Fig 1: Identification of galectin-3 as a target of mast cell Sirt6.a, b mRNA levels (a, n = 6 per group) in EAT tissues and protein levels (b, n = 6 per group) in plasma for galectin-1, galectin-3 and galectin-9 in WT and KO mice. c Heatmap displaying the ligand-receptor signaling network of the galectin pathway between immune cell types from WT and KO mice. Each cell in the heatmap represents the predicted communication probability from a sender to a receiver cell type. The bar plot above the heatmap quantifies the total outgoing signaling strength of each cell type, while the bar plot to the right reflects the total incoming signaling strength. TCP, total communication probability. d Bone marrow-derived mast cells (BMMCs) were transfected with control siRNA (siCtrl) or Sirt6 siRNA (siSirt6). Successful Sirt6 silencing was confirmed by qPCR and western blotting (n = 6 per group). e–i Lgals3 and Lgals9 mRNA levels (e, n = 6 per group), RELA (p65 subunit of NF-κB) binding to the promoters of Lgals3 and Lgals9 (f, n = 5 per group), Sirt6 binding to the promoters of Lgals3 and Lgasl9 (g, n = 5 per group), enrichment of Ac-H3K9 on the Lgals3 and Lgals9 promoters (h, n = 4 per group), and acetylation of H3K9 (i, n = 3 per group) were compared between control and Sirt6 silenced BMMCs. j, k. Plasma levels of galectin-3 and galectin-9 in human subjects were measured by ELISA (n = 24 for lean, n = 14 for overweight, n = 6 for obese). A scatter plot was created to examine the correlation between mast cell Sirt6 protein levels and plasma galectin-3 and galectin-9 levels. Values are presented as mean ± SD. Unpaired two-tailed t test between the two groups (a, b, d, e, i), one-way ANOVA followed by Sidak’s multiple comparisons analysis (j, k) and two-way ANOVA followed by Bonferroni’s post hoc analysis were conducted for statistical analyses (f–h). Pearson correlation coefficients were calculated between continuous variables in two-sided distributions (j, k). Source data are provided as a Source Data file.
Fig 2: The recruitment and maturation of DC subsets by Ad-LGALS9/PSMA in a subcutaneous tumor model. On day 42 post tumor inoculation, immunized mice (n=5 mice per group) were euthanized, and splenocytes were isolated for flow cytometric analysis. (A) Representative flow cytometry plots showing the percentages of CD11b+CD11c+, CD8+CD11c+ and CD103+CD11c+ DC subsets in the spleen. (B–D) Quantification of the DC subsets shown in (A). (E) Representative flow cytometry plots showing the percentages of CD80+CD11c+, CD86+CD11c+ and MHC-II+CD11c+ mature DCs in the spleen. (F–H) Statistical analysis of CD80+, CD86+, and MHC-II+ DC subsets. (I, J) Serum anti-LGALS9 and anti-PSMA total IgG levels determined by ELISA on day 35 post tumor inoculation. (K) Concentrations of IFN-γ, TNF-α, IL-10, and IL-4 in splenocyte culture supernatants were assessed by ELISA after 48 hours stimulation with PSMA protein (10 µg/mL). Data were presented as the mean±SD. Statistical significance levels were set at *p<0.05, **p<0.01, ***p<0.001, and ****p<0.0001. DC, dendritic cell; IFN, interferon; IL, interleukin; MHC, major histocompatibility complex; ns, not significant; PSMA, prostate-specific membrane antigen; TNF, tumor necrosis factor.
Supplier Page from Thermo Fisher Scientific for Mouse Galectin-9 ELISA Kit