A general molecular affinity strategy for global detection and proteomic analysis of lysine methylation.

Lysine methylation of histone proteins regulates chromatin dynamics and plays important roles in diverse physiological and pathological processes. However, beyond histone proteins, the proteome-wide extent of lysine methylation remains largely unknown. We have engineered the naturally occurring MBT domain repeats of L3MBTL1 to serve as a universal affinity reagent for detecting, enriching, and identifying proteins carrying a mono- or dimethylated lysine. The domain is broadly specific for methylated lysine ("pan-specific") and can be applied to any biological system. We have used our approach to demonstrate that SIRT1 is a substrate of the methyltransferase G9a both in vitro and in cells, to perform proteome-wide detection and enrichment of methylated proteins, and to identify candidate in-cell substrates of G9a and the related methyltransferase GLP. Together, our results demonstrate a powerful new approach for global and quantitative analysis of methylated lysine, and they represent the first systems biology understanding of lysine methylation.

Integrated systems biology analysis of KSHV latent infection reveals viral induction and reliance on peroxisome mediated lipid metabolism.

Kaposi's Sarcoma associated Herpesvirus (KSHV), an oncogenic, human gamma-herpesvirus, is the etiological agent of Kaposi's Sarcoma the most common tumor of AIDS patients world-wide. KSHV is predominantly latent in the main KS tumor cell, the spindle cell, a cell of endothelial origin. KSHV modulates numerous host cell-signaling pathways to activate endothelial cells including major metabolic pathways involved in lipid metabolism. To identify the underlying cellular mechanisms of KSHV alteration of host signaling and endothelial cell activation, we identified changes in the host proteome, phosphoproteome and transcriptome landscape following KSHV infection of endothelial cells. A Steiner forest algorithm was used to integrate the global data sets and, together with transcriptome based predicted transcription factor activity, cellular networks altered by latent KSHV were predicted. Several interesting pathways were identified, including peroxisome biogenesis. To validate the predictions, we showed that KSHV latent infection increases the number of peroxisomes per cell. Additionally, proteins involved in peroxisomal lipid metabolism of very long chain fatty acids, including ABCD3 and ACOX1, are required for the survival of latently infected cells. In summary, novel cellular pathways altered during herpesvirus latency that could not be predicted by a single systems biology platform, were identified by integrated proteomics and transcriptomics data analysis and when correlated with our metabolomics data revealed that peroxisome lipid metabolism is essential for KSHV latent infection of endothelial cells.

A computationally engineered RAS rheostat reveals RAS-ERK signaling dynamics.

Synthetic protein switches controlled with user-defined inputs are powerful tools for studying and controlling dynamic cellular processes. To date, these approaches have relied primarily on intermolecular regulation. Here we report a computationally guided framework for engineering intramolecular regulation of protein function. We utilize this framework to develop chemically inducible activator of RAS (CIAR), a single-component RAS rheostat that directly activates endogenous RAS in response to a small molecule. Using CIAR, we show that direct RAS activation elicits markedly different RAS-ERK signaling dynamics from growth factor stimulation, and that these dynamics differ among cell types. We also found that the clinically approved RAF inhibitor vemurafenib potently primes cells to respond to direct wild-type RAS activation. These results demonstrate the utility of CIAR for quantitatively interrogating RAS signaling. Finally, we demonstrate the general utility of our approach in design of intramolecularly regulated protein tools by applying it to the Rho family of guanine nucleotide exchange factors.

Endogenous N-terminal Domain Cleavage Modulates α1D-Adrenergic Receptor Pharmacodynamics.

The α1D-adrenergic receptor (ADRA1D) is a key regulator of cardiovascular, prostate, and central nervous system functions. This clinically relevant G protein-coupled receptor has proven difficult to study, as it must form an obligate modular homodimer containing the PDZ proteins scribble and syntrophin or become retained in the endoplasmic reticulum as non-functional protein. We previously determined that targeted removal of the N-terminal (NT) 79 amino acids facilitates ADRA1D plasma membrane expression and agonist-stimulated functional responses. However, whether such an event occurs in physiological contexts was unknown. Herein, we report the ADRA1D is subjected to innate NT processing in cultured human cells. SNAP near-infrared imaging and tandem-affinity purification revealed the ADRA1D is expressed as both full-length and NT truncated forms in multiple human cell lines. Serial truncation mapping identified the cleavage site as Leu(90)/Val(91) in the 95-amino acid ADRA1D NT domain, suggesting human cells express a Δ1-91 ADRA1D species. Tandem-affinity purification MS/MS and co-immunoprecipitation analysis indicate NT processing of ADRA1D is not required to form scribble-syntrophin macromolecular complexes. Yet, label-free dynamic mass redistribution signaling assays demonstrate that Δ1-91 ADRA1D agonist responses were greater than WT ADRA1D. Mutagenesis of the cleavage site nullified the processing event, resulting in ADRA1D agonist responses less than the WT receptor. Thus, we propose that processing of the ADRA1D NT domain is a physiological mechanism employed by cells to generate a functional ADRA1D isoform with optimal pharmacodynamic properties.

The Tec Kinase-Regulated Phosphoproteome Reveals a Mechanism for the Regulation of Inhibitory Signals in Murine Macrophages.

Previous work has shown conflicting roles for Tec family kinases in regulation of TLR-dependent signaling in myeloid cells. In the present study, we performed a detailed investigation of the role of the Tec kinases Btk and Tec kinases in regulating TLR signaling in several types of primary murine macrophages. We demonstrate that primary resident peritoneal macrophages deficient for Btk and Tec secrete less proinflammatory cytokines in response to TLR stimulation than do wild-type cells. In contrast, we found that bone marrow-derived and thioglycollate-elicited peritoneal macrophages deficient for Btk and Tec secrete more proinflammatory cytokines than do wild-type cells. We then compared the phosphoproteome regulated by Tec kinases and LPS in primary peritoneal and bone marrow-derived macrophages. From this analysis we determined that Tec kinases regulate different signaling programs in these cell types. In additional studies using bone marrow-derived macrophages, we found that Tec and Btk promote phosphorylation events necessary for immunoreceptor-mediated inhibition of TLR signaling. Taken together, our results are consistent with a model where Tec kinases (Btk, Tec, Bmx) are required for TLR-dependent signaling in many types of myeloid cells. However, our data also support a cell type-specific TLR inhibitory role for Btk and Tec that is mediated by immunoreceptor activation and signaling via PI3K.

Dynamic mass redistribution reveals diverging importance of PDZ-ligands for G protein-coupled receptor pharmacodynamics.

G protein-coupled receptors (GPCRs) are essential membrane proteins that facilitate cell-to-cell communication and co-ordinate physiological processes. At least 30 human GPCRs contain a Type I PSD-95/DLG/Zo-1 (PDZ) ligand in their distal C-terminal domain; this four amino acid motif of X-[S/T]-X-[φ] sequence facilitates interactions with PDZ domain-containing proteins. Because PDZ protein interactions have profound effects on GPCR ligand pharmacology, cellular localization, signal-transduction effector coupling and duration of activity, we analyzed the importance of Type I PDZ ligands for the function of 23 full-length and PDZ-ligand truncated (ΔPDZ) human GPCRs in cultured human cells. SNAP-epitope tag polyacrylamide gel electrophoresis revealed most Type I PDZ GPCRs exist as both monomers and multimers; removal of the PDZ ligand played minimal role in multimer formation. Additionally, SNAP-cell surface staining indicated removal of the PDZ ligand had minimal effects on plasma membrane localization for most GPCRs examined. Label-free dynamic mass redistribution functional responses, however, revealed diverging effects of the PDZ ligand. While no clear trend was observed across all GPCRs tested or even within receptor families, a subset of GPCRs displayed diminished agonist efficacy in the absence of a PDZ ligand (i.e. HT2RB, ADRB1), whereas others demonstrated enhanced agonist efficacies (i.e. LPAR2, SSTR5). These results demonstrate the utility of label-free functional assays to tease apart the contributions of conserved protein interaction domains for GPCR signal-transduction coupling in cultured cells.

Protein kinase PKN1 represses Wnt/ß-catenin signaling in human melanoma cells.

Advances in phosphoproteomics have made it possible to monitor changes in protein phosphorylation that occur at different steps in signal transduction and have aided the identification of new pathway components. In the present study, we applied this technology to advance our understanding of the responses of melanoma cells to signaling initiated by the secreted ligand WNT3A. We started by comparing the phosphopeptide patterns of cells treated with WNT3A for different periods of time. Next, we integrated these data sets with the results from a siRNA screen that targeted protein kinases. This integration of siRNA screening and proteomics enabled us to identify four kinases that exhibit altered phosphorylation in response to WNT3A and that regulate a luciferase reporter of ß-catenin-responsive transcription (ß-catenin-activated reporter). We focused on one of these kinases, an atypical PKC kinase, protein kinase N1 (PKN1). Reducing the levels of PKN1 with siRNAs significantly enhances activation of ß-catenin-activated reporter and increases apoptosis in melanoma cell lines. Using affinity purification followed by mass spectrometry, we then found that PKN1 is present in a protein complex with a WNT3A receptor, Frizzled 7, as well as with proteins that co-purify with Frizzled 7. These data establish that the protein kinase PKN1 inhibits Wnt/ß-catenin signaling and sensitizes melanoma cells to cell death stimulated by WNT3A.

Lysate microarrays enable high-throughput, quantitative investigations of cellular signaling.

Lysate microarrays (reverse-phase protein arrays) hold great promise as a tool for systems-level investigations of signaling and multiplexed analyses of disease biomarkers. To date, however, widespread use of this technology has been limited by questions concerning data quality and the specificity of detection reagents. To address these concerns, we developed a strategy to identify high-quality reagents for use with lysate microarrays. In total, we tested 383 antibodies for their ability to quantify changes in protein abundance or modification in 20 biological contexts across 17 cell lines. Antibodies yielding significant differences in signal were further evaluated by immunoblotting and 82 passed our rigorous criteria. The large-scale data set from our screen revealed that cell fate decisions are encoded not just by the identities of proteins that are activated, but by differences in their signaling dynamics as well. Overall, our list of validated antibodies and associated protocols establish lysate microarrays as a robust tool for systems biology.

Machine Learning Prediction of Adenovirus D8 Conjunctivitis Complications from Viral Whole-Genome Sequence.

Objective: To obtain complete DNA sequences of adenoviral (AdV) D8 genome from patients with conjunctivitis and determine the relation of sequence variation to clinical outcomes. Design: This study is a post hoc analysis of banked conjunctival swab samples from the BAYnovation Study, a previously conducted, randomized controlled clinical trial for AdV conjunctivitis. Participants: Ninety-six patients with AdV D8-positive conjunctivitis who received placebo treatment in the BAYnovation Study were included in the study. Methods: DNA from conjunctival swabs was purified and subjected to whole-genome viral DNA sequencing. Adenovirus D8 variants were identified and correlated with clinical outcomes, including 2 machine learning methods. Main Outcome Measures: Viral DNA sequence and development of subepithelial infiltrates (SEIs) were the main outcome measures. Results: From initial sequencing of 80 AdV D8-positive samples, full adenoviral genome reconstructions were obtained for 71. A total of 630 single-nucleotide variants were identified, including 156 missense mutations. Sequence clustering revealed 3 previously unappreciated viral clades within the AdV D8 type. The likelihood of SEI development differed significantly between clades, ranging from 83% for Clade 1 to 46% for Clade 3. Genome-wide analysis of viral single-nucleotide polymorphisms failed to identify single-gene determinants of outcome. Two machine learning models were independently trained to predict clinical outcome using polymorphic sequences. Both machine learning models correctly predicted development of SEI outcomes in a newly sequenced validation set of 16 cases (P = 1.5 × 10-5). Prediction was dependent on ensemble groups of polymorphisms across multiple genes. Conclusions: Adenovirus D8 has ≥ 3 prevalent molecular substrains, which differ in propensity to result in SEIs. Development of SEIs can be accurately predicted from knowledge of full viral sequence. These results suggest that development of SEIs in AdV D8 conjunctivitis is largely attributable to pathologic viral sequence variants within the D8 type and establishes machine learning paradigms as a powerful technique for understanding viral pathogenicity.

Tunable electroconductive decellularized extracellular matrix hydrogels for engineering human cardiac microphysiological systems.

Cardiomyocytes differentiated from human induced pluripotent stem cells (hiPSCs) offer tremendous potential when used to engineer human tissues for drug screening and disease modeling; however, phenotypic immaturity reduces assay reliability when translating in vitro results to clinical studies. To address this, we have developed hybrid hydrogels comprised of decellularized porcine myocardial extracellular matrix (dECM) and reduced graphene oxide (rGO) to provide a more instructive microenvironment for proper cell and tissue development. A tissue-specific protein profile was preserved post-decellularization, and through the modulation of rGO content and degree of reduction, the mechanical and electrical properties of the hydrogels could be tuned. Engineered heart tissues (EHTs) generated using dECM-rGO hydrogel scaffolds and hiPSC-derived cardiomyocytes exhibited significantly increased twitch forces and had increased expression of genes that regulate contractile function. Improvements in various aspects of electrophysiological function, such as calcium-handling, action potential duration, and conduction velocity, were also induced by the hybrid biomaterial. dECM-rGO hydrogels could also be used as a bioink to print cardiac tissues in a high-throughput manner, and these tissues were utilized to assess the proarrhythmic potential of cisapride. Action potential prolongation and beat interval irregularities was observed in dECM-rGO tissues at clinical doses of cisapride, indicating that the enhanced electrophysiological function of these tissues corresponded well with a capability to produce physiologically relevant drug responses.

Linear combinations of docking affinities explain quantitative differences in RTK signaling.

Receptor tyrosine kinases (RTKs) process extracellular cues by activating a broad array of signaling proteins. Paradoxically, they often use the same proteins to elicit diverse and even opposing phenotypic responses. Binary, 'on-off' wiring diagrams are therefore inadequate to explain their differences. Here, we show that when six diverse RTKs are placed in the same cellular background, they activate many of the same proteins, but to different quantitative degrees. Additionally, we find that the relative phosphorylation levels of upstream signaling proteins can be accurately predicted using linear models that rely on combinations of receptor-docking affinities and that the docking sites for phosphoinositide 3-kinase (PI3K) and Shc1 provide much of the predictive information. In contrast, we find that the phosphorylation levels of downstream proteins cannot be predicted using linear models. Taken together, these results show that information processing by RTKs can be segmented into discrete upstream and downstream steps, suggesting that the challenging task of constructing mathematical models of RTK signaling can be parsed into separate and more manageable layers.

TWIST1 Heterodimerization with E12 Requires Coordinated Protein Phosphorylation to Regulate Periostin Expression.

Diffuse invasion into adjacent brain matter by glioblastoma (GBM) is largely responsible for their dismal prognosis. Previously, we showed that the TWIST1 (TW) bHLH transcription factor and its regulated gene periostin (POSTN) promote invasive phenotypes of GBM cells. Since TW functional effects are regulated by phosphorylation and dimerization, we investigated how phosphorylation of serine 68 in TW regulates TW dimerization, POSTN expression, and invasion in glioma cells. Compared with wild-type TW, the hypophosphorylation mutant, TW(S68A), impaired TW heterodimerization with the E12 bHLH transcription factor and cell invasion in vitro but had no effect on TW homodimerization. Overexpression of TW:E12 forced dimerization constructs (FDCs) increased glioma cell invasion and upregulated pro-invasive proteins, including POSTN, in concert with cytoskeletal reorganization. By contrast, TW:TW homodimer FDCs inhibited POSTN expression and cell invasion in vitro. Further, phosphorylation of analogous PXSP phosphorylation sites in TW:E12 FDCs (TW S68 and E12 S139) coordinately regulated POSTN and PDGFRa mRNA expression. These results suggested that TW regulates pro-invasive phenotypes in part through coordinated phosphorylation events in TW and E12 that promote heterodimer formation and regulate downstream targets. This new mechanistic understanding provides potential therapeutic strategies to inhibit TW-POSTN signaling in GBM and other cancers.

Modeling HER2 effects on cell behavior from mass spectrometry phosphotyrosine data.

Cellular behavior in response to stimulatory cues is governed by information encoded within a complex intracellular signaling network. An understanding of how phenotype is determined requires the distributed characterization of signaling processes (e.g., phosphorylation states and kinase activities) in parallel with measures of resulting cell function. We previously applied quantitative mass spectrometry methods to characterize the dynamics of tyrosine phosphorylation in human mammary epithelial cells with varying human epidermal growth factor receptor 2 (HER2) expression levels after treatment with epidermal growth factor (EGF) or heregulin (HRG). We sought to identify potential mechanisms by which changes in tyrosine phosphorylation govern changes in cell migration or proliferation, two behaviors that we measured in the same cell system. Here, we describe the use of a computational linear mapping technique, partial least squares regression (PLSR), to detail and characterize signaling mechanisms responsible for HER2-mediated effects on migration and proliferation. PLSR model analysis via principal component inner products identified phosphotyrosine signals most strongly associated with control of migration and proliferation, as HER2 expression or ligand treatment were individually varied. Inspection of these signals revealed both previously identified and novel pathways that correlate with cell behavior. Furthermore, we isolated elements of the signaling network that differentially give rise to migration and proliferation. Finally, model analysis identified nine especially informative phosphorylation sites on six proteins that recapitulated the predictive capability of the full model. A model based on these nine sites and trained solely on data from a low HER2-expressing cell line a priori predicted migration and proliferation in a HER2-overexpressing cell line. We identify the nine signals as a "network gauge," meaning that when interrogated together and integrated according to the quantitative rules of the model, these signals capture information content in the network sufficiently to predict cell migration and proliferation under diverse ligand treatments and receptor expression levels. Examination of the network gauge in the context of previous literature indicates that endocytosis and activation of phosphoinositide 3-kinase (PI3K)-mediated pathways together represent particularly strong loci for the integration of the multiple pathways mediating HER2's control of mammary epithelial cell proliferation and migration. Thus, a PLSR modeling approach reveals critical signaling processes regulating HER2-mediated cell behavior.

Synthesizing Signaling Pathways from Temporal Phosphoproteomic Data.

We present a method for automatically discovering signaling pathways from time-resolved phosphoproteomic data. The Temporal Pathway Synthesizer (TPS) algorithm uses constraint-solving techniques first developed in the context of formal verification to explore paths in an interaction network. It systematically eliminates all candidate structures for a signaling pathway where a protein is activated or inactivated before its upstream regulators. The algorithm can model more than one hundred thousand dynamic phosphosites and can discover pathway members that are not differentially phosphorylated. By analyzing temporal data, TPS defines signaling cascades without needing to experimentally perturb individual proteins. It recovers known pathways and proposes pathway connections when applied to the human epidermal growth factor and yeast osmotic stress responses. Independent kinase mutant studies validate predicted substrates in the TPS osmotic stress pathway.

Effects of HER2 overexpression on cell signaling networks governing proliferation and migration.

Although human epidermal growth factor receptor 2 (HER2) overexpression is implicated in tumor progression for a variety of cancer types, how it dysregulates signaling networks governing cell behavioral functions is poorly understood. To address this problem, we use quantitative mass spectrometry to analyze dynamic effects of HER2 overexpression on phosphotyrosine signaling in human mammary epithelial cells stimulated by epidermal growth factor (EGF) or heregulin (HRG). Data generated from this analysis reveal that EGF stimulation of HER2-overexpressing cells activates multiple signaling pathways to stimulate migration, whereas HRG stimulation of these cells results in amplification of a specific subset of the migration signaling network. Self-organizing map analysis of the phosphoproteomic data set permitted elucidation of network modules differentially regulated in HER2-overexpressing cells in comparison with parental cells for EGF and HRG treatment. Partial least-squares regression analysis of the same data set identified quantitative combinations of signals within the networks that strongly correlate with cell proliferation and migration measured under the same battery of conditions. Combining these modeling approaches enabled association of epidermal growth factor receptor family dimerization to activation of specific phosphorylation sites, which appear to most critically regulate proliferation and/or migration.

Quantitative proteomic analysis of phosphotyrosine-mediated cellular signaling networks.

Receptor tyrosine kinases receive extracellular cues, such as ligand binding, and transmit this information to the cell through both autophosphorylation and phosphorylation of tyrosine residues on selected substrates, stimulating a variety of signal transduction pathways. Quantitative features, including intensity, timing, and duration of phosphorylation of particular residues, may play a role in determining cellular response, but experimental data required for analysis of these features have not previously been available. We have recently developed a methodology enabling the simultaneous quantification of tyrosine phosphorylation of specific residues on dozens of key proteins in a time-resolved manner, downstream of receptor tyrosine kinase activation. In this chapter, we present a detailed description of this mass spectrometry-based method, including conditions for cell culture and stimulation, sample preparation for stable isotope labeling and peptide immunoprecipitation, immobilized metal affinity chromatography-liquid chromatography-tandem mass spectrometry analysis of affinity-enriched tyrosine phosphorylated peptides, and analysis of the resulting MS data.

Development of Selected Reaction Monitoring Methods to Systematically Quantify Kinase Abundance and Phosphorylation Stoichiometry in Human Samples.

Protein phosphorylation, one of the most common types of post-translational modifications, is the central regulatory mechanism of cellular signaling networks. In human cells, thousands of proteins are continuously and dynamically phosphorylated and dephosphorylated at specific sites and times in response to external and internal stimuli. Reversible phosphorylation is facilitated by the action of two protein superfamilies: kinases and phosphatases. Kinases play an essential role in almost every relevant physiological process in human cells and their deregulation is linked to pathologies ranging from cancer to autoimmune diseases.Systematic identification of kinases expressed in a particular cell type, quantification of their abundance, and precise determination of their phosphorylation stoichiometry are essential to understand the cellular signaling networks and physiology of a sample. Our protocol outlines the steps to build and use a high-throughput, comprehensive, modular, and robust selected reaction monitoring (SRM) proteomics framework to facilitate quantification of the kinome state in research or clinical human samples.

Methods for the Analysis of Protein Phosphorylation-Mediated Cellular Signaling Networks.

Protein phosphorylation-mediated cellular signaling networks regulate almost all aspects of cell biology, including the responses to cellular stimulation and environmental alterations. These networks are highly complex and comprise hundreds of proteins and potentially thousands of phosphorylation sites. Multiple analytical methods have been developed over the past several decades to identify proteins and protein phosphorylation sites regulating cellular signaling, and to quantify the dynamic response of these sites to different cellular stimulation. Here we provide an overview of these methods, including the fundamental principles governing each method, their relative strengths and weaknesses, and some examples of how each method has been applied to the analysis of complex signaling networks. When applied correctly, each of these techniques can provide insight into the topology, dynamics, and regulation of protein phosphorylation signaling networks.

Technical advances in proteomics: new developments in data-independent acquisition.

The ultimate aim of proteomics is to fully identify and quantify the entire complement of proteins and post-translational modifications in biological samples of interest. For the last 15 years, liquid chromatography-tandem mass spectrometry (LC-MS/MS) in data-dependent acquisition (DDA) mode has been the standard for proteomics when sampling breadth and discovery were the main objectives; multiple reaction monitoring (MRM) LC-MS/MS has been the standard for targeted proteomics when precise quantification, reproducibility, and validation were the main objectives. Recently, improvements in mass spectrometer design and bioinformatics algorithms have resulted in the rediscovery and development of another sampling method: data-independent acquisition (DIA). DIA comprehensively and repeatedly samples every peptide in a protein digest, producing a complex set of mass spectra that is difficult to interpret without external spectral libraries. Currently, DIA approaches the identification breadth of DDA while achieving the reproducible quantification characteristic of MRM or its newest version, parallel reaction monitoring (PRM). In comparative de novo identification and quantification studies in human cell lysates, DIA identified up to 89% of the proteins detected in a comparable DDA experiment while providing reproducible quantification of over 85% of them. DIA analysis aided by spectral libraries derived from prior DIA experiments or auxiliary DDA data produces identification and quantification as reproducible and precise as that achieved by MRM/PRM, except on low­abundance peptides that are obscured by stronger signals. DIA is still a work in progress toward the goal of sensitive, reproducible, and precise quantification without external spectral libraries. New software tools applied to DIA analysis have to deal with deconvolution of complex spectra as well as proper filtering of false positives and false negatives. However, the future outlook is positive, and various researchers are working on novel bioinformatics techniques to address these issues and increase the reproducibility, fidelity, and identification breadth of DIA.

Individual protomers of a G protein-coupled receptor dimer integrate distinct functional modules.

Recent advances in proteomic technology reveal G-protein-coupled receptors (GPCRs) are organized as large, macromolecular protein complexes in cell membranes, adding a new layer of intricacy to GPCR signaling. We previously reported the α1D-adrenergic receptor (ADRA1D)-a key regulator of cardiovascular, urinary and CNS function-binds the syntrophin family of PDZ domain proteins (SNTA, SNTB1, and SNTB2) through a C-terminal PDZ ligand interaction, ensuring receptor plasma membrane localization and G-protein coupling. To assess the uniqueness of this novel GPCR complex, 23 human GPCRs containing Type I PDZ ligands were subjected to TAP/MS proteomic analysis. Syntrophins did not interact with any other GPCRs. Unexpectedly, a second PDZ domain protein, scribble (SCRIB), was detected in ADRA1D complexes. Biochemical, proteomic, and dynamic mass redistribution analyses indicate syntrophins and SCRIB compete for the PDZ ligand, simultaneously exist within an ADRA1D multimer, and impart divergent pharmacological properties to the complex. Our results reveal an unprecedented modular dimeric architecture for the ADRA1D in the cell membrane, providing unexpected opportunities for fine-tuning receptor function through novel protein interactions in vivo, and for intervening in signal transduction with small molecules that can stabilize or disrupt unique GPCR:PDZ protein interfaces.