Single cell transcriptome profiling reveals cutaneous immune microenvironment remodeling by photodynamic therapy in photoaged skin

Abstract

Background: The immune microenvironment plays a critical role in maintaining skin homeostasis, which is closely related to the dysfunction in photoaged skin such as autoimmunity and tumorigenesis. Several recent studies have demonstrated the efficacy of 5-aminolevulinic acid photodynamic therapy (ALA-PDT) in alleviating photoaging and skin cancer. However, the underlying immune mechanisms and the immune microenvironment change by ALA-PDT remain largely unknown.

Methods: To illustrate the effects of ALA-PDT on immune microenvironment in photoaged skin, single cell RNA sequencing (scRNA-seq) analysis of photoaged skin on the extensor side of the human forearm before and after ALA-PDT was performed. R-packages of Seurat, clusterProfiler, Monocle, CellChat were used for cell clustering, differentially expressed genes analysis, functional annotation, pseudotime analysis and cell-cell communication analysis. The gene sets related to specific functions were extracted from the MSigDB database, which were used to score the functions of immune cells in different states. We also compared our result with published scRNA-seq data of photoaged skin of the eyelids.

Results: The increase score of cellular senescence, hypoxia and reactive oxygen species pathway in immune cells and the decrease of immune receptor activity function and proportion of naive T cells were found in skin photoaging. Moreover, the function of T cell ribosomal synthesis was also impaired or down regulated and function of G2M checkpoint was up regulated. However, ALA-PDT showed promising results in reversing these effects, as it improved the above functions of T cells. The ratio of M1/M2 and percentage of Langerhans cells also decreased with photoaging and increased after ALA-PDT. Additionally, ALA-PDT restored the antigen presentation and migration function of dendritic cells and enhanced cell-cell communication among immune cells. These effects were observed to last for 6 months.

Conclusion: ALA-PDT has potential to rejuvenate immune cells, partially reversed immunosenescence and improved the immunosuppressive state, ultimately remodelling the immune microenvironment in photoaged skin. These results provide an important immunological basis for further exploring strategies to reverse skin photoaging, chronological aging and potentially systemic aging.

Keywords: ALA-PDT; immune microenvironment; immunosenescence; photoaging; single cell RNA sequencing (scRNA-seq).

Figure 1

Immune cell type identification in ALA-PDT and changes in cell ratio and functions before and after treatment. (A) Schematic diagram of the ALA-PDT process. The extensor forearms and the back of hands were treated every two weeks, with scRNA-seq performed before treatment (Con) and Iat 1 week (1W) and 6 months (6M) after final treatment. (B) UMAP plot visualizing immune cells in ALA-PDT (left). Bar chart of changes in the proportion of immune cell subsets in ALA-PDT (right). (C) Circle plot of markers of different cell subpopulations. (D, E) Boxplots of AUCell scores of GO or HALLMARK pathway of immune cells (* P.adj<0.05, **P.adj<0.01, *** P.adj<0.001, by Wilcox test). (Con, 1W and 6M represented the photoaged skin before PDT, 1 week and 6 months after PDT, respectively. Y, M and O represented the photoaged skin from the young, middle-aged and old, respectively.).

Figure 2

T sub-clusters in ALA-PDT and photoaging. (A, B) UMAP plots visualizing the T sub-clusters in ALA-PDT and photoaging, respectively. (C, D) Pseudotime analysis of CD8+T cells in ALA-PDT marked by cell type and stage, respectively. (E, F) Pseudotime analysis of CD4+T cells in ALA-PDT marked by cell type and stage, respectively. (G, H) Bar charts of changes in the proportion of T cell subsets in photoaging and ALA-PDT, respectively. (I) Bar chart of changes in the proportion of naive and memory T cells by ALA-PDT and photoaging.

Figure 3

Changes of ribosome biogenesis function of T cells in ALA-PDT and photoaging. (A, B) GO function enrichment analysis of DEGs upregulated of T cells in 1W/Con and 6M/Con in ALA-PDT, respectively. (C) KEGG function enrichment analysis of DEGs upregulated of T cells in 1W/Con (top) and 6M/Con (bottom) in ALA-PDT. (D) KEGG function enrichment analysis of DEGs downregulated of T cells in Old/Young (top) and Old/Middle (bottom) in photoaging. (E) Venn plot of DEGs upregulated of T cells in ALA-PDT and DEGs downregulated in photoaging. (F) Heatmaps of the expression of up-regulated (top) and down-regulated (bottom) DEGs in T cells by ALA-PDT in photoaged T cells.

Figure 4

Changes of T cells function in ALA-PDT and photoaging. (A, B) Boxplots of AUCell scores of HALLMARK pathways of T cells in ALA-PDT and photoaging (* P.adj<0.05, ** P.adj<0.01, *** P.adj<0.001, by Wilcox test). (C) Heatmap of the expression of DEGs of T cells during photoaging in T cells of ALA-PDT.

Figure 5

Changes of ratio and function of Mø, LC and DC in ALA-PDT and photoaging. (A) UMAP plots visualizing the Mø sub-clusters in ALA-PDT. (B) UMAP plots of markers of different Mø subpopulations in ALA-PDT. (C) Bar charts of changes in the proportion of Mø subsets in ALA-PDT and photoaging. (D) Bar charts of changes in the proportion of LC in photoaging and ALA-PDT, respectively (Pearson’s chi-squared test). (E) GO function enrichment analysis of DEGs upregulated of DC in 1W/Con (top) and 6M/Con (bottom) in ALA-PDT. (F) Heatmap of the expression of upregulated DEGs in DC by ALA-PDT in photoaging’s DC cells. (G) KEGG function enrichment analysis of DEGs downregulated of DC in M/Y in photoaging.

Figure 6

Cell-cell communication between immune cells in ALA-PDT. (A–C) Number (top) and strength (bottom) of interactions between different immune cell subtypes before ALA-PDT and at 1 week and 6 months after ALA-PDT, respectively.