High-throughput phenotypic profiling of gene–environment interactions by quantitative growth curve analysis in Saccharomyces cerevisiae

Cell-based assays are widely used in high-throughput screening to determine the effects of toxicants and drugs on their biological targets. To enable a functional genomics modeling of gene–environment interactions, quantitative assays are required both for gene expression and for the phenotypic resp...

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Veröffentlicht in:Analytical biochemistry 2004-04, Vol.327 (1), p.23-34
Hauptverfasser: Weiss, Andrew, Delproposto, James, Giroux, Craig N
Format: Artikel
Sprache:eng
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Zusammenfassung:Cell-based assays are widely used in high-throughput screening to determine the effects of toxicants and drugs on their biological targets. To enable a functional genomics modeling of gene–environment interactions, quantitative assays are required both for gene expression and for the phenotypic responses to environmental challenge. To address this need, we describe an automated high-throughput methodology that provides phenotypic profiling of the cellular responses to environmental stress in Saccharomyces cerevisiae. Standardized assay conditions enable the use of a single metric value to quantify yeast microculture growth curves. This assay format allows precise control of both genetic and environmental determinants of the cellular responses to oxidative stress, a common mechanism of environmental insult. These yeast-cell-based assays are validated with hydrogen peroxide, a simple direct-acting oxidant. Phenotypic profiling of the oxidative stress response of a yap1 mutant strain demonstrates the mechanistic analysis of genetic susceptibility to oxidative stress. As a proof of concept for analysis of more complex gene–environment interactions, we describe a combinatorial assay design for phenotypic profiling of the cellular responses to tert-butyl hydroperoxide, a complex oxidant that is actively metabolized by its target cells. Thus, the yeast microculture assay format supports comprehensive applications in toxicogenomics.
ISSN:0003-2697
1096-0309
DOI:10.1016/j.ab.2003.12.020