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ADAR1 prevents autoinflammation by suppressing spontaneous ZBP1 activation

Nature volume 607, pages 784–789 (2022)Cite this article

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Abstract

The RNA-editing enzyme adenosine deaminase acting on RNA 1 (ADAR1) limits the accumulation of endogenous immunostimulatory double-stranded RNA (dsRNA)1. In humans, reduced ADAR1 activity causes the severe inflammatory disease Aicardi–Goutières syndrome (AGS)2. In mice, complete loss of ADAR1 activity is embryonically lethal3,4,5,6, and mutations similar to those found in patients with AGS cause autoinflammation7,8,9,10,11,12. Mechanistically, adenosine-to-inosine (A-to-I) base modification of endogenous dsRNA by ADAR1 prevents chronic overactivation of the dsRNA sensors MDA5 and PKR3,7,8,9,10,13,14. Here we show that ADAR1 also inhibits the spontaneous activation of the left-handed Z-nucleic acid sensor ZBP1. Activation of ZBP1 elicits caspase-8-dependent apoptosis and MLKL-mediated necroptosis of ADAR1-deficient cells. ZBP1 contributes to the embryonic lethality of Adar-knockout mice, and it drives early mortality and intestinal cell death in mice deficient in the expression of both ADAR and MAVS. The Z-nucleic-acid-binding Zα domain of ADAR1 is necessary to prevent ZBP1-mediated intestinal cell death and skin inflammation. The Zα domain of ADAR1 promotes A-to-I editing of endogenous Alu elements to prevent dsRNA formation through the pairing of inverted Alu repeats, which can otherwise induce ZBP1 activation. This shows that recognition of Alu duplex RNA by ZBP1 may contribute to the pathological features of AGS that result from the loss of ADAR1 function.

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Fig. 1: ZBP1 causes early postnatal lethality of Adar and Mavs double-knockout mice and accelerates the death of Adar–/– embryos.
Fig. 2: The Zα domain of ADAR1-p150 is crucial for the prevention of spontaneous ZBP1 activation.
Fig. 3: Loss of ADAR1 function induces ZBP1-mediated caspase-8-dependent apoptosis and MLKL-dependent necroptosis.
Fig. 4: Alu duplex RNA stimulates ZBP1-dependent cell death.

Data availability

Raw RNA sequencing data used in this study are available from the European Nucleotide Archive (https://www.ebi.ac.uk/ena/browser/home) with accession codes PRJEB52610 (mouse primary lung fibroblasts) and PRJEB52618 (HEK293 cells). Source data are provided with this paper.

Code availability

The complete pipeline used for the A-to-I editing analysis from raw RNA sequencing data to the original output of the editing site prediction tool RDDpred with references to the genome and STAR indices is made available on GitHub (https://github.com/vibbits/rnaseq-editing). Any additional information required to reanalyse the data reported in this paper is available from the lead contact upon request.

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Acknowledgements

We are grateful to the VIB-UGent IRC Animal house for mouse husbandry, and the VIB Flow and Bioimaging Cores for training, support and access to the instrument park. Research in the J.M. group was supported by an Odysseus II Grant (G0H8618N), EOS INFLADIS (40007512), a junior research grant (G031022N) from the Research Foundation Flanders (FWO), a CRIG young investigator proof-of-concept grant and by Ghent University. Research in the P.V. group was supported by EOS MODEL-IDI (30826052), EOS INFLADIS (40007512), FWO senior research grants (G.0C76.18N, G.0B71.18N, G.0B96.20N and G.0A9322N), Methusalem (BOF16/MET_V/007), iBOF20/IBF/039 ATLANTIS, the Foundation against Cancer (F/2016/865, F/2020/1505), CRIG and GIGG consortia, and VIB. Research in the S.H. group was supported by NIH grants R01AI154653 and R01AI111784. R.d.R. was supported by a Ghent University BOF PhD fellowship. S.V. and J.N. were supported by FWO PhD fellowships.

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Author notes

  1. These authors contributed equally: Richard de Reuver, Simon Verdonck

Authors and Affiliations

  1. VIB-UGent Center for Inflammation Research, Ghent, Belgium

    Richard de Reuver, Simon Verdonck, Evelien Dierick, Josephine Nemegeer, Eline Hessmann, Maude Jans, Gillian Blancke, Lars Vereecke, Geert van Loo, Wim Declercq, Peter Vandenabeele & Jonathan Maelfait

  2. Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium

    Richard de Reuver, Simon Verdonck, Evelien Dierick, Josephine Nemegeer, Eline Hessmann, Maude Jans, Geert van Loo, Wim Declercq, Peter Vandenabeele & Jonathan Maelfait

  3. Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Howard Hughes Medical Institute, Boston, MA, USA

    Sadeem Ahmad & Sun Hur

  4. Program in Cellular and Molecular Medicine, Boston Children’s Hospital, Howard Hughes Medical Institute, Boston, MA, USA

    Sadeem Ahmad & Sun Hur

  5. Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium

    Gillian Blancke & Lars Vereecke

  6. NXTGNT, Faculty of Pharmaceutical Sciences, Ghent University, Ghent, Belgium

    Filip Van Nieuwerburgh

  7. Laboratory of Pharmaceutical Biotechnology, Faculty of Pharmaceutical Sciences, Ghent University, Ghent, Belgium

    Filip Van Nieuwerburgh

  8. VIB Bioinformatics Core, VIB, Ghent, Belgium

    Alexander Botzki

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Contributions

R.d.R., S.V. and J.M. conceived the study. R.d.R., S.V., E.D., J.N. and J.M. designed, performed and analysed experiments and interpreted data. E.H., M.J. and G.B. performed and analysed experiments. F.V.N., L.V., G.v.L. and W.D. helped with experimental design. R.d.R. and A.B. performed bioinformatical analyses. S.A. and S.H. generated the Alu–Alu hybrids. J.M. supervised the experiments. R.d.R., S.V., P.V. and J.M. wrote the manuscript.

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Correspondence to Jonathan Maelfait.

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Extended data figures and tables

Extended Data Fig. 1 Characterisation of Adar-/- Mavs-/- Zbp1Zα1α2/Zα1α2 mice.

a, Numbers and percentages of pups obtained from Adar+/- Mavs-/- Zbp1+/+, +/ Zα1α2 or Zα1α2/Zα1α2 breeding pairs. Lower panels show representative images of 3 or 4 day old pups. Arrows indicate Adar/Mavs double knockout mice with the indicated Zbp1 genotypes. b, Sanger sequencing chromatograms of A-to-I editing sites in brain (Htr2c) or spleen (Mad2l1 and Rpa1) tissues derived from mice of the indicated genotypes. ADAR1-, ADAR2- and ADAR1/ADAR2-specific sites indicated by blue, red and purple triangles, respectively. c, Weight in grams (g) of 5 (P5) or 12 (P12) day old mice of the indicated genotypes. d, Weight in grams (g) of male mice of the indicated genotypes measured weekly from birth till 30 weeks of age. Right panel shows a representative picture of a 10 week old Adar-/- Mavs-/- Zbp1Zα1α2/Zα1α2 mouse and an Adar+/+ Mavs-/- Zbp1Zα1α2/Zα1α2 littermate. e, TUNEL assay on ileum sections from 1 week or 5 week old Adar-/- Mavs-/- mice expressing Zα domain mutant ZBP1 from one (Zbp1+/Zα1α2) or two (Zbp1Zα1α2/Zα1α2) alleles. Scale bar = 100 µm. f, quantification of TUNEL+ cells per crypt. Each data point in (c,d,f) represents an individual mouse. The numbers of mice (n) that were analysed per genotype in (c,d,f) are indicated in the graph. Lines in (c,f) represent the mean; P values by Mann-Whitney test. Lines in (d) represent a sigmoidal, 4PL fit; P values by two-way ANOVA

Source data

Extended Data Fig. 2 Immune phenotyping of Adar-/- Mavs-/- Zbp1Zα1α2/Zα1α2 mice.

a, Flow cytometric quantification of numbers of immune cell populations in spleens of 4 to 5 day old Adar-/- Mavs-/- mice expressing wild-type (Zbp1+/+, +/Zα1Zα2) or Zα domain mutant ZBP1 (Zbp1Zα1α2/Zα1α2). b, Representative flow plots showing the presence of neutrophils in live cell populations in spleens of mice of the indicated genotypes. c, Percentage of neutrophils in the population of live cells in spleens. d, Flow cytometry gating strategy of immune cell populations in spleens shown in (a,b). Lines in (a,c) represent the mean; each data point represents an individual mouse; the numbers of mice (n) that were analysed per genotype are indicated in the graph; P values by Mann-Whitney test

Source data

Extended Data Fig. 3 Immune phenotyping of surviving Adar-/- Mavs-/- Zbp1Zα1α2/Zα1α2 mice and analysis of Adar-/- Zbp1Zα1α2/Zα1α2 embryos.

a, Peripheral blood of 20 week old Adar-/- Mavs-/- Zbp1Zα1α2/Zα1α2 pups and their littermates was analysed for total red blood cell (RBC), white blood cell (WBC) and platelet (PLT) numbers, together with haemoglobin (Hb) and haematocrit (HCT) levels. b, Flow cytometric quantification of numbers of circulating lymphocytes (B cells, CD4 and CD8 T cells, and NK and NKT cells) or myeloid cells (neutrophils, basophils, eosinophils and Ly-6C- and Ly-6C+ monocytes) per µL of blood. c, Gating strategy for flow cytometry analysis in (b). d, Immunoblot analysis of embryonic (E) day 12.5 whole embryo lysates of the indicated genotypes. e, Numbers of embryos resulting from interbreeding of Adar+/- Zbp1+/+ or Zα1α2/Zα1α2 breeding pairs and dissected on the indicated embryonic (E) days. f,g, RT-qPCR analysis of the indicated ISGs and Ifnb (f) or inflammatory genes (g) analysed in E12.5 embryos of the indicated genotypes. Lines in (a,b,f,g) represent the mean; each data point represents an individual mouse; each data point represents an individual mouse; the numbers of mice (n) that were analysed per genotype are indicated in the graph; P values by Mann-Whitney test. For gel source data, see Supplementary Figure 1

Source data

Extended Data Fig. 4 Characterisation of AdarZα/- Zbp1Zα1α2/Zα1α2 and AdarZα/- Mavs+/- Zbp1Zα1α2/Zα1α2 mice.

a, Percentages of offspring (n = 195) with the indicated genotypes obtained from Adar+/- Zbp1Zα1α2/Zα1α2 X Adar+/Zα Zbp1+/Zα1α2 breeding pairs. b, Representative image of a 14 week old AdarZα/- Zbp1Zα1α2/Zα1α2 mouse and its Adar+/- Zbp1Zα1α2/Zα1α2 littermate. c, Weight in grams (g) of male mice of the indicated genotypes measured weekly from birth till 20 weeks of age. Each data point represents an individual mouse; lines represent a sigmoidal, 4PL fit; P value by two-way ANOVA. d, H&E staining of longitudinal sections of whole intestines from 1 day old mice from the indicated genotypes. Jejunum and ileum are indicated by arrows. Caecum and colon are indicated by a pink and purple line, respectively. Scale bar = 0.2 cm. Red triangles indicate necrotic tissue in caecum and colon. e, RT-qPCR analysis of the indicated ISGs, analysed in whole tissue lysates of lungs and brains of 1 day old pups of the indicated genotypes. f, RT-qPCR analysis of the indicated inflammatory genes, analysed in whole tissue lysates of intestines, lungs and brains of 1 day old pups of the indicated genotypes. Lines in (e, f) represent the mean; each data point represents an individual mouse; P values by Mann-Whitney test. g, Kaplan-Meier survival curve of mice from the indicated genotypes. P value by log-rank test. Numbers of mice (n) that were analysed per genotype in (c,e,f,g) are indicated in the graph

Source data

Extended Data Fig. 5 Adar+/Zα Ripk1EKO mice develop severe skin inflammation.

a, Macroscopic images of 21 day old Adar+/+ Ripk1EKO mice, Adar+/Zα Ripk1EKO mice and control littermates from 3 experiments. b, Kaplan-Meier plot of macroscopically visible lesion appearance of epidermis-specific RIPK1 knockout mice (Ripk1EKO) carrying heterozygous ADAR1 Zα domain mutant alleles (Adar+/Zα) or expressing wild type ADAR1. Littermate offspring containing two or one wild type Ripk1 alleles (Ripk1+/+, fl/+) or heterozygously expressing a functional Ripk1 allele in the epidermis (Ripk1EHZ) did not develop lesions and are shown as controls. Numbers of mice (n) that were analysed per genotype are indicated in the graph. P value by log-rank test

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Extended Data Fig. 6 Flow cytometry gating strategy of CD45+ immune cell subsets in the skin.

Representative flow plots of the immune cell subsets of the indicated genotypes are shown. The data are shown quantified in Fig. 2g.

Extended Data Fig. 7 ADAR1 deletion or Zα domain mutation induces ZBP1-mediated cell death of mouse fibroblasts.

a-j, Primary mouse lung fibroblasts isolated from mice of the indicated genotypes were stimulated with 200 U/mL IFN-α (a-c, e-j) or 200 U/mL IFN-γ (d) for 16 h or left untreated (ctrl). Next, cells were treated with 5 µg/mL CHX and 1 µg/mL anti-mouse TNF (a), 50 µM zVAD-fmk and 1 µg/mL anti-mouse TNF (b,c,g,h), 30 ng/mL mouse TNF and 10 µg/mL CHX or 50 µM zVAD-fmk (e,f,i,j) or infected with HSV1 ICP6mutRHIM at a multiplicity of infection of 5 (d). Cell death in (a,b,d,e,g,i) was quantified by measuring relative (rel.) SYTOX Green uptake every 2 h. c, Immunoblot related to (b). Samples were harvested 4 h post treatment. f,j Immunoblot related to (e,i). Samples were harvested 7 (TNF + CHX) and 3 (TNF + zVAD) hours, respectively. h, Immunoblot related to (g). Samples were harvested 8 h post treatment. Data points in (a,b,d,e,g,i) show the mean of 2-6 technical replicates (see Source Data) + SD and are representative of 3 independent experiments. Fitted lines represent a logistic growth fit. For gel source data, see Supplementary Figure 1

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Extended Data Fig. 8 ADAR1 depletion causes ZBP1-dependent cell death of human HT-29 cells.

a, Immunoblot of HT-29 cells 48 h post transfection with non-targeting control siRNAs (si-CTRL), siRNAs targeting ADAR (si-ADAR) or the p150 isoform of ADAR (si-ADAR-p150). As controls, cells were treated with 1,000 U/mL IFN-α or 100 ng/mL IFN-γ. b, HT-29 cells stably expressing wild type ZBP1 (ZBP1WT) or Zα domain mutant ZBP1 (ZBP1Zα1Zα2mut) were transfected with non-targeting control siRNAs (si-CTRL) or siRNAs targeting ADAR (si-ADAR). Cell death was quantified by measuring relative (rel.) SYTOX Green uptake every 2 h. c, HT-29 ZBP1WT and ZBP1Zα1Zα2mut cells were treated with 30 ng/mL human TNF, 5 µM BV6 and 20 µM zVAD-fmk (TNF + BV6/ZVAD) or 30 ng/mL TNF and 20 µg/mL CHX (TNF + CHX). Cell death was quantified as in (b). d, Immunoblot related to (c). Cells were harvested 3 (TNF + BV6/ZVAD) or 6 (TNF+CHX) hours post treatment. FL, full length. e, HT-29 ZBP1WT cells were transfected with si-ADAR only or si-ADAR and si-ZBP1. After five hours, cells were treated with 20 µM zVAD-fmk and/or 3 µM GSK’840 or left untreated. Cell death was analysed as in (b). f, Immunoblot related to (e). Samples were harvested 30 h post transfection. TNF + CHX and TNF + BV6/ZVAD control samples were treated and harvested as in (d). g, HT-29 ZBP1WT cells were transfected with si-CTRL or si-ADAR-p150. si-ADAR-p150 was combined with si-ZBP1, or siRNAs targeting RIPK1 (si-RIPK1), RIPK3 (si-RIPK3), TICAM1 (TRIF; si-TICAM1) or CASP8 (si-CASP8). Cell death was quantified as in (b). h, HT-29 ZBP1WT cells transfected with the indicated siRNAs were harvested at 48 h post transfection for protein expression analysis. Fitted lines in (b,c,e) represent a logistic growth fit; Data points show mean of 3 (b,c,e) or 4 (g) technical replicates + SD and are representative of 3 independent experiments. For gel source data, see Supplementary Figure 1

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Extended Data Fig. 9 Characterisation of AdarZα/- Ripk3-/- and AdarZα/- Mlkl-/- Casp8-/- mice.

a, Sections from ileum or jejunum of Adar+/Zα Zbp1+/+ and AdarZα/- Zbp1+/+ or Zbp1Zα1Zα2/Zα1Zα2 mice stained for cleaved caspase-8 (D387) and counterstained with haematoxylin. Scale bars = 100 µm. At least 3 mice per genotype were analysed. b, Numbers (n) and percentages of pups obtained from interbreeding of Adar+/- Ripk3+/- X Adar+/Zα Ripk3+/- mice. c, Number of AdarZα/- Ripk3+/+, AdarZα/- Ripk3+/- or AdarZα/- Ripk3-/- that survived beyond day 2 after birth (> P2). d, Numbers and percentages of pups obtained from interbreeding of Adar+/- Mlkl-/- X Adar+/Zα Mlkl-/- mice. e, Numbers and percentages of pups obtained from interbreeding of Adar+/- Mlkl-/- X Adar Zα/Zα Mlkl-/- mice. f, Numbers and percentages of pups obtained from interbreeding of Adar+/- Mlkl-/- Casp8+/- X Adar+/Zα Mlkl-/- Casp8+/- mice. g, Numbers and percentages of pups obtained from interbreeding of Adar+/- Mlkl-/- Casp8+/- X Adar Zα/Zα Mlkl-/- Casp8+/- mice. h, Number of AdarZα/- Mlkl-/- Casp8+/+, AdarZα/- Mlkl-/- Casp8+/- or AdarZα/- Mlkl-/- Casp8-/- mice that survived beyond day 2 after birth (> P2).

Extended Data Fig. 10 A-to-I editing analysis of mRNA in mouse and human ADAR1 Zα domain mutant cells.

a, Primary lung fibroblasts derived from mice of the indicated genotypes were stimulated for 16 h with 200 U/mL IFN-α or left untreated. The total number of mouse repeat elements that underwent A-to-I editing was determined for 3 independent cell lines per genotype. Lines represent the mean. b, Boxplot illustrating the distribution of repeat elements in which editing activity was observed in 3 individual cell lines per genotype treated or not with IFN-α as indicated in (a). c, Venn diagrams displaying the number of repeat elements of which A-to-I editing activity was restricted to a single genotype (Adar+/- Mavs-/- or AdarZα/- Mavs-/-) or those that were detected in both groups without stimulation or following IFN-α treatment as indicated in (a). d, Graphical representation of the differential A-to-I editing profile of ADARPar/WT and ADARZαmut HEK293 cells detected on the indicated AluSp element in Fig. 4c and its nearest inverted repeat element (AluSx1). Data points show mean + SD; P values by Welch’s t-test. e,f, The RNAfold webtool was used to predict the folding structure and minimum free energy (MFE) of dsRNA formed by the AluSp:AluSx1 hybrid in complete absence of A-to-I editing (e) and when fully edited (f) at the A-to-I sites identified in (d). The A-to-I editing sites are indicated with black arrows. g, Transfection of HT-29 ZBP1WT with 50 ng of BPNT1 3’UTR duplex RNA in combination with 3 µM GSK’840 and/or 20 µM zVAD-fmk. Cell death was analysed as in Fig. 3d. Fitted lines represent a logistic growth fit. Data points show the mean of 2 technical replicates + SD and are representative of 3 independent experiments

Source data

Supplementary information

Supplementary Fig. 1

Reporting Summary

Supplementary Table 1

Sequences of primers used for genotyping and RT–qPCR and Alu sequences.

Supplementary Table 2

List of differentially edited repeat elements from Adar+/–Mavs–/– or AdarZα/–Mavs–/– mouse lung fibroblasts stimulated for 16 h with 200 U ml–1 IFNα and Alu elements from wild-type (HEK293 parental cells and 2 wild-type clones; ADARpar./WT) or ADARZαmut HEK293 clones stimulated for 16 h with 1,00 U ml–1 IFNα.

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de Reuver, R., Verdonck, S., Dierick, E. et al. ADAR1 prevents autoinflammation by suppressing spontaneous ZBP1 activation. Nature 607, 784–789 (2022). https://doi.org/10.1038/s41586-022-04974-w

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