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Hindawi Publishing CorporationInternational Journal of ProteomicsVolume 2012, Article ID 560391, 7 pagesdoi:10.1155/2012/560391

Research Article

Increasing the Productivity of Glycopeptides Analysis byUsing Higher-Energy Collision Dissociation-AccurateMass-Product-Dependent Electron Transfer Dissociation

Julian Saba, Sucharita Dutta, Eric Hemenway, and Rosa Viner

Thermo Fisher Scientific, San Jose, CA 95134, USA

Correspondence should be addressed to Julian Saba, [email protected]

Received 6 February 2012; Accepted 15 March 2012

Academic Editor: Qiangwei Xia

Copyright © 2012 Julian Saba et al. This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Currently, glycans are attracting attention from the scientific community as potential biomarkers or as posttranslationalmodifications (PTMs) of therapeutic proteins. However, structural characterization of glycoproteins and glycopeptides remainsanalytically challenging. Here, we report on the implementation of a novel acquisition strategy termed higher-energy collisiondissociation-accurate mass-product-dependent electron transfer dissociation (HCD-PD-ETD) on a hybrid linear ion trap-orbitrapmass spectrometer. This acquisition strategy uses the complementary fragmentations of ETD and HCD for glycopeptides analysisin an intelligent fashion. Furthermore, the approach minimizes user input for optimizing instrumental parameters and enablesstraightforward detection of glycopeptides. ETD spectra are only acquired when glycan oxonium ions from MS/MS HCD aredetected. The advantage of this approach is that it streamlines data analysis and improves dynamic range and duty cycle. Here,we present the benefits of HCD-PD-ETD relative to the traditional alternating HCD/ETD for a trainer set containing twelve-protein mixture with two glycoproteins: human serotransferrin, ovalbumin and contaminations of two other: bovine alpha 1 acidglycoprotein (bAGP) and bovine fetuin.

1. Introduction

Glycosylation is an important PTM that plays crucial rolesin various biochemical processes, ranging from mediationof interactions between cells to defining cellular identitieswithin complex tissues [1, 2]. In addition, glycan structuresare unique to the proteins which they are attached to andto the site of attachment and, thus, play crucial roles incontrolling the activities of the proteins. Many glycans, also,show disease-related expression level changes [3, 4]. Forexample, changes in glycosylation patterns have been usedas a means to monitor progression of cancer [3–6]. In manyinstances, it is essential to characterize the exact glycanstructure and site of glycosylation to better understand theprotein-mediated interaction that these glycans undergo.

Mass spectrometry (MS) has emerged as one of the mostpowerful tools for proteomics due to its sensitivity of detec-tion and its ability to analyze complex mixtures derived froma variety of organisms and cell lines. However, structural

characterization of glycoproteins/glycopeptides remains ana-lytically challenging due to the reliance on traditional acqui-sition strategies and MS/MS fragmentation techniques.

Conventional proteomics has benefitted tremendouslyfrom collision-activated dissociation (CAD) due to the easeof implementation of the technique on most commercialmass spectrometers and the abundant peptide bond cleav-ages that this technique generates, resulting in large numberof peptides and proteins identified. Unfortunately for glyco-proteomics, CAD does not provide the necessary fragmentions to thoroughly characterize intact glycopeptide struc-tures [7]. Depending upon the mass spectrometers used,CAD provides varying degrees of structural information. Forexample, low-energy CAD on most mass spectrometers pre-dominantly generates glycosidic bond cleavages with mini-mal fragmentation occurring along the peptide backbone [8–11]. Additionally, cleavages also tend to occur between thepeptide-glycan bond, resulting in loss of information aboutthe site of glycosylation. The increase of collision energy can

2 International Journal of Proteomics

result in more efficient fragmentation of the peptide back-bone, but this strategy can result in mixed MS/MS spectrawhere both the glycan and peptide fragment ions are presentin the same spectra, complicating spectral interpretation[12]. Regardless of whether high- or low-energy CAD isemployed, fragmentation of the peptide-glycan bond stilloccurs limiting the ability to derive information about thesite of glycosylation. Majority of the current approacheshave foregone the strategy of examining intact glycopeptidesand have focused on obtaining partial information, suchas sequencing peptide backbone and identifying sites ofglycosylation. For example, the use of N-glycosidase F or A(PNGase F/A) enzymes results in the removal of glycans andconversion of asparagines, the site of glycosylation to asparticacid. This conversion process can then be monitored by high-resolution MS due to a mass shift of 0.9840 Da to identifythe site of glycosylation. Additionally, one can increase theconfidence in the glycosylation site assignment by incorpo-ration of stable isotope labeling by performing PNGaseF/Adigestion in the presence of H2O18. Such approach involvesthe release of glycans by a deamidation reaction, and theincorporation of H2O18 will lead to a mass shift of 2.9890 Daon the asparagine residue. But, studies have shown that thesetypes of chemical deamidations can occur spontaneouslyduring sample preparation for release of glycans in thepresence and absence of H2O18 leading to number of falsepositives [13–17]. These issues underline the importanceof intact glycopeptides structural analysis, and only thisapproach enables comprehensive structural characterization.Though CAD is limiting for glycopeptides analysis, alter-native fragmentation techniques such as electron-capturedissociation (ECD) [18] and ETD [19, 20] are better suitedfor glycopeptides analysis due to their nonergodic type ofdissociation. These dissociation techniques induce extensivefragmentation of the peptide backbone enabling sequencingof the peptide but preserving glycans on the peptide back-bone allowing unambiguous assignment of the glycosylationsites, thus providing complementary information to CAD.

Previously, several studies have demonstrated the utilityof combining CAD and ETD fragmentation for glycopep-tides characterization [19–22]. For example, Catalina et al.have performed detailed analysis of horse peroxidase usingalternating CID, ETD fragmentation [20]. We have shownin the past the importance of combining ETD and CAD,specifically HCD, for full structural characterization ofglycopeptides [22]. However, all of these studies have usedboth types of fragmentation in an unselective fashion. Here,we expand on this approach to report a novel acquisitionstrategy termed HCD-PD-ETD that enables on the fly iden-tification of glycopeptides and improves overall productivityof glycopeptides analysis. In this approach, the LTQ OrbitrapVelos acquires HCD spectra in a data-dependent fashion. Theinstrument identifies glycan oxonium ions on the fly in theHCD spectra and triggers ETD spectra on the glycopeptidesprecursor only. The advantage of this approach is that itstreamlines data analysis and improves dynamic range andduty cycle. The benefits of this novel acquisition strategy areexamined for a trainer set containing twelve-protein mixturewith two glycoproteins and contaminants of two others

and compared against the traditional alternating HCD/ETDapproach.

2. Materials and Methods

All protein and glycoprotein standards used in these experi-ments were purchased from Sigma-Aldrich Chemical Co. (St.Louis, MO, USA).

2.1. Protein Reduction, Alkylation, and Digestion. 100 µg ofequal molar twelve-protein mixture (lysozyme, glyceralde-hyde-3-phosphate dehydrogenase, beta-casein, cytochromec, bovine serum albumin, ovalbumin, carbonic anhy-drase, serotransferrin, alpha-lactalbumin, apo-myoglobulin,bAGP, and bovine fetuin) was dissolved in 100 µL of50 mM TrisHCl, pH 8.6/0.1% SDS buffer. This was fol-lowed by reduction with 5 µL of 100 mM tris(2-car-boxyethyl)phosphine (TCEP) and incubation at 37◦C for30 mins. The reduced twelve-protein mixture was then alky-lated with 5 µL of 375 mM iodoacetic acid for 60 minutes,protected from light. Upon alkylation, the twelve-proteinmixture was acetone precipitated over night at −30◦C. Theacetone-precipitated twelve-protein mixture was dissolved in100 µL of 100 mM triethyl ammonium bicarbonate (TEAB)and digested at 37◦C for 4 hours with 2.5 µg of trypsin (1 : 40enzyme : protein ratio).

2.2. TMT Labeling. Isobaric labeling was accomplished withTMT6 reagent (Thermo Scientific, Rockford, IL, USA) permanufacturer’s suggestion. Briefly, the reagent was dissolvedin 41 µL of anhydrous acetonitrile and added to 100 µgof tryptically digested twelve-protein mixture. The samplewas then incubated at room temperature for 1 hour andquenched with the addition of 8 µL of 5% hydroxylamine andconcentrated to 10 µL using Speed Vac (Thermo Scientific,Waltham, MA, USA).

2.3. LC/MS. A Thermo Scientific EASY-nLC nano-HPLCsystem and Michrom Magic C18 spray tip 15 cm× 75 µm i.d.column (Auburn, CA) were used. Gradient elution was per-formed from 5 to 45% ACN in 0.1% formic acid over 60 minat a flow rate of 300 nL/min. The samples were analyzed witha Thermo Scientific LTQ Orbitrap Velos hybrid mass spec-trometer with ETD. The following MS and MS/MS settingswere used: FT: MSn AGC Target = 5e4; MS/MS = 1 µscans,200 ms max ion time; MS = 400–2000 m/z, 60000 resolutionat m/z 400, MS Target = 1e6; MS/MS = Top 10 data-dependent acquisition HCD product-dependent acquisitionion trap ETD (Figure 1), dynamic exclusion = repeat count 1,Duration 30 sec, exclusion duration 90 sec; HCD Parameters:collision energy = 35%; resolution 7500. MSn target iontrap = 1e4, 3 µscans, 150 ms max ion time; ETD anion AGCtarget = 2e5, and charge-dependent ETD reaction time wasused.

2.4. Data Processing. The prototype GlycoMaster (Bioinfor-matics Solution, Waterloo, ON, Canada) software was usedfor intact glycopeptides analysis. Searches were performedusing a 5 ppm precursor ion tolerance and 0.8 Da ETD

International Journal of Proteomics 3

100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600 1700

m/z

990.459366.140

204.087

138.055

1126.127

314.085917.412

1389.719657.237 718.368 1308.7001227.668 1471.243786.352

528.195 1067.854868.424458.294 1146.772588.411

391.978

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101520253035404550556065707580859095

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440.40

1238.73341.36

1651.40242.24 385.35

1259.63

553.50 1199.581925.90

1322.051612.79

1789.52

114.12 1486.86787.67 1960.311588.84 1811.591706.501125.55897.59670.45272.30

454.41 1022.40198.21 1456.27802.27

Oxonium ions

HexNAc

HexNAc fragment ions

Hex-HexNAc

ETD

HCD

05

101520253035404550556065707580859095

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Hex m/z 163.060

m/z 204.087

m/z 138.055m/z 186.076m/z 366.138

Figure 1: Schematic representation of HCD-PD-ETD acquisition method.

0

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Base peak chromatogram

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34.69204.087

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XIC for m/z 204.087 from HCD spectra

Hex5HexNAc4Neu5Gc2dHexHex4HexNAc4Neu5Gc2

Hex6HexNAc6Hex4HexNAc6Neu5AcHex5HexNAc5Neu5Ac

RPTGEVYDIEIDTLETTCHVLDPTPLANCSVR

QNGTL SK

(b)

Figure 2: (a) Base peak chromatogram and (b) HCD XIC of HexNAc oxonium ion at m/z 204.087 of twelve-protein mixture digest byHCD-PD-ETD.


375.35

661.56360.46 718.60

1414.96

1552.33

1533.001387.09

1471.44750.69

1656.95560.52 1050.04 1297.12 1967.88447.281887.871732.54788.57 1031.88

x20 x15

C1

(M+3H)+3

dHexHex HexNAC4Neu5Gc2

Q N G T L S K

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1414.87

734.55

1305.31

1479.53560.47

447.301073.08

1241.05517.431722.89 1899.10331.42 962.65750.52

x30 x15 x15

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m/z

Q N G T L S KC1

Z1

Z2

Z3

Z4

Z5

Z +26

(M+3H)+3

(b)

Figure 3: LC-MS ion trap ETD spectrum of bAGP N-linked glycopeptide T103–109 precursor at (a) m/z 1165.823 (3+) and (b) m/z 1148.174(3+).

tolerance and 0.02 Da HCD tolerance, while allowing up toone missed cleavage. For peptide searches, carboxymethyla-tion of cysteine residues (+58.005478 Da) was set as staticmodification. TMT6 tag on lysine residues and peptide Ntermini (+229.16293 Da) were set as variable modification.For glycan identification, the following possible monosac-charide combinations were searched: Hexose, HexNAc,Deoxyhexose, Neu5Gc, and Neu5Ac. Both O- and N-linkedglycosylations were considered with H, Na, and K as potentialadducts. To minimize on false hits for site of glycosylation,GlycoMaster considered N-linked glycosylation to occur atthe amide residue of asparagine in a consensus sequence ofAsn-Xaa-Ser/Thr (X can be any amino acid except proline)

and O-linked glycosylation to occur at serine or threonineresidues. All results were manually validated.

3. Results and Discussion

Current MS/MS acquisition strategies for glycopeptidesanalysis rely on acquiring MS/MS spectra for all precursors ina mass spectrum regardless of whether the precursor belongsto a glycopeptide. The resultant spectra are then interrogatedafter acquisition for characteristic glycan oxonium ions(which are dominant in the MS/MS CAD spectra) fordetection of glycopeptides, and the corresponding spectraare then used in the identification [19–25]. The limitation


1525.36

1220.31

247.34

1496.481829.95

1994.47787.68658.60

1626.76

1200.47842.57

1464.001049.79 1813.86886.85 1361.07989.731770.57258.29 557.51

601.64 1164.67345.25118.11 674.50 1744.05 1945.36202.22 1067.20389.47 760.69500.34

C2

C3

C4

C5

C6

C7

C8

1277.84

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+2

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Hex6HexNAc

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R P T G E V Y D I E I D T L E T T C H V L D P T P L A N C S V R

x5 x5

(M+5H)+5 (M+4H)+4

200 400 600 800 1000 1200 1400 1600 1800 2000

m/z

Figure 4: LC-MS ion trap ETD spectrum of bovine fetuin N-linked glycopeptide T72–103 precursor at m/z 1219.950 (5+).

of this approach is that both data acquisition and datainterrogation are not performed as efficiently as possible. Bytriggering MS/MS spectra on all precursors, both duty cycleand dynamic range of analysis are decreased. Furthermore,postacquisition extraction of glycan oxonium ions requiresadditional tools to ascertain information about detectedglycopeptides: their charge state and m/z. Further adding tothe inefficiency of the current MS/MS acquisition strategiesis that if a mass spectrometer with nominal mass accuracyis used, then more than one glycan oxonium ion must beextracted to minimize on false positives due to near massisobaric ions [26]. However, in our approach, we employHCD to generate glycan oxonium ions. The advantage ofusing HCD is that the generated fragment ions are measuredwithin the orbitrap mass analyzer with high resolution andmass accuracy (HR/AM) allowing for unambiguous assign-ment of glycan oxonium ions [23]. Using orbitrap detectionto our advantage, we have implanted a novel instrumentalcontrol within the hybrid linear ion trap-orbitrap massspectrometer termed HCD-PD-ETD (Figure 1). This instru-mental control enables the mass spectrometer to identifyglycopeptides on the fly and acquire data in an intelligentfashion. In this approach, we specify certain glycan oxoniumions for the instruments to monitor within the HCDspectrum (up to ten different product ions can be specified).We typically use m/z 204.0864 HexNAc oxonium ion andits fragments 168.0653 and 138.0550 as diagnostic ionsto be monitored in HCD fragmentation, and, by methoddefinition, the monitored ions should be in the top 20–30most intense fragment ions. However, if glycopeptides ofinterest do not contain terminal HexNAc, other diagnosticoxonium/product ions can be selected and collision energy

optimized accordingly. The hybrid linear ion trap-orbitrapmass spectrometer equipped with ETD then acquires HCDspectra in a data-dependent fashion. Each HCD spectrum isinterrogated by the instrument on the fly for the presenceof diagnostic glycan oxonium (product) ions at ppm massaccuracy. If a diagnostic glycan oxonium (product) ion isdetected, an ETD spectrum for the glycopeptide precur-sor is acquired. It should be noted that we can specifymass accuracy as low as 5 ppm for high selectivity. Thisnovel acquisition strategy provides numerous advantages.Primarily, it increases overall productivity for MS analysisof glycopeptides by acquiring ETD spectra only when aglycopeptide is detected, enabling improvements in bothduty cycle and dynamic range of analysis. Additionally, thisapproach improves data analysis by decreasing the rate offalse positives, the overall file size, and the number of ETDspectra that are extrapolated to characterize glycopeptides.

To demonstrate the advantage of our novel acquisitionstrategy, we selected a twelve-protein mixture containing twoglycoproteins: human serotransferrin and ovalbumin andcontaminants of two others: bAGP and bovine fetuin. Themixture was digested with trypsin and analyzed by the tradi-tional alternating HCD/ETD approach and the novel HCD-PD-ETD approach. Enrichment steps were avoided prior toanalysis to ensure that the glycopeptides would be very lowin abundances; this gave us the opportunity to evaluate thedynamic range of analysis for both acquisition strategies.Of the two, only HCD-PD-ETD approach identified gly-copeptides from the contaminant glycoproteins (bAGP andbovine fetuin) present in the sample (Figure 2). While theHCD/ETD acquisition strategy identified numerous peptidesand expected glycopeptides (eluted at 34, 40, and 48 min


Table 1: List of identified contaminant glycopeptides and corresponding glycoforms from the 12-protein mixture digest by HCD-PD-ETD.

Peptide sequence Glycan no. Glycan composition

T103–109 QNGTLSK(bAGP)1 dHexHex4HexNAc4Neu5Gc2

2 Hex5HexNAc4Neu5Gc2

T72–103 RPTGEVYDIEDTLETTCHVLDPTPLANCSVR (bovine fetuin)3 Hex6HexNAc6

4 Hex4HexNAc6Neu5Ac

5 Hex5HexNAc5Neu5Ac

as shown in Figure 2 for HCD-PD-ETD approach) fromserotransferrin and ovalbumin, it was unable to identifyglycopeptides from the contaminant glycoproteins. Manualinspection of the RAW data confirmed this, as precursorsassociated with the contaminant glycopeptides were nottargeted for MS/MS by HCD or ETD in the alternatingapproach. Analysis of the HCD-PD-ETD data revealed theidentification of glycopeptides from expected glycoproteinsand the contaminant glycoproteins. Identified minor gly-copeptides from the contaminant glycoproteins by HCD-PD-ETD acquisition method are presented in Table 1, andrepresentative ETD MS/MS spectra used in identification areshown in Figures 3 and 4. Because HCD-PD-ETD acqui-sition strategy did not waste time acquiring ETD data fornonglycosylated peptides, it was able to dig deeper into thesample and identify this low abundant glycopeptides that thealternating HCD/ETD acquisition strategy could not target.

In summary, we have been able to develop a novel acqui-sition strategy that minimizes some of the pain points asso-ciated with glycopeptide analysis. By combining the com-plementary information provided by HCD and ETD in anintelligent acquisition control, the overall productivity ofglycopeptides analysis is improved.

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