Using databases and web resources for glycomics research

Carbohydrate Structure Database: current state and recent developments

Carbohydrate Structure Database (CSDB) is a curated glycan data collection and a glycoinformatic platform. In this report, its database, analytical, and other components that have appeared for the recent years are reviewed. The major improvements were achieving close-to-full coverage on glycans from microorganisms, launching modules for glycosyltransferases and saccharide conformations, online glycan builder and 3D modeler, NMR simulator, NMR-based structure predictor, and other tools.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2019-2020

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2020. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. The review is basically divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of arrays. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other areas such as medicine, industrial processes and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. The reported work shows increasing use of incorporation of new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented nearly 40 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show little sign of diminishing.

Source files of the Carbohydrate Structure Database: the way to sophisticated analysis of natural glycans

The Carbohydrate Structure Database (CSDB, http://csdb.glycoscience.ru/ ) is a free curated repository storing various data on glycans of bacterial, fungal and plant origins. Currently, it maintains a close-to-full coverage on bacterial and fungal carbohydrates up to the year 2020. The CSDB web-interface provides free access to the database content and dedicated tools. Still, the number of these tools and the types of the corresponding analyses is limited, whereas the database itself contains data that can be used in a broader scope of analytical studies. In this paper, we present CSDB source data files and a self-contained SQL dump, and exemplify their possible application in glycan-related studies. By using CSDB in an SQL format, the user can gain access to the chain length distribution or charge distribution (as an example) in a given set of glycans defined according to specific structural, taxonomic, or other parameters, whereas the source text dump files can be imported to any dedicated database with a specific internal architecture differing from that of CSDB.

Three-Dimensional Structures of Carbohydrates and Where to Find Them

Analysis and systematization of accumulated data on carbohydrate structural diversity is a subject of great interest for structural glycobiology. Despite being a challenging task, development of computational methods for efficient treatment and management of spatial (3D) structural features of carbohydrates breaks new ground in modern glycoscience. This review is dedicated to approaches of chemo- and glyco-informatics towards 3D structural data generation, deposition and processing in regard to carbohydrates and their derivatives. Databases, molecular modeling and experimental data validation services, and structure visualization facilities developed for last five years are reviewed.

Glycosciences.DB: an annotated data collection linking glycomics and proteomics data (2018 update)

Glycosciences.DB, the glycan structure database of the Glycosciences.de portal, collects various kinds of data on glycan structures, including carbohydrate moieties from worldwide Protein Data Bank (wwPDB) structures. This way it forms a bridge between glycomics and proteomics resources. A major update of this database combines a redesigned web interface with a series of new functions. These include separate entry pages not only for glycan structures but also for literature references and wwPDB entries, improved substructure search options, a newly available keyword search covering all types of entries in one query, and new types of information that is added to glycan structures. These new features are described in detail in this article, and options how users can provide information to the database are discussed as well. Glycosciences.DB is available at http://www.glycosciences.de/database/ and can be freely accessed.

LM-GlycomeAtlas Ver. 1.0: A Novel Visualization Tool for Lectin Microarray-Based Glycomic Profiles of Mouse Tissue Sections

For the effective discovery of the biological roles and disease-specific alterations concerning protein glycosylation in tissue samples, it is important to know beforehand the quantitative and qualitative variations of glycan structures expressed in various types of cells, sites, and tissues. To this end, we used laser microdissection-assisted lectin microarray (LMA) to establish a simple and reproducible method for high-throughput and in-depth glycomic profiling of formalin-fixed paraffin-embedded tissue sections. Using this “tissue glycome mapping” approach, we present 234 glycomic profiling data obtained from nine tissue sections (pancreas, heart, lung, thymus, gallbladder, stomach, small intestine, colon, and skin) of two 8-week-old male C57BL/6J mice. We provided this LMA-based dataset in the similar interface as that of GlycomeAtlas, a previously developed tool for mass spectrometry-based tissue glycomic profiling, allowing easy comparison of the two types of data. This online tool, called “LM-GlycomeAtlas”, allows users to visualize the LMA-based tissue glycomic profiling data associated with the sample information as an atlas. Since the present dataset allows the comparison of glycomic profiles, it will facilitate the evaluation of site- and tissue-specific glycosylation patterns. Taking advantage of its extensibility, this tool will continue to be updated with the expansion of deposited data.

Quantitative glycomics using liquid phase separations coupled to mass spectrometry

Post-translational modification of proteins by the attachment of glycans is governed by a variety of highly specific enzymes and is associated with fundamental impacts on the parent protein's physical, chemical and biological properties. The inherent connection between cellular physiology and specific glycosylation patterns has been shown to offer potential for diagnostic and prognostic monitoring of altered glycosylation in the disease state. Conversely, glycoprotein based biopharmaceuticals have emerged as dominant therapeutic strategies in the treatment of intricate diseases. Glycosylation present on these biopharmaceuticals represents a major critical quality attribute with impacts on both pharmacokinetics and pharmacodynamics. The structural variety of glycans, based upon their non-template driven assembly, poses a significant analytical challenge for both qualitative and quantitative analysis. Labile monosaccharide constituents, isomeric species and often low sample availability from biological sources necessitates meticulous sample handling, ultra-high-resolution analytical separation and sensitive detection techniques, respectively. In this article a critical review of analytical quantitation approaches using liquid phase separations coupled to mass spectrometry for released glycans of biopharmaceutical and biomedical significance is presented. Considerations associated with sample derivatisation strategies, ionisation, relative quantitation through isotopic as well as isobaric labelling, metabolic/enzymatic incorporation and targeted analysis are all thoroughly discussed.

The Interaction of the Gut Microbiota with the Mucus Barrier in Health and Disease in Human

Glycoproteins are major players in the mucus protective barrier in the gastrointestinal and other mucosal surfaces. In particular the mucus glycoproteins, or mucins, are responsible for the protective gel barrier. They are characterized by their high carbohydrate content, present in their variable number, tandem repeat domains. Throughout evolution the mucins have been maintained as integral components of the mucosal barrier, emphasizing their essential biological status. The glycosylation of the mucins is achieved through a series of biosynthetic pathways processes, which generate the wide range of glycans found in these molecules. Thus mucins are decorated with molecules having information in the form of a glycocode. The enteric microbiota interacts with the mucosal mucus barrier in a variety of ways in order to fulfill its many normal processes. How bacteria read the glycocode and link to normal and pathological processes is outlined in the review.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2013-2014

This review is the eighth update of the original article published in 1999 on the application of Matrix-assisted laser desorption/ionization mass spectrometry (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2014. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, and arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly- saccharides, glycoproteins, glycolipids, glycosides, and biopharmaceuticals. Much of this material is presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions, and applications to chemical synthesis. © 2018 Wiley Periodicals, Inc. Mass Spec Rev 37:353-491, 2018.

A Golden Age for Working with Public Proteomics Data

Data sharing in mass spectrometry (MS)-based proteomics is becoming a common scientific practice, as is now common in the case of other, more mature ‘omics’ disciplines like genomics and transcriptomics. We want to highlight that this situation, unprecedented in the field, opens a plethora of opportunities for data scientists. First, we explain in some detail some of the work already achieved, such as systematic reanalysis efforts. We also explain existing applications of public proteomics data, such as proteogenomics and the creation of spectral libraries and spectral archives. Finally, we discuss the main existing challenges and mention the first attempts to combine public proteomics data with other types of omics data sets.

The field of proteomics has matured and diversified substantially over the past 10 years.

Proteomics data are increasingly shared through centralized, public repositories.

Standardization efforts have ensured that a large proportion of these public data can be read and processed by any interested researcher.

Because any proteomics data set is only partially understood, there is great opportunity for (orthogonal) reuse of public data.

While public proteomics data has so far remained outside ethics and privacy discussions, recent work indicates that there is an inherent risk.

Biological roles of glycans

Simple and complex carbohydrates (glycans) have long been known to play major metabolic, structural and physical roles in biological systems. Targeted microbial binding to host glycans has also been studied for decades. But such biological roles can only explain some of the remarkable complexity and organismal diversity of glycans in nature. Reviewing the subject about two decades ago, one could find very few clear-cut instances of glycan-recognition-specific biological roles of glycans that were of intrinsic value to the organism expressing them. In striking contrast there is now a profusion of examples, such that this updated review cannot be comprehensive. Instead, a historical overview is presented, broad principles outlined and a few examples cited, representing diverse types of roles, mediated by various glycan classes, in different evolutionary lineages. What remains unchanged is the fact that while all theories regarding biological roles of glycans are supported by compelling evidence, exceptions to each can be found. In retrospect, this is not surprising. Complex and diverse glycans appear to be ubiquitous to all cells in nature, and essential to all life forms. Thus, >3 billion years of evolution consistently generated organisms that use these molecules for many key biological roles, even while sometimes coopting them for minor functions. In this respect, glycans are no different from other major macromolecular building blocks of life (nucleic acids, proteins and lipids), simply more rapidly evolving and complex. It is time for the diverse functional roles of glycans to be fully incorporated into the mainstream of biological sciences.

Quantitative profiling of glycans and glycopeptides: an informatics' perspective

Experimental techniques to identify and quantify glycan structures in a given sample are continuously improving. However, as they advance data analysis and annotation seems to become more complex. To address this issue, much progress has been made in developing software for interpretation of quantitative glycan profiles. Here, we focus on these informatics tools for high/ultra performance liquid chromatography (H/UPLC), mass spectrometry (MS), tandem mass spectrometry (MSⁿ) and combinations thereof. Software for biomarker discovery, pathway, genomic and disease analysis and a final note on some future prospects for glycoinformatics are also mentioned.

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.

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

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

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.