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Interrogating cAMP-dependent Kinase Signaling in Jurkat T Cells via a Protein Kinase A Targeted Immune-precipitation Phosphoproteomics Approach

2013; Elsevier BV; Volume: 12; Issue: 11 Linguagem: Inglês

10.1074/mcp.o113.028456

1535-9484

Piero Giansanti, Matthew P. Stokes, Jeffrey C. Silva, Arjen Scholten, Albert J. R. Heck,

Receptor Mechanisms and Signaling

In the past decade, mass-spectrometry-based methods have emerged for the quantitative profiling of dynamic changes in protein phosphorylation, allowing the behavior of thousands of phosphorylation sites to be monitored in a single experiment. However, when one is interested in specific signaling pathways, such shotgun methodologies are not ideal because they lack selectivity and are not cost and time efficient with respect to instrument and data analysis time.Here we evaluate and explore a peptide-centric antibody generated to selectively enrich peptides containing the cAMP-dependent protein kinase (PKA) consensus motif. This targeted phosphoproteomic strategy is used to profile temporal quantitative changes of potential PKA substrates in Jurkat T lymphocytes upon prostaglandin E2 (PGE2) stimulation, which increases intracellular cAMP, activating PKA. Our method combines ultra-high-specificity motif-based immunoaffinity purification with cost-efficient stable isotope dimethyl labeling. We identified 655 phosphopeptides, of which 642 (i.e. 98%) contained the consensus motif [R/K][R/K/X]X[pS/pT]. When our data were compared with a large-scale Jurkat T-lymphocyte phosphoproteomics dataset containing more than 10,500 phosphosites, a minimal overlap of 0.2% was observed. This stresses the need for such targeted analyses when the interest is in a particular kinase.Our data provide a resource of likely substrates of PKA, and potentially some substrates of closely related kinases. Network analysis revealed that about half of the observed substrates have been implicated in cAMP-induced signaling. Still, the other half of the here-identified substrates have been less well characterized, representing a valuable resource for future research. In the past decade, mass-spectrometry-based methods have emerged for the quantitative profiling of dynamic changes in protein phosphorylation, allowing the behavior of thousands of phosphorylation sites to be monitored in a single experiment. However, when one is interested in specific signaling pathways, such shotgun methodologies are not ideal because they lack selectivity and are not cost and time efficient with respect to instrument and data analysis time. Here we evaluate and explore a peptide-centric antibody generated to selectively enrich peptides containing the cAMP-dependent protein kinase (PKA) consensus motif. This targeted phosphoproteomic strategy is used to profile temporal quantitative changes of potential PKA substrates in Jurkat T lymphocytes upon prostaglandin E2 (PGE2) stimulation, which increases intracellular cAMP, activating PKA. Our method combines ultra-high-specificity motif-based immunoaffinity purification with cost-efficient stable isotope dimethyl labeling. We identified 655 phosphopeptides, of which 642 (i.e. 98%) contained the consensus motif [R/K][R/K/X]X[pS/pT]. When our data were compared with a large-scale Jurkat T-lymphocyte phosphoproteomics dataset containing more than 10,500 phosphosites, a minimal overlap of 0.2% was observed. This stresses the need for such targeted analyses when the interest is in a particular kinase. Our data provide a resource of likely substrates of PKA, and potentially some substrates of closely related kinases. Network analysis revealed that about half of the observed substrates have been implicated in cAMP-induced signaling. Still, the other half of the here-identified substrates have been less well characterized, representing a valuable resource for future research. The identification and quantification of protein phosphorylation under system perturbations is an integral part of systems biology (1Bensimon A. Heck A.J. Aebersold R. Mass spectrometry-based proteomics and network biology.Annu. Rev. Biochem. 2012; 81: 379-405Crossref PubMed Scopus (317) Google Scholar, 2Altelaar A.F. Munoz J. Heck A.J. Next-generation proteomics: towards an integrative view of proteome dynamics.Nat. Rev. Genet. 2012; 14: 35-48Crossref PubMed Scopus (521) Google Scholar). The combination of phosphopeptide enrichment (3Beausoleil S.A. Jedrychowski M. Schwartz D. Elias J.E. Villen J. Li J. Cohn M.A. Cantley L.C. Gygi S.P. Large-scale characterization of HeLa cell nuclear phosphoproteins.Proc. Natl. Acad. Sci. U.S.A. 2004; 101: 12130-12135Crossref PubMed Scopus (1236) Google Scholar, 4Villen J. Gygi S.P. The SCX/IMAC enrichment approach for global phosphorylation analysis by mass spectrometry.Nat. Protoc. 2008; 3: 1630-1638Crossref PubMed Scopus (498) Google Scholar, 5Pinkse M.W. Mohammed S. Gouw J.W. van Breukelen B. Vos H.R. Heck A.J. Highly robust, automated, and sensitive online TiO2-based phosphoproteomics applied to study endogenous phosphorylation in Drosophila melanogaster.J. Proteome Res. 2008; 7: 687-697Crossref PubMed Scopus (163) Google Scholar, 6Zhou H. Low T.Y. Hennrich M.L. van der Toorn H. Schwend T. Zou H. Mohammed S. Heck A.J. Enhancing the identification of phosphopeptides from putative basophilic kinase substrates using Ti (IV) based IMAC enrichment.Mol. Cell. Proteomics. 2011; 10 (M110.006452)Abstract Full Text Full Text PDF Scopus (77) Google Scholar), stable isotope labeling, and high-resolution mass spectrometry (MS) methods (7Good D.M. Wirtala M. McAlister G.C. Coon J.J. Performance characteristics of electron transfer dissociation mass spectrometry.Mol. Cell. Proteomics. 2007; 6: 1942-1951Abstract Full Text Full Text PDF PubMed Scopus (327) Google Scholar, 8Wiesner J. Premsler T. Sickmann A. Application of electron transfer dissociation (ETD) for the analysis of posttranslational modifications.Proteomics. 2008; 8: 4466-4483Crossref PubMed Scopus (186) Google Scholar, 9Frese C.K. Altelaar A.F. Hennrich M.L. Nolting D. Zeller M. Griep-Raming J. Heck A.J. Mohammed S. Improved peptide identification by targeted fragmentation using CID, HCD and ETD on an LTQ-Orbitrap Velos.J. Proteome Res. 2011; 10: 2377-2388Crossref PubMed Scopus (250) Google Scholar) has become the method of choice for the identification of novel phosphorylation sites and for the quantitation of temporal dynamics within signaling networks (10Olsen J.V. Blagoev B. Gnad F. Macek B. Kumar C. Mortensen P. Mann M. Global, in vivo, and site-specific phosphorylation dynamics in signaling networks.Cell. 2006; 127: 635-648Abstract Full Text Full Text PDF PubMed Scopus (2807) Google Scholar, 11Oberprieler N.G. Lemeer S. Kalland M.E. Torgersen K.M. Heck A.J. Tasken K. High-resolution mapping of prostaglandin E2-dependent signaling networks identifies a constitutively active PKA signaling node in CD8+CD45RO+ T cells.Blood. 2010; 116: 2253-2265Crossref PubMed Scopus (35) Google Scholar), allowing the behavior of thousands of phosphorylation sites to be studied in a single experiment (10Olsen J.V. Blagoev B. Gnad F. Macek B. Kumar C. Mortensen P. Mann M. Global, in vivo, and site-specific phosphorylation dynamics in signaling networks.Cell. 2006; 127: 635-648Abstract Full Text Full Text PDF PubMed Scopus (2807) Google Scholar, 12Mayya V. Lundgren D.H. Hwang S.I. Rezaul K. Wu L. Eng J.K. Rodionov V. Han D.K. Quantitative phosphoproteomic analysis of T cell receptor signaling reveals system-wide modulation of protein-protein interactions.Sci. Signal. 2009; 2: ra46Crossref PubMed Scopus (306) Google Scholar, 13Zhou H. Di Palma S. Preisinger C. Peng M. Polat A.N. Heck A.J. Mohammed S. Toward a comprehensive characterization of a human cancer cell phosphoproteome.J. Proteome Res. 2013; 12: 260-271Crossref PubMed Scopus (297) Google Scholar). Nowadays, one of the most commonly adopted high-throughput phosphoproteomics strategies utilizes two consecutive separation steps: (i) an initial fractionation to reduce the sample complexity, and (ii) a phosphopeptide-specific affinity purification. Such techniques include strong cation exchange fractionation under acidic conditions (3Beausoleil S.A. Jedrychowski M. Schwartz D. Elias J.E. Villen J. Li J. Cohn M.A. Cantley L.C. Gygi S.P. Large-scale characterization of HeLa cell nuclear phosphoproteins.Proc. Natl. Acad. Sci. U.S.A. 2004; 101: 12130-12135Crossref PubMed Scopus (1236) Google Scholar), followed by a chelation-based method with the use of metal ions (i.e. immobilized metal ion affinity chromatography (4Villen J. Gygi S.P. The SCX/IMAC enrichment approach for global phosphorylation analysis by mass spectrometry.Nat. Protoc. 2008; 3: 1630-1638Crossref PubMed Scopus (498) Google Scholar), metal oxide affinity chromatography (10Olsen J.V. Blagoev B. Gnad F. Macek B. Kumar C. Mortensen P. Mann M. Global, in vivo, and site-specific phosphorylation dynamics in signaling networks.Cell. 2006; 127: 635-648Abstract Full Text Full Text PDF PubMed Scopus (2807) Google Scholar, 14Pinkse M.W. Uitto P.M. Hilhorst M.J. Ooms B. Heck A.J. Selective isolation at the femtomole level of phosphopeptides from proteolytic digests using 2D-nanoLC-ESI-MS/MS and titanium oxide precolumns.Anal. Chem. 2004; 76: 3935-3943Crossref PubMed Scopus (825) Google Scholar), or Ti4+ immobilized metal ion affinity chromatography (6Zhou H. Low T.Y. Hennrich M.L. van der Toorn H. Schwend T. Zou H. Mohammed S. Heck A.J. Enhancing the identification of phosphopeptides from putative basophilic kinase substrates using Ti (IV) based IMAC enrichment.Mol. Cell. Proteomics. 2011; 10 (M110.006452)Abstract Full Text Full Text PDF Scopus (77) Google Scholar)). Alternatives to strong cation exchange for the first sample fractionation step have also been reported, including the use of electrostatic repulsion liquid chromatography (15Alpert A.J. Electrostatic repulsion hydrophilic interaction chromatography for isocratic separation of charged solutes and selective isolation of phosphopeptides.Anal. Chem. 2008; 80: 62-76Crossref PubMed Scopus (444) Google Scholar, 16Chien K.Y. Liu H.C. Goshe M.B. Development and application of a phosphoproteomic method using electrostatic repulsion-hydrophilic interaction chromatography (ERLIC), IMAC, and LC-MS/MS analysis to study Marek's Disease Virus infection.J. Proteome Res. 2011; 10: 4041-4053Crossref PubMed Scopus (39) Google Scholar), which is well suited for the identification of multiply phosphorylated peptides, or hydrophilic interaction chromatography (17McNulty D.E. Annan R.S. Hydrophilic interaction chromatography reduces the complexity of the phosphoproteome and improves global phosphopeptide isolation and detection.Mol. Cell. Proteomics. 2008; 7: 971-980Abstract Full Text Full Text PDF PubMed Scopus (307) Google Scholar). Although the number of detected phosphorylated peptides is nowadays impressive, these kinds of methodologies are still inclined to identify/quantify the more abundant phosphoproteins present in a sample. For example, phosphotyrosine peptides are underrepresented because of their relatively lower abundance. In order to analyze key signaling events that may occur on less abundant phosphoproteins, more targeted approaches, focused on a specific pathway or a specific post-translational modification, are thus still essential. Studies examining post-translational modifications are often based on immunoaffinity purification at the protein or peptide level using dedicated antibodies. Recent examples include the selective enrichment of acetylated lysines (18Choudhary C. Kumar C. Gnad F. Nielsen M.L. Rehman M. Walther T.C. Olsen J.V. Mann M. Lysine acetylation targets protein complexes and co-regulates major cellular functions.Science. 2009; 325: 834-840Crossref PubMed Scopus (3152) Google Scholar) and phosphorylated tyrosines (19Zhang Y. Wolf-Yadlin A. Ross P.L. Pappin D.J. Rush J. Lauffenburger D.A. White F.M. Time-resolved mass spectrometry of tyrosine phosphorylation sites in the epidermal growth factor receptor signaling network reveals dynamic modules.Mol. Cell. Proteomics. 2005; 4: 1240-1250Abstract Full Text Full Text PDF PubMed Scopus (474) Google Scholar, 20Boersema P.J. Foong L.Y. Ding V.M. Lemeer S. van Breukelen B. Philp R. Boekhorst J. Snel B. den Hertog J. Choo A.B. Heck A.J. In-depth qualitative and quantitative profiling of tyrosine phosphorylation using a combination of phosphopeptide immunoaffinity purification and stable isotope dimethyl labeling.Mol. Cell. Proteomics. 2010; 9: 84-99Abstract Full Text Full Text PDF PubMed Scopus (145) Google Scholar). More recently, the first specific methods targeting serine/threonine phosphorylation motifs using immune-affinity assays have emerged (21Matsuoka S. Ballif B.A. Smogorzewska A. McDonald 3rd, E.R. Hurov K.E. Luo J. Bakalarski C.E. Zhao Z. Solimini N. Lerenthal Y. Shiloh Y. Gygi S.P. Elledge S.J. ATM and ATR substrate analysis reveals extensive protein networks responsive to DNA damage.Science. 2007; 316: 1160-1166Crossref PubMed Scopus (2356) Google Scholar, 22Moritz A. Li Y. Guo A. Villen J. Wang Y. MacNeill J. Kornhauser J. Sprott K. Zhou J. Possemato A. Ren J.M. Hornbeck P. Cantley L.C. Gygi S.P. Rush J. Comb M.J. Akt-RSK-S6 kinase signaling networks activated by oncogenic receptor tyrosine kinases.Sci. Signal. 2010; 3: ra64Crossref PubMed Scopus (254) Google Scholar). The advantages of targeted approaches are their potentially higher sensitivity and more specific throughput with, as a consequence, relatively faster and easier data interpretation, which make them attractive for many systems biology applications. Immunoaffinity enrichment can be applied at both the protein and the peptide level, and both have been explored to study protein tyrosine phosphorylation (23Salomon A.R. Ficarro S.B. Brill L.M. Brinker A. Phung Q.T. Ericson C. Sauer K. Brock A. Horn D.M. Schultz P.G. Peters E.C. Profiling of tyrosine phosphorylation pathways in human cells using mass spectrometry.Proc. Natl. Acad. Sci. U.S.A. 2003; 100: 443-448Crossref PubMed Scopus (264) Google Scholar). The first one results mainly in information on total protein phosphorylation levels. The detection of the actual phosphoresidue might be hampered by the high content of unmodified peptides derived from the immune-purified phosphoprotein and its binding partners. Immunoprecipitation at the peptide level (20Boersema P.J. Foong L.Y. Ding V.M. Lemeer S. van Breukelen B. Philp R. Boekhorst J. Snel B. den Hertog J. Choo A.B. Heck A.J. In-depth qualitative and quantitative profiling of tyrosine phosphorylation using a combination of phosphopeptide immunoaffinity purification and stable isotope dimethyl labeling.Mol. Cell. Proteomics. 2010; 9: 84-99Abstract Full Text Full Text PDF PubMed Scopus (145) Google Scholar, 24Rush J. Moritz A. Lee K.A. Guo A. Goss V.L. Spek E.J. Zhang H. Zha X.M. Polakiewicz R.D. Comb M.J. Immunoaffinity profiling of tyrosine phosphorylation in cancer cells.Nat. 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Global, in vivo, and site-specific phosphorylation dynamics in signaling networks.Cell. 2006; 127: 635-648Abstract Full Text Full Text PDF PubMed Scopus (2807) Google Scholar) or via chemical peptide labeling of the proteolytic digests (26Bantscheff M. Schirle M. Sweetman G. Rick J. Kuster B. Quantitative mass spectrometry in proteomics: a critical review.Anal. Bioanal. Chem. 2007; 389: 1017-1031Crossref PubMed Scopus (1256) Google Scholar, 27Kovanich D. Cappadona S. Raijmakers R. Mohammed S. Scholten A. Heck A.J. Applications of stable isotope dimethyl labeling in quantitative proteomics.Anal. Bioanal. Chem. 2012; 404: 991-1009Crossref PubMed Scopus (54) Google Scholar). To identify low-abundant signaling events, phosphoprotein/phosphopeptide immunoprecipitation is typically performed on several milligrams of material because of the substoichiometric abundance of post-translational modifications. This may hamper the use of expensive isotope-labeling reagents such as iTRAQ or tandem mass tag reagents, given the large amount of chemicals needed. Boersema et al. (28Boersema P.J. Raijmakers R. Lemeer S. Mohammed S. Heck A.J. Multiplex peptide stable isotope dimethyl labeling for quantitative proteomics.Nat. Protoc. 2009; 4: 484-494Crossref PubMed Scopus (1055) Google Scholar) introduced an alternative sensitive and accurate triplex labeling approach using inexpensive reagents (i.e. formaldehyde) that is much less limited in terms of the sample type or amount. We combined this latter stable-isotope dimethyl labeling approach (27Kovanich D. Cappadona S. Raijmakers R. Mohammed S. Scholten A. Heck A.J. Applications of stable isotope dimethyl labeling in quantitative proteomics.Anal. Bioanal. Chem. 2012; 404: 991-1009Crossref PubMed Scopus (54) Google Scholar, 28Boersema P.J. Raijmakers R. Lemeer S. Mohammed S. Heck A.J. Multiplex peptide stable isotope dimethyl labeling for quantitative proteomics.Nat. Protoc. 2009; 4: 484-494Crossref PubMed Scopus (1055) Google Scholar, 29Hsu J.L. Huang S.Y. Chow N.H. Chen S.H. Stable-isotope dimethyl labeling for quantitative proteomics.Anal. Chem. 2003; 75: 6843-6852Crossref PubMed Scopus (599) Google Scholar) with highly specific antibodies raised against a set of cAMP-dependent protein kinase (PKA) phosphorylated substrates as based on the current literature (11Oberprieler N.G. Lemeer S. Kalland M.E. Torgersen K.M. Heck A.J. Tasken K. High-resolution mapping of prostaglandin E2-dependent signaling networks identifies a constitutively active PKA signaling node in CD8+CD45RO+ T cells.Blood. 2010; 116: 2253-2265Crossref PubMed Scopus (35) Google Scholar, 30Tegge W. Frank R. Hofmann F. Dostmann W.R. Determination of cyclic nucleotide-dependent protein kinase substrate specificity by the use of peptide libraries on cellulose paper.Biochemistry. 1995; 34: 10569-10577Crossref PubMed Scopus (103) Google Scholar, 31Shabb J.B. Physiological substrates of cAMP-dependent protein kinase.Chem. Rev. 2001; 101: 2381-2411Crossref PubMed Scopus (279) Google Scholar, 32Hutti J.E. Jarrell E.T. Chang J.D. Abbott D.W. Storz P. Toker A. Cantley L.C. Turk B.E. A rapid method for determining protein kinase phosphorylation specificity.Nat. Methods. 2004; 1: 27-29Crossref PubMed Scopus (282) Google Scholar, 33Kim M. Park Y.S. Shin D.S. Kim J. Kim B.G. Lee Y.S. Antibody-free peptide substrate screening of serine/threonine kinase (protein kinase A) with a biotinylated detection probe.Anal. Biochem. 2011; 413: 30-35Crossref PubMed Scopus (3) Google Scholar, 34Smith F.D. Samelson B.K. Scott J.D. Discovery of cellular substrates for protein kinase A using a peptide array screening protocol.Biochem. J. 2011; 438: 103-110Crossref PubMed Scopus (35) Google Scholar). It is generally accepted that PKA phosphorylates sites with the reasonably stringent consensus motif [R/K][R/K/X]X[pS/pT]. It should be noted that this consensus motif resembles somewhat the motifs of other AGC kinases (e.g. Akt, PKG, PKC). The basicity of the PKA motifs may hamper their analysis via MS-based proteomics, especially when trypsin is used as a protease, as the peptides may become too small to be sequenced. The use of trypsin is also unfavorable in the approach presented here when attempting to immunoprecipitate peptides bearing the PKA motif. Therefore, we decided to use Lys-C in order to keep the (dominant (RRX[pS/pT])) phosphorylated motif intact. To enhance identification, we applied decision-tree MS/MS technology (9Frese C.K. Altelaar A.F. Hennrich M.L. Nolting D. Zeller M. Griep-Raming J. Heck A.J. Mohammed S. Improved peptide identification by targeted fragmentation using CID, HCD and ETD on an LTQ-Orbitrap Velos.J. Proteome Res. 2011; 10: 2377-2388Crossref PubMed Scopus (250) Google Scholar), which makes use of HCD and ETD for more efficient fragmentation, higher mass accuracy in tandem MS mode, and less background noise (35Swaney D.L. McAlister G.C. Coon J.J. Decision tree-driven tandem mass spectrometry for shotgun proteomics.Nat. Methods. 2008; 5: 959-964Crossref PubMed Scopus (268) Google Scholar). We applied this method to screen the response of Jurkat T cells to prostaglandin E2 (PGE2) treatment. PGE2 is a potent inflammatory mediator that plays an important role in several immune-regulatory actions (36Kalinski P. Regulation of immune responses by prostaglandin E2.J. Immunol. 2012; 188: 21-28Crossref PubMed Scopus (1035) Google Scholar). It is produced by many different cell types, including tumor cells, where carcinogenesis is associated with chronic inflammatory responses (37Chemnitz J.M. Driesen J. Classen S. Riley J.L. Debey S. Beyer M. Popov A. Zander T. Schultze J.L. Prostaglandin E2 impairs CD4+ T cell activation by inhibition of lck: implications in Hodgkin's lymphoma.Cancer Res. 2006; 66: 1114-1122Crossref PubMed Scopus (86) Google Scholar). PGE2 signaling in T cells is initiated by its binding to the G protein–coupled receptors EP1, -2, -3, and -4. Signaling pathways that are initiated by PGE2 are for the most part under control of the second messenger cyclic adenosine monophosphate (cAMP), 1The abbreviations used are: cAMPcyclic adenosine monophosphateETDelectron transfer dissociationHCDhigher energy collision dissociationIPimmunoprecipitationMS/MStandem mass spectrometryPGE2prostaglandin E2PKAcAMP-dependent protein kinase A. 1The abbreviations used are: cAMPcyclic adenosine monophosphateETDelectron transfer dissociationHCDhigher energy collision dissociationIPimmunoprecipitationMS/MStandem mass spectrometryPGE2prostaglandin E2PKAcAMP-dependent protein kinase A. which is generated from ATP by adenylyl cyclase when PGE2 binds to EP2 or EP4 receptors. One of the primary targets of cAMP is PKA—cAMP binding releases the catalytic subunit activating the kinase. In the current study, we efficiently enriched close to 650 phosphopeptides containing the [R/K][R/K/X]X[pS/pT] consensus motif. Almost all these sites were absent in a recently reported comprehensive phosphoproteomics dataset of Jurkat T cells (12Mayya V. Lundgren D.H. Hwang S.I. Rezaul K. Wu L. Eng J.K. Rodionov V. Han D.K. Quantitative phosphoproteomic analysis of T cell receptor signaling reveals system-wide modulation of protein-protein interactions.Sci. Signal. 2009; 2: ra46Crossref PubMed Scopus (306) Google Scholar), compiled using shotgun strong cation exchange–immobilized metal ion affinity chromatography analysis and containing ∼10,500 phosphorylation sites, illustrative of the complementarity and selectivity of our approach. The qualitative and quantitative data presented here provide a wide-ranging and credible resource of likely PKA substrates. Network analysis confirmed several established cAMP-dependent signaling nodes in our dataset, although most identified potential PKA substrates are "novel" (i.e. not previously reported and/or linked to PKA). Therefore, the dataset presented here can be considered as a comprehensive and reliable resource for future research into cAMP-related signaling. cyclic adenosine monophosphate electron transfer dissociation higher energy collision dissociation immunoprecipitation tandem mass spectrometry prostaglandin E2 cAMP-dependent protein kinase A. cyclic adenosine monophosphate electron transfer dissociation higher energy collision dissociation immunoprecipitation tandem mass spectrometry prostaglandin E2 cAMP-dependent protein kinase A. Jurkat T lymphoma cells were grown in RPMI 1640 medium supplemented with 10% fetal bovine serum and penicillin/streptomycin (Lonza, Basel, Switzerland). For PGE2 stimulation, cells were centrifuged for 2 min at 1500 × g. The growth medium was removed, and the cells were resuspended at a final concentration of 1 × 106 to 2 × 106 cells/ml in RPMI, supplemented with 0 (control) or 10 μm PGE2, and incubated for 1 or 60 min. After treatment, Jurkat cells were harvested and lysed on ice via sonication in 20 mm HEPES pH 8.0, 8 m urea, 1 mm sodium vanadate supplemented with 2.5 mm sodium pyrophosphate, 1 mm β-glycerophosphate, and an EDTA-free protease inhibitor mixture (Roche). The total protein concentration was determined using a Bradford assay (Bio-Rad). The total protein lysate from each condition (6 mg) was reduced with DTT at a final concentration of 4 mm at 56 °C for 30 min; subsequently, samples were alkylated with iodoacetamide at a final concentration of 8 mm at room temperature for 30 min in the dark. For digestion, the protease Lys-C (1:50; Wako, Richmond, VA) was added. Digestion was performed for 4 h at 37 °C. Lys-C peptides were desalted and stable-isotope labeled using a Sep-Pak C18 column (Waters, Etten-Leur, The Netherlands) as described previously (28Boersema P.J. Raijmakers R. Lemeer S. Mohammed S. Heck A.J. Multiplex peptide stable isotope dimethyl labeling for quantitative proteomics.Nat. Protoc. 2009; 4: 484-494Crossref PubMed Scopus (1055) Google Scholar). Equal amounts of protein sample were labeled on-column using "light," "intermediate," and "heavy" dimethyl labeling reagents. The light label (L) was used for the control sample and the intermediate (I) and heavy (H) dimethyl labels were used for the PGE2-stimulated cells for 1 and 60 min, respectively. The resulting solution was then dried in vacuo and stored at −80 °C. The differentially dimethyl-labeled samples were mixed in a 1:1:1 ratio. The immunoprecipitation (IP) was performed according to the manufacturer's protocol. Briefly, the mixed, labeled peptides from the three experiments were desalted, dried down, and resuspended in 1.4 ml of IP buffer (50 mm MOPS, pH 7.2, 10 mm sodium phosphate, and 50 mm NaCl). The labeled peptide mixture was added to 80 μl of the phospho-PKA substrate antibody beads (Cell Signaling Technology, Danvers, MA), and incubation was performed for 2 h at 4 °C with gentle shaking. Beads were washed two times with 1 ml IP buffer and four times with 1 ml MQ-water, all at 4 °C. Peptides were eluted by the addition of 0.15% TFA for 20 min at room temperature. Eluted peptides were desalted and concentrated on stop-and-go extraction tips. The analysis of the enriched phosphopeptides and of the pre-IP cell lysate digest (MIX) was performed on a reversed-phase nano-LC coupled to an LTQ Orbitrap Velos mass spectrometer equipped with an ETD source (Thermo Fisher Scientific). An EASY-nLC 1000 (Thermo Fisher Scientific) was equipped with a 20-mm Aqua C18 (Phenomenex, Utrecht, The Netherlands) trapping column (packed in-house; 100-μm inner diameter, 5-μm particle size) and a 400-mm Zorbax SB-C18 (Agilent, Amstelveen, The Netherlands) analytical column (packed in-house; either 50-μm or 75-μm inner diameter; 1.8-μm particle size). Trapping and washing were performed at 10 μl/min for 4 min with solvent A (0.1 m acetic acid in water). Subsequently, peptides were transferred to the analytical column at about 150 nl/min in a total analysis time of 180 min with a gradient of 3%–40% (v/v) solvent B (0.1 m acetic acid in 80% acetonitrile) in 150 min. The eluent was sprayed by a distal coated fused silica emitter (360-μm outer diameter, 20-μm inner diameter, 10-μm tip inner diameter; constructed in-house) butt-connected to the analytical columns. The ion spray voltage was set to 1.7 kV. The mass spectrometer was operated in a data-dependent mode to automatically switch between MS and MS/MS. Briefly, survey full-scan MS spectra were acquired after accumulation to a target value of 500,000 in the linear ion trap from m/z 350 to m/z 1500 in the Orbitrap with a resolution of 60,000 at m/z 400. For internal mass calibration, the 445.120025 ion was used as a lock mass with a target lock mass abundance of 0%. Charge state screening was enabled, and precursors with an unknown charge state or a charge state of 1 were excluded. After the survey scans, the 10 most intense precursors were subjected to HCD, ETD with ion trap detection, or ETD–Fourier transform fragmentation. A programmed data-dependent decision tree determined the choice of the most appropriate technique for a selected precursor (9Frese C.K. Altelaar A.F. Hennrich M.L. Nolting D. Zeller M. Griep-Raming J. Heck A.J. Mohammed S. Improved peptide identification by targeted fragmentation using CID, HCD and ETD on an LTQ-Orbitrap Velos.J. Proteome Res. 2011; 10: 2377-2388Crossref PubMed Scopus (250) Google Scholar). In essence, doubly charged peptides were subjected to HCD fragmentation, and more highly charged peptides were fragmented using ETD. The normalized collision energy for HCD was set to 40%. Supplemental activation was enabled for ETD. Dynamic exclusion was enabled (exclusion size list = 500, exclusion duration = 60 s). Each raw data file recorded by the mass spectrometer was processed and quantified with Proteome Discoverer (version 1.3, Thermo Scientific). Peak lists containing HCD and ETD fragmentation were generated with Proteome Discoverer with a signal-to-noise threshold of 1.5. The ETD non-fragment filter was also taken into account with the following settings: the precursor peak was removed within a 4-Da window, charged reduced precursors were removed within a 2-Da window, neutral losses from charged reduced precursors were removed within a 2-Da window, and the maximum neutral loss mass was set to 120 Da. All generated peak lists of the IP were searched against a concatenated forwar