A latent activated olfactory stem cell state revealed by single-cell transcriptomic and epigenomic profiling

Abstract

The olfactory epithelium is one of the few regions of the nervous system that sustains neurogenesis throughout life. Its experimental accessibility makes it especially tractable for studying molecular mechanisms that drive neural regeneration in response to injury. In this study, we used single-cell sequencing to identify transcriptional and epigenetic processes involved in determining olfactory epithelial stem cell fate during injury-induced regeneration. By combining gene expression and accessible chromatin profiles of individual lineage-traced olfactory stem cells, we identified transcriptional heterogeneity among activated stem cells at a stage when cell fates are being specified. We further identified a subset of resting cells that appears poised for activation, characterized by accessible chromatin around silent genes prior to their expression in response to injury. These results provide evidence for a latent activated stem cell state in which a subset of quiescent olfactory epithelial stem cells are epigenetically primed to support injury-induced regeneration.

Keywords: adult tissue stem cell; epigenetic; epigenomics; horizontal basal cell; neural regeneration; neurogenesis; olfactory; olfactory epithelium; olfactory stem cell; regeneration; single-cell ATAC-seq; single-cell RNA-seq.

Graphical abstract

Figure 1

Trajectory inference and differential expression analysis (A) 3D UMAP of inferred trajectory with cells colored by cell type. Starting from HBCs^∗, the trajectory consists of three lineages ending in rHBCs, Sus, and mOSNs. (B) 2D UMAP of cells colored by cell type (top left) or by expression of known markers (all other panels), gray denoting no/low expression and blue high expression. (C–E) Expression of markers for the mOSN (C), Sus (D), and rHBC (E) lineages over pseudotime.

Figure 2

HBCs^∗ express lineage-enriched TFs (A) Heatmaps of TF expression cascades using fitted expression measures from tradeSeq. The x axis represents 100 equal pseudotime bins. The most abundant cell type in each bin is indicated in the color bar at the top; where there are too few cells in a bin, no color is provided. Each row represents the expression of a TF normalized to zero mean and unit variance within the lineage. TFs are ordered by the pseudotime of their most significant peak. (B) Heatmap with each row representing the scaled expression of a “shared” TF in HBCs^∗. The color bar at the top indicates cluster. (C) Expression of Ebf2, Uncx, and Pdlim4 over pseudotime. Cell type indicated by the key in (A). (D) UMAPs of HBCs^∗ colored by cluster or gene expression. (E) FISH of Ebf2 (magenta), Uncx (cyan), and Pdlim4 (yellow); immunohistochemistry (IHC) for KRT5 (to mark HBCs) in gray. Arrows, cells that co-express Ebf2 and Uncx; arrowheads, cells that express Pdlim4. Dashed line, basal lamina. HPI, hours post injury; scale bars, 40 μM; detached dead tissue cropped out in injured samples.

Figure 3

Deconvolution of gene expression to TF activity along the mOSN lineage (A) Clustered heatmap of scaled activity for TFs (rows) along the mOSN lineage. The x axis represents pseudotime, and the dominant cell type in each bin is indicated at the top. Hierarchical clustering on the y axis shows early (mauve), mid (amber), and late (aqua) TF groups. (B) Heatmap of scaled activity for the 20 most variable TFs. (C) Change in activity over pseudotime for representative TFs from each group. Box plots show the contribution of the TF to total gene expression in each cell. (D, left-right) FISH of Sox11 (cyan) and Rfx3 (yellow), or E2f1 (cyan) and Ezh2 (yellow) at 96 HPI. HBCs were identified by IHC for KRT5 (magenta) and nuclei by DAPI (gray). (E, left-right) FISH of Egr1 or Fos (cyan) co-labeled with KRT5 (magenta); multiplex FISH of Foxa1 (cyan), Foxa2 (magenta), and Foxa3 (yellow) at 48 HPI (Foxa2/3 signal is non-specific). Dashed line, basal lamina. HPI, hours post injury. Scale bars in (D) and (E), 50 μM; detached dead tissue cropped out in injured samples.

Figure 4

Wound response genes are primed for activation (A) Heatmaps of ATAC-seq signal around the TSS of highly expressed (top) or silent (bottom) genes in UI HBCs. (B) Heatmap of normalized bulk gene expression (average RPKM of two biological replicates) in UI HBCs versus injured HBCs (HBC^∗) for the top 506 genes upregulated after injury; genes ordered from left to right according to descending expression after injury (top). Bar graph showing log2(fold-change) in chromatin accessibility after injury (bottom); dotted lines indicate log2(fold-change) of 0.5 and −0.5. (C) ATAC-seq (top) and RNA-seq (bottom) read counts before (green) and after (blue) injury of genes that decrease (Icam1) or increase (Krt5) in expression in injured HBCs. (D) Same as (C) for wound response genes (Krt6a, Ecm1, Sprr1a, and Emp1).

Figure 5

scATAC-seq uncovers HBC states (A and B) UMAP of nuclei colored by origin (A) or state (B). (C) Barplot of the number of (un)injured nuclei in each cluster. (D) Heatmap of the Benjamini-Hochberg FDR-adjusted p values (Benjamini and Hochberg, 1995) of the top 10 enriched TF motifs (rows) for each state (columns). Gray indicates high p value; black indicates low p value. (E) ArchR module scores for sets of genes predicted to be regulated by JUNB, FOS, or FOXA1.

Figure 6

Integration of scRNA-seq and scATAC-seq (A–E) UMAPs of HBC transcriptomes colored by source (A) expression of marker genes (B–D), and inferred cell type (E). (F) Workflow for label transfer. (G) UMAP of HBC epigenomes colored by inferred cell type.

Figure 7

Hybrid gene expression after injury (A) UMAP of cells colored by gene expression. (B) UMAP of nuclei colored by gene activity. (C) FISH (red) of each hybrid gene in UI OE, OE at 24 HPI, and OE at 48 HPI co-labeled with KRT5 IHC (HBCs, blue) and DAPI (nuclei, gray). Bottom panels in each condition show hybrid gene FISH with DAPI alone. Dashed line, basal lamina; scale bars, 20 μM; detached dead tissue cropped out in injured samples.