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Protein glycosylation is a highly important, yet poorly understood protein post-translational modification. Thousands of possible glycan structures and compositions create potential for tremendous site heterogeneity. A lack of suitable analytical methods for large-scale analyses of intact glycopeptides has limited our abilities both to address the degree of heterogeneity across the glycoproteome and to understand how this contributes biologically to complex systems. Here we show that N-glycoproteome site-specific microheterogeneity can be captured via large-scale glycopeptide profiling methods enabled by activated ion electron transfer dissociation (AI-ETD), ultimately characterizing 1,545 N-glycosites (>5,600 unique N-glycopeptides) from mouse brain tissue. Our data reveal that N-glycosylation profiles can differ between subcellular regions and structural domains and that N-glycosite heterogeneity manifests in several different forms, including dramatic differences in glycosites on the same protein. Moreover, we use this large-scale glycoproteomic dataset to develop several visualizations that will prove useful for analyzing intact glycopeptides in future studies. Mass spectrometry facilitates large-scale glycosylation profiling but in-depth analysis of intact glycopeptides is still challenging. Here, the authors show that activated ion electron transfer dissociation is suitable for glycopeptide fragmentation and improves glycoproteome coverage.

Canine distemper virus (CDV) is the cause of a multisystem disease in domestic dogs and wild animals, infecting more than 20 carnivore and non-carnivore families and even infecting human cell lines in in vitro conditions. Phylogenetic classification based on the hemagglutinin gene shows 17 lineages with a phylogeographic distribution pattern. In Medellín (Colombia), the lineage South America-3 is considered endemic. Phylogenetic studies conducted in Ecuador using fragment coding for the fusion protein signal peptide (Fsp) characterized a new strain belonging to a different lineage. For understanding the distribution of the South America-3 lineage in the north of the South American continent, we characterized CDV from three Colombian cities (Medellín, Bucaramanga, and Bogotá). Using phylogenetic analysis of the hemagglutinin gene and the Fsp region, we confirmed the circulation of CDV South America-3 in different areas of Colombia. We also described, for the first time to our knowledge, the circulation of a new lineage in Medellín that presents a group monophyletic with strains previously characterized in dogs in Ecuador and in wildlife and domestic dogs in the United States, for which we propose the name “South America/North America-4” due its intercontinental distribution. In conclusion, our results indicated that there are at least four different CDV lineages circulating in domestic dogs in South America: the Europe/South America-1 lineage circulating in Brazil, Uruguay, and Argentina; the South America-2 lineage restricted to Argentina; the South America-3 lineage, which has only been reported in Colombia; and lastly an intercontinental lineage present in Colombia, Ecuador, and the United States, referred to here as the “South America/North America-4” lineage.

Mass spectrometry plays an increasingly important role in structural glycomics. This review provides an overview on currently used mass spectrometric approaches such as the characterization of glycans, the analysis of glycopeptides obtained by proteolytic cleavage of proteins and the analysis of glycosphingolipids. The given examples are demonstrating the application of mass spectrometry to study glycosylation changes associated with congenital disorders of glycosylation, lysosomal storage diseases, autoimmune diseases and cancer.

Recent advances in methods for enrichment and mass spectrometric analysis of intact glycopeptides have produced large-scale glycoproteomics datasets, but interpreting these data remains challenging. We present MSFragger-Glyco, a glycoproteomics mode of the MSFragger search engine, for fast and sensitive identification of N - and O -linked glycopeptides and open glycan searches. Reanalysis of recent N -glycoproteomics data resulted in annotation of 80% more glycopeptide spectrum matches (glycoPSMs) than previously reported. In published O -glycoproteomics data, our method more than doubled the number of glycoPSMs annotated when searching the same glycans as the original search, and yielded 4- to 6-fold increases when expanding searches to include additional glycan compositions and other modifications. Expanded searches also revealed many sulfated and complex glycans that remained hidden to the original search. With greatly improved spectral annotation, coupled with the speed of index-based scoring, MSFragger-Glyco makes it possible to comprehensively interrogate glycoproteomics data and illuminate the many roles of glycosylation. MSFragger-Glyco allows identification of N - and O -linked glycopeptides using the localization-aware open search strategy of the MSFragger search engine.

We report O-Pair Search, an approach to identify O-glycopeptides and localize O-glycosites. Using paired collision- and electron-based dissociation spectra, O-Pair Search identifies O-glycopeptides via an ion-indexed open modification search and localizes O-glycosites using graph theory and probability-based localization. O-Pair Search reduces search times more than 2,000-fold compared to current O-glycopeptide processing software, while defining O-glycosite localization confidence levels and generating more O-glycopeptide identifications. Beyond the mucin-type O-glycopeptides discussed here, O-Pair Search also accepts user-defined glycan databases, making it compatible with many types of O-glycosylation. O-Pair Search is freely available within the open-source MetaMorpheus platform at https://github.com/smith-chem-wisc/MetaMorpheus . O-Pair search identifies O-glycopeptides and localizes O-glycosites using a fragment-ion-indexed open modification search combined with a graph-based approach. It also introduces a classification scheme to unify data reporting for glycoproteomics.

Protein glycosylation is known to be involved in biological progresses such as cell recognition, growth, differentiation, and apoptosis. Fucosylation of glycoproteins plays an important role for structural stability and function of N-linked glycoproteins. Although many of biological and clinical studies of protein fucosylation by fucosyltransferases has been reported, structural classification of fucosylated N-glycoproteins such as core or outer isoforms remains a challenge. Here, we report for the first time the classification of N-glycopeptides as core- and outer-fucosylated types using tandem mass spectrometry (MS/MS) and machine learning algorithms such as the deep neural network (DNN) and support vector machine (SVM). Training and test sets of more than 800 MS/MS spectra of N-glycopeptides from the immunoglobulin gamma and alpha 1-acid-glycoprotein standards were selected for classification of the fucosylation types using supervised learning models. The best-performing model had an accuracy of more than 99% against manual characterization and area under the curve values greater than 0.99, which were calculated by probability scores from target and decoy datasets. Finally, this model was applied to classify fucosylated N-glycoproteins from human plasma. A total of 82N-glycopeptides, with 54 core-, 24 outer-, and 4 dual-fucosylation types derived from 54 glycoproteins, were commonly classified as the same type in both the DNN and SVM. Specifically, outer fucosylation was dominant in tri- and tetra-antennary N-glycopeptides, while core fucosylation was dominant in the mono-, bi-antennary and hybrid types of N-glycoproteins in human plasma. Thus, the machine learning methods can be combined with MS/MS to distinguish between different isoforms of fucosylated N-glycopeptides.

Comprehensive and selective enrichment of N-glycans, N-glycopeptides, and N-glycoproteins prior to analysis is of great significance in N-glycomics research, reducing sample complexity, removing impurity interference, increasing sample abundance and enhancing signal intensity. However, only an Fbs1 (F-box protein that recognizes sugar chain 1) GYR variant (Fg) can enrich these N-glycomolecules solely due to its substantial binding affinity for the core pentasaccharide motif of N-glycans. Stationary phase separation is commonly used to enrich N-glycomolecules efficiently. Herein, DNA encoding the Fg was cloned into pGEX-4T-1, and the protein was expressed with a GST tag, which facilitates the convenient and efficient immobilization of recombinant GST-tagged Fg to GSH agarose resin. The yield of the GST-tagged Fg reached to 0.05 g/L after optimization of the induction condition, and the purified protein exhibited good identification ability and excellent stability for months. In particular, the immobilized GST-tagged Fg can enrich N-glycans released by PNGase F and capture derivatized N-glycans possessing an intact terminal N-acetyl glucosamine (GlcNAc). Validation of immobilized GST-tagged Fg with standard N-glycopeptides and N-glycoproteins revealed its high loading capacity, sensitivity, and selectivity. The novel immobilized GST-tagged Fg is a convenient and efficient enrichment material specific for N-glycans, N-glycopeptides, and N-glycoproteins, suggesting excellent performance and prospects for industrial application.

This trends article provides an overview of the state of the art in the analysis of intact glycopeptides by proteomics technologies based on LC–MS analysis. A brief description of the main techniques used at the different steps of the analytical workflow is provided, giving special attention to the most recent developments. The topics discussed include the need for dedicated sample preparation for intact glycopeptide purification from complex biological matrices. This section covers the common approaches with a special description of new materials and innovative reversible chemical derivatization strategies, specifically devised for intact glycopeptide analysis or dual enrichment of glycosylation and other post-translational modifications. The approaches are described for the characterization of intact glycopeptide structures by LC–MS and data analysis by bioinformatics for spectra annotation. The last section covers the open challenges in the field of intact glycopeptide analysis. These challenges include the need of a detailed description of the glycopeptide isomerism, the issues with quantitative analysis, and the lack of analytical methods for the large-scale characterization of glycosylation types that remain poorly characterized, such as C-mannosylation and tyrosine O-glycosylation. This bird’s-eye view article provides both a state of the art in the field of intact glycopeptide analysis and open challenges to prompt future research on the topic. Graphical Abstract

A novel hydrophilic porous biocomposite was fabricated by incorporating graphene oxide (GO) @chitosan (CS) foam substrate (GO@CS@ZIF-8 foam) with ZIF-8 crystals in situ via a facile stirring method for simultaneous enrichment of glycopeptides and phosphopeptides from complex biological samples. The experimental results demonstrated that GO@CS@ZIF-8 foam exhibited favorable specificity for simultaneous enrichment of N-glycopeptides and phosphopeptides under the same condition for HRP and β-casein tryptic digest mixtures. The novel material was further applied to enriching both glycopeptides and phosphopeptides simultaneously from 4 μL complex human serum, and 423 N-glycopeptides and 40 phosphopeptides corresponding to 133 glycoproteins and 29 phosphoproteins were identified, respectively.

In glycomic and glycoproteomic studies, solutions containing diluted organic acids such as formic acid (FA) have been widely used for dissolving intact glycopeptide and glycan samples prior to mass spectrometry analysis. Here, we show that an undesirable + 28 Da modification occurred in a time-dependent manner when the glycan and glycopeptide samples were stored in FA solution at − 20 °C. We confirmed that this unexpected modification was caused by formylation between the hydroxyl groups of glycans and FA with a relatively low reaction rate. As this incomplete modification affected the glycan and glycopeptide identification and quantification in glycomic and glycoproteomic studies, the storage at − 20 °C should be avoided once the glycan and glycopeptide samples have been dissolved in FA solution.