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SweetNET: A Bioinformatics Workflow for Glycopeptide MS/MS Spectral Analysis

Artikel i vetenskaplig tidskrift
Författare Waqas Nasir
Alejandro Gomez Toledo
Fredrik Noborn
Jonas Nilsson
M. X. Wang
N. Bandeira
Göran Larson
Publicerad i Journal of Proteome Research
Volym 15
Nummer/häfte 8
Sidor 2826-2840
ISSN 1535-3893
Publiceringsår 2016
Publicerad vid Institutionen för biomedicin, avdelningen för klinisk kemi och transfusionsmedicin
Sidor 2826-2840
Språk en
Länkar dx.doi.org/10.1021/acs.jproteome.6b...
Ämnesord MS/MS molecular networking glycopeptides, oxonium ion, bioinformatics, glycosylation, mass, INTACT N-GLYCOPEPTIDES, TANDEM MASS-SPECTRA, HEPARAN-SULFATE, PROTEOGLYCANS, SPECTROMETRY-BASED PROTEOMICS, O-LINKED GLYCOPEPTIDES, MOLECULAR NETWORKING, GLYCAN STRUCTURE, LC-MS/MS, DE-NOVO, AUTOMATED, IDENTIFICATION
Ämneskategorier Bioinformatik och systembiologi

Sammanfattning

Glycoproteomics has rapidly become an independent analytical platform bridging the fields of glycomics and proteomics to address site-specific protein glycosylation and its impact in biology. Current glycopeptide characterization relies on time-consuming manual interpretations and demands high levels of personal expertise. Efficient data interpretation constitutes one of the major challenges to be overcome before true high throughput glycopeptide analysis can be achieved. The development of new glyco-related bioinformatics tools is thus of crucial importance to fulfill this goal. Here we present SweetNET: a data-oriented bioinformatics workflow for efficient analysis of hundreds of thousands of glycopeptide MS/MS-spectra. We have analyzed MS data sets from two separate glycopeptide enrichment protocols targeting sialylated glycopeptides and chondroitin sulfate linkage region glycopeptides, respectively. Molecular networking was performed to organize the glycopeptide MS/MS data based on spectral similarities. The combination of spectral clustering, oxonium ion intensity profiles, and precursor ion m/z shift distributions provided typical signatures for the initial assignment of different N-, O- and CS-glycopeptide classes and their respective glycoforms. These signatures were further used to guide database searches leading to the identification and validation of a large number of glycopeptide variants including novel deoxyhexose (fucose) modifications in the linkage region of chondroitin sulfate proteoglycans.

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