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

Multiplatform Lipid Analysis of the Brain of Aging Mice by Mass Spectrometry

Lipids are critical to brain structure and function, accounting for approximately 50% of its dry weight. However, the impact of aging on brain lipids remains poorly characterized. To address this, here we applied three complementary mass spectrometry techniques: multiple reaction monitoring (MRM) profiling, untargeted liquid chromatography tandem mass spectrometry (LC-MS/MS), and desorption electrospray ionization-MS imaging (DESI-MSI). We used brains from mice of three age groups: adult (3-4 months), middle-aged (10 months), and old (19-21 months). Phospholipids such as phosphatidylcholine, phosphatidylethanolamine, and phosphatidylglycerol were more abundant, while phosphatidylinositol and phosphatidylserine were reduced in old mice compared to adults or middle-aged mice. Key lipids such as polyunsaturated fatty acids, including DHA, AA, HexCer, SHexCer, and SM, were among the most abundant lipids in aged brains. DESI-MSI revealed spatial lipid distribution patterns consistent with findings from MRM profiling and LC-MS/MS. Integration of lipidomic data with the recently published proteomics data from the same tissues highlighted changes in proteins and phosphorylation levels of several proteins associated with Cer, HexCer, FA, PI, SM, and SHexCer metabolism, aligning with the multiplatform lipid surveillance. These findings shed insight into age-dependent brain lipid changes and their potential contribution to age-related cognitive decline.

Deep structure-level N-glycan identification using feature-induced structure diagnosis integrated with a deep learning model

Being a widely occurring protein post-translational modification, N-glycosylation features unique multi-dimensional structures including sequence and linkage isomers. There have been successful bioinformatics efforts in N-glycan structure identification using N-glycoproteomics data; however, symmetric "mirror" branch isomers and linkage isomers are largely unresolved. Here, we report deep structure-level N-glycan identification using feature-induced structure diagnosis (FISD) integrated with a deep learning model. A neural network model is integrated to conduct the identification of featured N-glycan motifs and boosts the process of structure diagnosis and distinction for linkage isomers. By adopting publicly available N-glycoproteomics datasets of five mouse tissues (17,136 intact N-glycopeptide spectrum matches) and a consideration of 23 motif features, a deep learning model integrated with a convolutional autoencoder and a multilayer perceptron was trained to be capable of predicting N-glycan featured motifs in the MS/MS spectra with previously identified compositions. In the test of the trained model, a prediction accuracy of 0.8 and AUC value of 0.95 were achieved; 5701 previously unresolved N-glycan structures were assigned by matched structure-diagnostic ions; and by using an explainable learning algorithm, two new fragmentation features of m/z = 674.25 and m/z = 835.28 were found to be significant to three N-glycan structure motifs with fucose, NeuAc, and NeuGc, proving the capability of FISD to discover new features in the MS/MS spectra.

Purification and characterization of α-fucosidase from Dichostereum sordulentum 1488

Biological glycans mediate several physiological processes, thus altered glycosylation patterns can lead to different diseases such as autoimmune, infectious, chronic anti-inflammatory diseases, or even cancer. In fact, alterations in fucosylation in either N- or O-glycans are among the most frequent changes in glycosylation patterns associated with cancer. Therefore, elucidation of the role of glycoconjugate glycans is essential for understanding the development of pathologies where they are involved. In this sense glycosidases are excellent tools, since they catalyse the selective removal of sugar residues, allowing the evaluation of changes in their biological role due to glycan removal. This work describes the purification and characterization of a α-fucosidase from the fungus Dichostereum sordulentum 1488. It is a homodimer with a molecular weight of 214 kDa and optimum pH and temperature of 4.0 and 70 °C respectively. It has a KM of 0.27 mM and VMax of 3.3 μmoles PNP/min per mg for the substrate p-nitrophenyl-α-l-fucopyranoside, showing a substrate inhibition profile. It showed high specificity for the hydrolysis of fucose linked by α-(1,2) bonds. The identification, purification, and characterization of this new α-fucosidase is highly relevant for enlarging the availability of glycosidases for use as tools for glycan elucidation.

Optimization of glycopeptide enrichment techniques for the identification of clinical biomarkers

INTRODUCTION

The identification and characterization of glycopeptides through LC-MS/MS and advanced enrichment techniques are crucial for advancing clinical glycoproteomics, significantly impacting the discovery of disease biomarkers and therapeutic targets. Despite progress in enrichment methods like Lectin Affinity Chromatography (LAC), Hydrophilic Interaction Liquid Chromatography (HILIC), and Electrostatic Repulsion Hydrophilic Interaction Chromatography (ERLIC), issues with specificity, efficiency, and scalability remain, impeding thorough analysis of complex glycosylation patterns crucial for disease understanding.

AREAS COVERED

This review explores the current challenges and innovative solutions in glycopeptide enrichment and mass spectrometry analysis, highlighting the importance of novel materials and computational advances for improving sensitivity and specificity. It outlines the potential future directions of these technologies in clinical glycoproteomics, emphasizing their transformative impact on medical diagnostics and therapeutic strategies.

EXPERT OPINION

The application of innovative materials such as Metal-Organic Frameworks (MOFs), Covalent Organic Frameworks (COFs), functional nanomaterials, and online enrichment shows promise in addressing challenges associated with glycoproteomics analysis by providing more selective and robust enrichment platforms. Moreover, the integration of artificial intelligence and machine learning is revolutionizing glycoproteomics by enhancing the processing and interpretation of extensive data from LC-MS/MS, boosting biomarker discovery, and improving predictive accuracy, thus supporting personalized medicine.

Functionalized DNA Origami-Enabled Detection of Biomarkers

Biomarkers are crucial physiological and pathological indicators in the host. Over the years, numerous detection methods have been developed for biomarkers, given their significant potential in various biological and biomedical applications. Among these, the detection system based on functionalized DNA origami has emerged as a promising approach due to its precise control over sensing modules, enabling sensitive, specific, and programmable biomarker detection. We summarize the advancements in biomarker detection using functionalized DNA origami, focusing on strategies for DNA origami functionalization, mechanisms of biomarker recognition, and applications in disease diagnosis and monitoring. These applications are organized into sections based on the type of biomarkers - nucleic acids, proteins, small molecules, and ions - and concludes with a discussion on the advantages and challenges associated with using functionalized DNA origami systems for biomarker detection.

Plasma glycoproteomics delivers high-specificity disease biomarkers by detecting site-specific glycosylation abnormalities

INTRODUCTION

The human plasma glycoproteome holds enormous potential to identify personalized biomarkers for diagnostics. Glycoproteomics has matured into a technology for plasma N-glycoproteome analysis but further evolution towards clinical applications depends on the clinical validity and understanding of protein- and site-specific glycosylation changes in disease.

OBJECTIVES

Here, we exploited the uniqueness of a patient cohort of genetic defects in well-defined glycosylation pathways to assess the clinical applicability of plasma N-glycoproteomics.

METHODS

Comparative glycoproteomics was performed of blood plasma from 40 controls and 74 patients with 13 different genetic diseases that impact the protein N-glycosylation pathway. Baseline glycosylation in healthy individuals was compared to reference glycome and intact transferrin protein mass spectrometry data. Use of glycoproteomics data for biomarker discovery and sample stratification was evaluated by multivariate chemometrics and supervised machine learning. Clinical relevance of site-specific glycosylation changes were evaluated in the context of genetic defects that lead to distinct accumulation or loss of specific glycans. Integrated analysis of site-specific glycoproteome changes in disease was performed using chord diagrams and correlated with intact transferrin protein mass spectrometry data.

RESULTS

Glycoproteomics identified 191 unique glycoforms from 58 unique peptide sequences of 34 plasma glycoproteins that span over 3 magnitudes of abundance in plasma. Chemometrics identified high-specificity biomarker signatures for each of the individual genetic defects with better stratification performance than the current diagnostic standard method. Bioinformatic analyses revealed site-specific glycosylation differences that could be explained by underlying glycobiology and protein-intrinsic factors.

CONCLUSION

Our work illustrates the strong potential of plasma glycoproteomics to significantly increase specificity of glycoprotein biomarkers with direct insights in site-specific glycosylation changes to better understand the glycobiological mechanisms underlying human disease.

Glycoproteomics: Charting new territory in mass spectrometry and glycobiology

Glycosylation is an incredibly common and diverse post-translational modification that contributes widely to cellular health and disease. Mass spectrometry is the premier technique to study glycoproteins; however, glycoproteomics has lagged behind traditional proteomics due to the challenges associated with studying glycosylation. For instance, glycans dissociate by collision-based fragmentation, thus necessitating electron-based fragmentation for site-localization. The vast glycan heterogeneity leads to lower overall abundance of each glycopeptide, and often, ion suppression is observed. One of the biggest issues facing glycoproteomics is the lack of reliable software for analysis, which necessitates manual validation and serves as a massive bottleneck in data processing. Here, I will discuss each of these challenges and some ways in which the field is attempting to address them, along with perspectives on how I believe we should move forward.

Mass Spectrometry Strategies for O-Glycoproteomics

Glycoproteomics has accelerated in recent decades owing to numerous innovations in the analytical workflow. In particular, new mass spectrometry strategies have contributed to inroads in O-glycoproteomics, a field that lags behind N-glycoproteomics due to several unique challenges associated with the complexity of O-glycosylation. This review will focus on progress in sample preparation, enrichment strategies, and MS/MS techniques for the identification and characterization of O-glycoproteins.

Amide and Multihydroxyl Complementary Tailored Metal-Organic Framework with Enhanced Glycan Affinity for Efficient Glycoproteomic Analysis

Protein glycosylation is ubiquitous and crucial for regulating biological processes in organisms. Given the heterogeneity and low abundance of glycoproteins, efficient and specific enrichment procedures are required for the mass spectrometry analysis of glycopeptides. Hydrophilic interaction liquid chromatography (HILIC) has emerged as an effective strategy for glycopeptide enrichment. However, the relatively weak hydrophilic affinity restricts the achievement of a satisfactory enrichment performance. Here, we presented a rational design of an amide and multihydroxyl complementary tailored metal-organic framework, denoted as U6N/Pv@Glc, which exhibited ultrahydrophilicity and enhanced glycan affinity. Our results demonstrated a significant increase in glycopeptide coverage after enrichment, accompanied by extremely low detection limits (0.05 fmol μL-1) and high selectivity (IgG/BSA, 1:4000) as evaluated using trypsin-digested standard glycoproteins. A total of 379 glycopeptides and 247 intact glycopeptides (containing a total of 1577 site-specific N-glycans) were identified and characterized within human serum samples from individuals with type 2 diabetes in-depth. Additionally, we extended the application of this material to capture undigested glycoproteins, demonstrating potential compatibility with top-down MS analysis. These results highlight the promising potential of this novel material for comprehensive glycoproteomic analysis of every potential aspect.

Dual-functionalized two-dimensional metal-organic framework composite with highly hydrophilicity for effective enrichment of glycopeptides

Protein glycosylation research is currently focused on the development of various functionalized materials that can effectively enrich the levels of glycopeptides in samples. However, most of these materials possess limited glycopeptide-specific recognition sites because of large steric hindrance, unsuitable mass transfer kinetics, and relatively low surface areas. Herein, a highly hydrophilic two-dimensional (2-D) metal-organic framework (MOF) nanosheet modified with glutathione (GSH) and l-cysteine (l-Cys) (denoted as Zr-Fc MOF@Au@GC) has been synthesized for efficient glycopeptide enrichment. Using this composite material, 39 and 44 glycopeptides from horseradish peroxidase (HRP) and human serum immunoglobulin G (IgG) digests were detected, respectively, which represents a higher efficiency for glycopeptide enrichment from model glycoprotein digests than has been previously reported. The material Zr-Fc MOF@Au@GC exhibited ultra-high sensitivity (0.1 fmol/µL), excellent selectivity (weight ratio of HRP tryptic digest to bovine serum albumin (BSA) tryptic digest = 1:2000), good binding capacity (200 mg/g), satisfactory reusability, and long-term storage capacity. In addition, 655 glycopeptides corresponding to 366 glycoproteins were identified from human serum samples. To the best of our knowledge, this is the largest number of glycoproteins detected in human serum samples to date. These results indicated that Zr-Fc MOF@Au@GC has the potential to be used for the enrichment of glycopeptides in biological samples and the analysis of protein glycosylation.

Profiling Human Cerebrospinal Fluid (CSF) Endogenous Peptidome in Alzheimer's Disease

Human cerebrospinal fluid (CSF) is a rich source for central nervous system (CNS)-related disease biomarker discovery due to its direct interchange with the extracellular fluid of the CNS. Though extensive proteome-level profiling has been conducted for CSF, studies targeting at its endogenous peptidome is still limited. It is more difficult to include the post-translational modifications (PTMs) characterization of the peptidome in the mass spectrometry (MS) analysis because of their low abundance and the challenge of data interpretation. In this chapter, we present a peptidomic workflow that combines molecular weight cut-off (MWCO) separation, electron-transfer and higher-energy collision dissociation (EThcD) fragmentation, and a three-step database searching strategy for comprehensive PTM analysis of endogenous peptides including both N-glycosylation and O-glycosylation and other common peptide PTMs. The method has been successfully adopted to analyze CSF samples from healthy donors, mild cognitive impairment (MCI), and Alzheimer's disease (AD) patients to provide a landscape of peptidome in different disease states.

Secretome Analysis: Reading Cellular Sign Language to Understand Intercellular Communication

A significant portion of mammalian proteomes is secreted to the extracellular space to fulfill crucial roles in cell-to-cell communication. To best recapitulate the intricate and multi-faceted crosstalk between cells in a live organism, there is an ever-increasing need for methods to study protein secretion in model systems that include multiple cell types. In addition, posttranslational modifications further expand the complexity and versatility of cellular communication. This review aims to summarize recent strategies and model systems that employ cellular coculture, chemical biology tools, protein enrichment, and proteomic methods to characterize the composition and function of cellular secretomes. This is all geared towards gaining better understanding of organismal biology in vivo mediated by secretory signaling.

ATP-Coated Dual-Functionalized Titanium(IV) IMAC Material for Simultaneous Enrichment and Separation of Glycopeptides and Phosphopeptides

Protein glycosylation and phosphorylation are two of the most common post-translational modifications (PTMs), which play an important role in many biological processes. However, low abundance and poor ionization efficiency of phosphopeptides and glycopeptides make direct MS analysis challenging. In this study, we developed a hydrophilicity-enhanced bifunctional Ti-IMAC (IMAC: immobilized metal affinity chromatography) material with grafted adenosine triphosphate (denoted as epoxy-ATP-Ti4+) to enable simultaneous enrichment and separation of common N-glycopeptides, phosphopeptides, and M6P glycopeptides from tissue/cells. The enrichment was achieved through a dual-mode mechanism based on the electrostatic and hydrophilic properties of the material. The epoxy-ATP-Ti4+ IMAC material was prepared from epoxy-functionalized silica particles via a convenient two-step process. The ATP molecule provided strong and active phosphate sites for binding phosphopeptides in the conventional IMAC mode and also contributed significantly to the hydrophilicity, which permitted the enrichment of glycopeptides via hydrophilic interaction chromatography. The two modes could be implemented simultaneously, allowing glycopeptides and phosphopeptides to be collected sequentially in a single experiment from the same sample. In addition to standard protein samples, the material was further applied to glycopeptide and phosphopeptide enrichment and characterization from HeLa cell digests and mouse lung tissue samples. In total, 2928 glycopeptides and 3051 phosphopeptides were identified from the mouse lung tissue sample, supporting the utility of this material for large-scale PTM analysis of complex biological samples. Overall, the newly developed epoxy-ATP-Ti4+ IMAC material and associated fractionation method enable simple and effective enrichment and separation of glycopeptides and phosphopeptides, offering a useful tool to study potential crosstalk between these two important PTMs in biological systems. The MS data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifier PXD029775.

O-Linked Sialoglycans Modulate the Proteolysis of SARS-CoV-2 Spike and Likely Contribute to the Mutational Trajectory in Variants of Concern

The emergence of a polybasic cleavage motif for the protease furin in SARS-CoV-2 spike has been established as a major factor for human viral transmission. The region N-terminal to that motif is extensively mutated in variants of concern (VOCs). Besides furin, spikes from these variants appear to rely on other proteases for maturation, including TMPRSS2. Glycans near the cleavage site have raised questions about proteolytic processing and the consequences of variant-borne mutations. Here, we identify that sialic acid-containing O-linked glycans on Thr678 of SARS-CoV-2 spike influence furin and TMPRSS2 cleavage and posit O-linked glycosylation as a likely driving force for the emergence of VOC mutations. We provide direct evidence that the glycosyltransferase GalNAc-T1 primes glycosylation at Thr678 in the living cell, an event that is suppressed by mutations in the VOCs Alpha, Delta, and Omicron. We found that the sole incorporation of N-acetylgalactosamine did not impact furin activity in synthetic O-glycopeptides, but the presence of sialic acid reduced the furin rate by up to 65%. Similarly, O-glycosylation with a sialylated trisaccharide had a negative impact on TMPRSS2 cleavage. With a chemistry-centered approach, we substantiate O-glycosylation as a major determinant of spike maturation and propose disruption of O-glycosylation as a substantial driving force for VOC evolution.

Systematic characterization of extracellular glycoproteins using mass spectrometry

Surface and secreted glycoproteins are essential to cells and regulate many extracellular events. Because of the diversity of glycans, the low abundance of many glycoproteins, and the complexity of biological samples, a system-wide investigation of extracellular glycoproteins is a daunting task. With the development of modern mass spectrometry (MS)-based proteomics, comprehensive analysis of different protein modifications including glycosylation has advanced dramatically. This review focuses on the investigation of extracellular glycoproteins using MS-based proteomics. We first discuss the methods for selectively enriching surface glycoproteins and investigating protein interactions on the cell surface, followed by the application of MS-based proteomics for surface glycoprotein dynamics analysis and biomarker discovery. We then summarize the methods to comprehensively study secreted glycoproteins by integrating various enrichment approaches with MS-based proteomics and their applications for global analysis of secreted glycoproteins in different biological samples. Collectively, MS significantly expands our knowledge of extracellular glycoproteins and enables us to identify extracellular glycoproteins as potential biomarkers for disease detection and drug targets for disease treatment.

GlycoSLASH: Concurrent Glycopeptide Identification from Multiple Related LC-MS/MS Data Sets by Using Spectral Clustering and Library Searching

Liquid chromatography coupled with tandem mass spectrometry is commonly adopted in large-scale glycoproteomic studies involving hundreds of disease and control samples. The software for glycopeptide identification in such data (e.g., the commercial software Byonic) analyzes the individual data set and does not exploit the redundant spectra of glycopeptides presented in the related data sets. Herein, we present a novel concurrent approach for glycopeptide identification in multiple related glycoproteomic data sets by using spectral clustering and spectral library searching. The evaluation on two large-scale glycoproteomic data sets showed that the concurrent approach can identify 105%-224% more spectra as glycopeptides compared to the glycopeptide identification on individual data sets using Byonic alone. The improvement of glycopeptide identification also enabled the discovery of several potential biomarkers of protein glycosylations in hepatocellular carcinoma patients.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2019-2020

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2020. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. The review is basically divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of arrays. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other areas such as medicine, industrial processes and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. The reported work shows increasing use of incorporation of new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented nearly 40 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show little sign of diminishing.

Integrating age, BMI, and serum N-glycans detected by MALDI mass spectrometry to classify suspicious mammogram findings as benign lesions or breast cancer

While mammograms are the standard tool for breast cancer screening, there remains challenges for mammography to effectively distinguish benign lesions from breast cancers, leading to many unnecessary biopsy procedures. A blood-based biomarker could provide a minimally invasive supplemental assay to increase the specificity of breast cancer screening. Serum N-glycosylation alterations have associations with many cancers and several of the clinical characteristics of breast cancer. The current study utilized a high-throughput mass spectrometry workflow to identify serum N-glycans with differences in intensities between patients that had a benign lesion from patients with breast cancer. The overall N-glycan profiles of the two patient groups had no differences, but there were several individual N-glycans with significant differences in intensities between patients with benign lesions and ductal carcinoma in situ (DCIS). Many N-glycans had strong associations with age and/or body mass index, but there were several of these associations that differed between the patients with benign lesions and breast cancer. Accordingly, the samples were stratified by the patient's age and body mass index, and N-glycans with significant differences between these subsets were identified. For women aged 50-74 with a body mass index of 18.5-24.9, a model including the intensities of two N-glycans, 1850.666 m/z and 2163.743 m/z, age, and BMI were able to clearly distinguish the breast cancer patients from the patients with benign lesions with an AUROC of 0.899 and an optimal cutoff with 82% sensitivity and 84% specificity. This study indicates that serum N-glycan profiling is a promising approach for providing clarity for breast cancer screening, especially within the subset of healthy weight women in the age group recommended for mammograms.

In-Depth Site-Specific O-Glycosylation Analysis of Glycoproteins and Endogenous Peptides in Cerebrospinal Fluid (CSF) from Healthy Individuals, Mild Cognitive Impairment (MCI), and Alzheimer's Disease (AD) Patients

Site-specific O-glycoproteome mapping in complex biological systems provides a molecular basis for understanding the structure-function relationships of glycoproteins and their roles in physiological and pathological processes. Previous O-glycoproteome analysis in cerebrospinal fluid (CSF) focused on sialylated glycoforms, while missing information on other glycosylation types. In order to achieve an unbiased O-glycosylation profile, we developed an integrated strategy combining universal boronic acid enrichment, high-pH fractionation, and electron-transfer and higher-energy collision dissociation (EThcD) for enhanced intact O-glycopeptide analysis. We applied this strategy to analyze the O-glycoproteome in CSF, resulting in the identification of 308 O-glycopeptides from 110 O-glycoproteins, covering both sialylated and nonsialylated glycoforms. To our knowledge, this is the largest data set of O-glycoproteins and O-glycosites reported for CSF to date. We also developed a peptidomics workflow that utilized the EThcD and a three-step database searching strategy for comprehensive PTM analysis of endogenous peptides, including N-glycosylation, O-glycosylation, and other common peptide PTMs. Interestingly, among the 1411 endogenous peptides identified, 89 were O-glycosylated, and only one N-glycosylated peptide was found, indicating that CSF endogenous peptides were predominantly O-glycosylated. Analyses of the O-glycoproteome and endogenous peptidome PTMs were also conducted in the CSF of MCI and AD patients to provide a landscape of glycosylation patterns in different disease states. Our results showed a decreasing trend in fucosylation and an increasing trend of endogenous peptide O-glycosylation, which may play an important role in AD progression.

Methods to improve quantitative glycoprotein coverage from bottom-up LC-MS data

Advances in mass spectrometry instrumentation, methods development, and bioinformatics have greatly improved the ease and accuracy of site-specific, quantitative glycoproteomics analysis. Data-dependent acquisition is the most popular method for identification and quantification of glycopeptides; however, complete coverage of glycosylation site glycoforms remains elusive with this method. Targeted acquisition methods improve the precision and accuracy of quantification, but at the cost of throughput and discoverability. Data-independent acquisition (DIA) holds great promise for more complete and highly quantitative site-specific glycoproteomics analysis, while maintaining the ability to discover novel glycopeptides without prior knowledge. We review additional features that can be used to increase selectivity and coverage to the DIA workflow: retention time modeling, which would simplify the interpretation of complex tandem mass spectra, and ion mobility separation, which would maximize the sampling of all precursors at a giving chromatographic retention time. The instrumentation and bioinformatics to incorporate these features into glycoproteomics analysis exist. These improvements in quantitative, site-specific analysis will enable researchers to assess glycosylation similarity in related biological systems, answering new questions about the interplay between glycosylation state and biological function.

Boost-DiLeu: Enhanced Isobaric N,N-Dimethyl Leucine Tagging Strategy for a Comprehensive Quantitative Glycoproteomic Analysis

Intact glycopeptide analysis has been of great interest because it can elucidate glycosylation site information and glycan structural composition at the same time. However, mass spectrometry (MS)-based glycoproteomic analysis is hindered by the low abundance and poor ionization efficiency of glycopeptides. Relatively large amounts of starting materials are needed for the enrichment, which makes the identification and quantification of intact glycopeptides from samples with limited quantity more challenging. To overcome these limitations, we developed an improved isobaric labeling strategy with an additional boosting channel to enhance N,N-dimethyl leucine (DiLeu) tagging-based quantitative glycoproteomic analysis, termed as Boost-DiLeu. With the integration of a one-tube sample processing workflow and high-pH fractionation, 3514 quantifiable N-glycopeptides were identified from 30 μg HeLa cell tryptic digests with reliable quantification performance. Furthermore, this strategy was applied to human cerebrospinal fluid (CSF) samples to differentiate N-glycosylation profiles between Alzheimer's disease (AD) patients and non-AD donors. The results revealed processes and pathways affected by dysregulated N-glycosylation in AD, including platelet degranulation, cell adhesion, and extracellular matrix, which highlighted the involvement of N-glycosylation aberrations in AD pathogenesis. Moreover, weighted gene coexpression network analysis (WGCNA) showed nine modules of glycopeptides, two of which were associated with the AD phenotype. Our results demonstrated the feasibility of using this strategy for in-depth glycoproteomic analysis of size-limited clinical samples. Taken together, we developed and optimized a strategy for the enhanced comprehensive quantitative intact glycopeptide analysis with DiLeu labeling, showing significant promise for identifying novel therapeutic targets or biomarkers in biological systems with a limited sample quantity.

Site-Specific Intact N-Linked Glycopeptide Characterization of Prostate-Specific Membrane Antigen from Metastatic Prostate Cancer Cells

The composition of N-linked glycans that are conjugated to the prostate-specific membrane antigen (PSMA) and their functional significance in prostate cancer progression have not been fully characterized. PSMA was isolated from two metastatic prostate cancer cell lines, LNCaP and MDAPCa2b, which have different tissue tropism and localization. Isolated PSMA was trypsin-digested, and intact glycopeptides were subjected to LC-HCD-EThcD-MS/MS analysis on a Tribrid Orbitrap Fusion Lumos mass spectrometer. Differential qualitative and quantitative analysis of site-specific N-glycopeptides was performed using Byonic and Byologic software. Comparative quantitative analysis demonstrates that multiple glycopeptides at asparagine residues 51, 76, 121, 195, 336, 459, 476, and 638 were in significantly different abundance in the two cell lines (p < 0.05). Biochemical analysis using endoglycosidase treatment and lectin capture confirm the MS and site occupancy data. The data demonstrate the effectiveness of the strategy for comprehensive analysis of PSMA glycopeptides. This approach will form the basis of ongoing experiments to identify site-specific glycan changes in PSMA isolated from disease-stratified clinical samples to uncover targets that may be associated with disease progression and metastatic phenotypes.

Progress of proteomics-driven precision medicine: From a glycosylation view

Currently, cancer is one of the leading causes of death worldwide, partially owing to the lack of early diagnosis methods and effective therapies. With the rapid development of various omics, the precision medicine strategy becomes a promising way to increase the survival rates by considering individual differences. Glycosylation is one of the most essential protein post-translational modifications and plays important roles in a variety of biological processes. Therefore, it is highly possible to acquire understanding of the molecular mechanisms as well as discover novel potential markers for diagnosis and prognosis based on glycoproteomics research. This review summarizes the recent glycoproteomics studies about N-glycosylation of several cancer types, mainly in the past 5 years. We also highlight corresponding mass spectrometry-based analytical methods to give a brief overview on the main techniques applied in glycoproteomics.

A Preliminary Study on Change of Serum Immunoglobulin G Glycosylation in Patients With Migraine

Background and Objective

Migraine is a common neurological disease, but its pathogenesis is still unclear. Previous studies suggested that migraine was related to immunoglobulin G (IgG). We intended to analyze the immune characteristics of migraine from the perspective of IgG glycosylation and provide theoretical assistance for exploring its pathogenesis.

Methods

The differences in the serum level of IgG glycosylation and glycopeptides between patients with episodic migraine and healthy controls were analyzed by applying the poly(glycerol methacrylate)@chitosan (PGMA@CS) nanomaterial in combination with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). We constructed a binary classification model with a feedforward neural network using PyTorch 1.6.0 in Python 3.8.3 to classify the episodic migraine and healthy control groups.

Results

Twenty patients with migraine and 20 healthy controls were enrolled and the blood samples and clinical information were collected. Forty-nine IgG N-glycopeptides were detected in the serum of the subjects. The serum level of N-glycopeptide IgG1 G0-NF (p = 0.012) was increased in patients with migraine. The serum level of N-glycopeptide IgG3/4 G2FS (p = 0.041) was decreased in patients with migraine with family history of headache. It was found that the serum level of the IgG1 G1 (p = 0.004) and IgG2 G0 (p = 0.045) was increased in patients with migraine with aura, while the serum level of IgG2 G0N (p = 0.043) in patients with migraine with aura was significantly lower than that in patients with migraine without aura. In addition, a linear feedforward neural network (FFNN) was used to construct a binary classification model by detected IgG N-glycopeptides. The area under the curve (AUC) value of the binary classification model, which was constructed with 7 IgG N-glycopeptides, was 0.857, suggesting a good prediction performance. Among these IgG N-glycopeptides that were constructed the model, IgG1 G0-NF was overlapped with the differential IgG N-glycopeptide between patients with migraine and healthy controls detected with MALDI-TOF-MS.

Conclusion

Our results indicated that the serum level of N-glycopeptides IgG1 G0-NF might be one of the important biomarkers for the diagnosis of migraine. To the best of our knowledge, this is the first study about the changes of IgG N-glycosylation in patients with migraine by the method of MALDI-TOF-MS. The results indicated a relationship between the migraine and immune response.

Design of a hydrophilic mercaptosuccinic acid-functionalized β-cyclodextrin polymer via host–guest interaction: toward highly efficient glycopeptide enrichment

A novel hydrophilic material (denoted as magCDP@Ada-MSA) was constructed through host–guest interaction between crosslinked β-cyclodextrin polymers and mercaptosuccinic acid derived adamantane, and was applied to specific glycopeptide enrichment.

Mass Spectrometry as a Crucial Analytical Basis for Omics Sciences

This review is devoted to the consideration of mass spectrometric platforms as applied to omics sciences. The most significant attention is paid to omics related to life sciences (genomics, proteomics, meta-bolomics, lipidomics, glycomics, plantomics, etc.). Mass spectrometric approaches to solving the problems of petroleomics, polymeromics, foodomics, humeomics, and exosomics, related to inorganic sciences, are also discussed. The review comparatively presents the advantages of various principles of separation and mass spectral techniques, complementary derivatization, used to obtain large arrays of various structural and quantitative information in the mentioned omics sciences.

IgG N-glycans

Glycosylation, one of the most common post-translational modifications in mammalian cells, impacts many biological processes such as cell adhesion, proliferation and differentiation. As the most abundant glycoprotein in human serum, immunoglobulin G (IgG) plays a vital role in immune response and protection. There is a growing body of evidence suggests that IgG structure and function are modulated by attached glycans, especially N-glycans, and aberrant glycosylation is associated with disease states. In this chapter, we review IgG glycan repertoire and function, strategies for profiling IgG N-glycome and recent studies. Mass spectrometry (MS) based techniques are the most powerful tools for profiling IgG glycome. IgG glycans can be divided into high-mannose, biantennary complex and hybrid types, modified with mannosylation, core-fucosylation, galactosylation, bisecting GlcNAcylation, or sialylation. Glycosylation of IgG affects antibody half-life and their affinity and avidity for antigens, regulates crystallizable fragment (Fc) structure and Fcγ receptor signaling, as well as antibody effector function. Because of their critical roles, IgG N-glycans appear to be promising biomarkers for various disease states. Specific IgG glycosylation can convert a pro-inflammatory response to an anti-inflammatory activity. Accordingly, IgG glycoengineering provides a powerful approach to potentially develop effective drugs and treat disease. Based on the understanding of the functional role of IgG glycans, the development of vaccines with enhanced capacity and long-term protection are possible in the near future.

Hydrophilic arginine-functionalized mesoporous polydopamine-graphene oxide composites for glycopeptides analysis

Considering the importance of glycopeptides in the clinical diagnosis of cancer and some serious diseases, the identification of glycopeptides from complex biological samples has attracted considerable attention. Effective pre-enrichment before mass spectrometry analysis plays an important role. In this work, a kind of hydrophilic two-dimensional composites (denoted as GO@MPDA@Arg) based on mesoporous polydopamine-graphene oxide were used to selectively enrich glycopeptides in biological samples. The mesoporous polydopamine (MPDA) layer self-assembled with template Pluronic F127 provided more binding sites to load arginine, and bound arginine enhanced the hydrophilicity of the material. As a result, GO@MPDA@Arg composites exhibited excellent enrichment performance for glycopeptides, containing good selectivity (IgG digests : BSA digests = 1:50, molar ratio), low detection limit for IgG digests (10 fmol μL^-1), high loading capacity for IgG digests (200 μg mg^-1), and good size exclusion (IgG digests : IgG : BSA = 1:100:100, mass ratio). In addition, mouse brain tissue was selected as the actual biological sample to further study the enrichment effect of GO@MPDA@Arg composites. In three parallel experiments, a total of 401 glycopeptides belonging to 233 glycoproteins were enriched from 200 μg digestion of mouse brain extract. The enrichment results demonstrate that GO@MPDA@Arg composites have application potential for glycopeptides enrichment in protein post-translational modification research.

[Recent advances in glycopeptide enrichment and mass spectrometry data interpretation approaches for glycoproteomics analyses]

蛋白质糖基化是生物体内最重要的翻译后修饰之一,在蛋白质稳定性、细胞内和细胞间信号转导、激素活化或失活和免疫调节等生理过程和病理进程中发挥重要作用。而异常的蛋白质糖基化往往和多种疾病的发生发展密切相关,目前应用于临床检测的多种肿瘤生物标志物大多属于糖蛋白或者糖抗原。因此在组学层次系统分析蛋白质糖基化的变化对阐明生物体内糖基化修饰的调控机理和发现新型疾病标志物都非常重要。基于质谱的蛋白质组学技术为全面分析蛋白质及其修饰提供了有效的分析手段。在自下而上的蛋白质组学研究中,由于完整糖基化肽段同时存在性质各异的肽段骨架和糖链结构、糖肽的相对丰度和离子化效率较低以及糖基化修饰有高度异质性等特点,完整糖肽的分析比其他翻译后修饰更加困难。近年来,为了更全面、系统地分析蛋白质糖基化,研究人员发展了一些新技术,包括完整糖肽的富集技术、质谱的碎裂模式和数据采集模式、质谱数据的解析方法和定量策略等等,大力推进了该领域的研究水平,也为研究蛋白质糖基化相关的生物标志物提供了技术支持。该篇综述主要关注近年来基于质谱的糖蛋白质组学研究中的新进展,重点介绍针对完整N-和O-糖基化肽段的富集新技术和谱图解析新方法,并讨论其在肿瘤早期诊断方面的应用潜力。

Bifunctional magnetic covalent organic framework for simultaneous enrichment of phosphopeptides and glycopeptides

Protein phosphorylation and glycosylation, which are closely related to various diseases, have been extensively studied recently. Mass spectrometry (MS) based phosphoproteomics and glycoproteomics analysis rely heavily on the pre-treatment. Due to the differences in enrichment conditions, there are still huge challenges in designing and preparing a single affinity material to achieve efficient simultaneous capture and elution of phosphopeptides and glycopeptides. Herein, a novel magnetic covalent organic framework, which was modified with functional molecule 4-(3-(2-(methacryloyloxy)ethyl)-ureido)benzoic acid (MUBA), was designed as a bifunctional enrichment platform for glycopeptides and phosphopeptides. Thanks to the multiple hydrogen bonding interactions between MUBA and hydrogen phosphates, the material possessed excellent enrichment performance for phosphopeptides. In addition, the hydrophilicity of the COF structure and modified molecules endowed this material recognition capability towards glycopeptides based on hydrophilic interaction chromatography. Combining with the inherent properties of COF structure, the established platform achieved simultaneous enrichment of phosphopeptides and glycopeptides with excellent selectivity (1:1:1000 M ratio of α-casein/IgG/BSA), high sensitivity (0.05 fmol/μL α-casein; 0.05 fmol/μL IgG), and good size-exclusion effect (α-casein digests/IgG digests/BSA, 1:1:500). More excitingly, the method was used for the identification of glycopeptides and phosphopeptides from rat liver tissue and the exosomes extracted from liver cancer patients' plasma, proving its specific phosphoproteomics and glycoproteomics study in complex biosamples.

Benefits of Chemical Sugar Modifications Introduced by Click Chemistry for Glycoproteomic Analyses

Mucin-type O-glycosylation is among the most complex post-translational modifications. Despite mediating many physiological processes, O-glycosylation remains understudied compared to other modifications, simply because the right analytical tools are lacking. In particular, analysis of intact O-glycopeptides by mass spectrometry is challenging for several reasons; O-glycosylation lacks a consensus motif, glycopeptides have low charge density which impairs ETD fragmentation, and the glycan structures modifying the peptides are unpredictable. Recently, we introduced chemically modified monosaccharide analogues that allowed selective tracking and characterization of mucin-type O-glycans after bioorthogonal derivatization with biotin-based enrichment handles. In doing so, we realized that the chemical modifications used in these studies have additional benefits that allow for improved analysis by tandem mass spectrometry. In this work, we built on this discovery by generating a series of new GalNAc analogue glycopeptides. We characterized the mass spectrometric signatures of these modified glycopeptides and their signature residues left by bioorthogonal reporter reagents. Our data indicate that chemical methods for glycopeptide profiling offer opportunities to optimize attributes such as increased charge state, higher charge density, and predictable fragmentation behavior.

Fabrication of magnetic dual-hydrophilic metal organic framework for highly efficient glycopeptide enrichment

Highly selective glycopeptide enrichment is important before mass spectrometry analysis because of the ultra-low abundance of glycopeptides in the peptide mixtures. Herein, a UiO-66-NH₂-based magnetic composite was prepared and used for the hydrophilic enrichment of glycopeptides. The composite was modified with phytic acid (PA) molecules by partially replacing 2-aminoterephthalic acid ligands in UiO-66-NH₂, with electrostatic interactions also promoting this modification process. Based on the hydrophilicity of both the PA molecules and the UiO-66-NH₂ skeleton, the resulting material, denoted as MUiO-66-NH₂/PA, showed excellent dual hydrophilicity towards glycopeptide enrichment. Compared with pure UiO-66-NH₂, the specific surface area and hydrophilicity of the prepared material were increased, and MUiO-66-NH₂/PA exhibited good magnetic responsiveness to facilitate a convenient enrichment procedure. HRP and IgG were used as standard proteins to evaluate the glycopeptide enrichment properties, with 21 and 34 glycopeptides enriched from their tryptic digests. Furthermore, MUiO-66-NH₂/PA showed outstanding sensitivity (1 fmol/μL) and selectivity (HRP/BSA = 1:1000), and achieved remarkable glycopeptide enrichment performance for practical human serum samples. Notably, MUiO-66-NH₂/PA showed perfect reusability and stability, achieving enrichment performance after five cycles similar to that of the first use. This material can be used for glycopeptide enrichment to obtain further glycosylation information, providing the possibility for cancer treatment.

Construction of a magnetic covalent organic framework with synergistic affinity strategy for enhanced glycopeptide enrichment

Considering the inherent properties of glycopeptides, such as glycan structure, size, and hydrophilicity, affinity materials possessing suitable functional molecule-glycan interactions, matched channels with size exclusion, and surfaces with hydrophilic interactions are preferred for glycopeptide separation in biological samples. Here, a novel boronic-acid-functionalized magnetic covalent organic framework was prepared through epitaxial growth and multi-ligand strategies. The multi-ligand strategy was firstly employed to prepare functionalized magnetic covalent organic framework without any post-functionalization protocol. Notably, the proposed strategy was found to be time saving, robust, and reproducible. The versatile magnetic covalent organic framework nanocomposite was endowed with phenylboronic acid functional molecules, strong hydrophilic features, mesoporous channels, fast magnetic responsiveness, and a large surface area. Benefitting from multiple affinity interactions, namely, synergistic reversible covalent interactions and hydrophilic affinity interactions, the nanocomposite presented extremely high performance in the recognition of intact N-glycopeptides. The inherent properties endowed the nanocomposite with excellent enrichment performance for N-glycopeptides: excellent selectivity (1 : 2000, IgG/BSA, m/m), an ultralow detection limit (0.05 fmol μL^-1), and a good size-exclusion effect (1 : 500, IgG digests/BSA, m/m). More excitingly, a total of 1921 unique intact glycopeptides assigned to 1154 glycoproteins were identified from rat liver tissue; this performance is superior to that of commercial products. Additionally, the nanocomposite was successfully applied to enrich intact glycopeptides of exosomes extracted from healthy individuals and renal failure patients, providing a novel concept for the design of materials using a synergistic affinity strategy for sample preparation in glycoproteomics.

Analysis of Intact Glycoproteins by Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) can be regarded as a key tool to rapidly obtain molecular mass information of intact glycoproteins in glycoproteomic studies and quality control of recombinant biopharmaceuticals. However, MALDI-TOF MS of these glycosylated compounds is a tricky task due to its low ionization efficiency and fragmentation of labile groups such as sialic acids.Here, we offer the reader a practical overview of the available methodologies for the confident analysis of intact glycoproteins with different glycosylation degree by MALDI-TOF MS. The three proposed methods fulfil the requirements of reproducibility and low extent of glycan fragmentation required to successfully analyze intact glycoproteins.

Dual-Functional Ti(IV)-IMAC Material Enables Simultaneous Enrichment and Separation of Diverse Glycopeptides and Phosphopeptides

Simultaneous enrichment and fractionation of diverse proteins/peptides possessing different post-translational modifications (PTMs) from the same biological samples is highly desirable to reduce sample consumption, avoid complicated sample processing, and enable studies of potential crosstalks between different PTMs. In this work, we report a new approach to enable simultaneous enrichment and separation of glycopeptides, phosphopeptides, and mannose-6-phosphate (M6P) glycopeptides by using a dual-functional Ti(IV)-IMAC material. Moreover, we also made the separation of neutral and sialyl glycopeptides and mono- and multi-phosphopeptides possible by performing different elution processes according to the differences in their electrostatic or hydrophilic properties. These separations are effective and efficient to eliminate the signal suppression from neutral glycopeptides for sialyl glycopeptide detection, allowing separation of mono-phosphopeptides from multi-phosphopeptides, as well as detection of M6P glycopeptides that are free from the abovementioned modifications. This new strategy significantly improves the coverage and identification numbers of glycopeptides, phosphopeptides, and M6P glycopeptides by 1.9, 2.3, and 4.3-fold compared with the conventional method, respectively. This is the first report on simultaneous enrichment and separation of neutral and sialyl glycopeptides, mono- and multi-phosphopeptides, and M6P glycopeptides via dual-functional Ti(IV)- IMAC, revealing novel insights into potential crosstalk among these important PTMs.

Automated Intact Glycopeptide Enrichment Method Facilitating Highly Reproducible Analysis of Serum Site-Specific N-Glycoproteome

Bottom-up proteomics has been increasingly applied in clinical research to study the disease pathophysiology and to discover disease biomarkers. However, glycoproteomic analysis always requires tedious experimental steps for intact glycopeptide enrichment, which has been the technique bottleneck for large-scale analysis of clinical samples. Herein, we developed an automated glycopeptide enrichment method for the analysis of serum site-specific N-glycoproteome. This automated method allowed for processing one sample within 20 min. It showed higher enrichment specificity, more intact glycopeptide identifications, and better quantitative reproducibility than the traditional manual method using microtip enrichment devices. We further applied this method to investigate the serum site-specific N-glycosylation changes between four patients with pancreatic cancer and seven healthy controls. The principal component analysis of intact N-glycopeptides showed good clustering across cancer and normal groups. Furthermore, we found that the site-specific glycoforms, monofucosylated and nonsialylated oligosaccharides, on IgG1 site 180 expressed a significant decrease in pancreatic cancer patients compared to healthy controls. Together, the automated method is a powerful tool for site-specific N-glycoproteomic analysis of complex biological samples, and it has great potential for clinical utilities.

In-depth Site-specific Analysis of N-glycoproteome in Human Cerebrospinal Fluid and Glycosylation Landscape Changes in Alzheimer's Disease

As the body fluid that directly interchanges with the extracellular fluid of the central nervous system (CNS), cerebrospinal fluid (CSF) serves as a rich source for CNS-related disease biomarker discovery. Extensive proteome profiling has been conducted for CSF, but studies aimed at unraveling site-specific CSF N-glycoproteome are lacking. Initial efforts into site-specific N-glycoproteomics study in CSF yield limited coverage, hindering further experimental design of glycosylation-based disease biomarker discovery in CSF. In the present study, we have developed an N-glycoproteomic approach that combines enhanced N-glycopeptide sequential enrichment by hydrophilic interaction chromatography (HILIC) and boronic acid enrichment with electron transfer and higher-energy collision dissociation (EThcD) for large-scale intact N-glycopeptide analysis. The application of the developed approach to the analyses of human CSF samples enabled identifications of a total of 2893 intact N-glycopeptides from 511 N-glycosites and 285 N-glycoproteins. To our knowledge, this is the largest site-specific N-glycoproteome dataset reported for CSF to date. Such dataset provides molecular basis for a better understanding of the structure-function relationships of glycoproteins and their roles in CNS-related physiological and pathological processes. As accumulating evidence suggests that defects in glycosylation are involved in Alzheimer's disease (AD) pathogenesis, in the present study, a comparative in-depth N-glycoproteomic analysis was conducted for CSF samples from healthy control and AD patients, which yielded a comparable N-glycoproteome coverage but a distinct expression pattern for different categories of glycoforms, such as decreased fucosylation in AD CSF samples. Altered glycosylation patterns were detected for a number of N-glycoproteins including alpha-1-antichymotrypsin, ephrin-A3 and carnosinase CN1 etc., which serve as potentially interesting targets for further glycosylation-based AD study and may eventually lead to molecular elucidation of the role of glycosylation in AD progression.

A biotechnological tool for glycoprotein desialylation based on immobilized neuraminidase from Clostridium perfringens

Background

Sialic acids are widely distributed in nature and have biological relevance owing to their varied structural and functional roles. Immobilized neuraminidase can selectively remove terminal N-acetyl neuraminic acid from glycoproteins without altering the protein backbone while it can be easily removed from the reaction mixture avoiding sample contamination. This enables the evaluation of changes in glycoprotein performance upon desialylation.

Methods

Neuraminidase was immobilized onto agarose activated with cyanate ester groups and further used for desialylation of model glycoproteins, a lysate from tumour cells and tumour cells. Desialylation process was analysed by lectin binding assay, determination of sialyl-Tn or flow cytometry.

Results

Clostridium perfringens neuraminidase was immobilized with 91 % yield and expressed activity yield was of 41%. It was effective in the desialylation of bovine fetal serum fetuin, bovine lactoferrin and ovine submaxilar mucin. A decrease in sialic-specific SNA lectin recognition of 83% and 53 % was observed for fetuin and lactoferrin with a concomitant increase in galactose specific ECA and PNA lectin recognition. Likewise, a decrease in the recognition of a specific antibody (82%) upon mucin desialylation was observed. Moreover, desialylation of a protein lysate from the sialic acid-rich cell line TA3/Ha was also possible leading to a decrease in 47 % in SNA recognition. Immobilized neuraminidase kept 100% of its initial activity upon five desialylation cycles.

Conclusions

Immobilized neuraminidase is an interesting as well as a robust biotechnological tool for enzymatic desialylation purposes.

General significance

Immobilized neuraminidase would contribute to understand the role of sialic acid in biological processes.

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Neuraminidase immobilization was successfully achieved.

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Immobilized neuraminidase was effective in the desialylation of several model glycoproteins.

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TA3/Ha tumour cell lysates were desialylated with immobilized neuraminidase.

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Immobilized neuraminidase was successfully re-used.

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.

Generating orthogonal glycosyltransferase and nucleotide sugar pairs as next-generation glycobiology tools

Protein glycosylation fundamentally impacts biological processes. Nontemplated biosynthesis introduces unparalleled complexity into glycans that needs tools to understand their roles in physiology. The era of quantitative biology is a great opportunity to unravel these roles, especially by mass spectrometry glycoproteomics. However, with high sensitivity come stringent requirements on tool specificity. Bioorthogonal metabolic labeling reagents have been fundamental to studying the cell surface glycoproteome but typically enter a range of different glycans and are thus of limited specificity. Here, we discuss the generation of metabolic 'precision tools' to study particular subtypes of the glycome. A chemical biology tactic termed bump-and-hole engineering generates mutant glycosyltransferases that specifically accommodate bioorthogonal monosaccharides as an enabling technique of glycobiology. We review the groundbreaking discoveries that have led to applying the tactic in the living cell and the implications in the context of current developments in mass spectrometry glycoproteomics.

Serum N-Glycomics Stratifies Bacteremic Patients Infected with Different Pathogens

Bacteremia—i.e., the presence of pathogens in the blood stream—is associated with long-term morbidity and is a potential precursor condition to life-threatening sepsis. Timely detection of bacteremia is therefore critical to reduce patient mortality, but existing methods lack precision, speed, and sensitivity to effectively stratify bacteremic patients. Herein, we tested the potential of quantitative serum N-glycomics performed using porous graphitized carbon liquid chromatography tandem mass spectrometry to stratify bacteremic patients infected with Escherichia coli (n = 11), Staphylococcus aureus (n = 11), Pseudomonas aeruginosa (n = 5), and Streptococcus viridans (n = 5) from healthy donors (n = 39). In total, 62 N-glycan isomers spanning 41 glycan compositions primarily comprising complex-type core fucosylated, bisecting N-acetylglucosamine (GlcNAc), and α2,3-/α2,6-sialylated structures were profiled across all samples using label-free quantitation. Excitingly, unsupervised hierarchical clustering and principal component analysis of the serum N-glycome data accurately separated the patient groups. P. aeruginosa-infected patients displayed prominent N-glycome aberrations involving elevated levels of fucosylation and bisecting GlcNAcylation and reduced sialylation relative to other bacteremic patients. Notably, receiver operating characteristic analyses demonstrated that a single N-glycan isomer could effectively stratify each of the four bacteremic patient groups from the healthy donors (area under the curve 0.93–1.00). Thus, the serum N-glycome represents a new hitherto unexplored class of potential diagnostic markers for bloodstream infections.

Generating orthogonal glycosyltransferase and nucleotide sugar pairs as next-generation glycobiology tools

Protein glycosylation fundamentally impacts biological processes. Nontemplated biosynthesis introduces unparalleled complexity into glycans that needs tools to understand their roles in physiology. The era of quantitative biology is a great opportunity to unravel these roles, especially by mass spectrometry glycoproteomics. However, with high sensitivity come stringent requirements on tool specificity. Bioorthogonal metabolic labeling reagents have been fundamental to studying the cell surface glycoproteome but typically enter a range of different glycans and are thus of limited specificity. Here, we discuss the generation of metabolic 'precision tools' to study particular subtypes of the glycome. A chemical biology tactic termed bump-and-hole engineering generates mutant glycosyltransferases that specifically accommodate bioorthogonal monosaccharides as an enabling technique of glycobiology. We review the groundbreaking discoveries that have led to applying the tactic in the living cell and the implications in the context of current developments in mass spectrometry glycoproteomics.

GlycoPOST realizes FAIR principles for glycomics mass spectrometry data

For the reproducibility and sustainability of scientific research, FAIRness (Findable, Accessible, Interoperable and Re-usable), with respect to the release of raw data obtained by researchers, is one of the most important principles underpinning the future of open science. In genomics and transcriptomics, the sharing of raw data from next-generation sequencers is made possible through public repositories. In addition, in proteomics, the deposition of raw data from mass spectrometry (MS) experiments into repositories is becoming standardized. However, a standard repository for such MS data had not yet been established in glycomics. With the increasing number of glycomics MS data, therefore, we have developed GlycoPOST (https://glycopost.glycosmos.org/), a repository for raw MS data generated from glycomics experiments. In just the first year since the release of GlycoPOST, 73 projects have already been registered by researchers around the world, and the number of registered projects is continuously growing, making a significant contribution to the future FAIRness of the glycomics field. GlycoPOST is a free resource to the community and accepts (and will continue to accept in the future) raw data regardless of vendor-specific formats.

A mass spectrometry-based glycotope-centric cellular glycomics is the more fruitful way forward to see the forest for the trees

The nature of protein glycosylation renders cellular glycomics a very challenging task in having to deal with all the disparate glycans carried on membrane glycoproteins. Rapid mapping by mass spectrometry analysis provides only a coarse sketch of the glycomic complexity based primarily on glycosyl compositions, whereby the missing high-resolution structural details require a combination of multi-mode separations and multi-stages of induced fragmentation to gain sufficiently discriminative precision, often at the expenses of throughput and sensitivity. Given the available technology and foreseeable advances in the near future, homing in on resolving the terminal fucosylated, sialylated and/or sulfated structural units, or glycotopes, maybe a more pragmatic and ultimately more rewarding approach to gain insights into myriad biological processes mediated by these terminal coding units carried on important glycoproteins, to be decoded by a host of endogenous glycan-binding proteins and antibodies. A broad overview of recent technical advances and limitations in cellular glycomics is first provided as a backdrop to the propounded glycotope-centric approach based on advanced nanoLC-MS2/MS3 analysis of permethylated glycans. To prioritize analytical focus on the more tangible glycotopes is akin to first identifying the eye-catching and characteristic-defining flowers and fruits of the glyco-forest, to see the forest for the trees. It has the best prospects of attaining the much-needed balance in sensitivity, structural precision and analytical throughput to match advances in other omics.

Towards structure-focused glycoproteomics

Facilitated by advances in the separation sciences, mass spectrometry and informatics, glycoproteomics, the analysis of intact glycopeptides at scale, has recently matured enabling new insights into the complex glycoproteome. While diverse quantitative glycoproteomics strategies capable of mapping monosaccharide compositions of N- and O-linked glycans to discrete sites of proteins within complex biological mixtures with considerable sensitivity, quantitative accuracy and coverage have become available, developments supporting the advancement of structure-focused glycoproteomics, a recognised frontier in the field, have emerged. Technologies capable of providing site-specific information of the glycan fine structures in a glycoproteome-wide context are indeed necessary to address many pending questions in glycobiology. In this review, we firstly survey the latest glycoproteomics studies published in 2018–2020, their approaches and their findings, and then summarise important technological innovations in structure-focused glycoproteomics. Our review illustrates that while the O-glycoproteome remains comparably under-explored despite the emergence of new O-glycan-selective mucinases and other innovative tools aiding O-glycoproteome profiling, quantitative glycoproteomics is increasingly used to profile the N-glycoproteome to tackle diverse biological questions. Excitingly, new strategies compatible with structure-focused glycoproteomics including novel chemoenzymatic labelling, enrichment, separation, and mass spectrometry-based detection methods are rapidly emerging revealing glycan fine structural details including bisecting GlcNAcylation, core and antenna fucosylation, and sialyl-linkage information with protein site resolution. Glycoproteomics has clearly become a mainstay within the glycosciences that continues to reach a broader community. It transpires that structure-focused glycoproteomics holds a considerable potential to aid our understanding of systems glycobiology and unlock secrets of the glycoproteome in the immediate future.