Implementation of a data repository-driven approach for targeted proteomics experiments by multiple reaction monitoring.
Multiple reaction monitoring (MRM), commonly employed for the mass spectrometric detection of small molecules, is rapidly gaining ground in proteomics. Its high sensitivity and specificity makes this targeted approach particularly useful when sample throughput or proteome coverage limits global studies. Existing tools to design MRM assays rely exclusively on theoretical predictions, or combine them with previous observations on the same type of sample. The additional mass spectrometric experimentation this requires can pose significant demands on time and material. To overcome these challenges, a new MRM worksheet was introduced into The Global Proteome Machine database (GPMDB) that provided all of the information needed to design MRM transitions based solely on archived observations made by other researchers in previous experiments. This required replacing the precursor ion intensity by the number of peptide observations, which proved to be an adequate substitute if peptides did not occur in multiple forms. While the absence of collision energy information proved largely inconsequential, successful prediction of unique transitions depended on the type of fragment ion involved. The design of MRM assays for iTRAQ-labeled tryptic peptides obtained from human platelet proteins demonstrated the usefulness of the MRM worksheet also for quantitative applications. This workflow, which relies exclusively on experimental observations stored in data repositories, therefore represents an attractive alternative for the prediction of MRM transitions prior to experimental validation and optimization.
Walsh
Geraldine M
GM
The Biomedical Research Centre, University of British Columbia, Vancouver, Canada.
Lin
Shujun
S
Evans
Daniel M
DM
Khosrovi-Eghbal
Arash
A
Beavis
Ronald C
RC
Kast
Juergen
J
D001792:Blood Platelets / Q000378:metabolism; D001798:Blood Proteins / Q000737:chemistry; D019295:Computational Biology / Q000379:methods; D030562:Databases, Protein; D006801:Humans; D007477:Ions; D013058:Mass Spectrometry / Q000379:methods; D010455:Peptides / Q000737:chemistry; D011506:Proteins / Q000737:chemistry; D020543:Proteome; D040901:Proteomics / Q000295:instrumentation* / Q000379:methods*
D001798:Blood Proteins; D007477:Ions; D010455:Peptides; D011506:Proteins; D020543:Proteome