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Multicenter evaluation of label-free quantification in human plasma on a high dynamic range benchmark set

Ute Distler (), Han Byul Yoo, Oliver Kardell, Dana Hein, Malte Sielaff, Marian Scherer, Anna M. Jozefowicz, Christian Leps, David Gomez-Zepeda, Christine Toerne, Juliane Merl-Pham, Teresa K. Barth, Johanna Tüshaus, Pieter Giesbertz, Torsten Müller, Georg Kliewer, Karim Aljakouch, Barbara Helm, Henry Unger, Dario L. Frey, Dominic Helm, Luisa Schwarzmüller, Oliver Popp, Di Qin, Susanne I. Wudy, Ludwig Roman Sinn, Julia Mergner, Christina Ludwig, Axel Imhof, Bernhard Kuster, Stefan F. Lichtenthaler, Jeroen Krijgsveld, Ursula Klingmüller, Philipp Mertins, Fabian Coscia, Markus Ralser, Michael Mülleder, Stefanie M. Hauck and Stefan Tenzer ()
Additional contact information
Ute Distler: University Medical Center of the Johannes Gutenberg University Mainz
Han Byul Yoo: University Medical Center of the Johannes Gutenberg University Mainz
Oliver Kardell: Helmholtz Zentrum München, German Research Center for Environmental Health
Dana Hein: University Medical Center of the Johannes Gutenberg University Mainz
Malte Sielaff: University Medical Center of the Johannes Gutenberg University Mainz
Marian Scherer: University Medical Center of the Johannes Gutenberg University Mainz
Anna M. Jozefowicz: University Medical Center of the Johannes Gutenberg University Mainz
Christian Leps: University Medical Center of the Johannes Gutenberg University Mainz
David Gomez-Zepeda: German Cancer Research Center (DKFZ)
Christine Toerne: Helmholtz Zentrum München, German Research Center for Environmental Health
Juliane Merl-Pham: Helmholtz Zentrum München, German Research Center for Environmental Health
Teresa K. Barth: LMU Munich
Johanna Tüshaus: Technical University of Munich
Pieter Giesbertz: German Center for Neurodegenerative Diseases (DZNE) Munich, DZNE
Torsten Müller: German Cancer Research Center (DKFZ)
Georg Kliewer: German Cancer Research Center (DKFZ)
Karim Aljakouch: German Cancer Research Center (DKFZ)
Barbara Helm: German Cancer Research Center (DKFZ), Member of the German Center for Lung Research (DZL)
Henry Unger: German Cancer Research Center (DKFZ), Member of the German Center for Lung Research (DZL)
Dario L. Frey: German Cancer Research Center (DKFZ), Member of the German Center for Lung Research (DZL)
Dominic Helm: Liver Systems Medicine against Cancer (LiSyM-Krebs)
Luisa Schwarzmüller: German Cancer Research Center (DKFZ)
Oliver Popp: Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC)
Di Qin: Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Spatial Proteomics Group
Susanne I. Wudy: Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), TUM School of Life Sciences, Technical University of Munich
Ludwig Roman Sinn: Charité Universitätsmedizin Berlin
Julia Mergner: Technical University of Munich
Christina Ludwig: Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), TUM School of Life Sciences, Technical University of Munich
Axel Imhof: LMU Munich
Bernhard Kuster: Technical University of Munich
Stefan F. Lichtenthaler: German Center for Neurodegenerative Diseases (DZNE) Munich, DZNE
Jeroen Krijgsveld: German Cancer Research Center (DKFZ)
Ursula Klingmüller: German Cancer Research Center (DKFZ), Member of the German Center for Lung Research (DZL)
Philipp Mertins: Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC)
Fabian Coscia: Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Spatial Proteomics Group
Markus Ralser: Charité Universitätsmedizin Berlin
Michael Mülleder: Charité Universitätsmedizin
Stefanie M. Hauck: Helmholtz Zentrum München, German Research Center for Environmental Health
Stefan Tenzer: University Medical Center of the Johannes Gutenberg University Mainz

Nature Communications, 2025, vol. 16, issue 1, 1-18

Abstract: Abstract 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.

Date: 2025
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DOI: 10.1038/s41467-025-64501-z

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