Capillary (Gel) Electrophoresis-Based Methods for Immunoglobulin (G) Glycosylation Analysis

Abstract

The in-depth characterization of protein glycosylation has become indispensable in many research fields and in the biopharmaceutical industry. Especially knowledge about modulations in immunoglobulin G (IgG) N-glycosylation and their effect on immunity enabled a better understanding of human diseases and the development of new, more effective drugs for their treatment. This chapter provides a deeper insight into capillary (gel) electrophoresis-based (C(G)E) glycan analysis, addressing its impressive performance and possibilities, its great potential regarding real high-throughput for large cohort studies, as well as its challenges and limitations. We focus on the latest developments with respect to miniaturization and mass spectrometry coupling, as well as data analysis and interpretation. The use of exoglycosidase sequencing in combination with current C(G)E technology is discussed, highlighting possible difficulties and pitfalls. The application section describes the detailed characterization of N-glycosylation, utilizing multiplexed CGE with laser-induced fluorescence detection (xCGE-LIF). Besides a comprehensive overview on antibody glycosylation by comparing species-specific IgGs and human immunoglobulins A, D, E, G, and M, the chapter comprises a comparison of therapeutic monoclonal antibodies from different production cell lines, as well as a detailed characterization of Fab and Fc glycosylation. These examples illustrate the full potential of C(G)E, resolving the smallest differences in sugar composition and structure.

Reliable N-Glycan Analysis–Removal of Frequently Occurring Oligosaccharide Impurities by Enzymatic Degradation

“…Promising enzyme candidates for this task are glucoside hydrolases. Therefore, we screened a selection of ten commercially available glucoside hydrolases using multiplexed capillary gel electrophoresis with laser-induced fluorescence detection (xCGE-LIF) [ 22 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 ] with 8-aminopyrene-1,3,6-trisulfonic acid (APTS)-labeled maltodextrins and dextrans as standard substrates. We also paid particular attention to show the activity of selected enzymes on OSIs in a complex sample matrix, while having no side-activity on N -glycans.…”

Unambiguous identification of α-Gal epitopes in intact monoclonal antibodies by NMR spectroscopy

“…Released N-glycans were prepared using a glyXprep™ kit and analyzed on a xCGE-LIF-based glyXboxCE™ system (glyXera, Magdeburg, Germany), according to Cajic et al 40 For migration time alignment, crucial for glycan peak annotation via migration time matching with database entries of glyXbaseCE™ (glyXera), 1.0 μL of sample was mixed with 1.0 μL of 2 nd NormMiX™ (glyXera) and 1.0 μL prediluted GeneScan™ 500 LIZ® Size Standard. The mixture was combined with 6.0 μL glyXinject (glyXera) and subjected to xCGE-LIF analysis.…”

High-Throughput Glycomic Methods

“…151 The development of databases containing CGE-LIF separated glycans has been lagging behind HPLC/UHPLC glycan databases due to more complex structural confirmation of individual glycans caused by difficulties of CGE coupling to MS. However, this is slowly changing, and nowadays several expanding databases, e.g., GUcal 152 (recently broadened with the GlycoStore data) 152,153 and glyXbase, 154 exist (Table 1). Populating these databases with glycans labeled with alternative fluorescent labels and originating from glycoproteins other than human IgG will facilitate the use of CGE-LIF technology for low-and HT glycomic studies.…”

“…Most of the current HT glycomics data processing methods are designed to target specific sets of analytes and prior to data processing, the glycomic analytes present in the sample should be explored and identified by employing strategies described earlier for the different HT glycomic technologies (see sections 5.1−5.5). 167 Dependent on the applied technique, various libraries, tools, and databases are available to identify the glycan compositions based upon (normalized) retention time (HPLC-FLD; GlycoStore, previously GlycoBase), 238 migration time (CGE-LIF; GlycoStore 239 and glyXbase), 154 accurate mass (MS; GlycoWorkbench, GlycanMass, UniCarb-DB (MS/MS), Gly-coStore, 239 and GlycoMod) or a combination of retention time and accurate mass data (UHPLC-FLR-MS, UNIFI). 240 An extensive overview of available databases and repositories is provided in Table 1 and described more comprehensively in a recent review.…”

“…Dependent on the applied technique, various libraries, tools, and databases are available to identify the glycan compositions based upon (normalized) retention time (HPLC-FLD; GlycoStore, previously GlycoBase), migration time (CGE-LIF; GlycoStore and glyXbase), accurate mass (MS; GlycoWorkbench, GlycanMass, UniCarb-DB (MS/MS), GlycoStore, and GlycoMod) or a combination of retention time and accurate mass data (UHPLC-FLR-MS, UNIFI) . An extensive overview of available databases and repositories is provided in Table and described more comprehensively in a recent review .…”