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      A Multi-Scale Model of Hepcidin Promoter Regulation Reveals Factors Controlling Systemic Iron Homeostasis

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          Abstract

          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 signaling cascades. Deregulation of either pathway causes iron-related diseases such as hemochromatosis or anemia of inflammation. We quantitatively analyzed how BMP6 and IL6 control hepcidin expression. Transcription factor (TF) phosphorylation and reporter gene expression were measured under co-stimulation conditions, and the promoter was perturbed by mutagenesis. Using mathematical modeling, we systematically analyzed potential mechanisms of cooperative and competitive promoter regulation by the transcription factors, and experimentally validated the model predictions. Our results reveal that hepcidin cross-regulation primarily occurs by combinatorial transcription factor binding to the promoter, whereas signaling crosstalk is insignificant. We find that the presence of two BMP-responsive elements enhances the steepness of the promoter response towards the iron-sensing BMP signaling axis, which promotes iron homeostasis in vivo. IL6 co-stimulation reduces the promoter sensitivity towards the BMP signal, because the SMAD and STAT transcription factors compete for recruiting RNA polymerase to the transcription start site. This may explain why inflammatory signals disturb iron homeostasis in anemia of inflammation. Taken together, our results reveal why the iron homeostasis circuit is sensitive to perturbations implicated in disease.

          Author Summary

          The nutritional iron uptake is tightly regulated because the body has limited capacity of iron excretion. Mammals maintain iron homeostasis by a negative feedback loop, in which the peptide hepcidin senses the iron blood level and controls iron resorption. Molecular perturbations in the homeostasis loop lead to iron-related diseases such as hemochromatosis or anemia of inflammation. Quantitative studies are required to understand the dynamics of the iron homeostasis circuitry in health and disease. We investigated how the biological activity of hepcidin is regulated by combining experiments with mathematical modeling. We present a multi-scale model that describes the signaling network and the gene promoter controlling hepcidin expression. Possible scenarios of hepcidin regulation were systematically tested against experimental data, and interpreted using a network model of iron metabolism in vivo. The analysis showed that the presence of multiple redundant regulatory elements in the hepcidin gene promoter facilitates homeostasis, because changes in iron blood levels are sensed with high sensitivity. We further suggest that inflammatory signals establish molecular competition at the hepcidin promoter, thereby reducing its iron sensitivity and leading to a loss of homeostasis in anemia of inflammation. We conclude that quantitative insights into hepcidin expression regulation explain features of systemic iron homeostasis.

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          Most cited references45

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          Hepcidin, a putative mediator of anemia of inflammation, is a type II acute-phase protein.

          Hepcidin is a liver-made peptide proposed to be a central regulator of intestinal iron absorption and iron recycling by macrophages. In animal models, hepcidin is induced by inflammation and iron loading, but its regulation in humans has not been studied. We report that urinary excretion of hepcidin was greatly increased in patients with iron overload, infections, or inflammatory diseases. Hepcidin excretion correlated well with serum ferritin levels, which are regulated by similar pathologic stimuli. In vitro iron loading of primary human hepatocytes, however, unexpectedly down-regulated hepcidin mRNA, suggesting that in vivo regulation of hepcidin expression by iron stores involves complex indirect effects. Hepcidin mRNA was dramatically induced by interleukin-6 (IL-6) in vitro, but not by IL-1 or tumor necrosis factor alpha (TNF-alpha), demonstrating that human hepcidin is a type II acute-phase reactant. The linkage of hepcidin induction to inflammation in humans supports its proposed role as a key mediator of anemia of inflammation.
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            Transcriptional regulation by the numbers: models.

            The expression of genes is regularly characterized with respect to how much, how fast, when and where. Such quantitative data demands quantitative models. Thermodynamic models are based on the assumption that the level of gene expression is proportional to the equilibrium probability that RNA polymerase (RNAP) is bound to the promoter of interest. Statistical mechanics provides a framework for computing these probabilities. Within this framework, interactions of activators, repressors, helper molecules and RNAP are described by a single function, the "regulation factor". This analysis culminates in an expression for the probability of RNA polymerase binding at the promoter of interest as a function of the number of regulatory proteins in the cell.
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              Interleukin-6 induces hepcidin expression through STAT3.

              Iron homeostasis is maintained through meticulous regulation of circulating hepcidin levels. Hepcidin levels that are inappropriately low or high result in iron overload or iron deficiency, respectively. Although hypoxia, erythroid demand, iron, and inflammation are all known to influence hepcidin expression, the mechanisms responsible are not well defined. In this report we show that the inflammatory cytokine interleukin-6 (IL-6) directly regulates hepcidin through induction and subsequent promoter binding of signal transducer and activator of transcription 3 (STAT3). STAT3 is necessary and sufficient for the IL-6 responsiveness of the hepcidin promoter. Our findings provide a mechanism by which hepcidin can be regulated by inflammation or, in the absence of inflammatory stimuli, by alternative mechanisms leading to STAT3 activation.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput. Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, USA )
                1553-734X
                1553-7358
                January 2014
                January 2014
                2 January 2014
                : 10
                : 1
                : e1003421
                Affiliations
                [1 ]Department of Pediatric Oncology, Hematology and Immunology, University Hospital of Heidelberg, Heidelberg, Germany
                [2 ]Molecular Medicine Partnership Unit, Heidelberg, Germany
                [3 ]European Molecular Biology Laboratory, Heidelberg, Germany
                [4 ]Institute of Molecular Biology (IMB), Mainz, Germany
                [5 ]BioQuant, Heidelberg, Germany
                Brigham & Women's Hospital and Harvard Medical School, United States of America
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: MUM SL. Performed the experiments: GC FdA. Analyzed the data: GC AB FdA MUM SL. Wrote the paper: SL. Performed the mathematical modeling: AB SL.

                Article
                PCOMPBIOL-D-13-00799
                10.1371/journal.pcbi.1003421
                3879105
                24391488
                3e761214-5524-45c6-9162-f0ad459261ec
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 8 May 2013
                : 8 November 2013
                Page count
                Pages: 13
                Funding
                This work was supported by the BMBF (Virtual Liver Network, to SL and MUM). SL is supported by the e:bio junior group program. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article

                Quantitative & Systems biology
                Quantitative & Systems biology

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