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

Recent advances in liquid chromatography–mass spectrometry (LC-MS) have accelerated the adoption of high-throughput workflows that deliver deep proteome coverage using minimal sample amounts. This trend is largely driven by single-cell proteomics, where sensitivity and reproducibility are essential. Here, we extend our previous benchmark dataset (PXD028735) that was generated using next-generation LC-MS platforms optimized for rapid proteome analysis. With shorter LC gradients and lower sample amounts, we generated an extensive DDA/DIA dataset on a standardized human-yeast-E. coli hybrid proteome. This new dataset includes data acquired by the Orbitrap Astral, which combines an Orbitrap with a time-of-flight (TOF) mass analyzer, and features new scanning quadrupole-based implementations, extending coverage across different instruments and acquisition strategies. Our comprehensive evaluation highlights how technological advances and reduced LC gradients affect proteome depth, quantitative precision, and cross-instrument consistency. The release of this benchmark dataset via ProteomeXchange (PXD070049), allows for the acceleration of cross-platform algorithm development, enhance data mining strategies, and support the continued standardization of short-gradient, high-throughput LC-MS-based proteomics.