冠状病毒感染动物模型组学数据集成分析

Integrative Analysis of Omics Data in Animal Models of Coronavirus Infection

目的分析各个公共数据库中可感染人的冠状病毒感染动物模型的组学数据资源情况,包括数据分布、数据集数量、数据类型、物种、品系、研究内容等,从而深入理解冠状病毒的生物学特征和致病机制,为研究有效的治疗方案和预防措施奠定基础。方法定义特定病毒名称、时间范围和物种等检索策略与纳入排除标准,检索GEO、ArrayExpress等大型公共组学数据库。根据不同字段类型进行二次过滤,获取更精确的数据列表。建立组学数据文本库,进行文献计量学分析,构建共现网络图,分析不同研究主题、技术方法和涉及物种之间的关联强度。同时,分析研究涉及的细胞类型、器官和参与的生物途径,以进一步阐明病原体与宿主之间的致病相互作用。结果含有冠状病毒组学数据的公共数据库有20余个,以新型冠状病毒感染组学数据为主。常用物种为人、小鼠、仓鼠和猴,常用病毒株为Wuhan-Hu-1和USA-WA1/2020。此外,人类相关研究主要集中于气道上皮细胞和Calu-3细胞,动物模型(如小鼠、猕猴与雪貂)则多采用肺组织。表达谱数据显示感染后参与炎症、细胞因子反应、补体途径、细胞损伤、增殖和分化等通路基因显著上调。蛋白组学研究揭示,在不同感染阶段的患者样本中磷酸化蛋白质组、泛素组和全蛋白质组具有显著变化。特定蛋白质类别,包括病毒受体和蛋白酶、转录因子、细胞因子、凝血系统相关蛋白、血管生成相关蛋白及纤维化标志物等六类蛋白均在冠状病毒感染后发生改变。此外,代谢组数据提示磷酸胆碱、磷酸乙醇胺、花生四烯酸和油酸可作为潜在的代谢标志物。表观组学研究结果显示,m6A甲基化在新冠病毒复制、感染和传播过程中发挥作用,并且对宿主细胞-病毒互作产生影响。N、S、非结构蛋白2和3泛素化最为显著。微生物组学研究趋势表明,肠道和废水中的微生物群落正在成为新的研究重点。结论冠状病毒组学数据类型丰富,模型与细胞类型多样。根据不同病毒的特征,造模物种和技术方法的选择具有差异性。研究冠状病毒感染动物模型的多组学数据可以揭示宿主-病原体之间的关键相互作用,发现生物标志物和潜在的治疗靶点,为深入理解冠状病毒的生物学特性和感染机制提供丰富信息。

Objective This study analyzes the omics data resources in human-infecting coronavirus animal models collected from various public databases,focusing on data distribution,dataset quantity,data types,species,strains,and research content.It aims to enhance our understanding of biological characteristics and pathogenic mechanisms of coronaviruses,thereby providing a solid foundation for devising effective therapeutic strategies and preventive measures.Methods Query strategies,including specific virus names,time ranges,and inclusion and exclusion criteria,were defined to retrieve data from major public omics databases such as GEO and ArrayExpress.Secondary filtering was performed based on different field types to obtain a more accurate data list.An omics data text database was established for bibliometric analysis.Co-occurrence networks were constructed for the analysis of the correlation strengths between different research themes,technical methods,and involved species.The cell types,organs,and biological pathways involved in studies were examined to further elucidate the pathogenic interplay between pathogens and hosts.Results About twenty public databases containing coronavirusrelated omics data were identified,with a primary focus on novel coronavirus infection.Commonly used species include humans,mice,hamsters,and monkeys,while the commonly used virus strains are WuhanHu-1 and USA-WA1/2020.Lung tissues are primarily used in animal models such as mice,macaques,and ferrets,while airway epithelial cells and Calu-3 cells are predominantly employed in human-related studies.Expression profiling data indicate that gene pathways involved in inflammation,cytokine response,complement pathway,cell damage,proliferation,and differentiation are significantly upregulated after infection.Proteomics studies reveal significant changes in phosphoproteome,ubiquitinome,and total proteome of patient samples at different infection stages.Specific protein categories,including viral receptors and proteases,transcription factors,cytokines,proteins associated with coagulation system,angiogenesis-related proteins,and fibrosis markers,show alterations after coronavirus infection.In addition,metabolomics data suggest that phosphocholine,phosphoethanolamine,arachidonic acid,and oleic acid could serve as potential metabolic markers.Epigenomics research indicates m6A methylation plays a role in SARS-CoV-2 replication,infection,and transmission,affecting host cell-virus interactions.Among these,N,S,and non-structural proteins 2 and 3 exhibit the most significant ubiquitination.Trends in microbiomics research suggest that microbial communities in the gut and wastewater are emerging as new research focuses.Conclusion The data types of coronavirus omics are diverse,with a wide variety of models and cell types used.The selection of species and technical methods for modelling varies based on the characteristics of different viruses.Multi-omics data from animal models of coronavirus infection can reveal key interactions between hosts and pathogens,identifying biomarkers and potential therapeutic targets,and provide valuable information for a deeper understanding of biological characteristics and infection mechanisms of coronaviruses.