Multicenter evaluation of label-free quantification in human plasma on a high dynamic range benchmark set
Human plasma is routinely collected during clinical care and constitutes a rich source of biomarkers for diagnostics and patient stratification. Liquid chromatography-mass spectrometry (LC-MS)-based proteomics is a key method for plasma biomarker discovery, but the high dynamic range of plasma proteins poses significant challenges for MS analysis and data processing. To benchmark the quantitative performance of neat plasma analysis, we introduce a multispecies sample set based on a human tryptic plasma digest containing varying low level spike-ins of yeast and E. coli tryptic proteome digests, termed PYE. By analysing the sample set on state-of-the-art LC-MS platforms across twelve different sites in data-dependent (DDA) and data-independent acquisition (DIA) modes, we provide a data resource comprising a total of 1116 individual LC-MS runs. Centralized data analysis shows that DIA methods outperform DDA-based approaches regarding identifications, data completeness, accuracy, and precision. DIA achieves excellent technical reproducibility, as demonstrated by coefficients of variation (CVs) between 3.3% and 9.8% at protein level. Comparative analysis of different setups clearly shows a high overlap in identified proteins and proves that accurate and precise quantitative measurements are feasible across multiple sites, even in a complex matrix such as plasma, using state-of-the-art instrumentation. The collected dataset, including the PYE sample set and strategy presented, serves as a valuable resource for optimizing the accuracy and reproducibility of LC-MS and bioinformatic workflows for clinical plasma proteome analysis.
Authors
- Juliane Merl‐Pham (ORCID: https://orcid.org/0000-0002-3422-4083)
- Ute Distler (ORCID: https://orcid.org/0000-0002-8031-6384)
- Ludwig Sinn (ORCID: https://orcid.org/0000-0003-4692-0681)
- Marc Scherer
- Horst Unger (ORCID: https://orcid.org/0009-0001-1798-4347)
- Stefanie M. Hauck (ORCID: https://orcid.org/0000-0002-1630-6827)
- Christine von Toerne (ORCID: https://orcid.org/0000-0002-4132-4322)
- Philipp Mertins (ORCID: https://orcid.org/0000-0002-2245-528X)
- Johanna Tüshaus (ORCID: https://orcid.org/0000-0001-9206-8093)
- Dominic Helm (ORCID: https://orcid.org/0000-0001-9321-2069)
- Christian Leps
- Julia Mergner (ORCID: https://orcid.org/0000-0002-4332-1280)
- Pieter Giesbertz (ORCID: https://orcid.org/0000-0001-7461-8602)
- Teresa K. Barth
- Malte Sielaff (ORCID: https://orcid.org/0000-0003-4942-6566)
- Stefan Tenzer (ORCID: https://orcid.org/0000-0003-3034-0017)
- Bernhard Küster (ORCID: https://orcid.org/0000-0002-9094-1677)
- David Gómez-Zepeda (ORCID: https://orcid.org/0000-0002-9467-1213)
- Ursula Klingmüller (ORCID: https://orcid.org/0000-0001-9845-3099)
- Dario L. Frey (ORCID: https://orcid.org/0000-0001-9572-9686)
- Luisa Schwarzmüller (ORCID: https://orcid.org/0000-0002-7151-9913)
- Michael Mülleder (ORCID: https://orcid.org/0000-0001-9792-3861)
- Anna Maria Józefowicz (ORCID: https://orcid.org/0000-0002-8423-0676)
- Markus Ralser (ORCID: https://orcid.org/0000-0001-9535-7413)
- Stefan F. Lichtenthaler (ORCID: https://orcid.org/0000-0003-2211-2575)
- Oliver Popp (ORCID: https://orcid.org/0000-0001-6240-4666)
- Karim Aljakouch (ORCID: https://orcid.org/0000-0002-8330-512X)
- Axel Imhof (ORCID: https://orcid.org/0000-0003-2993-8249)
- D. Hein
- Christina Ludwig (ORCID: https://orcid.org/0000-0002-6131-7322)
- Fabian Coscia (ORCID: https://orcid.org/0000-0002-2244-5081)
- Oliver Kardell (ORCID: https://orcid.org/0000-0002-6703-7997)
- Di Qin (ORCID: https://orcid.org/0000-0002-9730-4072)
- Han Byul Yoo
- Barbara Helm (ORCID: https://orcid.org/0000-0002-8817-2979)
- Jeroen Krijgsveld
- Susanne I. Wudy (ORCID: https://orcid.org/0009-0001-6333-5233)
- Torsten Müller
- Georg Kliewer
Institutions
- German Cancer Research Center (DE)
- Center for Integrated Protein Science Munich (DE)
- Johannes Gutenberg University Mainz (DE)
- Max Delbrück Center (DE)
- Heidelberg University (DE)
- German Center for Neurodegenerative Diseases (DE)
- University Hospital Heidelberg (DE)
- TUM Klinikum (DE)
- Center for Environmental Health (US)
- Helmholtz Zentrum München (DE)
- University Medical Center of the Johannes Gutenberg University Mainz (DE)
- Munich Cluster for Systems Neurology (DE)
- Helmholtz Institute Mainz (DE)
- League Against Cancer (US)
- German Center for Lung Research (DE)
- Technical University of Munich (DE)
- Charité - Universitätsmedizin Berlin (DE)
- Ludwig-Maximilians-Universität München (DE)
Publication Details
- Journal
- Nature Communications
- Published
- 2025-10-02
- DOI
- https://doi.org/10.1038/s41467-025-64501-z
- Citations
- 4
- Primary Topic
- Advanced Proteomics Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 3.03
Funders
- Deutsche Forschungsgemeinschaft
- Bundesministerium für Bildung und Forschung
- Deutsches Zentrum für Lungenforschung
- HORIZON EUROPE Framework Programme