RNA Editing Tool Repairs Disease-Causing Genetic Messages Without Altering DNA

Researchers at the University of Hong Kong developed RNA Segment Editing (RSE), a reversible RNA editing tool that targets and repairs faulty genetic messages in living cells without altering DNA, offering potential treatment for neurodegenerative diseases like Huntington’s. The method uses engineered Cas13 enzymes to precisely cut and replace harmful RNA segments, preserving healthy genetic functions and enabling adjustable therapies with minimal risk to patients.
Researchers at the School of Biomedical Sciences at the LKS Faculty of Medicine, the University of Hong Kong (HKUMed), have created a novel RNA editing tool called RNA Segment Editing (RSE) that can correct disease-causing genetic messages in cells without permanently modifying DNA. The breakthrough, published in *Nature Communications*, leverages an engineered version of the Cas13 enzyme to act like molecular scissors, precisely targeting and replacing faulty RNA segments in living cells. Unlike traditional gene-editing tools that either destroy entire RNA messages or fix single errors, RSE allows for targeted corrections of long, toxic RNA segments. This method could address conditions like Huntington’s disease, where repetitive RNA sequences disrupt brain cell function. Current treatments often delete entire RNA strands, risking loss of essential proteins, but RSE selectively removes harmful segments while preserving healthy genetic material. The tool’s reversibility is a key advantage, as treatments can be adjusted or stopped without permanent DNA changes. Professor Kwon Sung Chul, lead researcher, emphasized that RSE offers a flexible, safe approach for RNA-based therapies, potentially transforming how neurodegenerative diseases are treated. The study builds on prior research involving Cas13, demonstrating its precision in RNA cleavage and repair. This innovation could pave the way for new, targeted therapies that avoid the risks of DNA editing while effectively correcting genetic errors at their source. The findings were published in *Nature Communications*, with the research team highlighting the tool’s potential for future clinical applications in genetic disorders.
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