Integrative multi-layer workflow for quantitative analysis of post-translational modifications

Abstract

Novel algorithms based on ultratolerant database searching have paved the way for comprehensive analysis of all possible post-translational modifications (PTM) that can be detected by mass spectrometry-based proteomics, obviating their prior knowledge. These tools together with novel quantitative statistical models allow hypothesis-free approaches to study the role and impact of PTM on biological systems. However, interpretation of this information from a pathophysiological perspective is challenging due to the huge amounts of PTM data, the existence of chemical, structural, and statistical artifacts and the lack of dedicated tools for their analysis. Here we propose a novel integrative workflow that automatically captures several layers of PTM-related information, including variations in trypsin efficiency, zonal changes, specific PTM changes and hypermodified regions, allowing advanced control of artefacts and coherent and comprehensive interpretation of PTM data. We show the performance of the new workflow by reanalyzing proteomics data from animal models of mitochondrial heteroplasmy and ischemia/reperfusion, revealing relevant PTM information not previously detectable, including consistent detection of novel oxidative modifications in Met and Cys residues from raw proteomics data. The workflow is available through the application PTM-compass.