Enhancing protein discoverability by data independent acquisition assisted by ion mobility mass spectrometry

Abstract

Ion mobility (IM) mass spectrometry allows conducting data independent acquisition (DIA) where all ions entering the instrument are fragmented based on their drift time. In this work, DIA operational parameters were first optimized using a design of experiments. The optimization of data treatment involved a smoothing algorithm of the IM dimension, which increased the number of identified peptides. Then, classical DDA and IM-based DIA were compared injecting increasing amounts of a complex proteome digest (E. coli). Results revealed that compared to DDA, DIA allowed to identify from 2 to 3.3 times more proteins, depending on the injected quantity. To evaluate proteome coverage, endogenous proteins in E. coli cells were sorted by abundance deciles. A large majority of the proteins uniquely observed in DDA were part of the 10% most abundant protein groups. Interestingly, owing to the absence of ion-picking algorithm, DIA allowed to identify proteins coming from a broader concentration range therefore greatly improving proteome coverage. Furthermore, ion mobility separation improved coverage by separating co-eluting peptides. Physicochemical properties of peptides uniquely detected by DIA or DDA were also compared using supervised and unsupervised multivariate analysis. As a result, peptides having a higher mass and being relatively hydrophobic were significantly more identified in DIA. Finally, semi-quantitative performance of both methods was investigated and proved to be comparable, except that DIA demonstrated a better sensitivity than DDA. As a conclusion, we demonstrated in this study that both acquisition modes provide complementary information about the proteome under investigation.