Comparison of Alternative MS/MS and Bioinformatics Approaches for Confident Phosphorylation Site Localization

Over the past years, phosphoproteomics has advanced to a prime tool in signaling research. Since then, an enormous amount of information about <i>in vivo</i> protein phosphorylation events has been collected providing a treasure trove for gaining a better understanding of the molecular processes involved in cell signaling. Yet, we still face the problem of how to achieve correct modification site localization. Here we use alternative fragmentation and different bioinformatics approaches for the identification and confident localization of phosphorylation sites. Phosphopeptide-enriched fractions were analyzed by multistage activation, collision-induced dissociation and electron transfer dissociation (ETD), yielding complementary phosphopeptide identifications. We further found that MASCOT, OMSSA and Andromeda each identified a distinct set of phosphopeptides allowing the number of site assignments to be increased. The postsearch engine SLoMo provided confident phosphorylation site localization, whereas different versions of PTM-Score integrated in MaxQuant differed in performance. Based on high-resolution ETD and higher collisional dissociation (HCD) data sets from a large synthetic peptide and phosphopeptide reference library reported by Marx et al. [<i>Nat. Biotechnol</i>. <b>2013</b>, <i>31</i> (6), 557–564], we show that an Andromeda/PTM-Score probability of 1 is required to provide an false localization rate (FLR) of 1% for HCD data, while 0.55 is sufficient for high-resolution ETD spectra. Additional analyses of HCD data demonstrated that for phosphotyrosine peptides and phosphopeptides containing two potential phosphorylation sites, PTM-Score probability cutoff values of <1 can be applied to ensure an FLR of 1%. Proper adjustment of localization probability cutoffs allowed us to significantly increase the number of confident sites with an FLR of