Regulated exit from cell division and initiation of a non-proliferative quiescent state is a criticl requirement in all organisms. Failure to maintain quiescence and inappropriate reinitiation of proliferative cell growth underlies many human cancers. Conversely, subpopulations of quiescent tumor cells may play critical roles in resistance to chemotherapy and tumor recurrence as cancer drugs typically target processes active during cell growth. Similarly, quiescent pathogenic microbes are frequently insensitive to standard drug treatments. We will use the single-celled eukaryotic microbes, Saccharomyces cerevisiae (budding yeast) and Schizosaccharomyces pombe (fission yeast) to identify the conserved networks that regulate cell quiescence. Microbes and some tumor cells enter quiescent states in response to nutrient depletion and are able to survive for prolonged periods of nutrient starvation. Our preliminary studies demonstrate that initiation of quiescence in response to defined nutrient starvation is actively regulated by conserved signaling pathways including the TORC1, Ras/Protein kinase A (PKA) and AMPK pathways.
In Aim 1 we will define the conserved genetic program that controls cell quiescence by quantifying the defect in quiescence attributable to loss of function mutations in each gene in both budding and fission yeast in three quiescence-inducing conditions: carbon, nitrogen and phosphorous starvation. We will complement this genetic approach with studies of the phenotypic hallmarks of quiescence in wildtype and mutant cells to identify processes defective in quiescent mutants.
In Aim 2 we will study how signaling pathways integrate environmental information to initiate the quiescence program by identifying targets of quiescence-regulating pathways and interactions between pathways using genome-wide genetic interaction mapping in quiescent conditions in both species. These experiments will allow us to identify conserved functional interactions that enable the cell to initiate quiescence n response to specific pro-quiescence signals while simultaneously receiving pro-growth signals that activate parallel pathways. We hypothesize that one means of coordinating signaling pathways is by dynamic subcellular localization of their components and we will test this hypothesis using mutants in which signaling components are mislocalized.
In Aim 3 we will quantify variation in mRNA synthesis and degradation rates as cells enter quiescence using in vivo metabolic labeling of mRNAs coupled with RNA-Seq. We will use this method to test whether cells alter the stability of specific transcripts as cell growth slows and they enter quiescence. We will then identify conserved determinants of mRNA degradation variation using computational methods. By focusing on conserved signaling pathways and cellular processes that regulate quiescence we will enhance our understanding of quiescence in both normal and diseased human cells as well as microbial pathogens. A detailed understanding of cell quiescence will ultimately enable new therapeutic strategies that specifically target quiescent cells in a variety of pathological settings including cancer and microbial infections.

Public Health Relevance

Most cells exist in a non-proliferative, quiescent state that frequently results in generalized dru resistance of human tumor cells and pathogenic microbes. Our understanding of the regulation of quiescence is poor. We will identify genes, interactions and post-transcriptional regulation required for quiescence providing valuable insight into pathological conditions including cancer and microbial infection.

Agency
National Institute of Health (NIH)
Type
Research Project (R01)
Project #
5R01GM107466-02
Application #
8727085
Study Section
Genomics, Computational Biology and Technology Study Section (GCAT)
Program Officer
Maas, Stefan
Project Start
Project End
Budget Start
Budget End
Support Year
2
Fiscal Year
2014
Total Cost
Indirect Cost
Name
New York University
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
City
New York
State
NY
Country
United States
Zip Code
10012
Gresham, David; Hong, Jungeui (2015) The functional basis of adaptive evolution in chemostats. FEMS Microbiol Rev 39:16-Feb
Robinson, David G; Chen, Wei; Storey, John D et al. (2014) Design and analysis of Bar-seq experiments. G3 (Bethesda) 4:11-8
Hong, Jungeui; Gresham, David (2014) Molecular specificity, convergence and constraint shape adaptive evolution in nutrient-poor environments. PLoS Genet 10:e1004041
Neymotin, Benjamin; Athanasiadou, Rodoniki; Gresham, David (2014) Determination of in vivo RNA kinetics using RATE-seq. RNA 20:1645-52
Ma, Sisi; Kemmeren, Patrick; Gresham, David et al. (2014) De-novo learning of genome-scale regulatory networks in S. cerevisiae. PLoS One 9:e106479