Systems-level interactions between insulin–EGF networks amplify mitogenic signaling

Nikolay Borisov^1,a, Edita Aksamitiene^1,a, Anatoly Kiyatkin^1,a, Stefan Legewie², Jan Berkhout¹, Thomas Maiwald^1,3, Nikolai P Kaimachnikov^1,4, Jens Timmer³, Jan B Hoek¹ & Boris N Kholodenko^1,5

^aThese authors contributed equally to this work

Synopsis

We present an integrated analysis of crosstalk between the insulin receptor (IR) and epidermal growth factor receptor (EGFR) signaling pathways. Our experimental and computational findings show how systems-level interactions between the EGFR and IR networks convert the insulin-induced increase in the phosphatidylinositol-3,4,5-triphosphate (PIP₃) concentration into enhanced activity of the extracellular signal-regulated kinase (ERK) pathway.

Physiological stimuli never act in isolation, and often cells in the body are simultaneously exposed to EGF and insulin. The EGFR and IR networks share many downstream components, yet their physiological responses to stimuli are different. In cells that express EGFR, including HEK293 cells, EGF acts as a potent activator of mitogenesis through activation of the Ras/ERK pathway. In contrast, mitogenesis and the Ras/ERK pathway are poorly activated by insulin. The main biological function of insulin is metabolic, involving the control of glucose metabolism and stimulation of protein and lipid syntheses. We show that in HEK293 cells, insulin amplifies Ras/ERK activation by low, physiological [EGF], and at saturating [EGF] the insulin effect becomes insignificant. Following 1.5- and 15-min co-stimulation with EGF plus insulin, the phospho-ERK level (which is directly related to ERK activity) is significantly larger than the sum of these levels observed for each ligand (Figure 3E, left and right panels), displaying EGF–insulin synergy. The peak ERK activity (at 5 min co-stimulation) does not display synergistic effects (Figure 3E, middle panel). We show that insulin–EGF crosstalk is not a consequence of extra activation of either receptor by co-stimulation with two ligands, or activation of insulin-like growth factor receptor-1 by insulin.

Figure 3

Insulin amplifies EGF-induced Ras/MAPK pathway activation at low EGF doses. Comparison of the calculated in silico dynamics of Ras-GTP (A), phospho-MEK (B), phospho-ERK1/2 (C), and phospho-GAB1 (D) stimulated with EGF (0.1 or 1 nM) or EGF plus insulin (EGF+Ins) in the absence or presence of PI3K inhibitor wortmannin (WT) with the corresponding kinetic measurements (shown in bottom (A, B) or right (C, D) panels) carried out in HEK293 cells stimulated with EGF (0.1, 1 or 20 nM) or co-stimulated with insulin (100 nM) plus EGF (+ or - indicate the presence or absence of the ligand). Grb2 levels serve as a loading control to show that equal amounts of protein were loaded per lane. Representative blots are shown (n=3). (E) HEK293 cells were pretreated with 100 nM WT (+) or equivalent amounts of solvent DMSO (-) for 30 min and stimulated with 0.1 nM EGF or 100 nM insulin or both ligands simultaneously for 1.5 min (left panel), 5 min (middle panel) or 15 min (right panel). Immunoblots were analyzed for phosphorylated MEK (S217/221), ERK1/2 (T202/Y204), or AKT (S473) (representative blots on the upper part of each panel). The ligand-induced ERK responses are expressed in arbitrary units (AU) (means.d., n=7).

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Multiple points of crosstalk between EGFR and IR make it difficult to comprehend and predict intricate Ras/ERK signaling dynamics in a cell-dependent context, using only qualitative arguments. These dynamics depend on a variety of non-linear interactions and feedback loops. A testable computational model helps us provide insights into the key causative relationships between the input stimuli and Ras/ERK signaling and reveal specific functions of critical network nodes in generating cellular responses (Kholodenko, 2006). Our mechanistic computational model, trained by the data from HEK293 cells, suggests that major crosstalk mechanisms that amplify ERK signaling are localized upstream of Ras and at the Ras/Raf level.

Some of the crosstalk interactions affect multiple Ras activation and deactivation routes, which involve the adaptor proteins, Grb2-associated binder-1 (GAB1) and insulin receptor substrates (IRS), and the SH2-domain containing protein tyrosine phosphatase-2 (SHP2). In the model, EGF and insulin co-stimulation increases the amount of PIP₃ produced by phosphatidylinositol 3-kinase (PI3K) and further facilitates the GAB1 membrane recruitment and its subsequent tyrosine phosphorylation. An increase in the membrane-bound phospho-GAB1 promotes Grb2–SOS binding and increases [SOS] (Ras activator) in close proximity to Ras. At the same time, this gain in phospho-GAB1 also increases the amounts of RasGAP (Ras deactivator) and SHP2 bound to GAB1. Although SHP2 negatively regulates IR, EGFR, IRS, and GAB1 phosphorylation levels, it has a positive effect on Ras activation, as we showed using a specific SHP2 inhibitor, NSC-87877 (Chen et al, 2006). This positive effect is related to the formation of the GAB1–SHP2 and IRS–SHP2 complexes and subsequent dephosphorylation of multiple docking sites, involved in RasGAP binding. Simulations predict that the net result of all these interactions is an increase in positive signaling and decrease in negative signaling to Ras, which amplifies the Ras-GTP level. Additional crosstalk interactions occur at the Ras/Raf level. In the model, at any given Ras-GTP load, the simultaneous exposure to insulin plus EGF increases Raf activity, relative to insulin alone, owing to EGF-induced stimulation of tyrosine kinases, which are assumed to belong to the Src family (Wellbrock et al, 2004).

We tested the model against the experiment, using kinetic data on responses to multiple perturbations, including different EGF doses, specific inhibitors and small interfering RNA (siRNA). We showed that the PI3K inhibitor wortmannin (WT) suppresses synergistic activation of the Ras/Raf/MEK/ERK pathway by insulin and EGF. The data demonstrate that the total GAB1 phosphorylation level and the concentrations of GAB1-bound Grb2, SHP2, and PI3K decrease dramatically in WT-treated cells. We conclude that the loss of insulin–EGF synergy caused by WT arises from the disruption of the GAB1–PI3K positive feedback and the loss of the GAB1-mediated membrane recruitment of signaling molecules.

To get further insight into crosstalk mechanisms, we simulated the dynamics of ERK responses to EGF versus EGF plus insulin in cells with different GAB1 expression levels (Figure 5A). As expected, GAB1 suppression reduces the phospho-ERK level to a larger degree for EGF than for EGF plus insulin. Model predictions shown in Figure 5B (left panel) illustrate this phospho-ERK level with decreasing GAB1 at 1.8 min following EGF or EGF plus insulin stimulation. To test the model, HEK293 cells were transfected with targeted siRNA against GAB1 mRNA, resulting in 75% reduced GAB1 protein level relative to control. The experimental data corroborate in silico predictions of the larger influence of GAB1 depletion on EGF- rather than on EGF plus insulin-induced ERK phosphorylation (Figure 5C). Thus, calculations suggest that insulin endows the mitogenic EGFR pathway with increased robustness towards GAB1 downregulation. The simulations show that for EGF plus insulin stimulation, the peak level of phospho-ERK decreases only slightly with GAB1 depletion, whereas for EGF-induced ERK activation, the peak level decreases dramatically (Figure 5B, right panel).

Figure 5

Effects of GAB1 depletion on ERK activation induced by EGF, insulin, or their combination. (A) Computational analysis of ERK activation kinetics in response to 0.1 nM EGF in the absence (left panel) or presence (right panel) of 100 nM insulin at the indicated levels of GAB1 protein. Time courses are shown for 225 nM (control; black—solid line), 150 nM (red—long dash line), 115 nM (dark yellow—short–long–short dash line), 95 nM (dark pink—long–short–short dash line), 75 nM (green—short dash line), 37.5 nM (blue—dash–dot line), 15.0 nM (cyan—dash–dot–dot line), 1.5 nM (gray—long–short dash line) and 0 nM (dark red—dotted line) GAB1 concentrations. (B) Simulated dependences of phospho-ERK level at 1.8 min (left panel) and maximal phospho-ERK level (right panel) on the GAB1 abundance for cells stimulated with 0.1 nM EGF in the presence (red solid line) or absence (blue dashed line) of 100 nM insulin. (C) HEK293 cells transfected with specific siRNA against GAB1 (+) or non-targeting siRNA (-) were stimulated with 100 nM insulin and/or 1 nM EGF for 1.5 min. Immunoblots were analyzed for phosphorylated ERK1/2 (T202/Y204) or GAB1 (Y627). GAB1 protein levels demonstrate the efficacy of GAB1 suppression. GAPDH was used as a loading control. Representative blot (left panel) and the bar graph of respective numerical values (right panel) are shown.

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The insight provided by computational analyses goes beyond revealing a critical role of GAB1, which is only one of several key nodes of interactions between the EGFR and IR networks. In fact, insulin enhances EGF-induced ERK activation even in GAB1 knockdown cells (Figure 5C). Coincidence detection of EGF and insulin stimuli by GAB1, together with multiple positive (PI3K–PIP₃–GAB1–PI3K) and negative (ERK–GAB1, ERK–SOS, mTOR–IRS) feedback loops, contributes to the control of insulin plus EGF signaling. Despite the fact that RNAi-mediated suppression of GAB1 significantly decreases EGF-induced ERK phosphorylation (Figure 5C), the downregulation of multiple network nodes is required to uncouple and completely suppress insulin plus EGF-induced Ras/ERK activation. Overall, the analysis presented here demonstrates the feasibility of using computational models to identify critical combinations of therapeutic targets and predict their effects on complex cellular responses to concurrent external cues.

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