Chromosomal context and epigenetic mechanisms control the efficacy of genome editing by rare-cutting designer endonucleases

Meganucleases

MNs derived from I-CreI were engineered as described previously (16,27,28). All MNs were used under a single chain format, as described in Grizot et al. (16), except for CAPNS1m and NACAm which were used in 293-H cells under a previously described heterodimeric format (16,28).

293-H cells culture and transfections

Human 293-H cells (Life Technologies, Carlsbad, CA, USA) and hamster CHO-KI cells (ATCC) were cultured at 37°C with 5% CO₂ in complete medium DMEM and F12-K, respectively, supplemented with 2 mM l-glutamine, penicillin (100 IU/ml), streptomycin (100 µg/ml), amphotericin B (Fongizone: 0.25 µg/ml, Life Technologies,) and 10% FBS. For extrachromosomal and survival assays, CHO-KI cells were plated at 2500 cells per well in 96-well plate. The next day, cells were transfected with 200 ng of total DNA using Polyfect transfection reagent according to the supplier’s (Qiagen) protocol. In the survival assay, a constant amount of GFP-encoding plasmid (10 ng) was added to various amounts of MN expression vectors. For mutagenesis and gene targeting assays, 293-H cells were plated at a density of 1.2 × 10⁶ cells per 10 cm dish. The next day, cells were transfected with 3 or 5 µg of plasmid DNA using Lipofectamine 2000 transfection reagent (Life Technologies) according to the manufacturer’s protocol.

Extrachromosomal activity assays in CHO-KI and HEK293 cells

Activity in mammalian cells was measured as previously reported by Grizot et al. (29) These assays are used to monitor the activity of the MNs in a non-chromatinized template, an activity that is a function of MN expression and specific activity.

Cell survival assay

The CHO-KI cell line was transfected as described above, with varying amounts of MN expression vector and a constant amount of GFP-encoding plasmid. GFP levels were monitored by flow cytometry (Guava EasyCyte, Guava Technologies) on Days 1 and 6 post-transfection. Cell survival was calculated as a ratio (MN-transfected cells expressing GFP on Day 6/control transfected cells expressing GFP on Day 6) corrected for the transfection efficiency determined on Day 1.

Area under the curve scores

Area under the curve (AUC) score is used to quantify (i) the activity of MN in extrachromosomal assays in CHO-KI and 293-H cells; (ii) cell survival in the toxicity assay; (iii) chromatin resistance to microccocal nuclease digestion at a given locus. Examples are given in Figure 2b and Supplementary Figure S2c. The classical approach based on the use of log-normal model (30) showed a very good fitting quality for both survival curves and activity curves (after normalization with respect to the maximal activity level). All the statistics done in this study are summarized in Supplementary Table S6.

Western blot

293-H and CHO-KI cells were plated at 1.2 × 10⁶ and 2 × 10⁵ cells per 10 cm dish, respectively. These two cell lines were transfected with the same DNA plasmid-encoding MN: 3 µg for 293-H cells and 1 µg for CHO-K1 cells, according to the usual transfection condition. Two days post-transfection, total protein extraction was performed with RIPA (150 mM sodium chloride, 1% NP-40, 0.5% sodium deoxycholate, 01% SDS, 50 mM Tris pH 8.0) buffer. Western blot was performed on 10 µg of total protein extract. The MN expression was revealed using a specific I-CreI antibody. Beta-tubulin antibody (Cell signaling 2128) was used as loading control. Quantification of signal was performed on low exposed blots using ImageJ software. Results were expressed as a ratio between MN and tubulin signals.

Monitoring of MN-induced TM

293-H cells were transfected with 3 µg of MN expressing vector or empty vector, except for ADCY9-induced mutagenesis where 293-H cells were transfected with 5 µg of MN-encoding plasmid. Two days post-transfection, genomic DNA was extracted and targets studied were amplified with specific primers flanked by specific adaptators needed for HTS sequencing (For: CCATCTCATCCCTGCGTGTCTCCGACTCAG-Tag and Rev: BiotinTEG/ CCTATCCCCTGTGTGCCTTGGCAGTCTCAG) on the 454 sequencing system (454 Life Sciences). An average of 10 000 sequences per sample were analysed. Sequence of the primers used to amplify the targeted locus are indicated on Supplementary Table S3. In clonal experiments (Rag1m and DMD21m), cells were plated after treatment and individual clones were grown. After 21 days, DNA extraction was performed with the ZR-96 genomic DNA kit (Zymo research) according to the supplier’s protocol. The region of the target was amplified by PCR as described above, and PCR product was sequenced.

Monitoring of MN-induced HGT

293-H cells were co-transfected with 3 µg of MN expressing vector, and 2 µg of DNA matrix and seeded at 10 cells per well in 96-well plate, and HGT was monitored by PCR 21 days later. Alternatively, cells were plated and individual colonies were picked 2–3 weeks later in 96-well plates and analysed (Supplementary Table S1). All DNA matrices comprise 1 kb of homologous sequences located on both sides of the MN recognition site. The two homology arms are separated by a heterologous fragment of 29 bp or 1.7 kb. DNA extraction was performed with the ZR-96 genomic DNA kit (Zymo research) according to the supplier’s protocol. The detection of targeted integration is performed by specific PCR amplification using a primer located within the heterologous insert of the DNA repair matrix, and another one located on the genomic sequence outside of the homology. In pool experiments (10 cells/well), HGT frequencies were normalized to plating efficiencies, e.g. 0.33. This method was validated by the good correlation between the frequencies in clonal analysis and the frequencies in pool analysis (Supplementary Table S1). Sequence of the primers used to amplify the homologous regions is available upon request. Sequence of the primers used to diagnostic targeted integrations are indicated on Supplementary Table S3. HGT was also confirmed by Southern Blot for Rag1m, DMD21m, ADCY9m, XPC4m and CLS3690m.

Simultaneous monitoring of MN-induced HGT and TM

HEK293-H cells were co-transfected with plasmids expressing the MN and 2 µg of repair matrix. In each experiment, we amplified the region surrounding the target site by nested PCR using deep sequencing primers, with the first set of primers being located outside of the repair matrix (see Supplementary Table S3 for primer sequence). We measured both HGT and TM by deep sequencing of the amplicons.

CHART-PCR

Cells were resuspended in 1 ml of sucrose buffer supplemented with 0.5% of NP-40. The pellet nuclei was resuspended in ice-cold nuclei buffer supplemented with DTT and PMSF at a concentration of 2 × 10⁴ nuclei/µl. Digestion was performed on 1.5 × 10⁵ nuclei at room temperature for 15 min with 10–500 U of micrococcal nuclease (Biolabs). Restriction cleavage was stopped by the addition of 10 mM EDTA. DNA was extracted in the presence of proteinase K and then quantify with picogreen (Quant-iT™ PicoGreen® dsDNA Assay, Molecular Probes). Q-PCR was performed in duplicate with specific primers described in Supplementary Table S3. The data are expressed as percentage of Q-PCR signal of undigested sample.

Target selection

We have previously described a combinatorial method to generate MNs that cleave selected sequences in virtually any gene or locus (16,28,31). Briefly, this approach relies on the use of an archive of locally engineered derivatives of the I-CreI MN. These MNs recognize targets differing from the I-CreI target by a few base pairs only, but can be used as building blocks to generate combinatorial libraries of fully redesigned MNs. MNs recognizing specific chosen targets, unrelated to the sequence recognized by the parental I-CreI scaffold, are identified using a high-throughput yeast cell assay. Typically, a MN cleavage site is placed between two direct repeats in a β-galactosidase (LacZ) reporter plasmid, as extra-chromosomal target (Supplementary Figure S1). Cleavage of the target site by the MN in this cell-based assay induces tandem-repeat recombination, by single-strand annealing (SSA) between two truncated copies of the LacZ gene thereby restoring a functional LacZ gene. This method allowed for the identification of a potential cleavable target every 250 bp, with a success rate of 40% at the protein engineering step (32). Based on this principle, we generated a large collection of 37 different engineered MNs, derived from the parental I-CreI natural protein, that cleaved 39 different sequences, specifically designed for genome editing in coding and non-coding sequences of the human genome (Figure 1 and Table 1). In this study, m refers to the MN and t its respective target sequence. For instance, Rag1 designates the chosen locus, Rag1m the MN, and Rag1t, the 22 bp target sequences cleaved by the Rag1 MN. Our selection was prioritized towards coding sequences, given their high potential interest (i.e. gene inactivation and gene correction) and translational relevance (i.e. gene therapy). Consequently, this prioritization resulted in a higher proportion of targets in GC- and CpG-rich regions (Figure 1b).

Characterization of MNs activity based on extrachromosomal cellular assays

A quantitative cell-based assay in CHO-KI and 293-H cells was used to characterize the MN activity of this MN collection was used (Figure 2a and Table 1). This extrachromosomal assay (29,31) is similar to the cellular assay in yeast and allows for a quantitative assessment of MN activity based on LacZ reporter gene expression (Figure 2b). Importantly, the activity measured in this extrachromosomal in vivo cellular assay depends not only on the intrinsic specific activity of the MN, but also on the MN expression level in the target cell. Whereas specific activity can vary widely even between closely related I-CreI derivatives (28,33), MN expression levels can also be strongly affected by the few amino acid substitutions that differ from one engineered MN to another (Figure 2c). Nevertheless, there is a strong correlation in relative MN expression levels in different cell types, at least based on 293-H and CHO-KI cells (Figure 2d).

Most importantly, when comparing MN activity in CHO-KI and 293-H cells, we observed very consistent results (Figure 2e), with linear (Pearson’s r) and non-linear (Spearman’s ρ) correlation coefficients ranging between 0.71 and 0.75, and P ≤ 0.002. We also compared MN activity measured in our CHO-KI cell assay with that obtained with aforementioned yeast assay, that also measures MN-induced tandem repeat recombination on a plasmid-borne reporter system (10,16,21,27). Here again, we observed a very good consistency (r = 0.8; and ρ = 0.79 with P < 2.2 × 10⁻¹⁶ in both cases; Supplementary Figure S1b), suggesting that our extrachromosomal assay in CHO cells is predictive for a wide range of different cell types. This MN activity assay in CHO cells therefore serves as an appropriate and representative assay for MN activity.

MN-induced TM and HGT efficiencies are strongly correlated

MNs were then tested for their efficacy, defined in this study as their ability to induce targeted gene modification at their cognate chromosomal locus in human cells. Results are summarized in Table 1. TM was monitored for all MNs by pyrosequencing of the targeted locus 7 days after transfection of 3 µg of MN-expressing vector (Figure 3a). The locus was amplified by PCR, and an average of 10 000 molecules was sequenced per amplicon. The MN-induced rate varied between background level (up to 0.06% due to PCR and sequencing errors) and 2.4% of the analyzed chromatids (Table 1). HGT was monitored for 18 MNs by PCR in pools of 10 cells grown in 96-well plates, 21 days after transfection, as described previously (16) (Figure 3b). HGT was also monitored in clonal experiments for 4 MNs, with the results confirming the results from pools in all cases (Supplementary Table S1). For the 18 MNs that were characterized for both TM and HGT, a strong linear correlation (r = 0.93 with P = 2 × 10⁻⁸) was observed between the frequency of TM ‘per chromatid’ and the frequency of HGT ‘per cell’ throughout the target genome (Figure 3c). Most importantly, this comprehensive analysis revealed that the efficiency of TM at a given chromosomal locus is predictive of that of HGT and that the HGT/TM ratio is relatively conserved throughout the genome.

In Figure 3c, we compared HGT events per cell and TM events ‘per chromatid’ in 293-H cells. However, these immortalized cells typically do not have a normal diploid genome. Therefore, we refined our analysis and conducted additional studies to simultaneous monitor HGT and TM ‘per chromatid’ by deep sequencing. Events were monitored at Day 2, to alleviate toxicity effect over time. Sixteen measurements were made with seven different MNs (Supplementary Table S2). Again, a very strong linear correlation (r = −0.90 with P = 3 × 10⁻⁶) was observed between the frequency of HGT ‘per chromatid’ and frequency of TM ‘per chromatid’ (Figure 3d, Supplementary Table S2), and in this case, a global HGT/TM ratio of 1.7 could be inferred from the slope of the regression line.

MN efficacies are poorly correlated with their activities based on extrachromosomal substrates

The differences in MN efficacy on chromosomal target loci may reflect different parameters, particularly the activity of a given MN, as measured using extrachromosomal substrates, and/or MN-associated cellular toxicities. However, other parameters may also contribute to these differences in MN efficacy, such as bona fide target site-dependent chromosomal position effects. Consequently, MN efficacy (i.e. TM, HGT) may result from a combination of ‘intrinsic’ factors (i.e. MN activity, MN toxicity) and ‘extrinsic’ factors (i.e. MN target locus).

To assess the contribution of each of these distinct parameters on the overall MN efficacy, we performed a comprehensive quantitative analysis. We first compared MN efficacy based on TM and HGT assays and MN activity based on the extra-chromosomal assay, as measured in CHO-KI and 293-H cells (Figure 4a). Overall, MN efficacies based on the frequency of TM per chromatid correlated poorly with their respective intrinsic activities on extrachromosomal substrates (Figure 4a and b), consistent with the low correlation coefficients and P-values. A somewhat higher correlation was observed only when comparing MN efficacies (based on the frequency of TM per chromatid) with activity in CHO-KI cells (r = 0.40 with P = 10⁻², ρ = 0.41 with P = 8 × 10⁻³), and was statistically significant only when a large sample (n = 39) was characterized (compare with n = 18 on Figure 4a), though the correlation coefficient remained low (r = 0.40). Notably, some of the highest frequencies of indels (as a measure of the frequency of TM per chromatid) were achieved with DMD21m, which has relatively moderate activities in the extrachromosomal assay (Figure 4a and Table 1). Similarly, HGT frequencies were poorly correlated with MN activity in CHO-KI and 293-H cells (Figure 4c and d). These modest correlations contrast with the high consistency observed between the extrachromosomal tests (Figure 2e and Supplementary Figure S1b) and between the two types of efficacy tests (Figure 3c and d).

Hence, the intrinsic activity of a given MN on extrachromosomal substrates is not predictive for its efficacy on chromosomal targets. Therefore, we decided to test the impact of other factors.

MN efficacies are not correlated with their cellular toxicity

It has been shown before that in a population of cells treated with a rare cutting endonuclease, the proportion of cells modified by the nuclease could vary over time, probably due to nuclease toxicity (34). We actually observed a similar phenomenon, whereas treatment with the non-toxic Rag1m molecule results in a stable rate of ∼1% of TM, most of the events generated by CLS4076m at Day 2 (∼5% of TM) have disappeared by Day 13 (Supplementary Figure S2a). Thus, cell death resulting from MN toxicity could impact with apparent efficacy of MN, especially when measured after day several days.

We assessed the toxicity of all MNs featured in this study, using a cell survival assay that was previously validated and relies on decreased green fluorescent protein (GFP) expression as a read-out for cellular toxicity (16,20,35; Supplementary Figure S2b and S2c). Toxicity was MN dose-dependent and typically ranged between that of I-SceI (the most specific reported rare-cutting endonuclease) and I-CreI, with the exception of two MNs (CLS3899 and CLS4633, see Table 1). Importantly, toxicity was found not to be related to the level of activity (r = −0. 15 with P = 0.52; and ρ = −0.14 with P = 0.43).

However, no correlation could be established between toxicity and efficacy. The estimated values of linear (Pearson’s r) and non-linear (Spearman, ρ) correlation coefficients between TM and toxicity are 0.04 and 0.03, respectively, with corresponding P-values of 0.81 and 0.86, respectively. Therefore, we looked for more complex correlations factors. Supplementary Figure S2d features an attempt of correlation between toxicity, on the one hand, and the ratio of the efficacy of TM in 293-H cells versus the activity in the extrachromosomal assay in CHO-KI cell (TM/SSA ratio), on the other. Correlation coefficients are very low, with very high P-values (r = 0.16 with P = 0.42; and ρ = 0.03 with P = 0.86), indicating a lack of correlation, in spite of the relatively large sample size (n = 39). Fitting of TM as a linear function of toxicity and SSA (TM = a*SSA + b*TOX + c), lead to similar results with a = 2.38 (P = 9 × 10⁻³), b = −0.24 (P = 0.55) and c = 7.9385 (P = 2 × 10⁻⁴). This outcome indicates that when measuring the contribution of activity in CHO-KI cells (SSA) and toxicity (TOX) to efficacy, the contribution of activity in CHO-KI cell is significant (P = 9 × 10⁻³), consistent with the results shown in Figure 4a for the same sample, but the contribution of toxicity is not (P = 0.55), consistent with the results of Supplementary Figure S2d.

While toxicity has no direct correlation with the efficacy of TM, it seems that it might play an important role in the dynamic of TM over time. There is a significant correlation between toxicity and the ratio of TM in 293-H at Day 7 versus Day 2 (r = 0.86 P = 6 × 10⁻³; ρ = 0.9, P = 5 × 10⁻³), with more toxic MNs having a bigger drop in the efficacy of TM from Day 2 to Day 7.

In conclusion, whereas toxicity can impact the apparent efficacy of MNs, it cannot account for the global discrepancies observed between the on extrachromosomal and chromosomal targets, and MN efficacy is not solely the consequence of its intrinsic properties (activity and toxicity). Therefore, we decided to test the impact of extrinsic factors, such as chromatin-based position effect.

MN efficacy is strongly correlated with chromosomal position effects

Chromatin-based position effects could impact on MN efficacy by modulating access of the MN, the repair matrix and/or cellular repair factors to the target DNA. Eukaryotic genomes are packaged in chromatin, and nuclease sensitivity remains one of the main methods used to monitor chromatin accessibility and/or the positioning of nucleosomes in vivo (24,25). Nuclease accessibility is known to vary largely across the genome and at least in the promoter region, to correlates with a transcriptionally active state (24,36). In order to assess the possible role of chromatin position effect on genome editing using MN, we first compared (i) the efficacy of different MNs (isoschizomers) at the same locus (ii) the efficacy of the same MN at different loci.

The Rag1m MN cleaves a sequence from the human Rag1 gene (16). DMD21m cleaves a sequence from the 38th intron of the gene (Table 1). Several isoschizomers were obtained when we engineered these proteins, and we compared Rag1m and DMD21m with two additional isoschizomers. At each individual locus, efficacy was found to correlate with activity in CHO-KI cells (Figs. 5a and 5b), with the most active cognate MN giving the highest rates of HGT. However, this correlation was not found when comparing the results achieved at the two loci. For example, the iso2DMDm MN is significantly less active than the iso2RAG1m MN, but has a similar efficacy. Thus, efficacy is correlated with activity in CHO-KI cells only when assessed at the ‘same target locus’. We also characterized CLS3902m, a MN whose cognate target is found four times in the genome. CLS3902m has the same activity as Rag1m, and a slightly higher toxicity (Figure 5c). Examination of TM at three target loci (the fourth one could not be amplified by PCR) gave clearly different frequencies of events, ranging from 0.39% to 1.17% at Day 2 and from 0.13 to 0.75 at Day 7 (Figure 5c), demonstrating locus dependence.

This type of position effect is likely the consequence of chromatin-based differences of target accessibility. We used CHART-PCR (36,37) to test micrococcal nuclease accessibility at 10 loci targeted by eight engineered MNs (Figure 5d), and a nuclease resistance index (AUC) was calculated for each locus, as indicated in figure legend and ‘Materials and Method’ section. CLS4076t and CAPNS1t, two targets for which we observed very high rates of TM, were indeed located in very accessible regions. Interestingly, CAPNS1t is in a non-methylated CpG island in the 5′UTR of the CAPNS1 gene, whereas CLS4076t is close to a CpG island, about 4 kb upstream of the region coding for the FUT8 protein. More generally, a very strong ‘negative’ correlation was observed between nuclease resistance and percentage of TM per chromatid at Day 2 (Figure 5e) and at Day 7 (Figure 5f), fitting with strong linear correlation between log (TM) and accessibility index (r = −0.93 with P = 7 × 10⁻⁵and r = −0.87 with P = 2 × 10⁻³, respectively). Thus, target accessibility is a major determinant of efficacy of rare-cutting designer endonucleases.