Transcriptomic analyses of NeuroD1-mediated astrocyte-to-neuron conversion

Abstract

Ectopic expression of a single neural transcription factor NeuroD1 can reprogram reactive glial cells into functional neurons both in vitro and in vivo, but the underlying mechanisms are not well understood yet. Here, we used RNA-sequencing technology to capture the transcriptomic changes at different time points during the reprogramming process. We found that following NeuroD1 overexpression, astroglial genes (ACTG1, ALDH1A3, EMP1, CLDN6, SOX21) were significantly downregulated, whereas neuronal genes (DCX, RBFOX3/NeuN, CUX2, RELN, SNAP25) were significantly upregulated. NeuroD family members (NeuroD1/2/6) and signaling pathways (Wnt, MAPK, cAMP) as well as neurotransmitter receptors (acetylcholine, somatostatin, dopamine) were also significantly upregulated. Gene co-expression analysis identified many central genes among the NeuroD1-interacting network, including CABP7, KIAA1456, SSTR2, GADD45G, LRRTM2, and INSM1. Compared to chemical conversion, we found that NeuroD1 acted as a strong driving force and triggered fast transcriptomic changes during astrocyte-to-neuron conversion process. Together, this study reveals many important downstream targets of NeuroD1 such as HES6, BHLHE22, INSM1, CHRNA1/3, CABP7, and SSTR2, which may play critical roles during the transcriptomic landscape shift from a glial profile to a neuronal profile.

Keywords: NeuroD1; RNA-sequencing; astrocyte; neuronal conversion; reprogramming; transcriptome.

FIGURE 1

Experimental design and overall global transcriptomic analysis. (a) Illustration of the experimental design. Each time point has three replicates. (b) Hierarchical clustering of sample relationship based on global expression profile. (c) Principal component analysis of 18 RNA samples. PC1 = 43.9%, PC2 = 28.4%. (d) Bar plot of the numbers of up‐ or downregulated DEGs in pairwise comparisons with untreated astrocytes. (e) Venn diagram of comparisons shows that GFP control and NeuroD1‐GFP samples at D1 infection share the majority of DEGs caused by viral infection.

FIGURE 2

DEG analysis revealed early inflammatory responses and transcriptomic shift toward neurons at late stage. (a) Heatmap of RNA‐seq data of 2994 DEGs, which were grouped into three clusters with most significant functional ontologies annotated. (b) Volcano plot of up‐ and downregulated genes in the control virus D1 group compared to the HA group (untreated astrocytes). The cutoff values are −1 and 1 for log₂(fold change), and 2 for ‐log₁₀(p‐adj). (c and d) Top up‐ and downregulated DEGs from panel (b)

FIGURE 3

NeuroD1 overexpression rapidly activated multiple transcription factors and neuronal receptors within the first 24 h. (a) A total of 123 DEGs were picked from the comparison between day 1 NeuroD1 samples versus the GFP control samples. (b) Representative transcription factors regulated by NeuroD1 at day 1. (c) Heatmap showing the distribution of downregulated DEGs (DRGs) and two classes of upregulated DEGs (URGs) among different samples. (d–f) Distinct patterns of some of the representative genes among DRGs and URGs

FIGURE 4

Activation of neurogenic factors along with the receding of viral responses after 3 days of NeuroD1 expression. (a) Volcano plot of genes at D3 versus D1 in the NeuroD1 group. (b) Enriched GO categories visualized in REVIGO. The p‐values are color coded. The size indicates the generalness of the GO term. Similar GO terms remained close together in the plot. (c) Bar plot of 21 transcription factors with fold change >3 from panel (a). Colors correspond to log2 expression base mean. (d) Activated and suppressed transcription factors with top fold changes

FIGURE 5

Modular associations with conversion traits and network analysis of NeuroD1 correlations. (a) An example of gene dendrogram. The color block below the dendrogram indicates the corresponding module color. (b) Dendrogram of eigengenes from 15 modules together with three traits (initiation, time, and infection). (c) The number of genes and DEGs associated with each colored module. (d) Network of NeuroD1 with its 49 interacting genes. Line width: weight (min = 0.0022, max = 0.7175). Circle size: degree, that is, connected nodes (min = 1, max = 17). Filled color: betweenness centrality (min = 0.0, max = 0.2835).

FIGURE 6

Regulatory network of transcription factors and cell type‐specific gene expression. (a) Network of 98 differentially expressed transcription factors from modules brown, blue, black, magenta, yellow, red, green, and pink. Circle size: degree (min = 1, max = 15). (b) Heatmap of progenitor‐, neuron‐, and astrocyte‐related genes over the reprogramming time course. (c) Gene set enrichment analysis of D14 compared to human astrocytes, showing Notch and EMT signaling pathways activated at day 14 after NeuroD1 expression.

FIGURE 7

Comparison between transcriptomic changes induced by NeuroD1 versus chemical reprogramming. (a) Heatmap of 1104 overlapping DEGs between NeuroD1 treatment and small molecule treatment (core drugs). Yellow indicates high expression; purple indicates low. The biological processes enriched in the top cluster and bottom cluster were annotated by GO analysis on the right. (b–e) Line plots of log‐read counts of representative up‐ and downregulated genes in the NeuroD1 group versus the core drug group. Solid lines for core drug group, and dashed lines for NeuroD1 group.