High-throughput site-specific N-glycoproteomics reveals glyco-signatures for liver disease diagnosis

Zhenyu Sun; Bin Fu; Guoli Wang; Lei Zhang; Ruofan Xu; Ying Zhang; Haojie Lu

doi:10.1093/nsr/nwac059

High-throughput site-specific N-glycoproteomics reveals glyco-signatures for liver disease diagnosis

Natl Sci Rev. 2022 Apr 5;10(1):nwac059. doi: 10.1093/nsr/nwac059. eCollection 2023 Jan.

Authors

Zhenyu Sun¹, Bin Fu², Guoli Wang¹, Lei Zhang¹, Ruofan Xu³, Ying Zhang^{1

2}, Haojie Lu^{1

2}

Affiliations

¹ Shanghai Cancer Center and Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China.
² Department of Chemistry and NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai 200032, China.
³ Eleanor Roosevelt College, University of California San Diego, La Jolla, CA92093, USA.

Abstract

The glycoproteome has emerged as a prominent target for screening biomarkers, as altered glycosylation is a hallmark of cancer cells. In this work, we incorporated tandem mass tag labeling into quantitative glycoproteomics by developing a chemical labeling-assisted complementary dissociation method for the multiplexed analysis of intact N-glycopeptides. Benefiting from the complementary nature of two different mass spectrometry dissociation methods for identification and multiplex labeling for quantification of intact N-glycopeptides, we conducted the most comprehensive site-specific and subclass-specific N-glycosylation profiling of human serum immunoglobulin G (IgG) to date. By analysing the serum of 90 human patients with varying severities of liver diseases, as well as healthy controls, we identified that the combination of IgG1-H3N5F1 and IgG4-H4N3 can be used for distinguishing between different stages of liver diseases. Finally, we used targeted parallel reaction monitoring to successfully validate the expression changes of glycosylation in liver diseases in a different sample cohort that included 45 serum samples.

Keywords: N-glycopeptides; glycoproteomics; high-throughput; liver disease; quantification.