N-Glycopeptide Identification from CID Tandem Mass Spectra using
Glycan Databases and False Discovery Rate Estimation
Kevin B. Chandler, Petr Pompach, Radoslav Goldman, Nathan J. Edwards
Georgetown University, Department of Biochemistry and Molecular & Cellular Biology, Washington, DC
Introduction and Background
Hypothesis and Aims
• Over half of all proteins are glycosylated (this rate is higher for
secreted, cell-surface and extracellular matrix proteins)
• Glycosylation mediates cell-cell & cell-matrix interactions
• N-linked glycosylation is enzyme-directed, occurs on Asn residues
• We hypothesize that N-glycopeptide MS/MS data interpretation
can be automated by adopting an algorithm that uses (1)
oxonium marker ions and intact peptide peak filters, (2) the
sequence(s) of the protein(s) of interest and (3) mass-matching
to publicly available glycan databases to match glycan-peptide
pairs to glycopeptide MS/MS spectra.
within the motif NXS/T (X ≠ Pro)
• Tandem mass spectrometry (MS/MS) is used to study protein
glycosylation; however, there are few software tools to aid in processing
and interpretation of large glycopeptide MS/MS datasets, and manual
interpretation of datasets is time consuming
• The aim of this research is to develop a novel software tool for rapid
interpretation of glycopeptide MS/MS datasets to facilitate the study
of glycoprotein microheterogeneity
GlycoPeptideSearch Software – Glycopeptide Discovery Workflow
GlycoPeptideSearch Scheme
Methods: GlycoPeptideSearch Software
11 x LC-MS/MS
MS/MS Spectra
3288
w/ glycan oxonium ion
(204, 366) peaks
2887
w/ 2+ “peptide” peaks
317
GlycomeDB1
263
Distinct
Glycopeptides
53
Test Dataset (Haptoglobin Glycopeptides)
• Proteolytic digest of Haptoglobin with trypsin and GluC
• Hydrophilic interaction liquid chromatography (HILIC) of glycopeptides
• Eleven glycopeptide fractions analyzed by nanoC18 RP LC-MS/MS using a
Q-STAR Elite mass-spectrometer.
• IDA: Four most abundant ions with 20 sec exclusion.
• 15,780 MS and 3,288 MS/MS spectra (msconvert)
• Automated in silico digestion (Trypsin, GluC) of user-submitted
protein sequence & N-glycosylation site ID
• Fixed (carbamidomethylation) & variable modifications (Methionine
oxidation) considered
• Spectra filtered for glycan oxonium ions & peptide + N-linked core
fragments & mass-lookup in GlycomeDB (glycan database)
• Isotope Cluster Scoring performed on precursor ion
• Decoy (non-motif containing) peptides submitted to search to enable
estimation of the False Discovery Rate
• Open format (XML) spectra input and Excel output.
Summary of Haptoglobin Glycopeptides
Controlling Error Using Spectra Filters and Hit Filters
No. of Accepted Spectra
Peptide Intensity Threshold
450
400
350
300
250
200
150
100
50
0
I=5
I=3
I=4
I=2
I=1
FDR
Determination
I = 10
I = 20
I = 30
0.0
1.0
2.0
3.0
4.0
5.0
6.0
Estimated FDR (%)
7.0
8.0
9.0
Target
Peptides
(with
NXS/T)
Decoy
Peptides
(without
motif)
Peptide Fragments (#)
# Accepted Spectra
600
F=0
GPS
500
400
300
Sample MS/MS Spectrum: Fraction 17, Scan 1407
F=2
200
100
F=3
F=4
0
0
5
10
15
Estimated FDR (%)
20
25
Target and Decoy
Spectra Hits
# Accepted Spectra
Isotope Cluster Score
350
300
250
200
150
100
50
0
IC = 50
IC = 20
IC = 10
IC = 5
IC = 2
IC = 1
0
2
4
IC = 100
IC = 200
6
8
10
Estimated FDR (%)
IC = 9999
12
FDR
14
References
Results and Conclusion
1. Ranzinger, Herget, von der Lieth, Frank. Nucleic Acids Res.
39(Database issue):D373-376 (2011).
• 52 glycan-peptide pairs matched 263 spectra (3.9% FDR).
• 52% (136) of filtered spectra matched a single glycopeptide pair (<0.2 Da), only 8 spectra matched
2. Fujimura, Shinohara, Tossot, Pang, Kurogochi, Saito, Arai, Sadilek,
glycopeptide pairs representing > 1 peptide.
• 27 distinct non-isobaric glycans at 4 sites were discovered, consistent with published reports2.
3. Goldberg, Sutton-Smith, Paulson, Dell. Proteomics 5:865-875
Murayama, Dell, Nishimura, Hakomori. Int. J. Cancer 122:39–49
(2008).
(2005).
4. Pompach, Chandler, Lan, Edwards, Goldman. J.Proteome Res. 11
(3); 1728-40 (2012).
Conclusion: Using characteristics of glycopeptide spectra including
oxonium ions and intact peptide peaks, it is possible to automate
glycopeptide CID MS/MS data interpretation with low false discovery.
Acknowledgements
Kevin B Chandler is supported by a Graduate Research Fellowship
from the National Science Foundation. Nathan J Edwards is
supported, in part, by NIH/NCI/CPTI grant CA126189. Rado slav
Goldman is supported by NCI’s R01 CA115625 and CA135069.