Broad researchers enhanced several prime editing components: the motifs that protect the guide pegRNA (in red), the reverse transcriptase enzyme (in purple), and delivery via lipid nanoparticles (yellow).
Image Credit: Susanna Hamilton, Broad Communications
Scientific Frontline: Extended "At a Glance" Summary: Prime Editing Advancements
The Core Concept: Prime editing is a precise genome-editing technology that replaces disease-causing DNA sequences with corrected segments without requiring double-strand DNA breaks.
Key Distinction/Mechanism: Unlike traditional CRISPR systems that rely on blunt DNA breaks, prime editing utilizes a prime editing guide RNA (pegRNA) to instruct a reverse transcriptase enzyme to write new genetic information directly into a targeted DNA site. Recent advancements enhance this mechanism by increasing component stability and delivery efficiency for in vivo applications.
Major Frameworks/Components:
- pegRNA Stabilization: The use of laboratory evolution to discover and implement novel structural motifs that shield pegRNA, extending its cellular lifespan and abundance.
- AI-Guided Enzyme Optimization: The application of artificial intelligence to redesign the reverse transcriptase enzyme, yielding highly mutated variants that maintain potent editing capabilities while demonstrating greater cellular stability.
- Lipid Nanoparticle (LNP) Delivery: The optimization of RNA packaging workflows to efficiently deliver prime editing components directly to target tissues, successfully demonstrated in mouse models.
Branch of Science: Molecular Biology, Medical Genetics, Computational Biology, and Nanotechnology.
Future Application: Direct in vivo editing of tissues such as the liver, lungs, and muscle to treat or cure common and complex genetic disorders, including phenylketonuria.
Why It Matters: By resolving the primary bottlenecks of delivery efficiency, component stability, and cellular abundance, these structural and computational optimizations transition prime editing from a laboratory constraint to a viable, systemic therapeutic tool for human genetic diseases.
Prime editing can potentially repair the vast majority of known disease-causing human mutations, but the technology, first developed in 2019, has not yet been widely used in the body, or in vivo, to treat genetic disease. The only clinical application of prime editing publicly announced to date uses the technology to edit cells outside the body before transplanting them back into the patient.
Now, scientists from the David Liu lab at the Broad Institute have addressed bottlenecks that previously impeded the use of prime editing in animals and in human patients. In two studies published last month in Nature Biotechnology and one published today in Nature Nanotechnology, the team described multiple changes to key components of the prime-editing system and optimized prime editing for delivery with lipid nanoparticles, which deliver genetic medicines to tissues in the body and are already used in several approved therapeutics. These advances together increase the efficiency and potency of prime editing, improving its performance when delivered into the body—a key requirement for in vivo prime-editing therapeutics.
“Collectively, these three papers improve the overall efficiency and clinical relevance of prime editing, which we hope will make the technique more useful both for research purposes and for therapeutic clinical applications,” said Liu, who is also the Richard Merkin Professor and director of the Merkin Institute for Transformative Technologies in Healthcare at Broad, the Dudley Cabot Professor of the Natural Sciences in the Faculty of Arts and Sciences at Harvard University, and a Howard Hughes Medical Institute investigator.
A Gene Editor Hits Its Prime
Prime editing is a precise gene-editing approach that can replace a disease-causing section of DNA with a new DNA segment, potentially treating or even curing a broad range of genetic diseases. The editing system comprises a prime editing guide RNA (pegRNA) that instructs the prime editor both where to edit and what edit to install at the target site in the genome; a prime editor protein that recognizes the target DNA sequence and then copies the edit from the pegRNA into the target DNA site; and a delivery system that brings the editor to the desired tissues in the body.
Prime editing has already been tested in human patients using an ex vivo strategy, in which blood cells are removed from the body, edited in a lab, and returned to the body as a treatment, with encouraging clinical results. However, to treat many diseases, edits need to be made in vivo—directly to tissues like the liver, lungs, and muscle.
Liu’s team identified key bottlenecks to prime-editing efficiency that they would need to overcome. “As prime editing moves into therapeutic in vivo applications, addressing these bottlenecks becomes critical,” said Nicholas Krasnow, a Harvard graduate student in the Liu lab and a co–first author of one of the papers.
One hurdle was the stability of the pegRNA. The prime-editing process involves a series of complicated chemical changes, which take time, and the lipid nanoparticle–delivered RNA cargos that are ideal for clinical use do not last long in the body. Therefore, the research group set out to make the pegRNA more abundant, stable, and long-lasting.
They knew that one end of the pegRNA tends to degrade in cells, limiting its function. In previous work, the Liu lab engineered a pegRNA with an additional protective tail, called a motif, that acts like a shield. In one of the new studies, the group used laboratory evolution to discover new motifs that were even better at shielding the pegRNA after evaluating thousands of diverse motifs, including natural and synthetic ones. They identified several that better protect the pegRNA and increase its abundance more than previous gold-standard motifs widely used by the scientific community for prime editing in cells and animal models.
“The lifetime of these pegRNAs is very limiting for the system, so increasing their longevity offers major benefits to overall performance,” said Holt Sakai, a postdoctoral researcher in the Liu lab and co–first author along with postdoctoral researcher Sarah Pierce.
In the study published today, members of the Liu lab improved how the editing components are packaged within lipid nanoparticles and delivered to the liver as RNA. Researchers had optimized prime editors and lipid nanoparticles independently; yet, “when they put the best of each together, it still wasn’t working very well,” said Ana Cristian, an MIT graduate student in the Liu lab and co–first author of the study along with postdoctoral researcher Allen Jiang.
To increase the performance of lipid nanoparticle–delivered prime-editing systems, the team evaluated and optimized each major parameter involved, defining a workflow that can serve as a model for developing efficient prime-editing strategies using lipid nanoparticles. “We hope that this workflow will be a useful resource to other groups trying to navigate how to package so many different prime editing components into a single system,” said Jiang.
The team collaborated with the labs of Kiran Musunuru and Xiao Wang at the University of Pennsylvania to test their optimized system in a mouse model of a genetic disease called phenylketonuria. They showed that they could edit liver cells and reduce blood phenylalanine to curative levels.
In the third study, lab members showed that previous efforts to engineer a more robust reverse transcriptase enzyme, the chemical driver of the prime-editing complex, had weakened the protein’s stability and abundance, limiting its performance. The researchers used an AI-driven tool to redesign the enzyme and generated new, highly mutated versions that, to their surprise, retained their potent editing ability but were more stable and abundant in cells. These new editors performed better than previous state-of-the-art versions at editing cells, especially in vivo, where they yielded severalfold higher editing efficiency in mouse models.
“AI helped us explore an enormous number of combinations of hundreds of possible mutations to these reverse transcriptases,” said Allen Tao, a Harvard graduate student in the Liu lab and co–first author along with Sakai, Jiang, and Krasnow.
The three papers represent a major step forward in the prime-editing field. “A few years ago, we couldn't have imagined that we'd be seeing editing systems that combine all these technologies and are efficient enough to be viable for potential clinical application,” said Jiang. “These papers advance our ability to use prime editing safely and effectively to benefit patients.”
Funding:
- This study was funded by National Institutes of Health grants R35GM118062 and RM1HG009490 and Howard Hughes Medical Institute (HHMI).
- This work was supported by the US National Institutes of Health grants R01EB031172, R35GM118062 and RM1HG009490, the Bill and Melinda Gates Award INV-056974 and the Howard Hughes Medical Institute.
- This work was supported by US National Institutes of Health grants R35GM118062, RM1HG009490, U19NS132301, and R01HD110733; the Bill and Melinda Gates Award INV-056974; and the Howard Hughes Medical Institute.
Published in journal:
- Nature Biotechnology
- Nature Biotechnology
- Nature Nanotechnology
Title:
- Directed evolution of small RNA-stabilizing motifs that improve prime-editing efficiency.
- AI-guided redesign of laboratory-evolved reverse transcriptases enhances prime editing
- Efficient prime editing in vivo and in vitro using lipid nanoparticles
Authors:
- Holt A. Sakai, Sarah E. Pierce, Allen Y. Jiang, Ana Cristian, Meirui An, Chae Rin Kim, Nouraiz Ahmed, Colin F. Hemez, Y. Allen Tao, Emily Zhang, Sophia J. Wu, and David R. Liu
- Y. Allen Tao, Holt A. Sakai, Allen Y. Jiang, Nicholas A. Krasnow, Vasilii S. Vaganov, Brian Shim, Zachary Barsdale, Smriti Pandey, Nouraiz Ahmed, Man Na, Ting-Wei Liao, Keyede Oye, Ana Cristian, Emily Zhang, Joy A. Xu, Mattijs Bulcaen, and David R. Liu
- Allen Y. Jiang, Ana Cristian, Dominique L. Brooks, Emily R. Feierman, Paul Z. Chen, Madelynn N. Whittaker, Sarah E. Pierce, Holt A. Sakai, Hongyu Chen, Dangliang Liu, Peyton B. Randolph, Angus H. Li, Alvin Hsu, Serena O. Omo-Lamai, Y. Allen Tao, Benista Owusu-Amo, Xiao Wang, Xiao Wang, Kiran Musunuru, and David R. Liu
Source/Credit: Broad Institute | Leah Eisenstadt
Edited by: Scientific Frontline
Reference Number: mbio061526_01
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