Data on lung and intestinal microbiome after air pollution exposure in ageing rats

Vincent Laiman, Yu Chun Lo, Hsin Chang Chen, Tzu Hsuen Yuan, Ta Chih Hsiao, Jen Kun Chen, Ching Wen Chang, Ting Chun Lin, Ssu Ju Li, You Yin Chen, Didik Setyo Heriyanto, Kian Fan Chung, Kai Jen Chuang, Kin Fai Ho, Jer Hwa Chang, Hsiao Chi Chuang

研究成果: 雜誌貢獻文章同行評審

1 引文 斯高帕斯(Scopus)

摘要

Air pollution has been linked to respiratory diseases, and urban air pollution can be attributed to a number of emission sources. The emitted particles and gases are the primary components of air pollution that enter the lungs during respiration. Particulate matter with an aerodynamic diameter of ≤ 2.5 µm (PM2.5) can deposit deep into the respiratory tract via inhalation and has been proposed as a causative agent for adverse respiratory health. In addition, the lung contains a diverse microbial community (microbiome) that maintains normal homeostasis and is significantly altered in a variety of pulmonary disorders. Air pollution, specifically PM2.5, has previously been shown to significantly alter the composition of the lower airway microbiome, which has been linked to decreased lung function in chronic obstructive pulmonary disease (COPD) patients. Surprisingly, the intestinal microbiome has also been implicated in the modulation of pulmonary inflammatory diseases. Therefore, dysbiosis of the lung and intestinal microbiomes pose significant negative effects on human health. This dataset describes the microbial community profiles of the lungs and intestines of ageing rats exposed to ambient unconcentrated traffic-related air pollution for three months. The whole-body exposure system was equipped with and without high efficiency particulate air (HEPA) filtration (gaseous vs. PM2.5 pollution). The data can provide valuable information on lung and intestinal microbiome changes, including that which was only found after traffic-related air pollution exposure.
原文英語
文章編號109004
期刊Data in Brief
47
DOIs
出版狀態已發佈 - 4月 2023

ASJC Scopus subject areas

  • 多學科

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