In order to understand the biological role(s) of glycosylation one has to know which proteins are glycosylated and what is the degree of macro- and microheterogeneity. We are interested in mucin-type O-glycosylation, and we are attempting to study site-specific glycan diversity from ‘wild-type’ sources in a high throughput manner. Currently we are investigating human urine samples.
Human urinary glycopeptides were enriched from tryptic digests by lectin-affinity chromatography using wheat germ agglutinin. The resulting mixtures were subjected to LC/MS/MS analyses using HCD and diagnostic fragment ion-triggered EThcD experiments performed on a Fusion Lumos Tribrid mass spectrometer. Data interpretation was performed in an iterative manner. First, peptides modified with the most common O-glycans were identified from a full database search. Then additional glycoform candidates were lined up using an HCD-data filtering script searching for Y0 and Y1 fragments, and suggesting glycan compositions from the mass differences between the unmodified peptide and the precursor ions. Finally the proposed structures were manually validated or discarded using both HCD and EThcD data.
We have found that EThcD performed at minimal CE frequently revealed significant structural details about the glycan structures, even permitted the differentiation of some isomeric oligosaccharides. Our investigation showed that urinary mucin-type structures display a much wider diversity than originally suspected. For example, we identified glycans displaying blood-type antigens, and oligosaccharides featuring sialic acids at different states of O-acetylation, even in disialo units. Permitting so many different structures, plus considering variable covalent glycan modifications, could be counterproductive in ‘normal’ database searches. Our iterative approach provides a better tool for ‘in-depth’ data mining, although further software development is necessary.
This work was supported by the following grants: New Szechenyi Plan GOP-1.1.1-11-2012-0452, the Economic Development and Innovation Operative Programmes GINOP-2.3.2-15-2016-00001, and GINOP-2.3.2-15-2016-00020 from the Ministry for National Economy of Hungary.