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Enhancing genome editing in hPSCs through dual inhibition of DNA damage response and repair pathways – Nature Communications

Ethical statement

All hESCs and iPSCs experiments were performed at the Seoul National University and followed the 2016 Guidelines for Stem Cell Research and Clinical Translation released by the International Society for Stem Cell Research (ISSCR). hESCs and iPSCs work was reviewed and approved by the Institutional Review Board at Seoul National University (SNU IRB protocol #2305/003-014).

Plasmid construction

p3s-Cas9-HN (addgene # 104171, from Dr. Jin-Soo Kim), pCMV CBEmax (addgene # 119801, from Dr. David Liu), pCMV-AncBE4max (addgene # 112094, from Dr. David Liu), T7-p53DD-pcDNA3 (addgene # 25989, from Dr. William Kaelin), AncBEStem and PE4stem plasmids were used in this research. BE4stem and PE4stem were constructed by Gibson cloning using Gibson Assembly Master Mix (NEB #E2611). Additional UGI in BE4stem was amplified from pCMV-BE3 (addgene # 73021, from Dr. David Liu) and p53DD in AncBE4stem and PE4stem was amplified from T7-p53DD-pcDNA3 (addgene # 25989) by PCR. PCR was performed with a KOD Multi & Epi PCR kit (TOYOBO).

Cell culture and transfection

H9 (WA09, WiCell Research Institute) hESC and iPSCs (BJ-iPSCs) were grown in StemMACS media (Miltenyi-Biotec) containing 50 mg/mL Gentamicin on dishes coated with Matrigel (BD Biosciences). 200 mL of Matrigel was diluted in 16 mL of chilled DMEM/F-12 fluid for the Matrigel coating (Gibco). A culture plate was doused with diluted Matrigel and then incubated for one hour in a cell culture incubator. Dulbecco’s phosphate-buffered saline (DPBS) was used to cleanse and separate hESCs before the transfer (#561527, BD Biosciences). Three rounds of DMEM/F-12 media washing were performed on detached cells. After washing, the cells were resuspended in 1 mL of StemMACS medium and then plated on a Matrigel-coated plate (Gibco). According to the standardized protocol for electroporation of hPSCs, gene delivery with the electroporator (NEPA-21, NEPAGENE), hPSCs were rinsed with DPBS and detached with Accutase (#561527, BD Biosciences). Cells were resuspended and diluted to 1 × 106 cells per 100 μL with Opti-MEM (#31985070, Gibco) after three rounds of Opti-MEM washing (#31985070, Gibco). 3 μg of the sgRNA or pegRNA vector and 2 μg of the Cas9, BE, or PE vectors were added to the cell solution. Additional 2 μg of siUNG and/or p53DD overexpression vector were added to the cell mixture for siUNG and/or p53DD overexpression vector, respectively. The same amount of siNC and pcDNA 3.0 was added to the cell solution for the control of siUNG and p53DD respectively. The electroporation was performed with NEPA-21 electroporator with 175 V, 2.5 ms of poring pulse as described20. Dissociated cells after electroporation were plated into a culture dish with 10 μM of Y-27632.

Targeted deep sequencing

At three days following transfection, genomic DNA was extracted from Cas9-, BE-, or PE-transfected cells using a Wizard Genomic DNA Purification Kit (#A1120, Promega) for the purpose of analyzing editing effectiveness. A KOD Multi & Epi PCR kit (TOYOBO) was used to amplify the target sites in order to create the sequencing library. These libraries were sequenced utilizing MiniSeq using an Illumina TruSeq HT Dual Index system. In a nutshell, the Illumina MiniSeq platform was used to perform paired-end read sequencing on an equal number of PCR amplicons. Following MiniSeq, paired-end reads were examined by utilizing BE-analyzer62 and PE-analyzer63 to analyze genome editing outcomes. The targeted deep sequencing was provided by Macrogen. Inc.(https://www.macrogen.com/ko/main).

Editing efficiency averaging and normalization

The arithmetic mean of each experiment was used to compute the average value of editing efficiency for each target. The arithmetic mean of the individual targets was used to compute the average value of editing efficiency in each cell line. By dividing the average value of the editing efficiency of each target from perturbation (such as siUNG or p53DD) by that of the control, editing efficiency was normalized.

Live-cell imaging and cell death assay

Concerning all of the bright field images captured, a light channel optical microscope (CKX-41, Olympus, Tokyo, Japan) or JULI-stage (NanoEntek, Seoul, Korea) was used in accordance with the manufacturer’s protocol. Cell death after electroporation was analyzed by JuLi-Stage live-cell imaging with SYTOX (#S7020, Thermofisher) staining and analyzed by JuLi-Stat as per the manufacturer’s manual.

Fluorescence-based competitive proliferation assay

EGFP-expressing hESC and TP53 mutant hESC were cultured together. Cells were detached with Accutase (#561527, BD Bioscience) and rinsed with DPBS three times before flow cytometry. EGFP+ cells in the total population were measured using flow cytometry.

Whole-exome sequencing

The gDNA sample for Whole-exome sequencing was harvested by using Wizard® Genomic DNA Purification Kit (Promega). Target enrichment and sequencing to generate a gDNA library were prepared from 50 ng input of gDNA using the Twist Library Preparation EF kit (96 samples, PN 101058) and TruSeq-compatible Y-adapters (Ilumina). The DNA quality and quantity were measured by PicoGreen and agarose gel electrophoresis. After the gDNA fragmentation, end-repair and addition of “A” tail were performed, followed by PCR amplification. The final product was quantified by TapeStation DNA screentape D1000 (Agilent) and PicoGreen. The Ilumina platform generates raw images and base calling with an integrated primary analysis software RTA. FASTQ files were generated by Illumina package bcl2fastq v2.20.0. The sequencing quality was validated by FastQC.

RNA-seq and whole-exome sequencing data analysis

The data results of RNA-seq and whole-exome sequencing were aligned to the Human Reference Genome (GRCh38) using BWA-mem with the default option. The alignment results were sorted using samtools. For detailed analysis of substitutions, REDItools2 (https://github.com/BioinfoUNIBA/REDItools2) was applied as described previously64. Substitutions were identified based on the following criteria: (i) The depth of coverage at the substitution site exceeds 10 in both CRISPR-treated and control samples, (ii) The substitution frequency surpasses 1% in the CRISPR-treated sample, and (iii) The substitution frequency remains below 1% in the control sample. These substitutions were analyzed in two distinct contexts: (i) C to T substitutions in samples treated with BEs; and (ii) all types of substitutions in samples treated with PEs. The plots were generated in Python using matplotlib and seaborn module.

Large deletion analysis using Nanopore

The targeted regions were amplified using long-range PCR with KOD multi & epi DNA polymerase (TOYOBO, KME-101). The primers used in long-range PCR were designed using Primer-BLAST. The PCR products were purified using AMPure XP beads (BECMAN COULTER, #A63881). The purified samples, quantified to 200 fmol, were used for Nanopore library preparation. The Nanopore library was prepared for R10.4.1 Minion Flow cell (Oxford Nanopore Technologies, FLO-MIN106D) using Ligation Sequencing Kit V14 (Oxford Nanopore Technologies, SQK-LSK114). The prepared library was sequenced on the MinION sequencer (Oxford Nanopore Technologies, Mk1B) using the 260 bps option. To generate FATSQ files, the sequencing outputs were processed using guppy basecaller, employing the super high accuracy module (dna_r10.4.1_e8.2_260bps_sup.cfg). The FASTQ files were aligned to the reference sequence using a guppy aligner with the default option. The alignment results were analyzed using Python. The mutations were classified into WT, deletions, insertions, and large deletions based on the length of mutations that spanned the cleavage sites±100 bp. The Python codes were uploaded to GitHub (https://github.com/Gue-ho/STEM_BE_PE_LD_Analysis).

Statistical analysis

The mean values and standard deviation are used to express the quantitative data (SD). Statistical analysis was performed using the GraphPad Prism 10.2.2. Software (SanDiego, CA). For hypothesis testing, analysis of variance(ANOVA), and Student’s t-test were used respectively. In order to be considered statistically significant, values had to be less than 0.05 (*p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001, 95% CI). The non-significant comparison was annotated as “ns”. One-way ANOVA was used for the comparison of the conversion ratio between multiple groups (Fig. 1D, E and S1E, F, S3B, 4B, 4D, 4E, S5B). Two-way ANOVA was used for the comparison of cell death between Mock and p53DD expression group (Fig. 1B, C and S1B, C, 3C, S3A) in a time-dependent manner. Student’s t-test (two-tailed) was used for the comparison of two unpaired groups (S1D, G, 2D, 2F, 3G, 3H, 3J, 4G, 4H, 4K, S4D). Post-hoc test p-values in figures have been corrected for multiple comparisons via the Prism recommendation (Tukey or Dunnett) method.

For each figure, the numbers (n) of samples in each experimental group were as follows:

Figure 1B: n = 3 biologically independent samples for Mock and p53DD. Two-way ANOVA; Time x Column Factor F(16,32) = 4.877, p < 0.0001. C: n = 3 biologically independent samples for Mock and p53DD. 2-Way ANOVA; Time x Column Factor F(16,64) = 1.843, p = 0.0441/Right panel of D: n = 21 biologically independent samples for Mock and p53DD, n = 20 biologically independent samples for siUNG and BE4DI. One-way ANOVA, p < 0.0001; Dunnett’s post-hoc test p-values corrected for multiple comparisons: Mock vs. siUNG Adjusted p < 0.0001, Mock vs. p53DD Adjusted p = 0.0003, Mock vs. BE4DI Adjusted p < 0.0001./Right panel of E:  n= 21 biologically independent samples for Mock and p53DD, n = 20 for siUNG and BE4DI. One-Way ANOVA Adjusted  p < 0.0001; Dunnett’s post-hoc test p-values corrected for multiple comparisons: Mock vs. siUNG Adjusted p < 0.0001, Mock vs. p53DD Adjusted p = 0.8270, Mock vs. BE4DI Adjusted p < 0.0001.

Figure S1B: n = 3 biologically independent samples for Mock and p53DD, 2-Way ANOVA; Time x Column Factor F(14,56) = 21.17, p < 0.0001./Right panel of D: n = 12 biologically independent samples for Mock and p53DD. Unpaired Student’s t-test (two-tailed), p = 0.5309/Right panel of E: n = 20 biologically independent samples for p53DD and Mock, n = 19 biologically independent samples for siUNG and BE4DI. One-way ANOVA, p < 0.0001; Dunnett’s post-hoc test p-values corrected for multiple comparisons: Mock vs. siUNG Adjusted p = 0.1123, Mock vs. p53DD Adjusted p = 0.0255, Mock vs. BE4DI p = 0.0151 /Right panel of F: n = 21 biologically independent samples for Mock and p53DD, n = 20 biologically independent samples for siUNG and BE4DI. One-way ANOVA, Adjusted p < 0.0001; Dunnett’s post-hoc test p-values corrected for multiple comparisons: Mock vs. siUNG p < 0.0001, Mock vs. p53DD Adjusted p = 0.7977, Mock vs. BE4DI Adjusted p < 0.0001/Right panel of G: n = 3 biologically independent samples for Mock and p53DD of HEK2, unpaired Student’s t-test (two-tailed), p = 0.0065 & n = 3 biologically independent samples for Mock and p53DD of HEK4, unpaired Student’s t-test, p < 0.0001

Figure 2D: n = 18 biologically independent samples for AncBE4max, n = 17 biologically independent samples for AncBE4stem. Unpaired Student’s t-test (two-tailed), p = 0.0002 for C to T and 0.0001 for C to G./F: n = 3 biologically independent samples for AncBE4max and AncBE4stem. Unpaired Student’s t-test (two-tailed), p = 0.2378.

Figure 3B: n = 5 for every group, one-way ANOVA p < 0.0001; Tukey’s post-hoc test p-values corrected for multiple comparisons: Mock(Cas9 only) vs. Cas9 Adjusted p < 0.0001, Mock (Cas9 only) vs. PE2 Adjusted p = 0.0017, Mock (Cas9 only) vs. PE2 + DD Adjusted p = 0.9373. C: n = 3 for Mock and p53DD. Two-way ANOVA; Time x Column Factor F(16,64) = 28.65, p < 0.0001./G: n = 12 biologically independent samples, unpaired Student’s t-test (two-tailed), p = 0.0022/H: n = 12 for PE5max, n = 11 biologically independent samples for PE5stem. Unpaired Student’s t-test (two-tailed), p < 0.0001/J: n = 3, unpaired Student’s t-test (two-tailed), p = 0.2378.

Figure S3A: n = 3 biologically independent samples, two-way ANOVA; Time x Column Factor F(19,76) = 1.925, p = 0.0239./B: n = 3 biologically independent samples, One-way ANOVA, p = 0.0001; Dunnett’s post-hoc test p-values corrected for multiple comparisons: PE2 vs. PE2DD Adjusted p = 0.0475, PE2DD vs. PE4 Adjusted p = 0.0007.

Figure 4B: n = 3 biologically independent samples for every group, One-way ANOVA p < 0.0001; Dunnett’s post-hoc test p-values corrected for multiple comparisons: Mock vs. Cas9 Adjusted p < 0.0001, Cas9 vs. PE2 Adjusted p = 0.0010, PE2 vs. PE2 + DD Adjusted p = 0.4796/D: n = 9 for Mock and n = 12 for every other group, one-way ANOVA p < 0.0001; Dunnett’s post-hoc test p-values corrected for multiple comparisons: Mock vs. siUNG Adjusted p < 0.0001, Mock vs. p53DD Adjusted p = 0.9227, Mock vs. BE4DI Adjusted p < 0.0001./E: n = 9 biologically independent samples for Mock and n = 12 biologically independent samples for siUNG, p53DD and BE4DI, One-way ANOVA p < 0.0001; Dunnett’s post-hoc test p-values corrected for multiple comparisons; Mock vs. siUNG Adjusted p < 0.0001, Mock vs. p53DD Adjusted p = 0.8158, Mock vs. BE4DI Adjusted p < 0.0001/Left panel of G (C to T): n = 12 biologically independent samples for AncBE4max and n = 11 biologically independent samples for AncBE4stem, unpaired Student’s t-test (two-tailed), p = 0.0045& Right panel of G(C to G): n = 12 biologically independent samples for AncBE4max, n = 11 biologically independent samples for AncBE4stem, unpaired Student’s t-test (two-tailed), p < 0.0001/H: n = 4 for PE2 and PE4, unpaired Student’s t-test (two-tailed), p = 0.0435/K: n = 12 biologically independent samples for both group, unpaired Student t-test (two-tailed), p < 0.0001.

Figure S5Bn = 15 biologically independent samples for Mock, n = 23 biologically independent samples for PE and PE2 + DD, one-way ANOVA p < 0.0001; Dunnett’s post-hoc test p-values corrected for multiple comparisons, Mock vs. PE Adjusted p < 0.0001, Mock vs. PE2 + DD Adjusted p = 0.0007, PE vs. PE2 + DD Adjusted p = 0.7055.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.