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Highly-sensitive label-free deep profiling of N-glycans released from biomedically-relevant samples

Alterations of protein glycosylation can serve as sensitive and specific disease biomarkers. Labeling procedures for improved separation and detectability of oligosaccharides have several drawbacks, including incomplete derivatization, side-products, noticeable desialylation/defucosylation, sample l...

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Autores principales: Marie, Anne-Lise, Ray, Somak, Ivanov, Alexander R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10036494/
https://www.ncbi.nlm.nih.gov/pubmed/36959283
http://dx.doi.org/10.1038/s41467-023-37365-4
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author Marie, Anne-Lise
Ray, Somak
Ivanov, Alexander R.
author_facet Marie, Anne-Lise
Ray, Somak
Ivanov, Alexander R.
author_sort Marie, Anne-Lise
collection PubMed
description Alterations of protein glycosylation can serve as sensitive and specific disease biomarkers. Labeling procedures for improved separation and detectability of oligosaccharides have several drawbacks, including incomplete derivatization, side-products, noticeable desialylation/defucosylation, sample loss, and interference with downstream analyses. Here, we develop a label-free workflow based on high sensitivity capillary zone electrophoresis-mass spectrometry (CZE-MS) for profiling of native underivatized released N-glycans. Our workflow provides a >45-fold increase in signal intensity compared to the conventional CZE-MS approaches used for N-glycan analysis. Qualitative and quantitative N-glycan profiling of purified human serum IgG, bovine serum fetuin, bovine pancreas ribonuclease B, blood-derived extracellular vesicle isolates, and total plasma results in the detection of >250, >400, >150, >310, and >520 N-glycans, respectively, using injected amounts equivalent to <25 ng of model protein and nL-levels of plasma-derived samples. Compared to reported results for biological samples of similar amounts and complexity, the number of identified N-glycans is increased up to ~15-fold, enabling highly sensitive analysis of sample amounts as low as sub-0.2 nL of plasma volume equivalents. Furthermore, highly sialylated N-glycans are identified and structurally characterized, and untreated sialic acid-linkage isomers are resolved in a single CZE-MS analysis.
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spelling pubmed-100364942023-03-25 Highly-sensitive label-free deep profiling of N-glycans released from biomedically-relevant samples Marie, Anne-Lise Ray, Somak Ivanov, Alexander R. Nat Commun Article Alterations of protein glycosylation can serve as sensitive and specific disease biomarkers. Labeling procedures for improved separation and detectability of oligosaccharides have several drawbacks, including incomplete derivatization, side-products, noticeable desialylation/defucosylation, sample loss, and interference with downstream analyses. Here, we develop a label-free workflow based on high sensitivity capillary zone electrophoresis-mass spectrometry (CZE-MS) for profiling of native underivatized released N-glycans. Our workflow provides a >45-fold increase in signal intensity compared to the conventional CZE-MS approaches used for N-glycan analysis. Qualitative and quantitative N-glycan profiling of purified human serum IgG, bovine serum fetuin, bovine pancreas ribonuclease B, blood-derived extracellular vesicle isolates, and total plasma results in the detection of >250, >400, >150, >310, and >520 N-glycans, respectively, using injected amounts equivalent to <25 ng of model protein and nL-levels of plasma-derived samples. Compared to reported results for biological samples of similar amounts and complexity, the number of identified N-glycans is increased up to ~15-fold, enabling highly sensitive analysis of sample amounts as low as sub-0.2 nL of plasma volume equivalents. Furthermore, highly sialylated N-glycans are identified and structurally characterized, and untreated sialic acid-linkage isomers are resolved in a single CZE-MS analysis. Nature Publishing Group UK 2023-03-23 /pmc/articles/PMC10036494/ /pubmed/36959283 http://dx.doi.org/10.1038/s41467-023-37365-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Marie, Anne-Lise
Ray, Somak
Ivanov, Alexander R.
Highly-sensitive label-free deep profiling of N-glycans released from biomedically-relevant samples
title Highly-sensitive label-free deep profiling of N-glycans released from biomedically-relevant samples
title_full Highly-sensitive label-free deep profiling of N-glycans released from biomedically-relevant samples
title_fullStr Highly-sensitive label-free deep profiling of N-glycans released from biomedically-relevant samples
title_full_unstemmed Highly-sensitive label-free deep profiling of N-glycans released from biomedically-relevant samples
title_short Highly-sensitive label-free deep profiling of N-glycans released from biomedically-relevant samples
title_sort highly-sensitive label-free deep profiling of n-glycans released from biomedically-relevant samples
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10036494/
https://www.ncbi.nlm.nih.gov/pubmed/36959283
http://dx.doi.org/10.1038/s41467-023-37365-4
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