Supplementary Figure 1: Wild-type and Ifnar1−/− mice recover from infection with a low dose of IAV equally well. | Nature Immunology

Supplementary Figure 1: Wild-type and Ifnar1−/− mice recover from infection with a low dose of IAV equally well.

From: Type I interferon restricts type 2 immunopathology through the regulation of group 2 innate lymphoid cells

Supplementary Figure 1

(a,b) WT and Ifnar1-/- mice (five age- and sex-matched animals per group) were either mock treated with PBS as a control or infected with 20 PFU of influenza virus. (a) Survival and (b) body weight loss were monitored throughout the course of infection. (c) Pulmonary expression of the non-structural 1 (Ns1) gene of influenza was determined by qRT-PCR 5, 10 and 15 days post infection. The bars represent the mean ± standard deviation of each cohort. Data are representative of two independent experiments; n.d., not detectable. (d-g) WT and Ifnar1-/- mice (three to seven age- and sex-matched animals per group) were either mock treated with PBS or infected intranasally with 20 PFU of influenza virus. Five days post infection lungs were perfused with PBS and the pulmonary expression levels of (d) IL1b, (e) Tnf and (f) Ccl2 were determined by qRT-PCR, and (g) the numbers of inflammatory monocytes were determined by flow cytometry. Data are representative of three independent experiments. The bars represent the mean ± standard deviation of triplicates of each cohort. The asterisks indicate statistically significant differences (*, p ≤ 0.05; **, p ≤ 0.01; ***, p ≤ 0.001). (h) WT and Ifnar1-/- mice (three to seven age- and sex-matched animals per group) were either mock treated with PBS or infected intranasally with 20 PFU of influenza virus. At indicated time points post infection lungs were perfused with PBS, homogenized, and the IL-33 content was determined by ELISA. Data are representative of two independent experiments. The bars represent the mean ± standard deviation of triplicates of each cohort. One-way ANOVA test including the Bonferroni’s multiple comparison was used to analyze statistical significance.

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