Transcriptome network analysis identifies protective role of the LXR/SREBP-1c axis in murine pulmonary fibrosis
Shigeyuki Shichino, Satoshi Ueha, Shinichi Hashimoto, Mikiya Otsuji, Jun Abe, Tatsuya Tsukui, Shungo Deshimaru, Takuya Nakajima, Mizuha Kosugi-Kanaya, Francis H.W. Shand, Yutaka Inagaki, Hitoshi Shimano, Kouji Matsushima
Shigeyuki Shichino, Satoshi Ueha, Shinichi Hashimoto, Mikiya Otsuji, Jun Abe, Tatsuya Tsukui, Shungo Deshimaru, Takuya Nakajima, Mizuha Kosugi-Kanaya, Francis H.W. Shand, Yutaka Inagaki, Hitoshi Shimano, Kouji Matsushima
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Research Article Inflammation Pulmonology

Transcriptome network analysis identifies protective role of the LXR/SREBP-1c axis in murine pulmonary fibrosis

Abstract

Pulmonary fibrosis (PF) is an intractable disorder with a poor prognosis. Although lung fibroblasts play a central role in PF, the key regulatory molecules involved in this process remain unknown. To address this issue, we performed a time-course transcriptome analysis on lung fibroblasts of bleomycin- and silica-treated murine lungs. We found gene modules whose expression kinetics were associated with the progression of PF and human idiopathic PF (IPF). Upstream analysis of a transcriptome network helped in identifying 55 hub transcription factors that were highly connected with PF-associated gene modules. Of these hubs, the expression of Srebf1 decreased in line with progression of PF and human IPF, suggesting its suppressive role in fibroblast activation. Consistently, adoptive transfer and genetic modification studies revealed that the hub transcription factor SREBP-1c suppressed PF-associated gene expression changes in lung fibroblasts and PF pathology in vivo. Moreover, therapeutic pharmacological activation of LXR, an SREBP-1c activator, suppressed the Srebf1-dependent activation of fibroblasts and progression of PF. Thus, SREBP-1c acts as a protective hub of lung fibroblast activation in PF. Collectively, the findings of the current study may prove to be valuable in the development of effective therapeutic strategies for PF.

Authors

Shigeyuki Shichino, Satoshi Ueha, Shinichi Hashimoto, Mikiya Otsuji, Jun Abe, Tatsuya Tsukui, Shungo Deshimaru, Takuya Nakajima, Mizuha Kosugi-Kanaya, Francis H.W. Shand, Yutaka Inagaki, Hitoshi Shimano, Kouji Matsushima

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Figure 1

Transcriptomic landscape of lung fibroblasts in bleomycin- and silica-induced pulmonary fibrosis.

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Transcriptomic landscape of lung fibroblasts in bleomycin- and silica-in...
(A) Experimental scheme. Lungs were collected from untreated, bleomycin-treated, and silica-treated Col-GFP mice at multiple time points. Lineage–Col-GFP+ lung fibroblasts were purified by cell sorting. Whole transcripts of purified fibroblasts were amplified, and transcriptome analysis was performed by the 3′ SAGE-seq method (n = 3 for each time point). (B) Gating scheme for lung fibroblasts and purity of fibroblasts after cell sorting. Representative plots of n = 7 from 2 independent experiments of the silica model data at 14 dpi are shown. (C) t-Distributed stochastic neighbor embedding (t-SNE) plot of 3′ SAGE-seq data of activated lung fibroblasts. (D) Coexpression network plot of differentially expressed 3,635 genes in activated lung fibroblasts. (E) Heatmap representation of eigengene kinetics of gene modules identified by the weighted coexpression network analysis. Each column represents group and time point, whereas each row represents an individual eigengene. Module size is shown on the right side of the heatmap. (F) Hierarchical clustering of eigengenes. Grouping threshold is shown as red dashed line. Module group is shown on the right side of the correlation heatmap. (G) Heatmap representation of the genes in module groups G2 and G5. Mean Z score of module groups is shown on the bottom of the heatmap. (H) Gene set enrichment analysis of fibrosis-associated module groups for the samples from IPF-derived lung fibroblasts (GSE17978) and idiopathic pulmonary fibrosis whole lungs (E-GEOD-47460). Enrichment plots for module groups G2-1, G2-2, G5-1, and G5-2 are shown. Black bars represent gene positions in the ranked gene list. NES, normalized enrichment score. P values and FDRs were determined using a permutation test–based method implemented in the GSEA software. Col-GFP mice, Col1a2-GFP reporter mice; SAGE, serial analysis of gene expression; FSC, forward scatter; SSC, side scatter; PI, propidium iodide; BLM, bleomycin model; SiO2, silica model; UT, untreated;IPF, idiopathic pulmonary fibrosis; NES, normalized enrichment score.