Gain-of-glycosylation in breast multi-drug-resistant MCF-7 adenocarcinoma cells and cancer stem cells characterized by site- and structure-specific N-glycoproteomics.

N-linked glycosylation (N-glycosylation) is a common protein post-translational modification, occurring on more than half of mammalian proteins; in striking contract with small molecule modifications (such as methylation, phosphorylation) with only single structures, N-glycosylation has multiple dimensional structural features (monosaccharide composition, sequence, linkage, anomer), which generates enormous N-glycan structures; and these structures widely regulate protein structure and functions. For the modification site, N-glycosylation occurs on the Asn residue among the consensus N-X-S/T/C (X≠P) motif; mutation-originated amino acid change may lead to loss of such an original motif and thus loss-of-glycosylation (LoG) or gain of such a new motif and thus gain-of-glycosylation (GoG). Both LoG and GoG generates new structures and functions of glycoproteins, which has been observed in the S protein of SARS-Cov-2 as well as malignant diseases. Here we report our glycoproteome-wide qualitative N-glycoproteomics characterization of GoGs in breast cancer Adriamycin drug resistance (ADR) cells (MCF-7/ADR) and cancer stem cells (MCF-7/ADR CSCs); comprehensive N-glycosite and N-glycan structure information at the intact N-glycopeptide level were reported.

Sialic acid linkage-specific quantitative N-glycoproteomics using selective alkylamidation and multiplex TMT-labeling.

Protein sialylation participates many biological processes in a linkage-specific manner, and aberrant sialylation has been associated with many malignant diseases. Mass spectrometry-based quantitative N-glycoproteomics has been widely adopted for quantitative analysis of aberrant sialylation, yet multiplexing method at intact N-glycopeptides level is still lacking. Here we report our study of sialic acid linkage-specific quantitative N-glycoproteomics using selective alkylamidation and multiplex tandem mass tags (TMT)-labeling. With lung cancer as a model system, differential sialylation in cancer tissues relative to adjacent non-tumor tissues was characterized at the intact N-glycopeptide level with N-glycosite information. TMT-labeled intact N-glycopeptides with and without sialic acid alkylamidation were subject to reversed-phase liquid chromatography-nano-electron spray ionization-tandem mass spectrometry (RPLC-nanoESI-MS/MS) analysis to provide comprehensive characterization of N-glycosylation with and without sialic acid at the intact N-glycopeptide level with structure and N-glycosite. In this study, 6384 intact N-glycopeptides without sialylation were identified and 521 differentially expressed intact N-glycopeptides from 254 intact N-glycoproteins were quantified. Eight intact N-glycoproteins responsible for N-glycan biosynthesis were identified as glycosyltransferases. In total, 307 sialylated intact N-glycopeptides with linkage-specific sialic acid residues were identified together with 29 N-glycans with α2,6-linked sialic acids and 55 N-glycans with α2,3-linked sialic acids. Intact N-glycoproteins with α2,6-sialylation were associated with coronavirus disease-(COVID)-19. Additionally, many types of N-glycosylation including terminal N-galactosylation, core and/or branch fucosylation, α2,6-sialylation and terminal bisecting N-acetylglucosamine were identified and quantified in intact N-glycoproteins from immunoglobulin family.

Serum N-glycomic profiling may provide potential signatures for surveillance of COVID-19.

Disease development and progression are often associated with aberrant glycosylation, indicating that changes in biological fluid glycome may potentially serve as disease signatures. The corona virus disease-2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) represents a significant threat to global human health. However, the effect of SARS-CoV-2 infection on the overall serum N-glycomic profile has been largely unexplored. Here, we extended our 96-well-plate-based high-throughput, high-sensitivity N-glycan profiling platform further with the aim of elucidating potential COVID-19-associated serum N-glycomic alterations. Use of this platform revealed both similarities and differences between the serum N-glycomic fingerprints of COVID-19 positive and control cohorts. Although there were no specific glycan peaks exclusively present or absent in COVID-19 positive cohort, this cohort showed significantly higher levels of glycans and variability. On the contrary, the overall N-glycomic profiles for healthy controls were well-contained within a narrow range. From the serum glycomic analysis, we were able to deduce changes in different glycan subclasses sharing certain structural features. Of significance was the hyperbranched and hypersialylated glycans and their derived glycan subclass traits. T-distributed stochastic neighbor embedding and hierarchical heatmap clustering analysis were performed to identify 13 serum glycomic variables that potentially distinguished the COVID-19 positive from healthy controls. Such serum N-glycomic changes described herein may indicate or correlate to the changes in serum glycoproteins upon COVID-19 infection. Furthermore, mapping the serum N-glycome following SARS-CoV-2 infection may help us better understand the disease and enable "Long-COVID" surveillance to capture the full spectrum of persistent symptoms.

Online Hydrophilic Interaction Chromatography (HILIC) Enhanced Top-Down Mass Spectrometry Characterization of the SARS-CoV-2 Spike Receptor-Binding Domain.

SARS-CoV-2 cellular infection is mediated by the heavily glycosylated spike protein. Recombinant versions of the spike protein and the receptor-binding domain (RBD) are necessary for seropositivity assays and can potentially serve as vaccines against viral infection. RBD plays key roles in the spike protein's structure and function, and thus, comprehensive characterization of recombinant RBD is critically important for biopharmaceutical applications. Liquid chromatography coupled to mass spectrometry has been widely used to characterize post-translational modifications in proteins, including glycosylation. Most studies of RBDs were performed at the proteolytic peptide (bottom-up proteomics) or released glycan level because of the technical challenges in resolving highly heterogeneous glycans at the intact protein level. Herein, we evaluated several online separation techniques: (1) C2 reverse-phase liquid chromatography (RPLC), (2) capillary zone electrophoresis (CZE), and (3) acrylamide-based monolithic hydrophilic interaction chromatography (HILIC) to separate intact recombinant RBDs with varying combinations of glycosylations (glycoforms) for top-down mass spectrometry (MS). Within the conditions we explored, the HILIC method was superior to RPLC and CZE at separating RBD glycoforms, which differ significantly in neutral glycan groups. In addition, our top-down analysis readily captured unexpected modifications (e.g., cysteinylation and N-terminal sequence variation) and low abundance, heavily glycosylated proteoforms that may be missed by using glycopeptide data alone. The HILIC top-down MS platform holds great potential in resolving heterogeneous glycoproteins for facile comparison of biosimilars in quality control applications.

GproDIA enables data-independent acquisition glycoproteomics with comprehensive statistical control.

Large-scale profiling of intact glycopeptides is critical but challenging in glycoproteomics. Data independent acquisition (DIA) is an emerging technology with deep proteome coverage and accurate quantitative capability in proteomics studies, but is still in the early stage of development in the field of glycoproteomics. We propose GproDIA, a framework for the proteome-wide characterization of intact glycopeptides from DIA data with comprehensive statistical control by a 2-dimentional false discovery rate approach and a glycoform inference algorithm, enabling accurate identification of intact glycopeptides using wide isolation windows. We further utilize a semi-empirical spectrum prediction strategy to expand the coverage of spectral libraries of glycopeptides. We benchmark our method for N-glycopeptide profiling on DIA data of yeast and human serum samples, demonstrating that DIA with GproDIA outperforms the data-dependent acquisition-based methods for glycoproteomics in terms of capacity and data completeness of identification, as well as accuracy and precision of quantification. We expect that this work can provide a powerful tool for glycoproteomic studies.

Integrated Chemoenzymatic Approach to Streamline the Assembly of Complex Glycopeptides in the Liquid Phase.

Glycosylation of proteins is a complicated post-translational modification. Despite the significant progress in glycoproteomics, accurate functions of glycoproteins are still ambiguous owing to the difficulty in obtaining homogeneous glycopeptides or glycoproteins. Here, we describe a streamlined chemoenzymatic method to prepare complex glycopeptides by integrating hydrophobic tag-supported chemical synthesis and enzymatic glycosylations. The hydrophobic tag is utilized to facilitate peptide chain elongation in the liquid phase and expeditious product separation. After removal of the tag, a series of glycans are installed on the peptides via efficient glycosyltransferase-catalyzed reactions. The general applicability and robustness of this approach are exemplified by efficient preparation of 16 well-defined SARS-CoV-2 O-glycopeptides, 4 complex MUC1 glycopeptides, and a 31-mer glycosylated glucagon-like peptide-1. Our developed approach will open up a new range of easy access to various complex glycopeptides of biological importance.

Nanopore-Based Single-Entity Electrochemistry for the Label-Free Monitoring of Single-Molecule Glycoprotein-Boronate Affinity Interaction and Its Sensing Application.

Nanopipettes provide a promising confined space that enables advances in single-molecule analysis, and their unique conical tubular structure is also suitable for single-cell analysis. In this work, functionalized-nanopore-based single-entity electrochemistry (SEE) analysis tools were developed for the label-free monitoring of single-molecule glycoprotein-boronate affinity interaction for the first time, and immunoglobulin G (IgG, one of the important biomarkers for many diseases such as COVID-19 and cancers) was employed as the model glycoprotein. The principle of this method is based on a single glycoprotein molecule passing through 4-mercaptophenylboronic acid (4-MPBA)-modified nanopipettes under a bias voltage and in the meantime interacting with the boronate group from modified 4-MPBA. This translocation and affinity interaction process can generate distinguishable current blockade signals. Based on the statistical analysis of these signals, the equilibrium association constant (κa) of single-molecule glycoprotein-boronate affinity interaction was obtained. The results show that the κa of IgG in the confined nanopore at the single-molecule level is much larger than that measured in the open system at the ensemble level, which is possibly due to the enhanced multivalent synergistic binding in the restricted space. Moreover, the functionalized-nanopore-based SEE analysis tools were further applied for the label-free detection of IgG, and the results indicate that our method has potential application value for the detection of glycoproteins in real samples, which also paves way for the single-cell analysis of glycoproteins.

Human Chorionic Gonadotropin and Related Peptides: Candidate Anti-Inflammatory Therapy in Early Stages of Sepsis.

Sepsis continues to be a major cause of morbidity, mortality, and post-recovery disability in patients with a wide range of non-infectious and infectious inflammatory disorders, including COVID-19. The clinical onset of sepsis is often marked by the explosive release into the extracellular fluids of a multiplicity of host-derived cytokines and other pro-inflammatory hormone-like messengers from endogenous sources ("cytokine storm"). In patients with sepsis, therapies to counter the pro-inflammatory torrent, even when administered early, typically fall short. The major focus of our proposed essay is to promote pre-clinical studies with hCG (human chorionic gonadotropin) as a potential anti-inflammatory therapy for sepsis.

Glycomics-informed glycoproteomic analysis of site-specific glycosylation for SARS-CoV-2 spike protein.

This protocol describes an integrated approach for analyzing site-specific N- and O-linked glycosylation of SARS-CoV-2 spike protein by mass spectrometry. Glycoproteomics analyzes intact glycopeptides to examine site-specific microheterogeneity of glycoproteins. Glycomics provides structural characterization on any glycan assignments by glycoproteomics. This procedure can be modified and applied to a variety of N- and/or O-linked glycoproteins. Combined with bioinformatics, the glycomics-informed glycoproteomics may be useful in generating 3D molecular dynamics simulations of certain glycoproteins alone or interacting with one another. For complete details on the use and execution of this protocol, please refer to Zhao et al. (2020).

The Need for Community Standards to Enable Accurate Comparison of Glycoproteomics Algorithm Performance.

Protein glycosylation that mediates interactions among viral proteins, host receptors, and immune molecules is an important consideration for predicting viral antigenicity. Viral spike proteins, the proteins responsible for host cell invasion, are especially important to be examined. However, there is a lack of consensus within the field of glycoproteomics regarding identification strategy and false discovery rate (FDR) calculation that impedes our examinations. As a case study in the overlap between software, here as a case study, we examine recently published SARS-CoV-2 glycoprotein datasets with four glycoproteomics identification software with their recommended protocols: GlycReSoft, Byonic, pGlyco2, and MSFragger-Glyco. These software use different Target-Decoy Analysis (TDA) forms to estimate FDR and have different database-oriented search methods with varying degrees of quantification capabilities. Instead of an ideal overlap between software, we observed different sets of identifications with the intersection. When clustering by glycopeptide identifications, we see higher degrees of relatedness within software than within glycosites. Taking the consensus between results yields a conservative and non-informative conclusion as we lose identifications in the desire for caution; these non-consensus identifications are often lower abundance and, therefore, more susceptible to nuanced changes. We conclude that present glycoproteomics softwares are not directly comparable, and that methods are needed to assess their overall results and FDR estimation performance. Once such tools are developed, it will be possible to improve FDR methods and quantify complex glycoproteomes with acceptable confidence, rather than potentially misleading broad strokes.

Brilliant glycans and glycosylation: Seq and ye shall find.

Proteoglycosylation is the addition of monosaccharides or glycans to the protein peptide chain. This is a common post-translational modification of proteins with a variety of biological functions. At present, more than half of all biopharmaceuticals in clinic are modified by glycosylation. Most glycoproteins are potential drug targets and biomarkers for disease diagnosis. Therefore, in-depth study of glycan structure of glycoproteins will ultimately improve the sensitivity and specificity of glycoproteins for clinical disease detection. With the deepening of research, the function and application value of glycans and glycosylation has gradually emerged. This review systematically introduces the latest research progress of glycans and glycosylation. It encompasses six cancers, four viruses, and their latest discoveries in Alzheimer's disease, allergic diseases, congenital diseases, gastrointestinal diseases, inflammation, and aging.

Engineering of Janus-Like Dendrimers with Peptides Derived from Glycoproteins of Herpes Simplex Virus Type 1: Toward a Versatile and Novel Antiviral Platform.

Novel antiviral nanotherapeutics, which may inactivate the virus and block it from entering host cells, represent an important challenge to face viral global health emergencies around the world. Using a combination of bioorthogonal copper-catalyzed 1,3-dipolar alkyne/azide cycloaddition (CuAAC) and photoinitiated thiol-ene coupling, monofunctional and bifunctional peptidodendrimer conjugates were obtained. The conjugates are biocompatible and demonstrate no toxicity to cells at biologically relevant concentrations. Furthermore, the orthogonal addition of multiple copies of two different antiviral peptides on the surface of a single dendrimer allowed the resulting bioconjugates to inhibit Herpes simplex virus type 1 at both the early and the late stages of the infection process. The presented work builds on further improving this attractive design to obtain a new class of therapeutics.

Designing of Potential Polyvalent Vaccine Model for Respiratory Syncytial Virus by System Level Immunoinformatics Approaches.

BACKGROUND: Respiratory syncytial virus (RSV) infection is a public health epidemic, leading to around 3 million hospitalization and about 66,000 deaths each year. It is a life-threatening condition exclusive to children with no effective treatment. METHODS: In this study, we used system-level and vaccinomics approaches to design a polyvalent vaccine for RSV, which could stimulate the immune components of the host to manage this infection. Our framework involves data accession, antigenicity and subcellular localization analysis, T cell epitope prediction, proteasomal and conservancy evaluation, host-pathogen-protein interactions, pathway studies, and in silico binding affinity analysis. RESULTS: We found glycoprotein (G), fusion protein (F), and small hydrophobic protein (SH) of RSV as potential vaccine candidates. Of these proteins (G, F, and SH), we found 9 epitopes for multiple alleles of MHC classes I and II bear significant binding affinity. These potential epitopes were linked to form a polyvalent construct using AAY, GPGPG linkers, and cholera toxin B adjuvant at N-terminal with a 23.9 kDa molecular weight of 224 amino acid residues. The final construct was a stable, immunogenic, and nonallergenic protein containing cleavage sites, TAP transport efficiency, posttranslation shifts, and CTL epitopes. The molecular docking indicated the optimum binding affinity of RSV polyvalent construct with MHC molecules (-12.49 and -10.48 kcal/mol for MHC classes I and II, respectively). This interaction showed that a polyvalent construct could manage and control this disease. CONCLUSION: Our vaccinomics and system-level investigation could be appropriate to trigger the host immune system to prevent RSV infection.

DBCOVP: A database of coronavirus virulent glycoproteins.

Since the emergence of SARS-CoV-1 (2002), novel coronaviruses have emerged periodically like the MERS- CoV (2012) and now, the SARS-CoV-2 outbreak which has posed a global threat to public health. Although, this is the third zoonotic coronavirus breakout within the last two decades, there are only a few platforms that provide information about coronavirus genomes. None of them is specific for the virulence glycoproteins and complete sequence-structural features of these virulence factors across the betacoronavirus family including SARS-CoV-2 strains are lacking. Against this backdrop, we present DBCOVP (http://covp.immt.res.in/), the first manually-curated, web-based resource to provide extensive information on the complete repertoire of structural virulent glycoproteins from coronavirus genomes belonging to betacoronavirus genera. The database provides various sequence-structural properties in which users can browse and analyze information in different ways. Furthermore, many conserved T-cell and B-cell epitopes predicted for each protein are present that may perform a significant role in eliciting the humoral and cellular immune response. The tertiary structure of the epitopes together with the docked epitope-HLA binding-complex is made available to facilitate further analysis. DBCOVP presents an easy-to-use interface with in-built tools for similarity search, cross-genome comparison, phylogenetic, and multiple sequence alignment. DBCOVP will certainly be an important resource for experimental biologists engaged in coronavirus research studies and will aid in vaccine development.

Is the Rigidity of SARS-CoV-2 Spike Receptor-Binding Motif the Hallmark for Its Enhanced Infectivity? Insights from All-Atom Simulations.

The severe acute respiratory syndrome coronavirus (SARS-CoV-2) pandemic is setting the global health crisis of our time, causing a devastating societal and economic burden. An idiosyncratic trait of coronaviruses is the presence of spike glycoproteins on the viral envelope, which mediate the virus binding to specific host receptor, enabling its entry into the human cells. In spite of the high sequence identity of SARS-CoV-2 with its closely related SARS-CoV emerged in 2002, the atomic-level determinants underlining the molecular recognition of SARS-CoV-2 to the angiotensin-converting enzyme 2 (ACE2) receptor and, thus, the rapid virus spread into human body, remain unresolved. Here, multi-microsecond-long molecular dynamics simulations enabled us to unprecedentedly dissect the key molecular traits liable of the higher affinity/specificity of SARS-CoV-2 toward ACE2 as compared to SARS-CoV. This supplies a minute per-residue contact map underlining its stunningly high infectivity. Harnessing this knowledge is pivotal for urgently developing effective medical countermeasures to face the ongoing global health crisis.

Vulnerabilities in coronavirus glycan shields despite extensive glycosylation.

Severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) coronaviruses (CoVs) are zoonotic pathogens with high fatality rates and pandemic potential. Vaccine development focuses on the principal target of the neutralizing humoral immune response, the spike (S) glycoprotein. Coronavirus S proteins are extensively glycosylated, encoding around 66-87 N-linked glycosylation sites per trimeric spike. Here, we reveal a specific area of high glycan density on MERS S that results in the formation of oligomannose-type glycan clusters, which were absent on SARS and HKU1 CoVs. We provide a comparison of the global glycan density of coronavirus spikes with other viral proteins including HIV-1 envelope, Lassa virus glycoprotein complex, and influenza hemagglutinin, where glycosylation plays a known role in shielding immunogenic epitopes. Overall, our data reveal how organisation of glycosylation across class I viral fusion proteins influence not only individual glycan compositions but also the immunological pressure across the protein surface.