Tools for generating and analyzing glycan microarray data

Insights Into Glycobiology and the Protein-Glycan Interactome Using Glycan Microarray Technologies

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.

Allergen Microarrays and New Physical Approaches to More Sensitive and Specific Detection of Allergen-Specific Antibodies

The prevalence of allergic diseases has increased tremendously in recent decades, which can be attributed to growing exposure to environmental triggers, changes in dietary habits, comorbidity, and the increased use of medications. In this context, the multiplexed diagnosis of sensitization to various allergens and the monitoring of the effectiveness of treatments for allergic diseases become particularly urgent issues. The detection of allergen-specific antibodies, in particular, sIgE and sIgG, is a modern alternative to skin tests due to the safety and efficiency of this method. The use of allergen microarrays to detect tens to hundreds of allergen-specific antibodies in less than 0.1 mL of blood serum enables the transition to a deeply personalized approach in the diagnosis of these diseases while reducing the invasiveness and increasing the informativeness of analysis. This review discusses the technological approaches underlying the development of allergen microarrays and other protein microarrays, including the methods of selection of the microarray substrates and matrices for protein molecule immobilization, the obtainment of allergens, and the use of different types of optical labels for increasing the sensitivity and specificity of the detection of allergen-specific antibodies.

Glycosaminoglycan microarrays for studying glycosaminoglycan-protein systems

More than 3000 proteins are now known to bind to glycosaminoglycans (GAGs). Yet, GAG-protein systems are rather poorly understood in terms of selectivity of recognition, molecular mechanism of action, and translational promise. High-throughput screening (HTS) technologies are critically needed for studying GAG biology and developing GAG-based therapeutics. Microarrays, developed within the past two decades, have now improved to the point of being the preferred tool in the HTS of biomolecules. GAG microarrays, in which GAG sequences are immobilized on slides, while similar to other microarrays, have their own sets of challenges and considerations. GAG microarrays are rapidly becoming the first choice in studying GAG-protein systems. Here, we review different modalities and applications of GAG microarrays presented to date. We discuss advantages and disadvantages of this technology, explain covalent and non-covalent immobilization strategies using different chemically reactive groups, and present various assay formats for qualitative and quantitative interpretations, including selectivity screening, binding affinity studies, competitive binding studies etc. We also highlight recent advances in implementing this technology, cataloging of data, and project its future promise. Overall, the technology of GAG microarray exhibits enormous potential of evolving into more than a mere screening tool for studying GAG - protein systems.

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.

Cancer cells and viruses share common glycoepitopes: exciting opportunities toward combined treatments

Aberrant glycosylation patterns of glycoproteins and glycolipids have long been recognized as one the major hallmarks of cancer cells that has led to numerous glycoconjugate vaccine attempts. These abnormal glycosylation profiles mostly originate from the lack of key glycosyltransferases activities, mutations, over expressions, or modifications of the requisite chaperone for functional folding. Due to their relative structural simplicity, O-linked glycans of the altered mucin family of glycoproteins have been particularly attractive in the design of tumor associated carbohydrate-based vaccines. Several such glycoconjugate vaccine formulations have generated potent monoclonal anti-carbohydrate antibodies useful as diagnostic and immunotherapies in the fight against cancer. Paradoxically, glycoproteins related to enveloped viruses also express analogous N- and O-linked glycosylation patterns. However, due to the fact that viruses are not equipped with the appropriate glycosyl enzyme machinery, they need to hijack that of the infected host cells. Although the resulting N-linked glycans are very similar to those of normal cells, some of their O-linked glycan patterns often share the common structural simplicity to those identified on tumor cells. Consequently, given that both cancer cells and viral glycoproteins share both common N- and O-linked glycoepitopes, glycoconjugate vaccines could be highly attractive to generate potent immune responses to target both conditions.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2019-2020

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2020. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. The review is basically divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of arrays. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other areas such as medicine, industrial processes and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. The reported work shows increasing use of incorporation of new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented nearly 40 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show little sign of diminishing.

Simple and practical sialoglycan encoding system reveals vast diversity in nature and identifies a universal sialoglycan-recognizing probe derived from AB5 toxin B subunits

Vertebrate sialic acids (Sias) display much diversity in modifications, linkages, and underlying glycans. Slide microarrays allow high-throughput explorations of sialoglycan-protein interactions. A microarray presenting ~150 structurally defined sialyltrisaccharides with various Sias linkages and modifications still poses challenges in planning, data sorting, visualization, and analysis. To address these issues, we devised a simple 9-digit code for sialyltrisaccharides with terminal Sias and underlying two monosaccharides assigned from the nonreducing end, with 3 digits assigning a monosaccharide, its modifications, and linkage. Calculations based on the encoding system reveal >113,000 likely linear sialyltrisaccharides in nature. Notably, a biantennary N-glycan with 2 terminal sialyltrisaccharides could thus have >1010 potential combinations and a triantennary N-glycan with 3 terminal sequences, >1015 potential combinations. While all possibilities likely do not exist in nature, sialoglycans encode enormous diversity. While glycomic approaches are used to probe such diverse sialomes, naturally occurring bacterial AB5 toxin B subunits are simpler tools to track the dynamic sialome in biological systems. Sialoglycan microarray was utilized to compare sialoglycan-recognizing bacterial toxin B subunits. Unlike the poor correlation between B subunits and species phylogeny, there is stronger correlation with Sia-epitope preferences. Further supporting this pattern, we report a B subunit (YenB) from Yersinia enterocolitica (broad host range) recognizing almost all sialoglycans in the microarray, including 4-O-acetylated-Sias not recognized by a Yersinia pestis orthologue (YpeB). Differential Sia-binding patterns were also observed with phylogenetically related B subunits from Escherichia coli (SubB), Salmonella Typhi (PltB), Salmonella Typhimurium (ArtB), extra-intestinal E.coli (EcPltB), Vibrio cholera (CtxB), and cholera family homologue of E. coli (EcxB).

Structural Insight into Terminal Galactose Recognition by Two Non-HBGA Binding GI.3 Noroviruses

Human noroviruses (huNoVs) cause epidemic acute gastroenteritis using histo-blood group antigens (HBGAs) as host receptors or attachment factors to initiate an infection. While most huNoVs have been shown to bind HBGAs, some known clinical isolates, such as GI.3 DSV and VA115, do not recognize any HBGAs and thus the molecular mechanism behind their infections remains elusive. In this study, we provided both phenotypic and structural evidence to show that huNoV DSV and VA115 recognize a group of glycans with terminal galactoses as ligands. First, through glycan array we found that both DSV and VA115 protruding (P) domain proteins bound two oligosaccharides that share common terminal galactoses. Then, by determination of the crystal structures of DSV/VA115 P proteins in complex with Galα1-3Galβ1-4Glc and/or NA2 N-Glycan, respectively, we showed that the terminal galactose is the main saccharide recognized by the two viral proteins. Our data demonstrated that GI huNoVs can interact with non-HBGA glycans through their conserved galactose binding site, shedding light on the mechanism of huNoV adaptation through recognizing new glycan receptors to facilitate their widespread nature in human population. These findings are also of significance in strategy development for huNoV control and prevention, as well as development of antiviral drugs.

IMPORTANCE Human noroviruses (huNoVs) are the most important viral pathogens causing epidemic acute gastroenteritis worldwide. Previous studies indicated that histo-blood group antigens (HBGAs) are critical host-susceptibility factors affecting huNoV host susceptibility, host range, and probably prevalence. However, certain huNoVs, such as GI.3 DSV and VA115, do not recognize any HBGAs. This implies that other unknown host factors might exist and the molecular mechanism underlying their host receptor recognition or attachment remains elusive. In this study, we found that purified capsid protruding domain proteins from two GI.3 huNoVs specifically bind two glycans that contain a common terminal galactose. We solved the crystal structures of the complexes at atomic resolution and validated the vital amino acids involved in glycan recognition. Our findings elucidate the mechanism of GI.3 huNoV-non-HBGA glycan interaction, which explains why GI.3 virus strains could not bind human HBGAs, paving a way to the prevention and treatment of huNoV-associated diseases.

OUP accepted manuscript

Glycan arrays continue to be the primary resource for determining the glycan-binding specificity of proteins. The volume and diversity of glycan-array data are increasing, but no common method and resource exist to analyze, integrate, and use the available data. To meet this need, we developed a resource of analyzed glycan-array data called CarboGrove. Using the ability to process and interpret data from any type of glycan array, we populated the database with the results from 35 types of glycan arrays, 13 glycan families, 5 experimental methods, and 19 laboratories or companies. In meta-analyses of glycan-binding proteins, we observed glycan-binding specificities that were not uncovered from single sources. In addition, we confirmed the ability to efficiently optimize selections of glycan-binding proteins to be used in experiments for discriminating between closely related motifs. Through descriptive reports and a programmatically accessible Application Programming Interface, CarboGrove yields unprecedented access to the wealth of glycan-array data being produced and powerful capabilities for both experimentalists and bioinformaticians.

A Bittersweet Computational Journey among Glycosaminoglycans

Glycosaminoglycans (GAGs) are linear polysaccharides. In proteoglycans (PGs), they are attached to a core protein. GAGs and PGs can be found as free molecules, associated with the extracellular matrix or expressed on the cell membrane. They play a role in the regulation of a wide array of physiological and pathological processes by binding to different proteins, thus modulating their structure and function, and their concentration and availability in the microenvironment. Unfortunately, the enormous structural diversity of GAGs/PGs has hampered the development of dedicated analytical technologies and experimental models. Similarly, computational approaches (in particular, molecular modeling, docking and dynamics simulations) have not been fully exploited in glycobiology, despite their potential to demystify the complexity of GAGs/PGs at a structural and functional level. Here, we review the state-of-the art of computational approaches to studying GAGs/PGs with the aim of pointing out the “bitter” and “sweet” aspects of this field of research. Furthermore, we attempt to bridge the gap between bioinformatics and glycobiology, which have so far been kept apart by conceptual and technical differences. For this purpose, we provide computational scientists and glycobiologists with the fundamentals of these two fields of research, with the aim of creating opportunities for their combined exploitation, and thereby contributing to a substantial improvement in scientific knowledge.