Semi-automated identification of N-Glycopeptides by hydrophilic interaction chromatography, nano-reverse-phase LC-MS/MS, and glycan database search

Glycopeptide database search and de novo sequencing with PEAKS GlycanFinder enable highly sensitive glycoproteomics

Here we present GlycanFinder, a database search and de novo sequencing tool for the analysis of intact glycopeptides from mass spectrometry data. GlycanFinder integrates peptide-based and glycan-based search strategies to address the challenge of complex fragmentation of glycopeptides. A deep learning model is designed to capture glycan tree structures and their fragment ions for de novo sequencing of glycans that do not exist in the database. We performed extensive analyses to validate the false discovery rates (FDRs) at both peptide and glycan levels and to evaluate GlycanFinder based on comprehensive benchmarks from previous community-based studies. Our results show that GlycanFinder achieved comparable performance to other leading glycoproteomics softwares in terms of both FDR control and the number of identifications. Moreover, GlycanFinder was also able to identify glycopeptides not found in existing databases. Finally, we conducted a mass spectrometry experiment for antibody N-linked glycosylation profiling that could distinguish isomeric peptides and glycans in four immunoglobulin G subclasses, which had been a challenging problem to previous studies.

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 immunoaffinity enrichment and N-glycan analysis of human plasma haptoglobin

Haptoglobin (Hp) is a positive acute phase protein, synthesized in the liver, with four N-glycosylation sites carrying mainly complex type N-glycans. Its glycosylation is altered in different types of diseases but still has not been extensively studied mainly due to analytical challenges, especially the lack of a fast, efficient, and robust high-throughput Hp isolation procedure. Here, we describe the development of a high-throughput method for Hp enrichment from human plasma, based on monolithic chromatographic support in immunoaffinity mode and downstream Hp N-glycome analysis by hydrophilic interaction ultrahigh-performance liquid chromatography with fluorescent detection (HILIC-UHPLC-FLR). Chromatographic monolithic supports in a 96-well format enable fast, efficient, and robust Hp enrichment directly from diluted plasma samples. The N-glycome analysis demonstrated that a degree of Hp deglycosylation differs depending on the conditions used for N-glycan release and on the specific glycosylation site, with Asn 241 being the most resistant to deglycosylation under tested conditions. HILIC-UHPLC-FLR analysis enables robust quantification of 28 individual chromatographic peaks, in which N-glycan compositions were determined by UHPLC coupled to electrospray ionization quadrupole time of flight mass spectrometry. The developed analytical approach enables fast evaluation of total Hp N-glycosylation and is applicable in large-scale studies.

The Influence of Clusterin Glycosylation Variability on Selected Pathophysiological Processes in the Human Body

The present review gathers together the most important information about variability in clusterin molecular structure, its profile, and the degree of glycosylation occurring in human tissues and body fluids in the context of the utility of these characteristics as potential diagnostic biomarkers of selected pathophysiological conditions. The carbohydrate part of clusterin plays a crucial role in many biological processes such as endocytosis and apoptosis. Many pathologies associated with neurodegeneration, carcinogenesis, metabolic diseases, and civilizational diseases (e.g., cardiovascular incidents and male infertility) have been described as causes of homeostasis disturbance, in which the glycan part of clusterin plays a very important role. The results of the discussed studies suggest that glycoproteomic analysis of clusterin may help differentiate the severity of hippocampal atrophy, detect the causes of infertility with an immune background, and monitor the development of cancer. Understanding the mechanism of clusterin (CLU) action and its binding epitopes may enable to indicate new therapeutic goals. The carbohydrate part of clusterin is considered necessary to maintain its proper molecular conformation, structural stability, and proper systemic and/or local biological activity. Taking into account the wide spectrum of CLU action and its participation in many processes in the human body, further studies on clusterin glycosylation variability are needed to better understand the molecular mechanisms of many pathophysiological conditions. They can also provide the opportunity to find new biomarkers and enrich the panel of diagnostic parameters for diseases that still pose a challenge for modern medicine.

Liquid chromatography and capillary electrophoresis in glycomic and glycoproteomic analysis

Glycosylation is one of the most significant and abundant post-translational modifications in cells. Glycomic and glycoproteomic analyses involve the characterization of oligosaccharides (glycans) conjugated to proteins. Glycomic and glycoproteomic analysis is highly challenging because of the large diversity of structures, low abundance, site-specific heterogeneity, and poor ionization efficiency of glycans and glycopeptides in mass spectrometry (MS). MS is a key tool for characterization of glycans and glycopeptides. However, MS alone does not always provide full structural and quantitative information for many reasons, and thus MS is combined with some separation technique. This review focuses on the role of separation techniques used in glycomic and glycoproteomic analyses, liquid chromatography and capillary electrophoresis. The most important separation conditions and results are presented and discussed.

Graphical abstract

Glycomic and Glycoproteomic Techniques in Neurodegenerative Disorders and Neurotrauma: Towards Personalized Markers

The proteome represents all the proteins expressed by a genome, a cell, a tissue, or an organism at any given time under defined physiological or pathological circumstances. Proteomic analysis has provided unparalleled opportunities for the discovery of expression patterns of proteins in a biological system, yielding precise and inclusive data about the system. Advances in the proteomics field opened the door to wider knowledge of the mechanisms underlying various post-translational modifications (PTMs) of proteins, including glycosylation. As of yet, the role of most of these PTMs remains unidentified. In this state-of-the-art review, we present a synopsis of glycosylation processes and the pathophysiological conditions that might ensue secondary to glycosylation shortcomings. The dynamics of protein glycosylation, a crucial mechanism that allows gene and pathway regulation, is described. We also explain how-at a biomolecular level-mutations in glycosylation-related genes may lead to neuropsychiatric manifestations and neurodegenerative disorders. We then analyze the shortcomings of glycoproteomic studies, putting into perspective their downfalls and the different advanced enrichment techniques that emanated to overcome some of these challenges. Furthermore, we summarize studies tackling the association between glycosylation and neuropsychiatric disorders and explore glycoproteomic changes in neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Huntington disease, multiple sclerosis, and amyotrophic lateral sclerosis. We finally conclude with the role of glycomics in the area of traumatic brain injury (TBI) and provide perspectives on the clinical application of glycoproteomics as potential diagnostic tools and their application in personalized medicine.

Hydroxyl radical footprinting analysis of a human haptoglobin-hemoglobin complex

Methods of structural mass spectrometry have become more popular to study protein structure and dynamics. Among them, fast photochemical oxidation of proteins (FPOP) has several advantages such as irreversibility of modifications and more facile determination of the site of modification with single residue resolution. In the present study, FPOP analysis was applied to study the hemoglobin (Hb) - haptoglobin (Hp) complex allowing identification of respective regions altered upon the complex formation. FPOP footprinting using a timsTOF Pro mass spectrometer revealed structural information for 84 and 76 residues in Hp and Hb, respectively, including statistically significant differences in the modification extent below 0.3%. The most affected residues upon complex formation were Met76 and Tyr140 in Hbα, and Tyr280 and Trp284 in Hpβ. The data allowed determination of amino acids directly involved in Hb - Hp interactions and those located outside of the interaction interface yet affected by the complex formation. Also, previously modeled interaction between Hb βTrp37 and Hp βPhe292 was not confirmed by our data. Data are available via ProteomeXchange with identifier PXD021621.

The glycosylation in SARS-CoV-2 and its receptor ACE2

Coronavirus disease 2019 (COVID-19), a highly infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has infected more than 235 million individuals and led to more than 4.8 million deaths worldwide as of October 5 2021. Cryo-electron microscopy and topology show that the SARS-CoV-2 genome encodes lots of highly glycosylated proteins, such as spike (S), envelope (E), membrane (M), and ORF3a proteins, which are responsible for host recognition, penetration, binding, recycling and pathogenesis. Here we reviewed the detections, substrates, biological functions of the glycosylation in SARS-CoV-2 proteins as well as the human receptor ACE2, and also summarized the approved and undergoing SARS-CoV-2 therapeutics associated with glycosylation. This review may not only broad the understanding of viral glycobiology, but also provide key clues for the development of new preventive and therapeutic methodologies against SARS-CoV-2 and its variants.

Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis

Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N- and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved 'high-coverage' and 'high-accuracy' glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics.

Recent Advances in Software Tools for More Generic and Precise Intact Glycopeptide Analysis

Intact glycopeptide identification has long been known as a key and challenging barrier to the comprehensive and accurate understanding the role of glycosylation in an organism. Intact glycopeptide analysis is a blossoming field that has received increasing attention in recent years. MS-based strategies and relative software tools are major drivers that have greatly facilitated the analysis of intact glycopeptides, particularly intact N-glycopeptides. This article provides a systematic review of the intact glycopeptide-identification process using MS data generated in shotgun proteomic experiments, which typically focus on N-glycopeptide analysis. Particular attention is paid to the software tools that have been recently developed in the last decade for the interpretation and quality control of glycopeptide spectra acquired using different MS strategies. The review also provides information about the characteristics and applications of these software tools, discusses their advantages and disadvantages, and concludes with a discussion of outstanding tools.

Glycan Compositions with GlyConnect Compozitor to Enhance Glycopeptide Identification

Glycoproteomics is unquestionably on the rise and its current development benefits from past experience in proteomics, in particular when attending to bioinformatics needs. An extensive range of software solutions is available, but the reproducibility of mass spectrometry data processing remains challenging. One of the key issues in running automated glycopeptide identification software is the selection of a reference glycan composition file. The default choices are often too broad, and a fastidious literature search to properly target this selection can be avoided. This chapter suggests the use of GlyConnect Compozitor to collect relevant information on glycosylation in a given tissue or cell line and shape an appropriate glycan composition set that can be input in the majority of search engines accommodating user-defined compositions.

Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis

Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N- and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved 'high-coverage' and 'high-accuracy' glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics.

Databases and Bioinformatic Tools for Glycobiology and Glycoproteomics

Glycosylation plays critical roles in various biological processes and is closely related to diseases. Deciphering the glycocode in diverse cells and tissues offers opportunities to develop new disease biomarkers and more effective recombinant therapeutics. In the past few decades, with the development of glycobiology, glycomics, and glycoproteomics technologies, a large amount of glycoscience data has been generated. Subsequently, a number of glycobiology databases covering glycan structure, the glycosylation sites, the protein scaffolds, and related glycogenes have been developed to store, analyze, and integrate these data. However, these databases and tools are not well known or widely used by the public, including clinicians and other researchers who are not in the field of glycobiology, but are interested in glycoproteins. In this study, the representative databases of glycan structure, glycoprotein, glycan-protein interactions, glycogenes, and the newly developed bioinformatic tools and integrated portal for glycoproteomics are reviewed. We hope this overview could assist readers in searching for information on glycoproteins of interest, and promote further clinical application of glycobiology.

Glycomics and glycoproteomics of viruses: Mass spectrometry applications and insights toward structure-function relationships

The advancement of viral glycomics has paralleled that of the mass spectrometry glycomics toolbox. In some regard the glycoproteins studied have provided the impetus for this advancement. Viral proteins are often highly glycosylated, especially those targeted by the host immune system. Glycosylation tends to be dynamic over time as viruses propagate in host populations leading to increased number of and/or "movement" of glycosylation sites in response to the immune system and other pressures. This relationship can lead to highly glycosylated, difficult to analyze glycoproteins that challenge the capabilities of modern mass spectrometry. In this review, we briefly discuss five general areas where glycosylation is important in the viral niche and how mass spectrometry has been used to reveal key information regarding structure-function relationships between viral glycoproteins and host cells. We describe the recent past and current glycomics toolbox used in these analyses and give examples of how the requirement to analyze these complex glycoproteins has provided the incentive for some advances seen in glycomics mass spectrometry. A general overview of viral glycomics, special cases, mass spectrometry methods and work-flows, informatics and complementary chemical techniques currently used are discussed. © 2020 The Authors. Mass Spectrometry Reviews published by John Wiley & Sons Ltd. Mass Spec Rev.

Flow Chemistry System for Carbohydrate Analysis by Rapid Labeling of Saccharides after Glycan Hydrolysis

This study demonstrates the utilization of a flow chemistry system for continuous glycan hydrolysis and saccharide labeling to assist with the existing methods in glycan structural analysis. Acidic hydrolysis of glycans could be accelerated in a flow system. Aldoses and α-ketoacid-type saccharides were effectively labeled with naphthalene-2,3-diamine (NADA) at 60 °C for 10 min to form the fluorescent naphthimidazole (NAIM) and quinoxalinone (QXO) derivatives, respectively. The NADA-labeled derivatives improved the structural determination and composition analysis for their parent saccharides by using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS), liquid chromatography mass spectrometry (LC-MS), and nuclear magnetic resonance (NMR). Furthermore, this protocol was applied to determine the SA–Gal–Glc sequence of GM3-sugar out of six possible permutations.

Integrated Strategy for Large-Scale Investigation on Protein Core Fucosylation Stoichiometry Based on Glycan-Simplification and Paired-Peaks-Extraction

Core fucosylation (CF) is a special form of N-glycosylation and plays an important role in pathological and biological processes. Increasing efforts in this area are focused on the identification of CF glycosites, whereas evidence showed that the stoichiometry of CF occupancy is functionally important. Here, an integrated strategy based on "Glycan-Simplification and Paired-Peaks-extraction" (GSPPE) for detecting large-scale stoichiometries of CF was developed. After HILIC enrichment of intact glycopeptides, sequential cleavages by endoglycosidases H and endoglycosidases F3 were performed to generate simplified glycopeptide forms (SGFs), i.e., peptide-GlcNAc (pep-HN) and peptide-GlcNAc-Fucose (pep-CF). These paired SGFs were found to be eluted consecutively on a reversed-phase chromatography column, which allowed us to obtain peak areas of SGF pairs, even if only one of the peaks was captured by the mass spectrometer (MS), by introducing the Paired-Peaks-Extraction algorithm. Thus, the missing value dilemma of random data-dependent MS/MS acquisition was reduced and the stoichiometry of site-specific CF could be calculated. We systematically evaluated the feasibility of this strategy using standard glycoproteins and then explored urinary samples from healthy individuals and hepatocellular carcinoma (HCC) patients. In total, 1449 highly reliable core fucose glycosites and their corresponding CF stoichiometries were obtained. Dozens of glycosites that differed significantly in the urine of healthy individuals and HCC patients were disclosed. The developed approach and program presented here may promote studies on core fucosylation and lead to a deeper understanding of their dysregulation in physiological- or pathological processes.

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.

DecoyDeveloper: An On-Demand, De Novo Decoy Glycopeptide Generator

Glycopeptide analysis is a growing field that is struggling to adopt effective, automated tools. Many creative workflows and software apps have emerged recently that offer promising capabilities for assigning glycopeptides to MS data in an automated fashion. The effectiveness of these tools is best measured and improved by determining how often they would select a glycopeptide decoy as a spectral match, instead of its correct assignment; yet generating the appropriate number and type of glycopeptide decoys can be challenging. To address this need, we have designed DecoyDeveloper, an on-demand decoy glycopeptide generator that can produce a high volume of decoys with low mass differences. DecoyDeveloper has a simple user interface and is capable of producing large sets of decoys containing complete, biologically relevant glycan and peptide sequences. We demonstrate the tool's efficiency by applying it to a set of 80 glycopeptide targets. This tool is freely available and can be found at http://glycopro.chem.ku.edu/J1.php .

An Improved Approach for N-Linked Glycan Structure Identification from HCD MS/MS Spectra

Glycosylation is a frequently observed post-translational modification on proteins. Currently, tandem mass spectrometry (MS/MS) serves as an efficient analytical technique for characterizing structures of oligosaccharides. However, developing effective computational approaches for identifying glycan structures from mass spectra is still a great challenge in glycoproteomics research. In this study, we proposed an approach for matching the input spectra with glycan structures acquired from a glycan structure database by incorporating a de novo sequencing assisted ranking scheme. The proposed approach is implemented as a software tool, GlycoNovoDB, for automated glycan structure identification from HCD MS/MS of glycopeptides. Experimental results showed that GlycoNovoDB can identify glycans effectively and has better performance than our previously proposed de novo sequencing algorithm as well as another software GlycoMaster DB.

Current Technologies for Complex Glycoproteomics and Their Applications to Biology/Disease-Driven Glycoproteomics

Glycoproteomics is an important recent advance in the field of glycoscience. In glycomics, glycan structures are comprehensively analyzed after glycans are released from glycoproteins. However, a major limitation of glycomics is the lack of insight into glycoprotein functions. The Biology/Disease-driven Human Proteome Project has a particular focus on biological and medical applications. Glycoproteomics technologies aimed at obtaining a comprehensive understanding of intact glycoproteins, i.e., the kind of glycan structures that are attached to particular amino acids and proteins, have been developed. This Review focuses on the recent progress of the technologies and their applications. First, the methods for large-scale identification of both N- and O-glycosylated proteins are summarized. Next, the progress of analytical methods for intact glycopeptides is outlined. MS/MS-based methods were developed for improving the sensitivity and speed of the mass spectrometer, in parallel with the software for complex spectrum assignment. In addition, a unique approach to identify intact glycopeptides using MS1-based accurate masses is introduced. Finally, as an advance of glycomics, two approaches to provide the spatial distribution of glycans in cells are described, i.e., MS imaging and lectin microarray. These methods allow rapid glycomic profiling of different types of biological samples and thus facilitate glycoproteomics.

N-Linked Glycopeptide Identification Based on Open Mass Spectral Library Search

Confident characterization of intact glycopeptides is a challenging task in mass spectrometry-based glycoproteomics due to microheterogeneity of glycosylation, complexity of glycans, and insufficient fragmentation of peptide bones. Open mass spectral library search is a promising computational approach to peptide identification, but its potential in the identification of glycopeptides has not been fully explored. Here we present pMatchGlyco, a new spectral library search tool for intact N-linked glycopeptide identification using high-energy collisional dissociation (HCD) tandem mass spectrometry (MS/MS) data. In pMatchGlyco, (1) MS/MS spectra of deglycopeptides are used to create spectral library, (2) MS/MS spectra of glycopeptides are matched to the spectra in library in an open (precursor tolerant) manner and the glycans are inferred, and (3) a false discovery rate is estimated for top-scored matches above a threshold. The efficiency and reliability of pMatchGlyco were demonstrated on a data set of mixture sample of six standard glycoproteins and a complex glycoprotein data set generated from human cancer cell line OVCAR3.

Reanalysis of Global Proteomic and Phosphoproteomic Data Identified a Large Number of Glycopeptides

Protein glycosylation plays fundamental roles in many cellular processes, and previous reports have shown dysregulation to be associated with several human diseases, including diabetes, cancer, and neurodegenerative disorders. Despite the vital role of glycosylation for proper protein function, the analysis of glycoproteins has been lagged behind to other protein modifications. In this study, we describe the reanalysis of global proteomic data from breast cancer xenograft tissues using recently developed software package GPQuest 2.0, revealing a large number of previously unidentified N-linked glycopeptides. More importantly, we found that using immobilized metal affinity chromatography (IMAC) technology for the enrichment of phosphopeptides had coenriched a substantial number of sialoglycopeptides, allowing for a large-scale analysis of sialoglycopeptides in conjunction with the analysis of phosphopeptides. Collectively, combined tandem mass spectrometry (MS/MS) analyses of global proteomic and phosphoproteomic data sets resulted in the identification of 6 724 N-linked glycopeptides from 617 glycoproteins derived from two breast cancer xenograft tissues. Next, we utilized GPQuest 2.0 for the reanalysis of global and phosphoproteomic data generated from 108 human breast cancer tissues that were previously analyzed by Clinical Proteomic Analysis Consortium (CPTAC). Reanalysis of the CPTAC data set resulted in the identification of 2 683 glycopeptides from the global proteomic data set and 4 554 glycopeptides from phosphoproteomic data set, respectively. Together, 11 292 N-linked glycopeptides corresponding to 1 731 N-linked glycosites from 883 human glycoproteins were identified from the two data sets. This analysis revealed an extensive number of glycopeptides hidden in the global and enriched in IMAC-based phosphopeptide-enriched proteomic data, information which would have remained unknown from the original study otherwise. The reanalysis described herein can be readily applied to identify glycopeptides from already existing data sets, providing insight into many important facets of protein glycosylation in different biological, physiological, and pathological processes.

Recent advances in mass spectrometry-based glycoproteomics

Protein glycosylation plays fundamental roles in many biological processes as one of the most common, and the most complex, posttranslational modification. Alterations in glycosylation profile are now known to be associated with many diseases. As a result, the discovery and detailed characterization of glycoprotein disease biomarkers is a primary interest of biomedical research. Advances in mass spectrometry (MS)-based glycoproteomics and glycomics are increasingly enabling qualitative and quantitative approaches for site-specific structural analysis of protein glycosylation. While the complexity presented by glycan heterogeneity and the wide dynamic range of clinically relevant samples like plasma, serum, cerebrospinal fluid, and tissue make comprehensive analyses of the glycoproteome a challenging task, the ongoing efforts into the development of glycoprotein enrichment, enzymatic digestion, and separation strategies combined with novel quantitative MS methodologies have greatly improved analytical sensitivity, specificity, and throughput. This review summarizes current MS-based glycoproteomics approaches and highlights recent advances in its application to cancer biomarker and neurodegenerative disease research.

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.

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

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

Conformational characterization of nerve growth factor-β reveals that its regulatory pro-part domain stabilizes three loop regions in its mature part

Nerve growth factor-β (NGF) is essential for the correct development of the nervous system. NGF exists in both a mature form and a pro-form (proNGF). The two forms have opposing effects on neurons: NGF induces proliferation, whereas proNGF induces apoptosis via binding to a receptor complex of the common neurotrophin receptor (p75NTR) and sortilin. The overexpression of both proNGF and sortilin has been associated with several neurodegenerative diseases. Insights into the conformational differences between proNGF and NGF are central to a better understanding of the opposing mechanisms of action of NGF and proNGF on neurons. However, whereas the structure of NGF has been determined by X-ray crystallography, the structural details for proNGF remain elusive. Here, using a sensitive MS-based analytical method to measure the hydrogen/deuterium exchange of proteins in solution, we analyzed the conformational properties of proNGF and NGF. We detected the presence of a localized higher-order structure motif in the pro-part of proNGF. Furthermore, by comparing the hydrogen/deuterium exchange in the mature part of NGF and proNGF, we found that the presence of the pro-part in proNGF causes a structural stabilization of three loop regions in the mature part, possibly through a direct molecular interaction. Moreover, using tandem MS analyses, we identified two N-linked and two O-linked glycosylations in the pro-part of proNGF. These results advance our knowledge of the conformational properties of proNGF and NGF and help provide a rationale for the diverse biological effects of NGF and proNGF at the molecular level.

Microfluidic Capillary Electrophoresis-Mass Spectrometry for Analysis of Monosaccharides, Oligosaccharides, and Glycopeptides

Glycomics and glycoproteomics analyses by mass spectrometry require efficient front-end separation methods to enable deep characterization of heterogeneous glycoform populations. Chromatography methods are generally limited in their ability to resolve glycoforms using mobile phases that are compatible with online liquid chromatography-mass spectrometry (LC-MS). The adoption of capillary electrophoresis-mass spectrometry methods (CE-MS) for glycomics and glycoproteomics is limited by the lack of convenient interfaces for coupling the CE devices to mass spectrometers. Here, we describe the application of a microfluidics-based CE-MS system for analysis of released glycans, glycopeptides and monosaccharides. We demonstrate a single CE method for three different modalities, thus contributing to comprehensive glycoproteomics analyses. In addition, we explored compatible sample derivatization methods. We used glycan TMT-labeling to improve electrophoretic migration and enable multiplexed quantitation by tandem MS. We used sialic acid linkage-specific derivatization methods to improve separation and the level of information obtained from a single analytical step. Capillary electrophoresis greatly improved glycoform separation for both released glycans and glycopeptides over that reported for chromatography modes more frequently employed for such analyses. Overall, the CE-MS method described here enables rapid setup and analysis of glycans and glycopeptides using mass spectrometry.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2011-2012

This review is the seventh update of the original article published in 1999 on the application of MALDI mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2012. General aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, and fragmentation are covered in the first part of the review and applications to various structural types constitute the remainder. The main groups of compound are oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides, and biopharmaceuticals. Much of this material is presented in tabular form. Also discussed are medical and industrial applications of the technique, studies of enzyme reactions, and applications to chemical synthesis. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:255-422, 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.

Changes in the expression of N- and O-glycopeptides in patients with colorectal cancer and hepatocellular carcinoma quantified by full-MS scan FT-ICR and multiple reaction monitoring

Alternations in the glycosylation of proteins have been described in connection with several cancers, including hepatocellular carcinoma (HCC) and colorectal cancer. Analytical tools, which use combination of liquid chromatography and mass spectrometry, allow precise and sensitive description of these changes. In this study, we use MRM and FT-ICR operating in full-MS scan, to determine ratios of intensities of specific glycopeptides in HCC, colorectal cancer, and liver metastasis of colorectal cancer. Haptoglobin, hemopexin and complement factor H were detected after albumin depletion and the N-linked glycopeptides with fucosylated glycans were compared with their non-fucosylated forms. In addition, sialylated forms of an O-linked glycopeptide of hemopexin were quantified in the same samples. We observe significant increase in fucosylation of all three proteins and increase in bi-sialylated O-glycopeptide of hemopexin in HCC of hepatitis C viral (HCV) etiology by both LC-MS methods. The results of the MRM and full-MS scan FT-ICR analyses provide comparable quantitative readouts in spite of chromatographic, mass spectrometric and data analysis differences. Our results suggest that both workflows allow adequate relative quantification of glycopeptides and suggest that HCC of HCV etiology differs in glycosylation from colorectal cancer and liver metastasis of colorectal cancer.

SIGNIFICANCE

The article compares N- and O-glycosylation of several serum proteins in different diseases by a fast and easy sample preparation procedure in combination with high resolution Fourier transform ion cyclotron resonance mass spectrometry. The results show successful glycopeptides relative quantification in a complex peptide mixture by the high resolution instrument and the detection of glycan differences between the different types of cancer diseases. The presented method is comparable to conventional targeted MRM approach but allows additional curation of the data.

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/ .

Integrated Omics and Computational Glycobiology Reveal Structural Basis for Influenza A Virus Glycan Microheterogeneity and Host Interactions

Despite sustained biomedical research effort, influenza A virus remains an imminent threat to the world population and a major healthcare burden. The challenge in developing vaccines against influenza is the ability of the virus to mutate rapidly in response to selective immune pressure. Hemagglutinin is the predominant surface glycoprotein and the primary determinant of antigenicity, virulence and zoonotic potential. Mutations leading to changes in the number of HA glycosylation sites are often reported. Such genetic sequencing studies predict at best the disruption or creation of sequons for N-linked glycosylation; they do not reflect actual phenotypic changes in HA structure. Therefore, combined analysis of glycan micro and macro-heterogeneity and bioassays will better define the relationships among glycosylation, viral bioactivity and evolution. We present a study that integrates proteomics, glycomics and glycoproteomics of HA before and after adaptation to innate immune system pressure. We combined this information with glycan array and immune lectin binding data to correlate the phenotypic changes with biological activity. Underprocessed glycoforms predominated at the glycosylation sites found to be involved in viral evolution in response to selection pressures and interactions with innate immune-lectins. To understand the structural basis for site-specific glycan microheterogeneity at these sites, we performed structural modeling and molecular dynamics simulations. We observed that the presence of immature, high-mannose type glycans at a particular site correlated with reduced accessibility to glycan remodeling enzymes. Further, the high mannose glycans at sites implicated in immune lectin recognition were predicted to be capable of forming trimeric interactions with the immune-lectin surfactant protein-D.

Site-specific characterization of N-linked glycosylation in human urinary glycoproteins and endogenous glycopeptides

Glycosylation is a very important post-translational modification involved in various cellular processes, such as cell adhesion, signal transduction and immune response. Urine is a rich source of glycoproteins and attractive biological fluid for biomarker discovery, owing to its availability, ease of collection, and correlation with pathophysiology of diseases. Although the urinary proteomics have been explored previously, the urinary glycoproteome characterization remains challenging requiring the development and optimization of analytical and bioinformatics methods for protein glycoprofiling. This study describes the high confident identification of 472 unique N-glycosylation sites covering 256 urinary glycoproteins. Besides, 202 unique N-glycosylation sites were identified in low molecular weight endogenous glycopeptides, which belong to 90 glycoproteins. Global site-specific characterization of the N-linked glycan heterogeneity was achieved by intact glycopeptide analysis, revealing 303 unique glycopeptides most of them displaying complex/hybrid glycans composed by sialic acid and fucose. These datasets consist in a valuable resource of glycoproteins and N-glycosylation sites found in healthy human urine that can be further explored in different disorders, in which the N-linked glycosylation may be aberrant.

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

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

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

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

Comprehensive analysis of protein glycosylation by solid-phase extraction of N-linked glycans and glycosite-containing peptides

Comprehensive characterization of protein glycosylation is critical for understanding the structure and function of glycoproteins. However, due to the complexity and heterogeneity of glycoprotein conformations, current glycoprotein analyses focus mainly on either the de-glycosylated glycosylation site (glycosite)-containing peptides or the released glycans. Here, we describe a chemoenzymatic method called solid phase extraction of N-linked glycans and glycosite-containing peptides (NGAG) for the comprehensive characterization of glycoproteins that is able to determine glycan heterogeneity for individual glycosites in addition to providing information about the total N-linked glycan, glycosite-containing peptide and glycoprotein content of complex samples. The NGAG method can also be applied to quantitatively detect glycoprotein alterations in total and site-specific glycan occupancies.

Carbohydrates on Proteins: Site-Specific Glycosylation Analysis by Mass Spectrometry

Glycosylation on proteins adds complexity and versatility to these biologically vital macromolecules. To unveil the structure-function relationship of glycoproteins, glycopeptide-centric analysis using mass spectrometry (MS) has become a method of choice because the glycan is preserved on the glycosylation site and site-specific glycosylation profiles of proteins can be readily determined. However, glycopeptide analysis is still challenging given that glycopeptides are usually low in abundance and relatively difficult to detect and the resulting data require expertise to analyze. Viewing the urgent need to address these challenges, emerging methods and techniques are being developed with the goal of analyzing glycopeptides in a sensitive, comprehensive, and high-throughput manner. In this review, we discuss recent advances in glycoprotein and glycopeptide analysis, with topics covering sample preparation, analytical separation, MS and tandem MS techniques, as well as data interpretation and automation.

Clusterin glycopeptide variant characterization reveals significant site-specific glycan changes in the plasma of clear cell renal cell carcinoma

Cancer-related alterations in protein glycosylation may serve as diagnostic or prognostic biomarkers or may be used for monitoring disease progression. Clusterin is a medium abundance, yet heavily glycosylated, glycoprotein that is upregulated in clear cell renal cell carcinoma (ccRCC) tumors. We recently reported that the N-glycan profile of clusterin is altered in the plasma of ccRCC patients. Here, we characterized the occupancy and the degree of heterogeneity of individual N-glycosylation sites of clusterin in the plasma of patients diagnosed with localized ccRCC, before and after curative nephrectomy (n = 40). To this end, we used tandem mass spectrometry of immunoaffinity-enriched plasma samples to analyze the individual glycosylation sites in clusterin. We determined the levels of targeted clusterin glycoforms containing either a biantennary digalactosylated disialylated (A2G2S2) glycan or a core fucosylated biantennary digalactosylated disialylated (FA2G2S2) glycan at N-glycosite N374. We showed that the presence of these two clusterin glycoforms differed significantly in the plasma of patients prior to and after curative nephrectomy for localized ccRCC. Removal of ccRCC led to a significant increase in the levels of both FA2G2S2 and A2G2S2 glycans in plasma clusterin. These changes were further confirmed by lectin blotting of plasma clusterin. It is envisioned that these identified glycan alterations may provide an additional level of therapeutic or biomarker sensitivity than levels currently achievable by monitoring expression differences alone.

Synthesis of a hydrophilic maltose functionalized Au NP/PDA/Fe3O4-RGO magnetic nanocomposite for the highly specific enrichment of glycopeptides

A novel approach was developed to synthesize a hydrophilic thiol-terminated maltose-functionalized Au NP/PDA/Fe₃O₄-RGO nanocomposite which exhibited high selectivity and detection sensitivity in the enrichment of glycopeptides from complex samples.