2023 Fiscal Year Final Research Report
An integrated approach for mapping RNA protein interactions in the ribosome
| Project/Area Number |
22K19291
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| Research Category |
Grant-in-Aid for Challenging Research (Exploratory)
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| Allocation Type | Multi-year Fund |
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| Review Section |
Medium-sized Section 43:Biology at molecular to cellular levels, and related fields
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| Research Institution | Kyoto University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
Packwood Daniel 京都大学, 高等研究院, 准教授 (40640884)
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| Project Period (FY) |
2022-06-30 – 2024-03-31
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| Keywords | Transcriptomics / RNA Structures / Nanopore technology / Chemical probes / Informatics / RNA protein interactions / RNA modifications |
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| Outline of Final Research Achievements |
Using this grant, we have successfully demonstrated the proof-of-concept (POC) studies to verify an integrated approach of harnessing the selective reactivity of chemical probes in the nanopore direct RNA sequencing platform and improving the prediction accuracy using an informatics workflow called Indo-C that can be programmed on demand. Using this methodology, we published initial results on deciphering the inosine and pseudouridine RNA modifications, the nano-bio interaction of the functionalized quantum dot probes as original articles and have summarized the potential of computational-aided discovery of natural product-derived small molecule probes as review articles. Currently, we are extending our strategy to map RNA structural and base modifications and their interaction using programmable nucleic acid-based nanopores in varied sizes, shapes, and constrictions and developing a universally adaptable biomolecular sequencing technology under a JST program.
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| Free Research Field |
Chemical Biology
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| Academic Significance and Societal Importance of the Research Achievements |
近年のCovid-19の世界的流行により健康についての信頼性の高い指標として、RNAから細胞内環境に関する正確な情報が得られることが明らかになった。本研究により開発された、ケミカルプローブを用いたディレクトRNAシークエンシング法は、他の研究室でも取り入れることのできる簡便なものである。したがって、感染症であれがんのような非感染性疾患であれ、未知のRNA修飾やその相互作用の場所を特定するマッピング研究への波及効果が期待できる。そうして得られたデータセットの解析は、診断用疾患マーカーあるいは新薬の標的となるようなRNAの新規構造の発見や、不治の希少疾患に対する核酸医薬の創出に役立つ可能性がある。
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