Unifying the analysis of bottom-up proteomics data with CHIMERYS
Proteomic workflows generate vastly complex peptide mixtures that are analyzed by liquid chromatography-tandem mass spectrometry, creating thousands of spectra, most of which are chimeric and contain fragment ions from more than one peptide. Because of differences in data acquisition strategies such as data-dependent, data-independent or parallel reaction monitoring, separate software packages employing different analysis concepts are used for peptide identification and quantification, even though the underlying information is principally the same. Here, we introduce CHIMERYS, a spectrum-centric search algorithm designed for the deconvolution of chimeric spectra that unifies proteomic data analysis. Using accurate predictions of peptide retention time, fragment ion intensities and applying regularized linear regression, it explains as much fragment ion intensity as possible with as few peptides as possible. Together with rigorous false discovery rate control, CHIMERYS accurately identifies and quantifies multiple peptides per tandem mass spectrum in data-dependent, data-independent or parallel reaction monitoring experiments.
Authors
- Patroklos Samaras (ORCID: https://orcid.org/0000-0001-6042-1585)
- Johanna Tüshaus (ORCID: https://orcid.org/0000-0001-9206-8093)
- Michael Graber (ORCID: https://orcid.org/0000-0002-9797-5183)
- Mathias Wilhelm (ORCID: https://orcid.org/0000-0002-9224-3258)
- Florian Seefried (ORCID: https://orcid.org/0000-0003-2334-6541)
- Daniel P. Zolg (ORCID: https://orcid.org/0000-0002-1692-6102)
- Bernhard Küster (ORCID: https://orcid.org/0000-0002-9094-1677)
- Martin Frejno (ORCID: https://orcid.org/0000-0002-6651-1773)
- Michelle T. Berger (ORCID: https://orcid.org/0000-0003-1438-3009)
- Alexander Hogrebe (ORCID: https://orcid.org/0000-0002-0203-6803)
- Siegfried Gessulat (ORCID: https://orcid.org/0000-0001-5530-0674)
- Igor Bronshtein
- Tobias Schmidt (ORCID: https://orcid.org/0000-0002-1883-6514)
- Layla Eljagh
- Lizi Mamisashvili
- Samia Ben Fredj
- Vishal Sukumar
- Markus Schneider (ORCID: https://orcid.org/0000-0003-0543-2593)
Institutions
- Isotopen Technologien München (Germany) (DE)
- Technical University of Munich (DE)
Publication Details
- Journal
- Nature Methods
- Published
- 2025-04-22
- DOI
- https://doi.org/10.1038/s41592-025-02663-w
- Citations
- 25
- Primary Topic
- Advanced Proteomics Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 17.39
Funders
- Bundesministerium für Bildung und Forschung
- Technische Universität München