Exploring site-specific N-glycosylation microheterogeneity of haptoglobin using glycopeptide CID tandem mass spectra and glycan database search

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.

NS1 Protein N-Linked Glycosylation Site Affects the Virulence and Pathogenesis of Dengue Virus

Live attenuated vaccine is one of the most effective vaccines against flavivirus. Recently, site-directed mutation of the flavivirus genome using reverse genetics techniques has been used for the rapid development of attenuated vaccines. However, this technique relies on basic research of critical virulence loci of the virus. To screen the attenuated sites in dengue virus, a total of eleven dengue virus type four mutant strains with deletion of N-glycosylation sites in the NS1 protein were designed and constructed. Ten of them (except for the N207-del mutant strain) were successfully rescued. Out of the ten strains, one mutant strain (N130del+207-209QQA) was found to have significantly reduced virulence through neurovirulence assay in suckling mice, but was genetically unstable. Further purification using the plaque purification assay yielded a genetically stable attenuated strain #11-puri9 with mutations of K129T, N130K, N207Q, and T209A in the NS1 protein and E99D in the NS2A protein. Identifying the virulence loci by constructing revertant mutant and chimeric viruses revealed that five amino acid adaptive mutations in the dengue virus type four non-structural proteins NS1 and NS2A dramatically affected its neurovirulence and could be used in constructing attenuated dengue chimeric viruses. Our study is the first to obtain an attenuated dengue virus strain through the deletion of amino acid residues at the N-glycosylation site, providing a theoretical basis for understanding the pathogenesis of the dengue virus and developing its live attenuated vaccines.

MS-based glycomics and glycoproteomics methods enabling isomeric characterization

Glycosylation is one of the most significant and abundant posttranslational modifications in mammalian cells. It mediates a wide range of biofunctions, including cell adhesion, cell communication, immune cell trafficking, and protein stability. Also, aberrant glycosylation has been associated with various diseases such as diabetes, Alzheimer's disease, inflammation, immune deficiencies, congenital disorders, and cancers. The alterations in the distributions of glycan and glycopeptide isomers are involved in the development and progression of several human diseases. However, the microheterogeneity of glycosylation brings a great challenge to glycomic and glycoproteomic analysis, including the characterization of isomers. Over several decades, different methods and approaches have been developed to facilitate the characterization of glycan and glycopeptide isomers. Mass spectrometry (MS) has been a powerful tool utilized for glycomic and glycoproteomic isomeric analysis due to its high sensitivity and rich structural information using different fragmentation techniques. However, a comprehensive characterization of glycan and glycopeptide isomers remains a challenge when utilizing MS alone. Therefore, various separation methods, including liquid chromatography, capillary electrophoresis, and ion mobility, were developed to resolve glycan and glycopeptide isomers before MS. These separation techniques were coupled to MS for a better identification and quantitation of glycan and glycopeptide isomers. Additionally, bioinformatic tools are essential for the automated processing of glycan and glycopeptide isomeric data to facilitate isomeric studies in biological cohorts. Here in this review, we discuss commonly employed MS-based techniques, separation hyphenated MS methods, and software, facilitating the separation, identification, and quantitation of glycan and glycopeptide isomers.

The next "sweet" spot for pancreatic ductal adenocarcinoma: Glycoprotein for early detection

Pancreatic ductal adenocarcinoma (PDAC) is the most common neoplastic disease of the pancreas, accounting for more than 90% of all pancreatic malignancies. As a highly lethal malignancy, PDAC is the fourth leading cause of cancer-related deaths worldwide with a 5-year overall survival of less than 8%. The efficacy and outcome of PDAC treatment largely depend on the stage of disease at the time of diagnosis. Surgical resection followed by adjuvant chemotherapy remains the only possibly curative therapy, yet 80%-90% of PDAC patients present with nonresectable PDAC stages at the time of clinical presentation. Despite our advancing knowledge of PDAC, the prognosis remains strikingly poor, which is primarily due to the difficulty of diagnosing PDAC at the early stages. Recent advances in glycoproteomics and glycomics based on mass spectrometry have shown that aberrations in protein glycosylation plays a critical role in carcinogenesis, tumor progression, metastasis, chemoresistance, and immuno-response of PDAC and other types of cancers. A growing interest has thus been placed upon protein glycosylation as a potential early detection biomarker for PDAC. We herein take stock of the advancements in the early detection of PDAC that were carried out with mass spectrometry, with special focus on protein glycosylation.

GlycoSLASH: Concurrent Glycopeptide Identification from Multiple Related LC-MS/MS Data Sets by Using Spectral Clustering and Library Searching

Liquid chromatography coupled with tandem mass spectrometry is commonly adopted in large-scale glycoproteomic studies involving hundreds of disease and control samples. The software for glycopeptide identification in such data (e.g., the commercial software Byonic) analyzes the individual data set and does not exploit the redundant spectra of glycopeptides presented in the related data sets. Herein, we present a novel concurrent approach for glycopeptide identification in multiple related glycoproteomic data sets by using spectral clustering and spectral library searching. The evaluation on two large-scale glycoproteomic data sets showed that the concurrent approach can identify 105%-224% more spectra as glycopeptides compared to the glycopeptide identification on individual data sets using Byonic alone. The improvement of glycopeptide identification also enabled the discovery of several potential biomarkers of protein glycosylations in hepatocellular carcinoma patients.

High-throughput immunoaffinity enrichment and N-glycan analysis of human plasma haptoglobin

Haptoglobin (Hp) is a positive acute phase protein, synthesized in the liver, with four N-glycosylation sites carrying mainly complex type N-glycans. Its glycosylation is altered in different types of diseases but still has not been extensively studied mainly due to analytical challenges, especially the lack of a fast, efficient, and robust high-throughput Hp isolation procedure. Here, we describe the development of a high-throughput method for Hp enrichment from human plasma, based on monolithic chromatographic support in immunoaffinity mode and downstream Hp N-glycome analysis by hydrophilic interaction ultrahigh-performance liquid chromatography with fluorescent detection (HILIC-UHPLC-FLR). Chromatographic monolithic supports in a 96-well format enable fast, efficient, and robust Hp enrichment directly from diluted plasma samples. The N-glycome analysis demonstrated that a degree of Hp deglycosylation differs depending on the conditions used for N-glycan release and on the specific glycosylation site, with Asn 241 being the most resistant to deglycosylation under tested conditions. HILIC-UHPLC-FLR analysis enables robust quantification of 28 individual chromatographic peaks, in which N-glycan compositions were determined by UHPLC coupled to electrospray ionization quadrupole time of flight mass spectrometry. The developed analytical approach enables fast evaluation of total Hp N-glycosylation and is applicable in large-scale studies.

Comparative glycoproteomics study on the surface of SKOV3 versus IOSE80 cell lines

Objective: Site- and structure-specific quantitative N-glycoproteomics study of differential cell-surface N-glycosylation of ovarian cancer SKOV3 cells with the non-cancerous ovarian epithelial IOSE80 cells as the control.

Methods: C18-RPLC-MS/MS (HCD with stepped normalized collision energies) was used to analyze the 1: 1 mixture of labeled intact N-glycopeptides from SKOV3 and IOSE80 cells, and the site- and structure-specific intact N-glycopeptide search engine GPSeeker was used to conduct qualitative and quantitative search on the obtained raw datasets.

Results: With the control of the spectrum-level false discovery rate ≤1%, 13,822 glycopeptide spectral matches coming from 2,918 N-glycoproteins with comprehensive N-glycosite and N-glycan structure information were identified; 3,733 N-glycosites and 3,754 N-glycan sequence structures were confirmed by site-determining and structure-diagnostic fragment ions, respectively. With the control of no less than two observations among the three technical replicates, fold change ≥1.5, and p-value ≤ 0.05, 746 DEPGs in SKOV3 cells relative to IOSE80 cells were quantified, where 421 were upregulated and 325 downregulated.

Conclusion: Differential cell-surface N-glycosylation of ovarian cancer SKOV3 cells were quantitatively analyzed by isotopic labeling and site- and structure-specific N-glycoproteomics. This discovery study provides putative N-glycoprotein biomarker candidates for future validation study using multiple reaction monitoring and biochemical methods.

Novel Isobaric Tagging Reagent Enabled Multiplex Quantitative Glycoproteomics via Electron-Transfer/Higher-Energy Collisional Dissociation (EThcD) Mass Spectrometry

Protein glycosylation, covalent attachment of carbohydrates to polypeptide chains, is a highly important post-translational modification involved in many essential physiological processes. Comprehensive site-specific and quantitative analysis is crucial for revealing the diverse functions and dynamics of glycosylation. To characterize intact glycopeptides, mass spectrometry (MS)-based glycoproteomics employs versatile fragmentation methods, among which electron-transfer/higher-energy collision dissociation (EThcD) has gained great popularity. However, the inherent limitation of EThcD in fragmenting low-charge ions has prevented its widespread applications. Furthermore, there is a need to develop a high-throughput strategy for comparative glycoproteomics with a large cohort of samples. Herein, we developed isobaric N,N-dimethyl leucine-derivatized ethylenediamine (DiLeuEN) tags to increase the charge states of glycopeptides, thereby improving the fragmentation efficiency and allowing for in-depth intact glycopeptide analysis, especially for sialoglycopeptides. Moreover, the unique reporter ions of DiLeuEN-labeled glycopeptides generated in tandem MS spectra enable relative quantification of up to four samples in a single analysis, which represents a new high-throughput method for quantitative glycoproteomics.

Mass spectrometry based biomarkers for early detection of HCC using a glycoproteomic approach

Hepatocellular carcinoma (HCC) is the fourth most common cause of cancer-related mortality worldwide and 80%-90% of HCC develops in patients that have underlying cirrhosis. Better methods of surveillance are needed to increase early detection of HCC and the proportion of patients that can be offered curative therapies. Recent work in novel mass spec-based methods for glycomic and glycopeptide analysis for discovery and confirmation of markers for early detection of HCC versus cirrhosis is reviewed in this chapter. Results from recent work in these fields by several groups and the progress made in developing markers of early HCC which can outperform the current serum-based markers are described and discussed. Also, recent developments in isoform analysis of glycans and glycopeptides and in various mass spec fragmentation methods will be described and discussed.

Glycopeptides with Sialyl Lewis Antigen in Serum Haptoglobin as Candidate Biomarkers for Nonalcoholic Steatohepatitis Hepatocellular Carcinoma Using a Higher-Energy Collision-Induced Dissociation Parallel Reaction Monitoring-Mass Spectrometry Method

Nonalcoholic steatohepatitis (NASH) is the fastest growing cause of hepatocellular carcinoma (HCC) in the United States. Changes in N-glycosylation on specific glycosites of serum proteins have been investigated as potential markers for the early detection of NASH-related HCC. Herein, we report a glycopeptide with a Sialyl Lewis structure derived from serum haptoglobin (Hp) as a potential marker for NASH related HCCs among 95 patients with NASH, including 46 cirrhosis, 32 early-stage HCC, and 17 late-stage HCC. Hp immuno-isolated from patient serum was analyzed using LC-HCD-PRM-MS/MS followed by data analysis via Skyline software. Two glycopeptides involving site N184 and four glycopeptides involving site N241 were significantly changed in patients with HCC vs NASH cirrhosis (P < 0.05). The two-marker panel using N-glycopeptide N241_A4G4F2S4 showed the best performance for HCC detection when combined with α-fetoprotein (AFP), with an improved estimated area under the curve (AUC) = 0.898 (95% CI: 0.835, 0.951), compared to the AUC of 0.790(95% CI, 0.697 0.872) using AFP alone (P = 0.048). At 90% specificity, the combination of N241_A4G4F2S4 + AFP had an improved sensitivity of 63.3%, compared to the sensitivity of 52.3% using AFP alone. When using three markers, the panel of AFP + N241_A2G2F1S2 + N241_A4G4F2S4 yielded an estimated AUC of 0.928 (95% CI: 0.877, 0.970). Our findings indicated that N241_A4G4F2S4 may play an important role in distinguishing HCC from NASH cirrhosis.

Integrated N-glycoproteomics Analysis of Human Saliva for Lung Cancer

Aberrant protein N-glycosylation is a cancer hallmark, which has great potential for cancer detection. However, large-scale and in-depth analysis of N-glycosylation remains challenging because of its high heterogeneity, complexity, and low abundance. Human saliva is an attractive diagnostic body fluid, while few efforts explored its N-glycoproteome for lung cancer. Here, we utilized a zwitterionic-hydrophilic interaction chromatography-based strategy to specifically enrich salivary glycopeptides. Through quantitative proteomics analysis, 1492 and 1234 intact N-glycopeptides were confidently identified from pooled saliva samples of 10 subjects in the nonsmall-cell lung cancer group and 10 subjects in the normal control group. Accordingly, 575 and 404 N-glycosites were revealed for the lung cancer group and normal control group. In particular, 154 N-glycosites and 259 site-specific glycoforms were significantly dysregulated in the lung cancer group. Several N-glycosites located at the same glycoprotein and glycans attached to the same N-glycosites were observed with differential expressions, including haptoglobin, Mucin-5B, lactotransferrin, and α-1-acid glycoprotein 1. These N-glycoproteins were mainly related to inflammatory responses, infectious diseases, and cancers. Our study achieved comprehensive characterization of salivary N-glycoproteome, and dysregulated site-specific glycoforms hold promise for noninvasive detection of lung cancer.

Precise O-Glycosylation Site Localization of CD24Fc by LC-MS Workflows

CD24Fc is a homodimeric recombinant Fc-fusion protein comprised of human CD24 connected to immunoglobulin G1 (IgG1) Fc fragment. CD24 is heavily glycosylated, and its biological function is considered mainly mediated by its glycosylation. Identification of the O-glycosylation sites would facilitate an in-depth understanding of the functional role of O-glycans in CD24. However, the presence of clustered mucin-type O-glycans together with N-glycans makes the determination of O-glycosylation sites and abundance very challenging. In this study, two sets of liquid chromatography-mass spectrometry (LC-MS) workflows were developed for the comprehensive characterization of O-glycosylation in CD24: (1) Fractionation and collision-induced dissociation (CID) workflow involving multienzyme digestion, fractionation, OpeRATOR/SialEXO digestion, and CID analysis; (2) Direct OpeRATOR/SialEXO digestion followed by electron-transfer/higher-energy collision dissociation (EThcD) analysis. The precise O-glycosylation sites were identified in CD24 for the first time, and the site occupancy was assessed. A total of 12 O-glycosylation sites were identified. Seven glycosylation sites were identified by both workflows, and five additional sites were identified only by the EThcD workflow. The predominant O-glycosylation site in CD24 was Thr25 followed by Thr15. The CID workflow provided an overall relative quantitation of O-glycoforms at the CD24 level and site localization for singly O-glycosylated peptides. The EThcD workflow directly identified glycosylation sites by tandem mass spectrometry (MS/MS) for singly, doubly, and triply O-glycosylated peptides. Together, both workflows validated each other's results and can be applied to a complex mucin-type O-glycosylation site analysis of other glycoproteins and Fc-fusion therapeutics.

A Single Mutation at Position 120 in the Envelope Protein Attenuates Tembusu Virus in Ducks

A live attenuated duck Tembusu virus (TMUV) vaccine FX2010-180P (180P) was successfully utilized to prevent TMUV infections in ducks in China. Compared with wild-type TMUV, 180P was highly attenuated and lost transmissibility in ducks. However, the mechanism of the attenuation of 180P remains poorly understood. To explore the key molecular basis of attenuation, chimeric and site mutant viruses in the background of the wild-type TMUV-FX2010 (FX) strain were rescued, and the replication, tissue tropism, and transmissibility were characterized in ducks. The results show that the envelope (E) protein was responsible for attenuation and loss of transmission in ducks. Further studies showed that a D120N amino acid mutation located in domain II of the E protein was responsible for the attenuation and transmissibility loss of 180P in ducks. The D120N substitution resulted in an extra high-mannose type N-linked glycosylation (NLG) in the E protein of 180P compared with the wild-type TMUV, which might restrict the tissue tropism and transmissibility of TMUV in ducks. Our findings elucidate that N120 in the E protein is a key molecular basis of TMUV attenuation in ducks and provide new insight into the role of NLG in TMUV tissue tropism and transmissibility.

Glycomic and Glycoproteomic Techniques in Neurodegenerative Disorders and Neurotrauma: Towards Personalized Markers

The proteome represents all the proteins expressed by a genome, a cell, a tissue, or an organism at any given time under defined physiological or pathological circumstances. Proteomic analysis has provided unparalleled opportunities for the discovery of expression patterns of proteins in a biological system, yielding precise and inclusive data about the system. Advances in the proteomics field opened the door to wider knowledge of the mechanisms underlying various post-translational modifications (PTMs) of proteins, including glycosylation. As of yet, the role of most of these PTMs remains unidentified. In this state-of-the-art review, we present a synopsis of glycosylation processes and the pathophysiological conditions that might ensue secondary to glycosylation shortcomings. The dynamics of protein glycosylation, a crucial mechanism that allows gene and pathway regulation, is described. We also explain how-at a biomolecular level-mutations in glycosylation-related genes may lead to neuropsychiatric manifestations and neurodegenerative disorders. We then analyze the shortcomings of glycoproteomic studies, putting into perspective their downfalls and the different advanced enrichment techniques that emanated to overcome some of these challenges. Furthermore, we summarize studies tackling the association between glycosylation and neuropsychiatric disorders and explore glycoproteomic changes in neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Huntington disease, multiple sclerosis, and amyotrophic lateral sclerosis. We finally conclude with the role of glycomics in the area of traumatic brain injury (TBI) and provide perspectives on the clinical application of glycoproteomics as potential diagnostic tools and their application in personalized medicine.

Recent Advances in Analytical Approaches for Glycan and Glycopeptide Quantitation

Growing implications of glycosylation in physiological occurrences and human disease have prompted intensive focus on revealing glycomic perturbations through absolute and relative quantification. Empowered by seminal methodologies and increasing capacity for detection, identification, and characterization, the past decade has provided a significant increase in the number of suitable strategies for glycan and glycopeptide quantification. Mass-spectrometry-based strategies for glycomic quantitation have grown to include metabolic incorporation of stable isotopes, deposition of mass difference and mass defect isotopic labels, and isobaric chemical labeling, providing researchers with ample tools for accurate and robust quantitation. Beyond this, workflows have been designed to harness instrument capability for label-free quantification, and numerous software packages have been developed to facilitate reliable spectrum scoring. In this review, we present and highlight the most recent advances in chemical labeling and associated techniques for glycan and glycopeptide quantification.

Recent Advances in Software Tools for More Generic and Precise Intact Glycopeptide Analysis

Intact glycopeptide identification has long been known as a key and challenging barrier to the comprehensive and accurate understanding the role of glycosylation in an organism. Intact glycopeptide analysis is a blossoming field that has received increasing attention in recent years. MS-based strategies and relative software tools are major drivers that have greatly facilitated the analysis of intact glycopeptides, particularly intact N-glycopeptides. This article provides a systematic review of the intact glycopeptide-identification process using MS data generated in shotgun proteomic experiments, which typically focus on N-glycopeptide analysis. Particular attention is paid to the software tools that have been recently developed in the last decade for the interpretation and quality control of glycopeptide spectra acquired using different MS strategies. The review also provides information about the characteristics and applications of these software tools, discusses their advantages and disadvantages, and concludes with a discussion of outstanding tools.

When Glycosylation Meets Blood Cells: A Glance of the Aberrant Glycosylation in Hematological Malignancies

Among neoplasia-associated epigenetic alterations, changes in cellular glycosylation have recently received attention as a key component of hematological malignancy progression. Alterations in glycosylation appear to not only directly impact cell growth and survival, but also alter the adhesion of tumor cells and their interactions with the microenvironment, facilitating cancer-induced immunomodulation and eventual metastasis. Changes in glycosylation arise from altered expression of glycosyltransferases, enzymes that catalyze the transfer of saccharide moieties to a wide range of acceptor substrates, such as proteins, lipids, and other saccharides in the endoplasmic reticulum (ER) and Golgi apparatus. Novel glycan structures in hematological malignancies represent new targets for the diagnosis and treatment of blood diseases. This review summarizes studies of the aberrant expression of glycans commonly found in hematological malignancies and their potential mechanisms and defines the specific roles of glycans as drivers or passengers in the development of hematological malignancies.

Screening siRNAs against host glycosylation pathways to develop novel antiviral agents against hepatitis B virus

AIM

Hepatitis B virus (HBV) relies on glycosylation for crucial functions, such as entry into host cells, proteolytic processing and protein trafficking. The aim of this study was to identify candidate molecules for the development of novel antiviral agents against HBV using an siRNA screening system targeting the host glycosylation pathway.

METHODS

HepG2.2.15.7 cells that consistently produce HBV were employed for our in vitro study. We investigated the effects of siRNAs that target 88 different host glycogenes on hepatitis B surface antigen (HBsAg) and HBV DNA secretion using the siRNA screening system.

RESULTS

We identified four glycogenes that reduced HBsAg and/or HBV DNA secretion; however, the observed results for two of them may be due to siRNA off-target effects. Knocking down ST8SIA3, a member of the sialyltransferase family, significantly reduced both HBsAg and HBV DNA secretion. Knocking down GALNT7, which transfers N-acetylgalactosamine to initiate O-linked glycosylation in the Golgi apparatus, also significantly reduced both HBsAg and HBV DNA levels.

CONCLUSIONS

These results showed that knocking down the ST8SIA3 and GALNT7 glycogenes inhibited HBsAg and HBV DNA secretion in HepG2.2.15.7 cells, indicating that the host glycosylation pathway is important for the HBV life cycle and could be a potential target for the development of novel anti-HBV agents.

Databases and Bioinformatic Tools for Glycobiology and Glycoproteomics

Glycosylation plays critical roles in various biological processes and is closely related to diseases. Deciphering the glycocode in diverse cells and tissues offers opportunities to develop new disease biomarkers and more effective recombinant therapeutics. In the past few decades, with the development of glycobiology, glycomics, and glycoproteomics technologies, a large amount of glycoscience data has been generated. Subsequently, a number of glycobiology databases covering glycan structure, the glycosylation sites, the protein scaffolds, and related glycogenes have been developed to store, analyze, and integrate these data. However, these databases and tools are not well known or widely used by the public, including clinicians and other researchers who are not in the field of glycobiology, but are interested in glycoproteins. In this study, the representative databases of glycan structure, glycoprotein, glycan-protein interactions, glycogenes, and the newly developed bioinformatic tools and integrated portal for glycoproteomics are reviewed. We hope this overview could assist readers in searching for information on glycoproteins of interest, and promote further clinical application of glycobiology.

Extending the Martini Coarse-Grained Force Field to N-Glycans

Glycans play a vital role in a large number of cellular processes. Their complex and flexible nature hampers structure-function studies using experimental techniques. Molecular dynamics (MD) simulations can help in understanding dynamic aspects of glycans if the force field parameters used can reproduce key experimentally observed properties. Here, we present optimized coarse-grained (CG) Martini force field parameters for N-glycans, calibrated against experimentally derived binding affinities for lectins. The CG bonded parameters were obtained from atomistic (ATM) simulations for different glycan topologies including high mannose and complex glycans with various branching patterns. In the CG model, additional elastic networks are shown to improve maintenance of the overall conformational distribution. Solvation free energies and octanol-water partition coefficients were also calculated for various N-glycan disaccharide combinations. When using standard Martini nonbonded parameters, we observed that glycans spontaneously aggregated in the solution and required down-scaling of their interactions for reproduction of ATM model radial distribution functions. We also optimized the nonbonded interactions for glycans interacting with seven lectin candidates and show that a relatively modest scaling down of the glycan-protein interactions can reproduce free energies obtained from experimental studies. These parameters should be of use in studying the role of glycans in various glycoproteins and carbohydrate binding proteins as well as their complexes, while benefiting from the efficiency of CG sampling.

Glycopeptide Biomarkers in Serum Haptoglobin for Hepatocellular Carcinoma Detection in Patients with Nonalcoholic Steatohepatitis

Nonalcoholic steatohepatitis (NASH) is rising in prevalence in the United States and is a growing cause of hepatocellular carcinomas (HCCs). Site-specific glycan heterogeneity on glycoproteins has been shown as a potential diagnostic biomarker for HCC. Herein, we have performed a comprehensive screening of site-specific N-glycopeptides in serum haptoglobin (Hp), a reporter molecule for aberrant glycosylation in HCC, to characterize glycopeptide markers for NASH-related HCCs. In total, 70 NASH patients (22 early HCC, 15 advanced HCC, and 33 cirrhosis cases) were analyzed, with Hp purified from 20 μL of serum in each patient, and 140 sets of mass spectrometry (MS) data were collected using liquid chromatography coupled with electron-transfer high-energy collisional dissociation tandem MS (LC-EThcD-MS/MS) for quantitative analysis on a novel software platform, Byos. Differential quantitation analysis revealed that five N-glycopeptides at sites N184 and N241 were significantly elevated during the progression from NASH cirrhosis to HCC (p < 0.05). Receiver operating characteristic (ROC) curve analysis demonstrated that the N-glycopeptides at sites N184 and N241 bearing a monofucosylated triantennary glycan A3G3F1S3 had the best diagnostic performance in detection of early NASH HCC, area under the curve (AUC) = 0.733 and 0.775, respectively, whereas α-fetoprotein (AFP) had an AUC of 0.692. When combined with AFP, the two panels improved the sensitivity for early NASH HCC from 59% (AFP alone) to 73% while maintaining a specificity of 70%, based on the optimal cutoff. Two-dimensional (2-D) scatter plots of the AFP value and N-glycopeptides showed that these N-glycopeptide markers detected 58% of AFP-negative HCC patients as distinct from cirrhosis. These site-specific N-glycopeptides could serve as potential markers for early detection of HCC in patients with NASH-related cirrhosis.

Biomarkers for the Early Detection of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide, and the cancer with the fastest increase in mortality in the United States, with more than 39,000 cases and 29,000 deaths in 2018. As with many cancers, survival is significantly improved by early detection. The median survival of patients with early HCC is >60 months but <15 months when detected at an advanced stage. Surveillance of at-risk patients improves outcome, but fewer than 20% of those at risk for HCC receive surveillance, and current surveillance strategies have limited sensitivity and specificity. Ideally, blood-based biomarkers with adequate sensitivity or specificity would be available for early detection of HCC; however, the most commonly used biomarker for HCC, alpha-fetoprotein, has inadequate performance characteristics. There are several candidate serum proteomic, glycomic, and genetic markers that have gone through early stages of biomarker validation and have shown promise for the early detection of HCC, but these markers require validation in well-curated cohorts. Ongoing prospective cohort studies will permit retrospective longitudinal (phase III biomarker study) validation of biomarkers. In this review, we highlight promising candidate biomarkers and biomarker panels that have completed phase II evaluation but require further validation prior to clinical use.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

A Perspective on the Confident Comparison of Glycoprotein Site-Specific Glycosylation in Sample Cohorts

Protein glycosylation, resulting from glycosyl transferase reactions under complex control in the secretory pathway, consists of a distribution of related glycoforms at each glycosylation site. Because the biosynthetic substrate concentration and transport rates depend on architecture and other aspects of cellular phenotypes, site-specific glycosylation cannot be predicted accurately from genomic, transcriptomic, or proteomic information. Rather, it is necessary to quantify glycosylation at each protein site and how this changes among a sample cohort to provide information about disease mechanisms. At present, mature mass spectrometry-based methods allow for qualitative assignment of the glycan composition and glycosylation site of singly glycosylated proteolytic peptides. To make such quantitative comparisons, it is necessary to sample the glycosylation distribution with sufficient coverage and accuracy for confident assessment of the glycosylation changes that occur in the biological cohort. In this Perspective, we discuss the unmet needs for mass spectrometry acquisition methods and bioinformatics for the confident comparison of protein site-specific glycosylation among sample cohorts.

Monitoring of antibody glycosylation pattern based on microarray MALDI-TOF mass spectrometry

Biologically manufactured monoclonal antibodies (mAb) can strongly vary in their efficacy and affinity. Therefore, engineering and production of the mAb is highly regulated and requires product monitoring, especially in terms of N-glycosylation patterns. In this work, we present a high-throughput matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) method based on a microarray technology to monitor N-glycopeptides of IgG1 produced in a perfusion cell culture. A bottom-up approach combined with zwitterionic-hydrophilic interaction liquid chromatography for sample purification was used to determine the day-by-day variation of the terminal galactose within two major N-glycoforms. Our results show that microarrays for mass spectrometry (MAMS) are a robust platform for the rapid determination of the carbohydrate distribution. The spectral repeatability is characterized by a low coefficient of variations (1.7% and 7.1% for the FA2 and FA2G1 structures, respectively) and allows to detect the N-glycosylation variability resulting from operating conditions during the bioreactor process. The observed trend of released N-glycans was confirmed using capillary gel electrophoresis with laser-induced fluorescence detection. Therefore, the microarray technology is a promising analytical tool for glycosylation control during the production process of recombinant proteins.

Plasma proteome plus site-specific N-glycoprofiling for hepatobiliary carcinomas

Hepatobiliary cancer is the third leading cause of cancer death worldwide. Appropriate markers for early diagnosis, monitoring of disease progression, and prediction of postsurgical outcome are still lacking. As the majority of circulating N‐glycoproteins are originated from the hepatobiliary system, we sought to explore new markers by assessing the dynamics of N‐glycoproteome in plasma samples from patients with hepatocellular carcinoma (HCC), cholangiocarcinoma (CCA), or combined HCC and CCA (cHCC‐CCA). Using a mass spectrometry‐based quantitative proteomic approach, we found that 57 of 5358 identified plasma proteins were differentially expressed in hepatobiliary cancers. The levels of four essential proteins, including complement C3 and apolipoprotein C‐III in HCC, galectin‐3‐binding protein in CCA, and 72 kDa inositol polyphosphate 5‐phosphatase in cHCC‐CCA, were highly correlated with tumor stage, tumor grade, recurrence‐free survival, and overall survival. Postproteomic site‐specific N‐glycan analyses showed that human complement C3 bears high‐mannose and hybrid glycoforms rather than complex glycoforms at Asn85. The abundance of complement C3 with mannose‐5 or mannose‐6 glycoform at Asn85 was associated with HCC tumor grade. Furthermore, stepwise Cox regression analyses revealed that HCC patients with a hybrid glycoform at Asn85 of complement C3 had a lower postsurgery tumor recurrence rate or mortality rate than those with a low amount of complement C3 protein. In conclusion, our data show that particular plasma N‐glycoproteins with specific N‐glycan compositions could be potential noninvasive markers to evaluate oncological status and prognosis of hepatobiliary cancers.

GlycopeptideGraphMS: Improved Glycopeptide Detection and Identification by Exploiting Graph Theoretical Patterns in Mass and Retention Time

The leading proteomic method for identifying N-glycosylated peptides is liquid chromatography coupled with tandem fragmentation mass spectrometry (LCMS/MS) followed by spectral matching of MS/MS fragment masses to a database of possible glycan and peptide combinations. Such database-dependent approaches come with challenges such as needing high-quality informative MS/MS spectra, ignoring unexpected glycan or peptide sequences, and making incorrect assignments because some glycan combinations are equivalent in mass to amino acids. To address these challenges, we present GlycopeptideGraphMS, a graph theoretical bioinformatic approach complementary to the database-dependent method. Using the AXL receptor tyrosine kinase (AXL) as a model glycoprotein with multiple N-glycosylation sites, we show that those LCMS features that could be grouped into graph networks on the basis of glycan mass and retention time differences were actually N-glycopeptides with the same peptide backbone but different N-glycan compositions. Conversely, unglycosylated peptides did not exhibit this grouping behavior. Furthermore, MS/MS sequencing of the glycan and peptide composition of just one N-glycopeptide in the graph was sufficient to identify the rest of the N-glycopeptides in the graph. By validating the identifications with exoglycosidase cocktails and MS/MS fragmentation, we determined the experimental false discovery rate of identifications to be 2.21%. GlycopeptideGraphMS detected more than 500 unique N-glycopeptides from AXL, triple the number found by a database search with Byonic software, and detected incorrect assignments due to a nonspecific protease cleavage. This method overcomes some limitations of the database approach and is a step closer to comprehensive automated glycoproteomics.

Glycoproteomic markers of hepatocellular carcinoma-mass spectrometry based approaches

Hepatocellular carcinoma (HCC) is the third most-common cause of cancer-related death worldwide. Most cases of HCC develop in patients that already have liver cirrhosis and have been recommended for surveillance for an early onset of HCC. Cirrhosis is the final common pathway for several etiologies of liver disease, including hepatitis B and C, alcohol, and increasingly non-alcoholic fatty liver disease. Only 20-30% of patients with HCC are eligible for curative therapy due primarily to inadequate early-detection strategies. Reliable, accurate biomarkers for HCC early detection provide the highest likelihood of curative therapy and survival; however, current early-detection methods that use abdominal ultrasound and serum alpha fetoprotein are inadequate due to poor adherence and limited sensitivity and specificity. There is an urgent need for convenient and highly accurate validated biomarkers for HCC early detection. The theme of this review is the development of new methods to discover glycoprotein-based markers for detection of HCC with mass spectrometry approaches. We outline the non-mass spectrometry based methods that have been used to discover HCC markers including immunoassays, capillary electrophoresis, 2-D gel electrophoresis, and lectin-FLISA assays. We describe the development and results of mass spectrometry-based assays for glycan screening based on either MALDI-MS or ESI analysis. These analyses might be based on the glycan content of serum or on glycan screening for target molecules from serum. We describe some of the specific markers that have been developed as a result, including for proteins such as Haptoglobin, Hemopexin, Kininogen, and others. We discuss the potential role for other technologies, including PGC chromatography and ion mobility, to separate isoforms of glycan markers. Analyses of glycopeptides based on new technologies and innovative softwares are described and also their potential role in discovery of markers of HCC. These technologies include new fragmentation methods such as EThcD and stepped HCD, which can identify large numbers of glycopeptide structures from serum. The key role of lectin extraction in various assays for intact glycopeptides or their truncated versions is also described, where various core-fucosylated and hyperfucosylated glycopeptides have been identified as potential markers of HCC. Finally, we describe the role of LC-MRMs or lectin-FLISA MRMs as a means to validate these glycoprotein markers from patient samples. These technological advancements in mass spectrometry have the potential to lead to novel biomarkers to improve the early detection of HCC.

Analysis of serum Haptoglobin using glycoproteomics and lectin immunoassay in liver diseases in Hepatitis B virus infection

BACKGROUND

Hepatocellular carcinoma (HCC) due to Hepatitis B viral (HBV) infection is a major cause in Asia-Pacific countries. Its early detection is of paramount importance using a marker having both sensitivity and specificity. The present study promises diagnostic and prognostic markers by the identification of site-specific glycoforms on Haptoglobin (Hp) using LC-MS/MS and lectin ELISA in liver diseased conditions in HBV infection.

METHODS

Three groups of patients: chronic, liver cirrhosis and HCC with HBV infection along with controls were enrolled. Hp was purified using affinity column chromatography and, peptide sequence, N-glycosylation site, glycan composition and glycoforms were identified using mass spectrometry. Quantitative lectin ELISA was used to measure levels of fucosylation on Hp in liver diseases due to HBV.

RESULTS

Hp levels were significantly lower in HCC when compared with Non-HCC cases (p < .05). Fucosylated glycoforms were significantly increased at site Asn184, Asn207 and Asn211 in liver diseased stages versus controls. A significant association was observed between the Fuc-Hp/Hp Elisa index and, advanced liver disease stages and controls using lectin Elisa (p < .001).

CONCLUSION

Quantitation of fucosylation levels on Hp protein using Lectin ELISA may be useful glycobiomarker either alone or in combination (AFP + DCP + FucHp; AUC = 0.94) in HBV HCC diagnosis in clinical practice.

Aberrant glycosylation and cancer biomarker discovery: a promising and thorny journey

Glycosylation is among the most important post-translational modifications for proteins and is of intrinsic complex character compared with DNAs and naked proteins. Indeed, over 50%-70% of proteins in circulation are glycosylated, and the "sweet attachments" have versatile structural and functional implications. Both the configuration and composition of the attached glycans affect the biological activities of consensus proteins significantly. Glycosylation is generated by complex biosynthetic pathways comprising hundreds of glycosyltransferases, glycosidases, transcriptional factors, transporters and the protein backbone. In addition, lack of direct genetic templates and glyco-specific antibodies such as those commonly used in DNA amplification and protein capture makes research on glycans and glycoproteins even more difficult, thus resulting in sparse knowledge on the pathophysiological implications of glycosylation. Fortunately, cutting-edge technologies have afforded new opportunities and approaches for investigating cancer-related glycosylation. Thus, glycans as well as aberrantly glycosylated protein-based cancer biomarkers have been increasingly recognized. This mini-review highlights the most recent developments in glyco-biomarker studies in an effort to discover clinically relevant cancer biomarkers using advanced analytical methodologies such as mass spectrometry, high-performance liquid chromatographic/ultra-performance liquid chromatography, capillary electrophoresis, and lectin-based technologies. Recent clinical-centered glycobiological studies focused on determining the regulatory mechanisms and the relation with diagnostics, prognostics and even therapeutics are also summarized. These studies indicate that glycomics is a treasure waiting to be mined where the growth of cancer-related glycomics and glycoproteomics is the next great challenge after genomics and proteomics.

Glycosylation markers in cancer

Alteration of glycosylation, a hallmark of cancer, results in the production of tumor-associated glycans or glycoproteins. These molecules are subsequently secreted or membrane-shed into the blood stream and thus serve as tumor-associated markers. Increased glycosylation in cancer is triggered by overexpression of glycoproteins that carry certain specific glycans, increase or decrease of nucleotide sugar donors and altered expression of glycosyltransferase and glycosidase enzymes. In this chapter, the biochemistry and function of glycoprotein, glycan and enzyme markers are reviewed. These glycosylation markers, applicable for detection and monitoring of cancer, include CA19-9, CA125, CEA, PSA and AFP. Because of their specific affinity to distinct sugar moieties, lectins are useful for developing assays to detect these tumor associated glycans and glycoproteins in clinical samples. As such, various enzyme-linked lectin assays (ELLA) have been developed for diagnosis, monitoring and prognosis. Because glycosylation changes occur early in cancer, the detection of tumor associated glycosylation markers using lectin based assays is an effective strategy to improve diagnosis and treatment resulting better outcomes clinically.

Differential Quantitative Determination of Site-Specific Intact N-Glycopeptides in Serum Haptoglobin between Hepatocellular Carcinoma and Cirrhosis Using LC-EThcD-MS/MS

Intact N-glycopeptide analysis remains challenging due to the complexity of glycopeptide structures, low abundance of glycopeptides in protein digests, and difficulties in data interpretation/quantitation. Herein, we developed a workflow that involved advanced methodologies, the EThcD-MS/MS fragmentation method and data interpretation software, for differential analysis of the microheterogeneity of site-specific intact N-glycopeptides of serum haptoglobin between early hepatocellular carcinoma (HCC) and liver cirrhosis. Haptoglobin was immunopurified from 20 μL of serum in patients with early HCC, liver cirrhosis, and healthy controls, respectively, followed by trypsin/GluC digestion, glycopeptide enrichment, and LC-EThcD-MS/MS analysis. Identification and differential quantitation of site-specific N-glycopeptides were performed using a combination of Byonic and Byologic software. In total, 93, 87, and 68 site-specific N-glycopeptides were identified in early HCC, liver cirrhosis, and healthy controls, respectively, with high confidence. The increased variety of N-glycopeptides in liver diseases compared to healthy controls was due to increased branching with hyper-fucosylation and sialylation. Differential quantitation analysis showed that 5 site-specific N-glycopeptides on sites N184 and N241 were significantly elevated in early HCC compared to cirrhosis ( p < 0.05) and normal controls ( p ≤ 0.001). The result demonstrates that the workflow provides a strategy for detailed profiles of N-glycopeptides of patient samples as well as for relative quantitation to determine the level changes in site-specific N-glycopeptides between disease states.

Current Technologies for Complex Glycoproteomics and Their Applications to Biology/Disease-Driven Glycoproteomics

Glycoproteomics is an important recent advance in the field of glycoscience. In glycomics, glycan structures are comprehensively analyzed after glycans are released from glycoproteins. However, a major limitation of glycomics is the lack of insight into glycoprotein functions. The Biology/Disease-driven Human Proteome Project has a particular focus on biological and medical applications. Glycoproteomics technologies aimed at obtaining a comprehensive understanding of intact glycoproteins, i.e., the kind of glycan structures that are attached to particular amino acids and proteins, have been developed. This Review focuses on the recent progress of the technologies and their applications. First, the methods for large-scale identification of both N- and O-glycosylated proteins are summarized. Next, the progress of analytical methods for intact glycopeptides is outlined. MS/MS-based methods were developed for improving the sensitivity and speed of the mass spectrometer, in parallel with the software for complex spectrum assignment. In addition, a unique approach to identify intact glycopeptides using MS1-based accurate masses is introduced. Finally, as an advance of glycomics, two approaches to provide the spatial distribution of glycans in cells are described, i.e., MS imaging and lectin microarray. These methods allow rapid glycomic profiling of different types of biological samples and thus facilitate glycoproteomics.

Glycoproteomic Alterations in Drug-Resistant Nonsmall Cell Lung Cancer Cells Revealed by Lectin Magnetic Nanoprobe-Based Mass Spectrometry

Understanding the functional role of glycosylation-mediated pathogenesis requires deep characterization of glycoproteome, which remains extremely challenging due to the inherently complex nature of glycoproteins. We demonstrate the utility of lectin-magnetic nanoprobe (MNP@lectin) coupled to Orbitrap HCD-CID-MS/MS for complementary glycotope-specific enrichment and site-specific glycosylation analysis of the glycoproteome. By three nanoprobes, MNP@ConA, MNP@AAL, and MNP@SNA, our results revealed the first large-scale glycoproteome of nonsmall cell lung cancer (NSCLC) with 2290 and 2767 nonredundant glycopeptides confidently identified (Byonic score ≥100) in EGFR-TKI-sensitive PC9 and -resistant PC9-IR cells, respectively, especially with more fucosylated and sialylated glycopeptides in PC9-IR cells. The complementary enrichment was demonstrated with only five glycopeptides commonly enriched in three MNP@lectins. Glycotope specificity of 79 and 62% for enrichment was achieved using MNP@AAL and MNP@SNA, respectively. Label-free quantitation revealed predominant fucosylation in PC9-IR cells, suggesting its potential role associated with NSCLC resistance. Moreover, without immunoprecipitation, this multilectin nanoprobe allows the sensitive identification of 51 glycopeptides from 10 of 12 reported sites from onco-protein EGFR. Our results not only demonstrated a sensitive approach to study the vastly under-represented N-glycoprotome but also may pave the way for a glycoproteomic atlas to further explore the site-specific function of glycoproteins associated with drug resistance in NSCLC.

N-Linked Glycopeptide Identification Based on Open Mass Spectral Library Search

Confident characterization of intact glycopeptides is a challenging task in mass spectrometry-based glycoproteomics due to microheterogeneity of glycosylation, complexity of glycans, and insufficient fragmentation of peptide bones. Open mass spectral library search is a promising computational approach to peptide identification, but its potential in the identification of glycopeptides has not been fully explored. Here we present pMatchGlyco, a new spectral library search tool for intact N-linked glycopeptide identification using high-energy collisional dissociation (HCD) tandem mass spectrometry (MS/MS) data. In pMatchGlyco, (1) MS/MS spectra of deglycopeptides are used to create spectral library, (2) MS/MS spectra of glycopeptides are matched to the spectra in library in an open (precursor tolerant) manner and the glycans are inferred, and (3) a false discovery rate is estimated for top-scored matches above a threshold. The efficiency and reliability of pMatchGlyco were demonstrated on a data set of mixture sample of six standard glycoproteins and a complex glycoprotein data set generated from human cancer cell line OVCAR3.

A Crude 1-DNJ Extract from Home Made Bombyx Batryticatus Inhibits Diabetic Cardiomyopathy-Associated Fibrosis in db/db Mice and Reduces Protein N-Glycosylation Levels

The traditional Chinese drug Bombyx Batryticatus (BB), which is also named the white stiff silkworm, has been widely used in Chinese clinics for thousands of years. It is famous for its antispasmodic and blood circulation-promoting effects. Cardiomyocyte hypertrophy, interstitial cell hyperplasia, and myocardial fibrosis are closely related to the N-glycosylation of key proteins. To examine the alterations of N-glycosylation that occur in diabetic myocardium during the early stage of the disease, and to clarify the therapeutic effect of 1-Deoxynojirimycin (1-DNJ) extracted from BB, we used the db/db (diabetic) mouse model and an approach based on hydrophilic chromatography solid-phase extraction integrated with an liquid Chromatograph Mass Spectrometer (LC-MS) identification strategy to perform a site-specific N-glycosylation analysis of left ventricular cardiomyocyte proteins. Advanced glycation end products (AGEs), hydroxyproline, connective tissue growth factor (CTGF), and other serum biochemical indicators were measured with enzyme-linked immunosorbent assays (ELISA). In addition, the α-1,6-fucosylation of N-glycans was profiled with lens culinaris agglutinin (LCA) lectin blots and fluorescein isothiocyanate (FITC)-labelled lectin affinity histochemistry. The results indicated that 1-DNJ administration obviously downregulated myocardium protein N-glycosylation in db/db mice. The expression levels of serum indicators and fibrosis-related cytokines were reduced significantly by 1-DNJ in a dose-dependent manner. The glycan α-1,6-fucosylation level of the db/db mouse myocardium was elevated, and the intervention effect of 1-DNJ administration on N-glycan α-1,6-fucosylation was significant. To verify this result, the well-known transforming growth factor-β (TGF-β)/Smad2/3 pathway was selected, and core α-1,6-fucosylated TGF-β receptor II (TGFR-βII) was analysed semi-quantitatively with western blotting. The result supported the conclusions obtained from LCA lectin affinity histochemistry and lectin blot analysis. The expression level of α-1,6-fucosyltransferase (FUT8) mRNA was also detected, and the results showed that 1-DNJ administration did not cause obvious inhibitory effects on FUT8 expression. Therefore, the mechanism of 1-DNJ for relieving diabetic cardiomyopathy (DCM)-associated fibrosis can be concluded as the inhibition of N-acetylglucosamine (N-GlcNAc) formation and the reduction of substrate concentration.

An approach for N-linked glycan identification from MS/MS spectra by target-decoy strategy

Glycan structure determination serves as an essential step for the thorough investigation of the structure and function of protein. Currently, appropriate sample preparation followed by tandem mass spectrometry has emerged as the dominant technique for the characterization of glycans and glycopeptides. Although extensive efforts have been made to the development of computational approaches for the automated interpretation of glycopeptide spectra, the previously appeared methods lack a reasonable quality control strategy for the statistical validation of reported results. In this manuscript, we introduced a novel method that constructed a decoy glycan database based on the glycan structures in the target database, and searched the experimental spectra against both the target and decoy databases to find the best matched glycans. Specifically, a two-layer scoring scheme for calculating a normalized matching score is applied in the search procedure which enables the unbiased ranking of the matched glycans. Experimental analysis showed that our proposed method can report more structures with high confidence compared with previous approaches.

Large-scale intact glycopeptide identification by Mascot database search

Workflows capable of determining glycopeptides in large-scale are missing in the field of glycoproteomics. We present an approach for automated annotation of intact glycopeptide mass spectra. The steps in adopting the Mascot search engine for intact glycopeptide analysis included: (i) assigning one letter codes for monosaccharides, (ii) linearizing glycan sequences and (iii) preparing custom glycoprotein databases. Automated annotation of both N- and O-linked glycopeptides was proven using standard glycoproteins. In a large-scale study, a total of 257 glycoproteins containing 970 unique glycosylation sites and 3447 non-redundant N-linked glycopeptide variants were identified in 24 serum samples. Thus, a single tool was developed that collectively allows the (i) elucidation of N- and O-linked glycopeptide spectra, (ii) matching glycopeptides to known protein sequences, and (iii) high-throughput, batch-wise analysis of large-scale glycoproteomics data sets.

Dissecting the Dissociation Patterns of Fucosylated Glycopeptides Undergoing CID: A Case Study in Improving Automated Glycopeptide Analysis Scoring Algorithms

The need to investigate the fragmentation of fucosylated glycopeptides is driven by recent work showing that at least one, and perhaps many, glycopeptide analysis scoring algorithms are less effective at identifying fucosylated glycopeptides than non-fucosylated glycopeptides. Herein, we study the CID fragmentation characteristics of fucosylated glycopeptides and the scoring rules of the glycopeptide analysis software, GlycoPep Grader, in an effort to improve automated assignments of these important glycopeptides. We identified some prominent product ions from a common fragmentation pathway of fucosylated glycopeptides that were not accounted for in the scoring rules. Based on this finding, we propose new scoring rules for fucosylated glycopeptides that can be incorporated into GlycoPep Grader and other similar analysis software tools to more accurately identify these species. The approach used here, to improve one particular scoring algorithm, could henceforth be used to improve any other algorithm that assigns glycopeptides based on their MS/MS data.

Intact glycopeptide characterization using mass spectrometry

Glycosylation is one of the most prominent and extensively studied protein post-translational modifications. However, traditional proteomic studies at the peptide level (bottom-up) rarely characterize intact glycopeptides (glycosylated peptides without removing glycans), so no glycoprotein heterogeneity information is retained. Intact glycopeptide characterization, on the other hand, provides opportunities to simultaneously elucidate the glycan structure and the glycosylation site needed to reveal the actual biological function of protein glycosylation. Recently, significant improvements have been made in the characterization of intact glycopeptides, ranging from enrichment and separation, mass spectroscopy (MS) detection, to bioinformatics analysis. In this review, we recapitulated currently available intact glycopeptide characterization methods with respect to their advantages and limitations as well as their potential applications.

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.

Electron-Transfer/Higher-Energy Collision Dissociation (EThcD)-Enabled Intact Glycopeptide/Glycoproteome Characterization

Protein glycosylation, one of the most heterogeneous post-translational modifications, can play a major role in cellular signal transduction and disease progression. Traditional mass spectrometry (MS)-based large-scale glycoprotein sequencing studies heavily rely on identifying enzymatically released glycans and their original peptide backbone separately, as there is no efficient fragmentation method to produce unbiased glycan and peptide product ions simultaneously in a single spectrum, and that can be conveniently applied to high throughput glycoproteome characterization, especially for N-glycopeptides, which can have much more branched glycan side chains than relatively less complex O-linked glycans. In this study, a redefined electron-transfer/higher-energy collision dissociation (EThcD) fragmentation scheme is applied to incorporate both glycan and peptide fragments in one single spectrum, enabling complete information to be gathered and great microheterogeneity details to be revealed. Fetuin was first utilized to prove the applicability with 19 glycopeptides and corresponding five glycosylation sites identified. Subsequent experiments tested its utility for human plasma N-glycoproteins. Large-scale studies explored N-glycoproteomics in rat carotid arteries over the course of restenosis progression to investigate the potential role of glycosylation. The integrated fragmentation scheme provides a powerful tool for the analysis of intact N-glycopeptides and N-glycoproteomics. We also anticipate this approach can be readily applied to large-scale O-glycoproteome characterization. Graphical Abstract ᅟ.

Direct analysis of aberrant glycosylation on haptoglobin in patients with gastric cancer

Based on our previous studies, differential analysis of N-glycan expression bound on serum haptoglobin reveals the quantitative variation on gastric cancer patients. In this prospective case-control study, we explore the clinically relevant glycan markers for gastric cancer diagnosis. Serum samples were collected from patients with gastric cancer (n = 44) and healthy control (n = 44). N-glycans alteration was monitored by intact analysis of Hp using liquid chromatography–mass spectrometry followed by immunoaffinity purification with the serum samples. Intensity and frequency markers were defined depending on the mass spectrometry data analysis. Multiple markers were found with high diagnostic efficacy. As intensity markers (I-marker), six markers were discovered with the AUC > 0.8. The high efficiency markers exhibited AUC of 0.93 with a specificity of 86% when the sensitivity was set to 95%. We additionally established frequency marker (f-marker) panels based on the tendency of high N-glycan expression. The AUC to conclude patients and control group were 0.82 and 0.79, respectively. This study suggested that N-glycan variation of serum haptoglobin were associated with patients with gastric cancer and might be a promising marker for the cancer screening.

Two New Tools for Glycopeptide Analysis Researchers: A Glycopeptide Decoy Generator and a Large Data Set of Assigned CID Spectra of Glycopeptides

The glycopeptide analysis field is tightly constrained by a lack of effective tools that translate mass spectrometry data into meaningful chemical information, and perhaps the most challenging aspect of building effective glycopeptide analysis software is designing an accurate scoring algorithm for MS/MS data. We provide the glycoproteomics community with two tools to address this challenge. The first tool, a curated set of 100 expert-assigned CID spectra of glycopeptides, contains a diverse set of spectra from a variety of glycan types; the second tool, Glycopeptide Decoy Generator, is a new software application that generates glycopeptide decoys de novo. We developed these tools so that emerging methods of assigning glycopeptides' CID spectra could be rigorously tested. Software developers or those interested in developing skills in expert (manual) analysis can use these tools to facilitate their work. We demonstrate the tools' utility in assessing the quality of one particular glycopeptide software package, GlycoPep Grader, which assigns glycopeptides to CID spectra. We first acquired the set of 100 expert assigned CID spectra; then, we used the Decoy Generator (described herein) to generate 20 decoys per target glycopeptide. The assigned spectra and decoys were used to test the accuracy of GlycoPep Grader's scoring algorithm; new strengths and weaknesses were identified in the algorithm using this approach. Both newly developed tools are freely available. The software can be downloaded at http://glycopro.chem.ku.edu/GPJ.jar.

Dengue Virus Glycosylation: What Do We Know?

In many infectious diseases caused by either viruses or bacteria, pathogen glycoproteins play important roles during the infection cycle, ranging from entry to successful intracellular replication and host immune evasion. Dengue is no exception. Dengue virus glycoproteins, envelope protein (E) and non-structural protein 1 (NS1) are two popular sub-unit vaccine candidates. E protein on the virion surface is the major target of neutralizing antibodies. NS1 which is secreted during DENV infection has been shown to induce a variety of host responses through its binding to several host factors. However, despite their critical role in disease and protection, the glycosylated variants of these two proteins and their biological importance have remained understudied. In this review, we seek to provide a comprehensive summary of the current knowledge on protein glycosylation in DENV, and its role in virus biogenesis, host cell receptor interaction and disease pathogenesis.