A stochastic model of size control in the budding yeast cell cycle
Abstract Background Cell size is a key characteristic that significantly affects many aspects of cellular physiology. There are specific control mechanisms during cell cycle that maintain the cell size within a range from generation to generation. Such control mechanisms introduce substantial variab...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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BMC
2019-06-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12859-019-2839-9 |
| _version_ | 1818136563671891968 |
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| author | Mansooreh Ahmadian John J. Tyson Yang Cao |
| author_facet | Mansooreh Ahmadian John J. Tyson Yang Cao |
| author_sort | Mansooreh Ahmadian |
| collection | DOAJ |
| description | Abstract Background Cell size is a key characteristic that significantly affects many aspects of cellular physiology. There are specific control mechanisms during cell cycle that maintain the cell size within a range from generation to generation. Such control mechanisms introduce substantial variabilities to important properties of the cell cycle such as growth and division. To quantitatively study the effect of such variability in progression through cell cycle, detailed stochastic models are required. Results In this paper, a new hybrid stochastic model is proposed to study the effect of molecular noise and size control mechanism on the variabilities in cell cycle of the budding yeast Saccharomyces cerevisiae. The proposed model provides an accurate, yet computationally efficient approach for simulation of an intricate system by integrating the deterministic and stochastic simulation schemes. The developed hybrid stochastic model can successfully capture several key features of the cell cycle observed in experimental data. In particular, the proposed model: 1) confirms that the majority of noise in size control stems from low copy numbers of transcripts in the G1 phase, 2) identifies the size and time regulation modules in the size control mechanism, and 3) conforms with phenotypes of early G1 mutants in exquisite detail. Conclusions Hybrid stochastic modeling approach can be used to provide quantitative descriptions for stochastic properties of the cell cycle within a computationally efficient framework. |
| first_indexed | 2024-12-11T09:42:24Z |
| format | Article |
| id | doaj.art-95999c350769441ca0e75dba8560b96c |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-12-11T09:42:24Z |
| publishDate | 2019-06-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-95999c350769441ca0e75dba8560b96c2022-12-22T01:12:38ZengBMCBMC Bioinformatics1471-21052019-06-0120S1211310.1186/s12859-019-2839-9A stochastic model of size control in the budding yeast cell cycleMansooreh Ahmadian0John J. Tyson1Yang Cao2Department of Computer Science, Virginia TechDepartment of Biological Sciences, Virginia TechDepartment of Computer Science, Virginia TechAbstract Background Cell size is a key characteristic that significantly affects many aspects of cellular physiology. There are specific control mechanisms during cell cycle that maintain the cell size within a range from generation to generation. Such control mechanisms introduce substantial variabilities to important properties of the cell cycle such as growth and division. To quantitatively study the effect of such variability in progression through cell cycle, detailed stochastic models are required. Results In this paper, a new hybrid stochastic model is proposed to study the effect of molecular noise and size control mechanism on the variabilities in cell cycle of the budding yeast Saccharomyces cerevisiae. The proposed model provides an accurate, yet computationally efficient approach for simulation of an intricate system by integrating the deterministic and stochastic simulation schemes. The developed hybrid stochastic model can successfully capture several key features of the cell cycle observed in experimental data. In particular, the proposed model: 1) confirms that the majority of noise in size control stems from low copy numbers of transcripts in the G1 phase, 2) identifies the size and time regulation modules in the size control mechanism, and 3) conforms with phenotypes of early G1 mutants in exquisite detail. Conclusions Hybrid stochastic modeling approach can be used to provide quantitative descriptions for stochastic properties of the cell cycle within a computationally efficient framework.http://link.springer.com/article/10.1186/s12859-019-2839-9Cell cycleSize control mechanismBudding yeastHybrid modelStochastic modelDeterministic model |
| spellingShingle | Mansooreh Ahmadian John J. Tyson Yang Cao A stochastic model of size control in the budding yeast cell cycle BMC Bioinformatics Cell cycle Size control mechanism Budding yeast Hybrid model Stochastic model Deterministic model |
| title | A stochastic model of size control in the budding yeast cell cycle |
| title_full | A stochastic model of size control in the budding yeast cell cycle |
| title_fullStr | A stochastic model of size control in the budding yeast cell cycle |
| title_full_unstemmed | A stochastic model of size control in the budding yeast cell cycle |
| title_short | A stochastic model of size control in the budding yeast cell cycle |
| title_sort | stochastic model of size control in the budding yeast cell cycle |
| topic | Cell cycle Size control mechanism Budding yeast Hybrid model Stochastic model Deterministic model |
| url | http://link.springer.com/article/10.1186/s12859-019-2839-9 |
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