A Perspective on the Confident Comparison of Glycoprotein Site-Specific Glycosylation in Sample Cohorts

Mass Spectrometry-Based Glycomics and Proteomics Profiling of On-Slide Digested Tissue from Complex Biological Samples

Mass spectrometry-based investigation of the heterogeneous glycoproteome from complex biological specimens is a robust approach to mapping the structure, function, and dynamics of the glycome and proteome. Sampling whole wet tissues often provides a large amount of starting material; however, there is a reasonable variability in tissue handling prior to downstream processing steps, and it is difficult to capture all the different biomolecules from a specific region. The on-slide tissue digestion approach, outlined in this protocol chapter, is a simple and cost-effective method that allows comprehensive mapping of the glycoproteome from a single spot of tissue of 1 mm or greater diameter. It provides a selection of target areas on tissue slides appropriate for tissue volumes of 10 nL or greater, corresponding to a 1 μL droplet of enzyme solution applied to a 1-mm diameter target on a 10-μm-thick tissue slice. Sequential enzymatic digestions and desalting of the biomolecules without any prior derivatization from the surface of fresh frozen or formalin-fixed paraffin-embedded tissue slides enable the simultaneous identification of glycosaminoglycan disaccharides such as hyaluronan, chondroitin sulfate and heparan sulfate, asparagine or N-linked glycans, and intact (glyco)peptides using liquid chromatography-tandem mass spectrometry. The in-depth information obtained from this method including the disaccharide compositions, glycan structures, peptide abundances, and site-specific glycan occupancies provides a detailed profiling of a single spot of tissue which has the potential to be disseminated to biomedical laboratories.

Mass spectrometry methods for analysis of extracellular matrix components in neurological diseases

The brain extracellular matrix (ECM) is a highly glycosylated environment and plays important roles in many processes including cell communication, growth factor binding, and scaffolding. The formation of structures such as perineuronal nets (PNNs) is critical in neuroprotection and neural plasticity, and the formation of molecular networks is dependent in part on glycans. The ECM is also implicated in the neuropathophysiology of disorders such as Alzheimer's disease (AD), Parkinson's disease (PD), and Schizophrenia (SZ). As such, it is of interest to understand both the proteomic and glycomic makeup of healthy and diseased brain ECM. Further, there is a growing need for site-specific glycoproteomic information. Over the past decade, sample preparation, mass spectrometry, and bioinformatic methods have been developed and refined to provide comprehensive information about the glycoproteome. Core ECM molecules including versican, hyaluronan and proteoglycan link proteins, and tenascin are dysregulated in AD, PD, and SZ. Glycomic changes such as differential sialylation, sulfation, and branching are also associated with neurodegeneration. A more thorough understanding of the ECM and its proteomic, glycomic, and glycoproteomic changes in brain diseases may provide pathways to new therapeutic options.

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.

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.

Charting the Proteoform Landscape of Serum Proteins in Individual Donors by High-Resolution Native Mass Spectrometry

Most proteins in serum are glycosylated, with several annotated as biomarkers and thus diagnostically important and of interest for their role in disease. Most methods for analyzing serum glycoproteins employ either glycan release or glycopeptide centric mass spectrometry-based approaches, which provide excellent tools for analyzing known glycans but neglect previously undefined or unknown glycosylation and/or other co-occurring modifications. High-resolution native mass spectrometry is a relatively new technique for the analysis of intact glycoproteins, providing a “what you see is what you get” mass profile of a protein, allowing the qualitative and quantitative observation of all modifications present. So far, a disadvantage of this approach has been that it centers mostly on just one specific serum glycoprotein at the time. To address this issue, we introduce an ion-exchange chromatography-based fractionation method capable of isolating and analyzing, in parallel, over 20 serum (glyco)proteins, covering a mass range between 30 and 190 kDa, from 150 μL of serum. Although generating data in parallel for all these 20 proteins, we focus the discussion on the very complex proteoform profiles of four selected proteins, i.e., α-1-antitrypsin, ceruloplasmin, hemopexin, and complement protein C3. Our analyses provide an insight into the extensive proteoform landscape of serum proteins in individual donors, caused by the occurrence of various N- and O-glycans, protein cysteinylation, and co-occurring genetic variants. Moreover, native mass intact mass profiling also provided an edge over alternative approaches revealing the presence of apo- and holo-forms of ceruloplasmin and the endogenous proteolytic processing in plasma of among others complement protein C3. We also applied our approach to a small cohort of serum samples from healthy and diseased individuals. In these, we qualitatively and quantitatively monitored the changes in proteoform profiles of ceruloplasmin and revealed a substantial increase in fucosylation and glycan occupancy in patients with late-stage hepatocellular carcinoma and pancreatic cancer as compared to healthy donor samples.

Comprehensive Plasma N-Glycoproteome Profiling Based on EThcD-sceHCD-MS/MS

Glycoproteins are involved in a variety of biological processes. More than one-third of the plasma protein biomarkers of tumors approved by the FDA are glycoproteins, and could improve the diagnostic specificity and/or sensitivity. Therefore, it is of great significance to perform the systematic characterization of plasma N-glycoproteome. In previous studies, we developed an integrated method based on the combinatorial peptide ligand library (CPLL) and stepped collision energy/higher energy collisional dissociation (sceHCD) for comprehensive plasma N-glycoproteome profiling. Recently, we presented a new fragmentation method, EThcD-sceHCD, which outperformed sceHCD in the accuracy of identification. Herein, we integrated the combinatorial peptide ligand library (CPLL) into EThcD-sceHCD and compared the performance of different mass spectrometry dissociation methods (EThcD-sceHCD, EThcD, and sceHCD) in the intact N-glycopeptide analysis of prostate cancer plasma. The results illustrated that EThcD-sceHCD was better than EThcD and sceHCD in the number of identified intact N-glycopeptides (two-folds). A combination of sceHCD and EThcD-sceHCD methods can cover almost all glycoproteins (96.4%) and intact N-glycopeptides (93.6%), indicating good complementarity between the two. Our study has great potential for medium- and low-abundance plasma glycoprotein biomarker discovery.

Comparative N-Glycoproteomics Analysis of Clinical Samples Via Different Mass Spectrometry Dissociation Methods

Site-specific N-glycosylation characterization requires intact N-glycopeptide analysis based on suitable tandem mass spectrometry (MS/MS) method. Electron-transfer/higher-energy collisional dissociation (EThcD), stepped collision energy/higher-energy collisional dissociation (sceHCD), higher-energy collisional dissociation-product-dependent electron-transfer dissociation (HCD-pd-ETD), and a hybrid mass spectrometry fragmentation method EThcD-sceHCD have emerged as valuable approaches for glycoprotein analysis. However, each of them incurs some compromise, necessitating the systematic performance comparisons when applied to the analysis of complex clinical samples (e.g., plasma, urine, cells, and tissues). Herein, we compared the performance of EThcD-sceHCD with those previous approaches (EThcD, sceHCD, HCD-pd-ETD, and sceHCD-pd-ETD) in the intact N-glycopeptide analysis, and determined its applicability for clinical N-glycoproteomic study. The intact N-glycopeptides of distinct samples, namely, plasma from prostate cancer (PCa) patients, urine from immunoglobulin A nephropathy (IgAN) patients, human hepatocarcinoma cell line (HepG2), and thyroid tissues from thyroid cancer (TC) patients were analyzed by these methods. We found that EThcD-sceHCD outperformed other methods in the balance of depth and accuracy of intact N-glycopeptide identification, and sceHCD and EThcD-sceHCD have good complementarity. EThcD-sceHCD holds great potential for biomarker discovery from clinical samples.

Calculating Glycoprotein Similarities From Mass Spectrometric Data

Complex protein glycosylation occurs through biosynthetic steps in the secretory pathway that create macro- and microheterogeneity of structure and function. Required for all life forms, glycosylation diversifies and adapts protein interactions with binding partners that underpin interactions at cell surfaces and pericellular and extracellular environments. Because these biological effects arise from heterogeneity of structure and function, it is necessary to measure their changes as part of the quest to understand nature. Quite often, however, the assumption behind proteomics that posttranslational modifications are discrete additions that can be modeled using the genome as a template does not apply to protein glycosylation. Rather, it is necessary to quantify the glycosylation distribution at each glycosite and to aggregate this information into a population of mature glycoproteins that exist in a given biological system. To date, mass spectrometric methods for assigning singly glycosylated peptides are well-established. But it is necessary to quantify glycosylation heterogeneity accurately in order to gauge the alterations that occur during biological processes. The task is to quantify the glycosylated peptide forms as accurately as possible and then apply appropriate bioinformatics algorithms to the calculation of micro- and macro-similarities. In this review, we summarize current approaches for protein quantification as they apply to this glycoprotein similarity problem.

Strategic Applications of Negative-Mode LC-MS/MS Analyses to Expedite Confident Mass Spectrometry-Based Identification of Multiple Glycosylated Peptides

Although recent advances in mass spectrometry (MS) have enabled meaningful glycoproteomic undertakings, many technical limitations remain unsolved. Among these, the ability to efficiently sequence the peptide backbone for de novo identification, delineating multiple N- and O-glycosylation sites on single glycopeptides, and deriving more glycan structure information to discriminate isomeric glycoforms are well acknowledged practical problems to be tackled. To address these issues, we explored the use of negative-mode MS²/MS³ fragmentation to supplement current nanoLC-MS²-based sequencing and identification of intact glycopeptides largely performed in positive mode. Consistent with previous reports by others, we found that sulfation and sialylation drastically alter the MS² fragmentation pattern of glycopeptides in negative mode and the characteristic features identified can be utilized to program the most informative MS³ on the glycan moiety itself. Importantly, direct elimination of one or more O-glycans under negative-mode MS² affords an easy way to discover additional O-glycosylations on a multiply glycosylated peptide by virtue of enumerating the dehydration scars imprinted on the O-glycosylated sites. Moreover, the characteristic peptide core ion carrying a ring cleavage remnant of the innermost amino sugar residue of an N-glycan can be relied upon to filter out all related N-glycopeptides carrying additional O-glycans defined by specific mass increments. Such enhanced ability to advance from definitive identification of single to multiple site-specific glycosylation on the same peptide backbones is anticipated to have a significant impact on the level of structural and biological insights one can gain in glycoproteomic applications.