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An integrative strategy for quantitative analysis of the N-glycoproteome in complex biological samples

BACKGROUND: The complexity of protein glycosylation makes it difficult to characterize glycosylation patterns on a proteomic scale. In this study, we developed an integrated strategy for comparatively analyzing N-glycosylation/glycoproteins quantitatively from complex biological samples in a high-th...

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Detalles Bibliográficos
Autores principales: Wang, Ji, Zhou, Chuang, Zhang, Wei, Yao, Jun, Lu, Haojie, Dong, Qiongzhu, Zhou, Haijun, Qin, Lunxiu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3923275/
https://www.ncbi.nlm.nih.gov/pubmed/24428921
http://dx.doi.org/10.1186/1477-5956-12-4
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author Wang, Ji
Zhou, Chuang
Zhang, Wei
Yao, Jun
Lu, Haojie
Dong, Qiongzhu
Zhou, Haijun
Qin, Lunxiu
author_facet Wang, Ji
Zhou, Chuang
Zhang, Wei
Yao, Jun
Lu, Haojie
Dong, Qiongzhu
Zhou, Haijun
Qin, Lunxiu
author_sort Wang, Ji
collection PubMed
description BACKGROUND: The complexity of protein glycosylation makes it difficult to characterize glycosylation patterns on a proteomic scale. In this study, we developed an integrated strategy for comparatively analyzing N-glycosylation/glycoproteins quantitatively from complex biological samples in a high-throughput manner. This strategy entailed separating and enriching glycopeptides/glycoproteins using lectin affinity chromatography, and then tandem labeling them with (18)O/(16)O to generate a mass shift of 6 Da between the paired glycopeptides, and finally analyzing them with liquid chromatography-mass spectrometry (LC-MS) and the automatic quantitative method we developed based on Mascot Distiller. RESULTS: The accuracy and repeatability of this strategy were first verified using standard glycoproteins; linearity was maintained within a range of 1:10–10:1. The peptide concentration ratios obtained by the self-build quantitative method were similar to both the manually calculated and theoretical values, with a standard deviation (SD) of 0.023–0.186 for glycopeptides. The feasibility of the strategy was further confirmed with serum from hepatocellular carcinoma (HCC) patients and healthy individuals; the expression of 44 glycopeptides and 30 glycoproteins were significantly different between HCC patient and control serum. CONCLUSIONS: This strategy is accurate, repeatable, and efficient, and may be a useful tool for identification of disease-related N-glycosylation/glycoprotein changes.
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spelling pubmed-39232752014-03-04 An integrative strategy for quantitative analysis of the N-glycoproteome in complex biological samples Wang, Ji Zhou, Chuang Zhang, Wei Yao, Jun Lu, Haojie Dong, Qiongzhu Zhou, Haijun Qin, Lunxiu Proteome Sci Research BACKGROUND: The complexity of protein glycosylation makes it difficult to characterize glycosylation patterns on a proteomic scale. In this study, we developed an integrated strategy for comparatively analyzing N-glycosylation/glycoproteins quantitatively from complex biological samples in a high-throughput manner. This strategy entailed separating and enriching glycopeptides/glycoproteins using lectin affinity chromatography, and then tandem labeling them with (18)O/(16)O to generate a mass shift of 6 Da between the paired glycopeptides, and finally analyzing them with liquid chromatography-mass spectrometry (LC-MS) and the automatic quantitative method we developed based on Mascot Distiller. RESULTS: The accuracy and repeatability of this strategy were first verified using standard glycoproteins; linearity was maintained within a range of 1:10–10:1. The peptide concentration ratios obtained by the self-build quantitative method were similar to both the manually calculated and theoretical values, with a standard deviation (SD) of 0.023–0.186 for glycopeptides. The feasibility of the strategy was further confirmed with serum from hepatocellular carcinoma (HCC) patients and healthy individuals; the expression of 44 glycopeptides and 30 glycoproteins were significantly different between HCC patient and control serum. CONCLUSIONS: This strategy is accurate, repeatable, and efficient, and may be a useful tool for identification of disease-related N-glycosylation/glycoprotein changes. BioMed Central 2014-01-15 /pmc/articles/PMC3923275/ /pubmed/24428921 http://dx.doi.org/10.1186/1477-5956-12-4 Text en Copyright © 2014 Wang et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Wang, Ji
Zhou, Chuang
Zhang, Wei
Yao, Jun
Lu, Haojie
Dong, Qiongzhu
Zhou, Haijun
Qin, Lunxiu
An integrative strategy for quantitative analysis of the N-glycoproteome in complex biological samples
title An integrative strategy for quantitative analysis of the N-glycoproteome in complex biological samples
title_full An integrative strategy for quantitative analysis of the N-glycoproteome in complex biological samples
title_fullStr An integrative strategy for quantitative analysis of the N-glycoproteome in complex biological samples
title_full_unstemmed An integrative strategy for quantitative analysis of the N-glycoproteome in complex biological samples
title_short An integrative strategy for quantitative analysis of the N-glycoproteome in complex biological samples
title_sort integrative strategy for quantitative analysis of the n-glycoproteome in complex biological samples
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3923275/
https://www.ncbi.nlm.nih.gov/pubmed/24428921
http://dx.doi.org/10.1186/1477-5956-12-4
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