Understanding the glycome: an interactive view of glycosylation from glycocompositions to glycoepitopes

Integration of Web-Based Tools to Visualize, Integrate, and Interpret Glycogene Expression and Glycomics Data

Glycosylation is the most abundant and diverse post-translational modification occurring on proteins. Glycans play important roles in modulating cell adhesion, growth, development, and differentiation. Changes in glycosylation affect protein structure and function and contribute to disease processes. Therefore, understanding glycosylation patterns is key for the identification of targets for the diagnosis of diseases, cellular states, and therapy. Glycosylation is a non template-driven process governed by the action of numerous enzymes and substrate availability that varies among cell types and species. Therefore, qualitative and quantitative assessment of global glycosylation and individual glycans remains challenging because it requires integration of multiple complex data types. Glycan structure and quantity data are often integrated with assessments of gene expression to aid contextualization of observed glycosylation changes within biological processes. However, correlating glycogene expression to the glycan structure is challenging because transcriptional changes may not always concur with the final gene product; there is often a lack of information on nucleotide sugar pools, and the final glycan structure is the result of many different glycogenes acting in concert. To overcome these challenges, interactive online tools are emerging as key resources for facilitating the analysis and integration of glycomics and glycogene expression data. Importantly, these tools work in concurrence with glycan biosynthetic schemes and therefore provide a clear indication of the molecular pathways where the glycan and glycogene are involved. In this chapter, we describe the applications of four freely available online tools that can be used for integrated visualization, interpretation, and presentation of RNAseq and glycomics results.

Supplementing the Carbohydrate Structure Database with glycoepitopes

Carbohydrate structures in the Carbohydrate Structure Database have been referenced to glycoepitopes from the Immune Epitope Database allowing users to explore the glycan structures and contained epitopes. Starting with an epitope, one can figure out the glycans from other organisms that share the same structural determinant, and retrieve the associated taxonomical, medical, and other data. This database mapping demonstrates the advantages of the integration of immunological and glycomic databases.

Worldwide Glycoscience Informatics Infrastructure: The GlySpace Alliance

The GlySpace Alliance was formed in 2018 among the principal investigators of three major glycoscience portals: Glyco@Expasy, GlyCosmos, and GlyGen, representing Europe, Asia, and the United States, respectively. While each of these portals has its unique user interface, the aim is to provide the same basic data set of glycan-related omics data. These portals will be introduced with the aim to enable users to find their target information in the most efficient manner, in particular, in terms of the chemical structures of glycans and their functions.

Theranostic Applications of Glycosaminoglycans in Metastatic Renal Cell Carcinoma

Renal cell carcinoma (RCC) makes up the majority of kidney cancers, with a poor prognosis for metastatic RCC (mRCC). Challenges faced in the management of mRCC, include a lack of reliable prognostic markers and biomarkers for precise monitoring of disease treatment, together with the potential risk of toxicity associated with more recent therapeutic options. Glycosaminoglycans (GAGs) are a class of carbohydrates that can be categorized into four main subclasses, viz., chondroitin sulfate, hyaluronic acid, heparan sulfate and keratan sulfate. GAGs are known to be closely associated with cancer progression and modulation of metastasis by modification of the tumor microenvironment. Alterations of expression, composition and spatiotemporal distribution of GAGs in the extracellular matrix (ECM), dysregulate ECM functions and drive cancer invasion. In this review, we focus on the clinical utility of GAGs as biomarkers for mRCC (which is important for risk stratification and strategizing effective treatment protocols), as well as potential therapeutic targets that could benefit patients afflicted with advanced RCC. Besides GAG-targeted therapies that holds promise in mRCC, other potential strategies include utilizing GAGs as drug carriers and their mimetics to counter cancer progression, and enhance immunotherapy through binding and transducing signals for immune mediators.

Developments and perspectives in high-throughput protein glycomics: enabling the analysis of thousands of samples

Glycans expand the structural complexity of proteins by several orders of magnitude, resulting in a tremendous analytical challenge when including them in biomedical research. Recent glycobiological research is painting a picture in which glycans represent a crucial structural and functional component of the majority of proteins, with alternative glycosylation of proteins and lipids being an important regulatory mechanism in many biological and pathological processes. Since interindividual differences in glycosylation are extensive, large studies are needed to map the structures and to understand the role of glycosylation in human (patho)physiology. Driven by these challenges, methods have emerged, which can tackle the complexity of glycosylation in thousands of samples, also known as high-throughput (HT) glycomics. For facile dissemination and implementation of HT glycomics technology, the sample preparation, analysis, as well as data mining, need to be stable over a long period of time (months/years), amenable to automation, and available to non-specialized laboratories. Current HT glycomics methods mainly focus on protein N-glycosylation and allow to extensively characterize this subset of the human glycome in large numbers of various biological samples. The ultimate goal in HT glycomics is to gain better knowledge and understanding of the complete human glycome using methods that are easy to adapt and implement in (basic) biomedical research. Aiming to promote wider use and development of HT glycomics, here, we present currently available, emerging, and prospective methods and some of their applications, revealing a largely unexplored molecular layer of the complexity of life.

Glycosoaminoglycans in cancer therapy

Glycosaminoglycans (GAGs) are an important component of the tumor microenvironment (TME). GAGs can interact with a variety of binding partners and thereby influence cancer progression on multiple levels. GAGs can modulate growth factor and chemokine signaling, invasion and metastasis formation. Moreover, GAGs are able to change the physical property of the extracellular matrix (ECM). Abnormalities in GAG abundance and structure (e.g., sulfation patterns and molecular weight) are found across various cancer types and show biomarker potential. Targeting GAGs, as well as the usage of GAGs and their mimetics, are promising approaches to interfere with cancer progression. In addition, GAGs can be used as drug and cytokine carriers to induce an anti-tumor response. In this review, we summarize the role of GAGs in cancer and the potential use of GAGs and GAG derivatives to target cancer.

An Interactive View of Glycosylation

The present chapter focuses on the interactive and explorative aspects of bioinformatics resources that have been recently released in glycobiology. The comparative analysis of data in a field where knowledge is scattered, incomplete, and disconnected from main biology requires efficient visualization, integration, and interactive tools that are currently only partially implemented. This overview highlights converging efforts toward building a consistent picture of protein glycosylation.

UniLectin, A One-Stop-Shop to Explore and Study Carbohydrate-Binding Proteins

All eukaryotic cells are covered with a dense layer of glycoconjugates, and the cell walls of bacteria are made of various polysaccharides, putting glycans in key locations for mediating protein-protein interactions at cell interfaces. Glycan function is therefore mainly defined as binding to other molecules, and lectins are proteins that specifically recognize and interact non-covalently with glycans. UniLectin was designed based on insight into the knowledge of lectins, their classification, and their biological role. This modular platform provides a curated and periodically updated classification of lectins along with a set of comparative and visualization tools, as well as structured results of screening comprehensive sequence datasets. UniLectin can be used to explore lectins, find precise information on glycan-protein interactions, and mine the results of predictive tools based on HMM profiles. This usage is illustrated here with two protocols. The first one highlights the fine-tuned role of the O blood group antigen in distinctive pathogen recognition, while the second compares the various bacterial lectin arsenals that clearly depend on living conditions of species even in the same genus. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Searching for the structural details of lectins binding the O blood group antigen Basic Protocol 2: Comparing the lectomes of related organisms in different environments.

Immunoaffinity Capillary Electrophoresis in the Era of Proteoforms, Liquid Biopsy and Preventive Medicine: A Potential Impact in the Diagnosis and Monitoring of Disease Progression

Over the years, multiple biomarkers have been used to aid in disease screening, diagnosis, prognosis, and response to therapy. As of late, protein biomarkers are gaining strength in their role for early disease diagnosis and prognosis in part due to the advancements in identification and characterization of a distinct functional pool of proteins known as proteoforms. Proteoforms are defined as all of the different molecular forms of a protein derived from a single gene caused by genetic variations, alternative spliced RNA transcripts and post-translational modifications. Monitoring the structural changes of each proteoform of a particular protein is essential to elucidate the complex molecular mechanisms that guide the course of disease. Clinical proteomics therefore holds the potential to offer further insight into disease pathology, progression, and prevention. Nevertheless, more technologically advanced diagnostic methods are needed to improve the reliability and clinical applicability of proteomics in preventive medicine. In this manuscript, we review the use of immunoaffinity capillary electrophoresis (IACE) as an emerging powerful diagnostic tool to isolate, separate, detect and characterize proteoform biomarkers obtained from liquid biopsy. IACE is an affinity capture-separation technology capable of isolating, concentrating and analyzing a wide range of biomarkers present in biological fluids. Isolation and concentration of target analytes is accomplished through binding to one or more biorecognition affinity ligands immobilized to a solid support, while separation and analysis are achieved by high-resolution capillary electrophoresis (CE) coupled to one or more detectors. IACE has the potential to generate rapid results with significant accuracy, leading to reliability and reproducibility in diagnosing and monitoring disease. Additionally, IACE has the capability of monitoring the efficacy of therapeutic agents by quantifying companion and complementary protein biomarkers. With advancements in telemedicine and artificial intelligence, the implementation of proteoform biomarker detection and analysis may significantly improve our capacity to identify medical conditions early and intervene in ways that improve health outcomes for individuals and populations.

Correcting for sparsity and interdependence in glycomics by accounting for glycan biosynthesis

Glycans are fundamental cellular building blocks, involved in many organismal functions. Advances in glycomics are elucidating the essential roles of glycans. Still, it remains challenging to properly analyze large glycomics datasets, since the abundance of each glycan is dependent on many other glycans that share many intermediate biosynthetic steps. Furthermore, the overlap of measured glycans can be low across samples. We address these challenges with GlyCompare, a glycomic data analysis approach that accounts for shared biosynthetic steps for all measured glycans to correct for sparsity and non-independence in glycomics, which enables direct comparison of different glycoprofiles and increases statistical power. Using GlyCompare, we study diverse N-glycan profiles from glycoengineered erythropoietin. We obtain biologically meaningful clustering of mutant cell glycoprofiles and identify knockout-specific effects of fucosyltransferase mutants on tetra-antennary structures. We further analyze human milk oligosaccharide profiles and find mother’s fucosyltransferase-dependent secretor-status indirectly impact the sialylation. Finally, we apply our method on mucin-type O-glycans, gangliosides, and site-specific compositional glycosylation data to reveal tissues and disease-specific glycan presentations. Our substructure-oriented approach will enable researchers to take full advantage of the growing power and size of glycomics data.

Glycomics can uncover important molecular changes but measured glycans are highly interconnected and incompatible with common statistical methods, introducing pitfalls during analysis. Here, the authors develop an approach to identify glycan dependencies across samples to facilitate comparative glycomics.

Big-Data Glycomics: Tools to Connect Glycan Biosynthesis to Extracellular Communication

Characteristically, cells must sense and respond to environmental cues. Despite the importance of cell-cell communication, our understanding remains limited and often lacks glycans. Glycans decorate proteins and cell membranes at the cell-environment interface, and modulate intercellular communication, from development to pathogenesis. Providing further challenges, glycan biosynthesis and cellular behavior are co-regulating systems. Here, we discuss how glycosylation contributes to extracellular responses and signaling. We further organize approaches for disentangling the roles of glycans in multicellular interactions using newly available datasets and tools, including glycan biosynthesis models, omics datasets, and systems-level analyses. Thus, emerging tools in big data analytics and systems biology are facilitating novel insights on glycans and their relationship with multicellular behavior.

Bioinformatics in Immunoglobulin Glycosylation Analysis

Analytical methods developed for studying immunoglobulin glycosylation rely heavily on software tailored for this purpose. Many of these tools are now used in high-throughput settings, especially for the glycomic characterization of IgG. A collection of these tools, and the databases they rely on, are presented in this chapter. Specific applications are detailed in examples of immunoglobulin glycomics and glycoproteomics data processing workflows. The results obtained in the glycoproteomics workflow are emphasized with the use of dedicated visualizing tools. These tools enable the user to highlight glycan properties and their differential expression.

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.

Cryogenic Infrared Spectroscopy Reveals Structural Modularity in the Vibrational Fingerprints of Heparan Sulfate Diastereomers

Heparan sulfate and heparin are highly acidic polysaccharides with a linear sequence, consisting of alternating glucosamine and hexuronic acid building blocks. The identity of hexuronic acid units shows a variability along their sequence, as d-glucuronic acid and its C5 epimer, l-iduronic acid, can both occur. The resulting backbone diversity represents a major challenge for an unambiguous structural assignment by mass spectrometry-based techniques. Here, we employ cryogenic infrared spectroscopy on mass-selected ions to overcome this challenge and distinguish isomeric heparan sulfate tetrasaccharides that differ only in the configuration of their hexuronic acid building blocks. High-resolution infrared spectra of a systematic set of synthetic heparan sulfate stereoisomers were recorded in the fingerprint region from 1000 to 1800 cm^-1. The experiments reveal a characteristic combination of spectral features for each of the four diastereomers studied and imply structural modularity in the vibrational fingerprints. Strong spectrum-structure correlations were found and rationalized by state-of-the-art quantum chemical calculations. The findings demonstrate the potential of cryogenic infrared spectroscopy to extend the mass spectrometry-based toolkit for the sequencing of heparan sulfate and structurally related biomolecules.

UniLectin3D, a database of carbohydrate binding proteins with curated information on 3D structures and interacting ligands

Lectins, and related receptors such as adhesins and toxins, are glycan-binding proteins from all origins that decipher the glycocode, i.e. the structural information encoded in the conformation of complex carbohydrates present on the surface of all cells. Lectins are still poorly classified and annotated, but since their functions are based on ligand recognition, their 3D-structures provide a solid foundation for characterization. UniLectin3D is a curated database that classifies lectins on origin and fold, with cross-links to literature, other databases in glycosciences and functional data such as known specificity. The database provides detailed information on lectins, their bound glycan ligands, and features their interactions using the Protein–Ligand Interaction Profiler (PLIP) server. Special care was devoted to the description of the bound glycan ligands with the use of simple graphical representation and numerical format for cross-linking to other databases in glycoscience. We conceived the design of the database architecture and the navigation tools to account for all organisms, as well as to search for oligosaccharide epitopes complexed within specified binding sites. UniLectin3D is accessible at https://www.unilectin.eu/unilectin3D.

Glycomics@ExPASy: Bridging the Gap

Glycomics@ExPASy (https://www.expasy.org/glycomics) is the glycomics tab of ExPASy, the server of SIB Swiss Institute of Bioinformatics. It was created in 2016 to centralize web-based glycoinformatics resources developed within an international network of glycoscientists. The hosted collection currently includes mainly databases and tools created and maintained at SIB but also links to a range of reference resources popular in the glycomics community. The philosophy of our toolbox is that it should be {glycoscientist AND protein scientist}-friendly with the aim of (1) popularizing the use of bioinformatics in glycobiology and (2) emphasizing the relationship between glycobiology and protein-oriented bioinformatics resources. The scarcity of data bridging these two disciplines led us to design tools as interactive as possible based on database connectivity to facilitate data exploration and support hypothesis building. Glycomics@ExPASy was designed, and is developed, with a long-term vision in close collaboration with glycoscientists to meet as closely as possible the growing needs of the community for glycoinformatics.

Comparative Glycomics of Immunoglobulin A and G From Saliva and Plasma Reveals Biomarker Potential

The N-glycosylation of immunoglobulin (Ig) G, the major antibody in the circulation of human adults, is well known for its influence on antibody effector functions and its alterations with various diseases. In contrast, knowledge on the role of glycans attached to IgA, which is a key immune defense agent in secretions, is very scarce. In this study we aimed to characterize the glycosylation of salivary (secretory) IgA, including the IgA joining chain (JC), and secretory component (SC) and to compare IgA and IgG glycosylation between human plasma and saliva samples to gain a first insight into oral cavity-specific antibody glycosylation. Plasma and whole saliva were collected from 19 healthy volunteers within a 2-h time window. IgG and IgA were affinity-purified from the two biofluids, followed by tryptic digestion and nanoLC-ESI-QTOF-MS(/MS) analysis. Saliva-derived IgG exhibited a slightly lower galactosylation and sialylation as compared to plasma-derived IgG. Glycosylation of IgA1, IgA2, and the JC showed substantial differences between the biofluids, with salivary proteins exhibiting a higher bisection, and lower galactosylation and sialylation as compared to plasma-derived IgA and JC. Additionally, all seven N-glycosylation sites, characterized on the SC of secretory IgA in saliva, carried highly fucosylated and fully galactosylated diantennary N-glycans. This study lays the basis for future research into the functional role of salivary Ig glycosylation as well as its biomarker potential.