Phosphoproteomics reveals conserved exercise-stimulated signaling and AMPK regulation of store-operated calcium entry.

Exercise stimulates cellular and physiological adaptations that are associated with widespread health benefits. To uncover conserved protein phosphorylation events underlying this adaptive response, we performed mass spectrometry-based phosphoproteomic analyses of skeletal muscle from two widely used rodent models: treadmill running in mice and in situ muscle contraction in rats. We overlaid these phosphoproteomic signatures with cycling in humans to identify common cross-species phosphosite responses, as well as unique model-specific regulation. We identified > 22,000 phosphosites, revealing orthologous protein phosphorylation and overlapping signaling pathways regulated by exercise. This included two conserved phosphosites on stromal interaction molecule 1 (STIM1), which we validate as AMPK substrates. Furthermore, we demonstrate that AMPK-mediated phosphorylation of STIM1 negatively regulates store-operated calcium entry, and this is beneficial for exercise in Drosophila. This integrated cross-species resource of exercise-regulated signaling in human, mouse, and rat skeletal muscle has uncovered conserved networks and unraveled crosstalk between AMPK and intracellular calcium flux.

Mitochondrial CoQ deficiency is a common driver of mitochondrial oxidants and insulin resistance.

Insulin resistance in muscle, adipocytes and liver is a gateway to a number of metabolic diseases. Here, we show a selective deficiency in mitochondrial coenzyme Q (CoQ) in insulin-resistant adipose and muscle tissue. This defect was observed in a range of in vitro insulin resistance models and adipose tissue from insulin-resistant humans and was concomitant with lower expression of mevalonate/CoQ biosynthesis pathway proteins in most models. Pharmacologic or genetic manipulations that decreased mitochondrial CoQ triggered mitochondrial oxidants and insulin resistance while CoQ supplementation in either insulin-resistant cell models or mice restored normal insulin sensitivity. Specifically, lowering of mitochondrial CoQ caused insulin resistance in adipocytes as a result of increased superoxide/hydrogen peroxide production via complex II. These data suggest that mitochondrial CoQ is a proximal driver of mitochondrial oxidants and insulin resistance, and that mechanisms that restore mitochondrial CoQ may be effective therapeutic targets for treating insulin resistance.

The transcriptional response to oxidative stress is part of, but not sufficient for, insulin resistance in adipocytes.

Insulin resistance is a major risk factor for metabolic diseases such as Type 2 diabetes. Although the underlying mechanisms of insulin resistance remain elusive, oxidative stress is a unifying driver by which numerous extrinsic signals and cellular stresses trigger insulin resistance. Consequently, we sought to understand the cellular response to oxidative stress and its role in insulin resistance. Using cultured 3T3-L1 adipocytes, we established a model of physiologically-derived oxidative stress by inhibiting the cycling of glutathione and thioredoxin, which induced insulin resistance as measured by impaired insulin-stimulated 2-deoxyglucose uptake. Using time-resolved transcriptomics, we found > 2000 genes differentially-expressed over 24 hours, with specific metabolic and signalling pathways enriched at different times. We explored this coordination using a knowledge-based hierarchical-clustering approach to generate a temporal transcriptional cascade and identify key transcription factors responding to oxidative stress. This response shared many similarities with changes observed in distinct insulin resistance models. However, an anti-oxidant reversed insulin resistance phenotypically but not transcriptionally, implying that the transcriptional response to oxidative stress is insufficient for insulin resistance. This suggests that the primary site by which oxidative stress impairs insulin action occurs post-transcriptionally, warranting a multi-level 'trans-omic' approach when studying time-resolved responses to cellular perturbations.

Metabolomic analysis of insulin resistance across different mouse strains and diets.

Insulin resistance is a major risk factor for many diseases. However, its underlying mechanism remains unclear in part because it is triggered by a complex relationship between multiple factors, including genes and the environment. Here, we used metabolomics combined with computational methods to identify factors that classified insulin resistance across individual mice derived from three different mouse strains fed two different diets. Three inbred ILSXISS strains were fed high-fat or chow diets and subjected to metabolic phenotyping and metabolomics analysis of skeletal muscle. There was significant metabolic heterogeneity between strains, diets, and individual animals. Distinct metabolites were changed with insulin resistance, diet, and between strains. Computational analysis revealed 113 metabolites that were correlated with metabolic phenotypes. Using these 113 metabolites, combined with machine learning to segregate mice based on insulin sensitivity, we identified C22:1-CoA, C2-carnitine, and C16-ceramide as the best classifiers. Strikingly, when these three metabolites were combined into one signature, they classified mice based on insulin sensitivity more accurately than each metabolite on its own or other published metabolic signatures. Furthermore, C22:1-CoA was 2.3-fold higher in insulin-resistant mice and correlated significantly with insulin resistance. We have identified a metabolomic signature composed of three functionally unrelated metabolites that accurately predicts whole-body insulin sensitivity across three mouse strains. These data indicate the power of simultaneous analysis of individual, genetic, and environmental variance in mice for identifying novel factors that accurately predict metabolic phenotypes like whole-body insulin sensitivity.

Correction: Unraveling Kinase Activation Dynamics Using Kinase-Substrate Relationships from Temporal Large-Scale Phosphoproteomics Studies.

[This corrects the article DOI: 10.1371/journal.pone.0157763.].

Cross-Species PTM Mapping from Phosphoproteomic Data.

Protein post-translational modifications (PTMs) are crucial for signal transduction in cells. In order to understand key cell signaling events, identification of functionally important PTMs, which are more likely to be evolutionarily conserved, is necessary. In recent times, high-throughput mass spectrometry (MS) has made quantitative datasets in diverse species readily available, which has led to a growing need for tools to facilitate cross-species comparison of PTM data. Cross-species comparison of PTM sites is difficult since they often lie in structurally disordered protein domains. Current tools that address this can only map known PTMs between species based on previously annotated orthologous phosphosites and do not enable cross-species mapping of newly identified modification sites. Here, we describe an automated web-based tool, PhosphOrtholog, that accurately maps annotated and novel orthologous PTM sites from high-throughput MS-based experimental data obtained from different species without relying on existing PTM databases. Identification of conserved PTMs across species from large-scale experimental data increases our knowledgebase of evolutionarily conserved and functional PTM sites that influence most biological processes. In this Chapter, we illustrate with examples how to use PhosphOrtholog to map novel PTM sites from cross-species MS-based phosphoproteomics data.

Skeletal muscle extracellular matrix remodeling after short-term overfeeding in healthy humans.

BACKGROUND: Skeletal muscle extracellular matrix (ECM) remodeling has been proposed as a feature of the pathogenic milieu associated with obesity and metabolic dysfunction. The aim of the current study was to examine the timeline of this response and determine whether 3 and 28days of overfeeding alters markers of ECM turnover. METHODS: Forty healthy individuals were overfed by 1250kcal/day for 28days. Hyperinsulinemic-euglycemic clamps and abdominal fat distribution were performed at baseline and day 28 of overfeeding and skeletal muscle biopsies taken at baseline, day 3 and day 28. mRNA expression (COL1a1, COL3a1, MMP2, MMP9, TIMP1, CD68, Integrin) was performed in 19 subjects that consented to having all biopsies performed and microarray analysis was performed in 8 participants at baseline and day 28. RESULTS: In the whole cohort, body weight increased by 0.6±0.1 and 2.7±0.3kg at days 3 and 28 (both P<0.001), respectively. Glucose infusion rate during the hyperinsulinemic-euglycemic clamp decreased from 54.8±2.8 at baseline to 50.3±2.5µmol/min/kg FFM at day 28 of overfeeding (P=0.03). Muscle COL1 and COL3 and MMP2 mRNA levels were significantly higher 28days after overfeeding (all P<0.05), with no significant changes in MMP9, TIMP1, CD68 and integrin expression. Microarray based gene set tests revealed that pathways related to ECM receptor interaction, focal adhesion and adherens junction were differentially altered. CONCLUSIONS: Skeletal muscle ECM remodeling occurs early in response to over-nutrition with as little as 3% body weight gain. Our findings contribute to the growing evidence linking muscle ECM remodeling and accumulation as another sequela of obesity-related insulin resistance.

Hyperactivation of the Insulin Signaling Pathway Improves Intracellular Proteostasis by Coordinately Up-regulating the Proteostatic Machinery in Adipocytes.

Hyperinsulinemia, which is associated with aging and metabolic disease, may lead to defective protein homeostasis (proteostasis) due to hyperactivation of insulin-sensitive pathways such as protein synthesis. We investigated the effect of chronic hyperinsulinemia on proteostasis by generating a time-resolved map of insulin-regulated protein turnover in adipocytes using metabolic pulse-chase labeling and high resolution mass spectrometry. Hyperinsulinemia increased the synthesis of nearly half of all detected proteins and did not affect protein degradation despite suppressing autophagy. Unexpectedly, this marked elevation in protein synthesis was accompanied by enhanced protein stability and folding and not by markers of proteostasis stress such as protein carbonylation and aggregation. The improvement in proteostasis was attributed to a coordinate up-regulation of proteins in the global proteostasis network, including ribosomal, proteasomal, chaperone, and endoplasmic reticulum/mitochondrial unfolded protein response proteins. We conclude that defects associated with hyperactivation of the insulin signaling pathway are unlikely attributed to defective proteostasis because up-regulation of protein synthesis by insulin is accompanied by up-regulation of proteostatic machinery.

mTORC2 and AMPK differentially regulate muscle triglyceride content via Perilipin 3.

OBJECTIVE: We have recently shown that acute inhibition of both mTOR complexes (mTORC1 and mTORC2) increases whole-body lipid utilization, while mTORC1 inhibition had no effect. Therefore, we tested the hypothesis that mTORC2 regulates lipid metabolism in skeletal muscle. METHODS: Body composition, substrate utilization and muscle lipid storage were measured in mice lacking mTORC2 activity in skeletal muscle (specific knockout of RICTOR (Ric mKO)). We further examined the RICTOR/mTORC2-controlled muscle metabolome and proteome; and performed follow-up studies in other genetic mouse models and in cell culture. RESULTS: Ric mKO mice exhibited a greater reliance on fat as an energy substrate, a re-partitioning of lean to fat mass and an increase in intramyocellular triglyceride (IMTG) content, along with increases in several lipid metabolites in muscle. Unbiased proteomics revealed an increase in the expression of the lipid droplet binding protein Perilipin 3 (PLIN3) in muscle from Ric mKO mice. This was associated with increased AMPK activity in Ric mKO muscle. Reducing AMPK kinase activity decreased muscle PLIN3 expression and IMTG content. AMPK agonism, in turn, increased PLIN3 expression in a FoxO1 dependent manner. PLIN3 overexpression was sufficient to increase triglyceride content in muscle cells. CONCLUSIONS: We identified a novel link between mTORC2 and PLIN3, which regulates lipid storage in muscle. While mTORC2 is a negative regulator, we further identified AMPK as a positive regulator of PLIN3, which impacts whole-body substrate utilization and nutrient partitioning.

Unraveling Kinase Activation Dynamics Using Kinase-Substrate Relationships from Temporal Large-Scale Phosphoproteomics Studies.

In response to stimuli, biological processes are tightly controlled by dynamic cellular signaling mechanisms. Reversible protein phosphorylation occurs on rapid time-scales (milliseconds to seconds), making it an ideal carrier of these signals. Advances in mass spectrometry-based proteomics have led to the identification of many tens of thousands of phosphorylation sites, yet for the majority of these the kinase is unknown and the underlying network topology of signaling networks therefore remains obscured. Identifying kinase substrate relationships (KSRs) is therefore an important goal in cell signaling research. Existing consensus sequence motif based prediction algorithms do not consider the biological context of KSRs, and are therefore insensitive to many other mechanisms guiding kinase-substrate recognition in cellular contexts. Here, we use temporal information to identify biologically relevant KSRs from Large-scale In Vivo Experiments (KSR-LIVE) in a data-dependent and automated fashion. First, we used available phosphorylation databases to construct a repository of existing experimentally-predicted KSRs. For each kinase in this database, we used time-resolved phosphoproteomics data to examine how its substrates changed in phosphorylation over time. Although substrates for a particular kinase clustered together, they often exhibited a different temporal pattern to the phosphorylation of the kinase. Therefore, although phosphorylation regulates kinase activity, our findings imply that substrate phosphorylation likely serve as a better proxy for kinase activity than kinase phosphorylation. KSR-LIVE can thereby infer which kinases are regulated within a biological context. Moreover, KSR-LIVE can also be used to automatically generate positive training sets for the subsequent prediction of novel KSRs using machine learning approaches. We demonstrate that this approach can distinguish between Akt and Rps6kb1, two kinases that share the same linear consensus motif, and provide evidence suggesting IRS-1 S265 as a novel Akt site. KSR-LIVE is an open-access algorithm that allows users to dissect phosphorylation signaling within a specific biological context, with the potential to be included in the standard analysis workflow for studying temporal high-throughput signal transduction data.

Integrated expression analysis of muscle hypertrophy identifies Asb2 as a negative regulator of muscle mass.

The transforming growth factor-ß (TGF-ß) signaling network is a critical regulator of skeletal muscle mass and function and, thus, is an attractive therapeutic target for combating muscle disease, but the underlying mechanisms of action remain undetermined. We report that follistatin-based interventions (which modulate TGF-ß network activity) can promote muscle hypertrophy that ameliorates aging-associated muscle wasting. However, the muscles of old sarcopenic mice demonstrate reduced response to follistatin compared with healthy young-adult musculature. Quantitative proteomic and transcriptomic analyses of young-adult muscles identified a transcription/translation signature elicited by follistatin exposure, which included repression of ankyrin repeat and SOCS box protein 2 (Asb2). Increasing expression of ASB2 reduced muscle mass, thereby demonstrating that Asb2 is a TGF-ß network-responsive negative regulator of muscle mass. In contrast to young-adult muscles, sarcopenic muscles do not exhibit reduced ASB2 abundance with follistatin exposure. Moreover, preventing repression of ASB2 in young-adult muscles diminished follistatin-induced muscle hypertrophy. These findings provide insight into the program of transcription and translation events governing follistatin-mediated adaptation of skeletal muscle attributes and identify Asb2 as a regulator of muscle mass implicated in the potential mechanistic dysfunction between follistatin-mediated muscle growth in young and old muscles.

Skeletal muscle and plasma lipidomic signatures of insulin resistance and overweight/obesity in humans.

OBJECTIVE: Alterations in lipids in muscle and plasma have been documented in insulin-resistant people with obesity. Whether these lipid alterations are a reflection of insulin resistance or obesity remains unclear. METHODS: Nondiabetic sedentary individuals not treated with lipid-lowering medications were studied (n = 51). Subjects with body mass index (BMI) > 25 kg/m(2) (n = 28) were stratified based on median glucose infusion rate during a hyperinsulinemic-euglycemic clamp into insulin-sensitive and insulin-resistant groups (above and below median, obesity/insulin-sensitive and obesity/insulin-resistant, respectively). Lean individuals (n = 23) served as a reference group. Lipidomics was performed in muscle and plasma by liquid chromatography electrospray ionization-tandem mass spectrometry. Pathway analysis of gene array in muscle was performed in a subset (n = 35). RESULTS: In muscle, insulin resistance was characterized by higher levels of C18:0 sphingolipids, while in plasma, higher levels of diacylglycerol and cholesterol ester, and lower levels of lysophosphatidylcholine and lysoalkylphosphatidylcholine, indicated insulin resistance, irrespective of overweight/obesity. The sphingolipid metabolism gene pathway was upregulated in muscle in insulin resistance independent of obesity. An overweight/obesity lipidomic signature was only apparent in plasma, predominated by higher triacylglycerol and lower plasmalogen species. CONCLUSIONS: Muscle C18:0 sphingolipids may play a role in insulin resistance independent of excess adiposity.

Dataset from the global phosphoproteomic mapping of early mitotic exit in human cells.

The presence or absence of a phosphorylation on a substrate at any particular point in time is a functional readout of the balance in activity between the regulatory kinase and the counteracting phosphatase. Understanding how stable or short-lived a phosphorylation site is required for fully appreciating the biological consequences of the phosphorylation. Our current understanding of kinases and their substrates is well established; however, the role phosphatases play is less understood. Therefore, we utilized a phosphatase dependent model of mitotic exit to identify potential substrates that are preferentially dephosphorylated. Using this method, we identified >16,000 phosphosites on >3300 unique proteins, and quantified the temporal phosphorylation changes that occur during early mitotic exit (McCloy et al., 2015 [1]). Furthermore, we annotated the majority of these phosphorylation sites with a high confidence upstream kinase using published, motif and prediction based methods. The results from this study have been deposited into the ProteomeXchange repository with identifier PXD001559. Here we provide additional analysis of this dataset; for each of the major mitotic kinases we identified motifs that correlated strongly with phosphorylation status. These motifs could be used to predict the stability of phosphorylated residues in proteins of interest, and help infer potential functional roles for uncharacterized phosphorylations. In addition, we provide validation at the single cell level that serine residues phosphorylated by Cdk are stable during phosphatase dependent mitotic exit. In summary, this unique dataset contains information on the temporal mitotic stability of thousands of phosphorylation sites regulated by dozens of kinases, and information on the potential preference that phosphatases have at both the protein and individual phosphosite level. The compellation of this data provides an invaluable resource for the wider research community.

Global Phosphoproteomic Analysis of Human Skeletal Muscle Reveals a Network of Exercise-Regulated Kinases and AMPK Substrates.

Exercise is essential in regulating energy metabolism and whole-body insulin sensitivity. To explore the exercise signaling network, we undertook a global analysis of protein phosphorylation in human skeletal muscle biopsies from untrained healthy males before and after a single high-intensity exercise bout, revealing 1,004 unique exercise-regulated phosphosites on 562 proteins. These included substrates of known exercise-regulated kinases (AMPK, PKA, CaMK, MAPK, mTOR), yet the majority of kinases and substrate phosphosites have not previously been implicated in exercise signaling. Given the importance of AMPK in exercise-regulated metabolism, we performed a targeted in vitro AMPK screen and employed machine learning to predict exercise-regulated AMPK substrates. We validated eight predicted AMPK substrates, including AKAP1, using targeted phosphoproteomics. Functional characterization revealed an undescribed role for AMPK-dependent phosphorylation of AKAP1 in mitochondrial respiration. These data expose the unexplored complexity of acute exercise signaling and provide insights into the role of AMPK in mitochondrial biochemistry.

Kinome Screen Identifies PFKFB3 and Glucose Metabolism as Important Regulators of the Insulin/Insulin-like Growth Factor (IGF)-1 Signaling Pathway.

The insulin/insulin-like growth factor (IGF)-1 signaling pathway (ISP) plays a fundamental role in long term health in a range of organisms. Protein kinases including Akt and ERK are intimately involved in the ISP. To identify other kinases that may participate in this pathway or intersect with it in a regulatory manner, we performed a whole kinome (779 kinases) siRNA screen for positive or negative regulators of the ISP, using GLUT4 translocation to the cell surface as an output for pathway activity. We identified PFKFB3, a positive regulator of glycolysis that is highly expressed in cancer cells and adipocytes, as a positive ISP regulator. Pharmacological inhibition of PFKFB3 suppressed insulin-stimulated glucose uptake, GLUT4 translocation, and Akt signaling in 3T3-L1 adipocytes. In contrast, overexpression of PFKFB3 in HEK293 cells potentiated insulin-dependent phosphorylation of Akt and Akt substrates. Furthermore, pharmacological modulation of glycolysis in 3T3-L1 adipocytes affected Akt phosphorylation. These data add to an emerging body of evidence that metabolism plays a central role in regulating numerous biological processes including the ISP. Our findings have important implications for diseases such as type 2 diabetes and cancer that are characterized by marked disruption of both metabolism and growth factor signaling.

PhosphOrtholog: a web-based tool for cross-species mapping of orthologous protein post-translational modifications.

BACKGROUND: Most biological processes are influenced by protein post-translational modifications (PTMs). Identifying novel PTM sites in different organisms, including humans and model organisms, has expedited our understanding of key signal transduction mechanisms. However, with increasing availability of deep, quantitative datasets in diverse species, there is a growing need for tools to facilitate cross-species comparison of PTM data. This is particularly important because functionally important modification sites are more likely to be evolutionarily conserved; yet cross-species comparison of PTMs is difficult since they often lie in structurally disordered protein domains. Current tools that address this can only map known PTMs between species based on known orthologous phosphosites, and do not enable the cross-species mapping of newly identified modification sites. Here, we addressed this by developing a web-based software tool, PhosphOrtholog ( www.phosphortholog.com ) that accurately maps protein modification sites between different species. This facilitates the comparison of datasets derived from multiple species, and should be a valuable tool for the proteomics community. RESULTS: Here we describe PhosphOrtholog, a web-based application for mapping known and novel orthologous PTM sites from experimental data obtained from different species. PhosphOrtholog is the only generic and automated tool that enables cross-species comparison of large-scale PTM datasets without relying on existing PTM databases. This is achieved through pairwise sequence alignment of orthologous protein residues. To demonstrate its utility we apply it to two sets of human and rat muscle phosphoproteomes generated following insulin and exercise stimulation, respectively, and one publicly available mouse phosphoproteome following cellular stress revealing high mapping and coverage efficiency. Although coverage statistics are dataset dependent, PhosphOrtholog increased the number of cross-species mapped sites in all our example data sets by more than double when compared to those recovered using existing resources such as PhosphoSitePlus. CONCLUSIONS: PhosphOrtholog is the first tool that enables mapping of thousands of novel and known protein phosphorylation sites across species, accessible through an easy-to-use web interface. Identification of conserved PTMs across species from large-scale experimental data increases our knowledgebase of functional PTM sites. Moreover, PhosphOrtholog is generic being applicable to other PTM datasets such as acetylation, ubiquitination and methylation.

Proteomic Analysis of GLUT4 Storage Vesicles Reveals Tumor Suppressor Candidate 5 (TUSC5) as a Novel Regulator of Insulin Action in Adipocytes.

Insulin signaling augments glucose transport by regulating glucose transporter 4 (GLUT4) trafficking from specialized intracellular compartments, termed GLUT4 storage vesicles (GSVs), to the plasma membrane. Proteomic analysis of GSVs by mass spectrometry revealed enrichment of 59 proteins in these vesicles. We measured reduced abundance of 23 of these proteins following insulin stimulation and assigned these as high confidence GSV proteins. These included established GSV proteins such as GLUT4 and insulin-responsive aminopeptidase, as well as six proteins not previously reported to be localized to GSVs. Tumor suppressor candidate 5 (TUSC5) was shown to be a novel GSV protein that underwent a 3.7-fold increase in abundance at the plasma membrane in response to insulin. siRNA-mediated knockdown of TUSC5 decreased insulin-stimulated glucose uptake, although overexpression of TUSC5 had the opposite effect, implicating TUSC5 as a positive regulator of insulin-stimulated glucose transport in adipocytes. Incubation of adipocytes with TNFα caused insulin resistance and a concomitant reduction in TUSC5. Consistent with previous studies, peroxisome proliferator-activated receptor (PPAR) γ agonism reversed TNFα-induced insulin resistance. TUSC5 expression was necessary but insufficient for PPARγ-mediated reversal of insulin resistance. These findings functionally link TUSC5 to GLUT4 trafficking, insulin action, insulin resistance, and PPARγ action in the adipocyte. Further studies are required to establish the exact role of TUSC5 in adipocytes.

Global Phosphoproteomic Mapping of Early Mitotic Exit in Human Cells Identifies Novel Substrate Dephosphorylation Motifs.

Entry into mitosis is driven by the coordinated phosphorylation of thousands of proteins. For the cell to complete mitosis and divide into two identical daughter cells it must regulate dephosphorylation of these proteins in a highly ordered, temporal manner. There is currently a lack of a complete understanding of the phosphorylation changes that occur during the initial stages of mitotic exit in human cells. Therefore, we performed a large unbiased, global analysis to map the very first dephosphorylation events that occur as cells exit mitosis. We identified and quantified the modification of >16,000 phosphosites on >3300 unique proteins during early mitotic exit, providing up to eightfold greater resolution than previous studies. The data have been deposited to the ProteomeXchange with identifier PXD001559. Only a small fraction (∼ 10%) of phosphorylation sites were dephosphorylated during early mitotic exit and these occurred on proteins involved in critical early exit events, including organization of the mitotic spindle, the spindle assembly checkpoint, and reformation of the nuclear envelope. Surprisingly this enrichment was observed across all kinase consensus motifs, indicating that it is independent of the upstream phosphorylating kinase. Therefore, dephosphorylation of these sites is likely determined by the specificity of phosphatase/s rather than the activity of kinase/s. Dephosphorylation was significantly affected by the amino acids at and surrounding the phosphorylation site, with several unique evolutionarily conserved amino acids correlating strongly with phosphorylation status. These data provide a potential mechanism for the specificity of phosphatases, and how they co-ordinate the ordered events of mitotic exit. In summary, our results provide a global overview of the phosphorylation changes that occur during the very first stages of mitotic exit, providing novel mechanistic insight into how phosphatase/s specifically regulate this critical transition.

Targeted phosphoproteomics of insulin signaling using data-independent acquisition mass spectrometry.

A major goal in signaling biology is the establishment of high-throughput quantitative methods for measuring changes in protein phosphorylation of entire signal transduction pathways across many different samples comprising temporal or dose data or patient samples. Data-independent acquisition (DIA) mass spectrometry (MS) methods, which involve tandem MS scans that are collected independently of precursor ion information and then are followed by targeted searching for known peptides, may achieve this goal. We applied DIA-MS to systematically quantify phosphorylation of components in the insulin signaling network in response to insulin as well as in stimulated cells exposed to a panel of kinase inhibitors targeting key downstream effectors in the network. We accurately quantified the effect of insulin on phosphorylation of 86 protein targets in the insulin signaling network using either stable isotope standards (SIS) or label-free quantification (LFQ) and mapped signal transmission through this network. By matching kinases to specific phosphorylation events (based on linear consensus motifs and temporal phosphorylation) to the quantitative phosphoproteomic data from cells exposed to inhibitors, we investigated predicted kinase-substrate relationships of AKT and mTOR in a targeted fashion. Furthermore, we applied this approach to show that AKT2-dependent phosphorylation of GAB2 promoted insulin signaling but inhibited epidermal growth factor (EGF) signaling in a manner dependent on 14-3-3 binding. Because DIA-MS can increase throughput and improve the reproducibility of peptide detection across multiple samples, this approach should facilitate more accurate, comprehensive, and quantitative assessment of signaling networks under various experimental conditions than are possible using other MS proteomic methods.