A molecular brain atlas reveals cellular shifts during the repair phase of stroke

Abstract

Ischemic stroke triggers a cascade of pathological events that affect multiple cell types and often lead to incomplete functional recovery. Despite advances in single-cell technologies, the molecular and cellular responses that contribute to long-term post-stroke impairment remain poorly understood. To gain better insight into the underlying mechanisms, we generated a single-cell transcriptomic atlas from distinct brain regions using a mouse model of permanent focal ischemia at one month post-injury. Our findings reveal cell- and region-specific changes within the stroke-injured and peri-infarct brain tissue. For instance, GABAergic and glutamatergic neurons exhibited upregulated genes in signaling pathways involved in axon guidance and synaptic plasticity, and downregulated pathways associated with aerobic metabolism. Using cell-cell communication analysis, we identified increased strength in predicted interactions within stroke tissue among both neural and non-neural cells via signaling pathways such as those involving collagen, protein tyrosine phosphatase receptor, neuronal growth regulator, laminin, and several cell adhesion molecules. Furthermore, we found a strong correlation between mouse transcriptome responses after stroke and those observed in human nonfatal brain stroke lesions. Common molecular features were linked to inflammatory responses, extracellular matrix organization, and angiogenesis. Our findings provide a detailed resource for advancing our molecular understanding of stroke pathology and for discovering therapeutic targets in the repair phase of stroke recovery.

Fig. 1

Cellular profiling of the stroke-injured mouse brain. (A) Scheme of experimental workflow (B) Laser Doppler imaging (LDI) illustrating relative perfusion in the mouse brain (C) Bar plot showing quantification of relative blood perfusion in the stroke core and the ischemic border zone (ibz) compared to the left hemisphere acutely after stroke (D) Illustration of brain regions for biopsy to perform snRNAseq (E) Dot plot representation of canonical cell type markers across different cell populations from the intact contralesional hemisphere, labeled by cell type: glutamatergic neurons (Glut), GABAergic neurons (GABA), astrocytes (Asc), fibroblasts (FB), oligodendrocytes (Olig), immune cells (Imm), vascular cells (Vasc), stem/progenitor cells (SPC), and mural cells (Per) (F-H) UMAP visualization of cell clusters from intact, ibz and stroke tissue. (I) Bar plot showing distribution of cell type by neural and non-neural cells and individual cell types (J) across the reference, intact, ibz and stroke samples. The data was generated with a cohort of n = 9 mice

Fig. 2

A distinct cell cluster termed injury-associated (IC) cells revealed by snRNAseq and immunohistochemistry. (A) Representative histological overview of brain sections stained with (from left to right) Gat/vGlut, IBA1/GFAP, CD68/IBA1, CD31/CD13, co-stained with DAPI. (B) Quantification of NeuN+, GFAP+, IBA1+, CD68+, CD31 + and CD13 + expression relative to intact tissue (dotted line). (C) Representative histological overview of brain sections stained with PDGFRb and co-stained with DAPI. (D) Quantification of PDGFRb + expression relative to intact tissue (dotted line). (E) Representative histological overview of brain sections stained with ITGAV and co-stained with DAPI. (F) Quantification of ITGAV + expression relative to intact tissue (dotted line). (G) Bar graph showing relative amount of major GABA and glutamatergic neuronal subtypes. (H) Dot plot showing expression of canonical cell type marker of injury-associated cells (IC), FB, and Asc. (I) Heatmap showing correlation of gene expression profiles between each cell type from stroke tissue. (J) Representative histological overview of brain sections stained with IGFBP5 (left) and quantification of IGFBP5 expression relative to intact tissue (right). (K) Feature plot showing the expression patterns of Apoe, Adam12, Cola1a2, and Vim in cells from stroke tissue. (L) Representative histological overview of brain sections stained with (from left to right) IGFBP5/GFAP and IGFBP/PDGFRB, co-stained with DAPI. (M) Cell counts (GFAP + and PDGFRb + positive cells, relative to all counted IGFBP5-positive cells) in the ibz and the stroke area. The data was generated with a cohort of n = 9 mice

Fig. 3

Transcriptomic responses of individual cell types to stroke in distinct mouse brain regions. (A) Heatmap showing number of significantly up- and downregulated genes per cell types in stroke vs. intact (left), ibz vs. intact (middle) and ibz vs. stroke (right) tissue. (B) Venn diagram showing the overlap and unique differentially expressed genes from neural cells between stroke and ibz tissue (C) Bar plot showing the common and differential expressed genes in non-neural cells (right). (D-I) Gene set enrichment analysis (GSEA) of biological pathways that are enriched in stroke vs. intact and ibz vs. intact tissue for (D) GABA, (E) Glut, and GSEA from stroke vs. intact tissue in (F) Imm, (G) Asc, (H) FB, and (I) Vasc (J) Olig, and (K) Per. Each panel displays the normalized enrichment score (NES) for pathways that are overrepresented (positive NES) or underrepresented (negative NES) in the post-stroke environment compared to intact tissue

Fig. 4

Mapping of intercellular molecular signaling post-stroke. (A) Schematic of cell-cell interaction analysis (B) Bar plot showing number and strength of interactions in cells from intact, ibz and stroke tissue. (C) Network diagram contrasting total number of cell-cell interactions between individual cell types in stroke vs. intact (left) and ibz vs. intact (right). Red lines indicate increased interaction, blue lines indicate reduced interaction, relative to intact tissue. (D) Hierarchy plot of interaction between all individual cell types to target cells in stroke (left), ibz (middle) and intact (right) datasets. (E) Heatmap showing differential interactions between cell types from stroke vs. intact (upper) and ibz vs. intact tissue (lower). Red squares indicating increased signaling and blue squared indicating decreased signaling, relative to cells from intact tissue. (F) Scatter plot projecting signaling groups onto a 2D space according to their functional similarity between cells from stroke and intact tissue. (G) Bar plot showing signaling pathway distance between stroke and intact tissue (H) Stacked bar plot illustrating the proportional relative information flow in signaling pathways between intact and stroke tissue. (I) Cell-cell communication networks for selected pathways: COLLAGEN, Protein Tyrosine Phosphatase Receptor (PTPR), and Pleiotrophin (PTN) across cell types in intact (left) and stroke (right) tissue. (J) Chord diagrams showing the most upregulated signaling ligand-receptor pairings in injury-associated cells (IC), fibroblasts (FB), astrocytes (Asc), and pericytes (Per)

Fig. 5

Comparative gene expression profiles in mouse and human post-stroke. (A) Schematic of human and mouse stroke (B) Scatter plot displaying the Person correlation for gene expression changes between mouse and human post-stroke. (C) Heatmap of common upregulated genes in human and mouse stroke (upper) and differentially expressed genes in human and mouse stroke (lower) (D) Stacked barplot of common and unique upregulated genes in the top 2000, 500 and 100 gene sets from both mouse and human datasets (upper) and Venn diagram of shared and unique genes with a fold change > 2. (E-G) Overrepresentation analysis of top 2000 genes present in (E) both mouse and human datasets, (F) genes exclusively identified in mouse stroke dataset (G) and genes only present in human stroke dataset. All p-values ***,< 0.001