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Prediction of kinetic parameters from DNA-binding site sequences for modeling global transcription dynamics in Escherichia coli

Paper ID Volume ID Publish Year Pages File Format Full-Text
31872 44847 2010 16 PDF Available
Title
Prediction of kinetic parameters from DNA-binding site sequences for modeling global transcription dynamics in Escherichia coli
Abstract

The majority of dynamic gene regulatory network (GRN) models are comprised of only a few genes and do not take multiple transcription regulation into account. The models are conceived in this way in order to minimize the number of kinetic parameters. In this paper, we propose a new approach for predicting kinetic parameters from DNA-binding site sequences by correlating the protein–DNA-binding affinities with nucleotide sequence conservation. We present the dynamic modeling of the cra modulon transcription in Escherichia coli during glucose-limited fed-batch cultivation. The concentration of the Cra regulator protein inhibitor, fructose 1,6-bis(phosphate), decreases sharply, eventually leading to the repression of transcription. Total RNA concentration data indicate a strong regulation of transcription through the availability of RNA polymerase. A critical assessment of the results of the model simulations supports this finding. This new approach for the prediction of transcription dynamics may improve the metabolic engineering of gene regulation processes.

Keywords
Cell volume; Central carbon metabolism; Cra; Fed-batch; Fructose 1,6-bis(phosphate); fruR; Glucose-limitation; Gene regulatory network; Growth rate-dependent regulation; Position weight matrix; Promoter; Regulation; RNA polymerase; Transcription rate
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Prediction of kinetic parameters from DNA-binding site sequences for modeling global transcription dynamics in Escherichia coli
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Publisher
Database: Elsevier - ScienceDirect
Journal: Metabolic Engineering - Volume 12, Issue 3, May 2010, Pages 196–211
Authors
, , , , , ,
Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
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