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Data-independent oxonium ion profiling of multi-glycosylated biotherapeutics

The characterization of glycosylation is required for many protein therapeutics. The emergence of antibody and antibody-like molecules with multiple glycan attachment sites has rendered glycan analysis increasingly more complicated. Reliance on site-specific glycopeptide analysis is therefore necess...

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Autores principales: Madsen, James A., Farutin, Victor, Lin, Yin Yin, Smith, Stephen, Capila, Ishan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6204843/
https://www.ncbi.nlm.nih.gov/pubmed/30067433
http://dx.doi.org/10.1080/19420862.2018.1494106
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author Madsen, James A.
Farutin, Victor
Lin, Yin Yin
Smith, Stephen
Capila, Ishan
author_facet Madsen, James A.
Farutin, Victor
Lin, Yin Yin
Smith, Stephen
Capila, Ishan
author_sort Madsen, James A.
collection PubMed
description The characterization of glycosylation is required for many protein therapeutics. The emergence of antibody and antibody-like molecules with multiple glycan attachment sites has rendered glycan analysis increasingly more complicated. Reliance on site-specific glycopeptide analysis is therefore necessary to fully analyze multi-glycosylated biotherapeutics. Established glycopeptide methodologies have generally utilized a priori knowledge of the glycosylation states of the investigated protein(s), database searching of results generated from data-dependent liquid chromatography–tandem mass spectrometry workflows, and extracted ion quantitation of the individual identified species. However, the inherent complexity of glycosylation makes predicting all glycoforms on all glycosylation sites extremely challenging, if not impossible. That is, only the “knowns” are assessed. Here, we describe an agnostic methodology to qualitatively and quantitatively assess both “known” and “unknown” site-specific glycosylation for biotherapeutics that contain multiple glycosylation sites. The workflow uses data-independent, all ion fragmentation to generate glycan oxonium ions, which are then extracted across the entirety of the chromatographic timeline to produce a glycan-specific “fingerprint” of the glycoprotein sample. We utilized both HexNAc and sialic acid oxonium ion profiles to quickly assess the presence of Fab glycosylation in a therapeutic monoclonal antibody, as well as for high-throughput comparisons of multi-glycosylated protein drugs derived from different clones to a reference product. An automated method was created to rapidly assess oxonium profiles between samples, and to provide a quantitative assessment of similarity.
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spelling pubmed-62048432018-10-30 Data-independent oxonium ion profiling of multi-glycosylated biotherapeutics Madsen, James A. Farutin, Victor Lin, Yin Yin Smith, Stephen Capila, Ishan MAbs Report The characterization of glycosylation is required for many protein therapeutics. The emergence of antibody and antibody-like molecules with multiple glycan attachment sites has rendered glycan analysis increasingly more complicated. Reliance on site-specific glycopeptide analysis is therefore necessary to fully analyze multi-glycosylated biotherapeutics. Established glycopeptide methodologies have generally utilized a priori knowledge of the glycosylation states of the investigated protein(s), database searching of results generated from data-dependent liquid chromatography–tandem mass spectrometry workflows, and extracted ion quantitation of the individual identified species. However, the inherent complexity of glycosylation makes predicting all glycoforms on all glycosylation sites extremely challenging, if not impossible. That is, only the “knowns” are assessed. Here, we describe an agnostic methodology to qualitatively and quantitatively assess both “known” and “unknown” site-specific glycosylation for biotherapeutics that contain multiple glycosylation sites. The workflow uses data-independent, all ion fragmentation to generate glycan oxonium ions, which are then extracted across the entirety of the chromatographic timeline to produce a glycan-specific “fingerprint” of the glycoprotein sample. We utilized both HexNAc and sialic acid oxonium ion profiles to quickly assess the presence of Fab glycosylation in a therapeutic monoclonal antibody, as well as for high-throughput comparisons of multi-glycosylated protein drugs derived from different clones to a reference product. An automated method was created to rapidly assess oxonium profiles between samples, and to provide a quantitative assessment of similarity. Taylor & Francis 2018-08-01 /pmc/articles/PMC6204843/ /pubmed/30067433 http://dx.doi.org/10.1080/19420862.2018.1494106 Text en © 2018 James A. Madsen, Victor Farutin, Yin Yin Lin, Stephen Smith, and Ishan Capila. Published 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
Madsen, James A.
Farutin, Victor
Lin, Yin Yin
Smith, Stephen
Capila, Ishan
Data-independent oxonium ion profiling of multi-glycosylated biotherapeutics
title Data-independent oxonium ion profiling of multi-glycosylated biotherapeutics
title_full Data-independent oxonium ion profiling of multi-glycosylated biotherapeutics
title_fullStr Data-independent oxonium ion profiling of multi-glycosylated biotherapeutics
title_full_unstemmed Data-independent oxonium ion profiling of multi-glycosylated biotherapeutics
title_short Data-independent oxonium ion profiling of multi-glycosylated biotherapeutics
title_sort data-independent oxonium ion profiling of multi-glycosylated biotherapeutics
topic Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6204843/
https://www.ncbi.nlm.nih.gov/pubmed/30067433
http://dx.doi.org/10.1080/19420862.2018.1494106
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