Research ArticleAPPLIED SCIENCES AND ENGINEERING

Single C-to-T substitution using engineered APOBEC3G-nCas9 base editors with minimum genome- and transcriptome-wide off-target effects

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Science Advances  15 Jul 2020:
Vol. 6, no. 29, eaba1773
DOI: 10.1126/sciadv.aba1773
  • Fig. 1 Base editing specificity of the wild-type A3G-nCas9 fusions.

    (A) Schematic showing the protein architecture of base editors. BE4max is used to replace the rAPOBEC1 with either full-length (NTD + CTD) or CTD-only human A3G to construct A3G-BE2.1 or A3G-BE4.4, respectively. Linkers between functional domains are shown as horizontal blue lines. NLS, nuclear localization signal; UGI, uracil glycosylase inhibitor. (B) C-to-T editing efficiency and specificity of A3G-BE2.1 and A3G-BE4.4 at EMX1 #1 and FANCF #a3 sites bearing the CC motif (red). (C) Nine endogenous sites of HEK293T bearing either CC or CCC motif (red) within the canonical BE4max activity window. Each PAM and the sequence motif identifying the nucleotides at +1 and −2 positions from the target C (underlined) are shown. (D) C-to-T editing efficiency and specificity of BE4max and A3G-BE4.4 at the endogenous sites listed in (C). Bar figures of (B) and (D) show means and error bars representing SD of n = 2 and n = 3 independent biological replicates performed on different days, respectively. Statistical significance shown on top of each bar using two-tailed Student’s t test compares to editing efficiency of the preceding bystander C of the same BE. For example, t test was performed between the BE4max editing efficiencies of C8 and C9 at DMD #1 site. ns (not significant), *P < 0.05, ***P < 0.001, ****P < 0.0001.

  • Fig. 2 Engineering A3G-BEs with enhanced base editing efficiency.

    (A) Set of residue mutations of A3G for improving catalytic activity (set A), ssDNA binding (set B), and protein solubility (set C) listed on each row. Counting of the residue number starts with the first residue of the original full-length A3G. (B) Screening of A3G-BE mutants at EMX1 #1 site to determine variants with enhanced editing efficiency and retained sequence specificity. C-to-T editing efficiencies are represented as bidirectional bars with values for the cognate C6 (blue) on the right and the bystander C5 (red) on the left. (C) An enlarged view of the interactions of Tyr315 (green sticks) with the ssDNA substrate (yellow sticks). The hydrogen bond between the 5′ phosphate group of the DNA backbone and the hydroxyl group of Tyr315, and the π–π interaction between the rings of the target cytidine (dC0) and Tyr315 are represented as dashed lines. (D) C-to-T editing efficiency and specificity of A3G-BE5.13 and A3G-BE5.14 at three endogenous sites previously poorly edited by A3G-BE4.4. Panels (B) and (D) show means and error bars representing SD of n = 3 independent biological replicates performed on different days. For (D), statistical significance shown on top of each bar using two-tailed Student’s t test compares to editing efficiency of the preceding bystander C of the same BE. ns (not significant), **P < 0.01, ***P < 0.001, ****P < 0.0001.

  • Fig. 3 Base editing specificity of A3G-BEs across the protospacer regions and the activity window size.

    (A) Heat maps are showing average C-to-T editing efficiencies of n = 3 independent biological replicates of BE4max, A3G-BE4.4, A3G-BE5.13, and A3G-BE5.14 at eight endogenous sites containing the preferential CC or CCC motif across the whole region within the protospacers. The cognate Cs predicted to be preferentially editable by A3G-BEs are indicated by the black triangles. (B) Average C-to-T base editing frequencies at each protospacer position from the six poly-C endogenous sites shown in fig. S4. Bidirectional arrows in between vertical dashed lines show the base-editable ranges within the protospacer region by the indicated A3G-BEs (C) Schematic representation of the activity window sizes of A3G-BE4.4, A3G-BE5.13, and A3G-BE5.14, with NGG PAM shown as positions 21 to 23. Standard, light, and near-transparent green represent the predicted relative base editing activity within the approximate regions of the protospacer.

  • Fig. 4 Modeling and correcting human pathogenic SNPs in vitro using A3G-BEs.

    (A) Sequences of the protospacers and PAMs (blue) for model 1 (cystic fibrosis), model 2 (hypertonic myopathy), and model 3 (transthyretin amyloidosis). Position of the disease-relevant C>T (or G>A) point mutations are red and indicated by black triangles shown with the nucleotide numbers within the disease-associated genes. (B) Percent of alleles modified to the indicated genotypes following the treatment of BE4max and A3G-BEs for generating the three models presented in (A). (C) Sequences of the protospacers and PAMs (blue) for correction 1 (hereditary pyropoikilocytosis), correction 2 (cystic fibrosis), and correction 3 (holocarboxylase synthetase deficiency), bearing T>C (or A>G) point mutations for which the positions are indicated with black triangles showing the nucleotide numbers within the disease-associated genes. (D) Percent of alleles modified to the indicated genotypes following the treatment of BE4max and A3G-BEs for correcting the three disease-associated variants presented in (C). Panels (B) and (D) show means and error bars representing SD of n = 3 independent biological replicates performed on different days. Statistical significance shown on top of each bar using two-tailed Student’s t test compares to the percentages of perfectly generated/corrected alleles by BE4max. ns (not significant), *P < 0.05, ****P < 0.0001.

  • Fig. 5 Genome and transcriptome-wide off-target effects by A3G-BE5.13.

    (A) Scheme of the experimental workflow of GOTI. (B) Comparison of the total number of detected DNA off-target SNVs using the GOTI method. The number of SNVs identified in Cre-, BE3-, and A3G-BE5.13–treated embryos were 14 ± 12 (SD; n = 2), 283 ± 32 (SD; n = 6), and 20 ± 5 (SD; n = 2), respectively. (C) Distribution of DNA mutation types in each group. (D) Scheme of the experimental workflow of identifying transcriptome-wide off-target SNVs through RNA-seq. (E) Comparison of the total number of detected RNA off-target SNVs. The number of SNVs identified in nCas9-, BE4max-, A3G-BE5.13–treated cells were 2669 ± 712 (SD; n = 2), 198,688 ± 37,775 (SD; n = 2), and 1410 ± 39 (SD; n = 2), respectively. (F) Distribution of RNA mutation types in each group. For (C) and (F), the number in each cell indicates the percentage of a certain type of mutation among all mutations. For (B) and (E), each data point represents independent biological replicates performed on different days.

Supplementary Materials

  • Supplementary Materials

    Single C-to-T substitution using engineered APOBEC3G-nCas9 base editors with minimum genome- and transcriptome-wide off-target effects

    Sangsin Lee, Ning Ding, Yidi Sun, Tanglong Yuan, Jing Li, Qichen Yuan, Lizhong Liu, Jie Yang, Qian Wang, Anatoly B. Kolomeisky, Isaac B. Hilton, Erwei Zuo, Xue Gao

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