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Synthetic immunomodulation with a CRISPR super-repressor in vivo

Nature Cell Biology volume 22, pages 1143–1154 (2020)Cite this article

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Abstract

Transient modulation of the genes involved in immunity, without exerting a permanent change in the DNA code, can be an effective strategy to modulate the course of many inflammatory conditions. CRISPR-Cas9 technology represents a promising platform for achieving this goal. Truncation of guide RNA (gRNA) from the 5′ end enables the application of a nuclease competent Cas9 protein for transcriptional modulation of genes, allowing multifunctionality of CRISPR. Here, we introduce an enhanced CRISPR-based transcriptional repressor to reprogram immune homeostasis in vivo. In this repressor system, two transcriptional repressors—heterochromatin protein 1 (HP1a) and Krüppel-associated box (KRAB)—are fused to the MS2 coat protein and subsequently recruited by gRNA aptamer binding to a nuclease competent CRISPR complex containing truncated gRNAs. With the enhanced repressor, we demonstrate transcriptional repression of the Myeloid differentiation primary response 88 (Myd88) gene in vitro and in vivo. We demonstrate that this strategy can efficiently downregulate Myd88 expression in lung, blood and bone marrow of Cas9 transgenic mice that receive systemic injection of adeno-associated virus (AAV)2/1-carrying truncated gRNAs targeting Myd88 and the MS2-HP1a-KRAB cassette. This downregulation is accompanied by changes in downstream signalling elements such as TNF-α and ICAM-1. Myd88 repression leads to a decrease in immunoglobulin G (IgG) production against AAV2/1 and AAV2/9 and this strategy modulates the IgG response against AAV cargos. It improves the efficiency of a subsequent AAV9/CRISPR treatment for repression of proprotein convertase subtilisin/kexin type 9 (PCSK9), a gene that, when repressed, can lower blood cholesterol levels. We also demonstrate that CRISPR-mediated Myd88 repression can act as a prophylactic measure against septicaemia in both Cas9 transgenic and C57BL/6J mice. When delivered by nanoparticles, this repressor can serve as a therapeutic modality to influence the course of septicaemia. Collectively, we report that CRISPR-mediated repression of endogenous Myd88 can effectively modulate the host immune response against AAV-mediated gene therapy and influence the course of septicaemia. The ability to control Myd88 transcript levels using a CRISPR-based synthetic repressor can be an effective strategy for AAV-based CRISPR therapies, as this pathway serves as a key node in the induction of humoral immunity against AAV serotypes.

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Fig. 1: Aptamer-mediated CRISPR repression in vitro.
Fig. 2: CRISPR-based targeted Myd88 repression in vitro and in vivo using MS2 repressors.
Fig. 3: Prophylactic administration of AAV1/MyD88 in vivo leads to modulation of humoral immunity against AAV.
Fig. 4: Long-term efficacy of AAV/Myd88 repression in vivo.
Fig. 5: CRISPR-based modulation of host inflammatory response can be a prophylactic measure against LPS-mediated septicaemia in Cas9 transgenic and WT mice.
Fig. 6: Developing protection following LPS-mediated septicaemia using a dual AAV CRISPR/Cas9 strategy with AAV1/Cas9 and AAV1 carrying gRNA-MS2-HP1a-KRAB.
Fig. 7: Therapeutic delivery of nanoparticles carrying DNA encoding Myd88-targeting CRISPR confers protection against LPS-mediated septicaemia.

Data availability

RNA–seq data that support the findings of this study have been deposited in the Gene Expression Omnibus (GEO) under accession code GSE152412. Source data are provided with this paper. All other data supporting the findings are available upon reasonable request. All materials are available upon completion of a material transfer agreement.

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Acknowledgements

This work was primarily supported by an RO1 grant from the National Institute of Biomedical Imaging and Bioengineering (R01EB024562), a start-up fund of the School of Biological and Health Systems Engineering of Ira. A Fulton Schools of Engineering at Arizona State University, Pittsburgh Liver Research Center, University of Pittsburgh School of Medicine(NIH/NIDDK P30DK120531), NIH 8-U01-EB029372-02 as well as a DARPA Young Faculty Award (D16AP00047) to S.K. S.K. and M.R.E. are also partly supported by an R01 grant from the National Institute of Biomedical Imaging and Bioengineering (EB028532) and an R01 grant from the National Heart, Lung and Blood Institute (HL141805). A.C. is supported by a Career Award for Medical Scientists from the Burroughs Welcome Fund. We thank P. Amrollahi for helping with the figures. We thank the Molecular Epidemiology Analytics Core and A. Bond at Arizona State University for the Multiplex-ELISA service. We thank all members of the Kiani and Ebrahimkhani laboratories for their assistance and insightful discussions. We also thank Novogene Corporation and UCLA Genomic Core for RNA sequencing and initial analysis.

Author information

Author notes

  1. These authors contributed equally: Ryan LeGraw, Jeremy J. Velazquez.

Authors and Affiliations

  1. Pittsburgh Liver Research Center, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA

    Farzaneh Moghadam, Ryan LeGraw, Jeremy J. Velazquez, Mo R. Ebrahimkhani & Samira Kiani

  2. Division of Experimental Pathology, Department of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA

    Farzaneh Moghadam, Ryan LeGraw, Jeremy J. Velazquez, Mo R. Ebrahimkhani & Samira Kiani

  3. School of Biological and Health Systems Engineering, Ira A. Fulton Schools of Engineering, Arizona State University, Tempe, AZ, USA

    Farzaneh Moghadam, Ryan LeGraw, Jeremy J. Velazquez, Mo R. Ebrahimkhani & Samira Kiani

  4. Department of Pharmacology and Toxicology, University of Alabama, Birmingham, AL, USA

    Nan Cher Yeo

  5. Precision Medicine Institute, University of Alabama, Birmingham, AL, USA

    Nan Cher Yeo

  6. Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ, USA

    Chenxi Xu & Jin Park

  7. Department of Pathology and Cell Biology, Columbia University College of Physicians and Surgeons, New York, NY, USA

    Alejandro Chavez

  8. McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, USA

    Mo R. Ebrahimkhani & Samira Kiani

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Contributions

F.M., M.R.E. and S.K. designed the study and the associated experiments. F.M., N.C.Y. and A.C. generated the constructs. F.M. and R.L. performed in vitro experiments. F.M., R.L. and J.J.V. performed in vivo experiments. C.X. and J.P. analysed the RNA-seq data. F.M. and S.K. analysed the data and prepared the figures. M.R.E. and S.K. supervised the study and provided advice on the research strategy. F.M., M.R.E. and S.K. wrote the manuscript.

Corresponding authors

Correspondence to Mo R. Ebrahimkhani or Samira Kiani.

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Competing interests

S.K. is a co-founder of SafeGen Therapeutics. An international patent application has been filed for this work (PCT/US19/60285).

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Extended data

Extended Data Fig. 1 Evaluation of endogenous Myd88 gene expression using different CRISPR-mediated repressor circuits.

(a-b) N2A cells were transfected with Myd88 gRNA pairs along with either dCas9 plasmid fused to HP1a-KRAB or dCas9 and MS2-HP1a-KRAB on two separate cassettes. Expression levels of (a) Myd88, (b) dCas9, and HP1a-KRAB are quantified relative to No-Guide group (N=3 independent samples) The bars represent the mean + S.E.M. Statistical analysis was performed using the non-parametric one-tailed Mann-Whitney test. A p value ≤ 0.05 was considered significant (*P ≤ 0.05). Statistical source data are provided in Source data extended data fig. 1.

Source data

Extended Data Fig. 2 In vivo analysis of AAV1 tropism towards different tissues.

AAV1-GFP was delivered to C57BL/6 mice via retro-orbital injection. GFP expression was assessed in different tissues by qRT-PCR. Average fold change expression levels are indicated above each group and are quantified relative to not injected mice (N=3 for not injected group, N=4 for AAV-GFP group, N=5 for AAV-GFP group in spleen, and N=6 for AAV-GFP group in liver). Statistical source data are provided in Source data extended data fig. 2.

Source data

Extended Data Fig. 3 RNA-seq analyses of bone marrow samples collected from mice treated with AAV1/Myd88-MS2-HP1aKr ab versus AAV1/Myd88-MS2-Krab.

(a) Scatter plot comparing expression of genes (Fragments Per Kilobase of transcript per Million mapped reads FPKM) in two replicates of bone marrow from Myd88-MS2-HP1a-KRAB versus Myd88-MS2-KRAB. Myd88, Il1β, Icam-1, Tnfa and Il6 are highlighted in red and the most downregulated genes in Myd88-MS2-HP1a-KRAB groups as compared to Myd88-MS2-KRAB are highlighted in Cyan (N=2 mice). (b) GO enrichment bar graph comparing bone marrow samples collected from mice treated with AAV1/Myd88-MS2-HP1a-KRAB versus AAV1/Myd88-MS2-KRAB. The top 20 significantly enriched terms in the GO enrichment analysis are displayed. Note that pathways such as defense response to bacteria, which are associated with Myd88 signaling are mostly down regulated when HP1a-KRAB was used (N=2 mice). (c) Reactome Enrichment bar graph displaying the top 20 enriched genes in the Reactome database comparing in the BM samples of Myd88-MS2-HP1a-KRAB versus Myd88-MS2-KRAB (N=2). Statistical analysis was performed using the two-tailed t test and the method of multiple comparisons adjustments was Benjamini-Hochberg. A p value ≤ 0.05 was considered significant (*P ≤ 0.05). p values are provided in supplementary information table 4. [AU: please define the “n” in above panels].

Extended Data Fig. 4 Evaluation of endogenous Myd88 gene expression following multiple AAV administration.

(a) Schematic of experiments demonstrating Cas9 transgenic mice treated with AAV1/Myd88 or AAV1/Mock at day 1, followed by a second administration of AAV1/Mock on day 21. (b) qRT-PCR analysis of Myd88 expression level in lung, blood, and bone marrow of Cas9 transgenic mice (N = 4 mice). Fold changes are relative to universal control. The bars represent the mean + S.E.M. (c) Schematic of the experiment. Cas9 nuclease transgenic mice were treated with AAV1-Myd88 or AAV1-Mock vectors via retro-orbital injection followed by a second and third injection of AAV9-PCSK9 vectors on day 7 and 21. (d) qRT-PCR analysis of Myd88 expression level in lung, blood, and bone marrow of Cas9 transgenic mice (N = 4 mice). The bars represent the mean + S.E.M. (Mock, Mock-HP1a-KRAB; Myd88, Myd88-HP1a-KRAB; PCSK9, PCSK9-HP1a-KRAB). Fold changes are relative to universal control. Universal control is a blood sample collected from an uninjected Cas9 transgenic mouse. Statistical analysis was performed using the non- parametric one-tailed Mann-Whitney U test. A p value ≤ 0.05 was considered significant (*P ≤ 0.05). Statistical source data are provided in Source data extended data fig. 4.

Source data

Extended Data Fig. 5 Analysis of a set of immune-related transcripts following LPS injury.

qRT-PCR analysis of Ncf, Il6, Ifnγ, and Il1β mRNA expression in lung, blood, and bone marrow quantified relative to the universal control following LPS injection (N = 6 mice for injected groups except for Blood and Bone marrow of Myd88+LPS N=5, and N = 2 mice for Not Injected group). The bars represent the mean + S.E.M. (Mock, Mock-HP1a-KRAB; Myd88, Myd88-HP1a-KRAB). Universal control is a blood sample collected from an uninjected Cas9 transgenic mouse. Statistical analysis was performed using the non-parametric one-tailed Mann-Whitney U test. A p value ≤ 0.05 was considered significant (*P ≤ 0.05 and **P ≤ 0.01). Statistical source data are provided in Source data extended data fig. 5.

Source data

Extended Data Fig. 6 Assessing the level of a panel of immune related genes in lung and bone marrow following LPS injection.

qRT-PCR analysis of in vivo CD68, Infα, Infβ, CD4, Cxcl1, and Stat4 relative to the universal control following LPS injection in lung and bone marrow. (N = 6 mice for injected groups except for Bone Marrow of Myd88+LPS group, Lung of Mock+LPS, and Lung of Myd88+LPS for Cxcl1 N=5 mice, and Lung of of Mock+LPS group for Cxcl1 N=4 mice, and N = 2 mice for Not Injected group). The bars represent the mean + S.E.M. (Mock, Mock-HP1a-KRAB; Myd88, Myd88-HP1a-KRAB). Universal control is a blood sample collected from an uninjected Cas9 transgenic mouse. Statistical analysis was performed using the non-parametric one-tailed Mann-Whitney U test A p value ≤ 0 05 was considered significant (*P ≤ 0 05 and **P ≤ 0 01). Statistical source data are provided in Source data extended data fig. 6.

Source data

Extended Data Fig. 7 Targeted gene silencing in wild-type mice using a dual CRISPR/Cas9 system with AAV1/Cas9 and AAV1 carrying gRNA-MS2- HP1a-KRAB.

AAV1 viruses were delivered to wild-type mice via retro-orbital injection. qRT-PCR analysis was performed to assess Myd88, Icam-1, Tnfα, Ncf, Il6, and Il1β mRNA expression in blood, bone marrow, and lung. Fold change expression levels were quantified relative to the universal control (N = 4 mice). The bars represent the mean + S.E.M. (Mock, Mock-HP1a-KRAB; Myd88, Myd88-HP1a-KRAB). Universal control is a blood sample collected from an uninjected Cas9 transgenic mouse. Statistical analysis was performed using the non-parametric one-tailed Mann-Whitney U test. A p value ≤ 0.05 was considered significant (*P ≤ 0.05 and **P ≤ 0.01). Statistical source data are provided in Source data extended data fig. 7.

Source data

Extended Data Fig. 8 Assessing the repression efficiency of AAV1-Myd88 targeting a different region of Myd88 in liver.

(a) qRT-PCR analysis of in vivo Myd88 expression in liver samples 3 weeks post retro-orbital injection of AAV1 in Cas9 transgenic animals. Gene expression fold-change was quantified relative to the universal control (N = 2 mice for Not Injected group, N=4 mice for Mock, N=7 mice for Myd88Guideset1, N=3 mice for Myd88Guideset2). The bars represent the mean + S.E.M. (b) qRT-PCR analysis of in vivo Myd88 expression in liver samples 6 hours post LPS injection. Fold change expression levels were quantified relative to the universal control (N = 2 mice for Not Injected group, N=6 mice for Mock, N=4 mice for Myd88Guideset2). The bars represent the mean + S.E.M. Universal control is a blood sample collected from an uninjected Cas9 transgenic mouse. Statistical analysis was performed using the non-parametric one-tailed Mann-Whitney U test. A p value ≤ 0.05 was considered significant (*P ≤ 0.05 and **P ≤ 0.01). Statistical source data are provided in Source data extended data fig. 8.

Source data

Supplementary information

Supplementary Information

Sequences of the MS2 fusion constructs.

Reporting Summary

Supplementary Tables

Supplementary Table 1-1: Repression levels of Myd88, Icam-1 and Tnfa assessed by qRT-PCR in lung, blood and bone marrow three weeks post retro-orbital injection of AAV N = 4 mice for injected groups except for the following: Mock/MS2-KRAB group N = 3 mice, Myd88/MS2-HP1a-KRAB in bone marrow N = 7 mice, Myd88/MS2-HP1a-KRAB in blood and lung N = 5 mice). Gene expression fold change was quantified relative to the universal control. The repression levels are reported as percentage of fold change of AAV-Myd88 group divided by the fold change of AAV-Mock group for each gene. NC = no change; Supplementary Table 2: Sequences for gRNA; Supplementary Table 3: sequences for primers. Table 2-1: Sequences of the Truncated gRNAs- 5′ to 3′. Table 2-2: sequences of the Truncated gRNAs- 5′ to 3′. Table 3-1: Sequences of the Mouse qPCR primers- 5′ to 3′. Table3-2: Sequences of the Human qPCR primers- 5′ to 3′.

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Moghadam, F., LeGraw, R., Velazquez, J.J. et al. Synthetic immunomodulation with a CRISPR super-repressor in vivo. Nat Cell Biol 22, 1143–1154 (2020). https://doi.org/10.1038/s41556-020-0563-3

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