University of Wisconsin System
Grant: $185,155 - National Institutes of Health - Jul. 16, 2009
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Award Description: DESCRIPTION (provided by applicant): All organisms must protect their internal system from cellular stress. Whether stress arises from external toxins or mutation and disease, cells must sensitively monitor stress signals and mount the appropriate responses to maintain internal homeostasis. Despite the importance of stress defense, much remains unknown about the mechanisms eukaryotes use to survive stressful situations. Functional genomics has uncovered functions for many genes in various genomes, largely by characterizing gene function under standard conditions. However, a substantial fraction of genes remains uncharacterized, and many of these are likely to be involved in stress defense and thus have not been uncovered through traditional studies. This proposal will use high-throughput functional genomics, genomic expression analysis, computational biology, and techniques in genetics and biochemistry to identify and characterize genes involved in stress defense in yeast. Aim 1 will exploit two new phenotypes related to stress defense to uncover novel genes involved in eukaryotic stress survival. The first is a phenomenon known as `acquired stress resistance', in which cells exposed to a small dose of one stress become resistant to an otherwise lethal dose of a different stress. The second is a phenomenon in which cells retain a `memory' of stress resistance that persists for many generations after mild-stress treatment, even after the mild stress has been removed. We will use these phenotypes in high-throughput selections to identify yeast deletion mutants that cannot acquire or retain resistance to severe stress after mild-stress treatment. Identified genes, as well as known regulators of acquired stress resistance, will be characterized to define their precise roles in these phenomena. Cells respond to stress with a multi-facetted response. This response, including reorganization of genomic expression, is coordinated by a complex signaling network that responds to stress. Aim 2 will elucidate the intricate stress-activated signaling network in yeast that orchestrates genomic expression responses to stress. Regulators of stress-dependent genes will be identified by screening the yeast-deletion library for mutants unable to induce expression upon stress treatments. Identified regulators and various known network components will be organized into a putative signaling network, using numerous computational approaches. This network will be subsequently dissected and refined based on genomic, genetic, and biochemical studies. These experiments will help to elucidate the complex stress-activated signaling network in yeast, which serves as an excellent model for such networks in humans and other organisms, while developing computational approaches that are likely to advance this area of biology. As many of these responses are conserved in humans, these results will foster stress minimization and disease prevention in human medicine. Project Relevance: Many stress-defense mechanisms used by yeast are conserved in humans, and therefore the results of this proposal will provide a strong foundation for understanding, and eventually modulating, stress resistance for human health. These results will have broad application, from minimizing debilitating side effects of chemotherapy, to reducing trauma inflicted by invasive surgery, heart attacks and strokes, to preventing cancer. Furthermore, understanding how yeast sense and respond to stress is an excellent model for how human cells respond to analogous cellular stresses.
Project Description: See Award Description
Jobs Summary: The University of Wisconsin - Madison appreciates the American Recovery and Reinvestment Act (ARRA) funding. This additional funding has allowed us to retain employees and create new jobs. The job classifications that have been created or retained for this award are: Research Support positions. (Total jobs reported: 1)
Project Status: Less Than 50% Completed
This award's data was last updated on Jul. 16, 2009. Help expand these official descriptions using the wiki below.
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