Glycans, Glycosite, and Intact Glycopeptide Analysis of N-Linked Glycoproteins Using Liquid Handling Systems

Hydrophilic Interaction Chromatography Coupled to Ultraviolet Photodissociation Affords Identification, Localization, and Relative Quantitation of Glycans on Intact Glycoproteins

Protein glycosylation is implicated in a wide array of diseases, yet glycoprotein analysis remains elusive owing to the extreme heterogeneity of glycans, including microheterogeneity of some of the glycosites (amino acid residues). Various mass spectrometry (MS) strategies have proven tremendously successful for localizing and identifying glycans, typically utilizing a bottom-up workflow in which glycoproteins are digested to create glycopeptides to facilitate analysis. An emerging alternative is top-down MS that aims to characterize intact glycoproteins to allow precise identification and localization of glycans. The most comprehensive characterization of intact glycoproteins requires integration of a suitable separation method and high performance tandem mass spectrometry to provide both protein sequence information and glycosite localization. Here, we couple ultraviolet photodissociation and hydrophilic interaction chromatography with high resolution mass spectrometry to advance the characterization of intact glycoproteins ranging from 15 to 34 kDa, offering site localization of glycans, providing sequence coverages up to 93%, and affording relative quantitation of individual glycoforms.

Uncovering missing glycans and unexpected fragments with pGlycoNovo for site-specific glycosylation analysis across species

Precision mapping of site-specific glycans using mass spectrometry is vital in glycoproteomics. However, the diversity of glycan compositions across species often exceeds database capacity, hindering the identification of rare glycans. Here, we introduce pGlycoNovo, a software within the pGlyco3 software environment, which employs a glycan first-based full-range Y-ion dynamic searching strategy. pGlycoNovo enables de novo identification of intact glycopeptides with rare glycans by considering all possible monosaccharide combinations, expanding the glycan search space to 16~1000 times compared to non-open search methods, while maintaining accuracy, sensitivity and speed. Reanalysis of SARS Covid-2 spike protein glycosylation data revealed 230 additional site-specific N-glycans and 30 previously unreported O-glycans. pGlycoNovo demonstrated high complementarity to six other tools and superior search speed. It enables characterization of site-specific N-glycosylation across five evolutionarily distant species, contributing to a dataset of 32,549 site-specific glycans on 4602 proteins, including 2409 site-specific rare glycans, and uncovering unexpected glycan fragments.

A Fully Automated Online Enrichment and Separation System for Highly Reproducible and In-Depth Analysis of Intact Glycopeptide

A fully automated online enrichment and separation system for intact glycopeptides, named AutoGP, was developed in this study by integrating three different columns in a nano-LC system. Specifically, the peptide mixture from the enzymatic digestion of a complex biological sample was first loaded on a hydrophilic interaction chromatography (HILIC) column. The nonglycopeptides in the sample were washed off the column, and the glycopeptides retained by the HILIC column were eluted to a C18 trap column to achieve an automated glycopeptide enrichment. The enriched glycopeptides were further eluted to a C18 column for separation, and the separated glycopeptides were eventually analyzed by using an orbitrap mass spectrometer (MS). The optimal operating conditions for AutoGP were systemically studied, and the performance of the fully optimized AutoGP was compared with a conventional manual system used for glycopeptide analysis. The experimental evaluation shows that the total number of glycopeptides identified is at least 1.5-fold higher, and the median coefficient of variation for the analyses is at least 50% lower by using AutoGP, as compared to the results acquired by using the manual system. In addition, AutoGP can perform effective analysis even with a 1-μg sample amount, while a 10-μg sample at least will be needed by the manual system, implying an order of magnitude better sensitivity of AutoGP. All the experimental results have consistently proven that AutoGP can be used for much better characterization of intact glycopeptides.

Recent progress in mass spectrometry-based urinary proteomics

Serum or plasma is frequently utilized in biomedical research; however, its application is impeded by the requirement for invasive sample collection. The non-invasive nature of urine collection makes it an attractive alternative for disease characterization and biomarker discovery. Mass spectrometry-based protein profiling of urine has led to the discovery of several disease-associated biomarkers. Proteomic analysis of urine has not only been applied to disorders of the kidney and urinary bladder but also to conditions affecting distant organs because proteins excreted in the urine originate from multiple organs. This review provides a progress update on urinary proteomics carried out over the past decade. Studies summarized in this review have expanded the catalog of proteins detected in the urine in a variety of clinical conditions. The wide range of applications of urine analysis-from characterizing diseases to discovering predictive, diagnostic and prognostic markers-continues to drive investigations of the urinary proteome.

Identification and characterization of intact glycopeptides in human urine

Glycoproteins in urine have the potential to provide a rich class of informative molecules for studying human health and disease. Despite this promise, the urine glycoproteome has been largely uncharacterized. Here, we present the analysis of glycoproteins in human urine using LC-MS/MS-based intact glycopeptide analysis, providing both the identification of protein glycosites and characterization of the glycan composition at specific glycosites. Gene enrichment analysis reveals differences in biological processes, cellular components, and molecular functions in the urine glycoproteome versus the urine proteome, as well as differences based on the major glycan class observed on proteins. Meta-heterogeneity of glycosylation is examined on proteins to determine the variation in glycosylation across multiple sites of a given protein with specific examples of individual sites differing from the glycosylation trends in the overall protein. Taken together, this dataset represents a potentially valuable resource as a baseline characterization of glycoproteins in human urine for future urine glycoproteomics studies.

Plasma/Serum Proteomics based on Mass Spectrometry

Human blood is a window of physiology and disease. Examination of biomarkers in blood is a common clinical procedure, which can be informative in diagnosis and prognosis of diseases, and in evaluating treatment effectiveness. There is still a huge demand on new blood biomarkers and assays for precision medicine nowadays, therefore plasma/serum proteomics has attracted increasing attention in recent years. How to effectively proceed with the biomarker discovery and clinical diagnostic assay development is a question raised to researchers who are interested in this area. In this review, we comprehensively introduce the background and advancement of technologies for blood proteomics, with a focus on mass spectrometry (MS). Analyzing existing blood biomarkers and newly-built diagnostic assays based on MS can shed light on developing new biomarkers and analytical methods. We summarize various protein analytes in plasma/serum which include total proteome, protein post-translational modifications, and extracellular vesicles, focusing on their corresponding sample preparation methods for MS analysis. We propose screening multiple protein analytes in the same set of blood samples in order to increase success rate for biomarker discovery. We also review the trends of MS techniques for blood tests including sample preparation automation, and further provide our perspectives on their future directions.

High-resolution mass spectrometry for glycoproteomics

Tweetable abstract Bottom-up glycoproteomics combined with top-down strategy allows direct analysis of glycoform-mapped glycosylation and its glycans by high-resolution mass spectrometry.

Protein glycosylation in urine as a biomarker of diseases

Human body fluids have become an indispensable resource for clinical research, diagnosis and prognosis. Urine is widely used to discover disease-specific glycoprotein biomarkers because of its recurrently non-invasive collection and disease-indicating properties. While urine is an unstable fluid in that its composition changes with ingested nutrients and further as it is excreted through micturition, urinary proteins are more stable and their abnormal glycosylation is associated with diseases. It is known that aberrant glycosylation can define tumor malignancy and indicate disease initiation and progression. However, a thorough and translational survey of urinary glycosylation in diseases has not been performed. In this article, we evaluate the clinical applications of urine, introduce methods for urine glycosylation analysis, and discuss urine glycoprotein biomarkers. We emphasize the importance of mining urinary glycoproteins and searching for disease-specific glycosylation in various diseases (including cancer, neurodegenerative diseases, diabetes, and viral infections). With advances in mass spectrometry-based glycomics/glycoproteomics/glycopeptidomics, characterization of disease-specific glycosylation will optimistically lead to the discovery of disease-related urinary biomarkers with better sensitivity and specificity in the near future.

MS-based glycomics and glycoproteomics methods enabling isomeric characterization

Glycosylation is one of the most significant and abundant posttranslational modifications in mammalian cells. It mediates a wide range of biofunctions, including cell adhesion, cell communication, immune cell trafficking, and protein stability. Also, aberrant glycosylation has been associated with various diseases such as diabetes, Alzheimer's disease, inflammation, immune deficiencies, congenital disorders, and cancers. The alterations in the distributions of glycan and glycopeptide isomers are involved in the development and progression of several human diseases. However, the microheterogeneity of glycosylation brings a great challenge to glycomic and glycoproteomic analysis, including the characterization of isomers. Over several decades, different methods and approaches have been developed to facilitate the characterization of glycan and glycopeptide isomers. Mass spectrometry (MS) has been a powerful tool utilized for glycomic and glycoproteomic isomeric analysis due to its high sensitivity and rich structural information using different fragmentation techniques. However, a comprehensive characterization of glycan and glycopeptide isomers remains a challenge when utilizing MS alone. Therefore, various separation methods, including liquid chromatography, capillary electrophoresis, and ion mobility, were developed to resolve glycan and glycopeptide isomers before MS. These separation techniques were coupled to MS for a better identification and quantitation of glycan and glycopeptide isomers. Additionally, bioinformatic tools are essential for the automated processing of glycan and glycopeptide isomeric data to facilitate isomeric studies in biological cohorts. Here in this review, we discuss commonly employed MS-based techniques, separation hyphenated MS methods, and software, facilitating the separation, identification, and quantitation of glycan and glycopeptide isomers.

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.

Developing quantitative assays for six urinary glycoproteins using parallel reaction monitoring, data-independent acquisition, and TMT-based data-dependent acquisition

Quantitative approaches encompassing parallel reaction monitoring (PRM), data-independent acquisition (DIA), and data-dependent acquisition (DDA) are commonly used to investigate protein expression profiles. However, analytical performances of assays developed using PRM, DIA, and Tandem Mass Tag (TMT)-based DDA for quantitative proteomics have yet not been investigated. Here, we developed assays for glycopeptides identified from six glycoproteins, including Leucine-rich alpha-2-glycoprotein (LRG1), Prostaglandin-H2 D-isomerase (PTGDS), Aminopeptidase N (ANPEP), CD63 antigen (CD63), Clusterin (CLU), and Prostatic acid phosphatase (ACPP), using PRM, DDA, and DIA and evaluated the analytical performances of each assay using the different acquisition modes. We also compared assays in each acquisition mode on three different orbitrap instruments: Thermo Fisher Q Exactive, Exploris 480, and Lumos. We found that DIA showed the largest linear range, highest sensitivity, and most reproducibility. We then applied our developed DIA assays to urine samples from non-aggressive (n = 48) and aggressive (n = 35) prostate cancer patients. In conclusion, we developed assays for the six glycoproteins, evaluated the analytical performances of each assay in DIA, PRM, and PRM acquisition modes on three types of mass spectrometry instruments, and chose the DIA assays for the quantitative analysis of urine samples from patients with aggressive and non-aggressive prostate cancer.

Differentially expressed glycoproteins in pre- and post-digital rectal examination urine samples for detecting aggressive prostate cancer

Urinary glycoproteins associated with aggressive prostate cancer (AG-PCa) were previously reported using post-digital rectal examination (DRE) urine specimens. To explore the potential of using pre-DRE urine specimens for detecting AG-PCa, we compared glycoproteins between pre- and post-DRE urine specimens, verified the previously identified post-DRE AG-PCa-associated urinary glycoproteins in pre-DRE urine specimens, and explored potential new glycoproteins for AG-PCa detection in pre-DRE urine specimens. Quantitative glycoproteomic data were acquired for 154 pre-DRE urine specimens from 41 patients with no cancer at biopsy, 48 patients with non-AG-PCa (Gleason score = 6), and 65 patients with AG-PCa (Gleason score 7 or above). Compared to glycopeptides from the post-DRE urine data, humoral immunity-related proteins were enriched in pre-DRE urine samples, whereas cell mediated immune response proteins were enriched in post-DRE urine samples. Analyses of AG-PCa-associated glycoproteins from pre-DRE urine revealed that the three urinary glycoproteins, prostate-specific antigen (PSA), prostatic acid phosphatase (ACPP), and CD97 antigen (CD97) that were previously identified in post-DRE urine samples, were also observed as AG-PCa associated glycoproteins in pre-DRE urine. In addition, we identified three new glycoproteins, fibrillin 1 (FBN1), vitronectin (VTN), and hemicentin 2 (HMCN2), to be potentially associated with AG-PCa in pre-DRE urine specimens. In summary, glycoprotein profiles differ between pre- and post-DRE urine specimens. The identified AG-PCa-associated glycoproteins may be further evaluated in large cohort of pre-DRE urine specimens for detecting clinically significant PCa.

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.

MS-based glycomics: An analytical tool to assess nervous system diseases

Neurological diseases affect millions of peopleochemistryorldwide and are continuously increasing due to the globe's aging population. Such diseases affect the nervous system and are characterized by a progressive decline in brain function and progressive cognitive impairment, decreasing the quality of life for those with the disease as well as for their families and loved ones. The increased burden of nervous system diseases demands a deeper insight into the biomolecular mechanisms at work during disease development in order to improve clinical diagnosis and drug design. Recently, evidence has related glycosylation to nervous system diseases. Glycosylation is a vital post-translational modification that mediates many biological functions, and aberrant glycosylation has been associated with a variety of diseases. Thus, the investigation of glycosylation in neurological diseases could provide novel biomarkers and information for disease pathology. During the last decades, many techniques have been developed for facilitation of reliable and efficient glycomic analysis. Among these, mass spectrometry (MS) is considered the most powerful tool for glycan analysis due to its high resolution, high sensitivity, and the ability to acquire adequate structural information for glycan identification. Along with MS, a variety of approaches and strategies are employed to enhance the MS-based identification and quantitation of glycans in neurological samples. Here, we review the advanced glycomic tools used in nervous system disease studies, including separation techniques prior to MS, fragmentation techniques in MS, and corresponding strategies. The glycan markers in common clinical nervous system diseases discovered by utilizing such MS-based glycomic tools are also summarized and discussed.

Urinary marker panels for aggressive prostate cancer detection

Majority of patients with indolent prostate cancer (PCa) can be managed with active surveillance. Therefore, finding biomarkers for classifying patients between indolent and aggressive PCa is essential. In this study, we investigated urinary marker panels composed of urinary glycopeptides and/or urinary prostate-specific antigen (PSA) for their clinical utility in distinguishing non-aggressive (Grade Group 1) from aggressive (Grade Group ≥ 2) PCa. Urinary glycopeptides acquired via data-independent acquisition mass spectrometry (DIA-MS) were quantitatively analyzed, where prostatic acid phosphatase (ACPP), clusterin (CLU), alpha-1-acid glycoprotein 1 (ORM1), and CD antigen 97 (CD97) were selected to be evaluated in various combinations with and without urinary PSA. Targeted parallel reaction monitoring (PRM) assays of the glycopeptides from urinary ACPP and CLU were investigated along with urinary PSA for the ability of aggressive PCa detection. The multi-urinary marker panels, combined via logistic regression, were statistically evaluated using bootstrap resampling and validated by an independent cohort. Majority of the multi-urinary marker panels (e.g., a panel consisted of ACPP, CLU, and Urinary PSA) achieved area under the curve (AUC) ranged from 0.70 to 0.85. Thus, multi-marker panels investigated in this study showed clinically meaningful results on aggressive PCa detection to separate Grade Group 1 from Grade Group 2 and above warranting further evaluation in clinical setting in future.

Multi-analyte High-Throughput Microplate-SERS Reader with Controllable Liquid Interfacial Arrays

High-throughput surface-enhanced Raman scattering (SERS) reader, especially for liquid sample testing, is of great significance and huge demand in biology, environment, and other analytical fields. Inspired by the principle of microplate reader, herein, we developed a microplate-SERS reader for semiautomatic and high-throughput assays by virtue of three-dimensional liquid interfacial arrays (LIAs). For the first time, the formation of LIA in oil-in-water state, water-in-oil state, and two-dimensional plane state is realized by operating the hydrophilicity (contact angle) of the container. Through the force analysis of LIA, the effect of organic (O) phase density on the relative position of LIA was quantified. In addition, the optimized reader offers fast and continuous semiautomatic detection of 12 samples below 10 min with great signal reproducibility (calibration with the characteristic peak of O phase as the internal standard). The isolated wells in the microplate prevent analyte cross talk, allowing accurate quantification of each sample. Multiplex analysis capability highlights that this reader has the ability of rapid identification and quantification of samples containing various analytes and concentrations. The results demonstrate high-resolution dual and triple analyte detection with fully preserved signal and Raman features of individual analytes in a mixture, which implies that it also has excellent anticounterfeiting applications. This microplate-SERS reader combines the superior advantages of the LIA, microplate, and SERS techniques to retrieve the molecular vibrational fingerprints of various chemicals in complex media.

Measuring change in glycoprotein structure

Biosynthetic enzymes in the secretory pathway create distributions of glycans at each glycosite that elaborate the biophysical properties and biological functions of glycoproteins. Because the biosynthetic glycosylation reactions do not go to completion, each protein glycosite is heterogeneous with respect to glycosylation. This heterogeneity means that it is not sufficient to measure protein abundance in omics experiments. Rather, it is necessary to sample the distribution of glycosylation at each glycosite to quantify the changes that occur during biological processes. On the one hand, the use of data-dependent acquisition methods to sample glycopeptides is limited by the instrument duty cycle and the missing value problem. On the other, stepped window data-independent acquisition samples all precursors, but ion abundances are limited by duty cycle. Therefore, the ability to quantify accurately the flux in glycoprotein glycosylation that occurs during biological processes requires the exploitation of emerging mass spectrometry technologies capable of deep, comprehensive sampling and selective high confidence assignment of the complex glycopeptide mixtures. This review summarizes recent technical advances and mass spectral glycoproteomics analysis strategies and how these developments impact our ability to quantify the changes in glycosylation that occur during biological processes. We highlight specific improvements to glycopeptide characterization through activated electron dissociation, ion mobility trends and instrumentation, and efficient algorithmic approaches for glycopeptide assignment. We also discuss the emerging need for unified standards to enable interlaboratory collaborations and effective monitoring of structural changes in glycoproteins.

Comparing Urinary Glycoproteins among Three Urogenital Cancers and Identifying Prostate Cancer-Specific Glycoproteins

Prostate cancer, bladder cancer, and renal cancers are major urogenital cancers. Of which, prostate cancer is the most commonly diagnosed and second leading cause of cancer death for men in the United States. For urogenital cancers, urine is considered as proximate body fluid to the tumor site for developing non-invasiveness tests. However, the specific molecular signatures from different urogenital cancers are needed to relate changes in urine to various cancer detections. Herein, we utilized a previously published C4-Tip and C18/MAX-Tip workflow for enrichment of glycopeptides from urine samples and evaluated urinary glycopeptides for its cancer specificity. We analyzed 66 urine samples from bladder cancer (n = 27), prostate cancer (n = 4), clear cell renal cell carcinoma (ccRCC, n = 3), and benign plastic hyperplasia (BPH, n = 32) and then compared them with a previous publication that reported glycopeptides associated with aggressive prostate cancer (Gleason score ≥ 8). We further demonstrated the cancer specificity of the glycopeptides associated with aggressive prostate cancer. In this study, a total of 33 glycopeptides were identified to be specifically differentially expressed in prostate cancer compared to other urogenital cancer types as well as BPH urines. By cross-comparison with our previous urinary glycoproteomic dataset for aggressive prostate cancer, we reported a total of four glycopeptides from glycoproteins DSC2, MGAM, PIK3IP1, and CD55, commonly identified to be prostate cancer-specific. Together, these results deepen our understanding of the urinary glycoproteins associated with urogenital cancer types and expand our knowledge of the cancer specificity of urinary glycoproteins among urogenital cancer progression.

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.

A fully integrated sample preparation strategy for highly sensitive intact glycoproteomics

A fully integrated sample preparation technology, termed Intact GlycoSISPROT, was developed for the highly sensitive analysis of site-specific glycopeptides. Through integrating all glycoproteomic sample preparation steps into a single spintip, Intact GlycoSISPROT provided a tool for site-specific glycosylation analysis with low micrograms to even nanograms of protein sample.

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.

Data-Independent Acquisition-Based Mass Spectrometry (DIA-MS) for Quantitative Analysis of Intact N-Linked Glycopeptides

N-linked protein glycosylation is a key regulator in various biological functions. Previous studies have shown that aberrant glycosylation is associated with many diseases. Therefore, it is essential to elucidate protein modifications of glycosylation by quantitatively profiling intact N-linked glycopeptides. Data-independent acquisition (DIA) mass spectrometry (MS) is a cost-effective, flexible, and high-throughput method for global proteomics. However, substantial challenges are still present in the quantitative analysis of intact glycopeptides with high accuracy at high throughput. In this study, we have established a novel integrated platform for the DIA analysis of intact glycopeptides isolated from complex samples. The established analysis platform utilizes a well-designed DIA-MS method for raw data collection, a spectral library constructed specifically for intact glycopeptide quantification providing accurate results by the inclusion of Y ions for quantification and filtering of quantified intact glycopeptides with low-quality MS2 spectra automatically using a set of criteria. Intact glycopeptides isolated from human serum were used to evaluate the performance of the integrated platform. By utilizing 100 isolation windows for DIA data acquisition, a well-constructed human serum spectral library containing 1123 nonredundant intact glycopeptides with Y ions, and automated data inspection, 620 intact glycopeptides were quantified with high confidence from DIA-MS. In summary, our integrated platform can serve as a reliable quantitative tool for characterizing intact glycopeptides isolated from complex biological samples to assist our understanding of biological functions of N-linked glycosylation.

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

Development of Parallel Reaction Monitoring Assays for the Detection of Aggressive Prostate Cancer Using Urinary Glycoproteins

Recently, we have found that two urinary glycoproteins, prostatic acid phosphatase (ACPP) and clusterin (CLU), combined with serum prostate-specific antigen (PSA) can serve as a three-signature panel for detecting aggressive prostate cancer (PCa) based on a quantitative glycoproteomic study. To facilitate the translation of candidates into clinically applicable tests, robust and accurate targeted parallel reaction monitoring (PRM) assays that can be widely adopted in multiple labs were developed in this study. The developed PRM assays for the urinary glycopeptides, FLN*ESYK from ACPP and EDALN*ETR from CLU, demonstrated good repeatability and a sufficient working range covering three to four orders of magnitude, and their performance in differentiating aggressive PCa was assessed by the quantitative analysis of urine specimens collected from 69 nonaggressive (Gleason score = 6) and 73 aggressive (Gleason ≥ 8) PCa patients. When ACPP combined with CLU, the discrimination power was improved from an area under a curve (AUC) of 0.66 to 0.78. By combining ACPP, CLU, and serum PSA to form a three-signature panel, the AUC was further improved to 0.83 (sensitivity: 84.9%, specificity: 66.7%). Since the serum PSA test alone had an AUC of 0.68, our results demonstrated that the new urinary glycopeptide PRM assays can serve as an adjunct to the serum PSA test to achieve better predictive power toward aggressive PCa. In summary, our developed PRM assays for urinary glycopeptides were successfully applied to clinical PCa urine samples with a promising performance in aggressive PCa detection.

Mass Spectrometry-Based Glycoproteomics and Prostate Cancer

Aberrant glycosylation has long been known to be associated with cancer, since it is involved in key mechanisms such as tumour onset, development and progression. This review will focus on protein glycosylation studies in cells, tissue, urine and serum in the context of prostate cancer. A dedicated section will cover the glycoforms of prostate specific antigen, the molecule that, despite some important limitations, is routinely tested for helping prostate cancer diagnosis. Our aim is to provide readers with an overview of mass spectrometry-based glycoproteomics of prostate cancer. From this perspective, the first part of this review will illustrate the main strategies for glycopeptide enrichment and mass spectrometric analysis. The molecular information obtained by glycoproteomic analysis performed by mass spectrometry has led to new insights into the mechanism linking aberrant glycosylation to cancer cell proliferation, migration and immunoescape.

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.

Serum and Plasma Immunoglobulin G Fc N-Glycosylation Is Stable during Storage

Immunoglobulin G (IgG) glycosylation is studied in biological samples to develop clinical markers for precision medicine, for example, in autoimmune diseases and oncology. Inappropriate storage of proteins, lipids, or metabolites can lead to degradation or modification of biomolecular features, which can have a strong negative impact on accuracy and precision of clinical omics studies. Regarding the preservation of IgG glycosylation, the range of appropriate storage conditions and time frame is understudied. Therefore, we investigated the effect of storage on IgG Fc N-glycosylation in the commonly analyzed biofluids, serum and plasma. Short-term storage and accelerated storage stability were tested by incubating samples from three healthy donors under stress conditions of up to 50 °C for 2 weeks using −80 °C for 2 weeks as the reference condition. All tested IgG glycosylation features—sialylation, galactosylation, bisection, and fucosylation—remained unchanged up to room temperature as well as during multiple freeze–thaw cycles and exposure to light. Only when subjected to 37 °C or 50 °C for 2 weeks, galactosylation and sialylation subtly changed. Therefore, clinical IgG glycosylation analysis does not rely as heavily on mild serum and plasma storage conditions and timely analysis as many other omics analyses.

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.

Urinary glycoproteins associated with aggressive prostate cancer

Background: There is an urgent need for the detection of aggressive prostate cancer. Glycoproteins play essential roles in cancer development, while urine is a noninvasive and easily obtainable biological fluid that contains secretory glycoproteins from the urogenital system. Therefore, here we aimed to identify urinary glycoproteins that are capable of differentiating aggressive from non-aggressive prostate cancer.

Methods: Quantitative mass spectrometry data of glycopeptides from a discovery cohort comprised of 74 aggressive (Gleason score ≥8) and 68 non-aggressive (Gleason score = 6) prostate cancer urine specimens were acquired via a data independent acquisition approach. The glycopeptides showing distinct expression profiles in aggressive relative to non-aggressive prostate cancer were further evaluated for their performance in distinguishing the two groups either individually or in combination with others using repeated 5-fold cross validation with logistic regression to build predictive models. Predictive models showing good performance from the discovery cohort were further evaluated using a validation cohort.

Results: Among the 20 candidate glycoproteins, urinary ACPP outperformed the other candidates. Urinary ACPP can also serve as an adjunct to serum PSA to further improve the discrimination power for aggressive prostate cancer (AUC= 0.82, 95% confidence interval 0.75 to 0.89). A three-signature panel including urinary ACPP, urinary CLU, and serum PSA displayed the ability to distinguish aggressive prostate cancer from non-aggressive prostate cancer with an AUC of 0.86 (95% confidence interval 0.8 to 0.92). Another three-signature panel containing urinary ACPP, urinary LOX, and serum PSA also demonstrated its ability in recognizing aggressive prostate cancer (AUC=0.82, 95% confidence interval 0.75 to 0.9). Moreover, consistent performance was observed from each panel when evaluated using a validation cohort.

Conclusion: We have identified glycopeptides of urinary glycoproteins associated with aggressive prostate cancer using a quantitative mass spectrometry-based glycoproteomic approach and demonstrated their potential to serve as noninvasive urinary glycoprotein biomarkers worthy of further validation by a multi-center study.