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A quantitative analysis of hepcidin promoter regulation using mathematical modelling techniques to reveal principles underlying systemic iron homeostasis

Banerji, Anashua

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Abstract

Since the development of advanced mathematical modelling techniques in biology, thermodynamics (and therefore equilibrium statistical mechanics) has played a key role in mathematically quantifying biological activities. We use this underlying notion of thermodynamic ‘micro-states’ to attempt to uncover how the hormone hepcidin under the influence of two major signalling pathways maintains systemic iron homeostasis. Systemic iron homeostasis involves a negative feedback circuit in which the expression level of the peptide hormone hepcidin depends on and controls the iron blood levels. Hepcidin expression is regulated by the BMP6/SMAD and IL6/STAT signalling cascades. Deregulation of either pathway causes iron storage diseases such as hemochromatosis or anaemia of inflammation (AI). We quantitatively analyzed how BMP and IL6 control hepcidin expression in human hepatoma (HuH7) cells. We used data from our experimental collaborators who measured transcription factor phosphorylation and reporter gene expression under co-stimulation conditions and perturbed the promoter by mutagenesis. We applied statistical data analysis and mathematical modelling to reveal possible biological mechanisms that control hepcidin expression at the promoter level. Specifically we develop a thermodynamic modelling framework that is able to simulate and predict possible molecular mechanisms that might underlie iron homeostasis by hepcidin. Our results reveal that hepcidin cross- regulation primarily occurs by combinatorial transcription factor binding to the promoter, whereas signalling crosstalk is insignificant. We find that the presence of two BMP-responsive elements in the promoter ensures high sensitivity towards the iron-sensing BMP signalling axis, which promotes iron homeostasis in vivo. IL6 stimulation reduces the promoter sensitivity to the BMP signal that may explain the disturbance of iron homeostasis in AI. We get to understand why the iron homeostasis circuit is sensitive to certain perturbations implicated in disease. Taken together, our work reveals how mathematical quantification and modelling can aid in understanding biological phenomenon that underlies gene expression.

Document type: Dissertation
Supervisor: Eils, Prof. Dr Roland
Place of Publication: Heidelberg
Date of thesis defense: 22 November 2013
Date Deposited: 28 May 2014 07:48
Date: 2013
Faculties / Institutes: The Faculty of Mathematics and Computer Science > Dean's Office of The Faculty of Mathematics and Computer Science
The Faculty of Mathematics and Computer Science > Department of Computer Science
Fakultät für Ingenieurwissenschaften > Institute of Pharmacy and Molecular Biotechnology
DDC-classification: 000 Generalities, Science
004 Data processing Computer science
010 Bibliography
500 Natural sciences and mathematics
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