Mapping site-specific protein N-glycosylations through liquid chromatography/mass spectrometry and targeted tandem mass spectrometry

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.

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.

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.

Novel methods in glycomics: a 2019 update

Introduction: Glycomics, which aims to define the glycome of a biological system to better assess the biological attributes of the glycans, has attracted increasing interest. However, the complexity and diversity of glycans present challenging barriers to glycome definition. Technological advances are major drivers in glycomics.Areas covered: This review summarizes the main methods and emphasizes the most recent advances in mass spectrometry-based methods regarding glycomics following the general workflow in glycomic analysis.Expert opinion: Recent mass spectrometry-based technological advances have significantly lowered the barriers in glycomics. The field of glycomics is moving toward both generic and precise analysis.

DecoyDeveloper: An On-Demand, De Novo Decoy Glycopeptide Generator

Glycopeptide analysis is a growing field that is struggling to adopt effective, automated tools. Many creative workflows and software apps have emerged recently that offer promising capabilities for assigning glycopeptides to MS data in an automated fashion. The effectiveness of these tools is best measured and improved by determining how often they would select a glycopeptide decoy as a spectral match, instead of its correct assignment; yet generating the appropriate number and type of glycopeptide decoys can be challenging. To address this need, we have designed DecoyDeveloper, an on-demand decoy glycopeptide generator that can produce a high volume of decoys with low mass differences. DecoyDeveloper has a simple user interface and is capable of producing large sets of decoys containing complete, biologically relevant glycan and peptide sequences. We demonstrate the tool's efficiency by applying it to a set of 80 glycopeptide targets. This tool is freely available and can be found at http://glycopro.chem.ku.edu/J1.php .

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.

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.

Large-scale identification and visualization of N-glycans with primary structures using GlySeeker

RATIONALE

Most of the current popular tandem mass spectrometers have the capability of resolving the primary structures (monosaccharide composition, sequence and linkage) of N-glycans; however, compositions or putative structures have mostly been reported so far. Identification and visualization tools of N-glycans are needed.

METHODS

The isotopic mass-to-charge ratio and envelope fingerprinting algorithm, which has been successfully used for intact protein database search and identification, was adapted for N-glycan database search, and a stand-alone N-glycan database search engine, GlySeeker, for automated N-glycan identification and visualization was developed and successfully benchmarked. Both pseudo 2D graph and one-line text formats with one-letter symbols for monosaccharides were proposed for representing N-glycans. N-glycans were identified with comprehensive interpretation of product ions and false discovery rate (FDR) control.

RESULTS

In a database search of reversed-phase liquid chromatography/tandem mass spectrometry (RPLC/MS/MS) datasets of the N-glycome enriched from OVCAR-3 ovarian cancer cells, with FDR ≤1% and number of best hits (NoBHs) = 1-30, 1525 N-glycans with comprehensive primary structural information (composition, sequence and linkage) were identified and visualized; among these 1525 N-glycans, 559 had NoBHs = 1, i.e. their structures were uniquely identified. This represents a large-scale identification and visualization of N-glycans with primary structures from tandem mass spectra.

CONCLUSIONS

A stand-alone N-glycan database search engine called GlySeeker has been developed for large-scale identification and visualization of N-glycans with comprehensive interpretation of tandem mass spectra and FDR control.

Human disease glycomics: technology advances enabling protein glycosylation analysis - part 1

INTRODUCTION

Protein glycosylation is recognized as an important post-translational modification, with specific substructures having significant effects on protein folding, conformation, distribution, stability and activity. However, due to the structural complexity of glycans, elucidating glycan structure-function relationships is demanding. The fine detail of glycan structures attached to proteins (including sequence, branching, linkage and anomericity) is still best analysed after the glycans are released from the purified or mixture of glycoproteins (glycomics). The technologies currently available for glycomics are becoming streamlined and standardized and many features of protein glycosylation can now be determined using instruments available in most protein analytical laboratories. Areas covered: This review focuses on the current glycomics technologies being commonly used for the analysis of the microheterogeneity of monosaccharide composition, sequence, branching and linkage of released N- and O-linked glycans that enable the determination of precise glycan structural determinants presented on secreted proteins and on the surface of all cells. Expert commentary: Several emerging advances in these technologies enabling glycomics analysis are discussed. The technological and bioinformatics requirements to be able to accurately assign these precise glycan features at biological levels in a disease context are assessed.

Glycoprotein Enrichment Analytical Techniques: Advantages and Disadvantages

Protein glycosylation is one of the most important posttranslational modifications. Numerous biological functions are related to protein glycosylation. However, analytical challenges remain in the glycoprotein analysis. To overcome the challenges associated with glycoprotein analysis, many analytical techniques were developed in recent years. Enrichment methods were used to improve the sensitivity of detection, while HPLC and mass spectrometry methods were developed to facilitate the separation of glycopeptides/proteins and enhance detection, respectively. Fragmentation techniques applied in modern mass spectrometers allow the structural interpretation of glycopeptides/proteins, while automated software tools started replacing manual processing to improve the reliability and throughput of the analysis. In this chapter, the current methodologies of glycoprotein analysis were discussed. Multiple analytical techniques are compared, and advantages and disadvantages of each technique are highlighted.

Glycoproteins Enrichment and LC-MS/MS Glycoproteomics in Central Nervous System Applications

Proteins and glycoproteins play important biological roles in central nervous systems (CNS). Qualitative and quantitative evaluation of proteins and glycoproteins expression in CNS is critical to reveal the inherent biomolecular mechanism of CNS diseases. This chapter describes proteomic and glycoproteomic approaches based on liquid chromatography/tandem mass spectrometry (LC-MS or LC-MS/MS) for the qualitative and quantitative assessment of proteins and glycoproteins expressed in CNS. Proteins and glycoproteins, extracted by a mass spectrometry friendly surfactant from CNS samples, were subjected to enzymatic (tryptic) digestion and three down-stream analyses: (1) a nano LC system coupled with a high-resolution MS instrument to achieve qualitative proteomic profile, (2) a nano LC system combined with a triple quadrupole MS to quantify identified proteins, and (3) glycoprotein enrichment prior to LC-MS/MS analysis. Enrichment techniques can be applied to improve coverage of low abundant glycopeptides/glycoproteins. An example described in this chapter is hydrophilic interaction liquid chromatographic (HILIC) enrichment to capture glycopeptides, allowing efficient removal of peptides. The combination of three LC-MS/MS-based approaches is capable of the investigation of large-scale proteins and glycoproteins from CNS with an in-depth coverage, thus offering a full view of proteins and glycoproteins changes in CNS.

Use of an informed search space maximizes confidence of site-specific assignment of glycoprotein glycosylation

In order to interpret glycopeptide tandem mass spectra, it is necessary to estimate the theoretical glycan compositions and peptide sequences, known as the search space. The simplest way to do this is to build a naïve search space from sets of glycan compositions from public databases and to assume that the target glycoprotein is pure. Often, however, purified glycoproteins contain co-purified glycoprotein contaminants that have the potential to confound assignment of tandem mass spectra based on naïve assumptions. In addition, there is increasing need to characterize glycopeptides from complex biological mixtures. Fortunately, liquid chromatography-mass spectrometry (LC-MS) methods for glycomics and proteomics are now mature and accessible. We demonstrate the value of using an informed search space built from measured glycomes and proteomes to define the search space for interpretation of glycoproteomics data. We show this using α-1-acid glycoprotein (AGP) mixed into a set of increasingly complex matrices. As the mixture complexity increases, the naïve search space balloons and the ability to assign glycopeptides with acceptable confidence diminishes. In addition, it is not possible to identify glycopeptides not foreseen as part of the naïve search space. A search space built from released glycan glycomics and proteomics data is smaller than its naïve counterpart while including the full range of proteins detected in the mixture. This maximizes the ability to assign glycopeptide tandem mass spectra with confidence. As the mixture complexity increases, the number of tandem mass spectra per glycopeptide precursor ion decreases, resulting in lower overall scores and reduced depth of coverage for the target glycoprotein. We suggest use of α-1-acid glycoprotein as a standard to gauge effectiveness of analytical methods and bioinformatics search parameters for glycoproteomics studies. Graphical Abstract Assignment of site specific glycosylation from LC-tandemMS data.

GlycoPep MassList: software to generate massive inclusion lists for glycopeptide analyses

Protein glycosylation drives many biological processes and serves as markers for disease; therefore, the development of tools to study glycosylation is an essential and growing area of research. Mass spectrometry can be used to identify both the glycans of interest and the glycosylation sites to which those glycans are attached, when proteins are proteolytically digested and their glycopeptides are analyzed by a combination of high-resolution mass spectrometry (MS) and tandem mass spectrometry (MS/MS) methods. One major challenge in these experiments is collecting the requisite MS/MS data. The digested glycopeptides are often present in complex mixtures and in low abundance, and the most commonly used approach to collect MS/MS data on these species is data-dependent acquisition (DDA), where only the most intense precursor ions trigger MS/MS. DDA results in limited glycopeptide coverage. Semi-targeted data acquisition is an alternative experimental approach that can alleviate this difficulty. However, due to the massive heterogeneity of glycopeptides, it is not obvious how to expediently generate inclusion lists for these types of analyses. To solve this problem, we developed the software tool GlycoPep MassList, which can be used to generate inclusion lists for liquid chromatography tandem-mass spectrometry (LC-MS/MS) experiments. The utility of the software was tested by conducting comparisons between semi-targeted and untargeted data-dependent analysis experiments on a variety of proteins, including IgG, a protein whose glycosylation must be characterized during its production as a biotherapeutic. When the GlycoPep MassList software was used to generate inclusion lists for LC-MS/MS experiments, more unique glycopeptides were selected for fragmentation. Generally, ∼30 % more unique glycopeptides can be analyzed per protein, in the simplest cases, with low background. In cases where background ions from proteins or other interferents are high, usage of an inclusion list is even more advantageous. The software is freely publically accessible. Graphical abstract Software increases the number of glycopeptides that get selected for MS/MS analysis.

A procedure for the analysis of site-specific and structure-specific fucosylation in alpha-1-antitrypsin

A MS-based methodology has been developed for analysis of core-fucosylated versus antennary-fucosylated glycosites in glycoproteins. This procedure is applied to the glycoprotein alpha-1-antitrypsin (A1AT), which contains both core- and antennary-fucosylated glycosites. The workflow involves digestion of intact glycoproteins into glycopeptides, followed by double digestion with sialidase and galactosidase. The resulting glycopeptides with truncated glycans were separated using an off-line HILIC (hydrophilic interaction liquid chromatography) separation where multiple fractions were collected at various time intervals. The glycopeptides in each fraction were treated with PNGase F and then divided into halves. One half of the sample was applied for peptide identification while the other half was processed for glycan analysis by derivatizing with a meladrazine reagent followed by MS analysis. This procedure provided site-specific identification of glycosylation sites and the ability to distinguish core fucosylation and antennary fucosylation via a double digestion and a mass profile scan. Both core and antennary fucosylation are shown to be present on various glycosites in A1AT.

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/ .

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.

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.

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.

High-Throughput Analysis and Automation for Glycomics Studies

This review covers advances in analytical technologies for high-throughput (HTP) glycomics. Our focus is on structural studies of glycoprotein glycosylation to support biopharmaceutical realization and the discovery of glycan biomarkers for human disease. For biopharmaceuticals, there is increasing use of glycomics in Quality by Design studies to help optimize glycan profiles of drugs with a view to improving their clinical performance. Glycomics is also used in comparability studies to ensure consistency of glycosylation both throughout product development and between biosimilars and innovator drugs. In clinical studies there is as well an expanding interest in the use of glycomics—for example in Genome Wide Association Studies—to follow changes in glycosylation patterns of biological tissues and fluids with the progress of certain diseases. These include cancers, neurodegenerative disorders and inflammatory conditions. Despite rising activity in this field, there are significant challenges in performing large scale glycomics studies. The requirement is accurate identification and quantitation of individual glycan structures. However, glycoconjugate samples are often very complex and heterogeneous and contain many diverse branched glycan structures. In this article we cover HTP sample preparation and derivatization methods, sample purification, robotization, optimized glycan profiling by UHPLC, MS and multiplexed CE, as well as hyphenated techniques and automated data analysis tools. Throughout, we summarize the advantages and challenges with each of these technologies. The issues considered include reliability of the methods for glycan identification and quantitation, sample throughput, labor intensity, and affordability for large sample numbers.

Software for automated interpretation of mass spectrometry data from glycans and glycopeptides

The purpose of this review is to provide those interested in glycosylation analysis with the most updated information on the availability of automated tools for MS characterization of N-linked and O-linked glycosylation types. Specifically, this review describes software tools that facilitate elucidation of glycosylation from MS data on the basis of mass alone, as well as software designed to speed the interpretation of glycan and glycopeptide fragmentation from MS/MS data. This review focuses equally on software designed to interpret the composition of released glycans and on tools to characterize N-linked and O-linked glycopeptides. Several websites have been compiled and described that will be helpful to the reader who is interested in further exploring the described tools.

Computational framework for identification of intact glycopeptides in complex samples

Glycosylation is an important protein modification that involves enzymatic attachment of sugars to amino acid residues. Understanding the structure of these sugars and the effects of glycosylation are vital for developing indicators of disease development and progression. Although computational methods based on mass spectrometric data have proven to be effective in monitoring changes in the glycome, developing such methods for the glycoproteome are challenging, largely due to the inherent complexity in simultaneously studying glycan structures with their corresponding glycosylation sites. This paper introduces a computational framework for identifying intact N-linked glycopeptides, i.e. glycopeptides with N-linked glycans attached to their glycosylation sites, in complex proteome samples. Scoring algorithms are presented for tandem mass spectra of glycopeptides resulting from collision-induced dissociation (CID), higher-energy C-trap dissociation (HCD), and electron transfer dissociation (ETD) fragmentation modes. An empirical false-discovery rate estimation method, based on a target-decoy search approach, is derived for assigning confidence. The power of our method is further enhanced when multiple data sets are pooled together to increase identification confidence. Using this framework, 103 highly confident N-linked glycopeptides from 53 sites across 33 glycoproteins were identified in complex human serum proteome samples using conventional proteomic platforms with standard depletion of the 7-most abundant proteins. These results indicate that our method is ready to be used for characterizing site-specific protein glycosylation in complex samples.

Automated assignments of N- and O-site specific glycosylation with extensive glycan heterogeneity of glycoprotein mixtures

Site-specific glycosylation (SSG) of glycoproteins remains a considerable challenge and limits further progress in the areas of proteomics and glycomics. Effective methods require new approaches in sample preparation, detection, and data analysis. While the field has advanced in sample preparation and detection, automated data analysis remains an important goal. A new bioinformatics approach implemented in software called GP Finder automatically distinguishes correct assignments from random matches and complements experimental techniques that are optimal for glycopeptides, including nonspecific proteolysis and high mass resolution liquid chromatography/tandem mass spectrometry (LC/MS/MS). SSG for multiple N- and O-glycosylation sites, including extensive glycan heterogeneity, was annotated for single proteins and protein mixtures with a 5% false-discovery rate, generating hundreds of nonrandom glycopeptide matches and demonstrating the proof-of-concept for a self-consistency scoring algorithm shown to be compliant with the target-decoy approach (TDA). The approach was further applied to a mixture of N-glycoproteins from unprocessed human milk and O-glycoproteins from very-low-density-lipoprotein (vLDL) particles.

Enzymatic preparation and structural determination of oligosaccharides derived from sea cucumber (Acaudina molpadioides) fucoidan

Sea cucumber fucoidan is a major bioactive component of sea cucumber. Sea cucumber is widely consumed in East Asian countries as healthy food. Employing the degrading enzyme from the marine bacterium strain Flavobacteriaceae CZ1127, sea cucumber (Acaudina molpadioides) fucoidan oligosaccharides were prepared by enzymatic hydrolysis. The oligosaccharide profile of the hydrolysate was determined by liquid chromatography coupled with mass spectrometry (LC-MS). With the assistance of LC-MS, four major oligosaccharides in the hydrolysate were purified. By using tandem mass spectrometry and nuclear magnetic resonance, delicate structures of the oligosaccharides were verified as α-l-Fucp-1→3-α-l-Fucp(2,4OSO3(2-))-1→3-α-l-Fucp, α-l-Fucp-1→3-α-l-Fucp(2,4OSO3(2-))-1→3-α-l-Fucp-1→3-α-l-Fucp, α-l-Fucp-1→3-α-l-Fucp(2,4OSO3(2-))-1→3-α-l-Fucp-1→3-α-l-Fucp-1→3-α-l-Fucp-1→3-α-l-Fucp(2,4OSO3(2-))-1→3-α-l-Fucp and α-l-Fucp-1→3-α-l-Fucp(2,4OSO3(2-))-1→3-α-l-Fucp-1→3-α-l-Fucp-1→3-α-l-Fucp-1→3-α-l-Fucp(2,4OSO3(2-))-1→3-α-l-Fucp-1→3-α-l-Fucp.

Automated glycopeptide analysis--review of current state and future directions

Glycosylation of proteins is involved in immune defense, cell-cell adhesion, cellular recognition and pathogen binding and is one of the most common and complex post-translational modifications. Science is still struggling to assign detailed mechanisms and functions to this form of conjugation. Even the structural analysis of glycoproteins-glycoproteomics-remains in its infancy due to the scarcity of high-throughput analytical platforms capable of determining glycopeptide composition and structure, especially platforms for complex biological mixtures. Glycopeptide composition and structure can be determined with high mass-accuracy mass spectrometry, particularly when combined with chromatographic separation, but the sheer volume of generated data necessitates computational software for interpretation. This review discusses the current state of glycopeptide assignment software-advances made to date and issues that remain to be addressed. The various software and algorithms developed so far provide important insights into glycoproteomics. However, there is currently no freely available software that can analyze spectral data in batch and unambiguously determine glycopeptide compositions for N- and O-linked glycopeptides from relevant biological sources such as human milk and serum. Few programs are capable of aiding in structural determination of the glycan component. To significantly advance the field of glycoproteomics, analytical software and algorithms are required that: (i) solve for both N- and O-linked glycopeptide compositions, structures and glycosites in biological mixtures; (ii) are high-throughput and process data in batches; (iii) can interpret mass spectral data from a variety of sources and (iv) are open source and freely available.

Site-specific N-glycosylation identification of recombinant human lectin-like oxidized low density lipoprotein receptor-1 (LOX-1)

Human LOX-1/OLR 1 plays a key role in atherogenesis and endothelial dysfunction. The N-glycosylation of LOX-1 has been shown to affect its biological functions in vivo and modulate the pathogenesis of atherosclerosis. However, the N-glycosylation pattern of LOX-1 has not been described yet. The present study was aimed at elucidating the N-glycosylation of recombinant human LOX-1 with regard to N-glycan profile and N-glycosylation sites. Here, an approach using nonspecific protease (Pronase E) digestion followed by MALDI-QIT-TOF MS and multistage MS (MS(3)) analysis is explored to obtain site-specific N-glycosylation information of recombinant human LOX-1, in combination with glycan structure confirmation through characterizing released glycans using tandem MS. The results reveal that N-glycans structures as well as their corresponding attached site of LOX-1 can be identified simultaneously by direct MS analysis of glycopeptides from non-specific protease digestion. With this approach, one potential glycosylation site of recombinant human LOX-1 on Asn(139) is readily identified and found to carry heterogeneous complex type N-glycans. In addition, manual annotation of multistage MS data utilizing diagnostic ions, which were found to be particularly useful in defining the structure of glycopeptides and glycans was addressed for proper spectra interpretation. The findings described herein will shed new light on further research of the structure-function relationships of LOX-1 N-glycan.

Improving confidence in detection and characterization of protein N-glycosylation sites and microheterogeneity

Protein glycosylation is one of the most common post-translational modifications, estimated to occur in over 50% of human proteins. Mass spectrometry (MS)-based approaches involving different fragmentation mechanisms have been frequently used to detect and characterize protein N-linked glycosylations. In addition to the popular Collision-Induced Dissociation (CID), high-energy C-trap dissociation (HCD) fragmentation, which is a feature of a linear ion trap orbitrap hybrid mass spectrometer (LTQ Orbitrap), has been recently used for the fragmentation of tryptic N-linked glycopeptides in glycoprotein analysis. The oxonium ions observed with high mass accuracy in the HCD spectrum of glycopeptides can be combined with characteristic fragmentation patterns in the CID spectrum resulting from consecutive glycosidic bond cleavages, to improve the detection and characterization of N-linked glycopeptides. As a means of automating this process, we describe here GlypID 2.0, a software tool that implements several algorithmic approaches to utilize MS information including accurate precursor mass and spectral patterns from both HCD and CID spectra, thus allowing for an unequivocal and accurate characterization of N-linked glycosylation sites of proteins.

Nano-LC-MS/MS of glycopeptides produced by nonspecific proteolysis enables rapid and extensive site-specific glycosylation determination

Given the biological importance of glycosylation on proteins, the identification of protein glycosylation sites is integral to understanding broader biological structure and function. Unfortunately, the determination of the microheterogeneity at the site of glycosylation still remains a significant challenge. Nanoflow liquid chromatography with tandem mass spectrometry provides both separation of glycopeptides and the ability to determine glycan composition and site-specific glycosylation. However, because of the size of glycopeptides, they are not often amenable to tandem MS. In this work, proteins are digested with multiple proteases to produce glycopeptides that are of suitable size for tandem MS analysis. The conditions for collision-induced dissociation are optimized to obtain diagnostic ions that maximize glycan and peptide information. The method is applied to glycoproteins with contrasting glycans and multiple sites of glycosylation and identifies multiple glycan compositions at each individual glycosylation site. This method provides an important improvement in the routine determination of glycan microheterogeneity by mass spectrometry.