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Quantitative analysis of SILAC data sets using spectral counting.


ABSTRACT: 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.

SUBMITTER: Parker SJ 

PROVIDER: S-EPMC4326228 | biostudies-literature | 2010 Apr

REPOSITORIES: biostudies-literature

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Quantitative analysis of SILAC data sets using spectral counting.

Parker Sarah J SJ   Halligan Brian D BD   Halligan Brian D BD   Greene Andrew S AS  

Proteomics 20100401 7


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 bef  ...[more]

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