| Project/Area Number |
20F20346
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| Research Category |
Grant-in-Aid for JSPS Fellows
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| Allocation Type | Single-year Grants |
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| Section | 外国 |
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| Review Section |
Basic Section 22060:Environmental systems for civil engineering-related
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| Research Institution | National Institute of Advanced Industrial Science and Technology |
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Principal Investigator |
延 優 国立研究開発法人産業技術総合研究所, 生命工学領域, 研究員 (40805644)
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| Co-Investigator(Kenkyū-buntansha) |
LENG LING 国立研究開発法人産業技術総合研究所, 生命工学領域, 外国人特別研究員
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| Project Period (FY) |
2020-11-13 – 2023-03-31
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| Project Status |
Granted (Fiscal Year 2021)
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| Budget Amount *help |
¥2,200,000 (Direct Cost: ¥2,200,000)
Fiscal Year 2021: ¥1,100,000 (Direct Cost: ¥1,100,000)
Fiscal Year 2020: ¥600,000 (Direct Cost: ¥600,000)
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| Keywords | Metagenomics / Biotechnology / Machine learning / Genome annotation / Metabolism |
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| Outline of Research at the Start |
微生物は様々な産業で利用されているが、自然界に存在する多くの微生物はまだ機能が未知であり、それ故産業利用に応用できていない。機械学習を通じ未知遺伝子や未知機能を発掘し、それらを更に深く調査するために多様な未知機能や未知微生物が出現する廃水処理プロセスをラボで構築し、 微生物の複合系で相互作用を担う未知遺伝子や複数の微生物に渡って機能する新規代謝機能を研究する。
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| Outline of Annual Research Achievements |
We employed a machine learning-based approach that utilizes two foundational biological features of aromatic compound degradation: activation and organization. The fellow and host successfully identified novel metabolic pathways and organisms involved in utilization and conversion of complex aromatics compounds in wastewater treatment processes. Further evolutionary analyses showed how many contemporarily evolved in plastics industry wastewater streams. The results are expected to bring high impact to the microbiology and engineering communities and will be submitted for publication soon.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
Research proceeded well despite setbacks from COVID-19.
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| Strategy for Future Research Activity |
We successfully identified many genes potentially comprising novel metabolic pathways for aromatic compound degradation. Among these, some were predicted to have evolved very recently and further analyses revealed that these were involved in degradation of xenobiotic pollutants in industrial plastics production wastewater streams, so we will further investigate these novel genes/pathways and their evolutionary history to bring high impact to the microbiology and engineering research community.
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