Optimal Dissociation Methods Differ for N- and O-Glycopeptides

Cosmc regulates O-glycan extension in murine hepatocytes

Hepatocytes synthesize a vast number of glycoproteins found in their membranes and secretions, many of which contain O-glycans linked to Ser/Thr residues. As the functions and distribution of O-glycans on hepatocyte-derived membrane glycoproteins and blood glycoproteins are not well understood, we generated mice with a targeted deletion of Cosmc (C1Galt1c1) in hepatocytes. Liver glycoproteins in WT mice express typical sialylated core 1 O-glycans (T antigen/CD176) (Galβ1-3GalNAcα1-O-Ser/Thr), whereas the Cosmc knockout hepatocytes (HEP-Cosmc-KO) lack extended O-glycans and express the Tn antigen (CD175) (GalNAcα1-O-Ser/Thr). Tn-containing glycoproteins occur in the sera of HEP-Cosmc-KO mice but not in WT mice. The LDL-receptor (LDLR), a well-studied O-glycosylated glycoprotein in hepatocytes, behaves as a ∼145kD glycoprotein in WT liver lysates, whereas it is reduced to ∼120 kDa in lysates from HEP-Cosmc-KO mice. Interestingly, the expression of the LDLR, as well as HMG-CoA reductase, which is typically altered in response to dysregulated cholesterol metabolism, are similar between WT and HEP-Cosmc-KO mice, indicating no significant effect by Cosmc deletion on either LDLR stability or cholesterol metabolism. Consistent with this, we observed no detectable phenotype in the HEP-Cosmc-KO mice regarding development, appearance or aging compared to WT. These results provide surprising, novel information about the pathway of O-glycosylation in the liver.

A chemoenzymatic method for simultaneous profiling N- and O-glycans on glycoproteins using one-pot format

Glycosylation is generally characterized and controlled as a critical quality attribute for therapeutic glycoproteins because glycans can impact protein drug-product efficacy, half-life, stability, and safety. Analytical procedures to characterize N-glycans are relatively well established, but the characterization of O-glycans is challenging due to the complex workflows and lack of enzymatic tools. Here, we present a simplified chemoenzymatic method to simultaneously profile N- and O-glycans from the same sample using a one-pot format by mass spectrometry (MS). N-glycans were first released by PNGase F, followed by O-glycopeptide generation by proteinase K, selective N-glycan reduction, and O-glycan release by β-elimination during permethylation of both N- and O-glycans. Glycan structural assignments and determination of N- to O-glycan ratio was obtained from the one-pot mass spectra. The streamlined, one-pot method is a reliable approach that will facilitate advanced characterizations for quality assessments of therapeutic glycoproteins.

The Plant PTM Viewer 2.0: in-depth exploration of plant protein modification landscapes

Post-translational modifications (PTMs) greatly increase protein diversity and functionality. To help the plant research community interpret the ever-increasing number of reported PTMs, the Plant PTM Viewer (https://www.psb.ugent.be/PlantPTMViewer) provides an intuitive overview of plant protein PTMs and the tools to assess it. This update includes 62 novel PTM profiling studies, adding a total of 112 000 modified peptides reporting plant PTMs, including 14 additional PTM types and three species (moss, tomato, and soybean). Furthermore, an open modification re-analysis of a large-scale Arabidopsis thaliana mass spectrometry tissue atlas identified previously uncharted landscapes of lysine acylations predominant in seed and flower tissues and 3-phosphoglycerylation on glycolytic enzymes in plants. An extra 'Protein list analysis' tool was developed for retrieval and assessing the enrichment of PTMs in a protein list of interest. We conducted a protein list analysis on nuclear proteins, revealing a substantial number of redox modifications in the nucleus, confirming previous assumptions regarding the redox regulation of transcription. We encourage the plant research community to use PTM Viewer 2.0 for hypothesis testing and new target discovery, and also to submit new data to expand the coverage of conditions, plant species, and PTM types, thereby enriching our understanding of plant biology.

Expanding N-glycopeptide identifications by modeling fragmentation, elution, and glycome connectivity

Accurate glycopeptide identification in mass spectrometry-based glycoproteomics is a challenging problem at scale. Recent innovation has been made in increasing the scope and accuracy of glycopeptide identifications, with more precise uncertainty estimates for each part of the structure. We present a dynamically adapting relative retention time model for detecting and correcting ambiguous glycan assignments that are difficult to detect from fragmentation alone, a layered approach to glycopeptide fragmentation modeling that improves N-glycopeptide identification in samples without compromising identification quality, and a site-specific method to increase the depth of the glycoproteome confidently identifiable even further. We demonstrate our techniques on a set of previously published datasets, showing the performance gains at each stage of optimization. These techniques are provided in the open-source glycomics and glycoproteomics platform GlycReSoft available at https://github.com/mobiusklein/glycresoft .

MOTAI: A Novel Method for the Study of O-GalNAcylation and Complex O-Glycosylation in Cancer

The Tn antigen, an immature truncated O-glycosylation, is a promising biomarker for cancer detection and diagnosis. However, reliable methods for analyzing O-GalNAcylation and complex O-glycosylation are lacking. Here, we develop a novel method, MOTAI, for the sequential analysis of O-glycosylation using different O-glycoproteases. MOTAI conjugates glycopeptides on a solid support and releases different types of O-glycosylation through sequential enzymatic digestion by O-glycoproteases, including OpeRATOR and IMPa. Because OpeRATOR has less activity on O-GalNAcylation, MOTAI enriches O-GalNAcylation for subsequent analysis. We demonstrate the effectiveness of MOTAI by analyzing fetuin O-glycosylation and Jurkat cell lines. We then apply MOTAI to analyze colorectal cancer and benign colorectal polyps. We identify 32 Tn/sTn-glycoproteins and 43 T/sT-glycoproteins that are significantly increased in tumor tissues. Gene Ontology analysis reveals that most of these proteins are ECM proteins involved in the adhesion process of the intercellular matrix. Additionally, the protein disulfide isomerase CRELD2 has a significant difference in Tn expression, and the abnormally glycosylated T345 and S349 O-glycosylation sites in cancer group samples may promote the secretion of CRELD2 and ultimately tumorigenesis through ECM reshaping. In summary, MOTAI provides a powerful new tool for the in-depth analysis of O-GalNAcylation and complex O-glycosylation. It also reveals the upregulation of Tn/sTn-glycoproteins in colorectal cancer, which may provide new insights into cancer biology and biomarker discovery.

Quantification and site-specific analysis of co-occupied N- and O-glycopeptides

Protein glycosylation is a complex post-translational modification that is generally classified as N- or O-linked. Site-specific analysis of glycopeptides is accomplished with a variety of fragmentation methods, depending on the type of glycosylation being investigated and the instrumentation available. For instance, collisional dissociation methods are frequently used for N-glycoproteomic analysis with the assumption that one N-sequon exists per tryptic peptide. Alternatively, electron-based methods are indispensable for O-glycosite localization. However, the presence of simultaneously N- and O-glycosylated peptides could suggest the necessity of electron-based fragmentation methods for N-glycoproteomics, which is not commonly performed. Thus, we quantified the prevalence of N- and O-glycopeptides in mucins and other glycoproteins. A much higher frequency of co-occupancy within mucins was detected whereas only a negligible occurrence occurred within non-mucin glycoproteins. This was demonstrated from analyses of recombinant and/or purified proteins, as well as more complex samples. Where co-occupancy occurred, O-glycosites were frequently localized to the Ser/Thr within the N-sequon. Additionally, we found that O-glycans in close proximity to the occupied Asn were predominantly unelaborated core 1 structures, while those further away were more extended. Overall, we demonstrate electron-based methods are required for robust site-specific analysis of mucins, wherein co-occupancy is more prevalent. Conversely, collisional methods are generally sufficient for analyses of other types of glycoproteins.

Glycan-Tailored Glycoproteomic Analysis Reveals Serine is the Sole Residue Subjected to O-Linked Glycosylation in Acinetobacter baumannii

Protein glycosylation is a ubiquitous process observed across all domains of life. Within the human pathogen Acinetobacter baumannii, O-linked glycosylation is required for virulence; however, the targets and conservation of glycosylation events remain poorly defined. In this work, we expand our understanding of the breadth and site specificity of glycosylation within A. baumannii by demonstrating the value of strain specific glycan electron-transfer/higher-energy collision dissociation (EThcD) triggering for bacterial glycoproteomics. By coupling tailored EThcD-triggering regimes to complementary glycopeptide enrichment approaches, we assessed the observable glycoproteome of three A. baumannii strains (ATCC19606, BAL062, and D1279779). Combining glycopeptide enrichment techniques including ion mobility (FAIMS), metal oxide affinity chromatography (titanium dioxide), and hydrophilic interaction liquid chromatography (ZIC-HILIC), as well as the use of multiple proteases (trypsin, GluC, pepsin, and thermolysis), we expand the known A. baumannii glycoproteome to 33 unique glycoproteins containing 42 glycosylation sites. We demonstrate that serine is the sole residue subjected to glycosylation with the substitution of serine for threonine abolishing glycosylation in model glycoproteins. An A. baumannii pan-genome built from 576 reference genomes identified that serine glycosylation sites are highly conserved. Combined this work expands our knowledge of the conservation and site specificity of A. baumannii O-linked glycosylation.

Experimentally Determined Diagnostic Ions for Identification of Peptide Glycotopes

The analysis of the structures of glycans present on glycoproteins is an essential component for determining glycoprotein function; however, detailed glycan structural assignment on glycopeptides from proteomics mass spectrometric data remains challenging. Glycoproteomic analysis by mass spectrometry currently can provide significant, yet incomplete, information about the glycans present, including the glycan monosaccharide composition and in some circumstances the site(s) of glycosylation. Advancements in mass spectrometric resolution, using high-mass accuracy instrumentation and tailored MS/MS fragmentation parameters, coupled with a dedicated definition of diagnostic fragmentation ions have enabled the determination of some glycan structural features, or glycotopes, expressed on glycopeptides. Here we present a collation of diagnostic glycan fragments produced by traditional positive-ion-mode reversed-phase LC-ESI MS/MS proteomic workflows and describe the specific fragmentation energy settings required to identify specific glycotopes presented on N- or O-linked glycopeptides in a typical proteomics MS/MS experiment.

Analysis of Mucin-Domain Glycoproteins Using Mass Spectrometry

Mucin-domain glycoproteins are characterized by their high density of glycosylated serine and threonine residues, which complicates their analysis by mass spectrometry. The dense glycosylation renders the protein backbone inaccessible to workhorse proteases like trypsin, the vast heterogeneity of glycosylation often results in ion suppression from unmodified peptides, and search algorithms struggle to confidently analyze and site-localize O-glycosites. We have made a number of advances to address these challenges, rendering mucinomics possible for the first time. Here, we summarize these contributions and provide a detailed protocol for mass spectrometric analysis of mucin-domain glycoproteins. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Enrichment of mucin-domain glycoproteins Basic Protocol 2: Enzymatic digestion of mucin-domain glycoprotein(s) Basic Protocol 3: Mass spectrometry data collection for O-glycopeptides Basic Protocol 4: Mass spectrometry data analysis of O-glycopeptides.

Quantitative proteome-wide O-glycoproteomics analysis with FragPipe

Identification of O-glycopeptides from tandem mass spectrometry data is complicated by the near complete dissociation of O-glycans from the peptide during collisional activation and by the combinatorial explosion of possible glycoforms when glycans are retained intact in electron-based activation. The recent O-Pair search method provides an elegant solution to these problems, using a collisional activation scan to identify the peptide sequence and total glycan mass, and a follow-up electron-based activation scan to localize the glycosite(s) using a graph-based algorithm in a reduced search space. Our previous O-glycoproteomics methods with MSFragger-Glyco allowed for extremely fast and sensitive identification of O-glycopeptides from collisional activation data but had limited support for site localization of glycans and quantification of glycopeptides. Here, we report an improved pipeline for O-glycoproteomics analysis that provides proteome-wide, site-specific, quantitative results by incorporating the O-Pair method as a module within FragPipe. In addition to improved search speed and sensitivity, we add flexible options for oxonium ion-based filtering of glycans and support for a variety of MS acquisition methods and provide a comparison between all software tools currently capable of O-glycosite localization in proteome-wide searches.

Maximizing Glycoproteomics Results through an Integrated Parallel Accumulation Serial Fragmentation Workflow

Glycoproteins play important roles in numerous physiological processes and are often implicated in disease. Analysis of site-specific protein glycobiology through glycoproteomics has evolved rapidly in recent years thanks to hardware and software innovations. Particularly, the introduction of parallel accumulation serial fragmentation (PASEF) on hybrid trapped ion mobility time-of-flight mass spectrometry instruments combined deep proteome sequencing with separation of (near-)isobaric precursor ions or converging isotope envelopes through ion mobility separation. However, the reported use of PASEF in integrated glycoproteomics workflows to comprehensively capture the glycoproteome is still limited. To this end, we developed an integrated methodology using timsTOF Pro 2 to enhance N-glycopeptide identifications in complex mixtures. We systematically optimized the ion optics tuning, collision energies, mobility isolation width, and the use of dopant-enriched nitrogen gas (DEN). Thus, we obtained a marked increase in unique glycopeptide identification rates compared to standard proteomics settings, showcasing our results on a large set of glycopeptides. With short liquid chromatography gradients of 30 min, we increased the number of unique N-glycopeptide identifications in human plasma samples from around 100 identifications under standard proteomics conditions to up to 1500 with our optimized glycoproteomics approach, highlighting the need for tailored optimizations to obtain comprehensive data.

Glycoproteomics: Charting new territory in mass spectrometry and glycobiology

Glycosylation is an incredibly common and diverse post-translational modification that contributes widely to cellular health and disease. Mass spectrometry is the premier technique to study glycoproteins; however, glycoproteomics has lagged behind traditional proteomics due to the challenges associated with studying glycosylation. For instance, glycans dissociate by collision-based fragmentation, thus necessitating electron-based fragmentation for site-localization. The vast glycan heterogeneity leads to lower overall abundance of each glycopeptide, and often, ion suppression is observed. One of the biggest issues facing glycoproteomics is the lack of reliable software for analysis, which necessitates manual validation and serves as a massive bottleneck in data processing. Here, I will discuss each of these challenges and some ways in which the field is attempting to address them, along with perspectives on how I believe we should move forward.

Global O-glycoproteome enrichment and analysis enabled by a combinatorial enzymatic workflow

A comprehensive analysis of site-specific protein O-glycosylation is hindered by the absence of a consensus O-glycosylation motif, the diversity of O-glycan structures, and the lack of a universal enzyme that cleaves attached O-glycans. Here, we report the development of a robust O-glycoproteomic workflow for analyzing complex biological samples by combining four different strategies: removal of N-glycans, complementary digestion using O-glycoprotease (IMPa) with/without another protease, glycopeptide enrichment, and mass spectrometry with fragmentation of glycopeptides using stepped collision energy. Using this workflow, we cataloged 474 O-glycopeptides on 189 O-glycosites derived from 79 O-glycoproteins from human plasma. These data revealed O-glycosylation of several abundant proteins that have not been previously reported. Because many of the proteins that contained unannotated O-glycosylation sites have been extensively studied, we wished to confirm glycosylation at these sites in a targeted fashion. Thus, we analyzed selected purified proteins (kininogen-1, fetuin-A, fibrinogen, apolipoprotein E, and plasminogen) in independent experiments and validated the previously unknown O-glycosites.

Prediction of glycopeptide fragment mass spectra by deep learning

Deep learning has achieved a notable success in mass spectrometry-based proteomics and is now emerging in glycoproteomics. While various deep learning models can predict fragment mass spectra of peptides with good accuracy, they cannot cope with the non-linear glycan structure in an intact glycopeptide. Herein, we present DeepGlyco, a deep learning-based approach for the prediction of fragment spectra of intact glycopeptides. Our model adopts tree-structured long-short term memory networks to process the glycan moiety and a graph neural network architecture to incorporate potential fragmentation pathways of a specific glycan structure. This feature is beneficial to model explainability and differentiation ability of glycan structural isomers. We further demonstrate that predicted spectral libraries can be used for data-independent acquisition glycoproteomics as a supplement for library completeness. We expect that this work will provide a valuable deep learning resource for glycoproteomics.

Genotype-dependent N-glycosylation and newly exposed O-glycosylation affect plasmin-induced cleavage of histidine-rich glycoprotein (HRG)

Histidine-rich glycoprotein (HRG) is an abundant plasma protein harboring at least three N-glycosylation sites. HRG integrates many biological processes, such as coagulation, antiangiogenic activity, and pathogen clearance. Importantly, HRG is known to exhibit five genetic variants with minor allele frequencies of more than 10%. Among them, Pro204Ser can induce a fourth N-glycosylation site (Asn202). Considerable efforts have been made to reveal the biological function of HRG, whereas data on HRG glycosylation are scarcer. To close this knowledge gap, we used C18-based LC-MS/MS to study the glycosylation characteristics of six HRG samples from different sources. We used endogenous HRG purified from human plasma and compared its glycosylation to that of the recombinant HRG produced in Chinese hamster ovary cells or human embryonic kidney 293 cells, targeting distinct genotypic isoforms. In endogenous plasma HRG, every N-glycosylation site was occupied predominantly with a sialylated diantennary complex-type glycan. In contrast, in the recombinant HRGs, all glycans showed different antennarities, sialylation, and core fucosylation, as well as the presence of oligomannose glycans, LacdiNAcs, and antennary fucosylation. Furthermore, we observed two previously unreported O-glycosylation sites in HRG on residues Thr273 and Thr274. These sites together showed more than 90% glycan occupancy in all HRG samples studied. To investigate the potential relevance of HRG glycosylation, we assessed the plasmin-induced cleavage of HRG under various conditions. These analyses revealed that the sialylation of the N- and O-glycans as well as the genotype-dependent N-glycosylation significantly influenced the kinetics and specificity of plasmin-induced cleavage of HRG.

Comparison of sialylated and fucosylated N-glycans attached to Asn 6 and Asn 41 with different roles in hyaluronan and proteoglycan link protein 1 (HAPLN1)

Hyaluronan and proteoglycan link protein 1 (HAPLN1) is an extracellular matrix protein stabilizing interactions between hyaluronan and proteoglycan. Although HAPLN1 is being investigated for various biological roles, its N-glycosylation is poorly understood. In this study, the structure of N-glycopeptides of trypsin-treated recombinant human HAPLN1 (rhHAPLN1) expressed from CHO cells were identified by nano-liquid chromatography-tandem mass spectrometry. A total of 66 N-glycopeptides were obtained, including 16 and 12 N-glycans at sites Asn 6 (located in the N-terminal region) and Asn 41 (located in the Ig-like domain, which interacts with proteoglycan), respectively. The quantities (%) of each N-glycan relative to the totals (100 %) at each site were calculated. Tri- and tetra-sialylation (to resist proteolysis and extend half-life) were more abundant at Asn 6, and di- (core- and terminal-) fucosylation (to increase binding affinity and stability) and sialyl-Lewis X/a epitope (a major ligand for E-selectin) were more abundant at Asn 41. These results indicate that N-glycans attached to Asn 6 (protecting HAPLN1) and Asn 41 (supporting molecular interactions) play different roles in HAPLN1. This is the first study of site-specific N-glycosylation in rhHAPLN1, which will be useful for understanding its molecular interactions in the extracellular matrix.

Mass Spectrometry Strategies for O-Glycoproteomics

Glycoproteomics has accelerated in recent decades owing to numerous innovations in the analytical workflow. In particular, new mass spectrometry strategies have contributed to inroads in O-glycoproteomics, a field that lags behind N-glycoproteomics due to several unique challenges associated with the complexity of O-glycosylation. This review will focus on progress in sample preparation, enrichment strategies, and MS/MS techniques for the identification and characterization of O-glycoproteins.

Can We Boost N-Glycopeptide Identification Confidence? Smart Collision Energy Choice Taking into Account Structure and Search Engine

High confidence and reproducibility are still challenges in bottom-up mass spectrometric N-glycopeptide identification. The collision energy used in the MS/MS measurements and the database search engine used to identify the species are perhaps the two most decisive factors. We investigated how the structural features of N-glycopeptides and the choice of the search engine influence the optimal collision energy, delivering the highest identification confidence. We carried out LC-MS/MS measurements using a series of collision energies on a large set of N-glycopeptides with both the glycan and peptide part varied and studied the behavior of Byonic, pGlyco, and GlycoQuest scores. We found that search engines show a range of behavior between peptide-centric and glycan-centric, which manifests itself already in the dependence of optimal collision energy on m/z. Using classical statistical and machine learning methods, we revealed that peptide hydrophobicity, glycan and peptide masses, and the number of mobile protons also have significant and search-engine-dependent influence, as opposed to a series of other parameters we probed. We envisioned an MS/MS workflow making a smart collision energy choice based on online available features such as the hydrophobicity (described by retention time) and glycan mass (potentially available from a scout MS/MS). Our assessment suggests that this workflow can lead to a significant gain (up to 100%) in the identification confidence, particularly for low-scoring hits close to the filtering limit, which has the potential to enhance reproducibility of N-glycopeptide analyses. Data are available via MassIVE (MSV000093110).

Analysis of the Healthy Platelet Proteome Identifies a New Form of Domain-Specific O-Fucosylation

Platelet activation induces the secretion of proteins that promote platelet aggregation and inflammation. However, detailed analysis of the released platelet proteome is hampered by platelets' tendency to preactivate during their isolation and a lack of sensitive protocols for low abundance releasate analysis. Here, we detail the most sensitive analysis to date of the platelet releasate proteome with the detection of >1300 proteins. Unbiased scanning for posttranslational modifications within releasate proteins highlighted O-glycosylation as being a major component. For the first time, we detected O-fucosylation on previously uncharacterized sites including multimerin-1 (MMRN1), a major alpha granule protein that supports platelet adhesion to collagen and is a carrier for platelet factor V. The N-terminal elastin microfibril interface (EMI) domain of MMRN1, a key site for protein-protein interaction, was O-fucosylated at a conserved threonine within a new domain context. Our data suggest that either protein O-fucosyltransferase 1, or a novel protein O-fucosyltransferase, may be responsible for this modification. Mutating this O-fucose site on the EMI domain led to a >50% reduction of MMRN1 secretion, supporting a key role of EMI O-fucosylation in MMRN1 secretion. By comparing releasates from resting and thrombin-treated platelets, 202 proteins were found to be significantly released after high-dose thrombin stimulation. Complementary quantification of the platelet lysates identified >3800 proteins, which confirmed the platelet origin of releasate proteins by anticorrelation analysis. Low-dose thrombin treatment yielded a smaller subset of significantly regulated proteins with fewer secretory pathway enzymes. The extensive platelet proteome resource provided here (larancelab.com/platelet-proteome) allows identification of novel regulatory mechanisms for drug targeting to address platelet dysfunction and thrombosis.

RAMZIS: a bioinformatic toolkit for rigorous assessment of the alterations to glycoprotein composition that occur during biological processes

Motivation

Glycosylation elaborates the structures and functions of glycoproteins; glycoproteins are common post-translationally modified proteins and are heterogeneous and non-deterministically synthesized as an evolutionarily driven mechanism that elaborates the functions of glycosylated gene products. Glycoproteins, accounting for approximately half of all proteins, require specialized proteomics data analysis methods due to micro- and macro-heterogeneities as a given glycosite can be divided into several glycosylated forms, each of which must be quantified. Sampling of heterogeneous glycopeptides is limited by mass spectrometer speed and sensitivity, resulting in missing values. In conjunction with the low sample size inherent to glycoproteomics, a specialized toolset is needed to determine if observed changes in glycopeptide abundances are biologically significant or due to data quality limitations.

Results

We developed an R package, Relative Assessment of m/z Identifications by Similarity (RAMZIS), that uses similarity metrics to guide researchers to a more rigorous interpretation of glycoproteomics data. RAMZIS uses a permutation test to generate contextual similarity, which assesses the quality of mass spectral data and outputs a graphical demonstration of the likelihood of finding biologically significant differences in glycosylation abundance datasets. Investigators can assess dataset quality, holistically differentiate glycosites, and identify which glycopeptides are responsible for glycosylation pattern change. RAMZIS is validated by theoretical cases and a proof-of-concept application. RAMZIS enables comparison between datasets too stochastic, small, or sparse for interpolation while acknowledging these issues in its assessment. Using this tool, researchers will be able to rigorously define the role of glycosylation and the changes that occur during biological processes.

Availability and implementation

https://github.com/WillHackett22/RAMZIS.

Direct and Detailed Site-Specific Glycopeptide Characterization by Higher-Energy Electron-Activated Dissociation Tandem Mass Spectrometry

Glycosylation is widely recognized as the most complex post-translational modification due to the widespread presence of macro- and microheterogeneities, wherein its biological consequence is closely related to both the glycosylation sites and the glycan fine structures. Yet, efficient site-specific detailed glycan characterization remains a significant analytical challenge. Here, utilizing an Orbitrap-Omnitrap platform, higher-energy electron-activated dissociation (heExD) tandem mass spectrometry (MS/MS) revealed extraordinary efficacy for the structural characterization of intact glycopeptides. HeExD produced extensive fragmentation within both the glycan and the peptide, including A-/B-/C-/Y-/Z-/X-ions from the glycan motif and a-/b-/c-/x-/y-/z-type peptide fragments (with or without the glycan). The intensity of cross-ring cleavage and backbone fragments retaining the intact glycan was highly dependent on the electron energy. Among the four electron energy levels investigated, electronic excitation dissociation (EED) provided the most comprehensive structural information, yielding a complete series of glycosidic fragments for accurate glycan topology determination, a wealth of cross-ring fragments for linkage definition, and the most extensive peptide backbone fragments for accurate peptide sequencing and glycosylation site localization. The glycan fragments observed in the EED spectrum correlated well with the fragmentation patterns observed in EED MS/MS of the released glycans. The advantages of EED over higher-energy collisional dissociation (HCD), stepped collision energy HCD (sceHCD), and electron-transfer/higher-energy collisional dissociation (EThcD) were demonstrated for the characterization of a glycopeptide bearing a biantennary disialylated glycan. EED can produce a complete peptide backbone and glycan sequence coverage even for doubly protonated precursors. The exceptional performance of heExD MS/MS, particularly EED MS/MS, in site-specific detailed glycan characterization on an Orbitrap-Omnitrap hybrid instrument presents a novel option for in-depth glycosylation analysis.

SiaNAl can be efficiently incorporated in glycoproteins of human mesenchymal stromal cells by metabolic glycoengineering

Metabolic glycoengineering involves the stimulation of cells with functionalized monosaccharides. Glucosamine, galactosamine, and mannosamine derivatives are commercially available, but their application may lead to undirected (i.e., chemical) incorporation into proteins. However, sialic acids are attached to the ends of complex sugar chains of glycoproteins, which might be beneficial for cell surface modification via click chemistry. Thus, we studied the incorporation of chemically synthesized unnatural alkyne modified sialic acid (SiaNAl) into glycoproteins of human telomerase-immortalized mesenchymal stromal cells (hMSC-TERT) and we show that SiaNAl can be efficiently incorporated in glycoproteins involved in signal transduction and cell junction.

O-Glycoproteomics Sample Preparation and Analysis Using NanoHPLC and Tandem MS

Glycosylation refers to the biological processes that covalently attach carbohydrates to the peptide backbone after the synthesis of proteins. As one of the most common post-translational modifications (PTMs), glycosylation can greatly affect proteins' features and functions. Moreover, aberrant glycosylation has been linked to various diseases. There are two major types of glycosylation, known as N-linked and O-linked glycosylation. Here, we focus on O-linked glycosylation and thoroughly describe a bottom-up strategy to perform O-linked glycoproteomics studies. The experimental section involves enzymatic digestions using trypsin and O-glycoprotease at 37 °C. The prepared samples containing O-glycopeptides are analyzed using nanoHPLC coupled with tandem mass spectrometry (MS) for accurate identification and quantification.

GlycoTCFM: Glycoproteomics Based on Two Complementary Fragmentation Methods Reveals Distinctive O-Glycosylation in Human Sperm and Seminal Plasma

Human semen, consisting of spermatozoa (sperm) and seminal plasma, represents a special clinical sample type in human body fluid. Protein glycosylation in sperm and seminal plasma plays key roles in spermatogenesis, maturation, capacitation, sperm-egg recognition, motility of sperm, and fertilization. In this study, we profiled the most comprehensive O-glycoproteome map of human sperm and seminal plasma using our recently presented Glycoproteomics based on Two Complementary Fragmentation Methods (GlycoTCFM). We showed that sperm and seminal plasma contain many novel and distinctive O-glycoproteins, which are mostly located in the extracellular region (seminal plasma) and sperm membrane, enriched in the biological processes of cell adhesion and angiogenesis, and mainly involved in multiple biological functions including extracellular matrix structural constituents and binding. Based on GlycoTCFM, we created a comprehensive human sperm and seminal plasma O-glycoprotein database that contains 371 intact O-glycopeptides and 202 O-glycosites from 68 O-glycoproteins. Interestingly, 105 manually confirmed O-glycosites from 25 O-glycoproteins were reported for the first time, and they were mainly modified by core 1 O-glycans. We also found that three highly abundant, highly complex, and highly O-glycosylated proteins (semenogelin-1, semenogelin-2, and equatorin) may play important roles in sperm or seminal plasma composition and function. These data deepen our knowledge about O-glycosylation in sperm and seminal plasma and lay the foundation for the functional study of O-glycoproteins in male infertility.

Evidence of H/D Exchange within Metal-Adducted Carbohydrates after Ion/Ion-Dissociation Reactions

Tandem mass spectrometry (MS/MS) using fragmentation has become one of the most effective methods for gaining sequence and structural information on biomolecules. Ion/ion reactions are competitive reactions, where either proton transfer (PT) or electron transfer (ET) can occur from interactions between multiply charged cations and singly charged anions. Utilizing ion/ion reactions with fluoranthene has offered a unique method of fragment formation for the structural elucidation of biomolecules. Fluoranthene is considered an ideal anion reagent because it selectively causes electron-transfer dissociation (ETD) and minimizes PT when interacting with peptides. However, limited investigations have sought to understand how fluoranthene─the primary, commercially available anion reagent─interacts with other biomolecules. Here, we apply deuterium labeling to investigate ion/ion reaction mechanisms between fluoranthene and divalent, metal-adducted carbohydrates (Ca2+, Mg2+, Co2+, and Ni2+). Deuterium labeling of carbohydrates allowed us to observe evidence of hydrogen/deuterium exchange (HDX) occurring after ion/ion dissociation reactions. The extent of deuterium loss is dependent on several factors, including the physical properties of the metal ion and the fragment structure. Based on the deuterium labeling data, we have proposed ETD, PTD, and intermolecular PT─also described as HDX─mechanisms. This research provides a fundamental perspective of ion/ion and ion/molecule reaction mechanisms and illustrates properties that impact ion/ion and ion/molecule reactions for carbohydrates. Together, this could improve the capability to distinguish complex and heterogeneous biomolecules, such as carbohydrates.

Analysis of complex proteoglycans using serial proteolysis and EThcD provides deep N- and O-glycoproteomic coverage

Proteoglycans are a small but diverse family of proteins that play a wide variety of roles at the cell surface and in the extracellular matrix. In addition to their glycosaminoglycan (GAG) chains, they are N- and O-glycosylated. All of these types of glycosylation are crucial to their function but present a considerable analytical challenge. We describe the combination of serial proteolysis followed by the application of higher-energy collisional dissociation (HCD) and electron transfer/higher-energy collisional dissociation (EThcD) to optimize protein sequence coverage and glycopeptide identification from proteoglycans. In many cases, the use of HCD alone allows the identification of more glycopeptides. However, the localization of glycoforms on multiply glycosylated peptides has remained elusive. We demonstrate the use of EThcD for the confident assignment of glycan compositions on multiply glycosylated peptides. Dense glycosylation on proteoglycans is key to their biological function; thus, developing tools to identify and quantify doubly glycosylated peptides is of interest. Additionally, glycoproteomics searches identify glycopeptides in otherwise poorly covered regions of proteoglycans. The development of these and other analytical tools may permit glycoproteomic similarity comparisons in biological samples.

Characterization of site-specific N-glycosylation signatures of isolated uromodulin from human urine

Uromodulin (Umod, Tamm-Horsfall protein) is the most abundant urinary N-glycoprotein produced exclusively by the kidney. It can form filaments to antagonize the adhesion of uropathogens. However, the site-specific N-glycosylation signatures of Umod in healthy individuals and patients with IgA nephropathy (IgAN) remain poorly understood due to the lack of suitable isolation and analytical methods. In this study, we first presented a simple and fast method based on diatomaceous earth adsorption to isolate Umod. These isolated glycoproteins were digested by trypsin and/or Glu-C. Intact N-glycopeptides with or without HILIC enrichment were analyzed using our developed EThcD-sceHCD-MS/MS. Based on the optimized workflow, we identified a total of 780 unique intact N-glycopeptides (7 N-glycosites and 152 N-glycan compositions) from healthy individuals. As anticipated, these glycosites exhibited glycoform heterogeneity. Almost all N-glycosites were modified completely by the complex type, except for one N-glycosite (N275), which was nearly entirely occupied by the high-mannose type for mediating Umod's antiadhesive activity. Then, we compared the N-glycosylation of Umod between healthy controls (n = 9) and IgAN patients (n = 9). The N-glycosylation of Umod in IgAN patients will drastically decrease and be lost. Finally, we profiled the most comprehensive site-specific N-glycosylation map of Umod and revealed its alterations in IgAN patients. Our method provides a high-throughput workflow for characterizing the N-glycosylation of Umod, which can aid in understanding its roles in physiology and pathology, as well as serving as a potential diagnostic tool for evolution of renal tubular function.

CD24 targeting with NK-CAR immunotherapy in testis, prostate, renal and (luminal-type) bladder cancer and identification of direct CD24 interaction partners

Alternative therapeutic options targeting urologic malignancies, such as germ cell tumours, as well as urothelial, renal and prostate carcinomas, are still urgently needed. The membrane protein CD24 represents a promising immunotherapeutical approach. The present study aimed to decipher the molecular function of CD24 in vitro and evaluate the cytotoxic capacity of a third-generation natural killer (NK) cell chimeric antigen receptor (CAR) against CD24 in urologic tumour cell lines. Up to 20 urologic tumour cell lines and several non-malignant control cells were included. XTT viability assays and annexin V/propidium iodide flow cytometry analyses were performed to measure cell viability and apoptosis rates, respectively. Co-immunoprecipitation followed by mass spectrometry analyses identified direct interaction partners of CD24. Luciferase reporter assays were used to functionally validate transactivation of CD24 expression by SOX2. N- and O-glycosylation of CD24 were evaluated by enzymatic digestion and mass spectrometry. The study demonstrates that SOX2 transactivates CD24 expression in embryonal carcinoma cells. In cells of different urological origins, CD24 interacted with proteins involved in cell adhesion, ATP binding, phosphoprotein binding and post-translational modifications, such as histone acetylation and ubiquitination. Treatment of urological tumour cells with NK-CD24-CAR cells resulted in a decreased cell viability and apoptosis induction specifically in CD24+ tumour cells. Limitations of the study include the in vitro setting, which still has to be confirmed in vivo. In conclusion, we show that CD24 is a promising novel target for immune therapeutic approaches targeting urologic malignancies.

Large-Scale and Site-Specific Mapping of the Murine Brain O-Glycoproteome with IMPa

Altered protein glycosylation is typically associated with cognitive defects and other phenotypes, but there is a lack of knowledge about the brain glycoproteome. Here, we used the newly available O-glycoprotease IMPa from Pseudomonas aeruginosa for comprehensive O-glycoproteomic analyses of the mouse brain. In this approach, total tryptic glycopeptides were prepared, extracted, purified, and conjugated to a solid support before an enzymatic cleavage by IMPa. O-glycopeptides were analyzed by electron-transfer/higher-energy collision dissociation (EThcD), which permits site-specific and global analysis of all types of O-glycans. We developed two complementary approaches for the analysis of the total O-glycoproteome using HEK293 cells and derivatives. The results demonstrated that IMPa and EThcD facilitate the confident localization of O-glycans on glycopeptides. We then applied these approaches to characterize the O-glycoproteome of the mouse brain, which revealed the high frequency of various sialylated O-glycans along with the unusual presence of the Tn antigen. Unexpectedly, the results demonstrated that glycoproteins in the brain O-glycoproteome only partly overlap with those reported for the brain N-glycoproteome. These approaches will aid in identifying the novel O-glycoproteomes of different cells and tissues and foster clinical and translational insights into the functions of protein O-glycosylation in the brain and other organs.

An identification method to distinguish monomeric sugar isomers on glycopeptides

A one-step protocol for the automated flow synthesis of protected glycosylated amino acids is described using pumps with open-source controls in overall yields of 21-50%. The resulting glycosylated amino acids could be used directly in solid-phase peptide synthesis (SPPS) protocols to quickly produce glycopeptide standards. Access to a variety of stereoisomers of the sugar enabled the development of an LC-MS/MS protocol that can distinguish between peptides modified with carbohydrates having the same exact mass. This method could definitively identify fucose in an O-glycosylation site on the transmembrane protein, Notch1.

Click-iG: Simultaneous Enrichment and Profiling of Intact N-linked, O-GalNAc, and O-GlcNAcylated Glycopeptides

Proteins are ubiquitously modified with glycans of varied chemical structures through distinct glycosidic linkages, making the landscape of protein glycosylation challenging to map. Profiling of intact glycopeptides with mass spectrometry (MS) has recently emerged as a powerful tool for revealing matched information of the glycosylation sites and attached glycans (i.e., intact glycosites), but is largely limited to individual glycosylation types. Herein, we describe Click-iG, which integrates metabolic labeling of glycans with clickable unnatural sugars, an optimized MS method, and a tailored version of pGlyco3 software to enable simultaneous enrichment and profiling of three types of intact glycopeptides: N-linked, mucin-type O-linked, and O-GlcNAcylated glycopeptides. We demonstrate the utility of Click-iG by the identification of thousands of intact glycosites in cell lines and living mice. From the mouse lung, heart, and spleen, a total of 2053 intact N-glycosites, 262 intact O-GalNAc glycosites, and 1947 O-GlcNAcylation sites were identified. Click-iG-enabled comprehensive coverage of the protein glycosylation landscape lays the foundation for interrogating crosstalk between different glycosylation pathways.

Optimum collision energies for proteomics: The impact of ion mobility separation

Ion mobility spectrometry (IMS) is a widespread separation technique used in various research fields. It can be coupled to liquid chromatography-mass spectrometry (LC-MS/MS) methods providing an additional separation dimension. During IMS, ions are subjected to multiple collisions with buffer gas, which may cause significant ion heating. The present project addresses this phenomenon from the bottom-up proteomics point of view. We performed LC-MS/MS measurements on a cyclic ion mobility mass spectrometer with varied collision energy (CE) settings both with and without IMS. We investigated the CE dependence of identification score, using Byonic search engine, for more than 1000 tryptic peptides from HeLa digest standard. We determined the optimal CE values-giving the highest identification score-for both setups (i.e., with and without IMS). Results show that lower CE is advantageous when IMS separation is applied, by 6.3 V on average. This value belongs to the one-cycle separation configuration, and multiple cycles may supposedly have even larger impact. The effect of IMS is also reflected in the trends of optimal CE values versus m/z functions. The parameters suggested by the manufacturer were found to be almost optimal for the setup without IMS; on the other hand, they are obviously too high with IMS. Practical consideration on setting up a mass spectrometric platform hyphenated to IMS is also presented. Furthermore, the two CID (collision induced dissociation) fragmentation cells of the instrument-located before and after the IMS cell-were also compared, and we found that CE adjustment is needed when the trap cell is used for activation instead of the transfer cell. Data have been deposited in the MassIVE repository (MSV000090944).

Mass spectrometry methods for analysis of extracellular matrix components in neurological diseases

The brain extracellular matrix (ECM) is a highly glycosylated environment and plays important roles in many processes including cell communication, growth factor binding, and scaffolding. The formation of structures such as perineuronal nets (PNNs) is critical in neuroprotection and neural plasticity, and the formation of molecular networks is dependent in part on glycans. The ECM is also implicated in the neuropathophysiology of disorders such as Alzheimer's disease (AD), Parkinson's disease (PD), and Schizophrenia (SZ). As such, it is of interest to understand both the proteomic and glycomic makeup of healthy and diseased brain ECM. Further, there is a growing need for site-specific glycoproteomic information. Over the past decade, sample preparation, mass spectrometry, and bioinformatic methods have been developed and refined to provide comprehensive information about the glycoproteome. Core ECM molecules including versican, hyaluronan and proteoglycan link proteins, and tenascin are dysregulated in AD, PD, and SZ. Glycomic changes such as differential sialylation, sulfation, and branching are also associated with neurodegeneration. A more thorough understanding of the ECM and its proteomic, glycomic, and glycoproteomic changes in brain diseases may provide pathways to new therapeutic options.

Collision energies: Optimization strategies for bottom-up proteomics

Mass-spectrometry coupled to liquid chromatography is an indispensable tool in the field of proteomics. In the last decades, more and more complex and diverse biochemical and biomedical questions have arisen. Problems to be solved involve protein identification, quantitative analysis, screening of low abundance modifications, handling matrix effect, and concentrations differing by orders of magnitude. This led the development of more tailored protocols and problem centered proteomics workflows, including advanced choice of experimental parameters. In the most widespread bottom-up approach, the choice of collision energy in tandem mass spectrometric experiments has outstanding role. This review presents the collision energy optimization strategies in the field of proteomics which can help fully exploit the potential of MS based proteomics techniques. A systematic collection of use case studies is then presented to serve as a starting point for related further scientific work. Finally, this article discusses the issue of comparing results from different studies or obtained on different instruments, and it gives some hints on methodology transfer between laboratories based on measurement of reference species.

Ultraviolet Photodissociation Permits Comprehensive Characterization of O-Glycopeptides Cleaved with O-Glycoprotease IMPa

Complete O-glycosite characterization, including identification of the peptides, localization of the glycosites, and mapping of the glycans, has been a persistent challenge in O-glycoproteomics owing to the technical challenges surrounding O-glycan analysis. Multi-glycosylated peptides pose an even greater challenge owing to their potential heterogeneity. Ultraviolet photodissociation (UVPD) can localize multiple post-translational modifications and is well-suited for the characterization of glycans. Three glycoproteins were assessed based on a strategy combining the use of O-glycoprotease IMPa and HCD-triggered UVPD for the complete characterization of O-glycopeptides. This approach localized multiple adjacent or proximal O-glycosites on individual glycopeptides and identified a previously unknown glycosite on etanercept at S218. Nine different glycoforms were characterized as a multi-glycosylated peptide from etanercept. The performance of UVPD was compared to that of HCD and EThcD for the localization of O-glycosites and the characterization of the constituent peptides and glycans.

Mutational screens highlight glycosylation as a modulator of colony-stimulating factor 3 receptor (CSF3R) activity

The colony-stimulating factor 3 receptor (CSF3R) controls the growth of neutrophils, the most abundant type of white blood cell. In healthy neutrophils, signaling is dependent on CSF3R binding to its ligand, CSF3. A single amino acid mutation in CSF3R, T618I, instead allows for constitutive, ligand-independent cell growth and leads to a rare type of cancer called chronic neutrophilic leukemia. However, the disease mechanism is not well understood. Here, we investigated why this threonine to isoleucine substitution is the predominant mutation in chronic neutrophilic leukemia and how it leads to uncontrolled neutrophil growth. Using protein domain mapping, we demonstrated that the single CSF3R domain containing residue 618 is sufficient for ligand-independent activity. We then applied an unbiased mutational screening strategy focused on this domain and found that activating mutations are enriched at sites normally occupied by asparagine, threonine, and serine residues-the three amino acids which are commonly glycosylated. We confirmed glycosylation at multiple CSF3R residues by mass spectrometry, including the presence of GalNAc and Gal-GalNAc glycans at WT threonine 618. Using the same approach applied to other cell surface receptors, we identified an activating mutation, S489F, in the interleukin-31 receptor alpha chain. Combined, these results suggest a role for glycosylated hotspot residues in regulating receptor signaling, mutation of which can lead to ligand-independent, uncontrolled activity and human disease.

RAMZIS: a bioinformatic toolkit for rigorous assessment of the alterations to glycoprotein structure that occur during biological processes

Motivation

Glycosylation elaborates the structures and functions of glycoproteins; glycoproteins are common post-translationally modified proteins and are heterogeneous and non-deterministically syn-thesized as an evolutionarily driven mechanism that elaborates the functions of glycosylated gene products. While glycoproteins account for approximately half of all proteins, their macro- and micro-heterogeneity requires specialized proteomics data analysis methods as a given glycosite can be divided into several glycosylated forms, each of which must be quantified. Sampling of heterogeneous glycopeptides is limited by mass spectrometer speed and sensitivity, resulting in missing values. In conjunction with the low sample size inherent to glycoproteomics, this necessitated specialized statistical metrics to identify if observed changes in glycopeptide abundances are biologically significant or due to data quality limitations.

Results

We developed an R package, Relative Assessment of m/z Identifications by Similarity (RAMZIS), that uses similarity metrics to guide biomedical researchers to a more rigorous interpretation of glycoproteomics data. RAMZIS uses contextual similarity to assess the quality of mass spectral data and generates graphical output that demonstrates the likelihood of finding biologically significant differences in glycosylation abundance dataset. Investigators can assess dataset quality, holistically differentiate glycosites, and identify which glycopeptides are responsible for glycosylation pattern expression change. Herein RAMZIS approach is validated by theoretical cases and by a proof-of-concept application. RAMZIS enables comparison between datasets too stochastic, small, or sparse for interpolation while acknowledging these issues in its assessment. Using our tool, researchers will be able to rigor-ously define the role of glycosylation and the changes that occur during biological processes.

Identification, characterization, and engineering of glycosylation in thrombolyticsa

Cardiovascular diseases, such as myocardial infarction, ischemic stroke, and pulmonary embolism, are the most common causes of disability and death worldwide. Blood clot hydrolysis by thrombolytic enzymes and thrombectomy are key clinical interventions. The most widely used thrombolytic enzyme is alteplase, which has been used in clinical practice since 1986. Another clinically used thrombolytic protein is tenecteplase, which has modified epitopes and engineered glycosylation sites, suggesting that carbohydrate modification in thrombolytic enzymes is a viable strategy for their improvement. This comprehensive review summarizes current knowledge on computational and experimental identification of glycosylation sites and glycan identity, together with methods used for their reengineering. Practical examples from previous studies focus on modification of glycosylations in thrombolytics, e.g., alteplase, tenecteplase, reteplase, urokinase, saruplase, and desmoteplase. Collected clinical data on these glycoproteins demonstrate the great potential of this engineering strategy. Outstanding combinatorics originating from multiple glycosylation sites and the vast variety of covalently attached glycan species can be addressed by directed evolution or rational design. Directed evolution pipelines would benefit from more efficient cell-free expression and high-throughput screening assays, while rational design must employ structure prediction by machine learning and in silico characterization by supercomputing. Perspectives on challenges and opportunities for improvement of thrombolytic enzymes by engineering and evolution of protein glycosylation are provided.

Development of an Integrated Platform for the Simultaneous Enrichment and Characterization of N- and O-Linked Intact Glycopeptides

Both N-linked glycosylation and O-linked glycosylation play essential roles in the onset and progression of various diseases including cancer, and N-/O-linked site-specific glycans have been proven to be promising biomarkers for the discrimination of cancer. However, the micro-heterogeneity and low abundance nature of N-/O-linked glycosylation, as well as the time-consuming and tedious procedures for the enrichment of O-linked intact glycopeptides, pose great challenges for their efficient and accurate characterization. In this study, we developed an integrated platform for the simultaneous enrichment and characterization of N- and O-linked intact glycopeptides from the same serum sample. By fine-tuning the experimental conditions, we demonstrated that this platform allowed the selective separation of N- and O-linked intact glycopeptides into two fractions, with 85.1% O-linked intact glycopeptides presented in the first fraction and 93.4% N-linked intact glycopeptides presented in the second fraction. Determined with high reproducibility, this platform was further applied to the differential analysis of serum samples of gastric cancer and health control, which revealed 17 and 181 significantly changed O-linked and N-linked intact glycopeptides. Interestingly, five glycoproteins containing both significant regulation of N- and O-glycosylation were observed, hinting potential co-regulation of different types of glycosylation during tumor progress. In summary, this integrated platform opened a potentially useful avenue for the global analysis of protein glycosylation and can serve as a useful tool for the characterization of N-/O-linked intact glycopeptides at the proteomics scale.

N-glycoproteomics of brain synapses and synaptic vesicles

At mammalian neuronal synapses, synaptic vesicle (SV) glycoproteins are essential for robust neurotransmission. Asparagine (N)-linked glycosylation is required for delivery of the major SV glycoproteins synaptophysin and SV2A to SVs. Despite this key role for N-glycosylation, the molecular compositions of SV N-glycans are largely unknown. In this study, we combined organelle isolation techniques and high-resolution mass spectrometry to characterize N-glycosylation at synapses and SVs from mouse brain. Detecting over 2,500 unique glycopeptides, we found that SVs harbor a distinct population of oligomannose and highly fucosylated N-glycans. Using complementary fluorescence methods, we identify at least one highly fucosylated N-glycan enriched in SVs compared with synaptosomes. High fucosylation was characteristic of SV proteins, plasma membrane proteins, and cell adhesion molecules with key roles in synaptic function and development. Our results define the N-glycoproteome of a specialized neuronal organelle and inform timely questions in the glycobiology of synaptic pruning and neuroinflammation.

Roles of glycosylation at the cancer cell surface: opportunities for large scale glycoproteomics

Cell surface glycosylation has a variety of functions, and its dysregulation in cancer contributes to impaired signaling, metastasis and the evasion of the immune responses. Recently, a number of glycosyltransferases that lead to altered glycosylation have been linked to reduced anti-tumor immune responses: B3GNT3, which is implicated in PD-L1 glycosylation in triple negative breast cancer, FUT8, through fucosylation of B7H3, and B3GNT2, which confers cancer resistance to T cell cytotoxicity. Given the increased appreciation of the relevance of protein glycosylation, there is a critical need for the development of methods that allow for an unbiased interrogation of cell surface glycosylation status. Here we provide an overview of the broad changes in glycosylation at the surface of cancer cell and describe selected examples of receptors with aberrant glycosylation leading to functional changes, with emphasis on immune checkpoint inhibitors, growth-promoting and growth-arresting receptors. Finally, we posit that the field of glycoproteomics has matured to an extent where large-scale profiling of intact glycopeptides from the cell surface is feasible and is poised for discovery of new actionable targets against cancer.

Conjugation site characterization of antibody-drug conjugates using electron-transfer/higher-energy collision dissociation (EThcD)

Antibody-drug conjugates (ADCs) are formed by binding of cytotoxic drugs to monoclonal antibodies (mAbs) through chemical linkers. A comprehensive evaluation of the critical quality attributes (CQAs) of ADCs is vital for drug development but remains challenging owing to ADC structural heterogeneity than mAbs. Drug conjugation sites can considerably affect ADC properties, such as stability and pharmacokinetics, however, few studies have focused on method development in this area owing to technical challenges. Hybrid electron-transfer/higher-energy collision dissociation (EThcD) produces more fragment ions than conventional higher-energy collision dissociation (HCD) fragmentation, which aids in identifying and localizing post-translational modifications. Herein, we systematically employ EThcD to assess the fragmentation mode impact on conjugation site characterization for randomly conjugated and site-specific ADCs. EThcD generates more fragment ions in tandem mass spectrometry (MS/MS) spectra compared with HCD. Additional ions aid in pinpointing the correct conjugation sites that bear complex linker payload structures. Our study may contribute to the quality control of various preclinical and clinical ADCs.

Critical considerations in N-glycoproteomics

N-Glycoproteomics, the system-wide study of glycans asparagine-linked to protein carriers, holds a unique and still largely untapped potential to provide deep insights into the complexity and dynamics of the heterogeneous N-glycoproteome. Despite the advent of innovative analytical and informatics tools aiding the analysis, N-glycoproteomics remains challenging and consequently largely restricted to specialised laboratories. Aiming to stimulate discussions of method harmonisation, data standardisation and reporting guidelines to make N-glycoproteomics more reproducible and accessible to the community, we here discuss critical considerations related to the design and execution of N-glycoproteomics experiments and highlight good practices in N-glycopeptide data collection, analysis, interpretation and sharing. Giving the rapid maturation and, expectedly, a wide-spread implementation of N-glycoproteomics capabilities across the community in future years, this piece aims to point out common pitfalls, to encourage good data sharing and documentation practices, and to highlight practical solutions and strategies to enhance the insight into the N-glycoproteome.

Peptidomics

Peptides are biopolymers, typically consisting of 2-50 amino acids. They are biologically produced by the cellular ribosomal machinery or by non-ribosomal enzymes and, sometimes, other dedicated ligases. Peptides are arranged as linear chains or cycles, and include post-translational modifications, unusual amino acids and stabilizing motifs. Their structure and molecular size render them a unique chemical space, between small molecules and larger proteins. Peptides have important physiological functions as intrinsic signalling molecules, such as neuropeptides and peptide hormones, for cellular or interspecies communication, as toxins to catch prey or as defence molecules to fend off enemies and microorganisms. Clinically, they are gaining popularity as biomarkers or innovative therapeutics; to date there are more than 60 peptide drugs approved and more than 150 in clinical development. The emerging field of peptidomics comprises the comprehensive qualitative and quantitative analysis of the suite of peptides in a biological sample (endogenously produced, or exogenously administered as drugs). Peptidomics employs techniques of genomics, modern proteomics, state-of-the-art analytical chemistry and innovative computational biology, with a specialized set of tools. The complex biological matrices and often low abundance of analytes typically examined in peptidomics experiments require optimized sample preparation and isolation, including in silico analysis. This Primer covers the combination of techniques and workflows needed for peptide discovery and characterization and provides an overview of various biological and clinical applications of peptidomics.

O-Linked Sialoglycans Modulate the Proteolysis of SARS-CoV-2 Spike and Likely Contribute to the Mutational Trajectory in Variants of Concern

The emergence of a polybasic cleavage motif for the protease furin in SARS-CoV-2 spike has been established as a major factor for human viral transmission. The region N-terminal to that motif is extensively mutated in variants of concern (VOCs). Besides furin, spikes from these variants appear to rely on other proteases for maturation, including TMPRSS2. Glycans near the cleavage site have raised questions about proteolytic processing and the consequences of variant-borne mutations. Here, we identify that sialic acid-containing O-linked glycans on Thr678 of SARS-CoV-2 spike influence furin and TMPRSS2 cleavage and posit O-linked glycosylation as a likely driving force for the emergence of VOC mutations. We provide direct evidence that the glycosyltransferase GalNAc-T1 primes glycosylation at Thr678 in the living cell, an event that is suppressed by mutations in the VOCs Alpha, Delta, and Omicron. We found that the sole incorporation of N-acetylgalactosamine did not impact furin activity in synthetic O-glycopeptides, but the presence of sialic acid reduced the furin rate by up to 65%. Similarly, O-glycosylation with a sialylated trisaccharide had a negative impact on TMPRSS2 cleavage. With a chemistry-centered approach, we substantiate O-glycosylation as a major determinant of spike maturation and propose disruption of O-glycosylation as a substantial driving force for VOC evolution.

Protein glycosylation in urine as a biomarker of diseases

Human body fluids have become an indispensable resource for clinical research, diagnosis and prognosis. Urine is widely used to discover disease-specific glycoprotein biomarkers because of its recurrently non-invasive collection and disease-indicating properties. While urine is an unstable fluid in that its composition changes with ingested nutrients and further as it is excreted through micturition, urinary proteins are more stable and their abnormal glycosylation is associated with diseases. It is known that aberrant glycosylation can define tumor malignancy and indicate disease initiation and progression. However, a thorough and translational survey of urinary glycosylation in diseases has not been performed. In this article, we evaluate the clinical applications of urine, introduce methods for urine glycosylation analysis, and discuss urine glycoprotein biomarkers. We emphasize the importance of mining urinary glycoproteins and searching for disease-specific glycosylation in various diseases (including cancer, neurodegenerative diseases, diabetes, and viral infections). With advances in mass spectrometry-based glycomics/glycoproteomics/glycopeptidomics, characterization of disease-specific glycosylation will optimistically lead to the discovery of disease-related urinary biomarkers with better sensitivity and specificity in the near future.

Recent advances in mass spectrometry analysis of neuropeptides

Due to their involvement in numerous biochemical pathways, neuropeptides have been the focus of many recent research studies. Unfortunately, classic analytical methods, such as western blots and enzyme-linked immunosorbent assays, are extremely limited in terms of global investigations, leading researchers to search for more advanced techniques capable of probing the entire neuropeptidome of an organism. With recent technological advances, mass spectrometry (MS) has provided methodology to gain global knowledge of a neuropeptidome on a spatial, temporal, and quantitative level. This review will cover key considerations for the analysis of neuropeptides by MS, including sample preparation strategies, instrumental advances for identification, structural characterization, and imaging; insightful functional studies; and newly developed absolute and relative quantitation strategies. While many discoveries have been made with MS, the methodology is still in its infancy. Many of the current challenges and areas that need development will also be highlighted in this review.

Methods for quantification of glycopeptides by liquid separation and mass spectrometry

Recent advances in analytical techniques provide the opportunity to quantify even low-abundance glycopeptides derived from complex biological mixtures, allowing for the identification of glycosylation differences between healthy samples and those derived from disease states. Herein, we discuss the sample preparation procedures and the mass spectrometry (MS) strategies that have facilitated glycopeptide quantification, as well as the standards used for glycopeptide quantification. For sample preparation, various glycopeptide enrichment methods are summarized including the columns used for glycopeptide separation in liquid chromatography separation. For MS analysis strategies, MS1 level-based quantification and MS2 level-based quantification are described, either with or without labeling, where we have covered isotope labeling, TMT/iTRAQ labeling, data dependent acquisition, data independent acquisition, multiple reaction monitoring, and parallel reaction monitoring. The strengths and weaknesses of these methods are compared, particularly those associated with the figures of merit that are important for clinical biomarker studies and the pathological and functional studies of glycoproteins in various diseases. Possible future developments for glycopeptide quantification are discussed.