Intact N-glycopeptides Research Articles

Distinct O-Acetylation Patterns of Serum Glycoproteins among Humans, Mice, and Rats.

O-Acetylation is a significant chemical modification of sialic acids on glycoproteins with diverse biological functions. As two important animal models, mice and rats have been widely used for various biomedical studies. In this study, we show that the sialic acid types and their O-acetylation patterns have large differences among serum glycoproteins of humans, rats, and mice. Based on intact N-glycopeptide analyses, all sialoglycopeptides in human sera were modified by Neu5Ac without any O-acetylation; 90% of sialoglycopeptides in rat sera were also modified by Neu5Ac, with more than 60% that were further O-acetylated. In contrast, 99% of sialoglycopeptides in mouse sera contained Neu5Gc including 12% in O-acetylated forms. Among all O-acetylated N-glycans, rat sera had hybrid glycans fivefold those of mouse sera, while mouse sera contained 5.5-fold core-fucosylated glycans and 4.6-31.5-fold mono-/penta-/hexa-antenna glycans compared to mice. The overall O-acetylation proportions of serum glycoproteins in rats were much higher than those in mice, and diverse O-acetylation proportions also commonly existed at different glycosites of the same glycoproteins. This study enhances our understanding of O-acetylated sialoglycan diversities and underscores the necessity of considering glycosylation profiles when selecting suitable animal models for various biomedical studies.

Investigation of adipocyte differentiation based on proteomics and intact N-glycopeptide modificationomics

ObjectiveTo investigate the role of N-glycosylation modification of proteins in adipocyte differentiation during the adipogenic process. MethodsSVF cells and adipocytes were analyzed for proteomics and intact N-glycopeptide modificationomics.Differential expression of proteins, glycoforms, and sites between the two groups was screened and subjected to Gene Ontology (GO) functional enrichment analysis, KEGG pathway enrichment analysis, and protein-protein interaction (PPI) network analysis. The top 20 most significantly differentially expressed adipogenic differentiation-related proteins were identified, and the most pronouncedly altered proteins were analyzed for glycoforms, glycan chains, and sites. ResultsProteomics analysis identified 39,392 peptides and 5208 proteins, while intact N-glycopeptide modification profiling identified 3293 intact glycopeptides, 426 proteins, and 161 glycan chains. Proteomics identified 2510 differentially expressed proteins, with CD36 (Cluster of Differentiation 36, CD36) significantly upregulated. In adipocytes, CD36 had 4 N-glycosylation sites: N79, N220, N320, N417, with N320 being a newly identified site. GO enrichment results indicated that CD36 is associated with fatty acid oxidation, lipid oxidation, and fatty acid uptake into cells. ConclusionMultiple proteins undergo N-glycosylation modification during adipocyte differentiation, with CD36, a fatty acid translocase, being significantly expressed in adipocytes. This suggests that N-glycosylation modification of CD36 may play a crucial role in adipocyte differentiation, providing a foundation for further investigation into the function of CD36 N-glycosylation in adipocyte differentiation.

Deep structure-level N-glycan identification using feature-induced structure diagnosis integrated with a deep learning model.

Being a widely occurring protein post-translational modification, N-glycosylation features unique multi-dimensional structures including sequence and linkage isomers. There have been successful bioinformatics efforts in N-glycan structure identification using N-glycoproteomics data; however, symmetric "mirror" branch isomers and linkage isomers are largely unresolved. Here, we report deep structure-level N-glycan identification using feature-induced structure diagnosis (FISD) integrated with a deep learning model. A neural network model is integrated to conduct the identification of featured N-glycan motifs and boosts the process of structure diagnosis and distinction for linkage isomers. By adopting publicly available N-glycoproteomics datasets of five mouse tissues (17,136 intact N-glycopeptide spectrum matches) and a consideration of 23 motif features, a deep learning model integrated with a convolutional autoencoder and a multilayer perceptron was trained to be capable of predicting N-glycan featured motifs in the MS/MS spectra with previously identified compositions. In the test of the trained model, a prediction accuracy of 0.8 and AUC value of 0.95 were achieved; 5701 previously unresolved N-glycan structures were assigned by matched structure-diagnostic ions; and by using anexplainable learning algorithm, two new fragmentation features of m/z = 674.25 and m/z = 835.28 were found to be significant to three N-glycan structure motifs with fucose, NeuAc, and NeuGc, proving the capability of FISD to discover new features in the MS/MS spectra.

GP-Marker facilitates the analysis of intact glycopeptide quantitative data at different levels.

Protein glycosylation is a highly heterogeneous post-translational modification that has been demonstrated to exhibit significant variations in various diseases. Due to the differential patterns observed in disease and healthy populations, the glycosylated proteins hold promise as early indicators for multiple diseases. With the continuous development of liquid chromatography-mass spectrometry (LC-MS) technology and spectrum analysis software, the sensitivity for the decipher of the tandem mass spectra of the glycopeptides carrying intact glycans, i.e., intact glycopeptides, enzymatic hydrolyzed from glycoproteins has been significantly improved. From quantified intact glycopeptides, the difference of protein glycosylation at multiple levels, e.g., glycoprotein, glycan, glycosite, and site-specific glycans, could be obtained for different samples. However, the manual analysis of the intact glycopeptide quantitative data at multiple levels is tedious and time consuming. In this study, we have developed a software tool named "GP-Marker" to facilitate large-scale data mining of spectra dataset of intact N-glycopeptide at multiple levels. This software provides a user-friendly and interactive interface, offering operational tools for machine learning to researchers without programming backgrounds. It includes a range of visualization plots displaying differential glycosylation and provides the ability to extract multi-level data analysis from intact glycopeptide data quantified by Glyco-Decipher.

Mass spectrometry-based structure-specific N-glycoproteomics and biomedical applications.

N-linked glycosylation is a common posttranslational modification of proteins that results in macroheterogeneity of the modification site. However, unlike simpler modifications, N-glycosylation introduces an additional layer of complexity with tens of thousands of possible structures arising from various dimensions, including different monosaccharide compositions, sequence structures, linking structures, isomerism, and three-dimensional conformations. This results in additional microheterogeneity of the modification site of N-glycosylation, i.e., the same N-glycosylation site can be modified with different glycans with a certain stoichiometric ratio. N-glycosylation regulates the structure and function of N-glycoproteins in a site- and structure-specific manner, and differential expression of N-glycosylation under disease conditions needs to be characterized through site- and structure-specific quantitative analysis. Numerous advanced methods ranging from sample preparation to mass spectrum analysis have been developed to distinguish N-glycan structures. Chemical derivatization of monosaccharides, online liquid chromatography separation and ion mobility spectrometry enable the physical differentiation of samples. Tandem mass spectrometry further analyzes the macro/microheterogeneity of intact N-glycopeptides through the analysis of fragment ions. Moreover, the development of search engines and AI-based software has enhanced our understanding of the dissociation patterns of intact N-glycopeptides and the clinical significance of differentially expressed intact N-glycopeptides. With the help of these modern methods, structure-specific N-glycoproteomics has become an important tool with extensive applications in the biomedical field.

Site-specific N-glycoproteomic analysis reveals up-regulated fucosylation in seminal plasma of asthenozoospermia.

N-linked glycoproteins are rich in seminal plasma, playing essential roles in supporting sperm function and fertilization process. The alteration of seminal plasma glycans and its correspond glycoproteins may lead to sperm dysfunction and even infertility. In present study, an integrative analysis of glycoproteomic and proteomic was performed to investigate the changes of site-specific glycans and glycoptoteins in seminal plasma of asthenozoospermia. By large scale profiling and quantifying 5,018 intact N-glycopeptides in seminal plasma, we identified 92 intact N-glycopeptides from 34 glycoproteins changed in asthenozoospermia. Especially, fucosylated glycans containing lewis x, lewis y and core fucosylation were significantly up-regulated in asthenozoospermia compared to healthy donors. The up-regulation of fucosylated glycans in seminal plasma may interfere sperm surface compositions and regulation of immune response, which subsequently disrupts sperm function. Three differentiated expression of seminal vesicle-specific glycoproteins (fibronectin, seminogelin-2, and glycodelin) were also detected with fucosylation alteration in seminal plasma of asthenozoospermia. The interpretation of the altered site-specific glycan structures provides data for the diagnosis and etiology analysis of male infertility, as well as providing new insights into the potential therapeutic targets for male infertility.

#2000 Analysis between site-specific N-glycosylation of monoclonal immunoglobulin and complement system activation

Abstract Background and Aims Monoclonal immunoglobulin produced by clonal plasma cells is the main cause in multiple myeloma (MM) and monoclonal gammopathy of renal significance (MGRS). Hypocomplementemia and deposition of complement components in the kidney is observed in some patients with MM or MGRS. Previous studies have suggested that glycosylation of the immunoglobulin was associated with complement-mediated-effector activities. Whereas, site-specific N-glycosylation characterization for monoclonal immunoglobulin in MM or MGRS and its effects on complement system activation still remains unclear. Method We separated plasma monoclonal IgG1 and IgA immunoglobulin from patients with MM and human plasma immunoglobulin from healthy controls (HC). Purified IgG and IgA molecules were digested by trypsin. Tryptic peptides without enrichment of intact N-glycopeptides were analyzed using a combination of electron-transfer/higher-energy collisional dissociation (EThcD) and stepped collision energy/higher-energy collisional dissociation (sceHCD) mass spectrometry (EThcD-sceHCD-MS/MS). N-glycosylation characterization was compared between monoclonal immunoglobulin from MM patients and healthy controls and its association with complement level was evaluated. Results A total of 46 IgG1 digestion samples (HC, n = 16; MM, n = 30) and 38 IgA1 digestion samples (HC, n = 16; MM, n = 22) were analyzed using the EThcDsceHCD-MS/MS. On average, 34 and 37 unique N-glycopeptides of IgG1, 19 unique N-glycans per IgG were identified from HC and MM. The relative abundance of fucosylated N-glycans of IgG1 in MM was significantly higher than HC (94.7% vs 88.8%, p = 0.002). Other types of N-glycans including sialylated, hybrid and complex were similar between the two groups. The types of N-glycans including fucosylated, sialylated, hybrid and complex were similar between patients with hypocomplementemia and normal complement levels. Regarding IgA1, on average, 63 and 52 unique N-glycopeptides of IgA1, 40 and 35 unique N-glycans per IgA were identified from HC and MM. The relative abundance of fucosylated (41.0% vs 26.4%, p < 0.001), sialylated (61.0% vs 45.6%, p = 0.003), mannose (2.44% vs 0.28%, p < 0.001) N-glycans of IgA1 in MM was significantly higher than HC. In MM, the relative abundance of mannose N-glycans of IgA1 in patients with hypocomplementemia was significantly lower than patients with normal complement levels (1.69% vs 7.52%, p < 0.001). The relative abundance of fucosylated and sialylated N-glycans were similar between patients with hypocomplementemia and normal complement levels. Conclusion Site-specific N-glycosylation characterization of monoclonal IgG1 and IgA1 in MM patients were differentially expressed from healthy controls. Certain specific N-glycan types were associated with complement levels. These findings laid a foundation for future investigations of their biological effects.

Characterisation and comparison site-specific N-glycosylation of whey proteins from donkey and human colostrum and mature milk using glycoproteomics

Although the composition of donkey milk is similar to that of human milk, systematic comparisons of the site-specific N-glycosylation patterns of their whey proteins are lacking. In this study, hydrophilic interaction chromatography-based enrichment of intact N-glycopeptides, coupled with a site-specific glycoproteomics strategy, was used to systematically characterise whey N-glycoproteins in donkey colostrum (DC), donkey mature milk (DM), human colostrum (HC), and human mature milk (HM) for the first time. We identified 628, 347, 868, and 425 site-specific N-glycans mapped to 135, 67, 113, and 60 glycoproteins in DC, DM, HC, and HM, respectively. Bioinformatic analysis revealed the potential biological effects of N-glycosylation modifications on the whey proteins themselves. Our findings elucidated the composition of donkey and human milk whey N-glycoproteins and their potential structure-activity relationships and provided guidance for the production of specific functional donkey milk products and the development of donkey milk-based infant formulas.

N-glycosylation of disease-specific haptoglobin for the early screening of diabetic retinopathy.

Diabetic retinopathy (DR), as one of the microvascular complications of diabetes, is a leading cause of acquired vision loss. Most DR cases are detected in the advanced stage through fundoscopy, making molecular biomarkers urgently needed for early diagnosis of DR. Serum disease-specific haptoglobin-β (Hp-β) chains of 100 patients with type 2 diabetes mellitus (T2DM) and 156 T2DM patients with non-proliferative diabetic retinopathy (NPDR) were separated using polyacrylamide gel electrophoresis. After in-gel digestion and enrichment, the intact N-glycopeptides were detected by mass spectrometry. Fucosylation of Hp-β was significantly increased and sialylation of Hp-β was significantly decreased in background DR (BDR, an early-stage DR) patients compared with non-diabetic retinopathy patients (p<0.05) and yielded area under curves (AUCs) of 0.801 and 0.829 in training and validation groups, respectively, which had an advantage over glycated hemoglobin A1c (AUC ≤ 0.691). Moreover, a significant increase in sialylated Hp-β was found in severe NPDR patients compared with BDR patients and yielded an AUC of 0.828 to distinguish severe NPDR from BDR. Changes in Hp-β glycosylation are closely related to DR, and may be used for early diagnosis and screening of DR.

Hydrophilic Peptide and Glycopeptide as Immobilized Sorbents for Glycosylation Analysis.

Hydrophilic interaction liquid chromatography (HILIC) is widely used for glycopeptide enrichment in shot-gun glycoproteomics to enhance the glycopeptide signal and minimize the ionization competition of peptides. In this work, we have developed a novel hydrophilic material (glycoHILIC) based on glycopeptides and peptides to provide hydrophilic properties. GlycoHILIC was synthesized by oxidizing cotton and then reacting the resulting aldehyde with the N-terminus of the glycopeptide or peptide by reductive amination. Due to the large amount of hydrophilic carbohydrates and hydrophilic amino acids contained in glycopeptides, glycoHILIC showed significantly better enrichment of glycopeptides than cotton itself. Our results demonstrate that glycoHILIC has high selectivity, a low detection limit, and good stability. Over 257 unique N-linked glycosylation sites in 1477 intact N-glycopeptides from 146 glycoproteins were identified from 1 μL of human serum using glycoHILIC. Serum analysis of pancreatic cancer patients found that 38 N-glycopeptides among 21 glycoproteins changed significantly, of which 7 N-glycopeptides increased and 31 N-glycopeptides decreased. These results demonstrate that glycoHILIC can be used for glycopeptide enrichment and analysis.

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.

Salivary Proteome and Intact N-Glycopeptides Analysis Reveal Specific Signatures in Periodontitis.

Periodontitis is a prevalent oral inflammatory disease that can result in tooth loss and is closely linked to type 2 diabetes (T2D). In this study, we analyzed the salivary proteome and intact N-glycopeptides (IGPs) of individuals with mild-moderate, severe, aggressive periodontitis, and periodontitis with T2D, including those treated with antidiabetic drugs, to identify specific signatures associated with the disease. Our results revealed that salivary proteins and glycoproteins were altered in all periodontitis groups (PRIDE ID: 1-20230612-72345), with fucose- and sialic acid-containing N-glycans showing the greatest increase. Additionally, differentially expressed proteins were classified into 9 clusters, including those that were increased in all periodontitis groups and those that were only altered in certain types of periodontitis. Interestingly, treatment with antidiabetic drugs reversed many of the changes observed in the salivary proteome and IGPs in T2D-related periodontitis, suggesting a potential therapeutic approach for managing periodontitis in patients with T2D. Consistent with MS/MS results, the expression of salivary IGHA2 and Fucα1-3/6GlcNAc (AAL) was significantly increased in MP. These findings provide new insights into the pathogenesis of periodontitis and highlight the potential of salivary biomarkers for diagnosis, prognosis, and monitoring of disease progression and treatment response.

High-throughput intact Glycopeptide quantification strategy with targeted-MS (HTiGQs-target) reveals site-specific IgG N-glycopeptides as biomarkers for hepatic disorder diagnosis and staging

Liver disease is one of the leading causes of global mortality, and identifying biomarkers for diagnosing the progression of liver diseases is crucial for improving its outcomes. Targeted mass spectrometry technology is a powerful tool with unique advantages for verifying biomarker candidates and clinical applications. It is particularly useful in validating protein biomarkers with post-translational modifications, eliminating the need for site-specific antibodies. Especially, targeted mass spectrometry technique is particularly critical for translation of glycoproteins into clinical applications as there are no site-specific antibodies for N-glycosylation. Nevertheless, its limitation in analyzing only one sample per run has become apparent when dealing with a large number of clinical samples. Herein, we developed a high-throughput intact N-glycopeptides quantification strategy with targeted-MS (HTiGQs-Target), which allows the validation of 20 samples per run with an average analysis time of only 3 min per sample. We applied HTiGQs-Target in a cohort of 461 serum samples (including 120 healthy controls (HC), 127 chronic hepatitis B (CHB) cases, 106 liver cirrhosis (LC) cases, and 108 hepatocellular carcinomas (HCC) cases) and found that a panel of 10 IgG N-glycopeptides have strong clinical utility in evaluating the severity of the liver disease.

Comparing and integrating TMT-SPS-MS3 and label-free quantitative approaches for proteomics scrutiny in recalcitrant Mango (Mangifera indica L.) peel tissue during postharvest period.

Despite substantial advances in the use of proteomic technologies, their widespread application in fruit tissues of non-model and recalcitrant species remains limited. This hampers the understanding of critical molecular events during the postharvest period of fleshy tropical fruits. Therefore, we evaluated label-free quantitation (LFQ) and TMT-SPS-MS3 (TMT) approaches to analyse changes in the protein profile of mango peels during postharvest period. We compared two extraction methods (phenol and chloroform/methanol) and two peptide fractionation schemes (SCX and HPRP). We accurately identified 3065 proteins, of which, 1492 were differentially accumulated over at 6 days after harvesting (DAH). Both LFQ and TMT approaches share 210 differential proteins including cell wall proteins associated with fruit softening, as well as aroma and flavour-related proteins, which were increased during postharvest period. The phenolic protein extraction and the high-pH reverse-phase peptide fractionation was the most effective pipeline for relative quantification. Nevertheless, the information provided by the other tested strategies was significantly complementary. Besides, LFQ spectra allowed us to track down intact N-glycopeptides corroborating N-glycosylations on the surface of a desiccation-related protein. This work represents the largest proteomic comparison of mango peels during postharvest period made so far, shedding light on the molecular foundation of edible fruit during ripening.

Maximal performance of intact N-glycopeptide enrichment using sequential HILIC and MAX columns.

Low abundance and heterogeneity of N-glycosylation at the peptide level poses a great challenge to the structural and functional analysis of glycosylation in the field of glycobiology. Solving this conundrum requires a sufficient and specific method for intact N-glycopeptide enrichment. Using the C18 or HLB desalting column followed by the mixed-mode strong anion exchange (MAX) or hydrophilic interaction chromatography (HILIC) glycopeptide enrichment column are commonly applied approaches for sample preparation of intact N-glycopeptides from complex samples. Herein, we compared the effects of different combinations of two desalting columns and two enrichment columns using equal amounts of mouse brain tissues from the same source. The results revealed the C18 column was a bit superior to the HLB column, and the MAX and HILIC columns were complementary on intact N-glycopeptides enrichment. Additionally, the results also demonstrated that enriching glycopeptides using a HILIC column followed by a MAX column from the flow-through solution got a better enrichment performance than the reversed order. Based on these results, the sequential enrichment of glycopeptides using HILIC and then MAX columns could maximize the enrichment performance of intact N-glycopeptides, and therefore is an option for in-depth analysis of site-specific glycoproteome.

Integrative proteomics and n-glycoproteomics reveal the synergistic anti-tumor effects of aspirin- and gemcitabine-based chemotherapy on pancreatic cancer cells.

Pancreatic cancer is a highly malignant tumor that is well known for its poor prognosis. Based on glycosylation, we performed integrated quantitative N-glycoproteomics to investigate the synergistic anti-tumor effects of aspirin and gemcitabine on pancreatic cancer cells and explore the potential molecular mechanisms of chemotherapy in pancreatic cancer. Two pancreatic cancer cell lines (PANC-1 and BxPC-3) were treated with gemcitabine, aspirin, and a combination (gemcitabine + aspirin). We found that the addition of aspirin enhanced the inhibitory effect of gemcitabine on the activity of PANC-1 and BxPC-3 cells. Quantitative N-glycoproteome, proteome, phosphorylation, and transcriptome data were obtained from integrated multi-omics analysis to evaluate the anti-tumor effects of aspirin and gemcitabine on pancreatic cancer cells. Mfuzz analysis of intact N-glycopeptide profiles revealed two consistent trends associated with the addition of aspirin, which showed a strong relationship between N-glycosylation and the synergistic effect of aspirin. Further analysis demonstrated that the dynamic regulation of sialylation and high-mannose glycoforms on ECM-related proteins (LAMP1, LAMP2, ITGA3, etc.) was a significant factor for the ability of aspirin to promote the anti-tumor activity of gemcitabine and the drug resistance of pancreatic cancer cells. In-depth analysis of N-glycosylation-related processes and pathways in pancreatic cancer cells can provide new insight for future studies regarding pancreatic cancer therapeutic targets and drug resistance mechanisms.

Sensitive N-Glycopeptide Profiling of Single and Rare Cells Using an Isobaric Labeling Strategy without Enrichment.

Single-cell omics is critical in revealing population heterogeneity, discovering unique features of individual cells, and identifying minority subpopulations of interest. As one of the major post-translational modifications, protein N-glycosylation plays crucial roles in various important biological processes. Elucidation of the variation in N-glycosylation patterns at single-cell resolution may largely facilitate the understanding of their key roles in the tumor microenvironment and immune therapy. However, comprehensive N-glycoproteome profiling for single cells has not been achieved due to the extremely limited sample amount and incompatibility with the available enrichment strategies. Here, we have developed an isobaric labeling-based carrier strategy for highly sensitive intact N-glycopeptide profiling for single cells or a small number of rare cells without enrichment. Isobaric labeling has unique multiplexing properties, by which the "total" signal from all channels triggers MS/MS fragmentation for N-glycopeptide identification, while the reporter ions provide quantitative information. In our strategy, a carrier channel using N-glycopeptides obtained from bulk-cell samples significantly improved the "total" signal of N-glycopeptides and, therefore, promoted the first quantitative analysis of averagely 260 N-glycopeptides from single HeLa cells. We further applied this strategy to study the regional heterogeneity of N-glycosylation of microglia in mouse brain and discovered region-specific N-glycoproteome patterns and cell subtypes. In conclusion, the glycocarrier strategy provides an attractive solution for sensitive and quantitative N-glycopeptide profiling of single/rare cells that cannot be enriched by traditional workflows.

Application of Microscopic Highly Hydrophilic Silica-Based Nanocomposites with High Surface Exposure in the Efficient Identification of Intact N-Glycopeptides.

Glycosylation of proteins regulates the life activities of organisms, while abnormalities of glycosylation sites and glycan structures occur in various serious diseases such as cancer. A separation and enrichment procedure is necessary to realize the analysis of the glycoproteins/peptides by mass spectrometry, for which the surface hydrophilicity of the material is an important factor for the separation and enrichment performance. In the present work, under the premise of an obvious increase of the surface silicon exposure (79.6%), the amount of surface polar silanol is remarkably generated accompanying the introduction of the active amino groups on the surface of silica. The microscopic hydrophilicity, which is determined with water physical-adsorption measurements and can directly reflect the interaction of water molecules and the intrinsic surface of the material, maximally increases by 44%. This microscopically highly hydrophilic material shows excellent enrichment ability for glycopeptides, such as extremely low detection limits (0.01 fmol μL-1), remarkable selectivity (1:8000), and size exclusion effects (1:8000). A total of 677 quantifiable intact N-glycopeptides were identified from the serum of patients with cervical cancer, and the glycosylation site and glycan structure were analyzed in depth, indicating that this novel material can show a broad practical application in cervical cancer diagnosis.

Integrative Proteomics and N-Glycoproteomics Analyses of Rheumatoid Arthritis Synovium Reveal Immune-Associated Glycopeptides

Rheumatoid arthritis (RA) is a typical autoimmune disease characterized by synovial inflammation, synovial tissue hyperplasia, and destruction of bone and cartilage. Protein glycosylation plays key roles in the pathogenesis of RA but in-depth glycoproteomics analysis of synovial tissues is still lacking. Here, by using a strategy to quantify intact N-glycopeptides, we identified 1260 intact N-glycopeptides from 481 N-glycosites on 334 glycoproteins in RA synovium. Bioinformatics analysis revealed that the hyper-glycosylated proteins in RA were closely linked to immune responses. By using DNASTAR software, we identified 20 N-glycopeptides whose prototype peptides were highly immunogenic. We next calculated the enrichment scores of nine types of immune cells using specific gene sets from public single-cell transcriptomics data of RA and revealed that the N-glycosylation levels at some sites, such as IGSF10_N2147, MOXD2P_N404, and PTCH2_N812, were significantly correlated with the enrichment scores of certain immune cell types. Furthermore, we showed that aberrant N-glycosylation in the RA synovium was related to increased expression of glycosylation enzymes. Collectively, this work presents, for the first time, the N-glycoproteome of RA synovium and describes immune-associated glycosylation, providing novel insights into RA pathogenesis.

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.