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Pharmacological and genetic reappraisals of protease and oxidative stress pathways in a mouse model of obstructive lung diseases.

ABSTRACT: Protease-antiprotease imbalance and oxidative stress are considered to be major pathophysiological hallmarks of severe obstructive lung diseases including chronic obstructive pulmonary disease (COPD) and cystic fibrosis (CF), but limited information is available on their direct roles in the regulation of pulmonary phenotypes. Here, we utilized βENaC-transgenic (Tg) mice, the previously established mouse model of severe obstructive lung diseases, to produce lower-mortality but pathophysiologically highly useful mouse model by backcrossing the original line with C57/BL6J mice. C57/BL6J-βENaC-Tg mice showed higher survival rates and key pulmonary abnormalities of COPD/CF, including mucous hypersecretion, inflammatory and emphysematous phenotypes and pulmonary dysfunction. DNA microarray analysis confirmed that protease- and oxidative stress-dependent pathways are activated in the lung tissue of C57/BL6J-βENaC-Tg mice. Treatments of C57/BL6J-βENaC-Tg mice with a serine protease inhibitor ONO-3403, a derivative of camostat methylate (CM), but not CM, and with an anti-oxidant N-acetylcystein significantly improved pulmonary emphysema and dysfunction. Moreover, depletion of a murine endogenous antioxidant vitamin C (VC), by genetic disruption of VC-synthesizing enzyme SMP30 in C57/BL6J-βENaC-Tg mice, exaggerated pulmonary phenotypes. Thus, these assessments clarified that protease-antiprotease imbalance and oxidative stress are critical pathways that exacerbate the pulmonary phenotypes of C57/BL6J-βENaC-Tg mice, consistent with the characteristics of human COPD/CF.

SUBMITTER: Shuto T

PROVIDER: S-EPMC5159865 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Pharmacological and genetic reappraisals of protease and oxidative stress pathways in a mouse model of obstructive lung diseases.

Shuto Tsuyoshi T Kamei Shunsuke S Nohara Hirofumi H Fujikawa Haruka H Tasaki Yukihiro Y Sugahara Takuya T Ono Tomomi T Matsumoto Chizuru C Sakaguchi Yuki Y Maruta Kasumi K Nakashima Ryunosuke R Kawakami Taisei T Suico Mary Ann MA Kondo Yoshitaka Y Ishigami Akihito A Takeo Toru T Tanaka Ken-Ichiro KI Watanabe Hiroshi H Nakagata Naomi N Uchimura Kohei K Kitamura Kenichiro K Li Jian-Dong JD Kai Hirofumi H

Scientific reports 20161216

Protease-antiprotease imbalance and oxidative stress are considered to be major pathophysiological hallmarks of severe obstructive lung diseases including chronic obstructive pulmonary disease (COPD) and cystic fibrosis (CF), but limited information is available on their direct roles in the regulation of pulmonary phenotypes. Here, we utilized βENaC-transgenic (Tg) mice, the previously established mouse model of severe obstructive lung diseases, to produce lower-mortality but pathophysiologicall ...[more]

PMID: 27982104

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Project description:A variety of cardiovascular, neurological, and neoplastic conditions have been associated with oxidative stress, i.e., conditions under which levels of reactive oxygen species (ROS) are elevated over significant periods. Nuclear factor erythroid 2-related factor (Nrf2) regulates the transcription of several gene products involved in the protective response to oxidative stress. The transcriptional regulatory and signaling relationships linking gene products involved in the response to oxidative stress are, currently, only partially resolved. Microarray data constitute RNA abundance measures representing gene expression patterns. In some cases, these patterns can identify the molecular interactions of gene products. They can be, in effect, proxies for protein-protein and protein-DNA interactions. Traditional techniques used for clustering coregulated genes on high-throughput gene arrays are rarely capable of distinguishing between direct transcriptional regulatory interactions and indirect ones. In this study, newly developed information-theoretic algorithms that employ the concept of mutual information were used: the Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNE), and Context Likelihood of Relatedness (CLR). These algorithms captured dependencies in the gene expression profiles of the mouse lung, allowing the regulatory effect of Nrf2 in response to oxidative stress to be determined more precisely. In addition, a characterization of promoter sequences of Nrf2 regulatory targets was conducted using a Support Vector Machine classification algorithm to corroborate ARACNE and CLR predictions. Inferred networks were analyzed, compared, and integrated using the Collective Analysis of Biological Interaction Networks (CABIN) plug-in of Cytoscape. Using the two network inference algorithms and one machine learning algorithm, a number of both previously known and novel targets of Nrf2 transcriptional activation were identified. Genes predicted as novel Nrf2 targets include Atf1, Srxn1, Prnp, Sod2, Als2, Nfkbib, and Ppp1r15b. Furthermore, microarray and quantitative RT-PCR experiments following cigarette-smoke-induced oxidative stress in Nrf2(+/+) and Nrf2(-/-) mouse lung affirmed many of the predictions made. Several new potential feed-forward regulatory loops involving Nrf2, Nqo1, Srxn1, Prdx1, Als2, Atf1, Sod1, and Park7 were predicted. This work shows the promise of network inference algorithms operating on high-throughput gene expression data in identifying transcriptional regulatory and other signaling relationships implicated in mammalian disease.

Dataset Information

Pharmacological and genetic reappraisals of protease and oxidative stress pathways in a mouse model of obstructive lung diseases.

Publications

Pharmacological and genetic reappraisals of protease and oxidative stress pathways in a mouse model of obstructive lung diseases.

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