LFQ Benchmark Dataset - Generation Beta: Assessing Modern Proteomics Instruments and Acquisition Workflows with High-Throughput LC Gradients

Recent advancements in liquid chromatography-mass spectrometry (LC-MS) have increasingly focused on high-throughput workflows, leveraging rapid chromatographic gradients and minimal sample input to maximize proteome coverage from limited material. This shift is particularly driven by the rise of single-cell proteomics, where sensitivity and reproducibility are critical. Building on our previous benchmark dataset (PXD028735), we now present an expanded study utilizing the latest generation of LC-MS platforms optimized for high-throughput proteomics. This study features shorter LC gradients and lower sample input to address the growing need for rapid and sensitive proteome analysis. Using a standardized hybrid proteome mixture with defined ratios of Human, Yeast, and E. coli, we generated a comprehensive Data-Dependent and Data-Independent Acquisition (DDA/DIA) dataset across multiple state-of-the-art LC-MS platforms. The updated dataset incorporates the latest acquisition methodologies and extends coverage across an even broader range of data formats, including enhanced ion mobility-enabled and scanning quadrupole-based acquisitions. Our results providea detailed assessment of the impact of technological advancements and demonstrate how shortening LC gradients influence proteome coverage, quantitative precision, and data consistency across instruments