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<p>Base editors (BEs), covalent fusions of a cytosine or adenine deaminase with a nuclease-impaired CRISPR protein, mediate site-specific conversion of C:G to T:A (CBEs) or A:T to G:C (ABEs) in the genome. Existing BEs modify all cytosines or adenines within the editing window, which limits their precision. Here we engineer nucleotide and context specificity of the <i>Escherichia coli</i> transfer RNA-specific adenosine deaminase (TadA) to pinpoint cytosine editing. Strategically sampling multiple nucleic-acid-recognition hotspots through directed evolution, we develop 16 TadA-derived N<Emphasis Type="Underline">C</Emphasis>N-specific deaminases that cover every possible −1 and +1 context for a target cytosine, providing on-demand deaminase choices for editor customization. We apply these variants to (1) correct disease-associated T:A-to-C:G transitions documented by ClinVar, achieving greater accuracy than conventional CBEs in 81.5% of cases, and (2) model two cancer-driver mutations—<i>KRAS</i><sup>G12D</sup> (A<Emphasis Type="Underline">C</Emphasis>C) and <i>TP53</i><sup>R248Q</sup> (C<Emphasis Type="Underline">C</Emphasis>G)—in vitro. Our approach offers a general strategy to access precise base editors for potential clinical applications.</p>

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High-precision cytosine base editors by evolving nucleic-acid-recognition hotspots in deaminase

  • 期刊论文

  • 发表日期：

    2025年7月7日

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  • Yuan Wu,
  • Yu-Lan Xiao,
  • Weixin Tang

摘要

Base editors (BEs), covalent fusions of a cytosine or adenine deaminase with a nuclease-impaired CRISPR protein, mediate site-specific conversion of C:G to T:A (CBEs) or A:T to G:C (ABEs) in the genome. Existing BEs modify all cytosines or adenines within the editing window, which limits their precision. Here we engineer nucleotide and context specificity of the Escherichia coli transfer RNA-specific adenosine deaminase (TadA) to pinpoint cytosine editing. Strategically sampling multiple nucleic-acid-recognition hotspots through directed evolution, we develop 16 TadA-derived NCN-specific deaminases that cover every possible −1 and +1 context for a target cytosine, providing on-demand deaminase choices for editor customization. We apply these variants to (1) correct disease-associated T:A-to-C:G transitions documented by ClinVar, achieving greater accuracy than conventional CBEs in 81.5% of cases, and (2) model two cancer-driver mutations—KRASG12D (ACC) and TP53R248Q (CCG)—in vitro. Our approach offers a general strategy to access precise base editors for potential clinical applications.