Computational framework for identification of intact glycopeptides in complex samples

Characterization of Site-Specific N-Glycopeptide Isoforms of α-1-Acid Glycoprotein from an Interlaboratory Study Using LC-MS/MS

Glycoprotein conformations are complex and heterogeneous. Currently, site-specific characterization of glycopeptides is a challenge. We sought to establish an efficient method of N-glycoprotein characterization using mass spectrometry (MS). Using alpha-1-acid glycoprotein (AGP) as a model N-glycoprotein, we identified its tryptic N-glycopeptides and examined the data reproducibility in seven laboratories running different LC-MS/MS platforms. We used three test samples and one blind sample to evaluate instrument performance with entire sample preparation workflow. 165 site-specific N-glycopeptides representative of all N-glycosylation sites were identified from AGP 1 and AGP 2 isoforms. The glycopeptide fragmentations by collision-induced dissociation or higher-energy collisional dissociation (HCD) varied based on the MS analyzer. Orbitrap Elite identified the greatest number of AGP N-glycopeptides, followed by Triple TOF and Q-Exactive Plus. Reproducible generation of oxonium ions, glycan-cleaved glycopeptide fragment ions, and peptide backbone fragment ions was essential for successful identification. Laboratory proficiency affected the number of identified N-glycopeptides. The relative quantities of the 10 major N-glycopeptide isoforms of AGP detected in four laboratories were compared to assess reproducibility. Quantitative analysis showed that the coefficient of variation was <25% for all test samples. Our analytical protocol yielded identification and quantification of site-specific N-glycopeptide isoforms of AGP from control and disease plasma sample.

Analysis of fucosylation in liver-secreted N-glycoproteins from human hepatocellular carcinoma plasma using liquid chromatography with tandem mass spectrometry

Fucosylation of N-glycoproteins has been implicated in various diseases, such as hepatocellular carcinoma (HCC). However, few studies have performed site-specific analysis of fucosylation in liver-secreted proteins. In this study, we characterized the fucosylation patterns of liver-secreted proteins in HCC plasma using a workflow to identify site-specific N-glycoproteins, where characteristic B- and/or Y-ion series with and without fucose in collision-induced dissociation were used in tandem mass spectrometry. In total, 71 fucosylated N-glycopeptides from 13 major liver-secreted proteins in human plasma were globally identified by LC-MS/MS. Additionally, 37 fucosylated N-glycopeptides were newly identified from nine liver-secreted proteins, including alpha-1-antichymotrypsin, alpha-1-antitrypsin, alpha-2-HS-glycoprotein, ceruloplasmin, alpha-1-acid glycoprotein 1/2, alpha-2-macroglobulin, serotransferrin, and beta-2-glycoprotein 1. Of the fucosylated N-glycopeptides, bi- and tri-antennary glycoforms were the most common ones identified in liver-secreted proteins from HCC plasma. Therefore, we suggest that this analytical method is effective for characterizing fucosylation in liver-secreted proteins. Graphical abstract A global map of fucosylated and non-fucosylated glycopeptides from 13 liver-secreted glycoproteins in hepatocellular carcinoma plasma.

Automated Glycan Sequencing from Tandem Mass Spectra of N-Linked Glycopeptides

Mass spectrometry has become a routine experimental tool for proteomic biomarker analysis of human blood samples, partly due to the large availability of informatics tools. As one of the most common protein post-translational modifications (PTMs) in mammals, protein glycosylation has been observed to alter in multiple human diseases and thus may potentially be candidate markers of disease progression. While mass spectrometry instrumentation has seen advancements in capabilities, discovering glycosylation-related markers using existing software is currently not straightforward. Complete characterization of protein glycosylation requires the identification of intact glycopeptides in samples, including identification of the modification site as well as the structure of the attached glycans. In this paper, we present GlycoSeq, an open-source software tool that implements a heuristic iterated glycan sequencing algorithm coupled with prior knowledge for automated elucidation of the glycan structure within a glycopeptide from its collision-induced dissociation tandem mass spectrum. GlycoSeq employs rules of glycosidic linkage as defined by glycan synthetic pathways to eliminate improbable glycan structures and build reasonable glycan trees. We tested the tool on two sets of tandem mass spectra of N-linked glycopeptides cell lines acquired from breast cancer patients. After employing enzymatic specificity within the N-linked glycan synthetic pathway, the sequencing results of GlycoSeq were highly consistent with the manually curated glycan structures. Hence, GlycoSeq is ready to be used for the characterization of glycan structures in glycopeptides from MS/MS analysis. GlycoSeq is released as open source software at https://github.com/chpaul/GlycoSeq/ .

Maturing Glycoproteomics Technologies Provide Unique Structural Insights into the N-glycoproteome and Its Regulation in Health and Disease

The glycoproteome remains severely understudied because of significant analytical challenges associated with glycoproteomics, the system-wide analysis of intact glycopeptides. This review introduces important structural aspects of protein N-glycosylation and summarizes the latest technological developments and applications in LC-MS/MS-based qualitative and quantitative N-glycoproteomics. These maturing technologies provide unique structural insights into the N-glycoproteome and its synthesis and regulation by complementing existing methods in glycoscience. Modern glycoproteomics is now sufficiently mature to initiate efforts to capture the molecular complexity displayed by the N-glycoproteome, opening exciting opportunities to increase our understanding of the functional roles of protein N-glycosylation in human health and disease.

pGlyco: a pipeline for the identification of intact N-glycopeptides by using HCD- and CID-MS/MS and MS3

Confident characterization of the microheterogeneity of protein glycosylation through identification of intact glycopeptides remains one of the toughest analytical challenges for glycoproteomics. Recently proposed mass spectrometry (MS)-based methods still have some defects such as lack of the false discovery rate (FDR) analysis for the glycan identification and lack of sufficient fragmentation information for the peptide identification. Here we proposed pGlyco, a novel pipeline for the identification of intact glycopeptides by using complementary MS techniques: 1) HCD-MS/MS followed by product-dependent CID-MS/MS was used to provide complementary fragments to identify the glycans, and a novel target-decoy method was developed to estimate the false discovery rate of the glycan identification; 2) data-dependent acquisition of MS3 for some most intense peaks of HCD-MS/MS was used to provide fragments to identify the peptide backbones. By integrating HCD-MS/MS, CID-MS/MS and MS3, intact glycopeptides could be confidently identified. With pGlyco, a standard glycoprotein mixture was analyzed in the Orbitrap Fusion, and 309 non-redundant intact glycopeptides were identified with detailed spectral information of both glycans and peptides.

Advancements in mass spectrometry-based glycoproteomics and glycomics

Protein N-glycosylation plays a crucial role in a considerable number of important biological processes. Research studies on glycoproteomes and glycomes have already characterized many glycoproteins and glycans associated with cell development, life cycle, and disease progression. Mass spectrometry (MS) is the most powerful tool for identifying biomolecules including glycoproteins and glycans, however, utilizing MS-based approaches to identify glycoproteomes and glycomes is challenging due to the technical difficulties associated with glycosylation analysis. In this review, we summarize the most recent developments in MS-based glycoproteomics and glycomics, including a discussion on the development of analytical methodologies and strategies used to explore the glycoproteome and glycome, as well as noteworthy biological discoveries made in glycoproteome and glycome research. This review places special emphasis on China, where scientists have made sizeable contributions to the literature, as advancements in glycoproteomics and glycomincs are occurring quite rapidly.

Integrated GlycoProteome Analyzer (I-GPA) for Automated Identification and Quantitation of Site-Specific N-Glycosylation

Human glycoproteins exhibit enormous heterogeneity at each N-glycosite, but few studies have attempted to globally characterize the site-specific structural features. We have developed Integrated GlycoProteome Analyzer (I-GPA) including mapping system for complex N-glycoproteomes, which combines methods for tandem mass spectrometry with a database search and algorithmic suite. Using an N-glycopeptide database that we constructed, we created novel scoring algorithms with decoy glycopeptides, where 95 N-glycopeptides from standard α1-acid glycoprotein were identified with 0% false positives, giving the same results as manual validation. Additionally automated label-free quantitation method was first developed that utilizes the combined intensity of top three isotope peaks at three highest MS spectral points. The efficiency of I-GPA was demonstrated by automatically identifying 619 site-specific N-glycopeptides with FDR ≤ 1%, and simultaneously quantifying 598 N-glycopeptides, from human plasma samples that are known to contain highly glycosylated proteins. Thus, I-GPA platform could make a major breakthrough in high-throughput mapping of complex N-glycoproteomes, which can be applied to biomarker discovery and ongoing global human proteome project.

Terminal Galactosylation and Sialylation Switching on Membrane Glycoproteins upon TNF-Alpha-Induced Insulin Resistance in Adipocytes

Insulin resistance (IR) is a complex pathophysiological state that arises from both environmental and genetic perturbations and leads to a variety of diseases, including type-2 diabetes (T2D). Obesity is associated with enhanced adipose tissue inflammation, which may play a role in disease progression. Inflammation modulates protein glycosylation in a variety of cell types, and this has been associated with biological dysregulation. Here, we have examined the effects of an inflammatory insult on protein glycosylation in adipocytes. We performed quantitative N-glycome profiling of membrane proteins derived from mouse 3T3-L1 adipocytes that had been incubated with or without the proinflammatory cytokine TNF-alpha to induce IR. We identified the regulation of specific terminal N-glycan epitopes, including an increase in terminal di-galactose- and a decrease in biantennary alpha-2,3-sialoglycans. The altered N-glycosylation of TNF-alpha-treated adipocytes correlated with the regulation of specific glycosyltransferases, including the up-regulation of B4GalT5 and Ggta1 galactosyltransferases and down-regulation of ST3Gal6 sialyltransferase. Knockdown of B4GalT5 down-regulated the terminal di-galactose N-glycans, confirming the involvement of this enzyme in the TNF-alpha-regulated N-glycome. SILAC-based quantitative glycoproteomics of enriched N-glycopeptides with and without deglycosylation were used to identify the protein and glycosylation sites modified with these regulated N-glycans. The combined proteome and glycoproteome workflow provided a relative quantification of changes in protein abundance versus N-glycosylation occupancy versus site-specific N-glycans on a proteome-wide level. This revealed the modulation of N-glycosylation on specific proteins in IR, including those previously associated with insulin-stimulated GLUT4 trafficking to the plasma membrane.

Computational Methods in Mass Spectrometry-Based Proteomics

This chapter introduces computational methods used in mass spectrometry-based proteomics, including those for addressing the critical problems such as peptide identification and protein inference, peptide and protein quantification, characterization of posttranslational modifications (PTMs), and data-independent acquisitions (DIA). The chapter concludes with emerging applications of proteomic techniques, such as metaproteomics, glycoproteomics, and proteogenomics.

A review of methods for interpretation of glycopeptide tandem mass spectral data

Despite the publication of several software tools for analysis of glycopeptide tandem mass spectra, there remains a lack of consensus regarding the most effective and appropriate methods. In part, this reflects problems with applying standard methods for proteomics database searching and false discovery rate calculation. While the analysis of small post-translational modifications (PTMs) may be regarded as an extension of proteomics database searching, glycosylation requires specialized approaches. This is because glycans are large and heterogeneous by nature, causing glycopeptides to exist as multiple glycosylated variants. Thus, the mass of the peptide cannot be calculated directly from that of the intact glycopeptide. In addition, the chemical nature of the glycan strongly influences product ion patterns observed for glycopeptides. As a result, glycopeptidomics requires specialized bioinformatics methods. We summarize the recent progress towards a consensus for effective glycopeptide tandem mass spectrometric analysis.

Engaging challenges in glycoproteomics: recent advances in MS-based glycopeptide analysis

The proteomic analysis of glycosylation is uniquely challenging. The numerous and varied biological roles of protein-linked glycans have fueled a tremendous demand for technologies that enable rapid, in-depth structural examination of glycosylated proteins in complex biological systems. In turn, this demand has driven many innovations in wide ranging fields of bioanalytical science. This review will summarize key developments in glycoprotein separation and enrichment, glycoprotein proteolysis strategies, glycopeptide separation and enrichment, the role of mass measurement accuracy in glycopeptide detection, glycopeptide ion dissociation methods for MS/MS, and informatic tools for glycoproteomic analysis. In aggregate, this selection of topics serves to encapsulate the present status of MS-based analytical technologies for engaging the challenges of glycoproteomic analysis.

Defining glycoprotein cancer biomarkers by MS in conjunction with glycoprotein enrichment

Protein glycosylation is an important and common post-translational modification. More than 50% of human proteins are believed to be glycosylated to modulate the functionality of proteins. Aberrant glycosylation has been correlated to several diseases, such as inflammatory skin diseases, diabetes mellitus, cardiovascular disorders, rheumatoid arthritis, Alzheimer's and prion diseases, and cancer. Many approved cancer biomarkers are glycoproteins which are not highly abundant proteins. Therefore, effective qualitative and quantitative assessment of glycoproteins entails enrichment methods. This chapter summarizes glycoprotein enrichment methods, including lectin affinity, immunoaffinity, hydrazide chemistry, hydrophilic interaction liquid chromatography, and click chemistry. The use of these enrichment approaches in assessing the qualitative and quantitative changes of glycoproteins in different types of cancers are presented and discussed. This chapter highlights the importance of glycoprotein enrichment techniques for the identification and characterization of new reliable cancer biomarkers.

Glycopeptide Site Heterogeneity and Structural Diversity Determined by Combined Lectin Affinity Chromatography/IMS/CID/MS Techniques

Glycopeptides from a tryptic digest of chicken ovomucoid were enriched using a simplified lectin affinity chromatography (LAC) platform, and characterized by high-resolution mass spectrometry (MS) as well as ion mobility spectrometry (IMS)-MS. The LAC platform effectively enriched the glycoproteome, from which a total of 117 glycopeptides containing 27 glycan forms were identified for this protein. IMS-MS analysis revealed a high degree of glycopeptide site heterogeneity. Comparison of the IMS distributions of the glycopeptides from different charge states reveals that higher charge states allow more structures to be resolved. Presumably the repulsive interactions between charged sites lead to more open configurations, which are more readily separated compared with the more compact, lower charge state forms of the same groups of species. Combining IMS with collision induced dissociation (CID) made it possible to determine the presence of isomeric glycans and to reconstruct their IMS profiles. This study illustrates a workflow involving hybrid techniques for determining glycopeptide site heterogeneity and evaluating structural diversity of glycans and glycopeptides.

Carbohydrates on Proteins: Site-Specific Glycosylation Analysis by Mass Spectrometry

Glycosylation on proteins adds complexity and versatility to these biologically vital macromolecules. To unveil the structure-function relationship of glycoproteins, glycopeptide-centric analysis using mass spectrometry (MS) has become a method of choice because the glycan is preserved on the glycosylation site and site-specific glycosylation profiles of proteins can be readily determined. However, glycopeptide analysis is still challenging given that glycopeptides are usually low in abundance and relatively difficult to detect and the resulting data require expertise to analyze. Viewing the urgent need to address these challenges, emerging methods and techniques are being developed with the goal of analyzing glycopeptides in a sensitive, comprehensive, and high-throughput manner. In this review, we discuss recent advances in glycoprotein and glycopeptide analysis, with topics covering sample preparation, analytical separation, MS and tandem MS techniques, as well as data interpretation and automation.

Carbamidomethylation Side Reactions May Lead to Glycan Misassignments in Glycopeptide Analysis

Iodoacetamide is perhaps the most widely used reagent for the alkylation of free sulfhydryls in proteomic experiments. Here, we report that both incomplete derivatization of Cys side chains and overalkylation of the peptides may lead to the misassignment of glycoforms when LC-MS/MS with electron-transfer dissociation (ETD) alone is used for the structural characterization of glycopeptides. Accurate mass measurements do not help, because the elemental compositions of the misidentified and correct modifications are identical. Incorporation of "higher-energy C-trap dissociation" (HCD), i.e., beam-type collision-induced dissociation data into the database searches with ETD data may prove decisive in most cases. However, the carbamidomethylation of Met residues leads to sulfonium ether formation, and the resulting fixed positive charge triggers a characteristic fragmentation, that eliminates the normal Y1 fragment from the HCD spectra of N-linked glycopeptides, producing an abundant Y1-48 Da ion instead (the nominal mass difference is given relative to the unmodified amino acid sequence), that easily can be mistaken for the side chain loss from Met sulfoxide. In such cases, good quality ETD data may indicate the discrepancy, and will also display abundant fragments due to CH3-S-CH2CONH2 elimination from the charge-reduced precursor ions. Our observations also draw attention to the underreported interference of different unanticipated covalent modifications.

Integration of systems glycobiology with bioinformatics toolboxes, glycoinformatics resources, and glycoproteomics data

The glycome constitutes the entire complement of free carbohydrates and glycoconjugates expressed on whole cells or tissues. 'Systems Glycobiology' is an emerging discipline that aims to quantitatively describe and analyse the glycome. Here, instead of developing a detailed understanding of single biochemical processes, a combination of computational and experimental tools are used to seek an integrated or 'systems-level' view. This can explain how multiple biochemical reactions and transport processes interact with each other to control glycome biosynthesis and function. Computational methods in this field commonly build in silico reaction network models to describe experimental data derived from structural studies that measure cell-surface glycan distribution. While considerable progress has been made, several challenges remain due to the complex and heterogeneous nature of this post-translational modification. First, for the in silico models to be standardized and shared among laboratories, it is necessary to integrate glycan structure information and glycosylation-related enzyme definitions into the mathematical models. Second, as glycoinformatics resources grow, it would be attractive to utilize 'Big Data' stored in these repositories for model construction and validation. Third, while the technology for profiling the glycome at the whole-cell level has been standardized, there is a need to integrate mass spectrometry derived site-specific glycosylation data into the models. The current review discusses progress that is being made to resolve the above bottlenecks. The focus is on how computational models can bridge the gap between 'data' generated in wet-laboratory studies with 'knowledge' that can enhance our understanding of the glycome.

Characterizing sialic acid variants at the glycopeptide level

Beam-type collision-induced dissociation (CID) data of intact glycopeptides isolated from mouse liver tissue are presented to illustrate characteristic fragmentation of differentially sialylated glycopeptides. Eight glycoforms of an O-linked glycopeptide from Nucleobindin-1 are distinguished on the basis of the precursor masses and characteristic oxonium ions. We report that all sialic acid variants are prone to neutral loss from the charge reduced species in electron-transfer dissociation (ETD) fragmentation. We show how changes in sialic acid composition affect reverse phase chromatographic retention times: sialic acid addition increases glycopeptide retention times significantly; replacing the N-acetylneuraminic acid with the N-glycolyl variant leads to slightly reduced retention times, while O-acetylated sialic acid-containing glycoforms are retained longer. We then demonstrate how MS-Filter in Protein Prospector can use these diagnostic oxonium ions to find glycopeptides, by showing that a wealth of different glycopeptides can be found in a published phosphopeptide data set.

Exploring the glycoproteomics landscape with advanced MS technologies

The advance of glycoproteomic technologies has offered unique insights into the importance of glycosylation in determining the functional roles of a protein within a cell. Biologically active glycoproteins include the categories of enzymes, hormones, proteins involved in cell proliferation, cell membrane proteins involved in cell-cell recognition, and communication events or secreted proteins, just to name a few. The recent progress in analytical instrumentation, methodologies, and computational approaches has enabled a detailed exploration of glycan structure, connectivity, and heterogeneity, underscoring the staggering complexity of the glycome repertoire in a cell. A variety of approaches involving the use of spectroscopy, MS, separation, microfluidic, and microarray technologies have been used alone or in combination to tackle the glycoproteome challenge, the research results of these efforts being captured in an overwhelming number of annual publications. This work is aimed at reviewing the major developments and accomplishments in the field of glycoproteomics, with focus on the most recent advancements (2012-2014) that involve the use of capillary separations and MS detection.

Glycoproteomics: identifying the glycosylation of prostate specific antigen at normal and high isoelectric points by LC-MS/MS

Prostate specific antigen (PSA) is currently used as a biomarker to diagnose prostate cancer. PSA testing has been widely used to detect and screen prostate cancer. However, in the diagnostic gray zone, the PSA test does not clearly distinguish between benign prostate hypertrophy and prostate cancer due to their overlap. To develop more specific and sensitive candidate biomarkers for prostate cancer, an in-depth understanding of the biochemical characteristics of PSA (such as glycosylation) is needed. PSA has a single glycosylation site at Asn69, with glycans constituting approximately 8% of the protein by weight. Here, we report the comprehensive identification and quantitation of N-glycans from two PSA isoforms using LC–MS/MS. There were 56 N-glycans associated with PSA, whereas 57 N-glycans were observed in the case of the PSA-high isoelectric point (pI) isoform (PSAH). Three sulfated/phosphorylated glycopeptides were detected, the identification of which was supported by tandem MS data. One of these sulfated/phosphorylated N-glycans, HexNAc5Hex4dHex1s/p1 was identified in both PSA and PSAH at relative intensities of 0.52 and 0.28%, respectively. Quantitatively, the variations were monitored between these two isoforms. Because we were one of the laboratories participating in the 2012 ABRF Glycoprotein Research Group (gPRG) study, those results were compared to that presented in this study. Our qualitative and quantitative results summarized here were comparable to those that were summarized in the interlaboratory study.

Confident assignment of site-specific glycosylation in complex glycoproteins in a single step

A glycoprotein may contain several sites of glycosylation, each of which is heterogeneous. As a consequence of glycoform diversity and signal suppression from nonglycosylated peptides that ionize more efficiently, typical reversed-phase LC-MS and bottom-up proteomics database searching workflows do not perform well for identification of site-specific glycosylation for complex glycoproteins. We present an LC-MS system for enrichment, separation, and analysis of glycopeptides from complex glycoproteins (>4 N-glycosylation sequons) in a single step. This system uses an online HILIC enrichment trap prior to reversed-phase C18-MS analysis. We demonstrated the effectiveness of the system using a set of glycoproteins including human transferrin (2 sequons), human alpha-1-acid glycoprotein (5 sequons), and influenza A virus hemagglutinin (9 sequons). The online enrichment renders glycopeptides the most abundant ions detected, thereby facilitating the generation of high-quality data-dependent tandem mass spectra. The tandem mass spectra exhibited product ions from both glycan and peptide backbone dissociation for a majority of the glycopeptides tested using collisionally activated dissociation that served to confidently assign site-specific glycosylation. We demonstrated the value of our system to define site-specific glycosylation using a hemagglutinin containing 9 N-glycosylation sequons from a single HILIC-C18-MS acquisition.

New glycoproteomics software, GlycoPep Evaluator, generates decoy glycopeptides de novo and enables accurate false discovery rate analysis for small data sets

Glycoproteins are biologically significant large molecules that participate in numerous cellular activities. In order to obtain site-specific protein glycosylation information, intact glycopeptides, with the glycan attached to the peptide sequence, are characterized by tandem mass spectrometry (MS/MS) methods such as collision-induced dissociation (CID) and electron transfer dissociation (ETD). While several emerging automated tools are developed, no consensus is present in the field about the best way to determine the reliability of the tools and/or provide the false discovery rate (FDR). A common approach to calculate FDRs for glycopeptide analysis, adopted from the target-decoy strategy in proteomics, employs a decoy database that is created based on the target protein sequence database. Nonetheless, this approach is not optimal in measuring the confidence of N-linked glycopeptide matches, because the glycopeptide data set is considerably smaller compared to that of peptides, and the requirement of a consensus sequence for N-glycosylation further limits the number of possible decoy glycopeptides tested in a database search. To address the need to accurately determine FDRs for automated glycopeptide assignments, we developed GlycoPep Evaluator (GPE), a tool that helps to measure FDRs in identifying glycopeptides without using a decoy database. GPE generates decoy glycopeptides de novo for every target glycopeptide, in a 1:20 target-to-decoy ratio. The decoys, along with target glycopeptides, are scored against the ETD data, from which FDRs can be calculated accurately based on the number of decoy matches and the ratio of the number of targets to decoys, for small data sets. GPE is freely accessible for download and can work with any search engine that interprets ETD data of N-linked glycopeptides. The software is provided at https://desairegroup.ku.edu/research.

LC-MS/MS quantitation of esophagus disease blood serum glycoproteins by enrichment with hydrazide chemistry and lectin affinity chromatography

Changes in glycosylation have been shown to have a profound correlation with development/malignancy in many cancer types. Currently, two major enrichment techniques have been widely applied in glycoproteomics, namely, lectin affinity chromatography (LAC)-based and hydrazide chemistry (HC)-based enrichments. Here we report the LC–MS/MS quantitative analyses of human blood serum glycoproteins and glycopeptides associated with esophageal diseases by LAC- and HC-based enrichment. The separate and complementary qualitative and quantitative data analyses of protein glycosylation were performed using both enrichment techniques. Chemometric and statistical evaluations, PCA plots, or ANOVA test, respectively, were employed to determine and confirm candidate cancer-associated glycoprotein/glycopeptide biomarkers. Out of 139, 59 common glycoproteins (42% overlap) were observed in both enrichment techniques. This overlap is very similar to previously published studies. The quantitation and evaluation of significantly changed glycoproteins/glycopeptides are complementary between LAC and HC enrichments. LC–ESI–MS/MS analyses indicated that 7 glycoproteins enriched by LAC and 11 glycoproteins enriched by HC showed significantly different abundances between disease-free and disease cohorts. Multiple reaction monitoring quantitation resulted in 13 glycopeptides by LAC enrichment and 10 glycosylation sites by HC enrichment to be statistically different among disease cohorts.

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.

Advances in LC-MS/MS-based glycoproteomics: getting closer to system-wide site-specific mapping of the N- and O-glycoproteome

Site-specific structural characterization of glycoproteins is important for understanding the exact functional relevance of protein glycosylation. Resulting partly from the multiple layers of structural complexity of the attached glycans, the system-wide site-specific characterization of protein glycosylation, defined as glycoproteomics, is still far from trivial leaving the N- and O-linked glycoproteomes significantly under-defined. However, recent years have seen significant advances in glycoproteomics driven, in part, by the developments of dedicated workflows and efficient sample preparation, including glycopeptide enrichment and prefractionation. In addition, glycoproteomics has benefitted from the continuous performance enhancement and more intelligent use of liquid chromatography and tandem mass spectrometry (LC-MS/MS) instrumentation and a wider selection of specialized software tackling the unique challenges of glycoproteomics data. Together these advances promise more streamlined N- and O-linked glycoproteome analysis. Tangible examples include system-wide glycoproteomics studies detecting thousands of intact glycopeptides from hundreds of glycoproteins from diverse biological samples. With a strict focus on the system-wide site-specific analysis of protein N- and O-linked glycosylation, we review the recent advances in LC-MS/MS based glycoproteomics. The review opens with a more general discussion of experimental designs in glycoproteomics and sample preparation prior to LC-MS/MS based data acquisition. Although many challenges still remain, it becomes clear that glycoproteomics, one of the last frontiers in proteomics, is gradually maturing enabling a wider spectrum of researchers to access this new emerging research discipline. The next milestone in analytical glycobiology is being reached allowing the glycoscientist to address the functional importance of protein glycosylation in a system-wide yet protein-specific manner.