In-depth characterization of protein N-glycosylation for a COVID-19 variant-design vaccine spike protein.

COVID-19 is caused by SARS-CoV-2 infection and remains one of the biggest pandemics around the world since 2019. Vaccination has proved to be an effective way of preventing SARS-CoV-2 infection and alleviating the hospitalization burden. Among different forms of COVID-19 vaccine design, the spike protein of SARS-CoV-2 virus is widely used as a candidate vaccine antigen. As a surface protein on the virus envelop, the spike was reported to be heavily N-glycosylated and glycosylation had a great impact on its immunogenicity and efficacy. Besides, N-glycosylation might vary greatly on different expression systems and sequence variant designs. Therefore, comprehensive analysis of spike N-glycosylation is of great significance for better vaccine understanding and quality control. In this study, full characterization of N-glycosylation was performed for a Chinese Hamster Ovary (CHO) cell expressed variant-designed spike protein. The spike protein featured the latest six-proline substitution design together with the incorporation of a combination of mutation sites. Trypsin and Glu-C digestion coupled with PNGase F strategies were adopted, and effective LC-MS/MS methods were applied to analyze samples. As a result, a total of 19 N-glycosites were identified in the recombinant pike protein at intact N-glycopeptide level. Quantitative analysis of released glycan by LC-MS/MS was also performed, and 31 high-abundance N-glycans were identified. Sequencing analysis of glycan was further provided to assist glycan structure confirmation. Moreover, all of the analyses were performed on three consecutive manufactured batches and the glycosylation results on both glycosite and glycans showed good batch-to-batch consistency. Thus, the reported analytical strategy and N-glycosylation information may well facilitate studies on SARS-CoV-2 spike protein analysis and quality studies.

gQuant, an Automated Tool for Quantitative Glycomic Data Analysis.

MALDI-MS-based glycan isotope labeling methods have been effectively and widely used for quantitative glycomics. However, interpretation of the data produced by MALDI-MS is inaccurate and tedious because the bioinformatic tools are inadequate. In this work, we present gQuant, an automated tool for MALDI-MS-based glycan isotope labeling data processing. gQuant was designed with a set of dedicated algorithms to improve the efficiency, accuracy and convenience of quantitation data processing. When tested on the reference data set, gQuant showed a fast processing speed, as it was able to search the glycan data of model glycoproteins in a few minutes and reported more results than the manual analysis did. The reported quantitation ratios matched well with the experimental glycan mixture ratios ranging from 1:10 to 10:1. In addition, gQuant is fully open-source and is coded in Python, which is supported by most operating systems, and it has a user-friendly interface. gQuant can be easily adapted by users for specific experimental designs, such as specific glycan databases, different derivatization types and relative quantitation designs and can thus facilitate fast glycomic quantitation for clinical sample analysis using MALDI-MS-based stable isotope labeling.

OGP: A Repository of Experimentally Characterized O-glycoproteins to Facilitate Studies on O-glycosylation.

Numerous studies on cancers, biopharmaceuticals, and clinical trials have necessitated comprehensive and precise analysis of protein O-glycosylation. However, the lack of updated and convenient databases deters the storage of and reference to emerging O-glycoprotein data. To resolve this issue, an O-glycoprotein repository named OGP was established in this work. It was constructed with a collection of O-glycoprotein data from different sources. OGP contains 9354 O-glycosylation sites and 11,633 site-specific O-glycans mapping to 2133 O-glycoproteins, and it is the largest O-glycoprotein repository thus far. Based on the recorded O-glycosylation sites, an O-glycosylation site prediction tool was developed. Moreover, an OGP-based website is already available (https://www.oglyp.org/). The website comprises four specially designed and user-friendly modules: statistical analysis, database search, site prediction, and data submission. The first version of OGP repository and the website allow users to obtain various O-glycoprotein-related information, such as protein accession Nos., O-glycosylation sites, O-glycopeptide sequences, site-specific O-glycan structures, experimental methods, and potential O-glycosylation sites. O-glycosylation data mining can be performed efficiently on this website, which will greatly facilitate related studies. In addition, the database is accessible from OGP website (https://www.oglyp.org/download.php).

Development of a Computational Tool for Automated Interpretation of Intact O-Glycopeptide Tandem Mass Spectra from Single Proteins.

Precise and automated analysis of site-specific O-glycosylation on single proteins is crucial for comprehensive characterization of some important glycoproteins, such as tumor biomarkers and recombinant drug proteins. Mass spectrometry has been proven to be a powerful technique for protein sequencing and N-glycosylation analysis. However, challenges remain in developing computational tools for intact O-glycopeptide analysis, which has greatly hindered the development of mass-spectrometry-based O-glycosylation analysis. Herein, an integrated strategy together with a dedicated automated computational tool termed AOGP was developed for intact O-glycopeptide analysis on single proteins. AOGP utilized de novo sequencing for O-glycans and a database search strategy for peptide backbones. The false discovery rate (FDR) of the identification results was controlled and validated by a mixed Gaussian distribution estimation method. AOGP exhibited superior performance in identifying intact O-glycopeptides of the human erythropoietin with a total of 188 O-glycopeptide spectra reported under 1% FDR. AOGP is developed in Python, is fully open-sourced, and is equipped with a user-friendly interface. Such an easy-operating and robust tool would greatly facilitate O-glycosylation analysis on single proteins in tumor biomarker and recombinant drug protein development.

Straightforward and Highly Efficient Strategy for Hepatocellular Carcinoma Glycoprotein Biomarker Discovery Using a Nonglycopeptide-Based Mass Spectrometry Pipeline.

Efficient detection of aberrant glycoproteins in serum is particularly important for biomarker discovery. However, direct quantitation of glycoproteins in serum remains technically challenging because of the extraordinary complexity of the serum proteome. In the current work, we proposed a straightforward and highly efficient strategy by using the nonglycopeptides releasing from the specifically enriched glycoproteins for targeted glycoprotein quantification. With this so-called nonglycopeptide-based mass spectrometry (NGP-MS) strategy, a powerful and nondiscriminatory pipeline for hepatocellular carcinoma (HCC) glycoprotein biomarker discovery, verification, and validation has been developed. First, a data set of 234 NGPs was strictly established for multiple-reaction monitoring (MRM) quantification in serum. Second, the NGPs enriched from 20 HCC serum mixtures and 20 normal serum mixtures were labeled with mTRAQ reagents (Δ0 and Δ8, respectively) to find the differentially expressed glycoproteins in HCC. A total of 97 glycoprotein candidates were preliminarily screened and submitted for absolute quantitation with NGP-based stable-isotope-labeled (SID)-MRM in the individual samples of 38 HCC serum and 24 normal controls. Finally, 21 glycoproteins were absolutely quantified with high quality. The diagnostic sensitivity results showed that three glycoproteins, ß-2-glycoprotein 1 (APOH), α-1-acid glycoprotein 2 (ORM2), and complement C3 (C3), could be used for the discrimination between HCC patients and healthy people. A novel glycoprotein biomarker panel [APOH, ORM2, C3, and α-fetoprotein (AFP)] has proven to outperform AFP, the known HCC serum biomarker, alone, in this study. We believe that this strategy and the panel of glycoproteins might hold great clinical value for HCC detection in the future.

A multi-parallel N-glycopeptide enrichment strategy for high-throughput and in-depth mapping of the N-glycoproteome in metastatic human hepatocellular carcinoma cell lines.

N-glycosylation is deeply involved in many biological processes, and approximately 50% of mammalian proteins are predicted to be glycosylated. Many large-scale studies have been carried out to reveal the glycosylation status involved in different physiological pathologies across species. However, the lack of a highly specific and high-throughput N-glycosylated enrichment method not only results in extended time requirements but also limits the depth of mapping when handling a large number of samples. In this study, we firstly optimized traditional zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC) enrichment and found that using of 70% acetonitrile (ACN), 0.1% trifluoroacetic acid (TFA) as the enrichment buffer, 2800 g as the washing speed and 600 µL as the washing volume achieved the best specificity, which is higher than 75%. On this basis, we developed a multi-parallel enrichment strategy assisted by a filter-coated 96-well plate, which achieved high specificity and high throughput simultaneously. This strategy allowed us to enrich large numbers of fractionated samples from hepatocellular carcinoma (HCC) cell lines in less than 2 h. Its good specificity helped us achieve in-depth mapping of the N-glycoproteome in metastatic HCC cell lines. A total of 5466 N-glycosites from 2383 glycoproteins were identified, among which 1900 N-glycosites were unannotated in UniProt. The in-depth glycoproteome mapping provides insight into the N-glycosylation status in HCC cell lines with differences in metastatic potential and contributes to biomarker discovery.

pGlyco 2.0 enables precision N-glycoproteomics with comprehensive quality control and one-step mass spectrometry for intact glycopeptide identification.

The precise and large-scale identification of intact glycopeptides is a critical step in glycoproteomics. Owing to the complexity of glycosylation, the current overall throughput, data quality and accessibility of intact glycopeptide identification lack behind those in routine proteomic analyses. Here, we propose a workflow for the precise high-throughput identification of intact N-glycopeptides at the proteome scale using stepped-energy fragmentation and a dedicated search engine. pGlyco 2.0 conducts comprehensive quality control including false discovery rate evaluation at all three levels of matches to glycans, peptides and glycopeptides, improving the current level of accuracy of intact glycopeptide identification. The N-glycoproteome of samples metabolically labeled with 15N/13C were analyzed quantitatively and utilized to validate the glycopeptide identification, which could be used as a novel benchmark pipeline to compare different search engines. Finally, we report a large-scale glycoproteome dataset consisting of 10,009 distinct site-specific N-glycans on 1988 glycosylation sites from 955 glycoproteins in five mouse tissues.Protein glycosylation is a heterogeneous post-translational modification that generates greater proteomic diversity that is difficult to analyze. Here the authors describe pGlyco 2.0, a workflow for the precise one step identification of intact N-glycopeptides at the proteome scale.

Value of three-dimensional strain parameters for predicting left ventricular remodeling after ST-elevation myocardial infarction.

This study was to evaluate the value of multi-directional strain parameters derived from three-dimensional (3D) speckle tracking echocardiography (STE) for predicting left ventricular (LV) remodeling after ST-elevation myocardial infarction (STEMI) treated with primary percutaneous coronary intervention (PCI) compared with that of two-dimensional (2D) global longitudinal strain (GLS). A total of 110 patients (mean age, 54 ± 9 years) after STEMI treated with primary PCI were enrolled in our study. At baseline (within 24 h after PCI), standard 2D echocardiography, 2D STE and 3D STE were performed to acquire the conventional echocardiographic parameters and strain parameters. At 3-month follow-up, standard 2D echocardiography was repeated to all the patients to determine LV remodeling, which was defined as a 20% increase in LV end-diastolic volume. At 3-month follow-up, LV remodeling occurred in 26 patients (24%). Compared with patients without LV remodeling, patients with remodeling had significantly reduced 2D GLS (-12.5 ± 3.2% vs -15.0 ± 3.1%, p < 0.001), 3D GLS (-9.9 ± 2.2% vs -13.1 ± 2.7%, p < 0.001), 3D global area strain (GAS) (-20.3 ± 3.9% vs -23.3 ± 4.8%, p = 0.005) and 3D global radial strain (GRS) (29.0 ± 7.4% vs 34.3 ± 8.5%, p = 0.007) at baseline, but there is no significant difference in 3D global circumferential strain (GCS) (-12.7 ± 2.9% vs -13.0 ± 3.2%, p = 0.822). Separated multivariate analysis shows that 2D GLS, 3D GLS, 3D GAS and 3D GRS all can be independent predictors of LV remodeling. However, receiver-operating characteristic curve analysis showed that the area under the curve of 3D GLS (0.82) for predicting LV remodeling was significantly higher than that of 2D GLS (0.72, p = 0.034), 3D GAS (0.68, p < 0.001) and 3D GRS (0.68, p < 0.001). In patients after STEMI, 2D GLS, 3D GLS, 3D GAS and 3D GRS but not 3D GCS measured after primary PCI are independent predictors of LV remodeling and 3D GLS is the most powerful predictor among them.

Highly Selective Enrichment of Glycopeptides Based on Zwitterionically Functionalized Soluble Nanopolymers.

Efficient glycopeptides enrichment prior to mass spectrometry analysis is essential for glycoproteome study. ZIC-HILIC (zwitterionic hydrophilic interaction liquid chromatography) based glycopeptides enrichment approaches have been attracting more attention for several benefits like easy operating, high enrichment specificity and intact glycopeptide retained. In this study, Poly (amidoamine) dendrimer (PAMAM) was adopted for the synthesis of zwitterionically functionalized (ZICF) materials for glycopeptide enrichment. The multiple branched structure and good solubility of ZICF-PAMAM enables a sufficient interaction with glycopeptides. The ZICF-PAMAM combined with the FASP-mode enrichment strategy exhibits more superior performance compared with the existing methods. It has the minimum detectable concentration of femtomolar level and high recovery rate of over 90.01%, and can efficiently enrich glycopeptides from complex biological samples even for merely 0.1 µL human serum. The remarkable glycopeptides enrichment capacity of ZICF-PAMAM highlights the potential application in in-depth glycoproteome research, which may open up new opportunities for the development of glycoproteomics.

Glycan reducing end dual isotopic labeling (GREDIL) for mass spectrometry-based quantitative N-glycomics.

A general and effective enzymatic labeling method, termed glycan reducing end dual isotopic labeling (GREDIL), was developed for mass spectrometry-based quantitative N-glycomics.

PNGase F-mediated incorporation of (18)O into glycans for relative glycan quantitation.

PNGase F-catalyzed glycosylation site (18)O-labeling is a widely used method for glycoprotein quantitation owing to its efficiency and simplicity. However, PNGase F-catalyzed glycan (18)O-labeling, which offers advantages for glycomics, has not yet been developed. In this study, PNGase F-mediated incorporation of (18)O into glycans during the N-glycan release from glycoproteins by PNGase F was finally realized, named as PCGOL (PNGase F-catalyzed glycan (18)O-labeling), which offers a potential strategy for relative glycan quantitation. This new method showed good linearity and high reproducibility within at least 2 orders of magnitude in the dynamic range. Furthermore, PCGOL combined with our previously developed TOSIL method (tandem (18)O stable isotope labeling for N-glycoproteome quantitation) can be used for comprehensive N-glycosylation quantification, achieving simultaneous quantification of glycans, glycopeptides and glycoproteins in a single workflow, which was also used to analyze glycosylation changes in immunoglobulin G (IgG) associated with hepatocellular carcinoma in the present work.

Discovery and confirmation of O-GlcNAcylated proteins in rat liver mitochondria by combination of mass spectrometry and immunological methods.

O-linked ß-N-acetylglucosamine (O-GlcNAc) is an important post-translational modification (PTM) consisting of a single N-acetylglucosamine moiety attached via an O-ß-glycosidic linkage to serine and threonine residues. Glycosylation with O-GlcNAc occurs on myriad nuclear and cytosolic proteins from almost all functional classes. However, with respect to O-GlcNAcylated proteins special in mitochondria, little attention has been paid. In this study, we combined mass spectrometry and immunological methods to perform global exploration of O-GlcNAcylated proteins specific in mitochondria of rat liver. First, highly purified mitochondrial proteins were obviously shown to be O-GlcNAcylated by immunoblot profiling. Then, ß-elimination followed by Michael Addition with Dithiothreitol (BEMAD) treatment and LC-MS/MS were performed to enrich and identify O-GlcNAcylated mitochondrial proteins, resulting in an unambiguous assignment of 14 O-GlcNAcylation sites, mapping to 11 O-GlcNAcylated proteins. Furthermore, the identified O-GlcNAcylated mitochondrial proteins were fully validated by both electron transfer dissociation tandem mass spectrometry (ETD/MS/MS) and western blot. Thus, for the first time, our study definitely not only identified but also validated that some mitochondrial proteins in rat liver are O-GlcNAcylated. Interestingly, all of these O-GlcNAcylated mitochondrial proteins are enzymes, the majority of which are involved in a wide variety of biological processes, such as urea cycle, tricarboxylic acid cycle and lipid metabolism, indicating a role for protein O-GlcNAcylation in mitochondrial function.

[Preliminary study of apoptotic inhibition and its molecular mechanism of dexamethasone on cisplatin-induced human lung adenocarcinoma cell line SPCA/I].

OBJECTIVE: To study the apoptotic inhibition and its molecular mechanism of dexamethasone (Dex) on cisplatin (CDDP)-induced human lung adenocarcinoma cells. METHODS: The human lung adenocarcinoma cell The human lung adenocarcinoma cell line, SPCA/I, was pre-cultured in vitro for 24 hours with Dex in different concentration and then different concentration of CDDP was added. The cells were cultured for another 48 hours. The survival rate of the cells was determined by MTT colorimetry. The appototic rate of SPCA/I cells measured by flow cytometer. Using 1 micromol/ L Dex to stimulate the SPCA/I cells RNAs of the cells at different time points (1 h, 2 h, 4 h, 6 h, 12 h) were extracted respectively. Semi-quantitative RT-PCR technology was used to detect the expression of the serum and glucocorticoid-induced kinase (SGK-1) and mitogen-activated protein kinase phosphatase-1(MKP-1) in SPCA/I cells. Simultaneously the glucocorticoid receptor (GR) of the SPCA/I cell line cells were measured by using biotin-labeled anti-glucocorticoid receptor antibody with immunohistochemistry assay. RESULTS: SPCA/I cells showed resistance to CDDP-induced apoptosis while pre-cultured with Dex and the resistance intensity was Dex concentration-dependent. After Dex stimulating the SPCA/I cells, SGK-1 expressed increased and reached the peak at 12 h. But the expression of MKP-1 was not detected. Immunohistochemistry results showed that upregulated GR in SPCA/I cells after stimulation with Dex. The number of intracellular GR was significantly higher than that of control group. CONCLUSION: The experimental results in vitro demonstrated that Dex inhibits apoptosis on CDDP-induced human lung adenocarcinoma cell line, SPCA/I. This anti-apoptosis effect might due to Dex increasing the expression of SGK-1, an anti-apoptotic protein, in its downstream signal pathway through the increasement of intracellular GR of SPCA/I cells.

Enhanced N-glycosylation site exploitation of sialoglycopeptides by peptide IPG-IEF assisted TiO2 chromatography.

Playing an important role in a broad range of biological and pathological processes, sialylation has been drawing wide interest. The efficient sialoglycopeptides enrichment methods are therefore attracting considerable attention. In this paper, we first compared two conventional enrichment methods, lectin and TiO(2), and analyzed their characteristics. Furthermore, considering the highly negatively charged nature of sialic acids, we developed a new strategy, peptide immobilized pH gradient isoelectric focusing (IPG-IEF) assisted TiO(2) chromatography (PIAT), for the highly efficient enrichment of sialoglycopeptides. In this method, peptides were first separated into 24 fractions using peptide IPG-IEF. Sialoglycopeptides were relatively concentrated in low-pH fractions of the immobilized pH strips and were captured using TiO(2) chromatography. As a result, 614 N-glycosylation sites were identified in 582 sialoglycopeptides within 322 sialoglycoproteins from rat liver using PIAT. To our knowledge, this work represents one of the most comprehensive sialoglycoproteomic analyses in general and exhibits the largest database of sialoglycoproteome in rat liver currently. So the new strategy introduced here exhibits high efficiency and universality in the sialoglycopeptide enrichment, and is a powerful tool for sialoglycoproteome exploration.