Multicenter Evaluation of Label-Free Quantification in Human Plasma: Benchmarking with a High Dynamic Range Multispecies Sample 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 generated 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. The sample set was distributed across twelve different sites and analysed on state-of-the-art LC-MS platforms in data-dependent (DDA) and data-independent acquisition (DIA) modes, resulting in a total of 1,116 individual LC-MS runs. Centralized data analysis showed that DIA methods outperform DDA-based approaches regarding identifications, data completeness, accuracy, and precision. DIA achieved excellent technical reproducibility, as demonstrated by coefficients of variation (CVs) between 1.5% and 4.6% 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.