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Type 2 diabetes is preceded by a defective insulin response, yet our knowledge of the precise mechanisms is incomplete. Here, we investigate how insulin resistance alters skeletal muscle signaling and how exercise partially counteracts this effect. We measured parallel phenotypes and phosphoproteomes of insulin-resistant (IR) and insulin-sensitive (IS) men as they responded to exercise and insulin (n = 19, 114 biopsies), quantifying over 12,000 phosphopeptides in each biopsy. Insulin resistance involves selective and time-dependent alterations to signaling, including reduced insulin-stimulated mTORC1 and non-canonical signaling responses. Prior exercise promotes insulin sensitivity even in IR individuals by "priming" a portion of insulin signaling prior to insulin infusion. This includes MINDY1 S441, which we show is an AKT substrate. We found that MINDY1 knockdown enhances insulin-stimulated glucose uptake in rat myotubes. This work delineates the signaling alterations in IR skeletal muscle and identifies MINDY1 as a regulator of insulin action., Competing Interests: Declaration of interests C.P. was an employee of Pfizer during the study, and the work was supported by a research grant from Pfizer, Inc. J.F.P.W. holds shares in Pfizer, Inc. and is currently a consultant at Pfizer Inc., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

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., Competing Interests: Conflict of interest—The authors declare that they have no conflicts of interest with the contents of this article., (© 2020 Krycer et al.)

Insulin triggers an extensive signaling cascade to coordinate adipocyte glucose metabolism. It is considered that the major role of insulin is to provide anabolic substrates by activating GLUT4-dependent glucose uptake. However, insulin stimulates phosphorylation of many metabolic proteins. To examine the implications of this on glucose metabolism, we performed dynamic tracer metabolomics in cultured adipocytes treated with insulin. Temporal analysis of metabolite concentrations and tracer labeling revealed rapid and distinct changes in glucose metabolism, favoring specific glycolytic branch points and pyruvate anaplerosis. Integrating dynamic metabolomics and phosphoproteomics data revealed that insulin-dependent phosphorylation of anabolic enzymes occurred prior to substrate accumulation. Indeed, glycogen synthesis was activated independently of glucose supply. We refer to this phenomenon as metabolic priming, whereby insulin signaling creates a demand-driven system to "pull" glucose into specific anabolic pathways. This complements the supply-driven regulation of anabolism by substrate accumulation and highlights an additional role for insulin action in adipocyte glucose metabolism., (Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.)

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., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

Insulin-secreting beta cells play an essential role in maintaining physiological blood glucose levels, and their dysfunction leads to the development of diabetes. To elucidate the signalling events regulating insulin secretion, we applied a recently developed phosphoproteomics workflow. We quantified the time-resolved phosphoproteome of murine pancreatic cells following their exposure to glucose and in combination with small molecule compounds that promote insulin secretion. The quantitative phosphoproteome of 30,000 sites clustered into three main groups in concordance with the modulation of the three key kinases: PKA, PKC and CK2A. A high-resolution time course revealed key novel regulatory sites, revealing the importance of methyltransferase DNMT3A phosphorylation in the glucose response. Remarkably a significant proportion of these novel regulatory sites is significantly downregulated in diabetic islets. Control of insulin secretion is embedded in an unexpectedly broad and complex range of cellular functions, which are perturbed by drugs in multiple ways., Competing Interests: This study was done as a collaboration between the Max-Planck Institute of Biochemistry and Sanofi-Aventis Deutschland (SAD), who provided a grant for this purpose to MPIB. M.M, A.S, T.K & M.S. are employed at Sanofi.

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., (Published by Oxford University Press 2015. This work is written by US Government employees and is in the public domain in the US.)

Mass spectrometry has enabled the study of cellular signaling on a systems-wide scale, through the quantification of post-translational modifications, such as protein phosphorylation. Here we describe EasyPhos, a scalable phosphoproteomics platform that now allows rapid quantification of hundreds of phosphoproteomes in diverse cells and tissues at a depth of >10,000 sites. We apply this technology to generate time-resolved maps of insulin signaling in the mouse liver. Our results reveal that insulin affects ~10% of the liver phosphoproteome and that many known functional phosphorylation sites, and an even larger number of unknown sites, are modified at very early time points (<15 s after insulin delivery). Our kinetic data suggest that the flow of signaling information from the cell surface to the nucleus can occur on very rapid timescales of less than 1 min in vivo. EasyPhos facilitates high-throughput phosphoproteomics studies, which should improve our understanding of dynamic cell signaling networks and how they are regulated and dysregulated in disease.

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., (Copyright © 2015, American Association for the Advancement of Science.)