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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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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. |
format | Online Article Text |
id | pubmed-3923275 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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