Analysis of DIA proteomics data using MSFragger-DIA and FragPipe computational platform.

Autor: Yu F; Department of Pathology, University of Michigan, Ann Arbor, MI, USA. yufe@umich.edu., Teo GC; Department of Pathology, University of Michigan, Ann Arbor, MI, USA., Kong AT; Department of Pathology, University of Michigan, Ann Arbor, MI, USA.; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA., Fröhlich K; Proteomics Core Facility, Biozentrum, University of Basel, Basel, Switzerland., Li GX; Department of Pathology, University of Michigan, Ann Arbor, MI, USA., Demichev V; Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany.; Department of Biochemistry, University of Cambridge, Cambridge, UK., Nesvizhskii AI; Department of Pathology, University of Michigan, Ann Arbor, MI, USA. nesvi@med.umich.edu.; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA. nesvi@med.umich.edu.
Jazyk: angličtina
Zdroj: Nature communications [Nat Commun] 2023 Jul 12; Vol. 14 (1), pp. 4154. Date of Electronic Publication: 2023 Jul 12.
DOI: 10.1038/s41467-023-39869-5
Abstrakt: Liquid chromatography (LC) coupled with data-independent acquisition (DIA) mass spectrometry (MS) has been increasingly used in quantitative proteomics studies. Here, we present a fast and sensitive approach for direct peptide identification from DIA data, MSFragger-DIA, which leverages the unmatched speed of the fragment ion indexing-based search engine MSFragger. Different from most existing methods, MSFragger-DIA conducts a database search of the DIA tandem mass (MS/MS) spectra prior to spectral feature detection and peak tracing across the LC dimension. To streamline the analysis of DIA data and enable easy reproducibility, we integrate MSFragger-DIA into the FragPipe computational platform for seamless support of peptide identification and spectral library building from DIA, data-dependent acquisition (DDA), or both data types combined. We compare MSFragger-DIA with other DIA tools, such as DIA-Umpire based workflow in FragPipe, Spectronaut, DIA-NN library-free, and MaxDIA. We demonstrate the fast, sensitive, and accurate performance of MSFragger-DIA across a variety of sample types and data acquisition schemes, including single-cell proteomics, phosphoproteomics, and large-scale tumor proteome profiling studies.
(© 2023. The Author(s).)
Databáze: MEDLINE
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