Automated workflow for large-scale selected reaction monitoring experiments

J Proteome Res. 2012 Mar 2;11(3):1644-53. doi: 10.1021/pr200844d. Epub 2012 Feb 10.


Targeted proteomics allows researchers to study proteins of interest without being drowned in data from other, less interesting proteins or from redundant or uninformative peptides. While the technique is mostly used for smaller, focused studies, there are several reasons to conduct larger targeted experiments. Automated, highly robust software becomes more important in such experiments. In addition, larger experiments are carried out over longer periods of time, requiring strategies to handle the sometimes large shift in retention time often observed. We present a complete proof-of-principle software stack that automates most aspects of selected reaction monitoring workflows, a targeted proteomics technology. The software allows experiments to be easily designed and carried out. The steps automated are the generation of assays, generation of mass spectrometry driver files and methods files, and the import and analysis of the data. All data are normalized to a common retention time scale, the data are then scored using a novel score model, and the error is subsequently estimated. We also show that selected reaction monitoring can be used for label-free quantification. All data generated are stored in a relational database, and the growing resource further facilitates the design of new experiments. We apply the technology to a large-scale experiment studying how Streptococcus pyogenes remodels its proteome under stimulation of human plasma.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Automation, Laboratory*
  • Bacterial Proteins / genetics
  • Bacterial Proteins / metabolism
  • Cluster Analysis
  • Culture Media
  • Data Interpretation, Statistical
  • Gene Expression Regulation, Bacterial
  • Humans
  • Principal Component Analysis
  • Proteome / genetics
  • Proteome / metabolism
  • Proteomics
  • ROC Curve
  • Research Design*
  • Software*
  • Streptococcus pyogenes / genetics
  • Streptococcus pyogenes / metabolism
  • Workflow*


  • Bacterial Proteins
  • Culture Media
  • Proteome