Large-scale quantitative glycoproteomics analysis of site-specific glycosylation occupancy

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

OBJECTIVE AND DESIGN

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.

METHODS AND RESULTS

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.

CONCLUSIONS

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.

Mass spectrometry analysis of intact protein N-glycosylation signatures of cells and sera in pancreatic adenocarcinomas

Pancreatic cancer is among the most malignant cancers, and thus early intervention is the key to better survival outcomes. However, no methods have been derived that can reliably identify early precursors of development into malignancy. Therefore, it is urgent to discover early molecular changes during pancreatic tumorigenesis. As aberrant glycosylation is closely associated with cancer progression, numerous efforts have been made to mine glycosylation changes as biomarkers for diagnosis; however, detailed glycoproteomic information, especially site-specific N-glycosylation changes in pancreatic cancer with and without drug treatment, needs to be further explored. Herein, we used comprehensive solid-phase chemoenzymatic glycoproteomics to analyze glycans, glycosites, and intact glycopeptides in pancreatic cancer cells and patient sera. The profiling of N-glycans in cancer cells revealed an increase in the secreted glycoproteins from the primary tumor of MIA PaCa-2 cells, whereas human sera, which contain many secreted glycoproteins, had significant changes of glycans at their specific glycosites. These results indicated the potential role for tumor-specific glycosylation as disease biomarkers. We also found that AMG-510, a small molecule inhibitor against Kirsten rat sarcoma viral oncogene homolog (KRAS) G12C mutation, profoundly reduced the glycosylation level in MIA PaCa-2 cells, suggesting that KRAS plays a role in the cellular glycosylation process, and thus glycosylation inhibition contributes to the anti-tumor effect of AMG-510.

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.

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.

Altered glycosylation in pancreatic cancer and beyond

Pancreatic ductal adenocarcinoma (PDA) is one of the deadliest cancers and is projected to soon be the second leading cause of cancer death. Median survival of PDA patients is 6-10 mo, with the majority of diagnoses occurring at later, metastatic stages that are refractory to treatment and accompanied by worsening prognoses. Glycosylation is one of the most common types of post-translational modifications. The complex landscape of glycosylation produces an extensive repertoire of glycan moieties, glycoproteins, and glycolipids, thus adding a dynamic and tunable level of intra- and intercellular signaling regulation. Aberrant glycosylation is a feature of cancer progression and influences a broad range of signaling pathways to promote disease onset and progression. However, despite being so common, the functional consequences of altered glycosylation and their potential as therapeutic targets remain poorly understood and vastly understudied in the context of PDA. In this review, the functionality of glycans as they contribute to hallmarks of PDA are highlighted as active regulators of disease onset, tumor progression, metastatic capability, therapeutic resistance, and remodeling of the tumor immune microenvironment. A deeper understanding of the functional consequences of altered glycosylation will facilitate future hypothesis-driven studies and identify novel therapeutic strategies in PDA.

Native glycan fragments detected by MALDI mass spectrometry imaging are independent prognostic factors in pancreatic ductal adenocarcinoma

Background

Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest malignancies to date. The impressively developed stroma that surrounds and modulates the behavior of cancer cells is one of the main factors regulating the PDAC growth, metastasis and therapy resistance. Here, we postulate that stromal and cancer cell compartments differentiate in protein/lipid glycosylation patterns and analyze differences in glycan fragments in those compartments with clinicopathologic correlates.

Results

We analyzed native glycan fragments in 109 human FFPE PDAC samples using high mass resolution matrix-assisted laser desorption/ionization Fourier-transform ion cyclotron resonance mass spectrometric imaging (MALDI-FT-ICR-MSI). Our method allows detection of native glycan fragments without previous digestion with PNGase or any other biochemical reaction. With this method, 8 and 18 native glycans were identified as uniquely expressed in only stromal or only cancer cell compartment, respectively. Kaplan–Meier survival model identified glycan fragments that are expressed in cancer cell or stromal compartment and significantly associated with patient outcome. Among cancer cell region-specific glycans, 10 predicted better and 6 worse patient survival. In the stroma, 1 glycan predicted good and 4 poor patient survival. Using factor analysis as a dimension reduction method, we were able to group the identified glycans in 2 factors. Multivariate analysis revealed that these factors can be used as independent survival prognostic elements with regard to the established Union for International Cancer Control (UICC) classification both in tumor and stroma regions.

Conclusion

Our method allows in situ detection of naturally occurring glycans in FFPE samples of human PDAC tissue and highlights the differences among glycans found in stromal and cancer cell compartment offering a basis for further exploration on the role of specific glycans in cancer–stroma communication.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13550-021-00862-y.

Global and site-specific analysis of protein glycosylation in complex biological systems with Mass Spectrometry

Protein glycosylation is ubiquitous in biological systems and plays essential roles in many cellular events. Global and site-specific analysis of glycoproteins in complex biological samples can advance our understanding of glycoprotein functions and cellular activities. However, it is extraordinarily challenging because of the low abundance of many glycoproteins and the heterogeneity of glycan structures. The emergence of mass spectrometry (MS)-based proteomics has provided us an excellent opportunity to comprehensively study proteins and their modifications, including glycosylation. In this review, we first summarize major methods for glycopeptide/glycoprotein enrichment, followed by the chemical and enzymatic methods to generate a mass tag for glycosylation site identification. We next discuss the systematic and quantitative analysis of glycoprotein dynamics. Reversible protein glycosylation is dynamic, and systematic study of glycoprotein dynamics helps us gain insight into glycoprotein functions. The last part of this review focuses on the applications of MS-based proteomics to study glycoproteins in different biological systems, including yeasts, plants, mice, human cells, and clinical samples. Intact glycopeptide analysis is also included in this section. Because of the importance of glycoproteins in complex biological systems, the field of glycoproteomics will continue to grow in the next decade. Innovative and effective MS-based methods will exponentially advance glycoscience, and enable us to identify glycoproteins as effective biomarkers for disease detection and drug targets for disease treatment. © 2019 Wiley Periodicals, Inc. Mass Spec Rev 9999: XX-XX, 2019.

The glycosylation landscape of pancreatic cancer

Pancreatic adenocarcinoma is a lethal disease with a 5-year survival rate of <5%, the lowest of all types of cancer. The diagnosis of pancreatic cancer relies on imaging and tissue biopsy, and the only curative therapy is complete surgical resection. Pancreatic cancer has the propensity to metastasise at an early stage and the majority of patients are diagnosed when surgery is no longer an option. Hence, there is an urgent need to identify biomarkers to enable early diagnosis, and to develop new therapeutic strategies. One approach for this involves targeting cancer-associated glycans. The most widely used serological marker in pancreatic cancer is the carbohydrate antigen CA 19-9 which contains a glycan known as sialyl Lewis A (sLeA). The CA 19-9 assay is used routinely to monitor response to treatment, but concerns have been raised about its sensitivity and specificity as a diagnostic biomarker. In addition to sLeA, a wide range of alterations to other important glycans have been observed in pancreatic cancer. These include increases in the sialyl Lewis X antigen (sLex), an increase in truncated O-glycans (Tn and sTn), increased branched and fucosylated N-glycans, upregulation of specific proteoglycans and galectins, and increased O-GlcNAcylation. Growing evidence supports crucial roles for glycans in all stages of cancer progression, and it is well established that glycans regulate tumour proliferation, invasion and metastasis. The present review describes the biological significance of glycans in pancreatic cancer, and discusses the clinical value of exploiting aberrant glycosylation to improve the diagnosis and treatment of this deadly disease.

Disrupting glutamine metabolic pathways to sensitize gemcitabine-resistant pancreatic cancer

Pancreatic cancer is a lethal disease with poor prognosis. Gemcitabine has been the first line systemic treatment for pancreatic cancer. However, the rapid development of drug resistance has been a major hurdle in gemcitabine therapy leading to unsatisfactory patient outcomes. With the recent renewed understanding of glutamine metabolism involvement in drug resistance and immuno-response, we investigated the anti-tumor effect of a glutamine analog (6-diazo-5-oxo-L-norleucine) as an adjuvant treatment to sensitize chemoresistant pancreatic cancer cells. We demonstrate that disruption of glutamine metabolic pathways improves the efficacy of gemcitabine treatment. Such a disruption induces a cascade of events which impacts glycan biosynthesis through Hexosamine Biosynthesis Pathway (HBP), as well as cellular redox homeostasis, resulting in global changes in protein glycosylation, expression and functional effects. The proteome alterations induced in the resistant cancer cells and the secreted exosomes are intricately associated with the reduction in cell proliferation and the enhancement of cancer cell chemosensitivity. Proteins associated with EGFR signaling, including downstream AKT-mTOR pathways, MAPK pathway, as well as redox enzymes were downregulated in response to disruption of glutamine metabolic pathways.

Algorithms and design strategies towards automated glycoproteomics analysis

Glycoproteomics involves the study of glycosylation events on protein sequences ranging from purified proteins to whole proteome scales. Understanding these complex post-translational modification (PTM) events requires elucidation of the glycan moieties (monosaccharide sequences and glycosidic linkages between residues), protein sequences, as well as site-specific attachment of glycan moieties onto protein sequences, in a spatial and temporal manner in a variety of biological contexts. Compared with proteomics, bioinformatics for glycoproteomics is immature and many researchers still rely on tedious manual interpretation of glycoproteomics data. As sample preparation protocols and analysis techniques have matured, the number of publications on glycoproteomics and bioinformatics has increased substantially; however, the lack of consensus on tool development and code reuse limits the dissemination of bioinformatics tools because it requires significant effort to migrate a computational tool tailored for one method design to alternative methods. This review discusses algorithms and methods in glycoproteomics, and refers to the general proteomics field for potential solutions. It also introduces general strategies for tool integration and pipeline construction in order to better serve the glycoproteomics community. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:475-498, 2017.

N-Glycoprofiling Analysis for Carbohydrate Composition and Site-Occupancy Determination in a Poly-Glycosylated Protein: Human Thyrotropin of Different Origins

Human thyrotropin (hTSH) is a glycoprotein with three potential glycosylation sites: two in the α-subunit and one in the β-subunit. These sites are not always occupied and occupancy is frequently neglected in glycoprotein characterization, even though it is related to folding, trafficking, initiation of inflammation and host defense, as well as congenital disorders of glycosylation (CDG). For the first time N-glycoprofiling analysis was applied to the site-occupancy determination of two native pituitary hTSH, in comparison with three recombinant preparations of hTSH, a widely used biopharmaceutical. A single methodology provided the: (i) average N-glycan mass; (ii) mass fraction of each monosaccharide and of sulfate; and (iii) percent carbohydrate. The results indicate that the occupancy (65%–87%) and carbohydrate mass (12%–19%) can be up to 34%–57% higher in recombinant hormones. The average glycan mass is 24% lower in pituitary hTSH and contains ~3-fold fewer moles of galactose (p < 0.005) and sialic acid (p < 0.01). One of the two native preparations, which had the smallest glycan mass together with the lowest occupancy and GalNAc, sulfate, Gal and sialic acid contents, also presented the lowest in vivo bioactivity and circulatory half-life. The methodology described, comparing a recombinant biopharmaceutical to its native equivalent, can be applied to any physiologically or clinical relevant glycoprotein.

Progress and potential of exosome analysis for early pancreatic cancer detection

INTRODUCTION

Pancreatic cancer (PaCa) is the most deadly malignancy, due to late diagnosis prohibiting surgery. Thus, strong efforts are taken improving early diagnosis via biomarkers recovered in the serum of PaCa patients.

AREAS COVERED

One promising option are PaCa-derived exosomes in patients' sera. Exosomes, small vesicles delivered by live cells and recovered in all body fluids, are a powerful diagnostic tool due to relative stability and composition covering the whole range of cancer-related biomarkers including proteins, metabolites, DNA, DNA modifications, coding and noncoding RNA. We discuss the mechanisms accounting for the condensed packaging of biomarkers, refer to studies using PaCa serum-exosomes for diagnosis. Based on an extensive literature search, we outline questions that answers may help establishing a serum-exosome-based screening for early PaCa detection. Expert commentary: Improved proteomic and genomic characterization and progress in the biogenesis of exosomes will allow for optimized and unified screening panels for PaCa diagnosis via TEX in body fluids.

Large-scale identification of core-fucosylated glycopeptide sites in pancreatic cancer serum using mass spectrometry

Glycosylation has significant effects on protein function and cell metastasis, which are important in cancer progression. It is of great interest to identify site-specific glycosylation in search of potential cancer biomarkers. However, the abundance of glycopeptides is low compared to that of nonglycopeptides after trypsin digestion of serum samples, and the mass spectrometric signals of glycopeptides are often masked by coeluting nonglycopeptides due to low ionization efficiency. Selective enrichment of glycopeptides from complex serum samples is essential for mass spectrometry (MS)-based analysis. Herein, a strategy has been optimized using LCA enrichment to improve the identification of core-fucosylation (CF) sites in serum of pancreatic cancer patients. The optimized strategy was then applied to analyze CF glycopeptide sites in 13 sets of serum samples from pancreatic cancer, chronic pancreatitis, healthy controls, and a standard reference. In total, 630 core-fucosylation sites were identified from 322 CF proteins in pancreatic cancer patient serum using an Orbitrap Elite mass spectrometer. Further data analysis revealed that 8 CF peptides exhibited a significant difference between pancreatic cancer and other controls, which may be potential diagnostic biomarkers for pancreatic cancer.

N-glycoprofiling analysis in a simple glycoprotein model: a comparison between recombinant and pituitary glycosylated human prolactin

Human prolactin (hPRL) is a polypeptide hormone occurring in the non-glycosylated (NG-hPRL) and glycosylated (G-hPRL) forms, with MM of approximately 23 and 25kDa, respectively. It has a single, partially occupied N-glycosylation site located at Asn-31, which makes it a particularly simple and interesting model for glycosylation studies. The bioactivity of G-hPRL is lower than that of NG-hPRL (by ca. 4-fold) and its physiological function is not clear. However, carbohydrate moieties generally play important roles in the biosynthesis, secretion, biological activity, and plasma survival of glycohormones and can vary depending on the host cell. The main objective of this study was to determine the N-glycan structures present in native, pituitary G-hPRL and compare them with those present in the recombinant hormone. To obtain recombinant G-hPRL, genetically modified Chinese hamster ovary cells (CHO), adapted to growth in suspension, were treated with cycloheximide, thus increasing the glycosylation site occupancy from 5.5% to 38.3%, thereby facilitating G-hPRL purification. CHO cell-derived G-hPRL (CHO-G-hPRL) was compared to pituitary G-hPRL (pit-G-hPRL) especially with regard to N-glycoprofiling. Among the main differences found in the pituitary sample were an extremely low presence of sialylated (1.7%) and a high percentage of sulfated (74.0%) and of fucosylated (90.5%) glycans. A ∼6-fold lower in vitro bioactivity and a higher clearance rate in mice were also found for pit-G-hPRL versus CHO-G-hPRL. N-Glycan profiling proved to be a useful and accurate methodology also for MM and carbohydrate content determination for the two G-hPRL preparations, in good agreement with the values obtained directly via MALDI-TOF-MS.

Label-free glycopeptide quantification for biomarker discovery in human sera

Glycan moieties of glycoproteins modulate many biological processes in mammals, such as immune response, inflammation, and cell signaling. Numerous studies show that many human diseases are correlated with quantitative alteration of protein glycosylation. In some cases, these changes can occur for certain types of glycans over specific sites in a glycoprotein rather than on the global abundance of the glycoprotein. Conventional analytical techniques that analyze the abundance of glycans cleaved from glycoproteins cannot reveal these subtle effects. Here we present a novel statistical method to quantify the site-specific glycosylation of glycoproteins in complex samples using label-free mass spectrometric techniques. Abundance variations between sites of a glycoprotein as well as different glycoforms, that is, glycopeptides with different glycans attached to the same site, can be detected using these techniques. We applied our method to an esophageal cancer study based on blood serum samples from cancer patients in an attempt to detect potential biomarkers of site-specific N-linked glycosylation. A few glycoproteins, including vitronectin, showed significantly different site-specific glycosylations within cancer/control samples, indicating that our method is ready to be used for the discovery of glycosylated biomarkers.

Reliable determination of site-specific in vivo protein N-glycosylation based on collision-induced MS/MS and chromatographic retention time

Site-specific glycopeptide mapping for simultaneous glycan and peptide characterization by MS is difficult because of the heterogeneity and diversity of glycosylation in proteins and the lack of complete fragmentation information for either peptides or glycans with current fragmentation technologies. Indeed, multiple peptide and glycan combinations can readily match the same mass of glycopeptides even with mass errors less than 5 ppm providing considerably ambiguity and analysis of complex mixtures of glycopeptides becomes quite challenging in the case of large proteins. Here we report a novel strategy to reliably determine site-specific N-glycosylation mapping by combining collision-induced dissociation (CID)-only fragmentation with chromatographic retention times of glycopeptides. This approach leverages an experimental pipeline with parallel analysis of glyco- and deglycopeptides. As the test case we chose ABCA4, a large integral membrane protein with 16 predicted sites for N-glycosylation. Taking advantage of CID features such as high scan speed and high intensity of fragment ions together combined with the retention times of glycopeptides to conclusively identify the non-glycolytic peptide from which the glycopeptide was derived, we obtained virtually complete information about glycan compositions and peptide sequences, as well as the N-glycosylation site occupancy and relative abundances of each glycoform at specific sites for ABCA4. The challenges provided by this example provide guidance in analyzing complex relatively pure glycoproteins and potentially even more complex glycoprotein mixtures.

Glycoproteomic and glycomic databases

Protein glycosylation serves critical roles in the cellular and biological processes of many organisms. Aberrant glycosylation has been associated with many illnesses such as hereditary and chronic diseases like cancer, cardiovascular diseases, neurological disorders, and immunological disorders. Emerging mass spectrometry (MS) technologies that enable the high-throughput identification of glycoproteins and glycans have accelerated the analysis and made possible the creation of dynamic and expanding databases. Although glycosylation-related databases have been established by many laboratories and institutions, they are not yet widely known in the community. Our study reviews 15 different publicly available databases and identifies their key elements so that users can identify the most applicable platform for their analytical needs. These databases include biological information on the experimentally identified glycans and glycopeptides from various cells and organisms such as human, rat, mouse, fly and zebrafish. The features of these databases - 7 for glycoproteomic data, 6 for glycomic data, and 2 for glycan binding proteins are summarized including the enrichment techniques that are used for glycoproteome and glycan identification. Furthermore databases such as Unipep, GlycoFly, GlycoFish recently established by our group are introduced. The unique features of each database, such as the analytical methods used and bioinformatical tools available are summarized. This information will be a valuable resource for the glycobiology community as it presents the analytical methods and glycosylation related databases together in one compendium. It will also represent a step towards the desired long term goal of integrating the different databases of glycosylation in order to characterize and categorize glycoproteins and glycans better for biomedical research.

Quantitative glycoproteomics analysis reveals changes in N-glycosylation level associated with pancreatic ductal adenocarcinoma

Glycosylation plays an important role in epithelial cancers, including pancreatic ductal adenocarcinoma. However, little is known about the glycoproteome of the human pancreas or its alterations associated with pancreatic tumorigenesis. Using quantitative glycoproteomics approach, we investigated protein N-glycosylation in pancreatic tumor tissue in comparison with normal pancreas and chronic pancreatitis tissue. The study lead to the discovery of a roster of glycoproteins with aberrant N-glycosylation level associated with pancreatic cancer, including mucin-5AC (MUC5AC), carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5), insulin-like growth factor binding protein (IGFBP3), and galectin-3-binding protein (LGALS3BP). Pathway analysis of cancer-associated aberrant glycoproteins revealed an emerging phenomenon that increased activity of N-glycosylation was implicated in several pancreatic cancer pathways, including TGF-β, TNF, NF-kappa-B, and TFEB-related lysosomal changes. In addition, the study provided evidence that specific N-glycosylation sites within certain individual proteins can have significantly altered glycosylation occupancy in pancreatic cancer, reflecting the complexity of the molecular mechanisms underlying cancer-associated glycosylation events.

Quantitative glycoproteomics for N-glycoproteome profiling

Glycoproteomics, the global analysis of glycoproteins, is a subfield of proteomics with high biological and clinical relevance. Glycoproteomics integrates knowledge and techniques drawing from glycotechnology, separation science, mass spectrometry, and bioinformatics to support systematic identification and quantification of glycoproteins in a complex biological sample. In this chapter, we describe a shotgun proteomics-based glycoproteomics platform that provides precise mapping of protein N-glycosylation sites and quantitative assessment of glycosylation site occupancy on a global scale.

The GlycoFilter: a simple and comprehensive sample preparation platform for proteomics, N-glycomics and glycosylation site assignment

Current strategies to study N-glycoproteins in complex samples are often discrete, focusing on either N-glycans or N-glycosites enriched by sugar-based techniques. In this study we report a simple and rapid sample preparation platform, the GlycoFilter, which allows a comprehensive characterization of N-glycans, N-glycosites, and proteins in a single workflow. Both PNGase F catalyzed de-N-glycosylation and trypsin digestions are accelerated by microwave irradiation and performed sequentially in a single spin filter. Both N-glycans and peptides (including de-N-glycosylated peptides) are separately collected by filtration. The condition to effectively collect complex and heterogeneous N-glycans was established on model glycoproteins, bovine ribonuclease B, bovine fetuin, and human serum IgG. With this platform, the N-glycome, N-glycoproteome and proteome of human urine and plasma were characterized. Overall, a total of 865 and 295 N-glycosites were identified from three pairs of urine and plasma samples, respectively. Many sites were defined unambiguously as partially occupied by the detection of their nonsugar-modified peptides (128 from urine and 61 from plasma), demonstrating that partial occupancy of N-glycosylation occurs frequently. Given the likely high prevalence and variability of partial occupancy, glycoprotein quantification based exclusively on deglycosylated peptides may lead to inaccurate quantification.

Mass Spectrometry Investigation of Glycosylation Aberration via De-N-Glycopeptide Analysis

Proteomics research on glycan alterations has received great attention owing to their implications in disease initiation and progression. Determination of the glycoprotein expression remains one of the most challenging tasks as the glycan residues in a given glycoprotein exist in complex branched structures and differ in linkage. In view of the vital role of glycan changes in cellular processes and disease progression, there has been an increased interest in developing methodologies for the detection of these changes. A subset of proteomics methods are discussed here that demonstrate the utility of the glycan-free de-N-glycopeptide analysis for the screening of complex glycoproteome as well as discovery of glycopeptide/glycoprotein biomarkers.