Computational protocol: Variability in Tuberculosis Granuloma T Cell Responses Exists, but a Balance of Pro- and Anti-inflammatory Cytokines Is Associated with Sterilization

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[…] Flow cytometry was performed on a random sampling of granulomas (4–12 granulomas per animal). Although about 300 granulomas were initially analyzed, a cutoff of total number of T cells by flow cytometry was used to avoid introducing error due to analysis of very small T cell populations. Thus, a total of 149 granulomas from 34 animals were fully analyzed for this study. Single cell suspension of individual lung granulomas was stimulated with peptide pools of Mtb specific antigens ESAT-6 and CFP-10 (10μg/ml of every peptide) in the presence of Brefeldin A (Golgiplug: BD biosciences) for 3.5 hours at 37°C with 5% CO2. Positive control included stimulation with phorbol dibutyrate (PDBu) and ionomycin and an isotype control were included whenever additional cells were available. The cells were then stained for Viability marker (Invitrogen), surface and intracellular cytokine markers. Flow cytometry for cell surface markers for T cells included CD3 (clone SP34-2; BD Pharmingen), CD4 (clone L200; BD Horizon) and CD8 (clone SK1; BD biosciences). In addition, B cell marker CD20 (clone 2H7; eBioscience) and macrophage marker CD11b (clone Mac-1; BD Pharmingen) were included as the dump channel. Intracellular cytokine staining panel included pro-inflammatory cytokines: T-1 [IFN-γ (clone B27), IL-2 (clone MQ1-17H12), TNF (clone MAB11)], T-17 [IL-17 (clone eBio64CAP17) and anti-inflammatory (Regulatory) IL-10 (clone JES3-9D7) markers. In a subset of granulomas, exhaustion markers PD-1 (clone EH12.2H7, Biolegend) and CTLA-4 (Clone BN13, BD Pharmigen) were used to stain a subset of granulomas. Data acquisition was performed using a LSR II (BD) and analyzed using FlowJo Software v.9.7 (Treestar Inc, Ashland, OR). Supplementary figure 8 () describes the gating strategies employed for analysis. Supplementary figure 9 () provides detailed description of gating strategies in comparison with PBMC for clarity. Cytokine data presented in this manuscript are gated on CD3+ T cells. [...] D’Agostino & Pearson Omibus normality test was performed, on all data described in this manuscript. Since the data were not normally distributed, nonparametric t test was used when comparing two groups (Mann-Whitney test). Kruskal-Wallis test was used to compare more than two groups with post hoc analysis Dunn’s multiple test comparisons. P values ≤0.05 were considered significant. Statistical analysis was performed using GraphPad Prism v6 (GraphPad Software, San Diego, CA). For multivariate analysis, JMP Pro 10 (SAS) package was used. Nonparametric Spearman’s ρ was calculated for correlations (multivariate analysis) using JMP Pro v10 (SAS Institute Inc.).Frequency of cytokine co-expression and sterilization in granulomas was implemented using Matlab (Mathworks, Natick, MA). Briefly, for each variable of T cell cytokine (IFN-γ, IL-2, TNF, IL-17 and IL-10) dataset, continuous values for each individual granuloma were binned into one of four categories depending on quartile distribution (bins 1, 2, 3, or 4) (). We counted the number of times a particular combination of the variables occur and summarized these in a 4×4 co-occurrence matrices spanning all four bins comparing in a pairwise fashion across all the potential combinations. For each of the pairwise combination, the frequency of that occurrence is plotted and summarized in a heat map. Similarly, sterilization frequency matrices were constructed calculating the number of times sterilization occurred in a given combination of bins (number of sterilizing granulomas with a variable A at level X and variable B at level Y out of the total number of granulomas with variable A at level X and variable B at level Y). Each comparison was plotted as a heat map. For this analysis granulomas from animals with established clinical status (active disease or latent infection) were used (N = 113).Euclidean distances were calculated in Microsoft Excel (for mac 2011), by utilizing the formula (GIFNγ−BIFNγ)2+(GIL2−BIL2)2+(GTNF−BTNF)2+(GIL17−BIL17)2 where suffix “G” represents T cell cytokine response from the granuloma (local) and “B” represents those from blood (systemic). Datasets for which complete cytokine data were available for individual granulomas (N = 120 granulomas) and blood (PBMC) (N = 28 animals) were used for this analysis. Distances were calculated for each granuloma with the T cell cytokine response of granuloma and blood of that animal. Average distances were then obtained by averaging the granuloma to blood distance for all the granulomas from a particular animal […]

Pipeline specifications

Software tools FlowJo, JMP Pro
Applications Miscellaneous, Flow cytometry
Organisms Mycobacterium tuberculosis, Macaca fascicularis, Homo sapiens, Bacteria
Diseases Infection, Infertility, Tuberculosis, Mastocytosis, Systemic