Proteomics of severe SARS-COV-2 infection and paraquat poisoning in human lung tissue samples: comparison of microbial infected and toxic pulmonary fibrosis.

严重 SARS-CoV-2 感染和百草枯中毒的人类肺组织样本蛋白质组学:微生物感染和毒性肺纤维化的比较

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作者:Min Jiang, Jiaqi Hou, Lihua Lin, Qianqian Chai, Shujuan Wang, Xiang Liu, Liang Liu, Liang Ren, Yiwu Zhou, Qian Liu
INTRODUCTION: Pulmonary fibrosis (PF) encompasses a spectrum of lung conditions characterized by the abnormal accumulation of scar tissue in the lungs, leading to impaired respiratory function. Various conditions can result in severe PF, among which viral infections have emerged as significant triggers. In addition to viral infections, exposure to toxic substances such as paraquat represents another significant risk factor for PF. Therefore, this study aimed to explore the dissimilarities and similarities between PF triggered by viral infections and chemical toxicants, using the mechanism of PF in IPF as a reference. METHODS: Data-independent acquisition proteomics technology was employed to identify COVID-19 and paraquat-induced PF from the autopsy of lung tissue samples obtained from individuals who died due to PF. Bioinformatics was employed for differential protein analysis, and selected indicators were validated on pathological sections. RESULTS: Our results showed that the differential proteins associated with the two causes of PF were enriched in similar lung fibrosis-related signaling pathways, such as the Wnt signaling pathway. However, differences were observed in proteins such as CACYBP, we verified the consistency of the results with proteomics using the IHC approach. CONCLUSION: This study illuminates distinct protein-level differences by investigating pulmonary fibrosis pathways in severe COVID-19 and paraquat poisoning. Although both conditions activate lung-protective and repair pathways, COVID-19 shows limited phosphorylation-independent ubiquitination of β-catenin compared to paraquat toxicity. These findings shed light on potential therapeutic targets for PF induced via diverse factors.

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