Analysis of immunoglobulin glycosylation by LC-ESI-MS of glycopeptides and oligosaccharides

Journal Article (2008)
Author(s)

Johannes Stadlmann (BOKU-University of Natural Resources and Life Sciences)

Martin Pabst (BOKU-University of Natural Resources and Life Sciences)

Daniel Kolarich (BOKU-University of Natural Resources and Life Sciences)

Renate Kunert (BOKU-University of Natural Resources and Life Sciences)

F. Altmann (BOKU-University of Natural Resources and Life Sciences)

Affiliation
External organisation
DOI related publication
https://doi.org/10.1002/pmic.200700968
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Publication Year
2008
Language
English
Affiliation
External organisation
Issue number
14
Volume number
8
Pages (from-to)
2858-2871

Abstract

Two LC-ESI-MS methods for the analysis of antibody glycosylation are presented. In the first approach, tryptic glycopeptides are separated by RP chromatography and analyzed by ESI-MS. This “glycopeptide strategy” allows a protein- and subclass-specific quantitation of both neutral and sialylated glycan structures. Additional information about under- or deglycosylation and the protein backbone, e.g., termini, can be extracted from the same data. In the second LC-ESI-MS method, released oligosaccharides are separated on porous graphitic carbon (PGC). A complete structural assignment of neutral and sialylated oligosaccharides occurring on antibodies is thereby achieved in one chromatographic run. The two methods were applied to polyclonal human IgG, to commercial mAb expressed in CHO cells (Rituximab, Xolair, and Herceptin), in SP2/0 (Erbitux and Remicade) or NS0 cells (Zenapax) and the anti-HIV antibody 4E10 produced either in CHO cells or in a human cell line. Both methods require comparably little sample preparation and can be applied to SDS-PAGE bands. They both outperform non-MS methods in terms of reliability of peak assignment and MALDI-MS of underivatized glycans with regard to the recording of sialylated structures. Regarding fast and yet detailed structural assignment, LC-MS on graphitic carbon supersedes all other current methods.

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