A quantitative estimation of the global translational activity in logarithmically growing yeast cells.

von der Haar, Tobias (2008) A quantitative estimation of the global translational activity in logarithmically growing yeast cells. BMC Systems Biology, 2 . ISSN 1752-0509. (Full text available)

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http://dx.doi.org/10.1186/1752-0509-2-87

Abstract

BACKGROUND: Translation of messenger mRNAs makes significant contributions to the control of gene expression in all eukaryotes. Because translational control often involves fractional changes in translational activity, good quantitative descriptions of translational activity will be required to achieve a comprehensive understanding of this aspect of biology. Data on translational activity are difficult to generate experimentally under physiological conditions, however, translational activity as a parameter is in principle accessible through published genome-wide datasets. RESULTS: An examination of the accuracy of genome-wide expression datasets generated for Saccharomyces cerevisiae shows that the available datasets suffer from large random errors within studies as well as systematic shifts in reported values between studies, which make predictions of translational activity at the level of individual genes relatively inaccurate. In contrast, predictions of cell-wide translational activity are possible from such datasets with higher accuracy, and current datasets predict a production rate of about 13,000 proteins per haploid cell per second under fast growth conditions. This prediction is shown to be consistent with independently derived kinetic information on nucleotide exchange reactions that occur during translation, and on the ribosomal content of yeast cells. CONCLUSIONS: This study highlights some of the limitations in published genome-wide expression datasets, but also demonstrates a novel use for such datasets in examining global properties of cells. The global translational activity of yeast cells predicted in this study is a useful benchmark against which biochemical data on individual translation factor activities can be interpreted.

Item Type: Article
Projects: [92] 210 20999
Additional information: Article no. 87
Subjects: Q Science > Q Science (General)
Q Science > QR Microbiology
Divisions: Faculties > Science Technology and Medical Studies > School of Biosciences > Protein Science Group
Depositing User: Tobias von der Haar
Date Deposited: 18 Apr 2009 09:31
Last Modified: 06 Sep 2011 01:38
Resource URI: http://kar.kent.ac.uk/id/eprint/14627 (The current URI for this page, for reference purposes)
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