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. 2022 Sep 27:13:1020000.
doi: 10.3389/fendo.2022.1020000. eCollection 2022.

Developmental heterogeneity of embryonic neuroendocrine chromaffin cells and their maturation dynamics

Affiliations

Developmental heterogeneity of embryonic neuroendocrine chromaffin cells and their maturation dynamics

Natalia Akkuratova et al. Front Endocrinol (Lausanne). .

Abstract

During embryonic development, nerve-associated Schwann cell precursors (SCPs) give rise to chromaffin cells of the adrenal gland via the "bridge" transient stage, according to recent functional experiments and single cell data from humans and mice. However, currently existing data do not resolve the finest heterogeneity of developing chromaffin populations. Here we took advantage of deep SmartSeq2 transcriptomic sequencing to expand our collection of individual cells from the developing murine sympatho-adrenal anlage and uncover the microheterogeneity of embryonic chromaffin cells and their corresponding developmental paths. We discovered that SCPs on the splachnic nerve show a high degree of microheterogeneity corresponding to early biases towards either Schwann or chromaffin terminal fates. Furthermore, we found that a post-"bridge" population of developing chromaffin cells gives rise to persisting oxygen-sensing chromaffin cells and the two terminal populations (adrenergic and noradrenergic) via diverging differentiation paths. Taken together, we provide a thorough identification of novel markers of adrenergic and noradrenergic populations in developing adrenal glands and report novel differentiation paths leading to them.

Keywords: SmartSeq2; adrenal medulla; chromaffin cell; microheterogeneity; single-cell transcriptomics; sympathoadrenal development.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relatthat could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Transcriptomic analysis of the adrenal medulla and Zuckerkandl organ reveals the parallel differentiation of Schwann cell precursors towards Schwann cells and chromaffin cells. (A) Overview of the experimental design for the acquisition of Wnt1TOMATO single-cell transcriptomes of cells of the adrenal medulla and Zuckerkandl organ from stages E12.5 up to P2, using the SmartSeq2 platform, (B) Heatmap showing the top 8 markers of each cluster resulting from the hierarchical clustering of cells with glial and chromaffin markers, (C) UMAP embedding of the glial and chromaffin cells from the adrenal medulla and Zuckerkandl organ, (D) Cell cycle phase of the selected cells from the adrenal medulla and Zuckerkandl organ, with the first chromaffin fate-biased cells circled, (E) Dynamic representation of differentiation dynamics using combined RNA velocity and CytoTRACE with the progenitor Schwann cell precursors (SCP) population annotated as the root, (F) RNA velocity latent time with the progenitor SCP annotated as the root, (G) Developmental time of single cells shown on the UMAP embedding with the number of cells per stage, (H) UMAP of classical markers of Schwann cell precursors and Schwann cells (Sox10, Plp1), intermediate chromaffin fate-biased “bridge” cells (Htr3a) and chromaffin cells (Chgb, Th, Dbh) reflecting the main cell types in the data set. Ad, adrenal gland; ZO, Zuckerkandl Organ; SCPs, Schwann cell precursors; iSCs, immature Schwann cells; ChC1-3, chromaffin cells 1-3.
Figure 2
Figure 2
Trajectory analysis from SCP diverging to glial and ChC fates. (A) Selected early diverging glial markers. (B) Sub-selection of the diverging pseudotime trajectory, confirmed by RNA velocity (middle). Binned (10 bins) pseudotime heatmap of min-max normalised expression of significantly changing markers leading to glial fate, ordered by activation. (C) Binned (10 bins) pseudotime heatmap of min-max normalised expression of significantly changing markers leading to ChC fate, ordered by activation. (D) Selected early diverging ChC markers.
Figure 3
Figure 3
Compositional and biasing analysis of SCP cells toward either of the fates. (A) Scoring of the cells using the two list of early diverging genes defined in Figure 2, with cells considered SCP when the scoring is low. (B) Gene module repulsion analysis between early diverging glia and ChC gene groups. Analysis is performed only in SCP cells (top left). The scatter plot (lower left and right side) depicts inter and intra-module correlation of each gene from both diverging gene group. A repulsion score is shown in the lower left plot. Top 4 gene showing highest intra-module correlation and inter-module anti-correlation are annotated on the right-side plot. (C) UMAP plots of log10(fpm) expression of three known markers, with SCP cells highlighted by the dashed lines. ChC, chromaffin cell; SCP, Schwann cell precursor.
Figure 4
Figure 4
Identification of two discrete paths of chromaffin cell differentiation. (A) Dynamic representation of differentiation dynamics using RNA velocity identifies two terminal states of chromaffin fates (red and blue) with the SCP population annotated as the root. (B) Heatmap presents main markers of the two chromaffin terminal states. (C) Left panel: Two putative paths to chromaffin terminal states. Middle and right panels: Heatmaps showing unbiased markers for each chromaffin terminal state. (D) Developmental time contribution of chromaffin cells to the two terminal paths. ChC, chromaffin cell.
Figure 5
Figure 5
Leiden analysis shows ten main clusters of chromaffin cells based on its gene expression in murine adrenal medulla from E13.5 to P2 developmental stages. (A) Dot plot showing top 5 markers identified by gene expression for each leiden cluster of chromaffin cells. (B) Unbiased plotting using Leiden clustering presented via UMAPs with highly expressed markers in different clusters.
Figure 6
Figure 6
Heterogeneity of intermediate states of chromaffin cells. (A) Selection of intermediate leiden clusters shown on UMAP, with three known markers represented in that subselection (knn smoothed log10 fpm). (B) Matrix plot of min-max normalized mean expression of selected DE markers from each leiden clusters. (C) UMAP of the selection markers for each leiden clusters (knn smoothed log10 fpm). ChC, chromaffin cell.
Figure 7
Figure 7
Expression of cluster-specific markers in embryonic murine adrenal medulla at E14.5 – P2. (A, B) Immunohistochemistry for TH and RNA in situ hybridization for Rgs5 and Myl1 on cross-sections of embryonic adrenal medulla at E14.5, E16.5, E18.5 and P2 accordingly. Percent of Rgs5+ and Myl1+ cells over total TH+ cells. UMAP plots of Rgs5 and Myl1 expression. (C, D) Immunohistochemistry for TH and RNA in situ hybridization for Notum and Scg2 on cross-sections of embryonic adrenal medulla at v accordingly. Percent of Notum+ and Scg2+ cells over total TH+ cells. UMAP plots of Notum and Scg2 expression. (E, F) Immunohistochemistry for TH and RNA in situ hybridization for Lrp1b and Scnn1g on cross-sections of embryonic adrenal medulla at E14.5, E16.5, E18.5 and P2 accordingly. Percent of Lrp1b+ and Scnn1g+ cells over total TH+ cells. UMAP plots of Lrp1b and Scnn1g expression. Scale bar is 10 μm, scale bar on insets is 5 μm. **pvalue ≤ 0.01; ****p-value ≤ 0.0001; ns, non-significant.

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