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Integrative in situ mapping of single-cell transcriptional states and tissue histopathology in a mouse model of Alzheimer’s disease

Nature Neuroscience volume 26, pages 430–446 (2023)Cite this article

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Abstract

Complex diseases are characterized by spatiotemporal cellular and molecular changes that may be difficult to comprehensively capture. However, understanding the spatiotemporal dynamics underlying pathology can shed light on disease mechanisms and progression. Here we introduce STARmap PLUS, a method that combines high-resolution spatial transcriptomics with protein detection in the same tissue section. As proof of principle, we analyze brain tissues of a mouse model of Alzheimer’s disease at 8 and 13 months of age. Our approach provides a comprehensive cellular map of disease progression. It reveals a core–shell structure where disease-associated microglia (DAM) closely contact amyloid-β plaques, whereas disease-associated astrocyte-like (DAA-like) cells and oligodendrocyte precursor cells (OPCs) are enriched in the outer shells surrounding the plaque-DAM complex. Hyperphosphorylated tau emerges mainly in excitatory neurons in the CA1 region and correlates with the local enrichment of oligodendrocyte subtypes. The STARmap PLUS method bridges single-cell gene expression profiles with tissue histopathology at subcellular resolution, providing a tool to pinpoint the molecular and cellular changes underlying pathology.

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Fig. 1: Simultaneous mapping of cell types, single-cell transcriptional states and tissue histopathology by STARmap PLUS.
Fig. 2: Top-level cell type classification and spatial analysis in the brain slices of TauPS2APP and control mice.
Fig. 3: Spatiotemporal gene expression analysis of microglia in TauPS2APP and control samples.
Fig. 4: Spatiotemporal gene expression analysis of astrocytes in TauPS2APP and control samples.
Fig. 5: Spatiotemporal gene expression analysis of oligodendrocyte lineage cells in TauPS2APP and control samples.
Fig. 6: Spatiotemporal gene expression analysis of neurons in TauPS2APP and control samples.
Fig. 7: Integrative spatiotemporal analysis of disease-associated cell types and gene programs.

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Data availability

The STARmap PLUS sequencing data are available on Single-Cell Portal at https://singlecell.broadinstitute.org/single_cell/study/SCP1375 and Zenodo at https://doi.org/10.5281/zenodo.7332091. Source data are provided with this paper.

Code availability

All code and analysis are available on GitHub at https://github.com/wanglab-broad/mAD-analysis and at https://doi.org/10.5281/zenodo.7458952.

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Acknowledgements

We thank H. Shi (Broad Institute), M. Pan (Broad Institute), Q. Li (Harvard University), Z. Lin (Harvard University) and S. Wade (Broad Institute) for technical assistance, H. Xu (Peking University), Y. Zhang (Harvard University) and H. Meng (Peking University) for helpful discussions and thoughtful comments on the manuscript. X.W. acknowledges the support from the Searle Scholars Program, Thomas D. and Virginia W. Cabot Professorship, E. Scolnick Professorship, Ono Pharma Breakthrough Science Initiative Award, Merkin Institute Fellowship, Stanley Center for Psychiatric Research and NIH Director’s New Innovator Award (DP2, 1DP2GM146245-01).

Author information

Author notes

  1. These authors contributed equally: Hu Zeng, Jiahao Huang, Haowen Zhou.

Authors and Affiliations

  1. Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Hu Zeng, Jiahao Huang, Haowen Zhou, Borislav Dejanovic, Yiming Zhou, Jingyi Ren, Zefang Tang, Morgan Sheng & Xiao Wang

  2. Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA

    Hu Zeng, Jiahao Huang, Yiming Zhou, Jingyi Ren, Albert Liu, Zefang Tang & Xiao Wang

  3. Department of Neuroscience, Genentech, Inc., South San Francisco, CA, USA

    William J. Meilandt, Christopher J. Bohlen & Seung-Hye Lee

  4. Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Borislav Dejanovic, Morgan Sheng & Xiao Wang

  5. John A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, MA, USA

    Hao Sheng & Jia Liu

  6. Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA

    Morgan Sheng

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Contributions

H.Z. and J.R. optimized STARmap PLUS probe design. H.Z. and Y.Z. performed STARmap PLUS experiments. J.H. and H.Z. performed computational analyses. W.L.M. prepared animal samples. H.Z., J.H., H.Z. and X.W. analyzed and interpreted the data with the inputs from W.J.M., B.D., C.J.B., S.-H.L., A.L., Z.T., H.S., J.L. and M.S. All authors contributed to writing and revising the manuscript and approved the final version. X.W. and M.S. conceptualized and supervised the project.

Corresponding authors

Correspondence to Morgan Sheng or Xiao Wang.

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Competing interests

X.W., H.Z. and J.R. are inventors on pending patent applications related to STARmap PLUS. X.W. is a scientific cofounder of Stellaromics. M.S. is a scientific cofounder of Neumora and a former employee of Genentech. W.J.M., C. J. B. and S.-H.L. are present employees of Genentech. All the other authors declare no competing interests.

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Nature Neuroscience thanks Je Lee and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Development of the STARmap PLUS method.

a, Flow chart of STARmap PLUS procedure where p-tau primary antibody staining was performed after mRNA in situ hybridization and amplification. The imaging results showed strong signals from both cDNA amplicons and proteins (N = 2 independent experiments). b, Alternative procedure where the p-tau primary antibody staining was conducted before mRNA in situ hybridization and amplification. The imaging results showed a much weaker signal from cDNA amplicons, suggesting RNA degradation during antibody incubation and washing steps (N = 2 independent experiments). PI staining, propidium iodide staining of cell nuclei. c, Schematic diagram of the experimental design to test if the tissue retains the same structure after STARmap PLUS. d, The imaging result before STARmap PLUS (left), after STARmap PLUS (middle), and overlay (right) of p-tau and Aβ-plaque signals were recorded (N = 2 independent experiments). e, Summary of the detection efficiency of RCA-based spatial transcriptomics methods. The efficiency of FISSEQ and padlock based in situ sequencing was extracted from Lein et al. 41, and the efficiency of BOLORAMIS was extracted from Liu et al. 37. f,g, The ACTB mRNA signal detected by STARmap PLUS (f) and BOLORAMIS37 (g) in Hela cells. h, Quantification of the number of DNA amplicons per cell identified by STARmap PLUS and BOLORAMIS. Error bars, standard deviation. Data are presented as mean ± s.e.m, n = 5 images per condition. Two-sided Student’s t-test, ****P = 1.39×10-6.

Source data

Extended Data Fig. 2 Data processing and quality control of the STARmap PLUS data analysis pipeline.

a, Examples showing the final imaging cycle detecting cell nuclei, cDNA amplicons, and protein signals in the 13-month control (left, N = 2 independent animals) and TauPS2APP (right, N = 2 independent animals) mouse brain samples. Blue, Propidium Iodide (PI) staining of cell nuclei. Green, fluorescent DNA probe staining of all cDNA amplicons. White, X-34 staining of Amyloid β plaque. Red, immunofluorescent staining of p-tau (AT8 primary antibody followed by fluorescent goat anti-mouse secondary antibody). b, The flowchart of the STARmap PLUS data analysis pipeline. c, Violin plot showing the accuracy (correct rate) of SEDAL sequencing for each FOV for all samples (96.87% ± 5.00%). d, Histograms showing the ln-transformed number of transcripts (left) and genes (right) per cell in the 2,766-genes dataset before quality control. Red vertical lines represent median values. e, Histogram showing the number of transcripts after logarithmic transformation in the 2,766-genes dataset. Red vertical lines represent the filtering thresholds estimated by median absolute deviation (MAD). f, Number of transcripts and genes across samples. Violin plots showing the distribution of the number of reads per cell (top) and genes per cell (bottom) detected in each sample after quality control (N = 72,165 cells). Box plots depict the median (center) and interquartile range (IQR, bounds of the box), with whiskers extending to either the maxima/minima or to the median ± 1.5× IQR, whichever is nearest. g, Number of transcripts and genes across major cell types. Violin plots showing the distribution of the number of reads per cell (top) and genes per cell (bottom) detected in each major cell type (N = 72,165 cells). Box plots as in (f).

Source data

Extended Data Fig. 3 Classification and spatial distribution of major cell types.

a, Dot plot showing the expression level of top five representative gene markers of each major cell type. b, Matrix plot showing the averaged expression level of canonical gene markers for each glial cell type of the 2,766-genes dataset. Values are normalized for each gene. c, Barplot showing the number of cells per cluster in Control and TauPS2APP mice. Data are represented as mean with 95% CI. Asterisks denote significant differences between Control and TauPS2APP (n = 4 samples per condition, two-sided *P < 0.05, t-test for two independent samples). d, Spatial atlas of top-level cell types in cortex and hippocampus regions of eight samples in the 2,766-gene dataset. Scale bars, 100 µm. e, Representative spatial distribution of cell-type compositions around Aβ plaque for TauPS2APP eight-month samples in both cortex and hippocampus. Stacked bar plot showing the density of each major cell type at different distance intervals to the Aβ plaque. The cell density of each major cell type in each area was included as the reference for comparison (overall). Asterisks denote significantly enriched cell types in each distance interval. One-sided one-sample t-Test, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001 vs. overall cell density. f, Cell-type composition around Aβ plaque at different distance intervals in both eight- and 13-month samples of the 2,766-gene dataset. Stacked bar plot showing the averaged density of major cell types in the cortex and hippocampus from different distance intervals around the Aβ plaque. The overall cell density of each cell type in each region was included as the reference for comparison (overall). Asterisks denote significantly enriched cell types in each distance interval. One-sided one-sample t-test, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001 vs. overall cell density.

Source data

Extended Data Fig. 4 Additional gene expression and spatial analysis of microglia.

a, UMAP showing three subclusters of 3,732 microglia cells across different samples. b, Diffusion maps showing the subpopulation identified by predicted labels generated by the CCA integration with the astrocyte population from Mathys et al12. Cells labeled as Mic0 and Mic1 from Mathys et al. were plotted separately for comparison. c, Heatmap showing the proportions (color bar, scaled per column) of microglia cluster IDs from Mathys et al12. (rows) mapped to STARmap PLUS microglia subpopulations (columns). Cells were excluded if their label prediction score were less than 0.5. d, Spatial map of microglia subtypes in control and TauPS2APP samples. Scale bars, 100 µm. e, Cell-type composition around Aβ plaque in different distance intervals for the TauPS2APP samples at eight months. Stacked bar plot showing the density of each microglia subpopulation in each distance interval around the Aβ plaque. Asterisks denote significantly enriched microglia subtypes in each distance interval. One-sided one-sample t-test, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001 vs. overall cell density. f, Volcano plots showing the differentially expressed genes (DEG) of microglia in TauPS2APP and control comparisons at eight- and 13-month time point (y-axis: -log adjusted p-value, x-axis: average log fold change). The two-sided Wilcoxon rank-sum test. Genes (p-value < 0.05, absolute value of lnFC > 0.1) are marked in red (up-regulated) or blue (down-regulated). g, Matrix plot showing the z-scores of SDEGs of microglia across multiple distance intervals from plaques. h, Gene ontology enrichment analysis (Fisher’s one-sided test) results of DEGs in microglia of the 13-month TauPS2APP samples. i, Barplots showing the DEG enrichment significance (the Chi squared test) of co-expression modules of microglia identified by scWGCNA. The gene module with the most significant DEG enrichment (MM1) is highlighted. j, Matrix plot showing the averaged z-score value of microglia gene modules across multiple distance intervals.

Source data

Extended Data Fig. 5 Identification of disease-associated astrocyte populations in TauPS2APP mouse model through comparative studies with other AD mouse models and human patient samples.

a, UMAP showing three subclusters of 6,789 astrocytes across samples. b, Schematic plot showing the basic idea of CCA integration and label transfer. In total, 72,165 cells from TauPS2APP and control mice were integrated with 80,660 cells from 48 human individuals with or without AD pathology in Mathys et al12. c, UMAPs showing the predicted labels (top) and scores (bottom) of STARmap PLUS cells generated by the CCA integration with cells from Mathys et al12. d, Heatmap showing the proportions (color bar, scaled per column) of cluster IDs from Mathys et al12. (rows) mapped to STARmap PLUS cells (columns). Cells were excluded if their label prediction score were less than 0.5. e, Diffusion maps showing the subpopulation identified by the present study (top) and predicted labels generated by the CCA integration with the astrocyte population from Mathys et al12. (bottom). f, Heatmap showing the proportions (color bar, scaled per column) of astrocyte cluster IDs from Mathys et al. (rows) mapped to STARmap PLUS astrocyte subpopulations (columns). Cells were excluded if their label prediction score were less than 0.5. g, Diffusion maps showing the subpopulation identified by the present study (top) and predicted labels generated by the CCA integration with the astrocyte population from Habib et al9. (bottom). h, Heatmap showing the proportions (color bar, scaled per column) of astrocyte cluster IDs from Habib et al9. (rows) mapped to STARmap PLUS astrocyte subpopulations (columns). Cells were excluded if their label prediction score were less than 0.5.

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Extended Data Fig. 6 Additional gene expression and spatial analysis of astrocytes.

a, Spatial map of astrocyte subtypes in control and TauPS2APP samples. Scale bars, 100 µm. b, Cell-type composition around Aβ plaque in different distance intervals for the TauPS2APP samples at eight months. Stacked bar plot showing the density of each astrocyte subpopulation in each distance interval around the Aβ plaque. The overall cell density of each subpopulation in each region was included as the reference for comparison. Asterisks denote significantly enriched astrocyte subclusters in each distance interval. One-sided one-sample t-test, *P < 0.05, **P < 0.01 vs. overall cell density. c, Volcano plots showing the differentially expressed genes of astrocytes in AD and control comparison at eight and 13 months (y-axis: -log adjusted p-value, x-axis: average log fold change). The two-sided Wilcoxon rank-sum test. Genes (p-value < 0.05, absolute value of lnFC > 0.1) are marked in red (up-regulated) or blue (down-regulated). d, Gene ontology enrichment analysis (Fisher’s one-sided test) results of DEGs in astrocytes of the 13-month TauPS2APP samples. e, Matrix plot showing the z-scores of SDEGs of microglia across multiple distance intervals from plaques. f, Barplots showing the DEG enrichment significance (the Chi squared test) of co-expression modules of astrocyte identified by scWGCNA. The gene module with the most significant DEG enrichment (AM3) is highlighted. g, Matrix plot showing the averaged z-score value of astrocyte gene modules across multiple distance intervals.

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Extended Data Fig. 7 Additional gene expression and spatial analysis of oligodendrocytes and OPC.

a, UMAP showing subclusters of 11,265 oligodendrocytes and 1,269 OPCs across samples. b, Diffusion map showing the normalized expression level of oligodendrocyte lineage marker genes in oligodendrocytes and OPCs. c, Cell-resolved spatial map for the oligodendrocyte and OPC population of control and TauPS2APP mice. Scale bars, 100 µm. d, Cell type composition around Aβ plaque in different distance intervals for the TauPS2APP samples at eight months. Stacked bar plot showing the density of each oligodendrocyte subpopulation and OPC in each distance interval around the Aβ plaque. Asterisks denote significantly enriched oligodendrocyte subclusters and OPC in each distance interval. One-sided one-sample t-test, *P < 0.05 vs. overall cell density. e, Cell compositions in grid regions with different Tau positive pixel percentage of the TauPS2APP samples at eight months: zero (0%), low (50%), high (100%). One-sided one-sample t-test, *P < 0.05, **P < 0.01, ****P < 0.0001 vs. zero p-tau bin. f, Volcano plots showing DEGs of oligodendrocyte in AD and control comparison at eight and 13 months (y-axis: -log adjusted p-value, x-axis: average log fold change). The two-sided Wilcoxon rank-sum test. Genes (p-value < 0.05, absolute value of lnFC > 0.1) are marked in red (up-regulated) or blue (down-regulated). g, Gene ontology enrichment analysis (Fisher’s one-sided test) results of DEGs in oligodendrocytes of the 13-month TauPS2APP samples. h, Matrix plot showing the z-scores of spatial DEGs of oligodendrocytes across multiple distance intervals from plaques. i, Barplots showing the DEG enrichment significance (the Chi squared test) of co-expression modules of astrocyte identified by scWGCNA. The gene module with the most significant DEG enrichment (AM3) is highlighted. j, Matrix plot showing the averaged z-score value of astrocyte gene modules across multiple distance intervals. k, Matrix plot showing the z-scores of DEGs or SDEGs in the disease-associated gene module of oligodendrocytes in each distance interval around the Aβ plaque in TauPS2APP 13-month sample. The total averaged scaled expression level in different distance intervals was visualized by the bars on top of the matrix plots. l, Gene ontology enrichment analysis (Fisher’s one-sided test) results of disease-associated gene module in oligodendrocytes.

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Extended Data Fig. 8 Spatial maps for neuron populations of control and TauPS2APP mice.

a, Cell-resolved spatial map for the excitatory neuron of control and TauPS2APP mice. Scale bars, 100 µm. b, Cell-resolved spatial map for the inhibitory neuron population of control and TauPS2APP mice. Scale bars, 100 µm.

Extended Data Fig. 9 Additional gene expression and spatial analysis of neurons.

a,b, Boxplot showing the density (number of cells per mm2) of each excitatory neuron subcluster (a) and inhibitory neuron subcluster (b) in the cortex and hippocampus region in Control and TauPS2APP mice at two time points in eight independent samples. Box, 75% and 25% quantiles. Line, median. Dots or forks, individual samples. Student’s t-test, one-sided *P < 0.05. c,d, Neuron composition around the plaque. Stacked bar charts showing the density (number of cells per mm2) of each subcluster of excitatory (c) and inhibitory (d) neuron population from different brain regions at each different distance intervals (0-10, 10-20, 20-30, 30-40, 40-50 µm) to the Aβ plaque from the cortex and hippocampus region of TauPS2APP eight-month sample. The cell density of each subpopulation in each area was included as the reference for comparison (Overall). Asterisks denote significantly enriched neuron subclusters in each distance interval. One-sided one-sample t-test, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001 vs. overall cell density. e,f, Synaptic gene ontology term enrichment of DEGs (p-value < 0.05) identified in the TauPS2APP and Control comparison for all neuron population (e) and neurons in the dentate gyrus region (f) using SynGO. Color of the sunburst plot represents -log10 Q-value at 1% FDR. g, Gene ontology enrichment analysis (Fisher’s one-sided test) results of DEGs in dentate gyrus neurons of the 13-month TauPS2APP samples.

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Extended Data Fig. 10 Validation of cell-type composition and spatial gene expression in TauPS2APP mice.

a, Gene expression heatmaps for representative markers aligned with each top-level cell type of 64-gene (validation) datasets. Expression for each gene is z-scored across all genes in each cell. b, UMAP plot visualizing a non-linear dimensionality reduction for the transcriptomic profiles of 36,625 cells from four samples of the validation dataset. Cells are colored as in (a). c, Spatial atlas of top-level cell types in cortex and hippocampus regions of four samples in the 64-gene dataset. Scale bars, 100 µm. d, Barplot showing the number of cells per top-level cluster in 2,766-genes and 64-genes datasets. Data are represented as mean with 95% CI. Student’s t-test, two-tailed *P < 0.05, **P < 0.01. e,f, UMAPs showing the Gfap gene expression (e) and normalized GFAP protein signal (f) in 64-genes validation dataset. g, Violin plot shows the normalized GFAP protein signal level in the astrocyte cell population (N = 3,423 cells) compared to others (N = 33,202 cells). Box plots depict the median (center) and interquartile range (IQR, bounds of the box), with whiskers extending to the maxima/minima or to the median ± 1.5× IQR. Two-sided t-test, ****P < 0.0001. h, Representative immunofluorescence images in the brain section of 64-gene validation samples (N = four independent animals). Astrocytes were marked by yellow arrows in the raw data. i, Cell-type composition around Aβ plaque at different distance intervals in both eight- and 13-month samples of the 64-gene validation dataset. Asterisks denote significantly enriched cell types in each distance interval. One-sided one-sample t-test, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001 vs. overall cell density. j, Barplot showing the cell density of astrocyte, microglia, oligodendrocyte and OPC in hippocampus alveus region in the 2,766- gene samples and validation samples. k, Matrix plot showing the row-wise scaled expression values of top significantly altered (rank by p-value) DEGs of glial cells and neuronal cells from TauPS2APP versus control samples. l,m, Matrix plot showing PIG that overlapped with 64-gene in each distance interval around the Aβ plaque in the eight-month (l) and TauPS2APP 13-month sample (m) of the 64-gene validation dataset. Colored by row-wise z-score.

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Zeng, H., Huang, J., Zhou, H. et al. Integrative in situ mapping of single-cell transcriptional states and tissue histopathology in a mouse model of Alzheimer’s disease. Nat Neurosci 26, 430–446 (2023). https://doi.org/10.1038/s41593-022-01251-x

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