title: Quantitative modeling and analytic assessment of the transcription dynamics of the XlnR regulon in Aspergillus niger.
abstract: BACKGROUND
  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).
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Molecular Genetics Department, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Nijenborgh 7, Groningen, 9747 AG, The Netherlands. jimmy.omony@gmail.com.|Biobased Chemistry and Technology, Wageningen University, P.O. Box 17, Wageningen, 6700 AA, The Netherlands. jimmy.omony@gmail.com.
authors.forename: Jimmy
authors.initials: J
authors.lastname: Omony
authors.affiliation: TU Wien, Institute of Chemical Engineering, Gumpendorfer Str. 1a, Wien, A-1060, Austria. astrid.mach-aigner@tuwien.ac.at.
authors.forename: Astrid R
authors.initials: AR
authors.lastname: Mach-Aigner
authors.affiliation: Biobased Chemistry and Technology, Wageningen University, P.O. Box 17, Wageningen, 6700 AA, The Netherlands. Gerrit.vanStraten@wur.nl.
authors.forename: Gerrit
authors.initials: G
authors.lastname: van Straten
authors.affiliation: Biobased Chemistry and Technology, Wageningen University, P.O. Box 17, Wageningen, 6700 AA, The Netherlands. Ton.vanBoxtel@wur.nl.
authors.forename: Anton J B
authors.initials: AJ
authors.lastname: van Boxtel
mesh_terms: D001234:Aspergillus niger / Q000235:genetics* / Q000378:metabolism; D025461:Feedback, Physiological; D005656:Fungal Proteins / Q000378:metabolism; D008957:Models, Genetic; D018085:Regulon / Q000235:genetics*; D014158:Transcription, Genetic
chemical_list: D005656:Fungal Proteins
references.citation: Appl Microbiol Biotechnol. 2008 Feb;78(2):211-20
references.pmid: 18197406
references.citation: Philos Trans A Math Phys Eng Sci. 2008 Feb 28;366(1865):519-44
references.pmid: 17698469
references.citation: Fungal Genet Biol. 2009 Mar;46 Suppl 1:S170-S179
references.pmid: 19618506
references.citation: Cell. 2010 Jan 8;140(1):13-8
references.pmid: 20085698
references.citation: PLoS Comput Biol. 2010 Mar;6(3):e1000696
references.pmid: 20221262
references.citation: J Integr Bioinform. 2010;7(3). doi: 10.2390/biecoll-jib-2010-133
references.pmid: 20375457
references.citation: BMC Syst Biol. 2011;5:14
references.pmid: 21255466
references.citation: BMC Syst Biol. 2011;5 Suppl 1:S14
references.pmid: 21689473
references.citation: Appl Environ Microbiol. 2012 May;78(9):3145-55
references.pmid: 22344641
references.citation: Neuron. 2000 Jun;26(3):567-80
references.pmid: 10896154
references.citation: Appl Environ Microbiol. 1999 Dec;65(12):5500-3
references.pmid: 10584009
references.citation: IEEE/ACM Trans Comput Biol Bioinform. 2012 Sep-Oct;9(5):1316-25
references.pmid: 22529332
references.citation: J Comput Biol. 2002;9(1):67-103
references.pmid: 11911796
references.citation: Genome Res. 2003 Nov;13(11):2467-74
references.pmid: 14559783
references.citation: Microbiology. 2004 May;150(Pt 5):1367-75
references.pmid: 15133098
references.citation: Sci STKE. 2004 May 11;2004(232):pe20
references.pmid: 15138328
references.citation: Biophys J. 1971 Jan;11(1):11-27
references.pmid: 4923389
references.citation: Mol Gen Genet. 1973 Nov 2;126(2):111-41
references.pmid: 4591376
references.citation: EMBO J. 1993 Apr;12(4):1375-85
references.pmid: 8467796
references.citation: Microbiology. 1997 Sep;143 ( Pt 9):2991-8
references.pmid: 9308182
references.citation: Mol Microbiol. 1998 Jan;27(1):131-42
references.pmid: 9466262
references.citation: Appl Environ Microbiol. 1998 Oct;64(10):3615-9
references.pmid: 9758775
references.citation: Bioinformatics. 1998;14(10):869-83
references.pmid: 9927716
references.citation: Appl Environ Microbiol. 1999 Jun;65(6):2453-60
references.pmid: 10347026
references.citation: Res Microbiol. 1999 May;150(4):281-5
references.pmid: 10376490
references.citation: Appl Environ Microbiol. 1999 Oct;65(10):4340-5
references.pmid: 10508057
references.citation: BMC Bioinformatics. 2007;8:20
references.pmid: 17244365
references.citation: PLoS Comput Biol. 2009 May;5(5):e1000390
references.pmid: 19468305