GlycoFragment and GlycoSearchMS: web tools to support the interpretation of mass spectra of complex carbohydrates

Quality control, safety assessment and preparation approaches of low molecular weight heparin

Low Molecular Weight Heparins (LMWHs) are well-established for use in the prevention and treatment of thrombotic diseases, and as a substitute for unfractionated heparin (UFH) due to their predictable pharmacokinetics and subcutaneous bioavailability. LMWHs are produced by various depolymerization methods from UFH, resulting in heterogeneous compounds with similar biochemical and pharmacological properties. However, the delicate supply chain of UFH and potential contamination from animal sources require new manufacturing approaches for LMWHs. Various LMWH preparation methods are emerging, such as chemical synthesis, enzymatic or chemical depolymerization and chemoenzymatic synthesis. To establish the sameness of active ingredients in both innovator and generic LMWH products, the Food and Drug Administration has implemented a stringent scientific method of equivalence based on physicochemical properties, heparin source material and depolymerization techniques, disaccharide composition and oligosaccharide mapping, biological and biochemical properties, and in vivo pharmacodynamic profiles. In this review, we discuss currently available LMWHs, potential manufacturing methods, and recent progress for manufacturing quality control of these LMWHs.

A MATLAB-based app to improve LC-MS/MS data analysis for N-linked glycan peak identification

BACKGROUND

Glycosylation is an important modification to proteins that plays a significant role in biological processes. Glycan structures are characterized by liquid chromatography (LC) combined with mass spectrometry (MS), but data interpretation of LC/MS and MS/MS data can be time-consuming and arduous when analyzed manually. Most of glycan analysis requires dedicated glycobioinformatics tools to process MS data, identify glycan structure, and display the results. However, software tools currently available are either too costly or heavily focused on academic applications, limiting their use within the biopharmaceutical industry for implementing the standardized LC/MS glycan analysis in high-throughput manner. Additionally, few tools provide the capability to generate report-ready annotated MS/MS glycan spectra.

RESULTS

Here, we present a MATLAB-based app, GlyKAn AZ, which can automate data processing, glycan identification, and customizable result displays in a streamlined workflow. MS1 and MS2 mass search algorithms along with glycan databases were developed to confirm the fluorescent labeled N-linked glycan species based on accurate mass. A user-friendly graphical user interface (GUI) streamlines the data analysis process, making it easy to implement the software tool in biopharmaceutical analytical laboratories. The databases provided with the app can be expanded through the Fragment Generator functionality which automatically identifies fragmentation patterns for new glycans. The GlyKAn AZ app can automatically annotate the MS/MS spectra, yet this data display feature remains flexible and customizable by users, saving analysts' time in generating individual report-ready spectra figures. This app accepts both OrbiTrap and matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) MS data and was successfully validated by identifying all glycan species that were previously identified manually.

CONCLUSIONS

The GlyKAn AZ app was developed to expedite glycan analysis while maintaining a high level of accuracy in positive identifications. The app's customizable user inputs, polished figures and tables, and unique calculated outputs set it apart from similar software and greatly improve the current manual analysis workflow. Overall, this app serves as a tool for streamlining glycan identification for both academic and industrial needs.

MS-based glycomics and glycoproteomics methods enabling isomeric characterization

Glycosylation is one of the most significant and abundant posttranslational modifications in mammalian cells. It mediates a wide range of biofunctions, including cell adhesion, cell communication, immune cell trafficking, and protein stability. Also, aberrant glycosylation has been associated with various diseases such as diabetes, Alzheimer's disease, inflammation, immune deficiencies, congenital disorders, and cancers. The alterations in the distributions of glycan and glycopeptide isomers are involved in the development and progression of several human diseases. However, the microheterogeneity of glycosylation brings a great challenge to glycomic and glycoproteomic analysis, including the characterization of isomers. Over several decades, different methods and approaches have been developed to facilitate the characterization of glycan and glycopeptide isomers. Mass spectrometry (MS) has been a powerful tool utilized for glycomic and glycoproteomic isomeric analysis due to its high sensitivity and rich structural information using different fragmentation techniques. However, a comprehensive characterization of glycan and glycopeptide isomers remains a challenge when utilizing MS alone. Therefore, various separation methods, including liquid chromatography, capillary electrophoresis, and ion mobility, were developed to resolve glycan and glycopeptide isomers before MS. These separation techniques were coupled to MS for a better identification and quantitation of glycan and glycopeptide isomers. Additionally, bioinformatic tools are essential for the automated processing of glycan and glycopeptide isomeric data to facilitate isomeric studies in biological cohorts. Here in this review, we discuss commonly employed MS-based techniques, separation hyphenated MS methods, and software, facilitating the separation, identification, and quantitation of glycan and glycopeptide isomers.

GlycoDeNovo2: An Improved MS/MS-Based De Novo Glycan Topology Reconstruction Algorithm

Glycan structure identification is essential to understanding the roles of glycans in various biological processes. Previously, we developed GlycoDeNovo, a de novo algorithm for reconstructing glycan topologies from tandem mass spectra (MS/MS). In this work, we introduce GlycoDeNovo2 that contains two major improvements to GlycoDeNovo. First, we use the precursor mass measured for a peak that likely corresponds to a glycan to determine its potential compositions, which are used to constrain the search space, enable parallel computation, and hence speed up topology reconstruction. Second, we developed a procedure to calculate the empirical p-value of a reconstructed topology candidate. Experimental results are provided to demonstrate the effectiveness of GlycoDeNovo2.

Advances in mass spectrometry-based glycomics-An update covering the period 2017-2021

The wide variety of chemical properties and biological functions found in proteins is attained via post-translational modifications like glycosylation. Covalently bonded to proteins, glycans play a critical role in cell activity. Complex structures with microheterogeneity, the glycan structures that are associated with proteins are difficult to analyze comprehensively. Recent advances in sample preparation methods, separation techniques, and MS have facilitated the quantitation and structural elucidation of glycans. This review focuses on highlighting advances in MS-based techniques for glycomic analysis that occurred over the last 5 years (2017-2021) as an update to the previous review on the subject. The topics of discussion will include progress in glycomic workflow such as glycan release, purification, derivatization, and separation as well as the topics of ionization, tandem MS, and separation techniques that can be coupled with MS. Additionally, bioinformatics tools used for the analysis of glycans will be described.

Glycosylation Biomarkers Associated with Age-Related Diseases and Current Methods for Glycan Analysis

Ageing is a complex process which implies the accumulation of molecular, cellular and organ damage, leading to an increased vulnerability to disease. In Western societies, the increase in the elderly population, which is accompanied by ageing-associated pathologies such as cardiovascular and mental diseases, is becoming an increasing economic and social burden for governments. In order to prevent, treat and determine which subjects are more likely to develop these age-related diseases, predictive biomarkers are required. In this sense, some studies suggest that glycans have a potential role as disease biomarkers, as they modify the functions of proteins and take part in intra- and intercellular biological processes. As the glycome reflects the real-time status of these interactions, its characterisation can provide potential diagnostic and prognostic biomarkers for multifactorial diseases. This review gathers the alterations in protein glycosylation profiles that are associated with ageing and age-related diseases, such as cancer, type 2 diabetes mellitus, metabolic syndrome and several chronic inflammatory diseases. Furthermore, the review includes the available techniques for the determination and characterisation of glycans, such as liquid chromatography, electrophoresis, nuclear magnetic resonance and mass spectrometry.

GlycoHunter: An Open-Source Software for the Detection and Relative Quantification of INLIGHT-Labeled N-Linked Glycans

Glycans are responsible for many biological activities; however, their structures are incredibly diverse and complex, often rendering the field of glycomics unsolvable by a single analytical technique. The development of multiple chemical derivatization strategies and bioinformatic software is responsible for some of the greatest analytical gains in the field of glycomics. The INLIGHT strategy is a chemical derivatization technique using hydrazide chemistry to derivatize the reducing end of N-linked glycans and incorporates either a natural (NAT, ¹²C₆) or a stable-isotope label (SIL, ¹³C₆) to carry out relative quantification. Here we present GlycoHunter, a user-friendly software created in MATLAB that enables researchers to accurately and efficiently process MS1 glycomics data where a NAT and SIL pair is generated for relative quantification, including but not limited to, INLIGHT. GlycoHunter accepts the commonly used data file formats imzML and mzXML and effectively identifies all peak pairs associated with NAT- and SIL-labeled N-linked glycans using MS1 data. It also includes the ability to tailor the search parameters and export the results for further analysis using Skyline or Excel.

Insights into Bioinformatic Applications for Glycosylation: Instigating an Awakening towards Applying Glycoinformatic Resources for Cancer Diagnosis and Therapy

Glycosylation plays a crucial role in various diseases and their etiology. This has led to a clear understanding on the functions of carbohydrates in cell communication, which eventually will result in novel therapeutic approaches for treatment of various disease. Glycomics has now become one among the top ten technologies that will change the future. The direct implication of glycosylation as a hallmark of cancer and for cancer therapy is well established. As in proteomics, where bioinformatics tools have led to revolutionary achievements, bioinformatics resources for glycosylation have improved its practical implication. Bioinformatics tools, algorithms and databases are a mandatory requirement to manage and successfully analyze large amount of glycobiological data generated from glycosylation studies. This review consolidates all the available tools and their applications in glycosylation research. The achievements made through the use of bioinformatics into glycosylation studies are also presented. The importance of glycosylation in cancer diagnosis and therapy is discussed and the gap in the application of widely available glyco-informatic tools for cancer research is highlighted. This review is expected to bring an awakening amongst glyco-informaticians as well as cancer biologists to bridge this gap, to exploit the available glyco-informatic tools for cancer.

GRITS Toolbox-a freely available software for processing, annotating and archiving glycomics mass spectrometry data

Mass spectrometry (MS) is one of the most effective techniques for high-throughput, high-resolution characterization of glycan structures. Although many software applications have been developed over the last decades for the interpretation of MS data of glycan structures, only a few are capable of dealing with the large data sets produced by glycomics analysis. Furthermore, these applications utilize databases that can lead to redundant glycan annotations and do not support post-processing of the data within the software or by third party applications. To address the needs, we present GRITS Toolbox, a freely-available, platform-independent software application capable of storing and processing glycomics MS data along with associated metadata. GRITS Toolbox automatically annotates MS data using an integrated glycan identification module that references manually curated databases of mammalian glycans (provided with the software) or any user-defined databases. Extensive display routines are provided to post-process the data and refine the automated annotation using expert knowledge of the user. The software also allows side by side comparison of annotations from different MS runs or samples and exporting of annotations into Excel format.

Toward Automatic and Comprehensive Glycan Characterization by Online PGC-LC-EED MS/MS

Despite the recent advances in mass spectrometry (MS)-based methods for glycan structural analysis, characterization of glycomes remains a significant analytical challenge, in part due to the widespread presence of isomeric structures and the need to define the many structural variables for each glycan. Interpretation of the complex tandem mass spectra of glycans is often laborious and requires substantial expertise. Broad adoption of MS methods for glycomics, within and outside the glycoscience community, has been hindered by the shortage of bioinformatics tools for rapid and accurate glycan sequencing. Here, we developed an online porous graphitic carbon liquid chromatography (PGC-LC)-electronic excitation dissociation (EED) MS/MS method that takes advantage of the superior isomer resolving power of PGC and the structural details provided by EED MS/MS for characterization of glycan mixtures. We also made improvements to GlycoDeNovo, our de novo glycan sequencing algorithm, so that it can automatically and accurately identify glycan topologies from EED tandem mass spectra acquired online. The majority of linkages can also be determined de novo, although in some cases, biological insight may be needed to fully define the glycan structure. Application of this method to the analysis of N-glycans released from ribonuclease B not only revealed the presence of 18 high-mannose structures, including new isomers not previously reported, but also provided relative quantification for each isomeric structure. With fully automated data acquisition and topology analysis, the approach presented here holds great potential for automated and comprehensive glycan characterization.

An approach for N-linked glycan identification from MS/MS spectra by target-decoy strategy

Glycan structure determination serves as an essential step for the thorough investigation of the structure and function of protein. Currently, appropriate sample preparation followed by tandem mass spectrometry has emerged as the dominant technique for the characterization of glycans and glycopeptides. Although extensive efforts have been made to the development of computational approaches for the automated interpretation of glycopeptide spectra, the previously appeared methods lack a reasonable quality control strategy for the statistical validation of reported results. In this manuscript, we introduced a novel method that constructed a decoy glycan database based on the glycan structures in the target database, and searched the experimental spectra against both the target and decoy databases to find the best matched glycans. Specifically, a two-layer scoring scheme for calculating a normalized matching score is applied in the search procedure which enables the unbiased ranking of the matched glycans. Experimental analysis showed that our proposed method can report more structures with high confidence compared with previous approaches.

Large-scale identification and visualization of N-glycans with primary structures using GlySeeker

RATIONALE

Most of the current popular tandem mass spectrometers have the capability of resolving the primary structures (monosaccharide composition, sequence and linkage) of N-glycans; however, compositions or putative structures have mostly been reported so far. Identification and visualization tools of N-glycans are needed.

METHODS

The isotopic mass-to-charge ratio and envelope fingerprinting algorithm, which has been successfully used for intact protein database search and identification, was adapted for N-glycan database search, and a stand-alone N-glycan database search engine, GlySeeker, for automated N-glycan identification and visualization was developed and successfully benchmarked. Both pseudo 2D graph and one-line text formats with one-letter symbols for monosaccharides were proposed for representing N-glycans. N-glycans were identified with comprehensive interpretation of product ions and false discovery rate (FDR) control.

RESULTS

In a database search of reversed-phase liquid chromatography/tandem mass spectrometry (RPLC/MS/MS) datasets of the N-glycome enriched from OVCAR-3 ovarian cancer cells, with FDR ≤1% and number of best hits (NoBHs) = 1-30, 1525 N-glycans with comprehensive primary structural information (composition, sequence and linkage) were identified and visualized; among these 1525 N-glycans, 559 had NoBHs = 1, i.e. their structures were uniquely identified. This represents a large-scale identification and visualization of N-glycans with primary structures from tandem mass spectra.

CONCLUSIONS

A stand-alone N-glycan database search engine called GlySeeker has been developed for large-scale identification and visualization of N-glycans with comprehensive interpretation of tandem mass spectra and FDR control.

GlycoDeNovo - an Efficient Algorithm for Accurate de novo Glycan Topology Reconstruction from Tandem Mass Spectra

A major challenge in glycomics is the characterization of complex glycan structures that are essential for understanding their diverse roles in many biological processes. We present a novel efficient computational approach, named GlycoDeNovo, for accurate elucidation of the glycan topologies from their tandem mass spectra. Given a spectrum, GlycoDeNovo first builds an interpretation-graph specifying how to interpret each peak using preceding interpreted peaks. It then reconstructs the topologies of peaks that contribute to interpreting the precursor ion. We theoretically prove that GlycoDeNovo is highly efficient. A major innovative feature added to GlycoDeNovo is a data-driven IonClassifier which can be used to effectively rank candidate topologies. IonClassifier is automatically learned from experimental spectra of known glycans to distinguish B- and C-type ions from all other ion types. Our results showed that GlycoDeNovo is robust and accurate for topology reconstruction of glycans from their tandem mass spectra. Graphical Abstract ᅟ.

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.

An Effective Approach for Glycan Structure De Novo Sequencing From HCD Spectra

Mass spectrometry has become a widely used analytical technique for proteomics study because of its high throughput and sensitivity. Among those applications, a specific one is to characterize glycan structure. Glycosylation is a frequently occurred post-translational modification of proteins which is relevant to humans' health. Therefore, it is significant to develop effective computational methods to automate the identification of glycan structures from mass spectral data. In our research, we mathematically formulated the glycan de novo sequencing problem and proposed a heuristic algorithm for glycan de novo sequencing from HCD MS/MS spectra of N-linked glycopeptides. The algorithm proceeds in a carefully designate pathway to construct the best matched tree structure from MS/MS spectrum. Experimental results showed that our proposed approach can effectively identify glycan structures from HCD MS/MS spectra.

A Machine Learning Based Approach to de novo Sequencing of Glycans from Tandem Mass Spectrometry Spectrum

Recently, glycomics has been actively studied and various technologies for glycomics have been rapidly developed. Currently, tandem mass spectrometry (MS/MS) is one of the key experimental tools for identification of structures of oligosaccharides. MS/MS can observe MS/MS peaks of fragmented glycan ions including cross-ring ions resulting from internal cleavages, which provide valuable information to infer glycan structures. Thus, the aim of de novo sequencing of glycans is to find the most probable assignments of observed MS/MS peaks to glycan substructures without databases. However, there are few satisfiable algorithms for glycan de novo sequencing from MS/MS spectra. We present a machine learning based approach to de novo sequencing of glycans from MS/MS spectrum. First, we build a suitable model for the fragmentation of glycans including cross-ring ions, and implement a solver that employs Lagrangian relaxation with a dynamic programming technique. Then, to optimize scores for the algorithm, we introduce a machine learning technique called structured support vector machines that enable us to learn parameters including scores for cross-ring ions from training data, i.e., known glycan mass spectra. Furthermore, we implement additional constraints for core structures of well-known glycan types including N-linked glycans and O-linked glycans. This enables us to predict more accurate glycan structures if the glycan type of given spectra is known. Computational experiments show that our algorithm performs accurate de novo sequencing of glycans. The implementation of our algorithm and the datasets are available at http://glyfon.dna.bio.keio.ac.jp/.

An Accurate de novo Algorithm for Glycan Topology Determination from Mass Spectra

Determining the glycan topology automatically from mass spectra represents a great challenge. Existing methods fall into approximate and exact ones. The former including greedy and heuristic ones can reduce the computational complexity, but suffer from information lost in the procedure of glycan interpretation. The latter including dynamic programming and exhaustive enumeration are much slower than the former. In the past years, nearly all emerging methods adopted a tree structure to represent a glycan. They share such problems as repetitive peak counting in reconstructing a candidate structure. Besides, tree-based glycan representation methods often have to give different computational formulas for binary and ternary glycans. We propose a new directed acyclic graph structure for glycan representation. Based on it, this work develops a de novo algorithm to accurately reconstruct the tree structure iteratively from mass spectra with logical constraints and some known biosynthesis rules, by a single computational formula. The experiments on multiple complex glycans extracted from human serum show that the proposed algorithm can achieve higher accuracy to determine a glycan topology than prior methods without increasing computational burden.

High-Throughput Analysis and Automation for Glycomics Studies

This review covers advances in analytical technologies for high-throughput (HTP) glycomics. Our focus is on structural studies of glycoprotein glycosylation to support biopharmaceutical realization and the discovery of glycan biomarkers for human disease. For biopharmaceuticals, there is increasing use of glycomics in Quality by Design studies to help optimize glycan profiles of drugs with a view to improving their clinical performance. Glycomics is also used in comparability studies to ensure consistency of glycosylation both throughout product development and between biosimilars and innovator drugs. In clinical studies there is as well an expanding interest in the use of glycomics—for example in Genome Wide Association Studies—to follow changes in glycosylation patterns of biological tissues and fluids with the progress of certain diseases. These include cancers, neurodegenerative disorders and inflammatory conditions. Despite rising activity in this field, there are significant challenges in performing large scale glycomics studies. The requirement is accurate identification and quantitation of individual glycan structures. However, glycoconjugate samples are often very complex and heterogeneous and contain many diverse branched glycan structures. In this article we cover HTP sample preparation and derivatization methods, sample purification, robotization, optimized glycan profiling by UHPLC, MS and multiplexed CE, as well as hyphenated techniques and automated data analysis tools. Throughout, we summarize the advantages and challenges with each of these technologies. The issues considered include reliability of the methods for glycan identification and quantitation, sample throughput, labor intensity, and affordability for large sample numbers.

GlycoMaster DB: software to assist the automated identification of N-linked glycopeptides by tandem mass spectrometry

Glycosylation is one of the most commonly observed post-translational modifications (PTMs) in eukaryotes. It is believed that more than 50% eukaryotic proteins are glycosylated. To reveal the biological functions of protein-linked glycans involved in numerous biological processes, the high-throughput identification of both glycoproteins and the attached glycan structures becomes fundamentally important. Tandem mass spectrometry (MS/MS) is an effective method for glycoproteomic analysis because of its high sensitivity and selectivity. Two experimental approaches exist to obtain MS/MS spectral data of glycopeptides. One consists of isolating glycans from glycopeptides and generating MS/MS spectra of the glycans and peptides separately. The other approach produces spectra directly from intact glycopeptides. The latter approach has the advantage of retaining the glycosylation site information. However, the spectral data cannot be readily analyzed because of the lack of software specifically designed for the identification of intact glycopeptides. To address this need, we developed a novel software tool, GlycoMaster DB, to assist the automated and high-throughput identification of intact N-linked glycopeptides from MS/MS spectra. The software simultaneously searches a protein sequence database and a glycan structure database to find the best pair of peptide and glycan for each input spectrum. GlycoMaster DB can analyze mass spectral data produced with HCD/ETD mixed fragmentation, where HCD spectra are used to identify glycans and ETD spectra are used to determine peptide sequences. When only HCD spectra are available, GlycoMaster DB can still help to identify the glycans, and a list of possible peptide sequences are reported according to the accurate precursor mass and the N-linked glycopeptide sequon. GlycoMaster DB is freely accessible at http://www-novo.cs.uwaterloo.ca:8080/GlycoMasterDB .

Characterization of intact N- and O-linked glycopeptides using higher energy collisional dissociation

Simultaneous elucidation of the glycan structure and the glycosylation site are needed to reveal the biological function of protein glycosylation. In this study, we employed a recent type of fragmentation termed higher energy collisional dissociation (HCD) to examine fragmentation patterns of intact glycopeptides generated from a mixture of standard glycosylated proteins. The normalized collisional energy (NCE) value for HCD was varied from 30 to 60% to evaluate the optimal conditions for the fragmentation of peptide backbones and glycoconjugates. Our results indicated that HCD with lower NCE values preferentially fragmented the sugar chains attached to the peptides to generate a ladder of neutral loss of monosaccharides, thereby enabling the putative glycan structure characterization. In addition, detection of the oxonium ions enabled unambiguous differentiation of glycopeptides from non-glycopeptides. In contrast, HCD with higher NCE values preferentially fragmented the peptide backbone and, thus, provided information needed for confident peptide identification. We evaluated the HCD approach with alternating NCE parameters for confident characterization of intact N- and O-linked glycopeptides in a single liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. In addition, we applied a novel data analysis pipeline, so-called GlycoFinder, to form a basis for automated data analysis. Overall, 38 unique intact glycopeptides corresponding to eight glycosylation sites (six N-linked and two O-linked sites) were confidently identified from a standard protein mixture. This approach provided concurrent characterization of both the peptide and the glycan, thereby enabling comprehensive structural characterization of glycoproteins in a single LC-MS/MS analysis.

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.

Electron capture dissociation of divalent metal-adducted sulfated N-glycans released from bovine thyroid stimulating hormone

Sulfated N-glycans released from bovine thyroid stimulating hormone (bTSH) were ionized with the divalent metal cations Ca(2+), Mg(2+), and Co by electrospray ionization (ESI). These metal-adducted species were subjected to infrared multiphoton dissociation (IRMPD) and electron capture dissociation (ECD) and the corresponding fragmentation patterns were compared. IRMPD generated extensive glycosidic and cross-ring cleavages, but most product ions suffered from sulfonate loss. Internal fragments were also observed, which complicated the spectra. ECD provided complementary structural information compared with IRMPD, and all observed product ions retained the sulfonate group, allowing sulfonate localization. To our knowledge, this work represents the first application of ECD towards metal-adducted sulfated N-glycans released from a glycoprotein. Due to the ability of IRMPD and ECD to provide complementary structural information, the combination of the two strategies is a promising and valuable tool for glycan structural characterization. The influence of different metal ions was also examined. Calcium adducts appeared to be the most promising species because of high sensitivity and ability to provide extensive structural information.

Structural feature ions for distinguishing N- and O-linked glycan isomers by LC-ESI-IT MS/MS

Glycomics is the comprehensive study of glycan expression in an organism, cell, or tissue that relies on effective analytical technologies to understand glycan structure-function relationships. Owing to the macro- and micro-heterogeneity of oligosaccharides, detailed structure characterization has required an orthogonal approach, such as a combination of specific exoglycosidase digestions, LC-MS/MS, and the development of bioinformatic resources to comprehensively profile a complex biological sample. Liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS/MS) has emerged as a key tool in the structural analysis of oligosaccharides because of its high sensitivity, resolution, and robustness. Here, we present a strategy that uses LC-ESI-MS/MS to characterize over 200 N- and O-glycans from human saliva glycoproteins, complemented by sequential exoglycosidase treatment, to further verify the annotated glycan structures. Fragment-specific substructure diagnostic ions were collated from an extensive screen of the literature available on the detailed structural characterization of oligosaccharides and, together with other specific glycan structure feature ions derived from cross-ring and glycosidic-linkage fragmentation, were used to characterize the glycans and differentiate isomers. The availability of such annotated mass spectrometric fragmentation spectral libraries of glycan structures, together with such substructure diagnostic ions, will be key inputs for the future development of the automated elucidation of oligosaccharide structures from MS/MS data.

Validation of the curation pipeline of UniCarb-DB: building a global glycan reference MS/MS repository

The UniCarb-DB database is an emerging public glycomics data repository, containing over 500 tandem mass spectra (as of March 2013) of glycans released from glycoproteins. A major challenge in glycomics research is to provide and maintain high-quality datasets that will offer the necessary diversity to support the development of accurate bioinformatics tools for data deposition and analysis. The role of UniCarb-DB, as an archival database, is to provide the glycomics community with open-access to a comprehensive LC MS/MS library of N- and O- linked glycans released from glycoproteins that have been annotated with glycosidic and cross-ring fragmentation ions, retention times, and associated experimental metadata descriptions. Here, we introduce the UniCarb-DB data submission pipeline and its practical application to construct a library of LC-MS/MS glycan standards that forms part of this database. In this context, an independent consortium of three laboratories was established to analyze the same 23 commercially available oligosaccharide standards, all by using graphitized carbon-liquid chromatography (LC) electrospray ionization (ESI) ion trap mass spectrometry in the negative ion mode. A dot product score was calculated for each spectrum in the three sets of data as a measure of the comparability that is necessary for use of such a collection in library-based spectral matching and glycan structural identification. The effects of charge state, de-isotoping and threshold levels on the quality of the input data are shown. The provision of well-characterized oligosaccharide fragmentation data provides the opportunity to identify determinants of specific glycan structures, and will contribute to the confidence level of algorithms that assign glycan structures to experimental MS/MS spectra. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

The glycolyzer: automated glycan annotation software for high performance mass spectrometry and its application to ovarian cancer glycan biomarker discovery

Human serum glycomics is a promising method for finding cancer biomarkers but often lacks the tools for streamlined data analysis. The Glycolyzer software incorporates a suite of analytic tools capable of identifying informative glycan peaks out of raw mass spectrometry data. As a demonstration of its utility, the program was used to identify putative biomarkers for epithelial ovarian cancer from a human serum sample set. A randomized, blocked, and blinded experimental design was used on a discovery set consisting of 46 cases and 48 controls. Retrosynthetic glycan libraries were used for data analysis and several significant candidate glycan biomarkers were discovered via hypothesis testing. The significant glycans were attributed to a glycan family based on glycan composition relationships and incorporated into a linear classifier motif test. The motif test was then applied to the discovery set to evaluate the disease state discrimination performance. The test provided strongly predictive results based on receiver operator characteristic curve analysis. The area under the receiver operator characteristic curve was 0.93. Using the Glycolyzer software, we were able to identify a set of glycan biomarkers that highly discriminate between cases and controls, and are ready to be formally validated in subsequent studies.

Electron detachment dissociation of underivatized chloride-adducted oligosaccharides

Chloride anion attachment has previously been shown to aid determination of saccharide anomeric configuration and generation of linkage information in negative ion post-source decay MALDI tandem mass spectrometry. Here, we employ electron detachment dissociation (EDD) and collision activated dissociation (CAD) for the structural characterization of underivatized oligosaccharides bearing a chloride ion adduct. Both neutral and sialylated oligosaccharides are examined, including maltoheptaose, an asialo biantennary glycan (NA2), disialylacto-N-tetraose (DSLNT), and two LS tetrasaccharides (LSTa and LSTb). Gas-phase chloride-adducted species are generated by negative ion mode electrospray ionization. EDD and CAD spectra of chloride-adducted oligosaccharides are compared to the corresponding spectra for doubly deprotonated species not containing a chloride anion to assess the role of chloride adduction in the stimulation of alternative fragmentation pathways and altered charge locations allowing detection of additional product ions. In all cases, EDD of singly chloridated and singly deprotonated species resulted in an increase in observed cross-ring cleavages, which are essential to providing saccharide linkage information. Glycosidic cleavages also increased in EDD of chloride-adducted oligosaccharides to reveal complementary structural information compared to traditional (non-chloride-assisted) EDD and CAD. Results indicate that chloride adduction is of interest in alternative anion activation methods such as EDD for oligosaccharide structural characterization.

Employment of tandem mass spectrometry for the accurate and specific identification of oligosaccharide structures

A method is described for the rapid identification of oligosaccharides employing a library of tandem MS spectra. Identification is aided by software that compares the sample tandem MS to those in the library. The method incorporates quadrupole time-of-flight mass spectrometry along with an annotated oligosaccharide (OS) structure library and the MassHunter Personal Compound Database and Library (PCDL) software. With an automated spectra search, OS structures in different samples are readily identified. This method is shown to be useful in the study of milk oligosaccharides but can be readily applied to oligosaccharide pools in other biological tissues.

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.

The use of glycoinformatics in glycochemistry

Glycoinformatics is a small but growing branch of bioinformatics and chemoinformatics. Various resources are now available that can be of use to glycobiologists, but also to chemists who work on the synthesis or analysis of carbohydrates. This article gives an overview of existing glyco-specific databases and tools, with a focus on their application to glycochemistry: Databases can provide information on candidate glycan structures for synthesis, or on glyco-enzymes that can be used to synthesize carbohydrates. Statistical analyses of glycan databases help to plan glycan synthesis experiments. 3D-Structural data of protein-carbohydrate complexes are used in targeted drug design, and tools to support glycan structure analysis aid with quality control. Specific problems of glycoinformatics compared to bioinformatics for genomics or proteomics, especially concerning integration and long-term maintenance of the existing glycan databases, are also discussed.

Harnessing glycomics technologies: integrating structure with function for glycan characterization

Glycans, or complex carbohydrates, are a ubiquitous class of biological molecule which impinge on a variety of physiological processes ranging from signal transduction to tissue development and microbial pathogenesis. In comparison to DNA and proteins, glycans present unique challenges to the study of their structure and function owing to their complex and heterogeneous structures and the dominant role played by multivalency in their sequence-specific biological interactions. Arising from these challenges, there is a need to integrate information from multiple complementary methods to decode structure-function relationships. Focusing on acidic glycans, we describe here key glycomics technologies for characterizing their structural attributes, including linkage, modifications, and topology, as well as for elucidating their role in biological processes. Two cases studies, one involving sialylated branched glycans and the other sulfated glycosaminoglycans, are used to highlight how integration of orthogonal information from diverse datasets enables rapid convergence of glycan characterization for development of robust structure-function relationships.

Electron detachment dissociation of fluorescently labeled sialylated oligosaccharides

We explored the application of electron detachment dissociation (EDD) and infrared multiphoton dissociation (IRMPD) tandem mass spectrometry to fluorescently labeled sialylated oligosaccharides. Standard sialylated oligosaccharides and a sialylated N-linked glycan released from human transferrin were investigated. EDD yielded extensive glycosidic cleavages and cross-ring cleavages in all cases studied, consistently providing complementary structural information compared with infrared multiphoton dissociation. Neutral losses and satellite ions such as C-2H ions were also observed following EDD. In addition, we examined the influence of different fluorescent labels. The acidic label 2-aminobenzoic acid (2-AA) enhanced signal abundance in negative-ion mode. However, few cross-ring fragments were observed for 2-AA-labeled oligosaccharides. The neutral label 2-aminobenzamide (2-AB) resulted in more cross-ring cleavages compared with 2-AA-labeled species, but not as extensive fragmentation as for native oligosaccharides, likely resulting from altered negative charge locations from introduction of the fluorescent tag.

Structure elucidation of native N- and O-linked glycans by tandem mass spectrometry (tutorial)

Oligosaccharides play important roles in many biological processes. However, the structural elucidation of oligosaccharides remains a major challenge due to the complexities of their structures. Mass spectrometry provides a powerful method for determining oligosaccharide composition. Tandem mass spectrometry (MS) provides structural information with high sensitivity. Oligosaccharide structures differ from other polymers such as peptides because of the large number of linkage combinations and branching. This complexity makes the analysis of oligosaccharide unique from that of peptides. This tutorial addresses the issue of spectral interpretation of tandem MS under conditions of collision-induced dissociation (CID) and infrared multiphoton dissociation (IRMPD). The proper interpretation of tandem MS data can provide important structural information on different types of oligosaccharides including O- and N-linked.

Determination of glycan structure from tandem mass spectra

Glycans are molecules made from simple sugars that form complex tree structures. Glycans constitute one of the most important protein modifications and identification of glycans remains a pressing problem in biology. Unfortunately, the structure of glycans is hard to predict from the genome sequence of an organism. In this paper, we consider the problem of deriving the topology of a glycan solely from tandem mass spectrometry (MS) data. We study, how to generate glycan tree candidates that sufficiently match the sample mass spectrum, avoiding the combinatorial explosion of glycan structures. Unfortunately, the resulting problem is known to be computationally hard. We present an efficient exact algorithm for this problem based on fixed-parameter algorithmics that can process a spectrum in a matter of seconds. We also report some preliminary results of our method on experimental data, combining it with a preliminary candidate evaluation scheme. We show that our approach is fast in applications, and that we can reach very well de novo identification results. Finally, we show how to count the number of glycan topologies for a fixed size or a fixed mass. We generalize this result to count the number of (labeled) trees with bounded out degree, improving on results obtained using Pólya's enumeration theorem.

Bioinformatics and molecular modeling in glycobiology

The field of glycobiology is concerned with the study of the structure, properties, and biological functions of the family of biomolecules called carbohydrates. Bioinformatics for glycobiology is a particularly challenging field, because carbohydrates exhibit a high structural diversity and their chains are often branched. Significant improvements in experimental analytical methods over recent years have led to a tremendous increase in the amount of carbohydrate structure data generated. Consequently, the availability of databases and tools to store, retrieve and analyze these data in an efficient way is of fundamental importance to progress in glycobiology. In this review, the various graphical representations and sequence formats of carbohydrates are introduced, and an overview of newly developed databases, the latest developments in sequence alignment and data mining, and tools to support experimental glycan analysis are presented. Finally, the field of structural glycoinformatics and molecular modeling of carbohydrates, glycoproteins, and protein-carbohydrate interaction are reviewed.

Software utilities for the interpretation of mass spectrometric data of glycoconjugates: application to glycosphingolipids of human serum

Glycosphingolipids (GSLs) are major components of the outer leaflet of the cell membrane. These lipids are involved in many cell surface events and show disease-related expression changes. GSLs could thus serve as useful targets for biomarker discovery. The GSL structure is characterized by two entities: a hydrophilic glycan and a hydrophobic ceramide moiety. Both components exhibit numerous structural variations, the combination of which results in a large diversity of GSL structures that can potentially exist. Mass spectrometry (MS) is a powerful tool for high-throughput analysis of GSL expression analysis and structural elucidation. Yet, the assignment of GSL structures using MS data is tedious and demands highly specialized expertise. SysBioWare, a software platform developed for MS data evaluation in glycomics, was here applied for the MS analysis of human serum GSLs. The program was tuned to provide automated compositional assignment, supporting a variety of glycan and ceramide structures. Upon in silico fragmentation, the masses of predicted ions arising from cleavages in the glycan as well as the ceramide moiety were calculated, thus enabling structural characterization of both entities. Validation of proposed structures was achieved by matching in silico calculated fragment ions with those of experimental MS/MS data. These results indicate that SysBioWare can facilitate data interpretation and, furthermore, help the user to deal with large sets of data by supporting management of MS and non-MS data. SysBioWare has the potential to be a powerful tool for high-throughput glycosphingolipidomics in clinical applications.

Strategies for analysis of the glycosylation of proteins: current status and future perspectives

More than half of human proteins are glycosylated by a bewildering array of complex and heterogeneous N- and O-linked glycans. They function in myriad biological processes, including cell adhesion and signalling and influence the physical characteristics, stability, function, activity and immunogenicity of soluble glycoproteins. A single protein may be glycosylated differently to yield heterogenous glycoforms. Glycosylation analysis is of increasing interest in biomedical and biological research, the pharmaceutical and healthcare industry and biotechnology. This is because it is increasingly apparent that glycosylation changes in diseases, such as cancer, making it a promising target for development of clinically useful biomarkers and therapeutics. Furthermore, as the non-human cells employed in expression systems glycosylate their proteins very differently to human cells, and as glycosylation changes unpredictably under changing environmental conditions, glycans analysis for quality control, optimum efficacy and safety of recombinant glycoproteins destined for human therapeutic use is paramount. The complexities of carbohydrate chemistry make analysis challenging and while there are a variety of robust methodologies available for glycan analysis, there is currently a pressing need for the development of new, streamlined, high throughput approaches accessible to non-specialist laboratories.

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

The aim of our study is to automatically analyze the glycan and peptide structures of N-glycopeptides without a need to release glycans from the glycopeptides. Our wet laboratory raw data represent a series of MS/MS mass spectra obtained from a reverse-phase liquid chromatography run of size-exclusion-enriched tryptic-digested glycopeptides from glycoproteins. The MS/MS spectra are first analyzed in order to identify glycosylated peptides and N-glycan monosaccharide compositions present on each glycopeptide. We further developed a Branch-and-Bound algorithm to search de novo N-glycan structures, i.e., monosaccharide compositions and their ordered sequences from native glycopeptides. Our de novo algorithm is based on iterative growth and selection of a population of glycan structures and it does not use databases of known glycan structures. We validate the algorithm with (i) in silico-generated spectra, with or without deteriorating deletions, (ii) with a purified glycoprotein transferrin, and (iii) with a complex mixture of N-glycopeptides enriched from human plasma. Our Branch-and-Bound algorithm depicted glycan structures from all the above-mentioned three input data types. Due to the large diversity of glycan structures, the results typically contained several proposed structures matching almost equally well to the spectra. In conclusion, this algorithm automatically identifies glycopeptides and their structures from the MS/MS spectra and thus greatly reduces the number of possible glycan structures from the vast amount of potential ones.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2003-2004

This review is the third update of the original review, published in 1999, on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings the topic to the end of 2004. Both fundamental studies and applications are covered. The main topics include methodological developments, matrices, fragmentation of carbohydrates and applications to large polymeric carbohydrates from plants, glycans from glycoproteins and those from various glycolipids. Other topics include the use of MALDI MS to study enzymes related to carbohydrate biosynthesis and degradation, its use in industrial processes, particularly biopharmaceuticals and its use to monitor products of chemical synthesis where glycodendrimers and carbohydrate-protein complexes are highlighted.

Glycan family analysis for deducing N-glycan topology from single MS

MOTIVATION

In the past few years, mass spectrometry (MS) has emerged as the premier tool for identification and quantification of biological molecules such as peptides and glycans. There are two basic strategies: single-MS, which uses a single round of mass analysis, and MS/MS (or higher order MS(n)), which adds one or more additional rounds of mass analysis, interspersed with fragmentation steps. Single-MS offers higher throughput, broader mass coverage and more direct quantitation, but generally much weaker identification. Single-MS, however, does work fairly well for the case of N-glycan identification, which are more constrained than other biological polymers. We previously demonstrated single-MS identification of N-glycans to the level of 'cartoons' (monosaccharide composition and topology) by a system that incorporates an expert's detailed knowledge of the biological sample. In this article, we explore the possibility of ab initio single-MS N-glycan identification, with the goal of extending single-MS, or primarily-single-MS, identification to non-expert users, novel conditions and unstudied tissues.

RESULTS

We propose and test three cartoon-assignment algorithms that make inferences informed by biological knowledge about glycan synthesis. To test the algorithms, we used 71 single-MS spectra from a variety of tissues and organisms, containing more than 2800 manually annotated peaks. The most successful of the algorithms computes the most richly connected subgraph within a 'cartoon graph'. This algorithm uniquely assigns the correct cartoon to more than half of the peaks in 41 out of the 71 spectra.

A computational approach to characterizing bond linkages of glycan isomers using matrix-assisted laser desorption/ionization tandem time-of-flight mass spectrometry

Glycans commonly exhibit variations in their branching structures and glycosidic bond linkages, in addition to their sequence variation. These glycan features are known to be highly correlated with their biological functions. It is relatively straightforward to deduce the composition and sequence of monosaccharides of a glycan from its tandem mass spectra. However, the characterization of the linkage types of each glycosidic bond is still analytically challenging. In this paper, we present a rank-based discriminative model to differentiate between two types of glycosidic linkages (namely, 1-4 and 1-6) based on the cross-ring fragmentation patterns of the corresponding glycans observed under high-energy collision-induced dissociation (CID). To train our models, we acquired tandem mass spectra for three groups of both native and permethylated linear oligoglucoses using a matrix-assisted laser desorption/ionization tandem time-of-flight (MALDI/TOF/TOF) instrument. Based on a 5-fold cross-validation, the prediction accuracies of our model for native glycans are determined to be about 88.4% and 92.9% for 1-6 and 1-4 linkages, respectively. The accuracies determined for permethylated glycans are slightly lower, but comparable: 85.6% and 89.0% for 1-6 and 1-4 linkages, respectively. Our method is implemented as a web-hosted utility, thus making it readily accessible to the public which can be accessed through http://ggdb.informatics.indiana.edu:8080/glycanview.

Characterizing the glycome of the mammalian immune system

The outermost layer of all immune cells, the glycocalyx, is composed of a complex mixture of glycoproteins, glycolipids and lectins, which specifically recognize particular glycan epitopes. As the glycocalyx is the cell's primary interface with the external environment many biologically significant events can be attributed to glycan recognition. For this reason the rapidly expanding glycomics field is being increasingly recognized as an important component in our quest to better understand the functioning of the immune system. In this review, we highlight the current status of immune cell glycomics, with particular attention being paid to T- and B-lymphocytes and dendritic cells. We also describe the strategies and methodologies used to define immune cell glycomes.