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Becker et al., (2010). Covering a broad dynamic range: information processing at the erythropoietin receptor.

October 2011, model of the month by Nick Juty
Original model: BIOMD0000000271, BIOMD0000000272

Cell surface receptors respond to specific signaling molecules from other cells or from the environment, and enable the cell to respond in an appropriate way. These signaling molecules, or ligands, can be hormones, drugs or metabolites, and once bound the receptor-ligand complex can be internalised through endocytosis. The number of receptors at a cell surface can be up or down-regulated, and alter ligand sensitivity. Hereditary receptor mutations can be responsible for various disorders such as 'Familial cholesterolemia' and 'Congenital hypothyroidism'. In conjunction with their accessibility at cell surfaces, this makes receptors key targets in therapeutic interventions.

The precise manner in which ligand-encoded information is processed is well documented in some cases. Some of the various strategies are illustrated in Figure 1.

Figure 1

Figure 1: Strategies for processing ligand-encoded information over a broad range of ligand concentrations (a): Mobilisation (b), where binding of ligand induces some process whereby additional intracellular ligand is carried to the cell surface. Recycling (c), where ligand-bound receptors are internalised, ligand removed, and receptor returned to the cell surface. Turnover (d), where receptors are transported to the cell surface and others removed and degraded, independent of whether they are ligand-associated. Figure taken from [1].

Figure 2

Figure 2: EpoR model and calibration (A) Core mathematical model. Coloured boxes indicate the experimentally accessible quantities “Epo in medium” (Epo + dEpoe, red), “Epo on surface” (Epo-EpoR, blue), and “Epo in cells” (Epo-EpoRi + dEpoi, green). The model was calibrated using experimental data from a murine cell line: (B) Experimental data used in calibration, showing trajectory of best fit. (C) Model predicted curves for experimentally unmeasured variables. Figure taken from [1].

Some receptors can encounter a wide range of ligand concentration; The ligand for the erythropoietin receptor (EpoR) which is responsible for erythrocyte replenishment, can show a 1000-fold increase between basal and acute levels as indicated in plasma concentrations. EpoR itself is known to reside in large intracellular pools, with only a small fraction of the total EpoR ever reaching the cell surface. The authors [1] in this study investigated the receptor properties that enable EpoR to contend with such a broad range of ligand concentrations, and the dynamic processes why underlie it. Two models were created: a core model [BIOMD0000000271] which incorporated EpoR recycling and turnover (Figure 2A), and an extended model [(BIOMD0000000272)] which also contained mobilisation as a single parameter kmob to summarise the overall effect of this process.

The calibrated model, which incorporated experimental data, was used to predict values for variables that could not be measured experimentally. The ratio of EpoR turnover (kt = 0.033 min−1) to that of ligand-induced endocytosis (ke = 0.075 min−1) indicated that Epo bound receptors were endocytosed twice as much. This, in comparison to the Epidermal Growth Factor Receptor system, was a much lower value, and so was not thought to be sufficient to contribute significantly to ligand induced removal of EpoR, and attenuation of receptor activity. Figure 2C (left) of a model simulation indicates that native Epo is rapidly removed from the medium, by EpoR-Epo complex endocytosis, followed by its subsequent degradation. Native EpoR levels on the other hand were predicted to never fall below 25% of their maximal cell surface occupancy levels. Hence, the EpoR system should always remain ligand sensitive.

Time course analyses of receptor activation in a murine cell line (exogenously expressing EpoR) were used to confirm EpoR recovery at the cell surface, and were found to concur with model predictions; endocytotic removal of cell surface EpoR does not attenuate long-term receptor signaling, and receptor-mediated Epo degradation is a property of the general EpoR system. This finding challenges the currently held belief that EpoR degradation is a major cause of attenuation of receptor activation. Indeed, the model simulation results seem more consistent with those from the related cytokine receptor systems, for example the interleukin-3 receptor, which also demonstrates rapid ligand depletion and receptor recovery.

Model simulations were used to demonstrate the action of increasing ligand concentrations. The peak value of Epo-EpoR complexes is a result of the finite receptor on the plasma membrane (Figure 3A middle). A linear relation for integral EpoR occupancy representing the amount of cell surface Epo-EpoR complexes integrated over time was predicted even for high concentrations of Epo (Figure 3A right). To differentiate between receptor recycling and turnover, those parameters were varied. The linear relation of ligand concentration and integral EpoR occupancy was maintained, with different slopes, despite changes to the recycling rate (Figure 3C). This linearity was dependent on turnover, allowing cells to repopulate the membrane from intracellular receptor pools. Therefore EpoR turnover at high rates allows its function as a signal integrator, enabling cells to detect a broad range of ligand concentrations. This large turnover rate is supported from the large intracellular pools that serve as a reservoir.

Figure 3

Figure 3: Signal integration simulations (A) Peak amplitude of Epo-EpoR plasma membrance complexes (middle), and EpoR occupancy as an integral (right) (B) Experimental data (triangles) from immunoblots, Michaelis-Menten-like saturation and linear function were fitted to peak amplitude data (middle) and EpoR and JAK2 activation integrals shown. (C and D) Simulations for integral EpoR occupancy for various estimated rates of (C) recycling kex and (D) turnover kt. pEpoR and pJAK2 represent the phosphorylated proteins. Figure taken from [1].

Bibliographic References

  1. Becker V., Schilling M., Bachmann J., Baumann U., Raue A., Maiwald T., Timmer J. and Klingmüller U. Covering a Broad Dynamic Range: Information Processing at the Erythropoietin Receptor. Science 328(5984):1404-1408, 2010. [CiteXplore]