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Carbohydrates are essential biomolecules that play a vital role in various biological processes across humans, plants, and bacteria. Despite their ubiquity, the structural elucidation of carbohydrates, particularly oligo- and polysaccharides, remains a significant challenge due to their complex and heterogeneous nature. The high-performance anion exchange chromatography (HPAEC) or called ion chromatography (IC) coupled with pulsed amperometric detection (PAD) has emerged as a powerful tool for highly effective separation and highly specific detection of glycans. The introduction of mass spectrometry (MS) into HPAEC-PAD systems has further advanced glycan analysis by enabling detailed structural elucidation, including branching, linkage patterns, and sequence determination. The use of suppressor technology allows for the coupling of HPAEC with MS by converting non-volatile salts in the mobile phase into volatile ones. This review highlights the current advancements in HPAEC-PAD/MS for oligo- and polysaccharide structural analysis, discussing the strengths and limitations of different suppressor systems, the role of MS in glycan analysis, and the emerging applications of this technology in the field of glycomics. With continued innovation, HPAEC-PAD/MS is poised to become an essential tool for the detailed characterization of polysaccharides, supporting advancements in pharmaceutical, biomedical, and biotechnological research., Competing Interests: Declaration of Competing Interest There is no conflict of interest for authors of this manuscript., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Purpose: Parathyroid carcinoma (PC) is a rare malignancy with a poor prognosis. Diagnosis of PC is often difficult in clinical practice and efficient diagnostic markers are still needed for differential diagnosis. Aberrant glycosylations of glycoproteins were identified with lectin microarray in various cancers, while relevant information is lacking in PC., Methods: In this study, 8 PC and 6 parathyroid adenoma (PA) tissues were assessed using a microarray consisting of 70 lectins. Overall lectin-specific glycosylation patterns were compared between PA and PC tissues. Lectins with significant differential response between PC and PA were further validated by lectin histochemistry., Results: The difference in signal intensities was found in 71.4% (50/70) of the lectins between the two groups (P < 0.05). The vast majority of PCs had higher intensity signals than PAs (PCs vs. PAs, ratio >1) and amaranthus caudatus (ACL) showed the most significantly different response between them (ratio = 2.45). Lectin histochemistry further confirmed higher ACL intensity in PCs than in PAs. The differentially expressed glycans in PC tissues were primarily glucose, mannose, and galactose-based., Conclusion: PC presented unique glycomic features and ACL may serve as a candidate diagnostic marker for PC., Competing Interests: Compliance with ethical standards. Conflict of interest: The authors declare no competing interests. Ethics approval: The study was approved by the Ethical Review Committee of Peking Union Medical College Hospital (K2494)., (© 2024. The Author(s).)

An efficient novel approach is introduced to predict the effectiveness of chemotherapy treatment in lung cancer by monitoring the serum N-glycome of patients combined with artificial intelligence-based data analysis. The study involved thirty-three lung cancer patients undergoing chemotherapy treatments. Serum samples were taken before and after the treatment. The N-linked oligosaccharides were enzymatically released, fluorophore-labeled, and analyzed by capillary electrophoresis with laser-induced fluorescence detection. The resulting electropherograms were thoroughly processed and evaluated by artificial intelligence-based classifiers, i.e., utilizing a machine learning algorithm to categorize the data into two (binary) classes. The classifier analysis method revealed a strong association between the structural changes in the N-glycans and the outcomes of the chemotherapy treatments (ROC >0.9). This novel combination of bioanalytical and AI methods provided a precise and rapid tool for predicting the effectiveness of chemotherapy., Competing Interests: Declaration of competing interest Authors declare no competing interests., (Copyright © 2025 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Extracellular vesicles (EVs) contain various glycans during their life cycle, from biogenesis to cellular recognition and uptake by recipient cells. EV glycosylation has substantial diagnostic significance in multiple health conditions, highlighting the necessity of determining an accurate glycosylation pattern for EVs from diverse biological fluids. Reliable and accessible glycan detection techniques help to elaborate the glycosylation-related functional alterations of specific proteins or lipids. However, multiple obstacles exist, including the inconsistency in glycosylation patterns between an entire batch of EVs and a specific EV protein, and difficulty in distinguishing glycosylation types after tedious separation and purification procedures. This review outlines recent advances in EV glycan detection, either at the glycomic level for a collection of intact EVs or at the molecular level for a specific protein on EVs. Particular emphasis has been placed on the abundance of EVs in body fluids and their unique characteristics for drug delivery of EVs, indicating an opportunity for diagnostic and therapeutic purposes via EV glycans., Competing Interests: Declaration of competing interest The authors declare no known competing financial interests or personal relationships that could have appeared to influence the paper., (Copyright © 2025. Published by Elsevier B.V.)

Glycosylation profoundly influences cellular function, yet deciphering its intricate patterns remains a formidable challenge. Current techniques often compromise sensitivity, multiplexing, or the ability to capture in-situ cell-to-cell variations. To address these limitations, we introduce 'Lectin-PAINT,' a super-resolution imaging method enabling multiplexed live-cell visualization of the cellular glycocalyx at the single-cell and single-molecule levels. Lectin-PAINT leverages the reversible binding of lectins to specific carbohydrate families to perform point accumulation in nanoscale topography (PAINT), enabling the identification, mapping, and tracking of carbohydrates with a resolution beyond the diffraction limit. Our technique harnesses a tailored lectin library, spanning key carbohydrate recognition, offering insights into their abundance, affinity, and mobility. Through 8-color super-resolution imaging, we extract more than 350 glycosylation parameters with single-cell resolution, creating a cell's 'glycotype' or glycan fingerprint. We showcase the power of this approach by glycotyping and categorizing a diverse set of cancer cell types, shedding light on the heterogeneity and variability of the glycocalyx in cancer. In the future, this research will contribute to the more fundamental understanding of changes in the glycocalyx due to disease., Competing Interests: Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Glycosylation is a common and structurally diverse protein modification that impacts a wide range of tumorigenic processes. Mass spectrometry-driven glycomics and glycoproteomics have emerged as powerful approaches to analyze liberated glycans and intact glycopeptides, respectively, offering a deeper understanding of the heterogeneous glycoproteome in the tumor microenvironment (TME). This protocol details the glycomics-guided glycoproteomics method, an integrated omics technology, which firstly employs porous graphitized carbon-LC-MS/MS-based glycomics to elucidate the glycan structures and their quantitative distribution in the glycome of tumor tissues, cell populations, or bodily fluids being investigated. This allows for a comparative glycomics analysis to identify altered glycosylation across patient groups, disease stages, or conditions, and, importantly, serves to enhance the downstream glycoproteomics analysis of the same sample(s) by creating a library of known glycan structures, thus reducing the data search time and the glycoprotein misidentification rate. Focusing on N-glycoproteome profiling, the sample preparation steps for the glycomics-guided glycoproteomics method are detailed in this protocol, and key aspects of the data collection and analysis are discussed. The glycomics-guided glycoproteomics method provides quantitative information on the glycoproteins present in the TME and their glycosylation sites, site occupancy, and site-specific glycan structures. Representative results are presented from formalin-fixed paraffin-embedded tumor tissues from colorectal cancer patients, demonstrating that the method is sensitive and compatible with tissue sections commonly found in biobanks. Glycomics-guided glycoproteomics, therefore, offers a comprehensive view into the heterogeneity and dynamics of the glycoproteome in complex TMEs, generating robust biochemical data required to better understand the glycobiology of cancers.

Background: The relationship between cancer development and alterations in IgG N-glycosylation has been well-established. However, comprehensive profiling of the N-glycome and N-glycoproteome in gastric cancer (GC) remains limited. Furthermore, the prognostic potential of IgG N-glycan patterns in identifying precursors to GC has yet to be fully elucidated., Methods: The IgG N-glycome in GC was characterized using a custom high-throughput orthogonal mass spectrometry approach. Multivariate analysis was employed to identify and assess glycomic alterations. A comprehensive bioinformatics analysis was also conducted to investigate the differential expression of N-glycosylation-related genes and their potential roles in GC pathogenesis. Additionally, interleukin-11 (IL-11) levels were quantified using a standardized enzyme-linked immunosorbent assay (ELISA)., Results: Galactosylation and sialylation of IgG decreased mainly in the IgG1 and IgG2 subclasses in GC, with subclass-specific changes in IgG3 and IgG4 galactosylation. These glycan modifications were represented by unique glycopeptides (IgG1&#95;H5N5, IgG2&#95;H4N3F1, IgG2&#95;H4N4, IgG2&#95;H4N4F1S1, IgG3/4&#95;H4N4F1, IgG3/4&#95;H4N4F1S1), which outperformed CA72-4 for GC diagnosis. Analysis of key glycogenes revealed differential expression patterns, implicating a functional role for IgG N-glycosylation in GC. Notably, the abundance of specific IgG glycosylation exhibited a significant correlation with serum level of IL-11., Conclusions: Alterations in subclass-specific IgG N-glycosylation represent promising biomarkers for the detection and monitoring of GC progression, potentially influenced by cytokine-driven inflammation. Understanding these changes could improve our knowledge of molecular mechanisms, aiding in diagnostic improvements and therapeutic development., Competing Interests: Declarations. Ethics approval and consent to participate: The study protocol was approved by the Ethics Committee of Tongji Hospital affiliated to Tongji Medical College of Huazhong University of Science & Technology (TJ-IRB20221109). Informed consent was obtained from all patients and healthy controls. The study complied with the latest version of the Declaration of Helsinki. Consent for publication: Not Applicable. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

In glycomics, two data repositories, GlycoPOST and UniCarb-DR, have been developed to accumulate experimental data generated by glycomics and glycoproteomics mass spectrometry experiments. In order to enhance the interrelation between these two data repositories, we have upgraded the framework for both of them; we have unified their respective data submission systems and constructed a mechanism that can automatically cross-reference corresponding entries. In addition to this integration, the metadata registration system was also extended so that liquid chromatography experiments can be reported according to standard reporting guidelines specified by MIRAGE (Minimum Information Required for A Glycomics Experiment). Furthermore, by augmenting the visualization software used in UniCarb-DR, we have been able to introduce new functionality into GlycoPOST to enable the visualization of unpublished experimental identification result files during an embargo period defined by the data provider. As a result, this work introduces a new framework by which glycomics researchers can take advantage of GlycoPOST and UniCarb-DR in an integrated manner., Competing Interests: Declarations. Competing interests: The authors declare that they have no conflicts of interest with the contents of this article. Kiyoko F. Aoki-Kinoshita is guest editor of ABC but was not involved in the peer review of this paper., (© 2024. The Author(s).)

Structural details of oligosaccharides, or glycans, often carry biological relevance, which is why they are typically elucidated using tandem mass spectrometry. Common approaches to distinguish isomers rely on diagnostic glycan fragments for annotating topologies or linkages. Diagnostic fragments are often only known informally among practitioners or stem from individual studies, with unclear validity or generalizability, causing annotation heterogeneity and hampering new analysts. Drawing on a curated set of 237,000 O-glycomics spectra, we here present a rule-based machine learning workflow to uncover quantifiably valid and generalizable diagnostic fragments. This results in fragmentation rules to robustly distinguish common O-glycan isomers for reduced glycans in negative ion mode. We envision this resource to improve glycan annotation accuracy and concomitantly make annotations more transparent and homogeneous across analysts., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Studying glycans and their functions in the body aids in the understanding of disease mechanisms and developing new treatments. This necessitates resources that provide comprehensive glycan data integrated with relevant information from other scientific fields such as genomics, genetics, proteomics, metabolomics, and chemistry. The present paper describes two resources at the U.S. National Center for Biotechnology Information (NCBI), the NCBI Glycans and PubChem, which provide glycan-related information useful for the glycoscience research community. The NCBI Glycans ( https://www.ncbi.nlm.nih.gov/glycans/ ) is a dedicated website for glycobiology data content at NCBI and provides quick access to glycan-related information scattered across multiple NCBI databases as well as other information resources external to NCBI. Importantly, the NCBI Glycans hosts the official web page for the symbol nomenclature for glycans (SNFG), which is the standard graphical representation of glycan structures recommended for scientific publication. On the other hand, PubChem ( https://pubchem.ncbi.nlm.nih.gov ) is a research-focused, large-scale public chemical database, containing a substantial number of glycan-containing records and is integrated with important glycoscience resources like GlyTouCan, GlyCosmos, and GlyGen. PubChem organizes glycan-related information within multiple data collections (i.e., Substance, Compound, Protein, Gene, Pathway, and Taxonomy) and provides various tools and services that allow users to access them both interactively through a web browser and programmatically through a REST-ful interface, including PUG-View. The NCBI Glycans and PubChem highlight glycan-related data and improve their accessibility, helping scientists exploit these data in their research., Competing Interests: Declarations. Ethics approval and consent to participate: Not applicable. Source of biological material: Not applicable. Statement of animal welfare: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Glycosylation, characterized by its complexity and diversity, is a common system across all domains of life. The glycosylation of proteins or lipids imparts them with structural and functional roles, ranging from development to infectious or Mendelian disease. The high-throughput-based omics data has revealed that glycans are involved in important cellular processes. Comprehensive knowledge of glycosylation has contributed not only to the fundamental concepts in glycoscience but also to its applications, including the development of molecular markers for diagnosis and therapeutic tools for treating diseases. The GlyCosmos Glycoscience Portal (GlyCosmos) has undergone significant updates to better support the scientific community in studying glycosylation-related phenomena. Key enhancements include the integration of expanded datasets linking glycans to other omics fields, improved tools for glycan structure prediction and analysis, and upgraded visualization capabilities to streamline data interpretation. A strengthened focus on data standardization has also been introduced, fostering interoperability between glycoscience resources and external databases. Since its release in 2019, the portal has seen a fivefold increase in user engagement, reflecting its growing relevance. These recent advancements aim to provide researchers with a more comprehensive and user-friendly platform, enabling deeper insights into glycan roles in cellular processes and disease mechanisms. GlyCosmos will continue to evolve, prioritizing community needs and advancing the integration of glycoscience with broader biological and biomedical research., Competing Interests: Declarations. Ethics approval: Not applicable. Rights and permissions: Open Access: This article is licensed under a Creative Commons Attribution 4.0 International License. Competing interests: The authors declare no competing interests. Kiyoko F. Aoki-Kinoshita is guest editor of ABC but was not involved in the peer review of this paper., (© 2024. The Author(s).)

The intricate interactions between the host immune system and its microbiome constituents undergo dynamic shifts in response to perturbations to the intestinal tissue environment. Our ability to study these events on the systems level is significantly limited by in situ approaches capable of generating simultaneous insights from both host and microbial communities. Here, we introduce Microbiome Cartography (MicroCart), a framework for simultaneous in situ probing of host and microbiome across multiple spatial modalities. We demonstrate MicroCart by investigating gut host and microbiome changes in a murine colitis model, using spatial proteomics, transcriptomics, and glycomics. Our findings reveal a global but systematic transformation in tissue immune responses, encompassing tissue-level remodeling in response to host immune and epithelial cell state perturbations, bacterial population shifts, localized inflammatory responses, and metabolic process alterations during colitis. MicroCart enables a deep investigation of the intricate interplay between the host tissue and its microbiome with spatial multi-omics., Competing Interests: Competing interests: S.J. is a co-founder of Elucidate Bio Inc, and serves on its Board of Directors and Scientific Advisory Board, and acknowledges research support from Roche. G.P.N. received research grants from Pfizer, Inc.; Vaxart, Inc.; Celgene, Inc.; and Juno Therapeutics, Inc. during the time of and unrelated to this work. G.P.N. and M.A. are co-founders of Ionpath Inc. G.P.N. is a co-founder of Akoya Biosciences, Inc., inventor on patent US9909167, and is a Scientific Advisory Board member for Akoya Biosciences, Inc. M.A. is a Scientific Advisory Board member for Ionpath Inc. A.K.S. reports compensation for consulting and/or scientific advisory board membership from Honeycomb Biotechnologies, Cellarity, Ochre Bio, Relation Therapeutics, IntrECate Biotherapeutics, Bio-Rad Laboratories, Fogpharma, Passkey Therapeutics, Senda Biosciences and Dahlia Biosciences unrelated to this work. The other authors declare no competing interests., (© 2025. The Author(s).)

Comparative glycomics data are compositional data, where measured glycans are parts of a whole, indicated by relative abundances. Applying traditional statistical analyses to these data often results in misleading conclusions, such as spurious "decreases" of glycans when other structures increase in abundance, or high false-positive rates for differential abundance. Our work introduces a compositional data analysis framework, tailored to comparative glycomics, to account for these data dependencies. We employ center log-ratio and additive log-ratio transformations, augmented with a scale uncertainty/information model, to introduce a statistically robust and sensitive data analysis pipeline. Applied to comparative glycomics datasets, including known glycan concentrations in defined mixtures, this approach controls false-positive rates and results in reproducible biological findings. Additionally, we present specialized analysis modalities: alpha- and beta-diversity analyze glycan distributions within and between samples, while cross-class glycan correlations shed light on previously undetected interdependencies. These approaches reveal insights into glycome variations that are critical to understanding roles of glycans in health and disease., Competing Interests: Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Glycosylation, a crucial posttranslational modification (PTM), plays important roles in numerous biological processes and is linked to various diseases. Despite its significance, the structural complexity and diversity of glycans present significant challenges for mass spectrometry (MS)-based quantitative analysis. This review aims to provide an in-depth overview of recent advancements in labeling strategies for N-glycomics and O-glycomics, with a specific focus on enhancing the sensitivity, specificity, and throughput of MS analyses. We categorize these advancements into three major areas: (1) the development of isotopic/isobaric labeling techniques that significantly improve multiplexing capacity and throughput for glycan quantification; (2) novel methods that aid in the structural elucidation of complex glycans, particularly sialylated and fucosylated glycans; and (3) labeling techniques that enhance detection ionization efficiency, separation, and sensitivity for matrix-assisted laser desorption/ionization (MALDI)-MS and capillary electrophoresis (CE)-based glycan analysis. In addition, we highlight emerging trends in single-cell glycomics and bioinformatics tools that have the potential to revolutionize glycan quantification. These developments not only expand our understanding of glycan structures and functions but also open new avenues for biomarker discovery and therapeutic applications. Through detailed discussions of methodological advancements, this review underscores the critical role of derivatization methods in advancing glycan identification and quantification., (© 2024 The Author(s). Proteomics published by Wiley‐VCH GmbH.)

Mass spectrometry-based investigation of the heterogeneous glycoproteome from complex biological specimens is a robust approach to mapping the structure, function, and dynamics of the glycome and proteome. Sampling whole wet tissues often provides a large amount of starting material; however, there is a reasonable variability in tissue handling prior to downstream processing steps, and it is difficult to capture all the different biomolecules from a specific region. The on-slide tissue digestion approach, outlined in this protocol chapter, is a simple and cost-effective method that allows comprehensive mapping of the glycoproteome from a single spot of tissue of 1 mm or greater diameter. It provides a selection of target areas on tissue slides appropriate for tissue volumes of 10 nL or greater, corresponding to a 1 μL droplet of enzyme solution applied to a 1-mm diameter target on a 10-μm-thick tissue slice. Sequential enzymatic digestions and desalting of the biomolecules without any prior derivatization from the surface of fresh frozen or formalin-fixed paraffin-embedded tissue slides enable the simultaneous identification of glycosaminoglycan disaccharides such as hyaluronan, chondroitin sulfate and heparan sulfate, asparagine or N-linked glycans, and intact (glyco)peptides using liquid chromatography-tandem mass spectrometry. The in-depth information obtained from this method including the disaccharide compositions, glycan structures, peptide abundances, and site-specific glycan occupancies provides a detailed profiling of a single spot of tissue which has the potential to be disseminated to biomedical laboratories., (© 2025. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

N-glycome analysis of individual proteins and tissues is crucial for fundamental and applied biomedical research and medical diagnosis and plays an important role in the evaluation of the quality of biopharmaceutical and biotechnological products. The interest in this research area continues to grow annually, thereby increasing the demand for the high-throughput profiling of human blood plasma N-glycome. In response to this need, we have developed an optimized, simple, and rapid protocol for the N-glycome profiling of human plasma proteins. This protocol encompasses the entire analysis cycle, from plasma isolation to N-glycan spectrum quantification. While the proposed method may have lower efficiency compared to already published high-throughput methods, its adaptability makes it suitable for implementation in virtually any molecular biological laboratory.

Aberrant protein glycosylation is a hallmark alteration of cancer and is highly associated with cancer progression. Papillary thyroid cancer (PTC) is the most common type of thyroid cancer, but the N -glycosylation of its glycoproteins has not been well characterized. In this work, we analyzed multiple freshly prepared PTC specimens along with paired normal tissue obtained from thyroidectomies. Glycomic analyses focused on Asn-linked ( N )-glycans and employed mass spectrometry (MS), along with Western blot approaches of total solubilized materials that were examined for binding by specific lectins and a monoclonal antibody (mAb) O6, specific for 3-O-sulfated galactose residues. We observed major differences in PTC versus paired normal specimens, as PTC specimens exhibited higher levels of N -glycan branching and bisection with N -acetylglucosamine residues, consistent with RNAseq data. We also found that 3- O -sulfated galactose was present in N -glycans of multiple glycoproteins from both PTC and control specimens, as recognized by the O6 mAb and as confirmed by MS analyses. These results provide new insights into the N -glycans present in glycoproteins of thyroid cancer and context for further studies of these altered glycans as biomarkers and targets for therapeutics.

Glycosylation is biochemically complex and functionally critical to a wide range of processes and disease states, making it a vibrant area of contemporary research. Here, we highlight a selection of notable recent advances in the glycobiology of SARS-CoV-2 infection and immunity, cancer biology and immunotherapy, and newly discovered glycosylated RNAs. Together, these studies illustrate the significance of glycosylation in normal biology and the great promise of manipulating glycosylation for therapeutic benefit in disease.

N-glycosylation is one of the most common protein modifications in eukaryotes, with immense importance at the molecular, cellular, and organismal level. Accurate and reliable N-glycan analysis is essential to obtain a systems-wide understanding of fundamental biological processes. Due to the structural complexity of glycans, their analysis is still highly challenging. Here we make publicly available a consistent N-glycome dataset of 20 different mouse tissues and demonstrate a multimodal data analysis workflow that allows for unprecedented depth and coverage of N-glycome features. This highly scalable, LC-MS/MS data-driven method integrates the automated identification of N-glycan spectra, the application of non-targeted N-glycome profiling strategies and the isomer-sensitive analysis of glycan structures. Our delineation of critical sub-structural determinants and glycan isomers across the mouse N-glycome uncovered tissue-specific glycosylation patterns, the expression of non-canonical N-glycan structures and highlights multiple layers of N-glycome complexity that derive from organ-specific regulations of glycobiological pathways., (© 2024. The Author(s).)

Glycans linked to proteins and lipids and also occurring in free forms have many functions, and these are partly elicited through specific interactions with glycan-binding proteins (GBPs). These include lectins, adhesins, toxins, hemagglutinins, growth factors, and enzymes, but antibodies can also bind glycans. While humans and other animals generate a vast repertoire of GBPs and different glycans in their glycomes, other organisms, including phage, microbes, protozoans, fungi, and plants also express glycans and GBPs, and these can also interact with their host glycans. This can be termed the protein-glycan interactome, and in nature is likely to be vast, but is so far very poorly described. Understanding the breadth of the protein-glycan interactome is also a key to unlocking our understanding of infectious diseases involving glycans, and immunology associated with antibodies binding to glycans. A key technological advance in this area has been the development of glycan microarrays. This is a display technology in which minute quantities of glycans are attached to the surfaces of slides or beads. This allows the arrayed glycans to be interrogated by GBPs and antibodies in a relatively high throughput approach, in which a protein may bind to one or more distinct glycans. Such binding can lead to novel insights and hypotheses regarding both the function of the GBP, the specificity of an antibody and the function of the glycan within the context of the protein-glycan interactome. This article focuses on the types of glycan microarray technologies currently available to study animal glycobiology and examples of breakthroughs aided by these technologies., Competing Interests: Conflicts of interest The authors declare that they have no conflicts of interest with the contents of this article., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Carbohydrates comprise the largest fraction of most diets and exert a profound impact on health. Components such as simple sugars and starch supply energy, while indigestible components, deemed dietary fiber, reach the colon to provide food for the tens of trillions of microbes that make up the gut microbiota. The interactions between dietary carbohydrates, our gastrointestinal tracts, the gut microbiome and host health are dictated by their structures. However, current methods for analysis of food glycans lack the sensitivity, specificity and throughput needed to quantify and elucidate these myriad structures. This protocol describes a multi-glycomic approach to food carbohydrate analysis in which the analyte might be any food item or biological material such as fecal and cecal samples. The carbohydrates are extracted by ethanol precipitation, and the resulting samples are subjected to rapid-throughput liquid chromatography (LC)-tandem mass spectrometry (LC-MS/MS) methods. Quantitative analyses of monosaccharides, glycosidic linkages, polysaccharides and alcohol-soluble carbohydrates are performed in 96-well plates at the milligram scale to reduce the biomass of sample required and enhance throughput. Detailed stepwise processes for sample preparation, LC-MS/MS and data analysis are provided. We illustrate the application of the protocol to a diverse set of foods as well as different apple cultivars and various fermented foods. Furthermore, we show the utility of these methods in elucidating glycan-microbe interactions in germ-free and colonized mice. These methods provide a framework for elucidating relationships between dietary fiber, the gut microbiome and human physiology. These structures will further guide nutritional and clinical feeding studies that enhance our understanding of the role of diet in nutrition and health., (© 2024. Springer Nature Limited.)

N-glycosylation is a critical post-translational modification involved in various biosynthetic pathways and disease mechanisms. In this study, we present an optimized oxidative release of natural glycans (ORNG) method using household bleach that enables the rapid and efficient release of N-glycans from biological samples. We thoroughly investigated the ORNG mechanism, identifying key intermediates and side products and providing valuable insights into the oxidative release process. The method is highly efficient, releasing a wide range of N-glycans, including high-mannose, hybrid, and complex structures, with minimal sample processing. Our ORNG-based specific N-glycan profiling approach has demonstrated high sensitivity and efficiency, particularly in releasing N-glycans resistant to enzymatic digestion, such as core α3-fucosylated N-glycans from soy protein. Validation through mass spectrometry confirmed the method's ability to accurately profile N-glycans from complex biological samples, including human serum, with results comparable to traditional PNGase F digestion. The ORNG-based method's scalability, versatility, and use of low-cost reagents make it especially suited for large-scale glycomics studies. Furthermore, the mass spectrometry data revealed that the ORNG-based method achieves high sensitivity and specificity, positioning it as a robust alternative for comprehensive glycan profiling and functional studies. Our findings highlight ORNG's potential to advance N-glycomics, offering promising improvements in speed, efficiency, and breadth of glycan analysis.

Gangliosides in the brain play a crucial role in modulating the integrity of vertebrate central nervous system in a region-specific manner. However, to date, a comprehensive structural elucidation of complex intact ganglioside isomers has not been achieved, resulting in the elusiveness into related molecular mechanism. Here, we present a glycolipidomic approach for isomer-specific and brain region-specific profiling of the mouse brain. Considerable region-specificity and commonality in specific group of regions are highlighted. Notably, we observe a similarity in the abundance of major isomers, GD1a and GD1b, within certain regions, which provides significant biological implications with interpretation through the lens of a theoretical retrosynthetic state-transition network. Furthermore, A glycocentric-omics approaches using gangliosides and N-glycans reveal a remarkable convergence in spatial dynamics, providing valuable insight into molecular interaction network. Collectively, this study uncovers the spatial dynamics of intact glyco-conjugates in the brain, which are relevant to regional function and accelerates the discovery of potential therapeutic targets for brain diseases., (© 2024. The Author(s).)

This report describes the development and characterization of a comprehensive collection of CHO cell glycosylation mutants with significant potential for advancing glycobiology and biotechnology. EPO-Fc and trastuzumab, two model molecules, were produced using these mutants to assess the effects of mutated glycogenes, and LC-MS/MS analysis was employed to quantitatively analyse their N-glycans. EPO-Fc exhibited exclusively homogeneous Man9 glycans only when nearly all α-mannosidases in the genome were inactivated, except lysosomal MAN2B1. Some mutants lacking GnT-I activity produce mostly Man5 N-glycans, while their O-glycan and glycolipid profiles can differ due to other mutations in the cell. GnT-II deficiency prevents GnT-V from adding GlcNAc to the core N-glycan, resulting in branches attaching solely to the α1,3-linked mannose, leaving the α1,6-linked mannose free. The mutant-produced antibody's single-branched glycan contains more sialic acid than the dual-branched glycans produced in CHO-K1 cells. Trastuzumab produced in these mutants provided insights into how Fc N-glycans impact the antibody's interaction with FcγR1 and FcγR2a, FcγR3a, and their influence on antibody-dependent cellular cytotoxicity (ADCC). In the study of Fc glycans in Fc-FcγR1 and FcγR2a interactions, we observed a consistent glycan-related impact on binding to both receptors, indicating a common interaction mechanism between Fc glycans and both FcγRI and FcγRIIa. CHO mutants produced trimeric gp120 demonstrated distinct reactivity with multiple broadly neutralizing anti-HIV antibodies, confirming the involvement of gp120 glycans in interactions with specific broadly neutralizing antibodies. Finally, one of the mutants produced human β-glucocerebrosidase with uniform Man5 N-glycans, showcasing its potential for glycoengineered production and enhancement in therapeutic efficacy., (© 2024. The Author(s).)

Glycans are sugar-based polymers found to modify biomolecules, including lipids and proteins, as well as occur unconjugated as free polysaccharides. Due to their ubiquitous cellular presentation, glycans mediate crucial biological processes and are frequently sought after as biomarkers for a wide range of diseases. Identification of glycans present in samples acquired with mass spectrometry (MS) is a cornerstone of glycomics research; thus, the ability to rapidly identify glycans in each acquisition is integral to glycomics analysis pipelines. Here we introduce GlyCombo (https://github.com/Protea-Glycosciences/GlyCombo), an open-source, freely available software tool designed to rapidly assign monosaccharide combinations to glycan precursor masses including those subjected to MS2 in LC-MS/MS experiments. GlyCombo was evaluated across six diverse data sets, demonstrating MS vendor, derivatization, and glycan-type neutrality. Compositional assignments using GlyCombo are shown to be faster than the current predominant approach, GlycoMod, a closed-source web application. Two unique features of GlyCombo, multiple adduct search and off-by-one error anticipation, reduced unassigned MS2 scans in a benchmark data set by 40%. Finally, the comprehensiveness of glycan feature identification is exhibited in Skyline, a software that requires predefined transitions that are derived from GlyCombo output files.

N-glycosylation is a highly heterogeneous post-translational modification that modulates protein function. Defects in N-glycosylation are directly linked to various human diseases. Despite the importance of quantifying N-glycans with high precision, existing glycoinformatics tools are limited. Here, we developed nQuant, a glycoinformatics tool that enables label-free and isotopic labeling quantification of N-glycomics data obtained via LC-MS/MS, ensuring a low false quantitation rate. Using the label-free quantification module, we profiled the N-glycans released from purified glycoproteins and HEK293 cells as well as the dynamic changes of N-glycosylation during mouse corpus callosum development. Through the isotopic labeling quantification module, we revealed the dynamic changes of N-glycans in acute promyelocytic leukemia cells after all-trans retinoic acid treatment. Taken together, we demonstrate that nQuant enables fast and precise quantitative N-glycomics.

The hypoxic tumor microenvironment significantly impacts cellular behavior and intercellular communication, with extracellular vesicles (EVs) playing a crucial role in promoting angiogenesis, metastasis, and host immunosuppression, and presumed cancer progression and metastasis are closely associated with the aberrant surface N-glycan expression in EVs. We hypothesize that hypoxic tumors synthesize specific hypoxia-induced N-glycans in response to or as a consequence of hypoxia. This study utilized nano-LC-MS/MS to integrate quantitative proteomic and N-glycomic analyses of both cells and EVs derived from the MDA-MB-231 breast cancer cell line cultured under normoxic and hypoxic conditions. Whole N-glycome and proteome profiling revealed that hypoxia has an impact on the asparagine N-linked glycosylation patterns and on the glycolysis/gluconeogenesis proteins in cells in terms of altered N-glycosylation for their adaptation to low-oxygen conditions. Distinct N-glycan types, high-mannose glycans like Man3 and Man9, were highly abundant in the hypoxic cells. On the other hand, alterations in the sialylation and fucosylation patterns were observed in the hypoxic cells. Furthermore, hypoxia-induced EVs exhibit a signature consisting of mono-antennary structures and specific N-glycans (H4N3F1S2, H3N3F1S0, and H7N4F3S2; H8N4F1S0 and H8N6F1S2), which are significantly associated with poor prognoses for breast tumors, presumably altering the interactions within the tumor microenvironment to promote tumorigenesis and metastasis. Our findings provide an overview of the N-glycan profiles, particularly under hypoxic conditions, and offer insights into the potential biomarkers for tracking tumor microenvironment dynamics and for developing precision medicine approaches in oncology.

In immunoglobulin G (IgG), N -glycosylation plays a pivotal role in structure and function. It is often altered in different diseases, suggesting that it could be a promising health biomarker. Studies indicate that IgG glycosylation not only associates with various diseases but also has predictive capabilities. Additionally, changes in IgG glycosylation correlate with physiological and biochemical traits known to reflect overall health state. This study aimed to investigate the power of IgG glycans to predict physiological and biochemical parameters. We developed two models using IgG N -glycan data as an input: a regression model using elastic net and a machine learning model using deep learning. Data were obtained from the Korčula and Vis cohorts. The Korčula cohort data were used to train both models, while the Vis cohort was used exclusively for validation. Our results demonstrated that IgG glycome composition effectively predicts several biochemical and physiological parameters, especially those related to lipid and glucose metabolism and cardiovascular events. Both models performed similarly on the Korčula cohort; however, the deep learning model showed a higher potential for generalization when validated on the Vis cohort. This study reinforces the idea that IgG glycosylation reflects individuals' health state and brings us one step closer to implementing glycan-based diagnostics in personalized medicine. Additionally, it shows that the predictive power of IgG glycans can be used for imputing missing covariate data in deep learning frameworks.

Human programmed cell death protein 1 (hPD-1) is an essential receptor in the immune checkpoint pathway. It has played an important role in cancer therapy. However, not all patients respond positively to the PD-1 antibody treatment, and the underlying mechanism remains unknown. PD-1 is a transmembrane glycoprotein, and its extracellular domain (ECD) is reported to be responsible for interactions and signal transduction. This domain contains 4 N -glycosylation sites and 25 potential O -glycosylation sites, which implicates the importance of glycosylation. The structure of hPD-1 has been intensively studied, but the glycosylation of this protein, especially the glycan on each glycosylation site, has not been comprehensively illustrated. In this study, hPD-1 ECD expressed by human embryonic kidney 293 (HEK 293) and Chinese hamster ovary (CHO) cells was analyzed; not only N - and O -glycosylation sites but also the glycans on these sites were comprehensively analyzed using mass spectrometry. In addition, hPD-1 ECD binding to different anti-hPD-1 antibodies was tested, and N-glycans were found functioned differently. All of this glycan information will be beneficial for future PD-1 studies.

Glycosaminoglycans (GAGs) are sulfated linear O -glycan chains abundantly expressed in the extracellular matrix (ECM). Among GAGs, chondroitin sulfate (CS) and dermatan sulfate (DS) play important roles at the brain level, where the distribution and location of the sulfates within the CS/DS chains are responsible for numerous biological events. The diversity of the neural hybrid CS/DS expressed in the brain and the need to elucidate their structure gave rise to considerable efforts toward the development of analytical methods able to discover novel regularly and irregularly sulfated domains. In this context, we report here the introduction of ion mobility separation (IMS) mass spectrometry (MS) in brain glycosaminoglycomics. Based on IMS MS and tandem MS (MS/MS) by collision-induced dissociation (CID), we have developed a powerful approach for the screening and structural analysis of neural CS/DS and optimized and validated the method for the structural analysis of octasaccharides that were released from brain proteoglycans by β-elimination and pooled after chain depolymerization using chondroitin AC lyase. The IMS MS data revealed the separation of CS/DS octamers into mobility families based on the amount of sulfation. Among the discovered oversulfated domains, of major biological importance is the pentasulfated-[4,5-Δ-GlcAGalNAc(IdoAGalNAc) 3 ], for which the (-) nanoESI IMS CID MS/MS analysis disclosed through the presence of distinct drift times, the incidence of two isomers. Moreover, the generated fragment ions revealed an uncommon trisulfated motif and an uncommon pentasulfated motif. Hence, using IMS MS and CID MS/MS, novel brain-related CS/DS domains of atypical sulfation patterns were discovered and structurally characterized in detail.

Protein glycosylation is the co- and/or post-translational modification of proteins with oligosaccharides (glycans). This process is not template based and can introduce a heterogeneous set of glycan modifications onto substrate proteins. Glycan structures preserve biomolecular information from the cell, with glycoproteins from different cell types and tissues displaying distinct patterns of glycosylation. Several decades of research have revealed that glycan structures also differ between normal physiology and disease. This suggests that the information stored in glycoproteins and glycans can be utilized for disease diagnosis and monitoring. Methods that enable sensitive and site-specific measurement of protein glycosylation in clinical settings, such as nano-flow liquid chromatography tandem mass spectrometry, are therefore essential. The purpose of this perspective is to discuss recent advances in mass spectrometry and the potential of these advances to facilitate the detection and monitoring of disease-specific glycoprotein glycoforms. Glycoproteomics, the system-wide characterization of glycoprotein identity inclusive of site-specific characterization of carbohydrate modifications on proteins, and glycomics, the characterization of glycan structures, will be discussed in this context. Quantitative measurement of glycopeptide markers via parallel reaction monitoring is highlighted. The development of promising glycopeptide markers for autoimmune disease, liver disease, and liver cancer is discussed. Synthetic glycopeptide standards, ambient ionization mass spectrometry, and consideration of glyco-biomarkers in two- and three-dimensional space within tissue will be critical to the advancement of this field. The authors envision a future in which glycoprotein mass spectrometry workflows will be integrated into clinical settings, to aid in the rapid diagnosis and monitoring of disease., (© 2024 John Wiley & Sons Ltd.)

High-throughput intact glycopeptide analysis is crucial for elucidating the physiological and pathological status of the glycans attached to each glycoprotein. Mass spectrometry-based glycoproteomic methods are challenging because of the diversity and heterogeneity of glycan structures. Therefore, we developed an MS1-based site-specific glycoform analysis method named "Glycan heterogeneity-based Relational IDentification of Glycopeptide signals on Elution profile (Glyco-RIDGE)" for a more comprehensive analysis. This method detects glycopeptide signals as a cluster based on the mass and chromatographic properties of glycopeptides and then searches for each combination of core peptides and glycan compositions by matching their mass and retention time differences. Here, we developed a novel browser-based software named GRable for semi-automated Glyco-RIDGE analysis with significant improvements in glycopeptide detection algorithms, including "parallel clustering." This unique function improved the comprehensiveness of glycopeptide detection and allowed the analysis to focus on specific glycan structures, such as pauci-mannose. The other notable improvement is evaluating the "confidence level" of the GRable results, especially using MS2 information. This function facilitated reduced misassignment of the core peptide and glycan composition and improved the interpretation of the results. Additional improved points of the algorithms are "correction function" for accurate monoisotopic peak picking; one-to-one correspondence of clusters and core peptides even for multiply sialylated glycopeptides; and "inter-cluster analysis" function for understanding the reason for detected but unmatched clusters. The significance of these improvements was demonstrated using purified and crude glycoprotein samples, showing that GRable allowed site-specific glycoform analysis of intact sialylated glycoproteins on a large-scale and in-depth. Therefore, this software will help us analyze the status and changes in glycans to obtain biological and clinical insights into protein glycosylation by complementing the comprehensiveness of MS2-based glycoproteomics. GRable can be freely run online using a web browser via the GlyCosmos Portal (https://glycosmos.org/grable)., Competing Interests: Conflicts of interest The authors declare that they have no conflicts of interest with the contents of this article., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Glycosylation, a crucial posttranslational modification, plays a significant role in numerous physiological and pathological processes. Lectin microarrays, which leverage the high specificity of lectins for sugar binding, are ideally suited for profiling the glycan spectra of diverse and complex biological samples. In this review, we explore the evolution of lectin detection technologies, as well as the applications and challenges of lectin microarrays in analyzing the glycome profiles of various clinical samples, including serum, saliva, tissues, sperm, and urine. This review not only emphasizes significant advancements in the high-throughput analysis of polysaccharides but also provides insight into the potential of lectin microarrays for diagnosing and managing diseases such as tumors, autoimmune diseases, and chronic inflammation. We aim to provide a clear, concise, and comprehensive overview of the use of lectin microarrays in clinical settings, thereby assisting researchers in conducting clinical studies in glycobiology.

The complex carbohydrate structures decorating human proteins and lipids, also called glycans, are abundantly present at cell surfaces and in the secretome. Glycosylation is vital for biological processes including cell-cell recognition, immune responses, and signaling pathways. Therefore, the structural and functional characterization of the human glycome is gaining more and more interest in basic biochemistry research and in the context of developing new therapies, diagnostic tools, and biotechnology applications. For glycomics to reach its full potential in these fields, it is critical to appreciate the specific factors defining the function of the human glycome. Here, we review the glycosyltransferases (the writers) that form the glycome and the glycan-binding proteins (the readers) with an essential role in decoding glycan functions. While abundantly present throughout different cells and tissues, the function of specific glycosylation features is highly dependent on their context. In this review, we highlight the relevance of studying the glycome in the context of specific carrier proteins, cell types, and subcellular locations. With this, we hope to contribute to a richer understanding of the glycome and a more systematic approach to identifying the roles of glycosylation in human physiology.

Accurate glycopeptide identification in mass spectrometry-based glycoproteomics is a challenging problem at scale. Recent innovation has been made in increasing the scope and accuracy of glycopeptide identifications, with more precise uncertainty estimates for each part of the structure. We present a dynamically adapting relative retention time model for detecting and correcting ambiguous glycan assignments that are difficult to detect from fragmentation alone, a layered approach to glycopeptide fragmentation modeling that improves N-glycopeptide identification in samples without compromising identification quality, and a site-specific method to increase the depth of the glycoproteome confidently identifiable even further. We demonstrate our techniques on a set of previously published datasets, showing the performance gains at each stage of optimization. These techniques are provided in the open-source glycomics and glycoproteomics platform GlycReSoft available at https://github.com/mobiusklein/glycresoft ., (© 2024. The Author(s).)

Glycans on proteins and lipids play important roles in maturation and cellular interactions, contributing to a variety of biological processes. Aberrant glycosylation has been associated with various human diseases including cancer; however, elucidating the distribution and heterogeneity of glycans in complex tissue samples remains a major challenge. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is routinely used to analyze the spatial distribution of a variety of molecules including N-glycans directly from tissue surfaces. Sialic acids are nine carbon acidic sugars that often exist as the terminal sugars of glycans and are inherently difficult to analyze using MALDI-MSI due to their instability prone to in- and postsource decay. Here, we report on a rapid and robust method for stabilizing sialic acid on N-glycans in FFPE tissue sections. The established method derivatizes and identifies the spatial distribution of α2,3- and α2,6-linked sialic acids through complete methylamidation using methylamine and PyAOP ((7-azabenzotriazol-1-yloxy)tripyrrolidinophosphonium hexafluorophosphate). Our in situ approach increases the glycans detected and enhances the coverage of sialylated species. Using this streamlined, sensitive, and robust workflow, we rapidly characterize and spatially localize N-glycans in human tumor tissue sections. Additionally, we demonstrate this method's applicability in imaging mammalian cell suspensions directly on slides, achieving cellular resolution with minimal sample processing and cell numbers. This workflow reveals the cellular locations of distinct N-glycan species, shedding light on the biological and clinical significance of these biomolecules in human diseases.

Idiopathic membranous nephropathy (IMN) is an antibody-mediated and kidney-specific autoimmune disease, with the antigen phospholipase A2 receptor 1 (PLA2R1) accounting for approximately 70% of IMN cases. Although a variety of new podocyte target antigens and their autoantibodies have been identified, they are still of limited diagnostic and therapeutic value due to lack of high specificity and sensitivity. N-glycans play vital roles in renal system and their pathobiological relevance has become increasingly recognized in many kidney diseases, but not fully explored in IMN. To find possible glyco-signatures for PLA2R1-related IMN diagnosis, we herein established a comprehensive workflow for total serum N-glycome analysis based on our recently developed mass spectrometry (MS)-based N-glycan purification method, named Ultrafast Glycoprotein Immobilization for Glycan extraction (UltraGIG). A total of 191 N-glycans were identified from IMN patients, representing the largest N-glycome dataset in IMN. Compared to healthy controls, up-regulation of sialylation and core-fucosylation as well as down-regulation of galactosylation were observed in PLA2R1-positive IMN patients, and up-regulation of hyper-galactosylation was specific for PLA2R1-negative IMN patients. A six-glycan marker panel consisting of H4N3S1, H4N3F1, H6N4S2, H6H5F1S2, H6N5 and H6N6F1S1, was proposed to aid in the accurate diagnosis of PLA2R1-related IMN, which provided new insights into IMN biomarker study. SIGNIFICANCE: PLA2R1-related IMN is a kidney-specific autoimmune disease with a high risk of developing end-stage renal disease (ESRD) and even kidney failure. Current biomarkers are still of limited diagnostic and therapeutic value due to lack of high specificity and sensitivity. An in-depth MS analysis of total serum N-glycome of PLA2R1-related IMN patients was conducted for the first time. We generated the largest dataset of serum N-glycome for IMN to date, and proposed a novel six-glycan marker panel that may help the accurate diagnosis of PLA2R1-related IMN., Competing Interests: Declaration of competing interest The authors declare no competing financial interest., (Copyright © 2024. Published by Elsevier B.V.)

Glycans constitute the most complicated post-translational modification, modulating protein activity in health and disease. However, structural annotation from tandem mass spectrometry (MS/MS) data is a bottleneck in glycomics, preventing high-throughput endeavors and relegating glycomics to a few experts. Trained on a newly curated set of 500,000 annotated MS/MS spectra, here we present CandyCrunch, a dilated residual neural network predicting glycan structure from raw liquid chromatography-MS/MS data in seconds (top-1 accuracy: 90.3%). We developed an open-access Python-based workflow of raw data conversion and prediction, followed by automated curation and fragment annotation, with predictions recapitulating and extending expert annotation. We demonstrate that this can be used for de novo annotation, diagnostic fragment identification and high-throughput glycomics. For maximum impact, this entire pipeline is tightly interlaced with our glycowork platform and can be easily tested at https://colab.research.google.com/github/BojarLab/CandyCrunch/blob/main/CandyCrunch.ipynb . We envision CandyCrunch to democratize structural glycomics and the elucidation of biological roles of glycans., (© 2024. The Author(s).)

Systems biology and multiomics research expand the prospects of planetary health innovations. In this context, this mini-review unpacks the twin scholarships of glycomedicine and precision medicine in the current era of single-cell multiomics. A significant growth in glycan research has been observed over the past decade, unveiling and establishing co- and post-translational modifications as dynamic indicators of both pathological and physiological conditions. Systems biology technologies have enabled large-scale and high-throughput glycoprofiling and access to data-intensive biological repositories for global research. These advancements have established glycans as a pivotal third code of life, alongside nucleic acids and amino acids. However, challenges persist, particularly in the simultaneous analysis of the glycome and transcriptome in single cells owing to technical limitations. In addition, holistic views of the complex molecular interactions between glycomics and other omics types remain elusive. We underscore and call for a paradigm shift toward the exploration of integrative glycan platforms and analysis methods for single-cell multiomics research and precision medicine biomarker discovery. The integration of multiple datasets from various single-cell omics levels represents a crucial application of systems biology in understanding complex cellular processes and is essential for advancing the twin scholarships of glycomedicine and precision medicine.

Glycomics, an emerging "omics" technology that was developed after genomics and proteomics, is a discipline that studies the composition, structure, and functions of glycomes in cells, tissues, and organisms. Glycomics plays key roles in understanding the laws of major life activities, disease prevention and treatment, and drug quality control and development. At present, the structural analysis of glycans relies mainly on mass spectrometry. However, glycans have low abundance in biological samples. In addition, factors such as variable monosaccharide compositions, differences in glycosidic bond positions and modes, diverse branching structures, contribute to the complexity of the compositions and structures of glycans, posing great challenges to glycomics research. Liquid chromatography can effectively remove matrix interferences and enhance glycan separation to improve the mass spectrometric response of glycans. Thus, liquid chromatography and liquid chromatography coupled with mass spectrometry are important technical tools that have been actively applied to solve these problems; these technologies play indispensable roles in glycomics research. Different studies have highlighted similarities and differences in the applications of various types of liquid chromatography, which also reflects the versatility and flexibility of this technology. In this review, we first discuss the enrichment methods for glycans and their applications in glycomics research from the perspective of chromatographic separation mechanisms. We then compare the advantages and disadvantages of these methods. Some glycan-enrichment modes include affinity, hydrophilic interactions, size exclusion, and porous graphitized carbon adsorption. A number of newly developed materials exhibit excellent glycan-enrichment ability. We enumerate the separation mechanisms of reversed-phase high performance liquid chromatography (RP-HPLC), high performance anion-exchange chromatography (HPAEC), hydrophilic interaction chromatography (HILIC), and porous graphitic carbon (PGC) chromatography in the separation and analysis of glycans, and describe the applications of these methods in the separation of glycans, glycoconjugates, and glyco-derivatives. Among these methods, HILIC and PGC chromatography are the most widely used, whereas HPAEC and RP-HPLC are less commonly used. The HILIC and RP-HPLC modes are often used for the separation of derived glycans. The ionization efficiency and detectability of glycans are significantly improved after derivatization. However, the derivatization process is relatively cumbersome, and byproducts inevitably affect the accuracy and completeness of the detection results. HPAEC and PGC chromatography exhibit good separation effects on nonderivative glycans, but issues related to the detection integrity of low-abundance glycans owing to their poor detection effect continue to persist. Therefore, the appropriate analytical method for a specific sample or target analyte or mutual verification must be selected. Finally, we highlight the research progress in various chromatographic methods coupled with mass spectrometry for glycomics analysis. Significant progress has been made in glycomics research in recent years owing to advancements in the development of chromatographic separation techniques. However, several significant challenges remain. As the development of novel separation materials and methods continues, chromatographic techniques may be expected to play a critical role in future glycomics research.

N-glycans play important roles in a variety of biological processes. In recent years, analytical technologies with high resolution and sensitivity have advanced exponentially, enabling analysts to investigate N-glycomic changes in different states. Specific glycan and glycosylation signatures have been identified in multiple diseases, including cancer, autoimmune diseases, nervous system disorders, and metabolic and cardiovascular diseases. These glycans demonstrate comparable or superior indicating capability in disease diagnosis and prognosis over routine biomarkers. Moreover, synchronous glycan alterations concurrent with disease initiation and progression provide novel insights into pathogenetic mechanisms and potential treatment targets. This review elucidates the biological significance of N-glycans, compares the existing glycomic technologies, and delineates the clinical performance of N-glycans across a range of diseases.

Introduction: Glycomics, focusing on the role of glycans in biological processes, particularly their influence on the folding, stability and receptor interactions of glycoconjugates like antibodies, is vital for our understanding of biology. Changes in immunoglobulin G (IgG) N-glycosylation have been associated with various physiological and pathophysiological conditions. Nevertheless, time-consuming manual sample preparation is one of the limitations in the glycomics diagnostic implementation. The study aimed to develop an automated method for sample preparation on the Tecan Freedom Evo 200 platform and compare its efficiency and precision with the manual counterpart., Materials and Methods: The initial method development included 32 pooled blood plasma technical replicates. An additional 24 pooled samples were used in the method comparison along with 78 random duplicates of plasma samples collected from 10,001 Dalmatians biobank to compare the manual and automated methods., Results: The development resulted in a new automated method. For the automated method, glycan peaks comprising 91% of the total sample glycan showed a variation of less than 5% while 92% of the total sample showed a variation of less than 5% for the manual method. The results of the Passing-Bablok regression indicated no differences between the automated and manual methods for 12 glycan peaks (GPs). However, for 8 GPs systematic difference was present, while both systematic and proportional differences were present for four GPs., Conclusions: The developed automated sample preparation method for IgG glycan analysis reduced exposure to hazardous chemicals and offered a simplified workflow. Despite slight differences between the methods, the new automated method showed high precision and proved to be highly comparable to its manual counterpart., Competing Interests: Potential conflict of interest None declared., (Copyright Croatian Society of Medical Biochemistry and Laboratory Medicine.)

The glycomic analysis holds significant appeal due to the diverse roles that glycans and glycoconjugates play, acting as modulators and mediators in cellular interactions, cell/organism structure, drugs, energy sources, glyconanomaterials, and more. The glycomic analysis relies on liquid-phase separation technologies for molecular purification, separation, and identification. As a miniaturized form of liquid-phase separation technology, microscale separation technologies offer various advantages such as environmental friendliness, high resolution, sensitivity, fast speed, and integration capabilities. For glycan analysis, microscale separation technologies are continuously evolving to address the increasing challenges in their unique manners. This review discusses the fundamentals and applications of microscale separation technologies for glycomic analysis. It covers liquid-phase separation technologies operating at scales generally less than 100 µm, including capillary electrophoresis, nanoflow liquid chromatography, and microchip electrophoresis. We will provide a brief overview of glycomic analysis and describe new strategies in microscale separation and their applications in glycan analysis from 2014 to 2023., (© 2024 The Author(s). Journal of Separation Science published by Wiley‐VCH GmbH.)

Alterations in the glycomic profile are a hallmark of cancer, including colorectal cancer (CRC). While, the glycosylation of glycoproteins and glycolipids has been widely studied for CRC cell lines and tissues, a comprehensive overview of CRC glycomics is still lacking due to the usage of different samples and analytical methods. In this study, we compared glycosylation features of N-, O-glycans, and glycosphingolipid glycans for a set of 22 CRC cell lines, all measured by porous graphitized carbon nano-liquid chromatography-tandem mass spectrometry. An overall, high abundance of (sialyl)Lewis antigens for colon-like cell lines was found, while undifferentiated cell lines showed high expression of H blood group antigens and α2-3/6 sialylation. Moreover, significant associations of glycosylation features were found between the three classes of glycans, such as (sialyl)Lewis and H blood group antigens. Integration of the datasets with transcriptomics data revealed positive correlations between (sialyl)Lewis antigens, the corresponding glycosyltransferase FUT3 and transcription factors CDX1, ETS, HNF1/4A, MECOM, and MYB. This indicates a possible role of these transcription factors in the upregulation of (sialyl)Lewis antigens, particularly on glycosphingolipid glycans, via FUT3/4 expression in colon-like cell lines. In conclusion, our study provides insights into the possible regulation of glycans in CRC and can serve as a guide for the development of diagnostic and therapeutic biomarkers., Competing Interests: Conflict of interest The authors declare no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

The application of bacterial oligosaccharyltransferases (OSTs) such as the Campylobacter jejuni PglB for glycoengineering has attracted considerable interest in glycoengineering and glycoconjugate vaccine development. However, PglB has limited specificity for glycans that can be transferred to candidate proteins, which along with other factors is dependent on the reducing end sugar of glycans. In this study, we developed a cell-free glycosylation assay that offers the speed and simplicity of a 'yes' or 'no' determination. Using the assay, we tested the activity of eleven PglBs from Campylobacter species and more distantly related bacteria. The following assorted glycans with diverse reducing end sugars were tested for transfer, including Streptococcus pneumoniae capsule serotype 4, Salmonella enterica serovar Typhimurium O antigen (B1), Francisella tularensis O antigen, Escherichia coli O9 antigen and Campylobacter jejuni heptasaccharide. Interestingly, while PglBs from the same genus showed high activity, whereas divergent PglBs differed in their transfer of glycans to an acceptor protein. Notably for glycoengineering purposes, Campylobacter hepaticus and Campylobacter subantarcticus PglBs showed high glycosylation efficiency, with C. hepaticus PglB potentially being useful for glycoconjugate vaccine production. This study demonstrates the versatility of the cell-free assay in rapidly assessing an OST to couple glycan/carrier protein combinations and lays the foundation for future screening of PglBs by linking amino acid similarity to glycosyltransferase activity., (© 2024 The Author(s). Microbial Biotechnology published by John Wiley & Sons Ltd.)

Extracellular vesicles (EVs) are lipid bilayer-enclosed particles that can be released by all type of cells. Whereas, as one of the most common post-translational modifications, glycosylation plays a vital role in various biological functions of EVs, such as EV biogenesis, sorting, and cellular recognition. Nevertheless, compared with studies on RNAs or proteins, those investigating the glycoconjugates of EVs are limited. An in-depth investigation of N-glycosylation of EVs can improve the understanding of the biological functions of EVs and help to exploit EVs from different perspectives. The general focus of studies on glycosylation of EVs primarily includes isolation and characterization of EVs, preparation of glycoproteome/glycome samples and MS analysis. However, the low content of EVs and non-standard separation methods for downstream analysis are the main limitations of these studies. In this review, we highlight the importance of glycopeptide/glycan enrichment and derivatization owing to the low abundance of glycoproteins and the low ionization efficiency of glycans. Diverse fragmentation patterns and professional analytical software are indispensable for analysing glycosylation via MS. Altogether, this review summarises recent studies on glycosylation of EVs, revealing the role of EVs in disease progression and their remarkable potential as biomarkers., (© 2023 Wiley‐VCH GmbH.)

Glycosylation is an incredibly common and diverse post-translational modification that contributes widely to cellular health and disease. Mass spectrometry is the premier technique to study glycoproteins; however, glycoproteomics has lagged behind traditional proteomics due to the challenges associated with studying glycosylation. For instance, glycans dissociate by collision-based fragmentation, thus necessitating electron-based fragmentation for site-localization. The vast glycan heterogeneity leads to lower overall abundance of each glycopeptide, and often, ion suppression is observed. One of the biggest issues facing glycoproteomics is the lack of reliable software for analysis, which necessitates manual validation and serves as a massive bottleneck in data processing. Here, I will discuss each of these challenges and some ways in which the field is attempting to address them, along with perspectives on how I believe we should move forward., (© 2024 John Wiley & Sons Ltd.)

Ganglioside glycans are ubiquitous and complex biomolecules that are involved in a wide range of biological functions and disease processes. Variations in sialylation and sulfation render the structural complexity and diversity of ganglioside glycans, and influence protein-carbohydrate interactions. Structural and functional insights into the biological roles of these glycans are impeded due to the limited accessibility of well-defined structures. Here we report an integrated chemoenzymatic strategy for expeditious and systematic synthesis of a comprehensive 65-membered ganglioside glycan library covering all possible patterns of sulfation and sialylation. This strategy relies on the streamlined modular assembly of three common sialylated precursors by highly stereoselective iterative sialylation, modular site-specific sulfation through flexible orthogonal protecting-group manipulations and enzymatic-catalysed diversification using three sialyltransferase modules and a galactosidase module. These diverse ganglioside glycans enable exploration into their structure-function relationships using high-throughput glycan microarray technology, which reveals that different patterns of sulfation and sialylation on these glycans mediate their unique binding specificities., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)