. 2021 Aug;18(8):965-974.

doi: 10.1038/s41592-021-01207-2. Epub 2021 Aug 2.

Transgenic mice for in vivo epigenome editing with CRISPR-based systems

Matthew P Gemberling^#^{1

2}, Keith Siklenka^#^{2

3}, Erica Rodriguez⁴, Katherine R Tonn-Eisinger⁴, Alejandro Barrera^{2

3}, Fang Liu⁴, Ariel Kantor^{1

2}, Liqing Li³, Valentina Cigliola^{5

6}, Mariah F Hazlett⁴, Courtney A Williams³, Luke C Bartelt^{2

3}, Victoria J Madigan⁷, Josephine C Bodle^{1

2}, Heather Daniels^{1

2}, Douglas C Rouse⁸, Isaac B Hilton^{1

9

10}, Aravind Asokan^{1

2

6

7

11}, Maria Ciofani^{2

12}, Kenneth D Poss^{2

5

6}, Timothy E Reddy^{2

3}, Anne E West^{2

4}, Charles A Gersbach^{13

14

15

16

17}

Affiliations

¹ Department of Biomedical Engineering, Duke University, Durham, NC, USA.
² Center for Advanced Genomic Technologies, Duke University, Durham, NC, USA.
³ Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA.
⁴ Department of Neurobiology, Duke University School of Medicine, Durham, NC, USA.
⁵ Department of Cell Biology, Duke University Medical Center, Durham, NC, USA.
⁶ Regeneration Next Initiative, Duke University, Durham, NC, USA.
⁷ Department of Surgery, Duke University Medical Center, Durham, NC, USA.
⁸ Division of Laboratory Animal Resources, Duke University School of Medicine, Durham, NC, USA.
⁹ Department of Bioengineering, Rice University, Houston, TX, USA.
¹⁰ Department of Biosciences, Rice University, Houston, TX, USA.
¹¹ Department of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, NC, USA.
¹² Department of Immunology, Duke University Medical Center, Durham, NC, USA.
¹³ Department of Biomedical Engineering, Duke University, Durham, NC, USA. charles.gersbach@duke.edu.
¹⁴ Center for Advanced Genomic Technologies, Duke University, Durham, NC, USA. charles.gersbach@duke.edu.
¹⁵ Department of Cell Biology, Duke University Medical Center, Durham, NC, USA. charles.gersbach@duke.edu.
¹⁶ Regeneration Next Initiative, Duke University, Durham, NC, USA. charles.gersbach@duke.edu.
¹⁷ Department of Surgery, Duke University Medical Center, Durham, NC, USA. charles.gersbach@duke.edu.

^# Contributed equally.

PMID: 34341582
PMCID: PMC8349887
DOI: 10.1038/s41592-021-01207-2

Transgenic mice for in vivo epigenome editing with CRISPR-based systems

Matthew P Gemberling et al. Nat Methods. 2021 Aug.

. 2021 Aug;18(8):965-974.

doi: 10.1038/s41592-021-01207-2. Epub 2021 Aug 2.

Authors

Affiliations

¹ Department of Biomedical Engineering, Duke University, Durham, NC, USA.
² Center for Advanced Genomic Technologies, Duke University, Durham, NC, USA.
³ Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA.
⁴ Department of Neurobiology, Duke University School of Medicine, Durham, NC, USA.
⁵ Department of Cell Biology, Duke University Medical Center, Durham, NC, USA.
⁶ Regeneration Next Initiative, Duke University, Durham, NC, USA.
⁷ Department of Surgery, Duke University Medical Center, Durham, NC, USA.
⁸ Division of Laboratory Animal Resources, Duke University School of Medicine, Durham, NC, USA.
⁹ Department of Bioengineering, Rice University, Houston, TX, USA.
¹⁰ Department of Biosciences, Rice University, Houston, TX, USA.
¹¹ Department of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, NC, USA.
¹² Department of Immunology, Duke University Medical Center, Durham, NC, USA.
¹³ Department of Biomedical Engineering, Duke University, Durham, NC, USA. charles.gersbach@duke.edu.
¹⁴ Center for Advanced Genomic Technologies, Duke University, Durham, NC, USA. charles.gersbach@duke.edu.
¹⁵ Department of Cell Biology, Duke University Medical Center, Durham, NC, USA. charles.gersbach@duke.edu.
¹⁶ Regeneration Next Initiative, Duke University, Durham, NC, USA. charles.gersbach@duke.edu.
¹⁷ Department of Surgery, Duke University Medical Center, Durham, NC, USA. charles.gersbach@duke.edu.

^# Contributed equally.

PMID: 34341582
PMCID: PMC8349887
DOI: 10.1038/s41592-021-01207-2

Abstract

CRISPR-Cas9 technologies have dramatically increased the ease of targeting DNA sequences in the genomes of living systems. The fusion of chromatin-modifying domains to nuclease-deactivated Cas9 (dCas9) has enabled targeted epigenome editing in both cultured cells and animal models. However, delivering large dCas9 fusion proteins to target cells and tissues is an obstacle to the widespread adoption of these tools for in vivo studies. Here, we describe the generation and characterization of two conditional transgenic mouse lines for epigenome editing, Rosa26:LSL-dCas9-p300 for gene activation and Rosa26:LSL-dCas9-KRAB for gene repression. By targeting the guide RNAs to transcriptional start sites or distal enhancer elements, we demonstrate regulation of target genes and corresponding changes to epigenetic states and downstream phenotypes in the brain and liver in vivo, and in T cells and fibroblasts ex vivo. These mouse lines are convenient and valuable tools for facile, temporally controlled, and tissue-restricted epigenome editing and manipulation of gene expression in vivo.

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Conflict of interest statement

Conflict of Interest Statement

CAG, IBH, and TER have filed patent applications related to CRISPR technologies for genome engineering. CAG is an advisor to Tune Therapeutics, Sarepta Therapeutics, Levo Therapeutics, and Iveric Bio, and a co-founder of Tune Therapeutics, Element Genomics, and Locus Biosciences. AA is a co-founder and advisor to StrideBio and TorqueBio. TER is a co-founder of Element Genomics. MPG is a co-founder and employee of Tune Therapeutics. All other authors declare no conflicts of interest.

Figures

**Figure 1:. AAV-based gRNA and Cre recombinase delivery to *Rosa26:LSL-dCas9*^p300 mice activates *Pdx1* gene expression and catalyzes targeted histone acetylation.**
A) Schematic of *Rosa26:LSL-dCas9p300* (dCas9^p300) knock-in locus. B) Experimental design for *in vivo Pdx1* activation. C) *Pdx1* mRNA quantification 8 weeks post-injection in liver tissue lysates isolated from mice injected with phosphate-buffered saline (PBS), or AAV9 encoding Cre and either a control non-targeting or *Pdx1*-targeting gRNA (n=4 per group, Kruskal-Wallis one-way ANOVA with Dunnett’s post-hoc, *p=0.0132). D) PDX1 immunostaining of liver tissue sections at 14 days post-injection of mice treated with control and *Pdx1*-targeted gRNAs. Scale bar = 50 μm E) Quantification of PDX1+ nuclei in control gRNA and *Pdx1* gRNA treated animals (7.0% vs 0.03%, p=0.019, students t-test, n = 3 animals, with 3 images counted per animal). F) Representative browser tracks of dCas9 and H2K27ac ChIP-Seq data from treated livers at 2 weeks post-treatment (replicates are presented in Figures S3 and S4). G) dCas9 ChIP-seq quantification of sequencing counts (CPM = counts per million) in the gRNA target region of Pdx1 in samples from mice treated with *Pdx1-*targeted gRNA, control gRNA, or PBS (n = 4, one-way ANOVA with Dunnett’s post-hoc, p=0.059). H) RNA-seq and *Pdx1* ChIP-seq analyses showing the relationship between changes in gene expression and occupancy of Cas9 genome-wide. Log₂(fold-change) was calculated using the ratio of read counts between samples treated with the *Pdx1*-targeted gRNA relative to control non-targeting gRNA in dCas9^p300 cells (n = 4, FDR < 0.05). I) H3K27ac ChIP-seq quantification of sequencing counts within a 1 kb window centered on the gRNA target site near the TSS of *Pdx1* in samples from mice treated with the *Pdx1*-targeted gRNA, control gRNA, or PBS (n = 4, two-tailed student’s t-test, p = 0.07). J) RNA-seq and H3K27ac ChIP-seq analysis showing the relationship between changes in gene expression and genome-wide H3K27 acetylation for samples from mice treated with the *Pdx1-*targeted gRNA and control gRNA, (n = 4, FDR < 0.05, DEG = differentially expressed gene, orange dot; Diff. ChIP = differentially enriched ChIP-seq signal, blue dot; DEG and Diff. ChIP = differentially expressed gene and ChIP-seq enrichment, red dot). All bar-plot error bars represent standard deviation, all boxplots are drawn from 25^th to 75^th percentile with the horizontal bar at the mean and whiskers extending to the minima and maxima

**Figure 2:. Epigenomic enhancement of *Fos in vivo* increases excitability in CA1 neurons.**
A) Contralateral AAV injection strategy for comparison of targeting and non-targeting control gRNAs. *AAV:Syn1-Cre.gRNA* was injected into in the hippocampus of dCas9^p300 mice. A gRNA targeting *LacZ* was used as control for the gRNA targeting *Fos* enh2. B) Immunoflourescence imaging of neurons in the dendate gyrus region of the hippocampus after transduction with AAV containing *LacZ* control-gRNA or *Fos* Enh2-gRNA and stimulation with novel objects. (AAV-gRNA+ neurons (green), FOS+ neurons (red). scale bar = 20 μm). C) Quantification of those FOS+ neurons in (B). The lines connect measurements from the two sides of the same mouse. Counts of FOS+ cells in tissue slices from n=6 paired ROIs per condition from 3 animals. p = 0.002 by student’s paired two-sided t-test. D) Representative current clamp traces from acute hippocampal slices. Virally-expressed GFP was used to identify CA1 neurons for recording. E) Summary of input/output. For current F(10,240) = 31.12, p < 0.0001, virus F(1,24) = 1.05, p = 0.32 and current x virus interaction F(10,240) = 4.64, p < 0.0001. For *Fos* Enh2 vs *LacZ* control at 350 pA p = 0.016, at 400 pA p = 0.031, at 450 pA p = 0.012, and at 500 pA p = 0.026 (two-way repeated measures ANOVA with post-hoc Fisher’s LSD test; * denotes p < 0.05.) F) Rheobase, minimal current to spike. G) Latency to first spike (p = 0.018). H) Input resistance (p = 0.092). I) Membrane time constant (p = 0.091). n=12 *LacZ*, n=14 *Fos* Enh2, each from 2 animals (For F-I, two-tailed students t-test; horizontal bars show mean; error bars show SEM).

**Figure 3:. AAV-based gRNA and Cre recombinase delivery to *Rosa26:LSL-dCas9*^KRAB mice represses *Pcsk9* and catalyzes targeted histone methylation.**
A) Schematic of *Rosa26:LSL-dCas9KRAB* (dCas9^KRAB) knock-in locus. B) Schematic of the experimental design to test *Pcsk9* repression in the dCas9^KRAB mice. C) *Pcsk9* mRNA quantification 8 weeks post injection in liver tissue lysates isolated from mice injected with phosphate-buffered saline (PBS), or AAV9 encoding *Cre* and either a control non-targeting or *Pcsk9*-targeting gRNA (n = 4 per group, one-way ANOVA with Dunnett’s post-hoc, *p = 0.0021) D) PCSK9 serum protein levels at 4 weeks post injection of PBS or AAV9 encoding *Cre* and either a control non-targeting or *Pcsk9*-targeting gRNA (n = 4 per group, one-way ANOVA with Dunnett’s post-hoc, * p=0.0001). E) LDL cholesterol levels in the serum at 8 weeks following administration of PBS, or *AAV9:Cbh.Cre* containing either a control non-targeting or *Pcsk9*-targeting gRNA (N=4 per group, two-way ANOVA with Tukey’s, * denotes p<0.0001). F) Representative browser tracks of *dCas9*^KRAB (FLAG epitope) and H3K9me3 ChIP-Seq data from liver samples at 8 weeks post treatment (replicates are presented in Figures S10 and S11). Highlighted region corresponds to the area surrounding the gRNA target site in the *Pcsk9* promoter. G) dCas9-FLAG ChIP-seq quantification of sequencing counts (CPM = counts per million) in the *Pcsk9* promoter in samples treated with *Pcsk9*-targeted gRNA (n = 4), control non-targeting gRNA (n = 3), or PBS (n = 4) (one-way ANOVA with Dunnett’s post-hoc, p < 0.05.). H) Log₂(fold-change) of RNA-seq and FLAG ChIP-seq signal comparing read counts in peaks between samples treated with *Pcsk9*-targeted gRNA (n = 4) and control non-targeting gRNA (n = 3) showing the relationship between gene expression and genome-wide dCas9^KRAB binding. (Diff. ChIP = differentially enriched ChIP-seq signal, blue; DEG and Diff. ChIP = differentially expressed gene and ChIP-seq enrichment, red; FDR < 0.05. I) H3K9me3 ChIP-seq quantification of sequencing counts (CPM = counts per million) in the *Pcsk9* promoter in samples treated with *Pcsk9*-targeted gRNA (n = 4), control non-targeting gRNA (n = 4), or PBS (n = 4) (one-way ANOVA with Dunnett’s post-hoc, p < 0.05.). J) Log₂(fold-change) of RNA-seq and H3K9me3 ChIP-seq signal comparing read counts in peaks for samples treated with the *Pcsk9*-targeting gRNA (n = 4) and control non-targeting gRNA (n = 4) (DEG = differentially expressed gene, orange; Diff. ChIP = differentially enriched ChIP-seq signal, blue; DEG and Diff. ChIP = differentially expressed gene and ChIP-seq enrichment, red; FDR < 0.05). All bar-plot error bars represent standard deviation, all boxplots are drawn from 25^th to 75^th percentile with the horizontal bar at the mean and whiskers extending to the minima and maxima

Figure 4:. Epigenome editing in T cells for activation and repression of *Foxp3.*
A) Flow cytometry analysis of FOXP3-eGFP expression in CD4+ T cells purified from *Rosa26:LSL-dCas9*^p300;CD4:Cre;Foxp3:*eGFP* mice cultured *in vitro* under Th0 polarization conditions (rIL-2) after transduction with retrovirus encoding the cell surface marker Thy1.1, for tracking transduced cells, and either the *Foxp3-*gRNA (green) or control-gRNA (blue). Cells cultured in iTreg polarization conditions (rIL-2, hTGFβ1) were included as a positive control for *Foxp3* expression (black). B) Summary data depicting the percentage of Thy1.1+ cells that were FOXP3-EGFP+ (p<0.0001; one-way ANOVA with Dunnett’s post-hoc, iTreg n = 3, control gRNA and *Foxp3*-gRNA n = 4). C) qRT-PCR measurement of *Foxp3* mRNA levels in Th0 cells compared to cells treated with *Foxp3*-targeting gRNA (green), control non-targeting gRNA (blue), or no virus (black) (p = 0.0190, one-way ANOVA with Dunnett’s post-hoc, n = 3 per condition). D) Flow cytometry histograms showing proliferation of Cell Trace Violet (CTV)-labelled CD4⁺/FOXP3-eGFP⁻ conventional T cells (Tconv) after 72 hrs of *in vitro* co-culture with aCD3/aCD28 dynabeads and either FOXP3-eGFP+ iTreg cells (grey, n = 3), Th0 cells (black, n = 2), FACS-purified Thy1.1+/FOXP3-eGFP+ cells treated with *Foxp3*-gRNA (green, n = 3), or Thy1.1+ cells treated with control non-targeting gRNA (blue, n = 3). Tconv cells with no aCD3/aCD28 and rIL-7 served as a no activation control (dashed). E) Suppressive capacity of Tregs summarized as division index of Tconv (p < 0.0001 one-way ANOVA with Tukey’s post-hoc. F) Browser track of H3K27ac ChIP-seq read counts at the *Foxp3* locus in Th0 cells from a *Rosa26:LSL-dCas9*^p300 mouse that was either *Cd4:Cre*+ or *Cd4:Cre*−. Cells were treated with retrovirus containing *Foxp3-*targeting or control non-targeting gRNA and *Thy1.1* reporter. ChIP-seq was performed 72hrs after transduction on sort-purified Thy1.1+ cells (red = *Cd4:Cre+ Foxp3*-gRNA; yellow = *Cd4:Cre+* control-gRNA; blue = *Cd4:Cre− Foxp3*-gRNA). G) Summary of H3K27ac ChIP-seq reads counts per million within the MACS2-called peak that intersects the *Foxp3*-gRNA target site for each genotype and gRNA treatment (green = *Foxp3*-gRNA treated *Cd4:Cre*+ Th0, blue = control-gRNA treated *Cd4:Cre*+ Th0; black = *Foxp3*-gRNA treated *Cd4:Cre*− Th0, n = 3 per condition). H) Scatter plot depicting log₂(fold-change) of gene expression and H3K27ac enrichment when comparing read counts from *Cd4:Cre+ Rosa26:LSL-dCas9*^p300 Th0 cells treated with *Foxp3*-gRNA to control-gRNA (FDR < 0.01; DEG = differentially expressed gene, orange dot; Diff. ChIP = differentially enriched ChIP-seq signal, blue dot; DEG and Diff. ChIP = differentially expressed gene and ChIP-seq enrichment, red dot) I) Flow cytometry analysis of FOXP3 expression in CD4+ T cells purified from *Rosa26:LSL-dCas9*^KRAB mice cultured *in vitro* under iTreg polarization conditions and transduced with retrovirus encoding the indicated gRNAs. J) Summary data showing the percentage of Thy1.1+ cells that were FOXP3-EGFP+ for each gRNA treatment (p < 0.0001, one-way ANOVA with Dunnett’s post-hoc, n = 3 per condition). K) qRT-PCR measurement of *Foxp3* mRNA levels in iTreg cells treated without virus (black), control-gRNA (blue), or *Foxp3*-targeting gRNA (red) (p < 0.0135, one-way ANOVA with Dunnett’s post-hoc, n = 3 per condition). All bar-plot error bars represent standard deviation, all boxplots are drawn from 25^th to 75^th percentile with the horizontal bar at the mean and whiskers extending to the minima and maxima.

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Transgenic mice for in vivo epigenome editing with CRISPR-based systems

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Transgenic mice for in vivo epigenome editing with CRISPR-based systems

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