A strategy for identification of oligosaccharide structures using observational multistage mass spectral library

A self-adapting first-principles exploration on the dissociation mechanism in sodiated aldohexose pyranoses assisted with neural network potentials

Understanding the mechanism of collision-induced dissociation (CID) in mono-saccharides with density functional theory (DFT) is challenging because of many possible reaction paths that originate from their high structural diversity. To search for the transition state (TS) from the huge number of conformers, we propose a three-step search scheme with the assistance of neural network potential (NNP). The search starts from a cross-checking of sugars, to a global search of all possible channels, and in the end, an exhaustive exploration around the low-lying channels. The cross-checking step quickly adapts the NNP from the studied molecules to the target ones. The other two steps utilize the adapted NNP to find the available pathways via random sampling of the structures. The study of the CID reactions in all eight types of aldohexose pyranoses was applied using the search scheme. The DFT calculations on AH-0 (Glc, Gal, and Man) in the previous study were utilized to construct an NNP and provide the TS structure database for searching AH-1 (All, Alt, Gul, Ido, and Tal). In total, we identified around 5200 TSs in AH-0 and AH-1, and the final NNP covers an energy range of more than 500 kJ mol^-1 with a mean absolute error of energy less than 4 kJ mol^-1. The search scheme is useful not only for saccharides but also for highly flexible bio-molecules.

Plants Metabolome Study: Emerging Tools and Techniques

Metabolomics is now considered a wide-ranging, sensitive and practical approach to acquire useful information on the composition of a metabolite pool present in any organism, including plants. Investigating metabolomic regulation in plants is essential to understand their adaptation, acclimation and defense responses to environmental stresses through the production of numerous metabolites. Moreover, metabolomics can be easily applied for the phenotyping of plants; and thus, it has great potential to be used in genome editing programs to develop superior next-generation crops. This review describes the recent analytical tools and techniques available to study plants metabolome, along with their significance of sample preparation using targeted and non-targeted methods. Advanced analytical tools, like gas chromatography-mass spectrometry (GC-MS), liquid chromatography mass-spectroscopy (LC-MS), capillary electrophoresis-mass spectrometry (CE-MS), fourier transform ion cyclotron resonance-mass spectrometry (FTICR-MS) matrix-assisted laser desorption/ionization (MALDI), ion mobility spectrometry (IMS) and nuclear magnetic resonance (NMR) have speed up precise metabolic profiling in plants. Further, we provide a complete overview of bioinformatics tools and plant metabolome database that can be utilized to advance our knowledge to plant biology.

Advances in mass spectrometry-based glycomics-An update covering the period 2017-2021

The wide variety of chemical properties and biological functions found in proteins is attained via post-translational modifications like glycosylation. Covalently bonded to proteins, glycans play a critical role in cell activity. Complex structures with microheterogeneity, the glycan structures that are associated with proteins are difficult to analyze comprehensively. Recent advances in sample preparation methods, separation techniques, and MS have facilitated the quantitation and structural elucidation of glycans. This review focuses on highlighting advances in MS-based techniques for glycomic analysis that occurred over the last 5 years (2017-2021) as an update to the previous review on the subject. The topics of discussion will include progress in glycomic workflow such as glycan release, purification, derivatization, and separation as well as the topics of ionization, tandem MS, and separation techniques that can be coupled with MS. Additionally, bioinformatics tools used for the analysis of glycans will be described.

Metabolomics: small molecules that matter more

Metabolomics, an analytical study with high-throughput profiling, helps to understand interactions within a biological system. Small molecules, called metabolites or metabolomes with the size of <1500 Da, depict the status of a biological system in a different manner. Currently, we are in need to globally analyze the metabolome and the pathways involved in healthy, as well as diseased conditions, for possible therapeutic applications. Metabolome analysis has revealed high-abundance molecules during different conditions such as diet, environmental stress, microbiota, and disease and treatment states. As a result, it is hard to understand the complete and stable network of metabolites of a biological system. This review helps readers know the available techniques to study metabolomics in addition to other major omics such as genomics, transcriptomics, and proteomics. This review also discusses the metabolomics in various pathological conditions and the importance of metabolomics in therapeutic applications.

Databases and Bioinformatic Tools for Glycobiology and Glycoproteomics

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

Best-first search guided multistage mass spectrometry-based glycan identification

MOTIVATION

Glycan identification has long been hampered by complicated branching patterns and various isomeric structures of glycans. Multistage mass spectrometry (MSn) is a promising glycan identification technique as it generates multiple-level fragments of a glycan, which can be explored to deduce branching pattern of the glycan and further distinguish it from other candidates with identical mass. However, the automatic glycan identification still remains a challenge since it mainly relies on expertise to guide a MSn instrument to generate spectra.

RESULTS

Here, we proposed a novel method, named bestFSA, based on a best-first search algorithm to guide the process of spectrum producing in glycan identification using MSn. BestFSA is able to select the most appropriate peaks for next round of experiments and complete the identification using as few experimental rounds. Our analysis of seven representative glycans shows that bestFSA correctly distinguishes actual glycans efficiently and suggested bestFSA could be used in practical glycan identification. The combination of the MSn technology coupled with bestFSA should greatly facilitate the automatic identification of glycan branching patterns, with significantly improved identification sensitivity, and reduce time and cost of MSn experiments.

AVAILABILITY AND IMPLEMENTATION

http://glycan.ict.ac.cn.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Automation of mass spectrometric detection of analytes and related workflows: A review

The developments in mass spectrometry (MS) in the past few decades reveal the power and versatility of this technology. MS methods are utilized in routine analyses as well as research activities involving a broad range of analytes (elements and molecules) and countless matrices. However, manual MS analysis is gradually becoming a thing of the past. In this article, the available MS automation strategies are critically evaluated. Automation of analytical workflows culminating with MS detection encompasses involvement of automated operations in any of the steps related to sample handling/treatment before MS detection, sample introduction, MS data acquisition, and MS data processing. Automated MS workflows help to overcome the intrinsic limitations of MS methodology regarding reproducibility, throughput, and the expertise required to operate MS instruments. Such workflows often comprise automated off-line and on-line steps such as sampling, extraction, derivatization, and separation. The most common instrumental tools include autosamplers, multi-axis robots, flow injection systems, and lab-on-a-chip. Prototyping customized automated MS systems is a way to introduce non-standard automated features to MS workflows. The review highlights the enabling role of automated MS procedures in various sectors of academic research and industry. Examples include applications of automated MS workflows in bioscience, environmental studies, and exploration of the outer space.

Advancing Solutions to the Carbohydrate Sequencing Challenge

Carbohydrates possess a variety of distinct features with stereochemistry playing a particularly important role in distinguishing their structure and function. Monosaccharide building blocks are defined by a high density of chiral centers. Additionally, the anomericity and regiochemistry of the glycosidic linkages carry important biological information. Any carbohydrate-sequencing method needs to be precise in determining all aspects of this stereodiversity. Recently, several advances have been made in developing fast and precise analytical techniques that have the potential to address the stereochemical complexity of carbohydrates. This perspective seeks to provide an overview of some of these emerging techniques, focusing on those that are based on NMR and MS-hybridized technologies including ion mobility spectrometry and IR spectroscopy.

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

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

Lectin-Based Assay for Glycoform-Specific Detection of α2,6-sialylated Transferrin and Carcinoembryonic Antigen in Tissue and Body Fluid

Antibodies are useful for detecting glycoprotein antigens, but a conventional antibody recognizes only a protein epitope rather than a glycan. Thus, glycan isoform detection generally requires time- and labor-consuming processes such as lectin affinity column chromatography followed by sandwich ELISA. We recently found antigen-antibody reactions that were inhibited by lectin binding to glycans on the glycoprotein antigen, leading to a convenient glycoform-specific assay. Indeed, Sambucus sieboldiana agglutinin (SSA) lectin, a binder to sialylα2,6galactose residue, inhibited antibody binding to α2,6-sialylated transferrin (Tf) (SSA inhibition). SSA inhibition was not observed with other glycoforms, such as periodate-treated, sialidase-treated and sialidase/galactosidase-treated Tf, suggesting that the assay was glycoform-specific. SSA inhibition was also applicable for visualizing localization of α2,6-sialylated-Tf in a liver section. This is the first immunohistochemical demonstration of glycoform localization in a tissue section. SSA inhibition was utilized for establishing ELISA to quantify α2,6-sialylated carcinoembryonic antigen (CEA), a marker for various cancers. In addition, α2,6-sialylated-CEA was visualized in a colonic adenocarcinoma section by SSA inhibition. The method would further be applicable to a simple and rapid estimation of other α2,6-sialylated glycoproteins and have a potential aid to histopathological diagnosis.

Synthesis and structural investigation of a series of mannose-containing oligosaccharides using mass spectrometry

A series of compounds associated with naturally occurring and biologically relevant glycans consisting of α-mannosides were prepared and analyzed using collision-induced dissociation (CID), energy-resolved mass spectrometry (ERMS), and ¹H nuclear magnetic resonance spectroscopy. The CID experiments of sodiated species of disaccharides and ERMS experiments revealed that the order of stability of mannosyl linkages was as follows: 6-linked > 4-linked ≧ 2-linked > 3-linked mannosyl residues. Analysis of linear trisaccharides revealed that the order observed in disaccharides could be applied to higher glycans. A branched trisaccharide showed a distinct dissociation pattern with two constituting disaccharide ions. The estimation of the content of this ion mixture was possible using the disaccharide spectra. The hydrolysis of mannose linkages at 3- and 6-positions in the branched trisaccharide revealed that the 3-linkage was cleaved twice as fast as the 6-linkage. It was observed that the solution-phase hydrolysis and gas-phase dissociation have similar energetics.

Extending a Tandem Mass Spectral Library to Include MS2 Spectra of Fragment Ions Produced In-Source and MSn Spectra

Tandem mass spectral library searching is finding increased use as an effective means of determining chemical identity in mass spectrometry-based omics studies. We previously reported on constructing a tandem mass spectral library that includes spectra for multiple precursor ions for each analyte. Here we report our method for expanding this library to include MS² spectra of fragment ions generated during the ionization process (in-source fragment ions) as well as MS³ and MS⁴ spectra. These can assist the chemical identification process. A simple density-based clustering algorithm was used to cluster all significant precursor ions from MS¹ scans for an analyte acquired during an infusion experiment. The MS² spectra associated with these precursor ions were grouped into the same precursor clusters. Subsequently, a new top-down hierarchical divisive clustering algorithm was developed for clustering the spectra from fragmentation of ions in each precursor cluster, including the MS² spectra of the original precursors and of the in-source fragments as well as the MSⁿ spectra. This algorithm starts with all the spectra of one precursor in one cluster and then separates them into sub-clusters of similar spectra based on the fragment patterns. Herein, we describe the algorithms and spectral evaluation methods for extending the library. The new library features were demonstrated by searching the high resolution spectra of E. coli extracts against the extended library, allowing identification of compounds and their in-source fragment ions in a manner that was not possible before. Graphical Abstract ᅟ.

Fragmentation of Oligosaccharides from Sodium Adduct Molecules Depends on the Position of N-Acetyl Hexosamine Residue in Their Sequences in Mass Spectrometry

Six different sequences of hexasaccharides, pyridylaminated malto-hexaoses containing one N-acetyl hexosamine (HexNAc) residue, were analyzed using matrix-assisted laser desorption/ionization (MALDI) tandem time-of-flight (TOF) mass spectrometry (MS). Based on the product ion spectra of sodium adducts [M+Na]⁺, the chemical species of the observed product ions contained a HexNAc residue and had high ion abundance, indicating that the HexNAc residue had a higher affinity to sodium atom than glucopyranose. The acetamide group coordinated easily to sodium atom. This general rule of product ion generation was useful to predict the structure of the oligosaccharides based on the MS/MS product ion spectra.

Glycoforest 1.0

Tandem mass spectrometry, when combined with liquid chromatography and applied to complex mixtures, produces large amounts of raw data, which needs to be analyzed to identify molecular structures. This technique is widely used, particularly in glycomics. Due to a lack of high throughput glycan sequencing software, glycan spectra are predominantly sequenced manually. A challenge for writing glycan-sequencing software is that there is no direct template that can be used to infer structures detectable in an organism. To help alleviate this bottleneck, we present Glycoforest 1.0, a partial de novo algorithm for sequencing glycan structures based on MS/MS spectra. Glycoforest was tested on two data sets (human gastric and salmon mucosa O-linked glycomes) for which MS/MS spectra were annotated manually. Glycoforest generated the human validated structure for 92% of test cases. The correct structure was found as the best scoring match for 70% and among the top 3 matches for 83% of test cases. In addition, the Glycoforest algorithm detected glycan structures from MS/MS spectra missing a manual annotation. In total 1532 MS/MS previously unannotated spectra were annotated by Glycoforest. A portion containing 521 spectra was manually checked confirming that Glycoforest annotated an additional 50 MS/MS spectra overlooked during manual annotation.

Mass spectrometric profiling reveals association of N-glycan patterns with epithelial ovarian cancer progression

Aberrant changes of N-glycan modifications on proteins have been linked to various diseases including different cancers, suggesting possible avenue for exploring their etiologies based on N-glycomic analysis. Changes in N-glycan patterns during epithelial ovarian cancer development have so far been investigated mainly using serum, plasma, ascites, and cell lines. However, changes in patterns of N-glycans in tumor tissues during epithelial ovarian cancer progression have remained largely undefined. To investigate whether changes in N-glycan patterns correlate with oncogenesis and progression of epithelial ovarian cancer, we profiled N-glycans from formalin-fixed paraffin-embedded tissue slides using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and quantitatively compared among different pathological grades of epithelial ovarian cancer and healthy controls. Our results show that among the 80 compositions of N-glycan detected, expression levels of high-mannose type were higher in epithelial ovarian cancer samples than that observed in healthy controls, accompanied by reduced levels of hybrid-type glycans. By applying receiver operating characteristic analysis, we show that a combined panel composed of four high-mannose and three fucosylated neutral complex N-glycans allows for good discrimination of epithelial ovarian cancer from healthy controls. Furthermore, using a statistical analysis of variance assay, we found that different N-glycan patterns, including 2 high-mannose-type, 2 fucosylated and sialylated complex structures, and 10 fucosylated neutral complex N-glycans, exhibited specific changes in N-glycan abundance across epithelial ovarian cancer grades. Together, our results provide strong evidence that N-glycomic changes are a strong indicator for epithelial ovarian cancer pathological grades and should provide avenues to identify novel biomarkers for epithelial ovarian cancer diagnosis and monitoring.

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.

Identification of sperm equatorial segment protein 1 in the acrosome as the primary binding target of peanut agglutinin (PNA) in the mouse testis

Peanut agglutinin (PNA), a plant lectin protein that recognizes the galactose β (1 -> 3) N-acetylgalactosamine carbohydrate sequence, has been widely used as a sperm acrosome-specific marker; however, the acrosomal glycoproteins that specifically bind to PNA have yet to be identified. We herein purified and identified PNA-binding glycoproteins in the mouse testis using biotinylated PNA and streptavidin-coupled magnetic beads, and liquid chromatography-tandem mass spectrometry (LC-MS/MS), respectively. In six repeated experiments, sperm equatorial segment protein 1 (SPESP1) was detected most frequently as a PNA-binding glycoprotein, followed by dipeptidase 3, proacrosin-binding protein, and acrosin prepropeptide. The identification of SPEPS1 in the testis lysate and its PNA-bound fraction was verified with lectin and Western blot analyses, and the co-localization of PNA and SPEPS1 in acrosomes was confirmed with lectin- and immunohistochemistry. Since the PNA reactivity of sperm acrosomes was observed not only in normal mice, but also in SPESP1-deficient mice, although at lower levels, PNA was also considered to bind to other candidate glycoproteins. The present study identified SPESP1 in the acrosome as the primary binding target of PNA in the mouse testis. Further defining the specific lectin-glycoprotein relationships in individual cells will enhance the value of lectin histochemistry.

Comprehensive analysis of the N-glycan biosynthetic pathway using bioinformatics to generate UniCorn: A theoretical N-glycan structure database

Glycan structures attached to proteins are comprised of diverse monosaccharide sequences and linkages that are produced from precursor nucleotide-sugars by a series of glycosyltransferases. Databases of these structures are an essential resource for the interpretation of analytical data and the development of bioinformatics tools. However, with no template to predict what structures are possible the human glycan structure databases are incomplete and rely heavily on the curation of published, experimentally determined, glycan structure data. In this work, a library of 45 human glycosyltransferases was used to generate a theoretical database of N-glycan structures comprised of 15 or less monosaccharide residues. Enzyme specificities were sourced from major online databases including Kyoto Encyclopedia of Genes and Genomes (KEGG) Glycan, Consortium for Functional Glycomics (CFG), Carbohydrate-Active enZymes (CAZy), GlycoGene DataBase (GGDB) and BRENDA. Based on the known activities, more than 1.1 million theoretical structures and 4.7 million synthetic reactions were generated and stored in our database called UniCorn. Furthermore, we analyzed the differences between the predicted glycan structures in UniCorn and those contained in UniCarbKB (www.unicarbkb.org), a database which stores experimentally described glycan structures reported in the literature, and demonstrate that UniCorn can be used to aid in the assignment of ambiguous structures whilst also serving as a discovery database.

Computational approaches to define a human milk metaglycome

MOTIVATION

The goal of deciphering the human glycome has been hindered by the lack of high-throughput sequencing methods for glycans. Although mass spectrometry (MS) is a key technology in glycan sequencing, MS alone provides limited information about the identification of monosaccharide constituents, their anomericity and their linkages. These features of individual, purified glycans can be partly identified using well-defined glycan-binding proteins, such as lectins and antibodies that recognize specific determinants within glycan structures.

RESULTS

We present a novel computational approach to automate the sequencing of glycans using metadata-assisted glycan sequencing, which combines MS analyses with glycan structural information from glycan microarray technology. Success in this approach was aided by the generation of a 'virtual glycome' to represent all potential glycan structures that might exist within a metaglycomes based on a set of biosynthetic assumptions using known structural information. We exploited this approach to deduce the structures of soluble glycans within the human milk glycome by matching predicted structures based on experimental data against the virtual glycome. This represents the first meta-glycome to be defined using this method and we provide a publically available web-based application to aid in sequencing milk glycans.

AVAILABILITY AND IMPLEMENTATION

http://glycomeseq.emory.edu

CONTACT

sagravat@bidmc.harvard.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

"Omics" in pharmaceutical research: overview, applications, challenges, and future perspectives

In the post-genomic era, biological studies are characterized by the rapid development and wide application of a series of "omics" technologies, including genomics, proteomics, metabolomics, transcriptomics, lipidomics, cytomics, metallomics, ionomics, interactomics, and phenomics. These "omics" are often based on global analyses of biological samples using high through-put analytical approaches and bioinformatics and may provide new insights into biological phenomena. In this paper, the development and advances in these omics made in the past decades are reviewed, especially genomics, transcriptomics, proteomics and metabolomics; the applications of omics technologies in pharmaceutical research are then summarized in the fields of drug target discovery, toxicity evaluation, personalized medicine, and traditional Chinese medicine; and finally, the limitations of omics are discussed, along with the future challenges associated with the multi-omics data processing, dynamics omics analysis, and analytical approaches, as well as amenable solutions and future prospects.

Development of M2BPGi: a novel fibrosis serum glyco-biomarker for chronic hepatitis/cirrhosis diagnostics

Many proteins in the living body are glycoproteins, which present glycans linked on their surface. Glycan structures reflect the degree of cell differentiation or canceration and are cell specific. These characteristics are advantageous in the development of various disease biomarkers. Glycoprotein-based biomarkers (glyco-biomarkers) are developed by utilizing the specific changes in the glycan structure on a glycoprotein secreted from the diseased cells of interest. Therefore, quantification of the altered glycan structures is the key to developing a new glyco-biomarker. Glycoscience is a relatively new area of molecular science, and recent advancement of glycotechnologies is remarkable. In the author's institute, new glycoscience technologies have been designed to be efficiently utilized for the development of new diagnostic agents. This paper introduces a strategy for glyco-biomarker development, which was successfully applied in the development of Wisteria floribunda agglutinin-positive Mac-2 binding protein M2BPGi, a liver fibrosis marker now commercially available for clinical use.

Highly sensitive fluorescence detection of glycoprotein based on energy transfer between CuInS2 QDs and rhodamine B

A highly sensitive fluorescence method for glycoprotein detection has been established based on fluorescence resonance energy transfer (FRET) between CuInS2 quantum dots (QDs) and rhodamine B (RB). Lectins comprise a group of proteins with unique affinities toward carbohydrate structures, so the process of FRET can occur between lectin-coated QDs (CuInS2 QDs-Con A conjugates, acceptors) and carbohydrate-coated RB (RB-NH2-glu conjugates, donors). The fluorescence of lectin-coated QDs was recovered in the presence of a glycoprotein such as glucose oxidase (GOx) and transferrin (TRF), which significantly reduced the FRET efficiency between the donor and the acceptor. Under optimal conditions, a linear correlation was established between the fluorescence intensity ratio I654/I577 and the TRF concentration over the range of 6.90 × 10(-10) to 3.45 × 10(-8) mol/L, with a detection limit of 2.5 × 10(-10) mol/L. The linear range for GOx is 3.35 × 10(-10) to 6.70 × 10(-8) mol/L, with a detection limit of 1.5 × 10(-10) mol/L. The proposed method was applied to the determination of glycoprotein in human serum and cell-extract samples with satisfactory results. Furthermore, CuInS2  QDs-Con A conjugates are used as safe and efficient optical nanoprobes in HepG2 cell imaging.

JCGGDB: Japan Consortium for Glycobiology and Glycotechnology Database

The biological significance of glycans has been widely studied and reported in the past. However, most achievements of our predecessors are not readily available in existing databases. JCGGDB is a meta-database involving 15 original databases in AIST and 5 cooperative databases in alliance with JCGG: Japan Consortium for Glycobiology and Glycotechnology. It centers on a glycan structure database and accumulates information such as glycan preferences of lectins, glycosylation sites in proteins, and genes related to glycan syntheses from glycoscience and related fields. This chapter illustrates how to use three major search interfaces (Keyword Search, Structure Search, and GlycoChem Explorer) available in JCGGDB to search across multiple databases.

Enhancing MS(n) mass spectrometry strategy for carbohydrate analysis: A b2 ion spectral library

Searchable mass spectral libraries for glycans may be enhanced using a B2 ion library. Using a quadrupole ion-trap mass spectrometer, successive fragmentations of sodiated oligosaccharides were carried out in the positive ion mode. In B,Y-type fragmentation, disaccharide B2 ions are generated which correspond to specific glycosidic linkages using progressive MS stages. Fragmentation of "B2 ions" corresponding to glycosidic linkages such as Hex-Fuc, Hex-Hex, Hex-HexNAc, HexNAc-Hex and HexNAc-HexNAc, were systematically studied in low energy CID and collected to form a "B2 library". Linkages produce characteristic fragmentation patterns in the absence of cross-ring fragmentation. Patterns of "B2 ions" rely on relative stability of glycosidic bonds and carbohydrate-metal complexes in the gas phase. MS(n) studies of linear, branched trisaccharides and tetrasaccharides show that isomers for which B2 ion information is not available are rarely a problem in practice by their absence in an isomeric sequence or by their scarcity in nature. This MS strategy for linkage determination of carbohydrates aided by a "B2 library" was developed with a scope for expansion, providing an improved tool for glycomics. We validated this method examining levels of expressed activities of two glycosyl transferases in cancer cell lines: β3(B3GALNT2) and β4GalNAcT(B4GALNT3&4) that generate GalNAcβ3GlcNAcβ and GalNAcβ4GlcNAcβ.

BIOLOGICAL SIGNIFICANCE

Glycosylation is an important class of the "postranslationome", which includes manifold aspects of post-translational protein modification, affecting protein conformation, providing ligands for protein receptors [1-5], and encoding unique haptenic [6,7] or antigenic markers for oncology [8-11] and other applications. Identification of individual monomeric units, linkages, ring size, branching and anomerity has posed significant challenges to mass spectrometrists. MS(n) is a growing key instrumental method to differentiate among isomers [12]. While the potential isomers in oligosaccharides are impossibly large [12], likely possibilities can be limited by the biological system, including the expressed glycosyl transferases [13-20]. Mass spectra from sequential stages of collision activation (MS(n)) can supply structural details for precise characterization of linkage, monomer ID, substitutions, anomerity and branching [21-25]. There is a fundamental need for high throughput tools in glycomics to complement proteome studies. In that regard, nothing could be more important than searchable spectral library files for structural confirmation. The National Academy of Science (NAS) report (http://glyco.nas.edu) recommends the need of more than 10,000 synthetic structures of carbohydrates to advance the field of glycomics. This study demonstrates that the general reproducibility of ion trap spectra, and energy independence from modes of ionization and collisional activation, make compiling an MS(n) library for carbohydrate identification an achievable research target [26]. We intend to use the new B2 library for carbohydrate differences found on cancers, where we profile the glycosyltransferases to predict classes of potential structures, and use the library for MS identification of the expected cohort of altered structures.

Discovery of specific metastasis-related N-glycan alterations in epithelial ovarian cancer based on quantitative glycomics

Generally, most of ovarian cancer cannot be detected until large scale and remote metastasis occurs, which is the major cause of high mortality in ovarian cancer. Therefore, it is urgent to discover metastasis-related biomarkers for the detection of ovarian cancer in its occult metastasis stage. Altered glycosylation is a universal feature of malignancy and certain types of glycan structures are well-known markers for tumor progressions. Thus, this study aimed to reveal specific changes of N-glycans in the secretome of the metastatic ovarian cancer. We employed a quantitative glycomics approach based on metabolic stable isotope labeling to compare the differential N-glycosylation of secretome between an ovarian cancer cell line SKOV3 and its high metastatic derivative SKOV3-ip. Intriguingly, among total 17 N-glycans identified, the N-glycans with bisecting GlcNAc were all significantly decreased in SKOV3-ip in comparison to SKOV3. This alteration in bisecting GlcNAc glycoforms as well as its corresponding association with ovarian cancer metastatic behavior was further validated at the glycotransferase level with multiple techniques including real-time PCR, western blotting, transwell assay, lectin blotting and immunohistochemistry analysis. This study illustrated metastasis-related N-glycan alterations in ovarian cancer secretome in vitro for the first time, which is a valuable source for biomarker discovery as well. Moreover, N-glycans with bisecting GlcNAc shed light on the detection of ovarian cancer in early peritoneal metastasis stage which may accordingly improve the prognosis of ovarian cancer patients.

Linkage determination of linear oligosaccharides by MS(n) (n > 2) collision-induced dissociation of Z₁ ions in the negative ion mode

Obtaining unambiguous linkage information between sugars in oligosaccharides is an important step in their detailed structural analysis. An approach is described that provides greater confidence in linkage determination for linear oligosaccharides based on multiple-stage tandem mass spectrometry (MS(n), n >2) and collision-induced dissociation (CID) of Z1 ions in the negative ion mode. Under low energy CID conditions, disaccharides (18)O-labeled on the reducing carbonyl group gave rise to Z1 product ions (m/z 163) derived from the reducing sugar, which could be mass-discriminated from other possible structural isomers having m/z 161. MS(3) CID of these m/z 163 ions showed distinct fragmentation fingerprints corresponding to the linkage types and largely unaffected by sugar unit identities or their anomeric configurations. This unique property allowed standard CID spectra of Z1 ions to be generated from a small set of disaccharide samples that were representative of many other possible isomeric structures. With the use of MS(n) CID (n = 3 - 5), model linear oligosaccharides were dissociated into overlapping disaccharide structures, which were subsequently fragmented to form their corresponding Z1 ions. CID data of these Z1 ions were collected and compared with the standard database of Z1 ion CID using spectra similarity scores for linkage determination. As the proof-of-principle tests demonstrated, we achieved correct determination of individual linkage types along with their locations within two trisaccharides and a pentasaccharide.

Amino and acetamide functional group effects on the ionization and fragmentation of sugar chains in positive-ion mass spectrometry

To elucidate the influence of amino (-NH2) and acetamide (-NHCOCH3, -NAc) groups in sugar chains on their ionization and fragmentation, cycloamyloses (cyclodextrins, CyDs) and lacto-oligosaccharide are analyzed by MALDI TOF/TOF and ESI Q-TOF mass spectrometry. CyD derivatives substituted by amino or acetamide groups are ideal analytes to extract the function group effects, which are amino-CyD with one hexosamine (HexNH2) and acetamide-CyD with one N-acetyl hexosamine (HexNAc). Interestingly, the relative ion intensities and isotope-like patterns in their product ion spectra depend on the functional groups and ion forms of sugar chains. Consequently, the results indicate that a proton (H(+)) localizes on the amino group of the amino sugar, and that the proton (H(+)) induces their fragmentation. Sodium cation (Na(+)) attachment is independent from amino group and exerts no influence on their fragmentation patterns in amino group except for mono- and disaccharide fragment ions because there is the possibility of the reducing end effect. In contrast, a sodium cation localizes much more frequently on the acetamide group in acetamide-CyDs because the chemical species with HexNAc are stable. Thus, their ions with HexNAc are abundant. These results are consistent with the fragmentation of lacto-neo-N-tetraose and maltotetraose, suggesting that a sodium cation generally localizes much more frequently on the acetamide group in sugar chains.

Analytical tools for the study of cellular glycosylation in the immune system

It is becoming increasingly clear that glycosylation plays important role in intercellular communication within the immune system. Glycosylation-dependent interactions are crucial for the innate and adaptive immune system and regulate immune cell trafficking, synapse formation, activation, and survival. These functions take place by the cis or trans interaction of lectins with glycans. Classical immunological and biochemical methods have been used for the study of lectin function; however, the investigation of their counterparts, glycans, requires very specialized methodologies that have been extensively developed in the past decade within the Glycobiology scientific community. This mini-review intends to summarize the available technology for the study of glycan biosynthesis, its regulation and characterization for their application to the study of glycans in immunology.

The Xeno-glycomics database (XDB): a relational database of qualitative and quantitative pig glycome repertoire

SUMMARY

In recent years, the improvement of mass spectrometry-based glycomics techniques (i.e. highly sensitive, quantitative and high-throughput analytical tools) has enabled us to obtain a large dataset of glycans. Here we present a database named Xeno-glycomics database (XDB) that contains cell- or tissue-specific pig glycomes analyzed with mass spectrometry-based techniques, including a comprehensive pig glycan information on chemical structures, mass values, types and relative quantities. It was designed as a user-friendly web-based interface that allows users to query the database according to pig tissue/cell types or glycan masses. This database will contribute in providing qualitative and quantitative information on glycomes characterized from various pig cells/organs in xenotransplantation and might eventually provide new targets in the α1,3-galactosyltransferase gene-knock out pigs era.

AVAILABILITY

The database can be accessed on the web at http://bioinformatics.snu.ac.kr/xdb.

Tandem mass spectra of glycan substructures enable the multistage mass spectrometric identification of determinants on oligosaccharides

RATIONALE

Glycosylation of proteins and lipids affects many biological processes, such as host-pathogen interactions, cell communication, and initiation of the immune responses. Terminal glycan substructures, or determinants, often govern the function or recognition of the carrier glycoconjugate and modulate these processes. In this study we describe a strategy using multistage mass spectrometry to identify and confirm these glycan substructures.

METHODS

An online tandem mass spectrometry (MS(2)) spectral fragment library of glycan substructures that typically occur at the non-reducing terminus of glycoconjugates was created to enable the easier identification and confirmation of glycan determinants on oligosaccharides released from glycoproteins. Oligosaccharides were separated by porous graphitized carbon capillary chromatography and analysed by ion trap MS. Candidate product ions that constitute the glycan substructure mass were identified in the MS(2) product ion spectrum, and used as the precursor ion for subsequent MS(3) fragmentation. The resulting MS(3) spectrum was matched against the MS(2) spectral fragment library to identify the glycan substructure(s) that comprise the parent oligosaccharide.

RESULTS

Thirty biologically important terminal glycan determinants commonly observed on glycoconjugates were fragmented by positive and negative ion mass spectrometry and the MS(2) product ion masses manually annotated and stored in the UniCarb-DB online database. Negative ion tandem mass spectra were especially useful in assigning isobaric glycan structures. We have applied this strategy for the identification of the sulphation, blood group antigens and sialic acid linkages on complex N-and O-glycans released from glycoproteins.

CONCLUSIONS

We show the potential of these glycan substructure MS(2) spectra in the negative ionization mode to facilitate the assignment of determinants on N- and O-linked glycans released from glycoproteins. Comparing the structural feature ions of known glycan reference substructures assists in the annotation of complex glycan product ion spectra, and can remove the need for other orthogonal confirmation analyses such as sequential glycosidase digestion.

Using databases and web resources for glycomics research

Many databases of carbohydrate structures and related information can be found on the World Wide Web. This review covers the major carbohydrate databases that have potential utility for glycoscientists and researchers entering the glycosciences. The first half provides a brief overview of carbohydrate databases and web resources (including a history of carbohydrate databases and carbohydrate notations used in these databases), and the second half provides a guide that can be used as an index to determine which resources provide the data of most interest to the user.

Functional protein microarray as molecular decathlete: a versatile player in clinical proteomics

Functional protein microarrays were developed as a high-throughput tool to overcome the limitations of DNA microarrays and to provide a versatile platform for protein functional analyses. Recent years have witnessed tremendous growth in the use of protein microarrays, particularly functional protein microarrays, to address important questions in the field of clinical proteomics. In this review, we will summarize some of the most innovative and exciting recent applications of protein microarrays in clinical proteomics, including biomarker identification, pathogen-host interactions, and cancer biology.

Employment of tandem mass spectrometry for the accurate and specific identification of oligosaccharide structures

A method is described for the rapid identification of oligosaccharides employing a library of tandem MS spectra. Identification is aided by software that compares the sample tandem MS to those in the library. The method incorporates quadrupole time-of-flight mass spectrometry along with an annotated oligosaccharide (OS) structure library and the MassHunter Personal Compound Database and Library (PCDL) software. With an automated spectra search, OS structures in different samples are readily identified. This method is shown to be useful in the study of milk oligosaccharides but can be readily applied to oligosaccharide pools in other biological tissues.

Infrared multiple photon dissociation spectroscopy and computational studies of O-glycosylated peptides

The infrared multiple photon dissociation (IRMPD) spectra of O-glycosylated peptides in the gas phase were studied in the IR scanning range of 5.7-9.5 μm. Fragmentation of protonated and sodiated O-glycopeptides was investigated using electrospray ionization (ESI) Fourier-transform ion cyclotron resonance (FTICR) mass spectrometry (MS) with a free electron laser (FEL). FEL is used in the IRMPD technique as a tunable IR light source. In the IRMPD spectroscopic analysis of the protonated O-glycopeptide, fragment ions of the b/y and B/Y types were observed in the range of 5.7-9.5 μm, corresponding to the cleavage of the backbone in the parent amino acid sequence and glycosyl bonds, whereas the spectra of the sodiated glycopeptide showed major peaks of photoproducts of the B/Y type in the range of 8.4-9.5 μm. The IRMPD spectra of the O-glycopeptides were compared with simulated IR spectra for the structures obtained from the molecular dynamics.

Differentiation of the stereochemistry and anomeric configuration for 1-3 linked disaccharides via tandem mass spectrometry and 18O-labeling

Collision-induced dissociation (CID) of deprotonated hexose-containing disaccharides (m/z 341) with 1-2, 1-4, and 1-6 linkages yields product ions at m/z 221, which have been identified as glycosyl-glycolaldehyde anions. From disaccharides with these linkages, CID of m/z 221 ions produces distinct fragmentation patterns that enable the stereochemistries and anomeric configurations of the non-reducing sugar units to be determined. However, only trace quantities of m/z 221 ions can be generated for 1-3 linkages in Paul or linear ion traps, preventing further CID analysis. Here we demonstrate that high intensities of m/z 221 ions can be built up in the linear ion trap (Q3) from beam-type CID of a series of 1-3 linked disaccharides conducted on a triple quadrupole/linear ion trap mass spectrometer. (18)O-labeling at the carbonyl position of the reducing sugar allowed mass-discrimination of the "sidedness" of dissociation events to either side of the glycosidic linkage. Under relatively low energy beam-type CID and ion trap CID, an m/z 223 product ion containing (18)O predominated. It was a structural isomer that fragmented quite differently than the glycosyl-glycolaldehydes and did not provide structural information about the non-reducing sugar. Under higher collision energy beam-type CID conditions, the formation of m/z 221 ions, which have the glycosyl-glycolaldehyde structures, were favored. Characteristic fragmentation patterns were observed for each m/z 221 ion from higher energy beam-type CID of 1-3 linked disaccharides and the stereochemistry of the non-reducing sugar, together with the anomeric configuration, were successfully identified both with and without (18)O-labeling of the reducing sugar carbonyl group.

Databases and tools in glycobiology

Glycans are crucial to the functioning of multicellular organisms. They may also play a role as mediators between host and parasite or symbiont. As many proteins (>50%) are posttranslationally modified by glycosylation, this mechanism is considered to be the most widespread posttranslational modification in eukaryotes. These surface modifications alter and regulate structure and biological activities/functions of proteins/biomolecules as they are largely involved in the recognition process of the appropriate structure in order to bind to the target cells. Consequently, the recognition of glycans on cellular surfaces plays a crucial role in the promotion or inhibition of various diseases and, therefore, glycosylation itself is considered to be a critical protein quality control attribute for commercial therapeutics, which is one of the fastest growing segments in the pharmaceutical industry. With the development of glycobiology as a separate discipline, a number of databases and tools became available in a similar way to other well-established "omics." Alleviating the recognized shortcomings of the available tools for data storage and retrieval is one of the highest priorities of the international glycoinformatics community. In the last decade, major efforts have been made, by leading scientific groups, towards the integration of a number of major databases and tools into a single portal, which would act as a centralized data repository for glycomics, equipped with a number of comprehensive analytical tools for data systematization, analysis, and comparison. This chapter provides an overview of the most important carbohydrate-related databases and glycoinformatic tools.

A multiplexed bead assay for profiling glycosylation patterns on serum protein biomarkers of pancreatic cancer

A multiplexed bead-based immunoassay was developed to simultaneously profile glycosylation patterns of serum proteins to investigate their usefulness as biomarkers for pancreatic cancer. The multiplex assay utilized protein-specific capture antibodies chemically coupled individually to beads labeled with specific amounts of fluorescent dye. Captured proteins were detected based on the extent and specific type of glycosylation as determined by successive binding of fluorescent lectin probes. Advantages to this technique include the fact that antibodies coupled to the beads had minimal nonspecific binding to the lectins ConA/SNA, avoiding the step of chemically blocking the antibody glycans and the bead assays were performed in a 96-well filter plate enabling high-throughput screening applications with improved reproducibility. The assay was tested with ConA and SNA lectins to examine the glycosylation patterns of α-1-β glycoprotein (A1BG) and serum amyloid p (SAP) component for use as potential biomarkers for the detection of pancreatic cancer based on the results from prior biomarker studies. The results showed that the SNA response on the captured A1BG protein could distinguish chronic pancreatitis samples from pancreatic cancer with a p-value of 0.035 and for the SAP protein with SNA, a p-value of 0.026 was found between the signal of normal controls and the pancreatic cancer samples. For the ConA response, a decline in the signal for both proteins in the serum samples was found to distinguish pancreatic cancer from normal controls and renal cell carnoma samples (A1BG, p<0.05; and SAP, p<0.0001).