Identification of Gβ5 Interactome Associated with Neuronal Development in Neuro-2a Cells through miniTurbo Proximity Labeling

Abstract

Gβ5 is a member of the Gβ family; however, unlike other heterotrimeric Gβ proteins, which transduce extracellular signals in response to G-protein coupled receptor (GPCR) activation, Gβ5 negatively regulates GPCR signaling by stabilizing the GTPase-activating proteins (GAP) R7 subfamily of Regulator of G-protein Signaling (R7-RGS) proteins. Mutations in Gβ5 have been implicated in a multisystem developmental disorder. While the regulation of GPCR signaling at the plasma membrane is likely important in this process, Gβ5/R7-RGS also localizes to the cytosol and nucleus. Potential protein–protein interactions of Gβ5 in these subcellular compartments are not well studied, so we sought to characterize the interactome of Gβ5 utilizing a live-cell biotin proximity-labeling assay in Neuro-2a cells coupled with mass spectrometry to identify novel protein interactions of the complex. We identified 48 potential interactors of Gβ5 with two analysis methods, most of which are previously unreported interactions important in neuronal development and function. The enriched phenotypes associated with the Gβ5 interactome in our results align with previously reported phenotypes of Gβ5 deficiencies.

1. Introduction

Gβ proteins generally function in a heterotrimeric complex with Gα and Gγ subunits in order to transduce extracellular signals from G-protein-coupled receptors (GPCRs). While a member of the Gβ family, Gβ5 does not engage in these signaling cascades but instead stabilizes the R7 subfamily of Regulator of G-protein Signaling (RGS) proteins in an obligate heterodimer, negatively regulating GPCR signaling events as RGS proteins are GTPase-activating proteins (GAPs). − If Gβ5 is genetically knocked out, the R7-RGS proteins are quickly degraded. The R7-RGS subfamily is made up of RGS6, RGS7, RGS9, and RGS11, and its members are highly enriched in the nervous system. ,

In mice, biallelic knockout of Gβ5 results in high preweaning mortality, developmental delay, low weight, and impaired brain development. , Similarly, in humans, mutations in the Gβ5 gene (GNB5) have been linked to the autosomal-recessive disorder Intellectual Development Disorder with Cardiac arrhythmia (IDDCA, also known as Loder–Merla Syndrome, OMIM #617173), characterized by cognitive impairment, epilepsy, hypotonia, and sinus bradycardia, along with other signs and symptoms that vary by case. − This would indicate that Gβ5/R7 plays a critical function in neuronal health and development. In addition, Gβ5/R7 has been implicated in a variety of disorders, including Alzheimer’s disease, − liver inflammation, ,− and addiction. ,−

Impaired GAP activity at the plasma membrane is likely important in IDDCA and other Gβ5/R7-related diseases, but Gβ5/R7 also localizes to the cytosol and nucleus − (some studies were unable to demonstrate nuclear localization), though the functional significance of such localization is not well-characterized. To identify potential cytosolic and nuclear binding partners of Gβ5, we utilized a live-cell biotin-ligase-based proximity-labeling assay with mass spectrometry to identify novel protein interactions to provide a further basis for future functional studies.

Proximity labeling in living cells is a robust technique that allows for in situ labeling of macromolecular targets utilizing a fusion of an enzyme to a protein of interest. One such enzyme used for proximity labeling is the promiscuous biotin ligase miniTurbo, which was developed from the R118S mutant BirA, the Escherichia coli biotin ligase, through error-prone PCR, optimizing for small size to reduce steric hindrance and decreased labeling time, resulting in a ∼10 min tagging window. Here we utilize a miniTurbo-Gβ5 recombinant fusion construct to map the Gβ5/R7 interactome in Neuro-2a mouse neuroblastoma cells employed as a model for neurons. Neuro-2a cells were selected because they endogenously express Gβ5 and RGS7. Previously published deep proteomic analysis of Neuro-2a cells identified RGS7 in the cell line but not other members of the R7 family (RGS6, RGS9, RGS11), which simplifies analysis.

2. Experimental Section

2.1. DNA Constructs

Plasmids and lentiviral prep were purchased from VectorBuilder. Plasmid maps and sequences are available for reference via VectorBuilder VectorIDs: miniTurbo-Gβ5 (VB230807-1370hqf; NM_138719.5), miniTurbo (VB230721-1304vfz), 3xFLAG-RGS7 (VB231113-1276ffk; XM_006496830.5), 3xHA-Gβ5 (VB241211-1289fyv; NM_138719.5), 3xFLAG-ALADIN (VB241211-1295ahq; NM_153416.2), ACAT2-3xFLAG (VB241203-1353fcq; NM_009338.3), EPS15L1-3xFLAG (VB241106-1475sft; NM_007944.3), 3xFLAG-RPTOR (VB241211-1294pgn; NM_028898.3), and 3xFLAG-ΔDEP/DHEX-ΔGGL-RGS7 (VB250131-1549yre). Lentivirus packaged with miniTurbo-Gβ5 or miniTurbo was purchased from VectorBuilder. The sequence for miniTurbo was originally described by Branon et al.

2.2. Antibodies

Rabbit anti-BirA (11582-RP01) was purchased from Sino Biological, Inc. (Beijing, China). Mouse anti-FLAG M2 (F3165) and rabbit anti-HA (H6908) were purchased from MilliporeSigma (Burlington, MA, USA). Streptavidin Alexa 680 (S21378) was purchased from Thermo Fisher Scientific (Waltham, MA, USA). Guinea pig anti-Gβ5 and rabbit anti-RGS6 (7RC-1) were generated in-house. Rabbit anti-Gβ1 (NBP2-1699), rabbit anti-GFP (NB600-308), and rabbit anti-topoisomerase I (NBP1-90365) were purchased from Novus Biologicals (Centennial, CO, USA). Goat anti-mouse IRDye 800CW (926-32210), goat anti-mouse IRDye 680RD (926-68070), goat anti-rabbit IRDye 800CW (926-32211), goat anti-rabbit IRDye 680RD (926-68071), donkey anti-guinea pig IRDye 800CW (926-32411), donkey anti-guinea pig IRDye 680LT (926-68030), and Revert 520 Total Protein Stain (926-10021) were purchased from LI-Cor Biotechnology (Lincoln, NE, USA).

All primary antibodies were used at a dilution of 1:1000; all secondary antibodies were used at a dilution of 1:5000. Both primary and secondary antibodies were diluted in SuperBlock blocking buffer in PBS (Thermo Fisher Scientific, 37515) supplemented with 0.1% Tween-20 (MilliporeSigma, P2287) and 0.02% w/v sodium azide (MilliporeSigma, S2002).

2.3. Cell Culture, Lentiviral Transduction, and Transfections

Neuro-2a mouse neuroblastoma cells were purchased from ATCC (CCL-131). Neuro-2a cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM, Gibco, 10569-010) supplemented with 10% Benchmark fetal bovine serum (FBS) (GeminiBio, West Sacramento, CA, USA, 100–106) in a humidified incubator at 37 °C with 5% CO₂.

Transduction with lentivirus containing miniTurbo-Gβ5 or miniTurbo was performed in half-volume DMEM supplemented with 10% FBS and 5 μg/mL Polybrene with a multiplicity of infection of 8 (8 transducing units per cell). After overnight incubation, the transduction media were removed and replaced with full-volume DMEM supplemented with 10% FBS. After another overnight incubation, antibiotic selection was initiated by supplementing the media with 10 μg/mL blasticidin S HCl (Gibco, A11139-03). After 7 days in selection media, the resulting stable cell lines (hereafter referred to as N2a-mTGβ5 and N2a-mT) were cultured in DMEM supplemented with 10% FBS and 2.5 μg/mL blasticidin for maintenance.

Transfections were performed with Lipofectamine 3000 (Thermo Fisher Scientific, L3000015) under reduced-serum conditions with Opti-MEM (Gibco, 31985070). After 4–6 h, the medium was replaced with DMEM supplemented with 0.5% FBS. Cells were then harvested after 24 h as detailed in each experimental subsection. In experiments for which no transfections were necessary, the media were replaced with DMEM supplemented with 0.5% FBS approximately 24 h before harvesting.

2.4. Preparation of Cell Lysates

Cell culture plates were removed from the incubator and placed on ice. After 2 min, the culture medium was aspirated, and the cell monolayer was washed with 4 °C PBS. PBS was then aspirated, and lysis buffer with 1× Halt protease inhibitor (Thermo Fisher Scientific, 1862209) was added to the wells. For co-immunoprecipitation, IP Lysis Buffer (Thermo Fisher Scientific, 87787) was used; for all other experiments, Pierce RIPA Buffer (Thermo Fisher Scientific, 89901) was used. Plates were then placed on a shaker at 4 °C for 10 min. Cells were then scraped and transferred to labeled 1.5 mL centrifuge tubes. To lyse the cells, tubes were kept on ice for 35 min, vortexed briefly approximately every 5 min, and then frozen overnight at −20 °C to complete lysis. After thawing, tubes were centrifuged at 4 °C for 10 min at 9168g. Protein concentration was determined via Pierce BCA Protein Assay Kit (Thermo Fisher Scientific, 23227), and samples were diluted with 4× NuPAGE LDS Sample Buffer (Thermo Fisher Scientific, NP0007), lysis buffer, and a final concentration of 100 mM dithiothreitol (DTT) to normalize protein concentration across experimental conditions.

2.5. Co-Immunoprecipitation (Co-IP)

Following lysis, samples were diluted to 1 μg/μL protein concentration to a final volume of 500 μL. After brief vortexing to ensure homogeneous mixing, 20 μL aliquots were removed from each sample to capture the total lysate, with the remaining 480 μL being the IP fraction. Total lysate fractions were then stored at −20 °C for future use.

For Figure A, 3 μL of rabbit anti-BirA (Sino Biological, Inc., 11582-RP01) was added to each IP fraction, with rabbit anti-GFP (Novus Biologicals, NB600-308) added to the negative control. The IP fractions were then placed on a rotator at 4 °C overnight. The next morning, 120 μL of Pierce Protein A/G Magnetic Beads (Thermo Fisher Scientific, 88803) was washed 3 times with 1 mL of IP Lysis Buffer using a magnetic rack to separate the beads. After the final wash, the tube was briefly centrifuged with a mini centrifuge to collect the beads, which were resuspended in 120 μL of IP Lysis Buffer. A 20 μL portion of beads was added to each IP fraction and then placed on a rotator at 4 °C for 1 h.

1.

miniTurbo-Gβ5 binds RGS7 and retains biotin ligase activity. (A) Representative western blot of co-immunoprecipitation. Transiently expressed RGS7 immunoprecipitated with miniTurbo-Gβ5 but not miniTurbo alone. Wild-type Neuro-2a cells and mTGβ5 immunoprecipitated with anti-GFP acted as negative controls. (B) Western blot of subcellular fractions. mTGβ5 localizes to the cytosol (cyt.), membrane (mem.), and nuclear (nuc.) fractions similarly to endogenous Gβ5 and RGS7. miniTurbo seems to localize only to the cytosol, though it may also be present in the membrane, though obscured by a nonspecific band at a slightly higher MW. Gβ1 acted as a membrane marker, and topoisomerase I as a nuclear marker. (C) Representative time course of biotinylation. Cells were treated with 50μM biotin for the indicated time. (D) Representative western blot of streptavidin pulldowns for mass spectrometry experiments. Lysate, flow-through (F.T.), and streptavidin bead elution (Strep.) were blotted and probed with anti-BirA, anti-RGS7, and Streptavidin Alexa 680 to ensure successful biotinylation and enrichment prior to mass spectrometry. mTGβ5 and miniTurbo were detected with anti-BirA, an antibody targeting the protein from which miniTurbo was derived. miniTurbo is denoted with a red asterisk. Total protein stain was used as a loading control. Representative blots of experiments done in triplicate.

For Fig , 160 μL of Pierce Anti-HA Magnetic Beads (Thermo Fisher Scientific, 88836) was washed 3 times with 1 mL of IP Lysis Buffer using a magnetic rack to separate the beads. After the final wash, the tube was briefly centrifuged with a mini centrifuge to collect the beads, which were resuspended in 160 μL of IP Lysis Buffer. A 20 μL portion of the washed beads was added to each IP fraction and then placed on a rotator at room temperature for 30 min.

6.

Confirmatory co-immunoprecipitation. (A) Total lysate showing expression of 3xFLAG-tagged RGS7 with and without 3xHA-tagged Gβ5, ALADIN (Aaas), ACAT2, EPS15L1, RPTOR, and RGS7 lacking the DEP/DHEX and GGL domains (ΔΔ-RGS7). (B) Immunoprecipitation using anti-HA-conjugated beads. RGS7 co-immunoprecipitates in the presence, but not the absence, of Gβ5 as expected. ALADIN, ACAT2, and RPTOR co-immunoprecipitate robustly, while EPS15L1 displays only a faint band. ΔΔ-RGS7 would be slightly above the antibody light-chain band and does not co-immunoprecipitate with Gβ5. Total protein stain was used as a loading control. Representative blot of triplicate experiments.

The supernatant was then removed, and the beads were washed 3 times with 1 mL of IP Lysis Buffer and 1 time with 1 mL of PBS, using a magnetic rack to separate the beads. After aspirating the PBS wash, IP fractions were centrifuged with a mini centrifuge to collect the beads. Beads were then resuspended in 4× LDS Sample Buffer diluted to 1× in IP Lysis Buffer with 100 mM dithiothreitol (DTT), and then boiled at 95 °C on a thermomixer at 750 rpm for 10 min. Total lysate fractions were thawed on ice, to which 4× LDS Sample Buffer and DTT were added to 1× and 100 mM, respectively. Total lysate fractions were then heated at 70 °C on a thermomixer at 500 rpm for 10 min. These samples were then stored at 4 °C overnight or immediately used for SDS-PAGE.

2.6. Subcellular Localization

Cells were lysed using a Subcellular Protein Fractionate Kit for Cultured Cells (Thermo Fisher Scientific, 78840) according to the manufacturer’s protocol. In brief, cells were washed with PBS, then harvested in 0.05% trypsin-EDTA (Gibco, 25300062), transferred to microcentrifuge tubes, and centrifuged at 500g for 5 min. Trypsin was aspirated, and then cell pellets were washed with 4 °C PBS and centrifuged at 500g for 3 min. The pellet was resuspended in 100 μL of cytosolic extraction buffer (CEB) with protease inhibitor and placed on a shaker at 4 °C for 10 min. Tubes were centrifuged at 500g for 5 min, and the supernatant was transferred to new, labeled tubes. Pellets were resuspended in 100 μL of membrane extraction buffer (MEB) with protease inhibitor, and then vortexed for 5 seconds before being placed on a shaker at 4 °C for 10 min. Tubes were then centrifuged at 3000g for 5 min, and the supernatant was transferred to new, labeled tubes. The pellets were then resuspended in 50 μL of nuclear extraction buffer (NEB) with protease inhibitor and vortexed for 15 seconds before being placed on a shaker at 4 °C for 30 min. Tubes were then centrifuged at 5000g for 5 min, and then the supernatant was transferred to new, labeled tubes. The CEB, MEB, and NEB extracts were then either stored at -20 °C for future use or immediately used for SDS-PAGE.

2.7. Biotin Time Course

10 mM biotin (Thermo Fisher Scientific, 29129) in DMSO was diluted in DMEM supplemented with 0.5% FBS to a 50 μM final concentration. Media were aspirated from the wells and replaced with biotin-supplemented medium for the indicated times, with the plate being returned to the incubator in between time points. Samples labeled 0 min had their medium replaced with DMEM supplemented with 0.5% FBS immediately before harvesting. Once the treatment time was complete, the plate was immediately placed on ice, and cells were harvested as described in Section 2.4.

2.8. Streptavidin Pulldown

N2A-mTGβ5 and N2A-mT were plated in 10 cm cell culture dishes and incubated to confluency. A 10 mM solution of biotin (Thermo Fisher Scientific, 29129) in DMSO was diluted in DMEM supplemented with 0.5% FBS to a 50 μM final concentration. Medium was aspirated from the dishes and replaced with biotin-supplemented medium, with one N2A-mTGβ5 dish being replaced with DMEM supplemented with 0.5% FBS without biotin. Dishes were placed at 37 °C with 5% CO₂ for 30 min and then placed on ice. Cells were harvested as described in Section 2.4. After lysis, protein concentration was determined, and samples were diluted to 1 μg/μL in RIPA buffer. A 5% portion of the total volume was transferred to a separate labeled tube for western blot analysis of the total lysate (Lysate).

160 μL of Roche Streptavidin Magnetic Particles (MilliporeSigma, 11641778001) was washed 3 times with 1 mL of RIPA Buffer using a magnetic rack to separate the beads. After the final wash, the tube was briefly centrifuged with a mini centrifuge to collect the beads, and they were resuspended to 160 μL with RIPA Buffer. 50 μL of beads was added to each sample and then placed on a rotator at room temperature for 30 min. After 30 min, the beads were separated using a magnetic rack, and 5% of the total volume was set aside for western blot analysis (referred to as the flow-through, F.T.).

The supernatant was then removed, and the beads were washed 3 times with 1 mL of IP Lysis Buffer and 1 time with 1 mL of PBS, using a magnetic rack to separate the beads. After the final resuspension, 5% of the total volume was set aside for western blot analysis of the streptavidin bead elution (Strep.). After aspirating the PBS wash, tubes were centrifuged with a mini centrifuge to collect beads. Beads were then resuspended in 100 μL of RIPA buffer and then frozen at −80 °C until used for mass spectrometry analysis. Lysate, F.T., and Strep. Aliquots were prepared for western blot analysis as described in Section 2.5.

2.9. SDS-Page and Western Blotting

Equal amounts of protein were resolved on 1.5 mm × 10 well NuPAGE 4–12% Bis-Tris gels (Thermo Fisher Scientific, NP0335BOX) or 1.5 mm × 15 well NuPAGE 4–12% Bis-Tris gels (Thermo Fisher Scientific, NP0336BOX) for 1 h at 160 V in MES Buffer (Thermo Fisher Scientific, NP0002) with Chameleon Duo Prestained Protein Ladder (Li-Cor Biosciences, 928-60000) for molecular weight reference. Protein was then transferred to an Immun-Blot LF PVDF membrane (Bio-Rad, 1620264) using NuPAGE Transfer Buffer (Thermo Fisher Scientific, NP0006-1). The membranes were then dried for 1 h, reactivated in methanol, and then stained with Revert 520 Total Protein Stain following the manufacturer’s protocol. After imaging and destaining, membranes were blocked with SuperBlock Blocking Buffer supplemented with 0.1% Tween-20 for 1 h at room temperature with mild agitation. Membranes were then incubated in primary antibody dilutions overnight at 4 °C with mild agitation. The following day, membranes were incubated with IRDye secondary antibody dilutions targeting the primary antibody species for 35 min at room temperature with mild agitation. After each antibody incubation, membranes were washed 4 times with PBS supplemented with 0.1% Tween-20 (PBS-T), with a final wash in PBS before imaging. Membranes were imaged using an iBright FL1000 imaging system (Thermo Fisher Scientific, A32752).

2.10. Mass Spectrometry and Peptide Identification

Samples were digested in solution with trypsin using S-Traps, according to the manufacturer’s instructions (ProtiFi; Fairport, New York). In brief, proteins were denatured in a buffer containing 5% SDS in 50 mM triethylammonium bicarbonate (a volatile mobile phase buffer) at pH 8.5. Next, the samples were reduced with 5 mM Tris­(2-carboxyethyl)­phosphine and alkylated with iodoacetamide at a concentration of 20 mM. The proteins were acidified to a final concentration of 2.5% phosphoric acid and diluted into 100 mM triethylammonium bicarbonate, pH 7.55, in 90% methanol. They were loaded onto the S-Traps, washed four times with 100 mM triethylammonium bicarbonate, pH 7.55, in 90% methanol, and digested by trypsinization overnight at 37 °C. Peptides were eluted from the S-Trap using 50 mM triethylammonium bicarbonate, pH 8.5; 0.2% formic acid in water; and 50% acetonitrile in water. These three elutions were pooled and taken to dryness by lyophilization.

The resulting peptides were analyzed on an Orbitrap Exploris 480 (Thermo Fisher Scientific) mass spectrometer using data-dependent acquisition (DDA) or on an Orbitrap Fusion Lumos mass spectrometer (Thermo Fisher Scientific) by data-independent acquisition (DIA). For the DDA experiments on the Exploris 480, peptides were separated on a 75 μm × 25 cm, 3 μm particle size, Acclaim PepMap C18 reversed phase silica column (Thermo Fisher Scientific) at a flow rate of 300 nL/min using an UltiMate 3000 RSLCnano UHPLC system (Thermo Fisher Scientific) and eluted directly into the mass spectrometer. Parent full-scan mass spectra (MS1) collected in the Orbitrap Exploris mass analyzer were set to acquire data at 1,20,000 FWHM resolution, and higher-energy collisional dissociation fragment ions (MS2) were acquired at 15,000 resolution. For DIA analysis on the Fusion Lumos, peptides were separated on a 75 μm × 25 cm, 3 μm particle size, Acclaim PepMap reversed phase column (Thermo Fisher Scientific) at a flow rate of 300 nL/min using an UltiMate 3000 RSLCnano UHPLC system (Thermo Fisher Scientific) and eluted directly into the mass spectrometer. Parent full-scan mass spectra (MS1) collected in the Orbitrap Exploris mass analyzer were set to acquire data at 1,20,000 FWHM resolution, followed by isolation of 4 Da nonoverlapping mass windows from 430–670 for higher-energy collisional dissociation fragmentation and detection in the Orbitrap Exploris at a resolution of 60,000.

DDA data were searched using the SequestHT node of Proteome Discoverer 3.0 (Thermo) against the Uniprot murine database. The search was restricted to tryptic peptides with a maximum of two missed cleavages allowed. Methionine oxidation was set as a variable modification, and cysteine carbamidomethylation was set as a fixed modification. Mass accuracy windows were as follows: the precursor mass tolerance was 10 ppm, and the fragment mass tolerance was 0.02 Da. The Percolator node was used to score and rank peptide-spectrum matches (PSMs) using a 1% false discovery rate (FDR). Percolator uses a decoy database containing reversed protein sequences to estimate the number of false positive identifications. Combined with the SequestHT scoring output, Percolator calculates the probability that a given peptide spectral match is incorrect (PEP) and the q-value minimum threshold at which a given match is accepted. Protein-level confidence scores are calculated as the sum of the logarithms of the PEP values for all peptides assigned to the protein. The Minora node was used to perform label-free quantitation (LFQ) of extracted-ion chromatograms from MS1 spectra.

DIA data were searched against a predicted spectral library built from the murine database from Uniprot using DIA-NN 1.9 using the default settings.35 DIA-NN uses a deep learning model to predict the likelihood that a given precursor ion matches a peptide sequence (CScore), comparing target and decoy databases. The CScore is converted into a q-value representing the false discovery rate for the peptide, with protein q-values calculated from peptide-level q-values using precursors specific to the protein of interest.

2.11. Protein–Protein Interaction Network Analysis

Datasets were input into the STRING database by gene name to construct interaction networks and calculate Protein–Protein Interaction p-values. These networks were then exported to Cytoscape for visualization and for creating figures.

2.12. Ingenuity Pathways Analysis

Data were analyzed through the use of QIAGEN Ingenuity Pathway Analysis (IPA). The Diseases & Functions Analysis identified the biological functions and/or diseases that were most significant from the dataset. Molecules from the dataset that met the fold-change cutoff threshold of 5-fold or greater (miniTurbo-Gβ5 compared to miniTurbo) with a p-value ≤ 0.05 and were linked to diseases and/or biological functions in the QIAGEN Knowledge Base were considered for subsequent analysis. To calculate a p-value to determine the probability that each disease and/or biological function assigned to that dataset is due to chance alone, a right-tailed Fisher’s exact test was used. To indicate the likelihood of an increase or decrease of that function or disease, a z-score was calculated. The pathways from the QIAGEN Ingenuity Pathway Analysis (IPA) library of canonical pathways that were most significant to the dataset were identified by Canonical Pathways analysis. Molecules present in the dataset that met the fold-change cutoff threshold of 5-fold or greater (miniTurbo-Gβ5 versus miniTurbo) with a p-value ≤ 0.05 and which were associated with a canonical pathway in the QIAGEN Knowledge Base were considered for subsequent analysis. The significance of the association linking the dataset and the canonical pathway was determined in two ways: (1) by calculating the ratio of the number of molecules from the dataset mapping to the pathway to the total number of molecules mapping to the same canonical pathway; and (2) by performing a right-tailed Fisher’s exact test to calculate a p-value to determine the likelihood that the association between the genes in the dataset and the canonical pathway could be explained by chance alone. In many cases, to evaluate the likelihood of activation or inhibition of that pathway, a z-score was calculated.

2.13. Statistical Analysis

To calculate the significance and fold-change of peptides identified via mass-spectrometry, the log2 of the relative abundance for each peptide identified was compared between miniTurbo-Gβ5 and miniTurbo with a Paired t test using a parametric test with no correction for multiple comparisons. All experiments were performed with three biological replicates. This analysis was performed in GraphPad Prism 10.4.0 (GraphPad, La Jolla, CA). Statistical analysis for IPA studies was performed as described in Section 2.12.

3. Results

3.1. Validation of the miniTurbo-Gβ5 Fusion Protein

Proximity labeling coupled with mass spectrometry is a well-established method undergoing continual development, and we used previously published and validated protocols to guide our experimental design. We used lentivirus particles packaged with either miniTurbo biotin ligase or miniTurbo fused to the N-terminal of Gβ5 to transduce Neuro-2a mouse neuroblastoma cells (we refer to these cell lines as N2A-mT or N2A-mTGβ5, respectively). After selecting with Blasticidin S HCL for 1 week (10 μg/mL), we verified the expression of the constructs (Figure A). A nonspecific band was present that migrated at a slightly higher molecular weight (MW) than miniTurbo, but miniTurbo expression was evident by comparing lanes. During this experiment, we also transiently transfected 3xFLAG-RGS7 into both N2A-mTGβ5 and N2A-mT cells to test if the fusion of miniTurbo interfered with Gβ5 binding RGS7 during co-immunoprecipitation. When we immunoprecipitated miniTurbo (using an anti-BirA antibody), RGS7 was pulled down in the presence of miniTurbo-Gβ5 but not miniTurbo. Next, we wanted to ensure the miniTurbo-Gβ5 fusion protein localized subcellularly in a similar manner to endogenous Gβ5 (Figure B). Like endogenous Gβ5 and RGS7, miniTurbo-Gβ5 expressed in the cytosol, membrane, and soluble nuclear fractions of Neuro-2a cells. miniTurbo itself expressed in the cytosol and membrane fractions, though the membrane band was obscured slightly by the previously identified nonspecific band.

Our next step was to verify that our constructs had active biotin ligase activity (Figure C). We treated N2A-mTGβ5 and N2A-mT cells with 50 μM biotin for 0, 10, 20, 30, or 60 min. We also treated wild-type Neuro-2a cells (N2A-WT) with 50 μM biotin for 0 or 60 min as a negative control. After resolving the lysates via SDS-PAGE and transferring to a PVDF membrane, we stained with Streptavidin Alexa 680 to image total biotinylation. We observed no biotinylation in N2A-WT, apart from three high-MW fluorescent bands present in every condition, likely corresponding to endogenously biotinylated proteins such as acetyl-CoA carboxylase (Acaca). Biotinylation increased with time in both N2A-mTGβ5 and N2A-mT. Interestingly, we not only observed self-biotinylation of miniTurbo-Gβ5 and miniTurbo, but also an intense signal in N2A-mTGβ5 lysates at the same MW as endogenous RGS7 (∼55 kDa). Given the constitutive dimerization of Gβ5 and RGS7, we determined that the likelihood that this band represented nonspecific biotinylation, which may interfere with interpreting our results, is low.

Having demonstrated that the miniTurbo-Gβ5 binds RGS7, retains endogenous-like subcellular localization, and possesses biotin ligase activity, we proceeded to streptavidin enrichment for mass spectrometry. To ensure that we successfully performed biotinylation and streptavidin enrichment, we first resolved fractions of the total lysate, flow-through (F.T.), and streptavidin bead elutions (Strep.) with SDS-PAGE before analyzing the samples via mass spectrometry (Figure D). Staining with Streptavidin Alexa 680 demonstrated biotinylation in N2A-mTGβ5 and N2A-mT samples treated with 50 μM biotin for 30 min, with reduced staining in the F.T. fractions. Minimal biotinylation was observed in the N2A-mTGβ5 samples not treated with biotin, as seen in the experiments described above, which functioned as an additional negative control. While we observe the ∼55 kDa biotinylated band from Figure C in the miniTurbo-Gβ5 streptavidin pulldown, we do not observe a signal when blotting for RGS7; if the ∼55 kDa band corresponds to RGS7, this is likely because streptavidin Alexa 680 can bind multiple sites on a biotinylated protein as opposed to one antigen site, thus providing a stronger signal when less protein is present on the membrane.

The enriched proteins were in-solution digested with trypsin and subjected to mass spectrometry analysis with label-free quantification. To ensure the deepest sensitivity and coverage for protein identification, data were collected by using both data-dependent acquisition (DDA) and data-independent acquisition (DIA) methods. In DDA, parent ions are individually isolated and fragmented, resulting in an MS/MS spectrum the corresponds to the isolated peptide; in DIA, all ions within a set m/z window are isolated and fragmented together, giving rise to an MS/MS spectrum with fragment ions from all peptides in that range. Although DDA methods provide a direct link between the parent ion mass and fragment ions, they tend to be biased toward higher-intensity ions; in contrast, though there is a requirement to deconvolute chimeric MS/MS spectra in a DIA, there are fewer missing values and greater protein identification since all ions have the potential to be fragmented regardless of abundance. Consistent with these differences, the DDA analysis identified a total of 2625 proteins across all samples, whereas the DIA analysis identified a total of 6744 (Tables S1 and S2).

3.2. Network and Pathway Analysis of Mass Spectrometry Results

From the mass spectrometry analysis, we first performed statistical analysis to identify high-confidence protein interactions (fold-change of abundance ≥ 5 relative to miniTurbo + biotin and p-value ≤ 0.05) for both DDA (Figure ) and DIA (Figure ) approaches. Next, we uploaded the statistically significant proteins of each dataset into the STRING Database to determine known interactions and calculate a protein–protein interaction (PPI) enrichment p-value to determine whether our results were indicative of a biologically plausible interaction network. Finally, we uploaded each dataset into QIAGEN’s Ingenuity Pathways Analysis (IPA) data analysis and visualization platform, restricted analysis to only high-confidence proteins, and examined the subcellular localization, pathways, diseases, and functions implicated by our results (Tables S3–S8, Figures , and ).

2.

DDA results. (A) Volcano plot of proteins identified via data-dependent acquisition mass-spectrometry. Proteins with p-value ≤ 0.05 and >5 fold-change relative to miniTurbo control are highlighted red (n = 25), with particularly enriched and significant ones labeled. (B) Pie graph of previously known interactors of Gβ5 (as determined by STRING Database v12) and previously unknown (novel) interactors identified in our mass-spectrometry results with >5 fold-change relative to miniTurbo control (n = 24 total interactors, excluding Gβ5). (C) Interaction network of all identified proteins with p-value ≤ 0.05 and positive fold-change relative to control. The red node is Gβ5, pink nodes are previously reported interactors of Gβ5, yellow nodes are those with >5 fold-change relative to control, and the orange node is a previously identified interactor of Gβ5 with >5 fold-change. The network was originally constructed in STRING and then exported to Cytoscape for visualization. Nodes with no interactions are not displayed.

3.

DIA results. (A) Volcano plot of proteins identified via data-independent acquisition mass-spectrometry. Proteins with p-value ≤ 0.05 and >5 fold-change relative to miniTurbo control are highlighted red (n = 25), with particularly enriched and significant ones labeled. (B) Pie graph of previously known interactors of Gβ5 (as determined by STRING Database v12) and previously unknown (novel) interactors identified in our mass-spectrometry results with >5 fold-change relative to miniTurbo control (n = 24 total interactors, excluding Gβ5). (C) Interaction network of all identified proteins with p-value ≤ 0.05 and positive fold-change relative to control. The red node is Gβ5, pink nodes are previously reported interactors of Gβ5, yellow nodes are those with >5 fold-change relative to control, and the orange node is a previously identified interactor of Gβ5 with >5 fold-change. The network was originally constructed in STRING and then exported to Cytoscape for visualization. Nodes with no interactions are not displayed.

4.

Subcellular localization of (A) DDA and (B) DIA results.

5.

Disease and function categories according to IPA. (A and B) The −log10­(p-value) of the ten most significant disease and function categories for proteins identified through (A) DDA and (B) DIA with >5 fold-change compared to control. The red dashed line denotes a p-value of 0.05. (C and D) The number of identified proteins in each of the ten most significant disease and function categories for proteins identified through (C) DDA and (D) DIA with >5 fold-change compared to control. The black dashed line denotes the total number of proteins (25) identified. (E and F) Venn diagram comparing the statistically significant disease and function categories (E) and specific diseases and functions (F) for DDA and DIA interactomes, as determined by IPA.

In our DDA results, 24 proteins were identified as high-confidence (excluding Gβ5 itself), and of those, 2 (CDC42 and Unconventional Myosin-Va, MYO5A) have been previously shown to interact with Gβ5 (Figure A,B). STRING network analysis of all statistically significant proteins resulted in a PPI enrichment p-value for the network of <10^–16 with 183 proteins, indicating that our results were statistically enriched for known protein–protein interactions and represent a plausible interaction network (Figure C). IPA analysis of our high-confidence results revealed the majority (17) of proteins localized to the cytoplasm, with some (4 each) found in the nucleus and on the plasma membrane (Figure A). From the Disease and Functions Categories analysis relevant to our scientific focus, our results were enriched with proteins important for cellular assembly and organization, cell morphology, nervous system development and function, and organismal development (Figure A,C). The full list of high-confidence proteins is presented in Table , and IPA analysis of Disease and Functions Categories (Table S3), Pathways (Table S4), and detailed Disease and Functions (Table S5) are presented in the supplemental materials. Tables S3–S5 include the mapped disease/function/pathway, which proteins map to which disease/function/pathway, and p-value as calculated by IPA analysis.

1. Identified Proteins, p-Values, and Fold-Change from DDA (5-Fold Cutoff).

UniProt ID	gene symbol	entrez gene name	fold-change	p-value	subcellular localization
Q60902	EPS15L1	epidermal growth factor receptor pathway substrate 15-like-1	682.176	0.000052	plasma membrane
P58742	AAAS	ALADIN WD repeat nucleoporin	3590.577	0.000667	nucleus
Q8CII2	CDC123	cell division cycle 123	641.364	0.00121	cytoplasm
Q07813	BAX	BCL2-associated X, apoptosis regulator	2005.853	0.0015	cytoplasm
Q8CI61	BAG4	BAG cochaperone 4	557.18	0.00184	cytoplasm
Q8CAY6	Acat2/Acat3	acetyl-Coenzyme A acetyltransferase 2	4067.707	0.00389	other
Q8R5J9	ARL6IP5	ADP ribosylation factor-like GTPase 6-interacting protein 5	5.487	0.00544	cytoplasm
Q9JJY4	DDX20	DEAD-box helicase 20	662.143	0.00587	nucleus
O54984	GET3	guided entry of tail-anchored proteins factor 3, ATPase	14.32	0.00783	nucleus
Q62418	DBNL	Drebrin-like	843.942	0.0117	cytoplasm
Q99104	MYO5A	myosin-VA	5.618	0.0122	cytoplasm
P04223	HLA-A	major histocompatibility complex, class I, A	1332.574	0.0132	plasma membrane
Q9D0M0	EXOSC7	exosome component 7	5.748	0.0138	nucleus
Q8K4Q0	RPTOR	regulatory-associated protein of mTOR complex 1	2076.589	0.0153	cytoplasm
P60766	CDC42	cell division cycle 42	5.901	0.017	cytoplasm
P61202	COPS2	COP9 signalosome subunit 2	7.265	0.0221	cytoplasm
Q9JMA1	USP14	ubiquitin-specific peptidase 14	5.95	0.0223	cytoplasm
P62881	GNB5	G protein subunit β 5	267.983	0.0257	plasma membrane
O89017	LGMN	legumain	6.916	0.031	cytoplasm
Q8VCM8	NCLN	nicalin	7.042	0.032	cytoplasm
Q9CXF4	TBC1D15	TBC1 domain family member 15	5.926	0.0329	other
Q62261	SPTBN1	spectrin β, nonerythrocytic 1	5.134	0.0336	plasma membrane
O88447	KLC1	kinesin light chain 1	5.326	0.0388	cytoplasm
Q3UJB9	EDC4	enhancer of mRNA decapping 4	5.776	0.0459	cytoplasm
Q9DBJ1	PGAM1	phosphoglycerate mutase 1	6.94	0.0491	cytoplasm

We performed the same analysis on our DIA results, with 24 proteins identified as high-confidence (excluding Gβ5 itself), of which one (Metabotropic Glycine Receptor, GPR158) has been previously shown to interact with Gβ5 (Figure A,B). STRING network analysis of all statistically significant proteins resulted in a PPI enrichment p-value for the network of 8.21 × 10^–16 with 113 total proteins, indicating that our results were statistically enriched for known protein–protein interactions and represent a plausible interaction network (Figure C). IPA analysis of our high-confidence results revealed similar subcellular localization to our DDA results with some differences: 11 proteins localized to the cytosol, 3 to the nucleus, 6 to the plasma membrane, 3 to other, and 2 to the extracellular space (Figure B). From the Disease and Functions Categories analysis relevant to our scientific focus, our results were enriched with proteins important for cellular assembly and organization, cell morphology, nervous system development and function, and organismal development (Figure A,C). The complete list of high-confidence proteins is presented in Table , and IPA analysis of Disease and Functions Categories (Table S6), Pathways (Table S7), and detailed Disease and Functions (Table S8) are presented in the supplemental materials. Tables S6–S8 include the mapped disease/function/pathway, which proteins map to which disease/function/pathway, and p-value as calculated by IPA analysis.

2. Identified Proteins, p-Values, and Fold-Change from DIA (5-Fold Cutoff).

UniProt ID	gene symbol	entrez gene name	fold-change	p-value	subcellular localization
P00158	MT-CYB	cytochrome b	38.77353	5.8 × 10–09	cytoplasm
Q8C419	GPR158	G-protein-coupled receptor 158	260.2943	4.59 × 10–08	plasma membrane
Q8R3L8	CDK8	cyclin-dependent kinase 8	134.6434277	8.97 × 10–08	other
Q8BGA2	LHFPL2	LHFPL tetraspan subfamily member 2	85.98422	0.000000132	other
Q9D4V0	ETNK1	ethanolamine kinase 1	46.0778	0.000000192	other
Q3UHR0	BAHCC1	BAH domain and coiled-coil containing 1	90.07158	0.000000295	cytoplasm
Q8VED2	BLOC1S4	biogenesis of lysosomal organelles complex 1 subunit 4	418.4757	0.0000111	plasma membrane
D3YZV8	CCDC8	coiled-coil domain containing 8	58.48521	0.0000111	nucleus
Q80WS3	FBLL1	fibrillarin-like-1	176.3136	0.0000137	plasma membrane
Q8R3L5	SLCO3A1	solute carrier organic anion transporter family member 3A1	41.298	0.0000585	cytoplasm
Q8R5A3	APBB1IP	amyloid β precursor protein binding family B member 1 interacting protein	39.83598	0.0000596	plasma membrane
P70414	SLC8A1	solute carrier family 8 member A1	30.19002	0.0000906	cytoplasm
Q9DCA2	MRPS11	mitochondrial ribosomal protein S11	60.33821	0.000112	cytoplasm
P58660	CARD10	caspase recruitment domain family member 10	115.2002	0.000116	other
Q3TZ65	CIMAP1D	CIMAP1 family member D	50.73818	0.000169	cytoplasm
Q9D1H0	RITA1	RBPJ interacting and tubulin-associated 1	36.15191	0.000192	extracellular space
Q6P6J9	TXNDC15	thioredoxin domain containing 15	37.84419	0.000217	plasma membrane
Q8K211	SLC31A1	solute carrier family 31 member 1	22.73747	0.00022	other
Q9QXW0	FBXL6	F-box and leucine-rich repeat protein 6	39.20593	0.000346	cytoplasm
Q9DBA6	TYSND1	trypsin-like peroxisomal matrix peptidase 1	39.47863	0.000545	cytoplasm
Q9D958	SPCS1	signal peptidase complex subunit 1	67.50863	0.00176	cytoplasm
P62881	GNB5	G protein subunit β 5	978.2097	0.0136	plasma membrane
Q6KAU4	MVB12B	multivesicular body subunit 12B	15.67072	0.0359	cytoplasm
Q99PI4	LPIN3	lipin 3	14.50019	0.046	nucleus
Q08879	FBLN1	fibulin 1	24.98517	0.0471	extracellular space

Peptides identified for high-confidence proteins are available in Table S9 (DDA) and Table S10 (DIA). For both DDA and DIA, we mapped the peptides onto the full protein sequences in Table S11.

3.3. Confirmatory Co-Immunoprecipitation of Select DDA Hits

Since proximity-labeling assays employing miniTurbo do not provide direct proof of physical interaction between two proteins but instead rely on their spatial proximity within a living cell, we wanted to perform an orthogonal assay to assess whether direct physical interactions between Gβ5 and the identified proteins were likely. To that end, we utilized co-immunoprecipitation between 3xHA-tagged Gβ5 and 3xFLAG-tagged versions of ALADIN (nucleus), ACAT2 (other localization), EPS15L1 (plasma membrane), and RPTOR (cytoplasm), which were identified via DDA (ALADIN was previously referred to by its gene symbol, Aaas, in Figure A,C). These candidates were selected to represent each subcellular localization and a fold-change of 2000 or higher, except for EPS15L1, which was included as the plasma membrane candidate due to being the most statistically significant identified protein since no plasma membrane protein met the 2000-fold-change cutoff. We limited our options to the DDA results due to their relatively higher fold-change and network connectivity compared to DIA. We intend to follow up on DIA candidate interactors by co-immunoprecipitation assays in future research.

For co-immunoprecipitation, we utilized 3xFLAG-tagged RGS7 as a positive control, and both 3xFLAG-tagged mutant RGS7 lacking the DEP/DHEX and GGL domains (not expected to bind Gβ5) and 3xFLAG-tagged RGS7 without 3xHA-tagged Gβ5 as negative controls (Figure A). After co-immunoprecipitation, we saw FLAG immunoreactivity for the RGS7 positive control but neither of the negative controls, indicating a successful IP (Figure B). We also saw strong FLAG immunoreactivity for ALADIN, and a moderate signal for ACAT2 and RPTOR in the anti-HA pulldowns. A faint band was present at the expected molecular weight for EPS15L1, which may indicate a weak or indirect interaction between it and Gβ5. Overall, these results affirm that proximity labeling via miniTurbo is an effective way to identify novel protein interactions, which can be confirmed via orthogonal methods.

4. Discussion

Gβ5 and RGS7 have previously been shown to express in the cytosol, nucleus, and at the plasma membrane, though only their function at the plasma membrane is well-characterized. To identify possible leads to investigate their role(s) in the cytosol and nucleus, we utilized live cell proximity labeling to uncover potential interacting proteins in these subcellular compartments. Across both DDA and DIA mass spectrometry, we identified a total of 48 high-confidence potential interactors, many of which are involved in development (Figure ). Minimal overlap was observed between the DDA and DIA datasets. This arises from fundamental differences in how the mass spectrometer is operated, with DIA being less sensitive to peptide abundance. Because miniTurbo does not seem to express in the nucleus, further validation is required to increase confidence in these results. The presence of several known interactors of Gβ5 in our results is promising. The absence of other known interactors may be explained by a lack of surface-exposed lysine residues for biotinylation, a lack of expression in Neuro-2a cells, a lack of expression of scaffolding/mediating interactors, or a lack of signaling or cellular conditions that initiate the interaction. RGS7 was present at high relative abundance in our MS results for both DDA and DIA; however, nonspecific labeling by miniTurbo in some replicates reduced the statistical significance. We believe this indicates that other potential interacting partners of Gβ5 may not be represented in our results and may require orthogonal methods, such as affinity purification, to identify.

On the basis of biological relevance, statistical significance, and fold-change, we selected five of our DDA hits for confirmatory co-immunoprecipitation: ALADIN, Bax, ACAT2, EPS15L1, and RPTOR (Figure ). Bax was ultimately excluded due to known overexpression toxicity, which would have required drug treatment or overexpression of apoptosis suppressors to overcome, thus potentially complicating our results (data not shown).

ALADIN, encoded by the gene Aaas, is a WD40 repeat protein that localizes to the cytosolic side of the nuclear pore complex, thus regulating nuclear import. , Mutations in Aaas are associated with a rare developmental disorder, Triple-A syndrome (also known as Allgrove disease), characterized by Achalasia (defective esophageal motility), Adrenal insufficiency in the absence of melanocortin receptor 2 mutations, and Alacrima (insufficient tear production). , While these three symptoms are nearly universal to the disorder, a wide variety of symptoms have been associated with it, including ataxia, hypotonia, intellectual disability, and optic atrophy. , Increased DNA damage due to oxidative stress is thought to play an important role in the pathology, and the mechanism underlying adrenocorticotropin hormone resistance is believed to result from impaired glucocorticoid precursor synthesis. , Given ALADIN’s role in nuclear import, the previously documented Gβ5/RGS7 nuclear localization, and the interaction between the Gβ5 and ALADIN that we identified in this study, we hypothesize that ALADIN is essential for Gβ5/RGS7 nuclear localization and intend to investigate this in future studies.

ACAT2 (Acyl coenzyme A:cholesterol acyltransferase type 2) is one of the enzymes responsible for cholesterol ester formation. ACAT2 is primarily expressed in the intestines, where it regulates cholesterol uptake. , It has also been found in the liver, motor neurons, and microglia as well. ACAT2 has been shown to be upregulated in a mouse model of amyotrophic lateral sclerosis. As an important metabolic protein, ACAT2 levels are also altered in several types of cancer. − ACAT2 has been linked to nonalcoholic fatty liver disease and cholesterol-induced steatosis and could possibly be relevant to previously described Gβ5/R7-associated liver inflammation. − The possible functional connection between Gβ5/RGS7 and ACAT2 is unclear and warrants further investigation.

EPS15L1 (Epidermal growth factor receptor Pathway Substrate 15-Like-1) is a constitutive component of clathrin-coated pits important for endocytosis. While EPS15L1 shares some redundancy with the closely related EPS15, EPS15L1 is uniquely important in the nervous system. EPS15L1 knockout mice show poor survivability due to its importance in neonatal development, with all Eps15l1^–/– mice dying within 2 weeks of birth. Eps15l1^–/– mice showed a reduced response to tail flick tests, severely impaired feeding behavior, reduced respiratory function, and a 50% reduction in synaptic vesicles. In humans, loss-of-function mutations in EPS15L1 have been linked to split hand/foot malformation, further indicating an important role in healthy development. − EPS15L1 is relatively understudied, with only 20 results on PubMed as of this publication. While EPS15L1 is not known to play a role in GPCR-related endocytosis, its localization to clathrin-coated pits is likely relevant to its interaction with Gβ5/RGS7 and should serve as a starting point for future investigations.

RPTOR (Regulatory-associated Protein of mTOR) is a scaffolding protein of mTOR complex 1 (mTORc1) important in mediating cell growth, mRNA translation, and protein synthesis. , RPTOR is known to be important for development in multiple tissues. Selective deletion of RPTOR in mouse preosteoblasts leads to reduced bone mass, limb length, and osteoblast differentiation while increasing marrow adiposity. , In retinal progenitor cells, RPTOR knockout results in reduced proliferation, reduced lamination, and increased apoptosis, resulting in abnormal retinal morphology in adult mice and impaired visual function. , Likewise, neural crest-specific deletion of RPTOR results in impaired proliferation and increased apoptosis, ultimately leading to deformities in all neural crest-derived tissues. Gβ5 was previously shown to co-immunoprecipitate with the carboxyl terminus of mTOR itself, though this was in a complex with Gγ2 and not with RGS7 or another R7 family member. In this study, the authors demonstrated that Gβ₁γ₂ enhanced mTOR signaling but did not examine Gβ5 specifically.

5. Conclusion

Utilizing proximity labeling via miniTurbo, we identified 48 putative proteins in multiple cellular compartments that interact with Gβ5. Our Gβ5 interactome is enriched with proteins involved in the nervous system and organismal development, processes in which Gβ5 is already heavily implicated. Of the four proteins we confirmed via co-immunoprecipitation, there is some pathological overlap with Gβ5 for three. With ALADIN, hypotonia, intellectual disability, and optic atrophy are all symptoms shared with IDDCA. The link with ACAT2, both mechanistically and pathologically, is uncertain and warrants further investigation. EPS15L1 and Gβ5 mouse knockout models both share high post-natal mortality, reduced body weight, and hyperactivity as measured by open field testing. , Both RPTOR and Gβ5 are implicated in neuronal development and healthy ocular function. Whether it is possible that these overlaps in function are superficial rather than mechanistic is for future studies to determine; however, identifying the Gβ5 interactome in a neuronal-like cell model provides a solid foundation for future research to understand the biological functions of Gβ5 and R7-RGS proteins in the cytosol and nucleus.

Glossary

Abbreviations

DDA

data-dependent acquisition

DIA

data-independent acquisition

GPCR

G-protein coupled receptor

GAP

GTPase-activating protein

PPI

protein–protein interaction

RGS

regulator of G-protein signaling

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsomega.6c05064.

• DDA identified proteins and abundance; DIA identified proteins and abundance; DDA enriched diseases and functions categories; DDA enriched pathways; DDA enriched specific diseases and functions; DIA enriched diseases and functions categories; DIA enriched pathways; DIA enriched specific diseases and functions; DDA identified peptides; and DIA identified peptides (XLSX)

• Identified peptides mapped to protein sequences (PDF)

H.J.M., J.Z., L.M.J., and W.F.S. contributed to experimental design, with L.M.J. specifically handling mass spectrometry experiments. H.J.M. conducted all experiments other than mass spectrometry, which was conducted by C.P.J. (preparing samples for analysis), W.Y. (DIA analysis), and L.M.J. H.J.M. primarily wrote the manuscript, with contributions and editing from J.Z., L.M.J., and W.F.S.

The authors declare no competing financial interest.