2020 Fiscal Year Final Research Report
Prediction and experimental verification of optimal mutation rate in bacterial evolution
Project/Area Number |
19K16114
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Research Category |
Grant-in-Aid for Early-Career Scientists
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Allocation Type | Multi-year Fund |
Review Section |
Basic Section 43060:System genome science-related
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Research Institution | Institute of Physical and Chemical Research |
Principal Investigator |
Shibai Atsushi 国立研究開発法人理化学研究所, 生命機能科学研究センター, 研究員 (40823620)
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Project Period (FY) |
2019-04-01 – 2021-03-31
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Keywords | 実験進化 / 大腸菌 |
Outline of Final Research Achievements |
This study aimed to demonstrate and understand the trade-off between bacterial mutation rates and evolutionary speed. The evolutionary speeds were quantified by the experimental evolution of E. coli with various mutation rates in the environments treated with growth inhibitors. As a material for the evolution experiment, E. coli strains with various mutation rates were prepared by deleting the DNA repair genes of E. coli. As a result, we obtained strains with mutation rates much higher than that of the wild type. The growth rates of these strains were then measured to reveal the growth-inhibitory effects of higher mutation rates. And the experiment evolution using various growth inhibitors was carried out by an automated experimental evolution system. We then succeeded in experimentally observing the peak of evolutionary speed versus mutation rate.
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Free Research Field |
細菌の実験室内進化
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Academic Significance and Societal Importance of the Research Achievements |
細菌にとって変異率が高いほど薬剤へ適応するための有益変異は多く生ずるはずであるが、同時に有害な作用を持つ変異による増殖阻害の効果もあるため、これらの間のトレードオフ関係が予想される。本研究では実験と並行してこのトレードオフの関係に基づくトイモデルを提唱した。そして、いろいろな作用機序からなる抗生物質での実験進化の結果と組み合わせ、殺菌剤よりも静菌剤のほうがよりよくフィットすることを明らかにした。これにより、当該のモデルの蓋然性や適用条件についても担保することができた。本研究の成果は適応進化の理解のみならず、人工進化の高速化や病原性細菌の薬剤耐性進化の抑制などを可能にするポテンシャルを有する。
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