Characterization of the glycated human cerebrospinal fluid proteome

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Characterization of the glycated human cerebrospinal fluid proteome☆ María Ramírez-Booa , Feliciano Priego-Capotea, b , Alexandre Hainarda , Florent Glucka , Pierre Burkhardc , Jean-Charles Sancheza,⁎ a

Biomedical Proteomics Research Group (BPRG), Department of Human Protein Sciences, University Medical Centre, University of Geneva, 1211 Geneva 4, Switzerland b Department of Analytical Chemistry, Annex C-3 Building, Campus of Rabanales, University of Córdoba, Spain c Department of Neurology, Geneva University Hospitals, Geneva, Switzerland

AR TIC LE I N FO Available online 25 January 2012 Keywords: Nonenzymatic glycation Advanced glycation end products Neurodegenerative disorders Cerebrospinal fluid Glycation isotopic labeling

ABS TR ACT Protein glycation is a nonenzymatic modification that involves pathological functions in neurological diseases. Despite the high number of studies showing accumulation of advanced end glycation products (AGEs) at clinical stage, there is a lack of knowledge about which proteins are modified, where those modifications occur, and to what extent. The goal of this study was to achieve a comprehensive characterization of proteins modified by early glycation in human cerebrospinal fluid (CSF). Approaches based on glucose diferential labeling and mass spectrometry have been applied to evaluate the glycated CSF proteome at two physiological conditions: native glucose level and in vitro high glucose content. For both purposes, detection of glycated proteins was carried out by HCD-MS2 and CID-MS3 modes after endoproteinase Glu-C digestion and boronate affinity chromatography. The abundance of glycation was assessed by protein labeling with 13C6-glucose incubation. The analysis of native glycated CSF identified 111 glycation sites corresponding to 48 glycated proteins. Additionally, the in vitro high glucose level approach detected 265 glycation sites and 101 glycated proteins. The comparison of glycation levels under native and 15 mM glucose conditions showed relative concentration increases up to ten folds for some glycated proteins. This report revealed for the first time a number of key glycated CSF proteins known to be involved in neuroinflammation and neurodegenerative disorders. Altogether, the present study contains valuable and unique information, which should further help to clarify the pathological role of glycation in central nervous system pathologies. This article is part of a Special Issue entitled: Translational Proteomics. © 2012 Elsevier B.V. All rights reserved.

Abbreviations: AD, Alzheimer's disease; AGEs, Advanced glycation end products; ALS, Amyotrophic lateral sclerosis; BAC, Boronate affinity chromatography; β2M, Beta-2 microglobulin; CID, Collision-induced dissociation; CJD, Creutzfeld–Jakob disease; CML, Nε-(carboxymethyl)lysine; CNS, Central nervous system; CSF, Cerebrospinal fluid; FDR, False discovery ratio; FL, Fructoselysine; GIL, Glycation Isotopic Labeling; GO, Gene ontology; HCD, Higher-energy collisional dissociation; IAA, Iodoacetamide; IPA, Ingenuity pathway analysis; MGO, Methylglyoxal; PD, Parkinson's disease; PGDS, Prostaglandin D2 synthase; PTM, Post-translational modification; RAGEs, Receptors of advanced glycation end products; SOD, Superoxide dismutase; TAGE, Toxic AGE; TCEP, Tris-(2-carboxyethyl) phosphine hydrochloride; TEAB, Triethylammonium hydrogen carbonate buffer; VD, Vascular dementia. ☆ This article is part of a Special Issue entitled: Translational Proteomics. ⁎ Corresponding author at: Biomedical Proteomics Research Group, DHPS/CMU, Rue Michel Servet, 1, CH-1211 Geneva 4, Switzerland. Tel.: +41 22 379 54 86; fax: +41 22 379 55 05. E-mail address: [email protected] (J.-C. Sanchez). 1874-3919/$ – see front matter © 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.jprot.2012.01.017

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1.

Introduction

Nonenzymatic glycation is one of the most widely spread nonenzymatic side-chain-specific post-translational modifications. According to Maillard hypothesis, the formation of proteinsugar conjugates is considered as an important cause of brain pathologies. The first stage of this reaction involves attachment of glucose or derivates with free amino groups of proteins to form a reversible Schiff base product, leading to the formation of stable fructosamine residue (ketoamine) following Amadori rearrangement. This is the early glycation process [1]. The Amadori products could subsequently cyclise, forming pyranose or furanose carbohydrate adducts. Further modifications in these early stage glycation products, such as rearrangement, polymerization and cleavage give rise to irreversible conjugates, called advanced glycation end products (AGEs) [2]. Most pronounced in neurological disorders, glycation is inherently related to oxidative stress as well. Thus, oxygen does frequently accelerate the glycation when it is present and conversely glycation products induce oxidative stress [3]. Oxidative decomposition of the Amadori product leads to the formation of a broad range of reactive carbonyl and dicarbonyl compounds (i.e. methylglyoxal, MGO) that serve as precursors for more complex AGE cross-links, such as pentosidine and glucosepane [4,5]. AGEs are present in all cells, tissues and body fluids and accumulate with age in long-lived tissue proteins, often altering their structure, function, and turnover [6–9]. Normal aging human brain was shown to accumulate AGEs within neurons and glial cells [10,11] as well as in senile plaques [12]. Beside this “physiological” occurrence of AGEs, pathological accumulations of glycated proteins were found in neurodegenerative diseases such as Alzheimer's (AD) [13], Parkinson's [14], amyotrophic lateral sclerosis (ALS) [15,16], vascular dementia (VD) [17], Creutzfeld– Jakob (CJD) [18], Pick’, and Lewy body diseases [7]. The role of AGEs in the development of neurological diseases has been mainly related with changing the physicochemical properties of AGE-modified proteins as well as the activation of receptors of advanced glycation end products (RAGEs) [19–23] that result in neurotoxic processes and inflammation [24]. Formation of insoluble and protease resistant aggregates, often leading to protein deposition and amyloidosis, is also associated with protein cross-linking by AGEs [4,5]. These observations led researchers to hypothesize that higher level of AGEs in brain tissue could become a promising biomarker for the central pathogenic processes in the above-mentioned diseases. In that respect, cerebrospinal fluid (CSF), which is in close contact with the brain, represents a reservoir of potential clinically relevant biomarkers for neurological diseases. Several studies have demonstrated the elevation of CSF Nε-(carboxymethyl)lysine (CML) [17] or Amadori product levels in patients with AD [25,26]. However, there was no clear evidence to demonstrate the biological role of these products in the pathogenesis of this disease. Because toxic AGEs (TAGE) such as glyceraldehydes-derived AGEs have direct effects on neural cells [27,28], recently it has been suggested that TAGE levels in the CSF could become a useful diagnostic tool for patients with devastating disorders such as AD and vascular dementia [29]. Alternatively, more than one biological marker will be probably necessary for the early diagnosis of disease. One line

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of evidence suggest that a combination of nitration and glycation adduct estimates in CSF may provide an indicator for the diagnosis of AD since concentrations of these adducts were increased in the clinical samples [26]. While it is clear that early glycation products and AGEs increase in neurodegenerative diseases, there are few studies on the specificity of glycation formation in the human CSF and brain proteins. Currently, only amyloid β protein and tau protein have been found to be glycated [12,30,31], which has been linked to AGEs formation detected in senile plaques and neurofibrillary tangles from AD brain [32,33]. Although they have been related with other chronic diseases (e.g. diabetes), apolipoprotein E, transthyretin, hemoglobin, albumin [34], lens crystallin [35,36], beta-2 microglobulin (β2M) [37] and RNase [38] represent some other proteins found to be modified by AGEs. Interestingly, recent studies with these proteins have demonstrated that the specificity of AGE formation appears to track that of glycation at the initial stage [37]. For example analyzing β2M showed that glycation in the Shiff base or Amadori product occurs at the same lysine residue than the modification by AGE pentosidine in glycated proteins [37]. Similarly, both intra- and intermolecular cross-linking of RNase by the AGE glucosepane occur primarily at the lysine and arginine residues, which are most reactive with glucose and MGO [38,39]. To this end, further investigations of early glycation products in CSF will become an important strategy for determination of proteins involved in the pathogenesis of brain diseases. Before undertaking a rational approach to study glycated CSF protein biomarkers in pathological condition, the characterization of the native glycated CSF proteome in healthy subjects is thought to be fundamentally important. In the current work, we have identified glycated proteins in human CSF of aged-matched normal healthy subjects to create a database of identified glycated peptides and proteins as a source for the neurodegenerative disease research community to facilitate the discovery of potential novel markers of brain pathologies. The method, previously applied to human plasma and hemolysates samples, is based on the differential labeling of proteins with isotopically labeled-glucose ([13C]), named Glycation Isotopic Labeling (GIL) [40,41]. The approach has enabled the identification of more than hundred glycated CSF proteins with many of them found specifically in high glucose perturbation in vitro.

2.

Materials and methods

2.1.

Reagents

Di-Sodium hydrogen phosphate, sodium hydroxide, ammonium acetate, acetic acid, [12C6]-glucose (≥99.5%) and [13C6]-glucose (99 atom % 13C) were purchased from Sigma. Triethylammonium hydrogen carbonate buffer (TEAB, 1 M pH 8.5), iodoacetamide (IAA, ≥99%), tris-(2-carboxyethyl) phosphine hydrochloride (TCEP, 0.5 M) and sodium phosphate were from Sigma-Aldrich. Endoproteinase Glu-C from Staphylococcus aureus V8 was from Fluka. Water for chromatography LiChrosolv and acetonitrile Chromasolv for HPLC (≥99.9%) were, respectively, from Merck and Sigma. Superpure formic acid (≥99%) was purchased from Biosolve Chemicals (Valkenswaard,

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the Netherlands) as ionizing agent for liquid chromatographymass spectrometry (LC–MS) analysis.

2.2.

Procedures

according to the protocol recommended by the manufacturer, which ends with elution of peptides with 400 μL 50% ACN/0.1% formic acid. This solution was evaporated to dryness for reconstitution with 50 μL 5% ACN/0.1% formic acid.

2.2.1.

Human CSF collection

2.2.5.

Human CSF used in this study was a pool obtained from samples collected in the Hôpitaux Universitaires de Genève (HUG). Samples were obtained by lumbar puncture from three cognitively normal, aged individuals subjects (2 males at 81 and 1 male at 82). Each patient or patient's relatives gave informed consent prior to enrollment. The local institutional ethical committee board approved the clinical protocol.

2.2.2.

Glucose labeling of the human CSF

Human CSF samples were pooled for subsequent incubation with 15 mM [12C6]-glucose and [13C6]-glucose for 24 h at 37 °C depending on the approach. After incubation, both aliquots were pooled at 1:1 ratio for standardization prior to proteomic analysis. Glucose and other salts were removed by Amicon Ultra 0.5 mL filters from Millipore in order to isolate the proteins that were reconstituted in 0.5 M pH 8.5 TEAB. Protein concentration was subsequently measured using the Bradford assay with bovine serum albumin as calibration protein.

2.2.3.

Endoproteinase Glu-C enzymatic digestion of proteins

1 mg of proteins according to the Bradford assay (diluted to 400 μL TEAB) was enzymatically digested using endoproteinase Glu-C. For this, cysteine groups were reduced with 50 mM TCEP in water (10 μL) by incubation of the reaction mixtures for 60 min at 60 °C. Then, cysteine residues were alkylated with 400 mM IAA (10 μL) for 30 min in the dark at room temperature. Freshly prepared endoproteinase Glu-C (1.0 mg/mL) was added (67 μL to obtain a ratio 1:15 w/w), and the digestion was performed overnight at 37 °C. Then, digestion mixtures were evaporated under speed-vacuum and reconstituted in 50 μL mobile phase A (0.2 M NH4Ac/50 mM MgCl2 pH 8.1) for isolation of glycated peptides.

2.2.4. Enrichment of glycated peptides by boronate affinity chromatography Reconstituted peptides were fractioned by boronate affinity chromatography (BAC) by interaction between boronic acids and cis-diol groups of glycated peptides. For this purpose, the target sample (50 μL) was injected in a Waters HPLC equipped with a TSK-Gel boronate affinity column Tosoh Bioscience (7.5 cm× 7.5 mm inner diameter; 10 mm particle size) at room temperature. An isocratic chromatographic method was used for affinity separation that consists of: 1) 0–10 min 100% mobile phase A for retention of glycated peptides by esterification between boronate ligands and 1,2-cis-diol groups of sugar moieties under alkaline conditions, with elution of non-glycated peptides; 2) 10–20 min 100% mobile phase B (0.1 M HAc) for elution of glycated peptides; and 3) 20–30 min 100% mobile phase A for the equilibration of the column to the initial conditions. Both the non-glycated and the glycated fractions were collected for subsequent evaporation and reconstitution in 5% ACN/0.1% formic acid. Then, peptides were desalted and pre-concentrated prior to LC–MS/MS analysis. This was carried out with C18 microspin columns (Harvard Apparatus, Holliston, MA, USA)

LC–MS/MS analysis of peptides

Peptide digests were analyzed by electrospray ionization in positive ion mode on a hybrid linear ion trap-Orbitrap mass spectrometer (Thermo Fisher, San Jose, CA). Nanoflow HPLC was performed using a Waters NanoAquity HPLC system (Milford, MA) equipped with a helium-degasser. Peptides were trapped on a home-made 100 μm i.d.× 18 mm long pre-column packed with 200 Å (5 μ Magic C18 particles C18AQ; Michrom). Subsequent peptide separation was performed on a homemade gravity-pulled 75 μm i.d. × 150 mm long analytical column packed with 100 Å (5 μm C18AQ particles C18AQ; Michrom) and directly interfaced to the mass spectrometer. For each LC–MS/MS analysis, an estimated amount of 0.5 μg of peptides (0.1 mg/mL) was loaded on the pre-column at 3 mL/min in water/ACN (95/5 v/v) with 0.1% formic acid (v/v). After retention, peptides were eluted using an ACN gradient at 220 nL/min with: mobile phase A, water, 0.1% formic acid; mobile phase B, ACN, 0.1% formic acid. The gradient program was as follows: 0 min, A (95%), B (5%); 55 min, A (65%), B (35%); 60 min, A (15%), B (85%); 65 min, A (85%), B (15%); 75–90 min, A (95%), B (5%). The electrospray ionization voltage was applied via a liquid junction using a platinum wire inserted into a micro-tee union (Upchurch Scientific, Oak Harbor, WA) located between the pre-column and the analytical column. Ion source conditions were optimized using the tuning and calibration solution recommended by the instrument provider. Two complementary data-dependent tandem mass spectrometry methods were used for analysis of glycated proteins: MS2 with higher-energy collisional dissociation (HCD) as activation mode and MS3 by neutral loss scan with collision-induced dissociation (CID) as activation mode. In data-dependent HCDMS2 analysis, fragmentation of the three most abundant precursor ions was carried out in the collision cell attached to the C-trap (normalized collision energy 50%) followed by Orbitrap detection. The precursor-ion isolation window was set to 2.5 m/z units. MS survey scans were acquired at resolution R = 60 000 in profile mode while MS2 spectra were acquired at resolution R = 7500. Precursor ions of charge state +2 and higher were included for data-dependent selection. In cases where the charge state could not be determined, the most abundant ion was selected for HCD. Data-dependent acquisition was then performed over the entire chromatographic cycle. Datadependent CID-MS3 neutral loss scan was entirely carried out in the linear trap (except MS survey scan, detected by the Orbitrap analyzer) with three steps: (1) first fragmentation at medium collision energy (35%) to promote dissociation of the glucose moiety (−162.05 Da, that correspond to −81.02 and −54.01 m/z units for doubly and triply charged peptides, respectively) or an intermediate fragmentation of the glucose molecule (−84.04 Da, that correspond to −42.02 and −28.01 m/z units for doubly and triply charged peptides, respectively); (2) isolation of those ions in which one of the neutral losses is detected; and (3) fragmentation of the isolated peptide (35%) followed by ion-trap detection. The precursor-ion isolation window was set to 2 m/z units.

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2.2.6.

Data analysis

After data-dependent acquisition, post-acquisition workflow was initiated specifically for each MS operation mode. Peak lists were generated from raw data using the embedded software from the instrument vendor (extract_MSN.exe). For HCDMS2 experiments, the workflow was based on detection of precursor ions in an accurate way and correction for mis-assigned precursor-ion isotopes [42]. The resulting data files for both MS operation modes were searched against UniProtKB/Swiss-Prot database (Swiss-Prot Release 57.11 of November 24, 2009, 512 994 entries) using EasyProt 2.2 (BPRG, Geneva, Switzerland). No taxonomy was used for the CSF proteome and Homo sapiens was specified for database searching of CSF experiments. Common amino acid modifications for both MS operation modes were carbamidomethylation of cysteines and oxidized methionine, which were set as fixed and variable modifications, respectively. For HCD-MS2 experiments, glycation of lysine and arginine residues or on N-terminal positions (162.052 and 168.072 Da for glycated peptides with [12C6]- or [13C6]-glucose) was selected as variable modification. For MS3 neutral loss experiments, a variable modification as a consequence of glucose fragmentation after neutral loss of 84.04 Da (78.01 Da for K, R and on N-terminal positions) was additionally specified. Endoproteinase Glu-C was selected as enzyme, with maximum three potential missed cleavages. The peptide precursor and fragment ion tolerance depended on the MS operation mode. For HCD-MS2, peptide and fragment ion tolerance was 6 ppm. This tolerance was set to 0.8 Da for fragment ions in MS3 neutral loss. For both modes, three missed cleavages were allowed in normal mode. This round was selected in “turbo” search mode. The minimum peptide length allowed was six in HCDMS2 and five in MS3 neutral loss. For HCD-MS2 experiments, the acceptance criteria were: peptide p value 1 10− 7, AC score and peptide Z-score 7.5, 7.2, 7.7 and 7.3 (specific scores regarding the analyzed samples of native CSF; native CSF incubated with 15 mM and 30 mM [13C6]-glucose; and CSF incubated with 15 mM [12C6]-glucose and [13C6]-glucose respectively), corresponding to an estimated false discovery ratio (FDR) of less than 5%. For MS3 in neutral loss experiments, these parameters were changed to peptide p value 1 10− 7, AC score and peptide Zscore 7.6, 7.8, 8.3 and 7.3 (scores corresponding to samples mentioned above), corresponding to an estimated false positive ratio of less than 5%. In all cases, FDR were estimated using a reverse decoy database. This estimation was performed using separate searches in the reverse database to keep the database size constant. This involved a slight underestimation of the estimated false positive ratio [43]. All data were acquired in triplicate (three analytical injections of the same sample) and analyzed in an independent manner. Protein and peptide identification data were submitted to PRIDE.

2.2.7.

Peptide quantification

Quantitation of glycated proteins was possible as after enzymatic digestion, the resulting glycated peptides (with addition of 162 or 168 mass units) produced doublet signals in precursor MS1 scans (labeling with light and heavy glucose). The mass shift of the doublet signals depended on the peptide charge and the number of glycation sites. Peptide quantification was carried out by calculation of the ratio between peak areas from extracted ion chromatograms corresponding to

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both isotopic forms of each glycated peptide. The peptide ratios [12C6]/[13C6] were obtained from the average values of intra-run triplicates in base 2 logarithm scale. Data treatment was performed by hand. All accepted identifications from the EasyProt export report were attributed to a heavy-light pair, if such a pair could be detected (~80% of the cases).

2.2.8.

Biological data mining

Proteomics studies generate large amounts of data that need to be structured for easier interpretation and evaluation of biological relevance. In this study, data were analyzed using Gene Ontology (GO) analysis as well as Ingenuity Pathway Analysis (IPA, Ingenuity Systems, www.ingenuity.com). GO analysis of the identified glycated CSF proteins was conducted by the ArrayUnlock 1.5 program, taking as a reference the whole human proteome. All GO terms which were significant with p value <0.005 were selected as over-represented. Ingenuity system can generate the functional analysis and networks that are most significant to the data set. IPA compares proteins in the input group and displays a rank-ordered list of pathways and networks, whose activities are most likely affected. Networks are displayed graphically as nodes (proteins) and edges (the biological relationship between the nodes). Highly interconnected networks are likely to represent significant biological functions. Fisher`s exact test was used to calculate a p value determining the probability that each biological function assigned to the data set is due to change alone. These p values are calculated based on the number of proteins that participate in a given pathway relative to the total number of occurrences of these proteins in all pathway annotations stored in the Ingenuity Pathways Knowledge Base. The score is the probability that a collection of proteins equal to or greater than the number in a network could be achieved by chance alone. A score of 3 indicates that there is a 1/1000 chance that the focus proteins are in a network due to random chance. Therefore, scores of 3 or higher have a 99.9% confidence of not being generated by random chance alone.

3.

Results and discussion

Protein glycation has been increasingly recognized as one of the prominent alterations involved in neurodegenerative disorders. For this reason, recently there have been several efforts to determine whether CSF levels of AGEs could become promising biomarkers for early detection of central nervous system (CNS)-based human diseases. Numerous reports have demonstrated elevation of AGEs in neurological patients, although none of them has elucidated the true impact of these products in the pathogenesis of diseases. In that aspect, further knowledge about identity of AGEs-modified proteins has been demanded. Using MS technology, an in-depth characterization of early glycation products in normal human CSF has been here carried out. This information might be crucial for the identification of potential peptides and corresponding proteins that could be target of AGE modification during neurological diseases, since the specificity of this modification seems to be similar between the early and advanced end glycation products.

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In this study, the objective has been to report an extensive list of glycated proteins identified in human CSF with a high degree of confidence and quantify them in relative terms. For this purpose, two bottom-up proteomic approaches were carried out using a pool of CSF samples from three healthy individuals. These approaches included: (1) assessment of the native level of CSF protein glycation; and (2) prediction of the glycation state as a result of the exposure of CSF to high glucose level stimuli. The analytical workflow is schematically shown in Fig. 1.

3.1.

Assessment of the native level of CSF protein glycation

The glycation pattern of CSF proteins was investigated by a combination of endoproteinase Glu-C digestion, isolation of glycated peptides by BAC and LC–MS/MS dual analysis by MS2 and MS3 modes. The use of a MS2 mode with HCD activation and CID-MS3 by neutral loss scan was applied for identification of glycated peptides and corresponding proteins as well as elucidation of sugar attachment sites. The high accuracy in HCD-MS2 mode for precursor and fragment ions is crucial to achieve a high identification level of glycated peptides, particularly if a protease such as Glu-C is used for hydrolysis. The CID-MS3 mode is a complementary approach to HCD-MS2 as the former is particularly useful for identification of

glycated peptides with charge states (+2) and (+3) while HCD-MS2 is more suited for multi-charged peptides (z > 3). Background glycation can be reflected by the chromatographic profile as shown in Supplementary Fig. 1. It represents extracted ion chromatograms in MS2 of immonium ions calculated for glycated Lys and Arg in native CSF analyses. Because of the selectivity of immonium ions and the high accuracy of MS2 with Orbitrap detection, glycated peptides can be localized by extracting ion chromatograms in MS2. Indeed, immonium ions pinpointed the existence of glycated Lys and Arg by considering the losses detected in glycated entities by collision-based dissociation in MS2 [41]. The loss of three water molecules and the intermolecular rearrangement of the glucose moiety (−54.031 and −84.042 Da), which have been previously defined in MS fragmentation of glycated peptides, must be taken into account [44,45]. Thus, immonium-derived ions calculated for glycated Lys were at 192.102 and 162.091 Da (the most favored Lys immonium ion provides a signal at 84.081 Da, which is displaced to 246.134 Da with glucose attachment). Here, typical losses detected in glycated entities generate two signals at 192.102 and 162.091 Da (Supplementary Fig. 1.A). Similarly, immonium-derived ions for glycated Arg were at 237.135 and 207.124 Da (Supplementary Fig. 1.B). A similar profile to illustrate this background glycation can be detected by MS3 total ion extracted chromatograms

Fig. 1 – Scheme of the sample preparation and analysis processes for identification of glycated peptides.

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obtained after neutral loss due to the high selectivity of this MS operational mode. MS3 chromatograms obtained by neutral loss are complementary to illustrate background glycations since only glycated peptides are re-isolated in the ion trap for a second fragmentation step. The detected neutral loss masses shift corresponds to the cleavage of the glucose moiety (162.05 Da), dehydration of up to three water molecules (18.01, 36.02 and 54.03 Da) to form pyrylium ion, and dehydration with additional loss of a formaldehyde molecule to generate the furylium and immonium ions (84.04 Da). After this fragmentation, ions formed by loss of 162.05 and 84.04 Da are isolated in the ion trap for a second fragmentation, which generates representative MS3 spectra for identification purposes. Ions formed by the other neutral losses (18.01, 36.02 and 54.03 Da) are excluded, as they do not provide sufficient information for identification in MS3 spectra. Since these ions still contain labile parts in their structure, the generated MS3 spectra are similar to CID-MS2 spectra of glycated peptides [46]. Neutral loss analysis was carried out in the ion trap to avoid transfers of ions to the Orbitrap analyser with the subsequent decrease of sensitivity. Supplementary Fig. 2 shows this profile that complements those illustrated in Supplementary Fig. 1 as glycation fingerprint. Database searches of native glycation led to the identification of 48 glycated proteins distributed on 111 glycation sites. Supplementary Table 1 lists the different peptide sequences that were detected in glycated state under native conditions. The results are organized depending on the MS operation mode that identified each peptide. Assessment of the native level of CSF protein glycation was also carried out through the incubation of CSF samples with 15 or 30 mM [13C6]-glucose. Fig. 2 shows the Venn Diagrams of the number of glycated CSF proteins identified after application of the complementary approaches. The analysis of CSF treated with 15 or 30 mM [13C6]-glucose led to the identification of 79 glycated proteins with detection of 196 glycation sites. This enhancement in the detection capability was supported by the identification of peptides labeled with [13C6]-glucose, which produced doublet signals in MS scan. In overall terms, the combination of approaches allowed the identification of 113 glycated proteins and 263 sugar attachment sites, with a false discovery rate of 5% as determined by the EasyProt program. Among all glycated proteins identified, 20% of them were identified by two or more unique peptides, indicating a comprehensive coverage of the glycated proteome in the CSF. The remaining proteins (80%) were identified with single unique peptides. As shown in Supplementary Table 2 (list of native glycation data detected with the approaches 1 and 2), most of these glycation targets were located in relatively abundant proteins such as albumin, transferrin, and haptoglobin beta chain with 44, 17, and 12 glycation sites, respectively. Special attention was given to the determination of glycated proteins from non-CSF origin. For example the albumin, alpha-1-antitrypsin, and apolipoprotein A-I are of plasma origin, whereas transthyretin is 90% expressed by choroid plexus epithelial cells [47] and PGDS derives exclusively from brain tissues [48,49]. These findings validate the assumption of Shuvaev et al. who stated that the origin of glycated proteins in the CSF is not clear and the exact place where the glycation occurs is not known, but

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can include potentially brain, plasma and/or CSF. At that point, it is well known the high dynamic range of CSF protein concentration. The dominance of particular proteins like immunoglobulins or albumin leads to a reduced detection capability of low abundant proteins by conventional techniques such as 2D-PAGE and mass spectrometry. Therefore, for a more effective coverage of low abundance proteins [50], enrichment of modified peptides was performed by boronate affinity chromatography. In the future, to enhance the CSF proteome coverage the implementation of separation techniques designed for selective depletion of high-abundance plasma proteins in CSF would be recommended. Despite the high abundance of blood-derived proteins in CSF, the strategy used here was efficient to detect some low abundance brain species. In particular, the method was able to detect either proteins known to be specifically expressed in the central nervous system (e.g. receptor-type tyrosine-protein phosphatase zeta, K864; and neuronal growth regulator 1, K194) and proteins widely expressed, with highest level in brain (e.g. Dickkopf-related protein 3, K43; protein kinase C and casein kinase substrate in neurons protein 1, R241; and WW domain-binding protein 11, R82). The detection of several enzymes and transcription factors like protein-tyrosine phosphatase mitochondrial 1 (K1/R8) and zinc finger and BTB domain-containing protein 16 (L99) was also of particular interest. Results of this study therefore suggest that the protein glycation pattern of CSF may potentially provide a window into the overall profile of the glycated brain proteome.

3.2. Predictive analysis of glycated CSF proteins by in vitro high glucose incubation For predictive analysis of CSF protein glycation, differential labeling with [12C6]-glucose and [13C6]-glucose method was applied to the pooled human CSF samples. The approach enabled to predict the influence of 15 mM and 30 mM glucose stimuli by detection of [13C6]-glucose labeled peptides. Only preferential glycation targets are labeled due to the chemo-selectivity of the process. Taken together, 122 glycated proteins were detected as shows Fig. 2. Corresponding information is collected in Supplementary Table 3. As compared to the analysis based on native glycation, 101 previously undiscovered glycated proteins were identified. In addition, a total number of 278 glycation sites were selectively detected from the in vitro glycated human CSF. A clear impact of high glucose concentration on the glycated CSF proteome was highlighted. While native CSF albumin was found to be glycated in 30 positions, the same protein under in vitro approach was modified in 47 glycation sites. These results support the need for quantitative analysis to elucidate the mechanisms involved in glycation reaction. For this purpose, current work has implemented the assessment of glycation levels in the identification analysis, including quantitative measurements for each glycation site identified. These data are in section “Quantitative assessment of glycated CSF proteins”. Particularly noteworthy were the identifications that did not overlap among the different approaches. As expected, glycation targets selectively found in the in vitro glycated CSF are a consequence of the artificial modification with high glucose concentration and, therefore, they represent potential amino groups prone to glycation under “glucotoxic” perturbation.

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Fig. 2 – Venn diagram depicting the relative comparison of unique glycated CSF proteins identified from approach 1 (pool of native glycated CSF samples), approach 2 (pool of native CSF samples incubated with 15 or 30 mM [13C6]-glucose) and approach 3 (pool of CSF samples incubated with 15 mM [12C6]-glucose and [13C6]-glucose). The number of sugar attachment sites is indicated as well.

Simultaneously, differences of the glycation pattern in human CSF may be related with structural changes associated to the glucose level; that is, presence of dominant modifications depending on the glycation level. One evidence that supports this fact is the detection in human serum albumin of residues (K199) modified by a fructosyl-lysine adduct in the early stages of glycation, while a pyrraline adduct was found at this site during later stages of glycation [51]. It should be emphasized that most of the glycated proteins detected here are not annotated as glycation-modified proteins by the UniprotKB database (http://www.uniprot.org/). Only complement factor B Bb fragment, apolipoprotein A-I, albumin, and beta-2-microglobulin are annotated as glycated proteins.

3.3.

Quantitative assessment of glycated CSF proteins

Qualitative identification of glycated CSF proteins was complemented by quantitative results. The isotopic labeling technique used in this analysis is based on the differential labeling of proteins with [12C6]-glu and [13C6]-glucose. A mass difference of 6 Da is produced for each labeling pair and glycation site. The reaction is reproducible and has been shown to be quantitative by studies of protein glycation in human plasma and hemolysates [40,41]. At the MS1 scan level, it is important to note that peptides labeled with “heavy” glucose are considered as internal standards. These isotopic forms specifically mimic physiological conditions since glycation is a chemoselective process. Simultaneously, the signals generated by glycated peptides with “light” glucose are indicative of the native concentration. Given a glycated peptide producing a doublet signal in MS scan, calculation of the ratio between peak areas corresponding to the peptides labeled with [12C6]- and

[13C6]-glucose enables to provide quantitative information in relative terms. In the present work, this strategy was useful for the relative estimation of the extent of CSF glycation at each potential attachment site, under two levels of glucose: native and as result of in vitro stimuli with glucose. Table 1 lists all quantified glycated peptides for the native human CSF. Fig. 3.A compares the glycation reactivity for 77 modified sites as a function of areas ratio in logarithm scale of the extracted chromatograms. The resulting graph provides structural information about localization of preferential glycation sites that is of great interest to clarify their biological role on the protein function. It can be deduced from this representation that the preferential glycation sites for prostaglandin D2 synthase (K138) as well as for other CSF/CNS proteins such as transthyretin (K76 and K80), receptor type tyrosine-protein phosphatase zeta (K864) or neuronal growth regulator 1 (K194). Notably, there were many preferential glycation sites targeted at plasma proteins such as albumin (K159, K233, K240, K389, K525, K573, and K574), haptoglobin beta chain (K113, K118, K123, K136, and K141), and transferrin (R352, K354, and K365). Previous studies already reported some of these localizations as preferential sites for early glycation in native human plasma proteins using the same methodology [41]. For example, Lys residues located at positions 233, 240 and 525 have been quantitatively described as preferential glycation sites for human serum albumin. Because glycation levels have been estimated with different concentrations of the internal standard from that used in this study, no comparison between glycation efficiency of those preferential glycation sites in human plasma and cerebrospinal fluid can be carried out. However, considering the most significant glycation sites detected in each body fluid, some differences were found with

Table 1 – Glycated proteins identified in human CSF under native and in vitro perturbances with 15 mM glucose, with information about the glycation sites and m/z value of the precursor ion corresponding to the glycated peptides. Quantitative data are based on peak area ratio in logarithmic scale between 12C6- and 13C6-glucose labeled peptides with standard deviation estimated by measurement of three analytical replicates. Identified unique proteins highlighted in green and glycation sites in red. Protein number

Analysis

AC

ID

Description

Glycation sites Peptide sequence

Position

Prec m/z

Prec Charge

Mean Peak area ratio at Gly-Site ±SD

Native glycation

P00441_CHAIN_0

SODC_HUMAN Superoxide dismutase [Cu-Zn] [CHAIN 0]

K9

ATKAVCVLKGDGPVQGIINFE

1-21

809.432

3

0.818

±

0.013

Predictive glycation

P00441_CHAIN_0

SODC_HUMAN Superoxide dismutase [Cu-Zn] [CHAIN 0]

K9

ATKAVCVLKGDGPVQGIINFE

1-21

807.422

3

1.014

±

0.002

2

Native glycation

P00738

HPT_HUMAN

Haptoglobin beta chain

K53

HSVRYQCKNYYKLRTE

46-61

577.537

4

0.839

±

0.019

2

Predictive glycation

P00738_CHAIN_0

HPT_HUMAN

Haptoglobin beta chain [CHAIN 0]

K94

HSVRYQCKNYYKLRTE

87-102

769.7142

3

1.020

±

0.009

2

Predictive glycation

P00738_CHAIN_0

HPT_HUMAN

Haptoglobin beta chain [CHAIN 0]

K98

HSVRYQCKNYYKLRTE

87-102

577.537

4

1.023

±

0.009

2

Native glycation

P00738_CHAIN_0

HPT_HUMAN

Haptoglobin beta chain [CHAIN 0]

K113

KQWINKAVGDKLPECE

113-128

665.42

3

0.856

±

0.001

2

Predictive glycation

P00738_CHAIN_0

HPT_HUMAN

Haptoglobin beta chain [CHAIN 0]

K113

KQWINKAVGDKLPE

113-126

894.9863

2

1.022

±

0.004

2

Native glycation

P00738_CHAIN_0

HPT_HUMAN

Haptoglobin beta chain [CHAIN 0]

K118

KQWINKAVGDKLPECE

113-128

695.023

3

0.855

±

0.003

2

Native glycation

P00738_CHAIN_0

HPT_HUMAN

Haptoglobin beta chain [CHAIN 0]

K123

KQWINKAVGDKLPECE

113-128

695.022

3

0.855

±

0.004

2

Native glycation

P00738

HPT_HUMAN

Haptoglobin beta chain

K136

KQWINKAVGDKLPECE

131-146

693.015

3

0.856

±

0.002

2

Native glycation

P00738

HPT_HUMAN

Haptoglobin beta chain

K141

KQWINKAVGDKLPECE

131-146

693.014

3

0.856

±

0.002

2

Native glycation

P00738_CHAIN_0

HPT_HUMAN

Haptoglobin beta chain [CHAIN 0]

K252

RVMPICLPSKDYAE

243-256

616.308

3

0.828

±

0.012

2

Predictive glycation

P00738_CHAIN_0

HPT_HUMAN

Haptoglobin beta chain [CHAIN 0]

K252

RVMPICLPSKDYAE

243-256

920.9476

2

1.016

±

0.009

3

Native glycation

P00751_CHAIN_0

CFAB_HUMAN Complement factor B Bb fragment [CHAIN 0]

K594

GTTRALRLPPTTTCQQQKEE

577-596

621.569

4

0.841

±

0.018

3

Native glycation

P00751_CHAIN_0

CFAB_HUMAN Complement factor B Bb fragment [CHAIN 0]

R583

GTTRALRLPPTTTCQQQKEE

577-596

828.427

3

0.835

±

0.017

4

Native glycation

P01019_CHAIN_0

ANGT_HUMAN Angiotensin-3 (Ang III) [CHAIN 0]

K415

ADEREPTESTQQLNKPEVLE

401-420

827.741

3

0.835

±

0.014

4

Predictive glycation

P01019_CHAIN_0

ANGT_HUMAN Angiotensin-3 (Ang III) [CHAIN 0]

K415

LEADEREPTESTQQLNKPE

399-417

792.709

3

1.015

±

0.005

5

Native glycation

P01023_CHAIN_0

A2MG_HUMAN Alpha-2-macroglobulin (Alpha-2-M) [CHAIN 0]

K5

SVSGKPQYMVLVPSLLHTE

1-19

751.734

3

0.861

±

0.036

6

Native glycation

P01834

IGKC_HUMAN

Ig kappa chain C region

K99

VTHQGLSSPVTKSFNRGEC

88-106

758.041

3

0.857

±

0.007

6

Predictive glycation

P01834

IGKC_HUMAN

Ig kappa chain C region

K99

VTHQGLSSPVTKSFNRGEC

88-106 1136.556

2

1.014

±

0.003

7

Native glycation

P01857

IGHG1_HUMAN Ig gamma-1 chain C region

K129

LLGGPSVFLFPPKPKDTLMISRTPE

117-141

727.907

4

0.881

±

0.011

7

Native glycation

P01857

IGHG1_HUMAN Ig gamma-1 chain C region

K131

LLGGPSVFLFPPKPKDTLMISRTPE

117-141

940.67

3

0.888

±

0.010

7

Native glycation

P01860

IGHG3_HUMAN Ig gamma-3 chain C region

K178

LLGGPSVFLFPPKPKDTLMISRTPE

164-188

940.67

3

0.888

±

0.010

8

Native glycation

P01876

IGHA1_HUMAN Ig alpha-1 chain C region

K212

SKTPLTATLSKSGNTFRPE

211-229

735.06

3

0.854

±

0.015

8

Predictive glycation

P01876

IGHA1_HUMAN Ig alpha-1 chain C region

K212

SKTPLTATLSKSGNTFRPE

211-229

733.051

3

1.019

±

0.001

9

Native glycation

P02675_CHAIN_0

FIBB_HUMAN

K195

YCRTPCTVSCNIPVVSGKECEE

178-199

938.417

3

0.850

±

0.018

10

Native glycation

P02749_CHAIN_0

APOH_HUMAN Beta-2-glycoprotein 1 (Apo-H) (B2GPI) (Beta(2)GPI) [CHAIN 0]

K317

HSSLAFWKTDASDVKPC

310-326

706.341

3

0.858

±

0.010

10

Predictive glycation

P02749_CHAIN_0

APOH_HUMAN Beta-2-glycoprotein 1 (Apo-H) (B2GPI) (Beta(2)GPI) [CHAIN 0]

K317

HSSLAFWKTDASDVKPC

310-326

704.331

3

1.014

±

0.003

10

Predictive glycation

P02749_CHAIN_0

APOH_HUMAN Beta-2-glycoprotein 1 (Apo-H) (B2GPI) (Beta(2)GPI) [CHAIN 0]

K19

GRTCPKPDDLPFSTVVPLKTFYEPGEE

1-27

1081.198

3

1.011

±

0.020

10

Predictive glycation

P02749_CHAIN_0

APOH_HUMAN Beta-2-glycoprotein 1 (Apo-H) (B2GPI) (Beta(2)GPI) [CHAIN 0]

K324

HSSLAFWKTDASDVKPC

11

Native glycation

P02768_CHAIN_0

ALBU_HUMAN Serum albumin [CHAIN 0]

K51

11

Predictive glycation

P02768_CHAIN_0

ALBU_HUMAN Serum albumin [CHAIN 0]

11

Native glycation

P02768_CHAIN_0

11

Predictive glycation

11

Native glycation

11

Predictive glycation

P02768_CHAIN_0

11

Native glycation

11

Fibrinopeptide B [CHAIN 0]

310-326

704.3304

3

1.014

±

0.003

FAKTCVADE

49-57

601.7684

2

0.828

±

0.008

K51

FAKTCVADESAE

49-60

745.3249

2

1.013

±

0.003

ALBU_HUMAN Serum albumin [CHAIN 0]

K64

NCDKSLHTLFGDKLCTVATLRE

61-82

687.345

4

0.879

±

0.013

P02768_CHAIN_0

ALBU_HUMAN Serum albumin [CHAIN 0]

K64

NCDKSLHTLFGDKLCTVATLRE

61-82

550.077

5

1.016

±

0.003

P02768_CHAIN_0

ALBU_HUMAN Serum albumin [CHAIN 0]

K73

NCDKSLHTLFGDKLCTVATLRE

61-82

687.346

4

0.874

±

0.008

ALBU_HUMAN Serum albumin [CHAIN 0]

K73

NCDKSLHTLFGDKLCTVATLRE

61-82

914.115

3

1.015

±

0.002

P02768_CHAIN_0

ALBU_HUMAN Serum albumin [CHAIN 0]

K93

TYGEMADCCAKQEPERNE

83-100

791.323

3

0.840

±

0.008

Predictive glycation

P02768_CHAIN_0

ALBU_HUMAN Serum albumin [CHAIN 0]

K93

MADCCAKQEPERNE

87-100

635.93

3

1.018

±

0.005

11

Native glycation

P02768_CHAIN_0

ALBU_HUMAN Serum albumin [CHAIN 0]

K106

CFLQHKDDNPNLPRLVRPE

101-119

504.06

5

0.864

±

0.007

11

Predictive glycation

P02768_CHAIN_0

ALBU_HUMAN Serum albumin [CHAIN 0]

K106

CFLQHKDDNPNLPRLVRPE

101-119

504.059

5

1.012

±

0.002

11

Native glycation

P02768_CHAIN_0

ALBU_HUMAN Serum albumin [CHAIN 0]

K136

TFLKKYLYE

133-141

683.8636

2

0.884

±

0.003

11

Predictive glycation

P02768_CHAIN_0

ALBU_HUMAN Serum albumin [CHAIN 0]

K136

TFLKKYLYE

133-141

642.04

2

1.011

±

0.001

11

Native glycation

P02768_CHAIN_0

ALBU_HUMAN Serum albumin [CHAIN 0]

K159

LLFFAKRYKAAFTE

154-167

934.507

2

0.889

±

0.003

11

Predictive glycation

P02768_CHAIN_0

ALBU_HUMAN Serum albumin [CHAIN 0]

R160

LLFFAKRYKAAFTE

154-167

934.0059

2

1.018

±

0.003

11

Native glycation

P02768_CHAIN_0

ALBU_HUMAN Serum albumin [CHAIN 0]

K174

CCQAADKAACLLPKLDE

168-184

711.002

3

0.851

±

0.009

11

Predictive glycation

P02768_CHAIN_0

ALBU_HUMAN Serum albumin [CHAIN 0]

K174

CCQAADKAACLLPKLDE

168-184

708.9927

3

1.015

±

0.005

J O U RN A L OF P ROT EO M I CS 7 5 ( 2 0 12 ) 47 6 6 –4 78 2

1 1

(continued on next page)

4773

Native glycation

Predictive glycation

Predictive glycation

Native glycation

Predictive glycation

Native glycation

Predictive glycation

Native glycation

Predictive glycation

Predictive glycation

Predictive glycation

Predictive glycation

Native glycation

Predictive glycation

Native glycation

Predictive glycation

Native glycation

Predictive glycation

Native glycation

Predictive glycation

Native glycation

Predictive glycation

Native glycation

Predictive glycation

Native glycation

Predictive glycation

Predictive glycation

Native glycation

Predictive glycation

Native glycation

Predictive glycation

Native glycation

Predictive glycation

Native glycation

Predictive glycation

Native glycation

Predictive glycation

Native glycation

Predictive glycation

Native glycation

Predictive glycation

Native glycation

Predictive glycation

Native glycation

Predictive glycation

Native glycation

Predictive glycation

Native glycation

Native glycation

Predictive glycation

Native glycation

Native glycation

Native glycation

Predictive glycation

Predictive glycation

Native glycation

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

11

12

12

12

12

P02774_CHAIN_0

P02774_ISOFORM_2

P02774_CHAIN_0

P02774_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

P02768_CHAIN_0

VTDB_HUMAN Vitamin D-binding protein (DBP) (VDB) [CHAIN 0]

VTDB_HUMAN Vitamin D-binding protein (DBP) (VDB) [ISOFORM 2]

VTDB_HUMAN Vitamin D-binding protein (DBP) (VDB) [CHAIN 0]

VTDB_HUMAN Vitamin D-binding protein (DBP) (VDB) [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

ALBU_HUMAN Serum albumin [CHAIN 0]

K386

K280

K276

K276

I142-E153

K574

K573

K573

K564

K545

K525

K519

K519

K475

K475

K466

LSSFIDKGQE

LSSFIDKGQE

HTVKLCDNLSTKNSKFEDCCQE

HTVKLCDNLSTKNSKFEDCCQE

IARRHPYFYAPE

GKKLVAASQAALGL

GKKLVAASQAALGL

GKKLVAASQAALGL

KCCKADDKETCFAEE

QLKAVMDDFAAFVE

KERQIKKQTALVE

TFTFHADICTLSEKE

TFTFHADICTLSEKE

KTPVSDRVTKCCTE

KTPVSDRVTKCCTE

KTPVSDRVTKCCTE

KTPVSDRVTKCCTE

AKRMPCAEDYLSVVLNQLCVLHE

K444 K466

AKRMPCAEDYLSVVLNQLCVLHE

VSRNLGKVGSKCCKHPE

VSRNLGKVGSKCCKHPE

VSRNLGKVGSKCCKHPE

VSRNLGKVGSKCCKHPE

VSRNLGKVGSKCCKHPE

FKPLVEEPQNLIKQNCE

FKPLVEEPQNLIKQNCE

FKPLVEEPQNLIKQNCE

TTLEKCCAAADPHECYAKVFDE

TTLEKCCAAADPHECYAKVFDE

KCCAAADPHECYAKVFDE

AKDVFLGMFLYE

AKDVFLGMFLYE

FVESKDVCKNYAE

NQDSISSKLKE

NQDSISSKLKE

NQDSISSKLKE

CADDRADLAKYICE

CADDRADLAKYICE

VSKLVTDLTKVHTECCHGDLLE

FAEVSKLVTDLTKVHTE

FAEVSKLVTDLTKVHTE

FAEVSKLVTDLTKVHTE

RAFKAWAVARLSQRFPKAE

RAFKAWAVARLSQRFPKAE

RAFKAWAVARLSQRFPKAE

RAFKAWAVARLSQRFPKAE

LRDEGKASSAKQRLKCASLQKFGE

LRDEGKASSAKQRLKCASLQKFGE

LRDEGKASSAKQRLKCASLQKFGE

LRDEGKASSAKQRLKCASLQKFGE

LRDEGKASSAKQRLKCASLQKFGE

LRDEGKASSAKQRLKCASLQKFGE

LRDEGKASSAKQRLKCASLQKFGE

LRDEGKASSAKQRLKCASLQKFGE

CCQAADKAACLLPKLDE

CCQAADKAACLLPKLDE

K444

K436

K436

K432

K432

R428

K389

K378

K378

K372

K372

K359

K323

K323

K313

K276

K274

K274

K262

K262

K240

K240

K233

K233

R218

R218

K212

R209

R197 K199

K199

K199

R197

R197

K195

K195

K190

K181

K181

711.002

957.171

575.91

574.706

575.91

574.706

575.91

718.129

2

805.8885

752.053

926.399

928.406

380-389

274-283

265-286

265-286

142-153

572-585

572-585

572-585

557-571

543-556

519-531

506-520

506-520

466-479

466-479

466-479

466-479

443-465

443-465

426-442

426-442

426-442

426-442

426-442

377-393

601.53

643.3121

959.096

719.571

760.71

747.949

745.4394

703.08

686.957

873.4225

578.334

983.958

656.308

614.959

616.969

924.945

616.968

969.81

733.116

530.268

531.775

425.621

531.775

530.268

750.045

377-393 1124.564

377-393

355-376

355-376

2

2

3

4

2

2

2

2

3

2

3

2

3

3

3

2

3

3

4

4

4

5

4

4

3

2

3

3

3

2

2

2

2

2

2

2

3

3

3

3

4

3

5

3

4

3

3

5

5

5

5

5

4

2

3

764.16

876.4023

705.8557

705.8546

705.8557

934.411

623.28

906.114

695.71

695.708

522.034

798.776

479.8629

798.775

599.333

359-376 1166.983

322-333

322-333

309-321

267-277

267-277

267-277

253-266

253-266

231-252

228-244

228-244

228-244

209-227

209-227

209-227

209-227

185-208 1013.192

185-208

185-208

185-208

185-208

185-208

185-208

185-208

168-184 1062.986

168-184

0.884

1.006

1.014

0.894

0.859

0.891

1.014

0.890

0.825

1.011

0.923

1.013

0.875

1.011

0.840

1.012

0.840

1.021

0.826

1.020

0.823

1.020

0.823

1.015

0.887

1.012

0.884

1.014

0.863

1.012

1.008

0.851

1.036

0.845

1.016

0.845

1.017

0.866

1.020

0.891

1.022

0.904

1.010

0.860

1.011

1.011

1.031

1.014

0.857

1.013

0.857

1.013

0.857

1.013

1.013

0.857

0.000 0.000 0.050

±

0.000

0.104

0.001 ±

±

0.010 ±

±

0.015 ±

±

0.038 ±

0.001

0.002 ±

0.001

0.002 ±

±

0.000 ±

±

0.006 ±

0.001

0.002

0.019 ±

0.006

0.003 ±

±

0.018 ±

±

0.004 ±

±

0.002 ±

0.010

0.004 ±

0.003

0.006 ±

±

0.004

±

0.006 ±

0.000

0.003

0.008 ±

±

0.002 ±

±

0.008 ±

±

0.004 ±

0.001

0.008 ±

0.004

0.001 ±

±

0.009

±

0.008 ±

0.001

±

0.010

0.014

±

±

0.001

±

±

0.010

±

0.005

0.000

±

±

0.010

±

±

0.000

±

0.001

0.010

±

0.004

0.000

±

±

0.004

±

±

0.008

±

4774 J O U RN A L OF P ROT EO M IC S 7 5 ( 2 0 12 ) 47 6 6 –47 8 2

Table 1 (continued) Protein number

Analysis

AC

ID

Description

Glycation sites Peptide sequence

Position

Prec m/z

Prec Charge

Mean Peak area ratio at Gly-Site ±SD

13

Native glycation

P02787_CHAIN_0

TRFE_HUMAN

Serotransferrin (Transferrin) [CHAIN 0]

K4

VPDKTVRWCAVSEHE

1-15

990.98

2

0.824

±

0.003

13

Predictive glycation P02787_CHAIN_0

TRFE_HUMAN

Serotransferrin (Transferrin) [CHAIN 0]

K4

VPDKTVRWCAVSEHE

1-15

658.982

3

1.015

±

0.003

13

Native glycation

P02787_CHAIN_0

TRFE_HUMAN

Serotransferrin (Transferrin) [CHAIN 0]

K78

AYLAPNNLKPVVAE

70-83

831.4464

2

0.853

±

0.005

13

Predictive glycation P02787_CHAIN_0

TRFE_HUMAN

Serotransferrin (Transferrin) [CHAIN 0]

K78

AYLAPNNLKPVVAE

70-83

789.16

2

1.014

±

0.000

13

Native glycation

P02787_CHAIN_0

TRFE_HUMAN

Serotransferrin (Transferrin) [CHAIN 0]

R352

RLKCDEWSVNSVGKIE

352-367 696.686

3

0.869

±

0.007

13

Predictive glycation P02787_CHAIN_0

TRFE_HUMAN

Serotransferrin (Transferrin) [CHAIN 0]

R352

RLKCDEWSVNSVGKIE

352-367 694.6763

3

1.013

±

0.008

Native glycation

P02787_CHAIN_0

TRFE_HUMAN

Serotransferrin (Transferrin) [CHAIN 0]

K354

RLKCDEWSVNSVGKIE

352-367 696.687

3

0.875

±

0.009

Native glycation

P02787_CHAIN_0

TRFE_HUMAN

Serotransferrin (Transferrin) [CHAIN 0]

K365

RLKCDEWSVNSVGKIE

352-367 696.687

3

0.869

±

0.013

352-367 694.679

3

1.014

±

0.000

4

1.016

±

0.000

±

0.004 0.000

13

Predictive glycation P02787_CHAIN_0

TRFE_HUMAN

Serotransferrin (Transferrin) [CHAIN 0]

K365

RLKCDEWSVNSVGKIE

13

Predictive glycation P02787_CHAIN_0

TRFE_HUMAN

Serotransferrin (Transferrin) [CHAIN 0]

K545

KGDVAFVKHQTVPQNTGGKNPDPWAKNLNEKDYE 527-560

13

Native glycation

P02787_CHAIN_0

TRFE_HUMAN

Serotransferrin (Transferrin) [CHAIN 0]

R568

LLCLDGTRKPVEE

561-573 804.63

2

0.856

561-573 845.9156

997.495

2

1.009

±

669.8326

2

0.856

±

0.002

VKKYVLPNFE

214-223 699.8798

2

1.011

±

0.000

K194

IKSGTVTPGRSGLIRCE

193-209 500.522

4

0.798

±

0.032

K875 R885

TTKEVEMMKAAYRKE

873-887 541.019

4

0.761

±

0.000

708.3332

2

0.880

±

0.000

726.3809

2

0.856

±

0.005

9-23

641.645

3

0.851

±

0.016

RKTLLSNLEE

45-54

640.326

2

0.840

±

0.004

ILSVDCSTNNPSQAKLRRE

81-99

588.299

4

0.844

±

0.006

286-307 905.122

3

0.847

±

0.005

13

Predictive glycation P02787_CHAIN_0

TRFE_HUMAN

Serotransferrin (Transferrin) [CHAIN 0]

K569

LLCLDGTRKPVEE

14

Native glycation

P0C0L4_CHAIN_2

CO4A_HUMAN

Complement C4 gamma chain [CHAIN 2]

K6

NVNFQKAINE

14

Predictive glycation P0C0L4_CHAIN_0

CO4A_HUMAN

Complement C4 gamma chain [CHAIN 0]

K215

15

Native glycation

Q7Z3B1_CHAIN_0

NEGR1_HUMAN Neuronal growth regulator 1 [CHAIN 0]

16

Native glycation

Q92574

TSC1_HUMAN

Hamartin

17

Native glycation

Q96L15_ISOFORM_2

NAR5_HUMAN

Ecto-ADP-ribosyltransferase 5 [ISOFORM 2]

T38-E48

TYVGCAEEMEE

38-48

18

Native glycation

P01034_CHAIN_0

CYTC_HUMAN

Cystatin-C [CHAIN 0]

G22-E33

GVRRALDFAVGE

22-33

19

Native glycation

P10909_CHAIN_0

CLUS_HUMAN

Clusterin alpha chain [CHAIN 0]

K18

LQEMSNQGSKYVNKE

19

Native glycation

P10909_CHAIN_1

CLUS_HUMAN

Clusterin alpha chain [CHAIN 1]

K46

19

Native glycation

P10909_CHAIN_2

CLUS_HUMAN

Clusterin alpha chain [CHAIN 2]

K95

19

Native glycation

P10909_CHAIN_0

CLUS_HUMAN

Clusterin alpha chain [CHAIN 0]

K300

ILSVDCSTNNPSQAKLRRELDE

20

Native glycation

P23471_ISOFORM_Short PTPRZ_HUMAN Receptor-type tyrosine-protein phosphatase zeta (R-PTP-zeta) [ISOFORM Short]

K864

FETLKEFYQE

860-869 748.3851

2

0.875

±

0.006

20

Predictive glycation P23471_ISOFORM_Short PTPRZ_HUMAN Receptor-type tyrosine-protein phosphatase zeta (R-PTP-zeta) [ISOFORM Short]

K864

FETLKEFYQE

860-869 706.53

2

1.015

±

0.000

1-10

21

Native glycation

P41222_CHAIN_0

PTGDS_HUMAN Prostaglandin-H2 D-isomerase (PGD2 synthase) (PGDS) [CHAIN 0]

K138

LKEKFTAFCKAQGFTE

137-152 662.09

3

0.910

±

0.077

21

Native glycation

P41222_CHAIN_0

PTGDS_HUMAN Prostaglandin-H2 D-isomerase (PGD2 synthase) (PGDS) [CHAIN 0]

K140

KFTAFCKAQGFTE

140-152 848.8997

2

0.847

±

0.004

21

Predictive glycation P41222_CHAIN_0

PTGDS_HUMAN Prostaglandin-H2 D-isomerase (PGD2 synthase) (PGDS) (PGDS2) [CHAIN 0]

K140

KFTAFCKAQGFTE

140-152 807.08

2

1.014

±

0.005

21

Native glycation

P41222_CHAIN_0

PTGDS_HUMAN Prostaglandin-H2 D-isomerase (PGD2 synthase) (PGDS) [CHAIN 0]

K146

KFTAFCKAQGFTE

140-152 566.269

3

0.850

±

0.003

22

Native glycation

Q684P5_ISOFORM_3

RPGP2_HUMAN Rap1 GTPase-activating protein 2 (Rap1GAP2) [ISOFORM 3]

M43-E54

MLEKMQGIKLEE

43-54

740.68

2

0.858

±

0.003

23

Native glycation

P02766_CHAIN_0

TTHY_HUMAN Transthyretin [CHAIN 0]

K76

IDTKSYWKALGISPFHE

73-89

720.708

3

0.838

±

0.010

23

Predictive glycation P02766_CHAIN_0

TTHY_HUMAN Transthyretin [CHAIN 0]

K76

IDTKSYWKALGISPFHE

73-89

718.698

3

1.012

±

0.018

23

Native glycation

P02766_CHAIN_0

TTHY_HUMAN Transthyretin [CHAIN 0]

K80

IDTKSYWKALGISPFHE

73-89

720.707

3

0.841

±

0.009

23

Predictive glycation P02766_CHAIN_0

TTHY_HUMAN Transthyretin [CHAIN 0]

K80

IDTKSYWKALGISPFHE

73-89

539.278

4

1.006

±

0.017

24

Predictive glycation P01009_ISOFORM_3

A1AT_HUMAN

K153

GLKLVDKFLE

147-156 662.3759

2

1.019

±

0.003

291-301 746.4024

0.004

Short peptide from AAT (SPAAT) [ISOFORM 3]

2

1.033

±

2

1.022

±

0.011

2

1.010

±

0.000

822.948

4

1.031

±

0.017

957.171

3

1.021

±

0.006

53-60

545.2675

3

0.995

±

0.025

29-37

578.36

2

1.011

±

0.000

61-73

740.43

24

Predictive glycation P01009_ISOFORM_3

A1AT_HUMAN

Short peptide from AAT (SPAAT) [ISOFORM 3]

K298

LTHDIITKFLE

25

Predictive glycation P01024_CHAIN_3

CO3_HUMAN

Complement C3c alpha' chain fragment 2 [CHAIN 3]

K50

ACKKVFLDCCNYITE

26

Predictive glycation P01861

IGHG4_HUMAN Ig gamma-4 chain C region

K101

SKYGPPCPSCPAPE

27

Predictive glycation P02647_CHAIN_1

APOA1_HUMAN Apolipoprotein A-I(1-242) [CHAIN 1]

K45

GSALGKQLNLKLLDNWDSVTSTFSKLRE

35-62

28

Predictive glycation O94985_ISOFORM_2

CSTN1_HUMAN CTF1-alpha [ISOFORM 2]

K64

NDNTVLLDPPLIALDKDAPLRFAGE

49-73

29

Predictive glycation O95801

TTC4_HUMAN

R56

IDPRENPD

30

Predictive glycation P05090_CHAIN_0

APOD_HUMAN Apolipoprotein D (Apo-D) (ApoD) [CHAIN 0]

K31

IEKIPTTFE

30

Predictive glycation P05090_CHAIN_0

APOD_HUMAN Apolipoprotein D (Apo-D) (ApoD) [CHAIN 0]

R62

LRADGTVNQIEGE

31

Predictive glycation P43652_CHAIN_0

AFAM_HUMAN Afamin (Alpha-Alb) [CHAIN 0]

K298

RGQCIINSNKDDRPKDLSLRE

32

Predictive glycation P49454_CHAIN_0

CENPF_HUMAN Centromere protein F (CENP-F) [CHAIN 0]

R1218 K1220

AMLRNKE

K104

NACHCSEDCLARGDCCTNYQVVCKGE

R380

KPYECKQCGKAFTWSSTFRE

362-381 893.41 195-201 545.2675 99-114 959.9131 191-197 571.2828

Tetratricopeptide repeat protein 4 (TPR repeat protein 4)

33

Predictive glycation Q13822_CHAIN_0

ENPP2_HUMAN

34

Predictive glycation Q68EA5

ZNF57_HUMAN Zinc finger protein 57

Ectonucleotide pyrophosphatase/phosphodiesterase family member 2 (E-NPP 2) (LysoPLD) [CHAIN 0]

35

Predictive glycation Q8IZP6

R113B_HUMAN RING finger protein 113B

K200

ICKDYKE

36

Predictive glycation Q969K4_ISOFORM_1

ABTB1_HUMAN Ankyrin repeat and BTB/POZ domain-containing protein 1 [ISOFORM 1]

R112

MALLADCALPPELRGD

37

Predictive glycation Q9H4T2

ZSC16_HUMAN Zinc finger and SCAN domain-containing protein 16

K194 K196

DMPKDKE

48-62

1041.965

100-113 854.868

2

1.021

±

0.000

289-309 669.842

4

1.022

±

0.006

1215-1221 545.2802

3

0.975

±

0.000

4

1.018

±

0.000

3

1.012

±

0.000

3

1.018

±

0.000

2

1.024

±

0.000

2

1.012

±

0.000

81-106 832.074

J O U RN A L OF P ROT EO M I CS 7 5 ( 2 0 12 ) 47 6 6 –4 78 2

13 13

4775

4776

J O U RN A L OF P ROT EO M IC S 7 5 ( 2 0 12 ) 47 6 6 –47 8 2

Fig. 3 – Glycation affinity of the different sites identified in glycated proteins found in native CSF (A) and in vitro treated CSF (B).

respect to targets only presents in human CSF or plasma. For example glycation on lysine 564 in albumin was uniquely detected in CSF. An identical modification of K564 has been identified in a previous study using glycated serum albumin prepared in vitro by incubation with 30.7 mmol/L [51]. Interestingly, the formed glycation adducts were fructose lysine (FL) and CML, and they were selectively found after 4 weeks of glucose incubation. In the same way, modifications on K4 and K78 in transferrin were found at CSF analysis (from native

and in vitro samples) and at Priego-Capote et al.’ plasma work (in vitro sample treated with 30 mM glucose for 24 h). Although further studies are needed, the findings of glycated CSF proteins demonstrated a higher sensitivity to glycation than did plasma proteins. Therefore, these results may offer a promising tool to distinguish potential biomarkers for glycation-associated brain diseases. Moreover, the predictive approach allowed assessing the impact of high glucose concentration on identified CSF sites. Fig. 3B

J O U RN A L OF P ROT EO M I CS 7 5 ( 2 0 12 ) 47 6 6 –4 78 2

evaluates the effect of 15 mM glucose stimuli for each glycated peptide as values of the ratio between the peak areas of the in vitro glycated peptides labeled with 15 mM [12C6]- and 15 mM [13C6]-glucose (corresponding data collected in Table 1). This graph includes a total number of 77 modified sites corresponding to 27 modified proteins. As shown, preferential glycation sites were found not only on relatively abundant plasma proteins, such as albumin (R197, K199, K233, K313, and K444), haptoglobin beta chain (K98 and K113) or alpha-1-antitrypsin (K298), but also on lower abundant brain proteins such as CTF1 alpha (K64), ankyrin repeat and BTB/POZ domain-containing protein 1 (R112), and ectonucleotide pyrophosphatase/phosphodiesterase family member 2 (K104). Overall, these results indicated increasing early glycation for the in vitro treated CSF, although no major glycation sites were highlighted at the native conditions. For targets detected at native and 15 mM glucose incubation, Supplementary Fig. 3 compares the obtained glycation levels at each

4777

protein site. As expected, exposure to glucose produced a higher extent of glycation than that reported in native CSF indicating that the impact of 15 mM glucose on CSF may increase up to 10 folds the glycation extent of native CSF proteins. As an example, Fig. 4 shows the spectra of a targeted peptide pair for superoxide dismutase (K9), which was found glycated.

3.4.

Potential biological significance of glycated CSF proteins

3.4.1.

Biological data mining

The glycated CSF proteins identified and included in this work were categorized according to their cellular locations and biological processes based on Gene Ontology analysis. Both categories report information of great interest since the glycation potential of a protein may depends on its cellular location, and glycation might disturb cellular processes by alteration of their function. The distributions of glycated proteins are

Fig. 4 – Mass scan obtained by LC–MS/MS analysis that shows the preferential glycation site of superoxide dismutase (ATKAVCVLK[Glc]GDGPVQGIINFE) from all approaches. Doublet signals are zoomed to check the glycation efficiency of [ 12C6]- and [ 13C6]-glucose.

4778

J O U RN A L OF P ROT EO M IC S 7 5 ( 2 0 12 ) 47 6 6 –47 8 2

shown in Supplementary Fig. 4. As it is observed, GO analysis of the native glycated CSF proteome indicated that by far the major predicted cellular localizations are extracellular region/space (39% and 24%, respectively), while membrane and intracellular categories like Golgi apparatus and endoplasmic reticulum account for less than 6% each (see Supplementary Fig. 4.A). In contrast, the major significant portions of the in vitro glycated proteins were membrane and nucleus localizations (20% each). Other predicted proteins were annotated with extracellular and cytoplasm regions (11% and 9%, respectively). These suggest high selectivity in the glycation process of CSF proteins: mostly occurring in extracellular proteins when they are under normal physiological conditions; and in intracellular proteins if targets are under “pathophysiological” conditions (here in vitro). Because membrane and extracellular proteins have been indicated to be the most representative proteins in human CSF [52,53], the results of the glycation localization reported by this study confirm these findings. A significant variety of biological processes was annotated for glycated CSF proteins, although most of them showed low distributions (see Supplementary Fig. 4.B). The most represented process of native glycated proteins was transport (9%), which was not surprising considering the predicted localization of analyzed proteins. The large percentage of in vitro glycated proteins was signal transduction process (7%), in agreement with previous studies on the human CSF proteome [53,54]. An additional analysis based on the Ingenuity knowledge database was performed. For both data sets, the results suggested implication of glycated proteins in cellular movement and immune cell trafficking; both functions working together and inside a network that reached the highest ingenuity score in each analysis (information collected in Supplementary documents). It is worth emphasizing that more than 19 glycated proteins were highlighted within this network, including alpha 2 macroglobulin, clusterin, and cadherin 11, among others. The results support the evidence of significant implication of CSF proteins in immune response [53,55–57]. Particularly in AGEs-associated diseases, potential regulation of inflammatory processes where glycation is the disease-causing factor may be deduced [58–60]. Moreover, IPA was able to predict for the in vitro glycated CSF a network associated with neurological diseases, organ injury and abnormalities, and development disorder. According to the connectivity diagram of Fig. 5 in which 35 molecules form the network, 10 were glycated proteins. These proteins highlight direct or indirect relationships with the principal cores of network, which are huntingtin and amyloid beta precursor protein. Both targets have been widely associated with CNS pathologies. As shows Fig. 5, IPA pointed out involvement of some of our glycated proteins in brain and/or CNS diseases. The highlighted proteins were dystonin, spectrin beta chain, neuronal pentraxin-1, and Heat shock 70 kDa protein 6. The last two glycated proteins have been reported to play a role in Alzheimer disease. From these findings, it could be hypothesized that the presented data sets contain valuable unique information on the pathological role of glycation in central nervous system pathologies.

with an implication in Huntington disease were antithrombinIII, complement C3c alpha, beta-2-glycoprotein 1, transthyretin, vitamin D-binding protein, hemopexin, ectonucleotide pyrophosphatase/phosphodiesterase family member 2, and MAGUK p55 subfamily member 2 [63]. The authors detected a general trend for brain-related proteins to decrease in HD CSF, whereas most proteins they detected with higher concentrations in HD CSF were associated with the immune system. The latter may relate to neuroinflammation, which is a common component of many neurodegenerative diseases. This trend is also consistent with the most significant function annotated for our glycated CSF proteome, meaning that the pathological role of glycation in neurodegenerative disorders may involve alteration of the immune response. Alzheimer's disease associated proteins detected in our study were cystatin-C [69], apolipoprotein A-I [65], Beta-2glycoprotein 1 [72], alpha-1-acid glycoprotein 1 [72], transthyretin [25,67], albumin [25], and hemopexin [73]. The majority of them were observed significantly up-regulated in AD. These observations provide new hypothesis for the role of glycation in AD. Indeed, increased accumulation of Amadori products was also found in albumin and transthyretin of AD CSF [25], as well as glycation-related alteration pattern of prostaglandin D2 synthase was suggested in CSF of patients with dementia [71]. Of note, cystatin was described as co-localizing with amyloid beta protein in AD [69] where formation of AGE was shown to be increased [12,32,33]. These results support therefore the potential biological relevance of our study in neurodegenerative processes. Multiple Sclerosis-related biomarkers were also detected in this study and include superoxide dismutase (SOD), complement C3c alpha, Ig lambda chain C regions, transthyretin, albumin, transferrin, osteopontin, and heat shock protein 90beta [62]. Superoxide dismutase is a protein involved in the protection against oxidative stress and cell death. The presence of oxidative stress events during advanced glycation product accumulation has been demonstrated by several studies. The modification of superoxide dismutase suggests that glycation might disturb the SOD function during AGEs-associated neurodegenerative disorders.

3.4.2.

Acknowledgments

Potential CSF biomarkers in neurological diseases

Some of the glycated proteins that have been found in this work were described as neurological diseases-related proteins in numerous studies [25,56,61–71]. Particularly, proteins reported

4.

Conclusions

The present work evaluated the early stage of glycation on native human CSF proteins. It greatly expanded the knowledge of the glycated human CSF proteome and enabled the quantitation of numerous glycation attachment sites under native and high glucose level conditions. It should be of a considerable help to further understand some of the underlying mechanisms implicated in protein dysfunction associated to neurodegenerative disorders. It might also generate new hypothesis on the development of new therapeutic targets. Supplementary materials related to this article can be found online at doi:10.1016/j.jprot.2012.01.017.

This research was supported by an IPP SystemsX grant. Feliciano Priego Capote is also grateful to the MICINN for a Ramón y Cajal

J O U RN A L OF P ROT EO M I CS 7 5 ( 2 0 12 ) 47 6 6 –4 78 2

Fig. 5 – Ingenuity pathway analysis diagram of a signalling network involved in neurological disease, organ injury and abnormalities and development disorder overlaid with glycation data from predictive approach. Molecules that are coloured highlighted glycated protein.

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contract (RYC-2009-03921) and the Junta de Andalucía for financial support (FQM-2010-6420). We also deeply appreciate those who have donated their CSF for our studies.

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