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This code was written and used for statistical analysis and visualisation of data included in Drube et al. 2021.

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Visualisation and Statistical Analysis

GPCR kinse knockout cells reveal the impact of individual GRKs on arrestin-binding and GPCR regulation

Julia Drube*[1] , Raphael Silvanus Haider*[1] , Edda Sofie Fabienne Matthees[1], Mona Reichel[1], Julian Zeiner[2], Sebastian Fritzwanker[3], Clara Ziegler[1], Saskia Barz[1], Laura Klement[1], Jenny Filor[1], Verena Weitzel[1], Andrea Kliewer[3], Elke Miess[3], Evi Kostenis[3], Stefan Schulz[3] and Carsten Hoffmann[1]

DOI: 10.1038/s41467-022-28152-8

[1]: Institut für Molekulare Zellbiologie, CMB – Center for Molecular Biomedicine, Universitätsklinikum Jena, Friedrich-Schiller-Universität Jena, Hans-Knöll Straße 2, D-07745 Jena, Germany

[2]: Molecular, Cellular and Pharmacobiology Section, Institute for Pharmaceutical Biology, University of Bonn, Nussallee 6, 53115 Bonn, Germany

[3]: Institut für Pharmakologie und Toxikologie, Universitätsklinikum Jena, Friedrich-Schiller-Universität Jena, Drackendorfer Straße 1, D-07747 Jena, Germany

[*] contributed equally


This code was written and used for statistical analysis and visualisation of data included in Drube et al. 2021. Cite this code DOI: 10.5281/zenodo.5764248


Statistical Analysis of all twelve tested GPCRs

ST1_vehicle_vs_stim.R : All concentration response curves presented, were statistically analysed to determine functional recruitment. Results are listed in Supplementary Table 1.

Beta-arrestin recruitment data from all twelve tested GPCRs (Supplementary Figure 5 and 6) was preprocessed using curve_formatting.py. Concentration response curves (Supplementary Figure 5) were analysed utilizing F3i_ST3_curve_analysis.R. Results (Supplementary Table 3) were ultimately plotted as heatmap (Figure 3i, F3i_heatmap.R). To identify increased baselines SF6,8_baseline_analysis.R was employed (Supplementary Figure 6, 8).

Phosphorylation Pattern Analysis

Potential phosphorylation sites (P), clusters (PPP, PXPP ref ) and patterns (PXPXXP, PXXPXXP ref ) were identified in the intracellular loop 3 (IL3) and the C-terminus (C-term) of the investigated GPCRs using moving_frame.py. Data of following format was used as input in which each GPCR - beta-arrestin pair is listed with their GRK preference, the class of the GPCR (according to Oakley et al. 1999 ) and the IL3 or C-term amino acid sequence. Aminio acid sequences were obtained from GPCRdb.

GPCR barr GRK arr_class IL3_or_Cterm seq
b2AR barr1 GRK2356 A IL3 GRFHVQNLSQVEQDGRTGHGLRRS

The number of identified phosphorylation sites, clusters and patterns are listed as part of Supplementary Table 2. The count and relative position of these phosphorylation sites were visualized grouped by GRK preference or class F7_pattern_analysis.R. Generated plots are presented in Figure 7. A possible association between the relative position of PXPP clusters and GRK preference or class was investigated in F7_Fisher_details.R.

Statistical Analysis of Miscellaneous Datasets

Data processed with the following scripts was imported in following format in which each signal recorded by the respective method ("Output") can be linked to a certain factor which was variied between the samples ("Condition"). A within factor variable ("State") was included for data measured before and after GPCR stimulation.

Condition State Output
dQ+EV baseline 1.03923
dQ+EV stimulated 0.81442
dQ+GRK2 baseline 1.93874
dQ+GRK2 stimulated 1.51442

F1d,f_SF3c_GRK_expression.R: Statistical analysis of GRK expression data presented in Figure 1d, f and Supplementary Figure 3c was statistically analysed.

F2b,c,d_EC50.R: Comparison of several EC50 as presented in Figure 2b-d.

F3g,h_SF7c,e_confocal.R: Comparison of colocalisation quantified from confocal microscopy before and after stimulation (Figure 3g ,h and Supplementary Figure 7c, e).

F5_SF11_ST4_AT1R.R: Statistical analysis of beta-arrestin recruitment to AT1R under various conditions as presented in Figure 5 and Supplementary Figure 11. Results are listed in Supplementary Table 4. Data was preprocessed before statistical analysis using compare_format.py.

SF13_Losartan_Tolvaptan_analysis.R: Statistical analysis of beta-arrestin recruitment under application of inverse agonists as displayed in Supplementary Figure 13.

SF1,2_stats.R: Statistical analysis of datasets presented in Supplementary Figure 1 and 2.

SF9,10d,f_V2R_endo_KD_analysis.R: Statstical analysis of beta-arrestin recruitment to V2R (Supplementary Figure 9) and AT1R (Supplementary Figure 10 d and f) in presence of catalitically inactive GRKs or endogenous expression of one specific GRK isoform.

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This code was written and used for statistical analysis and visualisation of data included in Drube et al. 2021.

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