Evaluating Data Acquisition Modes and Fragmentation Types in Label-Free Proteomics on an Orbitrap Ascend Tribrid Mass Spectrometer

Abstract

Proteome-wide abundance profiling entails careful optimization of mass spectrometry acquisition strategies, yet systematic comparisons of acquisition modes and fragmentation types remain limited. Here, we evaluated four distinct data acquisition conditions: data-independent acquisition (DIA) and data-dependent acquisition (DDA), each combined with either higher-energy collisional dissociation (HCD) or collision-induced dissociation (CID). To showcase these strategies, we profiled five human cell lines (HCT116, HEK293T, HeLa, U2OS, and RPE1) in biological triplicate using unfractionated, single-shot injections on a FAIMS-equipped Orbitrap Ascend mass spectrometer. Our results reveal that DIA outperformed DDA in both peptide and protein identification yields across all conditions tested. Within each acquisition mode, HCD provided a modest identification advantage over CID; however, both fragmentation types yielded highly overlapping identifications and equivalent quantitative reproducibility. Furthermore, unsupervised hierarchical clustering and pairwise correlation analyses confirmed that all four conditions generated quantitatively concordant differential abundance measurements. Each data acquisition condition reproduced known cell line-specific protein expression signatures, while quantifying a shared core proteome of 7,213 proteins. Ultimately, these findings support DIA: HCD as the optimal strategy for deep, reproducible proteomics on this platform, while demonstrating that all evaluated acquisition conditions yield consistent quantitative data.