diaTracer enables spectrum-centric analysis of diaPASEF proteomics data

Kai Li, Guo Ci Teo, Kevin L. Yang, Fengchao Yu () and Alexey I. Nesvizhskii ()
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Kai Li: University of Michigan
Guo Ci Teo: University of Michigan
Kevin L. Yang: University of Michigan
Fengchao Yu: University of Michigan
Alexey I. Nesvizhskii: University of Michigan

Nature Communications, 2025, vol. 16, issue 1, 1-14

Abstract: Abstract Data-independent acquisition has become a widely used strategy for peptide and protein quantification in liquid chromatography-tandem mass spectrometry-based proteomics studies. The integration of ion mobility separation into data-independent acquisition analysis, such as the diaPASEF technology available on Bruker’s timsTOF platform, further improves the quantification accuracy and protein depth achievable using data-independent acquisition. We introduce diaTracer, a spectrum-centric computational tool optimized for diaPASEF data. diaTracer performs three-dimensional (mass to charge ratio, retention time, ion mobility) peak tracing and feature detection to generate precursor-resolved “pseudo-tandem mass spectra”, facilitating direct (“spectral-library free”) peptide identification and quantification from diaPASEF data. diaTracer is available as a stand-alone tool and is fully integrated into the widely used FragPipe computational platform. We demonstrate the performance of diaTracer and FragPipe using diaPASEF data from triple-negative breast cancer, cerebrospinal fluid, and plasma samples, data from phosphoproteomics and human leukocyte antigens immunopeptidomics experiments, and low-input data from a spatial proteomics study. We also show that diaTracer enables unrestricted identification of post-translational modifications from diaPASEF data using open/mass-offset searches.

Date: 2025
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DOI: 10.1038/s41467-024-55448-8

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