Incorporating a phosphopeptide enrichment step prior to LC-MS (liquid chromatography - mass spectrometry) enhances the sensitivity of detection for the treatment effect on the abundance of phosphorylated proteins (Cheng et al. 2018). However, the raw data are produced at such scale that quantitative data processing is quite cumbersome, so that very few labs are capable of analyzing phosphoproteome data without collaborations with laboratories specialized in the field or with core facilities at considerable cost.
To alleviate these bottlenecks, we have established Galaxy workflows comprising an existing MaxQuant wrapper and new wrappers for subsequent steps: (1) phosphorylation-site localization, (2) mapping of phosphopeptides to proteins and to known phosphorylation and substrate motifs, and (3) ANOVA. The process of wrapping preexisting scripts occasioned the review and improvement of the sequence-search algorithm's efficiency, substantially reducing the time required to execute the pipeline. An additional Kinome-Set Enrichment Analysis module is in development. This pipeline will be made available for deployment to almost any Galaxy instance allowing users at other institutions to analyze phosphoproteomic datasets.
Cheng, L. C., Li, Z., Graeber, T. G., Graham, N. A., & Drake, J. M. (2018). Phosphopeptide Enrichment Coupled with Label-free Quantitative Mass Spectrometry to Investigate the Phosphoproteome in Prostate Cancer. Journal of Visualized Experiments, (138). https://doi.org/10.3791/57996
