Iron is an essential nutrient which must be provided in sufficient amounts to support growth of eukaryotic cells. All organisms devote specialized pathways to ensure proper delivery. Yet, a quantitative assessment of the intra-cellular iron concentration needed to allow the cell cycle to proceed in mammalian cells is missing. Starting from iron-depleted cell lines or primary hematopoietic progenitors prepared with clinically implemented iron chelators, replenishment via transferrin and other iron sources has been quantitatively monitored through the main endogenous markers of the cellular iron status, namely proteins involved in the uptake (transferrin receptor), the storage (ferritin), and the sensing (Iron Regulatory Proteins) of iron. When correlated with measurements of iron concentrations and indicators of growth, this minimally intrusive approach provided an unprecedented estimate of the intracellular iron concentration acting upon iron-centered regulatory pathways. The data were analyzed with the help of a previously developed theoretical treatment of cellular iron regulation. The minimal cellular iron concentration required for cell division was named functional iron concentration (FIC) to distinguish it from previous estimates of the cellular labile iron. The FIC falls in the low nanomolar range for all studied cells, including hematopoietic progenitors. These data shed new light on basic aspects of cellular iron homeostasis by demonstrating that sensing and regulation of iron occur well below the concentrations requiring storage or becoming noxious in pathological conditions. The quantitative assessment provided here is relevant for monitoring treatments of conditions in which iron provision must be controlled to avoid unwanted cellular proliferation.
This paper presents a novel framework for the modeling of biological networks. It makes use of recent tools analyzing the robust satisfaction of properties of (hybrid) dynamical systems. The main challenge of this approach as applied to biological systems is to get access to the relevant parameter sets despite gaps in the available knowledge. An initial estimate of useful parameters was sought by formalizing the known behavior of the biological network in the STL logic using the tool Breach. Then, once a set of parameter values consistent with known biological properties was found, we tried to locally expand it into the largest possible valid region. We applied this methodology in an effort to model and better understand the complex network regulating iron homeostasis in mammalian cells. This system plays an important role in many biological functions, including erythropoiesis, resistance against infections, and proliferation of cancer cells
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