Novel LC-MS2 Product Dependent Parallel Data Acquisition Function and Data Analysis Workflow for Sequencing and Identification of Intact Glycopeptides

Prostate-specific membrane antigen (PSMA) glycoforms in prostate cancer patients seminal plasma

INTRODUCTION

Prostate-specific membrane antigen (PSMA) is a US Food and Drug Administration-approved theranostic target for prostate cancer (PCa). Although PSMA is known to be glycosylated, the composition and functional roles of its N-linked glycoforms have not been fully characterized.

METHODS

PSMA was isolated from pooled seminal plasma from low-risk grade Groups 1 and 2 PCa patients. Intact glycopeptides were analyzed by mass spectrometry to identify site-specific glycoforms.

RESULTS

We observed a rich distribution of PSMA glycoforms in seminal plasma from low and low-intermediate-risk PCa patients. Some interesting generalities can be drawn based on the predicted topology of PSMA on the plasma membrane. The glycoforms at ASN-459, ASN-476, and ASN-638 residues that are located at the basal domain facing the plasma membrane in cells, are predominantly high mannose glycans. ASN-76 which is located in the interdomain region adjacent to the apical domain of the protein shows a mixture of high mannose glycans and complex glycans, whereas ASN-121, ASN-195 and ASN-336 that are located and are exposed at the apical domain of the protein predominantly possess complex sialylated and fucosylated N-linked glycans. These highly accessible glycosites display the greatest diversity in isoforms across the patient samples.

CONCLUSIONS

Our study provides novel qualitative insights into PSMA glycoforms that are present in the seminal fluid of PCa patients. The presence of a rich diversity of glycoforms in seminal plasma provides untapped potential for glycoprotein biomarker discovery and as a clinical sample for noninvasive diagnostics of male urological disorders and diseases including PCa. Specifically, our glycomics approach will be critical in uncovering PSMA glycoforms with utility in staging and risk stratification of PCa.

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).

An N-glycopeptide MS/MS data analysis workflow leveraging two complementary glycoproteomic software tools for more confident identification and assignments

Complete coverage of all N-glycosylation sites on the SARS-CoV2 spike protein would require the use of multiple proteases in addition to trypsin. Subsequent identification of the resulting glycopeptides by searching against database often introduces assignment errors due to similar mass differences between different permutations of amino acids and glycosyl residues. By manually interpreting the individual MS2 spectra, we report here the common sources of errors in assignment, especially those introduced by the use of chymotrypsin. We show that by applying a stringent threshold of acceptance, erroneous assignment by the commonly used Byonic software can be controlled within 15%, which can be reduced further if only those also confidently identified by a different search engine, pGlyco3, were considered. A representative site-specific N-glycosylation pattern could be constructed based on quantifying only the overlapping subset of N-glycopeptides identified at higher confidence. Applying the two complimentary glycoproteomic software in a concerted data analysis workflow, we found and confirmed that glycosylation at several sites of an unstable Omicron spike protein differed significantly from those of the stable trimeric product of the parental D614G variant.

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.

Improved analysis ZIC-HILIC-HCD-Orbitrap method for mapping the glycopeptide by mass spectrometry

Glycosylation is one of the most common post-translational modifications (PTMs). Protein glycosylation analysis is the bottleneck to deeply understand their functions. At present, the LC-MS analysis of glycosylated post-translational modification is mainly focused on the analysis of glycopeptides. However, the factors affecting the identification of glycopeptides were not fully elucidated. In the paper, we have carefully studied the factors, e.g., HILIC materials, search engines, protein amount, gradient duration, extraction solution, etc. According to the results, HILIC materials were the most important factors affecting the glycopeptides identification, and the amphoteric sulfoalkyl betaine stationary phase enriched glycopeptides 6-fold more compared to the amphiphilic ion-bonded fully porous spherical silica stationary phase. We explored the influence of the extraction solutions on glycan identification. Comparing sodium dodecyl sulfate (SDS) and urea (UA), the results showed that N-glycolylneuraminic acid (NeuGc) type of glycan content was found to be increased 1.4-fold in the SDS compared to UA. Besides, we explored the influence of the search engine on glycopeptide identification. Comparing pGlyco3.0 and MSFragger-Glyco, it was observed that pGlyco3.0 outperformed MSFragger-Glyco in identifying glycopeptides. Then, using our optimized method we found that there was a significant difference in the distribution of monosaccharide types in plasma and brain tissue, e.g., the content of NeuAc in brain was 5-fold higher than that in plasma. To importantly, two glycoproteins (Neurexin-2 and SUN domain-containing protein 2) were also found for the first time by our method. In summary, we have comprehensively studied the factors influencing glycopeptide identification than any previous research, and the optimized method could be widely used for identifying the glycoproteins or glycolpeptides biomarkers for disease detection and therapeutic targets.

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.

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.

The human disease gene LYSET is essential for lysosomal enzyme transport and viral infection

Lysosomes are key degradative compartments of the cell. Transport to lysosomes relies on GlcNAc-1-phosphotransferase-mediated tagging of soluble enzymes with mannose 6-phosphate (M6P). GlcNAc-1-phosphotransferase deficiency leads to the severe lysosomal storage disorder mucolipidosis II (MLII). Several viruses require lysosomal cathepsins to cleave structural proteins and thus depend on functional GlcNAc-1-phosphotransferase. Here, we used genome-scale CRISPR screens to identify Lysosomal Enzyme Trafficking factor (LYSET) as essential for infection by cathepsin-dependent viruses including SARS-CoV-2. LYSET deficiency resulted in global loss of M6P tagging and mislocalization of GlcNAc-1-phosphotransferase from the Golgi complex to lysosomes. Lyset knockout mice exhibited MLII-like phenotypes and human pathogenic LYSET alleles failed to restore lysosomal sorting defects. Thus, LYSET is required for correct functioning of the M6P trafficking machinery, and mutations in LYSET can explain the phenotype of the associated disorder.

Site-Specific Intact N-Linked Glycopeptide Characterization of Prostate-Specific Membrane Antigen from Metastatic Prostate Cancer Cells

The composition of N-linked glycans that are conjugated to the prostate-specific membrane antigen (PSMA) and their functional significance in prostate cancer progression have not been fully characterized. PSMA was isolated from two metastatic prostate cancer cell lines, LNCaP and MDAPCa2b, which have different tissue tropism and localization. Isolated PSMA was trypsin-digested, and intact glycopeptides were subjected to LC-HCD-EThcD-MS/MS analysis on a Tribrid Orbitrap Fusion Lumos mass spectrometer. Differential qualitative and quantitative analysis of site-specific N-glycopeptides was performed using Byonic and Byologic software. Comparative quantitative analysis demonstrates that multiple glycopeptides at asparagine residues 51, 76, 121, 195, 336, 459, 476, and 638 were in significantly different abundance in the two cell lines (p < 0.05). Biochemical analysis using endoglycosidase treatment and lectin capture confirm the MS and site occupancy data. The data demonstrate the effectiveness of the strategy for comprehensive analysis of PSMA glycopeptides. This approach will form the basis of ongoing experiments to identify site-specific glycan changes in PSMA isolated from disease-stratified clinical samples to uncover targets that may be associated with disease progression and metastatic phenotypes.

Measuring change in glycoprotein structure

Biosynthetic enzymes in the secretory pathway create distributions of glycans at each glycosite that elaborate the biophysical properties and biological functions of glycoproteins. Because the biosynthetic glycosylation reactions do not go to completion, each protein glycosite is heterogeneous with respect to glycosylation. This heterogeneity means that it is not sufficient to measure protein abundance in omics experiments. Rather, it is necessary to sample the distribution of glycosylation at each glycosite to quantify the changes that occur during biological processes. On the one hand, the use of data-dependent acquisition methods to sample glycopeptides is limited by the instrument duty cycle and the missing value problem. On the other, stepped window data-independent acquisition samples all precursors, but ion abundances are limited by duty cycle. Therefore, the ability to quantify accurately the flux in glycoprotein glycosylation that occurs during biological processes requires the exploitation of emerging mass spectrometry technologies capable of deep, comprehensive sampling and selective high confidence assignment of the complex glycopeptide mixtures. This review summarizes recent technical advances and mass spectral glycoproteomics analysis strategies and how these developments impact our ability to quantify the changes in glycosylation that occur during biological processes. We highlight specific improvements to glycopeptide characterization through activated electron dissociation, ion mobility trends and instrumentation, and efficient algorithmic approaches for glycopeptide assignment. We also discuss the emerging need for unified standards to enable interlaboratory collaborations and effective monitoring of structural changes in glycoproteins.

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.

Mucinomics as the Next Frontier of Mass Spectrometry

Mucin-domain glycoproteins comprise a class of proteins whose densely O-glycosylated mucin domains adopt a secondary structure with unique biophysical and biochemical properties. The canonical family of mucins is well-known to be involved in various diseases, especially cancer. Despite this, very little is known about the site-specific molecular structures and biological activities of mucins, in part because they are extremely challenging to study by mass spectrometry (MS). Here, we summarize recent advancements toward this goal, with a particular focus on mucin-domain glycoproteins as opposed to general O-glycoproteins. We summarize proteolytic digestion techniques, enrichment strategies, MS fragmentation, and intact analysis, as well as new bioinformatic platforms. In particular, we highlight mucin directed technologies such as mucin-selective proteases, tunable mucin platforms, and a mucinomics strategy to enrich mucin-domain glycoproteins from complex samples. Finally, we provide examples of targeted mucin-domain glycoproteomics that combine these techniques in comprehensive site-specific analyses of proteins. Overall, this Review summarizes the methods, challenges, and new opportunities associated with studying enigmatic mucin domains.

Mass Spectrometry-based Proteomics and Glycoproteomics in COVID-19 Biomarkers Identification: A Mini-review

The first corona-pandemic, coronavirus disease 2019 (COVID-19) caused a huge health crisis and incalculable damage worldwide. Knowledge of how to cure the disease is urgently needed. Emerging immune escaping mutants of the virus suggested that it may be potentially persistent in human society as a regular health threat as the flu virus. Therefore, it is imperative to identify appropriate biomarkers to indicate pathological and physiological states, and more importantly, clinic outcomes. Proteins are the performers of life functions, and their abundance and modification status can directly reflect the immune status. Protein glycosylation serves a great impact in modulating protein function. The use of both unmodified and glycosylated proteins as biomarkers has also been proved feasible in the studies of SARS, Zika virus, influenza, etc. In recent years, mass spectrometry-based glycoproteomics, as well as proteomics approaches, advanced significantly due to the evolution of mass spectrometry. We focus on the current development of the mass spectrometry-based strategy for COVID-19 biomarkers' investigation. Potential application of glycoproteomics approaches and challenges in biomarkers identification are also discussed.

Recent Advances in Software Tools for More Generic and Precise Intact Glycopeptide Analysis

Intact glycopeptide identification has long been known as a key and challenging barrier to the comprehensive and accurate understanding the role of glycosylation in an organism. Intact glycopeptide analysis is a blossoming field that has received increasing attention in recent years. MS-based strategies and relative software tools are major drivers that have greatly facilitated the analysis of intact glycopeptides, particularly intact N-glycopeptides. This article provides a systematic review of the intact glycopeptide-identification process using MS data generated in shotgun proteomic experiments, which typically focus on N-glycopeptide analysis. Particular attention is paid to the software tools that have been recently developed in the last decade for the interpretation and quality control of glycopeptide spectra acquired using different MS strategies. The review also provides information about the characteristics and applications of these software tools, discusses their advantages and disadvantages, and concludes with a discussion of outstanding tools.

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.

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.

Integrated Glycoproteomics Identifies a Role of N-Glycosylation and Galectin-1 on Myogenesis and Muscle Development

Many cell surface and secreted proteins are modified by the covalent addition of glycans that play an important role in the development of multicellular organisms. These glycan modifications enable communication between cells and the extracellular matrix via interactions with specific glycan-binding lectins and the regulation of receptor-mediated signaling. Aberrant protein glycosylation has been associated with the development of several muscular diseases, suggesting essential glycan- and lectin-mediated functions in myogenesis and muscle development, but our molecular understanding of the precise glycans, catalytic enzymes, and lectins involved remains only partially understood. Here, we quantified dynamic remodeling of the membrane-associated proteome during a time-course of myogenesis in cell culture. We observed wide-spread changes in the abundance of several important lectins and enzymes facilitating glycan biosynthesis. Glycomics-based quantification of released N-linked glycans confirmed remodeling of the glycome consistent with the regulation of glycosyltransferases and glycosidases responsible for their formation including a previously unknown digalactose-to-sialic acid switch supporting a functional role of these glycoepitopes in myogenesis. Furthermore, dynamic quantitative glycoproteomic analysis with multiplexed stable isotope labeling and analysis of enriched glycopeptides with multiple fragmentation approaches identified glycoproteins modified by these regulated glycans including several integrins and growth factor receptors. Myogenesis was also associated with the regulation of several lectins, most notably the upregulation of galectin-1 (LGALS1). CRISPR/Cas9-mediated deletion of Lgals1 inhibited differentiation and myotube formation, suggesting an early functional role of galectin-1 in the myogenic program. Importantly, similar changes in N-glycosylation and the upregulation of galectin-1 during postnatal skeletal muscle development were observed in mice. Treatment of new-born mice with recombinant adeno-associated viruses to overexpress galectin-1 in the musculature resulted in enhanced muscle mass. Our data form a valuable resource to further understand the glycobiology of myogenesis and will aid the development of intervention strategies to promote healthy muscle development or regeneration.

Meta-heterogeneity: Evaluating and Describing the Diversity in Glycosylation Between Sites on the Same Glycoprotein

Mass spectrometry-based glycoproteomics has gone through some incredible developments over the last few years. Technological advances in glycopeptide enrichment, fragmentation methods, and data analysis workflows have enabled the transition of glycoproteomics from a niche application, mainly focused on the characterization of isolated glycoproteins, to a mature technology capable of profiling thousands of intact glycopeptides at once. In addition to numerous biological discoveries catalyzed by the technology, we are also observing an increase in studies focusing on global protein glycosylation and the relationship between multiple glycosylation sites on the same protein. It has become apparent that just describing protein glycosylation in terms of micro- and macro-heterogeneity, respectively, the variation and occupancy of glycans at a given site, is not sufficient to describe the observed interactions between sites. In this perspective we propose a new term, meta-heterogeneity, to describe a higher level of glycan regulation: the variation in glycosylation across multiple sites of a given protein. We provide literature examples of extensive meta-heterogeneity on relevant proteins such as antibodies, erythropoietin, myeloperoxidase, and a number of serum and plasma proteins. Furthermore, we postulate on the possible biological reasons and causes behind the intriguing meta-heterogeneity observed in glycoproteins.

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.

Databases and Bioinformatic Tools for Glycobiology and Glycoproteomics

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

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.

New Energy Setup Strategy for Intact N-Glycopeptides Characterization Using Higher-Energy Collisional Dissociation

With the optional setting of multiple stepped collisional energies (NCEs), higher-energy collisional dissociation (HCD) as available on Orbitrap instruments is a widely adopted dissociation method for intact N-glycopeptides characterization, where peptide backbones and N-glycan moieties are selectively fragmented at high and low NCEs, respectively. Initially, a dependent setting of a central value plus minus a variation is available to the users to set up NCEs, and the combination of 30 ± 10% to give the energies 20%/30%/40% has been mostly adopted in the literature. With the recent availability of an independent NCEs setup, we found that the combination of 20%/30%/30% is better than 20%/30%/40%; in the analysis of complex intact N-glycopeptides enriched from gastric cancer tissues, total IDs with spectrum-level FDR ≤ 1%, site-specific IDs with site-determining fragment ions, and structure-specific IDs with structure-diagnostic fragment ions were increased by 42% (4,767 → 6,746), 57% (599 → 942), and 97% (1771 → 3495), respectively. This finding will benefit all the coming N-glycoproteomics studies using HCD as the dissociation method.

The effectiveness of filtering glycopeptide peak list files for Y ions

Intact glycopeptide analysis is becoming more common with developments in mass spectrometry instrumentation and fragmentation approaches. In particular, collision-based fragmentation approaches such as higher energy collisional dissociation (HCD) and radical-driven fragmentation approaches such as electron transfer dissociation (ETD) provide complementary information, but bioinformatic strategies to utilize this combined information are currently lacking. In this work we adapted a software tool, MS-Filter, to search HCD peak list files for predicted Y ions based on matched EThcD results to propose additional glycopeptide assignments. The strategy proved to be extremely powerful for O-glycopeptide data, and also of benefit for N-linked data, where it allowed rescue of low confidence results from database searching.

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.

Isolation and characterization of glycosylated neuropeptides

Glycosylation is one of the most ubiquitous and complex post-translational modifications (PTMs). It plays pivotal roles in various biological processes. Studies at the glycopeptide level are typically considered as a downstream work resulting from enzymatic digested glycoproteins. Less attention has been focused on glycosylated endogenous signaling peptides due to their low abundance, structural heterogeneity and the lack of enabling analytical tools. Here, protocols are presented to isolate and characterize glycosylated neuropeptides utilizing nanoflow liquid chromatography coupled with mass spectrometry (LC-MS). We first demonstrate how to extract neuropeptides from raw tissues and perform further separation/cleanup before MS analysis. Then we describe hybrid MS methods for glycosylated neuropeptide profiling and site-specific analysis. We also include recommendations for data analysis to identify glycosylated neuropeptides in crustaceans where a complete neuropeptide database is still lacking. Other strategies and future directions are discussed to provide readers with alternative approaches and further unravel biological complexity rendered by glycosylation.

Simply Extending the Mass Range in Electron Transfer Higher Energy Collisional Dissociation Increases Confidence in N-Glycopeptide Identification

Glycopeptide-centric mass spectrometry has become a popular approach for studying protein glycosylation. However, current approaches still utilize fragmentation schemes and ranges originally optimized and intended for the analysis of typically much smaller unmodified tryptic peptides. Here, we show that by merely increasing the tandem mass spectrometry m/z range from 2000 to 4000 during electron transfer higher energy collisional dissociation (EThcD) fragmentation, a wealth of highly informative c and z ion fragment ions are additionally detected, facilitating improved identification of glycopeptides. We demonstrate the benefit of this extended mass range on various classes of glycopeptides containing phosphorylated, fucosylated, and/or sialylated N-glycans. We conclude that the current software solutions for glycopeptide identification also require further improvements to realize the full potential of extended mass range glycoproteomics. To stimulate further developments, we provide data sets containing all classes of glycopeptides (high mannose, hybrid, and complex) measured with standard (2000) and extended (4000) m/z range that can be used as test cases for future development of software solutions enhancing automated glycopeptide analysis.

DecoyDeveloper: An On-Demand, De Novo Decoy Glycopeptide Generator

Glycopeptide analysis is a growing field that is struggling to adopt effective, automated tools. Many creative workflows and software apps have emerged recently that offer promising capabilities for assigning glycopeptides to MS data in an automated fashion. The effectiveness of these tools is best measured and improved by determining how often they would select a glycopeptide decoy as a spectral match, instead of its correct assignment; yet generating the appropriate number and type of glycopeptide decoys can be challenging. To address this need, we have designed DecoyDeveloper, an on-demand decoy glycopeptide generator that can produce a high volume of decoys with low mass differences. DecoyDeveloper has a simple user interface and is capable of producing large sets of decoys containing complete, biologically relevant glycan and peptide sequences. We demonstrate the tool's efficiency by applying it to a set of 80 glycopeptide targets. This tool is freely available and can be found at http://glycopro.chem.ku.edu/J1.php .

Mapping human N-linked glycoproteins and glycosylation sites using mass spectrometry

N-linked glycoprotein is a highly interesting class of proteins for clinical and biological research. Over the last decade, large-scale profiling of N-linked glycoproteins and glycosylation sites from biological and clinical samples has been achieved through mass spectrometry-based glycoproteomic approaches. In this paper, we reviewed the human glycoproteomic profiles that have been reported in more than 80 individual studies, and mainly focused on the N-glycoproteins and glycosylation sites identified through their deglycosylated forms of glycosite-containing peptides. According to our analyses, more than 30,000 glycosite-containing peptides and 7,000 human glycoproteins have been identified from five different body fluids, twelve human tissues (or related cell lines), and four special cell types. As the glycoproteomic data is still missing for many organs and tissues, a systematical glycoproteomic analysis of various human tissues and body fluids using a uniform platform is still needed for an integrated map of human N-glycoproteomes.

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.

LC-MS Analysis of (Glyco-)Proteins of Pichia pastoris

In this chapter, we will present two methods for comprehensive glycoprotein characterization that are particularly but not exclusively useful for Pichia pastoris glycoproteins. One approach is intact protein mass measurement, where deglycosylation may be used to determine the mass of the unmodified protein. The other method is the classical bottom-up approach, where peptides and glycopeptides are analyzed by reversed-phase chromatography and detected by electrospray ionization mass spectrometry. The choice of chromatography solvents with a high ionic strength simplifies the identification of peaks of a particular peptide's glycopattern as it leads to co-elution of neutral and charged, i.e., phosphorylated, glycoforms.

Distinctive and Complementary MS2 Fragmentation Characteristics for Identification of Sulfated Sialylated N-Glycopeptides by nanoLC-MS/MS Workflow

High sensitivity identification of sulfated glycans carried on specific sites of glycoproteins is an important requisite for investigation of molecular recognition events involved in diverse biological processes. However, aiming for resolving site-specific glycosylation of sulfated glycopeptides by direct LC-MS² sequencing is technically most challenging. Other than the usual limiting factors such as lower abundance and ionization efficiency compared to analysis of non-glycosylated peptides, confident identification of sulfated glycopeptides among the more abundant non-sulfated glycopeptides requires additional considerations in the selective enrichment and detection strategies. Metal oxide has been applied to enrich phosphopeptides and sialylated glycopeptides, but its use to capture sulfated glycopeptides has not been investigated. Likewise, various complementary MS² fragmentation modes have yet to be tested against sialylated and non-sialylated sulfoglycopeptides due to limited appropriate sample availability. In this study, we have investigated the feasibility of sequencing tryptic sulfated N-glycopeptide and its MS² fragmentation characteristics by first optimizing the enrichment methods to allow efficient LC-MS detection and MS² analysis by a combination of CID, HCD, ETD, and EThcD on hybrid and tribrid Orbitrap instruments. Characteristic sulfated glyco-oxonium ions and direct loss of sulfite from precursors were detected as evidences of sulfate modification. It is anticipated that the technical advances demonstrated in this study would allow a feasible extension of our sulfoglycomic analysis to sulfoglycoproteomics. Graphical Abstract ᅟ.

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

A very complex mixture of intact, human N- and O-glycopeptides, enriched from the tryptic digest of urinary proteins of three healthy donors using a two-step lectin affinity enrichment, was analyzed by LC-MS/MS, leading to approximately 45,000 glycopeptide EThcD spectra. Two search engines, Byonic and Protein Prospector, were used for the interpretation of the data, and N- and O-linked glycopeptides were assigned from separate searches. The identification rate was very low in all searches, even when results were combined. Thus, we investigated the reasons why was it so, to help to improve the identification success rate. Focusing on O-linked glycopeptides, we noticed that in EThcD, larger glycan oxonium ions better survive the activation than those in HCD. These fragments, combined with reducing terminal Y ions, provide important information about the glycan(s) present, so we investigated whether filtering the peaklists for glycan oxonium ions indicating the presence of a tetra- or hexasaccharide structure would help to reveal all molecules containing such glycans. Our study showed that intact glycans frequently do not survive even mild supplemental activation, meaning one cannot rely on these oxonium ions exclusively. We found that ETD efficiency is still a limiting factor, and for highly glycosylated peptides, the only information revealed in EThcD was related to the glycan structures. The limited overlap of results delivered by the two search engines draws attention to the fact that automated data interpretation of O-linked glycopeptides is not even close to being solved. Graphical abstract ᅟ.

Large-scale intact glycopeptide identification by Mascot database search

Workflows capable of determining glycopeptides in large-scale are missing in the field of glycoproteomics. We present an approach for automated annotation of intact glycopeptide mass spectra. The steps in adopting the Mascot search engine for intact glycopeptide analysis included: (i) assigning one letter codes for monosaccharides, (ii) linearizing glycan sequences and (iii) preparing custom glycoprotein databases. Automated annotation of both N- and O-linked glycopeptides was proven using standard glycoproteins. In a large-scale study, a total of 257 glycoproteins containing 970 unique glycosylation sites and 3447 non-redundant N-linked glycopeptide variants were identified in 24 serum samples. Thus, a single tool was developed that collectively allows the (i) elucidation of N- and O-linked glycopeptide spectra, (ii) matching glycopeptides to known protein sequences, and (iii) high-throughput, batch-wise analysis of large-scale glycoproteomics data sets.

Mapping and Quantification of Over 2000 O-linked Glycopeptides in Activated Human T Cells with Isotope-Targeted Glycoproteomics (Isotag)

Post-translational modifications (PTMs) on proteins often function to regulate signaling cascades, with the activation of T cells during an adaptive immune response being a classic example. Mounting evidence indicates that the modification of proteins by O-linked N-acetylglucosamine (O-GlcNAc), the only mammalian glycan found on nuclear and cytoplasmic proteins, helps regulate T cell activation. Yet, a mechanistic understanding of how O-GlcNAc functions in T cell activation remains elusive, partly because of the difficulties in mapping and quantifying O-GlcNAc sites. Thus, to advance insight into the role of O-GlcNAc in T cell activation, we performed glycosite mapping studies via direct glycopeptide measurement on resting and activated primary human T cells with a technique termed Isotope Targeted Glycoproteomics. This approach led to the identification of 2219 intact O-linked glycopeptides across 1045 glycoproteins. A significant proportion (>45%) of the identified O-GlcNAc sites lie near or coincide with a known phosphorylation site, supporting the potential for PTM crosstalk. Consistent with other studies, we find that O-GlcNAc sites in T cells lack a strict consensus sequence. To validate our results, we employed gel shift assays based on conjugating mass tags to O-GlcNAc groups. Notably, we observed that the transcription factors c-JUN and JUNB show higher levels of O-GlcNAc glycosylation and higher levels of expression in activated T cells. Overall, our findings provide a quantitative characterization of O-GlcNAc glycoproteins and their corresponding modification sites in primary human T cells, which will facilitate mechanistic studies into the function of O-GlcNAc in T cell activation.

Glycosylation status of bone sialoprotein and its role in mineralization

The highly glycosylated bone sialoprotein (BSP) is an abundant non-collagenous phosphoprotein in bone which enhances osteoblast differentiation and new bone deposition in vitro and in vivo. However, the structural details of its different glycosylation linkages have not been well studied and their functions in bone homeostasis are not clear. Previous studies suggested that the O-glycans, but not the N-glycans on BSP, are highly sialylated. Herein, we employed tandem mass spectrometry (MS/MS) to demonstrate that the N-glycanson the recombinant human integrin binding sialoprotein (rhiBSP) are also enriched in sialic acids (SAs) at their termini. We also identified multiple novel sites of N-glycan modification. Treatment of rhiBSP enhances osteoblast differentiation and mineralization of MC3T3-E1 cells and this effect could be partially reversed by efficient enzymatic removal of its N-glycans. Removal of all terminal SAs has a greater effect in reversing the effect of rhiBSP on osteogenesis, especially on mineralization, suggesting that sialylation at the termini of both N-glycans and O-glycans plays an important role in this regulation. Moreover, BSP-conjugated SAs may affect mineralization via ERK activation of VDR expression. Collectively, our results identified novel N-glycans enriched in SAs on the rhiBSP and demonstrated that SAs at both N- and O-glycans are important for BSP regulation of osteoblast differentiation and mineralization in vitro.

pGlyco 2.0 enables precision N-glycoproteomics with comprehensive quality control and one-step mass spectrometry for intact glycopeptide identification

The precise and large-scale identification of intact glycopeptides is a critical step in glycoproteomics. Owing to the complexity of glycosylation, the current overall throughput, data quality and accessibility of intact glycopeptide identification lack behind those in routine proteomic analyses. Here, we propose a workflow for the precise high-throughput identification of intact N-glycopeptides at the proteome scale using stepped-energy fragmentation and a dedicated search engine. pGlyco 2.0 conducts comprehensive quality control including false discovery rate evaluation at all three levels of matches to glycans, peptides and glycopeptides, improving the current level of accuracy of intact glycopeptide identification. The N-glycoproteome of samples metabolically labeled with ¹⁵N/¹³C were analyzed quantitatively and utilized to validate the glycopeptide identification, which could be used as a novel benchmark pipeline to compare different search engines. Finally, we report a large-scale glycoproteome dataset consisting of 10,009 distinct site-specific N-glycans on 1988 glycosylation sites from 955 glycoproteins in five mouse tissues.

Protein glycosylation is a heterogeneous post-translational modification that generates greater proteomic diversity that is difficult to analyze. Here the authors describe pGlyco 2.0, a workflow for the precise one step identification of intact N-glycopeptides at the proteome scale.

Electron-Transfer/Higher-Energy Collision Dissociation (EThcD)-Enabled Intact Glycopeptide/Glycoproteome Characterization

Protein glycosylation, one of the most heterogeneous post-translational modifications, can play a major role in cellular signal transduction and disease progression. Traditional mass spectrometry (MS)-based large-scale glycoprotein sequencing studies heavily rely on identifying enzymatically released glycans and their original peptide backbone separately, as there is no efficient fragmentation method to produce unbiased glycan and peptide product ions simultaneously in a single spectrum, and that can be conveniently applied to high throughput glycoproteome characterization, especially for N-glycopeptides, which can have much more branched glycan side chains than relatively less complex O-linked glycans. In this study, a redefined electron-transfer/higher-energy collision dissociation (EThcD) fragmentation scheme is applied to incorporate both glycan and peptide fragments in one single spectrum, enabling complete information to be gathered and great microheterogeneity details to be revealed. Fetuin was first utilized to prove the applicability with 19 glycopeptides and corresponding five glycosylation sites identified. Subsequent experiments tested its utility for human plasma N-glycoproteins. Large-scale studies explored N-glycoproteomics in rat carotid arteries over the course of restenosis progression to investigate the potential role of glycosylation. The integrated fragmentation scheme provides a powerful tool for the analysis of intact N-glycopeptides and N-glycoproteomics. We also anticipate this approach can be readily applied to large-scale O-glycoproteome characterization. Graphical Abstract ᅟ.

Glycomic and glycoproteomic analysis of glycoproteins-a tutorial

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

Glycomic and glycoproteomic analysis of glycoproteins-a tutorial

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

Development of IsoTaG, a Chemical Glycoproteomics Technique for Profiling Intact N- and O-Glycopeptides from Whole Cell Proteomes

Protein glycosylation can have an enormous variety of biological consequences, reflecting the molecular diversity encoded in glycan structures. This same structural diversity has imposed major challenges on the development of methods to study the intact glycoproteome. We recently introduced a method termed isotope-targeted glycoproteomics (IsoTaG), which utilizes isotope recoding to characterize azidosugar-labeled glycopeptides bearing fully intact glycans. Here, we describe the broad application of the method to analyze glycoproteomes from a collection of tissue-diverse cell lines. The effort was enabled by a new high-fidelity pattern-searching and glycopeptide validation algorithm termed IsoStamp v2.0, as well as by novel stable isotope probes. Application of the IsoTaG platform to 15 cell lines metabolically labeled with Ac₄GalNAz or Ac₄ManNAz revealed 1375 N- and 2159 O-glycopeptides, variously modified with 74 discrete glycan structures. Glycopeptide-bound glycans observed by IsoTaG were found to be comparable to released N-glycans identified by permethylation analysis. IsoTaG is therefore positioned to enhance structural understanding of the glycoproteome.

Combining Higher-Energy Collision Dissociation and Electron-Transfer/Higher-Energy Collision Dissociation Fragmentation in a Product-Dependent Manner Confidently Assigns Proteomewide ADP-Ribose Acceptor Sites

Protein adenosine diphosphate (ADP)-ribosylation is a physiologically and pathologically important post-translational modification. Recent technological advances have improved analysis of this complex modification and have led to the discovery of hundreds of ADP-ribosylated proteins in both cultured cells and mouse tissues. Nevertheless, accurate assignment of the ADP-ribose acceptor site(s) within the modified proteins identified has remained a challenging task. This is mainly due to poor fragmentation of modified peptides. Here, using an Orbitrap Fusion Tribrid mass spectrometer, we present an optimized methodology that not only drastically improves the overall localization scores for ADP-ribosylation acceptor sites but also boosts ADP-ribosylated peptide identifications. First, we systematically compared the efficacy of higher-energy collision dissociation (HCD), electron-transfer dissociation with supplemental collisional activation (ETcaD), and electron-transfer/higher-energy collision dissociation (EThcD) fragmentation methods when determining ADP-ribose acceptor sites within complex cellular samples. We then tested the combination of HCD and EThcD fragmentation, which were employed in a product-dependent manner, and the unique fragmentation properties of the ADP-ribose moiety were used to trigger targeted fragmentation of only the modified peptides. The best results were obtained with a workflow that included initial fast, high-energy HCD (Orbitrap, FT) scans, which produced intense ADP-ribose fragmentation ions. These potentially ADP-ribosylated precursors were then selected and analyzed via subsequent high-resolution HCD and EThcD fragmentation. Using these resulting high-quality spectra, we identified a xxxxxxKSxxxxx modification motif where lysine can serve as an ADP-ribose acceptor site. Due to the appearance of serine within this motif and its close presence to the lysine, further analysis revealed that serine serves as a new ADP-ribose acceptor site across the proteome.

Multi-Lectin Affinity Chromatography for Separation, Identification, and Quantitation of Intact Protein Glycoforms in Complex Biological Mixtures

Protein glycosylation is considered to be one of the most abundant post-translational modifications and is recognized for playing key roles in cellular functions. Aberrant N-linked glycosylation has been associated with several human diseases and has prompted the development and constant improvement of analytical tools to separate, characterize, and quantify glycoproteins in complex mixtures extracted from various biological samples (such as blood and tissue). Lectins, or carbohydrate-binding proteins, have been used as valuable tools for enriching for glycoproteins and selecting for specific types of glycosylation. Herein a method using multidimensional intact protein fractionation and LC-MS/MS analysis is described. Immunodepletion is used to remove highly abundant proteins from human plasma, followed by glycoform separation using multi-lectin affinity chromatography, in which specific lectins are chosen to capture and elute specific types of glycosylation. Reversed-phase chromatography prior to digestion is used for further fractionation, allowing for an increased number of protein identifications of moderate- to low-abundant proteins detectable in plasma. This method also incorporates isotopic labeling during alkylation for relative quantitation between two samples (such as a case and control). A bottom-up, tandem mass spectrometry-based proteomics approach is used for protein identification and quantitation, and allows for screening glycoform-specific changes across hundreds of plasma proteins.

Characterizing Glycoproteins by Mass Spectrometry in Campylobacter jejuni

The glycosylation systems of Campylobacter jejuni (C. jejuni) are considered archetypal examples of both N- and O-linked glycosylations in the field of bacterial glycosylation. The discovery and characterization of these systems both have revealed important biological insight into C. jejuni and have led to the refinement and enhancement of methodologies to characterize bacterial glycosylation. In general, mass spectrometry-based characterization has become the preferred methodology for the study of C. jejuni glycosylation because of its speed, sensitivity, and ability to enable both qualitative and quantitative assessments of glycosylation events. In these experiments the generation of insightful data requires the careful selection of experimental approaches and mass spectrometry (MS) instrumentation. As such, it is essential to have a deep understanding of the technologies and approaches used for characterization of glycosylation events. Here we describe protocols for the initial characterization of C. jejuni glycoproteins using protein-/peptide-centric approaches and discuss considerations that can enhance the generation of insightful data.