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Binary gene induction and protein expression in individual cells. Theor Biol Med Model
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@MISC{Zhang_binarygene,
author = {Qiang Zhang and Melvin E Andersen and Rory B Conolly Biomed Central},
title = {Binary gene induction and protein expression in individual cells. Theor Biol Med Model},
year = {}
}
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Abstract
Background: Eukaryotic gene transcription is believed to occur in either a binary or a graded fashion. With binary induction, a transcription activator (TA) regulates the probability with which a gene template is switched from the inactive to the active state without affecting the rate at which RNA molecules are produced from the template. With graded, also called rheostat-like, induction the gene template has continuously varying levels of transcriptional activity, and the TA regulates the rate of RNA production. Support for each of these two mechanisms arises primarily from experimental studies measuring reporter proteins in individual cells, rather than from direct measurement of induction events at the gene template. Methods and results: In this paper, using a computational model of stochastic gene expression, we have studied the biological and experimental conditions under which a binary induction mode operating at the gene template can give rise to differentially expressed "phenotypes " (i.e., binary, hybrid or graded) at the protein level. We have also investigated whether the choice of reporter genes plays a significant role in determining the observed protein expression patterns in individual cells, given the diverse properties of commonly-used reporter genes. Our simulation confirmed
Keyphrases
individual cell gene template binary gene induction theor biol med model protein expression reporter protein transcriptional activity rna production experimental condition mechanism arises direct measurement protein level reporter gene observed protein expression pattern graded fashion transcription activator eukaryotic gene transcription commonly-used reporter gene significant role binary induction diverse property computational model rna molecule induction event experimental study expressed quot active state binary induction mode operating stochastic gene expression varying level
