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Threshold-controlled ubiquitination of the EGFR directs receptor fate

2013; Springer Nature; Volume: 32; Issue: 15 Linguagem: Inglês

10.1038/emboj.2013.149

1460-2075

Sara Sigismund, Veronica Algisi, Gilda Nappo, Alexia Conte, Roberta Pascolutti, Alessandro Cuomo, Tiziana Bonaldi, Elisabetta Argenzio, Lisette G. G. C. Verhoef, Elena Maspero, Fabrizio Bianchi, Fabrizio Capuani, Andrea Ciliberto, Simona Polo, Pier Paolo Di Fiore,

Peptidase Inhibition and Analysis

Article25 June 2013Open Access Threshold-controlled ubiquitination of the EGFR directs receptor fate Sara Sigismund Sara Sigismund IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy Search for more papers by this author Veronica Algisi Veronica Algisi IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy Search for more papers by this author Gilda Nappo Gilda Nappo IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy Search for more papers by this author Alexia Conte Alexia Conte IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy Search for more papers by this author Roberta Pascolutti Roberta Pascolutti IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy Search for more papers by this author Alessandro Cuomo Alessandro Cuomo Department of Experimental Oncology, Istituto Europeo di Oncologia, Milan, Italy Search for more papers by this author Tiziana Bonaldi Tiziana Bonaldi Department of Experimental Oncology, Istituto Europeo di Oncologia, Milan, Italy Search for more papers by this author Elisabetta Argenzio Elisabetta Argenzio IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, ItalyPresent address: The Netherlands Cancer Institute, Amsterdam, The Netherlands. Search for more papers by this author Lisette G G C Verhoef Lisette G G C Verhoef IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy Search for more papers by this author Elena Maspero Elena Maspero IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy Search for more papers by this author Fabrizio Bianchi Fabrizio Bianchi Department of Experimental Oncology, Istituto Europeo di Oncologia, Milan, Italy Search for more papers by this author Fabrizio Capuani Fabrizio Capuani IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, ItalyPresent address: Dipartimento di Fisica, Università di Roma La Sapienza, Rome, Italy. Search for more papers by this author Andrea Ciliberto Andrea Ciliberto IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy Search for more papers by this author Simona Polo Corresponding Author Simona Polo IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy Dipartimento di Scienze della Salute, Università degli Studi di Milano, Milan, Italy Search for more papers by this author Pier Paolo Di Fiore Corresponding Author Pier Paolo Di Fiore IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy Department of Experimental Oncology, Istituto Europeo di Oncologia, Milan, Italy Dipartimento di Scienze della Salute, Università degli Studi di Milano, Milan, Italy Search for more papers by this author Sara Sigismund Sara Sigismund IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy Search for more papers by this author Veronica Algisi Veronica Algisi IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy Search for more papers by this author Gilda Nappo Gilda Nappo IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy Search for more papers by this author Alexia Conte Alexia Conte IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy Search for more papers by this author Roberta Pascolutti Roberta Pascolutti IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy Search for more papers by this author Alessandro Cuomo Alessandro Cuomo Department of Experimental Oncology, Istituto Europeo di Oncologia, Milan, Italy Search for more papers by this author Tiziana Bonaldi Tiziana Bonaldi Department of Experimental Oncology, Istituto Europeo di Oncologia, Milan, Italy Search for more papers by this author Elisabetta Argenzio Elisabetta Argenzio IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, ItalyPresent address: The Netherlands Cancer Institute, Amsterdam, The Netherlands. Search for more papers by this author Lisette G G C Verhoef Lisette G G C Verhoef IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy Search for more papers by this author Elena Maspero Elena Maspero IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy Search for more papers by this author Fabrizio Bianchi Fabrizio Bianchi Department of Experimental Oncology, Istituto Europeo di Oncologia, Milan, Italy Search for more papers by this author Fabrizio Capuani Fabrizio Capuani IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, ItalyPresent address: Dipartimento di Fisica, Università di Roma La Sapienza, Rome, Italy. Search for more papers by this author Andrea Ciliberto Andrea Ciliberto IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy Search for more papers by this author Simona Polo Corresponding Author Simona Polo IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy Dipartimento di Scienze della Salute, Università degli Studi di Milano, Milan, Italy Search for more papers by this author Pier Paolo Di Fiore Corresponding Author Pier Paolo Di Fiore IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy Department of Experimental Oncology, Istituto Europeo di Oncologia, Milan, Italy Dipartimento di Scienze della Salute, Università degli Studi di Milano, Milan, Italy Search for more papers by this author Author Information Sara Sigismund1, Veronica Algisi1, Gilda Nappo1, Alexia Conte1, Roberta Pascolutti1, Alessandro Cuomo2, Tiziana Bonaldi2, Elisabetta Argenzio1, Lisette G G C Verhoef1, Elena Maspero1, Fabrizio Bianchi2, Fabrizio Capuani1, Andrea Ciliberto1, Simona Polo 1,3 and Pier Paolo Di Fiore 1,2,3 1IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy 2Department of Experimental Oncology, Istituto Europeo di Oncologia, Milan, Italy 3Dipartimento di Scienze della Salute, Università degli Studi di Milano, Milan, Italy *Corresponding authors. Department of Experimental Oncology, IEO - European Institute of Oncology, Via Adamello 16, 20139 Milan, Italy. Tel.:+39 02 574303247; Fax:+39 02 574303231; E-mail: [email protected], Fondazione Instituto FIRC di Oncologia Molecolare, Milan, Italy, Via Adamello 16, 20139 Milan, Italy. Tel.:+39 02 574303242; Fax:+39 02 574303231; E-mail: [email protected] The EMBO Journal (2013)32:2140-2157https://doi.org/10.1038/emboj.2013.149 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info How the cell converts graded signals into threshold-activated responses is a question of great biological relevance. Here, we uncover a nonlinear modality of epidermal growth factor receptor (EGFR)-activated signal transduction, by demonstrating that the ubiquitination of the EGFR at the PM is threshold controlled. The ubiquitination threshold is mechanistically determined by the cooperative recruitment of the E3 ligase Cbl, in complex with Grb2, to the EGFR. This, in turn, is dependent on the simultaneous presence of two phosphotyrosines, pY1045 and either one of pY1068 or pY1086, on the same EGFR moiety. The dose–response curve of EGFR ubiquitination correlate precisely with the non-clathrin endocytosis (NCE) mode of EGFR internalization. Finally, EGFR-NCE mechanistically depends on EGFR ubiquitination, as the two events can be simultaneously re-engineered on a phosphorylation/ubiquitination-incompetent EGFR backbone. Since NCE controls the degradation of the EGFR, our findings have implications for how the cell responds to increasing levels of EGFR signalling, by varying the balance of receptor signalling and degradation/attenuation. Introduction The conversion of graded stimuli into switch-like, threshold-controlled, biological outputs presents the cell with different challenges according to whether the signal has to be resolved in space or in time. The former case is exemplified by the specification of boundaries during patterning in development. In this instance, the process is frequently instructed by morphogens that diffuse from a localized source to create a gradient in an area of unpatterned cells. Within this area, the graded morphogenetic signal is transduced into sharp response borders: a process that requires the activation of threshold-controlled mechanisms, and that has been analysed in various developmental contexts (see for instance, Ashe and Briscoe, 2006; Lander, 2007; Barkai and Shilo, 2009). A different biological setting is represented by those occurrences in which the gradient is not extended in space, but in which cells must enact strategies to respond to varying concentrations of a stimulus, such as a growth factor. In this context, one obvious possibility is that cellular responses are directly proportional to the stimulus, that is, graded input elicits graded output. Another, not mutually exclusive, possibility is that some signalling events are threshold controlled. In the case of the epidermal growth factor (EGF), we have recently uncovered a phenotype that might be underpinned by such a mechanism. The EGF receptor (EGFR) is internalized through both clathrin-mediated endocytosis (CME) and non-clathrin endocytosis (NCE). However, while CME is active at all ligand concentrations, NCE is observed only when high EGF concentrations are applied to cells (Lund et al, 1990; Yamazaki et al, 2002; Sigismund et al, 2005; Orth et al, 2006; Sigismund et al, 2008), suggesting that it might be threshold controlled. The functional meaning and relevance of EGFR-NCE is still somehow obscure. For instance, its presence depends on the cellular context ((Sigismund et al, 2005; Kazazic et al, 2006; Orth et al, 2006; Madshus and Stang, 2009; Rappoport and Simon, 2009), see also Results in this paper). In the cellular populations in which EGFR-NCE is active, however, it might impinge heavily on the regulation of EGFR signalling, since we have shown that while CME is primarily coupled with EGFR recycling to the cell surface (and therefore with sustainment of signalling), NCE is largely devoted to commit the receptor to lysosomal degradation (Sigismund et al, 2008). Thus, the sharp activation of NCE above a certain ligand threshold (while CME nevertheless persists) might regulate the net signalling output, in response to increasing EGF concentrations, in a nonlinear fashion. Intriguingly, a post-translational modification of the EGFR, that is, EGFR ubiquitination, might also be threshold controlled, as we have shown that pronounced EGFR ubiquitination occurs only at high EGF concentrations (Sigismund et al, 2005, 2008). EGFR ubiquitination is executed by the E3 ligase Cbl (Levkowitz et al, 1998, 1999). Cbl is recruited to the activated EGFR by two distinct mechanisms: it can interact directly with the receptor at pY1045 (Levkowitz et al, 1999), or indirectly, through Grb2, at pY1068 or pY1086 (Waterman et al, 2002; Jiang et al, 2003). A possible mechanistic link between EGFR ubiquitination and EGFR-NCE was provided by the observation that an ubiquitination-impaired mutant of the EGFR (Y1045F) (Levkowitz et al, 1999) is internalized exclusively through CME, regardless of the concentration of EGF (Sigismund et al, 2005, 2008). Thus, one could hypothesize a threshold-controlled scenario in which a linear EGF signal is converted, above a certain dose, in a ubiquitination signal, which in turn switches on the NCE mode of EGFR internalization. The present studies were undertaken to test this possibility and to experimentally challenge various mechanistic models through which this might occur. Results A threshold effect for EGFR ubiquitination Upon EGF treatment, the ubiquitination of the EGFR—measured by immunoblot (IB)—increased sharply over a narrow range of EGF concentrations, being minimal at 1 ng/ml and nearly maximal at 10 ng/ml, both in epithelial cells (HeLa) and in fibroblasts (NR6-EGFR cells) (Figure 1A). Conversely, the EGFR phosphotyrosine (pY) content, used as a surrogate for receptor activation, displayed a typical hyperbolic dose–response curve, which translated in a semi-linear behaviour when a log scale was used for EGF doses (Figures 1A and B and Supplementary Figures 1A-C; see also Supplementary Figures 1D–F for a series of specificity controls). More precisely, the dose–response curves for EGFR phosphorylation and ubiquitination displayed different degrees of sigmoidicity, best approximated by Hill functions with Hill coefficients (nH) of 1 and 3, respectively. Figure 1.Analysis of EGFR ubiquitination. (A) HeLa or NR6 cells were stimulated with the indicated concentrations of EGF for 2 min (in this and all subsequent figures). IP and IB were performed as indicated (Ub, ubiquitin P4D1 antibody). (B) HeLa cells were stimulated with EGF, followed by IB with the indicated antibodies. (C, D) Lysates of HeLa cells stimulated with EGF, as indicated, were subjected to ELISA, forward approach (Supplementary Figure 2A), using the indicated detecting Ab (Ub, FK2 antibody). Results are shown as % of max (see Materials and methods). (E) Lysates of HeLa cells stimulated with EGF, as indicated, were subjected to ELISA, reverse approach (Supplementary Figure 2B), using the indicated detecting Ab (Ub, FK2 antibody). (F) Comparison of the EGFR ubiquitination and phosphorylation curves of HeLa cells obtained by forward and reverse ELISA. In all panels (and in all subsequent figures), error bars indicate s.d. calculated on at least three independent experiments. P-values were calculated using two-way ANOVA analysis. When comparing curves that showed significant differences (in all figures), we show the relative P-values; when comparing curves that did not show significant differences (in all figures), we display R, the Pearson correlation coefficient.Source data for this figure is available on the online supplementary information page. Source data for Figure 1 [embj2013149-sup-0001-SourceData-S1.pdf] Download figure Download PowerPoint To obtain independent quantitative measurements, we exploited an ELISA-based approach (Supplementary Figures 2A and B). In this assay, performed both as a 'forward' or 'reverse' ELISA, the dose–response curve of EGFR ubiquitination was clearly different from those of EGFR-pY or of individual phosphosites and displayed an evident threshold effect (Figures 1C–F and Supplementary Figure 2C). We also performed quantitative mass spectrometry (MS) analysis (that is, SILAC, stable isotope-labelled amino acid in cell culture) of EGFR ubiquitination and tyrosine phosphorylation (Figures 2A and B and Supplementary Figure 3A). The amount of ubiquitin peptides in EGFR-enriched preparation of cells stimulated with different EGF doses was compared to the amount obtained upon stimulation with EGF at the maximal dose (100 ng/ml). Also by this method, a clear threshold effect for total EGFR ubiquitination was visible (Figures 2C and D and Supplementary Figures 3B and C), with quantitative estimates obtained by MS and ELISA almost coincident (Figure 2D, bottom). Importantly, we could unequivocally identify a ubiquitinated EGFR peptide, corresponding to K692-Ub and previously identified as one of the major EGFR-Ub sites (Huang et al, 2006), which also showed a threshold behaviour (Figure 2E, top), while several EGFR-pY sites displayed more gradual increments (Supplementary Figures 3D–F). The mean ratio of different phosphosites is reported in Figure 2E bottom. Additional technical information on the MS experiments is reported in Supplementary Figures 3G–K and in Supplementary Table 1. Figure 2.SILAC-MS for quantitative analysis of ubiquitinated and phosphorylated EGFR. (A) Schematic representation of the SILAC-MS approach. HeLa cells were grown in SILAC-encoded 'light' or 'heavy' media (Supplementary Experimental Procedures). 'Light' (L) cells were stimulated with 100 ng/ml of EGF; 'heavy' (H) cells were treated independently with increasing concentrations of EGF, as indicated. Cells were then harvested and mixed (H/L) in 1:1 ratio for each pair. (B) Lysates from the seven H/L mixtures were subjected to anti-EGFR IP and SDS–PAGE. Lanes were cut (shown by red lines) starting from the position of the EGFR (asterisk), to cover potential differentially ubiquitinated forms. (C) Left, LTQ-FTICR mass spectra of Ub (UBC, peptide 11–27, left) and EGFR (peptide 81–98, right) from each H/L mixture (a more detailed representation is in Supplementary Figures 3B and C). (D) Threshold ubiquitination of EGFR, detected by MS. Top, high-accuracy quantification of total EGFR (87) and Ub (13) peptides; see Supplementary Table 1 for raw data. Bottom, comparison of EGFR-Ub data obtained with forward ELISA (Figure 1C) and SILAC-MS (from top panel). R, Pearson correlation coefficient. (E) Top, SILAC ratios of the EGFR ubiquitination site (K692-Ub) shown in Supplementary Figure 3G. Bottom, mean SILAC ratios of EGFR phosphorylation were calculated on the basis of the three pY sites shown in Supplementary Figures 3D–F. Note that, while mean pY increases linearly upon EGF stimulation (R2=0.97, square of correlation coefficient; see also Supplementary Figures 3D–F for the linear behaviour of single pY sites), the abundance of the EGFR-Ub peptide increases with a threshold behaviour, similarly to total Ub (panel D). SILAC ratios are calculated using MaxQuant (see Supplementary Figures 3H–K for more detailed pictures). Download figure Download PowerPoint We concluded that EGFR ubiquitination is threshold controlled. The threshold effect for EGFR ubiquitination occurs at the PM One of the goals of this study is to establish a mechanistic connection between EGFR ubiquitination and EGFR-NCE (see below). It was critical, therefore, to establish that the threshold effect was already operative at the PM, where internalization occurs. For this reason, we performed all experiments after 2 min of EGF treatment, when EGFR internalization is minimal. However, since it is known that EGFR ubiquitination begins at the PM and continues in endosomes (Umebayashi et al, 2008), it was also necessary to determine exactly where the observed EGFR ubiquitination threshold occurred, under our experimental conditions. To address this question, we inhibited both CME and NCE internalization of the EGFR, by silencing the expression of dynamin 2 in HeLa cells (Figures 3A and B), and then analysed ligand-induced EGFR ubiquitination. The threshold effect for EGFR ubiquitination, evidenced both by IB (Figure 3A) and—quantitatively—by ELISA (Figure 3C), persisted in dynamin 2-knockdown (KD) cells, thus proving that it occurs at the PM. In addition, the magnitude of both EGFR ubiquitination and tyrosine phosphorylation was comparable in KD and wild-type (WT) cells (Figure 3A), arguing that—under our conditions of analysis—the vast majority of these events takes place at the PM. We note that our results do not imply that endosomal ubiquitination of EGFR is not threshold controlled, but simply that the threshold effect occurs already at the PM. Figure 3.The threshold effect for EGFR ubiquitination occurs at the PM. (A) Top, HeLa cells were subjected to dynamin 2-KD and treated for 2 min with EGF at the indicated concentrations. IP and IB were as shown. (B) EGFR internalization kinetics in dynamin 2-KD cells was measured using 125I-EGF at low (1 ng/ml) or high (30 ng/ml) EGF concentrations. Results are expressed as the internalization rate constant (Ke, left panel) or as % of Ke in control cells (right panel), and are the mean of triplicate points (s.e.m.<8%). Dynamin 2-KD (Dyn 2-KD) severely impaired EGFR internalization both at low and high EGF concentrations, reducing rates to background levels. Similar background levels have previously been observed by us in clathrin-KD+filipin-treated HeLa cells, in which both CME and NCE are inhibited (Sigismund et al, 2005, 2008). These results confirm that both CME and NCE of the EGFR are dynamin 2 dependent. Comparable results were obtained with two different silencing oligos for dynamin 2 (data not shown). (C) Lysates of HeLa cells, control and dynamin 2-KD, stimulated with EGF for 2 min at the indicated concentrations were subjected to ELISA, forward approach (Supplementary Figure 2A), using anti-Ub (FK2) and anti-pY as detecting antibodies. Results are shown as a percentage of the maximal tyrosine phosphorylation or ubiquitination (% of max, see Materials and methods). Graph error bars indicate s.d. calculated on at least three independent experiments. All P-values were calculated using two-way ANOVA analysis. As shown the Ub curves were not significantly different between control and KD; the same was true for the pY curves. Conversely, the Ub curves were significantly different from the pY curves.Source data for this figure is available on the online supplementary information page. Source data for Figure 3 [embj2013149-sup-0002-SourceData-S2.pdf] Download figure Download PowerPoint A threshold effect for Cbl recruitment to the EGFR EGFR ubiquitination is executed by the E3 ligase Cbl (Levkowitz et al, 1998, 1999). We investigated how the activity of Cbl is controlled in the cell to produce the EGFR ubiquitination threshold. The Cbl family is composed of three genes, c-Cbl, Cbl-b and Cbl-c (Schmidt and Dikic, 2005; Lipkowitz and Weissman, 2011). By quantitative RT–PCR analysis (Q-PCR), we found that our HeLa cells express c-Cbl and, to a lower extent, Cbl-b, but little if any Cbl-c (Figure 4A). The expression level of c-Cbl and Cbl-b was confirmed by IB (Figure 4B). The silencing of c-Cbl caused a sizable reduction in EGFR ubiquitination, while silencing of Cbl-b produced modest effects, even when it was silenced together with c-Cbl (Figure 4C). We concluded that, in the cellular system under scrutiny, c-Cbl is the major E3 ligase responsible for EGFR ubiquitination at the PM. Thus, we concentrated on c-Cbl (henceforth, Cbl) in the subsequent experiments. Figure 4.The EGFR–Cbl interaction is threshold controlled. (A) Q-PCR of c-Cbl, Cbl-b and Cbl-c in HeLa cells. Both Ct values (threshold cycles) and mRNA level of c-Cbl, Cbl-b and Cbl-c (normalized on 18S mRNA and expressed as fraction of c-Cbl mRNA) are reported. (B) HeLa cells were subjected to c-Cbl and Cbl-b-KD, alone or in combination (Contr, HeLa cells transfected with control oligo). IB was as shown (Tub, tubulin; loading control). (C) HeLa cells, transfected with the indicated oligos as in B, were stimulated with EGF as shown. Lysates were subjected to IP and IB as shown. For the Ub blots: l.e., long exposure; s.e., short exposure. Note that two different oligos targeting c-Cbl and Cbl-b were used, with comparable results. In panel B and C, results obtained with UTR1 (for both c-Cbl and Cbl-b) are shown (see Materials and methods for details). (D) Top, HeLa cells were treated with EGF as indicated for 2 min and then IP and IB as shown. Bottom, quantitative assessment. Results are expressed as a percentage of the maximal amount (% of max, see Materials and methods) of EGFR that coimmunoprecipitates (Co-IP) with c-Cbl (from now on Cbl), Grb2 or Shc.Source data for this figure is available on the online supplementary information page. Source data for Figure 4 [embj2013149-sup-0003-SourceData-S3.pdf] Download figure Download PowerPoint We analysed the association between Cbl and EGFR in vivo. We detected a clear threshold effect in the EGF-induced co-immunoprecipitation (co-IP) between the two proteins, an effect that was not evident when the physical association of EGFR with other known interactors, such as Grb2 or Shc, was analysed (Figure 4D, see also Supplementary Figure 4 for additional experiments relevant to the interaction between Grb2 and the EGFR). Thus, the association of Cbl with the EGFR exhibits a unique dose–response behaviour that correlates with a similar behaviour of the Cbl-mediated ubiquitination of the EGFR. Experimental challenge of models of threshold control of EGFR ubiquitination There are several mechanisms that, in principle, could explain the EGFR ubiquitination threshold. One obvious possibility is that the phosphorylation of individual Cbl-binding sites on EGFR (pY1045 or one between Y1068 and Y1086) increases in a sigmoidal fashion with the doses of EGF (Figure 5A, threshold phosphorylation model). We have, however, tested and excluded this possibility (Figure 1B). Indeed, individual EGFR phosphosites do not display threshold phosphorylation, as shown both for the direct (pY1045, Figure 1B) and for the indirect Cbl-binding phosphosites (pY1068 or pY1086, Figures 1B and D). Figure 5.Models describing the generation of EGFR-Ub threshold. (A) Top, schematic representation of EGFR ubiquitination and EGFR phosphorylation, as a function of ligand concentration. xT represents the half-maximal EGF dose for EGFR ubiquitination (i.e., the ubiquitination threshold) and it is used to separate in the pictograms underneath (dashed line) the events occurring at low EGF (left) from those occurring at high EGF (right). In the inset, the various symbols used in the models are shown. Various models potentially accounting for the EGFR ubiquitination threshold (in all models the ubiquitination of EGFR by Cbl is indicated by a solid arrow line). 1) Threshold phosphorylation model. The model contemplates that the phosphorylation of individual Cbl-binding sites on EGFR (pY1045 or one between Y1068 and Y1086) increases in a sigmoidal fashion with the doses of EGF. The model is depicted for pY1045, but it could be equally applied to the indirect (Grb2-mediated) binding site(s) (pY1068/pY1086). 2) Threshold Cbl activation model. The model contemplates that the enzymatic function of Cbl is activated in a nonlinear fashion by signalling events (e.g., direct tyrosine phosphorylation of Cbl by the EGFR, indicated by a dashed arrow line) that occur only under high EGF. 3) Competition model. This model invokes the existence of a high affinity, rate-limiting (low amount) competitor X. At low EGF (left), such competitor—that in the model would bind only to activated EGFR—prevents Cbl from interacting with the EGFR or from ubiquitinating the receptor (in this latter case, either directly inhibiting Cbl activity or masking Ub sites on the EGFR, not shown). At high EGF (right), the competitor becomes limiting and Cbl could therefore bind and ubiquitinate the EGFR. 4) Cooperative model. Cbl/Grb2 complex binds stably to EGFR only when pY1045 and at least one of pY1068 and pY1086 are present in the same EGFR molecule. In this case, the EGFR phosphorylation pattern determines the ubiquitination threshold. At low EGF (left), EGFR is poorly phosphorylated and the probability of having the two key sites in the same EGFR molecule is low (possible low-affinity binding of the Cbl:Grb2 complex to single sites is shown by a dotted line). However, this probability increases at high EGF (right) allowing for the cooperative recruitment of Cbl/Grb2. This model implies that phosphorylation sites are phosphorylated independently of one another (as shown experimentally in Figure 7C and Supplementary Figure 7) and therefore the probability of having one site phosphorylated within the same EGFR molecule increases gradually with the EGF concentration, while the probability of having two sites increases sharply. (B) EGF dose–response curve of Cbl phosphorylation. Left, HeLa cells were treated with EGF for 2 min as indicated. Lysates were prepared in RIPA buffer (w/ 1% SDS) and then diluted to 0.2% SDS (see Materials and methods). IP and IB was as shown. Right, quantitation of the blots.Source data for this figure is available on the online supplementary information page. Source data for Figure 5 [embj2013149-sup-0004-SourceData-S4.pdf] Download figure Download PowerPoint A second group of models is based on either positive or negative regulation of Cbl. In the first case (threshold Cbl activation model, Figure 5A), the enzymatic activity of Cbl could be activated in a nonlinear fashion. It is known that the activation of Cbl depends on its phosphorylation by EGFR (Levkowitz et al, 1999; Kassenbrock and Anderson, 2004), which induces—and possibly stabilizes—an open Cbl conformation, required for the interaction with the E2 enzyme (Dou et al, 2012). However, the EGF-induced Cbl phosphorylation displays a gradual increment over a range of EGF concentrations (Figure 5B), arguing against this hypothesis (see also Supplementary Figure 5 for additional experiments on Cbl phosphorylation). Inhibition of Cbl function has been extensively investigated in the literature (Schmidt and Dikic, 2005; Ryan et al, 2006). Various permutations of models centred on Cbl-negative regulation can be envisaged. One example is represented in the 'competition model' (Figure 5A), where there might be competition between high-affinity and low-affinity proteins for binding to the EGFR. When the number of binding sites (pY sites) is limited (as it would occur at low EGF doses), low-affinity binders (as Cbl hypothetically might be) would be prevented from interacting with the EGFR. If the number of high-affinity ligands is limiting, they would be titrated as the number of binding sites increases, in response to EGF escalation, allowing for the low-affinity ligands to interact with EGFR. A variation of this scenario, which still relies on negative Cbl regulation, is