Improvements in Data-Dependent Acquisition for Enhanced Protein Identification

Comprehensive proteome analysis can be very challenging due to complexity and range of protein concentrations. Techniques such as 2D LC, pI-based fractionation and gel electrophoresis are typically employed to increase separation efficiency as a strategy for obtaining more peptide MS/MS spectra and thus increasing the number of proteins identified. In data-dependent mode, efficient and comprehensive protein identification depends on several conditions during the acquisition, among them: the number of precursors examined per unit time, selection of the most promising precursors for fragmentation, and application of the appropriate fragmentation conditions to yield the highest quality product ion spectrum during acquisition. This work describes changes to the precursor selection and fragmentation steps to select the precursors most likely to produce good quality peptide MS/MS spectra, and to increase the quality of those spectra.