N-Glycan Analysis: Better Together - Agilent and ProZyme sample preparation workflow

Significance of the Topic

Glycosylation, and in particular N-linked glycosylation, profoundly influences the safety and efficacy of biotherapeutics such as monoclonal antibodies and Fc fusion proteins. Accurate characterization of N-glycan structures is therefore critical throughout biopharmaceutical development to ensure consistent product quality, optimal pharmacokinetics, and reduced immunogenic risk.

Objectives and Study Overview

This application note describes integrated workflows combining Agilent and ProZyme reagents and instruments for streamlined, high-throughput N-glycan sample preparation and analysis. Key objectives include:

• Reducing sample preparation times from days to hours or less
• Facilitating compatibility with fluorescence detection (FLD), mass spectrometry (MS), and capillary electrophoresis (CE)
• Ensuring robust reproducibility and high sensitivity across diverse glycan labels

Methodology

Two main sample preparation platforms are compared:

• Gly-X: A next-generation, in-solution method using five-minute PNGase F digestion and InstantPC labeling, enabling sample readiness in ≈60 minutes. Optional 2-AB or APTS label workflows (~2 hours) support legacy data comparison.
  
• GlykoPrep: A spin-based cartridge system introduced in 2012. It supports “instant” labeling with multiple dyes and processes samples in 3–5 hours, with validated inter-laboratory reproducibility by UHPLC and CE.
• Traditional workflows: Native or denaturant-driven PNGase F digestion, chromatographic cleanup, and reductive amination labeling (2-AB, 2-AA, APTS). These workflows require 1–2 days and are not suited for high throughput but remain supported.

Used Instrumentation

• AssayMAP Bravo Liquid Handler for automated sample cleanup
• 1260 Infinity II Bio-Inert UHPLC system
• 1290 Infinity II UHPLC system
• 6545XT AdvanceBio LC/Q-TOF mass spectrometer
• MassHunter BioConfirm B.10.00 data analysis software
• AdvanceBio Glycan Mapping HILIC columns (1.8 µm fully porous and 2.7 µm superficially porous)
• 96-well vacuum-driven cleanup plate for high-throughput processing

Main Results and Discussion

Gly-X workflows labeled with InstantPC delivered strong FLD and enhanced positive-mode MS signals, outperforming traditional labels in peak response. HILIC-UHPLC separation of Rituximab and etanercept glycans demonstrated high resolution of key glycoforms (e.g., G0F, G1F, G2F isomers) with relative standard deviations below 3% and coefficient of variation under 2%. These results confirm high reproducibility, even at sample loads up to 40 µg.

Comparison of FLD and MS responses across labels showed InstantPC yielding the highest FLD peak area for G0F and superior MS sensitivity versus procainamide and 2-AB. The modular nature of glycoanalysis kits permits adoption of legacy labeling chemistries where required by existing workflows.

Benefits and Practical Applications of the Method

• Rapid turnaround: Complete N-glycan sample prep in as little as 60 minutes with Gly-X and InstantPC.
• High sensitivity and resolution: Enhanced fluorescence and MS detection improves quantitation and glycoform assignment.
• Flexible workflow design: Multiple labeling reagents and formats support LC/FLD/MS and CE applications.
• Scalability and automation: 96-well plate formats and automation compatibility enable high throughput.

Future Trends and Opportunities

Advances in glycoengineering and analytical automation will further accelerate biotherapeutic development. Emerging trends include:

• Integration of artificial intelligence for automated data interpretation and glycan peak assignment.
• Development of novel fluorescent and MS-active labels for deeper glycome coverage.
• Expansion of glycosyltransferase and exoglycosidase panels for site-specific glycan remodeling.
• Implementation of continuous flow and microfluidic platforms for ultra-fast sample prep.

Conclusion

The combined Agilent–ProZyme workflows deliver a comprehensive, modular approach for reliable and efficient N-glycan analysis. By enabling rapid sample preparation, high-resolution separation, and sensitive FLD/MS detection, these platforms support robust characterization of glycan profiles essential to modern biopharmaceutical research and quality control.

References

1. Jones A. N-Glycan Analysis of Biotherapeutic Proteins. BioPharm Int. 2017;30(6):20–25.
2. Planinc A, et al. Glycan characterization of biopharmaceuticals: Updates and perspectives. Anal Chim Acta. 2016;921:13–27.
3. Szekrényes Á, et al. Multi-site N-Glycan Mapping study 2: UHPLC. Electrophoresis. 2018;39(7):998–1005.
4. Szekrényes Á, et al. Multi-site N-Glycan Mapping study 1: CE-LIF. MAbs. 2016;8(1):56–64.
5. Yan J, et al. Comparison of Common Fluorescent Labels for LC/MS of Released N-Linked Glycans. Agilent Tech. 2019;5994-0942EN.
6. Lee EU, et al. Alteration of terminal glycosylation by β-galactoside α2,6-sialyltransferase. J Biol Chem. 1989;264(23):13848–55.
7. Anthony RM, et al. Recapitulation of IVIG anti-inflammatory activity with recombinant IgG Fc. Science. 2008;320(5874):373–6.
8. Raymond C, et al. Production of α2,6-sialylated IgG1 in CHO cells. MAbs. 2015;7(3):571–83.
9. Varki A, et al. Symbol Nomenclature for Glycans. Glycobiology. 2015;25(12):1323–4.
10. Ceroni A, et al. GlycoWorkbench for glycan MS annotation. J Proteome Res. 2008;7(4):1650–9.