Universal and Confident Phosphorylation Site Localization Using phosphoRS

Abstract

An algorithm for the assignment of phosphorylation sites in peptides is described. The program uses tandem mass spectrometry data in conjunction with the respective peptide sequences to calculate site probabilities for all potential phosphorylation sites. Tandem mass spectra from synthetic phosphopeptides were used for optimization of the scoring parameters employing all commonly used fragmentation techniques. Calculation of probabilities was adapted to the different fragmentation methods and to the maximum mass deviation of the analysis. The software includes a novel approach to peak extraction, required for matching experimental data to the theoretical values of all isoforms, by defining individual peak depths for the different regions of the tandem mass spectrum. Mixtures of synthetic phosphopeptides were used to validate the program by calculation of its false localization rate versus site probability cutoff characteristic. Notably, the empirical obtained precision was higher than indicated by the applied probability cutoff. In addition, the performance of the algorithm was compared to existing approaches to site localization such as Ascore. In order to assess the practical applicability of the algorithm to large data sets, phosphopeptides from a biological sample were analyzed, localizing more than 3000 nonredundant phosphorylation sites. Finally, the results obtained for the different fragmentation methods and localization tools were compared and discussed.

Quantitative global phosphoproteomics of human umbilical vein endothelial cells after activation of the Rap signaling pathway

“…A decoy database search was enabled. For phosphorylation site localization we used the PhosphoRS algorithm, 32 which is integrated in Proteome Discoverer 1.3. For peptide quantitation, a dimethyl-based quantitation method with a mass precision requirement of 2 ppm for consecutive precursor measurements was chosen.…”

“…This algorithm was generated, validated and optimized based on the fragmentation spectra of a training set of 150 synthetic phosphopeptides with known phosphorylated residues, which were selected as a representative reflection of phosphorylated peptides present in any phosphoproteome. 32 We define an unambiguously localized phosphopeptide, hereafter called a Class I phosphopeptide, as a phosphopeptide that possesses a PhosphoRS site probability of at least 75% for each of its phosphorylation sites. A phosphosite was designated Class I if its own PhosphoRS site probability was at least 75%, independent of the presence of another phosphosite in the same PSM that did not comply to this criterion.…”

PHOTOSYSTEM II SUBUNIT R Is Required for Efficient Binding of LIGHT-HARVESTING COMPLEX STRESS-RELATED PROTEIN3 to Photosystem II-Light-Harvesting Supercomplexes in Chlamydomonas reinhardtii

“…Subscript numbers indicate positions of phosphorylation sites within the unprocessed polypeptide. Phosphorylation site validation was done with phosphoRS (Taus et al, 2011 diminished PSII quantum efficiency and decreased rates of oxygen evolution after 24 h of HL (Figs. 3 and 8).…”

“…Peptide identification and determination of false discovery rates were carried out as described (Höhner et al, 2013) with the following modifications: oxidation of Met and phosphorylation of Ser, Thr, and Tyr were allowed as variable modifications during the database search. Phosphorylation site assignments were validated by phosphoRS (Taus et al, 2011) with fragment ion mass accuracy set to 0.5 D.…”

Exploring the potential of public proteomics data

“…Finding and localizing PTMs are essential tasks in proteomics data analysis 97, and for this purpose multiple PTM localization scores have been developed 98, for example A‐score 99, PTM score 100, MD‐score 101, phosphoRS 102, and D‐score 103. Setting a threshold for these scores is, however, challenging, and solutions have only recently been established 104, 105.…”