J Proteome Res
BioCentrum-DTU, Technical University of Denmark, Kgs. Lyngby, Denmark.
Published: January 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.
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http://dx.doi.org/10.1021/pr700580m | DOI Listing |
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University of Connecticut, Department of Marine Sciences, 1080 Shennecossett Road, Groton, CT, USA. Electronic address:
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Department of Chemistry and Biochemistry, Old Dominion University, Norfolk, Virginia 23529, United States.
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Department of Earth and Environmental Sciences, Ludwig-Maximilians-Universität München, Richard-Wagner Str. 10, 80333 Munich, Germany.
Studies on microbial sulfur cycling in marine sediment have primarily centered on the cycling of inorganic sulfur. The microbial diversity underlying the cycling of organosulfur compounds is largely unexplored. In this study, we present the first quantification of dissolved organic sulfur (DOS) microbial assimilation in marine surface sediments using C-DOS quantitative DNA stable isotope probing (qSIP).
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Inner Mongolia Key Laboratory of River and Lake Ecology, School of Ecology and Environment, Inner Mongolia University, Hohhot, 010021, China.
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Research Center for Eco - Environment Sciences, Chinese Academy of Sciences, Beijing 100085, China.
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