Mass spectrometry based glycoproteomics--from a proteomics perspective

Integration of proteomics in the molecular tumor board

Cancer remains one of the most complex and challenging diseases in mankind. To address the need for a personalized treatment approach for particularly complex tumor cases, molecular tumor boards (MTBs) have been initiated. MTBs are interdisciplinary teams that perform in-depth molecular diagnostics to cooperatively and interdisciplinarily advise on the best therapeutic strategy. Current molecular diagnostics are routinely performed on the transcriptomic and genomic levels, aiming to identify tumor-driving mutations. However, these approaches can only partially capture the actual phenotype and the molecular key players of tumor growth and progression. Thus, direct investigation of the expressed proteins and activated signaling pathways provide valuable complementary information on the tumor-driving molecular characteristics of the tissue. Technological advancements in mass spectrometry-based proteomics enable the robust, rapid, and sensitive detection of thousands of proteins in minimal sample amounts, paving the way for clinical proteomics and the probing of oncogenic signaling activity. Therefore, proteomics is currently being integrated into molecular diagnostics within MTBs and holds promising potential in aiding tumor classification and identifying personalized treatment strategies. This review introduces MTBs and describes current clinical proteomics, its potential in precision oncology, and highlights the benefits of multi-omic data integration.

Analysis of N- and O-linked site-specific glycosylation by ion mobility mass spectrometry: State of the art and future directions

Glycosylation, the major post-translational modification of proteins, significantly increases the diversity of proteoforms. Glycans are involved in a variety of pivotal structural and functional roles of proteins, and changes in glycosylation are profoundly connected to the progression of numerous diseases. Mass spectrometry (MS) has emerged as the gold standard for glycan and glycopeptide analysis because of its high sensitivity and the wealth of fragmentation information that can be obtained. Various separation techniques have been employed to resolve glycan and glycopeptide isomers at the front end of the MS. However, differentiating structures of isobaric and isomeric glycopeptides constitutes a challenge in MS-based characterization. Many reports described the use of various ion mobility-mass spectrometry (IM-MS) techniques for glycomic analyses. Nevertheless, very few studies have focused on N- and O-linked site-specific glycopeptidomic analysis. Unlike glycomics, glycoproteomics presents a multitude of inherent challenges in microheterogeneity, which are further exacerbated by the lack of dedicated bioinformatics tools. In this review, we cover recent advances made towards the growing field of site-specific glycosylation analysis using IM-MS with a specific emphasis on the MS techniques and capabilities in resolving isomeric peptidoglycan structures. Furthermore, we discuss commonly used software that supports IM-MS data analysis of glycopeptides.

Triplex glycan quantification by metabolic labeling with isotopically labeled glucose in yeast

Mass spectrometry-based approaches encompass a powerful collection of tools for the analysis biological molecules, including glycans and glycoconjugates. Unlike most traditional bioanalytical methods focusing on these molecules, mass spectrometry is especially suited for multiplexing, by utilizing stable-isotope labeling. Indeed, stable isotope-based multiplexing can be regarded as the gold-standard approach in reducing noise and uncertainty in quantitative mass spectrometry and quantitative analyses generally. The increasing sophistication and depth of biological questions being asked continue to challenge the practitioners of mass spectrometry method development. To understand the biological relevance of glycans, many stable isotope labeling-based mass spectrometry methods have been developed. Based on the duplex MILPIG (metabolic isotope labeling of polysaccharides with isotopic glucose), we establish here a novel triplex isotope labeling method using baker's yeast as the model system. Two differentially isotope-labeled glucoses (medium: 1-13C1 and heavy: 1,2-13C2), in addition to natural abundance glucose (light), were successfully used to label each monosaccharide ring in N-linked glycans in three different cell culture conditions, that, after sample mixing, resulted in a predictable triplet spectrum amenable for relative quantitation. We demonstrate excellent accuracy and precision of relative quantitation for a 1:1:1 mixture of glycans labeled in such a fashion. In addition, we applied triplex MILPIG to interrogate differential N-glycan profiles in tunicamycin-treated and control yeast cells and show that different N-glycans respond differently to tunicamycin.

An Updated Overview of Existing Cancer Databases and Identified Needs

Our search of existing cancer databases aimed to assess the current landscape and identify key needs. We analyzed 71 databases, focusing on genomics, proteomics, lipidomics, and glycomics. We found a lack of cancer-related lipidomic and glycomic databases, indicating a need for further development in these areas. Proteomic databases dedicated to cancer research were also limited. To assess overall progress, we included human non-cancer databases in proteomics, lipidomics, and glycomics for comparison. This provided insights into advancements in these fields over the past eight years. We also analyzed other types of cancer databases, such as clinical trial databases and web servers. Evaluating user-friendliness, we used the FAIRness principle to assess findability, accessibility, interoperability, and reusability. This ensured databases were easily accessible and usable. Our search summary highlights significant growth in cancer databases while identifying gaps and needs. These insights are valuable for researchers, clinicians, and database developers, guiding efforts to enhance accessibility, integration, and usability. Addressing these needs will support advancements in cancer research and benefit the wider cancer community.

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.

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

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

Profiling Serum Intact N-Glycopeptides Using Data-Independent Acquisition Mass Spectrometry

Large-scale profiling of intact glycopeptides is critical but challenging in glycoproteomics. Data-independent acquisition (DIA) mass spectrometry is an emerging technology with deep proteome coverage as well as accurate quantitative capability for large-scale proteomics studies and has also been applied to the field of glycoproteomics. In this protocol, we describe how to analyze data from a DIA experiment for profiling serum intact N-glycopeptides. We present a comprehensive data analysis workflow using GproDIA, including glycopeptide spectral library building, chromatographic feature extraction from the DIA data, and feature scoring with appropriate statistical control of error rates. We anticipate that this method could provide a powerful tool to explore the serum glycoproteome.

Simultaneous N-Deglycosylation and Digestion of Complex Samples on S-Traps Enables Efficient Glycosite Hypothesis Generation

N-linked glycosylation is an important post-translational modification that is difficult to identify and quantify in traditional bottom-up proteomics experiments. Enzymatic deglycosylation of proteins by peptide:N-glycosidase F (PNGase F) prior to digestion and subsequent mass spectrometry analysis has been shown to improve coverage of various N-linked glycopeptides, but the inclusion of this step may add up to a day to an already lengthy sample preparation process. An efficient way to integrate deglycosylation with bottom-up proteomics would be a valuable contribution to the glycoproteomics field. Here, we demonstrate a proteomics workflow in which deglycosylation and proteolytic digestion of samples occur simultaneously using suspension trapping (S-Trap). This approach adds no time to standard digestion protocols. Applying this sample preparation strategy to a human serum sample, we demonstrate improved identification of potential N-glycosylated peptides in deglycosylated samples compared with non-deglycosylated samples, identifying 156 unique peptides that contain the N-glycosylation motif (asparagine-X-serine/threonine), the deamidation modification characteristic of PNGase F, and an increase in peptide intensity over a control sample. We expect that this rapid sample preparation strategy will assist in the identification and quantification of both known and potential glycoproteins. Data are available via ProteomeXchange with the identifier PXD037921.

Glycan-Based Electrochemical Biosensors: Promising Tools for the Detection of Infectious Diseases and Cancer Biomarkers

Glycan-based electrochemical biosensors are emerging as analytical tools for determining multiple molecular targets relevant to diagnosing infectious diseases and detecting cancer biomarkers. These biosensors allow for the detection of target analytes at ultra-low concentrations, which is mandatory for early disease diagnosis. Nanostructure-decorated platforms have been demonstrated to enhance the analytical performance of electrochemical biosensors. In addition, glycans anchored to electrode platforms as bioreceptors exhibit high specificity toward biomarker detection. Both attributes offer a synergy that allows ultrasensitive detection of molecular targets of clinical interest. In this context, we review recent advances in electrochemical glycobiosensors for detecting infectious diseases and cancer biomarkers focused on colorectal cancer. We also describe general aspects of structural glycobiology, definitions, and classification of electrochemical biosensors and discuss relevant works on electrochemical glycobiosensors in the last ten years. Finally, we summarize the advances in electrochemical glycobiosensors and comment on some challenges and limitations needed to advance toward real clinical applications of these devices.

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

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

Molecular Basis and Role of Siglec-7 Ligand Expression on Chronic Lymphocytic Leukemia B Cells

Siglec-7 (sialic acid-binding immunoglobulin-like lectin 7) is an immune checkpoint-like glycan recognition protein on natural killer (NK) cells. Cancer cells often upregulate Siglec ligands to subvert immunosurveillance, but the molecular basis of Siglec ligands has been elusive. In this study, we investigated Siglec-7 ligands on chronic lymphocytic leukemia (CLL) B cells. CLL B cells express higher levels of Siglec-7 ligands compared with healthy donor B cells, and enzymatic removal of sialic acids or sialomucins makes them more sensitive to NK cell cytotoxicity. Gene knockout experiments have revealed that the sialyltransferase ST6GalNAc-IV is responsible for the biosynthesis of disialyl-T (Neu5Acα2-3Galβ1-3[Neu5Acα2-6]GalNAcα1-), which is the glycotope recognized by Siglec-7, and that CD162 and CD45 are the major carriers of this glycotope on CLL B cells. Analysis of public transcriptomic datasets indicated that the low expression of GCNT1 (encoding core 2 GlcNAc transferase, an enzyme that competes against ST6GalNAc-IV) and high expression of ST6GALNAC4 (encoding ST6GalNAc-IV) in CLL B cells, together enhancing the expression of the disialyl-T glycotope, are associated with poor patient prognosis. Taken together, our results determined the molecular basis of Siglec-7 ligand overexpression that protects CLL B cells from NK cell cytotoxicity and identified disialyl-T as a potential prognostic marker of CLL.

Pathological implication of protein post-translational modifications in cancer

Protein post-translational modifications (PTMs) profoundly influence protein functions and play crucial roles in essentially all cell biological processes. The diverse realm of PTMs and their crosstalk is linked to many critical signaling events involved in neoplastic transformation, carcinogenesis and metastasis. The pathological roles of various PTMs are implicated in all aspects of cancer hallmark functions, cancer metabolism and regulation of tumor microenvironment. Study of PTMs has become an important area in cancer research to understand cancer biology and discover novel biomarkers and therapeutic targets. With a limited scope, this review attempts to discuss some PTMs of high frequency with recognized importance in cancer biology, including phosphorylation, acetylation, glycosylation, palmitoylation and ubiquitination, as well as their implications in clinical applications. These protein modifications are among the most abundant PTMs and profoundly implicated in carcinogenesis.

A Glycoproteomic Approach to Identify Novel Proteoglycans

In this chapter, we describe a glycoproteomic approach for the identification of novel chondroitin sulfate proteoglycans (CSPGs) using a combination of biochemical enrichments, enzymatic digestions, and nanoscale liquid chromatography tandem mass spectrometry (nLC-MS/MS) analysis. The identification is achieved by trypsin digestion of CSPG-containing samples, followed by enrichment of chondroitin sulfate (CS) glycopeptides by strong anion exchange chromatography (SAX). The enriched CS glycopeptides are then digested with chondroitinase ABC to depolymerize the CS polysaccharides, generating a residual hexasaccharide structure, composed of the linkage region tetrasaccharide extended with a terminal dehydrated disaccharide, still attached to the peptide. The obtained CS glycopeptides are analyzed by nLC-MS/MS, and the generated data sets are evaluated through proteomic software with adjustment in the settings to allow for glycopeptide identification. This approach has enabled the identification of several novel core proteins in human samples and in Caenorhabditis elegans. Here we specifically describe the procedure for the enrichment and characterization of CS glycopeptides from human cerebrospinal fluid (CSF).

Development of a Glycoform Library-based Strategy to Decipher the Role of Protein Glycosylation

Glycoproteins obtained from cell culture supernatants or lysates generally exist as mixtures of over 100 differently glycosylated protein forms (glycoforms). The study of glycosylation is significantly impeded because of the heterogeneous nature of glycoproteins. To overcome this challenge, we developed and optimized a glycoform library-based strategy to investigate the role of protein glycosylation. In this strategy, chemical synthesis was used to prepare individual homogeneous glycoforms and the role of glycosylation was determined by comparing a series of glycoforms with systematic differences in their glycosylation patterns.

Serum Glycoproteomics and Identification of Potential Mechanisms Underlying Alzheimer’s Disease

Objectives. This study compares glycoproteomes in Thai Alzheimer’s disease (AD) patients with those of cognitively normal individuals. Methods. Study participants included outpatients with clinically diagnosed AD ( $N=136$ ) and healthy controls without cognitive impairment ( $N=183$ ). Blood samples were collected from all participants for biochemical analysis and for $\text{Apolipoprotein}\text{E}$ (APOE) genotyping by real-time TaqMan PCR assays. Comparative serum glycoproteomic profiling by liquid chromatography-tandem mass spectrometry was then performed to identify differentially abundant proteins with functional relevance. Results. Statistical differences in age, educational level, and APOE ɛ3/ɛ4 and ɛ4/ɛ4 haplotype frequencies were found between the AD and control groups. The frequency of the APOE ɛ4 allele was significantly higher in the AD group than in the control group. In total, 871 glycoproteins were identified, including 266 and 259 unique proteins in control and AD groups, respectively. There were 49 and 297 upregulated and downregulated glycoproteins, respectively, in AD samples compared with the controls. Unique AD glycoproteins were associated with numerous pathways, including Alzheimer’s disease-presenilin pathway (16.6%), inflammation pathway mediated by chemokine and cytokine signaling (9.2%), Wnt signaling pathway (8.2%), and apoptosis signaling pathway (6.7%). Conclusion. Functions and pathways associated with protein-protein interactions were identified in AD. Significant changes in these proteins can indicate the molecular mechanisms involved in the pathogenesis of AD, and they have the potential to serve as AD biomarkers. Such findings could allow us to better understand AD pathology.

The role of proteomics in the multiplexed analysis of gene alterations in human cancer

INTRODUCTION

Proteomics has played a pivotal role in identifying proteins perturbed in disease conditions when compared with healthy samples. Study of dysregulated proteins aids in identifying diagnostic markers and potential therapeutic targets. Cancer is an outcome of interplay of several such disarrayed proteins and molecular pathways which perturb cellular homeostasis, resulting in transformation. In this review, we discuss various facets of proteomic approaches, including tools and technological advancements, aiding in understanding differentially expressed molecules and signaling mechanisms.

AREAS COVERED

In this review, we have taken the approach of documenting the different methods of proteomic studies, ranging from labeling techniques, data analysis methods, and the nature of molecule detected. We summarize each technique and provide a glimpse of cancer research carried out using them, highlighting the advantages and drawbacks in comparison with others. Literature search using online resources, such as PubMed and Google Scholar were carried out for this approach.

EXPERT OPINION

Technological advancements in proteomics studies have come a long way from the study of two-dimensional mapping of proteins separated on gels in the early 1970s. Higher precision in molecular identification and quantification (high throughput), and greater number of samples analyzed have been the focus of researchers.

Benchmark of site- and structure-specific quantitative tissue N-glycoproteomics for discovery of potential N-glycoprotein markers: a case study of pancreatic cancer

Pancreatic cancer is a highly malignant tumor of the digestive tract that is difficult to diagnose and treat. It is more common in developed countries and has become one of the main causes of death in some countries and regions. Currently, pancreatic cancer generally has a poor prognosis, partly due to the lack of symptoms in the early stages of pancreatic cancer. Therefore, most cases are diagnosed at advanced stage. With the continuous in-depth research of glycoproteomics in precision medical diagnosis, there have been some reports on quantitative analysis of cancer-related cells, plasma or tissues to find specific biomarkers for targeted therapy. This research is based on the developed complete N-linked glycopeptide database search engine GPSeeker, combined with liquid-mass spectrometry and stable diethyl isotope labeling, providing a benchmark of site- and structure-specific quantitative tissue N-glycoproteomics for discovery of potential N-glycoprotein markers. With spectrum-level FDR ≤1%, 20,038 intact N-Glycopeptides corresponding to 4518 peptide backbones, 228 N-glycan monosaccharide compositions 1026 N-glycan putative structures, 4460 N-glycosites and 3437 intact N-glycoproteins were identified. With the criteria of ≥1.5-fold change and p value<0.05, 52 differentially expressed intact N-glycopeptides (DEGPs) were found in pancreatic cancer tussues relative to control, where 38 up-regulated and 14 down-regulated, respectively.

Site- and structure-specific characterization of the human urinary N-glycoproteome with site-determining and structure-diagnostic product ions

RATIONALE

N-glycosylation is one of the most common protein post-translational modifications; it is extremely complex with multiple glycoforms from different monosaccharide compositions, sequences, glycosidic linkages, and anomeric positions. Each glycoform functions with a particular site- and structure-specific N-glycan that can be fully characterized using state-of-the-art tandem mass spectrometry (MS/MS) and the intact N-glycopeptide database search engine GPSeeker that we recently developed. Urine has recently gained increasing attention as a non-invasive source for disease marker discovery. In this study, we report our structure-specific N-glycoproteomics study of human urine.

METHODS

We performed trypsin digestion, Zwitterionic Hydrophilic Interaction chromatography (ZIC-HILIC) enrichment, C18-RPLC/nano-ESI-MS/MS using HCD with stepped normalized collisional energies, and GPSeeker database search for a comprehensive site- and structure-specific N-glycoproteomics characterization of the human urinary N-glycoproteome at the intact N-glycopeptide level. For this, we used b/y product ion pairs from the GlcNAc-containing site-determining peptide backbone and structure-diagnostic product ions from the N-glycan moieties, respectively.

RESULTS

We identified 2986 intact N-glycopeptides with comprehensive site and structure information for the peptide backbones (amino acid sequences and N-glycosites) and the N-glycan moieties (monosaccharide compositions, sequences/linkages). The 2986 intact N-glycopeptide IDs corresponded to 754 putative N-glycan linkage structures on 419 N-glycosites of 450 peptide backbones from 327 intact N-glycoproteins. Next, 146 linkage structures and 200 N-glycosites were confirmed with structure-diagnostic and GlcNAc-containing site-determining product ions, respectively.

CONCLUSIONS

We found 106 new N-glycosites not annotated in the current UniProt database. The elution-abundance patterns of urinary intact N-glycopeptide oxonium ions (m/z 138 and 204) of the same subject were temporally stable during the day and over 6 months. These patterns are rather different among different subjects. The results implied an interesting possibility that glycopeptide oxonium ion patterns could serve as distinguishing markers between individuals and/or between physiological and pathological states.

Robustness and Ruggedness of Isoelectric Focusing and Superficially Porous Liquid Chromatography with Fourier Transform Mass Spectrometry

An investigation of a multidimensional proteomics workflow composed of off-gel isoelectric focusing (IEF) and superficially porous liquid chromatography (SPLC) with Fourier transform mass spectrometry (FTMS) was completed in order to assess various figures of merit associated with intact protein measurements. Triplicate analysis performed at both high and low FTMS resolutions on the E. coli proteome resulted in ∼900 redundant proteoforms from 3 to 95 kDa. Normalization of the chromatographic axis to identified proteoforms enabled reproducible physicochemical property measurements between proteome replicates with inter-replicate variances of ±3 ppm mass error for proteoforms <30 kDa, ±1.1 Da for proteins >30 kDa, ±12 s retention time error, and ±0.21 pI units. The results for E. coli and standard proteins revealed a correlation between pI precision and proteoform abundance with species detected in multiple IEF fractions exhibiting pI precisions less than the theoretical resolution of the off-gel system (±0.05 vs ±0.17, respectively). Evaluation of differentially modified proteoforms of standard proteins revealed that high sample loads (100s μgrams) change the IEF pH gradient profile, leading to sample broadening that facilitates resolution of charged post-translational modifications (e.g., phosphorylation, sialylation). Despite the impact of sample load on IEF resolution, results on standard proteins measured directly or after being spiked into E. coli demonstrated that the reproducibility of the workflow permitted recombination of the MS signal across IEF fractions in a manner supporting the evaluation of three label-free quantitation metrics for intact protein studies (proteoforms, proteoform ratios, and protein) over 102-103 sample amount with low femtomole detection limits.

Mass spectrometry-based proteomics analyses of post-translational modifications and proteoforms in human pituitary adenomas

Pituitary adenoma (PA) is a common intracranial neoplasm, which affects the hypothalamus-pituitary-target organ axis systems, and is hazardous to human health. Post-translational modifications (PTMs), including phosphorylation, ubiquitination, nitration, and sumoylation, are vitally important in the PA pathogenesis. The large-scale analysis of PTMs could provide a global view of molecular mechanisms for PA. Proteoforms, which are used to define various protein structural and functional forms originated from the same gene, are the future direction of proteomics research. The global studies of different proteoforms and PTMs of hypophyseal hormones such as growth hormone (GH) and prolactin (PRL) and the proportion change of different GH proteoforms or PRL proteoforms in human pituitary tissue could provide new insights into the clinical value of pituitary hormones in PAs. Multiple quantitative proteomics methods, including mass spectrometry (MS)-based label-free and stable isotope-labeled strategies in combination with different PTM-peptide enrichment methods such as TiO₂ enrichment of tryptic phosphopeptides and antibody enrichment of other PTM-peptides increase the feasibility for researchers to study PA proteomes. This article reviews the research status of PTMs and proteoforms in PAs, including the enrichment method, technical limitation, quantitative proteomics strategies, and the future perspectives, to achieve the goals of in-depth understanding its molecular pathogenesis, and discovering effective biomarkers and clinical therapeutic targets for predictive, preventive, and personalized treatment of PA patients.

Semiautomated glycoproteomics data analysis workflow for maximized glycopeptide identification and reliable quantification

Glycoproteomic data are often very complex, reflecting the high structural diversity of peptide and glycan portions. The use of glycopeptide-centered glycoproteomics by mass spectrometry is rapidly evolving in many research areas, leading to a demand in reliable data analysis tools. In recent years, several bioinformatic tools were developed to facilitate and improve both the identification and quantification of glycopeptides. Here, a selection of these tools was combined and evaluated with the aim of establishing a robust glycopeptide detection and quantification workflow targeting enriched glycoproteins. For this purpose, a tryptic digest from affinity-purified immunoglobulins G and A was analyzed on a nano-reversed-phase liquid chromatography-tandem mass spectrometry platform with a high-resolution mass analyzer and higher-energy collisional dissociation fragmentation. Initial glycopeptide identification based on MS/MS data was aided by the Byonic software. Additional MS1-based glycopeptide identification relying on accurate mass and retention time differences using GlycopeptideGraphMS considerably expanded the set of confidently annotated glycopeptides. For glycopeptide quantification, the performance of LaCyTools was compared to Skyline, and GlycopeptideGraphMS. All quantification packages resulted in comparable glycosylation profiles but featured differences in terms of robustness and data quality control. Partial cysteine oxidation was identified as an unexpectedly abundant peptide modification and impaired the automated processing of several IgA glycopeptides. Finally, this study presents a semiautomated workflow for reliable glycoproteomic data analysis by the combination of software packages for MS/MS- and MS1-based glycopeptide identification as well as the integration of analyte quality control and quantification.

An ultrafast and highly efficient enrichment method for both N-Glycopeptides and N-Glycans by bacterial cellulose

A powerful and fast glycopeptide/glycan enrichment method is critical for the efficiency and throughput of mass spectrometry (MS)-based glycoproteomic and glycomic analyses, especially for large-scale sample analysis. Here, we report an ultrafast and effective method for both intact N-glycopeptide and N-glycan enrichment and apply it to human serum samples. In this method, a natural hydrophilic material, bacterial cellulose (BC), was adopted and fully optimized for enrichment. This method offers the following advantages: (i) The enrichment material has natural hydrophilicity and is low-cost, biocompatible, biodegradable and easily accessible; (ii) the whole enrichment procedure is remarkably simple and fast. It takes only 10 min for intact glycopeptides/glycans to be easily purified from mixtures; (iii) the specificity of this method is over 94% for both glycan and glycopeptide enrichment; and (iv) the outstanding specificity of this technique enables high isolation efficiency for the enrichment of both intact glycopeptides and glycans. A total of 36 N-glycans and 31 N-glycopeptides were identified from human immunoglobulin G (IgG). The glycan and glycopeptide absorption capacity of BC was as high as 333 μg/mg and 250 μg/mg (IgG/BC) respectively. The selectivity for glycan and glycopeptide enrichment reached 1:100 (IgG/bovine serum albumin (BSA), molar ratio) and 1:200 (maltoheptaose (DP7)/BSA, molar ratio), respectively. Furthermore, a total of 159 N-glycans and 523 N-glycopeptides were identified in human serum by using this method. Overall, the BC-based enrichment method we present here provides an ultrafast and highly efficient method for the enrichment of both N-glycopeptides and N-glycans in complex samples and shows great potential in large-scale glycoproteomic and glycomic analyses.

In-depth proteomics approach reveals novel biomarkers of cardiac remodelling after myocardial infarction: An exploratory analysis

Cardiac remodelling following myocardial infarction (MI) is a maladaptive change associated with progressive heart failure and compromises long‐term clinical outcome. A substantial proportion of patients afflicted by MI still develop adverse outcomes associated with cardiac remodelling. Therefore, it is crucial to identify biomarkers for the early prediction of cardiac remodelling. An in‐depth proteomics approach, including both semi‐quantitative and quantitative antibody arrays, was used to identify circulating biomarkers that may be associated with detrimental cardiac remodelling. Furthermore, statistical correlation analysis was performed between the candidate biomarkers and clinical cardiac remodelling data to demonstrate their clinical utility. A systematic proteomics approach revealed that sclerostin (SOST), growth differentiation factor‐15 (GDF‐15), urokinase‐type plasminogen activator (uPA), and midkine (MK) were increased, while monocyte chemotactic protein‐3 (MCP‐3) was uniquely decreased in MI patients who developed cardiac remodelling, compared to MI patients who did not develop cardiac remodelling and healthy humen. Moreover, correlation analyses between serum proteomes and cardiac remodelling echocardiographic parameters demonstrated a moderate positive association between left ventricular end‐diastolic volume index (LVEDVi) and the three serum proteins, uPA, MK and GDF‐15 (P < .05, respectively), and a moderate negative correlation between LV ejection fraction (LVEF) and these serum proteins (P < .05, respectively). Importantly, uPA and MK were firstly identified to be associated with the development of cardiac remodelling. The present study contributes to a better understanding of the various cytokines expressed during adverse cardiac remodelling. The identified biomarkers may facilitate early identification of patients at high risk of ischaemic heart failure pending further confirmation through larger clinical trials.

The Emerging Role of the Mammalian Glycocalyx in Functional Membrane Organization and Immune System Regulation

All cells in the human body are covered by a dense layer of sugars and the proteins and lipids to which they are attached, collectively termed the "glycocalyx." For decades, the organization of the glycocalyx and its interplay with the cellular state have remained enigmatic. This changed in recent years. Latest research has shown that the glycocalyx is an organelle of vital significance, actively involved in and functionally relevant for various cellular processes, that can be directly targeted in therapeutic contexts. This review gives a brief introduction into glycocalyx biology and describes the specific challenges glycocalyx research faces. Then, the traditional view of the role of the glycocalyx is discussed before several recent breakthroughs in glycocalyx research are surveyed. These results exemplify a currently unfolding bigger picture about the role of the glycocalyx as a fundamental cellular agent.

Comparative Analysis of the Effect of Inorganic and Organic Chemicals with Silver Nanoparticles on Soybean under Flooding Stress

Extensive utilization of silver nanoparticles (NPs) in agricultural products results in their interaction with other chemicals in the environment. To study the combined effects of silver NPs with nicotinic acid and potassium nitrate (KNO3), a gel-free/label-free proteomic technique was used. Root length/weight and hypocotyl length/weight of soybean were enhanced by silver NPs mixed with nicotinic acid and KNO3. Out of a total 6340 identified proteins, 351 proteins were significantly changed, out of which 247 and 104 proteins increased and decreased, respectively. Differentially changed proteins were predominantly associated with protein degradation and synthesis according to the functional categorization. Protein-degradation-related proteins mainly consisted of the proteasome degradation pathway. The cell death was significantly higher in the root tips of soybean under the combined treatment compared to flooding stress. Accumulation of calnexin/calreticulin and glycoproteins was significantly increased under flooding with silver NPs, nicotinic acid, and KNO3. Growth of soybean seedlings with silver NPs, nicotinic acid, and KNO3 was improved under flooding stress. These results suggest that the combined mixture of silver NPs, nicotinic acid, and KNO3 causes positive effects on soybean seedling by regulating the protein quality control for the mis-folded proteins in the endoplasmic reticulum. Therefore, it might improve the growth of soybean under flooding stress.

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

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

Large-Scale Identification and Fragmentation Pathways Analysis of N-Glycans from Mouse Brain

N-linked glycosylation is one of the most common protein PTMs, and the topological structure (monosaccharide composition and sequence as well as glycosidic linkages) of N-glycans is vital information to understand their biological functions and roles. Tandem mass spectrometry has been widely used for topological structure characterization of N-glycans, where comprehensive understanding of fragmentation pathways and characteristics of product ions are essential to achieve best interpretation of MS/MS data and highest confidence of identification. Here, we report our glycomic study of N-glycome of mouse brain as well as fragmentation pathway analysis of the identified N-glycans. With LC-MS/MS analysis at both the positive and negative ESI modes together with our recently developed N-glycan database search engine GlySeeker, 221 unique N-glycans with putative topological structures were identified with target-decoy searches and number of best hits of 1. Analysis of fragmentation pathways and characteristics of product ions of permethylated N-glycans in the positive mode and native N-glycans in the negative mode were further carried out. The reported N-glycans serve as a basic reference for future glycosylation study of mouse brain; and in general database search of tandem mass spectra of N-glycans, B/Y/Z ions should be preferentially considered for the permethylated form in the positive mode and B/C/Z ions for the native form in the negative mode.

Probing N-glycoprotein microheterogeneity by lectin affinity purification-mass spectrometry analysis

A lectin affinity purification-mass spectrometry approach to characterize lectin-reactive glycoproteoforms and elucidate lectin specificities at the intact protein level.

Lectins are carbohydrate binding proteins that recognize specific epitopes present on target glycoproteins. Changes in lectin-reactive carbohydrate repertoires are related to many biological signaling pathways and recognized as hallmarks of several pathological processes. Consequently, lectins are valuable probes, commonly used for examining glycoprotein structural and functional microheterogeneity. However, the molecular interactions between a given lectin and its preferred glycoproteoforms are largely unknown due to the inherent complexity and limitations of methods used to investigate intact glycoproteins. Here, we apply a lectin-affinity purification procedure coupled with native mass spectrometry to characterize lectin-reactive glycoproteoforms at the intact protein level. We investigate the interactions between the highly fucosylated and highly branched glycoproteoforms of haptoglobin and α1-acid glycoprotein using two different lectins Aleuria aurantia lectin (AAL) and Phaseolus vulgaris leucoagglutinin (PHA-L), respectively. Firstly we show a co-occurrence of fucosylation and N-glycan branching on haptoglobin, particularly among highly fucosylated glycoproteoforms. Secondly, we analyze the global heterogeneity of highly branched glycoproteoforms of haptoglobin and α1-acid glycoprotein and reveal that while multi-fucosylation attenuates the lectin PHA-L binding to haptoglobin, it has no impact on AGP. Taken together, our lectin affinity purification native MS approach elucidates lectin specificities between intact glycoproteins, not achievable by other methods. Moreover, since aberrant glycosylation of Hp and AGP are potential markers for many diseases, including pancreatic, hepatic and ovarian cancers, understanding their interactions with lectins will help the development of carbohydrate-centric monitoring methods to understand their pathophysiological implications.

Multi-Omics Strategies Uncover Host-Pathogen Interactions

With the success of the Human Genome Project, large-scale systemic projects became a reality that enabled rapid development of the systems biology field. Systems biology approaches to host-pathogen interactions have been instrumental in the discovery of some specifics of Gram-negative bacterial recognition, host signal transduction, and immune tolerance. However, further research, particularly using multi-omics approaches, is essential to untangle the genetic, immunologic, (post)transcriptional, (post)translational, and metabolic mechanisms underlying progression from infection to clearance of microbes. The key to understanding host-pathogen interactions lies in acquiring, analyzing, and modeling multimodal data obtained through integrative multi-omics experiments. In this article, we will discuss how multi-omics analyses are adding to our understanding of the molecular basis of host-pathogen interactions and systemic maladaptive immune response of the host to microbes and microbial products.

N-Glycoproteomics of Patient-Derived Xenografts: A Strategy to Discover Tumor-Associated Proteins in High-Grade Serous Ovarian Cancer

High-grade serous ovarian carcinoma (HGSC) is the most common and lethal subtype of gynecologic malignancy in women. The current standard of treatment combines cytoreductive surgery and chemotherapy. Despite the efficacy of initial treatment, most patients develop cancer recurrence, and 70% of patients die within 5 years of initial diagnosis. CA125 is the current FDA-approved biomarker used in the clinic to monitor response to treatment and recurrence, but its impact on patient survival is limited. New strategies for the discovery of HGSC biomarkers are urgently needed. Here, we describe a proteomics strategy to detect tumor-associated proteins in serum of HGSC patient-derived xenograft models. We demonstrate proof-of-concept applicability using two independent, longitudinal serum cohorts from HGSC patients.

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

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

Facile Fabrication of Biomimetic Chitosan Membrane with Honeycomb-Like Structure for Enrichment of Glycosylated Peptides

In the study of glycoproteomics with mass spectrometry, certain pretreatments of samples are required for eliminating the interference of nonglycopeptides and improving the efficiency of glycopeptides detection. Although hydrophilic interaction chromatography (HILIC) has been developed for enrichment of glycosylated peptides, a plethora of hydrophilic materials always suffered from large steric hindrance, great cost, and difficulty with modifications of high-density hydrophilic groups. In this work, a 1 mm thick biomimetic honeycomb chitosan membrane (BHCM) with honeycomb-like accessible macropores was directly prepared by the freeze-casting method as an adsorbent for HILIC. The N-glycopeptides from trypsin digests of immunoglobulin G (IgG), mixture of IgG and bovine serum albumin (BSA), and serum proteins were enriched using this material and compared with a commercial material ZIC-HILIC. The biomimetic membrane could identify as many as 32 N-glycopeptides from the IgG digest, exhibiting high sensitivity (about 50 fmol) and a wide scope for glycopeptide enrichment. A molar ratio of IgG trypsin digest to bovine serum albumin trypsin digest as low as 1/500 verified the outstanding specificity and efficiency for glycopeptide enrichment. In addition, 270 unique N-glycosylation sites of 400 unique glycopeptides from 146 glycosylated proteins were identified from the triplicate analysis of 2 μL human serum. Furthermore, 48 unique O-glycosylation sites of 278 unique O-glycopeptides were identified from the triplicate analysis of 30 μg deglycosylated fetuin digest. These results indicated that the chitosan-based membrane prepared in this work had great potential for pretreatment of samples in glycoproteomics.

Glycoproteomic identification of novel plasma biomarkers for oral cancer

Oral cancer with high incidence rates is occurring in many countries including in India, Pakistan, Bangladesh, Sri Lanka and Taiwan. Smoking, alcoholism, and betel nut chewing are considered to be the main risk factors for oral cancer. Further, deaths from oral cancer have increased year by year. Although several oral cancer-associated biomarkers have been reported, very few useful biomarkers have been applied for early diagnosis. Therefore, the investigation of oral cancer-specific biomarkers is urgently needed. We previously investigated N-glycomes of oral cancer cells and patient plasma. We found that both mRNA levels of FUT8 and core-fucosylated glycoproteins increase in cases of oral cancer relative to normal cases. In this study we aim to discover novel core-fucosylated glycoprotein biomarkers for oral cancer diagnosis with glycoproteomic approaches. First, forty plasma samples obtained from the Human Bioinformation Bank of NCKUH were subjected to AAL (Aleuria aurantia lectin) affinity chromatography. Core-fucosylated proteins were collected and applied for LC-MS/MS followed by electrophoresis. Fourteen proteins were identified, and expression levels of proteins in plasma were verified by western blot. Expression levels of some glycoproteins were elevated in the oral cancer group, including ceruloplasmin, haptoglobin, and leucin-rich alpha-2-glycoprotein 1 (LRG1). However, levels of some glycoproteins decreased in the cancer group, including apolipoprotein A-I (apo A-I) and apolipoprotein A-IV (apo A-IV). Via ELISA analysis, we found that apo A-IV and apo A-IV/total protein ratios were decreased in plasma accompanied with cancer stages. The LRG1/total protein ratio was found to increase while plasma levels of LRG1 were not found to differ between the oral cancer plasma and normal groups. An ROC curve analysis reveals strong diagnosis performance when combining apo A-IV levels and LRG1/total protein ratios. Taken together, apo A-IV and LRG1, given their strong performance in detecting oral cancer, can serve as useful biomarkers and may be used as a useful tool for oral cancer screening and early diagnosis.

Comparative Glycomics Study of Cell-Surface N-Glycomes of HepG2 versus LO2 Cell Lines

Cell-surface N-glycans play important roles in both inter- and intracellular processes, including cell adhesion and development, cell recognition, as well as cancer development and metastasis; detailed structural characterization of these N-glycans is thus paramount. Here we report our comparative N-glycomics study of cell-surface N-glycans of the hepatocellular carcinoma (HCC) HepG2 cells vs the normal liver LO2 cells. With sequential trypsin digestion of proteins, C18 depletion of peptides without glycosylation, PNGase F digestion of N-glycopeptides, PGC enrichment of N-glycans, CH₃I permethylation of the enriched N-glycans, cell-surface N-glycomes of the HepG2 and LO2 cells were analyzed using C18-RPLC-MS/MS (HCD). With spectrum-level FDR no bigger than 1%, 351 and 310 N-glycans were identified for HepG2 and LO2, respectively, with comprehensive structural information (not only monosaccharide composition, but also sequence and linkage) by N-glycan database search engine GlySeeker. The percentage of hybrid N-glycans with tetra-antennary structures was substantially increased in the HepG2 cells. This comprehensive discovery study of differentially expressed cell-surface N-glycans in HepG2 vs LO2 serves as a solid reference for future validation study of glycosylation markers in HCC.

High-throughput detection of low abundance sialylated glycoproteins in human serum by TiO2 enrichment and targeted LC-MS/MS analysis: application to a prostate cancer sample set

Glycopeptide enrichment can be a strategy to allow the detection of peptides belonging to low abundance proteins in complex matrixes such as blood serum or plasma. Though several glycopeptide enrichment protocols have shown excellent sensitivities in this respect, few reports have demonstrated the applicability of these methods to relatively large sample cohorts. In this work, a fast protocol based on TiO₂ enrichment and highly sensitive mass spectrometric analysis by Selected Reaction Monitoring (SRM) has been applied to a cohort of serum samples from prostate cancer and benign prostatic hyperplasia patients in order to detect low abundance proteins in a single LC-MS/MS analysis in nanoscale format, without immunodepletion or peptide fractionation. A peptide library of over 700 formerly N-glycosylated peptides was created by data dependent analysis. Then, 16 medium to low abundance proteins were selected for detection by single injection LC-MS/MS based on selected-reaction monitoring. Results demonstrated the consistent detection of the low-level proteins under investigation. Following label-free quantification, four proteins (Adipocyte plasma membrane-associated protein, Periostin, Cathepsin D and Lysosome-associated membrane glycoprotein 2) were found significantly increased in prostate cancer sera compared to the control group. Graphical abstract ᅟ.

Proteomic analysis of rat serum revealed the effects of chronic sleep deprivation on metabolic, cardiovascular and nervous system

Sleep is an essential and fundamental physiological process that plays crucial roles in the balance of psychological and physical health. Sleep disorder may lead to adverse health outcomes. The effects of sleep deprivation were extensively studied, but its mechanism is still not fully understood. The present study aimed to identify the alterations of serum proteins associated with chronic sleep deprivation, and to seek for potential biomarkers of sleep disorder mediated diseases. A label-free quantitative proteomics technology was used to survey the global changes of serum proteins between normal rats and chronic sleep deprivation rats. A total of 309 proteins were detected in the serum samples and among them, 117 proteins showed more than 1.8-folds abundance alterations between the two groups. Functional enrichment and network analyses of the differential proteins revealed a close relationship between chronic sleep deprivation and several biological processes including energy metabolism, cardiovascular function and nervous function. And four proteins including pyruvate kinase M1, clusterin, kininogen1 and profilin-1were identified as potential biomarkers for chronic sleep deprivation. The four candidates were validated via parallel reaction monitoring (PRM) based targeted proteomics. In addition, protein expression alteration of the four proteins was confirmed in myocardium and brain of rat model. In summary, the comprehensive proteomic study revealed the biological impacts of chronic sleep deprivation and discovered several potential biomarkers. This study provides further insight into the pathological and molecular mechanisms underlying sleep disorders at protein level.

Do fragments and glycosylated isoforms of alpha-1-antitrypsin in CSF mirror spinal pathophysiological mechanisms in chronic peripheral neuropathic pain? An exploratory, discovery phase study

Background

Post-translational modifications (PTMs) generate a tremendous protein diversity from the ~ 20,000 protein-coding genes of the human genome. In chronic pain conditions, exposure to pathological processes in the central nervous system could lead to disease-specific PTMs detectable in the cerebrospinal fluid (CSF). In a previous hypothesis-generating study, we reported that seven out of 260 CSF proteins highly discriminated between neuropathic pain patients and healthy controls: one isoform of angiotensinogen (AG), two isoforms of alpha-1-antitrypsin (AT), three isoforms of haptoglobin (HG), and one isoform of pigment epithelium-derived factor (PEDF). The present study had three aims: (1) To examine the multivariate inter-correlations between all identified isoforms of these seven proteins; (2) Based on the results of the first aim, to characterize PTMs in a subset of interesting proteins; (3) To regress clinical pain data using the 260 proteins as predictors, thereby testing the hypothesis that the above-mentioned seven discriminating proteins and/or the characterized isoforms/fragments of aim (2) would be among the proteins having the highest predictive power for clinical pain data.

Methods

CSF samples from 11 neuropathic pain patients and 11 healthy controls were used for biochemical analysis of protein isoforms. PTM characterization was performed using enzymatic reaction assay and mass spectrometry. Multivariate data analysis (principal component analysis and orthogonal partial least square regression) was applied on the quantified protein isoforms.

Results

We identified 5 isoforms of AG, 18 isoforms of AT, 5 isoforms of HG, and 5 isoforms of PEDF. Fragments and glycosylated isoforms of AT were studied in depth. When regressing the pain intensity data of patients, three isoforms of AT, two isoforms of PEDF, and one isoform of angiotensinogen “reappeared” as major results, i.e., they were major findings both when comparing patients with healthy controls and when regressing pain intensity in patients.

Conclusions

Altered levels of fragments and/or glycosylated isoforms of alpha-1-antitrypsin might mirror pathophysiological processes in the spinal cord of neuropathic pain patients. In particular, we suggest that a putative disease-specific combination of the levels of two different N-truncated fragments of alpha-1-antitrypsin might be interesting for future CSF and/or plasma biomarker investigations in chronic neuropathic pain.

Electronic supplementary material

The online version of this article (10.1186/s12883-018-1116-2) contains supplementary material, which is available to authorized users.