Nucleic Acids Research Advance Access originally published online on September 22, 2006
Nucleic Acids Research 2006 34(18):5175-5183; doi:10.1093/nar/gkl654
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Nucleic Acids Research, 2006, Vol. 34, No. 18 5175-5183
© 2006 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Molecular Biology |
Mechanisms of transcriptional regulation underlying temporal integration of signals
Fondation pour Recherches Médicales, University of Geneva Switzerland
*To whom correspondence should be addressed at Fondation pour Recherches Médicales, Avenue de la Roseraie 64, 1211 Geneva, Switzerland. Tel: +41 22 382 38 11; Fax: +41 22 347 59 79; Email: werner.schlegel{at}medecine.unige.ch
Received June 2, 2006. Revised August 22, 2006. Accepted August 25, 2006.
How cells convert the duration of signals into differential adaptation of gene expression is a poorly understood issue. Signal-induced immediate-early gene (IEG) expression couples early signals to late expression of downstream <target> genes. Here we study how kinetic features of the IEG-<target> system allow temporal integration of stimuli in a pancreatic beta cell model of metabolic stimulation. Gene expression profiling revealed that beta cells produce drastically different transcriptional outputs in response to different stimuli durations. Noteworthy, most genes (87%) regulated by a sustained stimulation (4 h) were not regulated by a transient stimulation (1 h followed by 3 h without stimulus). We analyzed the induction kinetics of several previously identified IEGs and <targets>. IEG expression persisted as long as stimulation was maintained, but was rapidly lost upon stimuli removal, abolishing the delayed <target> induction. The molecular mechanisms coupling the duration of stimuli to quantitative <target> transcription were demonstrated for the AP-1 transcription factor. In conclusion, we propose that the network composed of IEGs and their <targets> dynamically functions to convert signal inputs of different durations into quantitative differences in global transcriptional adaptation. These findings provide a novel and more comprehensive view of dynamic gene regulation.
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