Bridging glycoinformatics and cheminformatics: integration efforts between GlyCosmos and PubChem

The GlyCosmos Glycoscience Portal (https://glycosmos.org) and PubChem (https://pubchem.ncbi.nlm.nih.gov/) are major portals for glycoscience and chemistry, respectively. GlyCosmos is a portal for glycan-related repositories, including GlyTouCan, GlycoPOST, and UniCarb-DR, as well as for glycan-related data resources that have been integrated from a variety of 'omics databases. Glycogenes, glycoproteins, lectins, pathways, and disease information related to glycans are accessible from GlyCosmos. PubChem, on the other hand, is a chemistry-based portal at the National Center for Biotechnology Information. PubChem provides information not only on chemicals, but also genes, proteins, pathways, as well as patents, bioassays, and more, from hundreds of data resources from around the world. In this work, these 2 portals have made substantial efforts to integrate their complementary data to allow users to cross between these 2 domains. In addition to glycan structures, key information, such as glycan-related genes, relevant diseases, glycoproteins, and pathways, was integrated and cross-linked with one another. The interfaces were designed to enable users to easily find, access, download, and reuse data of interest across these resources. Use cases are described illustrating and highlighting the type of content that can be investigated. In total, these integrations provide life science researchers improved awareness and enhanced access to glycan-related information.

Worldwide Glycoscience Informatics Infrastructure: The GlySpace Alliance

The GlySpace Alliance was formed in 2018 among the principal investigators of three major glycoscience portals: Glyco@Expasy, GlyCosmos, and GlyGen, representing Europe, Asia, and the United States, respectively. While each of these portals has its unique user interface, the aim is to provide the same basic data set of glycan-related omics data. These portals will be introduced with the aim to enable users to find their target information in the most efficient manner, in particular, in terms of the chemical structures of glycans and their functions.

Representation of polysaccharide molecules by SNFG and 3D-SNFG methods--Take Potentilla anserina L polysaccharide molecule as an example

With the continuous deepening of international research in the field of biology, more and more studies have found that polysaccharides have multiple biological functions, so that polysaccharides have gradually become the research objects of more and more scientists in the world, and a large number of relevant researchers have carried out Glycobiology research, most of the current research is on the separation, extraction, structural characterization and activity experiments of polysaccharides. However, at this stage, research on the structure-activity relationship of various polysaccharides extracted from plants is relatively rare, and the representation method of polysaccharide structures is not perfect, not unified, complicated in drawing, and not beautiful and convenient to read. The SNFG (Symbol Nomenclature For Glycans) method, which is the symbolic nomenclature of polysaccharides and the 3D-SNFG method, can solve the above problems well, and can use unified rules to describe and describe the molecular structure of polysaccharides, and the painting process is more convenient and more convenient. It is beautiful and makes it easier for readers to read. In this paper, the fern hemp polysaccharide molecule is taken as an example. After drawing it with chemoffice, SNFG and 3D-SNFG are used to describe it, and then compared. It is clear at a glance that the use of SNFG and 3D-SNFG methods has been widely recognized and accepted internationally, which can provide great convenience for sugar-related research and information exchange.

Informatics Ecosystems to Advance the Biology of Glycans

Glycomics researchers have identified the need for integrated database systems for collecting glycomics information in a consistent format. The goal is to create a resource for knowledge discovery and dissemination to wider research communities. This has the potential and has exhibited initial success, to extend the research community to include biologists, clinicians, chemists, and computer scientists. This chapter discusses the technology and approach needed to create integrated data resources and informatics ecosystems to empower the broader community to leverage extant glycomics data. The focus is on glycosaminoglycan (GAGs) and proteoglycan research, but the approach can be generalized. The methods described span the development of glycomics standards from CarbBank to Glyco Connection Tables. Integrated data sets provide a foundation for novel methods of analysis such as machine learning and deep learning for knowledge discovery. The implications of predictive analysis are examined in relation to disease biomarker to expand the target audience of GAG and proteoglycan research.

An Interactive View of Glycosylation

The present chapter focuses on the interactive and explorative aspects of bioinformatics resources that have been recently released in glycobiology. The comparative analysis of data in a field where knowledge is scattered, incomplete, and disconnected from main biology requires efficient visualization, integration, and interactive tools that are currently only partially implemented. This overview highlights converging efforts toward building a consistent picture of protein glycosylation.

Glycan characteristics of human heart constituent cells maintaining organ function: relatively stable glycan profiles in cellular senescence

Cell surface glycoproteins, which are good indicators of cellular types and biological function; are suited for cell evaluation. Tissue remodeling using various cells is a key feature of regenerative therapy. For artificial heart remodeling, a mixture of heart constituent cells has been investigated for organ assembly, however, the cellular characteristics remain unclear. In this study, the glycan profiles of human cardiomyocytes (HCMs), human cardiac fibroblasts (HCFs), and human vascular endothelial cells (ECs) were analyzed using evanescent-field lectin microarray analysis, a tool of glycan profiling, to clarify the required cellular characteristics. We found that ECs had more “α1-2fucose” and “core α1-6fucose” residues than other cells, and that “α2-6sialic acid” residue was more abundant in ECs and HCMs than in HCFs. HCFs showed higher abundance of “β-galactose” and “β-N-acetylgalactosamine” residues on N-glycan and O-glycan, respectively, compared to other cells. Interestingly, cardiac glycan profiles were insignificantly changed with cellular senescence. The residues identified in this study may participate in organ maintenance by contributing to the preservation of glycan components. Therefore, future studies should investigate the roles of glycans in optimal tissue remodeling since identifying cellular characteristics is important for the development of regenerative therapies.

LM-GlycomeAtlas Ver. 2.0: An Integrated Visualization for Lectin Microarray-based Mouse Tissue Glycome Mapping Data with Lectin Histochemistry

Laser microdissection-assisted lectin microarray has been used to obtain quantitative and qualitative information on glycans on proteins expressed in microscopic regions of formalin-fixed paraffin-embedded tissue sections. For the effective visualization of this "tissue glycome mapping" data, a novel online tool, LM-GlycomeAtlas (https://glycosmos.org/lm_glycomeatlas/index), was launched in the freely available glycoscience portal, the GlyCosmos Portal (https://glycosmos.org). In LM-GlycomeAtlas Version 1.0, nine tissues from normal mice were used to provide one data set of glycomic profiles. Here we introduce an updated version of LM-GlycomeAtlas, which includes more spatial information. We designed it to deposit multiple data sets of glycomic profiles with high-resolution histological images, which included staining images with multiple lectins on the array. The additionally implemented interfaces allow users to display multiple histological images of interest (e.g., diseased and normal mice), thereby facilitating the evaluation of tissue glycomic profiling and glyco-pathological analysis. Using these updated interfaces, 451 glycomic profiling data and 42 histological images obtained from 14 tissues of normal and diseased mice were successfully visualized. By easy integration with other tools for glycoproteomic data and protein glycosylation machinery, LM-GlycomeAtlas will be one of the most valuable open resources that contribute to both glycoscience and proteomics communities.

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.

Aberration of Serum and Tissue N-Glycans in Mouse β1,4-GalT1 Y286L Mutant Variants

β1,4-GalT1 is a type II membrane glycosyltransferase. It catalyzes the production of lactose in the lactating mammary gland and is supposedly also involved in the galactosylation of terminal GlcNAc of complex-type N-glycans. In-vitro studies of the bovine β4Gal-T1 homolog showed that replacing a single residue of tyrosine with leucine at position 289 alters the donor substrate specificity from UDP-Gal to UDP-N-acetyl-galactosamine (UDP-GalNAc). The effect of this peculiar change in β1,4GalT1 specificity was investigated in-vivo, by generating biallelic Tyr286Leu β1,4GalT1 mice using CRISPR/Cas9 and crossbreeding. Mice bearing this mutation showed no appreciable defects when compared to wild-type mice, with the exception of biallelic female B4GALT1 mutant mice, which were unable to produce milk. The detailed comparison of wild-type and mutant mice derived from liver, kidney, spleen, and intestinal tissues showed only small differences in their N-glycan pattern. Comparable N-glycosylation was also observed in HEK 293 wild-type and knock-out B4GALT1 cells. Remarkably and in contrast to the other analyzed tissue samples, sialylation and galactosylation of serum N-glycans of biallelic Tyr286Leu GalT1 mice almost disappeared completely. These results suggest that β1,4GalT1 plays a special role in the synthesis of serum N-glycans. The herein described Tyr286Leu β1,4GalT1 mutant mouse model may, therefore, prove useful in the investigation of the mechanism which regulates tissue-dependent galactosylation.

GlycanFormatConverter: a conversion tool for translating the complexities of glycans

Motivation

Glycans are biomolecules that take an important role in the biological processes of living organisms. They form diverse, complicated structures such as branched and cyclic forms. Web3 Unique Representation of Carbohydrate Structures (WURCS) was proposed as a new linear notation for uniquely representing glycans during the GlyTouCan project. WURCS defines rules for complex glycan structures that other text formats did not support, and so it is possible to represent a wide variety glycans. However, WURCS uses a complicated nomenclature, so it is not human-readable. Therefore, we aimed to support the interpretation of WURCS by converting WURCS to the most basic and widely used format IUPAC.

Results

In this study, we developed GlycanFormatConverter and succeeded in converting WURCS to the three kinds of IUPAC formats (IUPAC-Extended, IUPAC-Condensed and IUPAC-Short). Furthermore, we have implemented functionality to import IUPAC-Extended, KEGG Chemical Function (KCF) and LinearCode formats and to export WURCS. We have thoroughly tested our GlycanFormatConverter and were able to show that it was possible to convert all the glycans registered in the GlyTouCan repository, with exceptions owing only to the limitations of the original format. The source code for this conversion tool has been released as an open source tool.

Availability and implementation

https://github.com/glycoinfo/GlycanFormatConverter.git

Supplementary information

Supplementary data are available at Bioinformatics online.

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.

A Bioinformatics View of Glycan⁻Virus Interactions

Evidence of the mediation of glycan molecules in the interaction between viruses and their hosts is accumulating and is now partially reflected in several online databases. Bioinformatics provides convenient and efficient means of searching, visualizing, comparing, and sometimes predicting, interactions in numerous and diverse molecular biology applications related to the -omics fields. As viromics is gaining momentum, bioinformatics support is increasingly needed. We propose a survey of the current resources for searching, visualizing, comparing, and possibly predicting host–virus interactions that integrate the presence and role of glycans. To the best of our knowledge, we have mapped the specialized and general-purpose databases with the appropriate focus. With an illustration of their potential usage, we also discuss the strong and weak points of the current bioinformatics landscape in the context of understanding viral infection and the immune response to it.

Understanding the glycome: an interactive view of glycosylation from glycocompositions to glycoepitopes

Nowadays, due to the advance of experimental techniques in glycomics, large collections of glycan profiles are regularly published. The rapid growth of available glycan data accentuates the lack of innovative tools for visualizing and exploring large amount of information. Scientists resort to using general-purpose spreadsheet applications to create ad hoc data visualization. Thus, results end up being encoded in publication images and text, while valuable curated data is stored in files as supplementary information. To tackle this problem, we have built an interactive pipeline composed with three tools: Glynsight, EpitopeXtractor and Glydin'. Glycan profile data can be imported in Glynsight, which generates a custom interactive glycan profile. Several profiles can be compared and glycan composition is integrated with structural data stored in databases. Glycan structures of interest can then be sent to EpitopeXtractor to perform a glycoepitope extraction. EpitopeXtractor results can be superimposed on the Glydin' glycoepitope network. The network visualization allows fast detection of clusters of glycoepitopes and discovery of potential new targets. Each of these tools is standalone or can be used in conjunction with the others, depending on the data and the specific interest of the user. All the tools composing this pipeline are part of the Glycomics@ExPASy initiative and are available at https://www.expasy.org/glycomics.

Systems glycomics of adult zebrafish identifies organ-specific sialylation and glycosylation patterns

The emergence of zebrafish Danio rerio as a versatile model organism provides the unique opportunity to monitor the functions of glycosylation throughout vertebrate embryogenesis, providing insights into human diseases caused by glycosylation defects. Using a combination of chemical modifications, enzymatic digestion and mass spectrometry analyses, we establish here the precise glycomic profiles of eight individual zebrafish organs and demonstrate that the protein glycosylation and glycosphingolipid expression patterns exhibits exquisite specificity. Concomitant expression screening of a wide array of enzymes involved in the synthesis and transfer of sialic acids shows that the presence of organ-specific sialylation motifs correlates with the localized activity of the corresponding glycan biosynthesis pathways. These findings provide a basis for the rational design of zebrafish lines expressing desired glycosylation profiles.

MCAW-DB: A glycan profile database capturing the ambiguity of glycan recognition patterns

Glycan-binding protein (GBP) interaction experiments, such as glycan microarrays, are often used to understand glycan recognition patterns. However, oftentimes the interpretation of glycan array experimental data makes it difficult to identify discrete GBP binding patterns due to their ambiguity. It is known that lectins, for example, are non-specific in their binding affinities; the same lectin can bind to different monosaccharides or even different glycan structures. In bioinformatics, several tools to mine the data generated from these sorts of experiments have been developed. These tools take a library of predefined motifs, which are commonly-found glycan patterns such as sialyl-Lewis X, and attempt to identify the motif(s) that are specific to the GBP being analyzed. In our previous work, as opposed to using predefined motifs, we developed the Multiple Carbohydrate Alignment with Weights (MCAW) tool to visualize the state of the glycans being recognized by the GBP under analysis. We previously reported on the effectiveness of our tool and algorithm by analyzing several glycan array datasets from the Consortium of Functional Glycomics (CFG). In this work, we report on our analysis of 1081 data sets which we collected from the CFG, the results of which we have made publicly and freely available as a database called MCAW-DB. We introduce this database, its usage and describe several analysis results. We show how MCAW-DB can be used to analyze glycan-binding patterns of GBPs amidst their ambiguity. For example, the visualization of glycan-binding patterns in MCAW-DB show how they correlate with the concentrations of the samples used in the array experiments. Using MCAW-DB, the patterns of glycans found to bind to various GBP-glycan binding proteins are visualized, indicating the binding "environment" of the glycans. Thus, the ambiguity of glycan recognition is numerically represented, along with the patterns of monosaccharides surrounding the binding region. The profiles in MCAW-DB could potentially be used as predictors of affinity of unknown or novel glycans to particular GBPs by comparing how well they match the existing profiles for those GBPs. Moreover, as the glycan profiles of diseased tissues become available, glycan alignments could also be used to identify glycan biomarkers unique to that tissue. Databases of these alignments may be of great use for drug discovery.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2011-2012

This review is the seventh update of the original article published in 1999 on the application of MALDI mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2012. General aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, and fragmentation are covered in the first part of the review and applications to various structural types constitute the remainder. The main groups of compound are oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides, and biopharmaceuticals. Much of this material is presented in tabular form. Also discussed are medical and industrial applications of the technique, studies of enzyme reactions, and applications to chemical synthesis. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:255-422, 2017.

A standardized method for lectin microarray-based tissue glycome mapping

The significance of glycomic profiling has been highlighted by recent findings that structural changes of glycans are observed in many diseases, including cancer. Therefore, glycomic profiling of the whole body (glycome mapping) under different physiopathological states may contribute to the discovery of reliable biomarkers with disease-specific alterations. To achieve this, standardization of high-throughput and in-depth analysis of tissue glycome mapping is needed. However, this is a great challenge due to the lack of analytical methodology for glycans on small amounts of endogenous glycoproteins. Here, we established a standardized method of lectin-assisted tissue glycome mapping. Formalin-fixed, paraffin-embedded tissue sections were prepared from brain, liver, kidney, spleen, and testis of two C57BL/6J mice. In total, 190 size-adjusted fragments with different morphology were serially collected from each tissue by laser microdissection and subjected to lectin microarray analysis. The results and subsequent histochemical analysis with selected lectins were highly consistent with previous reports of mass spectrometry-based N- and/or O-glycome analyses and histochemistry. This is the first report to look at both N- and O-glycome profiles of various regions within tissue sections of five different organs. This simple and reproducible mapping approach is also applicable to various disease model mice to facilitate disease-related biomarker discovery.

SugarBindDB, a resource of glycan-mediated host-pathogen interactions

The SugarBind Database (SugarBindDB) covers knowledge of glycan binding of human pathogen lectins and adhesins. It is a curated database; each glycan-protein binding pair is associated with at least one published reference. The core data element of SugarBindDB is a set of three inseparable components: the pathogenic agent, a lectin/adhesin and a glycan ligand. Each entity (agent, lectin or ligand) is described by a range of properties that are summarized in an entity-dedicated page. Several search, navigation and visualisation tools are implemented to investigate the functional role of glycans in pathogen binding. The database is cross-linked to protein and glycan-relaled resources such as UniProtKB and UniCarbKB. It is tightly bound to the latter via a substructure search tool that maps each ligand to full structures where it occurs. Thus, a glycan-lectin binding pair of SugarBindDB can lead to the identification of a glycan-mediated protein-protein interaction, that is, a lectin-glycoprotein interaction, via substructure search and the knowledge of site-specific glycosylation stored in UniCarbKB. SugarBindDB is accessible at: http://sugarbind.expasy.org.

Informatics tools to advance the biology of glycosaminoglycans and proteoglycans

Glycomics researchers have identified the need for integrated database systems for collecting glycomics information in a consistent format. The goal is to create a resource for knowledge discovery and dissemination to wider research communities. This has the potential to extend the research community to include biologists, clinicians, chemists, and computer scientists. This chapter discusses the technology and approach needed to create integrated data resources to empower the broader community to leverage extant glycomics data. The focus is on glycosaminoglycan (GAGs) and proteoglycan research, but the approach can be generalized. The methods described span the development of glycomics standards from CarbBank to Glyco Connection Tables. The existence of integrated data sets provides a foundation for novel methods of analysis such as machine learning for knowledge discovery. The implications of predictive analysis are examined in relation to disease biomarker to expand the target audience of GAG and proteoglycan research.

A computational framework for the automated construction of glycosylation reaction networks

Glycosylation is among the most common and complex post-translational modifications identified to date. It proceeds through the catalytic action of multiple enzyme families that include the glycosyltransferases that add monosaccharides to growing glycans, and glycosidases which remove sugar residues to trim glycans. The expression level and specificity of these enzymes, in part, regulate the glycan distribution or glycome of specific cell/tissue systems. Currently, there is no systematic method to describe the enzymes and cellular reaction networks that catalyze glycosylation. To address this limitation, we present a streamlined machine-readable definition for the glycosylating enzymes and additional methodologies to construct and analyze glycosylation reaction networks. In this computational framework, the enzyme class is systematically designed to store detailed specificity data such as enzymatic functional group, linkage and substrate specificity. The new classes and their associated functions enable both single-reaction inference and automated full network reconstruction, when given a list of reactants and/or products along with the enzymes present in the system. In addition, graph theory is used to support functions that map the connectivity between two or more species in a network, and that generate subset models to identify rate-limiting steps regulating glycan biosynthesis. Finally, this framework allows the synthesis of biochemical reaction networks using mass spectrometry (MS) data. The features described above are illustrated using three case studies that examine: i) O-linked glycan biosynthesis during the construction of functional selectin-ligands; ii) automated N-linked glycosylation pathway construction; and iii) the handling and analysis of glycomics based MS data. Overall, the new computational framework enables automated glycosylation network model construction and analysis by integrating knowledge of glycan structure and enzyme biochemistry. All the implemented features are provided as part of the Glycosylation Network Analysis Toolbox (GNAT), an open-source, platform-independent, MATLAB based toolbox for studies of Systems Glycobiology.

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.

Glycosylation Network Analysis Toolbox: a MATLAB-based environment for systems glycobiology

Systems glycobiology studies the interaction of various pathways that regulate glycan biosynthesis and function. Software tools for the construction and analysis of such pathways are not yet available. We present GNAT, a platform-independent, user-extensible MATLAB-based toolbox that provides an integrated computational environment to construct, manipulate and simulate glycans and their networks. It enables integration of XML-based glycan structure data into SBML (Systems Biology Markup Language) files that describe glycosylation reaction networks. Curation and manipulation of networks is facilitated using class definitions and glycomics database query tools. High quality visualization of networks and their steady-state and dynamic simulation are also supported.

AVAILABILITY

The software package including source code, help documentation and demonstrations are available at http://sourceforge.net/projects/gnatmatlab/files/.