<10. IL-1β IL-6 TNF + _ TGF-β + IL-23

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1 3 ns 25 ns 2 IL-17 (pg/ml) 15 1 ns ns 5 IL-1β IL-6 TNF <1 TGF-β IL-23 Supplementary Figure 1. Human T H -17 differentiation does not require TNF. Naive T cells differentiated in the presence of TGF-β, IL-23 and different combinations of pro-inflammatory cytokines (IL-1β, IL-6 and TNF). IL-17 production was measured by ELISA after 24 h of re-stimulation with anti-cd3 anti-cd28. The comparison of pairs, with or without TNF, were statistically not significant (ns: P >.5) (Wilcoxon test). Data are represented as mean ± s.e.m. of 5 independent experiments.

2 a b Fold expansion T cells Fold expansion Tcells Infl TGF-β IL-23 IL-1β IL-6 TNF TGF-β IL-23 Supplementary Figure 2. Cytokine stimulation of naive T cells polyclonally activated does not affect their expansion. (a,b) The numbers of viable T cells after 5 days of TH differentiation in presence of anti-cd3 anti-cd28 and the indicated cytokines determined by trypan blue exclusion. Results are expressed as fold-expansion compared to the initial T cell number. Infl: IL-1β IL-6 TNF. Data represent the mean ± s.e.m. of 8 independent experiments.

3 a b 25 * Isotype Anti-TGF-β 1 IL-17 (pg/ml) ns IL-17 (pg/ml) <1 <1 T H T H -17 T H -17 No TGF-β Infl. IL-23 TGF-β (ng/ml) < Supplementary Figure 3. Exogenous, but not endogenous TGF-β is essential to promote IL-17 production in presence of inflammatory cytokines and IL-23. (a) ELISA assay for production of IL-17 from naive T cells cultured under TH (in absence of any polarizing cytokine), TH-17 (IL-1β, IL-6, TNF, IL-23 and TGF-β) or TH-17 No TGF-β (IL-1β, IL-6, TNF, IL-23) conditions. Cultures were performed in presence of 1 mg/ml of blocking anti-human TGF-β (white bars) or the corresponding isotype control (black bars). IL-17 production was measured after 24h of re-stimulation with anti-cd3 anti-cd28. (b) ELISA assay for IL-17 produced by naive T cells differentiated in presence of IL-23, pro-inflammatory cytokines and different doses of TGF-β after 24h of re-stimulation with anti-cd3 anti-cd28. Infl: IL-1β IL-6 TNF. ns: P >.5. * P <.5. Data are represented as mean ± s.e.m. of 5 independent experiments.

4 IL-17 (pg/ml) IL-17 (pg/ml) 1,2 1, IL-17 (pg/ml) Infl TGF-β IL-23 <1 <1 <1 2 Infl TGF-β IL-23 <1 <1 <1 <1 <1 2 1 Infl TGF-β IL-23 <1 <1 <1 <1 <1 <1 Supplementary Figure 4. Endogenous factors, such as serum or autocrine IFN-γ and IL-4, do not modify the cytokine requirements for human T H -17 differentiation. ELISA assay for production of IL-17 from naive T cells differentiated in Yssel s medium containing serum (left) or serum-free medium (middle) with different combinations of pro-inflammatory cytokines (IL-1β, IL-6 and TNF) TGF-β, IL-23. Antibodies blocking IFN-γ and IL-4 were added in serum free medium (right). IL-17 production was measured after 24h of re-stimulation with anti-cd3 anti-cd28. Infl: IL-1β IL-6 TNF. Data are represented as mean ± s.e.m. of 3 independent experiments.

5 2. R =,48 P = RORc/L IL-17F/L34 Supplementary Figure 5. RORc correlates with IL-17F expression. The expression of RORc and IL-17F was analyzed by RT-PCR after 24h of re-stimulation with anti-cd3 anti-cd28 in cells stimulated with different combinations of T H -17- inducing cytokines (as described in Fig. 1a,b) in 6 independent experiments. Ct values were normalized to mrna for ribosomal protein L-34 expression. Correlation between levels of IL-17F and RORc was performed using a Pearson correlation.

6 ROR / L T H mock 1/1 T H -17 1/25 1/12 IL-23R / L T H mock 1/1 1/25 T H -17 1/12 TNF / L T H mock 1/1 T H -17 1/25 1/ IFN-γ / L IFN-γ (pg/ml) T H mock 1/1 1/25 1/12 T H mock 1/1 1/25 1/12 T H -17 T H -17 Supplementary Figure 6. Selective RORc transcript inhibition does not down-regulate IL-23R, TNF and IFN-γ expression. RT-PCR for RORc, IL-23R, IFN-γ, TNF mrna transcript and IFN-γ protein produced by naive T cells cultured in serum free medium under T H or T H -17 conditions and infected with different concentrations of shrna-expressing lentiviral vectors specific for RORc or empty vector (negative control) during the first day of T H -17 differentiation. Cells were extensively washed and cultured for additional 5 days under T H or T H -17 conditions. Levels of mrna transcript and were analysed after 24h of restimulation with anti-cd3 anti-cd28. Data are represented as mean ± s.e.m. of 3 independent experiments.

7 2, 1,5 IL-21 (pg/ml) 1, 5 Infl. TGF-β IL-23 (ng/ml) Supplementary Figure 7. IL-21 production by T H -17 cells depends on IL-23 in a dose-dependent manner. ELISA assay for production of IL-21 by naive T cells differentiated in presence of TGF-β, pro-inflammatory cytokines and different concentrations of IL-23; IL-21 was measured after 24 h of re-stimulation with anti-cd3 anti-cd28. Infl: IL-1β IL-6 TNF. Data represent the mean ± s.e.m. of 3 independent experiments.

8 ISOTYPE CD45RO CD45RA % CD45RA % % of Max CD3 CD Fluorescence intensity Supplementary Figure 8. Purity of human naive T cells. Flow cytometry of naive CD4 T cells after purification and staining with anti-cd3-fitc, anti-cd4-apc, anti-cd45ra-pe and anti-cd45ro-fitc. Percentage of CD3 CD45RA cells was calculated gating on total viable cells. Percentage of CD4 cells was calculated gating on CD3 CD45RA cells. Histogram shows total viable cells stained for CD45RO overlaid with their isotype. Results are from one representative naive T cells purification.

9 Supplementary Methods Principal Component Analysis 1/ Data input: The data are represented with the following X matrix: T H T H1 T H2 No IL-1β No IL-6 No TNF No TGF-β No IL-23 IL-4 IL-5 IL-6 IL-1 IL-13 IL-17 IL-21 IL-22 TNF IFN-γ Each column corresponds to a cytokine. Each row corresponds to a condition. Inside a cell, the value corresponds to the average value over the six donors. Each column of the X matrix has been centered on the mean over the 9 conditions 2/ Computation of the principal components The first two principal components are computing according to the following procedure: the first component P1 is a linear combination of the X columns such that its variance is maximal to have the best representation of the data. The mathematical formulation is the following: P1 = Xw under the constraints w =1 and Var(P1) is maximal the second component P2 is a linear combination of the X columns and is orthogonal to the first component P1. The variance of P2 is maximal under the orthogonality constraint with P1. The mathematical formulation is the following: P2 = Xz under the constraints z =1, P2 is orthogonal to P1 and Var(P2) is maximal 3/ Correlation of the cytokines with the principal components

10 A red arrow in the plot represents the correlation between one cytokine and the principal components. For the cytokine i, the computation is done as follows: x=cor(p1,x i ) y=cor(p2,x i ) where X i is the i-th colomn of X Each cytokine is represented by its coordinates (x,y). Notations: is the euclidean norm. Var is the variance of the vector. Cor is the correlation between two vectors.