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2019年冠状病毒病(COVID-19)感染的血清蛋白质生物标志物筛查与分析

Screening and Analysis of Serum Protein Biomarkers Infected by Coronavirus Disease 2019 (COVID-19).

作者信息

Feng Zhaomin, Pan Yang, Liu Yimeng, Zhao Jiachen, Peng Xiaomin, Lu Guilan, Shi Weixian, Zhang Daitao, Cui Shujuan

机构信息

Institute for Infectious Disease and Endemic Disease Control, Beijing Center for Disease Prevention and Control, Beijing 100013, China.

出版信息

Trop Med Infect Dis. 2022 Nov 25;7(12):397. doi: 10.3390/tropicalmed7120397.

Abstract

Coronavirus disease 2019 (COVID-19) has spread widely around the world, and in-depth research on COVID-19 is necessary for biomarkers and target drug discovery. This analysis collected serum from six COVID-19-infected patients and six healthy people. The protein changes in the infected and healthy control serum samples were evaluated by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and high-performance liquid chromatography (HPLC). The differential protein signature in both groups was retrieved and analyzed by the Kyoto Encyclopedia of Gene and Genomes (KEGG), Gene ontology, COG/KOG, protein-protein interaction, and protein domain interactions tools. We shortlisted 24 differentially expressed proteins between both groups. Ten genes were significantly up-regulated in the infection group, and fourteen genes were significantly down-regulated. The GO and KEGG pathway enrichment analysis suggested that the chromosomal part and chromosome were the most enriched items. The oxytocin signaling pathway was the most enriched item of KEGG analysis. The netrin module (non-TIMP type) was the most enriched protein domain in this study. Functional analysis of S100A9, PIGR, C4B, IL-6R, IGLV3-19, IGLV3-1, and IGLV5-45 revealed that SARS-CoV-2 was closely related to immune response.

摘要

2019冠状病毒病(COVID-19)已在全球广泛传播,对COVID-19进行深入研究对于生物标志物和靶向药物发现至关重要。本分析收集了6名COVID-19感染患者和6名健康人的血清。通过液相色谱-串联质谱(LC-MS/MS)和高效液相色谱(HPLC)评估感染组和健康对照组血清样本中的蛋白质变化。利用京都基因与基因组百科全书(KEGG)、基因本体论、COG/KOG、蛋白质-蛋白质相互作用和蛋白质结构域相互作用工具检索并分析两组中的差异蛋白质特征。我们筛选出两组之间24种差异表达的蛋白质。感染组中有10个基因显著上调,14个基因显著下调。GO和KEGG通路富集分析表明,染色体部分和染色体是最富集的条目。催产素信号通路是KEGG分析中最富集的条目。在本研究中,netrin模块(非TIMP类型)是最富集的蛋白质结构域。对S100A9、PIGR、C4B、IL-6R、IGLV3-19、IGLV3-1和IGLV5-45的功能分析表明,SARS-CoV-2与免疫反应密切相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6cfb/9788497/234c9d0abaa7/tropicalmed-07-00397-g001.jpg

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