| Literature DB >> 25476245 |
Christopher M Colangelo1, Gordana Ivosev, Lisa Chung, Thomas Abbott, Mark Shifman, Fumika Sakaue, David Cox, Robert R Kitchen, Lyle Burton, Stephen A Tate, Erol Gulcicek, Ron Bonner, Jesse Rinehart, Angus C Nairn, Kenneth R Williams.
Abstract
We present a comprehensive workflow for large scale (>1000 transitions/run) label-free LC-MRM proteome assays. Innovations include automated MRM transition selection, intelligent retention time scheduling that improves S/N by twofold, and automatic peak modeling. Improvements to data analysis include a novel Q/C metric, normalized group area ratio, MLR normalization, weighted regression analysis, and data dissemination through the Yale protein expression database. As a proof of principle we developed a robust 90 min LC-MRM assay for mouse/rat postsynaptic density fractions which resulted in the routine quantification of 337 peptides from 112 proteins based on 15 observations per protein. Parallel analyses with stable isotope dilution peptide standards (SIS), demonstrate very high correlation in retention time (1.0) and protein fold change (0.94) between the label-free and SIS analyses. Overall, our method achieved a technical CV of 11.4% with >97.5% of the 1697 transitions being quantified without user intervention, resulting in a highly efficient, robust, and single injection LC-MRM assay.Entities:
Keywords: Multiple reaction monitoring; Postsynaptic density; Proteomics database; Targeted proteomics; Technology
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Year: 2015 PMID: 25476245 PMCID: PMC4698340 DOI: 10.1002/pmic.201400353
Source DB: PubMed Journal: Proteomics ISSN: 1615-9853 Impact factor: 3.984