image: The intact N-glycopeptides, present in 24 glycopeptide enriched fractions (12× elution 1 + 12× elution 2) were analyzed by LC-MS/MS using both fragmentation energies, HCD.step and HCD.low. A1 and A2: The spectra file acquired at each fragmentation regime was searched for N-glycopeptides using Byonic software. B1 and B2: All individual searches corresponding to the same fragmentation energy were combined using Byologic. After this step, two large N-glycopeptide identification lists were produced: HCD.step-HBP list and HCD.low-HBP list. C: The N-glycopeptides contained in the HCD.step-HBP list were manually validated to confirm the peptide and N-glycan composition assigned by the software. D: The N-glycopeptide-identifications confirmed were imported into the HCD.low-HBP list to substitute corresponding precursor ions potentially incorrectly identified, using their mass and retention time. E: Features annotated in the HCD.step-HBP list were transferred to the HCD.low-HBP list and an additional revision for N-glycan structural evidence is conducted in the HCD.low–HPB list. F: A second Byonic search focused on the new features identified was triggered. G: Finally, a second HCD.step-HBP list containing corrected N-glycopeptide identifications was generated using Byologic. Image created with BioRender.com.
Credit: Frania J. Zuniga-Banuelos et al.
A recent study published in Engineering presents a novel approach to analyzing the low-abundant N–glycoproteome in human blood plasma (HBP), which could significantly advance the discovery of plasma biomarkers.
Protein glycosylation plays a crucial role in clinical diagnostics and biopharmaceuticals. However, current N-glycoproteomic methods face challenges such as incorrect identifications, difficulties in detecting rare and modified N-glycans, and insufficient coverage, especially in complex samples like blood plasma. To address these issues, the research team developed an innovative N-glycoproteomic workflow.
The workflow begins with the depletion of the top 14 high-abundant blood plasma proteins (HAP) and a fractionation strategy. This is followed by tryptic digestion and glycopeptide enrichment. The samples are then analyzed using high-resolution mass spectrometry with stepped collision fragmentation (HCD.step and HCD.low). A new decision tree procedure is incorporated for data validation.
The results of the study are promising. The sample preparation workflow extends the detection range of glycoproteins in blood plasma. It can detect glycoproteins with concentrations as low as 6.31 pg·mL−1, expanding the range by five orders of magnitude compared to direct plasma analysis. The data analysis workflow enables the reliable differentiation of ambiguous N-glycan structures. For example, it can distinguish between antenna and core fucosylation, as well as identify modified and rare N-glycans such as sulfated and glucuronidated ones.
In total, 1929 N-glycopeptides and 942 N-glycosites derived from 805 human middle- to low-abundant glycoproteins were identified. The researchers also detected sulfated and phosphorylated N-glycopeptides in common HBP glycoproteins. Moreover, they discovered three rare N-glycan building blocks with masses of 176.0314, 245.0524, and 259.0672 Da.
This new workflow not only improves our understanding of protein glycosylation but also has the potential to be applied in various fields. It can be used to explore biomarker candidates in HBP, evaluate biotherapeutic proteins, and study biological models. Although the study has limitations, such as the relatively long measurement time of the instrument, the findings provide valuable insights for future glycoproteomic research. Overall, this research offers a new avenue for the in-depth analysis of HBP glycoproteins and biomarker discovery.
The paper “New Avenues for Human Blood Plasma Biomarker Discovery via Improved In-Depth Analysis of the Low-Abundant N–glycoproteome,” is authored by Frania J. Zuniga-Banuelos, Marcus Hoffmann, Udo Reichl, Erdmann Rapp. Full text of the open access paper: https://doi.org/10.1016/j.eng.2024.11.039. For more information about the Engineering, For more information about Engineering, visit the website at https://www.sciencedirect.com/journal/engineering.
Journal
Engineering
Article Title
New Avenues for Human Blood Plasma Biomarker Discovery via Improved In-Depth Analysis of the Low-Abundant N–glycoproteome
Article Publication Date
1-Feb-2025