Nature Methods
- 4, 3 - 4 (2007)
doi:10.1038/nmeth0107-3
BRET analysis of GPCR oligomerization: newer does not mean betterMichel Bouvier1, Nikolaus Heveker2, Ralf Jockers3, Stefano Marullo3 & Graeme Milligan41 Institute of Research in Immunology and Cancer, Department of Biochemistry, Université de Montréal, C.P. 6128 Succursale Centre-Ville, Montréal, Québec H3C 3J7, Canada. 2 Ste-Justine Hospital Research Center, Department of Biochemistry, Université de Montréal, 3175 Chemin de la Côte Sainte-Catherine, Montréal, Québec H3T 1C5, Canada. 3 Institut Cochin, Département de Biologie Cellulaire; INSERM, U567; Centre National de la Recherche Scientifique, Unité Mixte de Recherche 8104; and Université Paris 5, Faculté de Médecine René Descartes, UM 3, Paris, F-75014, France. 4 Institute of Biomedical & Life Sciences, Division of Biochemistry and Molecular Biology, University of Glasgow, Wolfson Building, Glasgow, G12 8QQ, UK. michel.bouvier@umontreal.ca To the editor: James et al.1 proposed a "rigorous" treatment of bioluminescence resonance energy transfer (BRET) data to distinguish random (nonspecific) from true oligomeric protein interactions. The question is not trivial, and the intention is laudable as BRET is becoming increasingly popular with more than 100 original articles published using the method. James et al., however, dismissed many studies that addressed similar issues, and several points deserve comments.
The authors preface their study by the statement: "Conventional BRET experiments are generally done at maximal expression levels and single acceptor/donor ratios". Although this is true of some studies, such a general statement ignores a large body of work in which these parameters had been taken into account. Expression levels had been monitored in many studies and were found to be within physiological range2,
3,
4,
5, and at least 15 papers had included BRET titration assays in which the donor/acceptor ratio was varied (for example, see refs. 2,4,
5,
6). Specificity of BRET signals allowing to distinguish oligomerization from random collisions also has been verified by several authors using BRET competition assays in which the occurrence of BRET between two partners expressed at a given donor/acceptor ratio can be inhibited by expression of the untagged partners but not of an untagged noninteracting protein (for example, see refs. 3,6,
7,
8).
James et al. propose to differentiate random from true oligomeric interactions based on theoretical considerations summarized in a seminal article by Kenworthy and Edidin9. The first approach consists of studying BRET efficiency in experiments in which the acceptor/donor (GFP/luciferase) ratio is varied ('type-1' assay). Random interactions are expected to be less sensitive to the acceptor/donor ratio if the surface density of the acceptor remains low. In multiple previous studies reported in the literature, the change of acceptor/donor ratio was obtained by maintaining the donor concentration fixed and progressively increasing the acceptor; thus, true oligomeric interactions were deduced from the hyperbolic progression of the BRET (for example, see refs. 2,4,
5,
6). In their experiments, James et al. maintained the total concentration of acceptor and donor constant by inversely changing the concentrations of both donor and acceptor, and used the difference between pseudo- and true-hyperbolic BRET curves to define random collision. Such analysis is technically difficult and complicated by the fact that the efficiency of transfer for random collisions becomes independent of the donor/acceptor ratio only if the acceptor concentration is kept constant (see Table 1 in ref. 9).
In 'type-1' assays, James et al. also interpreted the lower maximal BRET value as evidence for the lack of dimerization, or equilibrium between dimers and monomers. Such interpretation is very hazardous given that the extent of resonance energy transfer signals vary with the distance between donors and acceptors within a dimer. Thus no direct conclusion can be drawn on the amount of dimers simply based on the maximal BRET signals observed.
In the second set of experiments,'type-2' assays, BRET for true oligomers should be independent of the concentrations of BRET partners at a fixed acceptor/donor ratio. This was previously shown to be the case for class-A G protein–coupled receptors (GPCRs)2,
10,
11 and in particular for the  2AR at receptor concentration below 15 pmol/mg of protein2. From their data, James et al. concluded otherwise. However, a close examination of the data in Figure 4 reveals that the 2AR BRET curve has a slope that appears closer to that of the constitutive CTLA-4 dimer than that of the CD2 or CD86 monomers, consistent with the notion that the BRET between 2AR-luciferase and 2AR-GFP may reflect constitutive oligomerization. Also, the BRET signal observed for the constitutive dimer CD80 increases more readily with increasing expression levels than that of the 2AR, further complicating data interpretation. The fact that BRET falls below detection level at low donor/acceptor ratio may reflect lack of detector sensitivity for pairs yielding low BRET signals. Despite these interpretational difficulties, the authors concluded that the entire concept of GPCR oligomerization needs reappraisal.
In their discussion concerning the specificity of the BRET signals observed in previous studies, James et al. argued that the GABAb type-2 receptor (GBR2) is a poor choice for a negative control because it can itself dimerize. The reason for using this receptor as a negative control has been precisely its demonstrated ability to dimerize, thus offering a reliable selectivity test using a dimerization-competent receptor. Also, contrary to what the authors implied, GBR2 is not the only negative control that has been used in BRET studies. Several other receptors have been used as negative controls in BRET studies addressing class-A GPCR oligomerization (for example, see refs. 3,12,
13,
14).
The observation that in some studies4,
15, ligand binding affects the maximal BRET signal between the proposed protomers of class-A GPCR oligomers, is difficult to reconcile with the implicit conclusion of James et al. that the BRET signals observed for class-A GPCRs most likely result from random collisions. In many of the previous studies, the ligand-promoted changes in BRET signal had been interpreted as conformational changes within pre-existing dimers that changed the distances between the energy acceptor and donor.
Finally, the notion that family-A GPCRs may form constitutive oligomers is not only based on BRET studies. Many other biochemical and biophysical approaches support this notion. These include co-immunoprecipitation, various types of FRET, atomic force microscopy, covalent cross-linking, gel filtration, neutron scattering experiments, functional complementation, cell biology studies demonstrating cross-internalization and co-processing of GPCRs as well as binding studies showing positive and negative cooperativity. These approaches, their relative strengths and caveats, including methodological considerations and potential functional outcomes, have recently been reviewed16,
17. It is therefore premature to dismiss the GPCR oligomer hypothesis based on the interpretations of a single BRET study.
In conclusion, we believe that the results reported in the article by James et al. can be interpreted in different ways and that more controls would have been necessary to challenge the multidisciplinary work conducted on this topic by many groups over the past ten years. Clearly, BRET is gaining popularity in assessment of protein-protein interactions in living cells, and additional quantitative approaches will certainly be forthcoming. Maybe more importantly, additional studies performed in native tissues are needed to establish the generality of GPCR dimerization in physiologically relevant systems.
REFERENCES
- James, J.R., Oliveira, M.I., Carmo, A.M., Iaboni, A. & Davis, S.J. Nat. Methods 3, 1001–1006 (2006). | Article | PubMed | ISI | ChemPort |
- Mercier, J.F., Salahpour, A., Angers, S., Breit, A. & Bouvier, M. J. Biol. Chem 277, 44925–44931 (2002). | Article | PubMed | ISI | ChemPort |
- Issafras, H. et al. J. Biol. Chem. 277, 34666–34673 (2002). | Article | PubMed | ISI | ChemPort |
- Percherancier, Y. et al. J. Biol. Chem. 280, 9895–9903 (2005). | Article | PubMed | ISI | ChemPort |
- Ramsay, D., Kellett, E., McVey, M., Rees, S. & Milligan, G. Biochem. J. 365, 429–440 (2002). | Article | PubMed | ISI | ChemPort |
- Urizar, E. et al. EMBO J. 24, 1954–1964 (2005). | Article | PubMed | ChemPort |
- Ayoub, M.A. et al. J. Biol. Chem. 277, 21522–21528 (2002). | Article | PubMed | ISI | ChemPort |
- Hanyaloglu, A.C., Seeber, R.M., Kohout, T.A., Lefkowitz, R.J. & Eidne, K.A. J. Biol. Chem. 277, 50422–50430 (2002). | Article | PubMed | ISI | ChemPort |
- Kenworthy, A.K. & Edidin, M. J. Cell. Biol. 142, 69–84 (1998). | Article | PubMed | ISI | ChemPort |
- Terrillon, S. et al. Mol. Endocrinol. 17, 677–691 (2003). | Article | PubMed | ISI | ChemPort |
- Breit, A., Lagacé, M. & Bouvier, M. J. Biol. Chem. 279, 28756–28765 (2004). | Article | PubMed | ISI | ChemPort |
- Anger, S. et al. Proc. Natl. Acad. Sci. USA 97, 3684–3689 (2000). | Article | PubMed | ChemPort |
- Wilson, S., Wilkinson, G. & Milligan, G. J.Biol. Chem. 280, 28663–28674 (2005). | Article | ChemPort |
- Levoye, A. et al. EMBO J. 25, 3012–3023 (2006). | Article | PubMed | ISI | ChemPort |
- Ayoub, M.A., Levoye, A., Delagrange, P. & Jockers, R. Mol. Pharmacol. 66, 312–321 (2004). | Article | PubMed | ISI | ChemPort |
- Milligan, G. & Bouvier, M. FEBS J. 272, 2914–2925 (2005). | Article | PubMed | ISI | ChemPort |
- Bulenger, S., Marullo, S. & Bouvier, M. Trends Pharmacol. Sci. 26, 131–137 (2005). | Article | PubMed | ISI | ChemPort |
|
