning of RNA polymerase activity in live Escherichia coli from analysis of single-molecule diffusive trajectories.

Authors:  Somenath Bakshi; Renée M Dalrymple; Wenting Li; Heejun Choi; James C Weisshaar
Journal:  Biophys J       Date:  2013-12-17       Impact factor: 4.033

7.  Functional characterization of alternate optimal solutions of Escherichia coli's transcriptional and translational machinery.

Authors:  Ines Thiele; Ronan M T Fleming; Aarash Bordbar; Jan Schellenberger; Bernhard Ø Palsson
Journal:  Biophys J       Date:  2010-05-19       Impact factor: 4.033

8.  Growth-rate-dependent partitioning of RNA polymerases in bacteria.

Authors:  Stefan Klumpp; Terence Hwa
Journal:  Proc Natl Acad Sci U S A       Date:  2008-12-10       Impact factor: 11.205

9.  Effects of transcriptional pausing on gene expression dynamics.

Authors:  Tiina Rajala; Antti Häkkinen; Shannon Healy; Olli Yli-Harja; Andre S Ribeiro
Journal:  PLoS Comput Biol       Date:  2010-03-12       Impact factor: 4.475

10.  The origins of time-delay in template biopolymerization processes.

Authors:  Luis Mier-y-Terán-Romero; Mary Silber; Vassily Hatzimanikatis
Journal:  PLoS Comput Biol       Date:  2010-04-01       Impact factor: 4.475

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