image: The workflow of high-throughput intact glycopeptides quantitation strategy includes protein extract, preparation of TMT and DMEN-labeled glycopeptides, stepped collision energies HCD followed bynproduct-dependent ETD (sceHCD-pd-ETD) acquisition for intact N-glycopeptide identification and quantification and the bioinformation analysis for biomarker discovery, healthy controls (A), HBV patients (B), CIR patients (C), and HCC patients (D). view more
Credit: ©Science China Press
This study is led by Dr. Haojie Lu from Fudan University. Researchers introduce a new glycoproteomics approach called high-throughput intact glycopeptides quantitation strategy (HTiGQs). They used N,N-dimethylethylenediamine (DMEN) labeling to improve the charge states of the glycopeptides for enhancing their dissociation efficiency in ETD-MS/MS. Meanwhile, chemical labeling can increase the dissociation of TMT reporter ions in the HCD-MS/MS, achieving a high-throughput quantitation for analysis of site-specific glycosylation. Moreover, HTiGQs can quantify 10 samples in a single experiment, greatly reducing the overall LC-MS measurement time. They used HTiGQs to analyze the IgG N-glycopeptides from the serum of 90 human patients with varying severities of liver diseases, which is the first systematic study of IgG glycosylation in liver disease at various severities of stages. 313 intact N-glcopeptides from IgG were identified, which represented the largest data set corresponding to the subclass-specific and site-specific N-glycosylation of IgG in human serum reported to date.
They detected dynamic changes in IgG glycosylation during the progression from hepatitis B virus to cirrhosis and hepatocellular carcinoma. And they further verified the combination of IgG1-H3N5F1 and IgG4-H4N3 can be used for distinguishing between different stages of liver diseases, which provided important insight for invasive monitoring and precision medicine liver diseases.
See the article:
High-throughput site-specific N-glycoproteomics reveals glyco-signatures for liver disease diagnosis
https://doi.org/10.1093/nsr/nwac059
Journal
National Science Review