Carbamidomethylation Side Reactions May Lead to Glycan Misassignments in Glycopeptide Analysis

An improved sulfur-nitroso-proteome strategy for global profiling of sulfur-nitrosylated proteins and sulfur-nitrosylation sites in mice

Comprehensive sulfur-nitrosylation (SNO) proteome coverage in complex biological systems remains challenging as a result of the low level of endogenous S-nitrosylation and its chemical instability. Herein, we optimized the synthesis route of SNOTRAP (SNO trapping by triaryl phosphine) probe and the proteomics pipeline (including preventing over-alkylation, sample washing, trypsin digestion). Preventing overalkylation was found to be the key factor resulting in a higher number of identified SNO proteins by evaluating various experimental conditions. With the improved SNOTRAP-based proteomic pipeline, we achieved an improvement of ∼10-fold on identification efficiency, and identified 1181 SNO proteins (1714 SNO sites) in mouse brain, representing the largest repository of endogenous S-nitrosylation. Moreover, we identified the consensus motif of SNO sites, suggesting the correlation with local hydrophobicity, acid-base catalysis, and the surrounding secondary structures for modification of specific cysteines by NO. Collectively, we provide a universal pipeline for the high-coverage identification of low-abundance SNO proteins with high enrichment efficiency, high specificity (98%), good reproducibility, and easy implementation, contributing to the elucidation of the mechanism(s) of nitrosative stress in multiple diseases.

Critical considerations in N-glycoproteomics

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

Multi-attribute Glycan Identification and FDR Control for Glycoproteomics

Rapidly improving methods for glycoproteomics have enabled increasingly large-scale analyses of complex glycopeptide samples, but annotating the resulting mass spectrometry data with high confidence remains a major bottleneck. We recently introduced a fast and sensitive glycoproteomics search method in our MSFragger search engine, which reports glycopeptides as a combination of a peptide sequence and the mass of the attached glycan. In samples with complex glycosylation patterns, converting this mass to a specific glycan composition is not straightforward; however, as many glycans have similar or identical masses. Here, we have developed a new method for determining the glycan composition of N-linked glycopeptides fragmented by collisional or hybrid activation that uses multiple sources of information from the spectrum, including observed glycan B-type (oxonium) and Y-type ions and mass and precursor monoisotopic selection errors to discriminate between possible glycan candidates. Combined with false discovery rate estimation for the glycan assignment, we show that this method is capable of specifically and sensitively identifying glycans in complex glycopeptide analyses and effectively controls the rate of false glycan assignments. The new method has been incorporated into the PTM-Shepherd modification analysis tool to work directly with the MSFragger glyco search in the FragPipe graphical user interface, providing a complete computational pipeline for annotation of N-glycopeptide spectra with false discovery rate control of both peptide and glycan components that is both sensitive and robust against false identifications.

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Identifying the glycan on intact glycopeptides remains difficult in glycoproteomics.

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We developed a method to assign glycan compositions in N-glycoproteomics searches.

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We demonstrate well-controlled glycan FDR in multiple sample types.

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The method annotates more glycopeptide spectra than competing tools.

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The method is included PTM-Shepherd for a full glycoproteomics workflow in FragPipe.

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.

ANALYSIS OF CARBOHYDRATES AND GLYCOCONJUGATES BY MATRIX-ASSISTED LASER DESORPTION/IONIZATION MASS SPECTROMETRY: AN UPDATE FOR 2015-2016

This review is the ninth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2016. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation and arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals. Much of this material is presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions and applications to chemical synthesis. The reported work shows increasing use of combined new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented over 30 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show no sign of deminishing. © 2020 Wiley Periodicals, Inc.

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.

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.

Semiautomated glycoproteomics data analysis workflow for maximized glycopeptide identification and reliable quantification

Glycoproteomic data are often very complex, reflecting the high structural diversity of peptide and glycan portions. The use of glycopeptide-centered glycoproteomics by mass spectrometry is rapidly evolving in many research areas, leading to a demand in reliable data analysis tools. In recent years, several bioinformatic tools were developed to facilitate and improve both the identification and quantification of glycopeptides. Here, a selection of these tools was combined and evaluated with the aim of establishing a robust glycopeptide detection and quantification workflow targeting enriched glycoproteins. For this purpose, a tryptic digest from affinity-purified immunoglobulins G and A was analyzed on a nano-reversed-phase liquid chromatography-tandem mass spectrometry platform with a high-resolution mass analyzer and higher-energy collisional dissociation fragmentation. Initial glycopeptide identification based on MS/MS data was aided by the Byonic software. Additional MS1-based glycopeptide identification relying on accurate mass and retention time differences using GlycopeptideGraphMS considerably expanded the set of confidently annotated glycopeptides. For glycopeptide quantification, the performance of LaCyTools was compared to Skyline, and GlycopeptideGraphMS. All quantification packages resulted in comparable glycosylation profiles but featured differences in terms of robustness and data quality control. Partial cysteine oxidation was identified as an unexpectedly abundant peptide modification and impaired the automated processing of several IgA glycopeptides. Finally, this study presents a semiautomated workflow for reliable glycoproteomic data analysis by the combination of software packages for MS/MS- and MS1-based glycopeptide identification as well as the integration of analyte quality control and quantification.

Relative Retention Time Estimation Improves N-Glycopeptide Identifications by LC-MS/MS

Glycopeptides identified by tandem mass spectrometry rely on the identification of the peptide backbone sequence and the attached glycan(s) by the incomplete fragmentation of both moieties. This may lead to ambiguous identifications where multiple structures could explain the same spectrum equally well due to missing information in the mass spectrum or incorrect precursor mass determination. To date, approaches to solving these problems have been limited, and few inroads have been made to address these issues. We present a technique to address some of these challenges and demonstrate it on previously published data sets. We use a linear modeling approach to learn the influence of the glycan composition on the retention time of a glycopeptide and use these models to validate glycopeptides within the same experiment, detecting over 400 incorrect cases during the MS/MS search and correcting 75 cases that could not be identified based on mass alone. We make this technique available as a command line executable program, written in Python and C, freely available at https://github.com/mobiusklein/glycresoft in source form, with precompiled binaries for Windows.

Antioxidant and cytoprotective effect of peptides produced by hydrolysis of whey protein concentrate with trypsin

Whey protein is one of the most relevant co-products manufactured by the dairy industry and it is a powerful environmental pollutant. Therefore, the enzymatic hydrolysis of whey protein concentrate (WPC 35) to produce antioxidant peptides is an innovative approach which can provide added value to whey. The WPC 35 hydrolysis with trypsin was carried out for 4.31 h at 41.1 °C with an enzyme/substrate ratio of 0.017. Under such hydrolysis conditions, the peptides produced have the highest radical scavenging activity and cytoprotector effect. The WPC hydrolysate and a permeate ≤3 kDa were characterized by SDS-page, RP-HPLC and MALDI-TOF-MS. Furthermore, O₂^•- and HO^• scavenging activity and the cytoprotective effect against a stress agent in epithelial cells of the rat ileum (IEC-18) were determined. In this study, strong antioxidant and cytoprotective peptides were obtained from a low-cost dairy industry product, which could improve consumers' health when used as functional ingredients.

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.

'Shotgun' proteomic analyses without alkylation of cysteine

It is a common belief that reduction of disulfide bridges and alkylation of thiols in proteins are indispensable steps in proteomic sample preparation. Since this chemical procedure is often incomplete and prone to side reactions we reexamined its importance. We found that reduction and alkylation do not increase the depth of analysis and quality of proteomic quantification and therefore these steps are not essential in 'shotgun'-type investigations of proteomes. Moreover, we found that compared to a standard procedure using iodoacetamide for thiol-alkylation, sample preparation under conditions protecting thiols from oxidation improves quality of peptides and allows identifying of 10-20% more peptides and proteins. Excluding thiol-alkylation from proteomic sample preparation shortens the workflows and decreases the probability of biases resulting from occurrence of artificially modified peptides.

Glyco-DIA: a method for quantitative O-glycoproteomics with in silico-boosted glycopeptide libraries

We report a liquid chromatography coupled to tandem mass spectrometry O-glycoproteomics strategy using data-independent acquisition (DIA) mode for direct analysis of O-glycoproteins. This approach enables characterization of glycopeptides and structures of O-glycans on a proteome-wide scale with quantification of stoichiometries (though it does not allow for direct unambiguous glycosite identification). The method relies on a spectral library of O-glycopeptides; the Glyco-DIA library contains sublibraries obtained from human cell lines and human serum, and it currently covers 2,076 O-glycoproteins (11,452 unique glycopeptide sequences) and the 5 most common core1 O-glycan structures. Applying the Glyco-DIA library to human serum without enrichment for glycopeptides enabled us to identify and quantify 269 distinct glycopeptide sequences bearing up to 5 different core1 O-glycans from 159 glycoproteins in a SingleShot analysis.

Characterization of Plant Glycoproteins: Analysis of Plant Glycopeptide Mass Spectrometry Data with plantGlycoMS, a Package in the R Statistical Computing Environment

plantGlycoMS is a set of tools, implemented in R, which is used to assess and validate glycopeptide spectrum matches (gPSMs). Validity of gPSMs is based on characteristic fragmentation patterns of glycopeptides (gPSMvalidator), adherence of the glycan moiety to the known N-glycan biosynthesis pathway in plants (pGlycoFilter), and elution of the glycopeptide within the observed retention time window of other glycopeptides sharing the same peptide backbone (rt.Restrict). plantGlycoMS also contains a tool for relative quantitation of glycoforms based on selected ion chromatograms of glycopeptide ion precursors in the mass spectrometry level 1 data (glycoRQ). This protocol walks the user through this workflow with example mass spectrometry data obtained for a plant glycoprotein.

A Comprehensive, Open-source Platform for Mass Spectrometry-based Glycoproteomics Data Analysis

Glycosylation is among the most abundant and diverse protein post-translational modifications (PTMs) identified to date. The structural analysis of this PTM is challenging because of the diverse monosaccharides which are not conserved among organisms, the branched nature of glycans, their isomeric structures, and heterogeneity in the glycan distribution at a given site. Glycoproteomics experiments have adopted the traditional high-throughput LC-MSⁿ proteomics workflow to analyze site-specific glycosylation. However, comprehensive computational platforms for data analyses are scarce. To address this limitation, we present a comprehensive, open-source, modular software for glycoproteomics data analysis called GlycoPAT (GlycoProteomics Analysis Toolbox; freely available from www.VirtualGlycome.org/glycopat). The program includes three major advances: (1) "SmallGlyPep," a minimal linear representation of glycopeptides for MSⁿ data analysis. This format allows facile serial fragmentation of both the peptide backbone and PTM at one or more locations. (2) A novel scoring scheme based on calculation of the "Ensemble Score (ES)," a measure that scores and rank-orders MS/MS spectrum for N- and O-linked glycopeptides using cross-correlation and probability based analyses. (3) A false discovery rate (FDR) calculation scheme where decoy glycopeptides are created by simultaneously scrambling the amino acid sequence and by introducing artificial monosaccharides by perturbing the original sugar mass. Parallel computing facilities and user-friendly GUIs (Graphical User Interfaces) are also provided. GlycoPAT is used to catalogue site-specific glycosylation on simple glycoproteins, standard protein mixtures and human plasma cryoprecipitate samples in three common MS/MS fragmentation modes: CID, HCD and ETD. It is also used to identify 960 unique glycopeptides in cell lysates from prostate cancer cells. The results show that the simultaneous consideration of peptide and glycan fragmentation is necessary for high quality MSⁿ spectrum annotation in CID and HCD fragmentation modes. Additionally, they confirm the suitability of GlycoPAT to analyze shotgun glycoproteomics data.

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.

Site-Specific N-Glycosylation of Recombinant Pentameric and Hexameric Human IgM

Glycosylation is known to play an important role in IgG antibody structure and function. Polymeric IgM, the largest known antibody in humans, displays five potential N-glycosylation sites on each heavy chain monomer. IgM can exist as a pentamer with a connecting singly N-glycosylated J-chain (with a total of 51 glycosylation sites) or as a hexamer (60 glycosylation sites). In this study, the N-glycosylation of recombinant pentameric and hexameric IgM produced by the same human cell type and culture conditions was site-specifically profiled by RP-LC-CID/ETD-MS/MS using HILIC-enriched tryptic and GluC glycopeptides. The occupancy of all putative N-glycosylation sites on the pentameric and hexameric IgM were able to be determined. Distinct glycosylation differences were observed between each of the five N-linked sites on the IgM heavy chains. While Asn171, Asn332, and Asn395 all had predominantly complex type glycans, differences in glycan branching and sialylation were observed between the sites. Asn563, a high mannose-rich glycosylation site that locates in the center of the IgM polymer, was only approximately 60% occupied in both the pentameric and hexameric IgM forms, with a difference in relative abundance of the glycan structures between the pentamer and hexamer. This study highlights the information obtained by characterization of the site-heterogeneity of a highly glycosylated protein of high molecular mass with quaternary structure, revealing differences that would not be seen by global glycan or deglycosylated peptide profiling. Graphical Abstract ᅟ.

Maturing Glycoproteomics Technologies Provide Unique Structural Insights into the N-glycoproteome and Its Regulation in Health and Disease

The glycoproteome remains severely understudied because of significant analytical challenges associated with glycoproteomics, the system-wide analysis of intact glycopeptides. This review introduces important structural aspects of protein N-glycosylation and summarizes the latest technological developments and applications in LC-MS/MS-based qualitative and quantitative N-glycoproteomics. These maturing technologies provide unique structural insights into the N-glycoproteome and its synthesis and regulation by complementing existing methods in glycoscience. Modern glycoproteomics is now sufficiently mature to initiate efforts to capture the molecular complexity displayed by the N-glycoproteome, opening exciting opportunities to increase our understanding of the functional roles of protein N-glycosylation in human health and disease.