Poster Presentation 24th Annual Lorne Proteomics Symposium 2019

Identifying PTM changes from DIA data – a computational workflow (#116)

Jemma Wu 1 , Conor McCafferty 2 , Thiri Zaw 1 , Vera Ignjatovic 2 3 , Xiaomin Song 1 , Mark Molloy 4 , Dana Pascovici 1
  1. Australian Proteome Analysis Facility, Macquarie University, Sydney, NSW, Australia
  2. Hematology Research Laboratory, Murdoch Childrens Research Institute, Melbourne, VIC, Australia
  3. Department of Paediatrics, The University of Melbourne, Melbourne, VIC, Australia
  4. Kolling Institute of Medical Research, The University of Sydney, St. Leonards, NSW , Australia

Post-translational modifications (PTMs) help regulate protein folding, activity, signalling and their interactions. PTMs are crucial to our understanding of biological functions and are particularly important for clinical research. With the fast improvement in high throughput MS technology such as DIA, large scale PTM studies have emerged, in which thousands of modifications can be found from a single DIA/SWATH experiment. Discovering reliable and biologically interesting PTMs has become a challenging problem, hence detailed and robust PTM workflows are now crucial to further our understanding of PTMs. Here we describe a computational workflow which aims to facilitate the discovery of reliable and relevant PTMs from DIA experiments.

The workflow starts from extracting the SWATH experiment data by using a peptide library containing the identified PTM peptides. The extracted Swath results can be optionally filtered by using FDR pass filtering criteria; then multivariate and differentially expression analysis will be performed on the normalised PTM data. Often hundreds of PTM peptides are found to be differentially expressed, but many of these changes are simply due to the underlying protein’s expression changes. In order to exclude these baseline cases, the relative stoichiometry is calculated and applied as an additional filtering criterion for each PTM. The reliability of the results can be further improved by checking the modification residues against the known residues in public repositories such as SwissProt. We evaluated this workflow with a previously published human plasma study searched with ID focus allowing Biological Modifications using ProteinPilot V5.0. Over 75% of the PTM peptides and 50% of the PTM proteins were filtered out by using both the differentially expressed and relative stoichiometry over threshold criteria. This workflow can be easily extended to PTM studies from other types of MS techniques.