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Analysis of Yeast Mutants to Test a Mathematical Model of the Cell Cycle Neil R. Adames 1, Logan Schuck 1, Kathy Chen 2, John J. Tyson 2, and Jean Peccoud.

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Presentation on theme: "Analysis of Yeast Mutants to Test a Mathematical Model of the Cell Cycle Neil R. Adames 1, Logan Schuck 1, Kathy Chen 2, John J. Tyson 2, and Jean Peccoud."— Presentation transcript:

1 Analysis of Yeast Mutants to Test a Mathematical Model of the Cell Cycle Neil R. Adames 1, Logan Schuck 1, Kathy Chen 2, John J. Tyson 2, and Jean Peccoud 1,3 1 Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA 2 Department of Biological Sciences, Virginia Tech, Blacksburg, VA 24061, USA 3 ICTAS Center for Systems Biology of Engineered Tissues, Virginia Tech, Blacksburg, VA 24061, USA The eukaryotic cell division cycle is a complex process in which cells grow, duplicate their chromosomes, and then divide while partitioning their chromosomes and organelles between the two new daughter cells. Intense genetic and molecular experimentation in the budding yeast Saccharomyces cerevisiae has elucidated many of the molecular interactions involved in cell cycle regulation – to the extent that current knowledge has outpaced biologists’ ability to predict the outcomes of perturbations to this network. A mathematical model of the cell cycle developed in Dr. John Tyson’s lab formalizes much of the known cell cycle interactions. Simulations of this model reproduce the known phenotypes of over 120 cell cycle mutants described in the literature. The Tyson lab has simulated the cell growth characteristics of new combinations of cell cycle mutants not described in the literature. To test the predictive power of the model, we are generating these new mutants and assessing their phenotypes using time-lapse imaging to extract information about cell cycle timing and cell size. ABSTRACT THIS RESEARCH SUPPORTED BY: NIH RO1-GM and R01-GM THE CELL CYCLE The yeast cell cycle is an excellent model process because: - the genes/proteins are highly conserved - unlike metazoans, there is only one essential CDK, Cdc28, simplifying interpretation of results - yeast is amenable to genetic manipulation and biochemical experiments (“the E. coli of eukaryotes”) - there are obvious morphological indicators of position in the cell cycle (Fig. 1) The most obvious morphological marker is the presence and size of the daughter bud. Buds form only after the cells pass the G1-S transition, also called START. This transition occurs only after the cell reaches a certain size. Budding is an asymmetric process. Almost all of the growth of a mother cell occurs during G1. During the rest of the cell cycle, growth is polarized to the daughter bud. Normally, buds grow to ~40% of mother size at the time of cell division and new daughters need a longer time in G1 to grow big enough to pass START. This means that: If G1-S occurs too soon, cells are smaller than average If G1-S is delayed, cells are larger than average. Figure 1. Cell cycle-dependent morphological changes in yeast. Actin patches and cables are polarized to the sites of growth and division. Microtubules form the mitotic spindle and cytoplasmic microtubules, which position the spindle in the neck. G1 START S Figure 2. Wiring diagram of the cell cycle model developed by the Tyson lab. CDK is not shown because its abundance is constant. Green box, G1 cyclin. Blue box, S cyclins. Orange box, mitotic cyclin. Red box, G1- S transition (START). Modified from Chen et al. (2004). Cell cycle regulation consists of a complex network of protein-protein and protein-DNA interactions. The heart of the cell cycle is a protein kinase whose activity requires cofactors called cyclins (Fig. 2, outlined in green, blue and orange). As their name suggests, cyclins are regulated so that their abundance oscillates during each cell cycle. Each cyclin is specific to a certain stage of the cell cycle and directs the cyclin- dependent kinase (CDK) to specific substrates during that stage of the cell cycle (e.g. replication proteins during S phase). The model shown in Fig. 2 has been updated to include more regulatory mechanisms, especially during the G1-S transition (Fig. 2, red box has been expanded to Fig. 3). THE CELL CYCLE MODEL Figure 3. Cell size control at START. Whi5 inhibits the SBF (Swi4/Swi6 dimer) and MBF (Mbp1/Swi6 dimer) transcription factors, which transcribe the S-phase cyclins. Whi5 is inhibited by high levels of Cln3 in sufficiently large cells. Bck2 kinase also promotes S-phase cyclin expression. RESULTS AND CONCLUSIONS We are testing the predictive power of the cell cycle model by generating new cell cycle mutants that have not been previously described. We do this by performing time-lapse imaging of live cells using GenoSIGHT (Fig. 4). GenoSIGHT performs cell segmentation and tracking, as well as calculating cell volumes during acquisition – yielding cell doubling times (Table I) and cell size distributions (Fig. 5). Strain Doubling Time Mean (SD) n=3 t-test p-value WT112 (12) bck2105 (5)0.4 mbp1110 (8)0.8 swi6122 (16)0.3 cln1 cln2127 (10)0.2 cdh1119 (10)0.5 swi4116 (3)0.6 whi5114 (6)0.8 bck2 mbp1101 (2)0.2 bck2 swi6ALIVE Not Tested cln1 cln2 cdh1124 (12)0.3 swi4 swi6DEAD swi4 whi5113 (9)0.9 swi4 swi6 whi5ALIVE Not Tested swi6 whi5128 (11)0.1 Table I. Volume doubling times Figure 4. Example movie images. Images from time-lapse movies. Scale bar = 10  m Fraction of Cells Below Volume Volume (fL) Fraction of Cells Below Volume Volume (fL) Figure 5. Cell size distributions. The distributions of cell sizes in the indicated strains are plotted as cumulative density functions (CDFs). Populations with large cells are shifted right and small cells left of wt. Most of the results agree with the model. Small changes in G1-S timing are tolerated because of the G2/M transition which speeds (big mother) or slows (small mother) in response, so we do not expect major changes in doubling times (Table I). Cell size distributions mostly agree with the model. For example, the swi4∆ mutant is larger than wt because cells lacking SBF are slower to induce the S cyclins (Figs. 3 & 5a). whi5∆ mutants are smaller because there is no SBF inhibition and cells enter S sooner. In the model, the whi5∆ swi4∆ mutant has the same phenotype as swi4∆ because Whi5 mostly inhibits SBF (Swi4/Swi6), which is missing in swi4∆ cells. Some results are surprising. The swi6∆ mutant is larger than wt, as expected (Figs. 3 & 5b). However, the whi5∆ mutation rescues swi6∆ - cell size in the whi5∆ swi6∆ mutant is normal. In the model, a hypothetical Swi4/Swi4 dimer can promote transcription of the S cyclins in the absence of Swi6, but Whi5 is thought to act only on Swi6 – so why would whi5∆ rescue a swi6∆ mutant? We need to resolve discrepancies between predicted and experimental phenotypes. ab REFERENCES Chen, K., L. Calzone, A. Csikasz-Nagy, F. R. Cross, B. Novak and J. J. Tyson Integrative analysis of cell cycle control in budding yeast. Mol. Biol. Cell 15:


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