Abstract: Protein glycosylation serves critical roles in the cellular
and biological processes of many organisms. Aberrant glycosylation has been
associated with many illnesses such as hereditary and chronic diseases like cancer,
cardiovascular diseases, neurological disorders, and immunological disorders.
Emerging mass spectrometry (MS) ... read moretechnologies that enable the high-throughput
identification of glycoproteins and glycans have accelerated the analysis and made
possible the creation of dynamic and expanding databases. Although
glycosylation-related databases have been established by many laboratories and
institutions, they are not yet widely known in the community. Our study reviews 15
different publicly available databases and identifies their key elements so that
users can identify the most applicable platform for their analytical needs. These
databases include biological information on the experimentally identified glycans and
glycopeptides from various cells and organisms such as human, rat, mouse, fly and
zebrafish. The features of these databases - 7 for glycoproteomic data, 6 for
glycomic data, and 2 for glycan binding proteins are summarized including the
enrichment techniques that are used for glycoproteome and glycan identification.
Furthermore databases such as Unipep, GlycoFly, GlycoFish recently established by our
group are introduced. The unique features of each database, such as the analytical
methods used and bioinformatical tools available are summarized. This information
will be a valuable resource for the glycobiology community as it presents the
analytical methods and glycosylation related databases together in one compendium. It
will also represent a step towards the desired long term goal of integrating the
different databases of glycosylation in order to characterize and categorize
glycoproteins and glycans better for biomedical research.
Baycin Hizal, Deniz, Daniel Wolozny, Joseph Colao, Elena
Jacobson, Yuan Tian, Sharon S. Krag, Michael J. Betenbaugh, and Hui Zhang.
"Glycoproteomic and glycomic databases." Clinical Proteomics 11, no. 1 (12, 2014):