bioRxiv (Cold Spring Harbor Laboratory) · 2019 · 17 citations · 38 references
Life SciencesBiochemistryMass Spectrometric AnalysisProteomicsProteomics InformaticsBottom-up ProteomicsMass Spectrometry Data AnalysisMass Spectrometry-based ProteomicsProtein IdentificationQuantitative ProteomicsData-independent AcquisitionData-independent Acquisition AnalysisData-independent Acquisition QuantificationHigh-performance Liquid ChromatographyMass Spectrometric IdentificationMass Spectrometric QuantificationPrecursor Mass AssignmentProteomic Identification
Abstract Bridging genotype to phenotype, the proteome has increasingly become of major importance to generate large, longitudinal sample series for data-driven biology and personalized medicine. Major improvements in laboratory automation, chromatography and software have increased the scale and precision of proteomics. So far missing are however mass spectrometric acquisition techniques that could deal with very fast chromatographic gradients. Here we present scanning SWATH, a data-independent acquisition (DIA) method, in which the DIA-typical stepwise windowed acquisition is replaced by a continuous movement of the precursor isolation window. Scanning SWATH accelerates the duty cycles to a few hundreds of milliseconds, and enables precursor mass assignment to the MS2 fragment traces for improving true positive precursor identification in fast proteome experiments. In combination with 800 µL/min high-flow chromatography, we report the quantification of 270 precursors per second, increasing the precursor identifications by 70% or more compared to previous methods. Scanning SWATH quantified 1,410 Human protein groups in conjunction with chromatographic gradients as fast as 30 seconds, 2,250 with 60-second gradients, and 4,586 in conjunction with 5-minute gradients. At high quantitative precision, our method hence increases the proteomic throughput to hundreds of samples per day per mass spectrometer. Scanning SWATH hence enables a broad range of new proteomic applications that depend on large numbers of cheap yet quantification precise proteomes.
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