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• W2965921488 abstract "Resource5 August 2019free access Source DataTransparent process Phosphoproteomics reveals conserved exercise-stimulated signaling and AMPK regulation of store-operated calcium entry Marin E Nelson Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author Benjamin L Parker Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author James G Burchfield Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author Nolan J Hoffman Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author Elise J Needham Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author Kristen C Cooke Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author Timur Naim Centre for Muscle Research, Department of Physiology, School of Biomedical Sciences, The University of Melbourne, Melbourne, Vic, Australia Search for more papers by this author Lykke Sylow Department of Nutrition, Exercise and Sports, Faculty of Science, The University of Copenhagen, Copenhagen, Denmark Search for more papers by this author Naomi XY Ling Metabolic Signalling Laboratory, St. Vincent's Institute of Medical Research, Melbourne, Vic., Australia Search for more papers by this author Deanne Francis Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author Dougall M Norris Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author Rima Chaudhuri Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author Jonathan S Oakhill Metabolic Signalling Laboratory, St. Vincent's Institute of Medical Research, Melbourne, Vic., Australia Exercise and Nutrition Research Program, Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Vic., Australia Search for more papers by this author Erik A Richter orcid.org/0000-0002-6850-3056 Department of Nutrition, Exercise and Sports, Faculty of Science, The University of Copenhagen, Copenhagen, Denmark Search for more papers by this author Gordon S Lynch Centre for Muscle Research, Department of Physiology, School of Biomedical Sciences, The University of Melbourne, Melbourne, Vic, Australia Search for more papers by this author Jacqueline Stöckli Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author David E James Corresponding Author [email protected] orcid.org/0000-0001-5946-5257 Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author Marin E Nelson Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author Benjamin L Parker Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author James G Burchfield Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author Nolan J Hoffman Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author Elise J Needham Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author Kristen C Cooke Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author Timur Naim Centre for Muscle Research, Department of Physiology, School of Biomedical Sciences, The University of Melbourne, Melbourne, Vic, Australia Search for more papers by this author Lykke Sylow Department of Nutrition, Exercise and Sports, Faculty of Science, The University of Copenhagen, Copenhagen, Denmark Search for more papers by this author Naomi XY Ling Metabolic Signalling Laboratory, St. Vincent's Institute of Medical Research, Melbourne, Vic., Australia Search for more papers by this author Deanne Francis Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author Dougall M Norris Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author Rima Chaudhuri Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author Jonathan S Oakhill Metabolic Signalling Laboratory, St. Vincent's Institute of Medical Research, Melbourne, Vic., Australia Exercise and Nutrition Research Program, Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Vic., Australia Search for more papers by this author Erik A Richter orcid.org/0000-0002-6850-3056 Department of Nutrition, Exercise and Sports, Faculty of Science, The University of Copenhagen, Copenhagen, Denmark Search for more papers by this author Gordon S Lynch Centre for Muscle Research, Department of Physiology, School of Biomedical Sciences, The University of Melbourne, Melbourne, Vic, Australia Search for more papers by this author Jacqueline Stöckli Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author David E James Corresponding Author [email protected] orcid.org/0000-0001-5946-5257 Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia Search for more papers by this author Author Information Marin E Nelson1,‡, Benjamin L Parker1,†,‡, James G Burchfield1,‡, Nolan J Hoffman1,†,‡, Elise J Needham1, Kristen C Cooke1, Timur Naim2, Lykke Sylow3, Naomi XY Ling4, Deanne Francis1, Dougall M Norris1, Rima Chaudhuri1, Jonathan S Oakhill4,5, Erik A Richter3, Gordon S Lynch2, Jacqueline Stöckli1 and David E James *,1 1Charles Perkins Centre, School of Life and Environmental Sciences, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia 2Centre for Muscle Research, Department of Physiology, School of Biomedical Sciences, The University of Melbourne, Melbourne, Vic, Australia 3Department of Nutrition, Exercise and Sports, Faculty of Science, The University of Copenhagen, Copenhagen, Denmark 4Metabolic Signalling Laboratory, St. Vincent's Institute of Medical Research, Melbourne, Vic., Australia 5Exercise and Nutrition Research Program, Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Vic., Australia †Present address: Department of Physiology, The University of Melbourne, Melbourne, Vic., Australia †Present address: Exercise and Nutrition Research Program, Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Vic., Australia ‡These authors contributed equally to this work *Corresponding author. Tel: +61 2 8627 1621; E-mail: [email protected] EMBO J (2019)38:e102578https://doi.org/10.15252/embj.2019102578 Correction(s) for this article Phosphoproteomics reveals conserved exercise-stimulated signaling and AMPK regulation of store-operated calcium entry15 April 2020 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract 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. Synopsis Exercise stimulates cellular and physiological adaptations associated with widespread health benefits, however the underlying signalling events remain unclear. Here, integrated cross-species analysis of exercise-regulated protein phosphorylation in the skeletal muscle uncovers conserved signaling networks including crosstalk between AMPK and intracellular calcium flux. Phospoproteomic analysis of human, rat and mouse skeletal muscle identifies > 5,000 exercise-regulated phosphosites. Cross-species integration reveals conserved pathways and a compendium of potential exercise regulators. AMPK phosphorylates stromal interaction molecule 1 (STIM1) and inhibits skeletal muscle store-operated calcium entry. Inhibition of STIM1 improves exercise tolerance and delays fatigue in Drosophila. Introduction Exercise remains the most effective treatment for a variety of chronic diseases such as type 2 diabetes, dementia, sarcopenia, and heart disease (Berlin & Colditz, 1990; Boulé et al, 2001; Pitkälä et al, 2013; Landi et al, 2014). Such health benefits are linked to activation of an extensive range of coordinated biochemical processes in the exercising muscle to restore homeostasis, and resulting adaptations confer the systemic and tissue-specific health benefits of exercise. Many of the long-term beneficial effects of exercise arise from the contracting muscle itself, and these likely have benefit within the muscle as well as have the potential to trigger beneficial effects in other tissues. These include increased energy expenditure and clearance of ectopic lipid stores, improved insulin sensitivity and reduced circulating insulin levels, and increased secretion of exercise-regulated myokines, such as IL-6 or irisin (Hawley et al, 2014) and extracellular vesicles (Whitham et al, 2018). The breadth of molecular machinery involved in eliciting these integrative exercise adaptations is unknown and is currently the focus of extensive research utilizing models of exercise and muscle contraction in rodents and humans. Filling this knowledge gap requires the development of highly rigorous methods capable of capturing the diverse biological changes that occur in muscle acutely during exercise. We suggest that protein phosphorylation regulates many of these biological processes, and with current developments in mass spectrometry, it is now feasible to quantify such changes on a global scale (Needham et al, 2019). We have previously used a phosphoproteomics approach to quantify and map > 1,000 phosphosites significantly regulated by a single high-intensity cycling bout in humans (Hoffman et al, 2015). Of these exercise-regulated sites, more than 900 have not been functionally validated. Such studies in humans have yielded invaluable information, but the ability to validate exercise-associated pathways is restricted, as genome-wide association studies have poor phenotype predictability power (Marigorta et al, 2018). Therefore, the use of rodent models of exercise and muscle contraction combined with genetic or pharmacological manipulations is essential to comprehensively explore signal transduction and mechanisms underlying the benefits of exercise. Two commonly used models to simulate the human exercise response are rodent treadmill running and in situ electrical stimulation of skeletal muscle with an intact nerve and blood supply (Gehrig et al, 2012; Sylow et al, 2017). For example, phosphoproteomic analysis of mouse skeletal muscle has been utilized to investigate the role of AMP-activated protein kinase (AMPK) in muscle contraction-stimulated fatty acid oxidation (Dzamko et al, 2008), the role of mTORC2 in treadmill exercise-induced signal transduction (Kleinert et al, 2017), and signal transduction during the recovery phase following muscle contraction (Potts et al, 2017). Herein, we mapped the phosphoproteomic responses to acute in situ contraction in rats and a single bout of treadmill running in mice. We then compared these datasets across species with our previously published human cycling dataset (Hoffman et al, 2015). Our goals were to pinpoint common and unique signaling events across commonly used experimental models of exercise, and to uncover exercise-regulated nodes that were robustly activated across exercise models and conserved across species. Among the most highly enriched signaling pathways across all three exercise models were AMPK and Ca2+. In view of the key roles of AMPK (Winder & Hardie, 1996; Mu et al, 2001; Narkar et al, 2008; O'Neill et al, 2011; Toyama et al, 2016) and Ca2+ (Ebashi & Endo, 1968; Melzer et al, 1995; Rose et al, 2006; Kwong et al, 2018) in the exercise response in skeletal muscle, we further interrogated a potential point of crosstalk between these two pathways. We found stromal interaction molecule 1 (STIM1), a protein critical for store-operated Ca2+ entry (SOCE), to be phosphorylated by AMPK across all three datasets at two sites (S257 and S521). We showed AMPK-mediated phosphorylation of STIM1 at S257 to play a key role in regulating STIM1 conformation and SOCE in L6 myoblasts, as well as exercise capacity in a Drosophila model of exercise. Through integrated, cross-species phosphoproteomic analysis of human, rat, and mouse skeletal muscle, we have uncovered conserved exercise-regulated signaling networks and unraveled a novel mechanism whereby AMPK regulates skeletal muscle Ca2+ dynamics. Results Rodent exercise models stimulate key exercise signaling pathways We have recently used phosphoproteomics analysis to construct a global map of exercise signaling, comprising more than 2,400 regulated phosphosites (1,004 changing by more than 50% after exercise) in human muscle from volunteers who underwent acute intense cycling exercise (Hoffman et al, 2015). Here we compared the human dataset to changes induced by in situ muscle contraction in rats or by treadmill running in mice (Fig 1A). For in situ contraction, intact rat tibialis anterior (TA) skeletal muscle was contracted by electrical stimulation of the sciatic nerve (100 Hz for 5 min; 1 s on followed by 3 s off). The contracted muscles were compared to the contralateral non-contracted muscles connected to the force transducer at resting tension (sham). This contraction protocol induced skeletal muscle fatigue over the 5-min period (Appendix Fig S1). For treadmill exercise, gastrocnemius muscle was collected from mice subjected to a single bout of treadmill running at 20 m/min over 30 min at a 10° incline (65% of maximal running capacity determined by a maximal running test as in Sylow et al (2017) and compared to mice that were placed on the treadmill but did not undergo the running protocol (rest). Western blotting confirmed that in situ contraction and treadmill running both induced activation of key signaling pathways that were observed in human muscle after cycling (Hoffman et al, 2015), including regulatory site phosphorylation of AMPK (T172) and the AMPK substrate acetyl-CoA carboxylase (ACC; S79) (Fig 1B). Figure 1. Skeletal muscle exercise-regulated phosphoproteome Illustration of the three exercise models analyzed in this study. Rat tibialis skeletal muscles were subjected to either in situ contraction or sham surgery. Protein was extracted and digested with Lys-C/trypsin, and peptides were isobarically labeled with TMT tags. Phosphopeptides were enriched by titanium dioxide chromatography and sequential elution from immobilized metal ion affinity chromatography (SIMAC). The unbound non-phosphorylated fraction and phosphorylated fraction were further separated by hydrophilic interaction liquid chromatography (HILIC). Each fraction was analyzed by nano-ultra high-pressure liquid chromatography coupled to tandem MS (nanoUHPLC-MS/MS). Western blots for exercise-associated phosphorylated proteins in (top) contracted (+) or sham (−) rat muscle and (bottom) muscle from mice that underwent a treadmill running protocol (+) or remained at rest (−). Total AMPK and 14-3-3 were used as loading controls. Schematic representation of the workflow for mass spectrometry from skeletal muscle. Pearson correlation plot representing the reproducibility of phosphoprotein protein profiles between samples analyzed via mass spectrometry. Venn diagrams representing the number of (left) total or (right) significantly regulated phosphopeptides detected in human, rat, and mouse models of exercise. Volcano plots of phosphopeptide median Log2 fold-change (contraction/sham surgery) plotted against the −Log10 p-value in rat contraction (left) or mouse running (right). Colored dots represent significantly regulated phosphopeptides (P < 0.05, n = 5, moderated t-test). Gray dots represent phosphopeptides that were detected but not significantly altered in exercise. Download figure Download PowerPoint Rodent exercise- and contraction-regulated phosphoproteomes reveal coordinate kinase activity and robust regulation of calcium machinery Quantitative phosphoproteomic analyses of skeletal muscle signaling induced by contraction in rats and treadmill running in mice was performed using multiplexed tandem mass tag (TMT) isobaric labeling and phosphopeptide enrichment coupled to LC-MS/MS (Fig 1C). The phosphorylation profiles in the biological replicates were more highly correlated in the respective groups (gray) compared to between the groups, highlighting reproducible quantification (Fig 1D). A total of 8,989 unique phosphopeptides (7,035 phosphosites with > 90% localization probability) were quantified in all 10 rat skeletal muscle samples subjected to sham or contraction (n = 5), while 9,722 unique phosphopeptides (8,725 phosphosites with > 90% localization probability) were quantified in all 10 mouse skeletal muscles samples subject to rest or treadmill running (n = 5) (Fig 1E; Table EV1). Of the phosphosites quantified, 1,887 and 1,752 were significantly regulated by rat contraction and mouse running, respectively (Fig 1E and F; q-value < 0.05 Benjamini–Hochberg FDR). Although the observed global fold-changes and number of significant sites were similar between the two exercise models, the overall P-values were lower for rat contraction, suggesting this model displays higher reproducibility compared to treadmill running (Fig 1F). We next mapped orthologous phosphosites between human, rat, and mouse muscles using PhosphOrtholog (Chaudhuri et al, 2015) and integrated these data with our previously published phosphoproteome of exercised human muscle (Hoffman et al, 2015). Here, our aim was to identify the regulation of highly conserved phosphorylation events, which are more likely to have important biological roles and represent top priorities for functional validation (Beltrao et al, 2012). Proteins were retrieved from orthologous reference databases followed by global sequence alignment and generation of a statistical significance score for the identification of exact orthologous phosphorylated amino acids. These integrated data contained > 22,000 unique phosphosites, of which 1,726 were orthologous across all three datasets. Sixty-seven orthologous phosphosites were significantly regulated across all three datasets and, of these, 78% were regulated in the same direction (Fig 1E; Appendix Table S1). Despite a relatively low degree of overlap between the models, Appendix Table S1 provides a high-confidence compendium of what likely constitute conserved exercise regulators, many of which have not previously been studied in this context. Notably, 19% of these sites represent proteins that are dually-phosphorylated (HSPB1, MLLT4, NFIX, C18orf25, TNS1, VAPA, SYNPO2, and NDRG2) or even triply-phosphorylated (STIM1, LMOD2, XIRP1, and ALPK3). Among the proteins listed in Appendix Table S2, there is a high degree of convergence on protein kinases (AMPK, PHKA1, SPEG, CAMK, S6K, ALPK3, and mTOR), protein phosphatases (PPP2R5A, PPP1R14A, and PPP1R3C) and transcription factors (NFIX and TFEB) that play a role in the regulation of metabolism and gene expression to allow muscle adaptation. Also observed were scaffolding and actin/myosin regulatory proteins (SYNPO2, LMOD2, AKAP13, RCSD1, CLASP1, FLNC, PLEC, SYNPO2, and TNS1); vesicle transport regulatory proteins (RABGEF2, TBC1D1, LNPEP, VIPAS39, VAPA, and GPHN); and proteins involved in proteostasis including regulators of protein synthesis (RPTOR, EIF4B, and EIF4G1) and chaperone proteins (TFEB, CRYAB, HSPB1, and MAPT). Many of these exercise-regulated proteins represent high-priority targets for further mechanistic interrogation. A relatively low number of conserved exercise-regulated phosphosites overlapped between the different models; however, we observed several examples of regulated phosphorylation of neighboring amino acids between human, rat, and mouse. That is, although the exact orthologous sites were not phosphorylated, we observed regulated phosphorylation in local protein regions conserved between the different species. Phosphorylation of a protein anywhere in a local structural region may serve a similar function via modulation of charge density (Holt et al, 2009; Beltrao et al, 2012). To investigate this, we created “sequence windows” consisting of ± 5% of the protein length around the phosphosites and searched for regulated phosphosites with the same directionality anywhere within the sequence window between the species. Like PhosphoSitePlus (PSP) and PhosphOrtholog, the sequence window filters out phosphosites in structural protein domains such as I-set, leaving a higher proportion of phosphosites in domains that are frequently of interest, including protein kinase and transcription factor domains (Appendix Fig S2A–D). As expected from expanding the stringency from PSP and PhosphOrtholog, the functional prediction score (preprint: Ochoa et al, 2019) was intermediate compared to all phosphosites identified in human muscle and high confidence mapped orthologs (Appendix Fig S2E). Mapping potential orthologs by sequence window resulted in the identification of 190 phosphosites regulated in all three models (114 up- and 76 down-regulated phosphosites), representing 80 proteins (Table EV2). For example, all three datasets identified increased phosphorylation of genethonin-1 (starch-binding domain-containing protein 1; STBD1), a glycogen binding protein associated with transport of glycogen to lysosomes and glycophagy (Jiang et al, 2010) (Appendix Fig S3). A cluster of four to five phosphosites was observed in all three datasets directly adjacent to or within the GABARAPL1 binding site in the Atg8 interacting motif (AIM; Jiang et al, 2011). However, an INDEL mutation and series of point mutations resulted in no single orthologous phosphosite identified in all three species, but rather adjacent phosphosites were regulated. A rodent-specific phosphorylation site (S199 and S195 in mouse and rat, respectively) is orthologous to D214 in human directly in the AIM suggesting evolutionary selection of local negative charge. It is worth noting that, although several phosphosites were co-regulated in sequence windows and may serve common functions, they are not necessarily within the same kinase consensus motifs. Therefore, the sites may be regulated by different, possibly redundant, kinases. To investigate kinase activity between the models, we mapped the phosphosites to the PSP database to retrieve kinase: substrate relationships (KSRs) and performed an enrichment analysis based on the direction of substrate phosphorylation changes (Fig 2A; q-value < 0.05). A total of 553 low-throughput or high-throughput KSRs were annotated in PSP and mapped to our combined phosphoproteomics data (204 mapped across all three species). Kinase enrichment analysis revealed consistent directionality of kinases across the rodent models and human cycling (Fig 2A). However, AMPK and PKA were the only kinases to be significantly enriched in all three exercise models using this directional kinase enrichment method (Fig 2A). To investigate similarities and differences in kinase activity in greater detail, we visualized individual substrates of these kinases (Fig 2B). Notably, substrates of these various kinases were not observed in all forms of exercise. Often, this was because the cognate site was not detected, rather than detected and not regulated. However, differences in regulated sites may reflect systemic versus local biochemical responses to exercise. For example, in the case of both human cycling and mouse running, we observed decreased Akt activity based on substrate enrichment analysis. However, in the case of rat contraction, AKT2 S474 was increased, whereas several downstream substrates were either not detected or not regulated. The observed inhibition of the PI3K/Akt/mTORC2 pathway in human cycling and mouse running but not rat contraction likely reflects a known role of catecholamines to inhibit insulin secretion during exercise, which likely does not occur in the contraction model. Figure 2. Phosphorylation landscapes of exercise models A–D. (A) Kinase activation enrichment analysis, (B) phosphorylation status of specific phosphosites associated with known or predicted upstream kinases, (C) biological pathway enrichment analysis, and (D) phosphorylation status of proteins involved in Ca2+ signaling in human, rat, and mouse models of exercise. Download figure Download PowerPoint We next interrogated differences in the downstream pathways by mapping the proteins containing regulated phosphosites to KEGG and performing an enrichment analysis. This analysis does not accommodate for directionality, as some proteins contain both up- and down-regulated phosphosites. This analysis revealed excellent concordance of the regulated pathways between models (Fig 2C; Table EV3). Two hundred and ten proteins contained at least one regulated phosphorylation site across all three datasets (Table EV3). Taken together, these data highlight differences in biological pathway activation between the models, such as those associated with catecholamine signaling, but also reveal potential conserved regulation at the protein and pathway levels. Exercise- and contraction-regulated phosphorylation of STIM1 by AMPK Our analyses of orthologous and local protein region phosphorylation regulated by exercise and contraction, as well as of kinase and pathway enrichment, identified AMPK and Ca2+ signaling as major points of convergence between the exercise models. We manually curated a comprehensive map of Ca2+ signaling and overlaid the regulated phosphosites from the models to investigate this regulation in greater detail (Fig 2D). Several of these proteins including ATP2B1, CAM2K, and MYH1 contained regulated phosphorylation sites in close proximity to sequence windows, whereas only PHKA1 (regulates glycogen metabolism downstream of the Ca2+-responsive protein CALM1) and STIM1 contained orthologous phosphosites regulated in all three datasets. STIM1 was of particular interest because it shared three orthologous phosphosites that were regulated with the same directionality across all three datasets (Appendix Table S1) and two of these sites (S257 and S521) are predicted AMPK phosphosites (Hoffman et al, 2015) (Fig 3A). STIM1 is a sarcoplasmic reticulum (SR) transmembrane protein that functions as an ER Ca2+ sensor critical for store-operated Ca2+ entry (SOCE; Roos et al, 2005). In response to reduced SR Ca2+ levels, STIM1 undergoes conformational changes that trigger its dimerization and interaction with the Ca2+ release activated Ca2+ (CRAC) channel Orai1 at the plasma membrane (PM) to facilitate SOCE (Feske & Prakriya, 2013). Given the central roles of Ca2+ and AMPK in the skeletal m" @default.
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• W2965921488 title "Phosphoproteomics reveals conserved exercise‐stimulated signaling and AMPK regulation of store‐operated calcium entry" @default.
• W2965921488 cites W1485297825 @default.
• W2965921488 cites W1488122477 @default.
• W2965921488 cites W1519982502 @default.
• W2965921488 cites W1552699877 @default.
• W2965921488 cites W1596515083 @default.
• W2965921488 cites W1622535892 @default.
• W2965921488 cites W1839260472 @default.
• W2965921488 cites W1856053518 @default.
• W2965921488 cites W1918394768 @default.
• W2965921488 cites W1960623258 @default.
• W2965921488 cites W1964205844 @default.
• W2965921488 cites W1966103529 @default.
• W2965921488 cites W1967155114 @default.
• W2965921488 cites W1967175288 @default.
• W2965921488 cites W1972032147 @default.
• W2965921488 cites W1974569431 @default.
• W2965921488 cites W1980881522 @default.
• W2965921488 cites W1980898941 @default.
• W2965921488 cites W1982478101 @default.
• W2965921488 cites W1982522146 @default.
• W2965921488 cites W1988523658 @default.
• W2965921488 cites W1989178712 @default.
• W2965921488 cites W1992547263 @default.
• W2965921488 cites W1996066682 @default.
• W2965921488 cites W1996458818 @default.
• W2965921488 cites W1996768724 @default.
• W2965921488 cites W1998780354 @default.
• W2965921488 cites W2004706099 @default.
• W2965921488 cites W2006240877 @default.
• W2965921488 cites W2010105936 @default.
• W2965921488 cites W2021884467 @default.
• W2965921488 cites W2027889563 @default.
• W2965921488 cites W2028279084 @default.
• W2965921488 cites W2036321220 @default.
• W2965921488 cites W2037244547 @default.
• W2965921488 cites W2038894034 @default.
• W2965921488 cites W2038958971 @default.
• W2965921488 cites W2039454492 @default.
• W2965921488 cites W2041474455 @default.
• W2965921488 cites W2042144124 @default.
• W2965921488 cites W2043431044 @default.
• W2965921488 cites W2047937501 @default.
• W2965921488 cites W2051018818 @default.
• W2965921488 cites W2060851332 @default.
• W2965921488 cites W2061075485 @default.
• W2965921488 cites W2066593167 @default.
• W2965921488 cites W2069989784 @default.
• W2965921488 cites W2076445219 @default.
• W2965921488 cites W2078964925 @default.
• W2965921488 cites W2080752012 @default.
• W2965921488 cites W2081098333 @default.
• W2965921488 cites W2081920342 @default.
• W2965921488 cites W2083511201 @default.
• W2965921488 cites W2085289028 @default.
• W2965921488 cites W2087432631 @default.
• W2965921488 cites W2098607851 @default.
• W2965921488 cites W2101586949 @default.
• W2965921488 cites W2101876702 @default.
• W2965921488 cites W2103168705 @default.
• W2965921488 cites W2104498985 @default.
• W2965921488 cites W2109488005 @default.
• W2965921488 cites W2110643873 @default.
• W2965921488 cites W2111677946 @default.
• W2965921488 cites W2118029488 @default.
• W2965921488 cites W2119484090 @default.
• W2965921488 cites W2124536446 @default.
• W2965921488 cites W2126037064 @default.
• W2965921488 cites W2132520315 @default.
• W2965921488 cites W2133603157 @default.
• W2965921488 cites W2135792340 @default.
• W2965921488 cites W2138002435 @default.
• W2965921488 cites W2140369651 @default.
• W2965921488 cites W2140808124 @default.
• W2965921488 cites W2149160854 @default.
• W2965921488 cites W2155621610 @default.
• W2965921488 cites W2156244206 @default.
• W2965921488 cites W2157658519 @default.
• W2965921488 cites W2159482845 @default.

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