nQuant Enables Precise Quantitative N-Glycomics

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

O-GlcNAc informatics: advances and trends

As a post-translational modification, protein glycosylation is critical in health and disease. O-Linked β-N-acetylglucosamine (O-GlcNAc) modification (O-GlcNAcylation), as an intracellular monosaccharide modification on proteins, was discovered 40 years ago. Thanks to technological advances, the physiological and pathological significance of O-GlcNAcylation has been gradually revealed and widely appreciated, especially in recent years. O-GlcNAc informatics has been quickly evolving. Clearly, O-GlcNAc informatics tools have not only facilitated O-GlcNAc functional studies, but also provided us a unique perspective on protein O-GlcNAcylation. In this article, we review O-GlcNAc-focused software tools and servers that have been developed for O-GlcNAc research over the past four decades. Specifically, we will (1) survey bioinformatics tools that have facilitated O-GlcNAc proteomics data analysis, (2) introduce databases/servers for O-GlcNAc proteins/sites that have been experimentally identified by individual research labs, (3) describe software tools that have been developed to predict O-GlcNAc sites, and (4) introduce platforms cataloging proteins that interact with the O-GlcNAc cycling enzymes (i.e., O-GlcNAc transferase and O-GlcNAcase). We hope these resources will provide useful information to both experienced researchers and new incomers to the O-GlcNAc field. We anticipate that this review provides a framework to stimulate the future development of more sophisticated informatic tools for O-GlcNAc research.

GlyCombo Enables Rapid, Complete Glycan Composition Identification across Diverse Glycomic Sample Types

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

Carbohydrate Structure Database: current state and recent developments

Carbohydrate Structure Database (CSDB) is a curated glycan data collection and a glycoinformatic platform. In this report, its database, analytical, and other components that have appeared for the recent years are reviewed. The major improvements were achieving close-to-full coverage on glycans from microorganisms, launching modules for glycosyltransferases and saccharide conformations, online glycan builder and 3D modeler, NMR simulator, NMR-based structure predictor, and other tools.

Recent advances in N-glycan biomarker discovery among human diseases

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

N-Glycosylation as a Modulator of Protein Conformation and Assembly in Disease

Glycosylation, a prevalent post-translational modification, plays a pivotal role in regulating intricate cellular processes by covalently attaching glycans to macromolecules. Dysregulated glycosylation is linked to a spectrum of diseases, encompassing cancer, neurodegenerative disorders, congenital disorders, infections, and inflammation. This review delves into the intricate interplay between glycosylation and protein conformation, with a specific focus on the profound impact of N-glycans on the selection of distinct protein conformations characterized by distinct interactomes-namely, protein assemblies-under normal and pathological conditions across various diseases. We begin by examining the spike protein of the SARS virus, illustrating how N-glycans regulate the infectivity of pathogenic agents. Subsequently, we utilize the prion protein and the chaperone glucose-regulated protein 94 as examples, exploring instances where N-glycosylation transforms physiological protein structures into disease-associated forms. Unraveling these connections provides valuable insights into potential therapeutic avenues and a deeper comprehension of the molecular intricacies that underlie disease conditions. This exploration of glycosylation's influence on protein conformation effectively bridges the gap between the glycome and disease, offering a comprehensive perspective on the therapeutic implications of targeting conformational mutants and their pathologic assemblies in various diseases. The goal is to unravel the nuances of these post-translational modifications, shedding light on how they contribute to the intricate interplay between protein conformation, assembly, and disease.

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.

Sulfated fucan could serve as a species marker of sea cucumber with endo-1,3-fucanase as the essential tool

In the past few decades, sulfated fucan from sea cucumber had attracted considerable interest owing to its abundant physiological activities. Nevertheless, its potential for species discrimination had not been investigated. Herein, particular attention was given to sea cucumber Apostichopus japonicus, Acaudina molpadioides, Holothuria hilla, Holothuria tubulosa, Isostichopus badionotus and Thelenota ananas to examine the feasibility of sulfated fucan as a species marker of sea cucumber. The enzymatic fingerprint suggested that sulfated fucan exhibited significant interspecific discrepancy and intraspecific stability, which revealed that sulfated fucan could serve as the species marker of sea cucumber, by utilizing the overexpressed endo-1,3-fucanase Fun168A and the ultra-performance liquid chromatography-high resolution mass spectrum. Moreover, oligosaccharide profile of sulfated fucan was determined. The oligosaccharide profile combined with hierarchical clustering analysis and principal components analysis further confirmed that sulfated fucan could serve as a marker with a satisfying performance. Besides, load factor analysis showed that the minor structure of sulfated fucan also contributed to the sea cucumber discrimination, besides the major structure. The overexpressed fucanase played an indispensable role in the discrimination, due to its specificity and high activity. The study would lead to a new strategy for species discrimination of sea cucumber based on sulfated fucan.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2017-2018

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization mass spectrometry (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2018. Also included are papers that describe methods appropriate to glycan and glycoprotein analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, new methods, matrices, derivatization, MALDI imaging, fragmentation and the use of arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides, and biopharmaceuticals. Most of the applications are presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions, and applications to chemical synthesis. The reported work shows increasing use of combined new techniques such as ion mobility and highlights the impact that MALDI imaging is having across a range of diciplines. MALDI is still an ideal technique for carbohydrate analysis and advancements in the technique and the range of applications continue steady progress.

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.

Representation of polysaccharide molecules by SNFG and 3D-SNFG methods--Take Potentilla anserina L polysaccharide molecule as an example

With the continuous deepening of international research in the field of biology, more and more studies have found that polysaccharides have multiple biological functions, so that polysaccharides have gradually become the research objects of more and more scientists in the world, and a large number of relevant researchers have carried out Glycobiology research, most of the current research is on the separation, extraction, structural characterization and activity experiments of polysaccharides. However, at this stage, research on the structure-activity relationship of various polysaccharides extracted from plants is relatively rare, and the representation method of polysaccharide structures is not perfect, not unified, complicated in drawing, and not beautiful and convenient to read. The SNFG (Symbol Nomenclature For Glycans) method, which is the symbolic nomenclature of polysaccharides and the 3D-SNFG method, can solve the above problems well, and can use unified rules to describe and describe the molecular structure of polysaccharides, and the painting process is more convenient and more convenient. It is beautiful and makes it easier for readers to read. In this paper, the fern hemp polysaccharide molecule is taken as an example. After drawing it with chemoffice, SNFG and 3D-SNFG are used to describe it, and then compared. It is clear at a glance that the use of SNFG and 3D-SNFG methods has been widely recognized and accepted internationally, which can provide great convenience for sugar-related research and information exchange.

Source files of the Carbohydrate Structure Database: the way to sophisticated analysis of natural glycans

The Carbohydrate Structure Database (CSDB, http://csdb.glycoscience.ru/ ) is a free curated repository storing various data on glycans of bacterial, fungal and plant origins. Currently, it maintains a close-to-full coverage on bacterial and fungal carbohydrates up to the year 2020. The CSDB web-interface provides free access to the database content and dedicated tools. Still, the number of these tools and the types of the corresponding analyses is limited, whereas the database itself contains data that can be used in a broader scope of analytical studies. In this paper, we present CSDB source data files and a self-contained SQL dump, and exemplify their possible application in glycan-related studies. By using CSDB in an SQL format, the user can gain access to the chain length distribution or charge distribution (as an example) in a given set of glycans defined according to specific structural, taxonomic, or other parameters, whereas the source text dump files can be imported to any dedicated database with a specific internal architecture differing from that of CSDB.

Carbohydrate structure database (CSDB) oligosaccharide conformation tool

Population analysis in terms of glycosidic torsion angles is frequently used to reveal preferred conformers of glycans. However, due to high structural diversity and flexibility of carbohydrates, conformational characterization of complex glycans can be a challenging task. Herein we present a conformation module of oligosaccharide fragments occurring in natural glycan structures developed on the platform of the Carbohydrate Structure Database (CSDB). Currently, this module deposits free energy surface and conformer abundance maps plotted as a function of glycosidic torsions for 194 inter-residue bonds. Data are automatically and continuously derived from explicit-solvent molecular dynamics (MD) simulations. The module was also supplemented with high-temperature MD data of saccharides (2403 maps) provided by GlycoMapsDB (hosted by GLYCOSCIENCES.de project). Conformational data defined by up to four torsional degrees of freedom can be freely explored using a web interface of the module available at http://csdb.glycoscience.ru/database/core/search_conf.html.

Identification microbial glycans substructure associate with disease and species

The microbial glycans mediate many significant biological acts, such as pathogen survival, host-microbe interactions, and immune evasion. The systematic study of microbial glycans structure remains challenging because of its high complexity and variability. In this study, we screened all the microbial glycans structures in the CSDB (Carbohydrate Structure Database), disassembled them into substructures, and calculated all the substructures' numbers. The results showed that a large number of glycan substructures are shared among different microorganisms. Further analysis showed that the glycan substructures appeared in specific bacterial groups may be related to the species and pathogenicity of microorganisms. Broadly, these findings provided an alternative approach or clue to discover the hidden information and the biological functions of glycans. The results can be used to detect broad-scope pathogen or prepare broad-spectrum vaccines.

Probiotic Bacteria with High Alpha-Gal Content Protect Zebrafish against Mycobacteriosis

Mycobacteriosis affects wild fish and aquaculture worldwide, and alternatives to antibiotics are needed for an effective and environmentally sound control of infectious diseases. Probiotics have shown beneficial effects on fish growth, nutrient metabolism, immune responses, disease prevention and control, and gut microbiota with higher water quality. However, the identification and characterization of the molecules and mechanisms associated with probiotics is a challenge that requires investigation. To address this challenge, herein we used the zebrafish model for the study of the efficacy and mechanisms of probiotic interventions against tuberculosis. First, bacteria from fish gut microbiota were identified with high content of the surface glycotope Galα1-3Galβ1-(3)4GlcNAc-R (α-Gal) that has been shown to induce protective immune responses. The results showed that probiotics of selected bacteria with high α-Gal content, namely Aeromonas veronii and Pseudomonas entomophila, were biosafe and effective for the control of Mycobacterium marinum. Protective mechanisms regulating immunity and metabolism activated in response to α-Gal and probiotics with high α-Gal content included modification of gut microbiota composition, B-cell maturation, anti-α-Gal antibodies-mediated control of mycobacteria, induced innate immune responses, beneficial effects on nutrient metabolism and reduced oxidative stress. These results support the potential of probiotics with high -Gal content for the control of fish mycobacteriosis and suggested the possibility of exploring the development of combined probiotic treatments alone and in combination with -Gal for the control of infectious diseases.

An Integrated Strategy Reveals Complex Glycosylation of Erythropoietin Using Mass Spectrometry

The characterization of therapeutic glycoproteins is challenging due to the structural heterogeneity of the therapeutic protein glycosylation. This study presents an in-depth analytical strategy for glycosylation of first-generation erythropoietin (epoetin beta), including a developed mass spectrometric workflow for N-glycan analysis, bottom-up mass spectrometric methods for site-specific N-glycosylation, and a LC-MS approach for O-glycan identification. Permethylated N-glycans, peptides, and enriched glycopeptides of erythropoietin were analyzed by nanoLC-MS/MS, and de-N-glycosylated erythropoietin was measured by LC-MS, enabling the qualitative and quantitative analysis of glycosylation and different glycan modifications (e.g., phosphorylation and O-acetylation). The newly developed Python scripts enabled the identification of 140 N-glycan compositions (237 N-glycan structures) from erythropoietin, especially including 8 phosphorylated N-glycan species. The site-specificity of N-glycans was revealed at the glycopeptide level by pGlyco software using different proteases. In total, 114 N-glycan compositions were identified from glycopeptide analysis. Moreover, LC-MS analysis of de-N-glycosylated erythropoietin species identified two O-glycan compositions based on the mass shifts between non-O-glycosylated and O-glycosylated species. Finally, this integrated strategy was proved to realize the in-depth glycosylation analysis of a therapeutic glycoprotein to understand its pharmacological properties and improving the manufacturing processes.

Comparative Analysis of Different N-glycan Preparation Approaches and Development of Optimized Solid-Phase Permethylation Using Mass Spectrometry

Protein N-glycosylation characterization is challenging due to structural micro- and macro-heterogeneity. Although various N-glycan preparation strategies, including purification and derivatization, have been previously developed prior to mass spectrometric analysis, systematic evaluation still needs to be performed. This study compared the different N-glycan purification strategies, including filter-aided sample preparation, de-N-glycosylated protein precipitation, and trypsin digestion followed by reversed phase-based solid-phase extraction, and derivatization approaches, such as solid-phase permethylation, reductive amination, and reduction. With the comparative analysis, an optimized solid-phase permethylation (OSPP) workflow was developed for mass spectrometric N-glycomics, showing simplified analysis for N-glycan compositions and high yields using etanercept. The N-glycan samples released from trastuzumab and adalimumab were utilized to test OSPP to obtain their N-glycan profiles using mass spectrometry. Based on different standard procedures across laboratories, this study provides the reference for analysts to select an appropriate N-glycan preparation method with their research purposes.

Proposal of the Annotation of Phosphorylated Amino Acids and Peptides Using Biological and Chemical Codes

Phosphorylation represents one of the most important modifications of amino acids, peptides, and proteins. By modifying the latter, it is useful in improving the functional properties of foods. Although all these substances are broadly annotated in internet databases, there is no unified code for their annotation. The present publication aims to describe a simple code for the annotation of phosphopeptide sequences. The proposed code describes the location of phosphate residues in amino acid side chains (including new rules of atom numbering in amino acids) and the diversity of phosphate residues (e.g., di- and triphosphate residues and phosphate amidation). This article also includes translating the proposed biological code into SMILES, being the most commonly used chemical code. Finally, it discusses possible errors associated with applying the proposed code and in the resulting SMILES representations of phosphopeptides. The proposed code can be extended to describe other modifications in the future.

CSDB_GT, a curated glycosyltransferase database with close-to-full coverage on three most studied nonanimal species

We report the accomplishment of the first stage of the development of a novel manually curated database on glycosyltransferase (GT) activities, CSDB_GT. CSDB_GT (http://csdb.glycoscience.ru/gt.html) has been supplemented with GT activities from Saccharomyces cerevisiae. Now it provides the close-to-complete coverage on experimentally confirmed GTs from the three most studied model organisms from the three kingdoms: plantae (Arabidopsis thaliana, ca. 930 activities), bacteria (Escherichia coli, ca. 820 activities) and fungi (S. cerevisiae, ca. 270 activities).

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.

Databases and Bioinformatic Tools for Glycobiology and Glycoproteomics

Glycosylation plays critical roles in various biological processes and is closely related to diseases. Deciphering the glycocode in diverse cells and tissues offers opportunities to develop new disease biomarkers and more effective recombinant therapeutics. In the past few decades, with the development of glycobiology, glycomics, and glycoproteomics technologies, a large amount of glycoscience data has been generated. Subsequently, a number of glycobiology databases covering glycan structure, the glycosylation sites, the protein scaffolds, and related glycogenes have been developed to store, analyze, and integrate these data. However, these databases and tools are not well known or widely used by the public, including clinicians and other researchers who are not in the field of glycobiology, but are interested in glycoproteins. In this study, the representative databases of glycan structure, glycoprotein, glycan-protein interactions, glycogenes, and the newly developed bioinformatic tools and integrated portal for glycoproteomics are reviewed. We hope this overview could assist readers in searching for information on glycoproteins of interest, and promote further clinical application of glycobiology.

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.

Recent advances in glycoinformatic platforms for glycomics and glycoproteomics

Protein glycosylation is the most complex and prevalent post-translation modification in terms of the number of proteins modified and the diversity generated. To understand the functional roles of glycoproteins it is important to gain an insight into the repertoire of oligosaccharides present. The comparison and relative quantitation of glycoforms combined with site-specific identification and occupancy are necessary steps in this direction. Computational platforms have continued to mature assisting researchers with the interpretation of such glycomics and glycoproteomics data sets, but frequently support dedicated workflows and users rely on the manual interpretation of data to gain insights into the glycoproteome. The growth of site-specific knowledge has also led to the implementation of machine-learning algorithms to predict glycosylation which is now being integrated into glycoproteomics pipelines. This short review describes commercial and open-access databases and software with an emphasis on those that are actively maintained and designed to support current analytical workflows.

Advancing Solutions to the Carbohydrate Sequencing Challenge

Carbohydrates possess a variety of distinct features with stereochemistry playing a particularly important role in distinguishing their structure and function. Monosaccharide building blocks are defined by a high density of chiral centers. Additionally, the anomericity and regiochemistry of the glycosidic linkages carry important biological information. Any carbohydrate-sequencing method needs to be precise in determining all aspects of this stereodiversity. Recently, several advances have been made in developing fast and precise analytical techniques that have the potential to address the stereochemical complexity of carbohydrates. This perspective seeks to provide an overview of some of these emerging techniques, focusing on those that are based on NMR and MS-hybridized technologies including ion mobility spectrometry and IR spectroscopy.