High-throughput site-specific N-glycoproteomics reveals glyco-signatures for liver disease diagnosis.
High-throughput site-specific N-glycoproteomics reveals glyco-signatures for liver disease diagnosis.
复制标题
DOI:
10.1093/nsr/nwac059
复制
发表时间:
2023-01
影响因子:
20.6
通讯作者:
中科院分区:
文献类型:
--
作者:
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. A high-throughput intact glycopeptide quantification strategy (HTiGQs) is developed. HTiGQs identified several glyco-signatures from IgG that can be used for diagosis and distinguishing different stages of liver diseases.
登录
查看更多内容
DOI:
10.1016/j.mcpro.2021.100081
发表时间:
2021
期刊:
Molecular & cellular proteomics : MCP
影响因子:
--
作者:
Chen Z;Yu Q;Yu Q;Johnson J;Shipman R;Zhong X;Huang J;Asthana S;Carlsson C;Okonkwo O;Li L
通讯作者:
Li L
影响因子:
14.9
作者:
Ma J;Chen T;Wu S;Yang C;Bai M;Shu K;Li K;Zhang G;Jin Z;He F;Hermjakob H;Zhu Y
通讯作者:
Zhu Y
影响因子:
4.4
作者:
Riley, Nicholas M.;Malaker, Stacy A.;Bertozzi, Carolyn R.
通讯作者:
Bertozzi, Carolyn R.
影响因子:
46.9
作者:
Sun S;Shah P;Eshghi ST;Yang W;Trikannad N;Yang S;Chen L;Aiyetan P;Höti N;Zhang Z;Chan DW;Zhang H
通讯作者:
Zhang H
影响因子:
16.6
作者:
Fang P;Ji Y;Silbern I;Doebele C;Ninov M;Lenz C;Oellerich T;Pan KT;Urlaub H
通讯作者:
Urlaub H