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

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

Comprehensive Review on Chiral Stationary Phases in Single-Column Simultaneous Chiral-Achiral HPLC Separation Methods.

This comprehensive review explores the utilization of chiral stationary phases (CSPs) in the context of single-column simultaneous chiral-achiral high-performance liquid chromatography (HPLC) separation methods. While CSPs have traditionally been pivotal for enantioselective drug analysis, contemporary CSPs often exhibit notable chemoselective properties. Consequently, there is a discernible trend towards the development of methodologies that enable simultaneous enantio- and chemoselective separations utilizing a single CSP-based chromatographic column. This review provides an exhaustive overview of reported HPLC methods in this domain, with a focus on four major CSP types: cyclodextrin-, glycopeptide antibiotic-, protein-, and polysaccharide-based CSPs. This article delves into the diverse applications of CSPs, encompassing various chromatographic modes such as normal phase (NP), reverse phase (RP), and polar organic (PO). This review critically discusses method development, emphasizing the additional chemoselective separation mechanisms of CSPs. It also explores possibilities for method optimization and development, concluding with future perspectives on this evolving field. Despite the inherent challenges in understanding the retention mechanisms involved in chemoselective separations, this review highlights promising trends and anticipates a growing number of simultaneous enantio- and chemoselective methods in pharmaceutical analyses, pharmacokinetic studies, and environmental sample determinations.

Mass Spectrometry-Compatible Elution Technique Enables an Improved Mucin-Selective Enrichment Strategy to Probe the Mucinome.

Mucin-domain glycoproteins are densely O-glycosylated and play critical roles in a host of healthy and disease-driven biological functions. Previously, we developed a mucin-selective enrichment strategy by employing a catalytically inactive mucinase (StcE) conjugated to a solid support. While this method was effective, it suffered from low throughput and high sample requirements. Further, the elution step required boiling in SDS, thus necessitating an in-gel digest with trypsin. Here, we introduce innovative elution conditions amenable to mucinase digestion and downstream analysis using mass spectrometry. This increased throughput and lowered sample input while maintaining mucin selectivity and enhancing the glycopeptide signal. We then benchmarked this technique against different O-glycan binding moieties for their ability to enrich mucins from various cell lines and human serum. Overall, the new method outperformed our previous procedure and all of the other enrichment techniques tested. This allowed for the effective isolation of more mucin-domain glycoproteins, resulting in a high number of O-glycopeptides, thus enhancing our ability to analyze the mucinome.

The potential of polyaniline-coated stationary phase in hydrophilic interaction liquid chromatography-based solid-phase extraction for glycopeptide enrichment.

Glycopeptide enrichment is a crucial step in glycoproteomic analysis, often achieved through solid-phase extraction (SPE) on polar stationary phases in hydrophilic interaction liquid chromatography (HILIC). This study explores the potential of polyaniline (PANI)-coated silica gel for enriching human immunoglobulin G (IgG). Experimental conditions were varied to assess their impact on glycopeptide enrichment efficiency, comparing PANI-cotton wool SPE with conventional cotton wool as SPE sorbents. Two formic acid concentrations (0.1% and 1%) in elution solvent were tested, revealing that higher concentrations led to earlier elution of studied glycopeptides, especially for sialylated glycopeptides. Substituting formic acid with acetic acid increased the interaction of neutral glycopeptides with the PANI-modified sorbent, while sialylated glycopeptides showed no significant change in enrichment efficiency. Acetonitrile concentration in the elution solvent (5%, 10%, and 20%) affected the enrichment efficiency with most glycopeptides eluting at the lowest acetonitrile concentration. The acetonitrile concentration in conditioning and washing solutions (65%, 75%, and 85%) played a crucial role; at 65% acetonitrile, glycopeptides were least retained on the stationary phase, and neutral glycopeptides were even detected in the flow-through fraction. This study shows the potential of in-house-prepared PANI-modified sorbents for SPE-HILIC glycopeptide enrichment, highlighting the crucial role of tuning experimental conditions in sample preparation to enhance enrichment efficiency and selectivity.

Prediction of glycopeptide fragment mass spectra by deep learning.

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

A multivalent CD44 glycoconjugate vaccine candidate for cancer immunotherapy.

Cancer presents a high mortality rate due to ineffective treatments and tumour relapse with progression. Cancer vaccines hold tremendous potential due to their capability to eradicate tumour and prevent relapse. In this study, we present a novel glycovaccine for precise targeting and immunotherapy of aggressive solid tumours that overexpress CD44 standard isoform (CD44s) carrying immature Tn and sialyl-Tn (sTn) O-glycans. We describe an enzymatic method and an enrichment strategy to generate libraries of well-characterized cancer-specific CD44s-Tn and/or sTn glycoproteoforms, which mimic the heterogeneity found in tumours. We conjugated CD44-Tn-derived glycopeptides with carrier proteins making them more immunogenic, with further demonstration of the importance of this conjugation to overcome the glycopeptides' intrinsic toxicity. We have optimized the glycopeptide-protein maleimide-thiol conjugation chemistry to avoid undesirable cross-linking between carrier proteins and CD44s glycopeptides. The resulting glycovaccines candidates were well-tolerated in vivo, inducing both humoral and cellular immunity, including immunological memory. The generated antibodies exhibited specific reactivity against synthetic CD44s-Tn glycopeptides, CD44s-Tn glycoengineered cells, and human tumours. In summary, we present a promising prototype of a cancer glycovaccine for future therapeutical pre-clinical efficacy validation.

Preparation of Mucin Glycopeptides by Organic Synthesis.

Mucins are sugar-rich glycoproteins. Glycoprotein sugar moieties are structurally diverse, making it difficult to obtain naturally pure glycoproteins. Chemical synthesis is a powerful tool for obtaining target or designed compounds. Automated peptide synthesizers are commercially available, and many use the solid-phase peptide synthesis (SPPS) method. In addition, some of these synthesizers apply microwave irradiation to obtain higher reaction yields, thereby enabling the synthesis of 40 to 50 amino acid residual glycopeptides. Theoretically, glycopeptides can be synthesized using methods similar to those used for peptide synthesis, but glycosylated amino acid synthons are less stable than amino acid synthons and are also very expensive. Therefore, they are not suitable for use in large excess amounts. Many of oligosaccharide-linked amino acid synthons are not commercially available, so they must be specially prepared, and they also require careful handling that demands specific organic synthesis experience and techniques. However, monosaccharide-linked amino acid synthons are commercially available and are relatively easy to handle. Here, as an entry into glycopeptide synthesis, we describe a typical glycopeptide synthesis procedure for a 27 amino acid residual MUC1 repeating unit with monosaccharides.

Solution NMR Analysis of O-Glycopeptide-Antibody Interaction.

O-Linked glycans potentially play a functional role in cellular recognition events. Recent structural analyses suggest that O-glycosylation can be a specific signal for a lectin receptor which recognizes both the O-glycan and the adjacent polypeptide region. Further, certain antibodies specifically bind to the O-glycosylated peptide. There is growing interest in the mechanism by which O-glycans on proteins are specifically recognized by lectins and antibodies. The recognition system may be common to many O-glycosylated proteins; however, there is limited 3D structural information on the dual recognition of glycan and protein. This chapter describes a solution NMR analysis of the interaction between MUC1 O-glycopeptide and anti-MUC1 antibody MY.1E12.

Molecular Dynamics Simulation and Docking of MUC1 O-Glycopeptide.

Advances in computer performance and computational simulations allow increasing sophistication in applications in biological systems. Molecular dynamics (MD) simulations are especially suitable for studying conformation, dynamics, and interaction of flexible biomolecules such as free glycans and glycopeptides. Computer simulations are best performed when the scope and limitations in performance have been thoroughly assessed. Proper outputs are obtained only under suitable parameter settings, and results need to be properly validated. In this chapter, we will introduce an example of molecular dynamics simulations of MUC1 O-glycopeptide and its docking to anti-MUC1 antibody Fv fragment.

O-Glycoproteomics Sample Preparation and Analysis Using NanoHPLC and Tandem MS.

Glycosylation refers to the biological processes that covalently attach carbohydrates to the peptide backbone after the synthesis of proteins. As one of the most common post-translational modifications (PTMs), glycosylation can greatly affect proteins' features and functions. Moreover, aberrant glycosylation has been linked to various diseases. There are two major types of glycosylation, known as N-linked and O-linked glycosylation. Here, we focus on O-linked glycosylation and thoroughly describe a bottom-up strategy to perform O-linked glycoproteomics studies. The experimental section involves enzymatic digestions using trypsin and O-glycoprotease at 37 °C. The prepared samples containing O-glycopeptides are analyzed using nanoHPLC coupled with tandem mass spectrometry (MS) for accurate identification and quantification.

IgG glycopeptide enrichment using hydrophilic interaction chromatography-based solid-phase extraction on an aminopropyl column.

The sample preparation step is pivotal in glycoproteomic analysis. An effective approach in glycoprotein sample preparation involves enriching glycopeptides by solid-phase extraction (SPE) using polar stationary phases in hydrophilic interaction liquid chromatography (HILIC) mode. The aim of this work is to show how different experimental conditions influence the enrichment efficiency of glycopeptides from human immunoglobulin G (IgG) on an aminopropyl-modified SPE column. Different compositions of the elution solvent (acetonitrile, methanol, and isopropanol), along with varying concentrations of elution solvent acidifiers (formic and acetic acid), and different concentrations of acetonitrile for the conditioning and washing solvents (65%, 75%, and 85% acetonitrile) were tested to observe their effects on the glycopeptide enrichment process. Isopropanol proved less effective in enriching glycopeptides, while acetonitrile was the most efficient, with methanol in between. Higher formic acid concentrations in the elution solvent weakened the ionic interactions, particularly with sialylated glycopeptides. Substituting formic acid with acetic acid led to earlier elution of more glycopeptides. The acetonitrile concentration in conditioning and washing solutions played a key role; at 65% acetonitrile, glycopeptides were not retained on the SPE column and were detected in the flow-through fraction. Ultimately, it was proven that the enrichment method was applicable to human plasma samples, resulting in a significant decrease in the abundances of non-glycosylated peptides. To the best of our knowledge, this study represents the first systematic investigation into the impact of the mobile phase on glycopeptide enrichment using an aminopropyl-modified SPE column in HILIC mode. This study demonstrates the substantial impact of even minor variations in experimental conditions, which have not yet been considered in the literature, on SPE-HILIC glycopeptide enrichment. Consequently, meticulous optimization of these conditions is imperative to enhance the specificity and selectivity of glycoproteomic analysis, ensuring accurate and reliable quantification.

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.

Inclusion of deuterated glycopeptides provides increased sequence coverage in hydrogen/deuterium exchange mass spectrometry analysis of SARS-CoV-2 spike glycoprotein.

RATIONALE: Hydrogen/deuterium exchange mass spectrometry (HDX-MS) can provide precise analysis of a protein's conformational dynamics across varied states, such as heat-denatured versus native protein structures, localizing regions that are specifically affected by such conditional changes. Maximizing protein sequence coverage provides high confidence that regions of interest were located by HDX-MS, but one challenge for complete sequence coverage is N-glycosylation sites. The deuteration of peptides post-translationally modified by asparagine-bound glycans (glycopeptides) has not always been identified in previous reports of HDX-MS analyses, causing significant sequence coverage gaps in heavily glycosylated proteins and uncertainty in structural dynamics in many regions throughout a glycoprotein. METHODS: We detected deuterated glycopeptides with a Tribrid Orbitrap Eclipse mass spectrometer performing data-dependent acquisition. An MS scan was used to identify precursor ions; if high-energy collision-induced dissociation MS/MS of the precursor indicated oxonium ions diagnostic for complex glycans, then electron transfer low-energy collision-induced dissociation MS/MS scans of the precursor identified the modified asparagine residue and the glycan's mass. As in traditional HDX-MS, the identified glycopeptides were then analyzed at the MS level in samples labeled with D2 O. RESULTS: We report HDX-MS analysis of the SARS-CoV-2 spike protein ectodomain in its trimeric prefusion form, which has 22 predicted N-glycosylation sites per monomer, with and without heat treatment. We identified glycopeptides and calculated their average isotopic mass shifts from deuteration. Inclusion of the deuterated glycopeptides increased sequence coverage of spike ectodomain from 76% to 84%, demonstrated that glycopeptides had been deuterated, and improved confidence in results localizing structural rearrangements. CONCLUSION: Inclusion of deuterated glycopeptides improves the analysis of the conformational dynamics of glycoproteins such as viral surface antigens and cellular receptors.

Fluorescence detecting glycopeptide antibiotics via a dynamic molecular switch.

BACKGROUND: Glycopeptide antibiotics (GPAs) represented by vancomycin (VAN) are clinically used as a first-line treatment for serious infections caused by Gram-positive pathogens. The use and dosing methods of GPAs are rigorously managed for safety considerations, which calls for fast and accurate quantification approaches. RESULT: A new sort of fluorescent probes for GPAs has been proposed, each of which was integrated by a fluorescein-based reporter and a GPAs' recognition peptide D-alanyl-D-alanine (D-Ala-D-Ala). These probes work as dynamic molecular switches, which mainly exist as non-fluorescent spirolactam forms in the absence of GPAs. GPAs binding with the dipeptide regulates the dynamic balance between fluorescence OFF lactam form and fluorescence ON ring-opened form, rendering these probes capable of GPAs detecting. The most promising one P1 exhibits excellent sensitivity and selectivity towards GPAs detection. SIGNIFICANCE: Different to previous developments, P1 consists of a single fluorophore without the need of a fluorescence-quenching group or a secondary dye, which is the smallest fluorescent probe for GPAs up to now. P1 realizes direct VAN quantification from complex biological samples including real serums, dispensing with additional drug extraction. More interestingly, both P1 and P6 can distinguish GPAs with different peptide backbones, which has not been achieved previously.

Can We Boost N-Glycopeptide Identification Confidence? Smart Collision Energy Choice Taking into Account Structure and Search Engine.

High confidence and reproducibility are still challenges in bottom-up mass spectrometric N-glycopeptide identification. The collision energy used in the MS/MS measurements and the database search engine used to identify the species are perhaps the two most decisive factors. We investigated how the structural features of N-glycopeptides and the choice of the search engine influence the optimal collision energy, delivering the highest identification confidence. We carried out LC-MS/MS measurements using a series of collision energies on a large set of N-glycopeptides with both the glycan and peptide part varied and studied the behavior of Byonic, pGlyco, and GlycoQuest scores. We found that search engines show a range of behavior between peptide-centric and glycan-centric, which manifests itself already in the dependence of optimal collision energy on m/z. Using classical statistical and machine learning methods, we revealed that peptide hydrophobicity, glycan and peptide masses, and the number of mobile protons also have significant and search-engine-dependent influence, as opposed to a series of other parameters we probed. We envisioned an MS/MS workflow making a smart collision energy choice based on online available features such as the hydrophobicity (described by retention time) and glycan mass (potentially available from a scout MS/MS). Our assessment suggests that this workflow can lead to a significant gain (up to 100%) in the identification confidence, particularly for low-scoring hits close to the filtering limit, which has the potential to enhance reproducibility of N-glycopeptide analyses. Data are available via MassIVE (MSV000093110).

Facile preparation of nitrogen/titanium-rich porous organic polymers for specific enrichment of N-glycopeptides and phosphopeptides.

The comprehensive investigation of protein phosphorylation and glycosylation aids in the discovery of novel biomarkers as well as the understanding of the pathophysiology of illness. In this work, a nitrogen/titanium-rich porous organic polymer was developed by copolymerizing carbohydrazide (CH) and 2,3-dihydroxyterephthalaldehyde (2,3-Dha) and modifying with Ti4+ (CH-Dha-Ti4+). The adequate nitrogen contributes to the enrichment of glycopeptides via HILIC, while titanium benefits from capturing phosphopeptides through IMAC. The proposed method exhibits excellent selectivity (1 : 1000, both for glycopeptides and phosphopeptides), LOD (for glycopeptides: 0.05 fmol µL-1, for phosphopeptides: 0.2 fmol), loading capacity (for glycopeptides: 100 mg g-1, for phosphopeptides: 125 mg g-1) and size-exclusion effect (1 : 10 000, both for glycopeptides and phosphopeptides). Furthermore, CH-Dha-Ti4+ was applied to capture glycopeptides and phosphopeptides from human serum; 205 glycopeptides and 45 phosphopeptides were detected in the serum of normal controls; and 294 glycopeptides and 63 phosphopeptides were found in the serum of uremia patients after being analyzed by nano LC-MS/MS. The discovered glycopeptides and phosphopeptides were involved in several molecular biological processes and activities, according to a gene ontology study.

High-throughput N-glycoproteomics with fast liquid chromatographic separation.

N-glycosylation is a common protein post translation modification, which has tremendous structure diversity and wide yet delicate regulation of protein structures and functions. Mass spectrometry-based N-glycoproteomics has become a state-of-the-art pipeline for both qualitative and quantitative characterization of N-glycosylation at the intact N-glycopeptide level, providing comprehensive information of peptide backbones, N-glycosites, monosaccharide compositions, sequence and linkage structures. For high-throughput analysis of large-cohort clinic samples, fast and high-performance separation is indispensable. Here we report our development of 1-h liquid chromatography gradient N-glycoproteomics method and accordingly optimized MS parameters. In the benchmark analysis of cancer and paracancerous tissue of hepatocellular carcinoma, 5,218 intact N-glycopeptides were identified, where 422 site- and structure-specific differential N-glycosylation on 145 N-glycoproteins was observed. The method, representing substantial increase of throughput, can be adopted for fast and efficient analysis of N-glycoproteomes at large scale.

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

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

An efficient strategy with a synergistic effect of hydrophilic and electrostatic interactions for simultaneous enrichment of N- and O-glycopeptides.

N- and O-glycosylation modifications of proteins are closely linked to the onset and development of many diseases and have gained widespread attention as potential targets for therapy and diagnosis. However, the low abundance and low ionization efficiency of glycopeptides as well as the high heterogeneity make glycosylation analysis challenging. Here, an enrichment strategy, using Knoevenagel copolymers modified with polydopamine-adenosine (denoted as PDA-ADE@KCP), was firstly proposed for simultaneous enrichment of N- and O-glycopeptides through the synergistic effects of hydrophilic and electrostatic interactions. The adjustable charged surface and hydrophilic properties endow the material with the capability to achieve effective enrichment of intact N- and O-glycopeptides. The experimental results exhibited excellent selectivity (1 : 5000) and sensitivity (0.1 fmol µL-1) of the prepared material for N-glycopeptides from standard protein digest samples. Moreover, it was further applied to simultaneous capturing of N- and O-glycopeptides from mouse liver protein digests. Compared to the commercially available zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC) material, the number of glycoproteins corresponding to all N- and O-glycopeptides enriched with PDA-ADE@KCP was much more than that with ZIC-HILIC. Furthermore, PDA-ADE@KCP captured more O-glycopeptides than ZIC-HILIC, revealing its superior performance in O-glycopeptide enrichment. All these results indicated that the strategy holds immense potential in characterizing N- and O-intact glycopeptides in the field of proteomics.

Site-Specific Profiling of N-Glycans in Drosophila melanogaster.

BACKGROUND: Drosophila melanogaster is a well-studied and highly tractable genetic model system for deciphering the molecular mechanisms underlying various biological processes. Although being one of the most critical post-translational modifications of proteins, the understanding of glycosylation in Drosophila is still lagging behind compared with that of other model organisms. METHODS: In this study, we systematically investigated the site-specific N-glycan profile of Drosophila melanogaster using intact glycopeptide analysis technique. This approach identified the glycans, proteins, and their glycosites in Drosophila, as well as information on site-specific glycosylation, which allowed us to know which glycans are attached to which glycosylation sites. RESULTS: The results showed that the majority of N-glycans in Drosophila were high-mannose type (69.3%), consistent with reports in other insects. Meanwhile, fucosylated N-glycans were also highly abundant (22.7%), and the majority of them were mono-fucosylated. In addition, 24 different sialylated glycans attached with 16 glycoproteins were identified, and these proteins were mainly associated with developmental processes. Gene ontology analysis showed that N-glycosylated proteins in Drosophila were involved in multiple biological processes, such as axon guidance, N-linked glycosylation, cell migration, cell spreading, and tissue development. Interestingly, we found that seven glycosyltransferases and four glycosidases were N-glycosylated, which suggested that N-glycans may play a regulatory role in the synthesis and degradation of N-glycans and glycoproteins. CONCLUSIONS: To our knowledge, this work represents the first comprehensive analysis of site-specific N-glycosylation in Drosophila, thereby providing new perspectives for the understanding of biological functions of glycosylation in insects.