4.5 Article

Implementation of a data repository-driven approach for targeted proteomics experiments by multiple reaction monitoring

期刊

JOURNAL OF PROTEOMICS
卷 72, 期 5, 页码 838-852

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.jprot.2008.11.015

关键词

Tandem mass spectrometry; Multiple reaction monitoring; Targeted proteomics; Data repository; Platelets

资金

  1. Canadian Blood Services
  2. National Institutes of Health [U24 CA126477-01]
  3. Canadian Institutes of Health Research/Heart and Stroke Foundation of Canada (CIHR/HSFC)
  4. Michael Smith Foundation for Health Research (MSFHR)

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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. (C) 2008 Elsevier B.V. All rights reserved.

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