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@ARTICLE{Distler:281523,
      author       = {Distler, Ute and Yoo, Han Byul and Kardell, Oliver and
                      Hein, Dana and Sielaff, Malte and Scherer, Marian and
                      Jozefowicz, Anna M and Leps, Christian and Gomez-Zepeda,
                      David and von Toerne, Christine and Merl-Pham, Juliane and
                      Barth, Teresa K and Tüshaus, Johanna and Giesbertz, Pieter
                      and Müller, Torsten and Kliewer, Georg and Aljakouch, Karim
                      and Helm, Barbara and Unger, Henry and Frey, Dario L and
                      Helm, Dominic and Schwarzmüller, Luisa and Popp, Oliver and
                      Qin, Di and Wudy, Susanne I and Sinn, Ludwig Roman and
                      Mergner, Julia and Ludwig, Christina and Imhof, Axel and
                      Kuster, Bernhard and Lichtenthaler, Stefan F and Krijgsveld,
                      Jeroen and Klingmüller, Ursula and Mertins, Philipp and
                      Coscia, Fabian and Ralser, Markus and Mülleder, Michael and
                      Hauck, Stefanie M and Tenzer, Stefan},
      title        = {{M}ulticenter evaluation of label-free quantification in
                      human plasma on a high dynamic range benchmark set.},
      journal      = {Nature Communications},
      volume       = {16},
      number       = {1},
      issn         = {2041-1723},
      address      = {[London]},
      publisher    = {Springer Nature},
      reportid     = {DZNE-2025-01141},
      pages        = {8774},
      year         = {2025},
      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.},
      keywords     = {Humans / Proteomics: methods / Chromatography, Liquid:
                      methods / Blood Proteins: analysis / Blood Proteins:
                      metabolism / Proteome: analysis / Benchmarking /
                      Reproducibility of Results / Mass Spectrometry: methods /
                      Biomarkers: blood / Escherichia coli: metabolism / Plasma:
                      chemistry / Blood Proteins (NLM Chemicals) / Proteome (NLM
                      Chemicals) / Biomarkers (NLM Chemicals)},
      cin          = {AG Lichtenthaler},
      ddc          = {500},
      cid          = {I:(DE-2719)1110006},
      pnm          = {352 - Disease Mechanisms (POF4-352)},
      pid          = {G:(DE-HGF)POF4-352},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:41038884},
      pmc          = {pmc:PMC12491457},
      doi          = {10.1038/s41467-025-64501-z},
      url          = {https://pub.dzne.de/record/281523},
}