Hina Agraval, Junfeng Gao, Niccolette Schaunaman, Huang Hua, R William Vandivier, Mari Numata, Brian J Day, Hong Wei Chu
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引用次数: 0
Abstract
Cigarette smoking is a primary cause of chronic obstructive pulmonary disease (COPD). Smokers have a higher risk of influenza-related mortality, but the underlying mechanisms remain unclear. Toll-interacting protein (TOLLIP), an immune regulator, inhibits influenza A virus (IAV) infection, but its regulation in COPD has not been well understood. We sought to determine if cigarette smoke (CS) exposure down-regulates TOLLIP expression via epigenetic mechanisms, including histone methylation. TOLLIP and histone-methylating enzymes enhancer of zeste homolog 1/2 (EZH1/2) were measured in healthy and COPD human lungs, human airway epithelial cells cultured under submerged and air-liquid interface conditions, and precision-cut lung slices (PCLSs) exposed to CS with or without IAV infection. EZH1/2 siRNA and inhibitors were used to investigate their effects on TOLLIP expression. In patients with COPD, TOLLIP levels decreased, whereas EZH1 and EZH2 expression increased. Repeated CS exposure decreased TOLLIP and increased EZH1, EZH2, H3K27me3, and IAV levels in human airway epithelial cells and PCLSs. EZH1/2 siRNA or their pharmacologic inhibitor valemetostat tosylate in part restored TOLLIP and reduced IAV levels in CS-exposed airway epithelial cells and PCLSs. Our findings suggest that repeated CS exposure during viral infection reduced TOLLIP levels and increased viral load in part through EZH1/EZH2-H3K27me3-mediated epigenetic mechanisms. Targeting EZH1 and EZH2 may serve as one of the potential therapeutic strategies to restore TOLLIP expression and host defense against viral infections in patients with COPD.
期刊介绍:
The American Journal of Pathology, official journal of the American Society for Investigative Pathology, published by Elsevier, Inc., seeks high-quality original research reports, reviews, and commentaries related to the molecular and cellular basis of disease. The editors will consider basic, translational, and clinical investigations that directly address mechanisms of pathogenesis or provide a foundation for future mechanistic inquiries. Examples of such foundational investigations include data mining, identification of biomarkers, molecular pathology, and discovery research. Foundational studies that incorporate deep learning and artificial intelligence are also welcome. High priority is given to studies of human disease and relevant experimental models using molecular, cellular, and organismal approaches.