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Neurotoxic microglia promote TDP-43 proteinopathy in progranulin deficiency

Nature volume 588, pages 459–465 (2020)Cite this article

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Abstract

Aberrant aggregation of the RNA-binding protein TDP-43 in neurons is a hallmark of frontotemporal lobar degeneration caused by haploinsufficiency in the gene encoding progranulin1,2. However, the mechanism leading to TDP-43 proteinopathy remains unclear. Here we use single-nucleus RNA sequencing to show that progranulin deficiency promotes microglial transition from a homeostatic to a disease-specific state that causes endolysosomal dysfunction and neurodegeneration in mice. These defects persist even when Grn−/− microglia are cultured ex vivo. In addition, single-nucleus RNA sequencing reveals selective loss of excitatory neurons at disease end-stage, which is characterized by prominent nuclear and cytoplasmic TDP-43 granules and nuclear pore defects. Remarkably, conditioned media from Grn−/− microglia are sufficient to promote TDP-43 granule formation, nuclear pore defects and cell death in excitatory neurons via the complement activation pathway. Consistent with these results, deletion of the genes encoding C1qa and C3 mitigates microglial toxicity and rescues TDP-43 proteinopathy and neurodegeneration. These results uncover previously unappreciated contributions of chronic microglial toxicity to TDP-43 proteinopathy during neurodegeneration.

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Fig. 1: snRNA-seq reveals age-dependent microglial pathology and neuronal vulnerability in the thalamus of Grn−/− mice.
Fig. 2: TDP-43 proteinopathy and nuclear pore defects in Grn−/− thalamic neurons.
Fig. 3: Progranulin-deficient microglia promote TDP-43 proteinopathy in Grn−/− neurons.
Fig. 4: Complements C1q and C3b promote TDP-43 granule formation and neurodegeneration in Grn−/− mice.

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Data availability

The raw snRNA-seq and scRNA-seq data have been deposited to the Sequence Read Archive under accession no. PRJNA507872 and no. PRJNA614533, respectively. The data that support the findings of this study are included in the manuscript. Source data are provided for Figs. 1–4 and Extended Data Figs. 1–11.

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Acknowledgements

This work has been supported by grants from the US National Institutes of Health (R01 AA027074 to E.J.H. and A.R.K., R01 AG057462 to E.J.H. and J.D., R01 AG068290 to E.J.H., U01 MH105989 to A.R.K. and E.J.H., K99 MH121534 to D.V., K99 GM126136 to X.S., R01 GM124334 to B.H., R01 NS107480 to T.W. and S10 RR026758 to T.W.), the Department of Veterans Affairs (I01 BX002978 to E.J.H.), The Bluefield Project to Cure FTD (to W.W.S., B.L.M., T.C.W., R.V.F. and E.J.H.), NSF Graduate Research Fellowship (to M.K.C.), AHA Predoctoral Fellowship 19PRE3480616 and UCSF Discovery Fellowship (to J.C.), Banting Postdoctoral Fellowship from the Government of Canada 201409BPF-335868 (to A.M.L.), the Glenn Foundation and the Cure Alzheimer’s Fund (to S.A.L.), and the Japan Society for the Promotion of Science and Ochanomizu University Scholarship (to K.H.). T.C.W. and J.P.T. are Howard Hughes Medical Institute (HHMI) Investigators, and B.H. is a Chan Zuckerberg Biohub Investigator. S.A.L. thanks anonymous donors for their support. We thank I. Hsieh for IEM, Y. Chen for mouse husbandry and histopathology, UCSF Nikon Imaging Center for 3D structured illumination microscopy, A. Alvarez-Buylla for many helpful advice, and L. Mitic and R. Pearlman for their support.

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Author notes

  1. These authors contributed equally: Jiasheng Zhang, Dmitry Velmeshev, Kei Hashimoto, Yu-Hsin Huang

Authors and Affiliations

  1. Department of Pathology, University of California San Francisco, San Francisco, CA, USA

    Jiasheng Zhang, Kei Hashimoto, Yu-Hsin Huang, Jeffrey W. Hofmann, Jiapei Chen, Andrew M. Leidal, Julian G. Dishart, Jayanta Debnath & Eric J. Huang

  2. Pathology Service 113B, San Francisco VA Health Care System, San Francisco, CA, USA

    Jiasheng Zhang & Eric J. Huang

  3. Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco, San Francisco, CA, USA

    Dmitry Velmeshev & Arnold R. Kriegstein

  4. Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, USA

    Xiaoyu Shi & Bo Huang

  5. Department of Developmental and Cell Biology, University of California Irvine, Irvine, CA, USA

    Xiaoyu Shi

  6. Biomedical Sciences Graduate Program, University of California San Francisco, San Francisco, CA, USA

    Jiapei Chen, Jayanta Debnath, Torsten Wittmann, Arnold R. Kriegstein & Eric J. Huang

  7. Neuroscience Graduate Program, University of California San Francisco, San Francisco, CA, USA

    Michelle K. Cahill, Kevin W. Kelley, William W. Seeley, Arnold R. Kriegstein & Eric J. Huang

  8. Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA

    Michelle K. Cahill, Kevin W. Kelley, William W. Seeley & Eric J. Huang

  9. Neuroscience Institute, Department of Neuroscience & Physiology, NYU Langone Medical Center, New York, NY, USA

    Shane A. Liddelow

  10. Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA

    William W. Seeley & Bruce L. Miller

  11. Department of Genetics and Complex Diseases, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA

    Tobias C. Walther & Robert V. Farese Jr

  12. Howard Hughes Medical Institute, Boston, MA, USA

    Tobias C. Walther

  13. Department of Cell and Molecular Biology, St Jude Children’s Hospital & Howard Hughes Medical Institute, Memphis, TN, USA

    J. Paul Taylor

  14. Department of Ophthalmology, University of California San Francisco, San Francisco, CA, USA

    Erik M. Ullian

  15. Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA, USA

    Bo Huang

  16. Chan Zuckerberg Biohub, San Francisco, CA, USA

    Bo Huang

  17. Department of Cell and Tissue Biology, University of California San Francisco, San Francisco, CA, USA

    Torsten Wittmann

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  1. Jiasheng Zhang
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Contributions

J.Z., D.V., K.H., Y.-H.H., A.R.K. and E.J.H. conceived the project, designed the experiments and wrote the paper. D.V., J.Z. and K.H. performed single-cell transcriptomics and related work. D.V. performed the bioinformatics analyses. K.H. performed the NanoString nCounter work. J.Z., K.H., Y.-H.H., J.W.H., M.K.C., A.M.L. and J.G.D. performed in vitro cultures, immunohistochemistry and quantifications for cell death, TDP-43 granules and nuclear pore defects. J.Z. performed stereology-based quantifications. A.M.L., E.M.U. and J.D. provided expertise related to stress granule and endolysosomal phenotypes. K.W.K., W.W.S., B.L.M., T.C.W. and R.V.F. contributed expertise, reagents and analyses related to Grn mouse models. X.S., J.W.H., J.C. and B.H. provided assistance with 3D structured illumination microscopy. J.P.T. and T.W. provided reagents and assisted with mCherry–TDP-43 live imaging. S.A.L. provided expertise in glial gene expression. All authors reviewed and edited the manuscript.

Corresponding author

Correspondence to Eric J. Huang.

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Extended data figures and tables

Extended Data Fig. 1 snRNA-seq analysis of age-dependent transcriptomic changes in the thalamus of Grn−/− mice.

a, Unbiased clustering of snRNA-seq data from the thalamus of 2, 4, 7, 12 and 19 months old Grn+/+ and Grn−/− mice identify 16 different cell types. The table outlines the number and age of Grn+/+ and Grn−/− mice used for microdissecting thalamus for snRNA-seq. Two samples, #1 in 2 months old Grn+/+ and #4 in 19 months old Grn−/−, are excluded due to suboptimal RNA quality. b, c, Subtype-specific markers for microglia (P2ry12), astrocytes (Aqp4 and Gfap), oligodendroglial precursor cells (OPC) (Pdgfra), endothelial cells (Cldn5), synaptic marker (Syt1), excitatory neurons (Cux2 and Satb2), oligodendroglia (Plp1) and inhibitory neurons (Gad2, Sst and Reln). c, Individual contribution to different cell clusters from each sample. d, Venn diagram shows the overlap of gene expression between cluster 11 and astrocyte and oligodendroglia clusters. These results indicate that cluster 11 contains mixed identity. e, Violin plots demonstrate that cells in cluster 11 express markers of myelinating oligodendroglia (Mog, Mag, Mbp and Plp1) and astrocytes (Slc1a2, Gja1, Nfia and Gpc5). Although cells in cluster 11 express a low level of the neuronal marker Syt1, they express very low levels of other neuronal markers, for example, Rbfox3, Gad1 and Gad2. f, Violin plots that show the cumulative Grn mRNA expression from 2 to 19 months in microglia (MG, c4), astrocytes (AST, c7), excitatory neurons (ExNeu, c3, c12, c13), inhibitory neurons (InNeu, c6, c9) and endothelial cells (END, c8). Statistical comparisons using MAST reveal that Grn mRNA expression MG is consistently higher than other cell clusters with the following P values: MG vs AST: 2.53 × 10−40, MG vs ExNeu: 1.15 × 10−8, MG vs InNeu: 8.79 × 10−17 and MG vs END: 1.45 × 10−17. In addition, comparisons between ExNeu and other cell clusters show the following P values: ExNeu vs AST: 8.46 × 10−75, ExNeu vs InNeu: 5.57 × 10−13 and ExNeu vs END: 1.38 × 10−09. g, h, Normalized cell counts for inhibitory neurons (c6, c9) and astrocytes (c7) in the Grn+/+ and Grn−/− thalamus. Data represent mean ± s.e.m. Statistics use two-tailed, unpaired Student’s t-test. i, Gene burden analysis for glia and neuronal clusters in Grn+/+ and Grn−/− thalamus at 12 months old. These analyses calculate the number of genes differentially expressed in each cluster in the Grn−/− thalamus after normalizing the number of nuclei in each cluster. Box plots show the median and 25-75th percentiles. Statistics were performed using Mann–Whitney U-test.

Extended Data Fig. 2 Age-dependent changes in the transcriptomes and subclustering of microglia in the Grn+/+ and Grn−/− thalamus.

a, Heatmap of differentially expressed genes in Grn−/− thalamic microglia show progressive transcriptomic changes from 7, 12 to 19 months. b, c, Pseudotime analyses of snRNA-seq data reveal modest transition of trajectory and subclusters in Grn+/+ thalamic microglia from 2 to 19 months. By contrast, Grn−/− microglia exhibit drastic changes in trajectory and subcluster distribution, especially at 12 and 19 months. The small clusters towards the right of UMAP graphs in Grn+/+ and Grn−/− Th-MG most likely represent a small number of microglia-related cells, such as macrophages, or other unidentified cell types. The presence of this very small cluster does not contribute to the pseudotime results for Grn+/+ or Grn−/− Th-MG. d, e, Combined pseudotime analyses show age-dependent downregulation of homeostasis genes, P2ry12 and Tmem119, and upregulation of genes associated with microglial activation, including Apoe and Ctsb, in Grn−/− microglia. f, Volcano plot showing persistent upregulated or downregulated genes in Grn−/− microglia from 7 to 19 months. Most differentially expressed genes (DEGs) in Grn−/− microglia are detected at 7 and 19 months (dark red), 12 and 19 months (light blue), or 7, 12 and 19 months (beige), whereas a smaller number of DEGs are detected only in 7 months (green), 12 months (red) or 19 months (dark blue). Statistics for DEGs in the volcano plot use MAST. See Methods for details of the “Meta Cell” pseudobulk approach to generate the volcano plot. g, Venn diagram showing a progressive increase in DEGs in Grn−/− Th-MG from 7, 12 to 19 months. h, Venn diagrams showing limited overlap of DEGs in 19 months Grn−/− Th-MG and AD DAM genes, and 19 months Grn−/− Th-MG and ALS DAM genes. Statistics use hypergeometric test. i, Metascape interacting map of GO terms of the 32 genes shared by 19 months Grn−/− Th-MG and AD DAM.

Extended Data Fig. 3 Immunohistochemical validations of DEGs in the thalamus of Grn−/− mice.

a, b, Validations using immunohistochemistry and confocal microscopy confirm the downregulation of P2Y12 and Tmem119 in Grn−/− thalamic microglia at 12 and 19 months, respectively (panel a). By contrast, Grn−/− thalamic microglia show marked increases in ApoE and Adam33 protein detected by immunohistochemical staining and confocal microscopy (panel b). Insets are high magnification images from the boxed areas in the ventral thalamus. Confocal images on the right panels are obtained from 12 months old Grn+/+ and Grn−/− thalamus. Immunohistochemistry was performed in 3 independent mice per genotype, whereas the confocal images were from two independent mice. c, Confocal images showing upregulated expression of Cathepsin B, IGF-1 and GPNMB in 12 months old Grn−/− thalamic microglia. By contrast, Grn−/− thalamic microglia show reduced expression of Numb. The validations were performed in N = 3 independent mice per genotype with similar results. d, A proposed model showing the age-dependent transition of Grn−/− thalamic microglia from a homeostatic state to disease state from 7 to 19 months. The defects in Grn−/− microglia downregulate homeostatic genes (C1qa, C1qb, Mef2c, Csf1r, Cx3cr1, Tgfbr1, Tmem119, Adam33, Igf1 and P2ry12), and upregulate genes related to lysosomal functions (Ctsb), lipid transport (Apoe), intracellular trafficking (Myo1f, Myo5a and Numb) and signal pathways (Arhgap24 and Dock3).

Extended Data Fig. 4 snRNA-seq analysis of excitatory neuron clusters in the thalamus of Grn+/+ and Grn−/− mice.

a–c, snRNA-seq identifies three distinct clusters of excitatory neurons based on the combined expression of Ttr (Transthyretin), Pde4d (Phosphodiesterase 4D) and Cntnap2 (Contactin associated protein like 2) in cluster 3, Prkcd (Protein kinase C Delta), Shisa6 (Shisa family member 6) and Plekhg1 (Pleckstrin homology and RhoGEF domain containing G1) in cluster 12, and Cntn5 (Contactin 5), Foxp2 (Forkhead Box P2) and Nxph1 (Neurexophilin 1) in cluster 13. d, Heatmaps of cluster 3 and cluster 13 show no definitive age-dependent changes in the transcriptomes. e, Comparison of excitatory neuron subtypes in 19 months old Grn+/+ and Grn−/− thalamus using immunohistochemical stains for PKCδ (upper panels) and Foxp2 (lower panels) reveals loss of PKCδ+ and Foxp2+ neurons, most prominently affecting neurons in the ventral posterolateral (VPL) and ventral posteromedial (VPM) nuclei of the thalamus. f, Stereology quantification of PKCδ+ and Foxp2+ neurons in the ventral thalamus of Grn+/+ and Grn−/− mice at 7, 12 and 19 months old. Data represent mean ± s.e.m., and the number of mice for each age and genotype is indicated at the bottom of each data set. Statistics uses two-tailed, unpaired Student’s t-test. ns, not significant.

Extended Data Fig. 5 Characterization of P3 primary microglia from Grn+/+ and Grn−/− mice using scRNA-seq, NanoString nCounter neuroinflammation panel and western blots.

a, A schematic diagram illustrating the study design to characterize primary microglia from postnatal day 3 (P3) Grn+/+ and Grn−/− mice using scRNA-seq and NanoString nCounter neuroinflammation panel, and to prepare serum-free conditioned media from Grn+/+ and Grn−/− P3-MG. In parallel, primary cortical neurons and GABAergic inhibitory neurons are isolated from the developing cortex and ganglionic eminences of embryonic day 15.5 (E15.5) Grn+/+ and Grn−/− mice. After 14 days in vitro (DIV), Grn+/+ and Grn−/− microglial conditioned media (MCM) are added to Grn+/+ and Grn−/− excitatory neurons or GABAergic inhibitory neurons and incubate for 24 h. b, t-SNE plots of scRNA-seq data from Grn+/+ and Grn−/− P3-MG revealed 4 distinct clusters and the extent of overlapping in cell density and cluster distribution between Grn+/+ and Grn−/− P3-MG. c, Comparison of cluster A of P3-MG with 2 to 19 months (mo) thalamic microglia (Th-MG) reveals more overlapping between P3-MG (black) and 19 mo Th-MG (red). d, Hierarchical clustering of gene expression in Grn+/+ and Grn−/− P3-MG cluster A and 19 months old Th-MG. e, Venn diagrams showing the extent of overlapping between DEGs from 12 and 19 months old Th-MG and DEGs in P3-MG identified by scRNA-seq (upper panel) or DEGs in P3-MG identified by NanoString nCounter Neuroinflammation panel (lower panel). Statistics use the hypergeometric test. f, Volcano plot showing the upregulated and downregulated genes in Grn−/− P3-MG revealed by nCounter neuroinflammation panel. Statistics use nSolver software version 4.0, provided by the NanoString Technologies, Inc. g, Quantification of the DEGs in Grn−/− P3-MG that are shared with 19 months Grn−/− Th-MG, including upregulation of Arhgap24 and Cables1, and downregulation of Chn2, Plxdc2, C1qa, Mef2c, Csf1r, Cx3cr1, Tgfbr1, Il6ra, Lair1 and Slco2b1. Data represent mean ± s.e.m., n = 4 for each genotype. Statistics uses two-tailed, unpaired Student’s t-test. h, Western blots and quantification show upregulation of cathepsin B, myosin Va, Adam33 and ATG7, but downregulation of Mef2c and Numb. Data represent mean ± s.e.m., n = 3 for each protein. Statistics uses two-tailed, unpaired Student’s t-test.

Extended Data Fig. 6 Grn−/− MCM-induced cell death in Grn+/+ and Grn−/− cortical neurons and GABAergic neurons.

a, Representative confocal images of Grn+/+ and Grn−/− cortical neurons treated with control media, Grn+/+ MCM or Grn−/− MCM (100 μg/ml) overnight. Immunofluorescent stains are performed using antibodies for MAP2 (green) and cleaved caspase 3 (red). Nuclei are highlighted using DAPI. b, Representative confocal microscopic images of GE-derived Grn+/+ and Grn−/− GABAergic interneurons treated with control media, Grn+/+ MCM or Grn−/− MCM (100 μg/ml) overnight. Immunofluorescent stains are performed using antibodies for GAD67 (green) and cleaved caspase 3 (red). Nuclei are highlighted using DAPI.

Extended Data Fig. 7 Nuclear pore defects in Grn−/−neurons treated with Grn−/− MCM.

a, 3D structured illumination microscopy (SIM) images of Nup98 and LMN A/B in Grn+/+ and Grn−/− cortical neurons treated with control media, Grn+/+ MCM and Grn−/− MCM (250 μg/ml). Nup98 is shown in red, Lamin A/B in green and MAP2 in blue. b, Nup98 intensity distribution per intranuclear grid (0.44 × 0.44 μm2) in Grn+/+ and Grn−/− cortical neurons treated with control media and Grn−/− MCM (250 μg/ml) (see Methods for specific algorithms). Nup98 is less evenly distributed in Grn−/− cortical neurons in control media. When Grn+/+ neurons are treated with Grn−/− MCM, they show significant uneven distribution of Nup98 compared to Grn+/+ neurons treated with control media. Interestingly, Grn−/− neurons treated with Grn−/− MCM do not show further defects in Nup98 distribution compared to Grn−/− in control media. Data represent mean ± s.e.m. from 3 independent cultures. Statistics use two-way ANOVA. c, Average of Nup98 intensity in the small grids in Grn+/+ and Grn−/− cortical neurons treated with control media, Grn+/+ MCM and Grn−/− MCM (250 μg/ml). Data represent mean ± s.e.m. The numbers listed below each data set represent the number of neurons analysed from 3 independent cultures. Statistics uses two-tailed, unpaired Student’s t-test.

Extended Data Fig. 8 Overlap between TDP-43 granules in Grn+/+ and Grn−/− neurons with lysosomal marker LAMP1, but not with the mitochondrial marker Tom20 and the stress granule marker ataxin-2.

a–c, Confocal images of TDP-43 granules and LAMP1+ lysosomes (a), Tom20+ mitochondria (b), or ataxin-2+ stress granules (c) in Grn+/+ and Grn−/− cortical neurons treated with control media, Grn+/+ MCM and Grn−/− MCM (250 μg/ml). TDP-43 is shown in red and LAMP1, Tom20 and ataxin-2 in green. Intensity plots shown below confocal images are performed using the Nikon Intensity Profile System. Images were collected in the cytoplasm and dendrites. d, Immunogold electron microscopic images of TDP-43 granules in Grn+/+ and Grn−/− neurons treated with control media, Grn+/+ MCM or Grn−/− MCM (250 μg/ml). The inset in the right lower panel shows a small spherical structure, which probably represent a cross-section of dendrite that contains many lysosomes with TDP-43 granules attached.

Extended Data Fig. 9 Sodium arsenite-induced TDP-43 granules in Grn+/+ and Grn−/− cortical neurons do not colocalize with G3BP1+ stress granules.

a, Sodium arsenite treatment (10 μM, 1 h) induces prominent TDP-43 granules (red) and G3BP1+ granules (green) in Grn+/+ and Grn−/− cortical neurons. However, the TDP-43 granules and G3BP1+ granules show no evidence of colocalization in these neurons. b, Quantification using NIH ImageJ shows that the majority of TDP-43 granules are smaller than 0.05 μm2. In contrast to Grn−/− MCM treatment, sodium arsenite induces similar TDP-43 granule formation in Grn+/+ and Grn−/− cortical neurons. Images in panel a and quantification in panel b were obtained from four independent cultures. Data represent mean ± s.e.m. Statistics use two-way ANOVA with multiple comparisons. c, Immunogold electron microscopy (IEM) reveals that TDP-43 granules induced by sodium arsenite (500 μM) have morphology similar to those in Grn−/− thalamic neurons (Fig. 2d) and Grn−/− cortical neurons treated with Grn−/− MCM (Extended Data Fig. 8d). At least 8 IEM images were analysed from 2 independent cultures per condition. d, Grn+/+ and Grn−/− cortical neurons are equally vulnerable to sodium arsenite treatment (10 μM, 1 h). Data represent mean ± s.e.m. N indicates the number of independent cultures. Statistics use two-tailed, unpaired Student’s t-test. ns, not significant.

Extended Data Fig. 10 C1q and C3b produced by Grn−/− microglia promote TDP-43 granule formation and cell death in Grn−/− neurons.

a, Immunohistochemical images of Grn+/+, Grn−/− and Grn−/−;C1qa−/−;C3−/− mice at 7 months show the upregulation of C1q and C3b in the ventral thalamus of Grn−/− mice. No C1q or C3b staining is detected in Grn−/−;C1q−/−;C3−/− mouse brain, confirming the specificity of these antibodies. Insets in Grn−/− panels represent higher magnification of the boxed regions in the ventral thalamus. Results were analysed in 3 mice per genotype. b, ELISA assays for C1q and C3b show increases of both proteins in Grn−/− MCM, but no C1q or C3b is detected in Grn−/−;C1qa−/−;C3−/− MCM. Data represent mean ± s.e.m. from 8 independent microglial cultures for Grn+/+ and Grn−/− MCM, and 3 independent cultures from Grn−/−;C1qa−/−;C3−/− MCM. Statistics use two-tailed, unpaired Student’s t-test. c, Confocal images of cultured Grn+/+ and Grn−/− cortical neurons treated with purified human C1q (1 μg/ml) or C1q+C3b (1 μg/ml, each) indicate that complements are sufficient to promote the formation of TDP-43 granules in Grn+/+ and Grn−/− cortical neurons, whereas Grn−/−;C1qa−/−;C3−/− MCM fail to induce TDP-43 granule formation. d, Quantification of cytoplasmic TDP-43 intensity (upper panel) and cell death (lower panel) in Grn+/+ and Grn−/− neurons treated with C1q, C1q+C3b and C4. N in the upper panel and the lower panel indicates the number of independent cultures analysed. On average, 6-8 images were obtained from each culture. Statistics use two-tailed, unpaired Student’s t-test. e, Quantification of cytoplasmic TDP-43 intensity (upper panel) and cell death (lower panel) in Grn+/+ and Grn−/− neurons treated with control media, Grn−/− MCM, Grn−/−;C1qa−/− MCM or Grn−/−;C1qa−/−;C3−/− MCM. Data represent mean ± s.e.m. Statistics use two-tailed, unpaired Student’s t-test. ns, not significant. N in the upper panel and the lower panel indicates the number of independent cultures analysed. On average, 6-8 images were obtained from each culture. f, Quantification of cell death of Grn+/+ and Grn−/− neurons treated with Grn−/− MCM (250 μg/ml) and two different concentrations of vitronectin (50 or 500 ng/ml), an inhibitor of the complement membrane attack complex. Data represent mean ± s.e.m. Statistics uses two-tailed, unpaired Student’s t-test. ns, not significant. Data are obtained from 3 independent cultures.

Extended Data Fig. 11 Proposed model for the neurotoxic properties of Grn−/− microglia in promoting neurodegeneration in Grn−/− neurons.

Grn−/− microglia show progressive transcriptomic changes from 7 to 12 months old. Based on gene burden analysis from snRNA-seq data, Grn−/− microglia is the first cell cluster in the thalamus to show significant transcriptomic changes at 12 months. By 19 months, Grn−/− microglia exhibit much more profound changes in their transcriptomes, affecting the expression of genes implicated in plasma membrane bounded cell projection, exocytosis, phagocytosis, protein complex assembly, ion homeostasis/transport, MAPK cascade and receptor tyrosine kinase signalling. Consistent with the snRNA-seq results, immunohistochemistry and in vitro cultures show that Grn−/− microglia show marked reduction in proteins required for homeostasis, including Tmem119 and P2Y12, but have elevated expression of lysosomal and pro-inflammatory proteins, including Cathepsin B, ApoE, Adam33 and many others. Our results suggest that the lysosomal defects in Grn−/− microglia may facilitate the production of complements, C1q and C3b, which promote the accumulation of nuclear and cytoplasmic TDP-43 granules, nuclear pore defects, and ultimately cell death in Grn−/− neurons. Interestingly, while purified human C1q and C3b can promote TDP-43 granule formation and cell death in Grn−/− neurons, these effects are less robust than in Grn−/− MCM. These results suggest that Grn−/− microglia may produce other unknown factors to facilitate neurodegeneration in Grn−/− neurons. This model does not exclude the possibility that complements C1q and C3b may have cell-autonomous effects to activate Grn−/− microglia.

Supplementary information

Supplementary Figure 1

Uncropped images for western blots of Cathepsin B, Myosin Va, Adam33, ATG7, Mef2c, Numb and GAPDH in Grn+/+ and Grn-/- P3 microglia. Uncropped images of western blots for several key up- or down-regulated genes in Grn-/- P3 microglia (P3-MG) presented in Extended Data Figure 5h. Each image contains 6 samples, including 3 from Grn+/+ P3-MG (left three lanes) and 3 from Grn-/- P3-MG (right three lanes). Each sample contains pools of primary microglia from two or more P3 mice, and therefore is considered as a biological replicate. Samples in different lanes are from different pools of microglia. The predicted molecular weight for each protein is presented on top of each panel, and the corresponding position of each protein on the western blot is indicated with an arrow.

Reporting Summary

Supplementary Table 1

Meta data for samples and cells in single-nucleus RNA-sequencing (snRNA-seq). This table contains information regarding the samples, the number of nuclei, and the number of reads from the snRNA-seq.

Supplementary Table 2

Pseudotime analyses of subclusters and subcluster-specific differentially expressed genes in Grn+/+ and Grn-/- thalamic microglia. This table contains information regarding the pseudotime trajectory analyses of Grn+/+ and Grn-/- thalamic microglia (Th-MG) using version 3 of Monocle R package. Supplementary Table 2A includes unique gene sets used to identify different subclusters in Grn+/+ and Grn-/- thalamic microglia (Th-MG). Supplementary Tables 2B and 2C contain the pseudotime trajectory analyses of the differentially expressed genes in each subcluster in Grn+/+ and Grn-/- Th-MG, respectively. Statistics in 2B and 2C were performed using Moran’s I test.

Supplementary Table 3

Age-specific differentially expressed genes in Grn+/+ and Grn-/- thalamic microglia at 7, 12 and 19 months. This table contains the lists of differentially expressed genes (DEGs) in Grn-/- Th-MG at 7 months (Table 3A), 12 months (Table 3B) and 19 months (Table 3C). DEGs were analyzed using two different approaches. The first approach uses MAST and the second approach uses pseudobulk to generate DEGs. Detailed methods and statistics are provided in METHODS.

Supplementary Video 1

Time-lapse imaging of nuclear mCherry-TDP-43 in Grn+/+ neurons treated with control media. Grn+/+ cortical neurons from E15.5 embryos were transfected with pcDNA-mCherry-FLAG-TDP-43 plasmid. At 18 hours after the transfection, control media (250μg/ml) was added to the neurons and time-laps images of nuclear m-Cherry-TDP-43 were captured for 14 hours at 10 minutes-intervals. Time-lapse sequences were acquired on a Yokogawa CSU-X1 spinning disk confocal microscope system with a Nikon 60x N.A. 1.49 objective and a Photometrics BSI Prime back-thinned sCMOS camera. A total of 15 Grn+/+ neurons treated with control media were imaged with similar results.

Supplementary Video 2

Time-lapse imaging of nuclear mCherry-TDP-43 in Grn+/+ neuron treated with Grn-/- MCM. Grn+/+ cortical neurons were transfected with pcDNA-mCherry-FLAG-TDP-43 plasmid. At 18 hours after the transfection, Grn-/- MCM (250μg/ml) was added to the neurons and time-laps images of nuclear m-Cherry-TDP-43 were captured for 14 hours at 10 minutes-intervals. Four of 16 Grn+/+ neurons treated with Grn-/- MCM exhibited >3 folds increase in nuclear mCherry-TDP-43 signal at the end of recording compared with time 0’. Collectively, Grn+/+ neurons treated with Grn-/- MCM exhibited a modest, but not statistically significant, increase in nuclear m-Cherry-TDP-43 signals.

Supplementary Video 3

Time-lapse imaging of nuclear mCherry-TDP-43 in Grn-/- neuron treated with control media. Grn-/- cortical neurons were transfected with pcDNA-mCherry-FLAG-TDP-43 plasmid. At 18 hours after the transfection, control media (250μg/ml) was added to the neurons and time-laps images of nuclear m-Cherry-TDP-43 were captured for 14 hours at 10 minutes-intervals. A total of 11 Grn-/- neurons treated with control media were recorded.

Supplementary Video 4

Time-lapse imaging of nuclear mCherry-TDP-43 in Grn-/- neuron treated with Grn-/- MCM. Grn-/- cortical neurons were transfected with pcDNA-mCherry-FLAG-TDP-43 plasmid. At 18 hours after the transfection, Grn-/- MCM (250μg/ml) was added to the neurons and time-laps images of nuclear m-Cherry-TDP-43 were captured for 14 hours at 10 minutes-intervals. Five of 17 Grn-/- neurons treated with Grn-/- MCM exhibited >5 folds increase, whereas 12 showed variable increases in nuclear m-Cherry-TDP-43 signals at the end of recording compared with time 0’. Overall, Grn-/- neurons treated with Grn-/- MCM exhibited significantly higher nuclear mCherry-TDP-43 signals.

Supplementary Video 5

Time-lapse imaging of nuclear and cytoplasmic mCherry-TDP-43 in Grn-/- neuron treated with Grn-/- MCM. Of the 17 Grn-/- cortical neurons treated with transfected with Grn-/- MCM, 5 showed extension of mCherry-TDP43 from the nucleus into the cytoplasm. Supplementary Video 5 represents one of such Grn-/- cortical neurons. Several of Grn-/- neurons with extension of nuclear mCherry-TDP-43 into the cytoplasm eventually died at or near the end of recording.

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Zhang, J., Velmeshev, D., Hashimoto, K. et al. Neurotoxic microglia promote TDP-43 proteinopathy in progranulin deficiency. Nature 588, 459–465 (2020). https://doi.org/10.1038/s41586-020-2709-7

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