Ultra-fast proteomics with Scanning SWATH
File(s)
Accepted version
Author(s)
Type
Journal Article
Abstract
Accurate quantification of the proteome remains challenging for large sample series and longitudinal experiments. We report a data-independent acquisition method, Scanning SWATH, that accelerates mass spectrometric (MS) duty cycles, yielding quantitative proteomes in combination with short gradients and high-flow (800 µl min–1) chromatography. Exploiting a continuous movement of the precursor isolation window to assign precursor masses to tandem mass spectrometry (MS/MS) fragment traces, Scanning SWATH increases precursor identifications by ~70% compared to conventional data-independent acquisition (DIA) methods on 0.5–5-min chromatographic gradients. We demonstrate the application of ultra-fast proteomics in drug mode-of-action screening and plasma proteomics. Scanning SWATH proteomes capture the mode of action of fungistatic azoles and statins. Moreover, we confirm 43 and identify 11 new plasma proteome biomarkers of COVID-19 severity, advancing patient classification and biomarker discovery. Thus, our results demonstrate a substantial acceleration and increased depth in fast proteomic experiments that facilitate proteomic drug screens and clinical studies.
Date Issued
2021-07-01
Date Acceptance
2021-02-18
Citation
Nature Biotechnology, 2021, 39 (7), pp.846-854
ISSN
1087-0156
Publisher
Springer Science and Business Media LLC
Start Page
846
End Page
854
Journal / Book Title
Nature Biotechnology
Volume
39
Issue
7
Copyright Statement
2021, The Author(s), under exclusive licence to Springer Nature America, Inc. part of Springer Nature. This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1038/s41587-021-00860-4
Subjects
Cell Line
Humans
Saccharomyces cerevisiae
Arabidopsis
Peptides
Saccharomyces cerevisiae Proteins
Proteome
Severity of Illness Index
Proteomics
Tandem Mass Spectrometry
Biomarkers
COVID-19
Publication Status
Published
Date Publish Online
2021-03-25