Sharing of worldwide distributed carbohydrate-related digital resources: online connection of the Bacterial Carbohydrate Structure DataBase and GLYCOSCIENCES.de

Simple and practical sialoglycan encoding system reveals vast diversity in nature and identifies a universal sialoglycan-recognizing probe derived from AB5 toxin B subunits

Vertebrate sialic acids (Sias) display much diversity in modifications, linkages, and underlying glycans. Slide microarrays allow high-throughput explorations of sialoglycan-protein interactions. A microarray presenting ~150 structurally defined sialyltrisaccharides with various Sias linkages and modifications still poses challenges in planning, data sorting, visualization, and analysis. To address these issues, we devised a simple 9-digit code for sialyltrisaccharides with terminal Sias and underlying two monosaccharides assigned from the nonreducing end, with 3 digits assigning a monosaccharide, its modifications, and linkage. Calculations based on the encoding system reveal >113,000 likely linear sialyltrisaccharides in nature. Notably, a biantennary N-glycan with 2 terminal sialyltrisaccharides could thus have >1010 potential combinations and a triantennary N-glycan with 3 terminal sequences, >1015 potential combinations. While all possibilities likely do not exist in nature, sialoglycans encode enormous diversity. While glycomic approaches are used to probe such diverse sialomes, naturally occurring bacterial AB5 toxin B subunits are simpler tools to track the dynamic sialome in biological systems. Sialoglycan microarray was utilized to compare sialoglycan-recognizing bacterial toxin B subunits. Unlike the poor correlation between B subunits and species phylogeny, there is stronger correlation with Sia-epitope preferences. Further supporting this pattern, we report a B subunit (YenB) from Yersinia enterocolitica (broad host range) recognizing almost all sialoglycans in the microarray, including 4-O-acetylated-Sias not recognized by a Yersinia pestis orthologue (YpeB). Differential Sia-binding patterns were also observed with phylogenetically related B subunits from Escherichia coli (SubB), Salmonella Typhi (PltB), Salmonella Typhimurium (ArtB), extra-intestinal E.coli (EcPltB), Vibrio cholera (CtxB), and cholera family homologue of E. coli (EcxB).

Monosaccharide Biosynthesis Pathways Database

A distinctive feature of glycans vis-à-vis proteins and nucleic acids is its structural complexity which arises from the huge repertoire of monosaccharides, isomeric linkages and branching. A very large number of monosaccharides have so far been discovered in natural glycans. Experimentally, pathways for the biosynthesis have been characterized completely for 55 monosaccharides and partially for a few more. However, there is no single platform which provides information about monosaccharide biosynthesis pathways and associated enzymes We have gathered 572 experimentally characterized enzymes of 66 biosynthesis pathways from literature and set up a first of its kind database called the Monosaccharide Biosynthesis Pathways Database http://www.bio.iitb.ac.in/mbpd/). Annotations such as the reaction catalysed, substrate specificity, biosynthesis pathway and PubMed IDs are provided for all the enzymes in the database. Sequence homologs of the experimentally characterized enzymes found in nearly 13,000 completely sequenced genomes from Bacteria and Archaea have also been included in the database. This platform will help in the deduction of evolutionary relationships among enzymes such as aminotransferases, nucleotidyltransferases, acetyltransferases and SDR family enzymes. It can also facilitate experimental studies such as direct enzyme assays to validate putative annotations, establish structure-function relationship, expression profiling to determine the function, determine the phenotypic consequences of gene knock-out/knock-in and complementation studies.

Insights into Bioinformatic Applications for Glycosylation: Instigating an Awakening towards Applying Glycoinformatic Resources for Cancer Diagnosis and Therapy

Glycosylation plays a crucial role in various diseases and their etiology. This has led to a clear understanding on the functions of carbohydrates in cell communication, which eventually will result in novel therapeutic approaches for treatment of various disease. Glycomics has now become one among the top ten technologies that will change the future. The direct implication of glycosylation as a hallmark of cancer and for cancer therapy is well established. As in proteomics, where bioinformatics tools have led to revolutionary achievements, bioinformatics resources for glycosylation have improved its practical implication. Bioinformatics tools, algorithms and databases are a mandatory requirement to manage and successfully analyze large amount of glycobiological data generated from glycosylation studies. This review consolidates all the available tools and their applications in glycosylation research. The achievements made through the use of bioinformatics into glycosylation studies are also presented. The importance of glycosylation in cancer diagnosis and therapy is discussed and the gap in the application of widely available glyco-informatic tools for cancer research is highlighted. This review is expected to bring an awakening amongst glyco-informaticians as well as cancer biologists to bridge this gap, to exploit the available glyco-informatic tools for cancer.

Biopolymer from marine Athelia and its application on heavy oil recovery in heterogeneous reservoir

Biopolymer produced from marine Athelia strain presented unique Pseudoplastic behaviors under extremely-high temperature and salinity conditions. Characteristic analysis with FT-IR spectroscopy, high performance liquid chromatography, 1H and 13C NMR and two-dimensional COSY and HMQC spectra showed the structure of β-(1-6) glucans. Single-factor and orthogonal experiment design were used to optimize the yield, the maximum yield of the biopolymer was 28.32 g/L with 56.64% carbon conversion rate under optimized conditions. Economic investigation demonstrated that this novel biopolymer has great potential of commercialization with the competitive cost of $2896.04-5228.94 per ton for powder. Resistance factor and residual resistance factor were evaluated with core flooding experiments showed that this biopolymer had excellent performance of plugging capacity and profile modification, and indicating the great potential of application on heavy oil recovery.

GlyTouCan: an accessible glycan structure repository

Rapid and continued growth in the generation of glycomic data has revealed the need for enhanced development of basic infrastructure for presenting and interpreting these datasets in a manner that engages the broader biomedical research community. Early in their growth, the genomic and proteomic fields implemented mechanisms for assigning unique gene and protein identifiers that were essential for organizing data presentation and for enhancing bioinformatic approaches to extracting knowledge. Similar unique identifiers are currently absent from glycomic data. In order to facilitate continued growth and expanded accessibility of glycomic data, the authors strongly encourage the glycomics community to coordinate the submission of their glycan structures to the GlyTouCan Repository and to make use of GlyTouCan identifiers in their communications and publications. The authors also deeply encourage journals to recommend a submission workflow in which submitted publications utilize GlyTouCan identifiers as a standard reference for explicitly describing glycan structures cited in manuscripts.

Solution conformation of carbohydrates: a view by using NMR assisted by modeling

Structural elucidation of complex carbohydrates in solution is not a trivial task. From the NMR view point, the limited chemical shift dispersion of sugar NMR spectra demands the combination of a variety of NMR techniques as well as the employment of molecular modeling methods. Herein, a general protocol for assignment of resonances and determination of inter-proton distances within the saccharides by homonuclear and heteronuclear experiments (i.e., (1)H and (13)C) is described. In addition, several computational tools and procedures for getting a final ensemble of geometries that represent the structure in solution are presented.

GlycomeDB

Over the last two decades, several carbohydrate structure databases have been developed and made publicly available by different research groups around the world. This led to the fragmentation of information about carbohydrate structures into different resources that have no or only weak interaction with each other. GlycomeDB was developed to integrate the carbohydrate structures from different resources by generating a single-indexed catalog of these structures that associates each structure with its reference in the original resources. GlycomeDB facilitates searching for carbohydrate structures in all the integrated resources by eliminating the need to use several different search interfaces and manually integrating the results. References provided by GlycomeDB make it possible to retrieve information that is beyond the scope of GlycomeDB but present in the integrated databases. This chapter illustrates the use of the GlycomeDB search interfaces and web services by way of three example cases.

Carbohydrate structure database merged from bacterial, archaeal, plant and fungal parts

The Carbohydrate Structure Databases (CSDBs, http://csdb.glycoscience.ru) store structural, bibliographic, taxonomic, NMR spectroscopic, and other data on natural carbohydrates and their derivatives published in the scientific literature. The CSDB project was launched in 2005 for bacterial saccharides (as BCSDB). Currently, it includes two parts, the Bacterial CSDB and the Plant&Fungal CSDB. In March 2015, these databases were merged to the single CSDB. The combined CSDB includes information on bacterial and archaeal glycans and derivatives (the coverage is close to complete), as well as on plant and fungal glycans and glycoconjugates (almost all structures published up to 1998). CSDB is regularly updated via manual expert annotation of original publications. Both newly annotated data and data imported from other databases are manually curated. The CSDB data are exportable in a number of modern formats, such as GlycoRDF. CSDB provides additional services for simulation of (1)H, (13)C and 2D NMR spectra of saccharides, NMR-based structure prediction, glycan-based taxon clustering and other.

Methods to identify the unexplored diversity of microbial exopolysaccharides

Microbial exopolysaccharides (EPS) are a structurally very diverse class of molecules. A number of them have found their application in rather diverging fields that extend from medicine, food, and cosmetics on the one side to construction, drilling, and chemical industry on the other side. The analysis of microbial strains for their competence in polysaccharide production has therefore been a major issue in the past, especially in the search for new polysaccharide variants among natural strain isolates. Concerning the fact that nearly all microbes carry the genetic equipment for the production of polysaccharides under specific conditions, the naturally provided EPS portfolio seems to be still massively underexplored. Therefore, there is a need for high throughput screening techniques capable of identifying novel variants of bacterial EPS with properties superior to the already described ones, or even totally new ones. A great variety of different techniques has been used in screening approaches for identifying microorganisms that are producing EPS in substantial amounts. Mucoid growth is often the method of choice for visual identification of EPS producing strains. Depending on the thickening characteristics of the polysaccharide, observation of viscosity in culture broth can also be an option to evaluate EPS production. Precipitation with different alcohols represents a common detection, isolation, and purification method for many EPS. A more quantitative approach is found in the total carbohydrate content analysis, normally determined, e.g., by phenol-sulfuric-acid-method. In addition, recently a new and reliable method for the detailed analysis of the monomeric composition and the presence of rare sugars and sugar substitutions has become available, which could give a first hint of the polymer structure of unknown EPS. This minireview will compare available methods and novel techniques and discuss their benefits and disadvantages.

GlycoRDF: an ontology to standardize glycomics data in RDF

MOTIVATION

Over the last decades several glycomics-based bioinformatics resources and databases have been created and released to the public. Unfortunately, there is no common standard in the representation of the stored information or a common machine-readable interface allowing bioinformatics groups to easily extract and cross-reference the stored information.

RESULTS

An international group of bioinformatics experts in the field of glycomics have worked together to create a standard Resource Description Framework (RDF) representation for glycomics data, focused on glycan sequences and related biological source, publications and experimental data. This RDF standard is defined by the GlycoRDF ontology and will be used by database providers to generate common machine-readable exports of the data stored in their databases.

AVAILABILITY AND IMPLEMENTATION

The ontology, supporting documentation and source code used by database providers to generate standardized RDF are available online (http://www.glycoinfo.org/GlycoRDF/).

Bacterial, plant, and fungal carbohydrate structure databases: daily usage

Natural carbohydrates play important roles in living systems and therefore are used as diagnostic and therapeutic targets. The main goal of glycomics is systematization of carbohydrates and elucidation of their role in human health and disease. The amount of information on natural carbohydrates accumulates rapidly, but scientists still lack databases and computer-assisted tools needed for orientation in the glycomic information space. Therefore, freely available, regularly updated, and cross-linked databases are demanded. Bacterial Carbohydrate Structure Database (Bacterial CSDB) was developed for provision of structural, bibliographic, taxonomic, NMR spectroscopic, and other related information on bacterial and archaeal carbohydrate structures. Its main features are (1) coverage above 90%, (2) high data consistence (above 90% of error-free records), and (3) presence of manually verified bibliographic, NMR spectroscopic, and taxonomic annotations. Recently, CSDB has been expanded to cover carbohydrates of plant and fungal origin. The achievement of full coverage in the plant and fungal domains is expected in the future. CSDB is freely available on the Internet as a web service at http://csdb.glycoscience.ru. This chapter aims at showing how to use CSDB in your daily scientific practice.

PTM-SD: a database of structurally resolved and annotated posttranslational modifications in proteins

Posttranslational modifications (PTMs) define covalent and chemical modifications of protein residues. They play important roles in modulating various biological functions. Current PTM databases contain important sequence annotations but do not provide informative 3D structural resource about these modifications. Posttranslational modification structural database (PTM-SD) provides access to structurally solved modified residues, which are experimentally annotated as PTMs. It combines different PTM information and annotation gathered from other databases, e.g. Protein DataBank for the protein structures and dbPTM and PTMCuration for fine sequence annotation. PTM-SD gives an accurate detection of PTMs in structural data. PTM-SD can be browsed by PDB id, UniProt accession number, organism and classic PTM annotation. Advanced queries can also be performed, i.e. detailed PTM annotations, amino acid type, secondary structure, SCOP class classification, PDB chain length and number of PTMs by chain. Statistics and analyses can be computed on a selected dataset of PTMs. Each PTM entry is detailed in a dedicated page with information on the protein sequence, local conformation with secondary structure and Protein Blocks. PTM-SD gives valuable information on observed PTMs in protein 3D structure, which is of great interest for studying sequence-structure- function relationships at the light of PTMs, and could provide insights for comparative modeling and PTM predictions protocols. Database URL: PTM-SD can be accessed at http://www.dsimb.inserm.fr/dsimb_tools/PTM-SD/.

Introducing glycomics data into the Semantic Web

BACKGROUND

Glycoscience is a research field focusing on complex carbohydrates (otherwise known as glycans)a, which can, for example, serve as "switches" that toggle between different functions of a glycoprotein or glycolipid. Due to the advancement of glycomics technologies that are used to characterize glycan structures, many glycomics databases are now publicly available and provide useful information for glycoscience research. However, these databases have almost no link to other life science databases.

RESULTS

In order to implement support for the Semantic Web most efficiently for glycomics research, the developers of major glycomics databases agreed on a minimal standard for representing glycan structure and annotation information using RDF (Resource Description Framework). Moreover, all of the participants implemented this standard prototype and generated preliminary RDF versions of their data. To test the utility of the converted data, all of the data sets were uploaded into a Virtuoso triple store, and several SPARQL queries were tested as "proofs-of-concept" to illustrate the utility of the Semantic Web in querying across databases which were originally difficult to implement.

CONCLUSIONS

We were able to successfully retrieve information by linking UniCarbKB, GlycomeDB and JCGGDB in a single SPARQL query to obtain our target information. We also tested queries linking UniProt with GlycoEpitope as well as lectin data with GlycomeDB through PDB. As a result, we have been able to link proteomics data with glycomics data through the implementation of Semantic Web technologies, allowing for more flexible queries across these domains.

Using glycome databases for drug discovery

BACKGROUND

The glycomics field has made great advancements in the last decade due to technologies for their synthesis and analysis including carbohydrate microarrays. Accordingly, databases for glycomics research have also emerged and been made publicly available by many major institutions worldwide.

OBJECTIVE

This review introduces these and other useful databases on which new methods for drug discovery can be developed.

METHODS

The scope of this review covers current documented and accessible databases and resources pertaining to glycomics. These were selected with the expectation that they may be useful for drug discovery research.

RESULTS/CONCLUSION

There is a plethora of glycomics databases that have much potential for drug discovery. This may seem daunting at first but this review helps to put some of these resources into perspective. Additionally, some thoughts on how to integrate these resources to allow more efficient research are presented.

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.

The use of glycoinformatics in glycochemistry

Glycoinformatics is a small but growing branch of bioinformatics and chemoinformatics. Various resources are now available that can be of use to glycobiologists, but also to chemists who work on the synthesis or analysis of carbohydrates. This article gives an overview of existing glyco-specific databases and tools, with a focus on their application to glycochemistry: Databases can provide information on candidate glycan structures for synthesis, or on glyco-enzymes that can be used to synthesize carbohydrates. Statistical analyses of glycan databases help to plan glycan synthesis experiments. 3D-Structural data of protein-carbohydrate complexes are used in targeted drug design, and tools to support glycan structure analysis aid with quality control. Specific problems of glycoinformatics compared to bioinformatics for genomics or proteomics, especially concerning integration and long-term maintenance of the existing glycan databases, are also discussed.

Bioinformatics and molecular modeling in glycobiology

The field of glycobiology is concerned with the study of the structure, properties, and biological functions of the family of biomolecules called carbohydrates. Bioinformatics for glycobiology is a particularly challenging field, because carbohydrates exhibit a high structural diversity and their chains are often branched. Significant improvements in experimental analytical methods over recent years have led to a tremendous increase in the amount of carbohydrate structure data generated. Consequently, the availability of databases and tools to store, retrieve and analyze these data in an efficient way is of fundamental importance to progress in glycobiology. In this review, the various graphical representations and sequence formats of carbohydrates are introduced, and an overview of newly developed databases, the latest developments in sequence alignment and data mining, and tools to support experimental glycan analysis are presented. Finally, the field of structural glycoinformatics and molecular modeling of carbohydrates, glycoproteins, and protein-carbohydrate interaction are reviewed.

Functional network of glycan-related molecules: glyco-net in glycoconjugate data bank

Background

Glycans are involved in a wide range of biological process, and they play an essential role in functions such as cell differentiation, cell adhesion, pathogen-host recognition, toxin-receptor interactions, signal transduction, cancer metastasis, and immune responses. Elucidating pathways related to post-translational modifications (PTMs) such as glycosylation are of growing importance in post-genome science and technology. Graphical networks describing the relationships among glycan-related molecules, including genes, proteins, lipids and various biological events are considered extremely valuable and convenient tools for the systematic investigation of PTMs. However, there is no database which dynamically draws functional networks related to glycans.

Description

We have created a database called Glyco-Net http://www.glycoconjugate.jp/functions/, with many binary relationships among glycan-related molecules. Using search results, we can dynamically draw figures of the functional relationships among these components with nodes and arrows. A certain molecule or event corresponds to a node in the network figures, and the relationship between the molecule and the event are indicated by arrows. Since all components are treated equally, an arrow is also a node.

Conclusions

In this paper, we describe our new database, Glyco-Net, which is the first database to dynamically show networks of the functional profiles of glycan related molecules. The graphical networks will assist in the understanding of the role of the PTMs. In addition, since various kinds of bio-objects such as genes, proteins, and inhibitors are equally treated in Glyco-Net, we can obtain a large amount of information on the PTMs.

Cell surface of Lactococcus lactis is covered by a protective polysaccharide pellicle

In Gram-positive bacteria, the functional role of surface polysaccharides (PS) that are not of capsular nature remains poorly understood. Here, we report the presence of a novel cell wall PS pellicle on the surface of Lactococcus lactis. Spontaneous PS-negative mutants were selected using semi-liquid growth conditions, and all mutations were mapped in a single chromosomal locus coding for PS biosynthesis. PS molecules were shown to be composed of hexasaccharide phosphate repeating units that are distinct from other bacterial PS. Using complementary atomic force and transmission electron microscopy techniques, we showed that the PS layer forms an outer pellicle surrounding the cell. Notably, we found that this cell wall layer confers a protective barrier against host phagocytosis by murine macrophages. Altogether, our results suggest that the PS pellicle could represent a new cell envelope structural component of Gram-positive bacteria.

Glycome-DB.org: a portal for querying across the digital world of carbohydrate sequences

Despite ongoing harmonization efforts, the major carbohydrate sequence databases following the first initiative in this field, CarbBank, are still isolated islands, with mechanisms for automatic structure exchange and comparison largely missing. This unfavorable situation has been overcome with a systematic data integration effort, resulting in the GlycomeDB, a meta-database for public carbohydrate sequences. It contains at present 35,056 unique structures in GlycoCT encoding, referencing more than 100,000 external records from 1845 different taxonomic sources. We have created a user-friendly, web-based graphical interface which allows taxonomic and structural data to be entered and searched for. The structural search possibilities include substructure search, similarity search, and maximum common substructure. A novel search refinement mechanism allows the assembly of complex queries. With GlycomeDB (www.glycome-db.org), it is now possible to use a single portal to access all digitally encoded, public structural data in glycomics and to perform complex queries with the help of a web-based user interface.

GlycomeDB - integration of open-access carbohydrate structure databases

Background

Although carbohydrates are the third major class of biological macromolecules, after proteins and DNA, there is neither a comprehensive database for carbohydrate structures nor an established universal structure encoding scheme for computational purposes. Funding for further development of the Complex Carbohydrate Structure Database (CCSD or CarbBank) ceased in 1997, and since then several initiatives have developed independent databases with partially overlapping foci. For each database, different encoding schemes for residues and sequence topology were designed. Therefore, it is virtually impossible to obtain an overview of all deposited structures or to compare the contents of the various databases.

Results

We have implemented procedures which download the structures contained in the seven major databases, e.g. GLYCOSCIENCES.de, the Consortium for Functional Glycomics (CFG), the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the Bacterial Carbohydrate Structure Database (BCSDB). We have created a new database called GlycomeDB, containing all structures, their taxonomic annotations and references (IDs) for the original databases. More than 100000 datasets were imported, resulting in more than 33000 unique sequences now encoded in GlycomeDB using the universal format GlycoCT. Inconsistencies were found in all public databases, which were discussed and corrected in multiple feedback rounds with the responsible curators.

Conclusion

GlycomeDB is a new, publicly available database for carbohydrate sequences with a unified, all-encompassing structure encoding format and NCBI taxonomic referencing. The database is updated weekly and can be downloaded free of charge. The JAVA application GlycoUpdateDB is also available for establishing and updating a local installation of GlycomeDB. With the advent of GlycomeDB, the distributed islands of knowledge in glycomics are now bridged to form a single resource.

An alpha-numeric code for representing N-linked glycan structures in secreted glycoproteins

Advances in high-throughput techniques have led to the creation of increasing amounts of glycome data. The storage and analysis of this data would benefit greatly from a compact notation for describing glycan structures that can be easily stored and interpreted by computers. Towards this end, we propose a fixed-length alpha-numeric code for representing N-linked glycan structures commonly found in secreted glycoproteins from mammalian cell cultures. This code, GlycoDigit, employs a pre-assigned alpha-numeric index to represent the monosaccharides attached in different branches to the core glycan structure. The present branch-centric representation allows us to visualize the structure while the numerical nature of the code makes it machine readable. In addition, a difference operator can be defined to quantitatively differentiate between glycan structures for further analysis. The usefulness and applicability of GlycoDigit were demonstrated by constructing and visualizing an N-linked glycosylation network.

GlycoBase and autoGU: tools for HPLC-based glycan analysis

SUMMARY

The development of robust high-performance liquid chromatography (HPLC) technologies continues to improve the detailed analysis and sequencing of glycan structures released from glycoproteins. Here, we present a database (GlycoBase) and analytical tool (autoGU) to assist the interpretation and assignment of HPLC-glycan profiles. GlycoBase is a relational database which contains the HPLC elution positions for over 350 2-AB labelled N-glycan structures together with predicted products of exoglycosidase digestions. AutoGU assigns provisional structures to each integrated HPLC peak and, when used in combination with exoglycosidase digestions, progressively assigns each structure automatically based on the footprint data. These tools are potentially very promising and facilitate basic research as well as the quantitative high-throughput analysis of low concentrations of glycans released from glycoproteins.

AVAILABILITY

http://glycobase.ucd.ie