Dataset Information

Identification of N-Glycopeptides based on Glycocarrier Strategy

ABSTRACT: In this work, we developed a glycocarrier strategy to amplify MS signals with isobaric labeling for highly sensitive intact N-glycopeptide characterization from single and small numbers of cells without enrichment. Successful application in cell lines and microglia from the regional mouse brain demonstrated its potential for N-glycoproteome profiling in previously unavailable biological systems.

ORGANISM(S): Homo Sapiens Mus Musculus

SUBMITTER: Weijie Qin

PROVIDER: PXD038212 | iProX | Fri Nov 18 00:00:00 GMT 2022

REPOSITORIES: iProX

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Publications

Sensitive N-Glycopeptide Profiling of Single and Rare Cells Using an Isobaric Labeling Strategy without Enrichment.

Kong Linlin L Li Fengzhi F Fang Wei W Du Zhuokun Z Wang Guibin G Zhang Yangjun Y Ge Woo-Ping WP Zhang Wanjun W Qin Weijie W

Analytical chemistry 20230706 30

Single-cell omics is critical in revealing population heterogeneity, discovering unique features of individual cells, and identifying minority subpopulations of interest. As one of the major post-translational modifications, protein N-glycosylation plays crucial roles in various important biological processes. Elucidation of the variation in N-glycosylation patterns at single-cell resolution may largely facilitate the understanding of their key roles in the tumor microenvironment a ...[more]

PMID: 37409763

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Project description:Large-scale identification of N-linked intact glycopeptides by liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) in human serum is challenging due to the wide dynamic range of serum protein abundances, the lack of a complete serum N-Glycan database and the existence of non-specifically digested peptides and numerous modifications. In this regard, a spectral library search method was presented for serum N-linked intact glycopeptides identification with target-decoy and motif-specific false discovery rate (FDR) control. Low-abundant glycoproteins were firstly separated from high-abundant proteins by acetonitrile (ACN) precipitation. After digestion, the N-linked intact glycopeptides were enriched by hydrophilic interaction liquid chromatography (HILIC) column and a portion of the enriched N-linked intact glycopeptides were processed by N-Glycosidase F (PNGase F) to generate de-glycopeptides. Both N-linked intact glycopeptides and de-glycopeptides were analyzed by LC-MS/MS. From N-linked de-glycopeptides datasets, 764 N-linked glycoproteins, 1,699 N-linked glycosites and 3,328 unique N-linked de-glycopeptides were identified. The spectra of these N-linked de-glycopeptides were utilized for N-linked de-glycopeptides library construction and identification of N-linked intact glycopeptides. Four types of N-linked glycosylation motifs (NXS/T/C/V, X≠P) were used to recognize the N-linked de-glycopeptides, and two different N-Glycan mass databases including 27 modified N-Glycan masses and 712 unmodified N-Glycan masses were combined and utilized during spectral library search for identification of N-linked intact glycopeptides. In total, from the N-linked intact glycopeptides datasets, 526 N-linked glycoproteins, 1,036 N-linked glycosites, 22,677 N-linked intact glycopeptides and 738 N-Glycan masses were identified under 1% FDR, representing the most in-depth serum N-glycoproteome identified by LC-MS/MS at N-linked intact glycopeptide level and N-linked de-glycopeptides level.

Dataset Information

Identification of N-Glycopeptides based on Glycocarrier Strategy

Publications

Sensitive <i>N</i>-Glycopeptide Profiling of Single and Rare Cells Using an Isobaric Labeling Strategy without Enrichment.

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