Identification of GPCR-Interacting Cytosolic Proteins Using HDL Particles and Mass Spectrometry-Based Proteomic Approach

PLOS ONE, January 2013

23372797

Ka Young Chung, Peter W. Day, Gisselle Vélez-Ruiz, Roger K. Sunahara, Brian K. Kobilka

G protein-coupled receptors (GPCRs) have critical roles in various physiological and pathophysiological processes, and more than 40% of marketed drugs target GPCRs. Although the canonical downstream target of an agonist-activated GPCR is a G protein heterotrimer; there is a growing body of evidence suggesting that other signaling molecules interact, directly or indirectly, with GPCRs. However, due to the low abundance in the intact cell system and poor solubility of GPCRs, identification of these GPCR-interacting molecules remains challenging. Here, we establish a strategy to overcome these difficulties by using high-density lipoprotein (HDL) particles. We used the β(2)-adrenergic receptor (β(2)AR), a GPCR involved in regulating cardiovascular physiology, as a model system. We reconstituted purified β(2)AR in HDL particles, to mimic the plasma membrane environment, and used the reconstituted receptor as bait to pull-down binding partners from rat heart cytosol. A total of 293 proteins were identified in the full agonist-activated β(2)AR pull-down, 242 proteins in the inverse agonist-activated β(2)AR pull-down, and 210 proteins were commonly identified in both pull-downs. A small subset of the β(2)AR-interacting proteins isolated was confirmed by Western blot; three known β(2)AR-interacting proteins (Gsα, NHERF-2, and Grb2) and 3 newly identified known β(2)AR-interacting proteins (AMPKα, acetyl-CoA carboxylase, and UBC-13). Profiling of the identified proteins showed a clear bias toward intracellular signal transduction pathways, which is consistent with the role of β(2)AR as a cell signaling molecule. This study suggests that HDL particle-reconstituted GPCRs can provide an effective platform method for the identification of GPCR binding partners coupled with a mass spectrometry-based proteomic analysis.