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Updated: Jul 16, 2026
14:48
Endogenous Protein Tagging in Human Induced Pluripotent Stem Cells Using CRISPR/Cas9
Published on: August 25, 2018
A simple and versatile fluorescence-based method to enhance prime editing in human pluripotent stem cells
Carlye Frisch1,2, Salma Leyasi1,2, William W Kostes2
1School for Engineering of Matter, Transport and Energy, Arizona State University, Tempe AZ 85287, USA.
BMC Methods
|July 15, 2026
Summary
Prime editing offers precise genome modification without double-strand breaks. A new PINE-TREE system boosts prime editing efficiency in human pluripotent stem cells (hPSCs) for regenerative medicine applications.
Area of Science:
- Genome Engineering
- Stem Cell Biology
- Molecular Biology
Background:
- Prime editing enables precise DNA modifications without double-strand breaks, reducing genomic instability.
- Current prime editing methods face low efficiency in human pluripotent stem cells (hPSCs).
- This limitation hinders applications in stem cell research and regenerative medicine.
Purpose of the Study:
- To develop a method for enhancing prime editing efficiency in hPSCs.
- To introduce a fluorescence-based system for real-time enrichment of edited cells.
- To ensure the precision and reliability of prime editing in hPSCs.
Main Methods:
- Described is the Prime-Induced Nucleotide Engineering using a Transient Reporter for Editing Enrichment (PINE-TREE) system.
- Methodology includes plasmid construction, transfection, and clonal isolation.
- Off-target effects and pluripotency maintenance were evaluated.
Main Results:
- PINE-TREE significantly improves prime editing efficiency in hPSCs.
- Real-time fluorescence-based enrichment facilitates isolation of edited cells.
- The system is adaptable across cell types and compatible with various prime editing strategies.
Conclusions:
- PINE-TREE addresses the challenge of low prime editing efficiency in hPSCs.
- This system streamlines the selection of edited cells, reducing labor.
- PINE-TREE is a valuable tool for genome engineering, disease modeling, and regenerative medicine.
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