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• W2113435863 abstract "In this study, the human cerebrospinal fluid (CSF) proteome was mapped using three different strategies prior to Orbitrap LC-MS/MS analysis: SDS-PAGE and mixed mode reversed phase-anion exchange for mapping the global CSF proteome, and hydrazide-based glycopeptide capture for mapping glycopeptides. A maximal protein set of 3081 proteins (28,811 peptide sequences) was identified, of which 520 were identified as glycoproteins from the glycopeptide enrichment strategy, including 1121 glycopeptides and their glycosylation sites. To our knowledge, this is the largest number of identified proteins and glycopeptides reported for CSF, including 417 glycosylation sites not previously reported. From parallel plasma samples, we identified 1050 proteins (9739 peptide sequences). An overlap of 877 proteins was found between the two body fluids, whereas 2204 proteins were identified only in CSF and 173 only in plasma. All mapping results are freely available via the new CSF Proteome Resource (http://probe.uib.no/csf-pr), which can be used to navigate the CSF proteome and help guide the selection of signature peptides in targeted quantitative proteomics. In this study, the human cerebrospinal fluid (CSF) proteome was mapped using three different strategies prior to Orbitrap LC-MS/MS analysis: SDS-PAGE and mixed mode reversed phase-anion exchange for mapping the global CSF proteome, and hydrazide-based glycopeptide capture for mapping glycopeptides. A maximal protein set of 3081 proteins (28,811 peptide sequences) was identified, of which 520 were identified as glycoproteins from the glycopeptide enrichment strategy, including 1121 glycopeptides and their glycosylation sites. To our knowledge, this is the largest number of identified proteins and glycopeptides reported for CSF, including 417 glycosylation sites not previously reported. From parallel plasma samples, we identified 1050 proteins (9739 peptide sequences). An overlap of 877 proteins was found between the two body fluids, whereas 2204 proteins were identified only in CSF and 173 only in plasma. All mapping results are freely available via the new CSF Proteome Resource (http://probe.uib.no/csf-pr), which can be used to navigate the CSF proteome and help guide the selection of signature peptides in targeted quantitative proteomics. Cerebrospinal fluid (CSF) 1The abbreviations used are:BBBblood-brain barrierCIDcollision-induced dissociationCNScentral nervous systemCSFcerebrospinal fluidFAformic acidFDRfalse discovery rateIAAiodoacetamideMARSmultiple affinity removal systemMPSmaximal protein setMM (RP-AX)mixed mode reversed phase-anion exchange chromatographyNOGN-octyl-β-D-glucopyranosidePNGase FPeptide-N-Glycosidase FPTMspost-translational modificationsSPEGsolid-phase extraction of N-linked glycopeptides. 1The abbreviations used are:BBBblood-brain barrierCIDcollision-induced dissociationCNScentral nervous systemCSFcerebrospinal fluidFAformic acidFDRfalse discovery rateIAAiodoacetamideMARSmultiple affinity removal systemMPSmaximal protein setMM (RP-AX)mixed mode reversed phase-anion exchange chromatographyNOGN-octyl-β-D-glucopyranosidePNGase FPeptide-N-Glycosidase FPTMspost-translational modificationsSPEGsolid-phase extraction of N-linked glycopeptides. surrounds and supports the central nervous system (CNS), including the ventricles and subarachnoid space (1Segal M.B. Extracellular and cerebrospinal fluids.J. Inherit. Metab. Dis. 1993; 16: 617-638Crossref PubMed Scopus (108) Google Scholar). About 80% of the total protein amount in CSF derives from size-dependent filtration of blood across the blood-brain barrier (BBB), and the rest originate from drainage of interstitial fluid from the CNS (2Kroksveen A.C. Opsahl J.A. Aye T.T. Ulvik R.J. Berven F.S. Proteomics of human cerebrospinal fluid: discovery and verification of biomarker candidates in neurodegenerative diseases using quantitative proteomics.J. Proteomics. 2011; 74: 371-388Crossref PubMed Scopus (107) Google Scholar, 3McComb J.G. Recent research into the nature of cerebrospinal fluid formation and absorption.J. Neurosurg. 1983; 59: 369-383Crossref PubMed Scopus (241) Google Scholar, 4Regeniter A. Kuhle J. Mehling M. Moller H. Wurster U. Freidank H. Siede W.H. A modern approach to CSF analysis: pathophysiology, clinical application, proof of concept, and laboratory reporting.Clin. Neurol. Neurosurg. 2009; 111: 313-318Crossref PubMed Scopus (42) Google Scholar). Because CSF is in direct contact with the CNS, it should be a promising source for finding biomarkers for diseases in the CNS (5Schutzer S.E. Liu T. Natelson B.H. Angel T.E. Schepmoes A.A. Purvine S.O. Hixson K.K. Lipton M.S. Camp D.G. Coyle P.K. Smith R.D. Bergquist J. Establishing the proteome of normal human cerebrospinal fluid.PLoS One. 2010; 5: e10980Crossref PubMed Scopus (161) Google Scholar). blood-brain barrier collision-induced dissociation central nervous system cerebrospinal fluid formic acid false discovery rate iodoacetamide multiple affinity removal system maximal protein set mixed mode reversed phase-anion exchange chromatography N-octyl-β-D-glucopyranoside Peptide-N-Glycosidase F post-translational modifications solid-phase extraction of N-linked glycopeptides. blood-brain barrier collision-induced dissociation central nervous system cerebrospinal fluid formic acid false discovery rate iodoacetamide multiple affinity removal system maximal protein set mixed mode reversed phase-anion exchange chromatography N-octyl-β-D-glucopyranoside Peptide-N-Glycosidase F post-translational modifications solid-phase extraction of N-linked glycopeptides. Mapping studies characterizing the human CSF proteome and peptidome has previously been carried out using various experimental designs, including both healthy and disease-affected individuals (5Schutzer S.E. Liu T. Natelson B.H. Angel T.E. Schepmoes A.A. Purvine S.O. Hixson K.K. Lipton M.S. Camp D.G. Coyle P.K. Smith R.D. Bergquist J. Establishing the proteome of normal human cerebrospinal fluid.PLoS One. 2010; 5: e10980Crossref PubMed Scopus (161) Google Scholar, 6Zougman A. Pilch B. Podtelejnikov A. Kiehntopf M. Schnabel C. Kumar C. Mann M. Integrated analysis of the cerebrospinal fluid peptidome and proteome.J. Proteome Res. 2008; 7: 386-399Crossref PubMed Scopus (152) Google Scholar, 7Yuan X. Desiderio D.M. Proteomics analysis of prefractionated human lumbar cerebrospinal fluid.Proteomics. 2005; 5: 541-550Crossref PubMed Scopus (72) Google Scholar, 8Pan S. Wang Y. Quinn J.F. Peskind E.R. Waichunas D. Wimberger J.T. Jin J. Li J.G. Zhu D. Pan C. Zhang J. Identification of glycoproteins in human cerebrospinal fluid with a complementary proteomic approach.J. Proteome Res. 2006; 5: 2769-2779Crossref PubMed Scopus (85) Google Scholar, 9Noben J.P. Dumont D. Kwasnikowska N. Verhaert P. Somers V. Hupperts R. Stinissen P. Robben J. Lumbar cerebrospinal fluid proteome in multiple sclerosis: characterization by ultrafiltration, liquid chromatography, and mass spectrometry.J. Proteome Res. 2006; 5: 1647-1657Crossref PubMed Scopus (69) Google Scholar, 10Sickmann A. Dormeyer W. Wortelkamp S. Woitalla D. Kuhn W. Meyer H.E. Identification of proteins from human cerebrospinal fluid, separated by two-dimensional polyacrylamide gel electrophoresis.Electrophoresis. 2000; 21: 2721-2728Crossref PubMed Scopus (82) Google Scholar, 11Maccarrone G. Milfay D. Birg I. Rosenhagen M. Holsboer F. Grimm R. Bailey J. Zolotarjova N. Turck C.W. Mining the human cerebrospinal fluid proteome by immunodepletion and shotgun mass spectrometry.Electrophoresis. 2004; 25: 2402-2412Crossref PubMed Scopus (81) Google Scholar, 12Davidsson P. Folkesson S. Christiansson M. Lindbjer M. Dellheden B. Blennow K. Westman-Brinkmalm A. Identification of proteins in human cerebrospinal fluid using liquid-phase isoelectric focusing as a prefractionation step followed by two-dimensional gel electrophoresis and matrix-assisted laser desorption/ionisation mass spectrometry.Rapid Commun. Mass Spectrom. 2002; 16: 2083-2088Crossref PubMed Scopus (82) Google Scholar, 13Ogata Y. Charlesworth M.C. Muddiman D.C. Evaluation of protein depletion methods for the analysis of total-, phospho- and glycoproteins in lumbar cerebrospinal fluid.J. Proteome Res. 2005; 4: 837-845Crossref PubMed Scopus (55) Google Scholar, 14Wenner B.R. Lovell M.A. Lynn B.C. Proteomic analysis of human ventricular cerebrospinal fluid from neurologically normal, elderly subjects using two-dimensional LC-MS/MS.J. Proteome Res. 2004; 3: 97-103Crossref PubMed Scopus (67) Google Scholar, 15Xu J. Chen J. Peskind E.R. Jin J. Eng J. Pan C. Montine T.J. Goodlett D.R. Zhang J. Characterization of proteome of human cerebrospinal fluid.Int. Rev. Neurobiol. 2006; 73: 29-98Crossref PubMed Scopus (30) Google Scholar, 16Pan S. Zhu D. Quinn J.F. Peskind E.R. Montine T.J. Lin B. Goodlett D.R. Taylor G. Eng J. Zhang J. A combined dataset of human cerebrospinal fluid proteins identified by multi-dimensional chromatography and tandem mass spectrometry.Proteomics. 2007; 7: 469-473Crossref PubMed Scopus (106) Google Scholar). A total of 2630 proteins were detected in normal CSF by immunoaffinity depletion of high abundant proteins followed by strong cation exchange fractionation and LC-MS (5Schutzer S.E. Liu T. Natelson B.H. Angel T.E. Schepmoes A.A. Purvine S.O. Hixson K.K. Lipton M.S. Camp D.G. Coyle P.K. Smith R.D. Bergquist J. Establishing the proteome of normal human cerebrospinal fluid.PLoS One. 2010; 5: e10980Crossref PubMed Scopus (161) Google Scholar), whereas proteome and peptidome analyses of human CSF (collected for diagnostic purposes and turned out normal) by gel separation and trypsin digestion followed by LC-MS analysis have shown 798 proteins and 563 peptide products (derived from 91 precursor proteins) (6Zougman A. Pilch B. Podtelejnikov A. Kiehntopf M. Schnabel C. Kumar C. Mann M. Integrated analysis of the cerebrospinal fluid peptidome and proteome.J. Proteome Res. 2008; 7: 386-399Crossref PubMed Scopus (152) Google Scholar). In another publication, Pan et al. combined several proteomics studies in CSF from both normal subjects and subjects with neurological diseases and created a dataset of 2594 identified proteins (16Pan S. Zhu D. Quinn J.F. Peskind E.R. Montine T.J. Lin B. Goodlett D.R. Taylor G. Eng J. Zhang J. A combined dataset of human cerebrospinal fluid proteins identified by multi-dimensional chromatography and tandem mass spectrometry.Proteomics. 2007; 7: 469-473Crossref PubMed Scopus (106) Google Scholar). But in general, the availability and usefulness of published data from proteome mapping experiments is scarce, and the format of the data often makes searching and comparison across datasets difficult. Thus, organizing the data in online databases would greatly benefit the scientific community by making the data more accessible and easier to query. Current online databases containing MS data for CSF include the Sys-BodyFluid, with a total of 1286 CSF proteins from six studies (17Li S.J. Peng M. Li H. Liu B.S. Wang C. Wu J.R. Li Y.X. Zeng R. Sys-BodyFluid: a systematical database for human body fluid proteome research.Nucleic Acids Res. 2009; 37: D907-912Crossref PubMed Scopus (76) Google Scholar). The proteome identifications database (PRIDE) (18Martens L. Hermjakob H. Jones P. Adamski M. Taylor C. States D. Gevaert K. Vandekerckhove J. Apweiler R. PRIDE: the proteomics identifications database.Proteomics. 2005; 5: 3537-3545Crossref PubMed Scopus (436) Google Scholar) includes 19 studies on human CSF, but none reporting more than 103 identified proteins. Glycosylation is one of the most common post-translational modifications (PTMs), and many known clinical biomarkers as well as therapeutic targets are glycoproteins (19Berger M.S. Locher G.W. Saurer S. Gullick W.J. Waterfield M.D. Groner B. Hynes N.E. Correlation of c-erbB-2 gene amplification and protein expression in human breast carcinoma with nodal status and nuclear grading.Cancer Res. 1988; 48: 1238-1243PubMed Google Scholar, 20Hudziak R.M. Schlessinger J. Ullrich A. Increased expression of the putative growth factor receptor p185HER2 causes transformation and tumorigenesis of NIH 3T3 cells.Proc. Natl. Acad. Sci. U. S. A. 1987; 84: 7159-7163Crossref PubMed Scopus (551) Google Scholar, 21Vogelzang N.J. Lange P.H. Goldman A. Vessela R.H. Fraley E.E. Kennedy B.J. Acute changes of alpha-fetoprotein and human chorionic gonadotropin during induction chemotherapy of germ cell tumors.Cancer Res. 1982; 42: 4855-4861PubMed Google Scholar, 22Bosl G.J. Lange P.H. Fraley E.E. Goldman A. Nochomovitz L.E. Rosai J. Waldmann T.A. Johnson K. Kennedy B.J. Human chorionic gonadotropin and alphafetoprotein in the staging of nonseminomatous testicular cancer.Cancer. 1981; 47: 328-332Crossref PubMed Scopus (35) Google Scholar, 23Thompson D.K. Haddow J.E. Serial monitoring of serum alpha-fetoprotein and chorionic gonadotropin in males with germ cell tumors.Cancer. 1979; 43: 1820-1829Crossref PubMed Scopus (36) Google Scholar, 24Catalona W.J. Richie J.P. Ahmann F.R. Hudson M.A. Scardino P.T. Flanigan R.C. Dekernion J.B. Ratliff T.L. Kavoussi L.R. Dalkin B.L. Waters W.B. MacFarlane M.T. Southwick P.C. Comparison of digital rectal examination and serum prostate specific antigen in the early detection of prostate cancer: results of a multicenter clinical trial of 6630 men.J. Urol. 1994; 151: 1283-1290Crossref PubMed Scopus (1332) Google Scholar, 25Canney P.A. Moore M. Wilkinson P.M. James R.D. Ovarian cancer antigen CA125: a prospective clinical assessment of its role as a tumour marker.Br. J. Cancer. 1984; 50: 765-769Crossref PubMed Scopus (303) Google Scholar). Furthermore, glycosylation plays important roles in cell communication, signaling, aging, and cell adhesion (26Roth J. Protein N-glycosylation along the secretory pathway: relationship to organelle topography and function, protein quality control, and cell interactions.Chem. Rev. 2002; 102: 285-303Crossref PubMed Scopus (342) Google Scholar, 27Sato Y. Endo T. Alteration of brain glycoproteins during aging.Geriatr. Gerontol. Int. 2010; 1: S32-40Crossref Scopus (21) Google Scholar). Nevertheless, there are few studies on glycoprotein identification in CSF. One study identified 216 glycoproteins in CSF using both lectin affinity and hydrazide chemistry (8Pan S. Wang Y. Quinn J.F. Peskind E.R. Waichunas D. Wimberger J.T. Jin J. Li J.G. Zhu D. Pan C. Zhang J. Identification of glycoproteins in human cerebrospinal fluid with a complementary proteomic approach.J. Proteome Res. 2006; 5: 2769-2779Crossref PubMed Scopus (85) Google Scholar), and another reported 36 N-linked and 44 O-linked glycosylation sites, from 23 and 22 glycoproteins respectively, by enriching for sialic-acid containing glycopeptides (28Nilsson J. Ruetschi U. Halim A. Hesse C. Carlsohn E. Brinkmalm G. Larson G. Enrichment of glycopeptides for glycan structure and attachment site identification.Nat. Methods. 2009; 6: 809-811Crossref PubMed Scopus (274) Google Scholar). Considering the sparse information about the CSF proteome available in public repositories, we have combined several proteomics approaches to create a map of the global CSF proteome, the CSF glycoproteome, and the respective plasma proteome from a pool of 21 (20 for the plasma pool) neurologically healthy individuals. The large amount of data generated through these four datasets (with linked and complementary information) would not easily be accessible through existing repositories. We therefore developed the open access CSF Proteome Resource (CSF-PR, www.probe.uib.no/csf-pr), an online database including the detailed data from the four different proteomics experiments described in this study. CSF-PR will be particularly useful in guiding the selection of appropriate signature peptides for the development of targeted CSF protein assays. The workflow of the four different experiments performed in this study is displayed in Fig. 1A, and described in detail below. CSF was collected by lumbar puncture of neurologically healthy (spinal anesthesia subjects (SAS) (29Teunissen C. Menge T. Altintas A. Alvarez-Cermeno J.C. Bertolotto A. Berven F.S. Brundin L. Comabella M. Degn M. Deisenhammer F. Fazekas F. Franciotta D. Frederiksen J.L. Galimberti D. Gnanapavan S. Hegen H. Hemmer B. Hintzen R. Hughes S. Iacobaeus E. Kroksveen A.C. Kuhle J. Richert J. Tumani H. Villar L.M. Drulovic J. Dujmovic I. Khalil M. Bartos A. Consensus definitions and application guidelines for control groups in cerebrospinal fluid biomarker studies in multiple sclerosis.Mult. Scler. 2013; Crossref Scopus (111) Google Scholar)) individuals who, under written informed consent, were to undergo spinal anesthesia for surgery at the Department of Anesthesia and Intensive Care Medicine, Haukeland University Hospital. Information about the subjects can be found in supplemental Table S1. Parallel CSF and plasma samples were collected according to the published consensus protocol for CSF collection and biobanking (30Teunissen C.E. Petzold A. Bennett J.L. Berven F.S. Brundin L. Comabella M. Franciotta D. Frederiksen J.L. Fleming J.O. Furlan R. Hintzen R.Q. Hughes S.G. Johnson M.H. Krasulova E. Kuhle J. Magnone M.C. Rajda C. Rejdak K. Schmidt H.K. van Pesch V. Waubant E. Wolf C. Giovannoni G. Hemmer B. Tumani H. Deisenhammer F. A consensus protocol for the standardization of cerebrospinal fluid collection and biobanking.Neurology. 2009; 73: 1914-1922Crossref PubMed Scopus (529) Google Scholar). None of the patients experienced traumatic CSF taps. CSF samples were centrifuged and cells removed prior to proteomics analysis. Plasma was collected in K2 EDTA tubes and centrifuged at room temperature at 2300 × g for 25 min. Aliquots of 500 μl CSF from each of the 21 individuals included in this study were combined into a pool. A similar pool was generated for the plasma samples from 20 of the patients, as plasma from one patient could not be obtained. The study was approved by The Regional Committee for Medical and Health Research Ethics of Western Norway. If not otherwise stated, all chemicals and products were purchased from Sigma-Aldrich (St. Louis, MO). All protein concentrations were measured using a Qubit™ fluorometer kit (Invitrogen, Carlsbrad, CA) according to the vendor's instructions. 3 ml (1400 μg protein) of the CSF pool was up-concentrated to 20 μl using 3 kDa ultracentrifugation filters (Amicon Ultra-4, Merck Millipore, Billerica, MA), prerinsed with deionized water (MilliQ). The concentrated sample was protein depleted of 14 high abundant proteins using the human Multiple Affinity Removal System (MARS HU-14) 4.6 mm x 50 mm LC column (Agilent Technologies, Santa Clara, CA) according to the vendor's recommendations. The two resulting protein fractions (depleted and bound) were then concentrated using ultracentrifugation filters as described above expect the filters were coated with 1 ml 0.1% N-octyl-Beta-d-glucopyranoside (NOG). Each fraction was dissolved in LDS sample buffer (Invitrogen) containing 10 mm DTT (GE Healthcare, Amersham Biosciences, Buckinghamshire, UK) at 95¦°C for 5 min, alkylated by adding up to 20 mm iodoacetamine (IAA), followed by incubation in room temperature and in the dark for 20 min, prior to gel separation in two separate lanes using a lab-casted 20 cm 5–15% SDS-polyacrylamide gradient gel. Samples were separated at 60 V for 16 h in 1x electrode running buffer (25 mm Tris base, 192 mm Glysine, and 0.1% SDS diluted in milliQ water). After protein separation, the gel was stained with Coomassie Brilliant Blue (GE Healthcare). The lanes were cut into a total of 83 gel slices as described in Fig. 1B, 37 slices from the lane with the bound (high abundant) protein fraction and 46 slices from the lane with the depleted fraction. The gel slices were in-gel digested (supplemental File S1A) using between 120 and 240 ng of trypsin, depending on the size of the band, before MS/MS analysis. 1.6 ml (750 μg protein) CSF was concentrated and immunoaffinity depleted as described above. The entire amount of the depleted fraction (∼40 μg) and an aliquot (100 μg) from the bound fraction was in-solution trypsin digested (Supplementary File 1B), using 0.8 and 2 μg trypsin, respectively. After digestion, the samples were desalted using C18 Oasis™ μElution plates (Waters, Milford, MA) as described elsewhere (31Kroksveen A.C. Aasebo E. Vethe H. Van Pesch V. Franciotta D. Teunissen C.E. Ulvik R.J. Vedeler C. Myhr K.M. Barsnes H. Berven F.S. Discovery and initial verification of differentially abundant proteins between multiple sclerosis patients and controls using iTRAQ and SID-SRM.J. Proteomics. 2012; 78: 312-325Crossref PubMed Scopus (43) Google Scholar). The two samples were then fractionated using mixed mode reversed phase-anion exchange (MM RP-AX) HPLC as described by Phillips et al. (32Phillips H.L. Williamson J.C. van Elburg K.A. Snijders A.P. Wright P.C. Dickman M.J. Shotgun proteome analysis utilizing mixed mode (reversed phase-anion exchange chromatography) in conjunction with reversed phase liquid chromatography mass spectrometry analysis.Proteomics. 2010; 10: 2950-2960Crossref PubMed Scopus (33) Google Scholar). A Promix MP 250 mm x 2.1 mm id, pore size 300 Å column (SIELC Technologies, Prospect Heights, IL) connected to an Agilent Technology 1260 off-line LC-system was used. The desalted and dried samples were resuspended in 120 μl buffer A (20 mm Ammonium formate/3% ACN, pH 6.5) and loaded onto the column. The setup for the LC was as follows. The flow was always 50 μl/min and the gradient length was 70 min. From 0–45 min buffer B (2 mm Ammonium formate/80% ACN) increased linearly from 15% to 60%, from 45–55 min 60% B, from 55–65 min 100% B, and from 65–70 min 15% B. The depleted CSF sample was separated into 80 fractions, where a fraction was collected every 0.87 min from 0–70 min (some fractions at each end of the gradient were later combined to give the total number of 66 fractions). Ten fractions were collected for the bound sample, one fraction the first 2 mins and then one fraction every 7 mins from 2–70 min. For the characterization of the plasma proteome, the same experimental setup as for the CSF characterization using MM (RP-AX) fractionation was applied to 40 μl plasma, representing roughly 2400 μg protein. Three milliliters (1200 μg protein) CSF was in-solution trypsin digested and further processed by solid-phase extraction of N-linked glycopeptides (SPEG) essentially as described in (33Tian Y. Zhou Y. Elliott S. Aebersold R. Zhang H. Solid-phase extraction of N-linked glycopeptides.Nat. Protoc. 2007; 2: 334-339Crossref PubMed Scopus (271) Google Scholar) and (34Berven F.S. Ahmad R. Clauser K.R. Carr S.A. Optimizing performance of glycopeptide capture for plasma proteomics.J. Proteome Res. 2010; 9: 1706-1715Crossref PubMed Scopus (47) Google Scholar), but with some exceptions. The CSF was purified and concentrated to 15 μl using 3 kDa ultracentrifugation filters precoated with 1 ml 0.1% NOG. Dilution with 135 μl denaturation buffer (8 m Urea/0.4 M Ammonium Bicarbonate (ambic)/0.1% SDS (Bio-Rad Laboratories, Hercules, CA) followed, and then 120 mm Tris(2-carboxyethyl)phosphine (TCEP) was added to a final concentration of 10 mm and a one hour incubation at 37¦°C. IAA was added to a final concentration of 12 mm, and incubated for 30 min in the dark. The sample was then diluted with 0.1 m ambic until the urea concentration in the sample was below 1 m, and trypsin digested (1:50 ratio trypsin:protein, Trypsin porcine (Promega, Madison, WI)) overnight at 37¦°C. The next day the sample was desalted using Oasis C18, oxidized and desalted again essentially as described in (33Tian Y. Zhou Y. Elliott S. Aebersold R. Zhang H. Solid-phase extraction of N-linked glycopeptides.Nat. Protoc. 2007; 2: 334-339Crossref PubMed Scopus (271) Google Scholar), with some exceptions. 100% formic acid (FA) was used for acidification, Oasis plates were used for the desalting, the sample was dried after the first desalting to remove ACN and resuspended in 400 μl 0.1% TFA before oxidation. The sample was coupled to 4 mg (133 μl) magnetic hydrazide beads (BioClone Inc. San Diego, CA) and further processed as described in (34Berven F.S. Ahmad R. Clauser K.R. Carr S.A. Optimizing performance of glycopeptide capture for plasma proteomics.J. Proteome Res. 2010; 9: 1706-1715Crossref PubMed Scopus (47) Google Scholar). Beads and supernatant were separated using a Dynal® magnetic bead separation rack (Invitrogen). The released and now deglycosylated peptides were collected the following day as previously described (33Tian Y. Zhou Y. Elliott S. Aebersold R. Zhang H. Solid-phase extraction of N-linked glycopeptides.Nat. Protoc. 2007; 2: 334-339Crossref PubMed Scopus (271) Google Scholar), except that the hydrazide resin was washed only once and with 200 μl ambic, and then acidified with 7 μl 5 m hydrochloric acid and 200 μl 0.1% FA before desalting by Oasis C18 as described in (34Berven F.S. Ahmad R. Clauser K.R. Carr S.A. Optimizing performance of glycopeptide capture for plasma proteomics.J. Proteome Res. 2010; 9: 1706-1715Crossref PubMed Scopus (47) Google Scholar). The SPEG processing was done in three separate experiments (1 ml CSF for each), which were combined before further processing. The digested and SPEG processed sample containing the deglycosylated peptides (former glycopeptides) were fractionated into 20 fractions using MM (RP-AX) as described above with the following set-up: one fraction was collected between 0–2 min, one between 2–7 min, from 7–55 min fractions were collected every 3 min, and from 55–70 min every 5 min. The entire peptide amount from each fraction was injected for LC-MS analysis. Dry samples were dissolved to a final concentration of 0.1–5% FA before analysis on an LTQ Orbitrap Velos Pro mass spectrometer (Thermo Fischer Scientific, Bremen, Germany) equipped with a nano spray Flex ion source (Thermo Fischer Scientific), coupled to a Dionex Ultimate NCS-3000 LC system (Thermo Fischer Scientific). Approximately 0.5 μg of digested protein was loaded and desalted on a precolumn (Acclaim PepMap 100, 2 cm × 75 μm i.d. nanoViper column, packed with 3 μm C18 beads) at a flow rate of 5 μl/min for 6 min using an isocratic flow of 0.1% FA (v/v) with 2% ACN (v/v). Peptides were separated during a biphasic ACN gradient from two nanoflow UPLC pumps with flow rate of 280 nl/min on the analytical column (Acclaim PepMap 100, 15 cm × 75 μm i.d. nanoViper column, packed with 2 μm C18 beads). Solvent A was 0.1% FA (v/v) with 2% ACN (v/v). Solvent B was 0.1% FA (v/v) with 90% ACN (v/v). The gradient was 0–61.5 min ramp from 8–38% B, 61.5–64.5 min ramp from 38–90% B, and 64.5–69.5 min 90% B, followed by column conditioning for 12 min with 5% B. Data dependent acquisition was utilized and collision-induced dissociation (CID) with normalized collision energy of 35% and wideband-activation enabled. Survey full scan MS spectra (from m/z 300–2000) were acquired with resolution r = 60,000 at m/z 400. The 15 ions with the highest intensity were selected for MS/MS fragmentation. MS data were acquired over 90 min. The acquired raw files were searched against the human Swiss-Prot database (from December 2012 - 20,226 entries) using SearchGUI v1.10.4 (35Vaudel M. Barsnes H. Berven F.S. Sickmann A. Martens L. SearchGUI: An open-source graphical user interface for simultaneous OMSSA and X!Tandem searches.Proteomics. 2011; 11: 996-999Crossref PubMed Scopus (277) Google Scholar) (search engines: OMSSA v2.1.9 (36Geer L.Y. Markey S.P. Kowalak J.A. Wagner L. Xu M. Maynard D.M. Yang X. Shi W. Bryant S.H. Open mass spectrometry search algorithm.J. Proteome Res. 2004; 3: 958-964Crossref PubMed Scopus (1167) Google Scholar) and X!Tandem CYCLONE (2010.12.01.1) (37Fenyo 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)) and processed in PeptideShaker v0.19.0, http://peptide-shaker.googlecode.com (38Barsnes H. Vaudel M. Colaert N. Helsens K. Sickmann A. Berven F.S. Martens L. Compomics-utilities: an open-source Java library for computational proteomics.BMC Bioinformatics. 2011; 12: 70Crossref PubMed Scopus (76) Google Scholar). The search criteria were: carbamidomethylation of cystein as a fixed modification and oxidized methionine as a variable modification for all datasets. Deamidation of asparagine was set as a variable modification only for the glyco dataset. Precursor mass tolerance was 10 ppm, fragment mass tolerance 0.7 Da, and maximum number of missed cleavages by trypsin was 2. PeptideShaker converts search engine e-values into confidence values using the distribution of decoy matches as described by Nesvizhskii (39Nesvizhskii A.I. A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics.J. Proteomics. 2010; 73: 2092-2123Crossref PubMed Scopus (380) Google Scholar). For all four of our datasets a validation threshold of 1% false discovery rate was employed individually at the protein, peptide and peptide spectrum match (PSM) level. ProteoWizard v.3.0.3650 (40Chambers M.C. Maclean B. Burke R. Amodei D. Ruderman D.L. Neumann S. Gatto L. Fischer B. Pratt B. Egertson J. Hoff K. Kessner D. Tasman N. Shulman N. Frewen B. Baker T.A. Brusniak M.Y. Paulse C. Creasy D. Flashner L. Kani K. Moulding C. Seymour S.L. Nuwaysir L.M. Lefebvre B. Kuhlmann F. Roark J. Rainer P. Detlev S. Hemenway T. Huhmer A. Langridge J. Connolly B. Chadick T. Holly K. Eckels J. Deutsch E.W. Moritz R.L. Katz J.E. Agus D.B. MacCoss M. Tabb D.L. Mallick P. A cross-platform toolkit for mass spectrometry and proteomics.Nat. 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• W2113435863 title "In-depth Characterization of the Cerebrospinal Fluid (CSF) Proteome Displayed Through the CSF Proteome Resource (CSF-PR)" @default.
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