Developing a computational method for microbial contaminant detection and functional inference using next-generation sequencing data
| Project/Area Number |
17K00396
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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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| Research Field |
Life / Health / Medical informatics
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| Research Institution | The University of Tokyo |
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Principal Investigator |
Park Sung-Joon 東京大学, 医科学研究所, 特任講師 (40759411)
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2019: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2018: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2017: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | コンタミネーション / バイオインフォマティクス / 次世代シークエンシング / 網羅的配列解読 |
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| Outline of Final Research Achievements |
In modern biology, cells are routinely manipulated by various experimental techniques under a range of conditions. These increase the risk of exposure of the cells to microorganisms that cause unexpected molecular changes and misunderstanding. Therefore, the prevention and detection of microbial contamination is a critical issue. In this study, we developed a computational method to comprehensively and accurately detect contaminants that present in the next-generation sequencing (NGS) data. This method can profile, for example, transcriptome and contamination simultaneously. Therefore, this method allows us to perform deeper analyses of the interaction with contaminants.
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| Academic Significance and Societal Importance of the Research Achievements |
開発した手法の公開とその解析結果のデータベース化を行ったことで、既存研究データから見られるコンタミの種類とその混入度分布がわかり、ホスト細胞に与える外来性ゲノムのインパクト推定が容易となった。これは、細胞培養方法と実験試薬の見直しや既存研究データの再解釈に資するものであり、さらに、核酸増幅法などの既存検査方法の代替方法として、例えば、再生医療製品の安全性と品質管理、新規細菌・ウイルス同定にも応用可能であることから、今後の応用発展を図りたい。
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Report
(4 results)
Research Products
(10 results)
