De novo glycan structure search with the CID MS/MS spectra of native N-glycopeptides

Altered microheterogeneity at several N-glycosylation sites in OPSCC in constant protein expression conditions

Protein glycosylation responds sensitively to disease states. It is implicated in every hallmark of cancer and has recently started to be considered as a hallmark itself. Changes in N-glycosylation microheterogeneity are more dramatic than those of protein expression due to the non-template nature of protein glycosylation. This enables their potential use in serum-based diagnostics. Here, we perform glycopeptidomics on serum from patients with oropharyngeal squamous cell carcinoma (OPSCC), compared to controls and comparing between cancers based on etiology (human papilloma virus- positive or negative). Using MS2, we then targeted glycoforms, significantly different between the groups, to identify their glycopeptide compositions. Simultaneously we investigate the same serum proteins, comparing whether N-glycosylation changes reflect protein-level changes. Significant glycoforms were identified from proteins such as alpha-1-antitrypsin (SERPINA1), haptoglobin, and different immunoglobulins. SERPINA1 had glycovariance at 2 N-glycosylation sites, that were up to 35 times more abundant in even early-stage OPSCCs, despite minimal differences between SERPINA1 protein levels between groups. Some identified glycoforms' fold changes (FCs) were in line with serum protein level FCs, others were less abundant in early-stage cancers but with great variance in higher-stage cancers, such as on immunoglobulin heavy constant gamma 2, despite no change in protein levels. Such findings indicate that glycovariant analysis might be more beneficial than proteomic analysis, which is yet to be fruitful in the search for biomarkers. Highly sensitive glycopeptide changes could potentially be used in the future for cancer screening. Additionally, characterizing the glycopeptide changes in OPSCC is valuable in the search for potential therapeutic targets.

Protonated α-N-Acetyl Galactose Glycopeptide Dissociation Chemistry

We recently provided mass spectrometric, H/D labeling, and computational evidence of pyranose to furanose N-acetylated ion isomerization reactions that occurred prior to glycosidic bond cleavage in both O- and N-linked glycosylated amino acid model systems (Guan et al. Phys. Chem. Chem. Phys., 2021, 23, 23256-23266). These reactions occurred irrespective of the glycosidic linkage stereochemistry (α or β) and the N-acetylated hexose structure (GlcNAc or GalNAc). In the present article, we test the generality of the preceding findings by examining threonyl α-GalNAc-glycosylated peptides. We utilize computational chemistry to compare the various dissociation and isomerization pathways accessible with collisional activation. We then interrogate the structure(s) of the resulting charged glycan and peptide fragments with infrared "action" spectroscopy. Isomerization of the original pyranose, the protonated glycopeptide [AT(GalNAc)A+H]⁺, is predicted to be facile compared to direct dissociation, as is the glycosidic bond cleavage of the newly formed furanose form, i.e., furanose oxazolinium ion structures are predicted to predominate. IR action spectra for the m/z 204, C₈H₁₄N₁O₅⁺, glycan fragment population support this prediction. The IR action spectra of the complementary m/z 262 peptide fragment were assigned as a mixture of the lowest-energy structures of [ATA+H]⁺ consistent with the literature. If general, the change to a furanose m/z 204 product ion structure fundamentally alters the ion population available for MS³ dissociation and glycopeptide sequence identification.

Evidence of gas-phase pyranose-to-furanose isomerization in protonated peptidoglycans

Peptidoglycans are diverse co- and post-translational modifications of key importance in myriad biological processes. Mass spectrometry is employed to infer their biomolecular sequences and stereochemisties, but little is known about the critical gas-phase dissociation processes involved. Here, using tandem mass spectrometry (MS/MS and MSⁿ), isotopic labelling and high-level simulations, we identify and characterize a facile isomerization reaction that produces furanose N-acetylated ions. This reaction occurs for both O- and N-linked peptidoglycans irrespective of glycosidic linkage stereochemistry (α/β). Dissociation of the glycosidic and other bonds thus occur from the furanose isomer critically altering the reaction feasibility and product ion structures.

Advancing Solutions to the Carbohydrate Sequencing Challenge

Carbohydrates possess a variety of distinct features with stereochemistry playing a particularly important role in distinguishing their structure and function. Monosaccharide building blocks are defined by a high density of chiral centers. Additionally, the anomericity and regiochemistry of the glycosidic linkages carry important biological information. Any carbohydrate-sequencing method needs to be precise in determining all aspects of this stereodiversity. Recently, several advances have been made in developing fast and precise analytical techniques that have the potential to address the stereochemical complexity of carbohydrates. This perspective seeks to provide an overview of some of these emerging techniques, focusing on those that are based on NMR and MS-hybridized technologies including ion mobility spectrometry and IR spectroscopy.

Tongue Cancer Patients Can be Distinguished from Healthy Controls by Specific N-Glycopeptides Found in Serum

PURPOSE

There are no blood biomarkers to detect early-stage oral cavity squamous cell carcinoma (OSCC) prior to clinical signs. Most OSCC incidence is associated with significant morbidity and poor survival. The authors aimed to use mass-spectrometry (MS) technology to find specific N-glycopeptides potentially serving as serum biomarkers for preclinical OSCC screening.

EXPERIMENTAL DESIGN

Serum samples from 14 patients treated for OSCC (stage I or stage IV) with 12 age- and sex-matched controls are collected. Quantitative label-free N-glycoproteomics is performed, with MS/MS analysis of the statistically significantly different N-glycopeptides.

RESULTS

Combined with a database search using web-based software (GlycopeptideID), MS/MS provided detailed N-glycopeptide information, including glycosylation site, glycan composition, and proposed structures. Thirty-eight tryptic N-glycopeptides are identified, having 19 unique N-glycosylation sites representing 14 glycoproteins. OSCC patients, including stage I tumors, can be differentiated from healthy controls based on the expression levels of these glycoforms. N-glycopeptides of IgG1, IgG4, haptoglobin, and transferrin have statistically significant different abundances between cases and controls.

CONCLUSIONS AND CLINICAL RELEVANCE

The authors are the first to suggest specific N-glycopeptides to serve as potential serum biomarkers to detect preclinical OSCC in patients. These N-glycopeptides are the lead candidates for validation as future diagnostic modalities of OSCC as early as stage I.

Investigation of O-glycosylation heterogeneity of recombinant coagulation factor IX using LC–MS/MS

Aim: Recombinant coagulation factor IX (rFIX) has extraordinarily multiple post-translational modifications including N-glycosylation and O-glycosylation which have a drastic effect on biological functions and in vivo recovery. Unlike N-glycosylation extensively characterized, there are a few studies on O-glycosylation due to its intrinsic complexity. In-depth O-glycosylation analysis is necessary to better understand and assess pharmacological activity of rFIX. Results: We determined unusual O-glycosylations including O-fucosylation and O-glucosylation which were located at Serine 53 and 61, respectively in EGF domain. Other O-glycosylations bearing core 1 glycan moiety were found on activation peptide. Conclusion: This is the first comprehensive study to characterize O-glycosylation of rFIX using MS-based glycomic and glycoproteomic approaches. Site-specific profiling will be a powerful platform to determine bioequivalence of biosimilars.

A Brief Review of Bioinformatics Tools for Glycosylation Analysis by Mass Spectrometry

The purpose of this review is to provide updated information regarding bioinformatic software for the use in the characterization of glycosylated structures since 2013. A comprehensive review by Woodin et al.Analyst 138: 2793-2803, 2013 (ref. 1) described two main approaches that are introduced for starting researchers in this area; analysis of released glycans and the identification of glycopeptide in enzymatic digests, respectively. Complementary to that report, this review focuses on mass spectrometry related bioinformatics tools for the characterization of N-linked and O-linked glycopeptides. Specifically, it also provides information regarding automated tools that can be used for glycan profiling using mass spectrometry.

Quantitative profiling of glycans and glycopeptides: an informatics' perspective

Experimental techniques to identify and quantify glycan structures in a given sample are continuously improving. However, as they advance data analysis and annotation seems to become more complex. To address this issue, much progress has been made in developing software for interpretation of quantitative glycan profiles. Here, we focus on these informatics tools for high/ultra performance liquid chromatography (H/UPLC), mass spectrometry (MS), tandem mass spectrometry (MSⁿ) and combinations thereof. Software for biomarker discovery, pathway, genomic and disease analysis and a final note on some future prospects for glycoinformatics are also mentioned.

SweetNET: A Bioinformatics Workflow for Glycopeptide MS/MS Spectral Analysis

Glycoproteomics has rapidly become an independent analytical platform bridging the fields of glycomics and proteomics to address site-specific protein glycosylation and its impact in biology. Current glycopeptide characterization relies on time-consuming manual interpretations and demands high levels of personal expertise. Efficient data interpretation constitutes one of the major challenges to be overcome before true high-throughput glycopeptide analysis can be achieved. The development of new glyco-related bioinformatics tools is thus of crucial importance to fulfill this goal. Here we present SweetNET: a data-oriented bioinformatics workflow for efficient analysis of hundreds of thousands of glycopeptide MS/MS-spectra. We have analyzed MS data sets from two separate glycopeptide enrichment protocols targeting sialylated glycopeptides and chondroitin sulfate linkage region glycopeptides, respectively. Molecular networking was performed to organize the glycopeptide MS/MS data based on spectral similarities. The combination of spectral clustering, oxonium ion intensity profiles, and precursor ion m/z shift distributions provided typical signatures for the initial assignment of different N-, O- and CS-glycopeptide classes and their respective glycoforms. These signatures were further used to guide database searches leading to the identification and validation of a large number of glycopeptide variants including novel deoxyhexose (fucose) modifications in the linkage region of chondroitin sulfate proteoglycans.

Glycan characterization of biopharmaceuticals: Updates and perspectives

Therapeutic proteins are rapidly becoming the most promising class of pharmaceuticals on the market due to their successful treatment of a vast array of serious diseases, such as cancers and immune disorders. Therapeutic proteins are produced using recombinant DNA technology. More than 60% of therapeutic proteins are posttranslationally modified following biosynthesis by the addition of N- or O-linked glycans. Glycosylation is the most common posttranslational modifications of proteins. However, it is also the most demanding and complex posttranslational modification from the analytical point of view. Moreover, research has shown that glycosylation significantly impacts stability, half-life, mechanism of action and safety of a therapeutic protein. Considering the exponential growth of biotherapeutics, this present review of the literature (2009-2015) focuses on the characterization of protein glycosylation, which has witnessed an improvement in methodology. Furthermore, it discusses current issues in the fields of production and characterization of therapeutic proteins. This review also highlights the problem of non-standard requirements for the approval of biosimilars with regard to their glycosylation and discusses recent developments and perspectives for improved glycan characterization.

N-Glycoproteomics of Human Seminal Plasma Glycoproteins

Seminal plasma aids sperm by inhibiting premature capacitation, helping in the intracervical transport and formation of an oviductal sperm reservoir, all of which appear to be important in the fertilization process. Epitopes such as Lewis x and y are known to be present on seminal plasma glycoproteins, which can modulate the maternal immune response. It is suggested by multiple studies that seminal plasma glycoproteins play, largely undiscovered, important roles in the process of fertilization. We have devised a strategy to analyze glycopeptides from a complex, unknown mixture of protease-digested proteins. This analysis provides identification of the glycoproteins, glycosylation sites, glycan compositions, and proposed structures from the original sample. This strategy has been applied to human seminal plasma total glycoproteins. We have elucidated glycan compositions and proposed structures for 243 glycopeptides belonging to 73 N-glycosylation sites on 50 glycoproteins. The majority of the proposed glycan structures were complex type (83%) followed by high-mannose (10%) and then hybrid (7%). Most of the glycoproteins were either sialylated, fucosylated, or both. Many Lewis x/a and y/b epitopes bearing glycans were found, suggesting immune-modulating epitopes on multiple seminal plasma glycoproteins. The study also shows that large scale N-glycosylation mapping is achievable with current techniques and the depth of the analysis is roughly proportional to the prefractionation and complexity of the sample.

Liquid chromatography-tandem mass spectrometry-based fragmentation analysis of glycopeptides

The use of liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS(n)) for the glycoproteomic characterization of glycopeptides is a growing field of research. The N- and O-glycosylated peptides (N- and O-glycopeptides) analyzed typically originate from protease-digested glycoproteins where many of them are expected to be biomedically important. Examples of LC-MS(2) and MS(3) fragmentation strategies used to pursue glycan structure, peptide identity and attachment-site identification analyses of glycopeptides are described in this review. MS(2) spectra, using the CID and HCD fragmentation techniques of a complex biantennary N-glycopeptide and a core 1 O-glycopeptide, representing two examples of commonly studied glycopeptide types, are presented. A few practical tips for accomplishing glycopeptide analysis using reversed-phase LC-MS(n) shotgun proteomics settings, together with references to the latest glycoproteomic studies, are presented.

A review of methods for interpretation of glycopeptide tandem mass spectral data

Despite the publication of several software tools for analysis of glycopeptide tandem mass spectra, there remains a lack of consensus regarding the most effective and appropriate methods. In part, this reflects problems with applying standard methods for proteomics database searching and false discovery rate calculation. While the analysis of small post-translational modifications (PTMs) may be regarded as an extension of proteomics database searching, glycosylation requires specialized approaches. This is because glycans are large and heterogeneous by nature, causing glycopeptides to exist as multiple glycosylated variants. Thus, the mass of the peptide cannot be calculated directly from that of the intact glycopeptide. In addition, the chemical nature of the glycan strongly influences product ion patterns observed for glycopeptides. As a result, glycopeptidomics requires specialized bioinformatics methods. We summarize the recent progress towards a consensus for effective glycopeptide tandem mass spectrometric analysis.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: an update for 2009-2010

This review is the sixth update of the original article published in 1999 on the application of MALDI mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2010. General aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, arrays and fragmentation are covered in the first part of the review and applications to various structural typed constitutes the remainder. The main groups of compound that are discussed in this section are oligo and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals. Many of these applications are presented in tabular form. Also discussed are medical and industrial applications of the technique, studies of enzyme reactions and applications to chemical synthesis.

Quantitative mass spectrometric analysis of glycoproteins combined with enrichment methods

Mass spectrometry (MS) has been a core technology for high sensitive and high-throughput analysis of the enriched glycoproteome in aspects of quantitative assays as well as qualitative profiling of glycoproteins. Because it has been widely recognized that aberrant glycosylation in a glycoprotein may involve in progression of a certain disease, the development of efficient analysis tool for the aberrant glycoproteins is very important for deep understanding about pathological function of the glycoprotein and new biomarker development. This review first describes the protein glycosylation-targeting enrichment technologies mainly employing solid-phase extraction methods such as hydrizide-capturing, lectin-specific capturing, and affinity separation techniques based on porous graphitized carbon, hydrophilic interaction chromatography, or immobilized boronic acid. Second, MS-based quantitative analysis strategies coupled with the protein glycosylation-targeting enrichment technologies, by using a label-free MS, stable isotope-labeling, or targeted multiple reaction monitoring (MRM) MS, are summarized with recent published studies.

N-linked (N-) glycoproteomics of urinary exosomes. [Corrected]

Epithelial cells lining the urinary tract secrete urinary exosomes (40-100 nm) that can be targeted to specific cells modulating their functionality. One potential targeting mechanism is adhesion between vesicle surface glycoproteins and target cells. This makes the glycopeptide analysis of exosomes important. Exosomes reflect the physiological state of the parent cells; therefore, they are a good source of biomarkers for urological and other diseases. Moreover, the urine collection is easy and noninvasive and urinary exosomes give information about renal and systemic organ systems. Accordingly, multiple studies on proteomic characterization of urinary exosomes in health and disease have been published. However, no systematic analysis of their glycoproteomic profile has been carried out to date, whereas a conserved glycan signature has been found for exosomes from urine and other sources including T cell lines and human milk. Here, we have enriched and identified the N-glycopeptides from these vesicles. These enriched N-glycopeptides were solved for their peptide sequence, glycan composition, structure, and glycosylation site using collision-induced dissociation MS/MS (CID-tandem MS) data interpreted by a publicly available software GlycopeptideId. Released glycans from the same sample was also analyzed with MALDI-MS. We have identified the N-glycoproteome of urinary exosomes. In total 126 N-glycopeptides from 51 N-glycosylation sites belonging to 37 glycoproteins were found in our results. The peptide sequences of these N-glycopeptides were identified unambiguously and their glycan composition (for 125 N-glycopeptides) and structures (for 87 N-glycopeptides) were proposed. A corresponding glycomic analysis with released N-glycans was also performed. We identified 66 unique nonmodified N-glycan compositions and in addition 13 sulfated/phosphorylated glycans were also found. This is the first systematic analysis of N-glycoproteome of urinary exosomes.

Software for automated interpretation of mass spectrometry data from glycans and glycopeptides

The purpose of this review is to provide those interested in glycosylation analysis with the most updated information on the availability of automated tools for MS characterization of N-linked and O-linked glycosylation types. Specifically, this review describes software tools that facilitate elucidation of glycosylation from MS data on the basis of mass alone, as well as software designed to speed the interpretation of glycan and glycopeptide fragmentation from MS/MS data. This review focuses equally on software designed to interpret the composition of released glycans and on tools to characterize N-linked and O-linked glycopeptides. Several websites have been compiled and described that will be helpful to the reader who is interested in further exploring the described tools.

Exploring site-specific N-glycosylation microheterogeneity of haptoglobin using glycopeptide CID tandem mass spectra and glycan database search

Glycosylation is a common protein modification with a significant role in many vital cellular processes and human diseases, making the characterization of protein-attached glycan structures important for understanding cell biology and disease processes. Direct analysis of protein N-glycosylation by tandem mass spectrometry of glycopeptides promises site-specific elucidation of N-glycan microheterogeneity, something that detached N-glycan and deglycosylated peptide analyses cannot provide. However, successful implementation of direct N-glycopeptide analysis by tandem mass spectrometry remains a challenge. In this work, we consider algorithmic techniques for the analysis of LC-MS/MS data acquired from glycopeptide-enriched fractions of enzymatic digests of purified proteins. We implement a computational strategy that takes advantage of the properties of CID fragmentation spectra of N-glycopeptides, matching the MS/MS spectra to peptide-glycan pairs from protein sequences and glycan structure databases. Significantly, we also propose a novel false discovery rate estimation technique to estimate and manage the number of false identifications. We use a human glycoprotein standard, haptoglobin, digested with trypsin and GluC, enriched for glycopeptides using HILIC chromatography, and analyzed by LC-MS/MS to demonstrate our algorithmic strategy and evaluate its performance. Our software, GlycoPeptideSearch (GPS), assigned glycopeptide identifications to 246 of the spectra at a false discovery rate of 5.58%, identifying 42 distinct haptoglobin peptide-glycan pairs at each of the four haptoglobin N-linked glycosylation sites. We further demonstrate the effectiveness of this approach by analyzing plasma-derived haptoglobin, identifying 136 N-linked glycopeptide spectra at a false discovery rate of 0.4%, representing 15 distinct glycopeptides on at least three of the four N-linked glycosylation sites. The software, GlycoPeptideSearch, is available for download from http://edwardslab.bmcb.georgetown.edu/GPS .

Automated assignments of N- and O-site specific glycosylation with extensive glycan heterogeneity of glycoprotein mixtures

Site-specific glycosylation (SSG) of glycoproteins remains a considerable challenge and limits further progress in the areas of proteomics and glycomics. Effective methods require new approaches in sample preparation, detection, and data analysis. While the field has advanced in sample preparation and detection, automated data analysis remains an important goal. A new bioinformatics approach implemented in software called GP Finder automatically distinguishes correct assignments from random matches and complements experimental techniques that are optimal for glycopeptides, including nonspecific proteolysis and high mass resolution liquid chromatography/tandem mass spectrometry (LC/MS/MS). SSG for multiple N- and O-glycosylation sites, including extensive glycan heterogeneity, was annotated for single proteins and protein mixtures with a 5% false-discovery rate, generating hundreds of nonrandom glycopeptide matches and demonstrating the proof-of-concept for a self-consistency scoring algorithm shown to be compliant with the target-decoy approach (TDA). The approach was further applied to a mixture of N-glycoproteins from unprocessed human milk and O-glycoproteins from very-low-density-lipoprotein (vLDL) particles.

GlycoPep Detector: a tool for assigning mass spectrometry data of N-linked glycopeptides on the basis of their electron transfer dissociation spectra

Electron transfer dissociation (ETD) is commonly used in fragmenting N-linked glycopeptides in their mass spectral analyses to complement collision-induced dissociation (CID) experiments. The glycan remains intact through ETD, while the peptide backbone is cleaved, providing the sequence of amino acids for a glycopeptide. Nonetheless, data analysis is a major bottleneck to high-throughput glycopeptide identification based on ETD data, due to the complexity and diversity of ETD mass spectra compared to CID counterparts. GlycoPep Detector (GPD) is a web-based tool to address this challenge. It filters out noise peaks that interfere with glycopeptide sequencing, correlates input glycopeptide compositions with the ETD spectra, and assigns a score for each candidate. By considering multiple ion series (c-, z-, and y-ions) and scoring them separately, the software gives more weighting to the ion series that matches peaks of high intensity in the spectra. This feature enables the correct glycopeptide to receive a high score while keeping scores of incorrect compositions low. GPD has been utilized to interpret data collected on six model glycoproteins (RNase B, avidin, fetuin, asialofetuin, transferrin, and AGP) as well as a clade C HIV envelope glycoprotein, C.97ZA012 gp140ΔCFI. In every assignment made by GPD, the correct glycopeptide composition earns a score that is about 2-fold higher than other incorrect glycopeptide candidates (decoys). The software can be accessed at http://glycopro.chem.ku.edu/ZZKHome.php .

Automated glycopeptide analysis--review of current state and future directions

Glycosylation of proteins is involved in immune defense, cell-cell adhesion, cellular recognition and pathogen binding and is one of the most common and complex post-translational modifications. Science is still struggling to assign detailed mechanisms and functions to this form of conjugation. Even the structural analysis of glycoproteins-glycoproteomics-remains in its infancy due to the scarcity of high-throughput analytical platforms capable of determining glycopeptide composition and structure, especially platforms for complex biological mixtures. Glycopeptide composition and structure can be determined with high mass-accuracy mass spectrometry, particularly when combined with chromatographic separation, but the sheer volume of generated data necessitates computational software for interpretation. This review discusses the current state of glycopeptide assignment software-advances made to date and issues that remain to be addressed. The various software and algorithms developed so far provide important insights into glycoproteomics. However, there is currently no freely available software that can analyze spectral data in batch and unambiguously determine glycopeptide compositions for N- and O-linked glycopeptides from relevant biological sources such as human milk and serum. Few programs are capable of aiding in structural determination of the glycan component. To significantly advance the field of glycoproteomics, analytical software and algorithms are required that: (i) solve for both N- and O-linked glycopeptide compositions, structures and glycosites in biological mixtures; (ii) are high-throughput and process data in batches; (iii) can interpret mass spectral data from a variety of sources and (iv) are open source and freely available.

GlycoPep grader: a web-based utility for assigning the composition of N-linked glycopeptides

GlycoPep grader (GPG) is a freely available software tool designed to accelerate the process of accurately determining glycopeptide composition from tandem mass spectrometric data. GPG relies on the identification of unique dissociation patterns shown for high mannose, hybrid, and complex N-linked glycoprotein types, including patterns specific to those structures containing fucose or sialic acid residues. The novel GPG scoring algorithm scores potential candidate compositions of the same nominal mass against MS/MS data through evaluation of the Y(1) ion and other peptide-containing product ions, across multiple charge states, when applicable. In addition to evaluating the peptide portion of a given glycopeptide, the GPG algorithm predicts and scores product ions that result from unique neutral losses of terminal glycans. GPG has been applied to a variety of glycoproteins, including RNase B, asialofetuin, and transferrin, and the HIV envelope glycoprotein, CON-S gp140ΔCFI. The GPG software is implemented predominantly in PostgreSQL, with PHP as the presentation tier, and is publicly accessible online. Thus far, the algorithm has identified the correct compositional assignment from multiple candidate N-glycopeptides in all tests performed.

Detection and characterization of low abundance glycopeptides via higher-energy C-trap dissociation and orbitrap mass analysis

Broad-scale mass spectrometric analyses of glycopeptides are constrained by the considerable complexity inherent to glycoproteomics, and techniques are still being actively developed to address the associated analytical difficulties. Here we apply Orbitrap mass analysis and higher-energy C-trap dissociation (HCD) to facilitate detailed insights into the compositions and heterogeneity of complex mixtures of low abundance glycopeptides. By generating diagnostic oxonium product ions at mass measurement errors of <5 ppm, highly selective glycopeptide precursor ion detections are made at sub-fmol limits of detection: analyses of proteolytic digests of a hen egg glycoprotein mixture detect 88 previously uncharacterized glycopeptides from 666 precursor ions selected for MS/MS, with only one false positive due to co-fragmentation of a non-glycosylated peptide with a glycopeptide. We also demonstrate that by (1) identifying multiple series of glycoforms using high mass accuracy single stage MS spectra, and (2) performing product ion scans at optimized HCD collision energies, the identification of peptide + N-acetylhexosamine (HexNAc) ions (Y1 ions) can be readily achieved at <5 ppm mass measurement errors. These data allow base peptide sequences and glycan compositional information to be attained with high confidence, even for glycopeptides that produce weak precursor ion signals and/or low quality MS/MS spectra. The glycopeptides characterized from low fmol abundances using these methods allow two previously unreported glycosylation sites on the Gallus gallus protein ovoglycoprotein (amino acids 82 and 90) to be confirmed; considerable glycan heterogeneities at amino acid 90 of ovoglycoprotein, and amino acids 34 and 77 of Gallus gallus ovomucoid are also revealed.

GlycoSpectrumScan: fishing glycopeptides from MS spectra of protease digests of human colostrum sIgA

With the emergence of glycoproteomics, there is a need to develop bioinformatic tools to identify glycopeptides in protease digests of glycoproteins. GlycoSpectrumScan is a web-based tool that identifies the glycoheterogeneity on a peptide from mass spectrometric data. Two experimental data sets are required as inputs: (1) oligosaccharide compositions of the N- and/or O-linked glycans present in the sample and (2) in silico derived peptide masses of proteolytically digested proteins with a potential number of N- and/or O-glycosylation sites. GlycoSpectrumScan uses MS data, rather than MS/MS data, to identify glycopeptides and determine the relative distribution of N- and O-glycoforms at each site. It is functional for assigning monosaccharide compositions on glycopeptides with single and multiple sites of glycosylation. The algorithm allows the input of raw mass data, including multiply charged ions, making it applicable for both ESI and MALDI data from all mass spectrometer platforms. Manual analysis time for identifying glycosylation heterogeneity at each site on glycoprotein(s) is substantially decreased. The application of this tool to characterize the N- and O-linked glycopeptides from human secretory IgA (sIgA), consisting of secretory component (7 N-linked sites), IgA1 (2 N-linked, <or=5 O-linked sites), IgA2 (4 N-linked sites) and J-chain (1 N-linked site) is described. GlycoSpectrumScan is freely available at www.glycospectrumscan.org .

Determination of glycosylation sites and site-specific heterogeneity in glycoproteins

Glycosylation is one of the most common post-translational modifications (PTMs) of proteins. At least 50% of human proteins are glycosylated with some estimates being as high as 70%. Glycoprotein analysis requires determining both the sites of glycosylation as well as the glycan structures associated with each site. Recent advances have led to the development of new analytical methods that employ mass spectrometry extensively making it possible to obtain the glycosylation site and the site microheterogeneity. These tools will be important for the eventual development of glycoproteomics.