Person:

Newby, Gregory

Base editors use DNA-modifying enzymes targeted with a catalytically impaired CRISPR protein to precisely install point mutations. Here, we develop phage-assisted continuous evolution of base editors (BE–PACE) to improve their editing efficiency and target sequence compatibility. We used BE–PACE to evolve cytosine base editors (CBEs) that overcome target sequence context constraints of canonical CBEs. One evolved CBE, evoAPOBEC1-BE4max, is up to 26-fold more efficient at editing cytosine in the GC context, a disfavored context for wild-type APOBEC1 deaminase, while maintaining efficient editing in all other sequence contexts tested. Another evolved deaminase, evoFERNY, is 29% smaller than APOBEC1 and edits efficiently in all tested sequence contexts. We also evolved a CBE based on CDA1 deaminase with much higher editing efficiency at difficult target sites. Finally, we used data from evolved CBEs to illuminate the relationship between deaminase activity, base editing efficiency, editing window width and byproduct formation. These findings establish a system for rapid evolution of base editors and inform their use and improvement.

Prime editing enables the installation of virtually any combination of point mutations, small insertions or small deletions in the DNA of living cells. A prime editing guide RNA (pegRNA) directs the prime editor protein to the targeted locus and also encodes the desired edit. Here we show that degradation of the 3′ region of the pegRNA that contains the reverse transcriptase template and the primer binding site can poison the activity of prime editing systems, impeding editing efficiency. We incorporated structured RNA motifs to the 3′ terminus of pegRNAs that enhance their stability and prevent degradation of the 3′ extension. The resulting engineered pegRNAs (epegRNAs) improve prime editing efficiency 3–4-fold in HeLa, U2OS and K562 cells and in primary human fibroblasts without increasing off-target editing activity. We optimized the choice of 3′ structural motif and developed pegLIT, a computational tool to identify non-interfering nucleotide linkers between pegRNAs and 3′ motifs. Finally, we showed that epegRNAs enhance the efficiency of the installation or correction of disease-relevant mutations.