Cellular stress results when external conditions or internal defects perturb cellular homeostasis. If left unattended, this stress can dramatically alter normal physiology, causing either cell death or rampant growth without normal control mechanisms. Cells therefore have intricate signaling networks that integrate and transmit the proper signals to mediate a multi-faceted response. These responses often involve coordinated changes in cell-cycle progression, gene expression, protein localization and function, and metabolism. How cells orchestrate multiple downstream processes is poorly understood. Furthermore, many of the players in this important regulatory network, and the interactions between them, remain unknown. This proposal aims to elucidate the complex global signaling network that orchestrates stress responses in the model eukaryote Saccharomyces cerevisiae. The work will apply mutant transcriptome profiling, phosphoproteomic analysis, computational biology, and genetics and molecular biology. A key innovation is generation of functional genomic and proteomic data collected under stress conditions, to aid in the computational network inference from available large-scale yeast datasets.
Aim 1 will refine and apply an integer linear programming approach that takes transcriptome profiles and functional data to infer the global regulatory network that coordinates genomic expression after osmotic or DTT reductive stress. Combined with molecular validation of the network, the end result will be a detailed, directional global network of signaling molecule that coordinate genomic expression in response to different stresses. Comparing and contrasting the responses to two distinct stressors will reveal condition-specific regulators and common players in the network.
Aim 2 will take a complementary approach to interrogate phospho-proteomic networks. Quantitative changes in the phospho-proteome will be identified by mass spectrometry, in wild-type and mutant cells lacking implicated kinases as cells respond to osmotic or DTT stress. The resulting phospho-networks will overlap with the signaling networks from Aim 1 but will include unique regulators of diverse physiological processes. Integrating the results from both aims will present a unified view of the signaling network that coordinates gene expression, protein phosphorylation, and physiological responses to several conditions. Together, this work will provide many new insights into stress biology and signaling, by identify new regulators of eukaryotic stress responses, uncovering the connections between them, and illuminating the mechanisms of network rewriting and information flow that coordinate stress responses. Because many yeast signaling proteins have human orthologs linked to disease, these results will provide an important backdrop for directed study in human cells.

Public Health Relevance

The complex signaling network that coordinates stress responses in yeast is highly conserved in humans and linked to a broad array of human diseases. Therefore, the results of this proposal will provide important information that is directly applicable to humans and disease biology. This information will provide a strong foundation for understanding, and eventually modulating, stress resistance for human health.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM083989-07
Application #
8644804
Study Section
Genomics, Computational Biology and Technology Study Section (GCAT)
Program Officer
Reddy, Michael K
Project Start
2008-05-01
Project End
2017-04-30
Budget Start
2014-05-01
Budget End
2015-04-30
Support Year
7
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of Wisconsin Madison
Department
Genetics
Type
Earth Sciences/Resources
DUNS #
City
Madison
State
WI
Country
United States
Zip Code
53715
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Gasch, Audrey P; Payseur, Bret A; Pool, John E (2016) The Power of Natural Variation for Model Organism Biology. Trends Genet 32:147-154
Ho, Yi-Hsuan; Gasch, Audrey P (2015) Exploiting the yeast stress-activated signaling network to inform on stress biology and disease signaling. Curr Genet 61:503-11

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