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Title: Characterization of Proteoforms with Unknown Post-translational Modifications Using the MIScore

Abstract

Various proteoforms may be generated from a single gene due to primary structure alterations (PSAs) such as genetic variations, alternative splicing, and post-translational modifications (PTMs). Top-down mass spectrometry is capable of analyzing intact proteins and identifying patterns of multiple PSAs, making it the method of choice for studying complex proteoforms. In top-down proteomics, proteoform identification is often performed by searching tandem mass spectra against a protein sequence database that contains only one reference protein sequence for each gene or transcript variant in a proteome. Because of the incompleteness of the protein database, an identified proteoform may contain unknown PSAs compared with the reference sequence. Proteoform characterization is to identify and localize PSAs in a proteoform. Although many software tools have been proposed for proteoform identification by top-down mass spectrometry, the characterization of proteoforms in identified proteoform-spectrum matches still relies mainly on manual annotation. We propose to use the Modification Identification Score (MIScore), which is based on Bayesian models, to automatically identify and localize PTMs in proteoforms. Experiments showed that the MIScore is accurate in identifying and localizing one or two modifications.

Authors:
; ; ; ; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Laboratory (PNNL), Richland, WA (US), Environmental Molecular Sciences Laboratory (EMSL)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1324898
Report Number(s):
PNNL-SA-119698
Journal ID: ISSN 1535-3893; 47441; 49209; KP1704020
DOE Contract Number:
AC05-76RL01830
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Proteome Research; Journal Volume: 15; Journal Issue: 8
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; proteoform; post-translational modification; Environmental Molecular Sciences Laboratory

Citation Formats

Kou, Qiang, Zhu, Binhai, Wu, Si, Ansong, Charles, Tolić, Nikola, Paša-Tolić, Ljiljana, and Liu, Xiaowen. Characterization of Proteoforms with Unknown Post-translational Modifications Using the MIScore. United States: N. p., 2016. Web. doi:10.1021/acs.jproteome.5b01098.
Kou, Qiang, Zhu, Binhai, Wu, Si, Ansong, Charles, Tolić, Nikola, Paša-Tolić, Ljiljana, & Liu, Xiaowen. Characterization of Proteoforms with Unknown Post-translational Modifications Using the MIScore. United States. doi:10.1021/acs.jproteome.5b01098.
Kou, Qiang, Zhu, Binhai, Wu, Si, Ansong, Charles, Tolić, Nikola, Paša-Tolić, Ljiljana, and Liu, Xiaowen. 2016. "Characterization of Proteoforms with Unknown Post-translational Modifications Using the MIScore". United States. doi:10.1021/acs.jproteome.5b01098.
@article{osti_1324898,
title = {Characterization of Proteoforms with Unknown Post-translational Modifications Using the MIScore},
author = {Kou, Qiang and Zhu, Binhai and Wu, Si and Ansong, Charles and Tolić, Nikola and Paša-Tolić, Ljiljana and Liu, Xiaowen},
abstractNote = {Various proteoforms may be generated from a single gene due to primary structure alterations (PSAs) such as genetic variations, alternative splicing, and post-translational modifications (PTMs). Top-down mass spectrometry is capable of analyzing intact proteins and identifying patterns of multiple PSAs, making it the method of choice for studying complex proteoforms. In top-down proteomics, proteoform identification is often performed by searching tandem mass spectra against a protein sequence database that contains only one reference protein sequence for each gene or transcript variant in a proteome. Because of the incompleteness of the protein database, an identified proteoform may contain unknown PSAs compared with the reference sequence. Proteoform characterization is to identify and localize PSAs in a proteoform. Although many software tools have been proposed for proteoform identification by top-down mass spectrometry, the characterization of proteoforms in identified proteoform-spectrum matches still relies mainly on manual annotation. We propose to use the Modification Identification Score (MIScore), which is based on Bayesian models, to automatically identify and localize PTMs in proteoforms. Experiments showed that the MIScore is accurate in identifying and localizing one or two modifications.},
doi = {10.1021/acs.jproteome.5b01098},
journal = {Journal of Proteome Research},
number = 8,
volume = 15,
place = {United States},
year = 2016,
month = 8
}
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