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Cobbs, Archie L.
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Systematic evaluation of data-independent acquisition for sensitive and reproducible proteomics—a prototype design for a single injection assay
Type:
Article
Description/Abstract:
Data-independent acquisition (DIA)-based proteomics has become increasingly complicated in recent years because of the vast number of workflows described, coupled with a lack of studies indicating a rational framework for selecting effective settings to use. To address this issue and provide a resource for the proteomics community, we compared 12 DIA methods that assay tryptic peptides using various mass-isolation windows. Our findings indicate that the most sensitive single injection LC-DIA method uses 6 m/z isolation windows to analyze the densely populated tryptic peptide range from 450 to 730 m/z, which allowed quantification of 4465 Escherichia coli peptides. In contrast, using the sequential windowed acquisition of all theoretical fragmentions (SWATH) approach with 26 m/z isolation windows across the entire 400–1200 m/z range, allowed quantification of only 3309 peptides. This reduced sensitivity with 26 m/z windows is caused by an increase in co-eluting compounds with similar precursor values detected in the same tandemMS spectra, which lowers the signal-to-noise of peptide fragment-ion chromatograms and reduces the amount of low abundance peptides that can be quantified from 410 to 920 m/z. Above 920 m/z, more peptides were quantified with 26 m/z windows because of substantial peptide 13C isotope distributions that parse peptide ions into separate isolation windows. Because reproducible quantification has been a long-standing aimof quantitative proteomics, and is a socalled trait of DIA, we sought to determine whether precursor-level chromatograms used in some methods rather than their fragment-level counterparts have similar precision. Our data show that extracted fragment-ion chromatograms are the reason DIA provides superior reproducibility. Copyright © 2015 John Wiley & Sons, Ltd.
Creator/Author:
Haffey, Wendy D.
;
Norris, Jeremy L.
;
McCullumsmith, Robert E.
;
Heaven, Michael R.
;
Cobbs, Archie L.
;
Funk, Adam J.
, and
Greis, Kenneth D.
Submitter:
Kenneth Greis
Date Uploaded:
03/03/2017
Date Modified:
04/07/2017
Date Created:
2016-01
License:
All rights reserved
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Cancer Biology
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2016-01
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