Role of Endosomal Trafficking Dynamics on the Regulation of Hepatic Insulin Receptor Activity: Models for Fao Cells

  • Sharon S. Hori
  • Irwin J. Kurland
  • Joseph J. DiStefanoIII

Evidence indicates that endosomal insulin receptor (IR) trafficking plays a role in regulating insulin signal transduction. To evaluate its importance, we developed a series of biokinetic models for quantifying activated surface and endosomal IR dynamics from published experimental data. Starting with a published two-compartment Fao hepatoma model, a four-pool model was formulated that depicts IR autophosphorylation after receptor binding, IR endosomal internalization/trafficking, insulin dissociation from and dephosphorylation of internalized IR, and recycling of unliganded, dephosphorylated IR to the plasma membrane. Quantification required three additional data sets, two measured, but unmodeled by the same group. A five-pool model created to include endosomal trafficking of the nonphosphorylated insulin-IR complex was fitted using the same data sets, augmented with another published data set. Creation of a six-pool model added the physiologically relevant dissociation of insulin ligand from the activated endosomal IR. More importantly, all three models, validated against additional data not used in model fitting, predict that, mechanistically, internalization of activated IR is a rate-limiting step, at least under the receptor saturating conditions of the fitting data. This rate includes the transit time to a site where insulin dissociation from and/or dephosphorylation of the IR occurs by docking with protein-tyrosine phosphatases (PTPases), or where a sufficient conformational change occurs in the IR, perhaps due to insulin-IR dissociation, where associated PTPases may complete IR dephosphorylation. Our new models indicate that key events in endosomal IR trafficking have significance in mediating IR activity, possibly serving to regulate insulin signal transduction.


Insulin receptor Insulin signaling Receptor endocytosis Receptor recycling Mathematical model Parameter estimation 



This investigation was supported in part by a National Institutes of Health (NIH), National Institute of General Medical Sciences (NIGMS), GM008185 to SSH, an NIH, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), R01 DK58132 to IJK and NIH-NIDDK R01 DK34839 to JJD.


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Copyright information

© Biomedical Engineering Society 2006

Authors and Affiliations

  • Sharon S. Hori
    • 1
    • 3
  • Irwin J. Kurland
    • 2
  • Joseph J. DiStefanoIII
    • 1
  1. 1.Biocybernetics Laboratory, Departments of Computer Science and Medicine and Biomedical Engineering Interdepartmental ProgramUniversity of CaliforniaLos AngelesUSA
  2. 2.Departments of MedicinePharmacological Sciences and Physiology and Biophysics, SUNYStony BrookUSA
  3. 3.Department of Computer Science, UCLABiocybernetics LaboratoryLos AngelesUSA

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