Engineered base editors with reduced bystander editing through directed evolution

Area of Science:

• Molecular Biology
• Genetics
• Biotechnology

Background:

• Base editors offer precise genome modification but suffer from bystander edits, limiting their use.
• Current precision strategies often reduce efficiency and are sequence-specific.

Purpose of the Study:

• To develop an improved base editing system with minimized bystander edits and maintained high efficiency.
• To establish a scalable framework for engineering highly precise base editors.

Main Methods:

• Designed and tested 3'-extended guide RNAs for improved specificity.
• Employed a precision-driven phage-assisted evolution system.
• Utilized protein language models for enzyme variant evolution.

Main Results:

• Identified context-dependent guide RNA variants that enhanced specificity.
• Evolved adenine base editor variants 2-3x more precise than ABE8e.
• Achieved high editing efficiency across diverse pathogenic contexts in vitro.

Conclusions:

• Developed a parallel engineering approach optimizing guide RNAs and deaminase enzymes.
• Created a scalable framework for base editor precision engineering.
• Addressed a key challenge in genome editing, enhancing therapeutic potential.