Decoding the IGF1 signaling gene regulatory network behind alveologenesis from a mouse model of bronchopulmonary dysplasia
- University of Southern California, United States
- Jiangsu Provincial Hospital of Traditional Chinese Medicine, China
- University of California, San Diego, United States
Abstract
Lung development is precisely controlled by underlying Gene Regulatory Networks (GRN). Disruption of genes in the network can interrupt normal development and cause diseases such as bronchopulmonary dysplasia (BPD)–a chronic lung disease in preterm infants with morbid and sometimes lethal consequences characterized by lung immaturity and reduced alveolarization. Here, we generated a transgenic mouse exhibiting a moderate severity BPD phenotype by blocking IGF1 signaling in secondary crest myofibroblasts (SCMF) at the onset of alveologenesis. Using approaches mirroring the construction of the model GRN in sea urchin’s development, we constructed the IGF1 signaling network underlying alveologenesis using this mouse model that phenocopies BPD. The constructed GRN, consisting of 43 genes, provides a bird’s-eye view of how the genes downstream of IGF1 are regulatorily connected. The GRN also reveals a mechanistic interpretation of how the effects of IGF1 signaling are transduced within SCMF from its specification genes to its effector genes and then from SCMF to its neighboring alveolar epithelial cells with WNT5A and FGF10 signaling as the bridge. Consistently, blocking WNT5A signaling in mice phenocopies BPD as inferred by the network. A comparative study on human samples suggests that a GRN of similar components and wiring underlies human BPD. Our network view of alveologenesis is transforming our perspective to understand and treat BPD. This new perspective calls for the construction of the full signaling GRN underlying alveologenesis, upon which targeted therapies for this neonatal chronic lung disease can be viably developed.
Data availability
Sequencing data generated for this study have been deposited in GEO under the accession code GSE182886.All other data generated or analyzed during this study are included in the manuscript and supporting files.Source Data files have been provided in Figure 3-Source Data 1&2, Figure 4-Source Data 1&2, and Figure 6-Source Data 1.An online repository of the network and the data presented in this paper has been made available to the public at https://sites.google.com/view/the-alveologenesis-grn/home.
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Decoding A Gene Regulatory Network Behind Bronchopulmonary DysplasiaNCBI Gene Expression Omnibus, GSE182886.
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The single cell RNA seq of pulmonary alveolar epithelial cellsNCBI Gene Expression Omnibus, GSE106960.
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A Single Cell Atlas of Alveolar DevelopmentNCBI Gene Expression Omnibus, GSEGSE165063.
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Age-determined expression of priming protease TMPRSS2 and localization of SARS-CoV-2 in lung epitheliumNCBI Gene Expression Omnibus, GSEGSE160876.
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The genomic, epigenomic and biophysical cues controlling the emergence of the gas exchange niche in the lungNCBI Gene Expression Omnibus, GSE149563.
Article and author information
Author details
Funding
National Heart, Lung, and Blood Institute (5R01HL144932-04)
- Changgong Li
National Heart, Lung, and Blood Institute (5R01HL143059-04)
- Parviz Minoo
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: BPD and non-BPD postnatal human lung tissues were provided by the International Institute for the Advancement of Medicine and the National Disease Research Interchange, and were classified exempt from human subject regulations per the University of Rochester Research Subjects Review Board protocol (RSRB00056775).
Copyright
© 2022, Gao et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Decoding the IGF1 signaling gene regulatory network behind alveologenesis from a mouse model of bronchopulmonary dysplasia
eLife 11:e77522.
https://doi.org/10.7554/eLife.77522
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