Steady-state expression of self-regulated genes.

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Serval ID
serval:BIB_32914927AA4F
Type
Article: article from journal or magazin.
Collection
Publications
Title
Steady-state expression of self-regulated genes.
Journal
Bioinformatics
Author(s)
Fournier T., Gabriel J.P., Mazza C., Pasquier J., Galbete J.L., Mermod N.
ISSN
1367-4811[electronic], 1367-4803[linking]
Publication state
Published
Issued date
10/2007
Volume
23
Number
23
Pages
3185-3192
Language
english
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: ppublish
Abstract
MOTIVATION: Regulatory gene networks contain generic modules such as feedback loops that are essential for the regulation of many biological functions. The study of the stochastic mechanisms of gene regulation is instrumental for the understanding of how cells maintain their expression at levels commensurate with their biological role, as well as to engineer gene expression switches of appropriate behavior. The lack of precise knowledge on the steady-state distribution of gene expression requires the use of Gillespie algorithms and Monte-Carlo approximations. METHODOLOGY: In this study, we provide new exact formulas and efficient numerical algorithms for computing/modeling the steady-state of a class of self-regulated genes, and we use it to model/compute the stochastic expression of a gene of interest in an engineered network introduced in mammalian cells. The behavior of the genetic network is then analyzed experimentally in living cells. RESULTS: Stochastic models often reveal counter-intuitive experimental behaviors, and we find that this genetic architecture displays a unimodal behavior in mammalian cells, which was unexpected given its known bimodal response in unicellular organisms. We provide a molecular rationale for this behavior, and we implement it in the mathematical picture to explain the experimental results obtained from this network.
Keywords
Gene Expression/physiology, Gene Expression Profiling/methods, Gene Expression Regulation/physiology, Models, Statistical, Proteome/metabolism, Signal Transduction/physiology, Stochastic Processes
Pubmed
Web of science
Open Access
Yes
Create date
24/01/2008 11:41
Last modification date
25/09/2019 7:08
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