Mouse Iron Distribution - Rich and Deficient iron diets (tracer)

  public model
Model Identifier
BIOMD0000000734
Short description

Mouse Iron Distribution Dynamics

Dynamic model of iron distribution in mice. This model attempts to fit the radioiron tracer data from Lopes et al. 2010 for mice fed iron deficient and rich diets by adjusting the rate of iron intake (vDiet) and the hepcidin synthesis rate (vhepcidin) independently for each experiment. All other parameters are those that provide the best fit for the adequate diet.

This model includes the radioiron tracer species.

Differences in parameter values between deficient, rich, and adequate diets:

Diet vDiet vhepcidin
Adequate 0.00377422 1.7393e-08
Deficient 0 8.54927e-09
Rich 0.00415624 2.30942e-08
Format
SBML (L2V4)
Related Publication
  • Modeling the dynamics of mouse iron body distribution: hepcidin is necessary but not sufficient.
  • Parmar JH, Davis G, Shevchuk H, Mendes P
  • BMC systems biology , 5/ 2017 , Volume 11 , Issue 1 , pages: 57 , PubMed ID: 28521769
  • Center for Quantitative Medicine and Department of Cell Biology, UConn Health, Farmington, CT, 06030, USA.
  • Iron is an essential element of most living organisms but is a dangerous substance when poorly liganded in solution. The hormone hepcidin regulates the export of iron from tissues to the plasma contributing to iron homeostasis and also restricting its availability to infectious agents. Disruption of iron regulation in mammals leads to disorders such as anemia and hemochromatosis, and contributes to the etiology of several other diseases such as cancer and neurodegenerative diseases. Here we test the hypothesis that hepcidin alone is able to regulate iron distribution in different dietary regimes in the mouse using a computational model of iron distribution calibrated with radioiron tracer data.A model was developed and calibrated to the data from adequate iron diet, which was able to simulate the iron distribution under a low iron diet. However simulation of high iron diet shows considerable deviations from the experimental data. Namely the model predicts more iron in red blood cells and less iron in the liver than what was observed in experiments.These results suggest that hepcidin alone is not sufficient to regulate iron homeostasis in high iron conditions and that other factors are important. The model was able to simulate anemia when hepcidin was increased but was unable to simulate hemochromatosis when hepcidin was suppressed, suggesting that in high iron conditions additional regulatory interactions are important.
Contributors
Submitter of the first revision: Krishna Kumar Tiwari
Submitter of this revision: Krishna Kumar Tiwari
Modellers: Krishna Kumar Tiwari

Metadata information

hasTaxon (1 statement)
Taxonomy Mus musculus

is (3 statements)
Gene Ontology iron ion homeostasis
BioModels Database MODEL1903040001
BioModels Database BIOMD0000000734

hasProperty (1 statement)
Mathematical Modelling Ontology Ordinary differential equation model

Curation status
Curated
Modelling approach(es)
ordinary differential equation model
Tags

Connected external resources

SBGN view in Newt Editor

Name Description Size Actions

Model files
BIOMD0000000734.xml SBML L2V4 representation of Parmar2017 - Mouse Iron Distribution - Deficient and rich iron diet (Tracer) 197.05 KB Preview | Download

Additional files
Fig4_all.png Figure 4 result images (reproduced) 123.75 KB Preview | Download
Parmar2017_Deficient_Rich_tracer.cps COPASI 4.24 (build196) file depicting literature figure 3 and 4. 293.47 KB Preview | Download
Parmar2017_Deficient_Rich_tracer.sedml SEDML file 1.19 KB Preview | Download

  • Model originally submitted by : Krishna Kumar Tiwari
  • Submitted: Mar 4, 2019 4:40:13 PM
  • Last Modified: Oct 10, 2019 4:16:43 PM
Revisions
  • Version: 6 public model Download this version
    • Submitted on: Oct 10, 2019 4:16:43 PM
    • Submitted by: Krishna Kumar Tiwari
    • With comment: Automatically added model identifier BIOMD0000000734
  • Version: 4 public model Download this version
    • Submitted on: Mar 4, 2019 4:40:13 PM
    • Submitted by: Krishna Kumar Tiwari
    • With comment: Automatically added model identifier BIOMD0000000734

(*) You might be seeing discontinuous revisions as only public revisions are displayed here. Any private revisions unpublished model revision of this model will only be shown to the submitter and their collaborators.

Legends
: Variable used inside SBML models


Species
Species Initial Concentration/Amount
FeDuo 0

iron cation 		0.0117590568706314 mol
FeSpleen

iron cation 		0.0 mol
Fe2Tf

Serotransferrin ; iron(3+) 		0.0 mol
Fe2Tf 0

iron(3+) ; Serotransferrin 		1.35248196757048E-5 mol
Tf

Serotransferrin 		1.5821833083706E-5 mol
Fe1Tf 0

Serotransferrin ; iron(3+) 		9.35334724058915E-6 mol
Reactions
Reactions Rate Parameters
Fe2Tf_0 => FeDuo_0 + Tf kInDuo*Fe2Tf_0*Plasma kInDuo = 0.0689984226081531
FeSpleen => NTBI; FeSpleen_0, Hepcidin VSpleenNTBI*Spleen*FeSpleen/((Km+FeSpleen+FeSpleen_0)*(1+Hepcidin/Ki)) VSpleenNTBI = 1.342204923; Km = 0.0159421218669513; Ki = 1.0E-9
FeBM_0 => FeSpleen kBMSpleen*FeBM_0*BoneMarrow kBMSpleen = 0.061902954378781
Fe2Tf => FeBM_0 + FeBM + Tf kInBM*Fe2Tf*Plasma kInBM = 15.7690636138556
Fe2Tf => FeRest + FeRest_0 + Tf kInRest*Fe2Tf*Plasma kInRest = 6.16356235352873
Fe1Tf_0 + NTBI_0 => Fe2Tf_0 Plasma*kFe1Tf_Fe2Tf*Fe1Tf_0*NTBI_0 kFe1Tf_Fe2Tf = 1.084322005E9
Fe1Tf + NTBI_0 => Fe2Tf Plasma*kFe1Tf_Fe2Tf*Fe1Tf*NTBI_0 kFe1Tf_Fe2Tf = 1.084322005E9
Fe2Tf_ => FeRest + Tf kInRest*Fe2Tf_*Plasma kInRest = 6.16356235352873
Fe1Tf + NTBI => Fe2Tf_ Plasma*kFe1Tf_Fe2Tf*Fe1Tf*NTBI kFe1Tf_Fe2Tf = 1.084322005E9
Curator's comment:
(added: 04 Mar 2019, 16:36:05, updated: 04 Mar 2019, 16:36:05)
Figure Reproduced: Figure 3 and 4. Uploaded image in curation section is figure 3 and image for figure 4 will be updated under additional file section. Simulation Protocol: simulated for 30 days post NTBI stimulation. Run need to be done as Tasks --> parameter estimation --> run. Model is reproduced and simulated using COPASI 2.64 (build196) and figures are created using libreoffice calc.