Fig. 8: Pseudotime trajectory of differentially regulated genes in CTA1-exposed CD103-targeted cDCs reveals plasticity of cDC1 cells and ability to induce Th17 cells.

The continued scRNAseq analysis explored the data set using Monocle 3 with which we established a developmental trajectory of the CTA1-exposed cDC1 cells. The data set from Seurat was analyzed in Monocle 3 and depicted in the UMAP plot (a) and as represented after using the gene signatures of cDC1 and cDC2 cells, as in Fig. 7e (b). We undertook a pseudotime trajectory analysis of the data with starting node in cluster 0 (c). The distribution of cDC1 cells in the UMAP following different i.n immunizations was depicted (d). The expression level of a Th17-promoting gene signature (IL-1b, IL-6, Tgfb1, Tgfb2, Tnfsf4(Ox40L), Tnfrsf9(CD137), IL-12b(p40), Timd4, Cd80, Cd86) was employed to follow gene expression from naïve PBS to CTA1-exposed cDC1 cells along the trajectory (e). An extended gene set enrichment analysis (GSEA) using a gene list taken from a publication of human inflammatory DCs, reported to promote Th17 responses, was compared with the list of co-differentially expressed genes found in CTA1-exposed cDC1 cells⁵⁵ (f). The distribution of gene modules which significantly vary across pseudotime is depicted (g–h). Selected genes from the modules in g are represented in the trajectory of cDC1 cells (i).