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Lipid metabolism analysis reveals that DGAT1 regulates Th17 survival by controlling lipid peroxidation in uveitis
Tianfu Wang, Runping Duan, Zhaohuai Li, Bowen Zhang, Qi Jiang, Loujing Jiang, Jianjie Lv, Wenru Su, Lei Feng
Tianfu Wang, Runping Duan, Zhaohuai Li, Bowen Zhang, Qi Jiang, Loujing Jiang, Jianjie Lv, Wenru Su, Lei Feng
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Research Article Immunology Ophthalmology

Lipid metabolism analysis reveals that DGAT1 regulates Th17 survival by controlling lipid peroxidation in uveitis

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Abstract

Lipid metabolism is closely linked with antitumor immunity and autoimmune disorders. However, the precise role of lipid metabolism in uveitis pathogenesis is not clear. In our study, we analyzed the single-cell RNA-Seq (scRNA-Seq) data from cervical draining lymph nodes (CDLNs) of mice with experimental autoimmune uveitis (EAU), revealing an increased abundance of fatty acids in Th17 cells. Subsequent scRNA-Seq analysis identified the upregulation of DGAT1 expression in EAU and its marked reduction under various immunosuppressive agents. Suppression of DGAT1 prevented the conversion of fatty acids into neutral lipid droplets, resulting in the accumulation of lipid peroxidation and subsequent reduction in the proportion of Th17 cells. Inhibiting lipid peroxidation by Ferrostatin-1 effectively restored Th17 cell numbers that were decreased by DGAT1 inhibitor. Moreover, we validated the upregulation of DGAT1 in CD4+ T cells from patients with Vogt-Koyanagi-Harada (VKH) disease, a human uveitis. Inhibiting DGAT1 induced lipid peroxidation in human CD4+ T cells and reduced the proportion of Th17 cells. Collectively, our study focused on elucidating the regulatory mechanisms underlying Th17 cell survival and proposed that targeting DGAT1 may hold promise as a therapeutic approach for uveitis.

Authors

Tianfu Wang, Runping Duan, Zhaohuai Li, Bowen Zhang, Qi Jiang, Loujing Jiang, Jianjie Lv, Wenru Su, Lei Feng

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Figure 4

T863 induced functional changes in the immune profile of CDLNs.

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T863 induced functional changes in the immune profile of CDLNs.
(A) Sche...
(A) Schematic of the experimental design for scRNA-Seq analysis. CDLN cells were harvested from EAU groups or T863-treated groups at day 14. Each sample included 3 mice. (B) UMAP plot showing clusters of CDLN cells from all mice groups. (C) Heatmap showing scaled expression of discriminative gene sets for major immune cell types in CDLN cells from all mice groups. (D) Volcano plot showing representative DEGs of total immune cells in the T863/EAU comparison groups. Red and blue dots indicate upregulated and downregulated DEGs in T863 groups compared with EAU groups, respectively. Significance was determined using“FindMarkers”function of Seurat package with Wilcoxon rank sum test and adjusted by Bonferroni correction. (E) Representative GO terms and KEGG pathways enriched in downregulated DEGs of all immune cells in the T863/EAU comparison group. (F) Representative GO terms and KEGG pathways enriched in upregulated DEGs of all immune cells in the T863/EAU comparison group. (G) UMAP plot showing clusters of T cells from all mice groups. (H) Representative GO terms and KEGG pathways enriched in upregulated DEGs of Th17 cells in the T863/EAU comparison group. (I) Heatmap showing lipid metabolism related genes of Th17 cells and CD4+ T cells in the T863/EAU comparison groups. (J) Venn diagrams showing the number of hub core upregulated DEGs in T863 groups compared with EAU groups (left). Violin plots of Txnip in Th17 cell subsets from all mice groups (right).

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ISSN 2379-3708

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