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Efficient mitochondrial A-to-G base editors for the generation of mitochondrial disease models

Nature Biotechnology (2025)Cite this article

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Abstract

Existing A-to-G base editors for mitochondrial DNA (mtDNA) are limited by low efficiency. We used directed evolution to discover variants of the TadA-8e base editors that have substantially increased activity and expanded targeting compatibility for both nuclear and mitochondrial adenine base editing, especially in previously unfavored sequence contexts. The engineered mtDNA editors (eTd-mtABEs) showed up to 87% editing efficiency in human cells, with greatly reduced DNA and RNA off-target effects. Strand-selective A-to-G editing was enhanced by an average of 3.2-fold with substitution of DddA to DNA nickases in eTd-mtABE backbones compared to mitochondrial ABEs. In rat cells, editing efficiencies of eTd-mtABEs were up to 145-fold higher compared to split DddA transcription activator-like effector-linked deaminase. We also generated rats with sensorineural hearing loss by installing targeted mutations with frequencies of up to 44% through embryonic injection. The developed eTd-mtABEs are efficient and precise mtDNA-engineering tools for basic research and translational studies.

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Fig. 1: Protein engineering of adenine deaminases in CRISPR-based ABEs.
Fig. 2: Characterization of enhanced CRISPR-derived ABEs.
Fig. 3: Evolved TadA variants improve A•T-to-G•C editing in mtDNA.
Fig. 4: TadA variants enhanced specificity of eTd-mtABE and strand-biased mtDNA editing.
Fig. 5: Application of eTd-mtABEs to install pathogenic mutations in human cells.
Fig. 6: Mitochondrial disease models generated by eTd-mtABEs in rats.

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Data availability

HTS data were deposited to the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) database under BioProjects PRJNA1249660, PRJNA1249952 and PRJNA1249944. Mitochondrial WGS data were deposited to the NCBI SRA database under BioProject PRJNA1249252. There are no restrictions on data availability. Source data are provided with this paper.

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Acknowledgements

We thank Y. Zhang from the Flow Cytometry Core Facility of School of Life Sciences at ECNU and acknowledge the support from the ECNU public platform for innovation (011). We thank L. Ji (HAVAS) for designing schematic diagrams. This work was partially supported by grants from the National Natural Science Foundation of China (32025023, 32230064 and 32311530111 to D.L.; 31930016 to W.W.; 82230002 to M.L.), National Key R&D Program of China (2024YFC3407900 to L.C.; 2023YFC3403400 to D.L.), Shanghai Municipal Commission for Science and Technology (21JC1402200 and 24J22800400 to D.L.), Young Elite Scientist Sponsorship Program by China Association for Science and Technology (2023QNRC001 to L.C.), Shanghai Oriental Talent Plan (QNZH2024131 to L.C.), Fellowship of China Postdoctoral Science Foundation (8206400139 to Z.Y.) and Lingang Laboratory. D.L. is a Shanghai Academy of Natural Sciences exploration scholar.

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  1. These authors contributed equally: Liang Chen, Mengjia Hong, Changming Luan.

Authors and Affiliations

  1. Shanghai Frontiers Science Center of Genome Editing and Cell Therapy, Shanghai Key Laboratory of Regulatory Biology, School of Life Sciences, East China Normal University, Shanghai, China

    Liang Chen, Mengjia Hong, Changming Luan, Meng Yuan, Xinyuan Guo, Hao Huang, Hongyi Gao, Dan Zhang, Dihao Meng, Molin Huang, Mingyao Liu, Liangcai Gao, Gaojie Song & Dali Li

  2. Lingang Laboratory, Shanghai, China

    Liang Chen, Yiming Wang & Xiaohua Dong

  3. School of Pharmacy, East China Normal University, Shanghai, China

    Liang Chen & Dali Li

  4. Key Laboratory of Brain Functional Genomics of Ministry of Education, Shanghai Key Laboratory of Brain Functional Genomics, School of Life Sciences, East China Normal University, Shanghai, China

    Yue Fang & Xiaoming Zhou

  5. New York University-East China Normal University Institute of Brain and Cognitive Science, New York University, Shanghai, Shanghai, China

    Yue Fang & Xiaoming Zhou

  6. School of Life Science and Technology, ShanghaiTech University, Shanghai, China

    Xiaohua Dong

  7. BRL Medicine, Inc., Shanghai, China

    Xi Chen & Mingyao Liu

  8. Biomedical Pioneering Innovation Center, Peking-Tsinghua Center for Life Sciences, Peking University Genome Editing Research Center, State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, China

    Zongyi Yi & Wensheng Wei

  9. Changping Laboratory, Beijing, China

    Wensheng Wei

  10. Shanghai Academy of Natural Sciences (SANS), Shanghai, China

    Dali Li

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Contributions

L.C. and D.L. designed the experiments. L.C., M.H., C.L., M.Y., Y.W., X.G., Y.F., H.H., X.D., H.G., X.C. and L.G. performed the experiments. L.C., M.H., C.L., M.Y., X.G., Y.F., H.H., X.D., D.Z., D.M., M.H., Z.Y., M.L., G.S., X.Z., W.W. and D.L. analyzed the data. L.C. and D.L. wrote the manuscript with input from all authors. L.C. and D.L. supervised the research.

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Correspondence to Liang Chen or Dali Li.

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The authors have submitted patent applications based on the results reported in this study (L.C., D.L., M.H. and C.L.). The remaining authors declare no competing interests.

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Supplementary Figs. 1–7 and Note.

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Supplementary Tables 1–3

Primer sequences used in this study, target sites used in this study and general architecture and DNA or amino acid sequences of plasmids used in this study.

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Chen, L., Hong, M., Luan, C. et al. Efficient mitochondrial A-to-G base editors for the generation of mitochondrial disease models. Nat Biotechnol (2025). https://doi.org/10.1038/s41587-025-02685-x

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