five

Role of Multiomics Data to Understand Host–Pathogen Interactions in COVID-19 Pathogenesis

收藏
NIAID Data Ecosystem2026-03-12 收录
下载链接:
https://figshare.com/articles/dataset/Role_of_Multiomics_Data_to_Understand_Host_Pathogen_Interactions_in_COVID-19_Pathogenesis/13553668
下载链接
链接失效反馈
官方服务:
资源简介:
Human infectious diseases are contributed equally by the host immune system’s efficiency and any pathogens’ infectivity. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the coronavirus strain causing the respiratory pandemic coronavirus disease 2019 (COVID-19). To understand the pathobiology of SARS-CoV-2, one needs to unravel the intricacies of host immune response to the virus, the viral pathogen’s mode of transmission, and alterations in specific biological pathways in the host allowing viral survival. This review critically analyzes recent research using high-throughput “omics” technologies (including proteomics and metabolomics) on various biospecimens that allow an increased understanding of the pathobiology of SARS-CoV-2 in humans. The altered biomolecule profile facilitates an understanding of altered biological pathways. Further, we have performed a meta-analysis of significantly altered biomolecular profiles in COVID-19 patients using bioinformatics tools. Our analysis deciphered alterations in the immune response, fatty acid, and amino acid metabolism and other pathways that cumulatively result in COVID-19 disease, including symptoms such as hyperglycemic and hypoxic sequelae.

人类传染病的发生由宿主免疫系统的功能效能与病原体的感染能力共同决定,二者的作用权重均等。严重急性呼吸综合征冠状病毒2(Severe acute respiratory syndrome coronavirus 2, SARS-CoV-2)是引发2019冠状病毒病(coronavirus disease 2019, COVID-19)这一呼吸道大流行的冠状病毒毒株。要阐明SARS-CoV-2的病理生物学机制,需解析宿主针对该病毒的免疫应答的复杂细节、该病毒的传播途径,以及宿主体内助力病毒存活的特定生物通路的异常改变。本综述批判性地分析了近期利用高通量组学(omics)技术(涵盖蛋白质组学(proteomics)与代谢组学(metabolomics))针对各类生物标本开展的相关研究,这些研究有助于加深对人类体内SARS-CoV-2病理生物学机制的认知。异常的生物分子谱可为解析异常生物通路提供有力支撑。此外,本研究借助生物信息学工具,对COVID-19患者体内显著异常的生物分子谱开展了荟萃分析。本次分析揭示了免疫应答、脂肪酸与氨基酸代谢及其他通路的异常改变,这些异常共同促成了COVID-19的发病,包括高血糖与缺氧后遗症等相关临床症状。
创建时间:
2021-01-11
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作