Scheduled data-independent acquisition mass spectrometry for global proteomics and proximity labeling

Mass spectrometry (MS)-based proteomics often faces challenges with redundant or uninformative tandem MS/MS spectra. Although data-independent acquisition (DIA) MS offers excellent reproducibility, the wide isolation windows used in DIA inevitably generate numerous MS/MS spectra that are not useful and compromise the specificity of peptide analysis. Here, we explored the possibility of scheduling DIA exclusively on useful peptides identified in a preceding data-dependent acquisition (DDA) survey run. We established and optimized a Scheduled-DIA method to reduce duty cycle and improve protein identification and quantification compared to the traditional static DIA method. We applied the Scheduled-DIA method to both global and proximity labeling proteomics. Lysosomal proximity labeling experiments particularly benefited from the Scheduled-DIA method, which increased sensitivity for identifying and quantifying key lysosomal membrane proteins and lysosomal interactors. To summarize, Scheduled-DIA is an alternative and useful strategy for acquiring high-quality DIA data for proteomics.