2022 Fiscal Year Final Research Report
Quantitative understanding of self-replication of cells
| Project/Area Number |
19H03216
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Review Section |
Basic Section 43060:System genome science-related
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| Research Institution | The University of Tokyo |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
若本 祐一 東京大学, 大学院総合文化研究科, 教授 (30517884)
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| Project Period (FY) |
2019-04-01 – 2022-03-31
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| Keywords | 自己複製 / 細胞分裂 / 理論生物学 / リボソーム |
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| Outline of Final Research Achievements |
This research comprehensively characterized the properties related to cellular self-replication by developing data analysis, experimental systems, and mathematical theory. For data analysis, we developed machine learning techniques to estimate the viability of cells as a hidden state based on information from experimentally measured time-series of cell division and cell lineage, and deep learning techniques to estimate the size control rules determining the homeostasis of cell size from time-series data. For the experimental system, we constructed a system to monitor the amount of ribosomes in cells over time. Regarding the mathematical theory related to self-replication, we developed a thermodynamic model of self-replication, which extends the existing models of cell growth law to be consistent with thermodynamics, and clarified the constraints incurred for self-replicating systems by the laws of thermodynamics.
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| Free Research Field |
定量生物学
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| Academic Significance and Societal Importance of the Research Achievements |
自己複製は生物システムを非生物的な化学・物理システムと峻別する特性である。にも関わらず、自己複製が可能である、ということに付随する普遍的性質は明らかになっていない。またそれら自己複製の性質を適切に計測し特徴づける実験・解析手法も十分に整備されていない。本研究は自己複製を特徴づけ熱力学理論を構築し、また同時に細胞の自己複製のコアとなるリボソームを経時計測するための系を構築した。さらに経時的に計測された細胞の分裂動態から、その性質を隠れ状態や制御則の形で推定する手法の開発にも成功した。これらの技術はより定量的で精密な自己複製過程の理解に貢献すると期待される。
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