Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

cGAS-mediated induction of type I interferon due to inborn errors of histone pre-mRNA processing

Abstract

Inappropriate stimulation or defective negative regulation of the type I interferon response can lead to autoinflammation. In genetically uncharacterized cases of the type I interferonopathy Aicardi–Goutières syndrome, we identified biallelic mutations in LSM11 and RNU7-1, which encode components of the replication-dependent histone pre-mRNA–processing complex. Mutations were associated with the misprocessing of canonical histone transcripts and a disturbance of linker histone stoichiometry. Additionally, we observed an altered distribution of nuclear cyclic guanosine monophosphate–adenosine monophosphate synthase (cGAS) and enhanced interferon signaling mediated by the cGAS–stimulator of interferon genes (STING) pathway in patient-derived fibroblasts. Finally, we established that chromatin without linker histone stimulates cyclic guanosine monophosphate–adenosine monophosphate (cGAMP) production in vitro more efficiently. We conclude that nuclear histones, as key constituents of chromatin, are essential in suppressing the immunogenicity of self-DNA.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Biallelic mutations in LSM11 and U7 snRNA in patients with AGS.
Fig. 2: Misprocessing of RDH pre-mRNAs.
Fig. 3: Global analysis of transcript expression using RNA-seq.
Fig. 4: ISG expression in whole blood and in fibroblasts from AGS8/9-mutation-positive patients.
Fig. 5: Interferon induction secondary to RDH pre-mRNA processing is mediated by the cGAS–STING pathway.
Fig. 6: Histone stoichiometry, nuclear morphology and cGAS distribution in patient-derived and control fibroblasts and in vitro cGAMP production.

Data availability

The RNA-seq data have been deposited at the National Center for Biotechnology Information Gene Expression Omnibus (accession no. GSE153079). The exome and genome sequencing data are not publicly available due to the possibility of compromising privacy. Human fibroblasts are primary cells and therefore a limited resource. Availability is through the corresponding author subject to technical constraints and completion of a material transfer agreement required to ensure patient privacy.

References

  1. 1.

    Roers, A., Hiller, B. & Hornung, V. Recognition of endogenous nucleic acids by the innate immune system. Immunity 44, 739–754 (2016).

    CAS  PubMed  Google Scholar 

  2. 2.

    Uggenti, C., Lepelley, A. & Crow, Y. J. Self-awareness: nucleic acid-driven inflammation and the type I interferonopathies. Annu. Rev. Immunol. 37, 247–267 (2019).

    CAS  PubMed  Google Scholar 

  3. 3.

    Bartsch, K. et al. Absence of RNase H2 triggers generation of immunogenic micronuclei removed by autophagy. Hum. Mol. Genet. 26, 3960–3972 (2017).

    CAS  PubMed  Google Scholar 

  4. 4.

    Harding, S. M. et al. Mitotic progression following DNA damage enables pattern recognition within micronuclei. Nature 548, 466–470 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. 5.

    Mackenzie, K. J. et al. cGAS surveillance of micronuclei links genome instability to innate immunity. Nature 548, 461–465 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Gentili, M. et al. The N-terminal domain of cGAS determines preferential association with centromeric DNA and innate immune activation in the nucleus. Cell Rep. 26, 3798 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. 7.

    Yang, H., Wang, H., Ren, J., Chen, Q. & Chen, Z. J. cGAS is essential for cellular senescence. Proc. Natl Acad. Sci. USA 114, E4612–E4620 (2017).

    CAS  PubMed  Google Scholar 

  8. 8.

    Zierhut, C. et al. The cytoplasmic DNA sensor cGAS promotes mitotic cell death. Cell 178, 302–315.e23 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. 9.

    Denais, C. M. et al. Nuclear envelope rupture and repair during cancer cell migration. Science 352, 353–358 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Raab, M. et al. ESCRT III repairs nuclear envelope ruptures during cell migration to limit DNA damage and cell death. Science 352, 359–362 (2016).

    CAS  PubMed  Google Scholar 

  11. 11.

    Jiang, H. et al. Chromatin-bound cGAS is an inhibitor of DNA repair and hence accelerates genome destabilization and cell death. EMBO J. 38, e102718 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Lahaye, X. et al. NONO detects the nuclear HIV capsid to promote cGAS-mediated innate immune activation. Cell 175, 488–501.e22 (2018).

    CAS  PubMed  Google Scholar 

  13. 13.

    Liu, H. et al. Nuclear cGAS suppresses DNA repair and promotes tumorigenesis. Nature 563, 131–136 (2018).

    CAS  PubMed  Google Scholar 

  14. 14.

    Volkman, H. E., Cambier, S., Gray, E. E. & Stetson, D. B. Tight nuclear tethering of cGAS is essential for preventing autoreactivity. eLife 8, e47491 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Crow, Y. J. et al. Mutations in the gene encoding the 3′-5′ DNA exonuclease TREX1 cause Aicardi–Goutières syndrome at the AGS1 locus. Nat. Genet. 38, 917–920 (2006).

    CAS  PubMed  Google Scholar 

  16. 16.

    Crow, Y. J. et al. Mutations in genes encoding ribonuclease H2 subunits cause Aicardi–Goutières syndrome and mimic congenital viral brain infection. Nat. Genet. 38, 910–916 (2006).

    CAS  PubMed  Google Scholar 

  17. 17.

    Rice, G. I. et al. Mutations involved in Aicardi–Goutières syndrome implicate SAMHD1 as regulator of the innate immune response. Nat. Genet. 41, 829–832 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. 18.

    Rice, G. I. et al. Mutations in ADAR1 cause Aicardi–Goutières syndrome associated with a type I interferon signature. Nat. Genet. 44, 1243–1248 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. 19.

    Rice, G. I. et al. Gain-of-function mutations in IFIH1 cause a spectrum of human disease phenotypes associated with upregulated type I interferon signaling. Nat. Genet. 46, 503–509 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. 20.

    Crow, Y. J. & Manel, N. Aicardi–Goutières syndrome and the type I interferonopathies. Nat. Rev. Immunol. 15, 429–440 (2015).

    CAS  Google Scholar 

  21. 21.

    Pillai, R. S. et al. Unique Sm core structure of U7 snRNPs: assembly by a specialized SMN complex and the role of a new component, Lsm11, in histone RNA processing. Genes Dev. 17, 2321–2333 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Kolev, N. G. & Steitz, J. A. In vivo assembly of functional U7 snRNP requires RNA backbone flexibility within the Sm-binding site. Nat. Struct. Mol. Biol. 13, 347–353 (2006).

    CAS  PubMed  Google Scholar 

  23. 23.

    Badrock, A. P. et al. Analysis of U8 snoRNA variants in zebrafish reveals how bi-allelic variants cause leukoencephalopathy with calcifications and cysts. Am. J. Hum. Genet. 106, 694–706 (2020).

    PubMed  PubMed Central  Google Scholar 

  24. 24.

    Marzluff, W. F., Wagner, E. J. & Duronio, R. J. Metabolism and regulation of canonical histone mRNAs: life without a poly(A) tail. Nat. Rev. Genet. 9, 843–854 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. 25.

    Müller, B. & Schümperli, D. The U7 snRNP and the hairpin binding protein: key players in histone mRNA metabolism. Semin. Cell Dev. Biol. 8, 567–576 (1997).

    PubMed  Google Scholar 

  26. 26.

    Dominski, Z. & Marzluff, W. F. Formation of the 3′ end of histone mRNA: getting closer to the end. Gene 396, 373–390 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Wang, Z. F., Whitfield, M. L., Ingledue, T. I.3rd, Dominski, Z. & Marzluff, W. F. The protein which binds the 3′ end of histone mRNA: a novel RNA- binding protein required for histone pre-mRNA processing. Genes Dev. 10, 3028–3040 (1996).

    CAS  PubMed  Google Scholar 

  28. 28.

    Martin, F., Schaller, A., Eglite, S., Schümperli, D. & Müller, B. The gene for histone RNA hairpin binding protein is located on human chromosome 4 and encodes a novel type of RNA binding protein. EMBO J. 16, 769–778 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. 29.

    Sabath, I. et al. 3′-End processing of histone pre-mRNAs in Drosophila: U7 snRNP is associated with FLASH and polyadenylation factors. RNA 19, 1726–1744 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Sullivan, E. et al. Drosophila stem loop binding protein coordinates accumulation of mature histone mRNA with cell cycle progression. Genes Dev. 15, 173–187 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. 31.

    Marzluff, W. F., Gongidi, P., Woods, K. R., Jin, J. & Maltais, L. J. The human and mouse replication-dependent histone genes. Genomics 80, 487–498 (2002).

    CAS  PubMed  Google Scholar 

  32. 32.

    Rice, G. I. et al. Assessment of interferon-related biomarkers in Aicardi–Goutières syndrome associated with mutations in TREX1, RNASEH2A, RNASEH2B, RNASEH2C, SAMHD1, and ADAR: a case-control study. Lancet Neurol. 12, 1159–1169 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Chen, Q., Sun, L. & Chen, Z. J. Regulation and function of the cGAS–STING pathway of cytosolic DNA sensing. Nat. Immunol. 17, 1142–1149 (2016).

    CAS  Google Scholar 

  34. 34.

    Streicher, F. & Jouvenet, N. Stimulation of innate immunity by host and viral RNAs. Trends Immunol. 40, 1134–1148 (2019).

    CAS  PubMed  Google Scholar 

  35. 35.

    Izquierdo-Bouldstridge, A. et al. Histone H1 depletion triggers an interferon response in cancer cells via activation of heterochromatic repeats. Nucleic Acids Res. 45, 11622–11642 (2017).

    PubMed  PubMed Central  Google Scholar 

  36. 36.

    Lepelley, A. et al. Mutations in COPA lead to abnormal trafficking of STING to the Golgi and interferon signaling. J. Exp. Med. 217, e20200600 (2020).

    PubMed  Google Scholar 

  37. 37.

    Gilbert, N. et al. Formation of facultative heterochromatin in the absence of HP1. EMBO J. 22, 5540–5550 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. 38.

    Gilbert, N. et al. DNA methylation affects nuclear organization, histone modifications, and linker histone binding but not chromatin compaction. J. Cell Biol. 177, 401–411 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. 39.

    Cook, A. J., Gurard-Levin, Z. A., Vassias, I. & Almouzni, G. A specific function for the histone chaperone NASP to fine-tune a reservoir of soluble H3-H4 in the histone supply chain. Mol. Cell 44, 918–927 (2011).

    CAS  PubMed  Google Scholar 

  40. 40.

    Peterson, C. L. & Hansen, J. C. Chicken erythrocyte histone octamer preparation. CSH Protoc. 2008, pdb.prot5112 (2008).

    PubMed  Google Scholar 

  41. 41.

    Allan, J., Staynov, D. Z. & Gould, H. Reversible dissociation of linker histone from chromatin with preservation of internucleosomal repeat. Proc. Natl Acad. Sci. USA 77, 885–889 (1980).

    CAS  PubMed  Google Scholar 

  42. 42.

    Yang, L., Duff, M. O., Graveley, B. R., Carmichael, G. G. & Chen, L.-L. Genomewide characterization of non-polyadenylated RNAs. Genome Biol. 12, R16 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Flicek, P. et al. Ensembl 2014. Nucleic Acids Res. 42, D749–D755 (2014).

    CAS  PubMed  Google Scholar 

  44. 44.

    Kim, D., Langmead, B. & Salzberg, S. L. HISAT: a fast spliced aligner with low memory requirements. Nat. Methods 12, 357–360 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. 45.

    Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    PubMed  PubMed Central  Google Scholar 

  46. 46.

    Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. 47.

    Kent, W. J. et al. The human genome browser at UCSC. Genome Res. 12, 996–1006 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. 48.

    Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank W. Bickmore, F. Taglini, P. Heyn, T. Chandra, R. O’Keefe, Z. Dominski, W. Marzluff, L. Murphy, L. Sanchez-Pulido and C. Ponting for help and advice. We acknowledge the help of the Genetics Core, Edinburgh Clinical Research Facility, University of Edinburgh. Y.J.C. acknowledges the European Research Council (grant nos. GA309449 and 786142-E-T1IFNs), a state subsidy managed by the National Research Agency (France) under the ‘Investments for the Future’ program bearing (no. ANR-10-IAHU-01) and the National Institute for Health Research UK Rare Genetic Disease Research Consortium. The project was supported by MSDAVENIR (Devo-Decode Project) and the Fondation Maladies Rare (GenOmics of rare diseases 2016-1). N.G., D.S., J.L.G.-P., A.P.J. and M.A.M.R. are supported by a UK Medical Research Council (MRC) Human Genetics Unit core grant (no. U127580972). D.S. is a Cancer Research UK Career Development fellow (no. C47648/A20837). This work was supported by a Chancellor’s fellowship of the University of Edinburgh and an Institutional Strategic Research Fund (ISSF3) to A. Dhir. J.R. is supported by the MRC (core funding of the MRC Human Immunology Unit). J.H. was supported by the European Commission under the Horizon 2020 program. We acknowledge the Edinburgh Super-Resolution Imaging Consortium, supported by the Wellcome Trust (grant no. 208345/Z/17/Z).

Author information

Affiliations

Authors

Contributions

C.U., A.L., M.D., A.P.B., M.P.R., M.-T.E.-D., G.I.R., A.P.W., A. Dhir, W.A., M.-L.F., L.S., J.D., N.B., M.J.M.-N., E.D.M., D.S., J.R., J.H., M.A.M.R. and N.G. performed the experiments. S.D., A.R.-R. and J.L.G.-P. performed the bioinformatic analyses. J.-F.D., A.B-A. and R.O. were responsible for genome sequencing. J. Baruteau, K.B., J. Buckley, V.C., C.C., L.M.H.D.W., A. Dobbie, D.D., F.E., M.K.-H., R.K., K.L., J.H.L., A.M., C.M.L., S.O., S.P., K.R., C.A.S., C.S., D.T., G.T., M. Valente, H.V.D.L., H.V.E., M. Vermelle and K.W. ascertained and diagnosed the clinical cases. C.U., A.P.J., M.A.M.R., N.G. and Y.J.C. wrote and edited the manuscript. Y.J.C. was responsible for the overall supervision of the project.

Corresponding author

Correspondence to Yanick J. Crow.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 RNU7-1 sequence variants and pedigrees.

a, CLUSTAL Omega alignment of RNU7-1 sequences. Single nucleotide substitutions identified in probands with Aicardi-Goutières syndrome shaded individually for ease of visualization. Human NR_023317.1 ENSG00000238923; Orangutan U7 ENSPPYG00000029105; Horse U7 ENSECAG00000027042; Chicken U7 ENSGALG00000025670; Anole U7 ENSACAG00000019795; Zebrafish CR388102.4 ENSDARG00000082384; Tetraodon U7 ENSTNIG00000020484; Xenopus U7-201 ENSXETT00000102447.1; Drosophila snRNA:U7 FBgn0053504. b, Structure of pedigrees in which individuals with an Aicardi-Goutières syndrome phenotype were recorded to harbor biallelic rare (allelic frequency ≤ 0.005 on gnomAD) variants in RNU7-1 encoding the snRNA U7. nt, not tested. Variants in grey (n.59C>T and n.62C>G) have a frequency < 0.005 but are considered likely non-pathogenic on the basis of familial segregation.

Extended Data Fig. 2 LSM11 knockdown and RDH pre-mRNA expression in fibroblasts.

a,b, The effect of knockdown of LSM11 in HCT116 (a) and U2OS (b) cells on the processing of replication-dependent histone mRNAs. Primers surrounding the cleavage site were used to assess the presence of polyadenylated RDH transcripts after 24 h knockdown of LSM11 by siRNA. Error bars indicate standard deviation from the mean. Two-tailed Mann-Whitney U test was used to compare differences between two groups. Experiments were performed with a minimum of 3 technical replicates. c, Misprocessing of RDH mRNAs in fibroblasts. Bar charts showing the expression of polyadenylated (Poly(A)+) and non-polyadenylated (Poly(A)-) replication dependent linker (H1) or core (H2A, H2B, H3, H4) histone transcripts in control (n = 3) and AGS8/9 patient-derived (n = 3) fibroblasts.

Extended Data Fig. 3 Interferon signaling in patient blood.

Relative quantification (RQ) values of a panel of six interferon-stimulated genes (ISGs) measured in whole blood in 12 AGS families (AGS114 mutated in LSM11; all others mutated in RNU7-1), compared to the combined results of 29 healthy controls. Numbers in brackets refer to decimalized age at sampling, followed by an interferon score calculated from the median fold change in relative quantification value for the panel of six ISGs. Shades denote individuals, with repeat samples indicated by different bars of the same shade.

Extended Data Fig. 4 ISGs expression and treatment with BX795 and ruxolitinib in patient-derived fibroblasts.

a, Gene set enrichment analysis (GSEA) of genome-wide RNA-seq data derived from control (n = 3) and patient-derived (n = 3) fibroblasts. P value is estimated using GSEA empirical phenotype-based permutation test. b, Treatment of patient fibroblasts with BX795 and ruxolitinib. Assessment of IFIT1 expression following treatment of patient fibroblasts with the TBK1 chemical inhibitor BX795, and the JAK1/2 inhibitor ruxolitinib. Kruskal-Wallis H test, followed by Dunn’s multiple comparison test. Experiments were performed with a minimum of 3 technical replicates. Box plots show the minimum and maximum scores (bottom and top whisker respectively) outside the interquartile range, the lower quartile, the median, and the upper quartile. Data points in the box plots represent the average value per cell line for each experiment.

Extended Data Fig. 5 ISG expression in THP-1 cells after LSM11 knockdown.

a, Expression of interferon beta and selected interferon stimulated genes (ISGs) following 4 to 5 days LSM11 lentivirus shRNA transduction of THP-1 cells. b,c, Expression of interferon beta and selected ISGs (b) and of ISG15 protein (c) following LSM11 lentivirus shRNA transduction of THP-1 cells wild-type or null for cGAS, STING or MAVS. Cofilin was used as a housekeeping protein. The white asterisk indicates a non-specific band. Box plots show the minimum and maximum scores (bottom and top whisker, respectively) outside the interquartile range, the lower quartile, the median, and the upper quartile. Data points in the box plots represent the value for each experiment. Differences in expression within groups were assessed by Kruskal-Wallis H test, followed by Dunn’s multiple comparison test. Error bars indicate standard deviation. Experiments were performed with a minimum of 3 technical replicates.

Extended Data Fig. 6 ISG and phospho-STING expression in THP-1 cells after LSM11 knockdown.

a, Full blot corresponding to Fig. 5e. b, Expression of phospho-STING (Ser366) following knockdown of LSM1 in THP-1 cells wild-type or null for cGAS, STING or MAVS. Vinculin was used as a housekeeping protein. The black arrows indicate the band corresponding to phospho-STING. Experiments were performed with a minimum of 3 biological and/or technical replicates.

Extended Data Fig. 7 Knockdown of nucleic acid sensing pathway molecules in fibroblasts.

a, Knockdown efficiency of MYD88, and expression of ISG15 following MYD88 downregulation. b, Knockdown efficiency of STING, cGAS, MYD88 or MAVS corresponding to Fig. 5f. Two-tailed Mann-Whitney U test was used to compare differences between two groups.

Extended Data Fig. 8 ISG expression in fibroblasts following knockdown of nucleic acid sensing pathway molecules in two different patient lines.

a, AGS8. b, AGS9 (full blot corresponding to Fig. 5f). Experiments were performed with a minimum of 3 biological and/or technical replicates. Vertical white dotted line in a and b (left panel) indicates where gel was cropped.

Extended Data Fig. 9 Assessment of histone protein levels in control and AGS patient fibroblasts.

a, Coomassie blue gel of fibroblast nuclear extract in control (C) and patient (AGS) fibroblasts, and in HEK293 cells. Bands corresponding to linker histones (H1) and core histones (H2A, H2B, H3 and H4) are indicated. The bottom panel shows the same samples run with higher amount of nuclear extract. n = 2 biologically independent samples of control and/or patient fibroblasts. b, Western blot of chromatin-bound histones using antibodies specific to H1.2 and H1.4. Full blot corresponding to Fig. 6b showing that samples were loaded on the same gel.

Extended Data Fig. 10 Proposed model explaining the induction of interferon signaling secondary to mutations in LSM11 or RNU7-1 (AGS8/9).

The U7 snRNP complex is essential for the processing of RDH pre-mRNAs in histone locus bodies (HLB). Mutations in LSM11 and RNU7-1 result in disturbed histone stoichiometry (perhaps particularly relating to linker histones), leading to increased binding of cGAS (green dots) to nuclear DNA and/or enhanced cGAS activation, and the subsequent induction of interferon signaling.

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2 and Tables 1–9

Reporting Summary

Peer Review Information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Uggenti, C., Lepelley, A., Depp, M. et al. cGAS-mediated induction of type I interferon due to inborn errors of histone pre-mRNA processing. Nat Genet 52, 1364–1372 (2020). https://doi.org/10.1038/s41588-020-00737-3

Download citation

Further reading

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing