Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry

Brian C. Searle, Lindsay K. Pino, Jarrett D. Egertson, Ying S. Ting, Robert T. Lawrence, Brendan X. MacLean, Judit Villén and Michael J. MacCoss ()
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Brian C. Searle: University of Washington
Lindsay K. Pino: University of Washington
Jarrett D. Egertson: University of Washington
Ying S. Ting: University of Washington
Robert T. Lawrence: University of Washington
Brendan X. MacLean: University of Washington
Judit Villén: University of Washington
Michael J. MacCoss: University of Washington

Nature Communications, 2018, vol. 9, issue 1, 1-12

Abstract: Abstract Data independent acquisition (DIA) mass spectrometry is a powerful technique that is improving the reproducibility and throughput of proteomics studies. Here, we introduce an experimental workflow that uses this technique to construct chromatogram libraries that capture fragment ion chromatographic peak shape and retention time for every detectable peptide in a proteomics experiment. These coordinates calibrate protein databases or spectrum libraries to a specific mass spectrometer and chromatography setup, facilitating DIA-only pipelines and the reuse of global resource libraries. We also present EncyclopeDIA, a software tool for generating and searching chromatogram libraries, and demonstrate the performance of our workflow by quantifying proteins in human and yeast cells. We find that by exploiting calibrated retention time and fragmentation specificity in chromatogram libraries, EncyclopeDIA can detect 20–25% more peptides from DIA experiments than with data dependent acquisition-based spectrum libraries alone.

Date: 2018
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DOI: 10.1038/s41467-018-07454-w

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