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Glycan characterization of the NIST RM monoclonal antibody using a total analytical solution: From sample preparation to data analysis

Glycosylation is an important attribute of biopharmaceutical products to monitor from development through production. However, glycosylation analysis has traditionally been a time-consuming process with long sample preparation protocols and manual interpretation of the data. To address the challenge...

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Autores principales: Hilliard, Mark, Alley, William R., McManus, Ciara A., Yu, Ying Qing, Hallinan, Sinead, Gebler, John, Rudd, Pauline M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5680791/
https://www.ncbi.nlm.nih.gov/pubmed/28895795
http://dx.doi.org/10.1080/19420862.2017.1377381
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author Hilliard, Mark
Alley, William R.
McManus, Ciara A.
Yu, Ying Qing
Hallinan, Sinead
Gebler, John
Rudd, Pauline M.
author_facet Hilliard, Mark
Alley, William R.
McManus, Ciara A.
Yu, Ying Qing
Hallinan, Sinead
Gebler, John
Rudd, Pauline M.
author_sort Hilliard, Mark
collection PubMed
description Glycosylation is an important attribute of biopharmaceutical products to monitor from development through production. However, glycosylation analysis has traditionally been a time-consuming process with long sample preparation protocols and manual interpretation of the data. To address the challenges associated with glycan analysis, we developed a streamlined analytical solution that covers the entire process from sample preparation to data analysis. In this communication, we describe the complete analytical solution that begins with a simplified and fast N-linked glycan sample preparation protocol that can be completed in less than 1 hr. The sample preparation includes labelling with RapiFluor-MS tag to improve both fluorescence (FLR) and mass spectral (MS) sensitivities. Following HILIC-UPLC/FLR/MS analyses, the data are processed and a library search based on glucose units has been included to expedite the task of structural assignment. We then applied this total analytical solution to characterize the glycosylation of the NIST Reference Material mAb 8761. For this glycoprotein, we confidently identified 35 N-linked glycans and all three major classes, high mannose, complex, and hybrid, were present. The majority of the glycans were neutral and fucosylated; glycans featuring N-glycolylneuraminic acid and those with two galactoses connected via an α1,3-linkage were also identified.
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spelling pubmed-56807912017-11-17 Glycan characterization of the NIST RM monoclonal antibody using a total analytical solution: From sample preparation to data analysis Hilliard, Mark Alley, William R. McManus, Ciara A. Yu, Ying Qing Hallinan, Sinead Gebler, John Rudd, Pauline M. MAbs Report Glycosylation is an important attribute of biopharmaceutical products to monitor from development through production. However, glycosylation analysis has traditionally been a time-consuming process with long sample preparation protocols and manual interpretation of the data. To address the challenges associated with glycan analysis, we developed a streamlined analytical solution that covers the entire process from sample preparation to data analysis. In this communication, we describe the complete analytical solution that begins with a simplified and fast N-linked glycan sample preparation protocol that can be completed in less than 1 hr. The sample preparation includes labelling with RapiFluor-MS tag to improve both fluorescence (FLR) and mass spectral (MS) sensitivities. Following HILIC-UPLC/FLR/MS analyses, the data are processed and a library search based on glucose units has been included to expedite the task of structural assignment. We then applied this total analytical solution to characterize the glycosylation of the NIST Reference Material mAb 8761. For this glycoprotein, we confidently identified 35 N-linked glycans and all three major classes, high mannose, complex, and hybrid, were present. The majority of the glycans were neutral and fucosylated; glycans featuring N-glycolylneuraminic acid and those with two galactoses connected via an α1,3-linkage were also identified. Taylor & Francis 2017-09-12 /pmc/articles/PMC5680791/ /pubmed/28895795 http://dx.doi.org/10.1080/19420862.2017.1377381 Text en © 2017 The Author(s). Published with license by Taylor & Francis Group, LLC http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
spellingShingle Report
Hilliard, Mark
Alley, William R.
McManus, Ciara A.
Yu, Ying Qing
Hallinan, Sinead
Gebler, John
Rudd, Pauline M.
Glycan characterization of the NIST RM monoclonal antibody using a total analytical solution: From sample preparation to data analysis
title Glycan characterization of the NIST RM monoclonal antibody using a total analytical solution: From sample preparation to data analysis
title_full Glycan characterization of the NIST RM monoclonal antibody using a total analytical solution: From sample preparation to data analysis
title_fullStr Glycan characterization of the NIST RM monoclonal antibody using a total analytical solution: From sample preparation to data analysis
title_full_unstemmed Glycan characterization of the NIST RM monoclonal antibody using a total analytical solution: From sample preparation to data analysis
title_short Glycan characterization of the NIST RM monoclonal antibody using a total analytical solution: From sample preparation to data analysis
title_sort glycan characterization of the nist rm monoclonal antibody using a total analytical solution: from sample preparation to data analysis
topic Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5680791/
https://www.ncbi.nlm.nih.gov/pubmed/28895795
http://dx.doi.org/10.1080/19420862.2017.1377381
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