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Title: Informed-Proteomics: open-source software package for top-down proteomics

Abstract

Top-down proteomics involves the analysis of intact proteins. This approach is very attractive as it allows for analyzing proteins in their endogenous form without proteolysis, preserving valuable information about post-translation modifications, isoforms, proteolytic processing or their combinations collectively called proteoforms. Moreover, the quality of the top-down LC-MS/MS datasets is rapidly increasing due to advances in the liquid chromatography and mass spectrometry instrumentation and sample processing protocols. However, the top-down mass spectra are substantially more complex compare to the more conventional bottom-up data. To take full advantage of the increasing quality of the top-down LC-MS/MS datasets there is an urgent need to develop algorithms and software tools for confident proteoform identification and quantification. In this study we present a new open source software suite for top-down proteomics analysis consisting of an LC-MS feature finding algorithm, a database search algorithm, and an interactive results viewer. The presented tool along with several other popular tools were evaluated using human-in-mouse xenograft luminal and basal breast tumor samples that are known to have significant differences in protein abundance based on bottom-up analysis.

Authors:
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Publication Date:
Research Org.:
Pacific Northwest National Laboratory (PNNL), Richland, WA (US), Environmental Molecular Sciences Laboratory (EMSL)
Sponsoring Org.:
USDOE
OSTI Identifier:
1398206
Report Number(s):
PNNL-SA-120171
Journal ID: ISSN 1548-7091; 48135; 49670; 47418; 48680; 453040220
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Journal Name:
Nature Methods
Additional Journal Information:
Journal Volume: 14; Journal Issue: 9; Journal ID: ISSN 1548-7091
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
Environmental Molecular Sciences Laboratory

Citation Formats

Park, Jungkap, Piehowski, Paul D., Wilkins, Christopher, Zhou, Mowei, Mendoza, Joshua, Fujimoto, Grant M., Gibbons, Bryson C., Shaw, Jared B., Shen, Yufeng, Shukla, Anil K., Moore, Ronald J., Liu, Tao, Petyuk, Vladislav A., Tolić, Nikola, Paša-Tolić, Ljiljana, Smith, Richard D., Payne, Samuel H., and Kim, Sangtae. Informed-Proteomics: open-source software package for top-down proteomics. United States: N. p., 2017. Web. doi:10.1038/nmeth.4388.
Park, Jungkap, Piehowski, Paul D., Wilkins, Christopher, Zhou, Mowei, Mendoza, Joshua, Fujimoto, Grant M., Gibbons, Bryson C., Shaw, Jared B., Shen, Yufeng, Shukla, Anil K., Moore, Ronald J., Liu, Tao, Petyuk, Vladislav A., Tolić, Nikola, Paša-Tolić, Ljiljana, Smith, Richard D., Payne, Samuel H., & Kim, Sangtae. Informed-Proteomics: open-source software package for top-down proteomics. United States. doi:10.1038/nmeth.4388.
Park, Jungkap, Piehowski, Paul D., Wilkins, Christopher, Zhou, Mowei, Mendoza, Joshua, Fujimoto, Grant M., Gibbons, Bryson C., Shaw, Jared B., Shen, Yufeng, Shukla, Anil K., Moore, Ronald J., Liu, Tao, Petyuk, Vladislav A., Tolić, Nikola, Paša-Tolić, Ljiljana, Smith, Richard D., Payne, Samuel H., and Kim, Sangtae. Mon . "Informed-Proteomics: open-source software package for top-down proteomics". United States. doi:10.1038/nmeth.4388.
@article{osti_1398206,
title = {Informed-Proteomics: open-source software package for top-down proteomics},
author = {Park, Jungkap and Piehowski, Paul D. and Wilkins, Christopher and Zhou, Mowei and Mendoza, Joshua and Fujimoto, Grant M. and Gibbons, Bryson C. and Shaw, Jared B. and Shen, Yufeng and Shukla, Anil K. and Moore, Ronald J. and Liu, Tao and Petyuk, Vladislav A. and Tolić, Nikola and Paša-Tolić, Ljiljana and Smith, Richard D. and Payne, Samuel H. and Kim, Sangtae},
abstractNote = {Top-down proteomics involves the analysis of intact proteins. This approach is very attractive as it allows for analyzing proteins in their endogenous form without proteolysis, preserving valuable information about post-translation modifications, isoforms, proteolytic processing or their combinations collectively called proteoforms. Moreover, the quality of the top-down LC-MS/MS datasets is rapidly increasing due to advances in the liquid chromatography and mass spectrometry instrumentation and sample processing protocols. However, the top-down mass spectra are substantially more complex compare to the more conventional bottom-up data. To take full advantage of the increasing quality of the top-down LC-MS/MS datasets there is an urgent need to develop algorithms and software tools for confident proteoform identification and quantification. In this study we present a new open source software suite for top-down proteomics analysis consisting of an LC-MS feature finding algorithm, a database search algorithm, and an interactive results viewer. The presented tool along with several other popular tools were evaluated using human-in-mouse xenograft luminal and basal breast tumor samples that are known to have significant differences in protein abundance based on bottom-up analysis.},
doi = {10.1038/nmeth.4388},
journal = {Nature Methods},
issn = {1548-7091},
number = 9,
volume = 14,
place = {United States},
year = {2017},
month = {8}
}

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