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Quantitative analysis of SILAC data sets using spectral counting
Author(s) -
Parker Sarah J.,
Halligan Brian D.,
Greene Andrew S.
Publication year - 2010
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.200900684
Subject(s) - stable isotope labeling by amino acids in cell culture , quantitative proteomics , proteomics , mass spectrometry , chemistry , quantitative analysis (chemistry) , label free quantification , chromatography , biological system , computational biology , biology , biochemistry , gene
We report a new quantitative proteomics approach that combines the best aspects of stable isotope labeling of amino acids in cell culture (SILAC) labeling and spectral counting. The SILAC peptide count ratio analysis (SPeCtRA, http://proteomics.mcw.edu/visualize) method relies on MS(2) spectra rather than ion chromatograms for quantitation and therefore does not require the use of high mass accuracy mass spectrometers. The inclusion of a stable isotope label allows the samples to be combined before sample preparation and analysis, thus avoiding many of the sources of variability that can plague spectral counting. To validate the SPeCtRA method, we have analyzed samples constructed with known ratios of protein abundance. Finally, we used SPeCtRA to compare endothelial cell protein abundances between high (20 mM) and low (11 mM) glucose culture conditions. Our results demonstrate that SPeCtRA is a protein quantification technique that is accurate and sensitive as well as easy to automate and apply to high-throughput analysis of complex biological samples.