Asking more from metabolic oligosaccharide engineering. Issue 39 (26th September 2018)

• Record Type: Journal Article
• Authors: Gilormini, Pierre-André; Batt, Anna R.; Pratt, Matthew R.; Biot, Christophe
• Is Part Of: Chemical science. Volume 9:Issue 39(2018)
• Page Start: 7585
• Page End: 7595
• Publication Date: 2018-09-26
• Subjects: Chemistry -- Periodicals; 540.5
• DOI: 10.1039/c8sc02241k
• Languages: English
• ISSNs: 2041-6520

Abstract

Abstract : Metabolic Oligosaccharide Engineering (MOE) is a groundbreaking strategy which has been largely used in the last decades, as a powerful strategy for glycans understanding. The present review aims to highlight recent studies that are pushing the boundaries of MOE applications. Abstract : Glycans form one of the four classes of biomolecules, are found in every living system and present a huge structural and functional diversity. As an illustration of this diversity, it has been reported that more than 50% of the human proteome is glycosylated and that 2% of the human genome is dedicated to glycosylation processes. Glycans are involved in many biological processes such as signalization, cell–cell or host pathogen interactions, immunity, etc. However, fundamental processes associated with glycans are not yet fully understood and the development of glycobiology is relatively recent compared to the study of genes or proteins. Approximately 25 years ago, the studies of Bertozzi's and Reutter's groups paved the way for metabolic oligosaccharide engineering (MOE), a strategy which consists in the use of modified sugar analogs which are taken up into the cells, metabolized, incorporated into glycoconjugates, and finally detected in a specific manner. This groundbreaking strategy has been widely used during the last few decades and the concomitant development of new bioorthogonal ligation reactions has allowed many advances in the field. Typically, MOE has been used to either visualize glycans or identify different classes of glycoproteins. The present review aims to highlight recent studies that lie somewhat outside of these more traditional approaches and that are pushing the boundaries of MOE applications.