Literature DB >> 21350333

Stochastic exit from mitosis in budding yeast: model predictions and experimental observations.

David A Ball1, Tae-Hyuk Ahn, Pengyuan Wang, Katherine C Chen, Yang Cao, John J Tyson, Jean Peccoud, William T Baumann.   

Abstract

Unlike many mutants that are completely viable or inviable, the CLB2-dbΔ clb5Δ mutant of Saccharomyces cerevisiae is inviable in glucose but partially viable on slower growth media such as raffinose. On raffinose, the mutant cells can bud and divide but in each cycle there is a chance that a cell will fail to divide (telophase arrest), causing it to exit the cell cycle. This effect gives rise to a stochastic phenotype that cannot be explained by a deterministic model. We measure the inter-bud times of wild type and mutant cells growing on raffinose and compute statistics and distributions to characterize the mutant's behavior. We convert a detailed deterministic model of the budding yeast cell cycle to a stochastic model and determine the extent to which it captures the stochastic phenotype of the mutant strain. Predictions of the mathematical model are in reasonable agreement with our experimental data and suggest directions for improving the model. Ultimately, the ability to accurately model stochastic phenotypes may prove critical to understanding disease and therapeutic interventions in higher eukaryotes.

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Year:  2011        PMID: 21350333      PMCID: PMC3100879          DOI: 10.4161/cc.10.6.14966

Source DB:  PubMed          Journal:  Cell Cycle        ISSN: 1551-4005            Impact factor:   4.534


  42 in total

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Authors:  D A Sinclair; K Mills; L Guarente
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4.  Dependency of size of Saccharomyces cerevisiae cells on growth rate.

Authors:  C B Tyson; P G Lord; A E Wheals
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5.  Two different modes of cyclin clb2 proteolysis during mitosis in Saccharomyces cerevisiae.

Authors:  M Bäumer; G H Braus; S Irniger
Journal:  FEBS Lett       Date:  2000-02-25       Impact factor: 4.124

6.  Single-cell quantification of molecules and rates using open-source microscope-based cytometry.

Authors:  Andrew Gordon; Alejandro Colman-Lerner; Tina E Chin; Kirsten R Benjamin; Richard C Yu; Roger Brent
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7.  Kinetic Monte Carlo method for rule-based modeling of biochemical networks.

Authors:  Jin Yang; Michael I Monine; James R Faeder; William S Hlavacek
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2008-09-10

8.  Single-RNA counting reveals alternative modes of gene expression in yeast.

Authors:  Daniel Zenklusen; Daniel R Larson; Robert H Singer
Journal:  Nat Struct Mol Biol       Date:  2008-11-16       Impact factor: 15.369

9.  Positive feedback of G1 cyclins ensures coherent cell cycle entry.

Authors:  Jan M Skotheim; Stefano Di Talia; Eric D Siggia; Frederick R Cross
Journal:  Nature       Date:  2008-07-17       Impact factor: 49.962

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Authors:  Ralph Wäsch; Frederick R Cross
Journal:  Nature       Date:  2002-08-01       Impact factor: 49.962

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  10 in total

1.  Mathematical modeling of fission yeast Schizosaccharomyces pombe cell cycle: exploring the role of multiple phosphatases.

Authors:  P Anbumathi; Sharad Bhartiya; K V Venkatesh
Journal:  Syst Synth Biol       Date:  2011-12-08

2.  Oscillatory dynamics of cell cycle proteins in single yeast cells analyzed by imaging cytometry.

Authors:  David A Ball; Julie Marchand; Magaly Poulet; William T Baumann; Katherine C Chen; John J Tyson; Jean Peccoud
Journal:  PLoS One       Date:  2011-10-26       Impact factor: 3.240

3.  Measurement and modeling of transcriptional noise in the cell cycle regulatory network.

Authors:  David A Ball; Neil R Adames; Nadine Reischmann; Debashis Barik; Christopher T Franck; John J Tyson; Jean Peccoud
Journal:  Cell Cycle       Date:  2013-09-04       Impact factor: 4.534

4.  A Model of Yeast Cell-Cycle Regulation Based on a Standard Component Modeling Strategy for Protein Regulatory Networks.

Authors:  Teeraphan Laomettachit; Katherine C Chen; William T Baumann; John J Tyson
Journal:  PLoS One       Date:  2016-05-17       Impact factor: 3.240

Review 5.  Modeling-Based Investigation of the Effect of Noise in Cellular Systems.

Authors:  Didier Gonze; Claude Gérard; Benjamin Wacquier; Aurore Woller; Alen Tosenberger; Albert Goldbeter; Geneviève Dupont
Journal:  Front Mol Biosci       Date:  2018-04-12

6.  Adaptive imaging cytometry to estimate parameters of gene networks models in systems and synthetic biology.

Authors:  David A Ball; Matthew W Lux; Neil R Adames; Jean Peccoud
Journal:  PLoS One       Date:  2014-09-11       Impact factor: 3.240

7.  A Stochastic Model of the Yeast Cell Cycle Reveals Roles for Feedback Regulation in Limiting Cellular Variability.

Authors:  Debashis Barik; David A Ball; Jean Peccoud; John J Tyson
Journal:  PLoS Comput Biol       Date:  2016-12-09       Impact factor: 4.475

8.  Genetic interactions derived from high-throughput phenotyping of 6589 yeast cell cycle mutants.

Authors:  Jenna E Gallegos; Neil R Adames; Mark F Rogers; Pavel Kraikivski; Aubrey Ibele; Kevin Nurzynski-Loth; Eric Kudlow; T M Murali; John J Tyson; Jean Peccoud
Journal:  NPJ Syst Biol Appl       Date:  2020-05-06

9.  A hybrid stochastic model of the budding yeast cell cycle.

Authors:  Mansooreh Ahmadian; John J Tyson; Jean Peccoud; Yang Cao
Journal:  NPJ Syst Biol Appl       Date:  2020-03-27

10.  Clb3-centered regulations are recurrent across distinct parameter regions in minimal autonomous cell cycle oscillator designs.

Authors:  Thierry D G A Mondeel; Oleksandr Ivanov; Hans V Westerhoff; Wolfram Liebermeister; Matteo Barberis
Journal:  NPJ Syst Biol Appl       Date:  2020-04-03
  10 in total

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