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• W2096845911 abstract "The discovery of new functions for platelets, particularly in inflammation and immunity, has expanded the role of these anucleate cell fragments beyond their primary hemostatic function. Here, four in-depth human platelet proteomic data sets were generated to explore potential new functions for platelets based on their protein content and this led to the identification of 2559 high confidence proteins. During a more detailed analysis, consistently high expression of the proteasome was discovered, and the composition and function of this complex, whose role in platelets has not been thoroughly investigated, was examined. Data set mining resulted in identification of nearly all members of the 26S proteasome in one or more data sets, except the β5 subunit. However, β5i, a component of the immunoproteasome, was identified. Biochemical analyses confirmed the presence of all catalytically active subunits of the standard 20S proteasome and immunoproteasome in human platelets, including β5, which was predominantly found in its precursor form. It was demonstrated that these components were assembled into the proteasome complex and that standard proteasome as well as immunoproteasome subunits were constitutively active in platelets. These findings suggest potential new roles for platelets in the immune system. For example, the immunoproteasome may be involved in major histocompatibility complex I (MHC I) peptide generation, as the MHC I machinery was also identified in our data sets. The discovery of new functions for platelets, particularly in inflammation and immunity, has expanded the role of these anucleate cell fragments beyond their primary hemostatic function. Here, four in-depth human platelet proteomic data sets were generated to explore potential new functions for platelets based on their protein content and this led to the identification of 2559 high confidence proteins. During a more detailed analysis, consistently high expression of the proteasome was discovered, and the composition and function of this complex, whose role in platelets has not been thoroughly investigated, was examined. Data set mining resulted in identification of nearly all members of the 26S proteasome in one or more data sets, except the β5 subunit. However, β5i, a component of the immunoproteasome, was identified. Biochemical analyses confirmed the presence of all catalytically active subunits of the standard 20S proteasome and immunoproteasome in human platelets, including β5, which was predominantly found in its precursor form. It was demonstrated that these components were assembled into the proteasome complex and that standard proteasome as well as immunoproteasome subunits were constitutively active in platelets. These findings suggest potential new roles for platelets in the immune system. For example, the immunoproteasome may be involved in major histocompatibility complex I (MHC I) peptide generation, as the MHC I machinery was also identified in our data sets. Although first described over a century ago, new roles and functions for platelets continue to emerge. Derived by budding from megakaryocytes and devoid of a nucleus, platelets were formerly not thought to produce proteins and their one role was to initiate and perform blood clotting. However, this view has changed in recent years; platelets have mRNA, microRNAs to regulate their mRNA, the machinery to synthesize proteins and they use it (1Weyrich A.S. Schwertz H. Kraiss L.W. Zimmerman G.A. Protein synthesis by platelets: historical and new perspectives.J. Thromb. Haemost. 2009; 7: 241-246Crossref PubMed Scopus (228) Google Scholar, 2Landry P. Plante I. Ouellet D.L. Perron M.P. Rousseau G. Provost P. Existence of a microRNA pathway in anucleate platelets.Nat. Struct. Mol. Biol. 2009; 16: 961-966Crossref PubMed Scopus (387) Google Scholar). Furthermore, in addition to their function in hemostasis, it has been recognized that platelets play a role in inflammatory processes (3Semple J.W. Italiano Jr., J.E. Freedman J. Platelets and the immune continuum.Nat. Rev. Immunol. 2011; 11: 264-274Crossref PubMed Scopus (1135) Google Scholar, 4Vieira-de-Abreu A. Campbell R.A. Weyrich A.S. Zimmerman G.A. Platelets: versatile effector cells in hemostasis, inflammation, and the immune continuum.Semin. Immunopathol. 2012; 34: 5-30Crossref PubMed Scopus (235) Google Scholar). Through their interactions with the endothelium and other blood cells, platelets are believed to play a critical role in defense, wound repair, and more (5Weyrich A. Cipollone F. Mezzetti A. Zimmerman G. Platelets in atherothrombosis: new and evolving roles.Curr. Pharm. Des. 2007; 13: 1685-1691Crossref PubMed Scopus (33) Google Scholar). Understanding of many of the new aspects of platelet function is still limited, but these recent advances raise the question of what other features are awaiting discovery that might be hidden in these small cell fragments. There are limited methods available with which to study platelets; DNA-based methods cannot be applied, and although mRNA is present in platelets, its low level only allows for restricted analysis. Mass spectrometry (MS)-based proteomics is particularly well set up to study platelets, and previous studies have analyzed the platelet proteome (6O'Neill E.E. Brock C.J. von Kriegsheim A.F. Pearce A.C. Dwek R.A. Watson S.P. Hebestreit H.F. Towards complete analysis of the platelet proteome.Proteomics. 2002; 2: 288-305Crossref PubMed Scopus (171) Google Scholar, 7Garcia A. Prabhakar S. Brock C.J. Pearce A.C. Dwek R.A. Watson S.P. Hebestreit H.F. Zitzmann N. Extensive analysis of the human platelet proteome by two-dimensional gel electrophoresis and mass spectrometry.Proteomics. 2004; 4: 656-668Crossref PubMed Scopus (149) Google Scholar, 8Martens L. Van Damme P. Van Damme J. Staes A. Timmerman E. Ghesquiere B. Thomas G.R. Vandekerckhove J. Gevaert K. The human platelet proteome mapped by peptide-centric proteomics: a functional protein profile.Proteomics. 2005; 5: 3193-3204Crossref PubMed Scopus (117) Google Scholar, 9Thon J.N. Schubert P. Duguay M. Serrano K. Lin S. Kast J. Devine D.V. Comprehensive proteomic analysis of protein changes during platelet storage requires complementary proteomic approaches.Transfusion. 2008; 48: 425-435Crossref PubMed Scopus (73) Google Scholar, 10Krishnan S. Gaspari M. Della Corte A. Bianchi P. Crescente M. Cerletti C. Torella D. Indolfi C. de Gaetano G. Donati M.B. Rotilio D. Cuda G. OFFgel-based multidimensional LC-MS/MS approach to the cataloging of the human platelet proteome for an interactomic profile.Electrophoresis. 2011; 32: 686-695Crossref PubMed Scopus (33) Google Scholar, 11Burkhart J.M. Vaudel M. Gambaryan S. Radau S. Walter U. Martens L. Geiger J. Sickmann A. Zahedi R.P. The first comprehensive and quantitative analysis of human platelet protein composition allows the comparative analysis of structural and functional pathways.Blood. 2012; 120: e73-82Crossref PubMed Scopus (508) Google Scholar), various subproteomes (12Piersma S.R. Broxterman H.J. Kapci M. de Haas R.R. Hoekman K. Verheul H.M. Jimenez C.R. Proteomics of the TRAP-induced platelet releasate.J. Proteomics. 2009; 72: 91-109Crossref PubMed Scopus (104) Google Scholar, 13Maguire P.B. Wynne K.J. Harney D.F. O'Donoghue N.M. Stephens G. Fitzgerald D.J. Identification of the phosphotyrosine proteome from thrombin activated platelets.Proteomics. 2002; 2: 642-648Crossref PubMed Scopus (157) Google Scholar, 14Lewandrowski U. Wortelkamp S. Lohrig K. Zahedi R.P. Wolters D.A. Walter U. Sickmann A. Platelet membrane proteomics: a novel repository for functional research.Blood. 2009; 114: e10-19Crossref PubMed Scopus (109) Google Scholar, 15Maynard D.M. Heijnen H.F. Horne M.K. White J.G. Gahl W.A. Proteomic analysis of platelet alpha-granules using mass spectrometry.J. Thromb. Haemost. 2007; 5: 1945-1955Crossref PubMed Scopus (224) Google Scholar, 16Zahedi R.P. Lewandrowski U. Wiesner J. Wortelkamp S. Moebius J. Schutz C. Walter U. Gambaryan S. Sickmann A. Phosphoproteome of resting human platelets.J. Proteome Res. 2008; 7: 526-534Crossref PubMed Scopus (143) Google Scholar), and have shed light on aspects of platelet signaling and function (17Garcia A. Prabhakar S. Hughan S. Anderson T.W. Brock C.J. Pearce A.C. Dwek R.A. Watson S.P. Hebestreit H.F. Zitzmann N. Differential proteome analysis of TRAP-activated platelets: involvement of DOK-2 and phosphorylation of RGS proteins.Blood. 2004; 103: 2088-2095Crossref PubMed Scopus (159) Google Scholar, 18Garcia A. Senis Y.A. Antrobus R. Hughes C.E. Dwek R.A. Watson S.P. Zitzmann N. A global proteomics approach identifies novel phosphorylated signaling proteins in GPVI-activated platelets: involvement of G6f, a novel platelet Grb2-binding membrane adapter.Proteomics. 2006; 6: 5332-5343Crossref PubMed Scopus (83) Google Scholar, 19Senis Y.A. Antrobus R. Severin S. Parguina A.F. Rosa I. Zitzmann N. Watson S.P. Garcia A. Proteomic analysis of integrin alphaIIbbeta3 outside-in signaling reveals Src-kinase-independent phosphorylation of Dok-1 and Dok-3 leading to SHIP-1 interactions.J. Thromb. Haemost. 2009; 7: 1718-1726Crossref PubMed Scopus (50) Google Scholar, 20Wright B. Stanley R.G. Kaiser W.J. Mills D.J. Gibbins J.M. Analysis of protein networks in resting and collagen receptor (GPVI)-stimulated platelet sub-proteomes.Proteomics. 2011; 11: 4588-4592Crossref PubMed Scopus (12) Google Scholar, 21Parguina A.F. Alonso J. Rosa I. Velez P. Gonzalez-Lopez M.J. Guitian E. Ebble J.A. Loza M.I. Garcia A. A detailed proteomic analysis of rhodocytin-activated platelets reveals novel clues on the CLEC-2 signalosome: implications for CLEC-2 signaling regulation.Blood. 2012; 120: e117-126Crossref PubMed Scopus (24) Google Scholar). In this study, proteomic analysis of human platelets was conducted, generating an inventory of platelet proteins, which was then explored by comparison to proteomic data sets of nucleated cells with the aim of identifying new biology-related functions. This approach revealed consistently high expression of the proteasome, the protein complex that is the main protein degradation machinery in cells (Fig. 1). The presence of the proteasome in platelets has been described earlier (22Ostrowska H. Ostrowska J.K. Worowski K. Radziwon P. Human platelet 20S proteasome: inhibition of its chymotrypsin-like activity and identification of the proteasome activator PA28. A preliminary report.Platelets. 2003; 14: 151-157Crossref PubMed Scopus (27) Google Scholar). It is known to be active and its activity increases in response to agonist stimulation (23Nayak M.K. Kumar K. Dash D. Regulation of proteasome activity in activated human platelets.Cell Calcium. 2011; 49: 226-232Crossref PubMed Scopus (25) Google Scholar); however, a detailed analysis of the many subunits of this multimeric complex has not been performed and its role in platelets, which produce less protein than nucleated cells, is not fully understood. The proteasome's core complex, the 20S proteasome, is composed of 28 nonidentical subunits, arranged in four rings, two comprising of seven α subunits and two of seven β subunits. Three of the β subunits (β1, β2, and β5) are catalytically active. The 20S proteasome forms the 26S proteasome together with the 19S regulator, which contains ATPase subunits and is responsible for the ATP 1The abbreviations used are:1D1-dimensionalATPAdenosine triphosphateGPMGlobal Proteome MachineHLAHuman leukocyte antigenIFNγInterferon γIPImmunoprecipitationMHCMajor histocompatibility complexPDPull-downPLTPlateletRBCRed blood cellWBCWhite blood cellRTRoom temperature.1The abbreviations used are:1D1-dimensionalATPAdenosine triphosphateGPMGlobal Proteome MachineHLAHuman leukocyte antigenIFNγInterferon γIPImmunoprecipitationMHCMajor histocompatibility complexPDPull-downPLTPlateletRBCRed blood cellWBCWhite blood cellRTRoom temperature. dependence of the 26S proteasome. The immunoproteasome, which is constitutively expressed in cells of the immune system or is synthesized following induction by interferon γ (IFNγ) in all other nucleated cells, is formed when the catalytically active β subunits are replaced by their immunoproteasome counterparts (β1i, β2i, and β5i). IFNγ also up-regulates the 11S regulator, which consists of PA28 α and β subunits, and both the immunoproteasome and the 11S proteasome are thought to be involved in improved peptide generation for major histocompatibility complex (MHC) I antigen presentation (24Kloetzel P.M. Ossendorp F. Proteasome and peptidase function in MHC-class-I-mediated antigen presentation.Curr. Opin. Immunol. 2004; 16: 76-81Crossref PubMed Scopus (339) Google Scholar). 1-dimensional Adenosine triphosphate Global Proteome Machine Human leukocyte antigen Interferon γ Immunoprecipitation Major histocompatibility complex Pull-down Platelet Red blood cell White blood cell Room temperature. 1-dimensional Adenosine triphosphate Global Proteome Machine Human leukocyte antigen Interferon γ Immunoprecipitation Major histocompatibility complex Pull-down Platelet Red blood cell White blood cell Room temperature. Here, discovery of the high expression of the proteasome in our platelet proteomic data set was followed up with traditional biochemical assays to explore in detail the composition of the proteasome in platelets. Not only were all components of the 26S proteasome detected in our global platelet data sets, but immunoproteasome subunits were also identified. We validated that all members of the 20S proteasome were present and assembled in human platelets. Furthermore, we show that the standard as well as the immunoproteasome catalytic subunits are active. The presence of not only active proteasome but active immunoproteasome subunits in platelets opens up the possibility of new roles for these anucleate players, and further illustrates the critical role proteomics plays in improving our understanding of platelet function. Hela, HEK293, and Jurkat cells (American Type Culture Collection (ATCC) Manassas, VA) were grown in Invitrogen Dulbecco's modified medium (high glucose) containing l-glutamine, 10% fetal bovine serum, and penicillin/streptomycin (both Invitrogen/Invitrogen, Burlington, ON). IFNγ was obtained from eBioscience (San Diego, CA). Protein concentrations were determined using a BCA assay (Thermo Scientific, Rockford, IL). Antibodies were from Boston Biochem (Cambridge, MA; mouse monoclonal anti-α7, clone 1A10–3G12), Enzo Life Sciences (Farmingdale, NY; mouse monoclonal anti-β5i, clone LMP7; rabbit polyclonal anti-β5; rabbit polyclonal anti-β1i; and mouse monoclonal anti-α2, clone MCP21), Santa Cruz Biotechnology (Santa Cruz, CA; mouse monoclonal anti-GAPDH), and Bio-Rad (Mississauga, ON; goat anti-mouse and anti-rabbit horseradish peroxidase). Activity probes MV151 and BioVS were purchased from Leiden Institute of Chemistry (Leiden, The Netherlands). Enzymatic digestion for mass spectrometry analysis was performed using sequencing grade modified trypsin (Promega, Madison, WI). Ethical approval was granted by the University of British Columbia Research Ethics Board (certificate number H07–01943) and written informed consent was granted by the donors. Whole blood was drawn from the antecubital vein of healthy human volunteers into acid-citrate-dextrose at a final volume of 15%. Platelets were isolated by centrifugation, washed twice in buffer (10 mm trisodium citrate, 30 mm dextrose, and 10 units/ml apyrase), and resuspended in Tris-buffered saline/5 mm EDTA. During all steps of preparation, care was taken to avoid activation of platelets and isolated platelets were rested before experiments for half an hour at RT. Platelets, red blood cells (RBCs), and white blood cells (WBCs) were counted using an Advia 120 Automated Hematology Analyzer (Siemens Canada, Mississauga, ON). These counts were used to estimate percentage RBC and WBC contamination. Although care was taken to minimize RBC and WBC contamination in all platelet preparations, for certain experiments extra precautions were taken, with platelets prepared using only the upper 1/3 of the platelet-rich plasma and visual exclusion of red blood cell contamination. Experiments were performed using platelets from three different donors unless otherwise indicated. Washed platelets from four individual platelet donors (PLT 1–4) as well as Jurkat and HEK293 cells were re-suspended in lysis buffer [20 mm Tris/HCl pH 7.4, 150 mm NaCl, 1 mm EDTA, 1% TX-100, 2.5 mm Na pyrophosphate, 1 mm β-glycerolphosphate, 1 mm Na3VO4, 1 X protease inhibitor mixture (Calbiochem/Millipore, Billerica, MA)], and immediately snap-frozen in liquid nitrogen. Lysates were mixed with nonreducing Laemmli buffer, boiled at 99 °C for 5 min and ∼250 μg protein/sample was separated by large (20 cm) 1-dimensional (1D) SDS-PAGE. Gels were stained with Coomassie Brilliant Blue and each lane was cut into 40 bands. Standard tryptic in-gel digestions were performed overnight at 37 °C, without reduction or alkylation. Following digestion, peptides were extracted for MS analysis as described previously (25Hoffman M.D. Walsh G.M. Rogalski J.C. Kast J. Identification of nitroxyl-induced modifications in human platelet proteins using a novel mass spectrometric detection method.Mol. Cell. Proteomics. 2009; 8: 887-903Abstract Full Text Full Text PDF PubMed Scopus (36) Google Scholar). Separation and identification of peptides was performed by nano-HPLC MS/MS on an Agilent 1100 (Agilent, Santa Clara, CA) coupled to either an LTQ-Orbitrap (Thermo Scientific; PLT 1) or an LTQ-FT (Thermo Scientific; PLT 2–4) using a 15 cm long, 75 μm I.D. fused silica column packed with 3 μm particle size reverse phase (C18) beads (Dr Maisch GmbH, Germany) with water/acetonitrile/formic acid as the mobile phase with gradient elution. Identification of proteins was performed by extracting the Mascot generic format files from the MS data using DTA Super Charge version 2.0b1, part of the MSQuant open source project (http://msquant.sourceforge.net) and searching them against ENSEMBL human database (GRCh37.55, total proteins used: 74,741) using the X!Tandem algorithm TORNADO (2009.04.01.4) (26Craig R. Beavis R.C. A method for reducing the time required to match protein sequences with tandem mass spectra.Rapid Commun. Mass Spectrom. 2003; 17: 2310-2316Crossref PubMed Scopus (398) Google Scholar, 27Fenyo D. Beavis R.C. A method for assessing the statistical significance of mass spectrometry-based protein identifications using general scoring schemes.Anal. Chem. 2003; 75: 768-774Crossref PubMed Scopus (404) Google Scholar) at the GPM (http://www.thegpm.org). The following search criteria were used: trypsin cleavage specificity with up to one missed cleavage site, no fixed modifications, variable modifications of oxidized methionine and dioxidized cysteine (sulfinic acid), and ± 20 ppm peptide tolerance and ± 0.4 Da MS/MS tolerance. ENSEMBL accession numbers, which are based on genomic information and therefore each protein isoform is assigned a different accession number, were used. A protein expect score (log(e)) cut-off of −2 was chosen, which equates to a 1 in 100 chance of a stochastic protein assignment. The data sets are archived in the GPM database (http://gpmdb.thegpm.org/) and can be accessed by searching for their GPM numbers (supplemental Table S1). The overall quality of the data set was assessed by using the false positive rate (FPR), which is defined as: FPR (%) = 100 × [N∑Ei]/N by the GPM, resulting in FPR values of 0.80% (PLT1), 0.40% (PLT2), 0.54% (PLT3), and 0.48% (PLT4), respectively. To compare the differences and the overlap to a published human platelet proteomic data set (11Burkhart J.M. Vaudel M. Gambaryan S. Radau S. Walter U. Martens L. Geiger J. Sickmann A. Zahedi R.P. The first comprehensive and quantitative analysis of human platelet protein composition allows the comparative analysis of structural and functional pathways.Blood. 2012; 120: e73-82Crossref PubMed Scopus (508) Google Scholar), accession IDs were linked using our in-house database. Because each data set used different proteomic analysis strategies, different spectral matching algorithms, and a different protein sequence database, the following strategy was chosen. ENSP protein accessions (Current data set) was converted to Uniprot/Swiss Protein IDs (Identifier) and linked to the database used in the Burkhart et al. manuscript. This can result in a one-to-one, one-to-many, or many-to-one mapping. Alternatively, we selected Uniprot/Swiss Protein IDs (the database used in the Burkhart et al. manuscript) as the baseline and linked them via our database to Ensemble (ENSP protein accessions). This can also result in a one-to-one, one-to-many, or many-to-one mapping. Expression of the immunoproteasome in Hela cells was induced by incubation for 48 h with 150 units/ml IFNγ at 37 °C. For Western blot analysis, 50 μg of platelet or Hela cell lysate were separated on a 12% SDS-PAGE. For glycerol gradient analysis, platelets were lysed by three freeze/thaw cycles (liquid nitrogen/30 °C). Four milligrams of protein lysate was separated on a 10–40% glycerol gradient (16 h, 4 °C, 25,000 rpm, SW41 rotor, Beckman Coulter, Mississauga, ON) and 18 fractions of 600 μl were taken from the top to the bottom and analyzed by Western blot. Standards (BSA, apoferritin, and 20S proteasome) were separated using a comparable gradient during the same run. Immunoprecipitation of the 20S proteasome was performed mainly as described (28Ducoux-Petit M. Uttenweiler-Joseph S. Brichory F. Bousquet-Dubouch M.P. Burlet-Schiltz O. Haeuw J.F. Monsarrat B. Scaled-down purification protocol to access proteomic analysis of 20S proteasome from human tissue samples: comparison of normal and tumor colorectal cells.J. Proteome Res. 2008; 7: 2852-2859Crossref PubMed Scopus (21) Google Scholar). Briefly, platelets were lysed by three freeze/thaw cycles (liquid nitrogen/30 °C) and 25 strokes in a Dounce homogenizer. Debris was removed by several centrifugation steps and 2 mg of the cytoplasmic fraction was incubated with Protein G Agarose (Thermo Scientific) for 2 h at 4 °C. The supernatant was incubated with 20 μg MCP21 or no antibody as control and 100 μl Protein G Agarose was added for the precipitation, which was performed overnight at 4 °C. Beads were washed three times, boiled with Laemmli buffer, and supernatant was separated on an “Any kDa” gel (Bio-Rad). Three bands from 20–30 kDa were excised, reduced and alkylated, and in-gel digested with trypsin. Peptides were analyzed by LTQ-Orbitrap and proteins were identified using the GPM and Mascot (29Perkins D.N. Pappin D.J. Creasy D.M. Cottrell J.S. Probability-based protein identification by searching sequence databases using mass spectrometry data.Electrophoresis. 1999; 20: 3551-3567Crossref PubMed Scopus (6771) Google Scholar). For this, Mascot generic format files were extracted from the MS data using DTA Super Charge version 2.0b1. The X!Tandem algorithm CYCLONE (2010.12.01.2) (26Craig R. Beavis R.C. A method for reducing the time required to match protein sequences with tandem mass spectra.Rapid Commun. Mass Spectrom. 2003; 17: 2310-2316Crossref PubMed Scopus (398) Google Scholar, 27Fenyo D. Beavis R.C. A method for assessing the statistical significance of mass spectrometry-based protein identifications using general scoring schemes.Anal. Chem. 2003; 75: 768-774Crossref PubMed Scopus (404) Google Scholar) in the GPM was applied to search against ENSEMBL human database (GRCh37.60, total proteins used: 82,080) using the following criteria: trypsin cleavage specificity with up to one missed cleavage site, fixed modification carbamidomethyl, variable modification of oxidized methionine, ± 20 ppm peptide tolerance, and ± 0.4 Da MS/MS tolerance. Protein score cutoffs were set to log (e) < −2 (GPM) and identification of at least two peptides for each protein were required. Data sets can be accessed by their GPM numbers (supplemental Table S2). Mascot version 2.3.01 and database SwissProt_57.1 (513,877 sequences) were used to identify proteins with the following criteria: trypsin cleavage specificity with up to one missed cleavage site, fixed modification carbamidomethyl, variable modification of oxidized methionine, ± 20 ppm peptide tolerance, and ± 0.6 Da MS/MS tolerance, and the scoring scheme was ESI-TRAP. Data sets are found in the supplemental data (IP1_F038211, IP2_F038244, IP3_F040058, and IP_control_F038242), their according F-numbers are also listed in supplemental Table S2. A protein score of > 40 and identification of at least two peptides for each protein were set for further analysis and spectral counting was performed using emPAI, which is included in the Mascot search engine. Proteasome activity probe assays were performed as described (30Florea B.I. Verdoes M. Li N. van der Linden W.A. Geurink P.P. van den Elst H. Hofmann T. de Ru A. van Veelen P.A. Tanaka K. Sasaki K. Murata S. den Dulk H. Brouwer J. Ossendorp F.A. Kisselev A.F. Overkleeft H.S. Activity-based profiling reveals reactivity of the murine thymoproteasome-specific subunit beta5t.Chem. Biol. 2010; 17: 795-801Abstract Full Text Full Text PDF PubMed Scopus (67) Google Scholar). Platelets were resuspended to 4 × 108 cells/ml in Tris buffered saline, incubated with 1 μm MV151 or dimethyl sulfoxide as vehicle control for 1 h at 37 °C, and lysed in 1% Triton X-100 lysis buffer. Alternatively, cells were lysed in a buffer containing 0.1% Nonidet P-40 and 20 μg Hela or 50 μg platelet lysate was incubated with 10 μm MV151 or vehicle control for 1 h at 37 °C. To destroy proteasome activity, lysates were boiled with 1% SDS at 99 °C for 5 min before incubation with MV151. Samples were incubated with Laemmli buffer, separated on a 12% SDS-PAGE, and the gel was scanned using the TAMRA settings on a Typhoon 9400 (GE Healthcare). Pull-down of active proteasome subunits was performed following the manufacturer's protocol (Leiden Institute of Chemistry). Briefly, 1.5 mg platelet lysate was incubated with 15 μm BioVS for 1 h at 37 °C and after denaturation and reduction, and alkylation of the proteins, the pull-down was performed by adding 50 μl Myone Streptavidin T1 Dynabeads (Invitrogen, Burlington, ON) for 1 h at RT. Proteins were eluted with Laemmli buffer and 10 μm biotin and separated on a 12% SDS-PAGE. Silver staining was performed and bands from 20–30 kDa were excised. Proteins were in-gel digested with trypsin, peptides analyzed by LC-MS/MS using a QStar XL Q-TOF (Applied Biosystems/Invitrogen, Burlington, ON), and proteins identified using the GPM and Mascot. Same databases and search criteria were applied as listed in the previous paragraph besides deviating peptide tolerances: 100 ppm (GPM) and 0.15 Da (Mascot). GPM and Mascot F-numbers are listed in supplemental Table S3 and Mascot data are found in the supplemental Data (PD1_1_F038123, PD1_2_F038126, PD1_3_F038129, PD2_1_F038670, PD2_2_F038671, PD2_3_F038672, and PD3_F039251). Global proteomic experiments were performed using four separate platelet preparations as well as two human cell lines, and proteins were identified using the GPM, where the generated data sets are archived (supplemental Table S1). The platelet (PLT) data sets (supplemental Table S4) contained 1818, 1279, 1501, and 1088 high confidence proteins (log(e) score <−2 with each protein having at least one unique peptide) following removal of common contaminants often found in MS experiments (e.g. trypsin and keratin). Combining these experiments resulted in the identification of 2559 platelet proteins, with 618 proteins being detected in all four data sets (Fig. 2A). Throughout the study, platelets were prepared using methods designed to minimize contamination from other blood cells. Percentages of WBC and RBC contamination were determined using an ADVIA 120 hematology analyzer at the end of the platelet preparation and were found to be at the lower limit of detection of the instrument, where the deviation range is higher than the number of counted cells: for WBCs, 0.01–0.06 × 109 cells/L were detected, but the deviation in this area can be up to 0.46 × 109 cells/L. RBCs were detected to be around 0.03–0.05 × 1012 cells/L with the deviation being 0.03 × 1012 cells/L (ADVIA 120 Hematology System Operator's guide, Siemens, V2.02.00 2002–07, 2002). As it was difficult to draw a conclusion regarding contaminations because of these measurements, assessment of the purity of the samples was also conducted post-MS analysis using the plasma and RBC databases at the Normal Clinical Tissue Alliance (http://wiki.thegpm.org/wiki/Normal_Clinical_Tissue_Alliance). The top 30 (by count) proteins in both the plasma and RBC data sets were searched against the platelet data sets. The majority of the proteins were not found in the platelet data sets, and those that were found were ranked low (supplemental Tables S5 and S6). Furthermore, the data sets were searched for the presence of CD45 and MHC II chains, proteins that are not found in platelets but are expressed in leukocytes. CD45 was detected in one data set (PLT3, rank 947, log(e) = −19.4) at a low rank indicating minor WBC contamination. An MHC II chain was found in a different data set (PLT4, rank 1088, log(e) = −2.2), but with very low confidence. Therefore, contamination from other blood components in the platelet data sets was concluded to be minimal. To gain insights into platelet biology, comparative analysis of the platelet data sets and the data sets derived from the nucleated HEK293 and Jurkat cell lines that had been obtained using the same protocols and instruments was performed using data mining tools at the GPM, including analysis of protein gene ontology and pathway analysis using Kyoto Encyclopedia of Genes and Genomes (31Kanehisa M. Goto S. KEGG: kyoto encyclopedia of genes and genomes.Nucleic Acids Res. 200" @default.
• W2096845911 created "2016-06-24" @default.
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• W2096845911 date "2014-12-01" @default.
• W2096845911 modified "2023-09-23" @default.
• W2096845911 title "Global Proteome Analysis Identifies Active Immunoproteasome Subunits in Human Platelets" @default.
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