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Updated: Sep 3, 2025

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Characterizing RNA Modifications in Single Neurons Using Mass Spectrometry
Published on: April 21, 2022
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Harnessing Nature's Molecular Recognition Capabilities to Map and Study RNA Modifications.
Ansley S Felix1, Alexandria L Quillin1,2, Shikufa Mousavi1
1Department of Chemistry, Emory University, Atlanta, Georgia 30322, United States.
Accounts of Chemical Research
|July 28, 2022
Summary
Researchers repurposed Endonuclease V to detect RNA modifications, offering a new tool for epitranscriptomics. This enzyme acts as an anti-inosine antibody, enabling sensitive detection and enrichment of RNA editing sites.
Area of Science:
- Molecular Biology
- Genetics
- Biochemistry
Background:
- RNA editing, or epitranscriptomic modification, alters RNA after transcription, impacting gene expression and function.
- Over 170 RNA modifications exist, with dysregulation linked to diseases, necessitating precise detection methods.
- Current methods like antibodies and chemical labeling have limitations in selectivity and ease of use.
Purpose of the Study:
- To develop novel, selective methods for identifying and mapping RNA editing sites.
- To overcome limitations of existing antibody-based and chemical labeling techniques for epitranscriptomic studies.
- To leverage protein-based recognition for enhanced RNA modification analysis.
Main Methods:
- Repurposing Endonuclease V (EndoV), an enzyme that recognizes inosine in RNA.
- Developing EndoVIPER-seq for preparative enrichment of inosine-edited RNAs for RNA sequencing.
- Creating EndoVLISA, a plate-based immunoassay for quantifying inosine in cellular RNA.
Main Results:
- EndoVIPER-seq improved RNA sequencing coverage and identified new A-to-I editing sites.
- EndoVLISA enabled cost-effective, high-throughput quantification of differential A-to-I editing levels.
- EndoV demonstrated efficacy as a selective 'anti-inosine antibody' for RNA analysis.
Conclusions:
- Repurposing enzymes like EndoV offers a promising new direction for epitranscriptomics.
- These novel methods provide sensitive and selective tools for studying RNA modifications.
- Exploiting natural molecular recognition capabilities enhances the study of RNA editing and its role in health and disease.
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