Introduction

Understanding relationships between structure, location, and function of glycoproteins requires detailed information about peptide sequence, glycan composition, and glyco-sylation sites. A wide variety of analytical approaches are employed to analyze intact glycoproteins, glycopeptides, and released glycans, with mass spectrometry playing a major role.

We have previously demonstrated the performance of the amaZon speed ETD system for the analysis of N-glyco-sylated peptides in simple glycoprotein digests using Collision Induced Dissociation (CID) and Electron Transfer Dissociation (ETD)1,2. However, biological samples are more usually complex mixtures of proteins and glycoproteins, which makes complete analysis of glycopeptides even more challenging.

In this study, we analyzed the Universal Proteomics Standard (UPS) from Sigma, which was developed in collaboration with the Association of Biomolecular Resource Facilities Proteomics Standards Research Group (ABRF sPRG).

Authors

Kristina Marx, Andrea Kiehne, Markus MeyerBruker Daltonik GmbH, Bremen, Germany

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Application Note # LCMS-93

amaZon speed ETD: Exploring glycopeptides in protein mixtures using Fragment Triggered ETD and CaptiveSpray nanoBooster

Keywords Instrumentation and Software

Glycopeptides amaZon speed ETD

CID/ETD CaptiveSpray nanoBooster

Fragment Triggered ETD ProteinScape

CaptiveSpray nanoBooster GlycoQuest

ProteinScape

GlycoQuest

Results

1. Protein Identification

The UPS1 standard represents a sample of moderate complexity and was selected to test the principle of our analytical approach.

The chromatogram in Figure 1 shows the separation of the tryptic peptides. Identification of the non-glycosylated peptides and characterization of the glycopeptide glycan moiety was based on ion trap low-energy CID data.

The acquired spectra were submitted to a database search for protein identification using Mascot (parameters are listed in Table 3). To simplify the results, although present, post-translational modifications were not included for the protein identification. All 48 proteins of the UPS standard were detected. Figure 2 shows the number of identified peptides and the sequence coverage for each protein.

The standard consists of 48 human proteins, whose molecular weights range from 6 to 83 kDa and which show differing degrees of post-translational modifications, including glycosylation. This standard represents a sample of moderate complexity and is therefore well-suited to test the principle of our analytical approach. The study used solvent-enriched sheath gas to enhance glycopeptide signal intensities. The efficient combination of CID and oxonium-ion–triggered ETD during data acquisition – “Fragment Triggered ETD” – enabled extensive protein sequence identification and detailed glycopeptide profiling in a single run.

Experimental

Sample preparation

Universal Proteomics Standard UPS1 (Sigma) was reduced, carbamidomethylated, and digested with trypsin. The tryptic peptides (100 fmol on column) were separated on an UltiMate® 3000 RSLCnano system with an Acclaim® PepMap C18 column (see Table 1 for more details).

An amaZon speed ETD mass spectrometer (Bruker Daltonics) equipped with a CaptiveSpray nanoBooster ionization source was used for data-dependent MS/MS experiments. Spectra were acquired in Enhanced Resolution mode using Fragment Triggered ETD. Further acquisition parameters are listed in Table 2. Acetonitrile-enriched nitrogen was used as sheath gas to increase the charge state of peptide ions and enhance the intensities of glycopeptide signals. Data processing was performed using ProteinScape 3.1. After protein identification, CID spectra of glycopeptides were identified and searched against the CarbBank database using the integrated search engine GlycoQuest. Finally, ETD spectra were used for glycopeptide sequencing.

LC settings

LC system UltiMate® 3000 RSLCnano

Trap columnAcclaim® PepMap RSLC, 100 µm x 2 cm, C18, 3 µm, 100 Å

Analytical columnAcclaim® PepMap RSLC, 75 µm x 50 cm, C18, 2 µm, 100 Å

Flow rate 250 nL/min

Oven temperature 40 °C

EluentsA: 0.1% formic acid in water, B: 0.1% formic acid in acetonitrile

Gradient2 to 20% B in 170 min, 20 to 40% B in 75 min

Table 1: LC parameters for separation of N-glycopeptides and non-glycosylated tryptic peptides.

Acquisition parameters

Source CaptiveSpray nanoBooster

MS settings:

Scan modeEnhanced Resolution mode (8,100 m/z s-1)

Scan range 400–2,000 m/z

ICC target Positive mode: 300,000

Spectra averages 4 (Rolling averaging: 2)

SPS tuning mass 1,000 m/z

MS/MS settings:

Scan modeEnhanced resolution mode (8,100 m/z s-1)

Scan range 100–3,000 m/z

ICC target Positive mode: 300,000

No. of precursor ions

4 (active exclusion after 1 spectrum, release after 0.2 min; reconsider precursor, if current intensity/previous intensity > 5)

Isolation width 3.5

Spectra averages 3

Fragmentation amplitude (CID)

70% (SmartFrag 80-120%)

Trigger ions 204.08, 292.10, and 366.14 m/z

ICC ETD 500,000

Fragmentation time (ETD)

100 ms

Table 2: MS and MS/MS settings used for acquisition with the amaZon speed ETD.

2. Glycopeptide Characterization

The low concentration and low ionization efficiency (compared to non-glycosylated peptides) makes the analysis of glycopeptides in complex mixtures challenging. A significant enhancement of glycopeptide detection can be achieved using acetonitrile-enriched sheath gas. Figure 3 compares intensities and charge states of two N-glycopeptides from hCG (human chorionic gonadotropin) measured using a standard CaptiveSpray source or a CaptiveSpray nanoBooster source using nitrogen or acetonitrile-enriched nitrogen3. Using nitrogen instead of air leads to an increase of glycopeptide signal intensities, due to improved solvent evaporation.

Separation of UPS1 tryptic digest

Figure 1: Separation of UPS1 tryptic digest. Insert: LC-MS Density Plot.

Overview of identified proteins

Figure 2: Overview of identified proteins (100 fmol on column) with number of identified unique peptides and sequence coverage. (Results not including glycopeptides.)

Using acetonitrile-enriched nitrogen as sheath gas further enhances the ionization efficiency and also shifts the average charge state to higher values, an effect that has already been described for peptides4. The extent of charge shift and signal enhancement depends on glycan structure, peptide sequence, glycosylation site, and eluent composition at the respective retention time. The higher charge state of the peptides is especially advantageous for glycopeptide profiling by ETD.

Because ETD is not necessarily required for protein identification, but is mandatory for the sequencing of the glycopeptide backbone, the smart MSn mode Fragment Triggered ETD was used. The ETD reaction is only triggered if “diagnostic” oxonium ions were detected in the previous CID spectrum. This new mode leads to fragmentation of all peptides by CID, but only glycopeptides are also subjected to ETD. This approach enables efficient analysis of non-glycosylated peptides and glycopeptides in protein mixtures.

Parameter Value

Submitted to search Classified glycopeptide CID spectra

Glycan type N-glycan core basic

Taxonomy No restriction

Database CarbBank

Composition restriction

Hex 3-5; HexNAc 2-4; Neu5Ac 0-2; Fuc 0

Derivatization Underivatized

Ionization H+ up to 5

MS tolerance ± 0.3 Da

MS/MS tolerance ± 0.35 Da

#13C 0

Fragmentation B-ions, Y-ions; max. 4 cleavages

Table 4: GlycoQuest search parameters.

Charge distribution and intesity of two different N-glycopeptides

Figure 3: Charge distribution and intensity of two different N-glycopeptides measured by CaptiveSpray and nanoBooster; A: CRPINATLAVEK and B: NVTSESTCCVAK.

A

B

Parameter Value

Submitted spectra CID spectra

Database UPS (from Sigma)

Variable modificationsCarbamidomethyl (C)Oxidation (M)

Peptide charge 2+, 3+, 4+, 5+, 6+

MS tolerance ± 0.3 Da

MS/MS tolerance ± 0.35 Da

#13C 1

Ion score threshold for significant peptide IDs

Identity score calculated by search engine

Protein assessmentAt least 1 peptide above the significance threshold

Table 3: Mascot search parameters.

Identification of glycan structures was performed using ProteinScape. To identify glycopeptides, CID spectra were classified on the basis of the presence of diagnostic oxonium ions (B-ions) and typical sugar distances (Y-ions). During this processing step, peptide and glycan masses were deduced from glycopeptide MS/MS spectra. Subsequently, glycan masses were submitted to a glycan search against the CarbBank database using the embedded search engine GlycoQuest.

ProteinScape overview

Figure 4: Example of a GlycoQuest search result.

LC-MS survey viewGlycan list

Fragment ion list

Glycan structure

Annotated spectrum

Annotated ETD spectrum

Figure 5: Annotated ETD spectrum of m/z 921.17 (+3): glycosylated CGLVPVLAENYNK from serotransferrin.

CGLVPVLAENYN411K

The search returned the glycan composition of fourteen glycopeptides, all of which had a biantennary complex type glycan structure with one or two neuraminic acids. Figure 4 shows an example of a GlycoQuest search result showing the identified glycan and corresponding fragment ions, LC-MS density plot, glycan structure view, and an annotated CID spectrum.

Glycopeptide sequencing and assignment of the glyco-sylation site was based on ETD data. Figure 5 shows a typical example of an identified glycopeptide sequence corresponding to CGLVPVLAENYN411K from serotransferrin.

This glycopeptide has a biantennary complex type glycan structure with two neuraminic acids attached. Other examples of unambiguously identified glycopeptides were QQQHLFGSN611VTDCSGNF (also from serotransferrin) and WVSN192K and LGACN96DTLQQLMEVFK from antithrombin-III.

The glycosylation status of the UPS sample is unknown as it is generally not tested for PTMs by the supplier. Therefore, different batches of the UPS may give different results in terms of their PTM status.

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Bruker Daltonik GmbH

Bremen · GermanyPhone +49 (0)421-2205-0 Fax +49 (0)421-2205-103 sales@bdal.de

Bruker Daltonics Inc.

Billerica, MA · USAPhone +1 (978) 663-3660 Fax +1 (978) 667-5993 ms-sales@bdal.com

Fremont, CA · USAPhone +1 (510) 683-4300 Fax +1 (510) 687-1217cam-sales@bruker.com

www.bruker.com

For research use only. Not for use in diagnostic procedures.

References

[1] Bruker Application Note LCMS-66: Kristina Neue, Andrea Kiehne,

Markus Meyer, Marcus Macht, Ulrike Schweiger-Hufnagel, Anja Resemann

(2012) Straightforward N-glycopeptide analysis combining fast ion trap data

acquisition with new ProteinScape functionalities

[2] Bruker Application Note LCMS-76: Kristina Marx, Anja Resemann,

Ulrike Schweiger-Hufnagel, Waltraud Evers, Andrea Kiehne, Markus Meyer

(2012) Identification of a Second N-glycosylation Site in a Human PSA

Sample by Combined CID/ETD Fragmentation

[3] In-depth Characterization of Glycopeptides by Combination of CID and

ETD Fragmentation after Charge State Enhancement; Andreas Brekenfeld;

Kristina Marx; Andrea Kiehne; Markus Meyer. ASMS 2013, Poster TP 716

[4] Charge enhancement of peptides, small and large proteins in a CaptiveSpray

Ionization (CSI) source. Pelzing M, Dolman S, and Nugent K. ASMS 2012,

Poster ThP 025

Conclusion

This study demonstrates the effective and beneficial combination of the CaptiveSpray nanoBooster ionization source and Fragment Triggered ETD on the amaZon speed ETD platform for greatly enhanced glycopeptide analysis in protein mixtures.

Because it causes improved signal intensities and a significant shift towards higher charge states, the use of the CaptiveSpray nanoBooster is the basis for glycopeptide detection and enhanced ETD fragmentation. The smart Fragment Triggered ETD acquisition mode enables an efficient combination of comprehensive protein identification by CID with in-depth glycopeptide analysis using both CID and ETD fragmentation.