The Glycan Structure Dictionary-a dictionary describing commonly used glycan structure terms.

Recent technological advances in glycobiology have resulted in a large influx of data and the publication of many papers describing discoveries in glycoscience. However, the terms used in describing glycan structural features are not standardized, making it difficult to harmonize data across biomolecular databases, hampering the harvesting of information across studies and hindering text mining and curation efforts. To address this shortcoming, the Glycan Structure Dictionary has been developed as a reference dictionary to provide a standardized list of widely used glycan terms that can help in the curation and mapping of glycan structures described in publications. Currently, the dictionary has 190 glycan structure terms with 297 synonyms linked to 3,332 publications. For a term to be included in the dictionary, it must be present in at least 2 peer-reviewed publications. Synonyms, annotations, and cross-references to GlyTouCan, GlycoMotif, and other relevant databases and resources are also provided when available. The purpose of this effort is to facilitate biocuration, assist in the development of text mining tools, improve the harmonization of search, and browse capabilities in glycoinformatics resources and help to map glycan structures to function and disease. It is also expected that authors will use these terms to describe glycan structures in their manuscripts over time. A mechanism is also provided for researchers to submit terms for potential incorporation. The dictionary is available at https://wiki.glygen.org/Glycan_structure_dictionary.

Enhancing the interoperability of glycan data flow between ChEBI, PubChem and GlyGen.

Glycans play a vital role in health, disease, bioenergy, biomaterials and bio-therapeutics. As a result, there is keen interest to identify and increase glycan data in bioinformatics databases like ChEBI and PubChem, and connecting them to resources at the EMBL-EBI and NCBI to facilitate access to important annotations at a global level. GlyTouCan is a comprehensive archival database that contains glycans obtained primarily through batch upload from glycan repositories, glycoprotein databases and individual laboratories. In many instances, the glycan structures deposited in GlyTouCan may not be fully defined or have supporting experimental evidence and citations. Databases like ChEBI and PubChem were designed to accommodate complete atomistic structures with well-defined chemical linkages. As a result, they cannot easily accommodate the structural ambiguity inherent in glycan databases. Consequently, there is a need to improve the organization of glycan data coherently to enhance connectivity across the major NCBI, EMBL-EBI and glycoscience databases. This paper outlines a workflow developed in collaboration between GlyGen, ChEBI and PubChem to improve the visibility and connectivity of glycan data across these resources. GlyGen hosts a subset of glycans (~29,000) from the GlyTouCan database and has submitted valuable glycan annotations to the PubChem database and integrated over 10,500 (including ambiguously defined) glycans into the ChEBI database. The integrated glycans were prioritized based on links to PubChem and connectivity to glycoprotein data. The pipeline provides a blueprint for how glycan data can be harmonized between different resources. The current PubChem, ChEBI and GlyTouCan mappings can be downloaded from GlyGen (https://data.glygen.org).

The human O-GlcNAcome database and meta-analysis.

Over the past 35 years, ~1700 articles have characterized protein O-GlcNAcylation. Found in almost all living organisms, this post-translational modification of serine and threonine residues is highly conserved and key to biological processes. With half of the primary research articles using human models, the O-GlcNAcome recently reached a milestone of 5000 human proteins identified. Herein, we provide an extensive inventory of human O-GlcNAcylated proteins, their O-GlcNAc sites, identification methods, and corresponding references ( www.oglcnac.mcw.edu ). In the absence of a comprehensive online resource for O-GlcNAcylated proteins, this list serves as the only database of O-GlcNAcylated proteins. Based on the thorough analysis of the amino acid sequence surrounding 7002 O-GlcNAc sites, we progress toward a more robust semi-consensus sequence for O-GlcNAcylation. Moreover, we offer a comprehensive meta-analysis of human O-GlcNAcylated proteins for protein domains, cellular and tissue distribution, and pathways in health and diseases, reinforcing that O-GlcNAcylation is a master regulator of cell signaling, equal to the widely studied phosphorylation.

GlyGen data model and processing workflow.

SUMMARY: Glycoinformatics plays a major role in glycobiology research, and the development of a comprehensive glycoinformatics knowledgebase is critical. This application note describes the GlyGen data model, processing workflow and the data access interfaces featuring programmatic use case example queries based on specific biological questions. The GlyGen project is a data integration, harmonization and dissemination project for carbohydrate and glycoconjugate-related data retrieved from multiple international data sources including UniProtKB, GlyTouCan, UniCarbKB and other key resources. AVAILABILITY AND IMPLEMENTATION: GlyGen web portal is freely available to access at https://glygen.org. The data portal, web services, SPARQL endpoint and GitHub repository are also freely available at https://data.glygen.org, https://api.glygen.org, https://sparql.glygen.org and https://github.com/glygener, respectively. All code is released under license GNU General Public License version 3 (GNU GPLv3) and is available on GitHub https://github.com/glygener. The datasets are made available under Creative Commons Attribution 4.0 International (CC BY 4.0) license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Antibacterial Activities of Bacteriagenic Silver Nanoparticles Against Nosocomial Acinetobacter baumannii.

Acinetobacter baumannii has emerged as one of the major nosocomial pathogens implicated in variety of severe infections and mortality. It is rapidly developing multi-drug resistance and also possesses surface colonization ability, which make it most difficult to treat through traditional antibiotics. This is an extensive study to describe the antibacterial activity of bacteriagenic silver nanoparticles (AgNPs) against A. baumannii AIIMS 7 in planktonic and biofilm mode. Minimum inhibitory concentration of antibiotics were in the range of 1 to 4096 µg/ml whereas AgNPs inhibited planktonic bacteria at concentration of 16 µg/ml. Fractional inhibitory concentration index revealed the synergistic interaction of AgNPs with doxycycline, tetracycline and erythromycin. Nanoparticles exhibited significant biofilm disruption activity with minimum biofilm eradication concentration of 2 mg/ml. Eradication of mature biofilm was enhanced on exposure to combination of AgNPs and antibiotics. These nanoparticles affected bacterial growth and distorted cellular morphology. Intracellular oxidative stress, induced in presence of AgNPs, also rendered bacteria susceptible to killing by nanoparticles. Besides this, AgNPs were found to interact with thiol-groups, which indicate their potential to interact with cellular proteins to exhibit antimicrobial activity.

Enabling precision medicine via standard communication of HTS provenance, analysis, and results.

A personalized approach based on a patient's or pathogen's unique genomic sequence is the foundation of precision medicine. Genomic findings must be robust and reproducible, and experimental data capture should adhere to findable, accessible, interoperable, and reusable (FAIR) guiding principles. Moreover, effective precision medicine requires standardized reporting that extends beyond wet-lab procedures to computational methods. The BioCompute framework (https://w3id.org/biocompute/1.3.0) enables standardized reporting of genomic sequence data provenance, including provenance domain, usability domain, execution domain, verification kit, and error domain. This framework facilitates communication and promotes interoperability. Bioinformatics computation instances that employ the BioCompute framework are easily relayed, repeated if needed, and compared by scientists, regulators, test developers, and clinicians. Easing the burden of performing the aforementioned tasks greatly extends the range of practical application. Large clinical trials, precision medicine, and regulatory submissions require a set of agreed upon standards that ensures efficient communication and documentation of genomic analyses. The BioCompute paradigm and the resulting BioCompute Objects (BCOs) offer that standard and are freely accessible as a GitHub organization (https://github.com/biocompute-objects) following the "Open-Stand.org principles for collaborative open standards development." With high-throughput sequencing (HTS) studies communicated using a BCO, regulatory agencies (e.g., Food and Drug Administration [FDA]), diagnostic test developers, researchers, and clinicians can expand collaboration to drive innovation in precision medicine, potentially decreasing the time and cost associated with next-generation sequencing workflow exchange, reporting, and regulatory reviews.