A streamlined pipeline for multiplexed quantitative site-specific N-glycoproteomics.
A streamlined pipeline for multiplexed quantitative site-specific N-glycoproteomics.
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DOI:
10.1038/s41467-020-19052-w
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发表时间:
2020-10-19
影响因子:
16.6
通讯作者:
Urlaub H
中科院分区:
文献类型:
--
作者:
Fang P;Ji Y;Silbern I;Doebele C;Ninov M;Lenz C;Oellerich T;Pan KT;Urlaub H
Regulation of protein N-glycosylation is essential in human cells. However, large-scale, accurate, and site-specific quantification of glycosylation is still technically challenging. We here introduce SugarQuant, an integrated mass spectrometry-based pipeline comprising protein aggregation capture (PAC)-based sample preparation, multi-notch MS3 acquisition (Glyco-SPS-MS3) and a data-processing tool (GlycoBinder) that enables confident identification and quantification of intact glycopeptides in complex biological samples. PAC significantly reduces sample-handling time without compromising sensitivity. Glyco-SPS-MS3 combines high-resolution MS2 and MS3 scans, resulting in enhanced reporter signals of isobaric mass tags, improved detection of N-glycopeptide fragments, and lowered interference in multiplexed quantification. GlycoBinder enables streamlined processing of Glyco-SPS-MS3 data, followed by a two-step database search, which increases the identification rates of glycopeptides by 22% compared with conventional strategies. We apply SugarQuant to identify and quantify more than 5,000 unique glycoforms in Burkitt’s lymphoma cells, and determine site-specific glycosylation changes that occurred upon inhibition of fucosylation at high confidence. Comprehensive quantitative profiling of intact glycopeptides remains technically challenging. To address this, the authors here develop an integrated quantitative glycoproteomic workflow, including optimized sample preparation, multiplexed quantification and a dedicated data processing tool.
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影响因子:
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作者:
Holman, Jerry D;Tabb, David L;Mallick, Parag
通讯作者:
Mallick, Parag
影响因子:
7.4
作者:
Mysling, Simon;Palmisano, Giuseppe;Thaysen-Andersen, Morten
通讯作者:
Thaysen-Andersen, Morten
影响因子:
4.4
作者:
Lee, Hyoung-Joo;Cha, Hyun-Jeong;Paik, Young-Ki
通讯作者:
Paik, Young-Ki
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:
Hogrebe A;von Stechow L;Bekker-Jensen DB;Weinert BT;Kelstrup CD;Olsen JV
通讯作者:
Olsen JV