2022 Fiscal Year Research-status Report
An integrated approach for mapping RNA protein interactions in the ribosome
| Project/Area Number |
22K19291
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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, 講師 (40640884)
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| Project Period (FY) |
2022-06-30 – 2024-03-31
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| Keywords | Nanopore / Direct RNA sequencing / RNA-protein interactions / Chemical probe / Machine learning |
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| Outline of Annual Research Achievements |
In this fiscal year, we have successfully demonstrated the proof-of-concept (POC) studies to verify that chemical probes can be harnessed in nanopore direct RNA sequencing (dRNA-Seq) platform and can aid in assessing RNA modifications. We published (ACS Chem. Biol. 2022) the part of our results to show that the chemical probe (acrylonitrile) could selectively react with the inosine modification and create a signature mismatch error to deduce the presence of actual inosine modifications. We also deduced the stoichiometry of inosine modification through deviation in signal intensity and trace value. Our methods showed that Adenosine to inosine (A-I) editing could be accurately identified using mismatch error with an accuracy greater than 80% using synthetic RNA and support vector machine learning. Furthermore, we have substituted the need for such a null data set and demonstrated that the acrylonitrile’s selective reactivity could facilitate distinguishing signature mismatch errors from noise. We also modified a `nanoRMS workflow` and showed that chemical probes efficiently alter trace value and signal intensity. We also summarized how machine-learning tools could aid the discovery of natural product-derived small molecules that can serve as targeted therapeutics and probes. Furthermore, the nano-bio interaction of the functionalized quantum dots, which is expected to harbor the bi-functional probe to decipher RNA-protein interaction, was tested using the in vitro and in vivo models. These results form an ideal platform for the integrated approach to mapping RNA dynamics.
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| Current Status of Research Progress |
Current Status of Research Progress
1: Research has progressed more than it was originally planned.
Reason
We have successfully integrated cutting-edge techniques like artificial intelligence (AI), nanopore sequencing, and nucleic acid-based small targeted small molecules to apply to developing a direct RNA sequencing (dRNA-Seq) methodology. Our dRNA-Seq on the mouse brain revealed bonafide Adenosine to inosine (A-I sites) through mismatch errors. However, the unbiased de novo capturing of A-I modifications using chemical probe-induced signal difference was hindered by lower coverage. Nevertheless, we addressed the issue of low coverage associated with the dRNA-Seq by developing Nano ICE-Seq, efficiently capt A-I sites not sampled by dRNA-Seq. The “quick to adapt” Nano ICE-Seq with 30 h of runtime (experiment to analysis) could efficiently probe clinically relevant differential A-I sites as diagnostic or prognostic markers. We published two original articles and two review papers. Web portals and oxford nanopore`s social media sites also highlighted our work. Because A-I differential editing is implicated in inflammatory skin disorders and Osteoarthritis, we also extended our approach through international collaborations. Through the JSPS exchange programs, Dr. Reihane Ziadlou from the University of Zurich and Dr. Valentina Basoli from AO Research Institute visited us for three months. In exchange, Dr. Namasivayam visited and gave an invited lecture at the University of Zurich`s skintegrity mini-symposium. Also, our team member Katsuhiko Abe visited AO Research Institute for six months to accelerate the collaboration and cover more new research areas this year.
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| Strategy for Future Research Activity |
Encouraged by the results obtained in the last fiscal year, we aim to develop a new type of bifunctional probe using a selective 2'-hydroxyl acylating agent (SHAPE) that is analyzed by primer extension. The plan this year is as follows,
1) Improve the design of the chemical probes that interact with RNA and amino acids by functionalizing them on the biodegradable carbon dots.
2) We encountered a bottleneck of a size limitation of the chemical probe, and there needs to be a trade-off between the size and selective reactivity and small molecule probes need to be of optimal size to enter the one nm-sized bacterial nanopore. To overcome this issue, we devised an approach to create a new protocol and device by ourselves. Because modifying the bacterial pores is laborious and not precise, we plan to perform a one-pot synthesis of DNA origami to create programmable nanopores of varied sizes (5-8 nm) and shapes (two or three constrictions).
3) We plan to optimize our device in an in vitro CRISPR system before transferring it to evaluate its efficacy in an in vitro cell line model. We will use human dermal fibroblasts to probe inflammatory skin disorders and mesenchymal stem cells to probe osteoarthritis.
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| Causes of Carryover |
In this challenging proposal, the existing methods like crystallization and electron microscopy can only elucidate RNA-protein interactions under non-cellular conditions. In this proposal, we are developing a new methodology by creating most protocols ourselves with no previous reference materials and having unanticipated challenges. Therefore, we took calculated measures to ensure that the grant is utilized effectively and conducted nanopore sequencing studies using the existing flow cells purchased in bulk beforehand and performed optimization studies. We have planned to allocate the incurred amount toward enhancing operational efficiency by hiring a program-specific researcher specializing in performing nanopore sequencing and machine learning. Furthermore, reagents for cellular and sequencing studies will be purchased. It may also be necessary to reassess budgetary needs and adjust plans based on changing circumstances and priorities.
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| Remarks |
Our integrated approaches to better-distinguish RNA changes affecting the genetic code was highlighted in several science portals, including the social networking sites of oxford nanopore.
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