Parmar2019 - Iron Mouse PV3 - tracer
Iron Mouse PV3
"A computational model to understand mouse iron physiology and diseases"
By Jignesh Parmar and Pedro Mendes
Parameter estimation using radioactive tracer data
This is a dynamic model of iron distribution in mice, covering seven compartments: plasma, bone marrow, red blood cells (RBC), spleen, duodenum, liver, and the rest of the body . This is mostly a physiological model with regulation by hepcidin and erythropoietin, including only a minimal amount of molecular details.
This version of the model includes normal iron species and radioactive-labelled tracer iron species. It was used specifically for parameter estimation using the data from Schümann et al. 2007 (see also Lopes et al. 2010 and Parmar et al. 2017) from three experiments of mice fed adequate, iron-deficient, and iron-rich diets. Mice in all three dietary regimes were injected with a radiactive tracer and its distribution measured along time. The model parameters were adjusted in order to minimize the distance of the model to the data of all three experiements simultaneously.
Model validation was carried out with another version of this model where the radioactive species are ommited but all parameters remain with the values determined here (see accompanying model). The model is able to match the phenotype of several iron-related diseases.
- A computational model to understand mouse iron physiology and disease.
- Jignesh H. Parmar, Mendes P
- PLoS computational biology , 1/ 2019 , Volume 15 , Issue 1 , pages: e1006680 , PubMed ID: 30608934
- Center for Quantitative Medicine and Department of Cell Biology, University of Connecticut School of Medicine, Farmington, Connecticut, United States of America.
- It is well known that iron is an essential element for life but is toxic when in excess or in certain forms. Accordingly there are many diseases that result directly from either lack or excess of iron. Yet many molecular and physiological aspects of iron regulation have only been discovered recently and others are still elusive. There is still no good quantitative and dynamic description of iron absorption, distribution, storage and mobilization that agrees with the wide array of phenotypes presented in several iron-related diseases. The present work addresses this issue by developing a mathematical model of iron distribution in mice calibrated with ferrokinetic data and subsequently validated against data from mouse models of iron disorders, such as hemochromatosis, β-thalassemia, atransferrinemia and anemia of inflammation. To adequately fit the ferrokinetic data required inclusion of the following mechanisms: a) transferrin-mediated iron delivery to tissues, b) induction of hepcidin by transferrin-bound iron, c) ferroportin-dependent iron export regulated by hepcidin, d) erythropoietin regulation of erythropoiesis, and e) liver uptake of NTBI. The utility of the model to simulate disease interventions was demonstrated by using it to investigate the outcome of different schedules of transferrin treatment in β-thalassemia.
Submitter of this revision: Krishna Kumar Tiwari
Modellers: Pedro Mendes, Krishna Kumar Tiwari
Connected external resources
OmicsDI Impact Metrics
|IronMousePV3_tracer.xml||SBML L2V4 representation of Iron Mouse PV3 - tracer||303.60 KB||Preview | Download|
|IronMousePV3_tracer.cps||Parmar2018 - IronMouse PV3 - tracer for parameter estimation, COPASI file||827.85 KB||Preview | Download|
|LopesData_40_Adequate_Deficient_Rich.txt||Parmar2018 - IronMouse PV3 - tracer for parameter estimation, data file||1.10 KB||Preview | Download|
- Model originally submitted by : Pedro Mendes
- Submitted: Jan 7, 2019 2:55:15 PM
- Last Modified: Sep 16, 2022 11:44:13 AM
- Submitted on: Sep 16, 2022 11:44:13 AM
- Submitted by: Krishna Kumar Tiwari
- With comment: added publication details and made public
- Submitted on: Jan 7, 2019 2:55:15 PM
- Submitted by: Pedro Mendes
- With comment: This model has been published and can now be made public (I cannot see where in the interface I could change it to public!)
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