The alarmin IL-33 exacerbates pulmonary inflammation and immune dysfunction in SARS-CoV-2 infection. Yuejin Liang et al.

Description

In this study, our hypothesis is that the alarmin IL-33 plays a pathogenic role in SARS-CoV-2 infection. In these raw data, we measured IL-33 levels in human nasal swabs and plasma (Fig. 1A). Next, we established an SARS-CoV-2 mouse model by using mouse-adapted virus. We analyzed the transcript levels of inflammatory markers in the lungs of infected mice on day 2 and 4 post-infection (Fig. 1B) as well as the cytokine/chemokine levels in mouse serum (Fig. 1C). In Fig. 1D, we assessed both transcript and protein levels of IL-33 in lung tissues of infected mice. In Fig. 2, mice were pretreated with rIL-33, followed by SARS-CoV-2 infection (Fig. 2A). Then, we evaluated bodyweight changes, viral burden, lung histology and inflammation (Fig. 2B-E). We further explored the role of IL-33 by using deficient mice. In Fig. 3, we infected WT and IL-33 KO mice, and evaluated bodyweight changes, viral burden, lung histology, immune cell infiltration and cytokine/chemokine in the sera (Fig. 3A-E). Finally, we performed bulk RNAseq assay for the lung tissues and compared the key signaling pathways and IPA network between WT and KO mice (Fig. 4). Uninfected mouse samples were also used as a control. The RNAseq data presented herein were deposited in NCBI’s Gene Expression Omnibus, accessible through GEO Series accession number GSE247370. Fig. S1 is the gating strategy of flow cytomtry. Fig. S2 shows the viral burden and inflammatory genes in delta strain-infected K18-hACE2 mice. Fig. S3 included the raw data of Bioplex for Fig. 1C. Fig. S4 shows the principal component axes and sample correlation heatmap of RNAseq data. Fig. 5 shows the hallmark analysis of RNAseq data. Rosalind platform was used to analyzed the RNAseq data for Fig. S4 and S5. Fig S6-S8 represent the IPA analysis of RNAseq data (KO vs. WT).

Institutions

Categories

Funding

Licence