Fig 2: Antibody Responses and Proliferation Capabilities of SARS-CoV-2-Specific T Cells in Convalescent COVID-19(A) Representative flow cytometry plots showing the proliferation (CTV−) and functionality (IFN-γ+) of SARS-CoV-2-specific T cells from a convalescent individual (group MC) after stimulation with overlapping peptides spanning the immunogenic domains of the SARS-CoV-2 S, M, and N proteins. Numbers indicate percentages in the drawn gates.(B) and (C) Dot plots summarizing the frequencies of CTV− IFN-γ+ SARS-CoV-2-specific CD4+ (B) and CD8+ T cells (C) by group and specificity. Each dot represents one donor. The dotted line indicates the cutoff for positive responses. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001. Kruskal-Wallis rank-sum test with Dunn’s post hoc test for multiple comparisons.(D) Dot plots comparing the frequencies of CTV− IFN-γ+ SARS-CoV-2-specific CD4+ versus CD8+ T cells by group and specificity. Each dot represents one donor. Data are shown as median ± IQR. Key as in (B) and (C). ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001. Paired t test or Wilcoxon signed-rank test.(E) Left: representative flow cytometry plots showing the production of IFN-γ and TNF among CTV− virus-specific CD4+ (top) and CD8+ T cells (bottom) from a convalescent individual (group MC). Numbers indicate percentages in the drawn gates. Right: heatmaps summarizing the functional profiles of CTV− IFN-γ+ virus-specific CD4+ (top) and CD8+ T cells (bottom). Data are shown as mean frequencies (key).(F) Dot plots summarizing the frequencies of CTV− IFN-γ+ SARS-CoV-2-specific CD4+ and CD8+ T cells by group, serostatus, and specificity. Each dot represents one donor. The dotted line indicates the cutoff for positive responses. Key as in (B) and (C). ∗∗∗p < 0.001. Mann-Whitney U test.(G) Left: bar graph summarizing percent seropositivity by group. Right: bar graph summarizing the percentage of individuals in each group with detectable T cell responses directed against the internal (N) and surface antigens (M and/or S) of SARS-CoV-2.

Fig 3: IL-33 and TNFR2 inhibition is a novel therapeutic avenue for DD.(A) Bar plot showing COL1A1, ACTA2, and ST2 gene expression by DD myofibroblasts treated with neutralizing anti–IL-33 antibody compared to isotype control (n = 8 DD patients, mean ± SEM). (B) Western blot analysis showing α-SMA protein expression by DD myofibroblasts following treatment with neutralizing anti–IL-33 antibody compared to isotype control. (C) Bar plot showing COL1A1, ACTA2, IL33, and ST2 gene expression by DD myofibroblasts following treatment with neutralizing anti-TNFR1, anti-TNFR2, and anti-TNF antibodies (n = 5 DD patients, mean ± SEM). (D) Bar plot showing COL1A1 and ACTA2 gene expression following siRNA-mediated knockdown for TNFRSF1A, TNFRSF1B, ST2, or combination treatment (n = 5 DD patients, mean ± SEM). (E) Western blot analysis of α-SMA protein expression by DD myofibroblasts following siRNA knockdown of TNFRSF1A, TNFRSF1B, and ST2. (F) Heatmaps of cellular traction force (in pascals) in DD myofibroblasts following treatment with indicated neutralizing antibodies. (G) Bar plots showing average traction force following treatment with anti-TNF, anti-TNFR2, anti–IL-33 antibodies, or combination therapy (n = 5 DD patients, mean ± SEM). Gene expression changes (mRNA fold induction) were calculated relative to GAPDH using the ΔΔ cycle threshold (ΔΔCt) method and normalized to isotype control at the corresponding concentration. *P < 0.05, **P < 0.01, ***P < 0.001, ***P < 0.0001.

Fig 4: Stromal–immune cell crosstalk mediated by IL-33 and TNF.(A) Bar plot of enzyme-linked immunosorbent assay (ELISA) showing TNF secretion in mast cell lines (HMC1.1, HMC1.2, and LAD2) following stimulation with increasing doses of rIL-33 (n = 3, mean ± SEM). (B) Bar plots of ELISA showing TNF secretion by human monocytes and macrophages following stimulation with increasing doses of rIL-33 (n = 3 independent donors, mean ± SEM). (C) Representative confocal images of immunofluorescence for ST2 expression on mast cells (tryptase) and macrophages (CD68) in DD nodules. Scale bars, 10 μm. (D) Conditional density plot of single-cell RNA-seq dataset showing IL33 expression by labeled cell types. Density is Gaussian kernel density estimate (n = 6 DD patients, k = 7332 cells). (E) Bar plots showing IL33 and ST2 gene expression by PF-D and NPF-D dermal fibroblasts from DD patients following stimulation with rTNF at 2, 8, and 24 hours (n = 3 DD patients, mean ± SEM). (F) Western blot analysis showing IL-33 and ST2 protein expression by PF-D and nonpalmar NPF-D dermal fibroblasts from DD patients following stimulation with rTNF(0.1 ng/ml) for 24 hours. *P < 0.05, **P < 0.01, ***P < 0.001. ns, not significant.

Fig 5: Differential TRM Phenotype after i.v. and s.c. Vaccine Administration Correlates with IL-10 ProductionRhesus macaques were immunized with Env peptides, anti-CD40Ab, and poly(IC:LC) (n = 4/group). BAL samples were stimulated overnight with an immunizing peptide pool to recall total memory Ag-specific T cells (CCR7+CD45RA+ naive T cells excluded, producing interferon-? (IFN-?), IL-2, or tumor necrosis factor [TNF]).(A–C) Frequency of Ag-specific CD8 or CD4 T cells 3 weeks (A) and 9 months (C) post-immunization. (B) Proportion of multifunctional T cells at 3 weeks.(D) Frequency of CD103+CD69+ TRMs of Ag-specific CD8 T cells.(E) MFI of CD103 expression on Ag-specific TRMs at 3 weeks.(F) IL-10 levels in plasma.(G) IL-10 levels in plasma after i.v. administration of Poly IC:LC, anti-CD40, or the combination (n = 2/group).(H) Correlation of frequency of TRM of Ag-specific CD8 T cells in BAL at 3 weeks (y axis) with IL-10 (pg/mL) in plasma at 6 h (x axis). Each data point represents a separate animal (mean ± SEM).Significance was tested using an unpaired Student’s t test (A–E), one-way ANOVA (F), or Spearman’s test (H). See also Figure S2.