title: Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis.
abstract: Most proteomic studies use liquid chromatography coupled to tandem mass spectrometry to identify and quantify the peptides generated by the proteolysis of a biological sample. However, with the current methods it remains challenging to rapidly, consistently, reproducibly, accurately, and sensitively detect and quantify large fractions of proteomes across multiple samples. Here we present a new strategy that systematically queries sample sets for the presence and quantity of essentially any protein of interest. It consists of using the information available in fragment ion spectral libraries to mine the complete fragment ion maps generated using a data-independent acquisition method. For this study, the data were acquired on a fast, high resolution quadrupole-quadrupole time-of-flight (TOF) instrument by repeatedly cycling through 32 consecutive 25-Da precursor isolation windows (swaths). This SWATH MS acquisition setup generates, in a single sample injection, time-resolved fragment ion spectra for all the analytes detectable within the 400-1200 m/z precursor range and the user-defined retention time window. We show that suitable combinations of fragment ions extracted from these data sets are sufficiently specific to confidently identify query peptides over a dynamic range of 4 orders of magnitude, even if the precursors of the queried peptides are not detectable in the survey scans. We also show that queried peptides are quantified with a consistency and accuracy comparable with that of selected reaction monitoring, the gold standard proteomic quantification method. Moreover, targeted data extraction enables ad libitum quantification refinement and dynamic extension of protein probing by iterative re-mining of the once-and-forever acquired data sets. This combination of unbiased, broad range precursor ion fragmentation and targeted data extraction alleviates most constraints of present proteomic methods and should be equally applicable to the comprehensive analysis of other classes of analytes, beyond proteomics.
authors.affiliation: Department of Biology, Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule Zürich, 8093 Zürich, Switzerland.
authors.forename: Ludovic C
authors.initials: LC
authors.lastname: Gillet
authors.forename: Pedro
authors.initials: P
authors.lastname: Navarro
authors.forename: Stephen
authors.initials: S
authors.lastname: Tate
authors.forename: Hannes
authors.initials: H
authors.lastname: Röst
authors.forename: Nathalie
authors.initials: N
authors.lastname: Selevsek
authors.forename: Lukas
authors.initials: L
authors.lastname: Reiter
authors.forename: Ron
authors.initials: R
authors.lastname: Bonner
authors.forename: Ruedi
authors.initials: R
authors.lastname: Aebersold
mesh_terms: D000595:Amino Acid Sequence; D002853:Chromatography, Liquid; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D057225:Data Mining; D057230:Limit of Detection; D008928:Mitochondria / Q000201:enzymology; D008969:Molecular Sequence Data; D010446:Peptide Fragments / Q000737:chemistry; D010449:Peptide Mapping / Q000592:standards; D011499:Protein Processing, Post-Translational; D020543:Proteome / Q000737:chemistry* / Q000378:metabolism; D012015:Reference Standards; D012441:Saccharomyces cerevisiae / Q000201:enzymology / Q000378:metabolism; D029701:Saccharomyces cerevisiae Proteins / Q000737:chemistry / Q000378:metabolism; D053719:Tandem Mass Spectrometry / Q000592:standards
chemical_list: D010446:Peptide Fragments; D020543:Proteome; D029701:Saccharomyces cerevisiae Proteins