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- Title
Generating high quality libraries for DIA MS with empirically corrected peptide predictions.
- Authors
Searle, Brian C.; Swearingen, Kristian E.; Barnes, Christopher A.; Schmidt, Tobias; Gessulat, Siegfried; Küster, Bernhard; Wilhelm, Mathias
- Abstract
Data-independent acquisition approaches typically rely on experiment-specific spectrum libraries, requiring offline fractionation and tens to hundreds of injections. We demonstrate a library generation workflow that leverages fragmentation and retention time prediction to build libraries containing every peptide in a proteome, and then refines those libraries with empirical data. Our method specifically enables rapid, experiment-specific library generation for non-model organisms, which we demonstrate using the malaria parasite Plasmodium falciparum, and non-canonical databases, which we show by detecting missense variants in HeLa. Data-independent acquisition-mass spectrometry (MS) typically requires many preparatory MS runs to produce experiment-specific spectral libraries. Here, the authors show that empirical correction of in silico predicted spectral libraries enables efficient generation of high-quality experiment-specific libraries.
- Subjects
PLASMODIUM falciparum; FORECASTING; DATA libraries; RF values (Chromatography); PLASMODIUM
- Publication
Nature Communications, 2020, Vol 11, Issue 1, p1
- ISSN
2041-1723
- Publication type
Article
- DOI
10.1038/s41467-020-15346-1