实验动物与比较医学 ›› 2024, Vol. 44 ›› Issue (1): 62-73.DOI: 10.12300/j.issn.1674-5817.2023.079

• 人类疾病动物模型 • 上一篇    下一篇

新冠病毒感染转录组学数据及比较医学分析

冯婷婷, 李依桐, 吴玥, 王珏, 孔琪()()   

  1. 中国医学科学院医学实验动物研究所, 北京协和医学院比较医学中心, 国家人类疾病动物模型资源库, 国家卫生健康委员会人类疾病比较医学重点实验室, 新发再发传染病动物模型研究北京市重点实验室, 北京市人类重大疾病实验动物模型工程技术研究中心, 北京 100021
  • 收稿日期:2023-06-16 修回日期:2023-10-13 出版日期:2024-02-25 发布日期:2024-03-07
  • 通讯作者: 孔 琪(1978—),男,博士,研究员,研究方向:比较医学。E-mail: kongqi@ cnilas.org。ORCID: 0000-0003-2867-7382
  • 作者简介:冯婷婷(1999—),女,硕士研究生,研究方向:比较医学。E-mail: fengtingting@ cnilas.org
  • 基金资助:
    北京市自然科学基金资助项目“基于大数据的新型冠状病毒肺炎动物模型数据库建立”(M21027)

Transcriptome Data and Comparative Medical Analysis of COVID-19 Virus Infection

Tingting FENG, Yitong LI, Yue WU, Jue WANG, Qi KONG()()   

  1. Institute of Laboratory Animal Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, National Human Diseases Animal Model Resource Center, NHC Key Laboratory of Human Disease Comparative Medicine, Beijing Key Laboratory for Animal Models of Emerging and Reemerging Infectious Diseases, Beijing Engineering Research Center for Experimental Animal Models of Human Critical Diseases, Beijing 100021, China
  • Received:2023-06-16 Revised:2023-10-13 Published:2024-02-25 Online:2024-03-07
  • Contact: KONG Qi (ORCID: 0000-0003-2867-7382), E-mail: kongqi@ cnilas.org

摘要:

目的 通过系统梳理与分析新冠病毒感染相关的转录组数据,为研究新冠病毒感染过程中的生物学变化和致病机制提供更多的比较医学基础信息。 方法 按照检索策略,以COVID-19和SARS-CoV-2为检索词,从GEO、ArrayExpress、GEN三大转录组数据库收集获得2020年1月—2023年5月的新冠病毒感染转录组数据集,分析得到新冠病毒感染转录组的数据资源组成、分布和研究应用情况,并对数据分布进行可视化展示及关联分析。从临床医学和比较医学两个方面,围绕临床相关分子机制、生物标志物及相关免疫反应、治疗干预策略等方面,分析现有新冠病毒感染转录组数据的研究应用和局限性,阐述其研究价值和应用前景。 结果 共纳入新冠病毒感染转录组数据975组,在3个数据库中样本来源于人的数据集最多,分别占71.9%、77.9%和90.0%。除人以外,小鼠等是数据主要来源物种,呼吸系统和神经系统是数据分布排名在前的两个系统。在临床意义方面关联27个数据集。分析显示,基于转录组数据挖掘得到呼吸道损伤等相关分子机制,cfDNA等生物标志物可作为治疗靶点,以M1型巨噬细胞为代表的细胞变化和失调与新冠病毒感染严重程度相关。比较医学分析表明小鼠、仓鼠等均为新冠病毒易感动物,其中恒河猴和食蟹猴与人类的感染特征高度相似,仓鼠除了呼吸道症状还存在消化系统症状。新冠病毒能在各种易感动物呼吸系统器官、雪貂的肠道及水貂的耳部进行复制,产生肺炎、弥漫性肺损伤等不同程度的病理变化;基于免疫应答差异,可使用仓鼠进行中和抗体反应研究。 结论 目前新冠病毒感染转录组数据较多,但缺少比较转录组研究,可将转录组学与比较医学进一步结合,从而对新冠病毒感染的比较医学差异进行更深入的挖掘。

关键词: 新冠病毒, 转录组, 大数据, 分子机制, 数据分析

Abstract:

Objective To provide more basic information of comparative medicine for the study of biological changes and pathogenesis of COVID-19 by systematical sorting and analyzing the transcriptome data. Methods Following a retrieval strategy, using COVID-19 and SARS-CoV-2 as key words, transcriptome datasets related to COVID-19 from January 2020 to May 2023 were collected from GEO, ArrayExpress and GEN Transcriptome databases. The composition, distribution, and research application of COVID-19 transcriptome data resources were analyzed. Data distribution was visually displayed and correlation analysis was performed. The research applications and limitations of existing COVID-19 transcriptome data were analyzed from the perspectives of clinical medicine and comparative medicine, focusing on clinical-related molecular mechanisms, biomarkers and related immune responses, treatment intervention strategies, etc. The research value and application prospects were discussed. Results A total of 975 sets of COVID-19 transcriptome data were included. Among three databases, datasets from humans accounted for the highest proportion, namely 71.9%, 77.9%, and 90%, respectively. Species other than humans, such as mice, were the main sources of data, with the respiratory and nervous systems having the highest distribution of data. Twenty-seven datasets were associated with clinical significance. Analysis revealed that respiratory tract injury and other related molecular mechanisms were obtained through transcriptome data mining. Biomarkers such as cfDNA could be used as therapeutic targets. The severity of COVID-19 infection was associated with cell changes and disorders represented by M1 macrophages. Comparative medical analysis showed that mice, hamsters, and other animals were susceptible to SARS-CoV-2. Rhesus monkeys and cynomolgus monkeys exhibited infection characteristics highly similar to human. Apart from respiratory symptoms, hamsters also exhibited digestive system symptoms. SARS-CoV-2 can replicate in the respiratory organs of various susceptible animals, the intestines of ferrets and the ears of minks, resulting in interstitial pneumonia, diffuse lung injury and other pathological changes of varying degrees. Based on the differences in immune responses, hamsters can be used for neutralizing antibody reaction research. Conclusion Currently there is a wealth of COVID-19 transcriptome data, but there is a lack of comparative transcriptome research. Transcriptomics can be combined with comparative medicine to further explore the differences in comparative medicine of COVID-19.

Key words: COVID-19, Transcriptome, Big data, Molecular mechanisms, Data analysis

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