Type 2 diabetes is a metabolic disease that profoundly affects energy homeostasis. The disease involves failure at several levels and subsystems and is characterized by insulin resistance in target cells and tissues (i.e. by impaired intracellular insulin signaling). We have previously used an iterative experimental-theoretical approach to unravel the early insulin signaling events in primary human adipocytes. That study, like most insulin signaling studies, is based on in vitro experimental examination of cells, and the in vivo relevance of such studies for human beings has not been systematically examined. Herein, we develop a hierarchical model of the adipose tissue, which links intracellular insulin control of glucose transport in human primary adipocytes with whole-body glucose homeostasis. An iterative approach between experiments and minimal modeling allowed us to conclude that it is not possible to scale up the experimentally determined glucose uptake by the isolated adipocytes to match the glucose uptake profile of the adipose tissue in vivo. However, a model that additionally includes insulin effects on blood flow in the adipose tissue and GLUT4 translocation due to cell handling can explain all data, but neither of these additions is sufficient independently. We also extend the minimal model to include hierarchical dynamic links to more detailed models (both to our own models and to those by others), which act as submodules that can be turned on or off. The resulting multilevel hierarchical model can merge detailed results on different subsystems into a coherent understanding of whole-body glucose homeostasis. This hierarchical modeling can potentially create bridges between other experimental model systems and the in vivo human situation and offers a framework for systematic evaluation of the physiological relevance of in vitro obtained molecular/cellular experimental data.

Insulin signaling through insulin receptor (IR) and insulin receptor substrate-1 (IRS1) is important for insulin control of target cells. We have previously demonstrated a rapid and simultaneous overshoot behavior in the phosphorylation dynamics of IR and IRS1 in human adipocytes. Herein, we demonstrate that in murine adipocytes a similar overshoot behavior is not simultaneous for IR and IRS1. The peak of IRS1 phosphorylation, which is a direct consequence of the phosphorylation and the activation of IR, occurs earlier than the peak of IR phosphorylation. We used a conclusive modeling framework to unravel the mechanisms behind this counter-intuitive order of phosphorylation. Through a number of rejections, we demonstrate that two fundamentally different mechanisms may create the reversed order of peaks: (i) two pools of phosphorylated IR, where a large pool of internalized IR peaks late, but phosphorylation of IRS1 is governed by a small plasma membrane-localized pool of IR with an early peak, or (ii) inhibition of the IR-catalyzed phosphorylation of IRS1 by negative feedback. Although (i) may explain the reversed order, this two-pool hypothesis alone requires extensive internalization of IR, which is not supported by experimental data. However, with the additional assumption of limiting concentrations of IRS1, (i) can explain all data. Also, (ii) can explain all available data. Our findings illustrate how modeling can potentiate reasoning, to help draw nontrivial conclusions regarding competing mechanisms in signaling networks. Our work also reveals new differences between human and murine insulin signaling.

Type 2 diabetes originates in an expanding adipose tissue that for unknown reasons becomes insulin resistant. Insulin resistance reflects impairments in insulin signaling, but mechanisms involved are unclear because current research is fragmented. We report a systems-level mechanistic understanding of insulin resistance in humans. We developed a dynamic mathematical model of insulin signaling – normally and in diabetes – based on quantitative steady-state and dynamic time-course data on signaling intermediaries in human mature adipocytes. At the core of insulin resistance is attenuation of a positive feedback from mammalian target of rapamycin in complex with raptor (mTORC1) to the insulin receptor substrate-1 (IRS1), which explains reduced sensitivity and signal strength throughout the signaling network. We demonstrate the potential of the model for identification of drug targets, e.g. increasing the feedback restores insulin signaling. Our findings suggest that insulin resistance in an expanded adipose tissue results from cell growth restriction to prevent cell necrosis.

Insulin acutely controls metabolism in adipocytes, but also nuclear transcription through the “mitogenic” signaling pathway mediated by Map-kinases ERK1/2 (ERK). The cellular metabolic response to insulin is attenuated in insulin resistance and type 2 diabetes, but whether this involves also signaling through ERK is unclear. Based on experimental data from primary mature human adipocytes from diabetic and nondiabetic individuals, we demonstrate a network-wide, model-based analysis of insulin signaling through ERK to phosphorylation of transcription factor Elk1 integrated with signaling for “metabolic” control. We use minimal modeling to analyze the idiosyncratic phosphorylation dynamics of ERK, i.e. a slow phosphorylation response that returns to basal in response to insulin, and conclude that sequestration of ERK is the simplest explanation to data. We also demonstrate a significant cross-talk between ERK and mTORC1 signaling to ribosomal protein S6 for control of protein synthesis. A reduced sensitivity and reduced maximal phosphorylation of ERK in response to insulin in the diabetic state can be explained by the same mechanisms that generate insulin resistance in the control of metabolism.