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. 2017 Aug 11;7:7885. doi: 10.1038/s41598-017-07392-5

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© The Author(s) 2017

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Influence of the Gα subunit expression level on the concentration-response curves of β-AR agonists-mediated G protein activation. (a–c) BRET in HEK293T cells co-expressing HA-β1-AR (upper panels) or HA-β2-AR (lower panels) receptors and low (black) or high (orange) expression levels of Gαs-Rluc8 (a), Gαi1-Rluc8 (b) or GαoA-Rluc8 (c) in presence of fixed GFP10-Gγ2 and Gβ3 untagged subunits. Cells were stimulated or not for 1 min with increasing concentrations of the indicated agonists (Isoproterenol, ISO; Norepinephrine, NE; Epinephrine, EPI). Results are expressed as the difference in BRET signals measured in presence and absence of ligand. Data represent the mean ± s.e.m. of at least four independent experiments. The statistical significance between unstimulated cells and cells stimulated with the different ligand concentrations in low (*) and high ($) Gα-Rluc8 conditions was assessed using one-way ANOVA followed by a Dunnett’s multiple comparison test (*P < 0.05, **P < 0.01, ***P < 0.001). The statistical significance between low and high dose-response curves was assessed using two-way ANOVA followed by a Bonferroni post-test (^# P < 0.05, ^## P < 0.01).