Confident and sensitive phosphoproteomics using combinations of collision induced dissociation and electron transfer dissociation

We present a workflow using an ETD-optimised version of Mascot Percolator and a modified version of SLoMo (turbo-SLoMo) for analysis of phosphoproteomic data. We have benchmarked this against several database searching algorithms and phosphorylation site localisation tools and show that it offers highly sensitive and confident phosphopeptide identification and site assignment with PSM-level statistics, enabling rigorous comparison of data acquisition methods. We analysed the Plasmodium falciparum schizont phosphoproteome using for the first time, a data-dependent neutral loss-triggered-ETD (DDNL) strategy and a conventional decision-tree method. At a posterior error probability threshold of 0.01, similar numbers of PSMs were identified using both methods with a 73% overlap in phosphopeptide identifications. The false discovery rate associated with spectral pairs where DDNL CID/ETD identified the same phosphopeptide was
Graphical abstract
Highlights • We report and benchmark a data analysis pipeline for phosphoproteomic data analysis. • Combined use of Mascot Percolator and turbo-SLoMo to compare fragmentation methods • CID and ETD fragmentation for phosphorylation site identification • Demonstrate the utility of data-dependent neutral loss triggered ETD fragmentation • High confidence of phosphoproteomic analysis using ETD/CID spectral pairs