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Human SNORA31 variations impair cortical neuron-intrinsic immunity to HSV-1 and underlie herpes simplex encephalitis

Nature Medicine volume 25, pages 1873–1884 (2019)Cite this article

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Abstract

Herpes simplex virus-1 (HSV-1) encephalitis (HSE) is typically sporadic. Inborn errors of TLR3- and DBR1-mediated central nervous system cell-intrinsic immunity can account for forebrain and brainstem HSE, respectively. We report five unrelated patients with forebrain HSE, each heterozygous for one of four rare variants of SNORA31, encoding a small nucleolar RNA of the H/ACA class that are predicted to direct the isomerization of uridine residues to pseudouridine in small nuclear RNA and ribosomal RNA. We show that CRISPR/Cas9-introduced bi- and monoallelic SNORA31 deletions render human pluripotent stem cell (hPSC)-derived cortical neurons susceptible to HSV-1. Accordingly, SNORA31-mutated patient hPSC-derived cortical neurons are susceptible to HSV-1, like those from TLR3- or STAT1-deficient patients. Exogenous interferon (IFN)-β renders SNORA31- and TLR3- but not STAT1-mutated neurons resistant to HSV-1. Finally, transcriptome analysis of SNORA31-mutated neurons revealed normal responses to TLR3 and IFN-α/β stimulation but abnormal responses to HSV-1. Human SNORA31 thus controls central nervous system neuron-intrinsic immunity to HSV-1 by a distinctive mechanism.

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Fig. 1: Heterozygous SNORA31 mutations in patients with HSE from five unrelated kindreds.
Fig. 2: Impaired expression of two SNORA31 variants found in three patients with HSE and the loss of a ribosomal modification in SNORA31-null hESC-derived CNS neurons.
Fig. 3: Cellular phenotypes of SV40-fibroblasts from patients with SNORA31 mutations.
Fig. 4: Transcription and propagation of selected viruses in SV40-fibroblasts of patients with SNORA31 mutations.
Fig. 5: Cellular phenotypes in CNS neurons derived from patient iPSCs and isogenic hESCs.
Fig. 6: Transcriptome responses to stimulations with poly(I:C), IFN-α2b or HSV-1 in SNORA31-mutated hPSC-derived cortical neurons.

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Data availability

For population genetics analyses of SNORA31, we used available data from the gnomAD public database (http://gnomad.broadinstitute.org/about). The pseudo-seq data reported in this manuscript are available under accession no. GSE102078. The RNA-seq data reported in this paper are available at the NCBI SRA repository under accession no. PRJNA580002. Other raw experimental data associated with the figures presented in the manuscript are available from the authors upon request.

Code availability

There is no restriction to access to the custom code for the cell lines used in this study. Information is available from the authors on request.

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Acknowledgements

We warmly thank the patients and their families for participating in this study. We thank F. Sami Alkuraya from the Saudi Human Genome Project for providing us with the minor allele frequency of the reported variant. We thank J. Tchieu and G. Ciceri for providing advice concerning the protocol for iPSC differentiation into CNS neurons. We thank K. Bohannon from the Feinberg School of Medicine at Northwestern University for providing HSV-1 strain Patton encoding the mCherry-UL25 fusion. We thank members of both branches of the Laboratory of Human Genetics of Infectious Diseases for helpful discussions: T. Kochetkov for technical assistance; B. Bigio, V. Ratinna, Y. Seeleuthner, B. Boisson and A. Cobat for bioinformatic assistance; and D. Papandrea, C. Patissier and Y. Nemirovskaya for administrative assistance. This work was conducted in the two branches of the Laboratory of Human Genetics of Infectious Diseases, and was funded in part by the National Center for Advancing Translational Sciences, National Institutes of Health (NIH), Clinical and Translational Science Award program (grant nos. UL1TR000043 and UL1TR001866), NIH grants (nos. R01AI088364 to J.L.C. and S.Y.Z., R01NS072381 to J.-L.C. and S.-Y.Z. and R01GM101316 to W.G.); a grant from the Integrative Biology of Emerging Infectious Diseases Laboratory of Excellence (no. ANR-10-LABX-62-IBEID to L.A.) and the French National Research Agency (ANR) under the ‘Investments for the future’ program (no. ANR-10-IAHU-01 to L.A.), the ANR grant IEIHSEER (no. ANR-14-CE14-0008-01 to S.-Y.Z.), the Lundbeck Foundation (grant no. R268-2016-3927 to S.R.P.), the Rockefeller University, INSERM, Paris Descartes University and the St Giles Foundation. The New York Stem Cell Foundation supported F.G.L. and D.P. F.G.L. also was supported by a Merck Postdoctoral Fellowship at The Rockefeller University. Funding for this work was also provided in part by the Division of Intramural Research, National Institute of Allergy and Infectious Diseases, NIH.

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Authors and Affiliations

  1. St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA

    Fabien G. Lafaille, Yoon Seung Lee, Peng Zhang, Mary L. Hasek, Yuval Itan, Franck Rapaport, Daxing Gao, Michael J. Ciancanelli, Laurent Abel, Jean-Laurent Casanova & Shen-Ying Zhang

  2. The Center for Stem Cell Biology, Sloan-Kettering Institute for Cancer Research, New York, NY, USA

    Oliver Harschnitz, Bastian Zimmer, Jessica L. McAlpine & Lorenz Studer

  3. Developmental Biology Program, Sloan-Kettering Institute for Cancer Research, New York, NY, USA

    Oliver Harschnitz, Bastian Zimmer, Jessica L. McAlpine & Lorenz Studer

  4. Laboratory of Human Genetics of Infectious Diseases, Necker Branch, Necker Hospital for Sick Children, Paris, France

    Yoon Seung Lee, Gaspard Kerner, Vimel Rattina, Lazaro Lorenzo, Soraya Boucherit, Laurent Abel, Jean-Laurent Casanova & Shen-Ying Zhang

  5. Paris Descartes University, Imagine Institute, Paris, France

    Yoon Seung Lee, Gaspard Kerner, Vimel Rattina, Lazaro Lorenzo, Soraya Boucherit, Laurent Abel, Jean-Laurent Casanova & Shen-Ying Zhang

  6. The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Yuval Itan

  7. Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Yuval Itan

  8. Department of Microbiology-Immunology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA

    Osefame Ewaleifoh & Gregory A. Smith

  9. Biogen, Cambridge, MA, USA

    Thomas M. Carlile & Marc Tessier-Lavigne

  10. Department of Infectious Diseases, Aarhus University Hospital, Aarhus, Denmark

    Madalina E. Carter-Timofte & Trine Hyrup Mogensen

  11. Department of Biomedicine, Aarhus University, Aarhus, Denmark

    Madalina E. Carter-Timofte, Søren R. Paludan & Trine Hyrup Mogensen

  12. Laboratory of Brain Development and Repair, The Rockefeller University, New York, NY, USA

    Dominik Paquet & Dylan Kwart

  13. Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany

    Dominik Paquet

  14. Munich Cluster for Systems Neurology (SyNergy), Munich, Germany

    Dominik Paquet

  15. Laboratory of Clinical Immunology and Microbiology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA

    Kerry Dobbs & Luigi D. Notarangelo

  16. Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA

    Maria F. Rojas-Duran & Wendy Gilbert

  17. Virology Department, Paris Descartes University, Sorbonne Paris Cité University, Welfare Services Paris Hospital, Hospital Group Paris Center University, Paris, France

    Flore Rozenberg

  18. Sharjah Institute for Medical Research (SIMR), Department of Clinical Sciences, College of Medicine, University of Sharjah, Sharjah, United Arab Emirates

    Rabih Halwani

  19. Department of Infectious Diseases, Pitié-Salpêtrière Hospital, Paris, France

    Benoit Henry

  20. Clinical Immunology Unit, Children’s Ibn Rushd Hospital and Clinical Immunology Laboratory, Inflammation and Allergy LICIA, Faculty of Medicine and Pharmacy, Hassan Ii University, Casablanca, Morocco

    Naima Amenzoui & Ahmed Aziz Bousfiha

  21. Immunology Research Laboratory, Department of Pediatrics, College of Medicine, King Saud University, Riyadh, Saudi Arabia

    Zobaida Alsum

  22. Pediatric Department, Infectious Diseases and Immunodeficiencies Unit, Porto Hospital Center, Porto, Portugal

    Laura Marques

  23. Department of Pediatrics, Children’s Hospital Los Angeles and Keck School of Medicine, University of Southern California, Los Angeles, CA, USA

    Joseph A. Church

  24. Prince Naif Center for Immunology Research, King Saud University, Riyadh, Saudi Arabia

    Saleh Al-Muhsen

  25. South Paris University Hospital, Paris Hospital Welfare Services, Department of Pediatric Neurology, Paris, France

    Marc Tardieu

  26. Department of Clinical Medicine, Aarhus University, Aarhus, Denmark

    Trine Hyrup Mogensen

  27. Unit of Human Evolutionary Genetics, CNRS UMR2000, Institut Pasteur, Paris, France

    Lluis Quintana-Murci

  28. Department of Biology, Stanford University, Stanford, CA, USA

    Marc Tessier-Lavigne

  29. Pediatric Immuno-Hematology Unit, Necker Hospital for Sick Children, Paris, France

    Jean-Laurent Casanova

  30. Howard Hughes Medical Institute, New York, NY, USA

    Jean-Laurent Casanova

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  1. Fabien G. Lafaille
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  43. Shen-Ying Zhang
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F.G.L., O.H. and Y.S.L. performed the experiments and analyzed the data. M.L.H., O.E., T.M.C., M.E.C.-T., D.P., K.D., B.Z., D.G., M.F.R.-D., D.K., M.J.C., J.L.M., L.L., F.R., S.R.P., T.H.M., M.T.-L., G.A.S., L.D.N., L.S. and W.G. performed the experiments. S.B. assisted with patient recruitment. R.H., B.H., N.A., Z.A., L.M., J.A.C., S.A.-M., M.T. and A.A.B. contributed patient samples and collected clinical data. P.Z., G.K., Y.I., F.R., V.R., L.Q.-M. and L.A. analyzed the data. J.-L.C. and S.-Y.Z. analyzed the data, supervised the research and wrote the paper with the help of all co-authors. F.G.L., O.H., Y.S.L. and P.Z. are co-first authors. M.L.H., G.K., Y.I., O.E., F.R., T.M.C. and M.E.C.-T. are co-second authors. D.P., K.D. and B.Z. are co-third authors. L.D.N., L.S., W.G. and L.A. are co-second-to-last authors. J.-L.C. and S.-Y.Z. are co-last authors who jointly supervised this work.

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Correspondence to Jean-Laurent Casanova or Shen-Ying Zhang.

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Extended data

Extended Data Fig. 1 Heterozygous SNORA31 mutations in HSE patients from five unrelated kindreds.

A, Ranking of the top 10 mutated genes for which enrichment was detected in the HSE cohort (205 patients) versus 4,267 controls. The selection filters for the variants were: MAF ExAC < 0.001 and CADD > MSC. This represents 1,274,230 variants in 20,691 genes. For each gene, the number of affected individuals among HSE cases and controls was determined. Individuals were considered affected if they carried at least one mutant allele passing the filters. The genes were ranked by p-values adjusted for ethnic heterogeneity, which was obtained by logistic regression comparing cases and controls adjusted for the three principal components and using the likelihood ratio test (see Methods for more details). B, Expression of snoRNA31 across the different cell types tested. N = 4 (for hESC, iPSC, hESC-derived cortical neurons, iPSC-derived cortical neurons), n = 6 (SV40-fibroblasts) or n = 8 (for primary fibroblasts, EBV-B) biological replicates were tested per cell type, in a single experiment. Each point represents one biological replicate. Means from the biological replicates are indicated with centre lines. C, Patient origin, age at the time of the HSE event, and the MAF of the SNORA31 variant in the GnomAD and BRAVO databases. The ancestry frequencies of the n.36 T > C variant were determined from WES data for 500 Moroccan individuals and 1,100 Saudi Arabian individuals. D, Genomic haplotypes of the n.36 T > C regions in kindreds A and B. The n.36 T > C mutation occurred independently in kindreds A and B. Genotypes for the mutation (M, in red) and 10 informative SNPs (black) are represented. Different haplotypes were found in kindreds A and B. E, Histogram representation of the patient-specific SNORA1 mutations, confirmed by Sanger sequencing on genomic DNA from leukocytes and/or fibroblasts from the 5 patients and a healthy control wild type (WT) for SNORA31. F, Plot of GDI values for all reported snoRNA genes (from Ensembl) against their rank, from the least to the most mutated, in the general population (1000 Genomes database). The ranks of SNORA31 and SNORD118 are indicated. G, Phylogenic conservation of the genomic sequence of SNORA31 across 14 different vertebrate species. The data were taken from the snoRNABase (https://www-snorna.biotoul.fr/). Invariant residues are indicated by asterisks below the sequence. Residues conserved in at least 78% of the species are indicated in black. Residues conserved in at least 64% of the species are indicated in blue. Residues conserved in at least 57% of the species are indicated in green. All other residues are indicated in gray. The positions of the variants found in the HSE patients are indicated in red below the sequence. H, Minimum free energy (MFE) of a SNORA31 stem (n.66-84; n.111-130) or loop (n.16-48 and n.85-110), for WT or mutated sequences. The MFE was calculated with the RNAfold program (http://rna.tbi.univie.ac.at/). The dot-bracket sequence of SNORA31 is indicated under each nucleotide. The location of each mutation is indicated in red and highlighted.

Extended Data Fig. 2 Expression of WT and mutant SNORA31 in HEK293T cells and in isogenic hESC-derived neurons.

A, Quantification, by qPCR, of SNORA31 copy numbers in 293T cells transfected with an empty plasmid or a plasmid containing the WT sequence of SNORA31. Copy numbers were calculated from a standard curve. Insect SF9 cells were used as a negative control in this experiment as they contain no SNORA31 homolog. N.T: not transfected. E.V: empty vector. Means and standard deviations from n = 3 independent experiments are shown. B, Northern blot of SNORA31 in HEK293T cells either not transfected or transfected with an empty vector or a vector containing WT or mutant SNORA31. Cropped images from the same blot are shown. The data presented are representative of n = 2 independent experiments. C, RT-qPCR quantification of the fold-change in SNORA31 expression in HEK293T cells. Cells were transfected with a vector containing WT SNORA31 alone or cotransfected with the same amount of empty vector and a vector containing the WT or one of the HSE SNORA31 mutant sequences. The data are expressed relative to SNORD96a expression and normalized relative to the expression of SNORA31 in HEK293T cells transfected with WT SNORA31 vector alone. Means and standard deviations from n = 3 independent experiments are shown. D, Plots of the relative expression levels of gnomAD SNORA31 mutant alleles (normalized relative to WT SNORA31 expression level) against minor allele frequency in gnomAD. RT-qPCR quantification of gnomAD SNORA31 mutant allele expression in HEK293T cells transfected with vectors containing each of the mutant alleles. The data are expressed relative to the expression of endogenous SNORD96a and normalized relative to that of SNORA31 in cells transfected with a plasmid carrying the WT sequence. The expression levels of each gnomAD variant were assessed in n = 2 independent experiment, and the mean value for each variant is shown as a dot. E, Plot of the relative levels of expression of gnomAD SNORA31 mutant alleles (normalized relative to WT SNORA31 expression levels) against their calculated change in minimum free energy. The expression levels of each gnomAD variant were assessed in n = 2 independent experiment, and the mean value for each variant is shown as a dot. F, Surveyor assay for full-length SNORA31 PCR in HEK293T cells transfected with Cas9-GFP vector alone (⃠) or together with a scrambled guide RNA (gRNA) vector, or a SNORA31 gRNA vector. The data shown is representative of data from n = 2 independent experiments. G, Histogram representation of the CRISPR-Cas9-introduced homozygous or heterozygous SNORA1 mutations (het del1 n.76-82, hom del1 n.81-86), confirmed by Sanger sequencing on genomic DNA from the gene-edited hESC lines. Sequencing results from the parental line is also shown. H, Demonstration of the CNS cortical identity (TBR1-positive) of neurons (TUJ1-positive) differentiated from the hESC control line H9. The images shown are representative of data from n = 6 independent experiments. I, Quantification of the proportion of cortical neurons among total neurons based on the immunostaining of parental and gene-edited hESCs harboring either a heterozygous (het del1) or a homozygous (hom del1) deletion in SNORA31. Results from technical duplicates from a single experiment are shown, representative of n = 3 independent neuron differentiations for each line. J, Northern blot of SNORA31 expression in isogenic hESC-derived CNS neurons. SNORA31 expression in parental cells is compared to that in cells carrying heterozygous del 1 (het del1) or homozygous del 1 (hom del1) in the genomic sequence of SNORA31. The data presented are representative of n = 2 independent experiments. K, Levels of TPT1 protein, encoded by the host gene of SNORA31, as assessed on western blots for isogenic CNS neurons. Cropped images from the same blot are shown. GAPDH was used as a loading control. The data are representative of n = 2 independent experiments. L, Pseudouridylation data obtained by pseudo-seq. Each point represents a pseudouridylation site. Mean values from n = 4 libraries each for the parental and het del1 lines and n = 3 libraries for the hom del1 line are shown. M, Genomic sequence of SNORA31B. The guide sequences for this putative snoRNA gene are highlighted in red.

Source data

Extended Data Fig. 3 Cellular phenotypes of the SV40-fibroblasts of patients with SNORA31 mutations.

A, Sequencing results for SNORA31 cDNA from the SV40-fibroblasts of four patients (P2-P5), after cloning in E. coli. The number of individual WT or mutant colonies detected by sequencing is indicated on the left of the table, whereas the corresponding percentage is indicated on the right. B, Levels of TPT1 protein (upper panel), encoded by the host gene of SNORA31, in the patient and control SV40-fibroblasts, as measured by western blotting. GAPDH was used as a loading control (middle panel). The data presented are representative of n = 2 independent experiments. Semi-quantification of TPT1 band density relative to GPADH was performed and the data are shown in the lower panel. C, IL-6 production in SV40-fibroblasts from patients (P2-P5), a TLR3−/− control, and five healthy controls, as measured by ELISA, in the supernatant of control and patient SV40-fibroblasts stimulated with 25 μg/mL poly(I:C) alone, Lipofectamine alone, or both. TLR3−/− cells were used as a negative control for the poly(I:C) response. N.S: not stimulated. N = 3 independent experiments were performed, with n = 1 biological replicate per cell line tested per experiment. Each point represents one biological replicate. The means of the three independent experiments are shown. The levels of IL-6 production upon poly(I:C) stimulation are compared between controls’ and patients’ cells, in one way ANOVA (F = 1.403, total df = 29) followed by Dunnett’s multiple comparison tests. ** 0.001 < p < 0.01. D Relative expression levels for SNORA31, as determined by RT-qPCR after stimulation with poly(I:C) or IFN-β in control SV40-fibroblasts. The data are expressed relative to SNORD96a expression. N = 3 independent experiments were performed, with n = 3 (for IFN-β stimulation) or n = 6 (all other conditions) biological replicates tested per experiment. Each point represents one biological replicate. Means and standard deviations from three independent experiments are shown. E, F, HSV-1 (strain KOS) abundance, as determined by measurements of GFP-capsid expression in SV40-fibroblasts at the indicated time points post infection with a MOI of 0.01 (E) followed by measurements of the corresponding titers, as determined by calculating the 50% end point (TCID50) in Vero cells (F), for four SNORA31-deficient patients (P2-P5), a TLR3−/− patient and a STAT1−/− patient as susceptible controls, and two healthy controls. Mean values from n = 2 independent experiments are shown. N = 1 (for TCID50 assay) or n = 3 (for measurement of GFP-capsid expression) biological replicates were tested per condition per experiment. G, Percentage of patient and control SV40-fibroblasts producing capsids 24 hours post infection with HSV-1 strain KOS (left), F (middle) or Patton (right) at a MOI of 3 (based on titers measured on Vero cells). Means and standard deviations of n = 3 independent experiments are shown. N = 1 biological replicate was tested per condition per experiment. H, I, HSV-1 (strain KOS) abundance, as determined by measurements of GFP-capsid expression in patient (P2-P5) and control SV40-fibroblasts at the indicated time points following infection at a MOI of 0.1, without (H) and with (I) IFN-β pretreatment for 16 hours. STAT1−/− cells were used as a control with no IFN-β response. Means and standard deviations from n = 3 independent experiments are shown. N = 3 biological duplicates were tested per condition per experiment.

Source data

Extended Data Fig. 4 HSV-1 propagation in immortalized B cells and iPSCs from patients with SNORA31 mutations.

A, Quantification of HSV-1 (strain KOS) in EBV-immortalized B cells from patients (P2, P4, P5), a TRIF−/− patient and a STAT1−/− patient, and healthy controls, at the indicated time points post infection with a MOI of 0.1. HSV-1 titers were determined by the TCID50 virus titration method. Means and standard deviations from n = 3 independent experiments are shown. B, HSV-1 (strain KOS) abundance, as determined by measurements of GFP-capsid expression in iPSCs (left) at the indicated time points post infection with a MOI of 0.1, for three SNORA31-mutated patients (P2, P3, P5), a TLR3−/− patient and a STAT1−/− patient, and hESCs from a healthy control (H9 line). HPSC-derived cortical neurons from a TLR3−/− patient and a healthy control were assessed in the same assay (right). Mean values from n = 2 independent experiments are shown. C, D, Expression levels of the VZV ORF40 (C) and ORF63 (D) transcripts, as measured by RT-qPCR on SV40-fibroblasts from patients (P2-P5), a TLR3−/− patient and a STAT1−/− patient, and healthy controls (C1 and C2), 48 h post exposure to VZV-infected MeWo cells (VZV) or MeWo cells that were not infected (N.I.). The data are expressed relative to GAPDH expression. Means and standard deviations from n = 3 independent experiments are shown.

Extended Data Fig. 5 Characterization of CNS neurons derived from patient iPSCs and isogenic hESCs.

A, Quantification of the proportion of neurons among total neuronal cells, based on immunostaining, for control hESC- and control iPSC-derived CNS neurons (H9 and J2) and for CNS neurons derived from the patients’ iPSCs. Results from technical duplicates from one experiment are shown, representative of n = 3 neuron differentiations per line (H9, J1, J2 control lines, and iPSC lines from P2, P3 and P5). B, Sequencing results for the SNORA31 cDNA obtained from the patients’ iPSC-derived neurons, after cloning in E. coli. The number of individual WT or mutant colonies detected by sequencing is indicated on the left side of the table, whereas the corresponding percentage is indicated on the right. C, Levels of TPT1 protein, encoded by the host gene of SNORA31, in control (H9 hESC) and patient iPSC-derived neurons, as assessed by western blotting. GAPDH was used as a loading control. Results of semi-quantification of TPT1 expression levels relative to GAPDH are shown in the lower panel. The data presented are representative of n = 2 independent experiments. D, Histogram representation of the CRISPR-Cas9-introduced homozygous or heterozygous SNORA1 mutations (hom del2 n.84-91, hom HDR n.75 C > G, het del2 n.80-85, het del3 n.79-82, het del4 n.77-83, het del5 n.76-88), confirmed by Sanger sequencing on genomic DNA from the gene-edited hESC lines. Sequencing results from the parental line is also shown. E, Levels of TPT1 protein, encoded by the host gene of SNORA31, as measured by western blotting (upper panel), in CNS neurons derived from isogenic hESCs carrying a homozygous HDR-introduced patient-specific point mutation (hom HDR), a homozygous deletion (hom del2), or various heterozygous mutations (het del1, het del2, het del3, het del4, het del5) in SNORA31. GAPDH was used as a loading control (lower panel). The data presented are representative of n = 3 independent experiments, with n = 1 biological replicate tested per condition per experiment. Semi-quantification of TPT1 band density relative to GPADH was performed and the data are shown in the lower panel. F, Quantification of HSV-1 in isogenic hPSC-derived CNS neurons, at various time points after HSV-1 infection at a MOI of 1, as assessed by measuring GFP-capsid expression. Four healthy control lines were used in these experiments: two control hESC lines and two control iPSC lines. Means and standard deviations from n = 3 independent experiments are shown.

Source data

Extended Data Fig. 6 Transcriptome responses to stimulation with poly(I:C), IFN-α2b or HSV-1 in SNORA31-mutated hPSC-derived cortical neurons.

A, B, Scatter plots of fold-changes in RNA-Seq-quantified gene expression following stimulation with 25 µg/ml poly(I:C) for 6 hours (A) or 100 IU/ml IFN-α2b for 8 hours (B), in hPSC-derived cortical neurons from one healthy control H9 hESC line (C1) versus one isogenic SNORA31-mutated line (hom del2 or het del1). Moderated fold-changes are expressed relative to the corresponding mock-treated samples. Each point represents a single gene, and each plot includes genes identified as differentially expressed (FDR < = 0.05) in response to the indicated stimulus relative to non-stimulated (N.S) samples in the isogenic control or SNORA31-mutated line. C, Transcriptome composition analysis of RNA-Seq-quantified gene expression, in hPSC-derived cortical neurons from healthy controls (C1 and C2), an isogenic SNORA31-mutated line, SNORA31-mutated patients (P2 and P5), and a STAT1−/− patient, with or without 24 hours of infection with HSV-1 at a MOI of 1. D, Heatmap of RNA-Seq-quantified HSV-1 transcript expression (RPKM relativity) in hPSC-derived cortical neurons from healthy controls (C1 and C2), SNORA31-mutated patients (P2 and P5), an isogenic SNORA31-mutated hESC line (het del1), and a STAT1−/− patient, following infection with HSV-1 for 24 hours at a MOI of 1. E, Scatter plot of averaged log2 fold-changes in gene expression by 24 hours of HSV-1 infection, in two healthy controls (C1, C2) versus hPSC-derived cortical neurons from three SNORA31-mutated lines (patient-specific lines from P2 and P5, and an isogenic SNORA31-mutated hESC line, SNORA31 het del1). Moderated fold-changes are expressed relative to the corresponding mock-treated samples. Each point represents a single gene, and the plot includes genes identified as differentially expressed (FDR < = 0.05, > 2-fold difference) in response to the indicated stimulus relative to N.S samples in the healthy control or SNORA31-mutated groups. F, Number of human transcripts up- or downregulated by HSV-1 infection in either or both of control (C1 and C2) and SNORA31-mutated (P2 and P5, and isogenic SNORA31 het del1 line) hPSC-derived cortical neurons.

Supplementary information

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Supplementary Patient Clinical Information.

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Supplementary Table 1.

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Unprocessed immunoblots.

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Lafaille, F.G., Harschnitz, O., Lee, Y.S. et al. Human SNORA31 variations impair cortical neuron-intrinsic immunity to HSV-1 and underlie herpes simplex encephalitis. Nat Med 25, 1873–1884 (2019). https://doi.org/10.1038/s41591-019-0672-3

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