2022 Fiscal Year Final Research Report
Bioinformatics analysis of the evolution strategy for wild-type Microcystis
| Project/Area Number |
19K04610
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 22040:Hydroengineering-related
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| Research Institution | Shizuoka Institute of Science and Technology (2020-2022)
Tohoku University (2019) |
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Principal Investigator |
Makino Ikuyo 静岡理工科大学, 理工学部, 准教授 (00542060)
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| Co-Investigator(Kenkyū-buntansha) |
小林 厚志 日本大学, 工学部, 教授 (90361138)
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| Project Period (FY) |
2019-04-01 – 2023-03-31
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| Keywords | アオコ / Microcystis / メタボローム解析 / RNA-seq / De novo解析 |
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| Outline of Final Research Achievements |
The phenomenon of algal blooms, constituted by the massive proliferation of cyanobacteria, has been a persistent global threat to water resources for some time. In this study, we focused initially on gaining a deeper understanding of the ecology of these blooms as a preparatory step towards implementing countermeasures. More specifically, we utilized genetic and metabolomic analyses to study the behavior of cyanobacteria and the underlying mechanisms of algal bloom formation. Our results elucidated that the biofilm crucial for algal bloom formation is composed of extracellular polysaccharides, produced through photosynthesis. This indicates that the most favorable period for bloom formation is likely during daylight hours. Moreover, we hypothesize that maintaining cellular conglomerates becomes more challenging during the night, due to decreased polysaccharide secretion, leading to regulation of biofilm matrix production.
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| Free Research Field |
水資源工学，流体科学，バイオインフォマティクス
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| Academic Significance and Societal Importance of the Research Achievements |
遺伝子解析とメタボローム解析を用いてアオコ形成の生物学的メカニズムの一部の可視化に成功した．これによりシアノバクテリアの挙動とアオコ形成との間の生物学的プロセスを詳細に理解することが可能となり，特に水資源工学の領域において新たな視点を提供することができた．具体的には，アオコ形成に最適な時間帯や細胞外多糖の生成，並びにバイオフィルムマトリクスへの影響など，未解明であったアオコ形成の過程について新たな理解を得た．本研究の成果は，アオコ問題に対する解決策の策定に必要な重要な情報源となり得ると考えられ，アオコに対する予防策や対策の開発において重要な基盤を提供できることが期待される．
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