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. 2023 Jul 3;13(12):3914-3924.
doi: 10.7150/thno.84912. eCollection 2023.

Senescent melanocytes driven by glycolytic changes are characterized by melanosome transport dysfunction

Affiliations

Senescent melanocytes driven by glycolytic changes are characterized by melanosome transport dysfunction

Young Joon Park et al. Theranostics. .

Abstract

Rationale: Senescent melanocytes accumulate in photoaged skin and are closely related to skin aging. A better understanding of the molecular characteristics of senescent melanocytes may be the key to controlling skin aging. Methods: We have developed an in vitro model of senescence in melanocytes using UV irradiation and investigated the functional characteristics and molecular mechanisms underlying senescence in UV-irradiated melanocytes. Results: We have highlighted that in vitro senescent melanocytes are characterized by melanosome transport dysfunction resulting in melanin accumulation. The defective melanosome transport was confirmed with the ultrastructural characterization of both in vitro UV-induced senescent melanocytes and in vivo melanocytes of hypopigmented aging skin. A single-cell transcriptomic analysis revealed that the glycolytic metabolism pathway appeared to be significantly upregulated in most senescent phenotypes. Furthermore, the inhibition of glycolysis by pharmacological compounds mitigates the pro-aging effects of melanocytes senescence, suggesting that alterations in cellular glucose metabolism act as a driving force for senescence in melanocytes. Conclusion: These results demonstrate that senescent melanocytes are characterized by glycolytic metabolism changes and a defective melanosome transport process, which may be related to impaired mitochondrial function, highlighting the importance of metabolic reprogramming in regulating melanocyte senescence.

Keywords: glycolysis; melanocyte; melanosome; photoaging; senescence; single-cell RNA sequencing.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interest exists.

Figures

Figure 1
Figure 1
Characterization of UVB-induced senescent melanocytes. Normal primary melanocytes were irradiated with 60 mJ/cm2 UVB for 4 consecutive days and then cultured for ten days following UV irradiation and cellular senescence was analyzed according to SA-β-Gal staining (A), heterochromatin foci formation (B) and p16INK4A/p21Waf1 mRNA expression levels (C). (D) Melanin contents and DOPA oxidase activity levels in UVB-induced senescent melanocytes. Similarity metrics and differential gene expression profiling including SASP of sham-irradiated and UVB-induced senescent melanocytes (UVSM) detected by RNA seq analysis (E, left and middle panels). Expression levels of the mRNA of SASPs as analyzed by real-time PCR (E, right panel). (F) GSEA was performed using the “FRIDMAN senescence,” “KEGG melanogenesis” and “GOBP melanocyte differentiation” gene sets to demonstrate the sequential transition in gene expression from sham-irradiated to UVB-induced senescent melanocytes. Statistical significances were assessed using chi-square test for categorical data (A and B) and Mann-Whitney U test for numerical data (C, D, E, and F) in independent two group comparison.
Figure 2
Figure 2
Senescent melanocytes exhibit melanosome accumulation with defective melanosome transport. Normal primary melanocytes were irradiated with UVB and cultured for ten days, and MITF/Tyrosinase mRNA (A) and protein (B) were analyzed by real-time PCR and western blotting, respectively. Quantitative results of western blotting were described with dot graph (B, lower panel). (C) Sham-irradiated and UVB-induced senescent melanocytes were analyzed by EM (left panel). '1' and '2' indicate fields observed with a higher magnification. 'N' and 'C' indicate nucleus and cytoplasm, respectively. The total melanosome count and melanosome distribution were analyzed and are presented as a bar graph (right panel). (D) IHC analyses of p16INK4A and MART1 were performed in series sections of IGH patients. Arrows indicates p16INK4A-positivemelanocytes. (E) EM analysis of IGH patient skin samples. 'M' and 'K' indicate melanocytes and keratinocytes, respectively. Red lines indicate the melanocyte boundary. (F) A schematic image of the melanosome transport process in melanocytes. (G) Heatmap showing log2 (-fold) changes in the expression levels of kinesin, and dynein as obtained from mRNA-seq (sham vs. UVB-induced senescent melanocytes). (H) The melanosome transport tripartite complex gene expression level was analyzed by mRNA seq (upper panel), real-time PCR and western blot (middle panel) analyses. Statistical significances were assessed using Mann-Whitney U test for numerical data (A, C, and H) in independent two group comparison.
Figure 3
Figure 3
Single-cell transcriptome analysis: (A) Normal primary melanocytes were irradiated with UVB and cultured for ten days, with single-cell transcriptome data revealing six different subclusters, subsequently termed cluster 1 (C1) to cluster 6 (C6) according to the pseudotime that elapsed. (B) Senescent module scores using the “FRIDMAN senescence” gene set show a sequential increase from C1 to C6. (C) MITF, TYR and CDKN2A mRNA expression levels in single cell clusters (left upper panel). GSEA was performed using the “FRIDMAN senescence,” “KEGG melanogenesis” and “GOBP melanocyte differentiation” gene sets to demonstrate the sequential transition in gene expression levels from C2 to C4 and C4 to C5 (right upper and lower panel). (D) Violin plots showing the expression levels of mRNA-encoding senescence-related (CDKN2A, CDKN1A, TP53), melanosome transport (MYO5A, RBA27A, MLPH) and melanogenesis-related (MITF, TYR, TYRP1) gene sets to demonstrate the sequential transition in gene expression levels from C2 to C4, C4 to C5, and C4 to C6. (E) Schematic image of the gene expression changes in single cell clusters. Statistical significances were assessed using Mann-Whitney U test for numerical data (D) in independent two group comparison.
Figure 4
Figure 4
Glycolytic metabolism dysfunction in senescent melanocytes: (A) Gene ontology analysis results of differentially expressed genes between C4 and C5. (B) Glycolysis-related gene expression in single cell clusters. (C) A schematic image of the glycolysis pathway and corresponding inhibitors (left panel) and a violin plot analysis of glycolysis-related gene expression levels between C4 and C5 (right panel). (D) GSEA was performed using the “CELLULAR RESPIRATION,” “HALLMARK HYPOXIA” and “HALLMARK GLYCOLYSIS” gene sets to demonstrate the sequential transition in gene expression levels from C4 to C5. (E) Glucose uptake and lactate production outcomes were analyzed in sham-irradiated and UVB-induced senescent melanocytes. Statistical significances were assessed using Mann-Whitney U test for numerical data (D and E) in independent two group comparison.
Figure 5
Figure 5
Inhibition of glycolysis delays melanocytes senescence. (A) Normal melanocytes were irradiated with UVB and maintained for 5 days in low- or high-glucose culture media and were then analyzed with SA-β-Gal staining and for mRNA expression. (B) Schematic image of the glycolysis inhibitor (2-DG) treatment schedule (upper panel). Glucose uptake and lactate production were analyzed in sham-irradiated and UVB-induced senescent melanocytes with or without 2-DG (lower panel). CDKN1A, CDKN2A (C) and SASPs (D) mRNA expression levels in sham-irradiated and UVB-induced senescent melanocytes with or without 2-DG. (E) SA-β-Gal staining in sham-irradiated and UVB-induced senescent melanocytes with or without 2-DG. Melanosome transport-related genes (MYO5A, RAB27A and MLPH) expression (F, left panel) and protein levels (F, right panel), melanogenesis-related genes (MITF and TYR) mRNA expression (G) and the total melanin content (H) were analyzed in UVB-induced senescent melanocytes with or without 2-DG. (I) UVB-induced senescent melanocytes and 2-DG treated senescent melanocytes were analyzed by EM (left panel). The melanosome distribution was analyzed and is presented here as a bar graph (right panel). Statistical significances were assessed using chi-square test for categorical data (A lower left and E; SA-β-Gal) and Mann-Whitney U test for numerical data (G and I) in independent two group comparison. One-way ANOVA with Tukey's post-hoc test was used for multiple comparisons among three groups (A lower right, B, C, D, F, and I), and only the significant results of post-hoc test between two group were indicated.

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