Automatic annotation of matrix-assisted laser desorption/ionizationN-glycan spectra

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.

High-Throughput Glycomic Methods

Glycomics aims to identify the structure and function of the glycome, the complete set of oligosaccharides (glycans), produced in a given cell or organism, as well as to identify genes and other factors that govern glycosylation. This challenging endeavor requires highly robust, sensitive, and potentially automatable analytical technologies for the analysis of hundreds or thousands of glycomes in a timely manner (termed high-throughput glycomics). This review provides a historic overview as well as highlights recent developments and challenges of glycomic profiling by the most prominent high-throughput glycomic approaches, with N-glycosylation analysis as the focal point. It describes the current state-of-the-art regarding levels of characterization and most widely used technologies, selected applications of high-throughput glycomics in deciphering glycosylation process in healthy and disease states, as well as future perspectives.

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.

Characterization of Glycosphingolipids and Their Diverse Lipid Forms through Two-Stage Matching of LC-MS/MS Spectra

Glycosphingolipids (GSLs) play a key role in various biological and pathological events. Thus, determination of the complete GSL compositions in human tissues is essential for comparative and functional studies of GSLs. In this work, a new strategy was developed for GSL characterization and glycolipidomics analysis based on two-stage matching of experimental and reference MS/MS spectra. In the first stage, carbohydrate fragments, which contain only glycans and thus are conserved within a GSL species, are directly matched to yield a species identification. In the second stage, glycolipid fragments from the matched GSL species, which contain both the lipid and glycans and thus shift due to lipid structural changes, are treated according to lipid rule-based matching to characterize the lipid compositions. This new strategy uses the whole spectrum for GSL characterization. Furthermore, simple databases containing only a single lipid form per GSL species can be utilized to identify multiple GSL lipid forms. It is expected that this method will help accelerate glycolipidomics analysis and disclose new and diverse lipid forms of GSLs.

Systems Glycobiology: Past, Present, and Future

Glycobiology is a glycan-based field of study that focuses on the structure, function, and biology of carbohydrates, and glycomics is a sub-study of the field of glycobiology that aims to define structure/function of glycans in living organisms. With the popularity of the glycobiology and glycomics, application of computational modeling expanded in the scientific area of glycobiology over the last decades. The recent availability of progressive Wet-Lab methods in the field of glycobiology and glycomics is promising for the impact of systems biology on the research area of the glycome, an emerging field that is termed “systems glycobiology.” This chapter will summarize the up-to-date leading edge in the use of bioinformatics tools in the field of glycobiology. The chapter provides basic knowledge both for glycobiologists interested in the application of bioinformatics tools and scientists of computational biology interested in studying the glycome.

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.

Best-first search guided multistage mass spectrometry-based glycan identification

MOTIVATION

Glycan identification has long been hampered by complicated branching patterns and various isomeric structures of glycans. Multistage mass spectrometry (MSn) is a promising glycan identification technique as it generates multiple-level fragments of a glycan, which can be explored to deduce branching pattern of the glycan and further distinguish it from other candidates with identical mass. However, the automatic glycan identification still remains a challenge since it mainly relies on expertise to guide a MSn instrument to generate spectra.

RESULTS

Here, we proposed a novel method, named bestFSA, based on a best-first search algorithm to guide the process of spectrum producing in glycan identification using MSn. BestFSA is able to select the most appropriate peaks for next round of experiments and complete the identification using as few experimental rounds. Our analysis of seven representative glycans shows that bestFSA correctly distinguishes actual glycans efficiently and suggested bestFSA could be used in practical glycan identification. The combination of the MSn technology coupled with bestFSA should greatly facilitate the automatic identification of glycan branching patterns, with significantly improved identification sensitivity, and reduce time and cost of MSn experiments.

AVAILABILITY AND IMPLEMENTATION

http://glycan.ict.ac.cn.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Recent advances in glycoinformatic platforms for glycomics and glycoproteomics

Protein glycosylation is the most complex and prevalent post-translation modification in terms of the number of proteins modified and the diversity generated. To understand the functional roles of glycoproteins it is important to gain an insight into the repertoire of oligosaccharides present. The comparison and relative quantitation of glycoforms combined with site-specific identification and occupancy are necessary steps in this direction. Computational platforms have continued to mature assisting researchers with the interpretation of such glycomics and glycoproteomics data sets, but frequently support dedicated workflows and users rely on the manual interpretation of data to gain insights into the glycoproteome. The growth of site-specific knowledge has also led to the implementation of machine-learning algorithms to predict glycosylation which is now being integrated into glycoproteomics pipelines. This short review describes commercial and open-access databases and software with an emphasis on those that are actively maintained and designed to support current analytical workflows.

Advancing Solutions to the Carbohydrate Sequencing Challenge

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

Isotopic labeling with cellular O-glycome reporter/amplification (ICORA) for comparative O-glycomics of cultured cells

Mucin-type O-glycans decorate >80% of secretory and cell surface proteins and contribute to health and disease. However, dynamic alterations in the O-glycome are poorly understood because current O-glycomic methodologies are not sufficiently sensitive nor quantitative. Here we describe a novel isotope labeling approach termed Isotope-Cellular O-glycome Reporter Amplification (ICORA) to amplify and analyze the O-glycome from cells. In this approach, cells are incubated with Ac3GalNAc-Bn (Ac3GalNAc-[1H7]Bn) or a heavy labeled Ac3GalNAc-BnD7 (Ac3GalNAc-[2D7]Bn) O-glycan precursor (7 Da mass difference), which enters cells and upon de-esterification is modified by Golgi enzymes to generate Bn-O-glycans secreted into the culture media. After recovery, heavy and light Bn-O-glycans from two separate conditions are mixed, analyzed by MS, and statistically interrogated for changes in O-glycan abundance using a semi-automated approach. ICORA enables ~100-1000-fold enhanced sensitivity and increased throughput compared to traditional O-glycomics. We validated ICORA with model cell lines and used it to define alterations in the O-glycome in colorectal cancer. ICORA is a useful tool to explore the dynamic regulation of the O-glycome in health and disease.

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.

Human disease glycomics: technology advances enabling protein glycosylation analysis - part 1

INTRODUCTION

Protein glycosylation is recognized as an important post-translational modification, with specific substructures having significant effects on protein folding, conformation, distribution, stability and activity. However, due to the structural complexity of glycans, elucidating glycan structure-function relationships is demanding. The fine detail of glycan structures attached to proteins (including sequence, branching, linkage and anomericity) is still best analysed after the glycans are released from the purified or mixture of glycoproteins (glycomics). The technologies currently available for glycomics are becoming streamlined and standardized and many features of protein glycosylation can now be determined using instruments available in most protein analytical laboratories. Areas covered: This review focuses on the current glycomics technologies being commonly used for the analysis of the microheterogeneity of monosaccharide composition, sequence, branching and linkage of released N- and O-linked glycans that enable the determination of precise glycan structural determinants presented on secreted proteins and on the surface of all cells. Expert commentary: Several emerging advances in these technologies enabling glycomics analysis are discussed. The technological and bioinformatics requirements to be able to accurately assign these precise glycan features at biological levels in a disease context are assessed.

High-throughput analysis of N-glycans using AutoTip via glycoprotein immobilization

Analysis of a large number of samples requires an efficient, rapid and reproducible method. Automation is an ideal approach for high-throughput sample preparation. Multi-plexing sample preparation via a 96-well plate format becomes popular in recent years; however, those methods lack specificity and require several cleanup steps via chromatography purification. To overcome these drawbacks, a chemoenzymatic method has been developed utilizing protein conjugation on solid-phase. Previously, sample preparation was successfully performed in a snap-cap spin-column (SCSC) format. However, sample preparation using SCSC is time-consuming and lacks reproducibility. In this work, we integrated the chemoenzymatic technique in a pipette tip (AutoTip) that was operated by an automated liquid handler. We established a multi-step protocol involving protein immobilization, sialic acid modification, and N-glycan release. We first optimized our automated protocol using bovine fetuin as a standard glycoprotein, and then assessed the reproducibility of the AutoTip using isobaric tags for relative N-linked glycan quantification. We then applied this methodology to profile N-glycans from 58 prostate cancer patient urine samples, revealing increased sialyation on urinary N-glycans derived from prostate cancer patients. Our results indicated AutoTip has applications for high-throughput sample preparation for studying the N-linked glycans.

Sialic acid linkage-specific permethylation for improved profiling of protein glycosylation by MALDI-TOF MS

Protein glycosylation mediates a wide range of cellular processes, affecting development and disease in mammals. Deciphering the "glycocodes" requires rapid, sensitive and in-depth characterization of diverse glycan structures derived from biological samples. In this study, we described a two-step derivatization strategy termed linkage-specific sialic acid permethylation (SSAP) consisting of dimethylamination and permethylation for the improved profiling of glycosylation by matrix-assisted laser desorption/ionization (MALDI) time-of-fight (TOF) mass spectrometry (MS). High linkage-specificity (∼99%) of SSAP to both the two most common forms of sialic acid, N-acetylneuraminic acid (Neu5Ac) and N-glycolylneuraminic acid (Neu5Gc), permitted direct discrimination of α2,3- and α2,6-linked sialic acids in MALDI-TOF MS. The enhanced intensity (>10-fold) and increased detection limit (>10-fold) of derivatized glycans were valued for sensitive glycomics. Moreover, the good compatibility and reaction efficiency of the two steps of SSAP allowed rapid sample preparation (<2 h), benefiting robust analysis of glycans in a high-throughput manner. The SSAP strategy was further applied to investigate the protein glycosylation of human serum associated with rheumatoid arthritis (RA). It was demonstrated that the relative abundances of individual glycans were different in RA negative and RA positive samples, and meanwhile the RA patient/control ratios of both α2,3- and α2,6-sialylated glycans tended to elevate accompanied with the increase of sialylation. Those findings of the glycosylation changes occurred in human serum protein may contribute to the diagnosis of RA. Herein, SSAP derivatization combined with MALDI-TOF MS exhibits unique advantages for glycomic analysis and shows potential in glycosylation profiling of therapeutic proteins and clinical glycan biomarker discovery.

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

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

Quantitative Glycomics: A Combined Analytical and Bioinformatics Approach

Glycosylation is one of the most common and essential protein modifications. Glycans conjugated to biomolecules modulate the function of such molecules through both direct recognition of glycan structures and indirect mechanisms that involve the control of protein turnover rates, stability, and conformation. The biological attributes of glycans in numerous biological processes and implications in a number of diseases highlight the necessity for comprehensive characterization of protein glycosylation. This chapter reviews cutting-edge methods and tools developed to facilitate quantitative glycomics. This chapter highlights the different methods employed for the release and purification of glycans from biological samples. The most effective labeling methods developed for sensitive quantitative glycomics are also described and discussed. The chromatographic approaches that have been used effectively in glycomics are also highlighted.

Analysis of Permethylated Glycan by Liquid Chromatography (LC) and Mass Spectrometry (MS)

The development of a reliable and high-throughput glycomic profiling strategy is in high demand due to the biological roles of glycans and their association with different diseases. Native analysis can be quite difficult because of the low ionization efficiency and microheterogeneity of glycans. In this chapter, the sample preparation protocols and LC-MS analysis of permethylated glycan strategies are introduced. Solid-phase permethylation is a fast, convenient, and high-yield method to stabilize sialic acid and improve glycan ionization efficiency and analysis in positive mode; this results in a more sensitive and reliable glycomic profiling strategy. Several modifications in the LC method are also mentioned in this chapter. Online purification simplifies sample preparation and reduces sample loss. Elevating the column temperature significantly improves the peak shape of permethylated glycans and results in isomeric separation. The identification and quantification of permethylated glycans can be achieved through high resolution MS and MS/MS experiments using a MRM method; both approaches are reliable, sensitive, and conducive to high-throughput glycomic studies.

gFinder: A Web-Based Bioinformatics Tool for the Analysis of N-Glycopeptides

Glycoproteins influence numerous indispensable biological functions, and changes in protein glycosylation have been observed in various diseases. The identification and characterization of glycoprotein and glycosylation sites by mass spectrometry (MS) remain challenging tasks, and great efforts have been devoted to the development of proteome informatics tools that facilitate the MS analysis of glycans and glycopeptides. Here we report on the development of gFinder, a web-based bioinformatics tool that analyzes mixtures of native N-glycopeptides that have been profiled by tandem MS. gFinder not only enables the simultaneous integration of collision-induced dissociation (CID) and high-energy collisional dissociation (HCD) fragmentation but also merges the spectra for high-throughput analysis. These merged spectra expedite the identification of both glycans and N-glycopeptide backbones in tandem MS data using the glycan database and a proteomic search tool (e.g., Mascot). These data can be used to simultaneously characterize peptide backbone sequences and possible N-glycan structures using assigned scores. gFinder also provides many convenient functions that make it easy to perform manual calculations while viewing the spectrum on-screen. We used gFinder to detect an additional protein (Q8N9B8) that was missed from the previously published data set containing N-linked glycosylation. For N-glycan analysis, we used the GlycomeDB glycan structure database, which integrates the structural and taxonomic data from all of the major carbohydrate databases available in the public domain. Thus, gFinder is a convenient, high-throughput analytical tool for interpreting the tandem mass spectra of N-glycopeptides, which can then be used for identification of potential missing proteins having glycans. gFinder is available publicly at http://gFinder.proteomix.org/ .

Quantitative profiling of glycans and glycopeptides: an informatics' perspective

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

Automated Glycan Sequencing from Tandem Mass Spectra of N-Linked Glycopeptides

Mass spectrometry has become a routine experimental tool for proteomic biomarker analysis of human blood samples, partly due to the large availability of informatics tools. As one of the most common protein post-translational modifications (PTMs) in mammals, protein glycosylation has been observed to alter in multiple human diseases and thus may potentially be candidate markers of disease progression. While mass spectrometry instrumentation has seen advancements in capabilities, discovering glycosylation-related markers using existing software is currently not straightforward. Complete characterization of protein glycosylation requires the identification of intact glycopeptides in samples, including identification of the modification site as well as the structure of the attached glycans. In this paper, we present GlycoSeq, an open-source software tool that implements a heuristic iterated glycan sequencing algorithm coupled with prior knowledge for automated elucidation of the glycan structure within a glycopeptide from its collision-induced dissociation tandem mass spectrum. GlycoSeq employs rules of glycosidic linkage as defined by glycan synthetic pathways to eliminate improbable glycan structures and build reasonable glycan trees. We tested the tool on two sets of tandem mass spectra of N-linked glycopeptides cell lines acquired from breast cancer patients. After employing enzymatic specificity within the N-linked glycan synthetic pathway, the sequencing results of GlycoSeq were highly consistent with the manually curated glycan structures. Hence, GlycoSeq is ready to be used for the characterization of glycan structures in glycopeptides from MS/MS analysis. GlycoSeq is released as open source software at https://github.com/chpaul/GlycoSeq/ .

Glycomics and glycoproteomics of membrane proteins and cell-surface receptors: Present trends and future opportunities

Membrane proteins mediate cell-cell interactions and adhesion, the transfer of ions and metabolites, and the transmission of signals from the extracellular environment to the cell interior. The extracellular domains of most cell membrane proteins are glycosylated, often at multiple sites. There is a growing awareness that glycosylation impacts the structure, interaction, and function of membrane proteins. The application of glycoproteomics and glycomics methods to membrane proteins has great potential. However, challenges also arise from the unique physical properties of membrane proteins. Successful analytical workflows must be developed and disseminated to advance functional glycoproteomics and glycomics studies of membrane proteins. This review explores the opportunities and challenges related to glycomic and glycoproteomic analysis of membrane proteins, including discussion of sample preparation, enrichment, and MS/MS analyses, with a focus on recent successful workflows for analysis of N- and O-linked glycosylation of mammalian membrane proteins.

Global Identification and Differential Distribution Analysis of Glycans in Subcellular Fractions of Bladder Cells

Compartmentalization of cellular components and their associated biological processes is crucial for cellular function. Protein glycosylation provides a basis for diversity of protein functions. Diversity of glycan composition in animal cells remains poorly understood. We used differential centrifugation techniques to isolate four subcellular protein fractions from homogenate of metastatic bladder YTS1 cells, low grade nonmuscle invasive bladder cancer KK47 cells and normal bladder epithelia HCV29 cells: microsomal (Mic), mitochondrial (Mito), nuclear (Nuc), and cytosolic (Cyto). An integrated strategy combining lectin microarray and mass spectrometry (MS) analysis was then applied to evaluate protein glycosylation of the four fractions. Lectin microarray analysis revealed significant differences among the four fractions in terms of glycan binding to the lectins LCA, AAL, MPL, WGA and PWM in YTS1 cell, STL, Jacalin, VVA, LCA and WGA in KK47, and ConA, GNA, VVA and ACA in HCV29 cell. Among a total of 40, 32 and 15 N-glycans in four fractions of three cells detected by MS analysis, high-mannose and fucosylated structures were predominant, 10 N-glycans in YTS1, 5 N-glycans in KK47 and 7 N-glycans in HCV29 were present in all four fractions; and 10 N-glycans in YTS1, 16 N-glycans in KK47, and 3 N-glycans in HCV29 were present in only one fraction. Glycans in the latter category are considered potential markers for the corresponding organelles. The integrated strategy described here allows detailed examination of glycomes subcellular fraction with high resolution and sensitivity, and will be useful for elucidation of the functional roles of glycans and corresponding glycosylated proteins in distinct organelles.

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.

Mass Spectrometry-Based N-Glycomics of Colorectal Cancer

Colorectal cancer (CRC) is one of the most prevalent cancers worldwide. An increased molecular understanding of the CRC pathology is warranted to gain insights into the underlying molecular and cellular mechanisms of the disease. Altered protein glycosylation patterns are associated with most diseases including malignant transformation. Recent advances in mass spectrometry and bioinformatics have accelerated glycomics research and present a new paradigm for cancer biomarker discovery. Mass spectrometry (MS)-based glycoproteomics and glycomics, therefore, hold considerable promise to improve the discovery of novel biomarkers with utility in disease diagnosis and therapy. This review focuses on the emerging field of glycomics to present a comprehensive review of advances in technologies and their application in studies aimed at discovering novel glycan-based biomarkers. We will also discuss some of the challenges associated with using glycans as biomarkers.

Chemoenzymatic method for glycomics: Isolation, identification, and quantitation

Over the past decade, considerable progress has been made with respect to the analytical methods for analysis of glycans from biological sources. Regardless of the specific methods that are used, glycan analysis includes isolation, identification, and quantitation. Derivatization is indispensable to increase their identification. Derivatization of glycans can be performed by permethylation or carbodiimide coupling/esterification. By introducing a fluorophore or chromophore at their reducing end, glycans can be separated by electrophoresis or chromatography. The fluorogenically labeled glycans can be quantitated using fluorescent detection. The recently developed approaches using solid-phase such as glycoprotein immobilization for glycan extraction and on-tissue glycan mass spectrometry imaging demonstrate advantages over methods performed in solution. Derivatization of sialic acids is favorably implemented on the solid support using carbodiimide coupling, and the released glycans can be further modified at the reducing end or permethylated for quantitative analysis. In this review, methods for glycan isolation, identification, and quantitation are discussed.

Engaging challenges in glycoproteomics: recent advances in MS-based glycopeptide analysis

The proteomic analysis of glycosylation is uniquely challenging. The numerous and varied biological roles of protein-linked glycans have fueled a tremendous demand for technologies that enable rapid, in-depth structural examination of glycosylated proteins in complex biological systems. In turn, this demand has driven many innovations in wide ranging fields of bioanalytical science. This review will summarize key developments in glycoprotein separation and enrichment, glycoprotein proteolysis strategies, glycopeptide separation and enrichment, the role of mass measurement accuracy in glycopeptide detection, glycopeptide ion dissociation methods for MS/MS, and informatic tools for glycoproteomic analysis. In aggregate, this selection of topics serves to encapsulate the present status of MS-based analytical technologies for engaging the challenges of glycoproteomic analysis.

Benchmark study of automatic annotation of MALDI-TOF N-glycan profiles

Human experts can annotate peaks in MALDI-TOF profiles of detached N-glycans with some degree of accuracy. Even though MALDI-TOF profiles give only intact masses without any fragmentation information, expert knowledge of the most common glycans and biosynthetic pathways in the biological system can point to a small set of most likely glycan structures at the "cartoon" level of detail. Cartoonist is a recently developed, fully automatic annotation tool for MALDI-TOF glycan profiles. Here we benchmark Cartoonist's automatic annotations against human expert annotations on human and mouse N-glycan data from the Consortium for Functional Glycomics. We find that Cartoonist and expert annotations largely agree, but the expert tends to annotate more specifically, meaning fewer suggested structures per peak, and Cartoonist more comprehensively, meaning more annotated peaks. On peaks for which both Cartoonist and the expert give unique cartoons, the two cartoons agree in over 90% of all cases. This article is part of a Special Issue entitled: Computational Proteomics.

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.

Automated annotation and quantitation of glycans by liquid chromatography/electrospray ionization mass spectrometric analysis using the MultiGlycan-ESI computational tool

RATIONALE

Liquid chromatography/mass spectrometry (LC/MS) is currently considered to be a conventional glycomics analysis strategy due to the high sensitivity and ability to handle complex biological samples. Interpretation of LC/MS data is a major bottleneck in high-throughput glycomics LC/MS-based analysis. The complexity of LC/MS data associated with biological samples prompts the needs to develop computational tools capable of facilitating automated data annotation and quantitation.

METHODS

An LC/MS-based automated data annotation and quantitation software, MultiGlycan-ESI, was developed and utilized for glycan quantitation. Data generated by the software from LC/MS analysis of permethylated N-glycans derived from fetuin were initially validated by manual integration to assess the performance of the software. The performance of MultiGlycan-ESI was then assessed for the quantitation of permethylated fetuin N-glycans analyzed at different concentrations or spiked with permethylated N-glycans derived from human blood serum.

RESULTS

The relative abundance differences between data generated by the software and those generated by manual integration were less than 5%, indicating the reliability of MultiGlycan-ESI in quantitation of permethylated glycans analyzed by LC/MS. Automated quantitation resulted in a linear relationship for all six N-glycans derived from 50 ng to 400 ng fetuin with correlation coefficients (R(2) ) greater than 0.93. Spiking of permethylated fetuin N-glycans at different concentrations in permethylated N-glycan samples derived from a 0.02 μL of HBS also exhibited linear agreement with R(2) values greater than 0.9.

CONCLUSIONS

With a variety of options, including mass accuracy, merged adducts, and filtering criteria, MultiGlycan-ESI allows automated annotation and quantitation of LC/ESI-MS N-glycan data. The software allows the reliable quantitation of glycan LC/MS data. The software is reliable for automated glycan quantitation, thus facilitating rapid and reliable high-throughput glycomics studies.

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 .

GlyQ-IQ: glycomics quintavariate-informed quantification with high-performance computing and GlycoGrid 4D visualization

Glycomics quintavariate-informed quantification (GlyQ-IQ) is a biologically guided glycomics analysis tool for identifying N-glycans in liquid chromatography-mass spectrometry (LC-MS) data. Glycomics LC-MS data sets have convoluted extracted ion chromatograms that are challenging to deconvolve with existing software tools. LC deconvolution into constituent pieces is critical in glycomics data sets because chromatographic peaks correspond to different intact glycan structural isomers. The biological targeted analysis approach offers several key advantages to traditional LC-MS data processing. A priori glycan information about the individual target's elemental composition allows for improved sensitivity by utilizing the exact isotope profile information to focus chromatogram generation and LC peak fitting on the isotopic species having the highest intensity. Glycan target annotation utilizes glycan family relationships and in source fragmentation in addition to high specificity feature LC-MS detection to improve the specificity of the analysis. The GlyQ-IQ software was developed in this work and evaluated in the context of profiling the N-glycan compositions from human serum LC-MS data sets. A case study is presented to demonstrate how GlyQ-IQ identifies and removes confounding chromatographic peaks from high mannose glycan isomers from human blood serum. In addition, GlyQ-IQ was used to generate a broad human serum N-glycan profile from a high resolution nanoelectrospray-liquid chromatography-tandem mass spectrometry (nESI-LC-MS/MS) data set. A total of 156 glycan compositions and 640 glycan isomers were detected from a single sample. Over 99% of the GlyQ-IQ glycan-feature assignments passed manual validation and are backed with high-resolution mass spectra.

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.

N-linked glycan profiling of GGTA1/CMAH knockout pigs identifies new potential carbohydrate xenoantigens

BACKGROUND

The temporary or long-term xenotransplantation of pig organs into people would save thousands of lives each year if not for the robust human antibody response to pig carbohydrates. Genetically engineered pigs deficient in galactose α1,3 galactose (gene modified: GGTA1) and N-glycolylneuraminic acid (gene modified: CMAH) have significantly improved cell survival when challenged by human antibody and complement in vitro. There remains, however, a significant portion of human antibody binding.

METHODS

To uncover additional xenoantigens, we compared the asparagine-linked (N-linked) glycome from serum proteins of humans, domestic pigs, GGTA1 knockout pigs, and GGTA1/CMAH knockout pigs using mass spectrometry. Carbohydrate structures were determined with assistance from GlycoWorkbench, Cartoonist, and SimGlycan software by comparison to existing database entries and collision-induced dissociation fragmentation data.

RESULTS

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) analysis of reduced and solid-phase permethylated glycans resulted in the detection of high-mannose, hybrid, and complex type N-linked glycans in the 1000-4500 m/z ion range. GGTA1/CMAH knockout pig samples had increased relative amounts of high-mannose, incomplete, and xylosylated N-linked glycans. All pig samples had significantly higher amounts of core and possibly antennae fucosylation.

CONCLUSIONS

We provide for the first time a comparison of the serum protein glycomes of the human, domestic pig, and genetically modified pigs important to xenotransplantation.

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

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

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.

Automated annotation and quantification of glycans using liquid chromatography-mass spectrometry

As a common post-translational modification, protein glycosylation plays an important role in many biological processes, and it is known to be associated with human diseases. Mass spectrometry (MS)-based glycomic profiling techniques have been developed to measure the abundances of glycans in complex biological samples and applied to the discovery of putative glycan biomarkers. To automate the annotation of glycomic profiles in the liquid chromatography-MS (LC-MS) data, we present here a user-friendly software tool, MultiGlycan, implemented in C# on Windows systems. We tested MultiGlycan by using several glycomic profiling datasets acquired using LC-MS under different preparations and show that MultiGlycan executes fast and generates robust and reliable results.

AVAILABILITY

MultiGlycan can be freely downloaded at http://darwin.informatics.indiana.edu/MultiGlycan/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Using glycome databases for drug discovery

BACKGROUND

The glycomics field has made great advancements in the last decade due to technologies for their synthesis and analysis including carbohydrate microarrays. Accordingly, databases for glycomics research have also emerged and been made publicly available by many major institutions worldwide.

OBJECTIVE

This review introduces these and other useful databases on which new methods for drug discovery can be developed.

METHODS

The scope of this review covers current documented and accessible databases and resources pertaining to glycomics. These were selected with the expectation that they may be useful for drug discovery research.

RESULTS/CONCLUSION

There is a plethora of glycomics databases that have much potential for drug discovery. This may seem daunting at first but this review helps to put some of these resources into perspective. Additionally, some thoughts on how to integrate these resources to allow more efficient research are presented.

Application of microarrays for deciphering the structure and function of the human glycome

Glycan structures were defined historically using multiple methods to determine composition, sequence, linkage, and anomericity of component monosaccharides. Such approaches have been replaced by more sensitive MS methods to profile or predict glycan structures, but these methods are limited in their ability to completely define glycan structures. Glycan-binding proteins, including lectins and antibodies, have been found to have exquisite binding specificities that can provide information about glycan structures. Here, we show glycan-binding proteins can be used along with MS to help define glycan linkages and other determinants in unknown glycans printed as shotgun glycan microarrays.

Developments in the identification of glycan biomarkers for the detection of cancer

Changes in glycosylation readily occur in cancer and other disease states. Thanks to recent advances in the development of analytical techniques and instrumentation, especially in mass spectrometry, it is now possible to identify blood-derived glycan-based biomarkers using glycomics strategies. This review is an overview of the developments made in the search for glycan-based cancer biomarkers and the technologies currently in use. It is anticipated that the progressing instrumental and bioinformatics developments will allow the identification of relevant glycan biomarkers for the diagnosis, early detection, and monitoring of cancer treatment with sufficient sensitivity and specificity for clinical use.

Quantitative glycomics strategies

The correlations between protein glycosylation and many biological processes and diseases are increasing the demand for quantitative glycomics strategies enabling sensitive monitoring of changes in the abundance and structure of glycans. This is currently attained through multiple strategies employing several analytical techniques such as capillary electrophoresis, liquid chromatography, and mass spectrometry. The detection and quantification of glycans often involve labeling with ionic and/or hydrophobic reagents. This step is needed in order to enhance detection in spectroscopic and mass spectrometric measurements. Recently, labeling with stable isotopic reagents has also been presented as a very viable strategy enabling relative quantitation. The different strategies available for reliable and sensitive quantitative glycomics are herein described and discussed.

Software tools for glycan profiling

We introduce three software tools, Cartoonist, GlycoWorkbench, and MultiGlycan, for N-glycan profiling of complex biological samples. Detailed instructions for using these tools are provided, and their performances are demonstrated by using real glycan profiling data.

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.