Comprehensive N-glycan analysis: Integrated workflow combining structural characterization and precise quantification

Abstract

N-glycosylation is a critical post-translational modification with far-reaching implications for cellular physiology and disease pathogenesis. Despite its biological significance, mass spectrometry-based N-glycomics continues to face substantial analytical challenges, particularly in the comprehensive interpretation of complex glycan structures. This study presents an integrated, multidisciplinary framework that combines advances in cell biology, analytical chemistry, and bioinformatics to enhance the capabilities and scope of N-glycomics research. We systematically evaluated three derivatization strategies: native reduced, acetohydrazide (Ah)-based, and permethylation using the nMatch algorithm. nMatch is a database-free method for N-glycan identification, optimized to maximize structural coverage in mass spectrometry-based N-glycomics. Comparative analysis using the nMatch algorithm detected permethylation as the most effective approach. Subsequent applications with Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) and Liquid chromatography tandem mass spectrometry (LC-MS/MS) revealed that LC-MS/MS offers superior performance for comprehensive N-glycan profiling. Application of this optimized workflow to cancer cell lines (A549, HepG2, HeLa) demonstrated distinct tumor-specific glycosylation signatures, including the immune-evasion-associated Sda trisaccharide epitope (GalNAcβ1-4[Neu5Acα2-3]Galβ1-4GlcNAc) in HeLa cells and characteristic core fucosylation in HepG2 cells. These findings provide critical insights into cancer-associated glycosylation alterations, with significant implications for biomarker discovery and therapeutic targeting. Furthermore, we developed nQuant, a validated glycoinformatics tool that integrates both label-free and isotopic labeling strategies for quantitative N-glycomics. The platform incorporates advanced algorithms for the identification of permethylated N-glycans, elemental composition analysis, and monoisotopic abundance validation. Validation studies across diverse biological systems-including chicken ovalbumin and HEK293 cells- demonstrated the robustness and high accuracy of nQuant in quantitative glycan analysis. In summary, this work establishes (1) optimized sample preparation and analytical workflows for structural N-glycomics, (2) novel bioinformatics solutions for glycan data interpretation, and (3) quantitative frameworks that facilitate biomarker discovery. These advancements substantially enhance our capability to investigate disease-related glycosylation abnormalities and expand the potential applications of N-glycomics in biomedical research. The open-source codes for nMatch and nQuant, have been uploaded to GitHub (https://github.com/GlycoinformaticsTool). These resources are publicly accessible for researchers in the field of glycomics.