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  Optimal precursor ion selection for LC-MALDI MS/MS

Zerck, A., Nordhoff, E., Lehrach, H., & Reinert, K. (2013). Optimal precursor ion selection for LC-MALDI MS/MS. BMC Bioinformatics, 14, 14:56-14:56. doi:10.1186/1471-2105-14-56.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0018-F327-8 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0019-CED8-E
Genre: Journal Article

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This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
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2013
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© 2013 Zerck et al.; licensee BioMed Central Ltd.

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Zerck, A.1, Author              
Nordhoff, E.1, Author              
Lehrach, H.1, Author              
Reinert, K., Author
Affiliations:
1Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433550              

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Free keywords: tandem mass-spectrometry protein identification shotgun proteomics proteotypic peptides accurate mass acquisition exclusion strategy prediction mixtures
 Abstract: Background: Liquid chromatography mass spectrometry (LC-MS) maps in shotgun proteomics are often too complex to select every detected peptide signal for fragmentation by tandem mass spectrometry (MS/MS). Standard methods for precursor ion selection, commonly based on data dependent acquisition, select highly abundant peptide signals in each spectrum. However, these approaches produce redundant information and are biased towards high-abundance proteins. Results: We present two algorithms for inclusion list creation that formulate precursor ion selection as an optimization problem. Given an LC-MS map, the first approach maximizes the number of selected precursors given constraints such as a limited number of acquisitions per RT fraction. Second, we introduce a protein sequence-based inclusion list that can be used to monitor proteins of interest. Given only the protein sequences, we create an inclusion list that optimally covers the whole protein set. Additionally, we propose an iterative precursor ion selection that aims at reducing the redundancy obtained with data dependent LC-MS/MS. We overcome the risk of erroneous assignments by including methods for retention time and proteotypicity predictions. We show that our method identifies a set of proteins requiring fewer precursors than standard approaches. Thus, it is well suited for precursor ion selection in experiments with limited sample amount or analysis time. Conclusions: We present three approaches to precursor ion selection with LC-MALDI MS/MS. Using a well-defined protein standard and a complex human cell lysate, we demonstrate that our methods outperform standard approaches. Our algorithms are implemented as part of OpenMS and are available under www.openms.de.

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Language(s): eng - English
 Dates: 2012-07-202013-01-232013-02-18
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1186/1471-2105-14-56
ISSN: 1471-2105
 Degree: -

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Title: BMC Bioinformatics
Source Genre: Journal
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Publ. Info: BioMed Central
Pages: - Volume / Issue: 14 Sequence Number: - Start / End Page: 14:56 - 14:56 Identifier: ISSN: 1471-2105
CoNE: https://pure.mpg.de/cone/journals/resource/111000136905000