The Role of Fucose-Containing Glycan Motifs Across Taxonomic Kingdoms

The evolving world of milk oligosaccharides: Biochemical diversity understood by computational advances

Milk oligosaccharides, complex carbohydrates unique to mammalian milk, play crucial roles in infant nutrition and immune development. This review explores their biochemical diversity, tracing the evolutionary paths that have led to their variation across different species. We highlight the intersection of nutrition, biology, and chemistry in understanding these compounds. Additionally, we discuss the latest computational methods and analytical techniques that have revolutionized the study of milk oligosaccharides, offering insights into their structural complexity and functional roles. This brief but essential review not only aims to provide a deeper understanding of milk oligosaccharides but also discuss the road toward their potential applications.

α-L-Fucosidases from an Alpaca Faeces Metagenome: Characterisation of Hydrolytic and Transfucosylation Potential

In various life forms, fucose-containing glycans play vital roles in immune recognition, developmental processes, plant immunity, and host-microbe interactions. Together with glucose, galactose, N-acetylglucosamine, and sialic acid, fucose is a significant component of human milk oligosaccharides (HMOs). Fucosylated HMOs benefit infants by acting as prebiotics, preventing pathogen attachment, and potentially protecting against infections, including HIV. Although the need for fucosylated derivatives is clear, their availability is limited. Therefore, synthesis methods for various fucosylated oligosaccharides are explored, employing enzymatic approaches and α-L-fucosidases. This work aimed to characterise α-L-fucosidases identified in an alpaca faeces metagenome. Based on bioinformatic analyses, they were confirmed as members of the GH29A subfamily. The recombinant α-L-fucosidases were expressed in Escherichia coli and showed hydrolytic activity towards p-nitrophenyl-α-L-fucopyranoside and 2'-fucosyllactose. Furthermore, the enzymes' biochemical properties and kinetic characteristics were also determined. All four α-L-fucosidases could catalyse transfucosylation using a broad diversity of fucosyl acceptor substrates, including lactose, maltotriose, L-serine, and L-threonine. The results contribute insights into the potential use of α-L-fucosidases for synthesising fucosylated amino acids.

Decoding glycomics with a suite of methods for differential expression analysis

Glycomics, the comprehensive profiling of all glycan structures in samples, is rapidly expanding to enable insights into physiology and disease mechanisms. However, glycan structure complexity and glycomics data interpretation present challenges, especially for differential expression analysis. Here, we present a framework for differential glycomics expression analysis. Our methodology encompasses specialized and domain-informed methods for data normalization and imputation, glycan motif extraction and quantification, differential expression analysis, motif enrichment analysis, time series analysis, and meta-analytic capabilities, synthesizing results across multiple studies. All methods are integrated into our open-source glycowork package, facilitating performant workflows and user-friendly access. We demonstrate these methods using dedicated simulations and glycomics datasets of N-, O-, lipid-linked, and free glycans. Differential expression tests here focus on human datasets and cancer vs. healthy tissue comparisons. Our rigorous approach allows for robust, reliable, and comprehensive differential expression analyses in glycomics, contributing to advancing glycomics research and its translation to clinical and diagnostic applications.

Mass Spectrometry Analysis of Shark Skin Proteins

The mucus layer covering the skin of fish has several roles, including protection against pathogens and mechanical damage in which proteins play a key role. While proteins in the skin mucus layer of various common bony fish species have been explored, the proteins of shark skin mucus remain unexplored. In this pilot study, we examine the protein composition of the skin mucus in spiny dogfish sharks and chain catsharks through mass spectrometry (NanoLC-MS/MS). Overall, we identified 206 and 72 proteins in spiny dogfish (Squalus acanthias) and chain catsharks (Scyliorhinus retifer), respectively. Categorization showed that the proteins belonged to diverse biological processes and that most proteins were cellular albeit a significant minority were secreted, indicative of mucosal immune roles. The secreted proteins are reviewed in detail with emphasis on their immune potentials. Moreover, STRING protein-protein association network analysis showed that proteins of closely related shark species were more similar as compared to a more distantly related shark and a bony fish, although there were also significant overlaps. This study contributes to the growing field of molecular shark studies and provides a foundation for further research into the functional roles and potential human biomedical implications of shark skin mucus proteins.

Identification of Novel Glycans in the Mucus Layer of Shark and Skate Skin

The mucus layer covering the skin of fish has several roles, including protection against pathogens and mechanical damage. While the mucus layers of various bony fish species have been investigated, the composition and glycan profiles of shark skin mucus remain relatively unexplored. In this pilot study, we aimed to explore the structure and composition of shark skin mucus through histological analysis and glycan profiling. Histological examination of skin samples from Atlantic spiny dogfish (Squalus acanthias) sharks and chain catsharks (Scyliorhinus retifer) revealed distinct mucin-producing cells and a mucus layer, indicating the presence of a functional mucus layer similar to bony fish mucus albeit thinner. Glycan profiling using liquid chromatography-electrospray ionization tandem mass spectrometry unveiled a diverse repertoire of mostly O-glycans in the mucus of the two sharks as well as little skate (Leucoraja erinacea). Elasmobranch glycans differ significantly from bony fish, especially in being more sulfated, and some bear resemblance to human glycans, such as gastric mucin O-glycans and H blood group-type glycans. This study contributes to the concept of shark skin having unique properties and provides a foundation for further research into the functional roles and potential biomedical implications of shark skin mucus glycans.

Comparative mucomic analysis of three functionally distinct Cornu aspersum Secretions

Every animal secretes mucus, placing them among the most diverse biological materials. Mucus hydrogels are complex mixtures of water, ions, carbohydrates, and proteins. Uncertainty surrounding their composition and how interactions between components contribute to mucus function complicates efforts to exploit their properties. There is substantial interest in commercializing mucus from the garden snail, Cornu aspersum, for skincare, drug delivery, tissue engineering, and composite materials. C. aspersum secretes three mucus-one shielding the animal from environmental threats, one adhesive mucus from the pedal surface of the foot, and another pedal mucus that is lubricating. It remains a mystery how compositional differences account for their substantially different properties. Here, we characterize mucus proteins, glycosylation, ion content, and mechanical properties that could be used to provide insight into structure-function relationships through an integrative "mucomics" approach. We identify macromolecular components of these hydrogels, including a previously unreported protein class termed Conserved Anterior Mollusk Proteins (CAMPs). Revealing differences between C. aspersum mucus shows how considering structure at all levels can inform the design of mucus-inspired materials.

Enrichment and fragmentation approaches for enhanced detection and characterization of endogenous glycosylated neuropeptides

Glycosylated neuropeptides were recently discovered in crustaceans, a model organism with a well-characterized neuroendocrine system. Several workflows exist to characterize enzymatically digested peptides; however, the unique properties of endogenous neuropeptides require methods to be re-evaluated. We investigate the use of hydrophilic interaction liquid chromatography (HILIC) enrichment and different fragmentation methods to further probe the expression of glycosylated neuropeptides in Callinectes sapidus. During the evaluation of HILIC, we observed the necessity of a less aqueous solvent for endogenous peptide samples. This modification enabled the number of detected neuropeptide glycoforms to increase almost two-fold, from 18 to 36. Product ion-triggered electron-transfer/higher-energy collision dissociation enabled the site-specific detection of 55 intact N- and O-linked glycoforms, while the faster stepped collision energy higher-energy collisional dissociation resulted in detection of 25. Additionally, applying this workflow to five neuronal tissues enabled the characterization of 36 more glycoforms of known neuropeptides and 11 more glycoforms of nine putative novel neuropeptides. Overall, the database of glycosylated neuropeptides in crustaceans was largely expanded from 18 to 136 glycoforms of 40 neuropeptides from 10 neuropeptide families. Both macro- and micro-heterogeneity were observed, demonstrating the chemical diversity of this simple invertebrate, establishing a framework to use crustacean to probe modulatory effects of glycosylation on neuropeptides.

Shedding Light on Bacterial Physiology with Click Chemistry

Bacteria constitute a major lifeform on this planet and play numerous roles in ecology, physiology, and human disease. However, conventional methods to probe their activities are limited in their ability to visualize and identify their functions in these diverse settings. In the last two decades, the application of click chemistry to label these microbes has deepened our understanding of bacterial physiology. With the development of a plethora of chemical tools that target many biological molecules, it is possible to track these microorganisms in real-time and at unprecedented resolution. Here, we review click chemistry, including bioorthogonal reactions, and their applications in imaging bacterial glycans, lipids, proteins, and nucleic acids using chemical reporters. We also highlight significant advances that have enabled biological discoveries that have heretofore remained elusive.

Glycoinformatics in the Artificial Intelligence Era

Artificial intelligence (AI) methods have been and are now being increasingly integrated in prediction software implemented in bioinformatics and its glycoscience branch known as glycoinformatics. AI techniques have evolved in the past decades, and their applications in glycoscience are not yet widespread. This limited use is partly explained by the peculiarities of glyco-data that are notoriously hard to produce and analyze. Nonetheless, as time goes, the accumulation of glycomics, glycoproteomics, and glycan-binding data has reached a point where even the most recent deep learning methods can provide predictors with good performance. We discuss the historical development of the application of various AI methods in the broader field of glycoinformatics. A particular focus is placed on shining a light on challenges in glyco-data handling, contextualized by lessons learnt from related disciplines. Ending on the discussion of state-of-the-art deep learning approaches in glycoinformatics, we also envision the future of glycoinformatics, including development that need to occur in order to truly unleash the capabilities of glycoscience in the systems biology era.

Structure-function relationship of a novel fucoside-binding fruiting body lectin from Coprinopsis cinerea exhibiting nematotoxic activity

Lectins are non-immunoglobulin-type proteins that bind to specific carbohydrate epitopes and play important roles in intra- and inter-organismic interactions. Here, we describe a novel fucose-specific lectin, termed CML1, which we identified from fruiting body extracts of Coprinopsis cinerea. For further characterization, the coding sequence for CML1 was cloned and heterologously expressed in Escherichia coli. Feeding of CML1-producing bacteria inhibited larval development of the bacterivorous nematode Caenorhabditis tropicalis, but not of C. elegans. The crystal structure of the recombinant protein in its apo-form and in complex with H type I or Lewis A blood group antigens was determined by X-ray crystallography. The protein folds as a sandwich of 2 antiparallel β-sheets and forms hexamers resulting from a trimer of dimers. The hexameric arrangement was confirmed by small-angle X-ray scattering (SAXS). One carbohydrate-binding site per protomer was found at the dimer interface with both protomers contributing to ligand binding, resulting in a hexavalent lectin. In terms of lectin activity of recombinant CML1, substitution of the carbohydrate-interacting residues His54, Asn55, Trp94, and Arg114 by Ala abolished carbohydrate-binding and nematotoxicity. Although no similarities to any characterized lectin were found, sequence alignments identified many non-characterized agaricomycete proteins. These results suggest that CML1 is the founding member of a novel family of fucoside-binding lectins involved in the defense of agaricomycete fruiting bodies against predation by fungivorous nematodes.

Nucleotide sugar dehydratases: Structure, mechanism, substrate specificity, and application potential

Nucleotide sugar (NS) dehydratases play a central role in the biosynthesis of deoxy and amino sugars, which are involved in a variety of biological functions in all domains of life. Bacteria are true masters of deoxy sugar biosynthesis as they can produce a wide range of highly specialized monosaccharides. Indeed, deoxy and amino sugars play important roles in the virulence of gram-positive and gram-negative pathogenic species and are additionally involved in the biosynthesis of diverse macrolide antibiotics. The biosynthesis of deoxy sugars relies on the activity of NS dehydratases, which can be subdivided into three groups based on their structure and reaction mechanism. The best-characterized NS dehydratases are the 4,6-dehydratases that, together with the 5,6-dehydratases, belong to the NS-short-chain dehydrogenase/reductase superfamily. The other two groups are the less abundant 2,3-dehydratases that belong to the Nudix hydrolase superfamily and 3-dehydratases, which are related to aspartame aminotransferases. 4,6-Dehydratases catalyze the first step in all deoxy sugar biosynthesis pathways, converting nucleoside diphosphate hexoses to nucleoside diphosphate-4-keto-6-deoxy hexoses, which in turn are further deoxygenated by the 2,3- and 3-dehydratases to form dideoxy and trideoxy sugars. In this review, we give an overview of the NS dehydratases focusing on the comparison of their structure and reaction mechanisms, thereby highlighting common features, and investigating differences between closely related members of the same superfamilies.

LectinOracle: A Generalizable Deep Learning Model for Lectin-Glycan Binding Prediction

Ranging from bacterial cell adhesion over viral cell entry to human innate immunity, glycan-binding proteins or lectins are abound in nature. Widely used as staining and characterization reagents in cell biology and crucial for understanding the interactions in biological systems, lectins are a focal point of study in glycobiology. Yet the sheer breadth and depth of specificity for diverse oligosaccharide motifs has made studying lectins a largely piecemeal approach, with few options to generalize. Here, LectinOracle, a model combining transformer-based representations for proteins and graph convolutional neural networks for glycans to predict their interaction, is presented. Using a curated data set of 564,647 unique protein-glycan interactions, it is shown that LectinOracle predictions agree with literature-annotated specificities for a wide range of lectins. Using a range of specialized glycan arrays, it is shown that LectinOracle predictions generalize to new glycans and lectins, with qualitative and quantitative agreement with experimental data. It is further demonstrated that LectinOracle can be used to improve lectin classification, accelerate lectin directed evolution, predict epidemiological outcomes in the context of influenza virus, and analyze whole lectomes in host-microbe interactions. It is envisioned that the herein presented platform will advance both the study of lectins and their role in (glyco)biology.