The isolated granulocytes were 95% pure and contained 1–3% CD3+ T cells. Granulocytes (2 × 106/ml) were stimulated with

PMA/ionomycin or Toll-like receptor (TLR) ligands [10–100 µg/ml zymosan, 1–10 µg/ml poly I:C, 0·1–1 µg/ml lipopolysaccharide BIBW2992 (LPS) or 1 mm CpG] or cytokine cocktails (10 ng/ml IL-1β+ 20 ng/ml IL-23, 4 ng/ml TGF-β+ 10 ng/ml IL-6 + 20 ng/ml IL-23 or 25 ng/ml IL-17) for 24 h in 24-well plates. Cell pellets were collected for RNA extraction. RNA was extracted from 2 × 106 granulocytes by using RNeasy Kit (Qiagen) as described by the manufacturer. RNA was reverse-transcribed to cDNA using MultiScribe RT (Applied Biosystems, Streetsville, Ontario, Canada). cDNA was then amplified using TaqMan Universal PCR Master Mix (Applied Biosystems). Primers for IL-17 (product number: Hs99999082_m1),

IL-22 (Hs00220924_m1) and β-actin (Hs99999903_m1) genes were purchased from GS-1101 order Applied Biosystems. The fold increase in signal relative to the controls was determined with the change in cycling threshold (ΔCTsample − ΔCTcontrol) and was calculated as follows: R = 2 − (Ctsample − Ctcontrol), where R is relative expression and Ct is cycle threshold. β-actin was used as an endogenous control. Statistical analysis was performed using Prism software (GraphPad) version 2.7.2. Two-tailed P-values were calculated using Wilcoxon test, Fisher’s exact test and non-parametric one-way analysis of variance (anova), as indicated in various figure legends. Because the data are not distributed normally, the non-parametric

Kruskal–Wallis test with Dunn’s post-test was performed. The receiver operating characteristic (ROC) cut-off values were generated using sensitivity and specificity values with GraphPad prism software. The area under the curve of a ROC curve is related closely to the Mann–Whitney or Wilcoxon’s rank test, which test whether positives are ranked higher than the negatives. As the data are not distributed normally (non-Gaussian), a non-parametric Fisher’s exact test was used to generate a ROC curve to create a cut-off in order to identify TB patients based on the presence of IL-17, IL-22 and IFN-γ-positive CD4+ cells compared to the healthy controls. The circulating levels of IFN-γ-, IL-17- and IL-22-expressing Arachidonate 15-lipoxygenase CD4+ T cells in whole blood were determined by intracellular cytokine assay. The frequencies of IFN-γ-, IL-17- and IL-22-producing CD4+ T cells were found to be lower in active TB patients compared to healthy controls and latent TB subjects (Fig. 1). The gating strategy employed for the identification of IL-17-, IL-22- and IFN-γ-expressing cells is shown (Fig. S1). Due to high variability, the data were analysed using cut-off values. The ROC curve was used to generate the cut-off values maximizing the sensitivity and specificity for predicting the true positives and true negatives within the healthy, latent TB and active TB patient group.