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Updated: Jan 31, 2026

TMT Sample Preparation for Proteomics Facility Submission and Subsequent Data Analysis
Published on: June 8, 2020
TMT-Based Quantitative Proteomics Analysis Reveals Airborne PM2.5-Induced Pulmonary Fibrosis
Shan Liu1,2, Wei Zhang3, Fang Zhang4
1Laboratory of Environment and Health, College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China. liushan14@mails.ucas.ac.cn.
Abstract:
Epidemiological and experimental studies have documented that long-term exposure to fine particulate matter (PM2.5) increases the risk of respiratory diseases. However, the details of the underlying mechanism remain unclear. In this study, male C57BL/6 mice were exposed to ambient PM2.5 (mean daily concentration ~64 µg/m³) for 12 weeks through a "real-world" airborne PM2.5 exposure system. We found that PM2.5 caused severe lung injury in mice as evidenced by histopathological examination. Then, tandem mass tag (TMT) labeling quantitative proteomic technology was performed to analyze protein expression profiling in the lungs from control and PM2.5-exposed mice. A total of 32 proteins were differentially expressed in PM2.5-exposed lungs versus the controls. Among these proteins, 24 and 8 proteins were up- and down-regulated, respectively. Gene ontology analysis indicated that PM2.5 exerts a toxic effect on lungs by affecting multiple biological processes, including oxidoreductase activity, receptor activity, and protein binding. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that extracellular matrix (ECM)⁻receptor interaction, phagosome, small cell lung cancer, and phosphatidylinositol 3-kinase(PI3K)-protein kinase B (Akt) signaling pathways contribute to PM2.5-induced pulmonary fibrosis. Taken together, these results provide a comprehensive proteomics analysis to further understanding of the molecular mechanisms underlying PM2.5-elicited pulmonary disease.
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