(623z) A Kinetic Model for the Storage of Iron In Ferritin

Ferritin plays a key role in the regulation of iron cellular levels, acting as the main intracellular iron storage protein. Studying the mechanism used by ferritin to store iron will lead to a better understanding of cellular iron homeostasis. We propose a kinetic model for iron storage in ferritin based on the main reactions for ferritin and iron, considering a heterogeneous population of ferritin species differentiated by the amount of iron stored in them. The dynamics of iron storage in ferritin during the process of intestinal iron absorption was studied simulating a set of differential equations based on the kinetic model. Kinetic parameters and enzymatic constants for the model were directly taken or calculated from published works. The simulation of the model generated results in agreement with experimental data. In particular, the model was able to recover the distribution pattern of iron into ferritin protein nanocages with different iron content experimentally observed, validating in this way the kinetic model and its parameters. Results highlight the function of ferritin as a controller of the cytoplasmic labile iron pool. Simulations show that ferritin stabilizes the cytosolic iron pool for a wide range of total iron concentrations, including the case when the system is subject of large iron perturbations, as well as iron starvation. According to our results the labile iron pool stabilization process occurs very fast, suggesting that ferritin is located in a first line of defense protecting the cell from excess or starvation iron conditions. This initial rapid response would be follow by slower transcriptional regulation mechanisms that promote long term adaptation to iron stress conditions. Finally, this results suggest that iron buffering and labile iron pool stabilization are possibly the main functions of ferritin in the cell.

This work was partially supported by the Millennium Scientific Initiative ICMproject P05-001-F, FONDECYT Research Initiation Grant 11080016 andFONDECYT Projects 1070840 and 1050048. AO-N was supported by an ICDBpost-doctoral fellowship