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Quantitative modeling and analytic assessment of the transcription dynamics of the XlnR regulon in Aspergillus niger

Overview of attention for article published in BMC Systems Biology, January 2016
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Title
Quantitative modeling and analytic assessment of the transcription dynamics of the XlnR regulon in Aspergillus niger
Published in
BMC Systems Biology, January 2016
DOI 10.1186/s12918-016-0257-4
Pubmed ID
Authors

Jimmy Omony, Astrid R. Mach-Aigner, Gerrit van Straten, Anton J.B. van Boxtel

Abstract

Transcription of genes coding for xylanolytic and cellulolytic enzymes in Aspergillus niger is controlled by the transactivator XlnR. In this work we analyse and model the transcription dynamics in the XlnR regulon from time-course data of the messenger RNA levels for some XlnR target genes, obtained by reverse transcription quantitative PCR (RT-qPCR). Induction of transcription was achieved using low (1 mM) and high (50 mM) concentrations of D-xylose (Xyl). We investigated the wild type strain (Wt) and a mutant strain with partial loss-of-function of the carbon catabolite repressor CreA (Mt). An improved kinetic differential equation model based on two antagonistic Hill functions was proposed, and fitted to the time-course RT-qPCR data from the Wt and the Mt by numerical optimization of the parameters. We show that perturbing the XlnR regulon with Xyl in low and high concentrations results in different expression levels and transcription dynamics of the target genes. At least four distinct transcription profiles were observed, particularly for the usage of 50 mM Xyl. Higher transcript levels were observed for some genes after induction with 1 mM rather than 50 mM Xyl, especially in the Mt. Grouping the expression profiles of the investigated genes has improved our understanding of induction by Xyl and the according regulatory role of CreA. The model explains for the higher expression levels at 1 mM versus 50 mM in both Wt and Mt. It does not yet fully encapsulate the effect of partial loss-of-function of CreA in the Mt. The model describes the dynamics in most of the data and elucidates the time-dynamics of the two major regulatory mechanisms: i) the activation by XlnR, and ii) the carbon catabolite repression by CreA.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Professor 3 17%
Researcher 3 17%
Other 2 11%
Student > Ph. D. Student 2 11%
Student > Doctoral Student 1 6%
Other 3 17%
Unknown 4 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 50%
Biochemistry, Genetics and Molecular Biology 2 11%
Computer Science 1 6%
Medicine and Dentistry 1 6%
Unknown 5 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 January 2016.
All research outputs
#18,437,241
of 22,842,950 outputs
Outputs from BMC Systems Biology
#834
of 1,142 outputs
Outputs of similar age
#286,818
of 396,346 outputs
Outputs of similar age from BMC Systems Biology
#33
of 37 outputs
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