• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

新型冠状病毒肺炎患者血清的蛋白质组学分析

Proteomics Analysis of Serum from COVID-19 Patients.

作者信息

Liu Xiaoling, Cao Yinghao, Fu Hongmei, Wei Jie, Chen Jianhong, Hu Jun, Liu Bende

机构信息

Department of endocrinology, Liyuan Hospital, Tongji Medical College, Huazhong University of Since and Technology, Wuhan, Hubei 430022, China.

Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.

出版信息

ACS Omega. 2021 Mar 9;6(11):7951-7958. doi: 10.1021/acsomega.1c00616. eCollection 2021 Mar 23.

DOI:10.1021/acsomega.1c00616
PMID:33778306
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7992154/
Abstract

Coronavirus disease 2019 (COVID-19) is a worldwide pandemic. To understand the changes in plasma proteomics upon SARS-CoV-2 infection, we analyzed the protein profiles of plasma samples from 10 COVID-19 patients and 10 healthy volunteers by using the DIA quantitative proteomics technology. We compared and identified differential proteins whose abundance changed upon SARS-CoV-2 infection. Bioinformatic analyses were then conducted for these identified differential proteins. The GO/KEEG database was used for functional annotation and enrichment analysis. The interaction relationship of differential proteins was evaluated with the STRING database, and Cytoscape software was used to conduct network analysis of the obtained data. A total of 323 proteins were detected in all samples. Difference between patients and healthy donors was found in 44 plasma proteins, among which 36 proteins were up-regulated and 8 proteins were down-regulated. GO functional annotation showed that these proteins mostly composed of cellular anatomical entities and proteins involved in biological regulation, cellular processes, transport, and other processes. KEEG functional annotation further showed that these proteins were mainly involved in complement system activation and infectious disease processes. Importantly, a KEEG pathway (natural killer cell-mediated cytotoxicity) was enriched, with three important activators of this pathway, ICAM1/2 and IgG, being up-regulated. Protein-protein interaction (PPI) statistics indicated that, among these 44 proteins, 6 were the most significantly up-regulated (DBH, SHGB, TF, ICAM2, THBS1, and C1RL) while 2 were the most significantly down-regulated (APCS and ORM1). Results from this study showed that a few proteins associated with immune activation were up-regulated in patient plasma. In addition, this study established a method for extraction and quantitative determination of plasma components in convalescent plasma from COVID-19 patients.

摘要

2019冠状病毒病(COVID-19)是一场全球大流行疾病。为了解严重急性呼吸综合征冠状病毒2(SARS-CoV-2)感染后血浆蛋白质组学的变化,我们采用数据独立采集(DIA)定量蛋白质组学技术分析了10例COVID-19患者和10名健康志愿者的血浆样本蛋白质谱。我们比较并鉴定了SARS-CoV-2感染后丰度发生变化的差异蛋白。然后对这些鉴定出的差异蛋白进行生物信息学分析。基因本体论(GO)/京都基因与基因组百科全书(KEGG)数据库用于功能注释和富集分析。利用STRING数据库评估差异蛋白的相互作用关系,并使用Cytoscape软件对所得数据进行网络分析。所有样本共检测到323种蛋白质。在44种血浆蛋白中发现患者与健康供体之间存在差异,其中36种蛋白上调,8种蛋白下调。GO功能注释表明,这些蛋白大多由细胞解剖实体以及参与生物调节、细胞过程、转运和其他过程的蛋白质组成。KEGG功能注释进一步表明,这些蛋白主要参与补体系统激活和传染病过程。重要的是,一条KEGG通路(自然杀伤细胞介导的细胞毒性)被富集,该通路的三个重要激活因子细胞间黏附分子1/2(ICAM1/2)和免疫球蛋白G(IgG)上调。蛋白质-蛋白质相互作用(PPI)统计表明,在这44种蛋白中,有6种上调最为显著(多巴胺β-羟化酶(DBH)、性激素结合球蛋白(SHGB)、转铁蛋白(TF)、ICAM2、血小板反应蛋白1(THBS1)和补体1r亚基(C1RL)),而有2种下调最为显著(补体因子S(APCS)和ORM蛋白1(ORM1))。本研究结果表明,患者血浆中一些与免疫激活相关的蛋白上调。此外,本研究建立了一种从COVID-19患者康复期血浆中提取和定量测定血浆成分的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0da/7992154/11d4f8c59ed1/ao1c00616_0009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0da/7992154/7a91c70b4037/ao1c00616_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0da/7992154/867624588107/ao1c00616_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0da/7992154/aebbd243f0e3/ao1c00616_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0da/7992154/65469fb829fd/ao1c00616_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0da/7992154/1d606f405ac2/ao1c00616_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0da/7992154/14f0dabb77aa/ao1c00616_0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0da/7992154/65db0fa41940/ao1c00616_0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0da/7992154/11d4f8c59ed1/ao1c00616_0009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0da/7992154/7a91c70b4037/ao1c00616_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0da/7992154/867624588107/ao1c00616_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0da/7992154/aebbd243f0e3/ao1c00616_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0da/7992154/65469fb829fd/ao1c00616_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0da/7992154/1d606f405ac2/ao1c00616_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0da/7992154/14f0dabb77aa/ao1c00616_0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0da/7992154/65db0fa41940/ao1c00616_0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0da/7992154/11d4f8c59ed1/ao1c00616_0009.jpg

相似文献

1
Proteomics Analysis of Serum from COVID-19 Patients.新型冠状病毒肺炎患者血清的蛋白质组学分析
ACS Omega. 2021 Mar 9;6(11):7951-7958. doi: 10.1021/acsomega.1c00616. eCollection 2021 Mar 23.
2
Proteomics analysis of serum from thymoma patients.胸腺瘤患者血清的蛋白质组学分析。
Sci Rep. 2023 Mar 29;13(1):5117. doi: 10.1038/s41598-023-32339-4.
3
Bioinformatics analyses of significant genes, related pathways, and candidate diagnostic biomarkers and molecular targets in SARS-CoV-2/COVID-19.严重急性呼吸综合征冠状病毒2/冠状病毒病19中重要基因、相关通路、候选诊断生物标志物及分子靶点的生物信息学分析
Gene Rep. 2020 Dec;21:100956. doi: 10.1016/j.genrep.2020.100956. Epub 2020 Nov 4.
4
"Fei Yan No. 1" as a Combined Treatment for COVID-19: An Efficacy and Potential Mechanistic Study.“肺炎一号方”用于新型冠状病毒肺炎的联合治疗:疗效及潜在机制研究
Front Pharmacol. 2020 Oct 8;11:581277. doi: 10.3389/fphar.2020.581277. eCollection 2020.
5
Identification of potential mRNA panels for severe acute respiratory syndrome coronavirus 2 (COVID-19) diagnosis and treatment using microarray dataset and bioinformatics methods.使用微阵列数据集和生物信息学方法鉴定用于严重急性呼吸综合征冠状病毒2(COVID-19)诊断和治疗的潜在mRNA面板。
3 Biotech. 2020 Oct;10(10):422. doi: 10.1007/s13205-020-02406-y. Epub 2020 Sep 11.
6
Plasma-based proteomics reveals immune response, complement and coagulation cascades pathway shifts in heat-stressed lactating dairy cows.基于血浆的蛋白质组学揭示了热应激泌乳奶牛的免疫反应、补体和凝血级联途径的变化。
J Proteomics. 2016 Sep 2;146:99-108. doi: 10.1016/j.jprot.2016.06.008. Epub 2016 Jun 15.
7
[Exploration of omics mechanism and drug prediction of coronavirus-induced heart failure based on clinical bioinformatics].基于临床生物信息学的冠状病毒诱导的心力衰竭的组学机制探索与药物预测
Zhonghua Xin Xue Guan Bing Za Zhi. 2020 Jul 24;48(7):587-592. doi: 10.3760/cma.j.cn112148-20200308-00172.
8
Identification and interaction analysis of key genes and microRNAs in hepatocellular carcinoma by bioinformatics analysis.基于生物信息学分析的肝细胞癌关键基因和微小RNA的鉴定与相互作用分析
World J Surg Oncol. 2017 Mar 16;15(1):63. doi: 10.1186/s12957-017-1127-2.
9
Molecular mechanisms underlying gliomas and glioblastoma pathogenesis revealed by bioinformatics analysis of microarray data.通过对微阵列数据的生物信息学分析揭示胶质瘤和神经胶质瘤发病机制的分子机制。
Med Oncol. 2017 Sep 26;34(11):182. doi: 10.1007/s12032-017-1043-x.
10
Integrated analysis of gene expression changes associated with coronary artery disease.与冠状动脉疾病相关的基因表达变化的综合分析。
Lipids Health Dis. 2019 Apr 9;18(1):92. doi: 10.1186/s12944-019-1032-5.

引用本文的文献

1
Identification of biomarkers associated with mitochondrial dysfunction and programmed cell death in chronic obstructive pulmonary disease via transcriptomics.通过转录组学鉴定慢性阻塞性肺疾病中与线粒体功能障碍和程序性细胞死亡相关的生物标志物
Front Genet. 2025 Jun 19;16:1567173. doi: 10.3389/fgene.2025.1567173. eCollection 2025.
2
Linking TLR-7 Signaling to Downregulation of Placental P-Glycoprotein: Implications for Fetal Drug Exposure.将Toll样受体7(TLR-7)信号传导与胎盘P-糖蛋白的下调联系起来:对胎儿药物暴露的影响。
Pharmaceutics. 2025 Jun 5;17(6):741. doi: 10.3390/pharmaceutics17060741.
3
Unbiased plasma profiling using pre-selected RNA aptamer pools predicts mortality in COVID-19 and identifies protein risk factors.

本文引用的文献

1
COVID-19 antibody seroprevalence in Santa Clara County, California.加利福尼亚州圣克拉拉县的新冠病毒抗体血清流行率。
Int J Epidemiol. 2021 May 17;50(2):410-419. doi: 10.1093/ije/dyab010.
2
SARS-CoV-2 proteome microarray for global profiling of COVID-19 specific IgG and IgM responses.SARS-CoV-2 蛋白组微阵列用于全面分析 COVID-19 特异性 IgG 和 IgM 反应。
Nat Commun. 2020 Jul 14;11(1):3581. doi: 10.1038/s41467-020-17488-8.
3
SARS-CoV-2-specific antibody detection in healthcare workers in Germany with direct contact to COVID-19 patients.
使用预先选择的RNA适配体库进行无偏倚血浆分析可预测COVID-19的死亡率并识别蛋白质风险因素。
Mol Ther Nucleic Acids. 2024 Jun 15;35(3):102253. doi: 10.1016/j.omtn.2024.102253. eCollection 2024 Sep 10.
4
Research Trends in Proteomic Studies Using Serum from COVID-19 Patients: A Bibliometric Analysis.使用新冠肺炎患者血清的蛋白质组学研究趋势:文献计量分析
Curr Med Chem. 2025;32(12):2275-2290. doi: 10.2174/0109298673286915240329063441.
5
Meta-analysis of the serum/plasma proteome identifies significant associations between COVID-19 with Alzheimer's/Parkinson's diseases.对血清/血浆蛋白质组的荟萃分析确定了 COVID-19 与阿尔茨海默病/帕金森病之间的显著关联。
J Neurovirol. 2024 Feb;30(1):57-70. doi: 10.1007/s13365-023-01191-7. Epub 2024 Jan 2.
6
Proteomic Investigation of COVID-19 Severity During the Tsunamic Second Wave in Mumbai.新冠病毒在孟买第二波海啸期间严重程度的蛋白质组学研究
Adv Exp Med Biol. 2023;1412:175-195. doi: 10.1007/978-3-031-28012-2_9.
7
Plasma proteome perturbation for CMV DNAemia in kidney transplantation.血浆蛋白质组扰动与肾移植中 CMV DNA 血症。
PLoS One. 2023 May 19;18(5):e0285870. doi: 10.1371/journal.pone.0285870. eCollection 2023.
8
Blood leukocyte transcriptional modules and differentially expressed genes associated with disease severity and age in COVID-19 patients.COVID-19 患者疾病严重程度和年龄相关的血液白细胞转录模块和差异表达基因。
Sci Rep. 2023 Jan 17;13(1):898. doi: 10.1038/s41598-023-28227-6.
9
Glutamine-Driven Metabolic Adaptation to COVID-19 Infection.谷氨酰胺驱动的对新型冠状病毒肺炎感染的代谢适应
Indian J Clin Biochem. 2023 Jan;38(1):83-93. doi: 10.1007/s12291-022-01037-9. Epub 2022 Apr 8.
10
The serum of COVID-19 asymptomatic patients up-regulates proteins related to endothelial dysfunction and viral response in circulating angiogenic cells ex-vivo.COVID-19 无症状患者的血清可在体外上调循环血管生成细胞中与血管内皮功能障碍和病毒反应相关的蛋白质。
Mol Med. 2022 Apr 9;28(1):40. doi: 10.1186/s10020-022-00465-w.
德国直接接触 COVID-19 患者的医护人员中 SARS-CoV-2 特异性抗体的检测。
J Clin Virol. 2020 Jul;128:104437. doi: 10.1016/j.jcv.2020.104437. Epub 2020 May 13.
4
The Role of Lipid Metabolism in COVID-19 Virus Infection and as a Drug Target.脂代谢在 COVID-19 病毒感染中的作用及其作为药物靶点的研究。
Int J Mol Sci. 2020 May 17;21(10):3544. doi: 10.3390/ijms21103544.
5
A SARS-CoV-2 protein interaction map reveals targets for drug repurposing.一种 SARS-CoV-2 蛋白相互作用图谱揭示了药物再利用的靶标。
Nature. 2020 Jul;583(7816):459-468. doi: 10.1038/s41586-020-2286-9. Epub 2020 Apr 30.
6
Antibody responses to SARS-CoV-2 in patients with COVID-19.新型冠状病毒肺炎(COVID-19)患者的 SARS-CoV-2 抗体反应。
Nat Med. 2020 Jun;26(6):845-848. doi: 10.1038/s41591-020-0897-1. Epub 2020 Apr 29.
7
Neutralizing Antibodies against SARS-CoV-2 and Other Human Coronaviruses.针对 SARS-CoV-2 和其他人类冠状病毒的中和抗体。
Trends Immunol. 2020 May;41(5):355-359. doi: 10.1016/j.it.2020.03.007. Epub 2020 Apr 2.
8
Structural basis of receptor recognition by SARS-CoV-2.SARS-CoV-2 受体识别的结构基础。
Nature. 2020 May;581(7807):221-224. doi: 10.1038/s41586-020-2179-y. Epub 2020 Mar 30.
9
Structural Genomics of SARS-CoV-2 Indicates Evolutionary Conserved Functional Regions of Viral Proteins.SARS-CoV-2 的结构基因组学表明病毒蛋白的进化保守功能区。
Viruses. 2020 Mar 25;12(4):360. doi: 10.3390/v12040360.
10
A pneumonia outbreak associated with a new coronavirus of probable bat origin.一种新型冠状病毒引发的肺炎疫情,该病毒可能来源于蝙蝠。
Nature. 2020 Mar;579(7798):270-273. doi: 10.1038/s41586-020-2012-7. Epub 2020 Feb 3.