Systems Glycobiology: Integrating Glycogenomics, Glycoproteomics, Glycomics, and Other ‘Omics Data Sets to Characterize Cellular Glycosylation Processes

Sandra V. Bennun, Deniz Baycin Hizal, Kelley Heffner, Ozge Can, Hui Zhang, Michael J. Betenbaugh

Research output: Contribution to journalReview articlepeer-review

28 Scopus citations

Abstract

The number of proteins encoded in the human genome has been estimated at between 20,000 and 25,000, despite estimates that the entire proteome contains more than a million proteins. One reason for this difference is due to many post-translational modifications of protein that contribute to proteome complexity. Among these, glycosylation is of particular relevance because it serves to modify a large number of cellular proteins. Glycogenomics, glycoproteomics, glycomics, and glycoinformatics are helping to accelerate our understanding of the cellular events involved in generating the glycoproteome, the variety of glycan structures possible, and the importance of roles that glycans play in therapeutics and disease. Indeed, interest in glycosylation has expanded rapidly over the past decade, as large amounts of experimental ‘omics data relevant to glycosylation processing have accumulated. Furthermore, new and more sophisticated glycoinformatics tools and databases are now available for glycan and glycosylation pathway analysis. Here, we summarize some of the recent advances in both experimental profiling and analytical methods involving N- and O-linked glycosylation processing for biotechnological and medically relevant cells together with the unique opportunities and challenges associated with interrogating and assimilating multiple, disparate high-throughput glycosylation data sets. This emerging era of advanced glycomics will lead to the discovery of key glycan biomarkers linked to diseases and help establish a better understanding of physiology and improved control of glycosylation processing in diverse cells and tissues important to disease and production of recombinant therapeutics. Furthermore, methodologies that facilitate the integration of glycomics measurements together with other ‘omics data sets will lead to a deeper understanding and greater insights into the nature of glycosylation as a complex cellular process.

Original languageEnglish (US)
Pages (from-to)3337-3352
Number of pages16
JournalJournal of molecular biology
Volume428
Issue number16
DOIs
StatePublished - Aug 14 2016

Keywords

  • Chinese hamster ovary
  • N-glycosylation
  • glycans
  • glycoinformatics
  • systems biology

ASJC Scopus subject areas

  • Molecular Biology
  • Biophysics
  • Structural Biology

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