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BioMed Research International Volume 2018 ,2018-08-14
N-Linked Glycopeptide Identification Based on Open Mass Spectral Library Search
Research Article
Zhiwu An 1 , 2 Qingbo Shu 2 , 3 Hao Lv 1 , 2 , 4 Lian Shu 2 , 3 Jifeng Wang 3 Fuquan Yang 2 , 3 Yan Fu 1 , 2
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DOI:10.1155/2018/1564136
Received 2018-05-04, accepted for publication 2018-07-29, Published 2018-07-29
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摘要

Confident characterization of intact glycopeptides is a challenging task in mass spectrometry-based glycoproteomics due to microheterogeneity of glycosylation, complexity of glycans, and insufficient fragmentation of peptide bones. Open mass spectral library search is a promising computational approach to peptide identification, but its potential in the identification of glycopeptides has not been fully explored. Here we present pMatchGlyco, a new spectral library search tool for intact N-linked glycopeptide identification using high-energy collisional dissociation (HCD) tandem mass spectrometry (MS/MS) data. In pMatchGlyco, (1) MS/MS spectra of deglycopeptides are used to create spectral library, (2) MS/MS spectra of glycopeptides are matched to the spectra in library in an open (precursor tolerant) manner and the glycans are inferred, and (3) a false discovery rate is estimated for top-scored matches above a threshold. The efficiency and reliability of pMatchGlyco were demonstrated on a data set of mixture sample of six standard glycoproteins and a complex glycoprotein data set generated from human cancer cell line OVCAR3.

授权许可

Copyright © 2018 Zhiwu An et al. 2018
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.

通讯作者

1. Fuquan Yang.University of Chinese Academy of Sciences, Beijing 100049, China, ucas.ac.cn;Laboratory of Proteomics, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China, cas.cn.fqyang@ibp.ac.cn
2. Yan Fu.National Center for Mathematics and Interdisciplinary Sciences, Key Laboratory of Random Complex Structures and Data Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100101, China, cas.cn;University of Chinese Academy of Sciences, Beijing 100049, China, ucas.ac.cn.yfu@amss.ac.cn

推荐引用方式

Zhiwu An,Qingbo Shu,Hao Lv,Lian Shu,Jifeng Wang,Fuquan Yang,Yan Fu. N-Linked Glycopeptide Identification Based on Open Mass Spectral Library Search. BioMed Research International ,Vol.2018(2018)

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参考文献
[1] A. M. Mayampurath, Y. Wu, Z. M. Segu, Y. Mechref. et al.(2011). Improving confidence in detection and characterization of protein n-glycosylation sites and microheterogeneity. Rapid Communications in Mass Spectrometry.25(14):2007-2019. DOI: 10.1016/j.cell.2010.11.008.
[2] K. Lynn, C. Chen, T. M. Lih, C. Cheng. et al.(2015). MAGIC: An Automated N-Linked Glycoprotein Identification Tool Using a Y1-Ion Pattern Matching Algorithm and. Analytical Chemistry.87(4):2466-2473. DOI: 10.1016/j.cell.2010.11.008.
[3] L. Cao, N. Tolić, Y. Qu, D. Meng. et al.(2014). Characterization of intact N- and O-linked glycopeptides using higher energy collisional dissociation. Analytical Biochemistry.452(1):96-102. DOI: 10.1016/j.cell.2010.11.008.
[4] S. Toghi Eshghi, P. Shah, W. Yang, X. Li. et al.(2015). GPQuest: A spectral library matching algorithm for site-specific assignment of tandem mass spectra to intact n-glycopeptides. Analytical Chemistry.87(10):5181-5188. DOI: 10.1016/j.cell.2010.11.008.
[5] J. E. Elias, S. P. Gygi. (2007). Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry. Nature Methods.4(3):207-214. DOI: 10.1016/j.cell.2010.11.008.
[6] L. He, L. Xin, B. Shan, G. A. Lajoie. et al.(2014). GlycoMaster DB: Software to assist the automated identification of N-linked glycopeptides by tandem mass spectrometry. Journal of Proteome Research.13(9):3881-3895. DOI: 10.1016/j.cell.2010.11.008.
[7] D. Ye, Y. Fu, R.-X. Sun, H.-P. Wang. et al.(2010). Open MS/MS spectral library search to identify unanticipated post-translational modifications and increase spectral identification rate. Bioinformatics.26(12):i399-i406. DOI: 10.1016/j.cell.2010.11.008.
[8] T. Nishikaze, S.-I. Kawabata, K. Tanaka. (2014). Fragmentation characteristics of deprotonated N-linked glycopeptides: Influences of amino acid composition and sequence. Journal of The American Society for Mass Spectrometry.25(6):988-998. DOI: 10.1016/j.cell.2010.11.008.
[9] Z.-F. Yuan, C. Liu, H.-P. Wang, R.-X. Sun. et al.(2012). pParse: A method for accurate determination of monoisotopic peaks in high-resolution mass spectra. Proteomics.12(2):226-235. DOI: 10.1016/j.cell.2010.11.008.
[10] G. W. Hart, R. J. Copeland. (2010). Glycomics hits the big time. Cell.143(5):672-676. DOI: 10.1016/j.cell.2010.11.008.
[11] A. Mayampurath, C.-Y. Yu, E. Song, J. Balan. et al.(2014). Computational framework for identification of intact glycopeptides in complex samples. Analytical Chemistry.86(1):453-463. DOI: 10.1016/j.cell.2010.11.008.
[12] S. A. Beausoleil, J. Villén, S. A. Gerber, J. Rush. et al.(2006). A probability-based approach for high-throughput protein phosphorylation analysis and site localization. Nature Biotechnology.24(10):1285-1292. DOI: 10.1016/j.cell.2010.11.008.
[13] H. Zhang, X. Li, D. B. Martin, R. Aebersold. et al.(2003). Identification and quantification of N-linked glycoproteins using hydrazide chemistry, stable isotope labeling and mass spectrometry. Nature Biotechnology.21(6):660-666. DOI: 10.1016/j.cell.2010.11.008.
[14] M. Bern, Y. J. Kil, C. Becker. (2012). Advanced Peptide And Protein Identification Software. Curr Protoc Bioinformatics.20. DOI: 10.1016/j.cell.2010.11.008.
[15] K. F. Medzihradszky, K. Kaasik, R. J. Chalkley. (2015). Tissue-specific glycosylation at the glycopeptide level. Molecular & Cellular Proteomics.14(8):2103-2110. DOI: 10.1016/j.cell.2010.11.008.
[16] P. Hägglund, J. Bunkenborg, F. Elortza, O. N. Jensen. et al.(2004). A new strategy for identification of N-glycosylated proteins and unambiguous assignment of their glycosylation sites using HILIC enrichment and partial deglycosylation. Journal of Proteome Research.3(3):556-566. DOI: 10.1016/j.cell.2010.11.008.
[17] R. Ranzinger, S. Herget, C.-W. Von Der Lieth, M. Frank. et al.(2011). GlycomeDB-A unified database for carbohydrate structures. Nucleic Acids Research.39(1):D373-D376. DOI: 10.1016/j.cell.2010.11.008.
[18] P. Pompach, K. B. Chandler, R. Lan, N. Edwards. et al.(2012). Semi-automated identification of N-glycopeptides by hydrophilic interaction chromatography, nano-reverse-phase LC-MS/MS, and glycan database search. Journal of Proteome Research.11(3):1728-1740. DOI: 10.1016/j.cell.2010.11.008.
[19] M. C. Chambers, B. Maclean, R. Burke, D. Amodei. et al.(2012). A cross-platform toolkit for mass spectrometry and proteomics. Nature Biotechnology.30(10):918-920. DOI: 10.1016/j.cell.2010.11.008.
[20] W. Zeng, M. Liu, Y. Zhang, J. Wu. et al.(2016). pGlyco: a pipeline for the identification of intact N-glycopeptides by using HCD- and CID-MS/MS and MS3. Scientific Reports.6(1). DOI: 10.1016/j.cell.2010.11.008.
[21] M. Liu, W. Zeng, P. Fang, W. Cao. et al.(2017). pGlyco 2.0 enables precision N-glycoproteomics with comprehensive quality control and one-step mass spectrometry for intact glycopeptide identification. Nature Communications.8(1). DOI: 10.1016/j.cell.2010.11.008.
[22] N. E. Scott, B. L. Parker, A. M. Connolly, J. Paulech. et al.(2011). Simultaneous glycan-peptide characterization using hydrophilic interaction chromatography and parallel fragmentation by CID, higher energy collisional dissociation, and electron transfer dissociation MS applied to the N-linked glycoproteome of Campylobacter jejuni. Molecular & Cellular Proteomics.10(2). DOI: 10.1016/j.cell.2010.11.008.
[23] J. S. Strum, C. C. Nwosu, S. Hua, S. R. Kronewitter. et al.(2013). Automated assignments of N- and O-site specific glycosylation with extensive glycan heterogeneity of glycoprotein mixtures. Analytical Chemistry.85(12):5666-5675. DOI: 10.1016/j.cell.2010.11.008.
[24] L. He, J. Diedrich, Y.-Y. Chu, J. R. Yates. et al.(2015). Extracting Accurate Precursor Information for Tandem Mass Spectra by RawConverter. Analytical Chemistry.87(22):11361-11367. DOI: 10.1016/j.cell.2010.11.008.
[25] L.-H. Wang, D.-Q. Li, Y. Fu, H.-P. Wang. et al.(2007). pFind 2.0: a software package for peptide and protein identification via tandem mass spectrometry. Rapid Communications in Mass Spectrometry.21(18):2985-2991. DOI: 10.1016/j.cell.2010.11.008.
[26] K. B. Chandler, P. Pompach, R. Goldman, N. Edwards. et al.(2013). Exploring site-specific N-glycosylation microheterogeneity of haptoglobin using glycopeptide CID tandem mass spectra and glycan database search. Journal of Proteome Research.12(8):3652-3666. DOI: 10.1016/j.cell.2010.11.008.
[27] S. Sun, P. Shah, S. T. Eshghi, W. Yang. et al.(2016). Comprehensive analysis of protein glycosylation by solid-phase extraction of N-linked glycans and glycosite-containing peptides. Nature Biotechnology.34(1):84-88. DOI: 10.1016/j.cell.2010.11.008.
[28] Y. Fu, Q. Yang, R. Sun, D. Li. et al.(2004). Exploiting the kernel trick to correlate fragment ions for peptide identification via tandem mass spectrometry. Bioinformatics.20(12):1948-1954. DOI: 10.1016/j.cell.2010.11.008.
[29] K. Cheng, R. Chen, D. Seebun, M. Ye. et al.(2014). Large-scale characterization of intact N-glycopeptides using an automated glycoproteomic method. Journal of Proteomics.110:145-154. DOI: 10.1016/j.cell.2010.11.008.
[30] H. Wang, C. Wong, A. Chin, A. Taguchi. et al.(2011). Integrated mass spectrometry–based analysis of plasma glycoproteins and their glycan modifications. Nature Protocols.6(3):253-269. DOI: 10.1016/j.cell.2010.11.008.
[31] W. R. Alley, B. F. Mann, M. V. Novotny. (2013). High-sensitivity analytical approaches for the structural characterization of glycoproteins. Chemical Reviews.113(4):2668-2732. DOI: 10.1016/j.cell.2010.11.008.
[32] D. F. Zielinska, F. Gnad, J. R. Wiśniewski, M. Mann. et al.(2010). Precision mapping of an in vivo N-glycoproteome reveals rigid topological and sequence constraints. Cell.141(5):897-907. DOI: 10.1016/j.cell.2010.11.008.
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