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.

Lysozyme's lectin-like characteristics facilitates its immune defense function.

Interactions between human lysozyme (HL) and the lipopolysaccharide (LPS) of Klebsiella pneumoniae O1, a causative agent of lung infection, were identified by surface plasmon resonance. To characterize the molecular mechanism of this interaction, HL binding to synthetic disaccharides and tetrasaccharides representing one and two repeating units, respectively, of the O-chain of this LPS were studied. pH-dependent structural rearrangements of HL after interaction with the disaccharide were observed through nuclear magnetic resonance. The crystal structure of the HL-tetrasaccharide complex revealed carbohydrate chain packing into the A, B, C, and D binding sites of HL, which primarily occurred through residue-specific, direct or water-mediated hydrogen bonds and hydrophobic contacts. Overall, these results support a crucial role of the Glu35/Asp53/Trp63/Asp102 residues in HL binding to the tetrasaccharide. These observations suggest an unknown glycan-guided mechanism that underlies recognition of the bacterial cell wall by lysozyme and may complement the HL immune defense function.

Development of the ECODAB into a relational database for Escherichia coli O-antigens and other bacterial polysaccharides.

Escherichia coli O-antigen database (ECODAB) is a web-based application to support the collection of E. coli O-antigen structures, polymerase and flippase amino acid sequences, NMR chemical shift data of O-antigens as well as information on glycosyltransferases (GTs) involved in the assembly of O-antigen polysaccharides. The database content has been compiled from scientific literature. Furthermore, the system has evolved from being a repository to one that can be used for generating novel data on its own. GT specificity is suggested through sequence comparison with GTs whose function is known. The migration of ECODAB to a relational database has allowed the automation of all processes to update, retrieve and present information, thereby, endowing the system with greater flexibility and improved overall performance. ECODAB is freely available at http://www.casper.organ.su.se/ECODAB/. Currently, data on 169 E. coli unique O-antigen entries and 338 GTs is covered. Moreover, the scope of the database has been extended so that polysaccharide structure and related information from other bacteria subsequently can be added, for example, from Streptococcus pneumoniae.

Towards a standardized bioinformatics infrastructure for N- and O-glycomics.

The mass spectrometry (MS)-based analysis of free polysaccharides and glycans released from proteins, lipids and proteoglycans increasingly relies on databases and software. Here, we review progress in the bioinformatics analysis of protein-released N- and O-linked glycans (N- and O-glycomics) and propose an e-infrastructure to overcome current deficits in data and experimental transparency. This workflow enables the standardized submission of MS-based glycomics information into the public repository UniCarb-DR. It implements the MIRAGE (Minimum Requirement for A Glycomics Experiment) reporting guidelines, storage of unprocessed MS data in the GlycoPOST repository and glycan structure registration using the GlyTouCan registry, thereby supporting the development and extension of a glycan structure knowledgebase.

Sample handling of gastric tissue and O-glycan alterations in paired gastric cancer and non-tumorigenic tissues.

Sample collection, handling and storage are the most critical steps for ensuring the highest preservation of specimens. Pre-analytical variability can influence the results as protein signatures alter rapidly after tissue excision or during long-term storage. Hence, we evaluated current state-of-the-art biobank preservation methods from a glycomics perspective and analyzed O-glycan alterations occurring in the gastric cancer tissues. Paired tumor and adjacent normal tissue samples were obtained from six patients undergoing gastric cancer surgery. Collected samples (n = 24) were either snap-frozen or heat stabilized and then homogenized. Glycans were released from extracted glycoproteins and analyzed by LC-MS/MS. In total, the relative abundance of 83 O-glycans and 17 derived structural features were used for comparison. There was no statistically significant difference found in variables between snap frozen and heat-stabilized samples, which indicated the two preservation methods were comparable. The data also showed significant changes between normal and cancerous tissue. In addition to a shift from high sialylation in the cancer area towards blood group ABO in the normal area, we also detected that the LacdiNAc epitope (N,N'-diacetyllactosamine) was significantly decreased in cancer samples. The O-glycan alterations that are presented here may provide predictive power for the detection and prognosis of gastric cancer.

Databases and Associated Tools for Glycomics and Glycoproteomics.

The access to biodatabases for glycomics and glycoproteomics has proven to be essential for current glycobiological research. This chapter presents available databases that are devoted to different aspects of glycobioinformatics. This includes oligosaccharide sequence databases, experimental databases, 3D structure databases (of both glycans and glycorelated proteins) and association of glycans with tissue, disease, and proteins. Specific search protocols are also provided using tools associated with experimental databases for converting primary glycoanalytical data to glycan structural information. In particular, researchers using glycoanalysis methods by U/HPLC (GlycoBase), MS (GlycoWorkbench, UniCarb-DB, GlycoDigest), and NMR (CASPER) will benefit from this chapter. In addition we also include information on how to utilize glycan structural information to query databases that associate glycans with proteins (UniCarbKB) and with interactions with pathogens (SugarBind).

Molecular Basis of the Receptor Interactions of Polysialic Acid (polySia), polySia Mimetics, and Sulfated Polysaccharides.

Polysialic acid (polySia) and polySia glycomimetic molecules support nerve cell regeneration, differentiation, and neuronal plasticity. With a combination of biophysical and biochemical methods, as well as data mining and molecular modeling techniques, it is possible to correlate specific ligand-receptor interactions with biochemical processes and in vivo studies that focus on the potential therapeutic impact of polySia, polySia glycomimetics, and sulfated polysaccharides in neuronal diseases. With this strategy, the receptor interactions of polySia and polySia mimetics can be understood on a submolecular level. As the HNK-1 glycan also enhances neuronal functions, we tested whether similar sulfated oligo- and polysaccharides from seaweed could be suitable, in addition to polySia, for finding potential new routes into patient care focusing on an improved cure for various neuronal diseases. The knowledge obtained here on the structural interplay between polySia or sulfated polysaccharides and their receptors can be exploited to develop new drugs and application routes for the treatment of neurological diseases and dysfunctions.

Statistical analysis of amino acids in the vicinity of carbohydrate residues performed by GlyVicinity.

Protein-carbohydrate interactions are involved in various essential biological events. 3D structural data from the Protein Data Bank (PDB) can help to understand the molecular basis of the specificity of carbohydrate recognition by proteins. Such interactions can be analyzed statistically using GlyVicinity. This chapter exemplifies the usage of this tool to find information on the frequency of the occurrence of specific amino acids in the vicinity of individual carbohydrate residues and to analyze the type of interacting atoms and their spatial distribution around the glycans.