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Mathematical modeling of the dynamic storage of iron in ferritin.

Salgado JC, Olivera-Nappa A, Gerdtzen ZP, Tapia V, Theil EC, Conca C, Nuñez MT - BMC Syst Biol (2010)

Bottom Line: Simulation results showing the evolution of ferritin iron content following a pulse of iron were compared with experimental data for ferritin iron distribution obtained with purified ferritin incubated in vitro with different iron levels.Distinctive features observed experimentally were successfully captured by the model, namely the distribution pattern of iron into ferritin protein nanocages with different iron content and the role of ferritin as a controller of the cytosolic labile iron pool (cLIP).The results presented support the role of ferritin as an iron buffer in a cellular system.

View Article: PubMed Central - HTML - PubMed

Affiliation: Laboratory of Process Modeling and Distributed Computing, Department of Chemical Engineering and Biotechnology, University of Chile, Santiago, Chile. jsalgado@ing.uchile.cl

ABSTRACT

Background: Iron is essential for the maintenance of basic cellular processes. In the regulation of its cellular levels, ferritin acts as the main intracellular iron storage protein. In this work we present a mathematical model for the dynamics of iron storage in ferritin during the process of intestinal iron absorption. A set of differential equations were established considering kinetic expressions for the main reactions and mass balances for ferritin, iron and a discrete population of ferritin species defined by their respective iron content.

Results: Simulation results showing the evolution of ferritin iron content following a pulse of iron were compared with experimental data for ferritin iron distribution obtained with purified ferritin incubated in vitro with different iron levels. Distinctive features observed experimentally were successfully captured by the model, namely the distribution pattern of iron into ferritin protein nanocages with different iron content and the role of ferritin as a controller of the cytosolic labile iron pool (cLIP). Ferritin stabilizes the cLIP for a wide range of total intracellular iron concentrations, but the model predicts an exponential increment of the cLIP at an iron content > 2,500 Fe/ferritin protein cage, when the storage capacity of ferritin is exceeded.

Conclusions: The results presented support the role of ferritin as an iron buffer in a cellular system. Moreover, the model predicts desirable characteristics for a buffer protein such as effective removal of excess iron, which keeps intracellular cLIP levels approximately constant even when large perturbations are introduced, and a freely available source of iron under iron starvation. In addition, the simulated dynamics of the iron removal process are extremely fast, with ferritin acting as a first defense against dangerous iron fluctuations and providing the time required by the cell to activate slower transcriptional regulation mechanisms and adapt to iron stress conditions. In summary, the model captures the complexity of the iron-ferritin equilibrium, and can be used for further theoretical exploration of the role of ferritin in the regulation of intracellular labile iron levels and, in particular, as a relevant regulator of transepithelial iron transport during the process of intestinal iron absorption.

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Simulation results for the steady state distributions for a set of iron-to-ferritin ratios. Simulation results for the steady state distributions for a set of iron-to-ferritin ratios ranging from 100:1 to 2500:1. A soft transition between steady state distributions from low to high iron to ferritin ratios is observed.
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Figure 3: Simulation results for the steady state distributions for a set of iron-to-ferritin ratios. Simulation results for the steady state distributions for a set of iron-to-ferritin ratios ranging from 100:1 to 2500:1. A soft transition between steady state distributions from low to high iron to ferritin ratios is observed.

Mentions: Figure 3 shows simulated steady state distributions for a number of iron to ferritin ratios ranging from 100:1 to 2500:1. Simulation results show that as the iron-to-ferritin ratio is increased, there is a soft transition between steady state distributions from low to high iron-to-ferritin ratios. This result is in agreement with experimental data indicating that the model is able to capture steady state iron content distribution in ferritin in vitro. This suggests that regulation of the iron-ferritin system could be modelled as a control system designed to keep a given iron-to-ferritin ratio. This would allow the system to maintain a controlled cytosolic cLIP. For example, in DU145 cells, the cLIP was decreased in cells pretreated with the iron chelator desferrioxamine or when ferritin synthesis was inhibited by TNF treatment, which induced a drop in the amount of ferritin light chains [31]. Such a ferritin feedback loop where iron and oxygen are both regulatory signals for ferritin synthesis and substrates consumed in ferritin protein mineralization has recently been described [23].


Mathematical modeling of the dynamic storage of iron in ferritin.

Salgado JC, Olivera-Nappa A, Gerdtzen ZP, Tapia V, Theil EC, Conca C, Nuñez MT - BMC Syst Biol (2010)

Simulation results for the steady state distributions for a set of iron-to-ferritin ratios. Simulation results for the steady state distributions for a set of iron-to-ferritin ratios ranging from 100:1 to 2500:1. A soft transition between steady state distributions from low to high iron to ferritin ratios is observed.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2992510&req=5

Figure 3: Simulation results for the steady state distributions for a set of iron-to-ferritin ratios. Simulation results for the steady state distributions for a set of iron-to-ferritin ratios ranging from 100:1 to 2500:1. A soft transition between steady state distributions from low to high iron to ferritin ratios is observed.
Mentions: Figure 3 shows simulated steady state distributions for a number of iron to ferritin ratios ranging from 100:1 to 2500:1. Simulation results show that as the iron-to-ferritin ratio is increased, there is a soft transition between steady state distributions from low to high iron-to-ferritin ratios. This result is in agreement with experimental data indicating that the model is able to capture steady state iron content distribution in ferritin in vitro. This suggests that regulation of the iron-ferritin system could be modelled as a control system designed to keep a given iron-to-ferritin ratio. This would allow the system to maintain a controlled cytosolic cLIP. For example, in DU145 cells, the cLIP was decreased in cells pretreated with the iron chelator desferrioxamine or when ferritin synthesis was inhibited by TNF treatment, which induced a drop in the amount of ferritin light chains [31]. Such a ferritin feedback loop where iron and oxygen are both regulatory signals for ferritin synthesis and substrates consumed in ferritin protein mineralization has recently been described [23].

Bottom Line: Simulation results showing the evolution of ferritin iron content following a pulse of iron were compared with experimental data for ferritin iron distribution obtained with purified ferritin incubated in vitro with different iron levels.Distinctive features observed experimentally were successfully captured by the model, namely the distribution pattern of iron into ferritin protein nanocages with different iron content and the role of ferritin as a controller of the cytosolic labile iron pool (cLIP).The results presented support the role of ferritin as an iron buffer in a cellular system.

View Article: PubMed Central - HTML - PubMed

Affiliation: Laboratory of Process Modeling and Distributed Computing, Department of Chemical Engineering and Biotechnology, University of Chile, Santiago, Chile. jsalgado@ing.uchile.cl

ABSTRACT

Background: Iron is essential for the maintenance of basic cellular processes. In the regulation of its cellular levels, ferritin acts as the main intracellular iron storage protein. In this work we present a mathematical model for the dynamics of iron storage in ferritin during the process of intestinal iron absorption. A set of differential equations were established considering kinetic expressions for the main reactions and mass balances for ferritin, iron and a discrete population of ferritin species defined by their respective iron content.

Results: Simulation results showing the evolution of ferritin iron content following a pulse of iron were compared with experimental data for ferritin iron distribution obtained with purified ferritin incubated in vitro with different iron levels. Distinctive features observed experimentally were successfully captured by the model, namely the distribution pattern of iron into ferritin protein nanocages with different iron content and the role of ferritin as a controller of the cytosolic labile iron pool (cLIP). Ferritin stabilizes the cLIP for a wide range of total intracellular iron concentrations, but the model predicts an exponential increment of the cLIP at an iron content > 2,500 Fe/ferritin protein cage, when the storage capacity of ferritin is exceeded.

Conclusions: The results presented support the role of ferritin as an iron buffer in a cellular system. Moreover, the model predicts desirable characteristics for a buffer protein such as effective removal of excess iron, which keeps intracellular cLIP levels approximately constant even when large perturbations are introduced, and a freely available source of iron under iron starvation. In addition, the simulated dynamics of the iron removal process are extremely fast, with ferritin acting as a first defense against dangerous iron fluctuations and providing the time required by the cell to activate slower transcriptional regulation mechanisms and adapt to iron stress conditions. In summary, the model captures the complexity of the iron-ferritin equilibrium, and can be used for further theoretical exploration of the role of ferritin in the regulation of intracellular labile iron levels and, in particular, as a relevant regulator of transepithelial iron transport during the process of intestinal iron absorption.

Show MeSH
Related in: MedlinePlus