The cell cycle is the process by which a growing cell replicates its genome and partitions the two copies of each chromosome to two daughter cells at division. It is of utmost importance to the perpetuation of life that these processes of replication (DNA synthesis) and partitioning (mitosis) be carried out with great fidelity. In eukaryotic cells, DNA synthesis (S phase) and mitosis (M phase) are separated in time by two gaps (G1 and G2). Proper alternation of S phase and M phase is enforced by `checkpoints' that block progression through the cell cycle if the genomic integrity of the cell is compromised in any way. For example, if DNA is damaged in G1 phase a checkpoint blocks progression into S phase until the damage can be repaired. If replicated chromosomes are not properly aligned on the mitotic spindle, a different checkpoint blocks progression into anaphase (the phase of sister chromatid separation) until all sister chromatids are properly attached to opposite poles of the spindle. Checkpoints are able to block cell cycle progression by sending a STOP signal to the molecular mechanisms that govern specific cell-cycle transitions (G1-S, G2-M, and M-G1). The molecular mechanisms that govern each of these transitions have a peculiar property called `bistability.' Under physiological conditions, the control mechanism can persist indefinitely in either of two characteristic states: the OFF state, which corresponds to holding the cell cycle in the pre-transition phase; and the ON state, which corresponds to pushing the cell cycle into the post-transition phase. Checkpoint STOP signals seem to act by stabilizing the appropriate bistable switches in its OFF state. Because these checkpoints are crucial to maintaining the integrity of an organism's genome from one generation of cells to the next, it is vital that they function reliably even in the face of random molecular fluctuations that are inevitable in a cell a small as a yeast cell (30 fL). Calculations based on stochastic models of the molecular mechanisms governing cell cycle progression suggest that checkpoint functions are indeed robust in wild-type budding yeast cells, but they may be compromised in strains carrying mutations of specific checkpoint genes. The purpose of this proposal is to provide the mathematical models and experimental data needed to understand how cell cycle checkpoints operate reliably in wild-type yeast cells and how they fail in mutant cells. To reach this goal wil require new advances in stochastic modeling and in the technology of measuring mRNA and protein molecules in single yeast cells. To test the models will require the expertise to construct and characterize the phenotypes of specific mutant strains of budding yeast that are predicted by the model to exhibit fragility of checkpoint arrest in the face of random fluctuations in yeast mRNAs and proteins. Because all eukaryotic organisms seem to employ the same fundamental molecular machinery that governs progression through the cell division cycle, the understanding of checkpoint operations in yeast cells will translate into a better understanding of checkpoint functions and failures in other types of cells, most notably human cells.

Public Health Relevance

The cell division cycle underlies all processes of biological growth and reproduction, and mistakes in cell growth and division cause many serious health problems, especially cancer. Mutations in checkpoint mechanisms are well known to cause genomic instability, leading (it is thought) to an avalanche of new mutations, some of which may transform normal cells into cancer cells. However, most checkpoint failures are lethal, and checkpoint 'fragility' (whereby checkpoints fail in a random fashion, from one cell to another, because of molecular fluctuations) may be an underappreciated mechanism of cancer progression in a clonal line of mutant cells. Hence, a better understanding of checkpoint robustness and fragility, i.e., of the effects of noise on cell cycle progression in normal and mutant cells, may improve our understanding of the etiology and treatment of cancer cells.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM078989-12
Application #
9296151
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Brazhnik, Paul
Project Start
2006-06-06
Project End
2019-04-30
Budget Start
2017-05-01
Budget End
2018-04-30
Support Year
12
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Colorado State University-Fort Collins
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
785979618
City
Fort Collins
State
CO
Country
United States
Zip Code
80523
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Laomettachit, Teeraphan; Chen, Katherine C; Baumann, William T et al. (2016) A Model of Yeast Cell-Cycle Regulation Based on a Standard Component Modeling Strategy for Protein Regulatory Networks. PLoS One 11:e0153738
Barik, Debashis; Ball, David A; Peccoud, Jean et al. (2016) A Stochastic Model of the Yeast Cell Cycle Reveals Roles for Feedback Regulation in Limiting Cellular Variability. PLoS Comput Biol 12:e1005230
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Wang, Shuo; Cao, Yang (2015) The Abridgment and Relaxation Time for a Linear Multi-Scale Model Based on Multiple Site Phosphorylation. PLoS One 10:e0133295
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Tyson, John J; Novak, Bela (2015) Bistability, oscillations, and traveling waves in frog egg extracts. Bull Math Biol 77:796-816
Hong, Tian; Oguz, Cihan; Tyson, John J (2015) A Mathematical Framework for Understanding Four-Dimensional Heterogeneous Differentiation of CD4+ T Cells. Bull Math Biol 77:1046-64

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