Understanding the role that sugars play

30 March 2018:

CNBP scientists Chris Ashwood (pictured) and Prof Nicki Packer at Macquarie University have shown that sugars with exactly the same chemical composition but slightly different structure break apart differently in their latest publication in the area of mass spectrometry. This work is their first step in automating sugar analysis, to understand the role sugars play in human disease.

Journal: Journal of The American Society for Mass Spectrometry.

Publication title: Discrimination of Isomers of Released N- and O-Glycans Using Diagnostic Product Ions in Negative Ion PGC-LC-ESI-MS/MS.

Authors: Christopher Ashwood, Chi-Hung Lin, Morten Thaysen-Andersen, Nicolle H. Packer.

Profiling cellular protein glycosylation is challenging due to the presence of highly similar glycan structures that play diverse roles in cellular physiology. As the anomericity and the exact linkage type of a single glycosidic bond can influence glycan function, there is a demand for improved and automated methods to confirm detailed structural features and to discriminate between structurally similar isomers, overcoming a significant bottleneck in the analysis of data generated by glycomics experiments. We used porous graphitized carbon-LC-ESI-MS/MS to separate and detect released N- and O-glycan isomers from mammalian model glycoproteins using negative mode resonance activation CID-MS/MS. By interrogating similar fragment spectra from closely related glycan isomers that differ only in arm position and sialyl linkage, product fragment ions for discrimination between these features were discovered. Using the Skyline software, at least two diagnostic fragment ions of high specificity were validated for automated discrimination of sialylation and arm position in N-glycan structures, and sialylation in O-glycan structures, complementing existing structural diagnostic ions. These diagnostic ions were shown to be useful for isomer discrimination using both linear and 3D ion trap mass spectrometers when analyzing complex glycan mixtures from cell lysates. Skyline was found to serve as a useful tool for automated assessment of glycan isomer discrimination. This platform-independent workflow can potentially be extended to automate the characterization and quantitation of other challenging glycan isomers.