Label-free glycopeptide quantification for biomarker discovery in human sera

Development of a novel lectin-based gold nanoparticle point-of-care immunoassay for rapid diagnosis of patients with severe Dengue infection

Rapid diagnosis of patients with severe Dengue infection can be useful for the efficient clinical management of cases caused by the Dengue virus. Lateral Flow Immunoassay (LFIA) have been broadly used for rapid Dengue diagnosis, because of their quick readouts with the human eye, simplicity of use, and affordability. Despite the availability of several commercial Dengue point-of-care assays, none has shown to be successful in discriminating between severe and nonsevere forms of Dengue infection. In the current study, for the first time, a novel lectin-based point-of-care assay for the early detection of patients with severe Dengue infection with gold-adorned sheets as detection labels is being reported. In this assay, Dengue severity was diagnosed by detecting the glycosylation profile of vitronectin, a known Dengue severity marker. Two lectins were employed namely DSA (Datura stramonium) and MAA (Maackia amurensis) that can recognize specific glycans like galactose Gal-(1-4) GlcNAc and sialic acid in an (α2-3) linkage, which displayed high sensitivity and high specificity, i.e. 90% and 85% for DSA and 90.91% and 95% for MAA. The new assay has a detection limit of 5 µg µl-1 and enables the quick (30 min) and sensitive detection of severe Dengue cases. The reported point-of-care immunoassay exhibits considerable promise for early identification of patients with Dengue severity.

GlycoHybridSeq: Automated Identification of N-Linked Glycopeptides Using Electron Transfer/High-Energy Collision Dissociation (EThcD)

Glycosylation is one of the most common post-translational modifications (PTM) occurring in a large variety of proteins with important biological functions in human and other higher organisms. Liquid chromatography tandem mass spectrometry (LC-MS/MS) has been routinely used to characterize site-specific protein glycosylation at high throughput in complex glycoproteomic samples. Recently, electron transfer/high-energy collision dissociation (EThcD) was introduced for glycopeptide identification, which offers rich structural information on glycopepides with the fragment ions from the cleavages of both the glycan and the peptide backbone. Herein, we present the software GlycoHybridSeq for automated interpretation of EThcD-MS/MS spectra from glycoproteomic data using a customized scoring function, which enables the functionalities of identifying glycopeptides, characterizing glycosylation sites, and distinguishing some isomeric glycans. We evaluate GlycoHybridSeq on glycoproteomic data collected for cancer biomarker discovery. The results showed that it achieved comparable or better performance than that of Byonic and MSFragger. GlycoHybridSeq is released as an open source software and is ready to be used in large-scale glycoproteomic data analyses.

Recent Advances in Analytical Approaches for Glycan and Glycopeptide Quantitation

Growing implications of glycosylation in physiological occurrences and human disease have prompted intensive focus on revealing glycomic perturbations through absolute and relative quantification. Empowered by seminal methodologies and increasing capacity for detection, identification, and characterization, the past decade has provided a significant increase in the number of suitable strategies for glycan and glycopeptide quantification. Mass-spectrometry-based strategies for glycomic quantitation have grown to include metabolic incorporation of stable isotopes, deposition of mass difference and mass defect isotopic labels, and isobaric chemical labeling, providing researchers with ample tools for accurate and robust quantitation. Beyond this, workflows have been designed to harness instrument capability for label-free quantification, and numerous software packages have been developed to facilitate reliable spectrum scoring. In this review, we present and highlight the most recent advances in chemical labeling and associated techniques for glycan and glycopeptide quantification.

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.

Proteogenomic examination of esophageal squamous cell carcinoma (ESCC): new lines of inquiry

Introduction: Esophageal squamous cell carcinoma (ESCC), a histopathologic subtype of esophageal cancer is a major cause of cancer-related morbidity and mortality worldwide. This is primarily because patients are diagnosed at an advanced stage by the time symptoms appear. The genomics and mass spectrometry-based proteomics continue to provide important leads toward biomarker discovery for ESCC. However, such leads are yet to be translated into clinical utilities. Areas covered: We gathered information pertaining to proteomics and proteogenomics efforts in ESCC from the literature search until 2020. An overview of omics approaches to discover the candidate biomarkers for ESCC were highlighted. We present a summary of recent investigations of alterations in the level of gene and protein expression observed in biological samples including body fluids, tissue/biopsy and in vitro-based models. Expert opinion: A large number of protein-based biomarkers and therapeutic targets are being used in cancer therapy. Several candidates are being developed as diagnostics and prognostics for the management of cancers. High-resolution proteomic and proteogenomic approaches offer an efficient way to identify additional candidate biomarkers for diagnosis, monitoring of disease progression, prediction of response to chemo and radiotherapy. Some of these biomarkers can also be developed as therapeutic targets.

Relative Retention Time Estimation Improves N-Glycopeptide Identifications by LC-MS/MS

Glycopeptides identified by tandem mass spectrometry rely on the identification of the peptide backbone sequence and the attached glycan(s) by the incomplete fragmentation of both moieties. This may lead to ambiguous identifications where multiple structures could explain the same spectrum equally well due to missing information in the mass spectrum or incorrect precursor mass determination. To date, approaches to solving these problems have been limited, and few inroads have been made to address these issues. We present a technique to address some of these challenges and demonstrate it on previously published data sets. We use a linear modeling approach to learn the influence of the glycan composition on the retention time of a glycopeptide and use these models to validate glycopeptides within the same experiment, detecting over 400 incorrect cases during the MS/MS search and correcting 75 cases that could not be identified based on mass alone. We make this technique available as a command line executable program, written in Python and C, freely available at https://github.com/mobiusklein/glycresoft in source form, with precompiled binaries for Windows.

Glycopeptide variable window SWATH for improved data independent acquisition glycoprotein analysis

N-glycosylation plays an essential role in regulating protein folding and function in eukaryotic cells. Sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH) has proven useful as a data independent acquisition (DIA) MS method for analysis of glycoproteins and their glycan modifications. By separating the entire m/z range into consecutive isolation windows, DIA-MS allows comprehensive MS data acquisition and high-sensitivity detection of molecules of interest. Variable width DIA windows allow optimal analyte measurement, as peptide ions are not evenly distributed across the full m/z range. However, the m/z distribution of glycopeptides is different to that of unmodified peptides because of their large glycan structures. Here, we improved the performance of DIA glycoproteomics by using variable width windows optimized for glycopeptides. This method allocates narrow windows at m/z ranges rich in glycopeptides, improving analytical specificity and performance. We show that related glycoforms must fall in separate windows to allow accurate glycopeptide measurement. We demonstrate the utility of the method by comparing the cell wall glycoproteomes of wild-type and N-glycan biosynthesis deficient yeast and showing improved measurement of glycopeptides with different glycan structures. Our results highlight the importance of appropriately optimized DIA methods for measurement of post-translationally modified peptides.

Machine Learning Classifies Core and Outer Fucosylation of N-Glycoproteins Using Mass Spectrometry

Protein glycosylation is known to be involved in biological progresses such as cell recognition, growth, differentiation, and apoptosis. Fucosylation of glycoproteins plays an important role for structural stability and function of N-linked glycoproteins. Although many of biological and clinical studies of protein fucosylation by fucosyltransferases has been reported, structural classification of fucosylated N-glycoproteins such as core or outer isoforms remains a challenge. Here, we report for the first time the classification of N-glycopeptides as core- and outer-fucosylated types using tandem mass spectrometry (MS/MS) and machine learning algorithms such as the deep neural network (DNN) and support vector machine (SVM). Training and test sets of more than 800 MS/MS spectra of N-glycopeptides from the immunoglobulin gamma and alpha 1-acid-glycoprotein standards were selected for classification of the fucosylation types using supervised learning models. The best-performing model had an accuracy of more than 99% against manual characterization and area under the curve values greater than 0.99, which were calculated by probability scores from target and decoy datasets. Finally, this model was applied to classify fucosylated N-glycoproteins from human plasma. A total of 82N-glycopeptides, with 54 core-, 24 outer-, and 4 dual-fucosylation types derived from 54 glycoproteins, were commonly classified as the same type in both the DNN and SVM. Specifically, outer fucosylation was dominant in tri- and tetra-antennary N-glycopeptides, while core fucosylation was dominant in the mono-, bi-antennary and hybrid types of N-glycoproteins in human plasma. Thus, the machine learning methods can be combined with MS/MS to distinguish between different isoforms of fucosylated N-glycopeptides.

N-glycopeptide Signatures of IgA2 in Serum from Patients with Hepatitis B Virus-related Liver Diseases

N-glycosylation alteration has been reported in liver diseases. Characterizing N-glycopeptides that correspond to N-glycan structure with specific site information enables better understanding of the molecular pathogenesis of liver damage and cancer. Here, unbiased quantification of N-glycopeptides of a cluster of serum glycoproteins with 40-55 kDa molecular weight (40-kDa band) was investigated in hepatitis B virus (HBV)-related liver diseases. We used an N-glycopeptide method based on 18O/16O C-terminal labeling to obtain 82 comparisons of serum from patients with HBV-related hepatocellular carcinoma (HCC) and liver cirrhosis (LC). Then, multiple reaction monitoring (MRM) was performed to quantify N-glycopeptide relative to the protein content, especially in the healthy donor-HBV-LC-HCC cascade. TPLTAN205ITK (H5N5S1F1) and (H5N4S2F1) corresponding to the glycopeptides of IgA2 were significantly elevated in serum from patients with HBV infection and even higher in HBV-related LC patients, as compared with healthy donor. In contrast, the two glycopeptides of IgA2 fell back down in HBV-related HCC patients. In addition, the variation in the abundance of two glycopeptides was not caused by its protein concentration. The altered N-glycopeptides might be part of a unique glycan signature indicating an IgA-mediated mechanism and providing potential diagnostic clues in HBV-related liver diseases.

Recent advances in mass spectrometry (MS)-based glycoproteomics in complex biological samples

Protein glycosylation plays a key role in various biological processes and disease-related pathological progression. Mass spectrometry (MS)-based glycoproteomics is a powerful approach that provides a system-wide profiling of the glycoproteome in a high-throughput manner. There have been numerous significant technological advances in this field, including improved glycopeptide enrichment, hybrid fragmentation techniques, emerging specialized software packages, and effective quantitation strategies, as well as more dedicated workflows. With increasingly sophisticated glycoproteomics tools on hand, researchers have extensively adapted this approach to explore different biological systems both in terms of in-depth glycoproteome profiling and comparative glycoproteome analysis. Quantitative glycoproteomics enables researchers to discover novel glycosylation-based biomarkers in various diseases with potential to offer better sensitivity and specificity for disease diagnosis. In this review, we present recent methodological developments in MS-based glycoproteomics and highlight its utility and applications in answering various questions in complex biological systems.

Global and site-specific analysis of protein glycosylation in complex biological systems with Mass Spectrometry

Protein glycosylation is ubiquitous in biological systems and plays essential roles in many cellular events. Global and site-specific analysis of glycoproteins in complex biological samples can advance our understanding of glycoprotein functions and cellular activities. However, it is extraordinarily challenging because of the low abundance of many glycoproteins and the heterogeneity of glycan structures. The emergence of mass spectrometry (MS)-based proteomics has provided us an excellent opportunity to comprehensively study proteins and their modifications, including glycosylation. In this review, we first summarize major methods for glycopeptide/glycoprotein enrichment, followed by the chemical and enzymatic methods to generate a mass tag for glycosylation site identification. We next discuss the systematic and quantitative analysis of glycoprotein dynamics. Reversible protein glycosylation is dynamic, and systematic study of glycoprotein dynamics helps us gain insight into glycoprotein functions. The last part of this review focuses on the applications of MS-based proteomics to study glycoproteins in different biological systems, including yeasts, plants, mice, human cells, and clinical samples. Intact glycopeptide analysis is also included in this section. Because of the importance of glycoproteins in complex biological systems, the field of glycoproteomics will continue to grow in the next decade. Innovative and effective MS-based methods will exponentially advance glycoscience, and enable us to identify glycoproteins as effective biomarkers for disease detection and drug targets for disease treatment. © 2019 Wiley Periodicals, Inc. Mass Spec Rev 9999: XX-XX, 2019.

Characterization of glycan isomers using magnetic carbon nanoparticles as a MALDI co-matrix

Matrix-assisted laser desorption ionization-in source decay (MALDI-ISD) analysis is a useful technique in the structural analysis of glycans. Our recent publication demonstrated that magnetic carbon nanoparticles (MCNPs), used as a MALDI co-matrix, significantly enhanced ISD efficiency for glycomic analysis by MALDI-TOF. In this study, MCNPs were used for the structural study of isomeric glycans. Results from the standard glycans confirmed easy distinction of positional and linkage isomers without the need for further derivatization of glycan molecules. Extensive glycosidic and cross-ring fragmented ions provided different fragment patterns for various glycan isomers. Core- and branch-fucosylated isomers were distinguished by several unique ions, and pseudo-MS³ data were used to recognize the fucosylated branch. Although no diagnostic fragment ion was observed for 2,3- and 2,6-linked sialic acid isomers, their MALDI-ISD patterns were found to be significantly different (P < 0.05). Furthermore, the method introduced in this study could not only be used for the identification of glycan isomers but has also proved effective for the isomeric structural confirmation of gangliosides. GD1a and GD1b gangliosides were easily distinguished by the diagnostic ion originated from GD1a, produced by Z_4αZ_2β cleavages. Moreover, liquid chromatography coupled with MALDI-TOF was applied to analyze N-glycan isomers derived from a pooled human blood serum sample, providing an alternative method of isomeric glycomic analysis of biological specimens.

Magnetic carbon nanoparticles as a MALDI co-matrix enable isomeric characterization of glycans in biological samples.

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

PURPOSE

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

EXPERIMENTAL DESIGN

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

RESULTS

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

CONCLUSIONS AND CLINICAL RELEVANCE

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

Targeted Measurements of O- and N-Glycopeptides Show That Proteins in High Density Lipoprotein Particles Are Enriched with Specific Glycosylation Compared to Plasma

High density lipoprotein (HDL) particles are believed to be protective due to their inverse correlation with the prevalence of cardiovascular diseases. However, recent studies show that in some conditions such as heart disease and diabetes, HDL particles can become dysfunctional. Great attention has been directed toward HDL particle composition because the relative abundances of HDL constituents determine HDL's functional properties. A key factor to consider when studying the structure and composition of plasma particles is the protein glycosylation. Here, we profile the O- and N-linked glycosylation of HDL associated-proteins including the truncated form of Apo CIII and their glycan heterogeneity in a site-specific manner. Apolipoprotein CIII, fetuin A, and alpha 1 antitrypsin are glycoproteins associated with lipoproteins and are implicated in many cardiovascular and other disease conditions. A targeted method (UHPLC-QQQ) was used to measure the glycoprotein concentrations and site-specific glycovariations of the proteins in human plasma and compared with HDL particles isolated from the same plasma samples. The proteins found in the plasma are differentially glycosylated compared to those isolated in HDL. The results of this study suggest that glycosylation may play a role in protein partitioning in the blood, with possible functional implications.

Vitronectin (Vn) glycosylation patterned by lectin affinity assays-A potent glycoproteomic tool to discriminate plasma Vn from cancer ascites Vn

Changes in glycosylation have been associated with human cancer, but their complexity poses an analytical challenge. Ovarian cancer is a major cause of death in women because of an often late diagnosis. At least one-third of patients presents ascites fluid at diagnosis, and almost all have ascites at recurrence. Vitronectin (Vn) is a multifunctional glycoprotein that is suggested to be implicated in ovarian cancer metastasis and is found within ascites. The present study evaluated the potential of using lectin affinity for characterizing the glycosylation pattern of Vn. Human Vn was purified from 1 sample of ovarian cancer ascites or a pool of plasma samples. Consistent findings were observed with both dot blot and lectin array assays. Based on a panel of 40 lectins, the lectin array revealed discriminant patterns of lectin binding to Vn glycans. Interestingly, almost all the highlighted interactions were found to be higher with Vn from ascites relative to the plasma counterpart. Also, the lectin array was able to discriminate profiles of lectin interactions (ConA, SNA-I, PHA-E, PHA-L) between Vn samples that were not evident using dot blot, indicating its high sensitivity. The model of ConA binding during thermal unfolding of Vn confirmed the higher accessibility of mannosylated glycans in Vn from ascites as monitored by turbidimetry. Thus, this study demonstrated the usefulness of lectins and the lectin array as a glycoproteomic tool for high throughput and sensitive analysis of glycosylation patterns. Our data provide novel insights concerning Vn glycosylation patterns in clinical specimens, paving the way for further investigations regarding their functional impact and clinical interest.

Algorithms and design strategies towards automated glycoproteomics analysis

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

Multi-Lectin Affinity Chromatography for Separation, Identification, and Quantitation of Intact Protein Glycoforms in Complex Biological Mixtures

Protein glycosylation is considered to be one of the most abundant post-translational modifications and is recognized for playing key roles in cellular functions. Aberrant N-linked glycosylation has been associated with several human diseases and has prompted the development and constant improvement of analytical tools to separate, characterize, and quantify glycoproteins in complex mixtures extracted from various biological samples (such as blood and tissue). Lectins, or carbohydrate-binding proteins, have been used as valuable tools for enriching for glycoproteins and selecting for specific types of glycosylation. Herein a method using multidimensional intact protein fractionation and LC-MS/MS analysis is described. Immunodepletion is used to remove highly abundant proteins from human plasma, followed by glycoform separation using multi-lectin affinity chromatography, in which specific lectins are chosen to capture and elute specific types of glycosylation. Reversed-phase chromatography prior to digestion is used for further fractionation, allowing for an increased number of protein identifications of moderate- to low-abundant proteins detectable in plasma. This method also incorporates isotopic labeling during alkylation for relative quantitation between two samples (such as a case and control). A bottom-up, tandem mass spectrometry-based proteomics approach is used for protein identification and quantitation, and allows for screening glycoform-specific changes across hundreds of plasma proteins.

Glycoproteins Enrichment and LC-MS/MS Glycoproteomics in Central Nervous System Applications

Proteins and glycoproteins play important biological roles in central nervous systems (CNS). Qualitative and quantitative evaluation of proteins and glycoproteins expression in CNS is critical to reveal the inherent biomolecular mechanism of CNS diseases. This chapter describes proteomic and glycoproteomic approaches based on liquid chromatography/tandem mass spectrometry (LC-MS or LC-MS/MS) for the qualitative and quantitative assessment of proteins and glycoproteins expressed in CNS. Proteins and glycoproteins, extracted by a mass spectrometry friendly surfactant from CNS samples, were subjected to enzymatic (tryptic) digestion and three down-stream analyses: (1) a nano LC system coupled with a high-resolution MS instrument to achieve qualitative proteomic profile, (2) a nano LC system combined with a triple quadrupole MS to quantify identified proteins, and (3) glycoprotein enrichment prior to LC-MS/MS analysis. Enrichment techniques can be applied to improve coverage of low abundant glycopeptides/glycoproteins. An example described in this chapter is hydrophilic interaction liquid chromatographic (HILIC) enrichment to capture glycopeptides, allowing efficient removal of peptides. The combination of three LC-MS/MS-based approaches is capable of the investigation of large-scale proteins and glycoproteins from CNS with an in-depth coverage, thus offering a full view of proteins and glycoproteins changes in CNS.

Current status of proteomics of esophageal carcinoma

INTRODUCTION

Esophageal cancer (EC) is one of the most common causes of cancer-related death worldwide. Identifying suitable biomarkers for early diagnosis as well as predicting lymph node metastasis, prognosis and the therapeutic response of EC is essential for the effective and efficient management for EC. There is an urgent need to develop effective, novel approaches for patients who do not respond to conventional treatment. Areas covered: EC is characterized by the presence of two main histological types such as squamous cell carcinoma and adenocarcinoma, which differ in their response to treatments and prognosis. Thus, this review describes the latest research into biomarkers and novel treatment targets generated by cancer proteomics for the two main histological types. Finally, the main difficulties facing the translation of biomarkers and novel treatment targets into the clinical settings are discussed. Expert commentary: EC proteomics have provided useful results and, after their validation, novel clinical tools should be developed to improve the clinical outcomes for EC patients.

Analysis of fucosylation in liver-secreted N-glycoproteins from human hepatocellular carcinoma plasma using liquid chromatography with tandem mass spectrometry

Fucosylation of N-glycoproteins has been implicated in various diseases, such as hepatocellular carcinoma (HCC). However, few studies have performed site-specific analysis of fucosylation in liver-secreted proteins. In this study, we characterized the fucosylation patterns of liver-secreted proteins in HCC plasma using a workflow to identify site-specific N-glycoproteins, where characteristic B- and/or Y-ion series with and without fucose in collision-induced dissociation were used in tandem mass spectrometry. In total, 71 fucosylated N-glycopeptides from 13 major liver-secreted proteins in human plasma were globally identified by LC-MS/MS. Additionally, 37 fucosylated N-glycopeptides were newly identified from nine liver-secreted proteins, including alpha-1-antichymotrypsin, alpha-1-antitrypsin, alpha-2-HS-glycoprotein, ceruloplasmin, alpha-1-acid glycoprotein 1/2, alpha-2-macroglobulin, serotransferrin, and beta-2-glycoprotein 1. Of the fucosylated N-glycopeptides, bi- and tri-antennary glycoforms were the most common ones identified in liver-secreted proteins from HCC plasma. Therefore, we suggest that this analytical method is effective for characterizing fucosylation in liver-secreted proteins. Graphical abstract A global map of fucosylated and non-fucosylated glycopeptides from 13 liver-secreted glycoproteins in hepatocellular carcinoma plasma.

Maturing Glycoproteomics Technologies Provide Unique Structural Insights into the N-glycoproteome and Its Regulation in Health and Disease

The glycoproteome remains severely understudied because of significant analytical challenges associated with glycoproteomics, the system-wide analysis of intact glycopeptides. This review introduces important structural aspects of protein N-glycosylation and summarizes the latest technological developments and applications in LC-MS/MS-based qualitative and quantitative N-glycoproteomics. These maturing technologies provide unique structural insights into the N-glycoproteome and its synthesis and regulation by complementing existing methods in glycoscience. Modern glycoproteomics is now sufficiently mature to initiate efforts to capture the molecular complexity displayed by the N-glycoproteome, opening exciting opportunities to increase our understanding of the functional roles of protein N-glycosylation in human health and disease.

Parallel data acquisition of in-source fragmented glycopeptides to sequence the glycosylation sites of proteins

Glycosylation plays important roles in maintaining protein stability and controlling biological processes. In recent years, the correlation between aberrant glycoproteins and many diseases has been reported. Hence, qualitative and quantitative analyses of glycoproteins are necessary to understand physiological processes. LC-MS/MS analysis of glycopeptides is faced with the low glycopeptide signal intensities and low peptide sequence identification. In our study, in-source fragmentation (ISF) was used in conjunction with LC-MS/MS to facilitate the parallel acquisition of peptide backbone sequence and glycan composition information. In ISF method, the identification of glycosylation sites depended on the detection of Y1 ion (ion of peptide backbone with an N-acetylglucosamine attached). To attain dominant Y1 ions, a range of source fragmentation voltages was studied using fetuin. A 45 V ISF voltage was found to be the most efficient voltage for the analysis of glycoproteins. ISF was employed to study the glycosylation sites of three model glycoproteins, including fetuin, α1-acid glycoprotein and porcine thyroglobulin. The approach was then used to analyze blood serum samples. Y1 ions of glycopeptides in tryptic digests of samples were detected. Y1 ions of glycopeptides with different sialic acid groups are observed at different retention times, representing the various numbers of sialic acid moieties associated with the same peptide backbone sequence. With ISF facilitating the peptide backbone sequencing of glycopeptides, identified peptide sequence coverage was increased. For example, identified fetuin sequence percentage was improved from 39 to 80% in MASCOT database searching compared to conventional CID method. The formation of Y1 ions and oxonium ions in ISF facilitates glycopeptide sequencing and glycan composition identification.

A case for protein-level and site-level specificity in glycoproteomic studies of disease

Abnormal glycosylation of proteins is known to be either resultant or causative of a variety of diseases. This makes glycoproteins appealing targets as potential biomarkers and focal points of molecular studies on the development and progression of human ailment. To date, a majority of efforts in disease glycoproteomics have tended to center on either determining the concentration of a given glycoprotein, or on profiling the total population of glycans released from a mixture of glycoproteins. While these approaches have demonstrated some diagnostic potential, they are inherently insensitive to the fine molecular detail which distinguishes unique and possibly disease relevant glycoforms of specific proteins. As a consequence, such analyses can be of limited sensitivity, specificity, and accuracy because they do not comprehensively consider the glycosylation status of any particular glycoprotein, or of any particular glycosylation site. Therefore, significant opportunities exist to improve glycoproteomic inquiry into disease by engaging in these studies at the level of individual glycoproteins and their exact loci of glycosylation. In this concise review, the rationale for glycoprotein and glycosylation site specificity is developed in the context of human disease glycoproteomics with an emphasis on N-glycosylation. Recent examples highlighting disease-related perturbations in glycosylation will be presented, including those involving alterations in the overall glycosylation of a specific protein, alterations in the occupancy of a given glycosylation site, and alterations in the compositional heterogeneity of glycans occurring at a given glycosylation site. Each will be discussed with particular emphasis on how protein-specific and site-specific approaches can contribute to improved discrimination between glycoproteomes and glycoproteins associated with healthy and unhealthy states.

Integrated GlycoProteome Analyzer (I-GPA) for Automated Identification and Quantitation of Site-Specific N-Glycosylation

Human glycoproteins exhibit enormous heterogeneity at each N-glycosite, but few studies have attempted to globally characterize the site-specific structural features. We have developed Integrated GlycoProteome Analyzer (I-GPA) including mapping system for complex N-glycoproteomes, which combines methods for tandem mass spectrometry with a database search and algorithmic suite. Using an N-glycopeptide database that we constructed, we created novel scoring algorithms with decoy glycopeptides, where 95 N-glycopeptides from standard α1-acid glycoprotein were identified with 0% false positives, giving the same results as manual validation. Additionally automated label-free quantitation method was first developed that utilizes the combined intensity of top three isotope peaks at three highest MS spectral points. The efficiency of I-GPA was demonstrated by automatically identifying 619 site-specific N-glycopeptides with FDR ≤ 1%, and simultaneously quantifying 598 N-glycopeptides, from human plasma samples that are known to contain highly glycosylated proteins. Thus, I-GPA platform could make a major breakthrough in high-throughput mapping of complex N-glycoproteomes, which can be applied to biomarker discovery and ongoing global human proteome project.

Glycosylation-Based Serum Biomarkers for Cancer Diagnostics and Prognostics

Cancer is the second most common cause of death in developed countries with approximately 14 million newly diagnosed individuals and over 6 million cancer-related deaths in 2012. Many cancers are discovered at a more advanced stage but better survival rates are correlated with earlier detection. Current clinically approved cancer biomarkers are most effective when applied to patients with widespread cancer. Single biomarkers with satisfactory sensitivity and specificity have not been identified for the most common cancers and some biomarkers are ineffective for the detection of early stage cancers. Thus, novel biomarkers with better diagnostic and prognostic performance are required. Aberrant protein glycosylation is well known hallmark of cancer and represents a promising source of potential biomarkers. Glycoproteins enter circulation from tissues or blood cells through active secretion or leakage and patient serum is an attractive option as a source for biomarkers from a clinical and diagnostic perspective. A plethora of technical approaches have been developed to address the challenges of glycosylation structure detection and determination. This review summarises currently utilised glycoprotein biomarkers and novel glycosylation-based biomarkers from the serum glycoproteome under investigation as cancer diagnostics and for monitoring and prognostics and includes details of recent high throughput and other emerging glycoanalytical techniques.

Defining glycoprotein cancer biomarkers by MS in conjunction with glycoprotein enrichment

Protein glycosylation is an important and common post-translational modification. More than 50% of human proteins are believed to be glycosylated to modulate the functionality of proteins. Aberrant glycosylation has been correlated to several diseases, such as inflammatory skin diseases, diabetes mellitus, cardiovascular disorders, rheumatoid arthritis, Alzheimer's and prion diseases, and cancer. Many approved cancer biomarkers are glycoproteins which are not highly abundant proteins. Therefore, effective qualitative and quantitative assessment of glycoproteins entails enrichment methods. This chapter summarizes glycoprotein enrichment methods, including lectin affinity, immunoaffinity, hydrazide chemistry, hydrophilic interaction liquid chromatography, and click chemistry. The use of these enrichment approaches in assessing the qualitative and quantitative changes of glycoproteins in different types of cancers are presented and discussed. This chapter highlights the importance of glycoprotein enrichment techniques for the identification and characterization of new reliable cancer biomarkers.

Cancer serum biomarkers based on aberrant post-translational modifications of glycoproteins: Clinical value and discovery strategies

Due to the increase in life expectancy in the last decades, as well as changes in lifestyle, cancer has become one of the most common diseases both in developed and developing countries. Early detection remains the most promising approach to improve long-term survival of cancer patients and this may be achieved by efficient screening of biomarkers in biological fluids. Great efforts have been made to identify specific alterations during oncogenesis. Changes at the cellular glycosylation profiles are among such alterations. The "glycosylation machinery" of cells is affected by malignant transformation due to the altered expression of glycogens, leading to changes in glycan biosynthesis and diversity. Alterations in the post-translational modifications of proteins that occur in cancer result in the expression of antigenically distinct glycoproteins. Therefore, these aberrant and cancer-specific glycoproteins and the autoantibodies that are produced in response to their presence constitute targets for cancer biomarkers' search. Different strategies have been implemented for the discovery of cancer glycobiomarkers and are herein reviewed, along with their potentialities and limitations. Practical issues related with serum analysis are also addressed, as well as the challenges that this area faces in the near future.

Exploring the glycoproteomics landscape with advanced MS technologies

The advance of glycoproteomic technologies has offered unique insights into the importance of glycosylation in determining the functional roles of a protein within a cell. Biologically active glycoproteins include the categories of enzymes, hormones, proteins involved in cell proliferation, cell membrane proteins involved in cell-cell recognition, and communication events or secreted proteins, just to name a few. The recent progress in analytical instrumentation, methodologies, and computational approaches has enabled a detailed exploration of glycan structure, connectivity, and heterogeneity, underscoring the staggering complexity of the glycome repertoire in a cell. A variety of approaches involving the use of spectroscopy, MS, separation, microfluidic, and microarray technologies have been used alone or in combination to tackle the glycoproteome challenge, the research results of these efforts being captured in an overwhelming number of annual publications. This work is aimed at reviewing the major developments and accomplishments in the field of glycoproteomics, with focus on the most recent advancements (2012-2014) that involve the use of capillary separations and MS detection.