STAT: a saccharide topology analysis tool used in combination with tandem mass spectrometry

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.

Identification of glycan branching patterns using multistage mass spectrometry with spectra tree analysis

Glycans are crucial to a wide range of biological processes, and their biological activities are closely related to the branching patterns of structures. Different from the simple linear chains of proteins, branching patterns of glycans are more complicated, making their identification extremely challenging. Tandem mass spectrometry (MS²) cannot provide sufficient structural information to deduce glycan branching patterns even with the assistance of various bioinformatic tools and algorithms.The promising technology to identify glycan branching patterns is multi-stage mass spectrometry (MSⁿ). The production-relationship among MSⁿ spectra of a glycan is essentially a tree, making deducing glycan structures from MSⁿ spectra a great challenge. In the present study, we report an approach called glyBranch (glycan Branching pattern identification based on spectra tree) to fully exploit the information contained in the MSⁿ spectra tree for glycan identification. Using 14 glycan standards, including 2 pairs with isomeric sequence, and 16 complex N-glycans isolated from RNase B and IgG, we demonstrated the successful application of glyBranch to branching pattern analysis. The source code of glyBranch is available at https://github.com/bigict/glyBranch/. We have also developed a web-server, which is freely accessible at http://glycan.ict.ac.cn/glyBranch/. SIGNIFICANCE: Glycans are crucial in various biological processes and their functions are closely related to the details of their structures; thus, the identification of glycan branching patterns is of great significance to biological studies. Multistage mass spectrometry (MSⁿ) can provide detailed structural information by generating multiple-level fragments through consecutive fragmentation; however, the interpretation of numerous MSⁿ spectra is extremely challenging. In this study, we present an approach called glyBranch (glycan Branching pattern identification based on spectra tree) to exploit the information contained in MSⁿ spectra tree for glycan identification. This approach will greatly facilitate the automated identification of glycan structures and related biological studies.

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.

Algorithms and design strategies towards automated glycoproteomics analysis

Glycoproteomics involves the study of glycosylation events on protein sequences ranging from purified proteins to whole proteome scales. Understanding these complex post-translational modification (PTM) events requires elucidation of the glycan moieties (monosaccharide sequences and glycosidic linkages between residues), protein sequences, as well as site-specific attachment of glycan moieties onto protein sequences, in a spatial and temporal manner in a variety of biological contexts. Compared with proteomics, bioinformatics for glycoproteomics is immature and many researchers still rely on tedious manual interpretation of glycoproteomics data. As sample preparation protocols and analysis techniques have matured, the number of publications on glycoproteomics and bioinformatics has increased substantially; however, the lack of consensus on tool development and code reuse limits the dissemination of bioinformatics tools because it requires significant effort to migrate a computational tool tailored for one method design to alternative methods. This review discusses algorithms and methods in glycoproteomics, and refers to the general proteomics field for potential solutions. It also introduces general strategies for tool integration and pipeline construction in order to better serve the glycoproteomics community. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:475-498, 2017.

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.

Computational approaches to define a human milk metaglycome

MOTIVATION

The goal of deciphering the human glycome has been hindered by the lack of high-throughput sequencing methods for glycans. Although mass spectrometry (MS) is a key technology in glycan sequencing, MS alone provides limited information about the identification of monosaccharide constituents, their anomericity and their linkages. These features of individual, purified glycans can be partly identified using well-defined glycan-binding proteins, such as lectins and antibodies that recognize specific determinants within glycan structures.

RESULTS

We present a novel computational approach to automate the sequencing of glycans using metadata-assisted glycan sequencing, which combines MS analyses with glycan structural information from glycan microarray technology. Success in this approach was aided by the generation of a 'virtual glycome' to represent all potential glycan structures that might exist within a metaglycomes based on a set of biosynthetic assumptions using known structural information. We exploited this approach to deduce the structures of soluble glycans within the human milk glycome by matching predicted structures based on experimental data against the virtual glycome. This represents the first meta-glycome to be defined using this method and we provide a publically available web-based application to aid in sequencing milk glycans.

AVAILABILITY AND IMPLEMENTATION

http://glycomeseq.emory.edu

CONTACT

sagravat@bidmc.harvard.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

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/.

Automating mass spectrometry-based quantitative glycomics using aminoxy tandem mass tag reagents with SimGlycan

Protein glycosylation is a common post-translational modification, which serves critical roles in the biological processes of organisms. Monitoring of changes in the abundance and structure of glycans may be necessary to explain the correlations between protein glycosylation and various diseases. Hence, the growing importance of glycoproteomics necessitates in-depth qualitative and quantitative studies of glycans. One of the emerging trends in glycomics research is the innovation related to accurate mass spectrometry based quantitative analysis of glycans. Recently, we have introduced aminoxyTMT reagents, which enable efficient relative quantitation of carbohydrates, improved glycan ionization efficiency and increased analytical throughput. These reagents can be used for quantitative analysis of N-glycans by direct infusion or liquid chromatography (LC)-coupled to electrospray ionization mass spectrometry (ESI-MS). However, unlike in proteomics, one of the major challenges left unaddressed is the lack of informatics tools to automate the qualitative and quantitative analysis of generated data. This analysis typically includes identification/quantitation of glycans using MS/MS data and differential analysis across biological samples. We have developed software modules to streamline such protocols for quantitative analysis of aminoxyTMT labeled-glycans derived from complex mixtures. This article is part of a Special Issue entitled: Proteomics in India.

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.

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 .

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.

Counting glycans revisited

We present an algorithm for counting glycan topologies of order n that improves on previously described algorithms by a factor n in both time and space. More generally, we provide such an algorithm for counting rooted or unrooted d-ary trees with labels or masses assigned to the vertices, and we give a "recipe" to estimate the asymptotic growth of the resulting sequences. We provide constants for the asymptotic growth of d-ary trees and labeled quaternary trees (glycan topologies). Finally, we show how a classical result from enumeration theory can be used to count glycan structures where edges are labeled by bond types. Our method also improves time bounds for counting alkanes.

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.

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.

Mass spectrometry for characterizing plant cell wall polysaccharides

Mass spectrometry is a selective and powerful technique to obtain identification and structural information on compounds present in complex mixtures. Since it requires only small sample amount it is an excellent tool for researchers interested in detecting changes in composition of complex carbohydrates of plants. This mini-review gives an overview of common mass spectrometry techniques applied to the analysis of plant cell wall carbohydrates. It presents examples in which mass spectrometry has been used to elucidate the structure of oligosaccharides derived from hemicelluloses and pectins and illustrates how information on sequence, linkages, branching, and modifications are obtained from characteristic fragmentation patterns.

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.

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.

New technologies for glycomic analysis: toward a systematic understanding of the glycome

Carbohydrates are the most difficult class of biological molecules to study by high-throughput methods owing to the chemical similarities between the constituent monosaccharide building blocks, template-less biosynthesis, and the lack of clearly identifiable consensus sequences for the glycan modification of cohorts of glycoproteins. These molecules are crucial for a wide variety of cellular processes ranging from cell-cell communication to immunity, and they are altered in disease states such as cancer and inflammation. Thus, there has been a dedicated effort to develop glycan analysis into a high-throughput analytical field termed glycomics. Herein we highlight major advances in applying separation, mass spectrometry, and microarray methods to the fields of glycomics and glycoproteomics. These new analytical techniques are rapidly advancing our understanding of the importance of glycosylation in biology and disease.

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.

Bioinformatics in glycomics: glycan characterization with mass spectrometric data using SimGlycan

Mass spectrometry (MS), with its low sample requirement and high sensitivity, has been the predominantly used methodology for characterization and elucidation of glycan structures. However, manual interpretation of MS data is complex and tedious due to large number of product ions observed and also due to the variation in their m/z values under various experimental conditions. We present an automated tool, SimGlycan, for this purpose, which accepts raw/standard MS data files as input and characterizes the associated glycan structure with high accuracy using database searching and scoring techniques. Not only does it predict the glycan structure using an MS/MS database searching technique, but it also facilitates predicting novel glycans by drawing a glycan and mapping it onto an experimental spectrum to check the degree of proximity between the theoretical and the experimental glycans. It serves as a platform for developing advanced tools that may be used for glycopeptide identification using MS data and 3D structural analysis of glycans with a few improvements in the existing features.

Sequence Analysis of Native Oligosaccharides Using Negative ESI Tandem MS

Carbohydrates exhibit many physiologically and pharmacologically important activities, yet their complicated structure and sequence pose major analytical challenges. Although their structural complexity makes analysis of carbohydrate difficult, mass spectrometry (MS) with high sensitivity, resolution and accuracy has become a vital tool in many applications related to analysis of carbohydrates or oligosaccharides. This application is essentially based on soft ionization technique which facilitates the ionization and vaporization of large, polar and thermally labile biomolecules. Electrospray-ionization (ESI), one of the soft ionization technique, tandem MS has been used in the sequencing of peptides, proteins, lipids, nucleic acids and more recently carbohydrates. The development of the ESI and tandem MS has begun to make carbohydrate analysis more routine. This review will focus on the application of the ESI tandem MS for the sequence analysis of native oligosaccharides, including neutral saccharides with multiple linkages, and the uronic acid polymers, alginate and glycosaminoglycans structures containing epimers.

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.

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.

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.

GlycoWorkbench: a tool for the computer-assisted annotation of mass spectra of glycans

Mass spectrometry is the main analytical technique currently used to address the challenges of glycomics as it offers unrivalled levels of sensitivity and the ability to handle complex mixtures of different glycan variations. Determination of glycan structures from analysis of MS data is a major bottleneck in high-throughput glycomics projects, and robust solutions to this problem are of critical importance. However, all the approaches currently available have inherent restrictions to the type of glycans they can identify, and none of them have proved to be a definitive tool for glycomics. GlycoWorkbench is a software tool developed by the EUROCarbDB initiative to assist the manual interpretation of MS data. The main task of GlycoWorkbench is to evaluate a set of structures proposed by the user by matching the corresponding theoretical list of fragment masses against the list of peaks derived from the spectrum. The tool provides an easy to use graphical interface, a comprehensive and increasing set of structural constituents, an exhaustive collection of fragmentation types, and a broad list of annotation options. The aim of GlycoWorkbench is to offer complete support for the routine interpretation of MS data. The software is available for download from: http://www.eurocarbdb.org/applications/ms-tools.

Automated N-glycopeptide identification using a combination of single- and tandem-MS

We describe Peptoonist, a program that can automatically identify the glycans (sugars) present at each N-glycosylation site of a protein. The input to Peptoonist is a series of mass spectra, both MS and MS/MS, obtained from a liquid chromatography (LC) run of proteolytically digested purified glycoproteins. The program uses MS/MS to identify glycosylated peptides and single-MS to identify the N-glycans present on each of these peptides, at least to the level of monosaccharide composition. We validate the program on an LC run of mouse zona pellucida proteins that had been intensively hand annotated by a human expert. Our program doubled the number of glycopeptide identifications, and also found several possible errors in the hand annotation. In addition, it automatically made most of the same glycan isomer identifications as the expert annotator.

N-Glycan structure annotation of glycopeptides using a linearized glycan structure database (GlyDB)

While glycoproteins are abundant in nature, and changes in glycosylation occur in cancer and other diseases, glycoprotein characterization remains a challenge due to the structural complexity of the biopolymers. This paper presents a general strategy, termed GlyDB, for glycan structure annotation of N-linked glycopeptides from tandem mass spectra in the LC-MS analysis of proteolytic digests of glycoproteins. The GlyDB approach takes advantage of low-energy collision-induced dissociation of N-linked glycopeptides that preferentially cleaves the glycosidic bonds while the peptide backbone remains intact. A theoretical glycan structure database derived from biosynthetic rules for N-linked glycans was constructed employing a novel representation of branched glycan structures consisting of multiple linear sequences. The commonly used peptide identification program, Sequest, could then be utilized to assign experimental tandem mass spectra to individual glycoforms. Analysis of synthetic glycopeptides and well-characterized glycoproteins demonstrate that the GlyDB approach can be a useful tool for annotation of glycan structures and for selection of a limited number of potential glycan structure candidates for targeted validation.

Rapid resolution of carbohydrate isomers by electrospray ionization ambient pressure ion mobility spectrometry-time-of-flight mass spectrometry (ESI-APIMS-TOFMS)

Carbohydrates are an extremely complex group of isomeric molecules that have been difficult to analyze in the gas phase by mass spectrometry because (1) precursor ions and product ions to successive stages of MS(n) are frequently mixtures of isomers, and (2) detailed information about the anomeric configuration and location of specific stereochemical variants of monosaccharides within larger molecules has not been possible to obtain in a general way. Herein, it is demonstrated that gas-phase analyses by direct combination of electrospray ionization, ambient pressure ion mobility spectrometry, and time-of-flight mass spectrometry (ESI-APIMS-TOFMS) provides sufficient resolution to separate different anomeric methyl glycosides and to separate different stereoisomeric methyl glycosides having the same anomeric configuration. Reducing sugars were typically resolved into more than one peak, which might represent separation of cyclic species having different anomeric configurations and/or ring forms. The extent of separation, both with methyl glycosides and reducing sugars, was significantly affected by the nature of the drift gas and by the nature of an adducting metal ion or ion complex. The study demonstrated that ESI-APIMS-TOFMS is a rapid and effective analytical technique for the separation of isomeric methyl glycosides and simple sugars, and can be used to differentiate glycosides having different anomeric configurations.

Congruent strategies for carbohydrate sequencing. 3. OSCAR: an algorithm for assigning oligosaccharide topology from MSn data

This is the third in a sequence of reports devoted to the development of congruent strategies for carbohydrate sequencing. Two previous reports outlined the strategies for observing structural detail from MSn data and introduced tools that compile, search, and compare fragment spectra in a bottom-up approach to oligosaccharide sequencing. In this third report, we introduce the operational details of an algorithm that we define as the Oligosaccharide Subtree Constraint Algorithm (OSCAR). This algorithm assimilates analyst-selected MSn ion fragmentation pathways into oligosaccharide topology (branching and linkage) using what may be considered a top-down sequencing strategy. Guided by a series of logical constraints, this de novo algorithm provides molecular topology without presumed biosynthetic constraints or external comparisons. In this introductory study, OSCAR is applied to a series of permethylated oligomers and isomeric glycans, and topologies are assigned in a few hundredths of a second.

Structural analysis of O-glycopeptides employing negative- and positive-ion multi-stage mass spectra obtained by collision-induced and electron-capture dissociations in linear ion trap time-of-flight mass spectrometry

Structural analyses of various glycans attached to proteins and peptides are highly desirable for elucidating their biological roles. An approach based on mass spectrometry (MS) combining both collision-induced dissociation (CID) and electron-capture dissociation (ECD) in the positive- and negative-ion modes has been proposed as a simple and direct method of assigning an O-glycan without releasing it from the peptide and of determining the amino acid sequence of the peptide and glycosylation site. The instrument used is an electrospray ionization (ESI) linear ion trap (LIT) time-of-flight (TOF) mass spectrometer with tandem LITs for CID by He gas and ECD. The proposed approach was tested with two synthetic O-glycopeptides binding a sialyl Lewis x (sLe(x)) oligosaccharide and a 3'-sialyl N-acetyllactosamine (3'-SLN) on a serine (S) residue. In the negative-ion mode, the CID MS(2) spectra of O-glycopeptides showed a relatively abundant glycoside-bond cleavage between the core N-acetylglucosamine (GlcNAc) and serine (S) that yields deprotonated C(3)-type fragment ions of O-glycan and deprotonated Z(0)-type peptide ions. The structure of the sLe(x) (3'-SLN) oligosaccharide was simply assigned by comparing the CID MS(3) spectrum derived from the C(3)-type fragment ion with the CID MS(2) spectra of the sLe(x) and sLe(a) (3'- and 6'-SLN) standards (i.e., negative-ion MS(n) spectral matching). The amino acid sequence of the peptide including the glycosylation site was determined from the ECD MS(2) spectrum in the positive-ion mode.

The use of mass spectrometry for the proteomic analysis of glycosylation

Of all protein PTMs, glycosylation is by far the most common, and is a target for proteomic research. Glycosylation plays key roles in controlling various cellular processes and the modifications of the glycan structures in diseases highlight the clinical importance of this PTM. Glycosylation analysis remains a difficult task. MS, in combination with modern separation methodologies, is one of the most powerful and versatile techniques for the structural analysis of glycoconjugates. This review describes methodologies based on MS for detailed characterization of glycoconjugates in complex biological samples at the sensitivity required for proteomic work.

Automated interpretation of MS/MS spectra of oligosaccharides

MOTIVATION

The emerging glycomics and glycoproteomics projects aim to characterize all forms of glycoproteins in different tissues and organisms. Tandem mass spectrometry (MS/MS) is the key experimental methodology for high-throughput glycan identification and characterization. Fragmentation of glycans from high energy collision-induced dissociation generates ions from glycosidic as well as internal cleavages. The cross-ring ions resulting from internal cleavages provide additional information that is important to reveal the type of linkage between monosaccharides. This information, however, is not incorporated into the current programs for analyzing glycan mass spectra. As a result, they can rarely distinguish from the mass spectra isomeric oligosaccharides, which have the same saccharide composition but different types of sequences, branches or linkages.

RESULTS

In this paper, we describe a novel algorithm for glycan characterization using MS/MS. This algorithm consists of three steps. First, we develop a scoring scheme to identify potential bond linkages between monosaccharides, based on the appearance pattern of cross-ring ions. Next, we use a dynamic programming algorithm to determine the most probable oligosaccharide structures from the mass spectrum. Finally, we re-evaluate these oligosaccharide structures, taking into account the double fragmentation ions. We also show the preliminary results of testing our algorithm on several MS/MS spectra of oligosaccharides.

AVAILABILITY

The program GLYCH is available upon request from the authors.

Automatic determination of O-glycan structure from fragmentation spectra

Glycosylation is one of the most important classes of post-translational protein modifications, but the identification of glycans is difficult because of their branched structures and numerous isomers. We describe an algorithm called CartoonistTwo that proposes structures for O-linked glycans by automatically analyzing fragmentation mass spectra. CartoonistTwo improves upon previous glycan identification software primarily in its scoring function, which can more successfully distinguish among a number of similar structures. CartoonistTwo was designed and tested with FTICR mass spectra, and includes automatic recalibration and peak selection especially tuned for such data, yet it can be easily adapted to fragmentation spectra (MS2 or MSn) from other instrument types. On a validated test set of 34 SORI-CID MSn FTICR spectra from Xenopus egg jelly, CartoonistTwo gave the manually determined structural assignment either the first or second highest score over 90% of the time. And for over 50% of these spectra, CartoonistTwo selected a unique highest scoring structure that agreed with the manually determined one.

Proteomic analysis of glycosylation: structural determination of N- and O-linked glycans by mass spectrometry

This review summarizes the methods, mainly based on mass spectrometry, for the structural determination of N- and O-linked carbohydrates that are post-translationally attached to a large number of proteins and which play a key role in determining the function and biophysical properties of these compounds. Analysis of these carbohydrates has proved difficult in the past due to their structural complexity. However, modern analytical methods such as mass spectrometry have the ability to elucidate most structural details at the concentration levels required for proteomics. This review describes methods for direct examination of glycoproteins by mass spectrometry, the release of N- and O-linked glycans from glycoproteins separated in sodium dodecyl sulfate polyacrylamide electrophoresis gels, and the analysis of these compounds by techniques such as matrix-assisted laser desorption/ionization and electrospray ionization mass spectrometry. Matrix-assisted laser desorption/ionization mass spectrometry provides the most rapid method for comparing glycan profiles and is probably most appropriate for clinical studies. One of the most promising techniques for determining the structures of N-glycans in proteomic studies is negative ion fragmentation of electrosprayed ions. This technique combines high throughput with ease of structural interpretation and provides structural details that are difficult to obtain by classical methods.

Infrared Multiphoton Dissociation and Electron Capture Dissociation of High-Mannose Type Glycopeptides

The combination of electron capture dissociation (ECD) and infrared multiphoton dissociation (IRMPD) for the structural characterization of high-mannose type glycopeptides is explored in depth for the first time. Contrary to previous applications to other glycan types, our analyses reveal that IRMPD does not necessarily selectively induce glycan cleavage in high-mannose type glycopeptides; rather peptide backbone cleavage can effectively compete with glycosidic cleavage. Poor glycan cleavage with IRMPD is due to a higher gas-phase stability of mannose-linking glycosidic bonds. This reasoning also explains mannose cleavage patterns observed for a xylose type glycopeptide with IRMPD. In addition, extensive peptide backbone cleavage is observed for a >6 kDa glycopeptide with ECD, to our knowledge the largest glycopeptide examined with this technique to date.