Abstract
Disease, injury and aging induce pathological reactive astrocyte states that contribute to neurodegeneration. Modulating reactive astrocytes therefore represent an attractive therapeutic strategy. Here we describe the development of an astrocyte phenotypic screening platform for identifying chemical modulators of astrocyte reactivity. Leveraging this platform for chemical screening, we identify histone deacetylase 3 (HDAC3) inhibitors as effective suppressors of pathological astrocyte reactivity. We demonstrate that HDAC3 inhibition reduces molecular and functional characteristics of reactive astrocytes in vitro. Transcriptional and chromatin mapping studies show that HDAC3 inhibition disarms pathological astrocyte gene expression and function while promoting the expression of genes associated with beneficial astrocytes. Administration of RGFP966, a small molecule HDAC3 inhibitor, blocks reactive astrocyte formation and promotes neuroprotection in vivo in mice. Collectively, these results establish a platform for discovering modulators of reactive astrocyte states, inform the mechanisms that control astrocyte reactivity and demonstrate the therapeutic benefits of modulating astrocyte reactivity for neurodegenerative diseases.
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Data availability
All sequencing datasets generated in this study have been deposited in GEO (https://www.ncbi.nlm.nih.gov/geo/) under SuperSeries accession code GSE185215 with subseries for astrocyte RNA-seq, ONC RNA-seq, scRNA-seq, CUT&RUN and ATAC-seq. Previously published data for ref. 46 (PMID: 34413515) is available under GEO accession GSE148612. Previously published data for ref. 22 (PMID: 31768052) is available under accession GSE138852. Previously published data for ref. 23 (PMID: 32070434) is available under GEO accession GSE180928. Previously published data for ref. 24 (PMID: 34919646) is available under GSE157783. Source data are provided with this paper.
Code availability
Data analysis was performed with publicly available packages by following available tutorials and vignettes.
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Acknowledgements
This study was supported by grants from the National Multiple Sclerosis Society (TA-2105-37619 to B.L.L.C.), the National Institutes of Health (R35NS116842 to P.J.T., F30HD096784 and T32GM007250 to K.C.A, K08EY029362 to A.R.S, and F31NS124282, T32NS077888 and T32GM007250 to E.F.C.), the Hartwell Foundation (to B.L.L.C.), as well as institutional support from the Case Western Reserve University (CWRU) School of Medicine and philanthropic support from sTF5 Care and the R. Blane & Claudia Walter, Long, Goodman, Geller and Weidenthal families and the Research Institute for Children’s Health. Additional support was provided by the Small Molecule Drug Development and Genomics core facilities of the CWRU Comprehensive Cancer Center (P30CA043703), the CWRU Light Microscopy Imaging Center (Shared Instrumentation Grant NIH ORIP S10OD024981) and the University of Chicago Genomics Facility (P30CA014599). We thank D. Adams, Y. Fedorov, W. Harte, M. Scavuzzo, M. Madhavan, D. Kassel and M. Elitt for technical assistance and/or discussion and C. Lilliehook for editorial support.
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Contributions
B.L.L.C. and P.J.T. conceived and managed the overall study. B.L.L.C., J.D.K. and A.M.S. performed, quantified and analyzed in vitro studies. H.E.S., A.M.S. and A.K. helped to generate astrocyte cultures. E.C.F. generated TMEV virus. B.L.L.C. performed and analyzed all scRNA-seq experiments. B.L.L.C. performed the small-molecule screen and validations. K.C.A. performed SE analysis. E.F.C. performed CUT&RUN and ATAC-seq. B.L.L.C. performed CUT&RUN, ATAC-seq and bulk RNA-seq data analysis. B.L.L.C., A.M.S. and A.K. performed and analyzed in vivo LPS studies. M.K., E.G. and R.H.M. performed in vivo LPC studies and generated EM images. A.D.J., A.R.S., J.A.S. and B.M.S. performed and analyzed ONC studies. Y.M.-H. analyzed EM images. B.L.L.C. assembled all figures. B.L.L.C. and P.J.T. wrote the paper with input from all authors.
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B.L.L.C. and P.J.T. are listed as inventors on pending patent claims filed by Case Western Reserve University covering methods and compositions for treating neurodegenerative disorders. The other authors declare no competing interests.
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Extended data
Extended Data Fig. 1 Purity and function of astrocyte cultures.
a, Overview diagram of astrocyte isolation and enrichment protocol (images generated by BioRender). b, Phase contrast image showing prototypical astrocyte morphology from a single astrocyte culture. Scale bar is 50 µm. Immunofluorescence images showing expression of canonical astrocyte markers AQP4, GLT-1 (SLC1A2) and ALDH1L1 in a single astrocyte culture. Scale bar is 100 µm. c, Bulk RNA-seq data showing high expression of astrocyte marker genes and no expression of marker genes for other CNS cell types. Data are from 3 biological replicates (independent astrocyte isolations). d, Glutamate uptake by physiological astrocytes in culture. Data presented as the mean ± s.e.m. for technical replicates (open circles) from 3 biological replicates (independent astrocyte isolations). e–h, ATAC-seq tracks at marker genes for CNS cell types. Chromatin is only open at astrocyte genes. i, Bulk RNA-seq data showing decreased expression of Meg10 and Mertk in agreement with decreased phagocytosis of myelin debris by reactive astrocytes. Data presented as mean ± s.e.m. for n = 3 biological replicates. P-value generated by paired two-tailed t-test. j, The log2 fold-change (log2(FC)) of secreted cytokines in reactive vs physiological astrocytes conditioned media. Data presented as mean ± s.e.m for n = 3 biological replicates.
Extended Data Fig. 2 In vitro reactive astrocytes correspond to in vivo counterparts.
a, Enrichment map of gene ontology terms for genes upregulated in reactive vs physiological astrocytes. b, Enrichment map of gene ontology terms for genes upregulated in physiological vs reactive astrocytes. c, Representative images of physiological astrocytes, astrocytes exposed to TIC cytokines and astrocytes infected with TMEV and stained for double stranded RNA to show viral infection (dsRNA in green) and GBP2 (red). d, Quantification of the percentage of astrocytes that are positive for the viral marker dsRNA. Data presented as mean ± s.e.m for n = 3 biological replicates, with p-value calculated by a one-way ANOVA. e, Quantification of the percentage of astrocytes that are GBP2 positive. Data presented as mean ± s.e.m for n = 3 biological replicates, with p-value calculated by a one-way ANOVA with Dunnett correction for multiple comparisons. f, Quantitative PCR results comparing the expression of pathological reactive astrocyte markers Gbp2 and Psmb8 by physiological astrocytes, astrocytes exposed to TIC cytokines and astrocytes infected with TMEV. P-value calculated by one-way ANOVA with Dunnett correction for multiple comparisons. g, UMAP plots from integrated single-cell RNA-seq analysis of in vitro physiological and reactive astrocytes from this study with in vivo astrocytes from LPS or vehicle treated mice46. h, Frequency of cells distributed across different astrocyte clusters. i, Expression of pathological reactive astrocyte genes and astrocyte marker genes in each single-cell cluster. j, Gene ontology results showing enriched terms for genes enriched in clusters 2, 6 and 7 that contain mainly astrocytes from reactive cultures and LPS treated mice. P-values generated by Benjamini-Hochberg false discovery rate.
Extended Data Fig. 3 Epigenomics of astrocyte reactivity.
a, Biological (Bio) replicate ATAC-seq tracks for Fig. 2c. b, Depiction of gained, lost, and shared H3K27ac or super-enhancer peaks during the transition from physiological to reactive astrocytes. c, Biological replicate H3K27ac CUT&RUN tracks in Fig. 2i. d, Gene ontology analysis of genes targeted by gained super-enhancers in reactive astrocytes that are also upregulated in reactive astrocytes compared to physiological in bulk RNA-seq analysis. P-values generated by Benjamini-Hochberg false discovery rate. e, Bulk RNA-seq volcano plot of genes with a gained H3K27ac CUT&RUN peak (+/−5 kb of the transcription start site (TSS)) in reactive astrocytes. log2(FC) and p-adj values were generated from bulk RNA-seq analysis with DESEQ2 f, Bulk RNA-seq volcano plot of genes with a shared H3K27ac CUT&RUN peak (+/−5 kb of the transcription start site (TSS)) in both reactive and physiological astrocytes. log2(FC) and p-adj values were generated from bulk RNA-seq analysis with DESEQ2 g, Bulk RNA-seq volcano plot of genes with a lost H3K27ac CUT&RUN peak (+/−5 kb of the transcription start site (TSS)) in reactive astrocytes. log2(FC) and p-adj values were generated from bulk RNA-seq analysis with DESEQ2. h, Gene ontology analysis of genes targeted by gained H3K27ac CUT&RUN peak in reactive astrocytes that are also upregulated in reactive astrocytes compared to physiological in bulk RNA-seq analysis. P-values generated by Benjamini-Hochberg false discovery rate.
Extended Data Fig. 4 High-throughput chemical screen quality control and validation of HDAC3.
a, Example images of DMSO vehicle-treated reactive and physiological control wells from the phenotypic screen. Scale bar is 100 µm. b, Z′ standard and robust scores for primary screen plates. c, Percent GBP2 positive astrocytes in DMSO vehicle treated reactive and physiological control wells on each primary screen plate. Data as the mean ± s.e.m., n = 16 wells per group on each primary screen plate. d, Dose curve of primary screen hits. Data are percent of GBP2 positive cells normalized to DMSO vehicle treated reactive astrocyte control wells. n = 2 biological replicates (independent astrocyte isolations). Black data points represent toxic doses where total cell number decreased by >50% compared to vehicle treated reactive astrocyte control wells. e, Dose curve analysis of hits from primary screen with Psmb8 positivity by in situ hybridization as a secondary endpoint. Data are percent of Psmb8 mRNA positive normalized to DMSO vehicle treated reactive astrocyte control wells with an n = 1 biological replicate (independent astrocyte isolation). Black data points represent toxic doses where total cell number decreased by >50% compared to vehicle treated reactive astrocyte control wells. f, Ranked inhibition against each HDAC isozyme for validated HDAC inhibitors in the primary screen. Highlighted is HDAC as the only shared target between all HDAC inhibitor hits. Ranked efficiency was pulled from target data provided by Selleck Chemical. g, Dose curve and IC50 value for the HDAC3 specific inhibitor RGFP966 to block astrocyte reactivity with an n = 5 biological replicates. h, Dose curve and IC50 value for the HDAC3 specific inhibitor T247 to block astrocyte reactivity with an n = 2 biological replicates. i–k, Representative images and quantification of wild-type (WT) and HDAC3 knockout (KO) astrocyte cultures exposed to TIC cytokines. Scale bar is 100 µm. Data are mean ± s.e.m., n = 3 independent experiments, p-value by a paired t-test. l, GBP2 and PSMB8 qPCR results for human iPSC derived physiological or reactive astrocyte cultures treated with vehicle or 5 μM RGFP966. Data are mean ± s.e.m., n = 4 technical replicates.
Extended Data Fig. 5 Histone acetylation does not predict HDAC3 inhibition induced gene expression changes in reactive astrocytes.
a, Tukey box and whisker plot showing the average log2 fold-change (log2(FC)), from bulk RNA-seq, of the top 100 upregulated genes targeted by gained super-enhancers, all genes targeted by shared super-enhancers, and the top 100 downregulated genes targeted by lost super-enhancers in pathological reactive astrocytes. Data are presented for n = 3 biological replicates. Two-tailed p-value is generated with a one-sample Wilcoxon signed ranked test comparing to a hypothetical median of log2(FC) = 0 which would designate no difference in expression between reactive and physiological astrocytes. b, Quantification of CCL5 ELISAs performed on astrocyte conditioned media. Data presented as mean ± s.e.m for an n = 3 biological replicates with p-values compared to reactive plus vehicle control and calculated by one-way ANOVA with Dunnett correction for multiple comparisons. c, Tukey box and whisker plot showing the level of H3K27ac, from CUT&RUN, at gained, shared and lost super-enhancer in reactive astrocytes treated with RGFP966. Data are presented for n = 3 biological replicates. Two-tailed p-value is generated with a one-sample Wilcoxon signed ranked test comparing to a hypothetical median of log2(FC) = 0. d,e, Representative images and quantification of physiological astrocytes treated with vehicle, 5 μM RGFP966, or 5 μM JSH-23 and then stained for acetyl-RelA/p65 (K310). Scale bar is 100 µm. Data are mean ± s.e.m, n = 3 biological replicates, p-value by one-way ANOVA with Dunnett multiple comparison correction. f, Uncropped western blots for Fig. 3g. g, Transcription factor motifs enriched in H3K27ac CUT&RUN peaks from vehicle treated reactive astrocytes versus RGFP966 (RGFP) treated reactive astrocytes. P-values generated by HOMER. h, Transcription factor motifs enriched in H3K27ac CUT&RUN peaks from RGFP treated reactive astrocytes versus vehicle treated reactive astrocytes. P-values generated by HOMER. i, Normalized NF-κB luciferase activity in Jurkat reporter cells treated with the validated hits from the primary drug screen. Data presented as percentage of NF-κB activity from a single independent experiment.
Extended Data Fig. 6 HDAC3 inhibition modulates pro- and anti-inflammatory gene expression in reactive astrocytes.
a, Biological (Bio) replicate tracks for RelA/p65 CUT&RUN in Fig. 4k. b, Enriched gene ontology terms for genes significantly upregulated in reactive astrocytes treated with RGFP. P-values generated by Benjamini-Hochberg false discovery rate. c, Enriched transcription factors targeting genes significantly upregulated in reactive astrocytes treated with RGFP. d, Biological replicate tracks for H3K27ac CUT&RUN in Fig. 4p.
Extended Data Fig. 7 In vivo pharmacology of RGFP966 and in vivo genetic validation of HDAC3 as a mediator of astrocyte reactivity.
a, Brain concentration of RGFP966 (RGFP) 4 hrs after treatment with vehicle (Veh) or 10 mg/kg RGFP. Data presented for n = 2 biological replicates (mice). Concentration of RGFP in brain from vehicle treated mice was below quantifiable levels (BQL). b–d, Representative images and quantification of immunohistochemistry for AcH4 in the cortex of mice treated with vehicle or 10 mg/kg RGFP and then exposed to systemic LPS injections to induce neuroinflammation. Scale bar is 100 µm. Data are mean ± s.e.m., n = 4 biological replicates (mice), p-value by unpaired two-tailed t-test e,f, Representative in situ hybridization images and quantification of untreated and LPS-exposed mice probed for the pan-reactive astrocyte marker Gfap (blue) and the reactive astrocyte marker Gbp2 (red) in the corpus callosum. Scale bar is 50 µm. Data are mean ± s.e.m., n = 4 biological replicates (mice), p-value by unpaired two-tailed t-test. g–m, Representative images and quantification of immunohistochemistry for GFAP (red) and IBA-1 (blue) in the cortex of mice treated with vehicle or 10 mg/kg RGFP and exposed to systemic LPS or saline vehicle. Scale bar is 100 µm. Data are mean ± s.e.m., n = 3 or 4 biological replicates (mice), p-value calculated by one-way ANOVA and Tukey multiple comparison correction. n, Diagram of astrocyte specific HDAC3 knockout mouse breeding. o–q, Representative in situ hybridization images and quantification of untreated wild-type (WT) and HDAC3 knockout (KO) mice and then probed for the pan-astrocyte marker Slc1a3 (green) and the reactive astrocyte marker C3 (red). Scale bar is 50 µm. Data are mean ± s.e.m., n = 3 biological replicates (mice), p-value by unpaired two-tailed t-test. r–u, Representative in situ hybridization images and quantification of wild-type and HDAC3 knockout (KO) mice exposed to systemic LPS and then probed for the pan-astrocyte marker Slc1a3 (green) and the reactive astrocyte marker C3 (red). Scale bar is 50 µm. Data are mean ± s.e.m., n = 4 biological replicates (mice), p-value by unpaired two-tailed t-test.
Extended Data Fig. 8 RGFP966 has no effect on generalized gliosis in the toxin-based injury model LPC.
a,b, Representative in situ hybridization images and quantification of naïve and LPC lesioned mice probed for the pan-astrocyte marker Slc1a3 (blue) and the reactive astrocyte marker C3 (red). Scale bar is 50 µm. Data are mean ± s.e.m., n = 3 or 4 biological replicates (mice), p-value by unpaired two-tailed t-test. c,d, Representative images and quantification of LPC lesions from vehicle or RGFP966 (RGFP) treated mice stained for IBA-1. Scale bar is 100 µm. Data are mean ± s.e.m., n = 4 biological replicates (mice). e–g, Representative images and quantification of LPC lesions from RGFP966 or vehicle treated mice stained for IBA-1 (orange), CD86 (blue) and CD206 (green). Scale bar is 100 µm. Data are mean ± s.e.m., n = 4 or 6 biological replicates (mice). h,i, Representative images, and quantification of LPC lesion from vehicle or RGFP treated mice stained for GFAP. Scale bar is 100 µm. Data are mean ± s.e.m., n = 4 biological replicates (mice).
Extended Data Fig. 9 RGFP decreases gene expression associated with reactive astrocytes in ONC.
a, Bulk RNA-seq volcano plot of genes up and downregulated in ONC retina versus naïve retina. log2(FC) and p-adj values were generated from bulk RNA-seq analysis with DESEQ2. b, Gene ontology terms for enriched for genes upregulated in ONC retina versus naïve retina. P-values generated by Benjamini-Hochberg false discovery rate. c, Tukey box and whisker plot depicting how the expression of genes upregulated in ONC retina change between crushed and naïve retina in mice treated with vehicle and mice treated with 10 mg/kg RGFP. Data are presented as log2(FC) for n = 7 biological replicates. P-value generated by a paired two-tailed t-test. d, Tukey box and whisker plot depicting the log2(FC) expression of ONC reactive astrocyte genes (same as in Fig. 5k) between naïve retina treated with 10 mg/kg RGFP and naïve retina treated with vehicle. Data are presented as log2(FC) for n = 7 biological replicates. P-value generated with a one-sample Wilcoxon signed ranked test comparing to a hypothetical median of log2(FC) = 0, which would designate no difference in expression. e,f, Representative images and quantification of retinal ganglion cells (RGCs) double stained with BRN3A (green) and beta-3 tubulin (red) in retina from naive mice treated with vehicle or 10 mg/kg RGFP966. Scale bar is 20 µm. Data are mean ± s.e.m., n = 9 biological replicates (mice), p-value by unpaired two-tailed t-test.
Supplementary information
Supplementary Table 1
Average expression of physiological and reactive astrocytes from scRNA-seq.
Supplementary Table 2
Differential gene expression by cluster in scRNA-seq integrated with publicly available data.
Supplementary Table 3
Gene ontology enrichment analysis.
Supplementary Table 4
log2(FC) for genes targeted by gained ATAC peak in reactive astrocytes.
Supplementary Table 5
Transcription factor motif analysis.
Supplementary Table 6
log2(FC) of gained, lost and shared SE targeted genes in reactive versus physiological astrocytes.
Supplementary Table 7
Primary chemical screen results.
Supplementary Table 8
log2(FC) for RelA/p65 target genes.
Supplementary Table 9
log2(FC) for ONC retina versus naïve retina.
Source data
Source Data Fig. 1
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Clayton, B.L.L., Kristell, J.D., Allan, K.C. et al. A phenotypic screening platform for identifying chemical modulators of astrocyte reactivity. Nat Neurosci 27, 656–665 (2024). https://doi.org/10.1038/s41593-024-01580-z
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DOI: https://doi.org/10.1038/s41593-024-01580-z
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