BET inhibition blocks inflammation-induced cardiac dysfunction and SARS-CoV-2 infection.

Cardiac injury and dysfunction occur in COVID-19 patients and increase the risk of mortality. Causes are ill defined but could be through direct cardiac infection and/or inflammation-induced dysfunction. To identify mechanisms and cardio-protective drugs, we use a state-of-the-art pipeline combining human cardiac organoids with phosphoproteomics and single nuclei RNA sequencing. We identify an inflammatory "cytokine-storm", a cocktail of interferon gamma, interleukin 1ß, and poly(I:C), induced diastolic dysfunction. Bromodomain-containing protein 4 is activated along with a viral response that is consistent in both human cardiac organoids (hCOs) and hearts of SARS-CoV-2-infected K18-hACE2 mice. Bromodomain and extraterminal family inhibitors (BETi) recover dysfunction in hCOs and completely prevent cardiac dysfunction and death in a mouse cytokine-storm model. Additionally, BETi decreases transcription of genes in the viral response, decreases ACE2 expression, and reduces SARS-CoV-2 infection of cardiomyocytes. Together, BETi, including the Food and Drug Administration (FDA) breakthrough designated drug, apabetalone, are promising candidates to prevent COVID-19 mediated cardiac damage.

µPhos: a scalable and sensitive platform for high-dimensional phosphoproteomics.

Mass spectrometry has revolutionized cell signaling research by vastly simplifying the analysis of many thousands of phosphorylation sites in the human proteome. Defining the cellular response to perturbations is crucial for further illuminating the functionality of the phosphoproteome. Here we describe µPhos ('microPhos'), an accessible phosphoproteomics platform that permits phosphopeptide enrichment from 96-well cell culture and small tissue amounts in <8 h total processing time. By greatly minimizing transfer steps and liquid volumes, we demonstrate increased sensitivity, >90% selectivity, and excellent quantitative reproducibility. Employing highly sensitive trapped ion mobility mass spectrometry, we quantify ~17,000 Class I phosphosites in a human cancer cell line using 20 µg starting material, and confidently localize ~6200 phosphosites from 1 µg. This depth covers key signaling pathways, rendering sample-limited applications and perturbation experiments with hundreds of samples viable. We employ µPhos to study drug- and time-dependent response signatures in a leukemia cell line, and by quantifying 30,000 Class I phosphosites in the mouse brain we reveal distinct spatial kinase activities in subregions of the hippocampal formation.

Synergistic Targeting of DNA-PK and KIT Signaling Pathways in KIT Mutant Acute Myeloid Leukemia.

Acute myeloid leukemia (AML) is the most common and aggressive form of acute leukemia, with a 5-year survival rate of just 24%. Over a third of all AML patients harbor activating mutations in kinases, such as the receptor tyrosine kinases FLT3 (receptor-type tyrosine-protein kinase FLT3) and KIT (mast/stem cell growth factor receptor kit). FLT3 and KIT mutations are associated with poor clinical outcomes and lower remission rates in response to standard-of-care chemotherapy. We have recently identified that the core kinase of the non-homologous end joining DNA repair pathway, DNA-PK (DNA-dependent protein kinase), is activated downstream of FLT3; and targeting DNA-PK sensitized FLT3-mutant AML cells to standard-of-care therapies. Herein, we investigated DNA-PK as a possible therapeutic vulnerability in KIT mutant AML, using isogenic FDC-P1 mouse myeloid progenitor cell lines transduced with oncogenic mutant KIT (V560G and D816V) or vector control. Targeted quantitative phosphoproteomic profiling identified phosphorylation of DNA-PK in the T2599/T2605/S2608/S2610 cluster in KIT mutant cells, indicative of DNA-PK activation. Accordingly, proliferation assays revealed that KIT mutant FDC-P1 cells were more sensitive to the DNA-PK inhibitors M3814 or NU7441, compared with empty vector controls. DNA-PK inhibition combined with inhibition of KIT signaling using the kinase inhibitors dasatinib or ibrutinib, or the protein phosphatase 2A activators FTY720 or AAL(S), led to synergistic cell death. Global phosphoproteomic analysis of KIT-D816V cells revealed that dasatinib and M3814 single-agent treatments inhibited extracellular signal-regulated kinase and AKT (RAC-alpha serine/threonine-protein kinase)/MTOR (serine/threonine-protein kinase mTOR) activity, with greater inhibition of both pathways when used in combination. Combined dasatinib and M3814 treatment also synergistically inhibited phosphorylation of the transcriptional regulators MYC and MYB. This study provides insight into the oncogenic pathways regulated by DNA-PK beyond its canonical role in DNA repair and demonstrates that DNA-PK is a promising therapeutic target for KIT mutant cancers.

Deep Proteome Profiling of White Adipose Tissue Reveals Marked Conservation and Distinct Features Between Different Anatomical Depots.

White adipose tissue is deposited mainly as subcutaneous adipose tissue (SAT), often associated with metabolic protection, and abdominal/visceral adipose tissue, which contributes to metabolic disease. To investigate the molecular underpinnings of these differences, we conducted comprehensive proteomics profiling of whole tissue and isolated adipocytes from these two depots across two diets from C57Bl/6J mice. The adipocyte proteomes from lean mice were highly conserved between depots, with the major depot-specific differences encoded by just 3% of the proteome. Adipocytes from SAT (SAdi) were enriched in pathways related to mitochondrial complex I and beiging, whereas visceral adipocytes (VAdi) were enriched in structural proteins and positive regulators of mTOR presumably to promote nutrient storage and cellular expansion. This indicates that SAdi are geared toward higher catabolic activity, while VAdi are more suited for lipid storage. By comparing adipocytes from mice fed chow or Western diet (WD), we define a core adaptive proteomics signature consisting of increased extracellular matrix proteins and decreased fatty acid metabolism and mitochondrial Coenzyme Q biosynthesis. Relative to SAdi, VAdi displayed greater changes with WD including a pronounced decrease in mitochondrial proteins concomitant with upregulation of apoptotic signaling and decreased mitophagy, indicating pervasive mitochondrial stress. Furthermore, WD caused a reduction in lipid handling and glucose uptake pathways particularly in VAdi, consistent with adipocyte de-differentiation. By overlaying the proteomics changes with diet in whole adipose tissue and isolated adipocytes, we uncovered concordance between adipocytes and tissue only in the visceral adipose tissue, indicating a unique tissue-specific adaptation to sustained WD in SAT. Finally, an in-depth comparison of isolated adipocytes and 3T3-L1 proteomes revealed a high degree of overlap, supporting the utility of the 3T3-L1 adipocyte model. These deep proteomes provide an invaluable resource highlighting differences between white adipose depots that may fine-tune their unique functions and adaptation to an obesogenic environment.

RagC phosphorylation autoregulates mTOR complex 1.

The mechanistic (or mammalian) target of rapamycin complex 1 (mTORC1) controls cell growth, proliferation, and metabolism in response to diverse stimuli. Two major parallel pathways are implicated in mTORC1 regulation including a growth factor-responsive pathway mediated via TSC2/Rheb and an amino acid-responsive pathway mediated via the Rag GTPases. Here, we identify and characterize three highly conserved growth factor-responsive phosphorylation sites on RagC, a component of the Rag heterodimer, implicating cross talk between amino acid and growth factor-mediated regulation of mTORC1. We find that RagC phosphorylation is associated with destabilization of mTORC1 and is essential for both growth factor and amino acid-induced mTORC1 activation. Functionally, RagC phosphorylation suppresses starvation-induced autophagy, and genetic studies in Drosophila reveal that RagC phosphorylation plays an essential role in regulation of cell growth. Finally, we identify mTORC1 as the upstream kinase of RagC on S21. Our data highlight the importance of RagC phosphorylation in its function and identify a previously unappreciated auto-regulatory mechanism of mTORC1 activity.

Trafficking regulator of GLUT4-1 (TRARG1) is a GSK3 substrate.

Trafficking regulator of GLUT4-1, TRARG1, positively regulates insulin-stimulated GLUT4 trafficking and insulin sensitivity. However, the mechanism(s) by which this occurs remain(s) unclear. Using biochemical and mass spectrometry analyses we found that TRARG1 is dephosphorylated in response to insulin in a PI3K/Akt-dependent manner and is a novel substrate for GSK3. Priming phosphorylation of murine TRARG1 at serine 84 allows for GSK3-directed phosphorylation at serines 72, 76 and 80. A similar pattern of phosphorylation was observed in human TRARG1, suggesting that our findings are translatable to human TRARG1. Pharmacological inhibition of GSK3 increased cell surface GLUT4 in cells stimulated with a submaximal insulin dose, and this was impaired following Trarg1 knockdown, suggesting that TRARG1 acts as a GSK3-mediated regulator in GLUT4 trafficking. These data place TRARG1 within the insulin signaling network and provide insights into how GSK3 regulates GLUT4 trafficking in adipocytes.

TSC-insensitive Rheb mutations induce oncogenic transformation through a combination of constitutively active mTORC1 signalling and proteome remodelling.

The mechanistic target of rapamycin complex 1 (mTORC1) is an important regulator of cellular metabolism that is commonly hyperactivated in cancer. Recent cancer genome screens have identified multiple mutations in Ras-homolog enriched in brain (Rheb), the primary activator of mTORC1 that might act as driver oncogenes by causing hyperactivation of mTORC1. Here, we show that a number of recurrently occurring Rheb mutants drive hyperactive mTORC1 signalling through differing levels of insensitivity to the primary inactivator of Rheb, tuberous sclerosis complex. We show that two activated mutants, Rheb-T23M and E40K, strongly drive increased cell growth, proliferation and anchorage-independent growth resulting in enhanced tumour growth in vivo. Proteomic analysis of cells expressing the mutations revealed, surprisingly, that these two mutants promote distinct oncogenic pathways with Rheb-T23M driving an increased rate of anaerobic glycolysis, while Rheb-E40K regulates the translation factor eEF2 and autophagy, likely through differential interactions with 5' AMP-activated protein kinase (AMPK) which modulate its activity. Our findings suggest that unique, personalized, combination therapies may be utilised to treat cancers according to which Rheb mutant they harbour.

Transcriptional network dynamics during the progression of pluripotency revealed by integrative statistical learning.

The developmental potential of cells, termed pluripotency, is highly dynamic and progresses through a continuum of naive, formative and primed states. Pluripotency progression of mouse embryonic stem cells (ESCs) from naive to formative and primed state is governed by transcription factors (TFs) and their target genes. Genomic techniques have uncovered a multitude of TF binding sites in ESCs, yet a major challenge lies in identifying target genes from functional binding sites and reconstructing dynamic transcriptional networks underlying pluripotency progression. Here, we integrated time-resolved 'trans-omic' datasets together with TF binding profiles and chromatin conformation data to identify target genes of a panel of TFs. Our analyses revealed that naive TF target genes are more likely to be TFs themselves than those of formative TFs, suggesting denser hierarchies among naive TFs. We also discovered that formative TF target genes are marked by permissive epigenomic signatures in the naive state, indicating that they are poised for expression prior to the initiation of pluripotency transition to the formative state. Finally, our reconstructed transcriptional networks pinpointed the precise timing from naive to formative pluripotency progression and enabled the spatiotemporal mapping of differentiating ESCs to their in vivo counterparts in developing embryos.

Insulin signaling requires glucose to promote lipid anabolism in adipocytes.

Adipose tissue is essential for metabolic homeostasis, balancing lipid storage and mobilization based on nutritional status. This is coordinated by insulin, which triggers kinase signaling cascades to modulate numerous metabolic proteins, leading to increased glucose uptake and anabolic processes like lipogenesis. Given recent evidence that glucose is dispensable for adipocyte respiration, we sought to test whether glucose is necessary for insulin-stimulated anabolism. Examining lipogenesis in cultured adipocytes, glucose was essential for insulin to stimulate the synthesis of fatty acids and glyceride-glycerol. Importantly, glucose was dispensable for lipogenesis in the absence of insulin, suggesting that distinct carbon sources are used with or without insulin. Metabolic tracing studies revealed that glucose was required for insulin to stimulate pathways providing carbon substrate, NADPH, and glycerol 3-phosphate for lipid synthesis and storage. Glucose also displaced leucine as a lipogenic substrate and was necessary to suppress fatty acid oxidation. Together, glucose provided substrates and metabolic control for insulin to promote lipogenesis in adipocytes. This contrasted with the suppression of lipolysis by insulin signaling, which occurred independently of glucose. Given previous observations that signal transduction acts primarily before glucose uptake in adipocytes, these data are consistent with a model whereby insulin initially utilizes protein phosphorylation to stimulate lipid anabolism, which is sustained by subsequent glucose metabolism. Consequently, lipid abundance was sensitive to glucose availability, both during adipogenesis and in Drosophila flies in vivo Together, these data highlight the importance of glucose metabolism to support insulin action, providing a complementary regulatory mechanism to signal transduction to stimulate adipose anabolism.

A Two-Dimensional Metallacycle Cross-Linked Switchable Polymer for Fast and Highly Efficient Phosphorylated Peptide Enrichment.

The selective and efficient capture of phosphopeptides is critical for comprehensive and in-depth phosphoproteome analysis. Here we report a new switchable two-dimensional (2D) supramolecular polymer that serves as an ideal platform for the enrichment of phosphopeptides. A well-defined, positively charged metallacycle incorporated into the polymer endows the resultant polymer with a high affinity for phosphopeptides. Importantly, the stimuli-responsive nature of the polymer facilitates switchable binding affinity of phosphopeptides, thus resulting in an excellent performance in phosphopeptide enrichment and separation from model proteins. The polymer has a high enrichment capacity (165 mg/g) and detection sensitivity (2 fmol), high enrichment recovery (88%), excellent specificity, and rapid enrichment and separation properties. Additionally, we have demonstrated the capture of phosphopeptides from the tryptic digest of real biosamples, thus illustrating the potential of this polymeric material in phosphoproteomic studies.

Sphingosine 1-phosphate but not Fingolimod protects neurons against excitotoxic cell death by inducing neurotrophic gene expression in astrocytes.

Sphingosine 1-phosphate (S1P) is an essential lipid metabolite that signals through a family of five G protein-coupled receptors, S1PR1-S1PR5, to regulate cell physiology. The multiple sclerosis drug Fingolimod (FTY720) is a potent S1P receptor agonist that causes peripheral lymphopenia. Recent research has demonstrated direct neuroprotective properties of FTY720 in several neurodegenerative paradigms; however, neuroprotective properties of the native ligand S1P have not been established. We aimed to establish the significance of neurotrophic factor up-regulation by S1P for neuroprotection, comparing S1P with FTY720. S1P induced brain-derived neurotrophic factor (BDNF), leukemia inhibitory factor (LIF), platelet-derived growth factor B (PDGFB), and heparin-binding EGF-like growth factor (HBEGF) gene expression in primary human and murine astrocytes, but not in neurons, and to a much greater extent than FTY720. Accordingly, S1P but not FTY720 protected cultured neurons against excitotoxic cell death in a primary murine neuron-glia coculture model, and a neutralizing antibody to LIF blocked this S1P-mediated neuroprotection. Antagonists of S1PR1 and S1PR2 both inhibited S1P-mediated neurotrophic gene induction in human astrocytes, indicating that simultaneous activation of both receptors is required. S1PR2 signaling was transduced through Gα13 and the small GTPase Rho, and was necessary for the up-regulation and activation of the transcription factors FOS and JUN, which regulate LIF, BDNF, and HBEGF transcription. In summary, we show that S1P protects hippocampal neurons against excitotoxic cell death through up-regulation of neurotrophic gene expression, particularly LIF, in astrocytes. This up-regulation requires both S1PR1 and S1PR2 signaling. FTY720 does not activate S1PR2, explaining its relative inefficacy compared to S1P.

QCMAP: An Interactive Web-Tool for Performance Diagnosis and Prediction of LC-MS Systems.

The increasing role played by liquid chromatography-mass spectrometry (LC-MS)-based proteomics in biological discovery has led to a growing need for quality control (QC) on the LC-MS systems. While numerous quality control tools have been developed to track the performance of LC-MS systems based on a pre-defined set of performance factors (e.g., mass error, retention time), the precise influence and contribution of the performance factors and their generalization property to different biological samples are not as well characterized. Here, a web-based application (QCMAP) is developed for interactive diagnosis and prediction of the performance of LC-MS systems across different biological sample types. Leveraging on a standardized HeLa cell sample run as QC within a multi-user facility, predictive models are trained on a panel of commonly used performance factors to pinpoint the precise conditions to a (un)satisfactory performance in three LC-MS systems. It is demonstrated that the learned model can be applied to predict LC-MS system performance for brain samples generated from an independent study. By compiling these predictive models into our web-application, QCMAP allows users to benchmark the performance of their LC-MS systems using their own samples and identify key factors for instrument optimization. QCMAP is freely available from: http://shiny.maths.usyd.edu.au/QCMAP/.

NanoBlow: A Simple Device To Limit Contaminants during NanoLC-MS.

Limiting contamination of liquid chromatography/tandem mass spectrometry (LC-MS) systems and reducing the downtime associated with maintenance and cleaning is essential for productivity. We developed a simple device that creates a gas curtain barrier to prevent ions from entering the MS inlet. The gas can be quickly and easily applied when certain contaminant ions are known to elute. We show that the device can prevent the buildup of contaminants on the heated transfer capillary following >100 injections of a crude tissue lysate and improves peptide identifications. The device may provide a promising approach toward improving instrument robustness.

Proteomic Analysis of Human Plasma during Intermittent Fasting.

Intermittent fasting (IF) increases lifespan and decreases metabolic disease phenotypes and cancer risk in model organisms, but the health benefits of IF in humans are less clear. Human plasma derived from clinical trials is one of the most difficult sample sets to analyze using mass spectrometry-based proteomics due to the extensive sample preparation required and the need to process many samples to achieve statistical significance. Here, we describe an optimized and accessible device (Spin96) to accommodate up to 96 StageTips, a widely used sample preparation medium enabling efficient and consistent processing of samples prior to LC-MS/MS. We have applied this device to the analysis of human plasma from a clinical trial of IF. In this longitudinal study employing 8-weeks IF, we identified significant abundance differences induced by the IF intervention, including increased apolipoprotein A4 (APOA4) and decreased apolipoprotein C2 (APOC2) and C3 (APOC3). These changes correlated with a significant decrease in plasma triglycerides after the IF intervention. Given that these proteins have a role in regulating apolipoprotein particle metabolism, we propose that IF had a positive effect on lipid metabolism through modulation of HDL particle size and function. In addition, we applied a novel human protein variant database to detect common protein variants across the participants. We show that consistent detection of clinically relevant peptides derived from both alleles of many proteins is possible, including some that are associated with human metabolic phenotypes. Together, these findings illustrate the power of accessible workflows for proteomics analysis of clinical samples to yield significant biological insight.

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.

Positive-unlabeled ensemble learning for kinase substrate prediction from dynamic phosphoproteomics data.

MOTIVATION: Protein phosphorylation is a post-translational modification that underlines various aspects of cellular signaling. A key step to reconstructing signaling networks involves identification of the set of all kinases and their substrates. Experimental characterization of kinase substrates is both expensive and time-consuming. To expedite the discovery of novel substrates, computational approaches based on kinase recognition sequence (motifs) from known substrates, protein structure, interaction and co-localization have been proposed. However, rarely do these methods take into account the dynamic responses of signaling cascades measured from in vivo cellular systems. Given that recent advances in mass spectrometry-based technologies make it possible to quantify phosphorylation on a proteome-wide scale, computational approaches that can integrate static features with dynamic phosphoproteome data would greatly facilitate the prediction of biologically relevant kinase-specific substrates. RESULTS: Here, we propose a positive-unlabeled ensemble learning approach that integrates dynamic phosphoproteomics data with static kinase recognition motifs to predict novel substrates for kinases of interest. We extended a positive-unlabeled learning technique for an ensemble model, which significantly improves prediction sensitivity on novel substrates of kinases while retaining high specificity. We evaluated the performance of the proposed model using simulation studies and subsequently applied it to predict novel substrates of key kinases relevant to insulin signaling. Our analyses show that static sequence motifs and dynamic phosphoproteomics data are complementary and that the proposed integrated model performs better than methods relying only on static information for accurate prediction of kinase-specific substrates. AVAILABILITY AND IMPLEMENTATION: Executable GUI tool, source code and documentation are freely available at https://github.com/PengyiYang/KSP-PUEL. CONTACT: pengyi.yang@nih.gov or jothi@mail.nih.gov SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

KinasePA: Phosphoproteomics data annotation using hypothesis driven kinase perturbation analysis.

Mass spectrometry (MS)-based quantitative phosphoproteomics has become a key approach for proteome-wide profiling of phosphorylation in tissues and cells. Traditional experimental design often compares a single treatment with a control, whereas increasingly more experiments are designed to compare multiple treatments with respect to a control. To this end, the development of bioinformatic tools that can integrate multiple treatments and visualise kinases and substrates under combinatorial perturbations is vital for dissecting concordant and/or independent effects of each treatment. Here, we propose a hypothesis driven kinase perturbation analysis (KinasePA) to annotate and visualise kinases and their substrates that are perturbed by various combinatorial effects of treatments in phosphoproteomics experiments. We demonstrate the utility of KinasePA through its application to two large-scale phosphoproteomics datasets and show its effectiveness in dissecting kinases and substrates within signalling pathways driven by unique combinations of cellular stimuli and inhibitors. We implemented and incorporated KinasePA as part of the "directPA" R package available from the comprehensive R archive network (CRAN). Furthermore, KinasePA also has an interactive web interface that can be readily applied to annotate user provided phosphoproteomics data (http://kinasepa.pengyiyang.org).

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.

TBC1D13 is a RAB35 specific GAP that plays an important role in GLUT4 trafficking in adipocytes.

Insulin stimulates glucose transport in adipocytes by triggering translocation of GLUT4 glucose transporters to the plasma membrane (PM) and several Rabs including Rab10 have been implicated in this process. To delineate the molecular regulation of this pathway, we conducted a TBC/RabGAP overexpression screen in adipocytes. This identified TBC1D13 as a potent inhibitor of insulin-stimulated GLUT4 translocation without affecting other trafficking pathways. To determine the potential Rab substrate for TBC1D13 we conducted a yeast two-hybrid screen and found that the GTP bound forms of Rabs 1 and 10 specifically interacted with TBC1D13 but not with eight other TBC proteins. Surprisingly, a comprehensive in vitro screen for TBC1D13 GAP activity revealed Rab35 but not Rab10 as a specific substrate. TBC1D13 also displayed in vivo GAP activity towards Rab35. Overexpression of constitutively active Rab35 but not constitutively active Rab10 reversed the block in insulin-stimulated GLUT4 translocation observed with TBC1D13 overexpression. These studies implicate an important role for Rab35 in insulin-stimulated GLUT4 translocation in adipocytes.