NDLI: Maximizing peptide identification events in proteomic workflows using data-dependent acquisition (DDA).

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Year: 2013 Volume: 12

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Maximizing peptide identification events in proteomic workflows using data-dependent acquisition (DDA).

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Bateman, Nicholas W. Goulding, Scott P. Shulman, Nicholas J. Gadok, Avinash K. Szumlinski, Karen K. MacCoss, Michael J. Wu, Christine C.
Description	Author Affiliation: Bateman NW ( Department of Cell Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15261)
Abstract	Current analytical strategies for collecting proteomic data using data-dependent acquisition (DDA) are limited by the low analytical reproducibility of the method. Proteomic discovery efforts that exploit the benefits of DDA, such as providing peptide sequence information, but that enable improved analytical reproducibility, represent an ideal scenario for maximizing measureable peptide identifications in 'shotgun'-type proteomic studies. Therefore, we propose an analytical workflow combining DDA with retention time aligned extracted ion chromatogram (XIC) areas obtained from high mass accuracy MS1 data acquired in parallel. We applied this workflow to the analyses of sample matrixes prepared from mouse blood plasma and brain tissues and observed increases in peptide detection of up to 30.5% due to the comparison of peptide MS1 XIC areas following retention time alignment of co-identified peptides. Furthermore, we show that the approach is quantitative using peptide standards diluted into a complex matrix. These data revealed that peptide MS1 XIC areas provide linear response of over three orders of magnitude down to low femtomole (fmol) levels. These findings argue that augmenting 'shotgun' proteomic workflows with retention time alignment of peptide identifications and comparative analyses of corresponding peptide MS1 XIC areas improve the analytical performance of global proteomic discovery methods using DDA.
File Format	HTM / HTML
ISSN	15359476
e-ISSN	15359484
DOI	10.1074/mcp.M112.026500
Journal	Molecular & Cellular Proteomics
Issue Number	1
Volume Number	13
Language	English
Publisher	American Society for Biochemistry and Molecular Biology
Publisher Date	2014-01-01
Publisher Place	United States
Access Restriction	Open
Subject Keyword	Discipline Proteomics Mass Spectrometry Peptides Isolation & Purification Proteomics Amino Acid Sequence Genetics Animals Chromatography, Liquid Mice Metabolism Research Support, N.i.h., Extramural
Content Type	Text
Resource Type	Article
Subject	Medicine Analytical Chemistry Molecular Biology Biochemistry

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