The long-term goal of this research is to gain a quantitative understanding of the regulation of the eukaryotic cell cycle, one of the most fundamental and complex biological processes. The specific goal of this proposal is to construct, analyze and validate mathematical models for several key cell cycle checkpoints and switches as well as for the entire cell cycle network in the budding yeast Saccharomyces cerevisiae, through a close coupling between mathematical modeling and quantitative experimentation. Cell cycle checkpoints and switches play essential roles in ensuring precise and robust execution of the cell cycle machinery. Defects in them, e.g. due to genetic perturbations, can lead to inappropriate cell proliferation or errors in chromosome segregation, which are commonly associated with tumorigenesis. This work will contribute to a deeper, quantitative and systems level understanding of the yeast cell cycle regulation, the studies of which have profoundly impacted on our knowledge about cell cycle control in higher organisms and on the mechanisms of cancer. Concepts and methods from dynamical systems theory will be applied here to analyze and comprehend this complex system. Quantitative single-cell assays using microfluidic devices will be set up to generate data for the mathematical model and to test the model predictions.
The specific aims are: (1) Global computational analyses of the yeast cell cycle network - Systematic computational analyses on the yeast cell cycle network will be carried out to investigate the global dynamic properties and the structural stability of the system to identify what kinds of perturbations the system is robust to and what is not. (2) Quantitative study of the G1 checkpoint as a fixed point - Computational models and quantitative experiments will be used together to investigate the stability of the G1 arrest and the network perturbations that can increase or decrease this stability. The hypothesis that the checkpoint is a dynamical system's fixed point will be tested. (3) Quantitative study of the G1/S switch - Computational models and quantitative experiments will be used together to investigate the switch-like behavior in S-phase entry. The role of the circuit topology in ensuring a robust switching behavior will be studied. (4) Quantitative study of the spindle assembly checkpoint and the M/A switch - Computational modeling and quantitative experiments will be used together to investigate the stability of the checkpoint arrest and the switching dynamics, focusing on the respective and synergistic roles of the multiple feedback loops.

Public Health Relevance

This work will provide a new mathematical framework to quantitatively understand the complexity in the control and regulation of cell division cycle. Uncontrolled cell division is a hallmark of cancer. This work will help us to understand why certain genetic mutations can lead to cancer and may suggest novel therapeutic strategies.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM097115-03
Application #
8476233
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Hamlet, Michelle R
Project Start
2011-08-08
Project End
2015-05-31
Budget Start
2013-06-01
Budget End
2014-05-31
Support Year
3
Fiscal Year
2013
Total Cost
$370,619
Indirect Cost
$122,786
Name
University of California San Francisco
Department
Pharmacology
Type
Schools of Pharmacy
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94143
Stern, Adi; Yeh, Ming Te; Zinger, Tal et al. (2017) The Evolutionary Pathway to Virulence of an RNA Virus. Cell 169:35-46.e19
Liu, Xili; Wang, Xin; Yang, Xiaojing et al. (2015) Reliable cell cycle commitment in budding yeast is ensured by signal integration. Elife 4:
Lu, Dan; Girard, Juliet R; Li, Weihan et al. (2015) Quantitative framework for ordered degradation of APC/C substrates. BMC Biol 13:96
Stern, Adi; Bianco, Simone; Yeh, Ming Te et al. (2014) Costs and benefits of mutational robustness in RNA viruses. Cell Rep 8:1026-36
Lu, Dan; Hsiao, Jennifer Y; Davey, Norman E et al. (2014) Multiple mechanisms determine the order of APC/C substrate degradation in mitosis. J Cell Biol 207:23-39
Li, Zhiyuan; Bianco, Simone; Zhang, Zhaoyang et al. (2013) Generic Properties of Random Gene Regulatory Networks. Quant Biol 1:253-260
Yang, Xiaojing; Jost, Anna Payne-Tobin; Weiner, Orion D et al. (2013) A light-inducible organelle-targeting system for dynamically activating and inactivating signaling in budding yeast. Mol Biol Cell 24:2419-30
Yang, Xiaojing; Lau, Kai-Yeung; Sevim, Volkan et al. (2013) Design principles of the yeast G1/S switch. PLoS Biol 11:e1001673