GlycoGlyph: a glycan visualizing, drawing and naming application

Small lectin ligands as a basis for applications in glycoscience and glycomedicine

Glycan recognition by lectins mediates important biological events. This Tutorial Review aims to introduce lectin-ligand interactions and show how these molecular recognition events inspire innovations such as: (i) glycomimetic ligands; (ii) multivalent ligand agonists/antagonists; (iii) ligands for precision delivery of therapies to cells, where therapies include vaccines, siRNA and LYTACs (iv) development of diagnostics. A small number of case studies are selected to demonstrate principles for development of new ligands for applications inspired by knowledge of natural glycan ligand structure and function.

GlyCompute: towards the automated analysis of protein N-linked glycosylation kinetics via an open-source computational framework

Understanding the complex biosynthetic pathways of glycosylation is crucial for the expanding field of glycosciences. Computer-aided glycosylation analysis has greatly benefited in recent years from the development of tools found in web-based portals and open-source libraries. However, the in silico analysis of cellular glycosylation kinetics is underrepresented in current glycoscience-related tools and databases. This could be partly attributed to the limited accessibility of kinetic models developed using proprietary software and the difficulty in reliably parameterising such models. This work aims to address these challenges by proposing GlyCompute, an open-source framework demonstrating a novel, streamlined approach for the assembly, simulation, and parameterisation of kinetic models of protein N-linked glycosylation. Specifically, given one or more sets of experimentally observed N-glycan structures and their relative abundances, minimum representations of a glycosylation reaction network are generated. The topology of the resulting networks is then used to automatically assemble the material balances and kinetic mechanisms underpinning the mathematical model. To match the experimentally observed relative abundances, a sequential parameter estimation strategy using Bayesian inference is proposed, with stages determined automatically based on the underlying network topology. The proposed framework was tested on a case study involving the simultaneous fitting of the kinetic model to two protein N-linked glycoprofiles produced by the same CHO cell culture, showing good agreement with experimental observations. We envision that GlyCompute could help glycoscientists gain quantitative insights into the effect of enzyme kinetics and their perturbations on experimentally observed glycoprofiles in biomanufacturing and clinical settings.

Structural Analysis of Mammalian Sialic Acid Esterase

Sialic acid esterase (SIAE) catalyzes the removal of O-acetyl groups from sialic acids found on cell surface glycoproteins to regulate cellular processes such as B cell receptor signalling and apoptosis. Loss-of-function mutations in SIAE are associated with several common autoimmune diseases including Crohn's, ulcerative colitis, and arthritis. To gain a better understanding of the function and regulation of this protein, we determined crystal structures of SIAE from three mammalian homologs, including an acetate bound structure. The structures reveal that the catalytic domain adopts the fold of the SGNH hydrolase superfamily. The active site is composed of a catalytic dyad, as opposed to the previously reported catalytic triad. Attempts to determine a substrate-bound structure yielded only the hydrolyzed product acetate in the active site. Rigid docking of complete substrates followed by molecular dynamics simulations revealed that the active site does not form specific interactions with substrates, rather it appears to be broadly specific to accept sialoglycans with diverse modifications. Based on the acetate bound structure, a catalytic mechanism is proposed. Structural mapping of disease mutations reveals that most are located on the surface of the enzyme and would only cause minor disruptions to the protein fold, suggesting that these mutations likely affect binding to other factors. These results improve our understanding of SIAE biology and may aid in the development of therapies for autoimmune diseases and cancer.

Hypoxia-Induced Adaptations of N-Glycomes and Proteomes in Breast Cancer Cells and Their Secreted Extracellular Vesicles

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.

Enrichment methods of N-linked glycopeptides from human serum or plasma: A mini-review

Human diseases often correlate with changes in protein glycosylation, which can be observed in serum or plasma samples. N-glycosylation, the most common form, can provide potential biomarkers for disease prognosis and diagnosis. However, glycoproteins constitute a relatively small proportion of the total proteins in human serum and plasma compared to the non-glycosylated protein albumin, which constitutes the majority. The detection of microheterogeneity and low glycan abundance presents a challenge. Mass spectrometry facilitates glycoproteomics research, yet it faces challenges due to interference from abundant plasma proteins. Therefore, methods have emerged to enrich N-glycans and N-linked glycopeptides using glycan affinity, chemical properties, stationary phase chemical coupling, bioorthogonal techniques, and other alternatives. This review focuses on N-glycans and N-glycopeptides enrichment in human serum or plasma, emphasizing methods and applications. Although not exhaustive, it aims to elucidate principles and showcase the utility and limitations of glycoproteome characterization.

Reusable glycan microarrays using a microwave assisted wet-erase (MAWE) process

Modern studies on binding of proteins to glycans commonly involve the use of synthetic glycans and their derivatives in which a small amount of the material is covalently printed onto a functionalized slide in a glycan microarray format. While incredibly useful to explore binding interactions with many types of samples, the common techniques involve drying the slides, which leads to irreversible association of the protein to the spots on slides to which they bound, thus limiting a microarray to a single use. We have developed a new technique which we term Microwave Assisted Wet-Erase (MAWE) glycan microarrays. In this approach we image the slides under wet conditions to acquire the data, after which the slides are cleaned of binding proteins by treatment with a denaturing SDS solution along with microwave treatment. Slides cleaned in this way can be reused multiple times, and an example here shows the reuse of a single array 15 times. We also demonstrate that this method can be used for a single-array per slide or multi-array per slide platforms. Importantly, the results obtained using this technique for a variety of lectins sequentially applied to a single array, are concordant to those obtained via the classical dry approaches on multiple slides. We also demonstrate that MAWE can be used for different types of samples, such as serum for antibody binding, and whole cells, such as yeast. This technique will greatly conserve precious glycans and prolong the use of existing and new glycan microarrays.

A periodic table of monosaccharides

It is important to recognize the great diversity of monosaccharides commonly encountered in animals, plants, and microbes, as well as to organize them in a visually interesting style that also emphasizes their similarities and relatedness. This article discusses the nature of building blocks, monosaccharides, and monosaccharide derivatives-terms commonly used in discussing "glycomolecules" found in nature. To aid in awareness of monosaccharide diversity, here is presented a Periodic Table of Monosaccharides. The rationale is given for construction of the Table and the selection of 103 monosaccharides, which is largely based on those presented in the KEGG and SNFG websites of monosaccharides, and includes room to enlarge as new discoveries are made. The Table should have educational value and is intended to capture the attention and foster imagination of those not very familiar with glycosciences, and encourage researchers to delve deeper into this fascinating area.

Serum antibody screening using glycan arrays

Humans and other animals produce a diverse collection of antibodies, many of which bind to carbohydrate chains, referred to as glycans. These anti-glycan antibodies are a critical part of our immune systems' defenses. Whether induced by vaccination or natural exposure to a pathogen, anti-glycan antibodies can provide protection against infections and cancers. Alternatively, when an immune response goes awry, antibodies that recognize self-glycans can mediate autoimmune diseases. In any case, serum anti-glycan antibodies provide a rich source of information about a patient's overall health, vaccination history, and disease status. Glycan microarrays provide a high-throughput platform to rapidly interrogate serum anti-glycan antibodies and identify new biomarkers for a variety of conditions. In addition, glycan microarrays enable detailed analysis of the immune system's response to vaccines and other treatments. Herein we review applications of glycan microarray technology for serum anti-glycan antibody profiling.

GlycoDraw: a python implementation for generating high-quality glycan figures

Glycans are essential to all scales of biology, with their intricate structures being crucial for their biological functions. The structural complexity of glycans is communicated through simplified and unified visual representations according to the Symbol Nomenclature for Glycans (SNFGs) guidelines adopted by the community. Here, we introduce GlycoDraw, a Python-native implementation for high-throughput generation of high-quality, SNFG-compliant glycan figures with flexible display options. GlycoDraw is released as part of our glycan analysis ecosystem, glycowork, facilitating integration into existing workflows by enabling fully automated annotation of glycan-related figures and thus assisting the analysis of e.g. differential abundance data or glycomics mass spectra.

Glycosylation and Crowded Membrane Effects on Influenza Neuraminidase Stability and Dynamics

All protein simulations are conducted with varying degrees of simplification, oftentimes with unknown ramifications about how these simplifications affect the interpretability of the results. In this work, we investigated how protein glycosylation and lateral crowding effects modulate an array of properties characterizing the stability and dynamics of influenza neuraminidase. We constructed three systems: (1) glycosylated neuraminidase in a whole virion (i.e., crowded membrane) environment, (2) glycosylated neuraminidase in its own lipid bilayer, and (3) unglycosylated neuraminidase in its own lipid bilayer. We saw that glycans tend to stabilize the protein structure and reduce its conformational flexibility while restricting the solvent movement. Conversely, a crowded membrane environment encouraged exploration of the free energy landscape and a large-scale conformational change, while making the protein structure more compact. Understanding these effects informs what factors one must consider in attempting to recapture the desired level of physical accuracy.

Glycosylation and Crowded Membrane Effects on Influenza Neuraminidase Stability and Dynamics

All protein simulations are conducted with varying degrees of simplifications, oftentimes with unknown ramifications on how these simplifications affect the interpretability of the results. In this work we investigated how protein glycosylation and lateral crowding effects modulate an array of properties characterizing the stability and dynamics of influenza neuraminidase. We constructed three systems: 1) Glycosylated neuraminidase in a whole virion (i.e. crowded membrane) environment 2) Glycosylated neuraminidase in its own lipid bilayer 3) Unglycosylated neuraminidase in its own lipid bilayer. We saw that glycans tend to stabilize the protein structure and reduce its conformational flexibility while restricting solvent movement. Conversely, a crowded membrane environment encouraged exploration of the free energy landscape and a large scale conformational change while making the protein structure more compact. Understanding these effects informs what factors one must consider while attempting to recapture the desired level of physical accuracy.

Protein glycosylation and glycoinformatics for novel biomarker discovery in neurodegenerative diseases

Glycosylation is a common post-translational modification of brain proteins including cell surface adhesion molecules, synaptic proteins, receptors and channels, as well as intracellular proteins, with implications in brain development and functions. Using advanced state-of-the-art glycomics and glycoproteomics technologies in conjunction with glycoinformatics resources, characteristic glycosylation profiles in brain tissues are increasingly reported in the literature and growing evidence shows deregulation of glycosylation in central nervous system disorders, including aging associated neurodegenerative diseases. Glycan signatures characteristic of brain tissue are also frequently described in cerebrospinal fluid due to its enrichment in brain-derived molecules. A detailed structural analysis of brain and cerebrospinal fluid glycans collected in publications in healthy and neurodegenerative conditions was undertaken and data was compiled to create a browsable dedicated set in the GlyConnect database of glycoproteins (https://glyconnect.expasy.org/brain). The shared molecular composition of cerebrospinal fluid with brain enhances the likelihood of novel glycobiomarker discovery for neurodegeneration, which may aid in unveiling disease mechanisms, therefore, providing with novel therapeutic targets as well as diagnostic and progression monitoring tools.

Anti-glycan monoclonal antibodies: Basic research and clinical applications

Anti-glycan monoclonal antibodies have important applications in human health and basic research. Therapeutic antibodies that recognize cancer- or pathogen-associated glycans have been investigated in numerous clinical trials, resulting in two FDA-approved biopharmaceuticals. Anti-glycan antibodies are also utilized to diagnose, prognosticate, and monitor disease progression, as well as to study the biological roles and expression of glycans. High-quality anti-glycan mAbs are still in limited supply, highlighting the need for new technologies for anti-glycan antibody discovery. This review discusses anti-glycan monoclonal antibodies with applications to basic research, diagnostics, and therapeutics, focusing on recent advances in mAbs targeting cancer- and infectious disease-associated glycans.

Highlighting the hygroscopic capacities of apiogalacturonans

To meet the needs of dehydrated skin, molecules with a high hygroscopic potential are necessary to hydrate it effectively and durably. In this context, we were interested in pectins, and more precisely in apiogalacturonans (AGA), a singular one that is currently only found in a few species of aquatic plants. As key structures in water regulation of these aquatic plants and thanks to their molecular composition and conformations, we hypothesized that they could have beneficial role for skin hydration. Spirodela polyrhiza is a duckweed known to be naturally rich in AGA. The aim of this study was to investigate the hygroscopic potential of AGA. Firstly, AGA models were built based on structural information obtained from previous experimental studies. Molecular dynamics (MD) simulations were performed, and the hygroscopic potential was predicted in silico by analyzing the frequency of interaction of water molecules with each AGA residue. Quantification of interactions identified the presence of 23 water molecules on average in contact with each residue of AGA. Secondly, the hygroscopic properties were investigated directly in vivo. Indeed, the water capture in the skin was measured in vivo by Raman microspectroscopy thanks to the deuterated water (D₂0) tracking. Investigations revealed that AGA significantly capture and retain more water in the epidermis and deeper than a placebo control. Not only do these original natural molecules interact with water molecules, but they capture and retain them efficiently in the skin.

Serum glycomic profile as a predictive biomarker of recurrence in patients with differentiated thyroid cancer

PURPOSE

Thyroid cancer recurrence following curative thyroidectomy is associated with increased morbidity and mortality, but current surveillance strategies are inadequate for early detection. Prior studies indicate that tissue glycosylation is altered in thyroid cancer, but the utility of serum glycosylation in thyroid cancer surveillance remains unexplored. We therefore assessed the potential utility of altered serum glycomic profile as a tumor-specific target for disease surveillance in recurrent thyroid cancer.

EXPERIMENTAL DESIGN

We employed banked serum samples from patients with recurrent thyroid cancer post thyroidectomy and healthy controls. N-glycans were enzymatically released from serum glycoproteins, labeled via permethylation, and analyzed by MALDI-TOF mass spectrometry. Global level and specific subtypes of glycan structures were compared between patients and controls.

RESULTS

We evaluated 28 independent samples from 13 patients with cancer recurrence and 15 healthy controls. Global features of glycosylation, including N-glycan class and terminal glycan modifications were similar between groups, but three of 35 individual glycans showed significant differences. The three glycans were biosynthetically related biantennary core fucosylated N-glycans that only varied by the degree of galactosylation (G0F, G1F, and G2F; G: galactose, F: fucose). The ratio of G0F:G1F that captures reduced galactosylation was observed in patients samples but not in healthy controls (p = 0.004) and predicted thyroid cancer recurrence (AUC = 0.82, CI 95% = 0.64-0.99).

CONCLUSIONS

Altered N-glycomic profile was associated with thyroid cancer recurrence. This serum-based biomarker would be useful as an effective surveillance tool to improve the care and prognosis of thyroid cancer after prospective validation.

Artificial intelligence in the analysis of glycosylation data

Glycans are complex, yet ubiquitous across biological systems. They are involved in diverse essential organismal functions. Aberrant glycosylation may lead to disease development, such as cancer, autoimmune diseases, and inflammatory diseases. Glycans, both normal and aberrant, are synthesized using extensive glycosylation machinery, and understanding this machinery can provide invaluable insights for diagnosis, prognosis, and treatment of various diseases. Increasing amounts of glycomics data are being generated thanks to advances in glycoanalytics technologies, but to maximize the value of such data, innovations are needed for analyzing and interpreting large-scale glycomics data. Artificial intelligence (AI) provides a powerful analysis toolbox in many scientific fields, and here we review state-of-the-art AI approaches on glycosylation analysis. We further discuss how models can be analyzed to gain mechanistic insights into glycosylation machinery and how the machinery shapes glycans under different scenarios. Finally, we propose how to leverage the gained knowledge for developing predictive AI-based models of glycosylation. Thus, guiding future research of AI-based glycosylation model development will provide valuable insights into glycosylation and glycan machinery.

The SGNH hydrolase family: a template for carbohydrate diversity

The substitution and de-substitution of carbohydrate materials are important steps in the biosynthesis and/or breakdown of a wide variety of biologically important polymers. The SGNH hydrolase superfamily is a group of related and well-studied proteins with a highly conserved catalytic fold and mechanism composed of 16 member families. SGNH hydrolases can be found in vertebrates, plants, fungi, bacteria, and archaea, and play a variety of important biological roles related to biomass conversion, pathogenesis, and cell signaling. The SGNH hydrolase superfamily is chiefly composed of a diverse range of carbohydrate-modifying enzymes, including but not limited to the carbohydrate esterase families 2, 3, 6, 12 and 17 under the carbohydrate-active enzyme classification system and database (CAZy.org). In this review, we summarize the structural and functional features that delineate these subfamilies of SGNH hydrolases, and which generate the wide variety of substrate preferences and enzymatic activities observed of these proteins to date.

Secreted filarial nematode galectins modulate host immune cells

Lymphatic filariasis (LF) is a mosquito-borne disease caused by filarial nematodes including Brugia malayi. Over 860 million people worldwide are infected or at risk of infection in 72 endemic countries. The absence of a protective vaccine means that current control strategies rely on mass drug administration programs that utilize inadequate drugs that cannot effectively kill adult parasites, thus established infections are incurable. Progress to address deficiencies in the approach to LF control is hindered by a poor mechanistic understanding of host-parasite interactions, including mechanisms of host immunomodulation by the parasite, a critical adaptation for establishing and maintaining infections. The canonical type 2 host response to helminth infection characterized by anti-inflammatory and regulatory immune phenotypes is modified by filarial nematodes during chronic LF. Current efforts at identifying parasite-derived factors driving this modification focus on parasite excretory-secretory products (ESP), including extracellular vesicles (EVs). We have previously profiled the cargo of B. malayi EVs and identified B. malayi galectin-1 and galectin-2 as among the most abundant EV proteins. In this study we further investigated the function of these proteins. Sequence analysis of the parasite galectins revealed highest homology to mammalian galectin-9 and functional characterization identified similar substrate affinities consistent with this designation. Immunological assays showed that Bma-LEC-2 is a bioactive protein that can polarize macrophages to an alternatively activated phenotype and selectively induce apoptosis in Th1 cells. Our data shows that an abundantly secreted parasite galectin is immunomodulatory and induces phenotypes consistent with the modified type 2 response characteristic of chronic LF infection.

Abnormal antibodies to self-carbohydrates in SARS-CoV-2-infected patients

Our immune system is critical for preventing and treating SARS-CoV-2 infections, but aberrant immune responses can have deleterious effects. While antibodies to glycans could recognize the virus and influence the clinical outcome, little is known about their roles. Using a carbohydrate antigen microarray, we profiled serum antibodies in healthy control subjects and COVID-19 patients from two separate cohorts. COVID-19 patients had numerous autoantibodies to self-glycans, including antiganglioside antibodies that can cause neurological disorders. Additionally, nearly all antiglycan IgM signals were lower in COVID-19 patients, indicating a global dysregulation of this class of antibodies. Autoantibodies to certain N-linked glycans correlated with more severe disease, as did low levels of antibodies to the Forssman antigen and ovalbumin. Collectively, this study indicates that expanded testing for antiglycan antibodies could be beneficial for clinical analysis of COVID-19 patients and illustrates the importance of including host and viral carbohydrate antigens when studying immune responses to viruses.

Mucin O-glycans are natural inhibitors of Candida albicans pathogenicity

Mucins are large gel-forming polymers inside the mucus barrier that inhibit the yeast-to-hyphal transition of Candida albicans, a key virulence trait of this important human fungal pathogen. However, the molecular motifs in mucins that inhibit filamentation remain unclear despite their potential for therapeutic interventions. Here, we determined that mucins display an abundance of virulence-attenuating molecules in the form of mucin O-glycans. We isolated and cataloged >100 mucin O-glycans from three major mucosal surfaces and established that they suppress filamentation and related phenotypes relevant to infection, including surface adhesion, biofilm formation and cross-kingdom competition between C. albicans and the bacterium Pseudomonas aeruginosa. Using synthetic O-glycans, we identified three structures (core 1, core 1 + fucose and core 2 + galactose) that are sufficient to inhibit filamentation with potency comparable to the complex O-glycan pool. Overall, this work identifies mucin O-glycans as host molecules with untapped therapeutic potential to manage fungal pathogens.

How molecular modelling can better broaden the understanding of glycosylations

Glycosylations are among the most ubiquitous post-translational modifications (PTMs) in proteins, and the effects of their perturbations are seen in various diseases such as cancers, diabetes and arthritis to name a few. Yet they remain one of the most enigmatic aspects of protein structure and function. On the other hand, molecular modelling techniques have been rapidly bridging this knowledge gap since the last decade. In this review, we discuss how these techniques have proven to be indispensable for a better understanding of the role of glycosylations in glycoprotein structure and function.

Novel fold of rotavirus glycan-binding domain predicted by AlphaFold2 and determined by X-ray crystallography

The VP8* domain of spike protein VP4 in group A and C rotaviruses, which cause epidemic gastroenteritis in children, exhibits a conserved galectin-like fold for recognizing glycans during cell entry. In group B rotavirus, which causes significant diarrheal outbreaks in adults, the VP8* domain (VP8*B) surprisingly lacks sequence similarity with VP8* of group A or group C rotavirus. Here, by using the recently developed AlphaFold2 for ab initio structure prediction and validating the predicted model by determining a 1.3-Å crystal structure, we show that VP8*B exhibits a novel fold distinct from the galectin fold. This fold with a β-sheet clasping an α-helix represents a new fold for glycan recognition based on glycan array screening, which shows that VP8*B recognizes glycans containing N-acetyllactosamine moiety. Although uncommon, our study illustrates how evolution can incorporate structurally distinct folds with similar functionality in a homologous protein within the same virus genus.

Crystal structure of a human MUC16 SEA domain reveals insight into the nature of the CA125 tumor marker

MUC16 is a membrane bound glycoprotein involved in the progression and metastasis of pancreatic and ovarian cancer. The protein is shed into the serum and the resulting cancer antigen 125 (CA125) can be detected by immunoassays. The CA125 epitope is used for monitoring ovarian cancer treatment progression, and has emerged as a potential target for antibody mediated immunotherapy. The extracellular tandem repeat domain of the protein is composed of repeating segments of heavily glycosylated sequence intermixed with homologous SEA (Sperm protein, Enterokinase and Agrin) domains. Here we report the purification and the first X-ray structure of a human MUC16 SEA domain. The structure was solved by molecular replacement using a Rosetta generated structure as a search model. The SEA domain reacted with three different MUC16 therapeutic antibodies, confirming that the CA125 epitope is localized to the SEA domain. The structure revealed a canonical ferredoxin-like fold, and contained a conserved disulfide bond. Analysis of the relative solvent accessibility of side chains within the SEA domain clarified the assignment of N-linked and O-linked glycosylation sites within the domain. A model of the glycosylated SEA domain revealed two major accessible faces, which likely represent the binding sites of CA125 specific antibodies. The results presented here will serve to accelerate future work to understand the functional role of MUC16 SEA domains and antibody recognition of the CA125 epitope.

Mammalian brain glycoproteins exhibit diminished glycan complexity compared to other tissues

Glycosylation is essential to brain development and function, but prior studies have often been limited to a single analytical technique and excluded region- and sex-specific analyses. Here, using several methodologies, we analyze Asn-linked and Ser/Thr/Tyr-linked protein glycosylation between brain regions and sexes in mice. Brain N-glycans are less complex in sequence and variety compared to other tissues, consisting predominantly of high-mannose and fucosylated/bisected structures. Most brain O-glycans are unbranched, sialylated O-GalNAc and O-mannose structures. A consistent pattern is observed between regions, and sex differences are minimal compared to those in plasma. Brain glycans correlate with RNA expression of their synthetic enzymes, and analysis of glycosylation genes in humans show a global downregulation in the brain compared to other tissues. We hypothesize that this restricted repertoire of protein glycans arises from their tight regulation in the brain. These results provide a roadmap for future studies of glycosylation in neurodevelopment and disease.

Glycosylation Changes in Prostate Cancer Progression

Prostate Cancer (PCa) is the most commonly diagnosed malignancy and second leading cause of cancer-related mortality in men. With the use of next generation sequencing and proteomic platforms, new biomarkers are constantly being developed to both improve diagnostic sensitivity and specificity and help stratify patients into different risk groups for optimal management. In recent years, it has become well accepted that altered glycosylation is a hallmark of cancer progression and that the glycan structures resulting from these mechanisms show tremendous promise as both diagnostic and prognostic biomarkers. In PCa, a wide range of structural alterations to glycans have been reported such as variations in sialylation and fucosylation, changes in branching, altered levels of Lewis and sialyl Lewis antigens, as well as the emergence of high mannose "cryptic" structures, which may be immunogenic and therapeutically relevant. Furthermore, aberrant expression of galectins, glycolipids, and proteoglycans have also been reported and associated with PCa cell survival and metastasis. In this review, we discuss the findings from various studies that have explored altered N- and O-linked glycosylation in PCa tissue and body fluids. We further discuss changes in O-GlcNAcylation as well as altered expression of galectins and glycoconjugates and their effects on PCa progression. Finally, we emphasize the clinical utility and potential impact of exploiting glycans as both biomarkers and therapeutic targets to improve our ability to diagnose clinically relevant tumors as well as expand treatment options for patients with advanced disease.

SugarDrawer: A Web-Based Database Search Tool with Editing Glycan Structures

In life science fields, database integration is progressing and contributing to collaboration between different research fields, including the glycosciences. The integration of glycan databases has greatly progressed collaboration worldwide with the development of the international glycan structure repository, GlyTouCan. This trend has increased the need for a tool by which researchers in various fields can easily search glycan structures from integrated databases. We have developed a web-based glycan structure search tool, SugarDrawer, which supports the depiction of glycans including ambiguity, such as glycan fragments which contain underdetermined linkages, and a database search for glycans drawn on the canvas. This tool provides an easy editing feature for various glycan structures in just a few steps using template structures and pop-up windows which allow users to select specific information for each structure element. This tool has a unique feature for selecting possible attachment sites, which is defined in the Symbol Nomenclature for Glycans (SNFG). In addition, this tool can input and output glycans in WURCS and GlycoCT formats, which are the most commonly-used text formats for glycan structures.

CSDB/SNFG Structure Editor: An Online Glycan Builder with 2D and 3D Structure Visualization

This article describes features, usage, and application of an CSDB/SNFG Structure Editor, a new online tool for quick and intuitive input of carbohydrate and derivative structures using Symbol Nomenclature for Glycans (SNFG). The Editor is built on a platform of the Carbohydrate Structure Database (CSDB) and relies on its online services via the dedicated web-API. The Editor allows building of oligo- and polymeric glycan structures and supports most features of natural glycans, such as underdetermined structures, alternative branches, repeating subunits, SMILES specification of atypical monomers, and others. The vocabulary of building blocks contains 600+ monomeric residues, including 327 monosaccharides. Support for SMILES allows input and visualization of chemical structures of virtually unlimited complexity. On the other hand, the interface follows the recognized GlycanBuilder style easy to novice users. The export feature includes support for CSDB Linear, GlycoCT, WURCS, SweetDB, and Glycam notations, SMILES codes, MOL/PDB atomic coordinate formats, raster and vector SNFG images, and on-the-fly visualization as 2D structural formulas and 3D molecular models. Integration of the Editor into any web-based glycoinformatics project is straightforward and simple, similarly to any other modern JavaScript application.

Anti-glycan antibodies: roles in human disease

Carbohydrate-binding antibodies play diverse and critical roles in human health. Endogenous carbohydrate-binding antibodies that recognize bacterial, fungal, and other microbial carbohydrates prevent systemic infections and help maintain microbiome homeostasis. Anti-glycan antibodies can have both beneficial and detrimental effects. For example, alloantibodies to ABO blood group carbohydrates can help reduce the spread of some infectious diseases, but they also impose limitations for blood transfusions. Antibodies that recognize self-glycans can contribute to autoimmune diseases, such as Guillain-Barre syndrome. In addition to endogenous antibodies that arise through natural processes, a variety of vaccines induce anti-glycan antibodies as a primary mechanism of protection. Some examples of approved carbohydrate-based vaccines that have had a major impact on human health are against pneumococcus, Haemophilus influeanza type b, and Neisseria meningitidis. Monoclonal antibodies specifically targeting pathogen associated or tumor associated carbohydrate antigens (TACAs) are used clinically for both diagnostic and therapeutic purposes. This review aims to highlight some of the well-studied and critically important applications of anti-carbohydrate antibodies.

Importance of evaluating protein glycosylation in pluripotent stem cell-derived cardiomyocytes for research and clinical applications

Proper protein glycosylation is critical to normal cardiomyocyte physiology. Aberrant glycosylation can alter protein localization, structure, drug interactions, and cellular function. The in vitro differentiation of human pluripotent stem cells into cardiomyocytes (hPSC-CM) has become increasingly important to the study of protein function and to the fields of cardiac disease modeling, drug testing, drug discovery, and regenerative medicine. Here, we offer our perspective on the importance of protein glycosylation in hPSC-CM. Protein glycosylation is dynamic in hPSC-CM, but the timing and extent of glycosylation are still poorly defined. We provide new data highlighting how observed changes in hPSC-CM glycosylation may be caused by underlying differences in the protein or transcript abundance of enzymes involved in building and trimming the glycan structures or glycoprotein gene products. We also provide evidence that alternative splicing results in altered sites of glycosylation within the protein sequence. Our findings suggest the need to precisely define protein glycosylation events that may have a critical impact on the function and maturation state of hPSC-CM. Finally, we provide an overview of analytical strategies available for studying protein glycosylation and identify opportunities for the development of new bioinformatic approaches to integrate diverse protein glycosylation data types. We predict that these tools will promote the accurate assessment of protein glycosylation in future studies of hPSC-CM that will ultimately be of significant experimental and clinical benefit.

FUT8 Alpha-(1,6)-Fucosyltransferase in Cancer

Aberrant glycosylation is a universal feature of cancer cells that can impact all steps in tumour progression from malignant transformation to metastasis and immune evasion. One key change in tumour glycosylation is altered core fucosylation. Core fucosylation is driven by fucosyltransferase 8 (FUT8), which catalyses the addition of α1,6-fucose to the innermost GlcNAc residue of N-glycans. FUT8 is frequently upregulated in cancer, and plays a critical role in immune evasion, antibody-dependent cellular cytotoxicity (ADCC), and the regulation of TGF-β, EGF, α3β1 integrin and E-Cadherin. Here, we summarise the role of FUT8 in various cancers (including lung, liver, colorectal, ovarian, prostate, breast, melanoma, thyroid, and pancreatic), discuss the potential mechanisms involved, and outline opportunities to exploit FUT8 as a critical factor in cancer therapeutics in the future.

A consensus-based and readable extension of Linear Code for Reaction Rules (LiCoRR)

Systems glycobiology aims to provide models and analysis tools that account for the biosynthesis, regulation, and interactions with glycoconjugates. To facilitate these methods, there is a need for a clear glycan representation accessible to both computers and humans. Linear Code, a linearized and readily parsable glycan structure representation, is such a language. For this reason, Linear Code was adapted to represent reaction rules, but the syntax has drifted from its original description to accommodate new and originally unforeseen challenges. Here, we delineate the consensuses and inconsistencies that have arisen through this adaptation. We recommend options for a consensus-based extension of Linear Code that can be used for reaction rule specification going forward. Through this extension and specification of Linear Code to reaction rules, we aim to minimize inconsistent symbology thereby making glycan database queries easier. With a clear guide for generating reaction rule descriptions, glycan synthesis models will be more interoperable and reproducible thereby moving glycoinformatics closer to compliance with FAIR standards. Here, we present Linear Code for Reaction Rules (LiCoRR), version 1.0, an unambiguous representation for describing glycosylation reactions in both literature and code.

Three-Dimensional Structures of Carbohydrates and Where to Find Them

Analysis and systematization of accumulated data on carbohydrate structural diversity is a subject of great interest for structural glycobiology. Despite being a challenging task, development of computational methods for efficient treatment and management of spatial (3D) structural features of carbohydrates breaks new ground in modern glycoscience. This review is dedicated to approaches of chemo- and glyco-informatics towards 3D structural data generation, deposition and processing in regard to carbohydrates and their derivatives. Databases, molecular modeling and experimental data validation services, and structure visualization facilities developed for last five years are reviewed.

Abnormal antibodies to self-carbohydrates in SARS-CoV-2 infected patients

SARS-CoV-2 is a deadly virus that is causing the global pandemic coronavirus disease 2019 (COVID-19). Our immune system plays a critical role in preventing, clearing, and treating the virus, but aberrant immune responses can contribute to deleterious symptoms and mortality. Many aspects of immune responses to SARS-CoV-2 are being investigated, but little is known about immune responses to carbohydrates. Since the surface of the virus is heavily glycosylated, pre-existing antibodies to glycans could potentially recognize the virus and influence disease progression. Furthermore, antibody responses to carbohydrates could be induced, affecting disease severity and clinical outcome. In this study, we used a carbohydrate antigen microarray with over 800 individual components to profile serum anti-glycan antibodies in COVID-19 patients and healthy control subjects. In COVID-19 patients, we observed abnormally high IgG and IgM antibodies to numerous self-glycans, including gangliosides, N -linked glycans, LacNAc-containing glycans, blood group H, and sialyl Lewis X. Some of these anti-glycan antibodies are known to play roles in autoimmune diseases and neurological disorders, which may help explain some of the unusual and prolonged symptoms observed in COVID-19 patients. The detection of antibodies to self-glycans has important implications for using convalescent serum to treat patients, developing safe and effective SARS-CoV-2 vaccines, and understanding the risks of infection. In addition, this study provides new insight into the immune responses to SARS-CoV-2 and illustrates the importance of including host and viral carbohydrate antigens when studying immune responses to viruses.

Computational tools for drawing, building and displaying carbohydrates: a visual guide

Drawing and visualisation of molecular structures are some of the most common tasks carried out in structural glycobiology, typically using various software. In this perspective article, we outline developments in the computational tools for the sketching, visualisation and modelling of glycans. The article also provides details on the standard representation of glycans, and glycoconjugates, which helps the communication of structure details within the scientific community. We highlight the comparative analysis of the available tools which could help researchers to perform various tasks related to structure representation and model building of glycans. These tools can be useful for glycobiologists or any researcher looking for a ready to use, simple program for the sketching or building of glycans.

Tools for generating and analyzing glycan microarray data

Glycans are one of the major biological polymers found in the mammalian body. They play a vital role in a number of physiologic and pathologic conditions. Glycan microarrays allow a plethora of information to be obtained on protein–glycan binding interactions. In this review, we describe the intricacies of the generation of glycan microarray data and the experimental methods for studying binding. We highlight the importance of this knowledge before moving on to the data analysis. We then highlight a number of tools for the analysis of glycan microarray data such as data repositories, data visualization and manual analysis tools, automated analysis tools and structural informatics tools.