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Marine algae are one of the largest sources of carbon on the planet. The microbial degradation of algal polysaccharides to their constitutive sugars is a cornerstone in the global carbon cycle in oceans. Marine polysaccharides are highly complex and heterogeneous, and poorly understood. This is also true for marine microbial proteins that specifically degrade these substrates and when characterized, they are frequently ascribed to new protein families. Marine (meta)genomic datasets contain large numbers of genes with functions putatively assigned to carbohydrate processing, but for which empirical biochemical activity is lacking. There is a paucity of knowledge on both sides of this protein/carbohydrate relationship. Addressing this ‘double blind’ problem requires high throughput strategies that allow large scale screening of protein activities, and polysaccharide occurrence. Glycan microarrays, in particular the Comprehensive Microarray Polymer Profiling (CoMPP) method, are powerful in screening large collections of glycans and we described the integration of this technology to a medium throughput protein expression system focused on marine genes. This methodology (Double Blind CoMPP or DB-CoMPP) enables us to characterize novel polysaccharide-binding proteins and to relate their ligands to algal clades. This data further indicate the potential of the DB-CoMPP technique to accommodate samples of all biological sources.

The mass spectrometry (MS)-based analysis of free polysaccharides and glycans released from proteins, lipids and proteoglycans increasingly relies on databases and software. Here, we review progress in the bioinformatics analysis of protein-released N - and O -linked glycans ( N - and O -glycomics) and propose an e-infrastructure to overcome current deficits in data and experimental transparency. This workflow enables the standardized submission of MS-based glycomics information into the public repository UniCarb-DR. It implements the MIRAGE (Minimum Requirement for A Glycomics Experiment) reporting guidelines, storage of unprocessed MS data in the GlycoPOST repository and glycan structure registration using the GlyTouCan registry, thereby supporting the development and extension of a glycan structure knowledgebase. Glycomics is gaining momentum in basic, translational and clinical research. Here, the authors review current reporting standards and analysis tools for mass-spectrometry-based glycomics, and propose an e-infrastructure for standardized reporting and online deposition of glycomics data.

The glycocalyx comprises glycosylated proteins and lipids and fcorms the outermost layer of cells. It is involved in fundamental inter- and intracellular processes, including non-self-cell and self-cell recognition, cell signaling, cellular structure maintenance, and immune protection. Characterization of the glycocalyx is thus essential to understanding cell physiology and elucidating its role in promoting health and disease. This protocol describes how to comprehensively characterize the glycocalyx N-glycans and O-glycans of glycoproteins, as well as intact glycolipids in parallel, using the same enriched membrane fraction. Profiling of the glycans and the glycolipids is performed using nanoflow liquid chromatography–mass spectrometry (nanoLC-MS). Sample preparation, quantitative LC–tandem MS (LC-MS/MS) analysis, and data processing methods are provided. In addition, we discuss glycoproteomic analysis that yields the site-specific glycosylation of membrane proteins. To reduce the amount of sample needed, N-glycan, O-glycan, and glycolipid analyses are performed on the same enriched fraction, whereas glycoproteomic analysis is performed on a separate enriched fraction. The sample preparation process takes 2–3 d, whereas the time spent on instrumental and data analyses could vary from 1 to 5 d for different sample sizes. This workflow is applicable to both cell and tissue samples. Systematic changes in the glycocalyx associated with specific glycoforms and glycoconjugates can be monitored with quantitation using this protocol. The ability to quantitate individual glycoforms and glycoconjugates will find utility in a broad range of fundamental and applied clinical studies, including glycan-based biomarker discovery and therapeutics. This protocol describes nanoflow liquid chromatography–mass spectrometry (nanoLC-MS) analysis of the N-glycans and O-glycans of glycoproteins and glycolipids, as well as site-specific glycosylation of membrane proteins.

Treating glycoproteins with household bleach releases N- and O-glycans for further structural probing. Bleach treatment of glycosphingolipids releases glycan nitriles. Glycans have essential roles in biology and the etiology of many diseases. A major hurdle in studying glycans through functional glycomics is the lack of methods to release glycans from diverse types of biological samples. Here we describe an oxidative strategy using household bleach to release all types of free reducing N-glycans and O-glycan-acids from glycoproteins, and glycan nitriles from glycosphingolipids. Released glycans are directly useful in glycomic analyses and can be derivatized fluorescently for functional glycomics. This chemical method overcomes the limitations in glycan generation and promotes archiving and characterization of human and animal glycomes and their functions.

The structural analysis of glycoproteins is a challenging endeavor and is under steadily increasing demand, but only a very limited number of labs have the expertise required to accomplish this task. This tutorial is aimed at researchers from the fields of molecular biology and biochemistry that have discovered that glycoproteins are important in their biological research and are looking for the tools to elucidate their structure. It provides brief descriptions of the major and most common analytical techniques used in glycomics and glycoproteomics analysis, including explanations of the rationales for individual steps and references to published literature containing the experimental details necessary to carry out the analyses. Glycomics includes the comprehensive study of the structure and function of the glycans expressed in a given cell or organism along with identification of all the genes that encode glycoproteins and glycosyltransferases. Glycoproteomics which is subset of both glycomics and proteomics is the identification and characterization of proteins bearing carbohydrates as posttranslational modification. This tutorial is designed to ease entry into the glycomics and glycoproteomics field for those without prior carbohydrate analysis experience.

We have explored the fundamental biological processes by which complex carbohydrates expressed on cellular glycoproteins and glycolipids and in secretions of cells promote cell adhesion and signaling. We have also explored processes by which animal pathogens, such as viruses, bacteria, and parasites adhere to glycans of animal cells and initiate disease. Glycans important in cell signaling and adhesion, such as key O-glycans, are essential for proper animal development and cellular differentiation, but they are also involved in many pathogenic processes, including inflammation, tumorigenesis and metastasis, and microbial and parasitic pathogenesis. The overall hypothesis guiding these studies is that glycoconjugates are recognized and bound by a growing class of proteins called glycan-binding proteins (GBPs or lectins) expressed by all types of cells. There is an incredible variety and diversity of GBPs in animal cells involved in binding N- and O-glycans, glycosphingolipids, and proteoglycan/glycosaminoglycans. We have specifically studied such molecular determinants recognized by selectins, galectins, and many other C-type lectins, involved in leukocyte recruitment to sites of inflammation in human tissues, lymphocyte trafficking, adhesion of human viruses to human cells, structure and immunogenicity of glycoproteins on the surfaces of human parasites. We have also explored the molecular basis of glycoconjugate biosynthesis by exploring the enzymes and molecular chaperones required for correct protein glycosylation. From these studies opportunities for translational biology have arisen, involving production of function-blocking antibodies, anti-glycan specific antibodies, and synthetic glycoconjugates, e.g. glycosulfopeptides, that specifically are recognized by GBPs. This invited short review is based in part on my presentation for the IGO Award 2019 given by the International Glycoconjugate Organization in Milan.

Comparative glycomics data are compositional data, where measured glycans are parts of a whole, indicated by relative abundances. Applying traditional statistical analyses to these data often results in misleading conclusions, such as spurious “decreases” of glycans when other structures increase in abundance, or high false-positive rates for differential abundance. Our work introduces a compositional data analysis framework, tailored to comparative glycomics, to account for these data dependencies. We employ center log-ratio and additive log-ratio transformations, augmented with a scale uncertainty/information model, to introduce a statistically robust and sensitive data analysis pipeline. Applied to comparative glycomics datasets, including known glycan concentrations in defined mixtures, this approach controls false-positive rates and results in reproducible biological findings. Additionally, we present specialized analysis modalities: alpha- and beta-diversity analyze glycan distributions within and between samples, while cross-class glycan correlations shed light on previously undetected interdependencies. These approaches reveal insights into glycome variations that are critical to understanding roles of glycans in health and disease. Bennett et al. develop a statistical approach for analyzing comparative glycomics data that accounts for inherent data dependencies, yielding robust and sensitive results. This approach can identify how these molecules vary in health and disease.

The in-depth, high-sensitivity characterization of the glycome from complex biological samples, such as biofluids and tissues, is of utmost importance in basic biological research and biomarker discovery. Major challenges often arise from the vast structural diversity of glycans in combination with limited sample amounts. Here, we present a method for the highly sensitive characterization of released N -glycans by combining a capillary electrophoresis-electrospray ionization-mass spectrometry (CE-ESI-MS) approach with linkage-specific derivatization of sialic acids and uniform cationic reducing end labelling of all glycans. This method allows the analysis of glycans at the attomole level, provides information on sialic acid isomers and enables the in-depth characterization of complex samples, even when available in minute amounts. In-depth characterization of complex glycomes is complicated by the immense structural diversity of glycans. Here, the authors present a mass spectrometry-based strategy for untargeted, sensitive glycan profiling and identify 167 N -glycan compositions in total human plasma.

This protocol shows how to obtain a detailed glycan compositional and structural profile from purified glycoproteins or protein mixtures, and it can be used to distinguish different isobaric glycan isomers. Glycoproteins are immobilized on PVDF membranes before the N -glycans are enzymatically released by PNGase F, isolated and reduced. Subsequently, O -glycans are chemically released from the same protein spot by reductive β-elimination. After desalting with cation exchange microcolumns, the glycans are separated and analyzed by porous graphitized carbon liquid chromatography–electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS). Optionally, the glycans can be treated with sialidases or other specific exoglycosidases to yield more detailed structural information. The sample preparation takes approximately 4 d, with a heavier workload on days 2 and 3, and a lighter load on days 1 and 4. The time for data interpretation depends on the complexity of the samples analyzed. This method can be used in conjunction with the analysis of enriched glycopeptides by capillary/nanoLC-ESI-MS/MS, which together provide detailed information regarding the site heterogeneity of glycosylation.

Glycans constitute the most complicated post-translational modification, modulating protein activity in health and disease. However, structural annotation from tandem mass spectrometry (MS/MS) data is a bottleneck in glycomics, preventing high-throughput endeavors and relegating glycomics to a few experts. Trained on a newly curated set of 500,000 annotated MS/MS spectra, here we present CandyCrunch, a dilated residual neural network predicting glycan structure from raw liquid chromatography–MS/MS data in seconds (top-1 accuracy: 90.3%). We developed an open-access Python-based workflow of raw data conversion and prediction, followed by automated curation and fragment annotation, with predictions recapitulating and extending expert annotation. We demonstrate that this can be used for de novo annotation, diagnostic fragment identification and high-throughput glycomics. For maximum impact, this entire pipeline is tightly interlaced with our glycowork platform and can be easily tested at https://colab.research.google.com/github/BojarLab/CandyCrunch/blob/main/CandyCrunch.ipynb . We envision CandyCrunch to democratize structural glycomics and the elucidation of biological roles of glycans. CandyCrunch is a deep learning-based tool for predicting glycan structures from tandem mass spectrometry data. The paper also introduces CandyCrumbs that automatically annotates fragment ions in higher-order tandem mass spectrometry spectra.