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Classification of Tandem Mass Spectra for Identification of N- and O-linked Glycopeptides

Analysis of intact glycopeptides by mass spectrometry is essential to determining the microheterogeneity of protein glycosylation. Higher-energy collisional dissociation (HCD) fragmentation of glycopeptides generates mono- or disaccharide ions called oxonium ions that carry information about the str...

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Autores principales: Toghi Eshghi, Shadi, Yang, Weiming, Hu, Yingwei, Shah, Punit, Sun, Shisheng, Li, Xingde, Zhang, Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5116676/
https://www.ncbi.nlm.nih.gov/pubmed/27869200
http://dx.doi.org/10.1038/srep37189
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author Toghi Eshghi, Shadi
Yang, Weiming
Hu, Yingwei
Shah, Punit
Sun, Shisheng
Li, Xingde
Zhang, Hui
author_facet Toghi Eshghi, Shadi
Yang, Weiming
Hu, Yingwei
Shah, Punit
Sun, Shisheng
Li, Xingde
Zhang, Hui
author_sort Toghi Eshghi, Shadi
collection PubMed
description Analysis of intact glycopeptides by mass spectrometry is essential to determining the microheterogeneity of protein glycosylation. Higher-energy collisional dissociation (HCD) fragmentation of glycopeptides generates mono- or disaccharide ions called oxonium ions that carry information about the structure of the fragmented glycans. Here, we investigated the link between glycan structures and the intensity of oxonium ions in the spectra of glycopeptides and utilized this information to improve the identification of glycopeptides in biological samples. Tandem spectra of glycopeptides from fetuin, glycophorin A, ovalbumin and gp120 tryptic digests were used to build a spectral database of N- and O-linked glycopeptides. Logistic regression was applied to this database to develop model to distinguish between the spectra of N- and O-linked glycopeptides. Remarkably, the developed model was found to reliably distinguish between the N- and O-linked glycopeptides using the spectral features of the oxonium ions using verification spectral set. Finally, the performance of the developed predictive model was evaluated in HILIC enriched glycopeptides extracted from human serum. The results showed that pre-classification of tandem spectra based on their glycosylation type improved the identification of N-linked glycopeptides. The developed model facilitates interpretation of tandem mass spectrometry data for assignment of glycopeptides.
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spelling pubmed-51166762016-11-28 Classification of Tandem Mass Spectra for Identification of N- and O-linked Glycopeptides Toghi Eshghi, Shadi Yang, Weiming Hu, Yingwei Shah, Punit Sun, Shisheng Li, Xingde Zhang, Hui Sci Rep Article Analysis of intact glycopeptides by mass spectrometry is essential to determining the microheterogeneity of protein glycosylation. Higher-energy collisional dissociation (HCD) fragmentation of glycopeptides generates mono- or disaccharide ions called oxonium ions that carry information about the structure of the fragmented glycans. Here, we investigated the link between glycan structures and the intensity of oxonium ions in the spectra of glycopeptides and utilized this information to improve the identification of glycopeptides in biological samples. Tandem spectra of glycopeptides from fetuin, glycophorin A, ovalbumin and gp120 tryptic digests were used to build a spectral database of N- and O-linked glycopeptides. Logistic regression was applied to this database to develop model to distinguish between the spectra of N- and O-linked glycopeptides. Remarkably, the developed model was found to reliably distinguish between the N- and O-linked glycopeptides using the spectral features of the oxonium ions using verification spectral set. Finally, the performance of the developed predictive model was evaluated in HILIC enriched glycopeptides extracted from human serum. The results showed that pre-classification of tandem spectra based on their glycosylation type improved the identification of N-linked glycopeptides. The developed model facilitates interpretation of tandem mass spectrometry data for assignment of glycopeptides. Nature Publishing Group 2016-11-21 /pmc/articles/PMC5116676/ /pubmed/27869200 http://dx.doi.org/10.1038/srep37189 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Toghi Eshghi, Shadi
Yang, Weiming
Hu, Yingwei
Shah, Punit
Sun, Shisheng
Li, Xingde
Zhang, Hui
Classification of Tandem Mass Spectra for Identification of N- and O-linked Glycopeptides
title Classification of Tandem Mass Spectra for Identification of N- and O-linked Glycopeptides
title_full Classification of Tandem Mass Spectra for Identification of N- and O-linked Glycopeptides
title_fullStr Classification of Tandem Mass Spectra for Identification of N- and O-linked Glycopeptides
title_full_unstemmed Classification of Tandem Mass Spectra for Identification of N- and O-linked Glycopeptides
title_short Classification of Tandem Mass Spectra for Identification of N- and O-linked Glycopeptides
title_sort classification of tandem mass spectra for identification of n- and o-linked glycopeptides
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5116676/
https://www.ncbi.nlm.nih.gov/pubmed/27869200
http://dx.doi.org/10.1038/srep37189
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