SARS-CoV-2 and its induced COVID-19 remains as a global health calamity. Severe symptoms and high mortality, caused by cytokine storm and acute respiratory distress syndrome in the lower respiratory airway, are always associated with elderly individuals and those with comorbidities; whereas mild or moderate COVID-19 patients have limited upper respiratory flu-like symptoms. There is an urgent need to investigate SARS-CoV-2 and other coronaviruses replication and immune responses in human respiratory systems. The human reconstituted airway epithelial air-liquid interface (ALI) models are the most physiologically relevant model for the investigation of coronavirus infection and virus-triggered innate immune signatures. We established ALI models representing both the upper and the lower respiratory airway to characterize the coronavirus infection kinetics, tissue pathophysiology, and innate immune signatures from upper and lower respiratory tract perspective. Our data suggested these in vitro ALI models maintain high physiological relevance with human airway tissues. The coronavirus induced immune response observed in these upper and lower respiratory airway models are similar to what has been reported in COVID-19 patients. The antiviral efficacy results of a few promising anti-coronavirus drugs in these models were consistent with previous reports and could be valuable for the human dose prediction. Taken together, our study demonstrates the importance of 3D airway epithelial ALI model for the understanding of coronavirus pathogenesis and the discovery and development of anti-coronavirus drugs.

中文翻译：

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用于冠状病毒药物发现的3D气道上皮的新颖，解剖学相似的体外模型

SARS-CoV-2及其诱导的COVID-19仍然是全球健康灾难。由细胞因子风暴和下呼吸道气道急性呼吸窘迫综合征引起的严重症状和高死亡率，通常与老年人和合并症患者有关；而轻度或中度的COVID-19患者的上呼吸道样症状有限。迫切需要研究SARS-CoV-2和其他冠状病毒在人类呼吸系统中的复制和免疫反应。人重组气道上皮气液界面（ALI）模型是研究冠状病毒感染和病毒触发的先天免疫特征的最生理相关模型。我们建立了代表上呼吸道和下呼吸道的ALI模型，以从上呼吸道和下呼吸道的角度表征冠状病毒的感染动力学，组织病理生理和先天免疫特征。我们的数据表明，这些体外ALI模型与人类气道组织保持高度的生理相关性。在这些上呼吸道和下呼吸道模型中观察到的冠状病毒诱导的免疫反应与在COVID-19患者中报道的相似。在这些模型中，几种有前途的抗冠状病毒药物的抗病毒功效结果与以前的报道一致，可能对人体剂量预测有价值。在一起