To understand implications of protein glycosylation for clinical diagnostic and biopharmaceuticals, innovative glycoproteomic technologies are required. Recently, significant advances were made, particularly toward structure-focused N-glycoproteomic analyses. The mass spectrometric analysis of intact N-glycopeptides using stepped collision fragmentation along with glycan oxonium ion profiling now enables to reliably discriminate between different N-glycan structures. Still, there are weaknesses that current N-glycoproteomic approaches must overcome: 1) handling of incorrect identifications, 2) identification of rare and modified N-glycans, and 3) insufficient glycoproteomic coverage, especially in complex samples. To address these shortcomings, we have developed an innovative N-glycoproteomic workflow that aims at providing comprehensive site-specific and structural N-glycoproteomic data on human blood plasma glycoproteins. The workflow features protein depletion plus various fractionation strategies and the use of high-resolution mass spectrometry with stepped collision fragmentation. Furthermore, by including a decision tree procedure established for data validation, we could significantly improve the description of the N-glycan micro-heterogeneity. Our data analysis workflow allows the reliable differentiation of ambiguous N-glycan structures like antenna- versus core-fucosylation plus the modified and rare N-glycans such as sulfated and glucuronidated ones. With this workflow, we were able to advance in the analysis of human blood plasma glycoproteins to concentrations as low as 10 pg/mL. A total of 1,929 N-glycopeptides and 942 N-glycosites derived from 805 human middle- to low-abundant glycoproteins were identified. Overall, the presented workflow holds great potential to improve our understanding of protein glycosylation and to foster the discovery of blood plasma biomarkers.

New avenues for human blood plasma biomarker discovery via improved in-depth analysis of the low-abundant N-glycoproteome