Glycopeptide Level Research Articles

Comprehensive characterization of bacterial glycoconjugate vaccines by liquid chromatography - mass spectrometry

Bacterial pathogens can cause a broad range of infections with detrimental effects on health. Vaccine development is essential as multi-drug resistance in bacterial infections is a rising concern. Recombinantly produced proteins carrying O-antigen glycosylation are promising glycoconjugate vaccine candidates to prevent bacterial infections. However, methods for their comprehensive structural characterization are lacking. Here, we present a bottom-up approach for their site-specific characterization, detecting N-glycopeptides by nano reversed-phase liquid chromatography-mass spectrometry (RP-LC-MS). Glycopeptide analyses revealed information on partial site-occupancy and site-specific glycosylation heterogeneity and helped corroborate the polysaccharide structures and their modifications. Bottom-up analysis was complemented by intact glycoprotein analysis using nano RP-LC-MS allowing the fast visualization of the polysaccharide distribution in the intact glycoconjugate. At the glycopeptide level, the model glycoconjugates analyzed showed different repeat unit (RU) distributions that spanned from 1 to 21 RUs attached to each of the different glycosylation sites. Interestingly, the intact glycoprotein analysis displayed a RU distribution ranging from 1 to 28 RUs, showing the predominant species when the different glycopeptide distributions are combined in the intact glycoconjugate. The complete workflow based on LC-MS measurements allows detailed and comprehensive analysis of the glycosylation state of glycoconjugate vaccines.

Comprehensive Glycosylation Characterization of Recombinant Human Erythropoietin by Electron-Activated Dissociation Mass Spectrometry.

Recombinant human erythropoietin (rhEPO) is a glycoprotein that acts as the main hormone involved in regulating red blood cell production to treat anemia caused by chronic kidney disease or chemotherapy, which has three N-glycosylation sites and one O-glycosylation site. It contains a variety of different glycosylation modifications, such as sialyation, O-acetylation on sialic acids, etc., which causes a big challenge for the glycosylation analysis of rhEPO. In this study, a liquid chromatography-mass spectrometry (LC-MS) method combined with electron-activated dissociation (EAD) technology was used in qualitative and quantitative characterization of rhEPO N-glycosylation and O-glycosylation in just one injection. The usage of EAD not only generated abundant MS/MS fragment ions of glycopeptides and improved the MS/MS sequence coverage but also preserved the glycan structures in the MS/MS fragment ions and the integrity of the glycosidic bond between the glycans and peptides. Three N-glycosylation sites (N24, N38, and N83) and one O-glycosylation site (S126) of rhEPO samples were successfully identified. Among them, the glycosylation ratios of N24, N38, and N83 sites were 82.7%, 100%, and 100% respectively, and 15, 10, and 12 different N-glycans could be identified at the glycopeptide level. The total average number of sialic acids, N-hydroxyacetylneuraminoic acid, and O-acetylation on sialic acid were 7.28, 4.21, and 0.66 at the intact protein level, respectively. For O-glycosylation site S126, O-glycosylation ratios analyzed at the intact protein level and the glycopeptide level were 80.2% and 80.3%, respectively, and two O-glycans were identified, including Core1_S1 and Core1_S2. This study also compared the difference of the glycans and their relative contents in batch-to-batch rhEPO samples. The results proved that the workflow using EAD fragmentation in LC-MS method could be effectively applied for characterizing the glycosylation analysis of rhEPO samples and batch-to-batch consistency analysis, which would help to reasonably guide the optimization of rhEPO production process.

Isomeric Separation of α2,3/α2,6-Linked 2-Aminobenzamide (2AB)-Labeled Sialoglycopeptides by C18-LC-MS/MS.

Determination of the relative expression levels of the α2,3/α2,6-sialic acid linkage isomers on glycoproteins is critical to the analysis of various human diseases such as cancer, inflammation, and viral infection. However, it remains a challenge to separate and differentiate site-specific linkage isomers at the glycopeptide level. Some derivatization methods on the carboxyl group of sialic acid have been developed to generate mass differences between linkage isomers. In this study, we utilized chemical derivatization that occurred on the vicinal diol of sialic acid to separate linkage isomers on a reverse-phase column using a relatively short time. 2-Aminobenzamide (2AB) labeling derivatization, including periodate oxidation and reductive amination, took only ∼3 h and achieved high labeling efficiency (>90%). Within a 66 min gradient, the sialic acid linkage isomers of 2AB-labeled glycopeptides from model glycoproteins can be efficiently resolved compared to native glycopeptides. Two different methods, neuraminidase digestion and higher-energy collision dissociation tandem mass spectrometry (HCD-MS2) fragmentation, were utilized to differentiate those isomeric peaks. By calculating the diagnostic oxonium ion ratio of Gal2ABNeuAc and 2ABNeuAc fragments, significant differences in chromatographic retention times and in mass spectral peak abundances were observed between linkage isomers. Their corresponding MS2 PCA plots also helped to elucidate the linkage information. This method was successfully applied to human blood serum. A total of 514 2AB-labeled glycopeptide structures, including 152 sets of isomers, were identified, proving the applicability of this method in linkage-specific structural characterization and relative quantification of sialic acid isomers.

Chemical Proteomic Approach for In-Depth Glycosylation Profiling of Plasma Carcinoembryonic Antigen in Cancer Patients

Carcinoembryonic antigen (CEA) of human plasma is a biomarker of many cancer diseases, and its N-glycosylation accounts for 60% of molecular mass. It is highly desirable to characterize its glycoforms for providing additional dimension of features to increase its performance in prognosis and diagnosis of cancers. However, to systematically characterize its site-specific glycosylation is challenging because of its low abundance. Here, we developed a highly sensitive strategy for in-depth glycosylation profiling of plasma CEA through chemical proteomics combined with multienzymatic digestion. A trifunctional probe was utilized to generate covalent bond of plasma CEA and its antibody upon UV irradiation. As low as 1 ng/ml CEA in plasma could be captured and digested with trypsin and chymotrypsin for intact glycopeptide characterization. Twenty six of 28 potential N-glycosylation sites were well identified, which were the most comprehensive N-glycosylation site characterization of CEA on intact glycopeptide level as far as we known. Importantly, this strategy was applied to the glycosylation analysis of plasma CEA in cancer patients. Differential site-specific glycoforms of plasma CEA were observed in patients with colorectal cancers (CRCs) and lung cancer. The distributions of site-specific glycoforms were different as the progression of CRC, and most site-specific glycoforms were overexpressed in stage II of CRC. Overall, we established a highly sensitive chemical proteomic method to profile site-specific glycosylation of plasma CEA, which should generally applicable to other well-established cancer glycoprotein biomarkers for improving their cancer diagnosis and monitoring performance.

Elucidation of N-/O-glycosylation and site-specific mapping of sialic acid linkage isomers of SARS-CoV-2 human receptor angiotensin-converting enzyme 2.

Human angiotensin-converting enzyme 2 (hACE2) is the primary receptor for cellular entry of SARS-CoV-2 into human host cells. hACE2 is heavily glycosylated and glycans on the receptor may play a role in viral binding. Thus, comprehensive characterization of hACE2 glycosylation could aid our understanding of interactions between the receptor and SARS-CoV-2 spike (S) protein, as well as provide a basis for the development of therapeutic drugs targeting this crucial interaction. Herein, 138 N-glycan compositions were identified, most of which are complex-type N-glycans, from seven N-glycosites of hACE2. Among them, 67% contain at least one sialic acid residue. At the level of glycopeptides, the overall quantification of sialylated glycan isomers observed on the sites N322 and N546 have a higher degree of NeuAc (α2-3)Gal (over 80.3%) than that of other N-glycosites (35.6-71.0%). In terms of O-glycans, 69 glycan compositions from 12 O-glycosites were identified, and especially, the C-terminus of hACE2 is heavily O-glycosylated. The terminal sialic acid linkage type of H1N1S1 and H1N1S2 are covered highly with α2,3-sialic acid. These findings could aid the investigation of the interaction between SARS-CoV-2 and human host cells.

PGlycoQuant with a deep residual network for quantitative glycoproteomics at intact glycopeptide level

Large-scale intact glycopeptide identification has been advanced by software tools. However, tools for quantitative analysis remain lagging behind, which hinders exploring the differential site-specific glycosylation. Here, we report pGlycoQuant, a generic tool for both primary and tandem mass spectrometry-based intact glycopeptide quantitation. pGlycoQuant advances in glycopeptide matching through applying a deep learning model that reduces missing values by 19–89% compared with Byologic, MSFragger-Glyco, Skyline, and Proteome Discoverer, as well as a Match In Run algorithm for more glycopeptide coverage, greatly expanding the quantitative function of several widely used search engines, including pGlyco 2.0, pGlyco3, Byonic and MSFragger-Glyco. Further application of pGlycoQuant to the N-glycoproteomic study in three different metastatic HCC cell lines quantifies 6435 intact N-glycopeptides and, together with in vitro molecular biology experiments, illustrates site 979-core fucosylation of L1CAM as a potential regulator of HCC metastasis. We expected further applications of the freely available pGlycoQuant in glycoproteomic studies.

An integrated stage-tip-based glycomic and glycoproteomic approach for simple and rapid N-glycosylation profiling of glycoproteins.

Glycosylation is a post-translational modification that plays an active role in many cellular events. It also regulates many functions of proteins. Monoclonal antibody-derived drugs are used to treat many diseases, and glycosylation affects the activity of such drugs developed. On the other hand, N-glycans may change in certain diseases. Therefore, rapid and efficient bioanalytical methods are needed for N-glycosylation profiling. The study aimed to develop an integrated stage-tip application for the simple and rapid N-glycosylation profiling of glycoproteins. A fast and inexpensive N-glycosylation profiling was achieved by integrating all glycoproteomic and glycomic sample preparation steps into a stage-tip. The glycomic approach of the integrated stage-tip reduces the N-glycan profiling time from 2 days to approximately 2.5hours. It also allows the profiling of immunoglobulin G (IgG) N-glycopeptides directly from human plasma. In addition, N-glycosylation profiling can be done in the developed method without sorbents, C18 or others, such as strong-cation exchange, at the glycopeptide level.

Site-specific N-glycosylation analysis of human thyroid thyroglobulin by mass spectrometry-based Glyco-analytical strategies

Human thyroglobulin (Tg), which has many glycosylation sites, is an essential protein produced by the human thyroid glands. Although human Tg N-glycans play critical roles in the cellular events of the Thyroid gland, the site-specific distribution of glycan structures has not been studied in detail. This study aimed to profile human Tg N-glycosylation sites and their glycan contents by using high-throughput glyco-analytical strategies, including glycopeptide and glycan levels. The sulfated complex and hybrid type N-glycan species were determined by the analysis of the human Tg samples with HPLC-HILIC-FLD-MS/MS. It was found that all fucosylated N-glycans carried fucose residue on their N-glycan core structure. The human Tg was digested with multiple enzymes by applying both in-gel and in-solution protocols to enhance site-specific glycosylation analysis. In total, 17 out of 20 N-glycosylation sites were characterized. It was noticed that 6 N-glycosylation sites contain only high-mannose type glycans, while other regions include complex and hybrid type glycans. In addition, sulfated glycoform structures were detected at the glycopeptide level in glycosylation sites containing complex and hybrid type glycans. It is expected that the results obtained from this study will contribute to functional studies to be conducted on human Tg protein. Biological significanceN-glycans of human thyroglobulin modulate thyroid hormone synthesis both in vivo and in vitro. Therefore, a comprehensive analysis of the N-glycosylation sites of human thyroglobulin is essential to improve our understanding of the function of its N-glycans. The present research significantly expanded the knowledge regarding N-glycosylation profiles of human thyroid thyroglobulin protein. For instance, as highlighted here, sulfated N-glycan structures were characterized using comprehensive glyco-analytical strategies. N-glycan patterns for the sites Asn110, Asn1869, and Asn2122 were described for the first time in this current work. In addition, N-glycan structures containing core-fucosylation and bisecting types were confirmed for all determined glycosylation sites.

Liquid-biopsy-derived glycoproteomic profiling as a novel means for noninvasive diagnosis of ovarian cancer.

e17604 Background: Ovarian cancer (OC) is the fifth- leading cause of cancer-related deaths among women, and the most lethal gynecological cancer. Currently available biomarkers, including CA-125 and HE4, show suboptimal diagnostic performance for differentiating among benign and malignant pelvic tumors, and the early recognition of OC. Differentiation of benign and malignant pelvic tumors is required for proper patient triaging and management, yet non-invasive methods remain a largely unmet medical need. Methods: We applied a novel platform for characterizing peripheral blood glycoproteomic biomarkers, combining liquid-chromatography/mass spectrometry (LC-MS) with artificial intelligence/neural networks (AI-NN) for the targeted quantification of serum protein glycosylation at intact glycopeptide level to analyze serum samples from 296 treatment-naïve women with histopathology-confirmed diagnosis of either benign (n = 151) or malignant (n = 145) tumors, and from 55 healthy control subjects, procured from a commercial biobank. Using data-dependent acquisition, a panel of 683 serum glycosylated and non-glycosylated peptides, representing 71 serum proteins, was interrogated. Samples were randomly divided into a training and a testing set for multivariable analysis. Data processing was performed using PB-Net, an in-house-developed high-throughput peak integration software. Raw data were normalized, processed by statistical analysis, and applied to machine learning models. Results: Comparison of glycopeptide abundances among patients with OC and benign pelvic tumors yielded 428 statistically significantly differentially expressed glycopeptides/peptides (at FDR < 0.05). A subpanel of these markers used to generate a score for predicting OC yielded areas under the receiver-operating-characteristic of 0.955 and 0.894 in the training and testing sets, respectively. The predicted probability of malignancy increased with cancer stage, and probability distributions were similar across training and test sets. Applying the model to healthy subjects, not utilized in training, resulted in few misclassifications and a spread nearly equivalent to that of the benign tumor cases. This indicates the signature robustly predicts malignancy and severity of disease. Conclusions: Our novel approach exhibited impressive levels of accuracy for the noninvasive differentiation of benign and malignant pelvic masses, compared with existing biomarkers and algorithms, thereby demonstrating the utility of glycoprotein profiles as a powerful, noninvasive new diagnostic modality.

A Preliminary Study on Change of Serum Immunoglobulin G Glycosylation in Patients With Migraine.

Background and ObjectiveMigraine is a common neurological disease, but its pathogenesis is still unclear. Previous studies suggested that migraine was related to immunoglobulin G (IgG). We intended to analyze the immune characteristics of migraine from the perspective of IgG glycosylation and provide theoretical assistance for exploring its pathogenesis.MethodsThe differences in the serum level of IgG glycosylation and glycopeptides between patients with episodic migraine and healthy controls were analyzed by applying the poly(glycerol methacrylate)@chitosan (PGMA@CS) nanomaterial in combination with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). We constructed a binary classification model with a feedforward neural network using PyTorch 1.6.0 in Python 3.8.3 to classify the episodic migraine and healthy control groups.ResultsTwenty patients with migraine and 20 healthy controls were enrolled and the blood samples and clinical information were collected. Forty-nine IgG N-glycopeptides were detected in the serum of the subjects. The serum level of N-glycopeptide IgG1 G0-NF (p = 0.012) was increased in patients with migraine. The serum level of N-glycopeptide IgG3/4 G2FS (p = 0.041) was decreased in patients with migraine with family history of headache. It was found that the serum level of the IgG1 G1 (p = 0.004) and IgG2 G0 (p = 0.045) was increased in patients with migraine with aura, while the serum level of IgG2 G0N (p = 0.043) in patients with migraine with aura was significantly lower than that in patients with migraine without aura. In addition, a linear feedforward neural network (FFNN) was used to construct a binary classification model by detected IgG N-glycopeptides. The area under the curve (AUC) value of the binary classification model, which was constructed with 7 IgG N-glycopeptides, was 0.857, suggesting a good prediction performance. Among these IgG N-glycopeptides that were constructed the model, IgG1 G0-NF was overlapped with the differential IgG N-glycopeptide between patients with migraine and healthy controls detected with MALDI-TOF-MS.ConclusionOur results indicated that the serum level of N-glycopeptides IgG1 G0-NF might be one of the important biomarkers for the diagnosis of migraine. To the best of our knowledge, this is the first study about the changes of IgG N-glycosylation in patients with migraine by the method of MALDI-TOF-MS. The results indicated a relationship between the migraine and immune response.

Coronavirus Disease 2019-Related Alterations of Total and Anti-Spike IgG Glycosylation in Relation to Age and Anti-Spike IgG Titer.

The coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been affecting the world since January 2020 and has caused millions of deaths. To gain a better insight into molecular changes underlying the COVID-19 disease, we investigated here the N-glycosylation of three immunoglobulin G (IgG) fractions isolated from plasma of 35 severe COVID-19 patients, namely total IgG1, total IgG2, and anti-Spike IgG, by means of MALDI-TOF-MS. All analyses were performed at the glycopeptide level to assure subclass- and site-specific information. For each COVID-19 patient, the analyses included three blood withdrawals at different time-points of hospitalization, which allowed profiling longitudinal alterations in IgG glycosylation. The COVID-19 patients presented altered IgG N-glycosylation profiles in all investigated IgG fractions. The most pronounced COVID-19-related changes were observed in the glycosylation profiles of antigen-specific anti-Spike IgG1. Anti-Spike IgG1 fucosylation and galactosylation showed the strongest variation during the disease course, with the difference in anti-Spike IgG1 fucosylation being significantly correlated with patients’ age. Decreases in anti-Spike IgG1 galactosylation and sialylation in the course of the disease were found to be significantly correlated with the difference in anti-Spike IgG plasma concentration. The present findings suggest that patients’ age and anti-S IgG abundance might influence IgG N-glycosylation alterations occurring in COVID-19.

Identifying intact N-glycopeptides from tandem mass spectrometry data using StrucGP.

Protein glycosylation is of great importance in many biological processes. Glycosylation has been increasingly analyzed at the intact glycopeptide level using mass spectrometry to study site-specific glycosylation changes under different physiological and pathological conditions. StrucGP is a glycan database-independent search engine for the structural interpretation of N-glycoproteins at the site-specific level. To ensure the accuracy of results, two collision energies are implemented in instrument settings for each precursor to separate fragments of peptides and glycans. In addition, the false discovery rates (FDR) of peptides and glycans as well as probabilities of detailed structures are estimated. In this protocol, the use of StrucGP is demonstrated, including environment configuration, data preprocessing as well as result inspection and visualization using our in-house software "GlycoVisualTool". The described workflow should be able to be performed by anyone with basic proteomic knowledge.

Identifying intact <i>N</i>-glycopeptides from tandem mass spectrometry data using StrucGP

Protein glycosylation is of great importance in many biological processes. Glycosylation has been increasingly analyzed at the intact glycopeptide level using mass spectrometry to study site-specific glycosylation changes under different physiological and pathological conditions. StrucGP is a glycan database-independent search engine for the structural interpretation of <i>N</i>-glycoproteins at the site-specific level. To ensure the accuracy of results, two collision energies are implemented in instrument settings for each precursor to separate fragments of peptides and glycans. In addition, the false discovery rates (FDR) of peptides and glycans as well as probabilities of detailed structures are estimated. In this protocol, the use of StrucGP is demonstrated, including environment configuration, data preprocessing as well as result inspection and visualization using our in-house software “GlycoVisualTool”. The described workflow should be able to be performed by anyone with basic proteomic knowledge.

Efficient HCD-pd-EThcD approach for N-glycan mapping of therapeutic antibodies at intact glycopeptide level

N-glycosylation is a critical quality attribute for monoclonal antibody (mAb)-based therapeutics due to its significant impact on drug efficacy and safety. Extensive glycosylation mapping is therefore necessary for mAb drug development and quality control. We utilized a higher-energy dissociation product ions-triggered electron-transfer/higher-energy collision dissociation (HCD-pd-EThcD) approach to mapping N-glycosylation in therapeutic mAbs. Due to the improved duty cycle and targeted ability, HCD-pd-EThcD could provide extensive N-glycan identifications as well as higher quality spectra than EThcD mode. On average, ten types of N-glycan were uncovered in two different lots of trastuzumab, demonstrating a significant increment in N-glycan species compared to only four types identified by EThcD. After integrating pre-enrichment of glycopeptides, up to 16 N-glycans were recognized. Significantly, this strategy facilitated the identification of glycopeptides containing fucosylated and sialylated glycans, meanwhile enabled the recognition of different N-glycan classes (high mannose, hybrid, and complex). Further application in the glycosylation analysis of adalimumab and bevacizumab resulted in 19 and 8 N-glycans species, providing a more comprehensive insight into their glycosylation modification status. We demonstrated the benefits of an integrated strategy in characterizing various N-glycans of mAb therapeutics and offer an alternative approach for their quality control at the intact glycopeptides level.

An Integrated Strategy Reveals Complex Glycosylation of Erythropoietin Using Mass Spectrometry.

The characterization of therapeutic glycoproteins is challenging due to the structural heterogeneity of the therapeutic protein glycosylation. This study presents an in-depth analytical strategy for glycosylation of first-generation erythropoietin (epoetin beta), including a developed mass spectrometric workflow for N-glycan analysis, bottom-up mass spectrometric methods for site-specific N-glycosylation, and a LC-MS approach for O-glycan identification. Permethylated N-glycans, peptides, and enriched glycopeptides of erythropoietin were analyzed by nanoLC-MS/MS, and de-N-glycosylated erythropoietin was measured by LC-MS, enabling the qualitative and quantitative analysis of glycosylation and different glycan modifications (e.g., phosphorylation and O-acetylation). The newly developed Python scripts enabled the identification of 140 N-glycan compositions (237 N-glycan structures) from erythropoietin, especially including 8 phosphorylated N-glycan species. The site-specificity of N-glycans was revealed at the glycopeptide level by pGlyco software using different proteases. In total, 114 N-glycan compositions were identified from glycopeptide analysis. Moreover, LC-MS analysis of de-N-glycosylated erythropoietin species identified two O-glycan compositions based on the mass shifts between non-O-glycosylated and O-glycosylated species. Finally, this integrated strategy was proved to realize the in-depth glycosylation analysis of a therapeutic glycoprotein to understand its pharmacological properties and improving the manufacturing processes.

Analysis of Monoclonal Antibody Glycopeptides by Capillary Electrophoresis-Mass Spectrometry Coupling (CE-MS).

Glycosylation is a crucial posttranslational modification (PTM) that might affect the safety and efficacy of monoclonal antibodies (mAbs). Capillary electrophoresis-mass spectrometry (CE-MS) enables the characterization of the primary structure of mAbs. A bottom-up proteomic workflow is designed to provide detailed information about the glycosylation. In this chapter, we describe the validated experimental protocol applied for the characterization and relative quantification of mAbs N-glycosylation at the glycopeptide level.

Lectin and Liquid Chromatography-Based Methods for Immunoglobulin (G) Glycosylation Analysis.

Immunoglobulin (Ig) glycosylation has been shown to dramatically affect its structure and effector functions. Ig glycosylation changes have been associated with different diseases and show a promising biomarker potential for diagnosis and prognosis of disease advancement. On the other hand, therapeutic biomolecules based on structural and functional features of Igs demand stringent quality control during the production process to ensure their safety and efficacy. Liquid chromatography (LC) and lectin-based methods are routinely used in Ig glycosylation analysis complementary to other analytical methods, e.g., mass spectrometry and capillary electrophoresis. This chapter covers analytical approaches based on LC and lectins used in low- and high-throughput N- and O-glycosylation analysis of Igs, with the focus on immunoglobulin G (IgG) applications. General principles and practical examples of the most often used LC methods for Ig purification are described, together with typical workflows for N- and O-glycan analysis on the level of free glycans, glycopeptides, subunits, or intact Igs. Lectin chromatography is a historical approach for the analysis of lectin-carbohydrate interactions and glycoprotein purification but is still being used as a valuable tool in Igs purification and glycan analysis. On the other hand, lectin microarrays have found their application in the rapid screening of glycan profiles on intact proteins.

Site-specific N-glycosylation Characterization of Recombinant SARS-CoV-2 Spike Proteins

AbstractThe glycoprotein spike (S) on the surface of severe acute respiratory syndrome coronavirus (SARS-CoV-2) is a determinant for viral invasion and host immune response. Herein, we characterized the site-specific N-glycosylation of S protein at the level of intact glycopeptides. All 22 potential N-glycosites were identified in the S-protein protomer and were found to be preserved among the 753 SARS-CoV-2 genome sequences. The glycosites exhibited glycoform heterogeneity as expected for a human cell-expressed protein subunit. We identified masses that correspond to 157 N-glycans, primarily of the complex type. In contrast, the insect cell-expressed S protein contained 38 N-glycans, completely of the high-mannose type. Our results revealed that the glycan types were highly determined by the differential processing of N-glycans among human and insect cells, regardless of the glycosites’ location. Moreover, the N-glycan compositions were conserved among different sizes of subunits. Our study indicates that the S protein N-glycosylation occurs regularly at each site, albeit the occupied N-glycans were diverse and heterogenous. This N-glycosylation landscape and the differential N-glycan patterns among distinct host cells are expected to shed light on the infection mechanism and present a positive view for the development of vaccines and targeted drugs.

Quantitative N-glycoproteomics using stable isotopic diethyl labeling

Protein N-glycosylation plays an essential role on cancers and other pathological processes. Its structural and functional studies rely on complete qualitative and quantitative information. Thus, it is important to quantify differentially expressed intact N-glycopeptides (DEGPs) at their molecular level. Here we report our application of stable isotopic diethyl labeling (SIDE) of amino groups for relative quantitation of intact N-glycopeptides. The amino groups from both the N-terminal and lysine residues of N-glycopeptides were diethylated with XH3XHO (X = 13C or C) and NaBH3CN. A linear quantitation dynamic range up to 50-fold was obtained with R2 = 0.9985 with intact N-glycopeptides from standard glycoprotein ribonuclease B (RNase B). In proof-of-principle comparative N-glycoproteomics study of aberrant N-glycosylation of gastric cancer tissues vs. adjacent tissues using SIDE, 644 DEGPs (≥1.5-fold change, p < 0.05, p was calculated using t-test) were discovered. With its accuracy and big dynamic range, SIDE can be applied to quantitative study of any aberrant glycosylation at the intact glycopeptide level.

Identifying Sialylation Linkages at the Glycopeptide Level by Glycosyltransferase Labeling Assisted Mass Spectrometry (GLAMS).

Precise assignment of sialylation linkages at the glycopeptide level is of importance in bottom-up glycoproteomics and an indispensable step to understand the function of glycoproteins in pathogen-host interactions and cancer progression. Even though some efforts have been dedicated to the discrimination of α2,3/α2,6-sialylated isomers, unambiguous identification of sialoglycopeptide isomers is still needed. Herein, we developed an innovative glycosyltransferase labeling assisted mass spectrometry (GLAMS) strategy. After specific enzymatic labeling, oxonium ions from higher-energy C-trap dissociation (HCD) fragmentation of α2,3-sailoglycopeptides then generate unique reporters to distinctly differentiate those of α2,6-sailoglycopeptide isomers. With this strategy, a total of 1236 linkage-specific sialoglycopeptides were successfully identified from 161 glycoproteins in human serum.