Unravelling G protein‐coupled receptor signalling networks using global phosphoproteomics

G protein‐coupled receptor (GPCR) activation initiates signalling via a complex network of intracellular effectors that combine to produce diverse cellular and tissue responses. Although we have an advanced understanding of the proximal events following receptor stimulation, the molecular detail of GPCR signalling further downstream often remains obscure. Unravelling these GPCR‐mediated signalling networks has important implications for receptor biology and drug discovery. In this context, phosphoproteomics has emerged as a powerful approach for investigating global GPCR signal transduction. Here, we provide a brief overview of the phosphoproteomic workflow and discuss current limitations and future directions for this technology. By highlighting some of the novel insights into GPCR signalling networks gained using phosphoproteomics, we demonstrate the utility of global phosphoproteomics to dissect GPCR signalling networks and to accelerate discovery of new targets for therapeutic development.

G protein-coupled receptor (GPCR) activation initiates signalling via a complex network of intracellular effectors that combine to produce diverse cellular and tissue responses.
Although we have an advanced understanding of the proximal events following receptor stimulation, the molecular detail of GPCR signalling further downstream often remains obscure.Unravelling these GPCR-mediated signalling networks has important implications for receptor biology and drug discovery.In this context, phosphoproteomics has emerged as a powerful approach for investigating global GPCR signal transduction.Here, we provide a brief overview of the phosphoproteomic workflow and discuss current limitations and future directions for this technology.By highlighting some of the novel insights into GPCR signalling networks gained using phosphoproteomics, we demonstrate the utility of global phosphoproteomics to dissect GPCR signalling networks and to accelerate discovery of new targets for therapeutic development.pipelines, these receptors will continue as targets for therapeutic development in many diseases (Hauser et al., 2017).Nonetheless, there are still challenges and great opportunities in GPCR drug discovery.
GPCR signalling is complex, involving tightly regulated interactions with numerous downstream effector enzymes and second messengers (Figure 1).Proximal GPCR signalling via G proteins and β-arrestin is well studied, yet there are major knowledge gaps relating to signalling events beyond these effectors.In this regard, a key regulatory mechanism is protein phosphorylation, resulting from the dynamic and rapid interplay between numerous protein substrates, kinases and phosphatases (Munk et al., 2016).Indeed, GPCR signalling is best described as a network of these interactions, incorporating positive and negative feedback loops, signal amplification and cooperativity that culminate in a cellular response.Improving our understanding of these signalling networks downstream of GPCR activation is a high priority to clarify the relationships between receptor pharmacology and cellular outcomes.
In the past decade, phosphoproteomics methods have emerged as powerful tools for obtaining global insights into signal transduction.
For GPCRs, phosphoproteomics is an unbiased pathway-independent approach that enables high-throughput elucidation of phosphorylation events in a single experiment.This represents an advance on commonly used single endpoint second messenger assays and immunoblotting.Widespread application of this technique has the potential to unravel GPCR signalling networks and identify novel targets for therapeutic development (Lawrence et al., 2016).

| PHOSPHOPROTEOMICS METHODOLOGY FOR MAPPING GPCR SIGNALLING NETWORKS
The primary goal of phosphoproteomics, as applied to GPCRs, is to identify and quantify global changes in protein phosphorylation following target receptor activation.A typical global phosphoproteomics workflow (Figure 2) involves receptor stimulation, sample processing, mass spectrometry (MS) acquisition and data analysis.

| GPCR stimulation and extraction of proteomic information
To investigate GPCR-dependent phosphorylation, cells or tissues expressing the receptor of interest are treated with agonist(s).As protein phosphorylation is a universal cellular response to extracellular stimuli, experimental designs should include multiple independent biological repeats and appropriate untreated and solvent controls for robust comparisons between basal and ligand-stimulated changes in phosphorylation.Additionally, given that ligand-induced phosphorylation events occur rapidly (seconds-minutes), time-series experiments are useful in capturing the gamut of signalling responses.At desired time points, cells are quickly lysed and heat-treated to limit further enzymatic activity and the extracted proteins digested into peptides for MS (Urban, 2022).Optionally, cultured cells may be enriched (prestimulation) with stable isotypes (e.g.stable isotope labelling using amino acids in cell culture [SILAC]) or isobaric labels may be added post-digestion (e.g.tandem mass tagging [TMT]) and multiplexed to aid with accurate quantification during data analysis (see Section 2.4).

| Enriching for phosphotargets
The resulting peptide population following tryptic digestion is expansive, containing a relatively low abundance of phosphorylated peptides among peptides derived from the proteome (<20%) (Urban, 2022).Consequently, two strategies are used to increase the sensitivity of detection of phosphorylated peptides.Fractionation divides the total peptide population into smaller manageable segments, allowing closer inspection of all peptides.Affinity-based methods enable the specific enrichment of phosphopeptides, commonly using metal oxide affinity chromatography (MOAC) using titanium dioxide (TiO 2 ), immobilised metal affinity chromatography (IMAC) or immunoprecipitation (Fíla & Honys, 2012).
Combining fractionation and enrichment can improve detection of phosphotargets, although the recently developed EasyPhos workflow has extended coverage and increased reproducibility without the need for fractionation (Humphrey et al., 2018).

| Mass spectrometry approaches
Liquid chromatography coupled to mass spectrometry (LC-MS) enables separation and detection of all peptides in a given sample

What is already known
• GPCRs and GPCR signalling networks are therapeutically tractable in a range of diseases.
• Global phosphoproteomics is a powerful approach to study 1000s of simultaneous cellular signalling events.

What does this study add
• We provide an accessible overview of phosphoproteomics methodology and its application to GPCR research.
• We highlight phosphoproteomics studies that have yielded novel insights into GPCR signalling networks.

What is the clinical significance
• Phosphoproteomics is an emerging technique in GPCR signalling that can accelerate drug target discovery.based on their chromatographic retention times and mass-to-charge ratios (m/z).Tandem mass spectrometers (MS/MS) use two mass analysers, the first analyser (MS1) separates and detects the intact ionised phosphopeptides, which are then fragmented into smaller ions detected by a second mass analyser (MS2) (Gillet et al., 2016).Due to the sheer number of ions detected, it is impractical to collect MS2 spectra for every m/z ratio in the MS1 spectrum.Therefore, different acquisition modes have been devised to collect MS2 data that yield the maximum useful information.In data-dependent acquisition (DDA), the instrument scans each narrow range of MS1 m/z ratios and selects the most intense peaks for MS2 analysis (Urban, 2022).In contrast, in data-independent acquisition (DIA) mode, a mass spectrometer fragments all precursor ions in predefined m/z windows.
Resulting fragment ion spectra are interrogated against a spectral library, using known precursor and fragment m/z ratios and retention times for individual peptides in the sample (Urban, 2022).DIA offers better reproducibility and sensitivity versus DDA, especially for detection of low abundance peptides, although it is more computationally intensive and increases instrument time (Hu et al., 2016).

| Phosphopeptide mapping and quantification
Converting m/z ratios to tangible proteomic information relies on predefined sequence information (DIA mode) or proteome database matching (DDA mode) to identify parent proteins with and without phosphorylated sites.Phosphosite location is determined by overlaying MS2 peptide ions to deduce phosphate addition at serine, threonine and tyrosine residues.Quantification can then be performed via several different strategies.The simplest quantification method is F I G U R E 1 Intracellular signal transduction networks following GPCR activation.Receptor stimulation promotes simultaneous signalling via multiple pathways that contribute to different cellular responses and functional outcomes, such as cell migration, cell proliferation and transcriptional regulation.GPCRs transmit signals via both G protein-dependent and G protein-independent (e.g.β-arrestin) mechanisms to activate well-characterised signalling cascades including cAMP-dependent protein kinase A (PKA), Ca 2+ -dependent protein kinase C (PKC), mitogen-activated protein kinase cascades (ERK1/ERK2, p38 MAPK) and small GTPases (Rho, Rac and Ras) that regulate actin cytoskeleton.Global phosphoproteomics studies have demonstrated that GPCR activation also leads to phosphorylation events involving numerous additional kinases and protein substrates.This approach has led to the discovery of new potential drug targets in GPCR signalling networks.
based on MS peak intensity, requiring no additional steps to the standard workflow.However, this method (termed label-free quantification) is prone to systematic biases (e.g.variable injection volume and sample carryover) when comparing sequentially acquired samples (Hogrebe et al., 2018).To this end, peptide labelling is a common strategy to improve quantitative accuracy and enables sample multiplexing, albeit at significant additional cost and experimental effort.This quantification algorithm relies on ratiometric comparison of labelled peptides in stimulated and control conditions within a multiplexed sample.Importantly, although both metabolic and isobaric labelling improve quantitative accuracy, the increased spectral complexity in multiplexed samples can reduce the total number of phosphopeptides identified (Hogrebe et al., 2018).Additionally, metabolic incorporation of stable isotope labelling using amino acids in cell culture (SILAC) labels to live cultured cells requires cellular protein turnover and label uptake for successful quantification, so can be substituted for isobaric labelling (TMT, isobaric tags for relative and absolute quantitation [iTRAQ labels]) as an alternative strategy (Hogrebe et al., 2018;Li et al., 2012).Commercial software packages, such as MaxQuant and Proteome Discoverer enable these qualitative and quantitative assessments with statistical evaluation (Tyanova et al., 2016), although the algorithms underpinning these assignments are somewhat opaque.

| Unlocking biological insights
The final step in phosphoproteomics pipelines involves interpreting large-scale phosphoproteomic datasets.Many free bioinformatics resources help translate phosphopeptide identification into biological insights, including enrichment analyses (e.g.Enrichr; DAVID) and protein: protein interaction databases, pathway and network analysis, and visualisation (STRING, KEGG, NetworKIN, Cytoscape).Importantly, these resources compile information from prior phosphoproteomic investigations, kinase and phosphatase interactions, and available signalling pathways (Urban, 2022), which may not be relevant to all cells and tissues.Likewise, assembly of a putative signalling network into a meaningful network from phosphoproteomic data involves significant manual curation, which is time-consuming and can introduce observer bias.Alternatively, sophisticated computational modelling approaches, such as PHONEMeS (PHOsphorylation NEtworks for Mass Spectrometry), integrate phosphoproteomics data with "prior knowledge networks" to probe kinase/phosphatasesubstrate relationships and define optimal signalling networks consistent with empirically observed phosphorylation (Terfve et al., 2015).
Beyond visualisation and contextualisation, PHONEMeS enables testable predictions to verify the network model.Finally, independent validation of key findings within signalling networks requires additional F I G U R E 2 Schematic workflow of mass spectrometry-based global phosphoproteomics approaches.Cells or tissues expressing GPCRs are stimulated with agonists at defined time point(s) (1).Harvested cells or tissues are lysed and homogenised to extract proteins (2), with lysates subsequently undergoing protease digestion with trypsin (3).Peptide mixtures may then be fractionated (4), before enrichment of phosphopeptides, typically using metal ion beads (5).Phosphopeptide-enriched samples are subjected to liquid chromatography coupled with tandem MS (LC-MS/MS) for analysis (6).Phosphoproteomic data analysis involves identification and quantification of phosphosites/ phosphoproteins using spectral libraries or proteomic databases.Quantification processes vary: label-free quantification (LFQ) requires no additional preparation steps, whereas metabolic (step 1) or isobaric labels (steps 3 and 4) are incorporated earlier in the workflow (7).Finally, phosphoproteomic data is contextualised using enrichment analyses and signalling network modelling (8).
T A B L E 1 Global phosphoproteomic studies on GPCR signalling.

GPCR target
Ligand(s) GTPase were downregulated by both ligands (Wenk et al., 2022) global/targeted MS methods or immunoblotting if suitable antibodies are available (Lawrence et al., 2016).Integration with pharmacological and genetic approaches (RNAi or CRISPR-Cas9) provides further target validation.

| NEW ASPECTS OF GPCR SIGNALLING FROM PHOSPHOPROTEOMICS STUDIES
Phosphoproteomics is steadily gaining popularity among GPCR researchers for target discovery, providing important insights about previously unrecognised phosphoproteins in GPCR signalling networks.Key studies are highlighted in Table 1, with receptor nomenclature conforming to BJP's "Concise Guide to Pharmacology" (Alexander et al., 2021).It is noteworthy that the vast majority of these studies have been published since 2019, occurring alongside the introduction of automated sample preparation, advances in enrichment techniques, instrumentation and phosphopeptide mapping.
A pair of studies in 2010 focussing on the angiotensin (AT 1 ) receptor paved the way for global phosphoproteomics to study receptor signalling (Christensen et al., 2010;Xiao et al., 2010).These used the endogenous agonist angiotensin II and the β-arrestin biased ligand, Sar 1 , Ile 4 , Ile 8 -angiotensin II to compare G protein-dependent and G protein-independent phosphorylation.In addition, to identifying common signalling pathways and phosphosites following AT 1 receptor activation, these data implicated distinct kinases in G protein versus β-arrestin-dependent signalling (Christensen et al., 2010;Xiao et al., 2010).
Another early study interrogated the phosphoproteome in mouse heart after selective β-adrenoceptor activation, identifying 670 regulated phosphosites (Lundby et al., 2013).Enrichment and network analyses established novel kinase signalling pathways associated with cardiac hypertrophy and regulation of cardiac excitability (Lundby et al., 2013).In another study, seven uncharacterised phosphosites were identified in mouse β 1 -adrenoceptor intracellular loops and Cterminus that may regulate cardiac function (Hayashi et al., 2017).
In a landmark study, Liu et al combined state-of-the-art phosphoproteomics with functionally selective κ receptor ligands to investigate in vivo brain opioid GPCR signalling and behavioural outcomes (Liu et al., 2018).By comparing the phosphorylation profiles in five different brain regions after 5-or 30-min stimulation, the authors clar- regulate cytoskeletal dynamics, cell-cell adhesion, proliferation and calcium/calmodulin-dependent signalling (Datta et al., 2021;Hoffert et al., 2012;Leo et al., 2022).These data provide the basis for further characterisation of at least six downstream vasopressin-regulated protein kinases as potential therapeutic targets (Datta et al., 2021).
We and others have used phosphoproteomics to study the signalling networks of chemokine receptors (Huang et al., 2020;Tsai et al., 2019;Yi et al., 2014) et al., 2020).In particular, we observed high representation of cytoskeleton-related and nuclear pore complex proteins, consistent with chemokine-driven migration and transcriptional regulation.
We are currently extending these findings in different cell types with multiple chemokines to identify novel targets for leukocyte chemotaxis.
In a comprehensive study, time-resolved endothelin (ET B ) receptor signalling was dissected using phosphoproteomics in two melanoma cell lines (Schäfer et al., 2019).This study was the first to utilise the PHONEMeS computational modelling approach for GPCR signalling networks, identifying four kinases that were linked to Technical advancements in MS workflows and further development of unbiased network analysis tools will add value to phosphoproteomics studies.Equally, accessible and user-friendly knowledge bases for phosphoproteomics data will allow study of context-specific signalling in relevant cells and tissues.This is especially important as the basis for functional predictions in network analyses.

| CONCLUDING REMARKS
Global phosphoproteomics studies provide new insights into the dynamics and mechanisms of GPCR signal transduction.Reduced sample requirements have enabled application of these techniques in heterologous and primary cells in vitro and in vivo.Phosphoproteomics is also an emerging tool in the field of precision medicine (Needham et al., 2022), where its use in clinical studies may uncover mechanisms of development and progression of various diseases related to GPCRs.However, the functional consequences of many kinase-substrate interactions remain unknown.The widespread application of phosphoproteomics to study GPCR signalling can therefore provide systems-level information, facilitate target discovery and illuminate important signalling events within the dark phosphoproteome (Needham et al., 2019).

| Nomenclature of targets and ligands
Abbreviations: DAVID, Database for Annotation, Visualisation and Integrated Discovery; DDA, data-dependent acquisition; DIA, data-independent acquisition; IMAC, immobilised metal affinity chromatography; iTRAQ, isobaric tags for relative and absolute quantitation; KEGG, Kyoto Encyclopedia of Genes and Genomes; MOAC, metal-oxide affinity chromatography; PHONEMeS, PHOsphorylation NEtworks for Mass Spectrometry; SILAC, Stable Isotope Labelling using Amino acids in Cell culture; STRING, Search Tool for the Retrieval of INteracting Genes/proteins; TMT, tandem mass tag.
endothelin-induced cell migration.Additional studies have provided interesting new detail about signalling via PTH1 receptor(Williams et al., 2016), formylpeptide receptor 2 (FPR2/ALX)(Cattaneo et al., 2019), 5-HT 2A receptor(Martín-Guerrero et al., 2021), dopamine D 2 receptor(Wenk et al., 2022) and PAR1(Lin et al., 2020;Molinar-Inglis et al., 2022).In the case of PAR1, these data predict potential kinases that mediate biased signalling and have implications for thrombin-induced p38 inflammatory signalling in endothelial cells.Collectively, these studies demonstrate the utility of phosphoproteomics to map different GPCR-mediated signalling pathways and discover potential targets in downstream signalling networks.4| CURRENT LIMITATIONS AND FUTURE DIRECTIONSAlthough there are enormous upsides of phosphoproteomics, there are methodological and practical limitations for GPCR research.The dynamic nature of phosphorylation poses challenges for data collection and introduces variability if not carefully controlled through enzymatic inhibition.While many studies include a single time point following stimulation to capture the rapid initial response, time courses may reveal nuanced data on response kinetics and other biological outcomes.Systematic variability in the phosphoproteomics experiments may be minimised by automated sample preparation, as demonstrated in the EasyPhos workflow(Humphrey et al., 2018), while membrane-enrichment protocols may help capture phosphorylation of membrane proteins in phosphoproteomics datasets.Another important consideration is the time (days-weeks) and cost associated with the entire phosphoproteomic workflow, although offset by the richness of data gleaned from a single experiment.