Improved Split TEV GPCR beta-arrestin-2 Recruitment Assays via Systematic Analysis of Signal Peptide and beta-arrestin Binding Motif Variants

Wu, Yuxin; Hauff, Isabelle V. V. von; Jensen, Niels; Roßner, Moritz J. und Wehr, Michael C. C. (2022): Improved Split TEV GPCR beta-arrestin-2 Recruitment Assays via Systematic Analysis of Signal Peptide and beta-arrestin Binding Motif Variants. In: Biosensors-Basel, Bd. 13, Nr. 1

Abstract

G protein-coupled receptors (GPCRs) are major disease-relevant drug targets;robust monitoring of their activities upon drug treatment is key to drug discovery. The split TEV cell-based assay technique monitors the interaction of an activated GPCR with beta-arrestin-2 through TEV protein fragment complementation using a luminescent signal as the readout. In this work, split TEV GPCR beta-arrestin-2 recruitment assays were optimized to monitor the endogenous ligand-induced activities of six GPCRs (DRD1, DRD2, HTR2A, GCGR, AVPR2, and GLP1R). Each GPCR was tested in four forms;i.e., its wildtype form, a variant with a signal peptide (SP) to facilitate receptor expression, a variant containing the C-terminal tail from the V2 vasopressin receptor (V2R tail) to promote beta-arrestin-2 recruitment, and a variant containing both the SP and V2R tail. These 24 GPCR variants were systematically tested for assay performance in four cell lines (HEK-293, PC12 Tet-Off, U-2 OS, and HeLa). We found that the assay performance differed significantly for each GPCR variant and was dependent on the cell line. We found that V2R improved the DRD2 split TEV assays and that HEK-293 cells were the preferred cell line across the GPCRs tested. When taking these considerations into account, the defined selection of assay modifications and conditions may improve the performance of drug development campaigns that apply the split TEV technique as a screening tool.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Medizin
• Themengebiete: 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit
• Sprache: Englisch
• DFG: Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 491502892