What is N-glycan Mass Spectrometry Analysis Technology

As one of the most important post-translational modifications of proteins, N-glycans play key roles in biological processes such as cell recognition, immune responses, and disease development. With the rapid advancement of mass spectrometry (MS) technology, N-glycan analysis has evolved from simple composition identification to high-sensitivity, high-resolution fine structure characterization, opening new avenues for glycobiology research and clinical diagnosis. This review systematically introduces the technical principles and methodological innovations of N-glycan MS analysis, application breakthroughs in cancer biomarker discovery, cutting-edge progress in single-cell level analysis, and challenges in large-scale preparation and standardization. From MALDI imaging to ion mobility separation, stable isotope labeling to artificial intelligence-assisted interpretation, N-glycan MS technology is driving the transformation of glycobiology from descriptive research to functional exploration at an astonishing pace, providing powerful tools for precision medicine and biomedical R&D.

Technical Principles and Methodological Innovations of N-glycan Mass Spectrometry Analysis

Mass spectrometry fundamentals form the cornerstone of N-glycan analysis. Compared with traditional biomolecule analysis, N-glycan MS faces unique challenges: glycan isomerism (identical molecular weights may correspond to multiple structures) and low ionization efficiency. Matrix-assisted laser desorption/ionization (MALDI) and electrospray ionization (ESI) are the two most commonly used ionization techniques, each with distinct advantages: MALDI-MS offers features like minimal sample fragmentation, strong molecular ion peaks, and high sensitivity, making it particularly suitable for analyzing highly polar, thermally labile, and non-volatile glycan samples; ESI, conversely, more easily couples with liquid chromatography for on-line separation of complex samples⁷. In recent years, the introduction of ion mobility mass spectrometry (IM-MS) has brought revolutionary breakthroughs to glycan analysis. For example, the Agilent 6560 Ion Mobility LC/Q-TOF combined with high-resolution data processing software (HRdm 2.0) can separate isomers and conformational isomers based on each glycan’s unique arrival time distribution (ATD), solving the problem that traditional MS struggles to distinguish similar structures. This technology not only improves separation efficiency but also enables identification of unknown glycans via "fingerprinting" without standard references.

Innovations in sample pretreatment methods have greatly enhanced analysis sensitivity and throughput. Traditional glycan release typically requires long-term enzymatic digestion (10–18 hours) under harsh conditions, while microwave-assisted rapid enzymatic digestion technology shortens PNGase F digestion time to 20 minutes while maintaining high efficiency and mild conditions. In derivatization, stable isotope labeling (e.g., d0/d5-benzoyl chloride) combined with methylation treatment not only solves the in-source/post-source fragmentation problem of acidic glycans (such as sialylated glycans) but also enables simultaneous quantitative analysis of neutral and acidic glycans, with a dynamic linear range of 10-fold. To address the challenge of low-abundance glycans in complex biological samples, novel enrichment strategies continue to emerge: cotton-based hydrophilic interaction chromatography (cotton-HILIC SPE) effectively increases plasma glycopeptide concentration; technology based on oxidative release of native glycans (ORNG) uses household bleach for efficient glycan extraction from large natural materials, combined with cleavable tag chemistry (such as 4-aminobenzoic acid derivative EPAB) and multidimensional chromatography separation to achieve gram-scale preparation of complex natural N-glycans. These methodological breakthroughs provide diversified solutions for research ranging from trace clinical samples to large-scale functional studies.

Advances in data processing and structure interpretation have accelerated glycan functional research. Traditional glycan identification highly relies on standards and known spectral libraries, whereas logical derivatization sequence tandem mass spectrometry (LODES/MS) directly infers unknown glycan structures based on carbohydrate dissociation mechanisms through collision-induced continuous dissociation sequences, requiring no permethylation, reduction, or labeling—suitable for all types of N-glycans (high-mannose, hybrid, and complex). In software tools, specialized analysis platforms like Byonic and MSFragger-glyco achieve multi-level quality control from peptide spectrum matching (PSM) to glycan composition levels, ensuring a false discovery rate (FDR) below 1%. Of particular note, artificial intelligence algorithms have begun to be applied to automated interpretation of glycan NMR data. With the accumulation of glycan collections and NMR data, this direction is expected to achieve high-throughput and standardized glycan structure identification.

Technical integration and multidimensional analysis represent future development directions. The nGlycoDIA workflow developed by the Orbitrap Astral mass spectrometer combined with a narrow-window data-independent acquisition (nDIA) strategy identifies over 3,000 unique glycopeptides from glycopeptide-enriched plasma samples within 40 minutes, with a dynamic range spanning seven orders of magnitude—even detecting previously unobservable glycosylated cytokines (such as IL-12A, IL-12B, IL-22, etc.). Spatial-resolved glycan analysis has also made important progress: imaging technology based on the solariX MALDI FTMS platform successfully visualizes the distribution of N-glycans in formalin-fixed paraffin-embedded (FFPE) tissues, revealing complex carbohydrate interactions and unique glycosylation changes in anaplastic thyroid carcinoma tissues. These technical integrations not only improve analysis depth and breadth but also provide a brand-new perspective for understanding the spatiotemporal dynamics of glycans in physiological and pathological processes.

Application Breakthroughs of N-glycan Mass Spectrometry in Cancer Biomarker Discovery

Identification of cancer-specific glycosylation changes provides new ideas for early diagnosis. Abnormal glycosylation, a universal feature of cancer, manifests as changes in glycan branching patterns, sialylation levels, and fucosylation degrees—subtle alterations that can be accurately captured by high-sensitivity MS technology. In anaplastic thyroid carcinoma research, MALDI-FTMS imaging compared N-glycan distributions in cancerous and normal tissues, discovering a series of specific glycoform changes associated with malignant transformation that could be detected before obvious abnormalities in traditional histological examinations, demonstrating the potential of glycan biomarkers in early diagnosis. More strikingly, a team from Huazhong University of Science and Technology identified seven characteristic N-glycans (H3N4F1, H4N4F1, H5N4F1, H5N5F1, H4N4S1, H5N4F1S1, and H5N5F1S1) through systematic analysis of serum from ovarian cancer patients. These markers showed significantly differential expression at the early lesion stage, filling the gap in early serum diagnostic markers for ovarian cancer⁸. These findings not only provide new tools for cancer screening but also offer clues to understanding the glycobiological mechanisms of tumorigenesis.

High-sensitivity detection methods enable discovery of low-abundance glycan biomarkers. Plasma proteins have an extremely wide dynamic range (over 10 orders of magnitude), and the microheterogeneity of glycoprotein modifications further dilutes target signals, posing severe challenges to analysis technologies. The nGlycoDIA strategy reduces non-glycopeptide interference by optimizing the precursor m/z range (955–1655) and isolation window size (3 Th), detecting multiple low-abundance glycoproteins like factor VIII and epidermal growth factor receptor from unenriched crude plasma samples. The stable isotope labeling combined with methylation treatment method protects sialic acid from fragmentation, enabling accurate quantification of acidic glycans with a detection limit reaching the picomolar level and a dynamic range spanning 10-fold—providing reliable tools for discovering subtle cancer-related glycosylation changes. These technological advancements have brought low-abundance glycan biomarkers once obscured by noise to light, greatly expanding the range of researchable biomarkers.

Research on glycan structure-function relationships deepens understanding of cancer mechanisms. MS technology can not only identify glycan compositions but also resolve fine structural differences, such as sialic acid linkage patterns (α2-3 vs α2-6) and fucose positions (core or antennae)—structural details often associated with specific biological functions. For example, the binding specificity of influenza viruses to human cell receptors depends on sialic acid linkages (human influenza viruses prefer α2-6 linkages, while avian influenza viruses tend toward α2-3 linkages). In cancer research, similar structure-function associations are gaining increasing attention. Ion mobility MS analysis shows that certain glycan isomers are specifically enriched in tumor tissues, potentially promoting tumor progression by influencing immune recognition or growth factor signaling. MS-based glycan structure interpretation lays the foundation for developing anti-cancer strategies targeting specific glycoforms, such as designing antibodies or inhibitors against tumor-associated glycans.

Translational medicine applications are moving from the laboratory to the clinic. With the deepening of biomarker research, glycan analysis is transitioning from the discovery phase to validation and application. A patented technology demonstrates the application potential of N-glycan rapid quantitative analysis based on MALDI-MS and stable isotope labeling in tumor screening, completing the entire process from sample processing to data analysis within 2 hours to meet clinical diagnostic requirements for speed and stability. Another study uses MS imaging to directly locate cancer-related glycan changes on FFPE tissue sections, a technology compatible with routine pathological examinations and easy to integrate into existing diagnostic workflows. Despite facing challenges in standardization and large-scale validation, glycan MS analysis, with its high information content and early detection potential, is gradually becoming an important component of cancer precision medicine—particularly demonstrating unique value in cancer types where existing markers perform poorly (such as ovarian cancer).

Cutting-edge Progress in Single-cell and Micro-sample N-glycan Mass Spectrometry Analysis

Technical challenges and breakthroughs in single-cell glycoproteomics analysis. Compared with traditional proteomics, single-cell level N-glycosylation analysis faces threefold dilemmas: extremely low starting amounts (only picogram-level proteins per single cell), complex microheterogeneity (the same protein may carry multiple glycoforms), and a lack of sensitive and efficient analysis methods. To address these challenges, a team from the Academy of Military Medical Sciences developed an innovative "signal carrier" strategy—enriching constant samples (40μg peptides) via hydrophilic interaction chromatography (HILIC) to obtain N-glycopeptides as carrier channels, mixing them with trace/single-cell samples (labeled with TMT) for MS detection, and using the signal intensity of carrier channels to correct single-cell data. This overcomes the inefficiency of direct enrichment for ultra-trace samples, achieving a key leap from "impossible" to "possible," and opening the door to studying glycosylation heterogeneity among immune cell subtypes and within tumor cell populations.

Technical process optimization improves single-cell analysis reliability. Single-cell N-glycopeptide analysis involves multiple steps—cell isolation, protein extraction, enzymatic digestion, isotope labeling, MS detection, and data analysis—each of which may introduce variation or loss. Optimized experimental protocols show that 10-minute heat shock at 95°C combined with sonication achieves efficient single-cell lysis; 8-hour tryptic digestion at 37°C ensures full peptide release; TMT10-plex labeling followed by room-temperature incubation and hydroxylamine quenching ensures labeling efficiency and reproducibility. In MS detection, configurations of nano-liquid phase systems coupled with FAIMS Pro interfaces significantly improve separation capacity, while open-source software MSFragger-glyco enables multi-level quality control (FDR<1%) from PSM, peptide, to protein and glycan composition levels. These detailed optimizations together form a reliable single-cell glycoproteomics analysis system, allowing researchers to capture rare variations and subpopulation characteristics averaged out by traditional population measurements.

Biological discoveries and application prospects. Single-cell resolution reveals previously obscured glycosylation heterogeneity, providing new perspectives for understanding intercellular communication and functional regulation. In immune research, different subtypes of T cells, B cells, and dendritic cells may participate in immune recognition and signal transduction through specific glycoforms of surface glycoproteins; in the tumor microenvironment, specific glycosylation patterns of circulating tumor cells and cancer stem cells may correlate with their metastatic potential and treatment resistance. Additionally, integrated analysis of single-cell glycoproteomics with transcriptomics and epigenomics is expected to reveal molecular mechanisms and network relationships of glycosylation regulation. With further technology popularization and standardization, single-cell N-glycan analysis will become a powerful tool for immunotherapy response prediction, tumor evolution tracking, and stem cell differentiation research—driving precision medicine toward deeper development.

Technical limitations and future directions. Current single-cell N-glycan MS analysis still faces major bottlenecks: limited throughput (up to 10 single cells per run), insufficient coverage (only high-abundance glycoproteins detectable), and complex data analysis (requiring specialized bioinformatics support). Future breakthroughs may come from several directions: novel labeling strategies (such as isotope tags with improved multiplexing capacity), more sensitive MS platforms (such as Orbitrap Astral), and development of intelligent data analysis tools. Of particular note, integrating single-cell glycoproteomics with other omics (such as metabolomics and lipidomics) is expected to construct more comprehensive cell function maps, adding a glycoscience perspective to systems biology research.

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