Large-scale Identification of N-linked Intact Glycopeptides in Human Serum using HILIC Enrichment and Spectral Library Search

Enrichment methods of N-linked glycopeptides from human serum or plasma: A mini-review

Human diseases often correlate with changes in protein glycosylation, which can be observed in serum or plasma samples. N-glycosylation, the most common form, can provide potential biomarkers for disease prognosis and diagnosis. However, glycoproteins constitute a relatively small proportion of the total proteins in human serum and plasma compared to the non-glycosylated protein albumin, which constitutes the majority. The detection of microheterogeneity and low glycan abundance presents a challenge. Mass spectrometry facilitates glycoproteomics research, yet it faces challenges due to interference from abundant plasma proteins. Therefore, methods have emerged to enrich N-glycans and N-linked glycopeptides using glycan affinity, chemical properties, stationary phase chemical coupling, bioorthogonal techniques, and other alternatives. This review focuses on N-glycans and N-glycopeptides enrichment in human serum or plasma, emphasizing methods and applications. Although not exhaustive, it aims to elucidate principles and showcase the utility and limitations of glycoproteome characterization.

Prediction of glycopeptide fragment mass spectra by deep learning

Deep learning has achieved a notable success in mass spectrometry-based proteomics and is now emerging in glycoproteomics. While various deep learning models can predict fragment mass spectra of peptides with good accuracy, they cannot cope with the non-linear glycan structure in an intact glycopeptide. Herein, we present DeepGlyco, a deep learning-based approach for the prediction of fragment spectra of intact glycopeptides. Our model adopts tree-structured long-short term memory networks to process the glycan moiety and a graph neural network architecture to incorporate potential fragmentation pathways of a specific glycan structure. This feature is beneficial to model explainability and differentiation ability of glycan structural isomers. We further demonstrate that predicted spectral libraries can be used for data-independent acquisition glycoproteomics as a supplement for library completeness. We expect that this work will provide a valuable deep learning resource for glycoproteomics.

Advancing mass spectrometry-based glycoproteomic software tools for comprehensive site-specific glycoproteome analysis

Glycoproteome analysis at a site-specific level and proteome scale stands out as a highly promising approach for gaining insights into the intricate roles of glycans in biological systems. Recent years have witnessed an upsurge in the development of innovative methodologies tailored for precisely this purpose. Breakthroughs in mass spectrometry-based glycoproteomic techniques, enabling the identification, quantification, and systematic exploration of site-specific glycans, have significantly enhanced our capacity to comprehensively and thoroughly characterize glycoproteins. In this short review, we delve into novel tools in advancing site-specific glycoproteomic analysis and summarize pertinent studies published in the past two years. Lastly, we discuss the ongoing challenges and outline future prospects in the field, considering both the analytical strategies of mass spectrometry and the tools employed for data interpretation.

Robust Glycoproteomics Platform Reveals a Tetra-Antennary Site-Specific Glycan Capping with Sialyl-Lewis Antigen for Early Detection of Gastric Cancer

The lack of efficient biomarkers for the early detection of gastric cancer (GC) contributes to its high mortality rate, so it is crucial to discover novel diagnostic targets for GC. Recent studies have implicated the potential of site-specific glycans in cancer diagnosis, yet it is challenging to perform highly reproducible and sensitive glycoproteomics analysis on large cohorts of samples. Here, a highly robust N-glycoproteomics (HRN) platform comprising an automated enrichment method, a stable microflow LC-MS/MS system, and a sensitive glycopeptide-spectra-deciphering tool is developed for large-scale quantitative N-glycoproteome analysis. The HRN platform is applied to analyze serum N-glycoproteomes of 278 subjects from three cohorts to investigate glycosylation changes of GC. It identifies over 20 000 unique site-specific glycans from discovery and validation cohorts, and determines four site-specific glycans as biomarker candidates. One candidate has branched tetra-antennary structure capping with sialyl-Lewis antigen, and it significantly outperforms serum CEA with AUC values > 0.89 compared against < 0.67 for diagnosing early-stage GC. The four-marker panel can provide improved diagnostic performances. Besides, discrimination powers of four candidates are also testified with a verification cohort using PRM strategy. This findings highlight the value of this strong tool in analyzing aberrant site-specific glycans for cancer detection.

Oxonium ion scanning mass spectrometry for large-scale plasma glycoproteomics

Protein glycosylation, a complex and heterogeneous post-translational modification that is frequently dysregulated in disease, has been difficult to analyse at scale. Here we report a data-independent acquisition technique for the large-scale mass-spectrometric quantification of glycopeptides in plasma samples. The technique, which we named 'OxoScan-MS', identifies oxonium ions as glycopeptide fragments and exploits a sliding-quadrupole dimension to generate comprehensive and untargeted oxonium ion maps of precursor masses assigned to fragment ions from non-enriched plasma samples. By applying OxoScan-MS to quantify 1,002 glycopeptide features in the plasma glycoproteomes from patients with COVID-19 and healthy controls, we found that severe COVID-19 induces differential glycosylation in IgA, haptoglobin, transferrin and other disease-relevant plasma glycoproteins. OxoScan-MS may allow for the quantitative mapping of glycoproteomes at the scale of hundreds to thousands of samples.

Salivary Proteome and Intact N-Glycopeptides Analysis Reveal Specific Signatures in Periodontitis

Periodontitis is a prevalent oral inflammatory disease that can result in tooth loss and is closely linked to type 2 diabetes (T2D). In this study, we analyzed the salivary proteome and intact N-glycopeptides (IGPs) of individuals with mild-moderate, severe, aggressive periodontitis, and periodontitis with T2D, including those treated with antidiabetic drugs, to identify specific signatures associated with the disease. Our results revealed that salivary proteins and glycoproteins were altered in all periodontitis groups (PRIDE ID: 1-20230612-72345), with fucose- and sialic acid-containing N-glycans showing the greatest increase. Additionally, differentially expressed proteins were classified into 9 clusters, including those that were increased in all periodontitis groups and those that were only altered in certain types of periodontitis. Interestingly, treatment with antidiabetic drugs reversed many of the changes observed in the salivary proteome and IGPs in T2D-related periodontitis, suggesting a potential therapeutic approach for managing periodontitis in patients with T2D. Consistent with MS/MS results, the expression of salivary IGHA2 and Fucα1-3/6GlcNAc (AAL) was significantly increased in MP. These findings provide new insights into the pathogenesis of periodontitis and highlight the potential of salivary biomarkers for diagnosis, prognosis, and monitoring of disease progression and treatment response.

Proteomic Analyses of the Mouse Brain

Proteomics is a scientific field that aims to identify and characterize all proteins within a biological system, including their posttranslational modifications (PTMs), quantitative changes, and protein-protein interactions. Over the last two decades, proteomic approaches have been widely used in neuroscience research, providing multidimensional insights into the biology and pathology of the brain.Here, we present a basic protocol for profiling protein expression in the mouse brain, which involves total protein extraction, fractionation, digestion, and identification through liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). This method is compatible with many prevalent techniques used for protein quantitation, PTM analysis, and protein-protein interaction mapping.

Improved analysis ZIC-HILIC-HCD-Orbitrap method for mapping the glycopeptide by mass spectrometry

Glycosylation is one of the most common post-translational modifications (PTMs). Protein glycosylation analysis is the bottleneck to deeply understand their functions. At present, the LC-MS analysis of glycosylated post-translational modification is mainly focused on the analysis of glycopeptides. However, the factors affecting the identification of glycopeptides were not fully elucidated. In the paper, we have carefully studied the factors, e.g., HILIC materials, search engines, protein amount, gradient duration, extraction solution, etc. According to the results, HILIC materials were the most important factors affecting the glycopeptides identification, and the amphoteric sulfoalkyl betaine stationary phase enriched glycopeptides 6-fold more compared to the amphiphilic ion-bonded fully porous spherical silica stationary phase. We explored the influence of the extraction solutions on glycan identification. Comparing sodium dodecyl sulfate (SDS) and urea (UA), the results showed that N-glycolylneuraminic acid (NeuGc) type of glycan content was found to be increased 1.4-fold in the SDS compared to UA. Besides, we explored the influence of the search engine on glycopeptide identification. Comparing pGlyco3.0 and MSFragger-Glyco, it was observed that pGlyco3.0 outperformed MSFragger-Glyco in identifying glycopeptides. Then, using our optimized method we found that there was a significant difference in the distribution of monosaccharide types in plasma and brain tissue, e.g., the content of NeuAc in brain was 5-fold higher than that in plasma. To importantly, two glycoproteins (Neurexin-2 and SUN domain-containing protein 2) were also found for the first time by our method. In summary, we have comprehensively studied the factors influencing glycopeptide identification than any previous research, and the optimized method could be widely used for identifying the glycoproteins or glycolpeptides biomarkers for disease detection and therapeutic targets.

In-Depth Mass Spectrometry Analysis Reveals the Plasma Proteomic and N-Glycoproteomic Impact of an Amish-Enriched Cardioprotective Variant in B4GALT1

B4GALT1 encodes β-1,4-galactosyltransferase 1, an enzyme that plays a major role in glycan synthesis in the Golgi apparatus by catalyzing the addition of terminal galactose. Studies increasingly suggest that B4GALT1 may be involved in the regulation of lipid metabolism pathways. Recently, we discovered a single-site missense variant Asn352Ser (N352S) in the functional domain of B4GALT1 in an Amish population, which decreases the level of LDL-cholesterol (LDL-c) as well as the protein levels of ApoB, fibrinogen, and IgG in the blood. To systematically evaluate the effects of this missense variant on protein glycosylation, expression, and secretion, we developed a nano-LC-MS/MS-based platform combined with TMT-labeling for in-depth quantitative proteomic and glycoproteomic analyses in the plasma of individuals homozygous for the B4GALT1 missense variant N352S versus non-carriers (n = 5 per genotype). A total of 488 secreted proteins in the plasma were identified and quantified, 34 of which showed significant fold changes in protein levels between N352S homozygotes and non-carriers. We determined N-glycosylation profiles from 370 glycosylation sites in 151 glycoproteins and identified ten proteins most significantly associated with decreased galactosylation and sialyation in B4GALT1 N352S homozygotes. These results further support that B4GALT1 N352S alters the glycosylation profiles of a variety of critical target proteins, thus governing the functions of these proteins in multiple pathways, such as those involved in lipid metabolism, coagulation, and the immune response.

Roles of glycosylation at the cancer cell surface: opportunities for large scale glycoproteomics

Cell surface glycosylation has a variety of functions, and its dysregulation in cancer contributes to impaired signaling, metastasis and the evasion of the immune responses. Recently, a number of glycosyltransferases that lead to altered glycosylation have been linked to reduced anti-tumor immune responses: B3GNT3, which is implicated in PD-L1 glycosylation in triple negative breast cancer, FUT8, through fucosylation of B7H3, and B3GNT2, which confers cancer resistance to T cell cytotoxicity. Given the increased appreciation of the relevance of protein glycosylation, there is a critical need for the development of methods that allow for an unbiased interrogation of cell surface glycosylation status. Here we provide an overview of the broad changes in glycosylation at the surface of cancer cell and describe selected examples of receptors with aberrant glycosylation leading to functional changes, with emphasis on immune checkpoint inhibitors, growth-promoting and growth-arresting receptors. Finally, we posit that the field of glycoproteomics has matured to an extent where large-scale profiling of intact glycopeptides from the cell surface is feasible and is poised for discovery of new actionable targets against cancer.

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.

Methods for quantification of glycopeptides by liquid separation and mass spectrometry

Recent advances in analytical techniques provide the opportunity to quantify even low-abundance glycopeptides derived from complex biological mixtures, allowing for the identification of glycosylation differences between healthy samples and those derived from disease states. Herein, we discuss the sample preparation procedures and the mass spectrometry (MS) strategies that have facilitated glycopeptide quantification, as well as the standards used for glycopeptide quantification. For sample preparation, various glycopeptide enrichment methods are summarized including the columns used for glycopeptide separation in liquid chromatography separation. For MS analysis strategies, MS1 level-based quantification and MS2 level-based quantification are described, either with or without labeling, where we have covered isotope labeling, TMT/iTRAQ labeling, data dependent acquisition, data independent acquisition, multiple reaction monitoring, and parallel reaction monitoring. The strengths and weaknesses of these methods are compared, particularly those associated with the figures of merit that are important for clinical biomarker studies and the pathological and functional studies of glycoproteins in various diseases. Possible future developments for glycopeptide quantification are discussed.

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.

Advances in glycopeptide enrichment methods for the analysis of protein glycosylation over the past decade

Advances in bioanalytical technology have accelerated the analysis of complex protein glycosylation, which is beneficial to understanding glycosylation in drug discovery and disease diagnosis. Due to its biological uniqueness in the course of disease occurrence and development, disease-specific glycosylation requires quantitative characterization of protein glycosylation. We provide a comprehensive review of recent advances in glycosylation analysis, including workflows for glycoprotein digestion, glycopeptide separation and enrichment, and mass-spectrometry sequencing. We specifically focus on different strategies for glycopeptide enrichment through physical interaction, chemical oxidation, or metabolic labeling of intact glycopeptides. The recent advances and challenges of O-glycosylation analysis are presented, and the development of improved enrichment methods combining different proteases to analyze O-glycosylation is also proposed. This article is protected by copyright. All rights reserved.

Integrated N-glycoproteomics Analysis of Human Saliva for Lung Cancer

Aberrant protein N-glycosylation is a cancer hallmark, which has great potential for cancer detection. However, large-scale and in-depth analysis of N-glycosylation remains challenging because of its high heterogeneity, complexity, and low abundance. Human saliva is an attractive diagnostic body fluid, while few efforts explored its N-glycoproteome for lung cancer. Here, we utilized a zwitterionic-hydrophilic interaction chromatography-based strategy to specifically enrich salivary glycopeptides. Through quantitative proteomics analysis, 1492 and 1234 intact N-glycopeptides were confidently identified from pooled saliva samples of 10 subjects in the nonsmall-cell lung cancer group and 10 subjects in the normal control group. Accordingly, 575 and 404 N-glycosites were revealed for the lung cancer group and normal control group. In particular, 154 N-glycosites and 259 site-specific glycoforms were significantly dysregulated in the lung cancer group. Several N-glycosites located at the same glycoprotein and glycans attached to the same N-glycosites were observed with differential expressions, including haptoglobin, Mucin-5B, lactotransferrin, and α-1-acid glycoprotein 1. These N-glycoproteins were mainly related to inflammatory responses, infectious diseases, and cancers. Our study achieved comprehensive characterization of salivary N-glycoproteome, and dysregulated site-specific glycoforms hold promise for noninvasive detection of lung cancer.

Separation of Serum and Plasma Proteins for In-Depth Proteomic Analysis

There are probably no biological samples that did more to spur interest in proteomics than serum and plasma. The belief was that comparing the proteomes of these samples obtained from healthy and disease-affected individuals would lead to biomarkers that could be used to diagnose conditions such as cancer. While the continuing development of mass spectrometers with greater sensitivity and resolution has been invaluable, the invention of strategic strategies to separate circulatory proteins has been just as critical. Novel and creative separation techniques were required because serum and plasma probably have the greatest dynamic range of protein concentration of any biological sample. The concentrations of circulating proteins can range over twelve orders of magnitude, making it a challenge to identify low-abundance proteins where the bulk of the useful biomarkers are believed to exist. The major goals of this article are to (i) provide an historical perspective on the rapid development of serum and plasma proteomics; (ii) describe various separation techniques that have made obtaining an in-depth view of the proteome of these biological samples possible; and (iii) describe applications where serum and plasma proteomics have been employed to discover potential biomarkers for pathological conditions.

A Fucosylated Glycopeptide as a Candidate Biomarker for Early Diagnosis of NASH Hepatocellular Carcinoma Using a Stepped HCD Method and PRM Evaluation

Aberrant specific N-glycosylation, especially the increase in fucosylation on specific peptide sites of serum proteins have been investigated as potential markers for diagnosis of nonalcoholic steatohepatitis (NASH)-related HCC. We have combined a workflow involving broad scale marker discovery in serum followed by targeted marker evaluation of these fucosylated glycopeptides. This workflow involved an LC-Stepped HCD-DDA-MS/MS method coupled with offline peptide fractionation for large-scale identification of N-glycopeptides directly from pooled serum samples (each n=10) as well as differential determination of N-glycosylation changes between disease states. We then evaluated the fucosylation level of the glycoprotein ceruloplasmin among 62 patient samples (35 cirrhosis, 27 early-stage NASH HCC) by LC-Stepped HCD-PRM-MS/MS to quantitatively analyze 18 targeted glycopeptides. Of these targets, we found the ratio of fucosylation of a tri-antennary glycopeptide from site N762, involving N762_ HexNAc(5)Hex(6)Fuc(2)NeuAc(3) (P=0.0486), increased significantly from cirrhosis to early HCC. This fucosylation ratio of a tri-antennary glycopeptide in CERU could be a potential biomarker for further validation in a larger sample set and could be a promising candidate for early detection of NASH HCC.

Calibr improves spectral library search for spectrum-centric analysis of data independent acquisition proteomics

Identifying peptides and proteins from mass spectrometry (MS) data, spectral library searching has emerged as a complementary approach to the conventional database searching. However, for the spectrum-centric analysis of data-independent acquisition (DIA) data, spectral library searching has not been widely exploited because existing spectral library search tools are mainly designed and optimized for the analysis of data-dependent acquisition (DDA) data. We present Calibr, a spectral library search tool for spectrum-centric DIA data analysis. Calibr optimizes spectrum preprocessing for pseudo MS2 spectra, generating an 8.11% increase in spectrum–spectrum match (SSM) number and a 7.49% increase in peptide number over the traditional preprocessing approach. When searching against the DDA-based spectral library, Calibr improves SSM number by 17.6–26.65% and peptide number by 18.45–37.31% over two state-of-the-art tools on three different data sets. Searching against the public spectral library from MassIVE, Calibr improves state-of-the-art tools in SSM and peptide numbers by more than 31.49% and 25.24%, respectively, for two data sets. Our analyses indicate higher sensitivity of Calibr results from the use of various spectral similarity measures and statistical scores, coupled with machine learning-based statistical validation for FDR control. Calibr executable files including a graphical user-interface application are available at https://ms.iis.sinica.edu.tw/COmics/Software_CalibrWizard.html and https://sourceforge.net/projects/comics-calibr.

Precision glycoproteomics reveals distinctive N-glycosylation in human spermatozoa

Spermatozoon represents a very special cell type in human body, and glycosylation plays essential roles in its whole life including spermatogenesis, maturation, capacitation, sperm–egg recognition, and fertilization. In this study, by mapping the most comprehensive N-glycoproteome of human spermatozoa using our recently developed site-specific glycoproteomic approaches, we show that spermatozoa contain a number of distinctive glycoproteins, which are mainly involved in spermatogenesis, acrosome reaction and sperm:oocyte membrane binding, and fertilization. Heavy fucosylation is observed on 14 glycoproteins mostly located at extracellular and cell surface regions in spermatozoa but not in other tissues. Sialylation and Lewis epitopes are enriched in the biological process of immune response in spermatozoa, while bisected core structures and LacdiNAc structures are highly expressed in acrosome. These data deepen our knowledge about glycosylation in spermatozoa and lay the foundation for functional study of glycosylation and glycan structures in male infertility.

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A precision site-specific glycoproteome is documented in human spermatozoa.

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Distinctive glycoproteins and heavy fucosylation are detected in spermatozoa.

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Sialylation and Lewis epitopes are related to immune response of spermatozoa.

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Bisected core structures and LacdiNAc are enriched on acrosome of spermatozoa.

Strategies for Proteome-Wide Quantification of Glycosylation Macro- and Micro-Heterogeneity

Protein glycosylation governs key physiological and pathological processes in human cells. Aberrant glycosylation is thus closely associated with disease progression. Mass spectrometry (MS)-based glycoproteomics has emerged as an indispensable tool for investigating glycosylation changes in biological samples with high sensitivity. Following rapid improvements in methodologies for reliable intact glycopeptide identification, site-specific quantification of glycopeptide macro- and micro-heterogeneity at the proteome scale has become an urgent need for exploring glycosylation regulations. Here, we summarize recent advances in N- and O-linked glycoproteomic quantification strategies and discuss their limitations. We further describe a strategy to propagate MS data for multilayered glycopeptide quantification, enabling a more comprehensive examination of global and site-specific glycosylation changes. Altogether, we show how quantitative glycoproteomics methods explore glycosylation regulation in human diseases and promote the discovery of biomarkers and therapeutic targets.

ZIC-cHILIC-Based StageTip for Simultaneous Glycopeptide Enrichment and Fractionation toward Large-Scale N-Sialoglycoproteomics

Alterations of protein glycosylation are closely related with pathophysiological regulation. Due to the structural macro- and microheterogeneity, low stoichiometry, and low ionization efficiency of glycopeptides, high-performance tools to enrich glycopeptides, especially the negatively charged and labile sialoglycopeptides, are essential to enhance the identification of the underexplored glycoproteome. Here, we present the first implementation of zwitterionic hydrophilic interaction chromatography with the exposed choline group (ZIC-cHILIC) in StageTip for simultaneous enrichment and fractionation of intact glycopeptides. In a model study using lung cancer cells, early elution by a high percentage of acetonitrile prominently prefilters nonglycopeptides, facilitating high enrichment specificity for glycopeptides (92-96%) and sialoglycopeptides (77-89%) in the subsequent hydrophilic fractions. The stepwise elution shows a high glycopeptide fractionation efficiency by a <10% overlap of glycopeptides between adjacent fractions. Most importantly, the ZIC-cHILIC stepwise strategy demonstrated good reproducibility (>80% in triplicate analysis) as well as superior coverage of 4.6- to 12.0-fold and 2.1- to 35.6-fold more glycopeptides and sialoglycopeptides compared to conventional TiO₂ and ZIC-HILIC, respectively. To the best of our knowledge, the result with 2742 sialoglycopeptides among 7367 unique glycopeptides and 166 glycans from 2434 N-glycosites of 1118 glycoproteins (Byonic score > 100) provides one of the deepest glycoproteomic profiles in single-cell type. Without the immunoprecipitation step, the large-scale glycoproteomic atlas also reveals site-specific glycosylation of many druggable receptor proteins, such as EGFR, MET, ERBB2, ERBB3, AXL, and IGF1R. The demonstrated high enrichment specificity and identification depth show that stepwise ZIC-cHILIC is an efficient method to explore the under-represented sialoglycoproteome.

GproDIA enables data-independent acquisition glycoproteomics with comprehensive statistical control

Large-scale profiling of intact glycopeptides is critical but challenging in glycoproteomics. Data independent acquisition (DIA) is an emerging technology with deep proteome coverage and accurate quantitative capability in proteomics studies, but is still in the early stage of development in the field of glycoproteomics. We propose GproDIA, a framework for the proteome-wide characterization of intact glycopeptides from DIA data with comprehensive statistical control by a 2-dimentional false discovery rate approach and a glycoform inference algorithm, enabling accurate identification of intact glycopeptides using wide isolation windows. We further utilize a semi-empirical spectrum prediction strategy to expand the coverage of spectral libraries of glycopeptides. We benchmark our method for N-glycopeptide profiling on DIA data of yeast and human serum samples, demonstrating that DIA with GproDIA outperforms the data-dependent acquisition-based methods for glycoproteomics in terms of capacity and data completeness of identification, as well as accuracy and precision of quantification. We expect that this work can provide a powerful tool for glycoproteomic studies.

Mucinomics as the Next Frontier of Mass Spectrometry

Mucin-domain glycoproteins comprise a class of proteins whose densely O-glycosylated mucin domains adopt a secondary structure with unique biophysical and biochemical properties. The canonical family of mucins is well-known to be involved in various diseases, especially cancer. Despite this, very little is known about the site-specific molecular structures and biological activities of mucins, in part because they are extremely challenging to study by mass spectrometry (MS). Here, we summarize recent advancements toward this goal, with a particular focus on mucin-domain glycoproteins as opposed to general O-glycoproteins. We summarize proteolytic digestion techniques, enrichment strategies, MS fragmentation, and intact analysis, as well as new bioinformatic platforms. In particular, we highlight mucin directed technologies such as mucin-selective proteases, tunable mucin platforms, and a mucinomics strategy to enrich mucin-domain glycoproteins from complex samples. Finally, we provide examples of targeted mucin-domain glycoproteomics that combine these techniques in comprehensive site-specific analyses of proteins. Overall, this Review summarizes the methods, challenges, and new opportunities associated with studying enigmatic mucin domains.

[Preparation of multi-functional magnetic nanoparticles for harvesting low-molecular-weight glycoproteins]

低分子量糖蛋白被认为是发现疾病生物标志物的宝库。特异性的萃取吸附剂对这一类化合物的萃取和富集是必不可少的。硼亲和材料在近年来取得了很大的发展,但专门用于选择性富集低分子量糖蛋白的硼亲和材料目前鲜有报道。该文提出了具有多种功能的磁性纳米颗粒(MNPs),用于低分子量糖蛋白的选择性捕获。该多功能磁性纳米颗粒是用硼酸功能化聚合物网络包裹的磁性纳米复合物。该多功能磁性纳米材料是利用磁性的纳米颗粒内核通过在其表面修饰苯硼酸功能团的聚丙烯酸高分子网络链制备得到。该材料不仅具有常规磁性材料在磁分离方面的基本优势,还能提供三重预先设计的先进功能:1)尺寸排阻效应,去除高分子量蛋白质的干扰;2)对低分子量糖蛋白的选择性萃取;3)保护捕获到的低分子量糖蛋白不被降解和污染。该材料的选择性萃取功能来自于硼酸配基与糖蛋白的顺式二醇部分的亲和性,而尺寸限制效应和保护功能则依赖于磁性纳米颗粒表面修饰的聚合物网络,允许低分子量化合物选择性通过。通过实验验证了这些预设的功能,且通过改变聚合物链长可以调节限径效应的阈值。这种多功能磁性纳米复合物可以进一步发展成有前景的纳米探针,不仅可以选择性捕获低分子量糖蛋白,还可以选择性捕获核苷和聚糖等其他具有重要生物学意义的顺式二醇分子。因此,该文报道的材料制备策略为从复杂样品中选择性萃取靶标化合物的多功能吸附剂的设计和合成提供了新思路。

Brilliant glycans and glycosylation: Seq and ye shall find

Proteoglycosylation is the addition of monosaccharides or glycans to the protein peptide chain. This is a common post-translational modification of proteins with a variety of biological functions. At present, more than half of all biopharmaceuticals in clinic are modified by glycosylation. Most glycoproteins are potential drug targets and biomarkers for disease diagnosis. Therefore, in-depth study of glycan structure of glycoproteins will ultimately improve the sensitivity and specificity of glycoproteins for clinical disease detection. With the deepening of research, the function and application value of glycans and glycosylation has gradually emerged. This review systematically introduces the latest research progress of glycans and glycosylation. It encompasses six cancers, four viruses, and their latest discoveries in Alzheimer's disease, allergic diseases, congenital diseases, gastrointestinal diseases, inflammation, and aging.

[Synthesis of zwitterionic dual-functional metal-organic framework nanocomposite with ultra-hydrophilicity for selective enrichment of glycopeptides]

蛋白糖基化是生物体中普遍发生且重要的生物学过程,其参与多种分子生物学的功能和途径,是临床诊断重要的生物标志物。但是,糖肽因其丰度低、离子化效率低、糖链异质性等难点,使糖蛋白分析一直面临巨大的挑战。因此,研究合成了一种新型的两性离子双功能化纳米金(AuGC)修饰的超亲水性沸石咪唑骨架(ZIF-8)纳米复合材料(AuGC/ZIF-8),并建立了亲水相互作用色谱(HILIC)和基质辅助激光解吸电离-飞行时间质谱(MALDI-TOF MS)联用选择性富集糖肽的分析方法。谷胱甘肽和半胱氨酸双功能化的协同作用,使MOF具有超亲水性和低空间位阻,为糖肽选择性富集提供了更多的亲和位点。研究以辣根过氧化物酶(HRP)为模式糖蛋白,通过AuGC/ZIF-8富集后,MALDI-TOF MS分析。结果表明,AuGC/ZIF-8对HRP糖肽的富集能力高达250 μg/mg,且在与牛血清白蛋白(BSA)混合溶液中(HRP-BSA (1∶200,质量比))显示出对HRP糖肽的高选择性,以及极低含量下(0.3 ng/μL)的高灵敏度。因此,在复杂生物样品糖蛋白的富集分离中具有很大的应用潜力。

High-Throughput Analyses of Glycans, Glycosites, and Intact Glycopeptides Using C4-and C18/MAX-Tips and Liquid Handling System

Protein glycosylation is one of the most common and diverse modifications. Aberrant protein glycosylation has been reported to associate with various diseases. High‐throughput and comprehensive characterization of glycoproteins is crucial for structural and functional studies of altered glycosylation in biological, physiological, and pathological processes. In this protocol, we detail a workflow for comprehensive analyses of intact glycopeptides (IGPs), glycosylation sites, and glycans from N‐linked glycoproteins. By utilizing liquid handling systems, our workflow could enrich IGPs in a high‐throughput manner while reducing sample processing time and human error involved in traditional proteomics sample processing techniques. Together, our workflow enables a high‐throughput enrichment of glycans, glycosites, and intact glycopeptides from complex biological or clinical samples. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC.

Basic Protocol 1: Enzymatic digestion of glycoproteins using C4‐tips

Basic Protocol 2: Intact glycopeptide analysis using C18/MAX‐tips

Basic Protocol 3: Glycan and glycosite analysis

An integrated strategy for the construction of a species-specific glycan library for mass spectrometry-based intact glycopeptide analyses

Mass spectrometry (MS)-based strategies and related software tools using glycan mass lists have greatly facilitated the analysis of intact glycopeptides. Most glycan mass lists are derived from normal glycans of mammals and contain limited monosaccharides, which has significantly hindered high throughput studies of unusual glycosylation events observed in other species. In this work, an integrated strategy was developed for the construction of a species-specific glycan mass list from glycan structure databases and published papers. We developed a computational tool called LibGlycan, which could process the different formats of glycans. Then, the software tool generated a glycan library that contained the monoisotope mass, average mass, isotope distribution, and glycan mass list for input into Byonic software. This strategy was applied to analyze the N-glycosylation of rice roots and O-glycosylation of Acinetobacter baumannii ATCC17978, leading to the identification of 296 and 145 intact glycopeptides respectively. Combined, these results show that this strategy is a robust computational approach for the determination of glycan diversity within different complex biological systems.

Integrating transcriptomics, proteomics, glycomics and glycoproteomics to characterize paclitaxel resistance in breast cancer cells

Chemoresistance is a major factor driving breast cancer (BC) relapse and the high rates of cancer-related deaths. Aberrant levels of glycans are closely correlated with chemoresistance. The essential functions of glycans in chemoresistance is not systematically studied. In this study, an integrated strategy with a combination of transcriptomics, proteomics, glycomics and glycoproteomics was applied to explore the dysregulation of glycogenes, glycan structures and glycoproteins in chemoresistance of breast cancer cells. In paclitaxel (PTX) resistant MCF7 cells, 19 differentially expressed N-glycan-related proteins were identified, of which MGAT4A was the most significantly down-regulated, consistent with decrease in MGAT4A expression at mRNA level in PTX treated BC cells. Glycomic analysis consistently revealed suppressed levels of multi-antennary branching structures using MALDI-TOF/TOF-MS and lectin microarray. Several target glycoproteins bearing suppressed levels of multi-antennary branching structures were identified, and ERK signaling pathway was strongly suppressed in PTX resistant MCF7 cells. Our findings demonstrated the aberrant levels of multi-antennary branching structures and their target glycoproteins on PTX resistance. Systematically integrative multi-omic analysis is expected to facilitate the discovery of the aberrant glycosyltransferases, N-glycosylation and glycoproteins in tumor progression and chemoresistance. SIGNIFICANCE: An integrated strategy with a combination of transcriptomics, proteomics, glycomics and glycoproteomics is crucial to understand the association between glycans and chemoresistance in BC. In this multi-omic analysis, we identified unique glycan-related protein, glycan and glycoprotein signatures defining PTX chemoresistance in BC. This study might provide valuable information to understand molecular mechanisms underlying chemoresistance in BC.

A Panel of Glycopeptides as Candidate Biomarkers for Early Diagnosis of NASH Hepatocellular Carcinoma Using a Stepped HCD Method and PRM Evaluation

Changes in N-glycosylation on specific peptide sites of serum proteins have been investigated as potential markers for diagnosis of nonalcoholic steatohepatitis (NASH)-related HCC. To accomplish this work, a novel workflow involving broad-scale marker discovery in serum followed by targeted marker evaluation of these glycopeptides were combined. The workflow involved an LC-Stepped HCD-DDA-MS/MS method coupled with offline peptide fractionation for large-scale identification of N-glycopeptides directly from pooled serum samples (each n = 10) as well as differential determination of N-glycosylation changes between disease states. We then evaluated several potentially diagnostic N-glycopeptides among 78 individual patient samples (40 cirrhosis, 28 early stage NASH HCC, and 10 late-stage NASH HCC) by LC-Stepped HCD-PRM-MS/MS to quantitatively analyze 65 targeted glycopeptides from 7 glycoproteins. Of these targets, we found site-specific N-glycopeptides n¹⁶⁹GSLFAFR_HexNAc(4)Hex(5)NeuAc(2) and n²⁴²ISDGFDGIPDNVDAALALPAHSYSGR_HexNAc(5)Hex(6)Fuc(1)NeuAc(3) from VTNC were significantly increased comparing samples from patients with NASH cirrhosis and NASH HCC (p < 0.05). When combining results of these 2 glycopeptides with AFP, the ROC curve analysis demonstrated the AUC value increased to 0.834 (95% CI, 0.748-0.921) and 0.847 (95% CI, 0.766-0.932), respectively, as compared to that of AFP alone (AUC = 0.791, 95% CI, 0.690-0.892). These 2 glycopeptides may serve as potential biomarkers for early HCC diagnosis in patients with NASH related cirrhosis.

Gold nanoparticle-glutathione functionalized MOFs as hydrophilic materials for the selective enrichment of glycopeptides

Herein, a novel zwitterionic hydrophilic metal-organic framework (MOF)-functionalized material was synthesized through grafting l-glutathione (GSH) onto the Au which acts as the intermediate layer to modify the base material (PEI-ZIF-8) by the sulfhydryl group provided by GSH and the affinity provided by Au (denoted as PEI-ZIF-8@Au@GSH). The obtained product was employed to capture glycopeptides. Benefit from its excellent hydrophilic properties, abundant amphoteric ions, and unique large specific surface area, this material demonstrated amazing ability in the enrichment and identification of glycopeptides. As a result, the PEI-ZIF-8@Au@GSH displayed high sensitivity (as low as 2 fmol), excellent binding capacity (500 mg/g), outstanding enrichment selectivity (maximum mass ratio HRP to BSA is 1:1000) toward glycopeptides, and the ability to recycle at least five times. Furthermore, 35 and 51 glycopeptides were successfully detected from 5 μL human saliva and human serum respectively in the examination of the actual sample by MALDI-TOF MS. The above results indicated that the PEI-ZIF-8@Au@GSH had a satisfactory potential in the field of glycoproteomics.

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

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

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.

A Pragmatic Guide to Enrichment Strategies for Mass Spectrometry-Based Glycoproteomics

Glycosylation is a prevalent, yet heterogeneous modification with a broad range of implications in molecular biology. This heterogeneity precludes enrichment strategies that can be universally beneficial for all glycan classes. Thus, choice of enrichment strategy has profound implications on experimental outcomes. Here we review common enrichment strategies used in modern mass spectrometry-based glycoproteomic experiments, including lectins and other affinity chromatographies, hydrophilic interaction chromatography and its derivatives, porous graphitic carbon, reversible and irreversible chemical coupling strategies, and chemical biology tools that often leverage bioorthogonal handles. Interest in glycoproteomics continues to surge as mass spectrometry instrumentation and software improve, so this review aims to help equip researchers with the necessary information to choose appropriate enrichment strategies that best complement these efforts.

Integrated Glycoproteomics Identifies a Role of N-Glycosylation and Galectin-1 on Myogenesis and Muscle Development

Many cell surface and secreted proteins are modified by the covalent addition of glycans that play an important role in the development of multicellular organisms. These glycan modifications enable communication between cells and the extracellular matrix via interactions with specific glycan-binding lectins and the regulation of receptor-mediated signaling. Aberrant protein glycosylation has been associated with the development of several muscular diseases, suggesting essential glycan- and lectin-mediated functions in myogenesis and muscle development, but our molecular understanding of the precise glycans, catalytic enzymes, and lectins involved remains only partially understood. Here, we quantified dynamic remodeling of the membrane-associated proteome during a time-course of myogenesis in cell culture. We observed wide-spread changes in the abundance of several important lectins and enzymes facilitating glycan biosynthesis. Glycomics-based quantification of released N-linked glycans confirmed remodeling of the glycome consistent with the regulation of glycosyltransferases and glycosidases responsible for their formation including a previously unknown digalactose-to-sialic acid switch supporting a functional role of these glycoepitopes in myogenesis. Furthermore, dynamic quantitative glycoproteomic analysis with multiplexed stable isotope labeling and analysis of enriched glycopeptides with multiple fragmentation approaches identified glycoproteins modified by these regulated glycans including several integrins and growth factor receptors. Myogenesis was also associated with the regulation of several lectins, most notably the upregulation of galectin-1 (LGALS1). CRISPR/Cas9-mediated deletion of Lgals1 inhibited differentiation and myotube formation, suggesting an early functional role of galectin-1 in the myogenic program. Importantly, similar changes in N-glycosylation and the upregulation of galectin-1 during postnatal skeletal muscle development were observed in mice. Treatment of new-born mice with recombinant adeno-associated viruses to overexpress galectin-1 in the musculature resulted in enhanced muscle mass. Our data form a valuable resource to further understand the glycobiology of myogenesis and will aid the development of intervention strategies to promote healthy muscle development or regeneration.

Glycoproteomics: growing up fast

Glycoproteomics is a rapidly growing field which seeks to identify and characterise glycosylation events at a proteome scale. Over the last few years considerable effort has been made in developing new technologies, enrichment systems, and analysis strategies to enhance the quality of glycoproteomic studies. Within this review we discuss the recent developments in glycoproteomics and the current state of the art approaches for analysing glycosylated substrates. We highlight key improvements in mass spectrometry instrumentation coupled with the advancements in enrichment approaches for key classes of glycosylation including mucin-O-glycosylation, O-GlcNAc glycosylation and N-linked glycosylation which now allow the identification/quantification of hundreds to thousands of glycosylation sites within individual experiments. Finally, we summarise the emerging trends within glycoproteomics to illustrate how the field is moving away from studies simply focused on identifying glycosylated substrates to studying specific mechanisms and disease states.