Status Report on the High-Throughput Characterization of Complex Intact O-Glycopeptide Mixtures

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.

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.

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.

Deciphering O-glycoprotease substrate preferences with O-Pair Search

O-Glycoproteases are an emerging class of enzymes that selectively digest glycoproteins at positions decorated with specific O-linked glycans. O-Glycoprotease substrates range from any O-glycoprotein (albeit with specific O-glycan modifications) to only glycoproteins harboring specific O-glycosylated sequence motifs, such as those found in mucin domains. Their utility for multiple glycoproteomic applications is driving the search to both discover new O-glycoproteases and to understand how structural features of characterized O-glycoproteases influence their substrate specificities. One challenge of defining O-glycoprotease specificity restraints is the need to characterize O-glycopeptides with site-specific analysis of O-glycosites. Here, we demonstrate how O-Pair Search, a recently developed O-glycopeptide-centric identification platform that enables rapid searches and confident O-glycosite localization, can be used to determine substrate specificities of various O-glycoproteases de novo from LC-MS/MS data of O-glycopeptides. Using secreted protease of C1 esterase inhibitor (StcE) from enterohemorrhagic Escherichia coli and O-endoprotease OgpA from Akkermansia mucinophila, we explore numerous settings that effect O-glycopeptide identification and show how non-specific and semi-tryptic searches of O-glycopeptide data can produce candidate cleavage motifs. These putative motifs can be further used to define new protease cleavage settings that lower search times and improve O-glycopeptide identifications. We use this platform to generate a consensus motif for the recently characterized immunomodulating metalloprotease (IMPa) from Pseudomonas aeruginosa and show that IMPa is a favorable O-glycoprotease for characterizing densely O-glycosylated mucin-domain glycoproteins.

Multiple Layers of Complexity in O-Glycosylation Illustrated With the Urinary Glycoproteome

While N-glycopeptides are relatively easy to characterize, O-glycosylation analysis is more complex. In this article, we illustrate the multiple layers of O-glycopeptide characterization that make this task so challenging. We believe our carefully curated dataset represents perhaps the largest intact human glycopeptide mixture derived from individuals, not from cell lines. The samples were collected from healthy individuals, patients with superficial or advanced bladder cancer (three of each group), and a single bladder inflammation patient. The data were scrutinized manually and interpreted using three different search engines: Byonic, Protein Prospector, and O-Pair, and the tool MS-Filter. Despite all the recent advances, reliable automatic O-glycopeptide assignment has not been solved yet. Our data reveal such diversity of site-specific O-glycosylation that has not been presented before. In addition to the potential biological implications, this dataset should be a valuable resource for software developers in the same way as some of our previously released data has been used in the development of O-Pair and O-Glycoproteome Analyzer. Based on the manual evaluation of the performance of the existing tools with our data, we lined up a series of recommendations that if implemented could significantly improve the reliability of glycopeptide assignments.

Measuring the multifaceted roles of mucin-domain glycoproteins in cancer

Mucin-domain glycoproteins are highly O-glycosylated cell surface and secreted proteins that serve as both biochemical and biophysical modulators. Aberrant expression and glycosylation of mucins are known hallmarks in numerous malignancies, yet mucin-domain glycoproteins remain enigmatic in the broad landscape of cancer glycobiology. Here we review the multifaceted roles of mucins in cancer through the lens of the analytical and biochemical methods used to study them. We also describe a collection of emerging tools that are specifically equipped to characterize mucin-domain glycoproteins in complex biological backgrounds. These approaches are poised to further elucidate how mucin biology can be understood and subsequently targeted for the next generation of cancer therapeutics.

Localization of Multiple O-Linked Glycans Exhibited in Isomeric Glycopeptides by Hot Electron Capture Dissociation

We describe a method to obtain a comprehensive profile of multiple glycosylations in glycopeptide isoforms. We detected a wide range of abundances of various O-glycoforms in isomeric glycopeptides using hot electron capture dissociation (hot ECD) in liquid chromatography-tandem mass spectrometry. To capture low abundant glycosylated species, a prototype of a ZenoTOF 7600 system incorporating an efficient electron-activated dissociation device to perform hot ECD was operated in targeted or scheduled high-resolution multiple reaction monitoring workflows. In addition, Zeno trap pulsing was activated to enhance the sensitivity of the time-of-flight mass spectrometer. Sixty-nine O-glycopeptides of the long O-glycopeptides in tryptic bovine fetuin digest were obtained with a relative abundance range from 100 to 0.2%, which included sialylated glycans with Neu5Ac and Neu5Gc.

Revealing the human mucinome

Mucin domains are densely O-glycosylated modular protein domains found in various extracellular and transmembrane proteins. Mucin-domain glycoproteins play important roles in many human diseases, such as cancer and cystic fibrosis, but the scope of the mucinome remains poorly defined. Recently, we characterized a bacterial O-glycoprotease, StcE, and demonstrated that an inactive point mutant retains binding selectivity for mucin-domain glycoproteins. In this work, we leverage inactive StcE to selectively enrich and identify mucin-domain glycoproteins from complex samples like cell lysate and crude ovarian cancer patient ascites fluid. Our enrichment strategy is further aided by an algorithm to assign confidence to mucin-domain glycoprotein identifications. This mucinomics platform facilitates detection of hundreds of glycopeptides from mucin domains and highly overlapping populations of mucin-domain glycoproteins from ovarian cancer patients. Ultimately, we demonstrate our mucinomics approach can reveal key molecular signatures of cancer from in vitro and ex vivo sources.

Mucin-domain glycoproteins are densely O-glycosylated proteins with unique secondary structure that imparts a large influence on cellular environments. Here, the authors develop a technique to selectively enrich and characterize mucin-domain glycoproteins from cell lysate and patient biofluids.

Precise O-Glycosylation Site Localization of CD24Fc by LC-MS Workflows

CD24Fc is a homodimeric recombinant Fc-fusion protein comprised of human CD24 connected to immunoglobulin G1 (IgG1) Fc fragment. CD24 is heavily glycosylated, and its biological function is considered mainly mediated by its glycosylation. Identification of the O-glycosylation sites would facilitate an in-depth understanding of the functional role of O-glycans in CD24. However, the presence of clustered mucin-type O-glycans together with N-glycans makes the determination of O-glycosylation sites and abundance very challenging. In this study, two sets of liquid chromatography-mass spectrometry (LC-MS) workflows were developed for the comprehensive characterization of O-glycosylation in CD24: (1) Fractionation and collision-induced dissociation (CID) workflow involving multienzyme digestion, fractionation, OpeRATOR/SialEXO digestion, and CID analysis; (2) Direct OpeRATOR/SialEXO digestion followed by electron-transfer/higher-energy collision dissociation (EThcD) analysis. The precise O-glycosylation sites were identified in CD24 for the first time, and the site occupancy was assessed. A total of 12 O-glycosylation sites were identified. Seven glycosylation sites were identified by both workflows, and five additional sites were identified only by the EThcD workflow. The predominant O-glycosylation site in CD24 was Thr25 followed by Thr15. The CID workflow provided an overall relative quantitation of O-glycoforms at the CD24 level and site localization for singly O-glycosylated peptides. The EThcD workflow directly identified glycosylation sites by tandem mass spectrometry (MS/MS) for singly, doubly, and triply O-glycosylated peptides. Together, both workflows validated each other's results and can be applied to a complex mucin-type O-glycosylation site analysis of other glycoproteins and Fc-fusion therapeutics.

Mass Spectrometry-Based Techniques to Elucidate the Sugar Code

Cells encode information in the sequence of biopolymers, such as nucleic acids, proteins, and glycans. Although glycans are essential to all living organisms, surprisingly little is known about the "sugar code" and the biological roles of these molecules. The reason glycobiology lags behind its counterparts dealing with nucleic acids and proteins lies in the complexity of carbohydrate structures, which renders their analysis extremely challenging. Building blocks that may differ only in the configuration of a single stereocenter, combined with the vast possibilities to connect monosaccharide units, lead to an immense variety of isomers, which poses a formidable challenge to conventional mass spectrometry. In recent years, however, a combination of innovative ion activation methods, commercialization of ion mobility-mass spectrometry, progress in gas-phase ion spectroscopy, and advances in computational chemistry have led to a revolution in mass spectrometry-based glycan analysis. The present review focuses on the above techniques that expanded the traditional glycomics toolkit and provided spectacular insight into the structure of these fascinating biomolecules. To emphasize the specific challenges associated with them, major classes of mammalian glycans are discussed in separate sections. By doing so, we aim to put the spotlight on the most important element of glycobiology: the glycans themselves.

Efficient HCD-pd-EThcD approach for N-glycan mapping of therapeutic antibodies at intact glycopeptide level

N-glycosylation is a critical quality attribute for monoclonal antibody (mAb)-based therapeutics due to its significant impact on drug efficacy and safety. Extensive glycosylation mapping is therefore necessary for mAb drug development and quality control. We utilized a higher-energy dissociation product ions-triggered electron-transfer/higher-energy collision dissociation (HCD-pd-EThcD) approach to mapping N-glycosylation in therapeutic mAbs. Due to the improved duty cycle and targeted ability, HCD-pd-EThcD could provide extensive N-glycan identifications as well as higher quality spectra than EThcD mode. On average, ten types of N-glycan were uncovered in two different lots of trastuzumab, demonstrating a significant increment in N-glycan species compared to only four types identified by EThcD. After integrating pre-enrichment of glycopeptides, up to 16 N-glycans were recognized. Significantly, this strategy facilitated the identification of glycopeptides containing fucosylated and sialylated glycans, meanwhile enabled the recognition of different N-glycan classes (high mannose, hybrid, and complex). Further application in the glycosylation analysis of adalimumab and bevacizumab resulted in 19 and 8 N-glycans species, providing a more comprehensive insight into their glycosylation modification status. We demonstrated the benefits of an integrated strategy in characterizing various N-glycans of mAb therapeutics and offer an alternative approach for their quality control at the intact glycopeptides level.

Sequential Analysis of the N/O-Glycosylation of Heavily Glycosylated HIV-1 gp120 Using EThcD-sceHCD-MS/MS

Deciphering the glycosylation of the viral envelope (Env) glycoprotein is critical for evaluating viral escape from the host’s immune response and developing vaccines and antiviral drugs. However, it is still challenging to precisely decode the site-specific glycosylation characteristics of the highly glycosylated Env proteins, although glycoproteomics have made significant advances in mass spectrometry techniques and data analysis tools. Here, we present a hybrid dissociation technique, EThcD-sceHCD, by combining electron transfer/higher-energy collisional dissociation (EThcD) and stepped collision energy/higher-energy collisional dissociation (sceHCD) into a sequential glycoproteomic workflow. Following this scheme, we characterized site-specific N/O-glycosylation of the human immunodeficiency virus type 1 (HIV-1) Env protein gp120. The EThcD-sceHCD method increased the number of identified glycopeptides when compared with EThcD, while producing more comprehensive fragment ions than sceHCD for site-specific glycosylation analysis, especially for accurate O-glycosite assignment. Finally, eighteen N-glycosites and five O-glycosites with attached glycans were assigned unambiguously from heavily glycosylated gp120. These results indicate that our workflow can achieve improved performance for analysis of the N/O-glycosylation of a highly glycosylated protein containing numerous potential glycosites in one process. Knowledge of the glycosylation landscape of the Env glycoprotein will be useful for understanding of HIV-1 infection and development of vaccines and drugs.

Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis

Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N- and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved 'high-coverage' and 'high-accuracy' glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics.

O-Glycosylation Landscapes of SARS-CoV-2 Spike Proteins

The densely glycosylated spike (S) proteins that are highly exposed on the surface of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) facilitate viral attachment, entry, and membrane fusion. We have previously reported all the 22 N-glycosites and site-specific N-glycans in the S protein protomer. Herein, we report the O-glycosylation landscapes of SARS-CoV-2 S proteins, which were characterized through high-resolution mass spectrometry. Following digestion with trypsin and trypsin/Glu-C, and de-N-glycosylation using PNGase F, we determined the GalNAc-type O-glycosylation pattern of S proteins, including O-glycosites and the six most common O-glycans occupying them, via Byonic identification and manual validation. Finally, 255 intact O-glycopeptides composed of 50 peptides sequences and 43 O-glycosites were discovered by higher energy collision-induced dissociation (HCD), and three O-glycosites were confidently identified by electron transfer/higher energy collision-induced dissociation (EThcD) in the insect cell-expressed S protein. Most glycosites were modified by non-sialylated O-glycans such as HexNAc(1) and HexNAc(1)Hex (1). In contrast, in the human cell-expressed S protein S1 subunit, 407 intact O-glycopeptides composed of 34 peptides sequences and 30 O-glycosites were discovered by HCD, and 11 O-glycosites were unambiguously assigned by EThcD. However, the measurement of O-glycosylation occupancy hasn’t been made. Most glycosites were modified by sialylated O-glycans such as HexNAc(1)Hex (1)NeuAc (1) and HexNAc(1)Hex (1)NeuAc (2). Our results reveal that the SARS-CoV-2 S protein is an O-glycoprotein; the O-glycosites and O-glycan compositions vary with the host cell type. These comprehensive O-glycosylation landscapes of the S protein are expected to provide novel insights into the viral binding mechanism and present a strategy for the development of vaccines and targeted drugs.

Linkage Memory in Underivatized Protonated Carbohydrates

Carbohydrates are among the most complex class of biomolecules, and even subtle variations in their structures are attributed to diverse biological functions. Mass spectrometry has been essential for large scale glycomics and glycoproteomics studies, but the gas-phase structures and sometimes anomalous fragmentation properties of carbohydrates present long-standing challenges. Here we investigate the gas-phase properties of a panel of isomeric protonated disaccharides differing in their linkage configurations. Multiple conformations were evident for most of the structures based on their fragment ion abundances by tandem mass spectrometry, their ion mobilities in several gases, and their deuterium uptake kinetics by gas-phase hydrogen-deuterium exchange. Most notably, we find that the properties of the Y-ion fragments are characteristically influenced by the precursor carbohydrate's linkage configuration. This study reveals how protonated carbohydrate fragment ions can retain "linkage memory" that provides structural insight into their intact precursor.

Generating orthogonal glycosyltransferase and nucleotide sugar pairs as next-generation glycobiology tools

Protein glycosylation fundamentally impacts biological processes. Nontemplated biosynthesis introduces unparalleled complexity into glycans that needs tools to understand their roles in physiology. The era of quantitative biology is a great opportunity to unravel these roles, especially by mass spectrometry glycoproteomics. However, with high sensitivity come stringent requirements on tool specificity. Bioorthogonal metabolic labeling reagents have been fundamental to studying the cell surface glycoproteome but typically enter a range of different glycans and are thus of limited specificity. Here, we discuss the generation of metabolic 'precision tools' to study particular subtypes of the glycome. A chemical biology tactic termed bump-and-hole engineering generates mutant glycosyltransferases that specifically accommodate bioorthogonal monosaccharides as an enabling technique of glycobiology. We review the groundbreaking discoveries that have led to applying the tactic in the living cell and the implications in the context of current developments in mass spectrometry glycoproteomics.

Towards structure-focused glycoproteomics

Facilitated by advances in the separation sciences, mass spectrometry and informatics, glycoproteomics, the analysis of intact glycopeptides at scale, has recently matured enabling new insights into the complex glycoproteome. While diverse quantitative glycoproteomics strategies capable of mapping monosaccharide compositions of N- and O-linked glycans to discrete sites of proteins within complex biological mixtures with considerable sensitivity, quantitative accuracy and coverage have become available, developments supporting the advancement of structure-focused glycoproteomics, a recognised frontier in the field, have emerged. Technologies capable of providing site-specific information of the glycan fine structures in a glycoproteome-wide context are indeed necessary to address many pending questions in glycobiology. In this review, we firstly survey the latest glycoproteomics studies published in 2018–2020, their approaches and their findings, and then summarise important technological innovations in structure-focused glycoproteomics. Our review illustrates that while the O-glycoproteome remains comparably under-explored despite the emergence of new O-glycan-selective mucinases and other innovative tools aiding O-glycoproteome profiling, quantitative glycoproteomics is increasingly used to profile the N-glycoproteome to tackle diverse biological questions. Excitingly, new strategies compatible with structure-focused glycoproteomics including novel chemoenzymatic labelling, enrichment, separation, and mass spectrometry-based detection methods are rapidly emerging revealing glycan fine structural details including bisecting GlcNAcylation, core and antenna fucosylation, and sialyl-linkage information with protein site resolution. Glycoproteomics has clearly become a mainstay within the glycosciences that continues to reach a broader community. It transpires that structure-focused glycoproteomics holds a considerable potential to aid our understanding of systems glycobiology and unlock secrets of the glycoproteome in the immediate future.

Calculating Glycoprotein Similarities From Mass Spectrometric Data

Complex protein glycosylation occurs through biosynthetic steps in the secretory pathway that create macro- and microheterogeneity of structure and function. Required for all life forms, glycosylation diversifies and adapts protein interactions with binding partners that underpin interactions at cell surfaces and pericellular and extracellular environments. Because these biological effects arise from heterogeneity of structure and function, it is necessary to measure their changes as part of the quest to understand nature. Quite often, however, the assumption behind proteomics that posttranslational modifications are discrete additions that can be modeled using the genome as a template does not apply to protein glycosylation. Rather, it is necessary to quantify the glycosylation distribution at each glycosite and to aggregate this information into a population of mature glycoproteins that exist in a given biological system. To date, mass spectrometric methods for assigning singly glycosylated peptides are well-established. But it is necessary to quantify glycosylation heterogeneity accurately in order to gauge the alterations that occur during biological processes. The task is to quantify the glycosylated peptide forms as accurately as possible and then apply appropriate bioinformatics algorithms to the calculation of micro- and macro-similarities. In this review, we summarize current approaches for protein quantification as they apply to this glycoprotein similarity problem.

Precise, fast and comprehensive analysis of intact glycopeptides and modified glycans with pGlyco3

Great advances have been made in mass spectrometric data interpretation for intact glycopeptide analysis. However, accurate identification of intact glycopeptides and modified saccharide units at the site-specific level and with fast speed remains challenging. Here, we present a glycan-first glycopeptide search engine, pGlyco3, to comprehensively analyze intact N- and O-glycopeptides, including glycopeptides with modified saccharide units. A glycan ion-indexing algorithm developed for glycan-first search makes pGlyco3 5-40 times faster than other glycoproteomic search engines without decreasing accuracy or sensitivity. By combining electron-based dissociation spectra, pGlyco3 integrates a dynamic programming-based algorithm termed pGlycoSite for site-specific glycan localization. Our evaluation shows that the site-specific glycan localization probabilities estimated by pGlycoSite are suitable to localize site-specific glycans. With pGlyco3, we confidently identified N-glycopeptides and O-mannose glycopeptides that were extensively modified by ammonia adducts in yeast samples. The freely available pGlyco3 is an accurate and flexible tool that can be used to identify glycopeptides and modified saccharide units.

Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis

Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N- and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved 'high-coverage' and 'high-accuracy' glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics.

A Pragmatic Guide to Enrichment Strategies for Mass Spectrometry-Based Glycoproteomics

Glycosylation is a prevalent, yet heterogeneous modification with a broad range of implications in molecular biology. This heterogeneity precludes enrichment strategies that can be universally beneficial for all glycan classes. Thus, choice of enrichment strategy has profound implications on experimental outcomes. Here we review common enrichment strategies used in modern mass spectrometry-based glycoproteomic experiments, including lectins and other affinity chromatographies, hydrophilic interaction chromatography and its derivatives, porous graphitic carbon, reversible and irreversible chemical coupling strategies, and chemical biology tools that often leverage bioorthogonal handles. Interest in glycoproteomics continues to surge as mass spectrometry instrumentation and software improve, so this review aims to help equip researchers with the necessary information to choose appropriate enrichment strategies that best complement these efforts.

Electron-Based Dissociation Is Needed for O-Glycopeptides Derived from OpeRATOR Proteolysis

The recently described O-glycoprotease OpeRATOR presents exciting opportunities for O-glycoproteomics. This bacterial enzyme purified from Akkermansia muciniphila cleaves N-terminally to serine and threonine residues that are modified with (preferably asialylated) O-glycans. This provides orthogonal cleavage relative to canonical proteases (e.g., trypsin) for improved O-glycopeptide characterization with tandem mass spectrometry (MS/MS). O-glycopeptides with a modified N-terminal residue, such as those generated by OpeRATOR, present several potential benefits, perhaps the most notable being de facto O-glycosite localization without the need of glycan-retaining fragments in MS/MS spectra. Indeed, O-glycopeptides modified exclusively at the N-terminus would enable O-glycoproteomic methods to rely solely on collision-based fragmentation rather than electron-driven dissociation because glycan-retaining peptide fragments would not be required for localization. The caveat is that modified peptides would need to reliably contain only a single O-glycosite. Here, we use methods that combine collision- and electron-based fragmentation to characterize the number of O-glycosites that are present in O-glycopeptides derived from the OpeRATOR digestion of four known O-glycoproteins. Our data show that over 50% of O-glycopeptides in our sample generated from combined digestion using OpeRATOR and trypsin contain multiple O-glycosites, indicating that collision-based fragmentation alone is not sufficient. Electron-based dissociation methods are necessary to capture the O-glycopeptide diversity present in OpeRATOR digestions.

O-Pair Search with MetaMorpheus for O-glycopeptide characterization

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 with MetaMorpheus for O-glycopeptide characterization

We report O-Pair Search, a new approach to identify O-glycopeptides and localize O-glycosites. Using paired collision- and electron-based dissociation spectra, O-Pair Search identifies O-glycopeptides using 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.

Improved online LC-MS/MS identification of O-glycosites by EThcD fragmentation, chemoenzymatic reaction, and SPE enrichment

O-glycosylation is a highly diverse and complex form of protein post-translational modification. Mucin-type O-glycosylation is initiated by the transfer of N-acetyl-galactosamine (GalNAc) to the hydroxyl group of serine, threonine and tyrosine residues through catalysis by a family of glycosyltransferases, the UDP-GalNAc:polypeptide N-acetylgalactosaminyltransferases (E.C. 2.4.1.41) that are conserved across metazoans. In the last decade, structural characterization of glycosylation has substantially advanced due to the development of analytical methods and advances in mass spectrometry. However, O-glycosite mapping remains challenging since mucin-type O-glycans are densely packed, often protecting proteins from cleavage by proteases. Adding to the complexity is the fact that a given glycosite can be modified by different glycans, resulting in an array of glycoforms rising from one glycosite. In this study, we investigated conditions of solid phase extraction (SPE) enrichment, protease digestion, and Electron-transfer/Higher Energy Collision Dissociation (EThcD) fragmentation to optimize identification of O-glycosites in densely glycosylated proteins. Our results revealed that anion-exchange stationary phase is sufficient for glycopeptide enrichment; however, the use of a hydrophobic-containing sorbent was detrimental to the binding of polar-hydrophilic glycopeptides. Different proteases can be employed for enhancing coverage of O-glycosites, while derivatization of negatively charged amino acids or sialic acids would enhance the identification of a short O-glycopeptides. Using a longer than normal electron transfer dissociation (ETD) reaction time, we obtained enhanced coverage of peptide bonds that facilitated the localization of O-glycosites. O-glycosite mapping strategy via proteases, cut-off filtration and solid-phase chemoenzymatic processing. Glycopeptides are enriched by SPE column, followed by release of N-glycans, collection of higher MW O-glycopeptides via MW cut-off filter, O-glycopeptide release via O-protease, and finally detected by LC-MS/MS using EThcD.

Classification of Mucin-Type O-Glycopeptides Using Higher-Energy Collisional Dissociation in Mass Spectrometry

Changes in mucin-type O-glycosylation of human proteins affect protein function, immune response, and cancer progression. Since O-glycoproteins are characterized by the microheterogeneity of diverse O-glycans with no conserved sequence and the macroheterogeneity of multiple glycosylation sites on serine and/or threonine in human proteins, the assessment of different mucin types, such as Tn-antigen, core 1, and core 2, and their extended core types in O-glycopeptides, is extremely challenging. Here, we present an O-GlycoProteome Analyzer (O-GPA) that automatically classifies mucin-type O-glycosylation using higher-energy collisional dissociation (HCD) in mass spectrometry. First, we estimated the number of GlcNAc residues using the intensity ratio of GlcNAc-specific fragment ions (HexNAc-CH₆O₃ and HexNAc-2H₂O) over GalNAc-specific fragment ions (HexNAc-C₂H₆O₃ and HexNAc-C₂H₄O₂) in the HCD spectrum. Furthermore, we classified the different mucin types of O-glycopeptides from characteristic B₂ (HexNAc₂) or Y_2α (PEP + HexNAc₂), and Y_2β (PEP + HexNAcHex) fragment ions, along with the number of GlcNAc. Furthermore, O-GPA automatically determined single or multiple O-glycosylation, regardless of the mucin types. The mucin type of O-glycopeptides from human urine and plasma was confirmed with an overall accuracy of 96%. We found 97 core 1, 56 core 2, 13 extended core 1, and 12 extended core 2 glycopeptides from urine; and 22 core 1, 13 core 2, 7 extended core 1, 1 extended core 2, and 1 Tn-antigen from plasma. Our strategy can be used to successfully characterize specific mucin types of O-glycoproteins in human biological samples.

Optimal Dissociation Methods Differ for N- and O-Glycopeptides

Site-specific characterization of glycosylation requires intact glycopeptide analysis, and recent efforts have focused on how to best interrogate glycopeptides using tandem mass spectrometry (MS/MS). Beam-type collisional activation, i.e., higher-energy collisional dissociation (HCD), has been a valuable approach, but stepped collision energy HCD (sceHCD) and electron transfer dissociation with HCD supplemental activation (EThcD) have emerged as potentially more suitable alternatives. Both sceHCD and EThcD have been used with success in large-scale glycoproteomic experiments, but they each incur some degree of compromise. Most progress has occurred in the area of N-glycoproteomics. There is growing interest in extending this progress to O-glycoproteomics, which necessitates comparisons of method performance for the two classes of glycopeptides. Here, we systematically explore the advantages and disadvantages of conventional HCD, sceHCD, ETD, and EThcD for intact glycopeptide analysis and determine their suitability for both N- and O-glycoproteomic applications. For N-glycopeptides, HCD and sceHCD generate similar numbers of identifications, although sceHCD generally provides higher quality spectra. Both significantly outperform EThcD methods in terms of identifications, indicating that ETD-based methods are not required for routine N-glycoproteomics even if they can generate higher quality spectra. Conversely, ETD-based methods, especially EThcD, are indispensable for site-specific analyses of O-glycopeptides. Our data show that O-glycopeptides cannot be robustly characterized with HCD-centric methods that are sufficient for N-glycopeptides, and glycoproteomic methods aiming to characterize O-glycopeptides must be constructed accordingly.

Novel O-linked sialoglycan structures in human urinary glycoproteins

Glycopeptides represent cross-linked structures between chemically and physically different biomolecules. Mass spectrometric analysis of O-glycopeptides may reveal the identity of the peptide, the composition of the glycan and even the connection between certain sugar units, but usually only the combination of different MS/MS techniques provides sufficient information for reliable assignment. Currently, HCD analysis followed by diagnostic sugar fragment-triggered ETD or EThcD experiments is the most promising data acquisition protocol. However, the information content of the different MS/MS data is handled separately by search engines. We are convinced that these data should be used in concert, as we demonstrate in the present study. First, glycopeptides bearing the most common glycans can be identified from EThcD and/or HCD data. Then, searching for Y₀ (the gas-phase deglycosylated peptide) in HCD spectra, the potential glycoforms of these glycopeptides could be lined up. Finally, these spectra and the corresponding EThcD data can be used to verify or discard the tentative assignments and to obtain further structural information about the glycans. We present 18 novel human urinary sialoglycan structures deciphered using this approach. To accomplish this in an automated fashion further software development is necessary.

Capturing site-specific heterogeneity with large-scale N-glycoproteome analysis

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.

Extended Sialylated O-Glycan Repertoire of Human Urinary Glycoproteins Discovered and Characterized Using Electron-Transfer/Higher-Energy Collision Dissociation

A relatively novel activation technique, electron-transfer/higher-energy collision dissociation (EThcD) was used in the LC-MS/MS analysis of tryptic glycopeptides enriched with wheat germ agglutinin from human urine samples. We focused on the characterization of mucin-type O-glycopeptides. EThcD in a single spectrum provided information on both the peptide modified and the glycan carried. Unexpectedly, glycan oxonium ions indicated the presence of O-acetyl, and even O-diacetyl-sialic acids. B and Y fragment ions revealed that (i) in core 1 structures the Gal residue featured the O-acetyl-sialic acid, when there was only one in the glycan; (ii) several glycopeptides featured core 1 glycans with disialic acids, in certain instances O-acetylated; (iii) the disialic acid was linked to the GalNAc residue whatever the degree of O-acetylation; (iv) core 2 isomers with a single O-acetyl-sialic acid were chromatographically resolved. Glycan fragmentation also helped to decipher additional core 2 oligosaccharides: a LacdiNAc-like structure, glycans carrying sialyl Lewis^X/A at different stages of O-acetylation, and blood antigens. A sialo core 3 structure was also identified. We believe this is the first study when such structures were characterized from a very complex mixture and were linked not only to a specific protein, but also the sites of modifications have been determined.