Data-driven Optimization of the Chromatographic Peak Sampling in dia-PASEF for Optimal Discovery Workflows

Bottom-up proteome approaches by mass spectrometry aim at identifying and quantifying all proteins present to fully access a sample’s physiological state. Such approaches require instrumentation methods that maximize the identification rates while retaining high quantitative precision and accuracy.

One of the key metrics of an analytical method that determines its precision and accuracy is the sampling of chromatographic peaks, commonly described as data points per peak (DPPP). The DPPP are a combination of the cycle time and analytical peak width and are defined by the PASEF cycle numbers on timsTOF instruments.

Lately, the optimum of DPPP in LC-MS methods has been a subject of controversy. Here, we aimed at empirically determining the optimal DPPP for short-gradient timsTOF acquisitions for discovery workflows.