Software Analysis of Uncorrelated MS1 Peaks for Discovery of Post-Translational Modifications

The goal in proteomics to identify all peptides in a complex mixture has been largely addressed using various LC MS/MS approaches, such as data dependent acquisition, SRM/MRM, and data independent acquisition instrumentation. Despite these developments, many peptides remain unsequenced, often due to low abundance, poor fragmentation patterns, or data analysis difficulties. Many of the unidentified peptides exhibit strong evidence in high resolution MS(1) data and are frequently post-translationally modified, playing a significant role in biological processes. Proteomics Workbench (PWB) software was developed to automate the detection and visualization of all possible peptides in MS(1) data, reveal candidate peptides not initially identified, and build inclusion lists for subsequent MS(2) analysis to uncover new identifications. We used this software on existing data on the autophagy regulating kinase Ulk1 as a proof of concept for this method, as we had already manually identified a number of phosphorylation sites Dorsey, F. C. et al (J. Proteome. Res. 8(11), 5253-5263 (2009)). PWB found all previously identified sites of phosphorylation. The software has been made freely available at http://www.proteomicsworkbench.com . Graphical Abstract ᅟ.

Bioinformatics for LC-MS/MS-based proteomics

Mass spectrometry instrumentation has continued to develop rapidly in the last two decades, enabled in part by advances in microelectronic hardware controllers and computerized control and data acquisition systems. The wealth and complexity of data produced by a modern instrument is such that the data can no longer be analyzed manually. Computerized data analysis has become de rigueur and the bioinformatics field has expanded to provide software applications for all aspects of the data analysis needed by LC-MS/MS. The bioinformatics field is evolving rapidly and software applications are continually being improved or replaced for existing applications as well as developed to support new types of experiments and analysis enabled by modern instrumentation. Entire books have been written on MS data analysis in proteomics but this review will be necessarily brief. In this chapter we will review the bioinformatics software applications available for different LC-MS/MS analysis tasks.