Fig 1.
Scheme of the model including iron pools, iron fluxes and regulation of systemic iron levels by the hepcidin/ferroportin regulatory system.
The iron content of seven compartments is described within the model. Besides serum, liver, spleen, bone marrow, red blood cells, and duodenum, the compartment ‘other organs’ accounts for the iron content of the remaining murine body. Iron absorption and loss in the duodenum and iron loss via skin and fur are considered. Iron export from the peripheral compartments into serum is regulated by ferroportin. The model accounts for inhibition of Fpn transcription by inflammation, regulation of Fpn translation by intracellular iron, as well as hepcidin-mediated post-translational destabilization of ferroportin protein. Transcriptional regulation of hepcidin by the BMP6/SMAD and IL6/STAT pathways are included in the model. Furthermore, the model considers regulation of BMP6 by liver and plasma iron.
Fig 2.
Summary of the different steps of the study.
A-The mathematical model based on ordinary differential equations for the time dynamics of iron pools and regulating proteins was derived from the data. Starting from a core model topology, model parameters were found by fitting simulated time courses to experimental measurements of the systems response to different perturbations. The starting model topology was successively improved by including new regulatory mechanisms (e.g. regulation of iron flows by ferroportin, regulation of ferroportin by hepcidin) and the fitting cycle repeated until the model could fit well all of the data. B-The model prediction accuracy was tested for perturbations not used in training (new experiment in this study and previously published data not used in step A). The effect of the different perturbations was simulated by changing parameter values or initial conditions of the simulations. C-The model response to inflammation and dietary iron overload was analyzed to learn the quantitative contributions of the different mechanisms included to the overall response. Several mechanisms were removed one by one and the model simulations were compared to the results of the full model.
Table 1.
Experimental data used for model calibration.
The table summarizes the experimental perturbations, time scales and measured quantities for the different datasets used.
Fig 3.
LPS-induced dynamics of iron-related parameters under normal/enriched iron diet is well reproduced/predicted by the model.
A-Serum iron, B-Liver Iron, C-Liver hepcidin, D-Spleen iron, E-Liver BMP6, F-Liver Fpn mRNA, G-Spleen Fpn protein, H-Liver pSTAT, I-Liver pSMAD, J-Duodenum iron, K-Red blood cells iron, L-Liver Fpn protein. 4–6 weeks old male C57BL/6-mice were administrated a normal diet, containing 200 ppm iron (blue), or a high iron diet, supplemented by 2% carbonyl iron containing about 20000 ppm iron (red). After 4 weeks, mice were injected with 1 μg LPS/g body weight and sacrificed 6/18/48 hours after the injection. Experimental data are given as means with standard deviation of 4–6 replicates and the model simulation for the best fitting parameter set is represented by curves (solid lines: fitted time courses, dashed lines: predicted time courses). Data represented be empty circles were used in fitting as a part of the calibration data set (LPS response for normal diet and the iron parameters after 4 weeks of high iron diet before injection of LPS). The LPS response for high iron diet data (filled circles) was used to test the model predictions. See Materials and Methods for the description of the experiment.
Table 2.
Experimental data used for model validation.
The table summarizes the experimental perturbations, time scales and measured quantities for the different datasets used.
Fig 4.
Model correctly predicts responses to perturbations in the SMAD4-hepcidin-pathway as well as development of anemia under chronic inflammation.
A-Model quantitatively predicts experimentally measured responses for 2 months old C326S knock-in mice expressing a hepcidin-resistant FPN mutant or or SMAD4-knockout mice. The model simulations are shown as blue bars and the corresponding data from [37] and [53] as red bars, respectively. Fold changes are referred to the wildtype levels. The model error bars are calculated from the predictions of the 30 best fitting parameter sets (see S1 Text). B-Model prediction for body iron pools when ferroportin regulation by hepcidin is out of action in one of the indicated organs. Shown are model simulations whithout experimental validation. C-Model qualitatively reproduces the development of anemia of inflammation upon chronic elevation of body LPS. Simulation of plasma, RBC and liver iron evolution when the inflammatory Il6/STAT pathway is permanently activated by a persistent LPS stimulus (0.17 μg/g body weight). Shown are model simulations without a quantitative comparison to experiments.
Fig 5.
Hepcidin-mediated Fpn control and inhibition of Fpn transcription contribute to the acute inflammatory response.
A-Experimental data (means with standard deviation) and simulated data (lines) for serum iron content following peritoneal injection of LPS for mice maintained on a standard or iron-enriched diet. Comparison of the full model with models where either hepcidin-mediated ferroportin degradation or inflammation-mediated ferroportin mRNA reduction are removed. The simulations correspond to the best fitting parameter set. B-LPS-induced changes of liver ferroportin mRNA and protein levels relative to the normal diet steady state.
Fig 6.
Iron overload as a consequence of an iron enriched diet leads to the preferential iron accumulation in the liver, which is quantitatively reproduced by the model considering NTBI uptake and liver ferritin storage.
A-The measured distribution of iron between the organs is reproduced by the model fits for both normal and an iron enriched diet. The iron content of all compartments increases in mice maintained for 4 weeks on an iron rich diet, with most iron accumulating in the liver (arrows). B-Measured liver iron content under conditions of dietary iron overload and in HAMP-KO mice as well as best fit for the full model and models lacking NTBI uptake or liver ferritin storage, or both.
Fig 7.
Hepcidin-mediated control and dietary uptake saturation are critical parameters for serum iron homeostasis under dietary iron overload.
Simulation of steady state serum iron levels as a function of the dietary iron content for different model variants. For comparison, a linear increase of serum iron levels with increased dietary iron content is depicted.