Characterization of Global Yeast Quantitative Proteome Data Generated from the Wild-Type and Glucose Repression Saccharomyces cerevisiae Strains: The comparison of two Quantitative Methods
Journal article, 2008

The quantitative proteomic analysis of complex protein mixtures is emerging as a technically challenging but viable systems-level approach for studying cellular function. This study presents a large-scale comparative analysis of protein abundances from yeast protein lysates derived from both wild-type yeast and yeast strains lacking key components of the Snf1 kinase complex. Four different strains were grown under well-controlled chemostat conditions. Multidimensional protein identification technology followed by quantitation using either spectral counting or stable isotope labeling approaches was used to identify relative changes in the protein expression levels between the strains. A total of 2388 proteins were relatively quantified, and more than 350 proteins were found to have significantly different expression levels between the two strains of comparison when using the stable isotope labeling strategy. The stable isotope labeling based quantitative approach was found to be highly reproducible among biological replicates when complex protein mixtures containing small expression changes were analyzed. Where poor correlation between stable isotope labeling and spectral counting was found, the major reason behind the discrepancy was the lack of reproducible sampling for proteins with low spectral counts. The functional categorization of the relative protein expression differences that occur in Snf1-deficient strains uncovers a wide range of biological processes regulated by this important cellular kinase.

proteomics

AMP-activated kinase

CenSus

MudPIT

15N

Snf4

mass spectrometry

Author

Renata Usaite

James Wohlschlegel

John D. Venable

Sung K. Park

Jens B Nielsen

Lisbeth Olsson

John R. Yates

Journal of Proteome Research

1535-3893 (ISSN) 1535-3907 (eISSN)

Vol. 266 7 266-275

Subject Categories

Industrial Biotechnology

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Created

10/10/2017