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Human Hemolysate Glycated Proteome Feliciano Priego-Capote,†,^ Maria Ramirez-Boo,† Christine Hoogland,†,‡ Alexander Scherl,† Markus Mueller,‡ Frederique Lisacek,‡ and Jean-Charles Sanchez*,† †
Biomedical Proteomics Research Group, Department of Human Protein Sciences, University Medical Centre, University of Geneva, 1211 Geneva 4, Switzerland ‡ Proteome Informatics Group, CMU-1, Rue Michel Servet, 1211 Geneva 4, Switzerland
bS Supporting Information ABSTRACT: Despite continuous advances in hyperglycemia treatments, a precise control through monitoring of glucose and glycated hemoglobin remains in most diabetic patients as the diagnosis/prognosis tool. An alternative perspective could be the discovery and quantitation of new blood glycated proteins formed by nonenzymatic reaction with circulatory glucose. As a result, the human hemolysate is an incomparable source of glycated proteins to further monitor glycemia and interpret changes at the level of this post-translational modification. The human hemolysate is here studied based on the differential labeling of proteins with isotopically labeledglucose ([13C6] glucose), named glycation isotopic labeling. Due to the chemoselectivity of glycation, only preferential targets are labeled by this protocol. The approach provides qualitative data through the detection of preferential protein glycation sites as well as quantitative information to evaluate the abundance of this modification. This strategy was applied to human hemolysate samples corresponding to different glycemic states estimated by laboratory-certified concentrations of glycated hemoglobin. The glycation level of each protein can then be employed to interpret the effect of glucose exposition as a consequence of glycemic unbalance. This information should provide new molecular insights into protein glycation mechanisms that might generate a new hypothesis to clinicians to improve the understanding of underlying pathologies associated to prolonged hyperglycemia.
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he prevalence of diabetes is increasing at an alarming rate, which results in reduced life expectancy and increased morbidity due to disease-specific complications. Although diabetes care should address a wide range of risk factors (dyslipidemia, hypertension, smoking, etc.), hyperglycemia not only defines the disease but is also the cause of its most characteristic symptoms and long-term complications. Considerable evidence currently reveals that the extent and duration of hyperglycemia are significant factors of the onset and severity of health problems frequently observed in type 1 and type 2 diabetes, including neuropathy, nephropathy, retinopathy, and cardiovascular diseases. In addition, an efficient glycemic control strongly reduces the incidence and progression of micro- and macrovascular diseases.1 4 The hypothesis of glucotoxicity has thus emerged justifying that hyperglycemia has long-lasting deleterious effects in both type 1 and type 2 diabetes.5 These disorders are often observed only several years after the development of the illness,6,7 so the glycemic control, if not started at a very early stage of the disease, is not efficient enough to completely reduce complications. Despite continuous advances in hyperglycemia treatment and blood glucose monitoring, markers of glycemic control remain in most diabetic patients a key issue. Initially, the urine glucose testing allowed documentation of severe hyperglycemia but was seriously restricted due to its limited semiquantitative character, significantly affected by urine concentration. An important change in r 2011 American Chemical Society
diabetes care occurred in the 1970s and 1980s when selfmonitoring of blood glucose (SMBG) and glycated hemoglobin (HbA1c) testing became available. The information derived from these two assessments is fundamentally different but complementary. The SMBG test reveals the immediate hour-to-hour blood glucose, which in people without diabetes varies only about 50% throughout a normal day, but may vary 10-fold in patients with diabetes. Long-term or month-to-month glycemia is assessed by the concentration of HbA1c.8 Circulating glucose reacts with hemoglobin via a quasi-irreversible nonenzymatic reaction, the rate of which is determined by blood glucose concentrations. The kinetics of the initial glycation process is governed by the formation of the Amadori compound, a slow process under human physiological conditions (37 C, ∼5 mM blood glucose concentration in healthy subjects).9 However, the reaction kinetics is enhanced under prolonged hyperglycemia exposure, being one of the pathophysiological mechanisms involved. The glycated hemoglobin test is most widely used to evaluate the long-term glycemic control and the risk for the development of complications in type 1 and type 2 diabetes. The exact period is dictated by the erythrocyte life span, which is Received: April 5, 2011 Accepted: June 1, 2011 Published: June 01, 2011 5673
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Analytical Chemistry around ∼120 days. Therefore, HbA1c concentration represents the memory effect of blood glucose concentrations over the previous 8 12 weeks.8,10 12 However, glycated hemoglobin is known to be affected by various conditions, especially by the modification of erythrocyte survival. For example, lower HbA1c levels are observed in subjects with decreased mean erythrocyte age. Hyperglycemia is also known to reduce the survival of erythrocytes and to underestimate HbA1c levels in diabetic patients under poor glycemic control.13,14 For all these reasons, alternative measurements indicative of short- to medium-term glucose perturbation are needed in hemolysate to understand its potential biological effect. It should also be taken into account that any protein could be potentially glycated. Due to the continuous exposition to glucose, the concentration of HbA1c in red blood cells and glycated human serum albumin in plasma from healthy subjects have been estimated around 5 7% and 15%, respectively.15,16 Therefore, the development of methods for the identification and quantification of glycated proteins as well as for prediction of new potential targets under different conditions in blood is crucial to elucidate their biological effect. It is worth emphasizing that the impact of glycation encompasses alterations of the structure, function, and turnover of proteins.17 Evidently, the effects on biological function will depend on the extent of glycation. From a clinical point of view, the detection of this posttranslational modification (PTM) at the initial stage would be helpful for both prognostic and treatment follow-up purposes. The current work presents the application of a method for analysis of nonenzymatic glycation sites in the human hemolysate proteome of samples at different glycemic states. The method, previously applied to plasma samples,18 is based on the differential labeling of proteins with isotopically labeledglucose ([13C6] glucose), named glycation isotopic labeling (GIL). By this procedure, only preferential glycation targets are labeled due to the chemoselectivity of this method. The approach enables us to obtain qualitative information by detection of glycation sites as well as quantitative reports to evaluate the level of the modification.
’ EXPERIMENTAL SECTION Chemicals. Disodium hydrogen phosphate, sodium hydroxide, ammonium acetate, acetic acid, [12C6]-glucose (g99.5%), and [13C6]-glucose (99 atom % 13C) were purchased from Sigma. A glycated hemoglobin calibrator set (Boerne, TX, U.S.A.) consisting of lyophilized and purified hemolysate at four levels of glycated hemoglobin (HbA1c) was used in this research. This set contains four concentration levels of HbA1c in order to simulate individuals with a normal glycemic level with 5% HbA1c and abnormal values such as 8.3%, 11.22%, and 13.43% HbA1c, which are clearly indicative of a poor glycemic control. Triethylammonium hydrogen carbonate buffer (TEAB, 1 M pH 8.5), iodoacetamide (IAA, g99%), 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 (ACN) Chromasolv for HPLC (g99.9%) were, respectively, from Merck and Sigma. Superpure formic acid (g99%) was purchased from Biosolve Chemicals (Valkenswaard, The Netherlands) as an ionizing agent for LC MS analysis. Glucose Labeling of the Calibrator Reference Blood Hemolysate. Blood hemolysate (4 mg) was reconstituted in 0.5 mL of phosphate buffer for subsequent incubation with 50 mM
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[13C6]-glucose by shaking for 24 h at 37 C. Then, each aliquot was separately analyzed. Glucose and other salts were similarly 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. Endoproteinase Glu-C Enzymatic Digestion of Proteins. An amount of 1 mg of reconstituted protein according to Bradford assay (diluted to 400 μL of TEAB) was enzymatically digested using endoproteinase Glu-C. For this purpose, 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 speedvacuum and reconstituted in 50 μL of mobile phase A (0.2 M NH4Ac/50 mM MgCl2 pH 8.1) for isolation of glycated peptides. Enrichment of Glycated Peptides by Boronate Affinity Chromatography. Reconstituted peptides were fractioned by boronate affinity chromatography by interaction between boronic acids and cis-diol groups of glycated peptides present at low concentration. For this purpose, the target sample (50 μL) was injected in a Waters high-performance liquid chromatograph (HPLC) equipped with a TSK-Gel boronate affinity column, Tosoh Bioscience (7.5 cm 7.5 mm i.d.; 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 nonglycated 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 nonglycated and the glycated fractions were collected for subsequent evaporation and reconstitution in 5% ACN/0.1% formic acid. Then, peptides were desalted and preconcentrated prior to liquid chromatography tandem mass spectrometry (LC MS/MS) analysis. This was carried out with C18 microspin columns (Harvard Apparatus, Holliston, MA, U.S.A.) according to the protocol recommended by the manufacturer, which ends with elution of peptides with 400 μL of 50% ACN/0.1% formic acid. This solution was evaporated to dryness for reconstitution with 50 μL of 5% ACN/0.1% formic acid. 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 homemade 100 μm i.d. 18 mm long precolumn packed with 200 Å 5 μm 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 (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 precolumn 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 the following: mobile phase A, water, 0.1% formic acid; mobile phase B, ACN, 0.1% formic acid. The gradient program 5674
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Analytical Chemistry 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 microtee union (Upchurch Scientific, Oak Harbor, WA) located between the precolumn 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 peptides: 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 HCD MS2 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, whereas 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. The data-dependent CID MS3 neutral loss scan was entirely carried out in the linear trap (excepting the 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 corresponds 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 corresponds 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. Data Analysis. After data-dependent acquisition, postacquisition 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 HCD MS2 experiments, the workflow was based on detection of precursor ions in an accurate way and correction for misassigned precursor-ion isotopes.19 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 Phenyx 2.6 (GeneBio, Geneva, Switzerland). No taxonomy was used for the model protein mixture, and Homo sapiens was specified for database searching of hemolysate 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 a maximum of 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.
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This tolerance was set to 0.8 Da for fragment ions in MS3 neutral loss. In both modes, two sequential search rounds were used. For HCD MS2 experiments, glycation was only included among the potential protein modifications in the second round. For both modes, in the first round, two missed cleavages were allowed in normal mode. This round was selected in “turbo” search mode. In the second round, three missed cleavages were allowed at halfcleaved mode. The minimum peptide length allowed was six for both rounds in HCD MS2 and five in MS3 neutral loss. The acceptance criteria were slightly lowered in the second round search. These were the values for HCD MS2 experiments: peptide p value 1 10 7, AC score and peptide Z-score 9 for round 1; peptide p value 1 10 3, AC score and peptide Z-score 7.1, 8.0, 8.0, 7.5 (specific scores regarding the analyzed samples of HbA1c at 5.0%, 8.3%, 11.22%, and 13.43%, respectively) for round 2, 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 Z-score 6.1, 6,1, 6.1, and 6.0 (scores corresponding to samples mentioned above), for round 1; peptide p value 1 10 3, AC score 6.1, 6,1, 6.1, 6.0, for round 2, 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.20 All data were acquired in triplicate (three analytical injections of the same sample) and analyzed in an independent manner. The identified proteins, peptides, and post-translational modifications as well as mass spectra were submitted to PRIDE (proteomics identifications database). 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 both isotopic forms of each glycated peptide. The peptide ratios [12C6]/[13C6] were obtained from the average values of intrarun triplicates. Data treatment was automated using SuperHirn (version 1.0).21 This software is freely available together with detailed documentation material on http://tools.proteomecenter. org/SuperHirn.php. The .raw data files were converted to mzXML22 file format in profile mode, and SuperHirn performed the feature extraction and alignment of the replicate runs (SuperHirn used standard Orbitrap settings). The postprocessing of the feature list was performed with in-house perl scripts. Briefly, the SuperHirn result files were parsed in order to find all heavy light pairs (within a mass tolerance of 10 ppm and retention time tolerance of 0.5 s) that appeared in at least two of the replicates. Then, all accepted identifications from the Phenyx Excel export were attributed to a heavy light pair, if such a pair could be detected (∼80% of the cases).
’ RESULTS AND DISCUSSION Identification of Glycated Proteins in Euglycemic Hemolysate Samples. Human blood is the most commonly used body
fluid in biomarker measurements due to the presence of most of the cellular components of the body. One example is found with HbA1c, which is used as a predictor of diabetic complications and 5675
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Figure 1. Extracted ion chromatogram in MS3 obtained by analysis of human blood hemolysate corresponding to a good glycemic control monitoring defined neutral losses indicated in the Experimental Section. This chromatogram represents a selective glycemic fingerprinting.
indirect medium-term glycemic control. Hemoglobin is the most concentrated protein in red blood cells (∼98%). A reasonable concentration of HbA1c in individuals with an efficient glycemic control is less than 7%.8 This level is mainly due to the continuous contact between circulating glucose and blood erythrocytes. As a result of this interaction, other erythrocyte proteins can be modified by glycation due to the nonspecific character of the glycation process. In order to obtain a profile of glycated proteins representative of a good glycemic control, blood lysates with 5% HbA1c were analyzed after endoproteinase Glu-C digestion, isolation of glycated peptides by BAC, and LC MS/MS dual analysis by MS2 and MS3 modes. A combination of an MS2 mode with HCD activation and CID MS3 by neutral loss scan was applied for qualitative analysis of glycated proteins. The high accuracy in HCD MS2 mode for precursor and fragment ions is crucial to achieve a high identification level19,23 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, whereas HCD MS2 is specially suited for multicharged peptides (z > 3).18 Supporting Information Table S-1 shows the list of glycated proteins that were detected with information of the identified peptides for each protein and glycation sites. The results are organized depending on the MS operation mode that detected each peptide. Most of the identifications were targeted at the different hemoglobin chains such as the subunits R, β, and δ with 5, 14, and 9 glycation sites, respectively. The site selectivity is of particular interest to elucidate the potential impact of glycation on the biological function of certain proteins. It is worth emphasizing that despite the fact of the extremely high concentration of hemoglobin in the proteome of erythrocytes, other minor glycated proteins were detected as well. As can be seen in Supporting Information Table S-1, these proteins were carbonic anhydrase 1, peroxiredoxin 2, and bisphosphoglycerate mutase, among others.
This background glycation can be reflected by the chromatographic profile as shown in Supporting Information Figure S-1. It represents extracted ion chromatograms in MS2 of immonium ions calculated for glycated Lys and Arg in blood lysate analysis. 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. In fact, immonium ions have pinpointed the existence of glycated Lys and Arg by considering the losses detected in glycated entities by collision-based dissociation in MS2.18 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 (Supporting Information Figure S-2).24,25 Thus, immoniumderived 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 (Supporting Information Figure S-1A). Similarly, immonium-derived ions for glycated Arg were at 237.135 and 207.124 Da (Supporting Information Figure S-1B). Additional information can be deduced when the same strategy is applied to estimate the immonium ions corresponding to the preferential glycation site occurring in hemoglobin, which is located at the N-terminal valine residue of the β chain.26 The immonium ions calculated for glycated Val were at 180.103 and 150.092 Da that pinpoint the localization of peptides with the preferred glycation site in HbA1c (Supporting Information Figure S-1C). A similar profile to illustrate this background glycation can be detected by MS3 total ion extracted chromatograms 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 reisolated in the ion trap for a second fragmentation step. The detected neutral loss masses shifts correspond 5676
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Figure 2. (A) Mass scan obtained by LC MS/MS analysis that shows the peptide containing the preferential glycation site of hemoglobin according to the literature (12Glu6VHLTPEEKSAVTALWGKVNVDE). Doublet signals are zoomed to check the glycation efficiency of [12C6]- and [13C6]-glucose. (B) Correlation between glycation level expressed as ratio of peak areas of extracted chromatograms corresponding to [12C6]- and [13C6]-labeled peptides with the percentage of the known HbA1c. Both A and B sections show the ratios in base 2 logarithmic scale.
with 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.27 Neutral loss analysis was carried out in the ion trap to avoid transfers of ions to the Orbitrap analyzer with the subsequent decrease of sensitivity. Figure 1 shows this profile that complements those illustrated in Supporting Information Figure S-1 as glycemic fingerprinting. Assessment of the Glycemic State by Monitoring HbA1c. The high concentration of hemoglobin in the proteome of red blood cells (∼98%) supports its clinical consideration as an ideal
indirect glycemic biomarker. Structural and functional properties of HbA1c have been studied thoroughly. Glycation induces structural alteration in hemoglobin, such as reduced R-helix content, higher hydrophobic tryptophan surface accessibility, increased thermostability, and weaker heme globular proteins binding, and consequently higher oxygen affinity.28 30 It is well-known that hemoglobin is preferentially glycated on the N-terminal position of the valine residue present in the β chain. The probability of glycation on this N-terminal site has been estimated around 95% versus other potential glycation sites. Hemoglobin glycation was monitored here by the analysis of hemolysates corresponding to different glycemic states, which could be associated to individuals with optimum (5%) or problematic (8.3%, 11.22%, and 13.43%) glycemic control. These samples were analyzed with the quantitative method described in the Experimental Section. This method is based on differential labeling of proteins with isotopically labeled-sugars ([13C6] sugars). With this approach, the labeling step is performed by natural incubation under physiological conditions mimicking the in vivo glycation process. By this procedure, only preferential glycation targets 5677
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Figure 3. Glycation curves for four representative proteins (hemoglobin R (K12) and δ (K145), carbonic anhydrase 1 (K58), and peroxiredoxin-2 (K177)) found in human blood hemolysate at four glycemic states. Curves were obtained by application of the GIL approach. Ratios are shown in base 2 logarithmic scale.
are labeled due to the chemoselectivity of this process. After labeling, this approach can be implemented in any proteomics workflow based on MS detection and relative quantitation of the two isotopic forms. Quantitation is based on the differential labeling with isotopic sugars under physiological conditions to compare biological states. Labeling with both isotopic glucose molecules enables the detection of glycated peptides by mass spectrometry because they produce a doublet signal in the MS scan (+6 Da per glycation site). With this approach, the signals corresponding to peptides labeled with [13C6]-glucose are a result of the in vitro incubation. On the other hand, the signals generated by glycated peptides with light glucose are indicative of their native concentration in the biological sample. Figure 2A shows the doublet signal provided by a peptide containing the preferential glycation site of hemoglobin according to the literature on the N-terminal position of the β chain. As it can be deduced, the ratio of peak areas in logarithmic scale of extracted chromatograms corresponding to [12C6]- and [13C6]labeled peptides increases with the percentage of the known HbA1c levels. The relationship between the estimated ratio and the concentration of HbA1c in erythrocyte lysates can be fitted with a grade 2 polynomial trend line. Therefore, it could be correlated with the glycemic state of individuals (Figure 2B). The behavior of this preferential glycation site can be observed by extraction of MS3 chromatograms obtained by neutral loss at the different glycemic levels. These chromatograms are represented in Supporting Information Figure S-3, which label the base peak in the MS3 spectra for each chromatographic peak. As can be observed, the increase of HbA1c concentration is accompanied by a significant area increase in relative terms of the chromatographic peak labeled with 1119.55 ( 0.2 Da as base peak. The chromatograms are complemented by extracted MS3 spectra within 41.00 43.00 min, the retention time window where this chromatographic peak is eluted. It can be deduced from the comparison of these spectra that they correspond to the glycated peptide with precursor ion at m/z 862.44. According to the MS3 strategy selected in this research,
this ion is initially fragmented in the trap forming by predefined neutral loss of the ion at m/z 834.26 by intermolecular rearrangement of the glucose unit. The new ion is isolated again in the trap for a second fragmentation generating MS3 spectra illustrated in Supporting Information Figure S-3 for each case. This peptide contains the preferential glycation site of HbA1c as shown in Figure 2. With these premises, Supporting Information Figure S-3 reveals that glycation on the preferential site of HbA1c is critically enhanced for hemolysate samples with higher glycemic unbalance. It is worth emphasizing that two separated chromatographic peaks with the same MS3 base peak can be observed for hemolysate samples with 5% and 8.3% HbA1c. Both chromatographic peaks shared the same MS3 spectra in their retention time window, which led to two isomeric glycated peptides. The former peak fitted the peptide with the sugar attachment site on the N-terminal site. The isomer peptide eluting later was identified as that one with the labeling site on the K8. Identification and Quantitation of Hemolysate Glycated Proteins. The next step was the analysis of hemolysates representing the different glycation states. Supporting Information Table S-2 includes the list of proteins that were detected in hemolysate samples corresponding to 8.3%, 11.22%, and 13.43% of HbA1c. Qualitative identification of glycated proteins was complemented by quantitative results. Labeling of proteins with [13C6]-glucose was achieved by incubation under physiological conditions mimicking the in vivo glycation process in order to evaluate the native glycated proteins labeled with [12C6]-glucose. Since [12C6]-glucose concentration is not modified during incubation a profile of glycated proteins present in a target sample is obtained. The ratio between peak areas corresponding to the peptides labeled with [12C6]- and [13C6]-glucose provides additional quantitative information in relative terms. For this purpose, the peak areas of the in vivo and in vitro glycated peptides (labeled with [12C6]- and [13C6]-glucose, respectively) were estimated from the extracted ion chromatograms. 5678
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Analytical Chemistry The application of the quantitative approach to human hemolysates corresponding to different glycemic states enables us to monitor the glycation level of each modified site and, therefore, each modified protein. Figure 3 shows the glycation curves for four representative proteins (hemoglobin R (K12) and δ (K145), carbonic anhydrase 1 (K58), and peroxiredoxin-2 (K177)). Supporting Information Table S-3 lists all quantified glycated peptides in human hemolysates. Results exposed in this research have revealed the presence of other glycated proteins apart from hemoglobin. The glycemic unbalance is clinically diagnosed at HbA1c concentrations above 7%. However, at these levels an increase in the presence of other glycated proteins is expected. As Supporting Information Table S-2 shows, new glycated proteins are detected (taking as reference Supporting Information Table S-1) as well as new modified sites in proteins that were previously detected with this PTM such as catalase (K92), peroxiredoxin-2 (R6), and cofilin-1 (K114). This increase in the identification of glycated proteins presumably might be associated to a decrease in protein function depending on the time exposition to supraphysiological glucose concentration. The glycation curves illustrated in Figure 3 reveal quantitative information that can be of interest to understand the mechanism of the glycation process. As can be seen, the glycation enhancement of both glycated hemoglobin peptides fits a linear model. For peroxiredoxin-2, no glycation is present at 5% HbA1c with a significant increase at 8.3%, 11.22%, and 13.43% HbA1c. Carbonic anhydrase provides a clear glycation increase from 5% to 8.3% HbA1c with a subsequent plateau from 8.3% to 13.43%.
’ CONCLUSIONS In conclusion, the glycated fraction of the human blood hemolysate has been characterized for different glycemic states. The importance of this study derives from the consideration of human hemolysate as a promising source of glycated proteins to monitor glycemia and interpret changes at the level of this PTM that could affect protein structure and function.31 34 Labeling with both isotopic glucose molecules enables the detection of glycated peptides by mass spectrometry. This approach can be also employed to obtain quantitative information associated to the glycation level of sugar attachment sites. Peptides labeled with “heavy” glucose are considered as internal standards, and these isotopic forms specifically mimic physiological conditions. Therefore, in vitro labeling with [13C6]-glucose depends on sample properties such as protein content or factors affecting glycation. The application of this approach is useful for the relative estimation of the extent of glycation at each potential attachment site. In addition, the isotopic glucose labeling is valid as a quantitative approach to compare between two glycation states for the same or different patients. ’ ASSOCIATED CONTENT
bS Supporting Information. Additional information as noted in text. This material is available free of charge via the Internet at http://pubs.acs.org. ’ AUTHOR INFORMATION Corresponding Author
*Phone: +41 (0) 22 379 54 86. Fax: +41 (0) 22 379 55 05. E-mail:
[email protected].
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Present Addresses ^
Department of Analytical Chemistry, University of Cordoba, E-14071 Cordoba, Spain.
’ ACKNOWLEDGMENT This work was supported by the Spanish Ministry of Science and Innovation, the Spanish Foundation for Science and Technology (Ramon y Cajal Program with reference RYC-2009-03921), and the Swiss SystemsX.ch initiative (Grant IPP-200N/ONN). ’ REFERENCES (1) The Diabetes Control and Complications Trial Research Group. N. Engl. J. Med. 1993, 329, 977–986. (2) Ohkubo, Y.; Kishikawa, H.; Araki, E.; Miyata, T.; Isami, S.; Motoyoshi, S.; Kojima, Y.; Furuyoshi, N.; Shichiri, M. Diabetes Res. Clin. Pract. 1995, 28, 103–117. (3) U.K. Prospective Diabetes Study. Lancet 1998, 352, 837–853. (4) U.K. Prospective Diabetes Study. Lancet 1998, 352, 854–865. (5) Ceriello, A.; Ihnat, M. A.; Thorpe, J. E. J. Clin. Endocrinol. Metab. 2009, 94, 410–415. (6) Brunner, Y.; Schvartz, D.; Priego-Capote, F.; Coute, Y.; Sanchez, J. C. J. Proteomics 2009, 71, 576–591. (7) Reusch, J. E. J. Clin. Invest. 2003, 112, 986–988. (8) Saudek, C. D.; Derr, R. L.; Kalyani, R. R. JAMA, J. Am. Med. Assoc. 2006, 295, 1688–1697. (9) Brock, J. W. C.; Hinton, D. J. S.; Cotham, W. E.; Metz, T. O.; Thorpe, S. R.; Baynes, J. W.; Ames, J. M. J. Proteome Res. 2003, 2, 506–513. (10) Miedema, K. Diabetologia 2004, 47, 1143–1148. (11) Ladyzynski, P.; Wojcicki, J. M.; Bak, M.; Sabalinska, S.; Kawiak, J.; Foltynski, P.; Krzymien, J.; Karnafel, W. Ann. Biomed. Eng. 2008, 36, 1188–1202. (12) Brownlee, M.; Hirsch, I. B. JAMA, J. Am. Med. Assoc. 2006, 295, 1707–1708. (13) Virtue, M. A.; Nuttall, F. Q.; Furne, J. K.; Levitt, M. A. Diabetes Care 2004, 27, 931–935. (14) Goldstein, D. E.; Little, R. R.; Lorenz, R. A.; Malone, J. I.; Nathan, D.; Peterson, C. M.; Sacks, D. B. Diabetes Care 2004, 27, 1761–1773. (15) Yoshiuchi, K.; Matsuhisa, M.; Katakami, N.; Nakatani, Y.; Sakamoto, K.; Matsuoka, T.; Umayahara, Y.; Kosugi, K.; Kaneto, H.; Yamakasi, Y.; Hori, M. Endocr. J. 2008, 55, 503–507. (16) Kisugi, R.; Kouzuma, T.; Yamamoto, T.; Akizuki, S.; Miyamoto, H.; Someya, Y.; Yokoyama, J.; Abe, I.; Hirai, N.; Ohnishi, A. Clin. Chim. Acta 2007, 382, 59–64. (17) Ulrich, P.; Cerami, A. Recent Prog. Horm. Res. 2001, 56, 1–22. (18) Priego-Capote, F.; Scherl, A.; M€uller, M.; Waridel, P.; Lisacek, F.; Sanchez, J. C. Mol. Cell. Proteomics 2010, 9, 579–592. (19) Scherl, A.; Shannon Tsai, Y.; Shaffer, S. A.; Goodlett, D. R. Proteomics 2008, 8, 2791–2797. (20) Elias, J. E.; Gygi, S. P. Nat. Methods 2007, 4, 207–214. (21) Mueller, L. N.; Rinner, O.; Schmidt, A.; Letarte, S.; Bodenmiller, B.; Brusniak, M.; Vitek, O.; Aebersold, R.; M€uller, M. Proteomics 2007, 7, 3470–3480. (22) Pedrioli, P. G.; Eng, J. K.; Hubley, R.; Vogelzang, M.; Deutsch, E. W.; Raught, B.; Pratt, B.; Nilsson, E.; Angeletti, R. H.; Apweiler, R.; Cheung, K.; Costello, C. E.; Hermjakob, H.; Huang, S.; Julian, R. K.; Kapp, E.; McComb, M. E.; Oliver, S. G.; Omenn, G.; Paton, N. W.; Simpson, R.; Smith, R.; Taylor, C. F.; Zhu, W.; Aebersold, R. Nat. Biotechnol. 2004, 22, 1459–1566. (23) Scherl, A.; Shaffer, S. A.; Taylor, G. K.; Hernandez, P.; Appel, R. D.; Binz, P. A.; Goodlett, D. R. J. Am. Soc. Mass Spectrom. 2008, 19, 891–901. (24) Jeric, I.; Versluis, C.; Horvat, S.; Heck, A. J. R. J. Mass Spectrom. 2002, 37, 803–811. (25) Frolov, A.; Hoffmann, P.; Hoffmann, R. J. Mass Spectrom. 2006, 41, 1459–1469. 5679
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